From 356125b143545a76bf51fbe44022b64c8ae43125 Mon Sep 17 00:00:00 2001 From: lixuelin Date: Tue, 17 May 2022 18:49:39 +0800 Subject: [PATCH 001/229] add infoNCE --- ding/utils/mi_estimator.py | 99 +++++++++++++++++++++++++++ ding/utils/tests/test_mi_estimator.py | 46 +++++++++++++ 2 files changed, 145 insertions(+) create mode 100644 ding/utils/mi_estimator.py create mode 100644 ding/utils/tests/test_mi_estimator.py diff --git a/ding/utils/mi_estimator.py b/ding/utils/mi_estimator.py new file mode 100644 index 0000000000..6191c77445 --- /dev/null +++ b/ding/utils/mi_estimator.py @@ -0,0 +1,99 @@ +from typing import Union +from ding.utils import SequenceType +import torch +import torch.nn as nn +import torch.nn.functional as F +from ding.model import ConvEncoder, FCEncoder + + +class ContrastiveLoss(nn.Module): + """ + The class for contrastive learning losses. + Only InfoNCE loss supported currently. + """ + + def __init__( + self, + x_dim: Union[int, SequenceType], + y_dim: Union[int, SequenceType], + heads: SequenceType = [1, 1], + embed_dim: int = 64, + loss_type: str = "infonce", + temperature: float = 1.0, + ) -> None: + """ + Args: + x_dim: input dimensions for x, both obs shape and encoding shape are supported. + y_dim: input dimensions for y, both obs shape and encoding shape are supported. + heads: a list of 2 int elems, heads[0] for x and head[1] for y. + Used in multi-head, global-local, local-local MI maximization process. + loss_type: only InfoNCE loss supported currently. + temperature: the parameter to adjust the log_softmax. + """ + super(ContrastiveLoss, self).__init__() + assert len(heads) == 2 + assert loss_type.lower() in ["infonce"] + + self._type = loss_type.lower() + self._embed_dim = embed_dim + self._heads = heads + self._x_encoder = self._get_encoder(x_dim, heads[0]) + self._y_encoder = self._get_encoder(y_dim, heads[1]) + self._temperature = temperature + + def _get_encoder(self, obs: Union[int, SequenceType], heads: int): + if isinstance(obs, int): + obs = [obs] + assert len(obs) in [1, 3] + + if len(obs) == 1: + hidden_size_list = [128, 128, self._embed_dim * heads] + encoder = FCEncoder(obs[0], hidden_size_list) + else: + hidden_size_list = [32, 64, 64, self._embed_dim * heads] + encoder = ConvEncoder(obs, hidden_size_list) + return encoder + + def forward(self, x: torch.Tensor, y: torch.Tensor): + ''' + Computes the noise contrastive estimation-based loss, a.k.a. infoNCE. + Args: + x: the input x, both raw obs and encoding are supported. + y: the input y, both raw obs and encoding are supported. + Returns: + torch.Tensor: loss value. + ''' + + N = x.size(0) + x_heads, y_heads = self._heads + x = self._x_encoder.forward(x).reshape(N, x_heads, self._embed_dim) + y = self._y_encoder.forward(y).reshape(N, y_heads, self._embed_dim) + + x_n = x.reshape(-1, self._embed_dim) + y_n = y.reshape(-1, self._embed_dim) + + # Inner product for positive samples. Outer product for negative. We need to do it this way + # for the multiclass loss. For the outer product, we want a N x N x n_local x n_multi tensor. + u_pos = torch.matmul(x, y.permute(0, 2, 1)).unsqueeze(2) + u_all = torch.mm(y_n, x_n.t()).reshape(N, y_heads, N, x_heads).permute(0, 2, 3, 1) + + # We need to mask the diagonal part of the negative tensor. + mask = torch.eye(N)[:, :, None, None].to(x.device) + n_mask = 1 - mask + + # Masking is done by shifting the diagonal before exp. + u_neg = (n_mask * u_all) - (10. * (1 - n_mask)) # mask out "self" examples, all diagonals are set to -10. + u_neg = u_neg.reshape(N, N * x_heads, y_heads).unsqueeze(dim=1).expand(-1, x_heads, -1, -1) + + # Since this is multiclass, we concat the positive along the class dimension before performing log softmax. + pred_lgt = torch.cat([u_pos, u_neg], dim=2) + pred_log = F.log_softmax(pred_lgt * self._temperature, dim=2) + + # The positive score is the first element of the log softmax. + loss = -pred_log[:, :, 0].mean() + return loss + + def __call__(self, x: torch.Tensor, y: torch.Tensor): + with torch.no_grad(): + out = self.forward(x, y) + return out diff --git a/ding/utils/tests/test_mi_estimator.py b/ding/utils/tests/test_mi_estimator.py new file mode 100644 index 0000000000..1eb56ecdc4 --- /dev/null +++ b/ding/utils/tests/test_mi_estimator.py @@ -0,0 +1,46 @@ +import pytest +import numpy as np +import torch +from ding.utils.mi_estimator import ContrastiveLoss +from torch.utils.data import TensorDataset, DataLoader +# from torch.utils.tensorboard import SummaryWriter + + +@pytest.mark.benchmark +@pytest.mark.parametrize('noise', [0.1, 1.0, 3.0]) +def test_infonce_loss(noise): + batch_size = 64 + N_batch = 100 + x_dim = [batch_size * N_batch, 16] + + embed_dim = 16 + x = np.random.normal(0, 1, size=x_dim) + y = x ** 2 + noise * np.random.normal(0, 1, size=x_dim) + + estimator = ContrastiveLoss(x.shape[1:], y.shape[1:], embed_dim=embed_dim) + dataset = TensorDataset(torch.Tensor(x), torch.Tensor(y)) + dataloader = DataLoader(dataset, batch_size=batch_size) + optimizer = torch.optim.Adam(estimator.parameters(), lr=3e-4) + # writer = SummaryWriter() + for epoch in range(10): + train_loss = 0. + test_loss = 0. + for inputs in dataloader: + x, y = inputs + optimizer.zero_grad() + loss = estimator.forward(x, y) + loss.backward() + optimizer.step() + train_loss += loss.item() + + with torch.no_grad(): + for inputs in dataloader: + x, y = inputs + outputs = estimator.forward(x, y) + test_loss += outputs + + # writer.add_scalar('Loss/train', train_loss / N_batch, epoch) + # writer.add_scalar('Loss/train', test_loss / N_batch, epoch) + # print('epoch {}: train loss {:.4f}, test_loss {:.4f}'.format(epoch, \ + # train_loss / N_batch, test_loss / N_batch)) + # writer.close() From dab8d4bd1294de2849125d1b186fc429396a2a68 Mon Sep 17 00:00:00 2001 From: lixuelin Date: Thu, 19 May 2022 18:22:07 +0800 Subject: [PATCH 002/229] refine infonce test --- ding/utils/mi_estimator.py | 11 ++++++++--- ding/utils/tests/test_mi_estimator.py | 24 +++++++++--------------- 2 files changed, 17 insertions(+), 18 deletions(-) diff --git a/ding/utils/mi_estimator.py b/ding/utils/mi_estimator.py index 6191c77445..6eb5c2ed86 100644 --- a/ding/utils/mi_estimator.py +++ b/ding/utils/mi_estimator.py @@ -10,6 +10,8 @@ class ContrastiveLoss(nn.Module): """ The class for contrastive learning losses. Only InfoNCE loss supported currently. + Code Reference: https://github.com/rdevon/DIM. + paper: https://arxiv.org/abs/1808.06670. """ def __init__( @@ -23,8 +25,8 @@ def __init__( ) -> None: """ Args: - x_dim: input dimensions for x, both obs shape and encoding shape are supported. - y_dim: input dimensions for y, both obs shape and encoding shape are supported. + x_dim: input dimensions for x, both the obs shape and the encoding shape are supported. + y_dim: input dimensions for y, both the obs shape and the encoding shape are supported. heads: a list of 2 int elems, heads[0] for x and head[1] for y. Used in multi-head, global-local, local-local MI maximization process. loss_type: only InfoNCE loss supported currently. @@ -51,7 +53,10 @@ def _get_encoder(self, obs: Union[int, SequenceType], heads: int): encoder = FCEncoder(obs[0], hidden_size_list) else: hidden_size_list = [32, 64, 64, self._embed_dim * heads] - encoder = ConvEncoder(obs, hidden_size_list) + if obs[-1] >= 36: + encoder = ConvEncoder(obs, hidden_size_list) + else: + encoder = ConvEncoder(obs, hidden_size_list, kernel_size=[4, 3, 2], stride=[2, 1, 1]) return encoder def forward(self, x: torch.Tensor, y: torch.Tensor): diff --git a/ding/utils/tests/test_mi_estimator.py b/ding/utils/tests/test_mi_estimator.py index 1eb56ecdc4..97bc423f12 100644 --- a/ding/utils/tests/test_mi_estimator.py +++ b/ding/utils/tests/test_mi_estimator.py @@ -3,15 +3,15 @@ import torch from ding.utils.mi_estimator import ContrastiveLoss from torch.utils.data import TensorDataset, DataLoader -# from torch.utils.tensorboard import SummaryWriter -@pytest.mark.benchmark +@pytest.mark.unittest @pytest.mark.parametrize('noise', [0.1, 1.0, 3.0]) -def test_infonce_loss(noise): - batch_size = 64 - N_batch = 100 - x_dim = [batch_size * N_batch, 16] +@pytest.mark.parametrize('dims', [[16], [1, 16, 16]]) +def test_infonce_loss(noise, dims): + batch_size = 128 + N_batch = 10 + x_dim = [batch_size * N_batch] + dims embed_dim = 16 x = np.random.normal(0, 1, size=x_dim) @@ -21,8 +21,8 @@ def test_infonce_loss(noise): dataset = TensorDataset(torch.Tensor(x), torch.Tensor(y)) dataloader = DataLoader(dataset, batch_size=batch_size) optimizer = torch.optim.Adam(estimator.parameters(), lr=3e-4) - # writer = SummaryWriter() - for epoch in range(10): + + for epoch in range(3): train_loss = 0. test_loss = 0. for inputs in dataloader: @@ -37,10 +37,4 @@ def test_infonce_loss(noise): for inputs in dataloader: x, y = inputs outputs = estimator.forward(x, y) - test_loss += outputs - - # writer.add_scalar('Loss/train', train_loss / N_batch, epoch) - # writer.add_scalar('Loss/train', test_loss / N_batch, epoch) - # print('epoch {}: train loss {:.4f}, test_loss {:.4f}'.format(epoch, \ - # train_loss / N_batch, test_loss / N_batch)) - # writer.close() + test_loss += outputs.item() From b7bbc59a3cbe36b673bebddba8b31883fde1e40a Mon Sep 17 00:00:00 2001 From: lixuelin Date: Fri, 20 May 2022 12:11:22 +0800 Subject: [PATCH 003/229] add dim --- ding/policy/__init__.py | 2 +- ding/policy/dqn.py | 228 +++++++++++++++++++++++++++++++++++++ ding/utils/mi_estimator.py | 16 +-- 3 files changed, 237 insertions(+), 9 deletions(-) diff --git a/ding/policy/__init__.py b/ding/policy/__init__.py index 67a2eae4dd..8348c1cdcb 100644 --- a/ding/policy/__init__.py +++ b/ding/policy/__init__.py @@ -1,5 +1,5 @@ from .base_policy import Policy, CommandModePolicy, create_policy, get_policy_cls -from .dqn import DQNPolicy +from .dqn import DQNAuxPolicy, DQNPolicy from .iqn import IQNPolicy from .qrdqn import QRDQNPolicy from .c51 import C51Policy diff --git a/ding/policy/dqn.py b/ding/policy/dqn.py index 58122bcaf1..ac48a85acd 100644 --- a/ding/policy/dqn.py +++ b/ding/policy/dqn.py @@ -10,6 +10,7 @@ from ding.utils.data import default_collate, default_decollate from .base_policy import Policy from .common_utils import default_preprocess_learn +from ding.utils.mi_estimator import ContrastiveLoss @POLICY_REGISTRY.register('dqn') @@ -381,3 +382,230 @@ def default_model(self) -> Tuple[str, List[str]]: by import_names path. For DQN, ``ding.model.template.q_learning.DQN`` """ return 'dqn', ['ding.model.template.q_learning'] + + +@POLICY_REGISTRY.register('dqn_aux') +class DQNAuxPolicy(DQNPolicy): + """ + Overview: + Policy class of DQN algorithm, extended by auxiliary objectives. + Config: + == ==================== ======== ============== ======================================== ======================= + ID Symbol Type Default Value Description Other(Shape) + == ==================== ======== ============== ======================================== ======================= + 1 ``type`` str dqn | RL policy register name, refer to | This arg is optional, + | registry ``POLICY_REGISTRY`` | a placeholder + 2 ``cuda`` bool False | Whether to use cuda for network | This arg can be diff- + | erent from modes + 3 ``on_policy`` bool False | Whether the RL algorithm is on-policy + | or off-policy + 4 ``priority`` bool False | Whether use priority(PER) | Priority sample, + | update priority + 5 | ``priority_IS`` bool False | Whether use Importance Sampling Weight + | ``_weight`` | to correct biased update. If True, + | priority must be True. + 6 | ``discount_`` float 0.97, | Reward's future discount factor, aka. | May be 1 when sparse + | ``factor`` [0.95, 0.999] | gamma | reward env + 7 ``nstep`` int 1, | N-step reward discount sum for target + [3, 5] | q_value estimation + 8 | ``learn.update`` int 3 | How many updates(iterations) to train | This args can be vary + | ``per_collect`` | after collector's one collection. Only | from envs. Bigger val + | valid in serial training | means more off-policy + 9 | ``learn.multi`` bool False | whether to use multi gpu during + | ``_gpu`` + 10 | ``learn.batch_`` int 64 | The number of samples of an iteration + | ``size`` + 11 | ``learn.learning`` float 0.001 | Gradient step length of an iteration. + | ``_rate`` + 12 | ``learn.target_`` int 100 | Frequence of target network update. | Hard(assign) update + | ``update_freq`` + 13 | ``learn.ignore_`` bool False | Whether ignore done for target value | Enable it for some + | ``done`` | calculation. | fake termination env + 14 ``collect.n_sample`` int [8, 128] | The number of training samples of a | It varies from + | call of collector. | different envs + 15 | ``collect.unroll`` int 1 | unroll length of an iteration | In RNN, unroll_len>1 + | ``_len`` + 16 | ``other.eps.type`` str exp | exploration rate decay type | Support ['exp', + | 'linear']. + 17 | ``other.eps.`` float 0.95 | start value of exploration rate | [0,1] + | ``start`` + 18 | ``other.eps.`` float 0.1 | end value of exploration rate | [0,1] + | ``end`` + 19 | ``other.eps.`` int 10000 | decay length of exploration | greater than 0. set + | ``decay`` | decay=10000 means + | the exploration rate + | decay from start + | value to end value + | during decay length. + 20 | ``loss_ratio`` float 0.01 | the ratio of auxiliary loss to main | any real value, + | loss | typically [-0.1, 0.1]. + == ==================== ======== ============== ======================================== ======================= + """ + + config = dict( + type='dqn', + # (bool) Whether use cuda in policy + cuda=False, + # (bool) Whether learning policy is the same as collecting data policy(on-policy) + on_policy=False, + # (bool) Whether enable priority experience sample + priority=False, + # (bool) Whether use Importance Sampling Weight to correct biased update. If True, priority must be True. + priority_IS_weight=False, + # (float) Discount factor(gamma) for returns + discount_factor=0.97, + # (int) The number of step for calculating target q_value + nstep=1, + learn=dict( + # (bool) Whether to use multi gpu + multi_gpu=False, + # How many updates(iterations) to train after collector's one collection. + # Bigger "update_per_collect" means bigger off-policy. + # collect data -> update policy-> collect data -> ... + update_per_collect=3, + # (int) How many samples in a training batch + batch_size=64, + # (float) The step size of gradient descent + learning_rate=0.001, + # ============================================================== + # The following configs are algorithm-specific + # ============================================================== + # (int) Frequence of target network update. + target_update_freq=100, + # (bool) Whether ignore done(usually for max step termination env) + ignore_done=False, + ), + # collect_mode config + collect=dict( + # (int) Only one of [n_sample, n_episode] shoule be set + # n_sample=8, + # (int) Cut trajectories into pieces with length "unroll_len". + unroll_len=1, + ), + eval=dict(), + # other config + other=dict( + # Epsilon greedy with decay. + eps=dict( + # (str) Decay type. Support ['exp', 'linear']. + type='exp', + # (float) Epsilon start value + start=0.95, + # (float) Epsilon end value + end=0.1, + # (int) Decay length(env step) + decay=10000, + ), + replay_buffer=dict(replay_buffer_size=10000, ), + ), + loss_ratio=0.01, + ) + + def _init_learn(self) -> None: + super()._init_learn() + self._main_encoder = self._model.encoder + x_size, y_size = self._get_encoding_size() + self._aux_model = ContrastiveLoss(x_size, y_size, **self._cfg.aux_model) + if self._cuda: + self._aux_model.cuda() + self._aux_optimizer = Adam(self._aux_model.parameters(), lr=self._cfg.learn.learning_rate) + self._aux_ratio = self._cfg.loss_ratio + + def _get_encoding_size(self): + test_data = { + "obs": torch.randn(1, *self._cfg.model.obs_shape), + "next_obs": torch.randn(1, *self._cfg.model.obs_shape), + } + with torch.no_grad(): + x, y = self._aux_encode(test_data) + return x.size()[1:], y.size()[1:] + + def _aux_encode(self, data): + x = data["obs"] + y = self._main_encoder(data["obs"]) + return x, y + + def _forward_learn(self, data: Dict[str, Any]) -> Dict[str, Any]: + """ + Overview: + Forward computation graph of learn mode(updating policy). + Arguments: + - data (:obj:`Dict[str, Any]`): Dict type data, a batch of data for training, values are torch.Tensor or \ + np.ndarray or dict/list combinations. + Returns: + - info_dict (:obj:`Dict[str, Any]`): Dict type data, a info dict indicated training result, which will be \ + recorded in text log and tensorboard, values are python scalar or a list of scalars. + ArgumentsKeys: + - necessary: ``obs``, ``action``, ``reward``, ``next_obs``, ``done`` + - optional: ``value_gamma``, ``IS`` + ReturnsKeys: + - necessary: ``cur_lr``, ``total_loss``, ``priority`` + - optional: ``action_distribution`` + """ + data = default_preprocess_learn( + data, + use_priority=self._priority, + use_priority_IS_weight=self._cfg.priority_IS_weight, + ignore_done=self._cfg.learn.ignore_done, + use_nstep=True + ) + if self._cuda: + data = to_device(data, self._device) + + # ==================== + # Q-learning forward + # ==================== + self._learn_model.train() + self._target_model.train() + # Current q value (main model) + q_value = self._learn_model.forward(data['obs'])['logit'] + # Target q value + with torch.no_grad(): + target_q_value = self._target_model.forward(data['next_obs'])['logit'] + # Max q value action (main model) + target_q_action = self._learn_model.forward(data['next_obs'])['action'] + + # ====================== + # Auxiliary model update + # ====================== + with torch.no_grad(): + x, y = self._aux_encode(data) + aux_loss_learn = self._aux_model.forward(x, y) + self._aux_optimizer.zero_grad() + aux_loss_learn.backward() + self._aux_optimizer.step() + + data_n = q_nstep_td_data( + q_value, target_q_value, data['action'], target_q_action, data['reward'], data['done'], data['weight'] + ) + value_gamma = data.get('value_gamma') + loss, td_error_per_sample = q_nstep_td_error(data_n, self._gamma, nstep=self._nstep, value_gamma=value_gamma) + + # ====================== + # Compute auxiliary loss + # ====================== + aux_loss_eval = self._aux_model.forward(x, y) * self._aux_ratio + loss += aux_loss_eval + + # ==================== + # Q-learning update + # ==================== + self._optimizer.zero_grad() + loss.backward() + if self._cfg.learn.multi_gpu: + self.sync_gradients(self._learn_model) + self._optimizer.step() + + # ============= + # after update + # ============= + self._target_model.update(self._learn_model.state_dict()) + return { + 'cur_lr': self._optimizer.defaults['lr'], + 'total_loss': loss.item(), + 'aux_loss': aux_loss_eval.item(), + 'q_value': q_value.mean().item(), + 'priority': td_error_per_sample.abs().tolist(), + # Only discrete action satisfying len(data['action'])==1 can return this and draw histogram on tensorboard. + # '[histogram]action_distribution': data['action'], + } diff --git a/ding/utils/mi_estimator.py b/ding/utils/mi_estimator.py index 6eb5c2ed86..c99fa7b0cb 100644 --- a/ding/utils/mi_estimator.py +++ b/ding/utils/mi_estimator.py @@ -19,7 +19,7 @@ def __init__( x_dim: Union[int, SequenceType], y_dim: Union[int, SequenceType], heads: SequenceType = [1, 1], - embed_dim: int = 64, + encode_shape: int = 64, loss_type: str = "infonce", temperature: float = 1.0, ) -> None: @@ -37,7 +37,7 @@ def __init__( assert loss_type.lower() in ["infonce"] self._type = loss_type.lower() - self._embed_dim = embed_dim + self._encode_shape = encode_shape self._heads = heads self._x_encoder = self._get_encoder(x_dim, heads[0]) self._y_encoder = self._get_encoder(y_dim, heads[1]) @@ -49,10 +49,10 @@ def _get_encoder(self, obs: Union[int, SequenceType], heads: int): assert len(obs) in [1, 3] if len(obs) == 1: - hidden_size_list = [128, 128, self._embed_dim * heads] + hidden_size_list = [128, 128, self._encode_shape * heads] encoder = FCEncoder(obs[0], hidden_size_list) else: - hidden_size_list = [32, 64, 64, self._embed_dim * heads] + hidden_size_list = [32, 64, 64, self._encode_shape * heads] if obs[-1] >= 36: encoder = ConvEncoder(obs, hidden_size_list) else: @@ -71,11 +71,11 @@ def forward(self, x: torch.Tensor, y: torch.Tensor): N = x.size(0) x_heads, y_heads = self._heads - x = self._x_encoder.forward(x).reshape(N, x_heads, self._embed_dim) - y = self._y_encoder.forward(y).reshape(N, y_heads, self._embed_dim) + x = self._x_encoder.forward(x).reshape(N, x_heads, self._encode_shape) + y = self._y_encoder.forward(y).reshape(N, y_heads, self._encode_shape) - x_n = x.reshape(-1, self._embed_dim) - y_n = y.reshape(-1, self._embed_dim) + x_n = x.reshape(-1, self._encode_shape) + y_n = y.reshape(-1, self._encode_shape) # Inner product for positive samples. Outer product for negative. We need to do it this way # for the multiclass loss. For the outer product, we want a N x N x n_local x n_multi tensor. From 4516c04ea79be2e5d99c83560e008a294e71f47a Mon Sep 17 00:00:00 2001 From: lixuelin Date: Fri, 20 May 2022 14:02:57 +0800 Subject: [PATCH 004/229] fix style and pytest --- ding/policy/dqn.py | 3 ++- ding/utils/tests/test_mi_estimator.py | 6 +++--- 2 files changed, 5 insertions(+), 4 deletions(-) diff --git a/ding/policy/dqn.py b/ding/policy/dqn.py index ac48a85acd..6b5028d225 100644 --- a/ding/policy/dqn.py +++ b/ding/policy/dqn.py @@ -438,7 +438,8 @@ class DQNAuxPolicy(DQNPolicy): | value to end value | during decay length. 20 | ``loss_ratio`` float 0.01 | the ratio of auxiliary loss to main | any real value, - | loss | typically [-0.1, 0.1]. + | loss | typically in + | [-0.1, 0.1]. == ==================== ======== ============== ======================================== ======================= """ diff --git a/ding/utils/tests/test_mi_estimator.py b/ding/utils/tests/test_mi_estimator.py index 97bc423f12..f840cd2ebb 100644 --- a/ding/utils/tests/test_mi_estimator.py +++ b/ding/utils/tests/test_mi_estimator.py @@ -5,7 +5,7 @@ from torch.utils.data import TensorDataset, DataLoader -@pytest.mark.unittest +@pytest.mark.lxl @pytest.mark.parametrize('noise', [0.1, 1.0, 3.0]) @pytest.mark.parametrize('dims', [[16], [1, 16, 16]]) def test_infonce_loss(noise, dims): @@ -13,11 +13,11 @@ def test_infonce_loss(noise, dims): N_batch = 10 x_dim = [batch_size * N_batch] + dims - embed_dim = 16 + encode_shape = 16 x = np.random.normal(0, 1, size=x_dim) y = x ** 2 + noise * np.random.normal(0, 1, size=x_dim) - estimator = ContrastiveLoss(x.shape[1:], y.shape[1:], embed_dim=embed_dim) + estimator = ContrastiveLoss(x.shape[1:], y.shape[1:], encode_shape=encode_shape) dataset = TensorDataset(torch.Tensor(x), torch.Tensor(y)) dataloader = DataLoader(dataset, batch_size=batch_size) optimizer = torch.optim.Adam(estimator.parameters(), lr=3e-4) From c966469035c51e76eba5eec4112f94d115f30d13 Mon Sep 17 00:00:00 2001 From: lixuelin Date: Fri, 20 May 2022 14:17:02 +0800 Subject: [PATCH 005/229] fix style and pytest --- ding/policy/dqn.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ding/policy/dqn.py b/ding/policy/dqn.py index 6b5028d225..c4c5e16500 100644 --- a/ding/policy/dqn.py +++ b/ding/policy/dqn.py @@ -438,7 +438,7 @@ class DQNAuxPolicy(DQNPolicy): | value to end value | during decay length. 20 | ``loss_ratio`` float 0.01 | the ratio of auxiliary loss to main | any real value, - | loss | typically in + | loss | typically in | [-0.1, 0.1]. == ==================== ======== ============== ======================================== ======================= """ From b27c3dbea0715eb4f2f85ab7765e86600327499e Mon Sep 17 00:00:00 2001 From: lixuelin Date: Fri, 20 May 2022 15:22:29 +0800 Subject: [PATCH 006/229] add dqn_dim test --- ding/entry/tests/test_serial_entry.py | 14 ++++ ding/policy/dqn.py | 7 +- ding/utils/tests/test_mi_estimator.py | 2 +- .../config/serial/pong/pong_dqn_aux_config.py | 65 ++++++++++++++++++ .../config/cartpole_dqn_aux_config.py | 67 +++++++++++++++++++ 5 files changed, 152 insertions(+), 3 deletions(-) create mode 100644 dizoo/atari/config/serial/pong/pong_dqn_aux_config.py create mode 100644 dizoo/classic_control/cartpole/config/cartpole_dqn_aux_config.py diff --git a/ding/entry/tests/test_serial_entry.py b/ding/entry/tests/test_serial_entry.py index f68edb4a15..7d5bc4bbc7 100644 --- a/ding/entry/tests/test_serial_entry.py +++ b/ding/entry/tests/test_serial_entry.py @@ -6,6 +6,7 @@ from ding.entry import serial_pipeline, collect_demo_data, serial_pipeline_offline from dizoo.classic_control.cartpole.config.cartpole_dqn_config import cartpole_dqn_config, cartpole_dqn_create_config +from dizoo.classic_control.cartpole.config.cartpole_dqn_aux_config import cartpole_dqn_aux_config, cartpole_dqn_aux_create_config from dizoo.classic_control.cartpole.config.cartpole_ppo_config import cartpole_ppo_config, cartpole_ppo_create_config from dizoo.classic_control.cartpole.config.cartpole_offppo_config import cartpole_offppo_config, \ cartpole_offppo_create_config @@ -101,6 +102,19 @@ def test_hybrid_mpdqn(): assert False, "pipeline fail" +@pytest.mark.unittest +def test_dqn_aux(): + config = [deepcopy(cartpole_dqn_aux_config), deepcopy(cartpole_dqn_aux_create_config)] + config[0].policy.learn.update_per_collect = 1 + config[0].exp_name = 'cartpole_dqn_aux_unittest' + try: + serial_pipeline(config, seed=0, max_train_iter=1) + except Exception: + assert False, "pipeline fail" + finally: + os.popen('rm -rf cartpole_dqn_aux_unittest') + + @pytest.mark.unittest def test_td3(): config = [deepcopy(pendulum_td3_config), deepcopy(pendulum_td3_create_config)] diff --git a/ding/policy/dqn.py b/ding/policy/dqn.py index c4c5e16500..915f6d6286 100644 --- a/ding/policy/dqn.py +++ b/ding/policy/dqn.py @@ -513,9 +513,12 @@ def _init_learn(self) -> None: self._aux_ratio = self._cfg.loss_ratio def _get_encoding_size(self): + obs = self._cfg.model.obs_shape + if isinstance(obs, int): + obs = [obs] test_data = { - "obs": torch.randn(1, *self._cfg.model.obs_shape), - "next_obs": torch.randn(1, *self._cfg.model.obs_shape), + "obs": torch.randn(1, *obs), + "next_obs": torch.randn(1, *obs), } with torch.no_grad(): x, y = self._aux_encode(test_data) diff --git a/ding/utils/tests/test_mi_estimator.py b/ding/utils/tests/test_mi_estimator.py index f840cd2ebb..dcb7d516d0 100644 --- a/ding/utils/tests/test_mi_estimator.py +++ b/ding/utils/tests/test_mi_estimator.py @@ -5,7 +5,7 @@ from torch.utils.data import TensorDataset, DataLoader -@pytest.mark.lxl +@pytest.mark.unittest @pytest.mark.parametrize('noise', [0.1, 1.0, 3.0]) @pytest.mark.parametrize('dims', [[16], [1, 16, 16]]) def test_infonce_loss(noise, dims): diff --git a/dizoo/atari/config/serial/pong/pong_dqn_aux_config.py b/dizoo/atari/config/serial/pong/pong_dqn_aux_config.py new file mode 100644 index 0000000000..86256b2b5c --- /dev/null +++ b/dizoo/atari/config/serial/pong/pong_dqn_aux_config.py @@ -0,0 +1,65 @@ +from easydict import EasyDict + +pong_dqn_aux_config = dict( + exp_name='pong_dqn_seed0', + env=dict( + collector_env_num=8, + evaluator_env_num=8, + n_evaluator_episode=8, + stop_value=20, + env_id='PongNoFrameskip-v4', + frame_stack=4, + ), + policy=dict( + cuda=True, + priority=False, + model=dict( + obs_shape=[4, 84, 84], + action_shape=6, + encoder_hidden_size_list=[128, 128, 512], + ), + aux_model=dict( + encode_shape=64, + heads = [1, 1], + loss_type = 'infonce', + temperature = 1.0, + ), + loss_ratio = 0.05, + nstep=3, + discount_factor=0.99, + learn=dict( + update_per_collect=10, + batch_size=128, + learning_rate=0.0001, + target_update_freq=500, + ), + collect=dict(n_sample=96, ), + eval=dict(evaluator=dict(eval_freq=4000, )), + other=dict( + eps=dict( + type='exp', + start=1., + end=0.05, + decay=250000, + ), + replay_buffer=dict(replay_buffer_size=100000, ), + ), + ), +) +pong_dqn_aux_config = EasyDict(pong_dqn_aux_config) +main_config = pong_dqn_aux_config +pong_dqn_aux_create_config = dict( + env=dict( + type='atari', + import_names=['dizoo.atari.envs.atari_env'], + ), + env_manager=dict(type='subprocess'), + policy=dict(type='dqn'), +) +pong_dqn_aux_create_config = EasyDict(pong_dqn_aux_create_config) +create_config = pong_dqn_aux_create_config + +if __name__ == '__main__': + # or you can enter `ding -m serial -c pong_dqn_config.py -s 0` + from ding.entry import serial_pipeline + serial_pipeline((main_config, create_config), seed=0) diff --git a/dizoo/classic_control/cartpole/config/cartpole_dqn_aux_config.py b/dizoo/classic_control/cartpole/config/cartpole_dqn_aux_config.py new file mode 100644 index 0000000000..8a40ee3aa1 --- /dev/null +++ b/dizoo/classic_control/cartpole/config/cartpole_dqn_aux_config.py @@ -0,0 +1,67 @@ +from easydict import EasyDict + +cartpole_dqn_aux_config = dict( + exp_name='cartpole_dqn_seed0', + env=dict( + collector_env_num=8, + evaluator_env_num=5, + n_evaluator_episode=5, + stop_value=195, + replay_path='cartpole_dqn_seed0/video', + ), + policy=dict( + cuda=False, + load_path='cartpole_dqn_seed0/ckpt/ckpt_best.pth.tar', # necessary for eval + model=dict( + obs_shape=4, + action_shape=2, + encoder_hidden_size_list=[128, 128, 64], + dueling=True, + ), + aux_model=dict( + encode_shape=64, + heads = [1, 1], + loss_type = 'infonce', + temperature = 1.0, + ), + loss_ratio = 0.05, + nstep=1, + discount_factor=0.97, + learn=dict( + batch_size=64, + learning_rate=0.001, + ), + collect=dict(n_sample=8), + eval=dict(evaluator=dict(eval_freq=40, )), + other=dict( + eps=dict( + type='exp', + start=0.95, + end=0.1, + decay=10000, + ), + replay_buffer=dict(replay_buffer_size=20000, ), + ), + ), +) +cartpole_dqn_aux_config = EasyDict(cartpole_dqn_aux_config) +main_config = cartpole_dqn_aux_config +cartpole_dqn_aux_create_config = dict( + env=dict( + type='cartpole', + import_names=['dizoo.classic_control.cartpole.envs.cartpole_env'], + ), + env_manager=dict(type='base'), + policy=dict(type='dqn'), + replay_buffer=dict( + type='deque', + import_names=['ding.data.buffer.deque_buffer_wrapper'] + ), +) +cartpole_dqn_aux_create_config = EasyDict(cartpole_dqn_aux_create_config) +create_config = cartpole_dqn_aux_create_config + +if __name__ == "__main__": + # or you can enter `ding -m serial -c cartpole_dqn_config.py -s 0` + from ding.entry import serial_pipeline + serial_pipeline((main_config, create_config), seed=0) From 4bc5a7719af4d1ef382946f6863ead1cd73e98e2 Mon Sep 17 00:00:00 2001 From: lixuelin Date: Fri, 20 May 2022 16:24:06 +0800 Subject: [PATCH 007/229] fix style --- ding/entry/tests/test_serial_entry.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/ding/entry/tests/test_serial_entry.py b/ding/entry/tests/test_serial_entry.py index 7d5bc4bbc7..db0f494004 100644 --- a/ding/entry/tests/test_serial_entry.py +++ b/ding/entry/tests/test_serial_entry.py @@ -6,7 +6,8 @@ from ding.entry import serial_pipeline, collect_demo_data, serial_pipeline_offline from dizoo.classic_control.cartpole.config.cartpole_dqn_config import cartpole_dqn_config, cartpole_dqn_create_config -from dizoo.classic_control.cartpole.config.cartpole_dqn_aux_config import cartpole_dqn_aux_config, cartpole_dqn_aux_create_config +from dizoo.classic_control.cartpole.config.cartpole_dqn_aux_config import cartpole_dqn_aux_config, \ + cartpole_dqn_aux_create_config from dizoo.classic_control.cartpole.config.cartpole_ppo_config import cartpole_ppo_config, cartpole_ppo_create_config from dizoo.classic_control.cartpole.config.cartpole_offppo_config import cartpole_offppo_config, \ cartpole_offppo_create_config From a027f6151c14c9c992d3df2d2db7abc2a1f3612f Mon Sep 17 00:00:00 2001 From: lixuelin Date: Fri, 20 May 2022 17:48:17 +0800 Subject: [PATCH 008/229] refine descriptions --- ding/utils/mi_estimator.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/ding/utils/mi_estimator.py b/ding/utils/mi_estimator.py index c99fa7b0cb..1507757074 100644 --- a/ding/utils/mi_estimator.py +++ b/ding/utils/mi_estimator.py @@ -77,20 +77,20 @@ def forward(self, x: torch.Tensor, y: torch.Tensor): x_n = x.reshape(-1, self._encode_shape) y_n = y.reshape(-1, self._encode_shape) - # Inner product for positive samples. Outer product for negative. We need to do it this way - # for the multiclass loss. For the outer product, we want a N x N x n_local x n_multi tensor. + # Use inner product to obtain postive samples. + # [N, x_heads, encode_dim] * [N, encode_dim, y_heads] -> [N, x_heads, y_heads] u_pos = torch.matmul(x, y.permute(0, 2, 1)).unsqueeze(2) + # Use outer product to obtain all sample permutations. + # [N * x_heads, encode_dim] X [encode_dim, N * y_heads] -> [N * x_heads, N * y_heads] u_all = torch.mm(y_n, x_n.t()).reshape(N, y_heads, N, x_heads).permute(0, 2, 3, 1) - # We need to mask the diagonal part of the negative tensor. + # Mask the diagonal part to obtain the negative samples, with all diagonals setting to -10. mask = torch.eye(N)[:, :, None, None].to(x.device) n_mask = 1 - mask - - # Masking is done by shifting the diagonal before exp. - u_neg = (n_mask * u_all) - (10. * (1 - n_mask)) # mask out "self" examples, all diagonals are set to -10. + u_neg = (n_mask * u_all) - (10. * (1 - n_mask)) u_neg = u_neg.reshape(N, N * x_heads, y_heads).unsqueeze(dim=1).expand(-1, x_heads, -1, -1) - # Since this is multiclass, we concat the positive along the class dimension before performing log softmax. + # Concatenate postive and negative samples and apply log softmax. pred_lgt = torch.cat([u_pos, u_neg], dim=2) pred_log = F.log_softmax(pred_lgt * self._temperature, dim=2) From df87665b6c54fb625d50b682f06ce7ffe0f1e1a8 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 24 May 2022 14:44:17 +0800 Subject: [PATCH 009/229] initial commit of envs --- dizoo/distar/__init__.py | 0 dizoo/distar/envs/__init__.py | 1 + dizoo/distar/envs/distar_env.py | 113 ++++++ dizoo/distar/envs/test_distar_config.yaml | 16 + dizoo/distar/envs/test_distar_env.py | 63 ++++ dizoo/distar/envs/test_distar_env2.py | 333 ++++++++++++++++++ .../distar/envs/test_distar_env_time_space.py | 88 +++++ 7 files changed, 614 insertions(+) create mode 100644 dizoo/distar/__init__.py create mode 100644 dizoo/distar/envs/__init__.py create mode 100644 dizoo/distar/envs/distar_env.py create mode 100644 dizoo/distar/envs/test_distar_config.yaml create mode 100644 dizoo/distar/envs/test_distar_env.py create mode 100644 dizoo/distar/envs/test_distar_env2.py create mode 100644 dizoo/distar/envs/test_distar_env_time_space.py diff --git a/dizoo/distar/__init__.py b/dizoo/distar/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/dizoo/distar/envs/__init__.py b/dizoo/distar/envs/__init__.py new file mode 100644 index 0000000000..10f49bdbca --- /dev/null +++ b/dizoo/distar/envs/__init__.py @@ -0,0 +1 @@ +from .distar_env import DIStarEnv \ No newline at end of file diff --git a/dizoo/distar/envs/distar_env.py b/dizoo/distar/envs/distar_env.py new file mode 100644 index 0000000000..4b5c2fa394 --- /dev/null +++ b/dizoo/distar/envs/distar_env.py @@ -0,0 +1,113 @@ +from distar.envs.env import SC2Env + +from ding.envs import BaseEnv +from distar.agent.default.lib.actions import ACTIONS, NUM_ACTIONS +from distar.agent.default.lib.features import MAX_DELAY, SPATIAL_SIZE, MAX_SELECTED_UNITS_NUM +from distar.pysc2.lib.action_dict import ACTIONS_STAT +import torch +import random + +class DIStarEnv(SC2Env,BaseEnv): + + def __init__(self,cfg): + super(DIStarEnv, self).__init__(cfg) + + def reset(self): + return super(DIStarEnv,self).reset() + + def close(self): + super(DIStarEnv,self).close() + + def step(self,actions): + # In DI-engine, the return of BaseEnv.step is ('obs', 'reward', 'done', 'info') + # Here in DI-star, the return is ({'raw_obs': self._obs[agent_idx], 'opponent_obs': opponent_obs, 'action_result': self._action_result[agent_idx]}, reward, episode_complete) + return super(DIStarEnv,self).step(actions) + + def seed(self, seed, dynamic_seed=False): + self._random_seed = seed + + @property + def observation_space(self): + #TODO + pass + + @property + def action_space(self): + #TODO + pass + + def random_action(self, obs): + raw = obs[0]['raw_obs'].observation.raw_data + + all_unit_types = set() + self_unit_types = set() + + for u in raw.units: + # Here we select the units except “buildings that are in building progress” for simplification + if u.build_progress == 1: + all_unit_types.add(u.unit_type) + if u.alliance == 1: + self_unit_types.add(u.unit_type) + + avail_actions = [ + {0: {'exist_selected_types':[], 'exist_target_types':[]}}, + {168:{'exist_selected_types':[], 'exist_target_types':[]}} + ] # no_op and raw_move_camera don't have seleted_units + + for action_id, action in ACTIONS_STAT.items(): + exist_selected_types = list(self_unit_types.intersection(set(action['selected_type']))) + exist_target_types = list(all_unit_types.intersection(set(action['target_type']))) + + # if an action should have target, but we don't have valid target in this observation, then discard this action + if len(action['target_type']) != 0 and len(exist_target_types) == 0: + continue + + if len(exist_selected_types) > 0: + avail_actions.append({action_id: {'exist_selected_types':exist_selected_types, 'exist_target_types':exist_target_types}}) + + current_action = random.choice(avail_actions) + func_id, exist_types = current_action.popitem() + + if func_id not in [0, 168]: + correspond_selected_units = [u.tag for u in raw.units if u.unit_type in exist_types['exist_selected_types'] and u.build_progress == 1] + correspond_targets = [u.tag for u in raw.units if u.unit_type in exist_types['exist_target_types'] and u.build_progress == 1] + + num_selected_unit = random.randint(0, min(MAX_SELECTED_UNITS_NUM, len(correspond_selected_units))) + + unit_tags = random.sample(correspond_selected_units, num_selected_unit) + target_unit_tag = random.choice(correspond_targets) if len(correspond_targets) > 0 else None + + else: + unit_tags = [] + target_unit_tag = None + + data = { + 'func_id': func_id, + 'skip_steps': random.randint(0, MAX_DELAY - 1), + # 'skip_steps': 8, + 'queued': random.randint(0, 1), + 'unit_tags': unit_tags, + 'target_unit_tag': target_unit_tag, + 'location': ( + random.randint(0, SPATIAL_SIZE[0] - 1), + random.randint(0, SPATIAL_SIZE[1] - 1) + ) + } + return {0:[data]} + + + @property + def reward_space(self): + + #TODO + pass + + def __repr__(self): + return "DI-engine DI-star Env" + +# if __name__ == '__main__': +# no_target_unit_actions = sorted([action['func_id'] for action in ACTIONS if action['target_unit'] == False]) +# no_target_unit_actions_dict = sorted([action_id for action_id, action in ACTIONS_STAT.items() if len(action['target_type']) == 0]) +# print(no_target_unit_actions) +# print(no_target_unit_actions_dict) +# assert no_target_unit_actions == no_target_unit_actions_dict diff --git a/dizoo/distar/envs/test_distar_config.yaml b/dizoo/distar/envs/test_distar_config.yaml new file mode 100644 index 0000000000..a3322baa54 --- /dev/null +++ b/dizoo/distar/envs/test_distar_config.yaml @@ -0,0 +1,16 @@ +actor: + job_type: 'train' # ['train', 'eval', 'train_test', 'eval_test'] +env: + map_name: 'KingsCove' + player_ids: ['agent1', 'bot10'] + races: ['zerg', 'zerg'] + map_size_resolutions: [True, True] # if True, ignore minimap_resolutions + minimap_resolutions: [[160, 152], [160, 152]] + realtime: False + replay_dir: '.' + random_seed: 'none' + game_steps_per_episode: 100000 + update_bot_obs: False + save_replay_episodes: 1 + update_both_obs: False + version: '4.10.0' \ No newline at end of file diff --git a/dizoo/distar/envs/test_distar_env.py b/dizoo/distar/envs/test_distar_env.py new file mode 100644 index 0000000000..6e25788431 --- /dev/null +++ b/dizoo/distar/envs/test_distar_env.py @@ -0,0 +1,63 @@ +import os +import shutil +import argparse + +from distar.ctools.utils import read_config, deep_merge_dicts +from distar.actor import Actor +import torch +import random +import time + +class TestDIstarEnv: + def __init__(self): + + cfg = read_config('C:/Users/hjs/DI-engine/dizoo/distar/envs/test_distar_config.yaml') + self._whole_cfg = cfg + self._whole_cfg.env.map_name = 'KingsCove' + + def _inference_loop(self, job={}): + from dizoo.distar.envs import DIStarEnv + import traceback + + torch.set_num_threads(1) + + self._env = DIStarEnv(self._whole_cfg) + + with torch.no_grad(): + for _ in range(5): + try: + observations, game_info, map_name = self._env.reset() + + for iter in range(1000): # one episode loop + # agent step + actions = self._env.random_action(observations) + # env step + next_observations, reward, done = self._env.step(actions) + if not done: + observations = next_observations + else: + break + + except Exception as e: + print('[EPISODE LOOP ERROR]', e, flush=True) + print(''.join(traceback.format_tb(e.__traceback__)), flush=True) + self._env.close() + self._env.close() + +if __name__ == '__main__': + + ## main + if os.path.exists(r'C:\Program Files (x86)\StarCraft II'): + sc2path = r'C:\Program Files (x86)\StarCraft II' + elif os.path.exists('/Applications/StarCraft II'): + sc2path = '/Applications/StarCraft II' + else: + assert 'SC2PATH' in os.environ.keys(), 'please add StarCraft2 installation path to your environment variables!' + sc2path = os.environ['SC2PATH'] + assert os.path.exists(sc2path), 'SC2PATH: {} does not exist!'.format(sc2path) + if not os.path.exists(os.path.join(sc2path, 'Maps/Ladder2019Season2')): + shutil.copytree(os.path.join(os.path.dirname(__file__), '../envs/maps/Ladder2019Season2'), os.path.join(sc2path, 'Maps/Ladder2019Season2')) + + ## actor_run + actor = TestDIstarEnv() + actor._inference_loop() \ No newline at end of file diff --git a/dizoo/distar/envs/test_distar_env2.py b/dizoo/distar/envs/test_distar_env2.py new file mode 100644 index 0000000000..5bc284ab3b --- /dev/null +++ b/dizoo/distar/envs/test_distar_env2.py @@ -0,0 +1,333 @@ +import os +import shutil +import argparse + +import os +import time +import traceback +import uuid +from collections import defaultdict +import torch +import torch.multiprocessing as mp +import random +import json +import platform + +from distar.agent.import_helper import import_module +from distar.ctools.utils import read_config, deep_merge_dicts +from distar.ctools.utils.log_helper import TextLogger, VariableRecord +from distar.ctools.worker.actor.actor_comm import ActorComm +from distar.actor import Actor +import torch +import random +import time + +from distar.ctools.worker.league.player import FRAC_ID +from distar_env import DIStarEnv +import traceback + +default_config = read_config('C:/Users/hjs/DI-star/distar/actor/actor_default_config.yaml') + +class TestDIstarEnv: + def __init__(self,cfg): + cfg = deep_merge_dicts(default_config, cfg) + self._whole_cfg = cfg + self._cfg = cfg.actor + self._job_type = cfg.actor.job_type + self._league_job_type = cfg.actor.get('league_job_type','test') + self._actor_uid = str(uuid.uuid1()) + self._gpu_batch_inference = self._cfg.get('gpu_batch_inference', False) + self._logger = TextLogger( + path=os.path.join(os.getcwd(), 'experiments', self._whole_cfg.common.experiment_name, 'actor_log'), + name=self._actor_uid) + if self._job_type == 'train': + self._comm = ActorComm(self._whole_cfg, self._actor_uid, self._logger) + self.max_job_duration = self._whole_cfg.communication.actor_ask_for_job_interval * random.uniform(0.7 , 1.3) + self._setup_agents() + + self._whole_cfg.env.map_name = 'KingsCove' + + def _setup_agents(self): + self.agents = [] + if self._job_type == 'train': + # comm setup agents + self._comm.ask_for_job(self) + else: + self.models = {} + map_names = [] + for idx, player_id in enumerate(self._cfg.player_ids): + if 'bot' in player_id: + continue + Agent = import_module(self._cfg.agents.get(player_id, 'default'), 'Agent') + agent = Agent(self._whole_cfg) + agent.player_id = player_id + agent.side_id = idx + self.agents.append(agent) + agent.side_id = idx + if agent.HAS_MODEL: + if player_id not in self.models.keys(): + if self._cfg.use_cuda: + assert 'test' in self._job_type, 'only test mode support gpu' + agent.model = agent.model.cuda() + else: + agent.model = agent.model.eval().share_memory() + if not self._cfg.fake_model: + state_dict = torch.load(self._cfg.model_paths[player_id], map_location='cpu') + if 'map_name' in state_dict: + map_names.append(state_dict['map_name']) + agent._fake_reward_prob = state_dict['fake_reward_prob'] + agent._z_path = state_dict['z_path'] + agent.z_idx = state_dict['z_idx'] + model_state_dict = {k: v for k, v in state_dict['model'].items() if + 'value_networks' not in k} + agent.model.load_state_dict(model_state_dict, strict=False) + self.models[player_id] = agent.model + else: + agent.model = self.models[player_id] + if len(map_names) == 1: + self._whole_cfg.env.map_name = map_names[0] + if len(map_names) == 2: + if not(map_names[0] == 'random' and map_names[1] != 'random'): + self._whole_cfg.env.map_name = 'NewRepugnancy' + if self._job_type == 'train_test': + teacher_models = {} + for idx, teacher_player_id in enumerate(self._cfg.teacher_player_ids): + if 'bot' in self._cfg.player_ids[idx]: + continue + agent = self.agents[idx] + agent.teacher_player_id = teacher_player_id + if agent.HAS_TEACHER_MODEL: + if teacher_player_id not in teacher_models.keys(): + if self._cfg.use_cuda: + agent.teacher_model = agent.teacher_model.cuda() + else: + agent.teacher_model = agent.teacher_model.eval() + if not self._cfg.fake_model: + state_dict = torch.load(self._cfg.teacher_model_paths[teacher_player_id], + map_location='cpu') + model_state_dict = {k: v for k, v in state_dict['model'].items() if + 'value_networks' not in k} + agent.teacher_model.load_state_dict(model_state_dict) + teacher_models[teacher_player_id] = agent.teacher_model + else: + agent.teacher_model = teacher_models[teacher_player_id] + + def _inference_loop(self, env_id=0, job={}, result_queue=None, pipe_c=None): + torch.set_num_threads(1) + frac_ids = job.get('frac_ids',[]) + env_info = job.get('env_info', {}) + races = [] + for frac_id in frac_ids: + races.append(random.choice(FRAC_ID[frac_id])) + if len(races) >0: + env_info['races']=races + mergerd_whole_cfg = deep_merge_dicts(self._whole_cfg, {'env': env_info}) + self._env = DIStarEnv(mergerd_whole_cfg) + + iter_count = 0 + if env_id == 0: + variable_record = VariableRecord(self._cfg.print_freq) + variable_record.register_var('agent_time') + variable_record.register_var('agent_time_per_agent') + variable_record.register_var('env_time') + if 'train' in self._job_type: + variable_record.register_var('post_process_time') + variable_record.register_var('post_process_per_agent') + variable_record.register_var('send_data_time') + variable_record.register_var('send_data_per_agent') + variable_record.register_var('send_data_per_agent') + variable_record.register_var('update_model_time') + + with torch.no_grad(): + episode_count = 0 + while episode_count < self._cfg.episode_num: + try: + game_start = time.time() + game_iters = 0 + observations, game_info, map_name = self._env.reset() + for idx in observations.keys(): + self.agents[idx].env_id = env_id + race = self._whole_cfg.env.races[idx] + self.agents[idx].reset(map_name, race, game_info[idx], observations[idx]) + + for iter in range(50): # one episode loop + # agent step + # if iter % 5 == 1: + # actions = {0: [{'func_id': 503, 'skip_steps': 0, 'queued': 0, 'unit_tags': [4350279681, 4350541825, 4350803969], + # 'target_unit_tag': 4309123073, 'location': (127, 17)}]} + # elif iter % 5 == 2: + # actions = {0: [{'func_id': 503, 'skip_steps': 9, 'queued': 0, + # 'unit_tags': [4346085377, 4346347521, 4346609665], 'target_unit_tag': 4345823233, 'location': (17, 121)}]} + # elif iter % 5 == 3: + # actions = {0: [{'func_id': 12, 'skip_steps': 8, 'queued': 0, + # 'unit_tags': [4350279681, 4350541825, 4350803969], 'target_unit_tag': 4309123073, 'location': (139, 16)}]} + # elif iter % 5 == 4: + # actions = {0: [{'func_id': 515, 'skip_steps': 3, 'queued': 0, + # 'unit_tags': [4350541825, 4350803969, 4358930433], 'target_unit_tag': 4309123073, 'location': (127, 15)}]} + # else: + # actions = {0: [{'func_id': 1, 'skip_steps': 10, 'queued': 0, + # 'unit_tags': [4354211841], 'target_unit_tag': 4350017537, 'location': (126, 27)}]} + + # agent step + agent_start_time = time.time() + agent_count = 0 + actions = {} + + players_obs = observations + for player_index, obs in players_obs.items(): + player_id = self.agents[player_index].player_id + if self._job_type == 'train': + self.agents[player_index]._model_last_iter = self._comm.model_last_iter_dict[player_id].item() + actions[player_index] = self.agents[player_index].step(obs) + agent_count += 1 + agent_time = time.time() - agent_start_time + + + # env step + env_start_time = time.time() + next_observations, reward, done = self._env.step(actions) + # print('reward: ', reward) + # print('next_observations', next_observations) + # print('done: ', done) + env_time = time.time() - env_start_time + next_players_obs = next_observations + time.sleep(1) + + # collect data + if 'train' in self._job_type: + post_process_time = 0 + post_process_count = 0 + send_data_time = 0 + send_data_count = 0 + for player_index, obs in next_players_obs.items(): + if self._job_type == 'train_test' or self.agents[player_index].player_id in self._comm.job[ + 'send_data_players']: + post_process_start_time = time.time() + traj_data = self.agents[player_index].collect_data(next_players_obs[player_index], + reward[player_index], done, player_index) + post_process_time += time.time() - post_process_start_time + post_process_count += 1 + if traj_data is not None and self._job_type == 'train': + send_data_start_time = time.time() + self._comm.send_data(traj_data, self.agents[player_index].player_id) + send_data_time += time.time() - send_data_start_time + send_data_count += 1 + else: + self.agents[player_index].update_fake_reward(next_players_obs[player_index]) + + # update log + iter_count += 1 + game_iters += 1 + if env_id == 0: + if 'train' in self._job_type: + variable_record.update_var( + {'agent_time': agent_time, + 'agent_time_per_agent': agent_time / (agent_count + 1e-6), + 'env_time': env_time, + }) + if post_process_count > 0: + variable_record.update_var( + {'post_process_time': post_process_time, + 'post_process_per_agent': post_process_time / post_process_count, + }) + if send_data_count > 0: + variable_record.update_var({ + 'send_data_time': send_data_time, + 'send_data_per_agent': send_data_time / send_data_count, + }) + + else: + variable_record.update_var({'agent_time': agent_time, + 'agent_time_per_agent': agent_time / (agent_count + 1e-6), + 'env_time': env_time, }) + self.iter_after_hook(iter_count, variable_record) + + if not done: + observations = next_observations + else: + players_obs = observations + if 'test' in self._whole_cfg and self._whole_cfg.test.get('tb_stat', False): + if not os.path.exists(self._env._result_dir): + os.makedirs(self._env._result_dir) + data = self.agents[0].get_stat_data() + path = os.path.join(self._env._result_dir, '{}_{}_{}_.json'.format(env_id, episode_count, player_index)) + with open(path, 'w') as f: + json.dump(data, f) + + if self._job_type == 'train': + player_idx = random.sample(players_obs.keys(), 1)[0] + game_steps = players_obs[player_idx]['raw_obs'].observation.game_loop + result_info = defaultdict(dict) + + for player_index in range(len(self.agents)): + player_id = self.agents[player_index].player_id + side_id = self.agents[player_index].side_id + race = self.agents[player_index].race + agent_iters = self.agents[player_index].iter_count + result_info[side_id]['race'] = race + result_info[side_id]['player_id'] = player_id + result_info[side_id]['opponent_id'] = self.agents[player_index].opponent_id + result_info[side_id]['winloss'] = reward[player_index] + result_info[side_id]['agent_iters'] = agent_iters + result_info[side_id].update(self.agents[player_index].get_unit_num_info()) + result_info[side_id].update(self.agents[player_index].get_stat_data()) + game_duration = time.time() - game_start + result_info['game_steps'] = game_steps + result_info['game_iters'] = game_iters + result_info['game_duration'] = game_duration + self._comm.send_result(result_info) + break + + except Exception as e: + print('[EPISODE LOOP ERROR]', e, flush=True) + print(''.join(traceback.format_tb(e.__traceback__)), flush=True) + self._env.close() + self._env.close() + if result_queue is not None: + print(os.getpid(), 'done') + result_queue.put('done') + time.sleep(1000000) + else: + return + def iter_after_hook(self, iter_count, variable_record): + if iter_count % self._cfg.print_freq == 0: + if hasattr(self,'_comm'): + variable_record.update_var({'update_model_time':self._comm._avg_update_model_time.item() }) + self._logger.info( + 'ACTOR({}):\n{}TimeStep{}{} {}'.format( + self._actor_uid, '=' * 35, iter_count, '=' * 35, + variable_record.get_vars_text() + ) + ) + +if __name__ == '__main__': + + ## main + if os.path.exists(r'C:\Program Files (x86)\StarCraft II'): + sc2path = r'C:\Program Files (x86)\StarCraft II' + elif os.path.exists('/Applications/StarCraft II'): + sc2path = '/Applications/StarCraft II' + else: + assert 'SC2PATH' in os.environ.keys(), 'please add StarCraft2 installation path to your environment variables!' + sc2path = os.environ['SC2PATH'] + assert os.path.exists(sc2path), 'SC2PATH: {} does not exist!'.format(sc2path) + if not os.path.exists(os.path.join(sc2path, 'Maps/Ladder2019Season2')): + shutil.copytree(os.path.join(os.path.dirname(__file__), '../envs/maps/Ladder2019Season2'), os.path.join(sc2path, 'Maps/Ladder2019Season2')) + + parser = argparse.ArgumentParser(description="rl_train") + parser.add_argument("--config", default='C:/Users/hjs/DI-star/distar/bin/user_config.yaml') + parser.add_argument("--type", default=None) + parser.add_argument("--task", default='bot') + parser.add_argument("--player_id", default='MP0') + parser.add_argument("--gpu_batch_inference", default='false') + parser.add_argument("--init_method", type=str, default=None) + parser.add_argument("--rank", type=int, default=0) + parser.add_argument("--world_size", type=int, default=1) + args = parser.parse_args() + config = read_config(args.config) + config.common.type = 'rl' + config.actor.traj_len = config.learner.data.trajectory_length + + ## actor_run + actor = TestDIstarEnv(config) + actor._inference_loop() \ No newline at end of file diff --git a/dizoo/distar/envs/test_distar_env_time_space.py b/dizoo/distar/envs/test_distar_env_time_space.py new file mode 100644 index 0000000000..d2f784a119 --- /dev/null +++ b/dizoo/distar/envs/test_distar_env_time_space.py @@ -0,0 +1,88 @@ +import os +import shutil +import argparse + +from distar.ctools.utils import read_config, deep_merge_dicts +from distar.actor import Actor +import torch +import random +import time +import sys + +class TestDIstarEnv: + def __init__(self): + + cfg = read_config('C:/Users/hjs/DI-star/ding-test/envs/test_distar_config.yaml') + self._whole_cfg = cfg + self._whole_cfg.env.map_name = 'KingsCove' + self._total_iters = 0 + self._total_time = 0 + self._total_space = 0 + + def _inference_loop(self, job={}): + from distar_env import DIStarEnv + import traceback + + torch.set_num_threads(1) + + self._env = DIStarEnv(self._whole_cfg) + + with torch.no_grad(): + for _ in range(5): + try: + observations, game_info, map_name = self._env.reset() + + for iter in range(1000): # one episode loop + # agent step + actions = self._env.random_action(observations) + # env step + before_step_time = time.time() + next_observations, reward, done = self._env.step(actions) + after_step_time = time.time() + + self._total_time += after_step_time - before_step_time + self._total_iters += 1 + self._total_space += sys.getsizeof((actions,observations,next_observations,reward,done)) + print('observations: ', sys.getsizeof(observations), ' Byte') + print('actions: ', sys.getsizeof(actions), ' Byte') + print('reward: ', sys.getsizeof(reward), ' Byte') + print('done: ', sys.getsizeof(done), ' Byte') + print('total: ', sys.getsizeof((actions,observations,next_observations,reward,done)),' Byte') + print(type(observations)) # dict + print(type(reward)) # list + print(type(done)) # bool + print(type(actions)) # dict + + + if not done: + observations = next_observations + else: + break + + except Exception as e: + print('[EPISODE LOOP ERROR]', e, flush=True) + print(''.join(traceback.format_tb(e.__traceback__)), flush=True) + self._env.close() + self._env.close() + + print('total iters:', self._total_iters) + print('average step time:', self._total_time/self._total_iters) + print('average step data space:', self._total_space/self._total_iters) + +if __name__ == '__main__': + + ## main + if os.path.exists(r'C:\Program Files (x86)\StarCraft II'): + sc2path = r'C:\Program Files (x86)\StarCraft II' + elif os.path.exists('/Applications/StarCraft II'): + sc2path = '/Applications/StarCraft II' + else: + assert 'SC2PATH' in os.environ.keys(), 'please add StarCraft2 installation path to your environment variables!' + sc2path = os.environ['SC2PATH'] + assert os.path.exists(sc2path), 'SC2PATH: {} does not exist!'.format(sc2path) + if not os.path.exists(os.path.join(sc2path, 'Maps/Ladder2019Season2')): + shutil.copytree(os.path.join(os.path.dirname(__file__), '../envs/maps/Ladder2019Season2'), os.path.join(sc2path, 'Maps/Ladder2019Season2')) + + ## actor_run + actor = TestDIstarEnv() + actor._inference_loop() \ No newline at end of file From 337684dbf81405144ca6355762d1440f3fbe448f Mon Sep 17 00:00:00 2001 From: lixuelin Date: Wed, 25 May 2022 15:53:38 +0800 Subject: [PATCH 010/229] polish infoNCE & ST-DIM --- ding/entry/tests/test_serial_entry.py | 12 +++---- ding/policy/__init__.py | 2 +- ding/policy/dqn.py | 11 +++--- ding/torch_utils/__init__.py | 2 +- ding/torch_utils/loss/__init__.py | 1 + .../loss/contrastive_loss.py} | 36 +++++++++---------- .../loss/tests/test_contrastive_loss.py} | 14 ++++++-- ...aux_config.py => pong_dqn_stdim_config.py} | 14 ++++---- ...config.py => cartpole_dqn_stdim_config.py} | 14 ++++---- 9 files changed, 59 insertions(+), 47 deletions(-) rename ding/{utils/mi_estimator.py => torch_utils/loss/contrastive_loss.py} (73%) rename ding/{utils/tests/test_mi_estimator.py => torch_utils/loss/tests/test_contrastive_loss.py} (78%) rename dizoo/atari/config/serial/pong/{pong_dqn_aux_config.py => pong_dqn_stdim_config.py} (83%) rename dizoo/classic_control/cartpole/config/{cartpole_dqn_aux_config.py => cartpole_dqn_stdim_config.py} (82%) diff --git a/ding/entry/tests/test_serial_entry.py b/ding/entry/tests/test_serial_entry.py index db0f494004..d88d8f861b 100644 --- a/ding/entry/tests/test_serial_entry.py +++ b/ding/entry/tests/test_serial_entry.py @@ -6,8 +6,8 @@ from ding.entry import serial_pipeline, collect_demo_data, serial_pipeline_offline from dizoo.classic_control.cartpole.config.cartpole_dqn_config import cartpole_dqn_config, cartpole_dqn_create_config -from dizoo.classic_control.cartpole.config.cartpole_dqn_aux_config import cartpole_dqn_aux_config, \ - cartpole_dqn_aux_create_config +from dizoo.classic_control.cartpole.config.cartpole_dqn_stdim_config import cartpole_dqn_stdim_config, \ + cartpole_dqn_stdim_create_config from dizoo.classic_control.cartpole.config.cartpole_ppo_config import cartpole_ppo_config, cartpole_ppo_create_config from dizoo.classic_control.cartpole.config.cartpole_offppo_config import cartpole_offppo_config, \ cartpole_offppo_create_config @@ -104,16 +104,16 @@ def test_hybrid_mpdqn(): @pytest.mark.unittest -def test_dqn_aux(): - config = [deepcopy(cartpole_dqn_aux_config), deepcopy(cartpole_dqn_aux_create_config)] +def test_dqn_stdim(): + config = [deepcopy(cartpole_dqn_stdim_config), deepcopy(cartpole_dqn_stdim_create_config)] config[0].policy.learn.update_per_collect = 1 - config[0].exp_name = 'cartpole_dqn_aux_unittest' + config[0].exp_name = 'cartpole_dqn_stdim_unittest' try: serial_pipeline(config, seed=0, max_train_iter=1) except Exception: assert False, "pipeline fail" finally: - os.popen('rm -rf cartpole_dqn_aux_unittest') + os.popen('rm -rf cartpole_dqn_stdim_unittest') @pytest.mark.unittest diff --git a/ding/policy/__init__.py b/ding/policy/__init__.py index 8348c1cdcb..8fa3a10a2f 100644 --- a/ding/policy/__init__.py +++ b/ding/policy/__init__.py @@ -1,5 +1,5 @@ from .base_policy import Policy, CommandModePolicy, create_policy, get_policy_cls -from .dqn import DQNAuxPolicy, DQNPolicy +from .dqn import DQNSTDIMPolicy, DQNPolicy from .iqn import IQNPolicy from .qrdqn import QRDQNPolicy from .c51 import C51Policy diff --git a/ding/policy/dqn.py b/ding/policy/dqn.py index 915f6d6286..d3f28f440f 100644 --- a/ding/policy/dqn.py +++ b/ding/policy/dqn.py @@ -10,7 +10,7 @@ from ding.utils.data import default_collate, default_decollate from .base_policy import Policy from .common_utils import default_preprocess_learn -from ding.utils.mi_estimator import ContrastiveLoss +from ding.torch_utils import ContrastiveLoss @POLICY_REGISTRY.register('dqn') @@ -384,8 +384,8 @@ def default_model(self) -> Tuple[str, List[str]]: return 'dqn', ['ding.model.template.q_learning'] -@POLICY_REGISTRY.register('dqn_aux') -class DQNAuxPolicy(DQNPolicy): +@POLICY_REGISTRY.register('dqn_stdim') +class DQNSTDIMPolicy(DQNPolicy): """ Overview: Policy class of DQN algorithm, extended by auxiliary objectives. @@ -573,8 +573,8 @@ def _forward_learn(self, data: Dict[str, Any]) -> Dict[str, Any]: # Auxiliary model update # ====================== with torch.no_grad(): - x, y = self._aux_encode(data) - aux_loss_learn = self._aux_model.forward(x, y) + x_no_grad, y_no_grad = self._aux_encode(data) + aux_loss_learn = self._aux_model.forward(x_no_grad, y_no_grad) self._aux_optimizer.zero_grad() aux_loss_learn.backward() self._aux_optimizer.step() @@ -588,6 +588,7 @@ def _forward_learn(self, data: Dict[str, Any]) -> Dict[str, Any]: # ====================== # Compute auxiliary loss # ====================== + x, y = self._aux_encode(data) aux_loss_eval = self._aux_model.forward(x, y) * self._aux_ratio loss += aux_loss_eval diff --git a/ding/torch_utils/__init__.py b/ding/torch_utils/__init__.py index 250c468233..ca48761136 100644 --- a/ding/torch_utils/__init__.py +++ b/ding/torch_utils/__init__.py @@ -2,9 +2,9 @@ from .data_helper import to_device, to_tensor, to_ndarray, to_list, to_dtype, same_shape, tensor_to_list, \ build_log_buffer, CudaFetcher, get_tensor_data, unsqueeze, get_null_data from .distribution import CategoricalPd, CategoricalPdPytorch -from .loss import * from .metric import levenshtein_distance, hamming_distance from .network import * +from .loss import * from .optimizer_helper import Adam, RMSprop, calculate_grad_norm, calculate_grad_norm_without_bias_two_norm from .nn_test_helper import is_differentiable from .math_helper import cov diff --git a/ding/torch_utils/loss/__init__.py b/ding/torch_utils/loss/__init__.py index e2795e2747..8668e53b98 100644 --- a/ding/torch_utils/loss/__init__.py +++ b/ding/torch_utils/loss/__init__.py @@ -1,2 +1,3 @@ from .cross_entropy_loss import LabelSmoothCELoss, SoftFocalLoss, build_ce_criterion from .multi_logits_loss import MultiLogitsLoss +from .contrastive_loss import ContrastiveLoss diff --git a/ding/utils/mi_estimator.py b/ding/torch_utils/loss/contrastive_loss.py similarity index 73% rename from ding/utils/mi_estimator.py rename to ding/torch_utils/loss/contrastive_loss.py index 1507757074..0ef3eb073f 100644 --- a/ding/utils/mi_estimator.py +++ b/ding/torch_utils/loss/contrastive_loss.py @@ -16,31 +16,31 @@ class ContrastiveLoss(nn.Module): def __init__( self, - x_dim: Union[int, SequenceType], - y_dim: Union[int, SequenceType], + x_size: Union[int, SequenceType], + y_size: Union[int, SequenceType], heads: SequenceType = [1, 1], encode_shape: int = 64, - loss_type: str = "infonce", + loss_type: str = "infoNCE", # Only the InfoNCE loss is available now. temperature: float = 1.0, ) -> None: """ Args: - x_dim: input dimensions for x, both the obs shape and the encoding shape are supported. - y_dim: input dimensions for y, both the obs shape and the encoding shape are supported. + x_size: input shape for x, both the obs shape and the encoding shape are supported. + y_size: input shape for y, both the obs shape and the encoding shape are supported. heads: a list of 2 int elems, heads[0] for x and head[1] for y. Used in multi-head, global-local, local-local MI maximization process. - loss_type: only InfoNCE loss supported currently. + loss_type: only the InfoNCE loss is available now. temperature: the parameter to adjust the log_softmax. """ super(ContrastiveLoss, self).__init__() - assert len(heads) == 2 + assert len(heads) == 2, "Expected length of 2, but got: {}".format(len(heads)) assert loss_type.lower() in ["infonce"] self._type = loss_type.lower() self._encode_shape = encode_shape self._heads = heads - self._x_encoder = self._get_encoder(x_dim, heads[0]) - self._y_encoder = self._get_encoder(y_dim, heads[1]) + self._x_encoder = self._get_encoder(x_size, heads[0]) + self._y_encoder = self._get_encoder(y_size, heads[1]) self._temperature = temperature def _get_encoder(self, obs: Union[int, SequenceType], heads: int): @@ -60,42 +60,42 @@ def _get_encoder(self, obs: Union[int, SequenceType], heads: int): return encoder def forward(self, x: torch.Tensor, y: torch.Tensor): - ''' + """ Computes the noise contrastive estimation-based loss, a.k.a. infoNCE. Args: x: the input x, both raw obs and encoding are supported. y: the input y, both raw obs and encoding are supported. Returns: torch.Tensor: loss value. - ''' + """ N = x.size(0) x_heads, y_heads = self._heads - x = self._x_encoder.forward(x).reshape(N, x_heads, self._encode_shape) - y = self._y_encoder.forward(y).reshape(N, y_heads, self._encode_shape) + x = self._x_encoder.forward(x).view(N, x_heads, self._encode_shape) + y = self._y_encoder.forward(y).view(N, y_heads, self._encode_shape) - x_n = x.reshape(-1, self._encode_shape) - y_n = y.reshape(-1, self._encode_shape) + x_n = x.view(-1, self._encode_shape) + y_n = y.view(-1, self._encode_shape) # Use inner product to obtain postive samples. # [N, x_heads, encode_dim] * [N, encode_dim, y_heads] -> [N, x_heads, y_heads] u_pos = torch.matmul(x, y.permute(0, 2, 1)).unsqueeze(2) # Use outer product to obtain all sample permutations. # [N * x_heads, encode_dim] X [encode_dim, N * y_heads] -> [N * x_heads, N * y_heads] - u_all = torch.mm(y_n, x_n.t()).reshape(N, y_heads, N, x_heads).permute(0, 2, 3, 1) + u_all = torch.mm(y_n, x_n.t()).view(N, y_heads, N, x_heads).permute(0, 2, 3, 1) # Mask the diagonal part to obtain the negative samples, with all diagonals setting to -10. mask = torch.eye(N)[:, :, None, None].to(x.device) n_mask = 1 - mask u_neg = (n_mask * u_all) - (10. * (1 - n_mask)) - u_neg = u_neg.reshape(N, N * x_heads, y_heads).unsqueeze(dim=1).expand(-1, x_heads, -1, -1) + u_neg = u_neg.view(N, N * x_heads, y_heads).unsqueeze(dim=1).expand(-1, x_heads, -1, -1) # Concatenate postive and negative samples and apply log softmax. pred_lgt = torch.cat([u_pos, u_neg], dim=2) pred_log = F.log_softmax(pred_lgt * self._temperature, dim=2) # The positive score is the first element of the log softmax. - loss = -pred_log[:, :, 0].mean() + loss = -pred_log[:, :, 0, :].mean() return loss def __call__(self, x: torch.Tensor, y: torch.Tensor): diff --git a/ding/utils/tests/test_mi_estimator.py b/ding/torch_utils/loss/tests/test_contrastive_loss.py similarity index 78% rename from ding/utils/tests/test_mi_estimator.py rename to ding/torch_utils/loss/tests/test_contrastive_loss.py index dcb7d516d0..8cbdec8f03 100644 --- a/ding/utils/tests/test_mi_estimator.py +++ b/ding/torch_utils/loss/tests/test_contrastive_loss.py @@ -1,14 +1,17 @@ import pytest import numpy as np import torch -from ding.utils.mi_estimator import ContrastiveLoss from torch.utils.data import TensorDataset, DataLoader +from ding.torch_utils import ContrastiveLoss @pytest.mark.unittest @pytest.mark.parametrize('noise', [0.1, 1.0, 3.0]) -@pytest.mark.parametrize('dims', [[16], [1, 16, 16]]) +@pytest.mark.parametrize('dims', [ + [16], +]) def test_infonce_loss(noise, dims): + print_loss = False batch_size = 128 N_batch = 10 x_dim = [batch_size * N_batch] + dims @@ -38,3 +41,10 @@ def test_infonce_loss(noise, dims): x, y = inputs outputs = estimator.forward(x, y) test_loss += outputs.item() + + if print_loss: + print( + "epoch {}: test_loss: {:.4f}, \t test_loss: {:.4f}".format( + epoch, train_loss / N_batch, test_loss / N_batch + ) + ) diff --git a/dizoo/atari/config/serial/pong/pong_dqn_aux_config.py b/dizoo/atari/config/serial/pong/pong_dqn_stdim_config.py similarity index 83% rename from dizoo/atari/config/serial/pong/pong_dqn_aux_config.py rename to dizoo/atari/config/serial/pong/pong_dqn_stdim_config.py index 86256b2b5c..2f91944bee 100644 --- a/dizoo/atari/config/serial/pong/pong_dqn_aux_config.py +++ b/dizoo/atari/config/serial/pong/pong_dqn_stdim_config.py @@ -1,7 +1,7 @@ from easydict import EasyDict -pong_dqn_aux_config = dict( - exp_name='pong_dqn_seed0', +pong_dqn_stdim_config = dict( + exp_name='pong_dqn_stdim_seed0', env=dict( collector_env_num=8, evaluator_env_num=8, @@ -46,9 +46,9 @@ ), ), ) -pong_dqn_aux_config = EasyDict(pong_dqn_aux_config) -main_config = pong_dqn_aux_config -pong_dqn_aux_create_config = dict( +pong_dqn_stdim_config = EasyDict(pong_dqn_stdim_config) +main_config = pong_dqn_stdim_config +pong_dqn_stdim_create_config = dict( env=dict( type='atari', import_names=['dizoo.atari.envs.atari_env'], @@ -56,8 +56,8 @@ env_manager=dict(type='subprocess'), policy=dict(type='dqn'), ) -pong_dqn_aux_create_config = EasyDict(pong_dqn_aux_create_config) -create_config = pong_dqn_aux_create_config +pong_dqn_stdim_create_config = EasyDict(pong_dqn_stdim_create_config) +create_config = pong_dqn_stdim_create_config if __name__ == '__main__': # or you can enter `ding -m serial -c pong_dqn_config.py -s 0` diff --git a/dizoo/classic_control/cartpole/config/cartpole_dqn_aux_config.py b/dizoo/classic_control/cartpole/config/cartpole_dqn_stdim_config.py similarity index 82% rename from dizoo/classic_control/cartpole/config/cartpole_dqn_aux_config.py rename to dizoo/classic_control/cartpole/config/cartpole_dqn_stdim_config.py index 8a40ee3aa1..0695d91475 100644 --- a/dizoo/classic_control/cartpole/config/cartpole_dqn_aux_config.py +++ b/dizoo/classic_control/cartpole/config/cartpole_dqn_stdim_config.py @@ -1,7 +1,7 @@ from easydict import EasyDict -cartpole_dqn_aux_config = dict( - exp_name='cartpole_dqn_seed0', +cartpole_dqn_stdim_config = dict( + exp_name='cartpole_dqn_stdim_seed0', env=dict( collector_env_num=8, evaluator_env_num=5, @@ -44,9 +44,9 @@ ), ), ) -cartpole_dqn_aux_config = EasyDict(cartpole_dqn_aux_config) -main_config = cartpole_dqn_aux_config -cartpole_dqn_aux_create_config = dict( +cartpole_dqn_stdim_config = EasyDict(cartpole_dqn_stdim_config) +main_config = cartpole_dqn_stdim_config +cartpole_dqn_stdim_create_config = dict( env=dict( type='cartpole', import_names=['dizoo.classic_control.cartpole.envs.cartpole_env'], @@ -58,8 +58,8 @@ import_names=['ding.data.buffer.deque_buffer_wrapper'] ), ) -cartpole_dqn_aux_create_config = EasyDict(cartpole_dqn_aux_create_config) -create_config = cartpole_dqn_aux_create_config +cartpole_dqn_stdim_create_config = EasyDict(cartpole_dqn_stdim_create_config) +create_config = cartpole_dqn_stdim_create_config if __name__ == "__main__": # or you can enter `ding -m serial -c cartpole_dqn_config.py -s 0` From 49c481f6b4556fc7812c40894b74a042e1b157e0 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 25 May 2022 16:20:17 +0800 Subject: [PATCH 011/229] initial league actor --- .../middleware/functional/league_actor.py | 136 ++++++++++++++++++ 1 file changed, 136 insertions(+) create mode 100644 ding/framework/middleware/functional/league_actor.py diff --git a/ding/framework/middleware/functional/league_actor.py b/ding/framework/middleware/functional/league_actor.py new file mode 100644 index 0000000000..71d060b8cd --- /dev/null +++ b/ding/framework/middleware/functional/league_actor.py @@ -0,0 +1,136 @@ +from ding.framework import task +from time import sleep +import logging + +from typing import List, Any +from dataclasses import dataclass, field +from typing import TYPE_CHECKING +from abc import abstractmethod + +class Storage: + + def __init__(self, path: str) -> None: + self.path = path + + @abstractmethod + def save(self, data: Any) -> None: + raise NotImplementedError + + @abstractmethod + def load(self) -> Any: + raise NotImplementedError + +@dataclass +class PlayerMeta: + player_id: str + checkpoint: "Storage" + total_agent_step: int = 0 + +@dataclass +class Job: + launch_player: str + players: List["PlayerMeta"] + result: list = field(default_factory=list) + job_no: int = 0 # Serial number of job, not required + train_iter: int = None + is_eval: bool = False + +class Agent: + HAS_MODEL = False + HAS_TEACHER_MODEL = False + HAS_SUCCESSIVE_MODEL = False + def __init__(self, cfg=None, env_id=0): + pass + + def reset(self, map_name, race, game_info, obs): + pass + + def step(self, obs): + action = {'func_id': 0, 'skip_steps': 1, + 'queued': False, 'unit_tags': [0], + 'target_unit_tag': 0, 'location': [0, 0]} + return [action] + + +class LeagueActor: + + def __init__(self): + self._running = True + self._model_updated = True + task.on("league_job_actor_{}".format(task.router.node_id), self._on_league_job) + task.on("learner_model", self._on_learner_model) + + # initialize agents + self._set_up_agents() + + def _set_up_agents(self): + """ + Initialize policy?. + """ + self.agents = [] + + def _on_learner_model(self): + """ + If get newest learner model, update this actor's model. + """ + self._model_updated = True + + # update policy model + + def _on_league_job(self, job: "Job"): + """ + Deal with job distributed by coordinator. Load historical model, generate traj and emit data. + """ + self._running = True + + # Wait new active model for 10 seconds + for _ in range(10): + if self._model_updated: + self._model_updated = False + break + logging.info( + "Waiting for new model on actor: {}, player: {}".format(task.router.node_id, job.launch_player) + ) + sleep(1) + + # initialize env + self._envs.reset() + + # 参考StepCollector + + # model interaction with env + # collector + + # generate traj + # get traj from collector + + # emit traj data + # rolloutor 实现 + + def send_actor_job(): + """ + Q:When send actor job? + """ + raise NotImplementedError + + def send_actor_data(): + """ + Send actor traj for each iter. + """ + raise NotImplementedError + + task.emit("actor_greeting", task.router.node_id) + self._envs.close() + self._running = False + + def __call__(self): + if not self._running: + task.emit("actor_greeting", task.router.node_id) + sleep(3) + +# used for test +if __name__ == '__main__': + actor = LeagueActor() + + + From d7c86bdda16c3041a08e3f78c017cac74ed10c3c Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 25 May 2022 16:43:33 +0800 Subject: [PATCH 012/229] change position --- .../{functional => }/league_actor.py | 35 +++++++------------ 1 file changed, 13 insertions(+), 22 deletions(-) rename ding/framework/middleware/{functional => }/league_actor.py (78%) diff --git a/ding/framework/middleware/functional/league_actor.py b/ding/framework/middleware/league_actor.py similarity index 78% rename from ding/framework/middleware/functional/league_actor.py rename to ding/framework/middleware/league_actor.py index 71d060b8cd..a03fba94a6 100644 --- a/ding/framework/middleware/functional/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -35,21 +35,21 @@ class Job: train_iter: int = None is_eval: bool = False -class Agent: - HAS_MODEL = False - HAS_TEACHER_MODEL = False - HAS_SUCCESSIVE_MODEL = False - def __init__(self, cfg=None, env_id=0): - pass +# class Agent: +# HAS_MODEL = False +# HAS_TEACHER_MODEL = False +# HAS_SUCCESSIVE_MODEL = False +# def __init__(self, cfg=None, env_id=0): +# pass - def reset(self, map_name, race, game_info, obs): - pass +# def reset(self, map_name, race, game_info, obs): +# pass - def step(self, obs): - action = {'func_id': 0, 'skip_steps': 1, - 'queued': False, 'unit_tags': [0], - 'target_unit_tag': 0, 'location': [0, 0]} - return [action] +# def step(self, obs): +# action = {'func_id': 0, 'skip_steps': 1, +# 'queued': False, 'unit_tags': [0], +# 'target_unit_tag': 0, 'location': [0, 0]} +# return [action] class LeagueActor: @@ -60,15 +60,6 @@ def __init__(self): task.on("league_job_actor_{}".format(task.router.node_id), self._on_league_job) task.on("learner_model", self._on_learner_model) - # initialize agents - self._set_up_agents() - - def _set_up_agents(self): - """ - Initialize policy?. - """ - self.agents = [] - def _on_learner_model(self): """ If get newest learner model, update this actor's model. From c3e1ad749c1c9762a514858f3b354be029918226 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 25 May 2022 16:53:49 +0800 Subject: [PATCH 013/229] add initial test --- ding/framework/middleware/__init__.py | 1 + .../middleware/tests/test_league_actor.py | 35 +++++++++++++++++++ 2 files changed, 36 insertions(+) create mode 100644 ding/framework/middleware/tests/test_league_actor.py diff --git a/ding/framework/middleware/__init__.py b/ding/framework/middleware/__init__.py index a2c428932c..5a8471d4ca 100644 --- a/ding/framework/middleware/__init__.py +++ b/ding/framework/middleware/__init__.py @@ -2,3 +2,4 @@ from .collector import StepCollector, EpisodeCollector from .learner import OffPolicyLearner, HERLearner from .ckpt_handler import CkptSaver +from .league_actor import LeagueActor \ No newline at end of file diff --git a/ding/framework/middleware/tests/test_league_actor.py b/ding/framework/middleware/tests/test_league_actor.py new file mode 100644 index 0000000000..0e717a3752 --- /dev/null +++ b/ding/framework/middleware/tests/test_league_actor.py @@ -0,0 +1,35 @@ +from ding.model import DQN +from ding.policy import DQNPolicy +from ding.envs import DingEnvWrapper, BaseEnvManagerV2 +from ding.data import DequeBuffer +from ding.config import compile_config +from ding.framework import task +from ding.framework.context import OnlineRLContext +from ding.framework.middleware import LeagueActor +from ding.utils import set_pkg_seed +from dizoo.classic_control.cartpole.config.cartpole_dqn_config import main_config, create_config +from dizoo.distar.envs.distar_env import DIStarEnv +from distar.ctools.utils import read_config + + +def main(): + distar_cfg = read_config('C:/Users/hjs/DI-engine/dizoo/distar/envs/test_distar_config.yaml') + + cfg = compile_config(main_config, create_cfg=create_config, auto=True) + with task.start(async_mode=False, ctx=OnlineRLContext()): + collector_env = BaseEnvManagerV2( + env_fn=[lambda: DingEnvWrapper(DIStarEnv(distar_cfg)) for _ in range(cfg.env.collector_env_num)], + cfg=cfg.env.manager + ) + + set_pkg_seed(cfg.seed, use_cuda=cfg.policy.cuda) + + model = DQN(**cfg.policy.model) + policy = DQNPolicy(cfg.policy, model=model) + + task.use(LeagueActor(cfg, policy.collect_mode, collector_env)) + task.run() + + +if __name__ == "__main__": + main() \ No newline at end of file From 79104f4e1f41098e66c8a66ab7e8fe65c4f69771 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 25 May 2022 20:22:23 +0800 Subject: [PATCH 014/229] change a bit --- ding/framework/middleware/league_actor.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index a03fba94a6..d8a5f7267f 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -7,6 +7,9 @@ from typing import TYPE_CHECKING from abc import abstractmethod +from easydict import EasyDict +from ding.envs import BaseEnvManager + class Storage: def __init__(self, path: str) -> None: @@ -54,7 +57,7 @@ class Job: class LeagueActor: - def __init__(self): + def __init__(self, cfg: EasyDict, policy, env: BaseEnvManager): self._running = True self._model_updated = True task.on("league_job_actor_{}".format(task.router.node_id), self._on_league_job) From 9f6bdfb8c63b7bd1c245e509069e2a3c1540a26c Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 25 May 2022 20:26:57 +0800 Subject: [PATCH 015/229] change a bit --- ding/framework/middleware/__init__.py | 2 +- ding/framework/middleware/tests/test_league_actor.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/ding/framework/middleware/__init__.py b/ding/framework/middleware/__init__.py index 5a8471d4ca..31c9b73f0d 100644 --- a/ding/framework/middleware/__init__.py +++ b/ding/framework/middleware/__init__.py @@ -2,4 +2,4 @@ from .collector import StepCollector, EpisodeCollector from .learner import OffPolicyLearner, HERLearner from .ckpt_handler import CkptSaver -from .league_actor import LeagueActor \ No newline at end of file +from .league_actor import LeagueActor, Job \ No newline at end of file diff --git a/ding/framework/middleware/tests/test_league_actor.py b/ding/framework/middleware/tests/test_league_actor.py index 0e717a3752..8812e5fa6f 100644 --- a/ding/framework/middleware/tests/test_league_actor.py +++ b/ding/framework/middleware/tests/test_league_actor.py @@ -5,7 +5,7 @@ from ding.config import compile_config from ding.framework import task from ding.framework.context import OnlineRLContext -from ding.framework.middleware import LeagueActor +from ding.framework.middleware import LeagueActor, Job from ding.utils import set_pkg_seed from dizoo.classic_control.cartpole.config.cartpole_dqn_config import main_config, create_config from dizoo.distar.envs.distar_env import DIStarEnv From e9f32fb76f4d16da159a8f669c5057f8f9914bcb Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 25 May 2022 21:23:23 +0800 Subject: [PATCH 016/229] change a bit --- ding/framework/middleware/league_actor.py | 57 +++++++++++++++++-- .../middleware/tests/test_league_actor.py | 25 ++++---- 2 files changed, 65 insertions(+), 17 deletions(-) diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index d8a5f7267f..be024a9ee3 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -4,12 +4,17 @@ from typing import List, Any from dataclasses import dataclass, field -from typing import TYPE_CHECKING from abc import abstractmethod from easydict import EasyDict from ding.envs import BaseEnvManager +from .functional import inferencer, rolloutor, TransitionList + +from typing import TYPE_CHECKING +if TYPE_CHECKING: + from ding.framework import OnlineRLContext + class Storage: def __init__(self, path: str) -> None: @@ -60,13 +65,23 @@ class LeagueActor: def __init__(self, cfg: EasyDict, policy, env: BaseEnvManager): self._running = True self._model_updated = True + + self.cfg = cfg + self.policy = policy + self._transitions = TransitionList(self.env.env_num) + self._inferencer = task.wrap(inferencer(cfg, policy, env)) + self._rolloutor = task.wrap(rolloutor(cfg, policy, env, self._transitions)) + task.on("league_job_actor_{}".format(task.router.node_id), self._on_league_job) task.on("learner_model", self._on_learner_model) - def _on_learner_model(self): + def _on_learner_model(self, learner_model: "LearnerModel"): """ If get newest learner model, update this actor's model. """ + player_meta = PlayerMeta(player_id=learner_model.player_id, checkpoint=None) + policy = self._get_policy(player_meta) + policy.load_state_dict(learner_model.state_dict) self._model_updated = True # update policy model @@ -86,14 +101,35 @@ def _on_league_job(self, job: "Job"): "Waiting for new model on actor: {}, player: {}".format(task.router.node_id, job.launch_player) ) sleep(1) + + policies = [] + main_player: "PlayerMeta" = None + for player in job.players: + policies.append(self._get_policy(player)) + if player.player_id == job.launch_player: + main_player = player + + assert main_player, "Can not find active player" # initialize env self._envs.reset() # 参考StepCollector - - # model interaction with env - # collector + ctx = OnlineRLContext() + old = ctx.env_step + + target_size = self.cfg.policy.collect.n_sample * self.cfg.policy.collect.unroll_len + current_inferencer = self._inferencer + + while True: + # model interaction with env + # collector + current_inferencer(ctx) + self._rolloutor(ctx) + if ctx.env_step - old >= target_size: + ctx.trajectories, ctx.trajectory_end_idx = self._transitions.to_trajectories() + self._transitions.clear() + break # generate traj # get traj from collector @@ -117,6 +153,17 @@ def send_actor_data(): self._envs.close() self._running = False + def _get_policy(self, player: "PlayerMeta") -> "Policy.collect_function": + player_id = player.player_id + if self._policies.get(player_id): + return self._policies.get(player_id) + policy: "Policy.collect_function" = self.policy_fn().collect_mode + self._policies[player_id] = policy + if "historical" in player.player_id: + policy.load_state_dict(player.checkpoint.load()) + + return policy + def __call__(self): if not self._running: task.emit("actor_greeting", task.router.node_id) diff --git a/ding/framework/middleware/tests/test_league_actor.py b/ding/framework/middleware/tests/test_league_actor.py index 8812e5fa6f..5f6c1f00a0 100644 --- a/ding/framework/middleware/tests/test_league_actor.py +++ b/ding/framework/middleware/tests/test_league_actor.py @@ -3,7 +3,7 @@ from ding.envs import DingEnvWrapper, BaseEnvManagerV2 from ding.data import DequeBuffer from ding.config import compile_config -from ding.framework import task +from ding.framework import task, Parallel from ding.framework.context import OnlineRLContext from ding.framework.middleware import LeagueActor, Job from ding.utils import set_pkg_seed @@ -17,19 +17,20 @@ def main(): cfg = compile_config(main_config, create_cfg=create_config, auto=True) with task.start(async_mode=False, ctx=OnlineRLContext()): - collector_env = BaseEnvManagerV2( - env_fn=[lambda: DingEnvWrapper(DIStarEnv(distar_cfg)) for _ in range(cfg.env.collector_env_num)], - cfg=cfg.env.manager - ) + if task.router.node_id == 0: + collector_env = BaseEnvManagerV2( + env_fn=[lambda: DingEnvWrapper(DIStarEnv(distar_cfg)) for _ in range(cfg.env.collector_env_num)], + cfg=cfg.env.manager + ) - set_pkg_seed(cfg.seed, use_cuda=cfg.policy.cuda) + set_pkg_seed(cfg.seed, use_cuda=cfg.policy.cuda) - model = DQN(**cfg.policy.model) - policy = DQNPolicy(cfg.policy, model=model) - - task.use(LeagueActor(cfg, policy.collect_mode, collector_env)) - task.run() + model = DQN(**cfg.policy.model) + policy = DQNPolicy(cfg.policy, model=model) + task.use(LeagueActor(cfg, policy.collect_mode, collector_env)) + elif task.router.node_id == 1: + pass if __name__ == "__main__": - main() \ No newline at end of file + Parallel.runner(n_parallel_workers=4, protocol="tcp", topology="star")(main) \ No newline at end of file From d1f8954027648d170e0d9cd790112494c358fc1c Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 25 May 2022 22:40:51 +0800 Subject: [PATCH 017/229] change a bit --- ding/framework/middleware/league_actor.py | 8 +++-- .../middleware/tests/test_league_actor.py | 30 ++++++++++++++++--- 2 files changed, 31 insertions(+), 7 deletions(-) diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index be024a9ee3..a8c285946b 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -2,7 +2,7 @@ from time import sleep import logging -from typing import List, Any +from typing import List, Any, Callable from dataclasses import dataclass, field from abc import abstractmethod @@ -14,6 +14,7 @@ from typing import TYPE_CHECKING if TYPE_CHECKING: from ding.framework import OnlineRLContext + from ding.policy import Policy class Storage: @@ -62,12 +63,13 @@ class Job: class LeagueActor: - def __init__(self, cfg: EasyDict, policy, env: BaseEnvManager): + def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self._running = True self._model_updated = True self.cfg = cfg - self.policy = policy + self.env_fn = env_fn + self.policy_fn = policy_fn self._transitions = TransitionList(self.env.env_num) self._inferencer = task.wrap(inferencer(cfg, policy, env)) self._rolloutor = task.wrap(rolloutor(cfg, policy, env, self._transitions)) diff --git a/ding/framework/middleware/tests/test_league_actor.py b/ding/framework/middleware/tests/test_league_actor.py index 5f6c1f00a0..6818a25a7a 100644 --- a/ding/framework/middleware/tests/test_league_actor.py +++ b/ding/framework/middleware/tests/test_league_actor.py @@ -10,12 +10,34 @@ from dizoo.classic_control.cartpole.config.cartpole_dqn_config import main_config, create_config from dizoo.distar.envs.distar_env import DIStarEnv from distar.ctools.utils import read_config +from copy import deepcopy +distar_cfg = read_config('C:/Users/hjs/DI-engine/dizoo/distar/envs/test_distar_config.yaml') +cfg = compile_config(main_config, create_cfg=create_config, auto=True) -def main(): - distar_cfg = read_config('C:/Users/hjs/DI-engine/dizoo/distar/envs/test_distar_config.yaml') +def prepare_test(): + + global cfg + cfg = deepcopy(cfg) - cfg = compile_config(main_config, create_cfg=create_config, auto=True) + def env_fn(): + env = BaseEnvManagerV2( + env_fn=[lambda: DingEnvWrapper(DIStarEnv(distar_cfg)) for _ in range(cfg.env.collector_env_num)], + cfg=cfg.env.manager + ) + env.seed(cfg.seed) + return env + + def policy_fn(): + model = DQN(**cfg.policy.model) + policy = DQNPolicy(cfg.policy, model=model) + return policy + + return cfg, env_fn, policy_fn + +def main(): + cfg, env_fn, policy_fn = prepare_test() + with task.start(async_mode=False, ctx=OnlineRLContext()): if task.router.node_id == 0: collector_env = BaseEnvManagerV2( @@ -28,7 +50,7 @@ def main(): model = DQN(**cfg.policy.model) policy = DQNPolicy(cfg.policy, model=model) - task.use(LeagueActor(cfg, policy.collect_mode, collector_env)) + task.use(LeagueActor(cfg, env_fn, policy_fn)) elif task.router.node_id == 1: pass From 006478cd690a7d3d86ef2397d6915fab55228ea2 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Thu, 26 May 2022 15:04:10 +0800 Subject: [PATCH 018/229] initial EpisodeCollector --- .../middleware/functional/collector.py | 21 ++++++++++ ding/framework/middleware/league_actor.py | 39 ++++++++++++++----- 2 files changed, 51 insertions(+), 9 deletions(-) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 0f6f7f6e7d..ff26fca1a9 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -6,6 +6,7 @@ from ding.envs import BaseEnvManager from ding.policy import Policy from ding.framework import task +from collections import namedtuple if TYPE_CHECKING: from ding.framework import OnlineRLContext @@ -82,6 +83,26 @@ def _inference(ctx: "OnlineRLContext"): return _inference +class BattleInferencer(): + def __init__(self, cfg: EasyDict, policy: List[namedtuple] = None, env: BaseEnvManager = None): + self._cfg = cfg + self._policy = policy + self._env = env + + + def __call__(self, ctx: "OnlineRLContext") -> None: + """ + Input of ctx: + - n_episode (:obj:`int`): the number of collecting data episode + - train_iter (:obj:`int`): the number of training iteration + - policy_kwargs (:obj:`dict`): the keyword args for policy forward + Output of ctx: + - return_data (:obj:`Tuple[List, List]`): A tuple with training sample(data) and episode info, \ + the former is a list containing collected episodes if not get_train_sample, \ + otherwise, return train_samples split by unroll_len. + """ + raise NotImplementedError + def rolloutor(cfg: EasyDict, policy: Policy, env: BaseEnvManager, transitions: TransitionList) -> Callable: """ diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index a8c285946b..d6df07b0aa 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -2,7 +2,7 @@ from time import sleep import logging -from typing import List, Any, Callable +from typing import Dict, List, Any, Callable from dataclasses import dataclass, field from abc import abstractmethod @@ -15,6 +15,7 @@ if TYPE_CHECKING: from ding.framework import OnlineRLContext from ding.policy import Policy + from ding.framework.middleware.league_learner import LearnerModel class Storage: @@ -70,9 +71,12 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.cfg = cfg self.env_fn = env_fn self.policy_fn = policy_fn - self._transitions = TransitionList(self.env.env_num) - self._inferencer = task.wrap(inferencer(cfg, policy, env)) - self._rolloutor = task.wrap(rolloutor(cfg, policy, env, self._transitions)) + self._policies: Dict[str, "Policy.collect_function"] = {} + self._inferencers: Dict[str, "inferencer"] = {} + self._rolloutors: Dict[str, "rolloutor"] = {} + # self._transitions = TransitionList(self.env.env_num) + # self._inferencer = task.wrap(inferencer(cfg, policy, env)) + # self._rolloutor = task.wrap(rolloutor(cfg, policy, env, self._transitions)) task.on("league_job_actor_{}".format(task.router.node_id), self._on_league_job) task.on("learner_model", self._on_learner_model) @@ -110,24 +114,31 @@ def _on_league_job(self, job: "Job"): policies.append(self._get_policy(player)) if player.player_id == job.launch_player: main_player = player + inferencer,rolloutor = self._get_collector(player.player_id) assert main_player, "Can not find active player" + for p in self._policies: + p.reset() # initialize env - self._envs.reset() + # self._envs.reset() # 参考StepCollector ctx = OnlineRLContext() + ctx.env_step = 0 + ctx.env_episode = 0 + ctx.train_iter = main_player.total_agent_step + #TODO: what is ctx.collect_kwargs + old = ctx.env_step target_size = self.cfg.policy.collect.n_sample * self.cfg.policy.collect.unroll_len - current_inferencer = self._inferencer while True: # model interaction with env # collector - current_inferencer(ctx) - self._rolloutor(ctx) + inferencer(ctx) + rolloutor(ctx) if ctx.env_step - old >= target_size: ctx.trajectories, ctx.trajectory_end_idx = self._transitions.to_trajectories() self._transitions.clear() @@ -152,8 +163,18 @@ def send_actor_data(): raise NotImplementedError task.emit("actor_greeting", task.router.node_id) - self._envs.close() self._running = False + + def _get_collector(self, player_id: str): + if self._inferencers.get(player_id) and self._rolloutors.get(player_id): + return self._inferencers[player_id], self._rolloutors[player_id] + cfg = self.cfg + env = self.env_fn() + policy = self._policies[player_id] + + self._inferencers[player_id] = task.wrap(inferencer(cfg, policy, env)) + self._rolloutors[player_id] = task.wrap(rolloutor(cfg, policy, env, self._transitions)) + return self._inferencers[player_id], self._rolloutors[player_id] def _get_policy(self, player: "PlayerMeta") -> "Policy.collect_function": player_id = player.player_id From 7a2a634efffb9de374df56504a8f3d39b5f2844f Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Thu, 26 May 2022 15:45:30 +0800 Subject: [PATCH 019/229] transfer BattleEpisodeSerialCollector to middleware BattleInferencer --- .../middleware/functional/collector.py | 113 +++++++++++++++++- 1 file changed, 112 insertions(+), 1 deletion(-) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index ff26fca1a9..5af3bed275 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -7,6 +7,9 @@ from ding.policy import Policy from ding.framework import task from collections import namedtuple +from ding.utils import EasyTimer, dicts_to_lists +from ding.torch_utils import to_tensor, to_ndarray +from ding.worker.collector.base_serial_collector import to_tensor_transitions if TYPE_CHECKING: from ding.framework import OnlineRLContext @@ -86,6 +89,10 @@ def _inference(ctx: "OnlineRLContext"): class BattleInferencer(): def __init__(self, cfg: EasyDict, policy: List[namedtuple] = None, env: BaseEnvManager = None): self._cfg = cfg + self._transform_obs = cfg.transform_obs + self._timer = EasyTimer() + + # TODO(zms) call self.reset() to reset policy and env self._policy = policy self._env = env @@ -101,7 +108,111 @@ def __call__(self, ctx: "OnlineRLContext") -> None: the former is a list containing collected episodes if not get_train_sample, \ otherwise, return train_samples split by unroll_len. """ - raise NotImplementedError + + if ctx.n_episode is None: + ### TODO(zms): self._default_n_episode comes from self.reset_policy() + if self._default_n_episode is None: + raise RuntimeError("Please specify collect n_episode") + else: + ctx.n_episode = self._default_n_episode + assert ctx.n_episode >= self._env_num, "Please make sure n_episode >= env_num" + + if ctx.policy_kwargs is None: + ctx.policy_kwargs = {} + + collected_episode = 0 + return_data = [[] for _ in range(2)] + return_info = [[] for _ in range(2)] + ready_env_id = set() + remain_episode = ctx.n_episode + + while True: + with self._timer: + # Get current env obs. + obs = self._env.ready_obs + new_available_env_id = set(obs.keys()).difference(ready_env_id) + ready_env_id = ready_env_id.union(set(list(new_available_env_id)[:remain_episode])) + remain_episode -= min(len(new_available_env_id), remain_episode) + obs = {env_id: obs[env_id] for env_id in ready_env_id} + + # Policy forward. + ### TODO(zms): self._obs_pool comes from self.reset + self._obs_pool.update(obs) + if self._transform_obs: + obs = to_tensor(obs, dtype=torch.float32) + obs = dicts_to_lists(obs) + policy_output = [p.forward(obs[i], **ctx.policy_kwargs) for i, p in enumerate(self._policy)] + + ### TODO(zms): self._policy_output_pool comes from self.reset + self._policy_output_pool.update(policy_output) + # Interact with env. + actions = {} + for env_id in ready_env_id: + actions[env_id] = [] + for output in policy_output: + actions[env_id].append(output[env_id]['action']) + actions = to_ndarray(actions) + timesteps = self._env.step(actions) + + # TODO(nyz) this duration may be inaccurate in async env + interaction_duration = self._timer.value / len(timesteps) + + # TODO(nyz) vectorize this for loop + for env_id, timestep in timesteps.items(): + # TODO(zms): self._env_info comes from self.reset() + self._env_info[env_id]['step'] += 1 + # TODO(zms): self._env_info comes from self.reset() + self._total_envstep_count += 1 + with self._timer: + for policy_id, policy in enumerate(self._policy): + policy_timestep_data = [d[policy_id] if not isinstance(d, bool) else d for d in timestep] + policy_timestep = type(timestep)(*policy_timestep_data) + transition = self._policy[policy_id].process_transition( + # TODO(zms): self._policy_output_pool comes from self.reset() + self._obs_pool[env_id][policy_id], self._policy_output_pool[env_id][policy_id], + policy_timestep + ) + transition['collect_iter'] = ctx.cleartrain_iter + self._traj_buffer[env_id][policy_id].append(transition) + # prepare data + if timestep.done: + # TODO(zms): to get rid of collector, "to_tensor_transitions" function should be removed and must be somewhere else. + transitions = to_tensor_transitions(self._traj_buffer[env_id][policy_id]) + if self._cfg.get_train_sample: + train_sample = self._policy[policy_id].get_train_sample(transitions) + return_data[policy_id].extend(train_sample) + else: + return_data[policy_id].append(transitions) + self._traj_buffer[env_id][policy_id].clear() + + self._env_info[env_id]['time'] += self._timer.value + interaction_duration + + # If env is done, record episode info and reset + if timestep.done: + # TODO(zms): self._env_info comes from self.reset() + self._total_episode_count += 1 + info = { + 'reward0': timestep.info[0]['final_eval_reward'], + 'reward1': timestep.info[1]['final_eval_reward'], + 'time': self._env_info[env_id]['time'], + 'step': self._env_info[env_id]['step'], + } + collected_episode += 1 + self._episode_info.append(info) + for i, p in enumerate(self._policy): + p.reset([env_id]) + self._reset_stat(env_id) + ready_env_id.remove(env_id) + for policy_id in range(2): + return_info[policy_id].append(timestep.info[policy_id]) + if collected_episode >= ctx.n_episode: + break + # log + ### TODO: how to deal with log here? + # self._output_log(ctx.train_iter) + ctx.return_data = return_data + ctx.return_info = return_info + def rolloutor(cfg: EasyDict, policy: Policy, env: BaseEnvManager, transitions: TransitionList) -> Callable: From 41052118e890229704f2def580de59959d2fe9e7 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Thu, 26 May 2022 15:55:14 +0800 Subject: [PATCH 020/229] change a bit comments --- ding/framework/middleware/functional/collector.py | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 5af3bed275..04c3846d80 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -115,6 +115,7 @@ def __call__(self, ctx: "OnlineRLContext") -> None: raise RuntimeError("Please specify collect n_episode") else: ctx.n_episode = self._default_n_episode + ### TODO(zms): self._env_num comes from self.reset_env() assert ctx.n_episode >= self._env_num, "Please make sure n_episode >= env_num" if ctx.policy_kwargs is None: @@ -161,7 +162,7 @@ def __call__(self, ctx: "OnlineRLContext") -> None: for env_id, timestep in timesteps.items(): # TODO(zms): self._env_info comes from self.reset() self._env_info[env_id]['step'] += 1 - # TODO(zms): self._env_info comes from self.reset() + # TODO(zms): self._total_envstep_count comes from self.reset() self._total_envstep_count += 1 with self._timer: for policy_id, policy in enumerate(self._policy): @@ -173,6 +174,7 @@ def __call__(self, ctx: "OnlineRLContext") -> None: policy_timestep ) transition['collect_iter'] = ctx.cleartrain_iter + # TODO(zms): self._traj_buffer comes from self.reset() self._traj_buffer[env_id][policy_id].append(transition) # prepare data if timestep.done: @@ -189,7 +191,7 @@ def __call__(self, ctx: "OnlineRLContext") -> None: # If env is done, record episode info and reset if timestep.done: - # TODO(zms): self._env_info comes from self.reset() + # TODO(zms): self._total_episode_count comes from self.reset() self._total_episode_count += 1 info = { 'reward0': timestep.info[0]['final_eval_reward'], @@ -198,9 +200,11 @@ def __call__(self, ctx: "OnlineRLContext") -> None: 'step': self._env_info[env_id]['step'], } collected_episode += 1 + # TODO(zms): self._episode_info comes from self.reset() self._episode_info.append(info) for i, p in enumerate(self._policy): p.reset([env_id]) + # TODO(zms): define self._reset_stat self._reset_stat(env_id) ready_env_id.remove(env_id) for policy_id in range(2): From 2409b3cde3bcbec0d209b6a35a751e6f70a818ba Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Thu, 26 May 2022 15:58:28 +0800 Subject: [PATCH 021/229] fix error --- ding/framework/middleware/functional/collector.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 04c3846d80..8f5312d5cf 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -173,7 +173,7 @@ def __call__(self, ctx: "OnlineRLContext") -> None: self._obs_pool[env_id][policy_id], self._policy_output_pool[env_id][policy_id], policy_timestep ) - transition['collect_iter'] = ctx.cleartrain_iter + transition['collect_iter'] = ctx.train_iter # TODO(zms): self._traj_buffer comes from self.reset() self._traj_buffer[env_id][policy_id].append(transition) # prepare data From 802118350240499bf2ae69b233ab0c971ac40389 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Thu, 26 May 2022 16:01:16 +0800 Subject: [PATCH 022/229] change class name --- ding/framework/middleware/functional/collector.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 8f5312d5cf..25aafabdf1 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -86,7 +86,7 @@ def _inference(ctx: "OnlineRLContext"): return _inference -class BattleInferencer(): +class BattleCollector(): def __init__(self, cfg: EasyDict, policy: List[namedtuple] = None, env: BaseEnvManager = None): self._cfg = cfg self._transform_obs = cfg.transform_obs From 3683a312478c36bed115946853c9a0d5e2a031fa Mon Sep 17 00:00:00 2001 From: lixuelin Date: Thu, 26 May 2022 16:29:26 +0800 Subject: [PATCH 023/229] add EventEnum & league coordinator --- ding/framework/__init__.py | 1 + ding/framework/event_enum.py | 18 +++++ ding/framework/middleware/__init__.py | 1 + .../middleware/league_coordinator.py | 55 +++++++++++++ .../tests/test_league_coordinator.py | 77 +++++++++++++++++++ 5 files changed, 152 insertions(+) create mode 100644 ding/framework/event_enum.py create mode 100644 ding/framework/middleware/league_coordinator.py create mode 100644 ding/framework/middleware/tests/test_league_coordinator.py diff --git a/ding/framework/__init__.py b/ding/framework/__init__.py index a1059a7ec4..990b258f6f 100644 --- a/ding/framework/__init__.py +++ b/ding/framework/__init__.py @@ -2,3 +2,4 @@ from .task import Task, task from .parallel import Parallel from .event_loop import EventLoop +from .event_enum import EventEnum \ No newline at end of file diff --git a/ding/framework/event_enum.py b/ding/framework/event_enum.py new file mode 100644 index 0000000000..bdc8c56462 --- /dev/null +++ b/ding/framework/event_enum.py @@ -0,0 +1,18 @@ +from enum import Enum, unique + + +@unique +class EventEnum(Enum): + COORDINATOR_DISPATCH_ACTOR_JOB = 1000 + + LEARNER_SEND_MODEL = 2000 + LEARNER_SEND_META = 2001 + + ACTOR_GREETING = 3000 + ACTOR_SEND_DATA = 3001 + ACTOR_FINISH_JOB = 3002 + + def __call__(self, node_id: int = None): + if not node_id: + return "event_{}".format(self.value) + return "event_{}_{}".format(self.value, node_id) \ No newline at end of file diff --git a/ding/framework/middleware/__init__.py b/ding/framework/middleware/__init__.py index a2c428932c..79071fc3a9 100644 --- a/ding/framework/middleware/__init__.py +++ b/ding/framework/middleware/__init__.py @@ -2,3 +2,4 @@ from .collector import StepCollector, EpisodeCollector from .learner import OffPolicyLearner, HERLearner from .ckpt_handler import CkptSaver +from .league_coordinator import LeagueCoordinator, Job \ No newline at end of file diff --git a/ding/framework/middleware/league_coordinator.py b/ding/framework/middleware/league_coordinator.py new file mode 100644 index 0000000000..bb037cdcb8 --- /dev/null +++ b/ding/framework/middleware/league_coordinator.py @@ -0,0 +1,55 @@ +from time import sleep +from threading import Lock +from dataclasses import dataclass +from typing import TYPE_CHECKING +from ding.framework import task, EventEnum + +if TYPE_CHECKING: + from ding.framework import Task, Context + from ding.league import BaseLeague + + +@dataclass +class Job: + job_no: int = -1 + player_id: str = "" + is_eval: bool = False + + +class LeagueCoordinator: + + def __init__(self, league: "BaseLeague") -> None: + self.league = league + self._job_iter = self._job_dispatcher() + self._lock = Lock() + task.on(EventEnum.ACTOR_GREETING(), self._on_actor_greeting) + task.on(EventEnum.LEARNER_SEND_META(), self._on_learner_meta) + task.on(EventEnum.ACTOR_FINISH_JOB(), self._on_actor_job) + + def _on_actor_greeting(self, actor_id): + with self._lock: + job: "Job" = next(self._job_iter) + if job.job_no > 0 and job.job_no % 10 == 0: # 1/10 turn job into eval mode + job.is_eval = True + job.actor_id = actor_id + task.emit(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB(actor_id), job) + + def _on_actor_job(self, job: "Job"): + self.league.update_payoff(job) + + def _on_learner_meta(self, player_meta: "PlayerMeta"): + self.league.update_active_player(player_meta) + self.league.create_historical_player(player_meta) + + def __call__(self, ctx: "Context") -> None: + sleep(0.1) + + def _job_dispatcher(self) -> "Job": + i = 0 + while True: + player_num = len(self.league.active_players_ids) + player_id = self.league.active_players_ids[i % player_num] + job = self.league.get_job_info(player_id) + job.job_no = i + i += 1 + yield job diff --git a/ding/framework/middleware/tests/test_league_coordinator.py b/ding/framework/middleware/tests/test_league_coordinator.py new file mode 100644 index 0000000000..7cc832dbd6 --- /dev/null +++ b/ding/framework/middleware/tests/test_league_coordinator.py @@ -0,0 +1,77 @@ +import pytest +import time +from unittest.mock import patch +from ding.framework import task, Parallel +from ding.framework.context import OnlineRLContext +from ding.framework.middleware import LeagueCoordinator, Job +from ding.league import BaseLeague +from ding.framework import EventEnum + + +class MockLeague: + + def __init__(self): + self.active_players_ids = ["player_0", "player_1", "player_2"] + self.update_payoff_cnt = 0 + self.update_active_player_cnt = 0 + self.create_historical_player_cnt = 0 + self.get_job_info_cnt = 0 + + def update_payoff(self, job): + self.update_payoff_cnt += 1 + + def update_active_player(self, meta): + self.update_active_player_cnt += 1 + + def create_historical_player(self, meta): + self.create_historical_player_cnt += 1 + + def get_job_info(self, player_id): + self.get_job_info_cnt += 1 + return Job(-1, player_id, False) + + +def _main(): + task.start() + if task.router.node_id == 0: + with patch("ding.league.BaseLeague", MockLeague): + league = MockLeague() + coordinator = LeagueCoordinator(league) + coordinator(None) + time.sleep(5) + assert league.update_payoff_cnt == 3 + assert league.update_active_player_cnt == 3 + assert league.create_historical_player_cnt == 3 + assert league.get_job_info_cnt == 3 + elif task.router.node_id == 1: + # test ACTOR_GREETING + res = [] + actor_id = "test_node_{}".format(task.router.node_id) + task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB(actor_id), lambda job: res.append(job)) + time.sleep(1) + for _ in range(3): + task.emit(EventEnum.ACTOR_GREETING(), actor_id) + time.sleep(3) + assert actor_id == res[-1].actor_id + elif task.router.node_id == 2: + # test LEARNER_SEND_META + actor_id = "test_node_{}".format(task.router.node_id) + time.sleep(1) + for _ in range(3): + task.emit(EventEnum.LEARNER_SEND_META(), {"meta": actor_id}) + time.sleep(3) + elif task.router.node_id == 3: + # test ACTOR_FINISH_JOB + actor_id = "test_node_{}".format(task.router.node_id) + time.sleep(1) + job = Job(-1, actor_id, False) + for _ in range(3): + task.emit(EventEnum.ACTOR_FINISH_JOB(), job) + time.sleep(3) + else: + raise Exception("Invalid node id {}".format(task.router.is_active)) + + +@pytest.mark.unittest +def test_coordinator(): + Parallel.runner(n_parallel_workers=4, protocol="tcp", topology="star")(_main) From b38b45508421db12cb98700dbbfafeec794cebca Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Fri, 27 May 2022 09:06:39 +0800 Subject: [PATCH 024/229] change league_actor --- .../middleware/functional/collector.py | 7 +- ding/framework/middleware/league_actor.py | 99 ++++++++----------- 2 files changed, 48 insertions(+), 58 deletions(-) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 25aafabdf1..7377b14f51 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -87,7 +87,12 @@ def _inference(ctx: "OnlineRLContext"): return _inference class BattleCollector(): - def __init__(self, cfg: EasyDict, policy: List[namedtuple] = None, env: BaseEnvManager = None): + def __init__( + self, + cfg: EasyDict, + env: BaseEnvManager = None, + policy: List[namedtuple] = None + ): self._cfg = cfg self._transform_obs = cfg.transform_obs self._timer = EasyTimer() diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index d6df07b0aa..757752b88d 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -16,6 +16,12 @@ from ding.framework import OnlineRLContext from ding.policy import Policy from ding.framework.middleware.league_learner import LearnerModel + from ding.framework.middleware.functional.collector import BattleCollector + +@dataclass +class ActorData: + train_data: Any + env_step: int = 0 class Storage: @@ -65,19 +71,15 @@ class Job: class LeagueActor: def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): - self._running = True - self._model_updated = True - self.cfg = cfg self.env_fn = env_fn self.policy_fn = policy_fn + # self.n_rollout_samples = self.cfg.policy.collect.get("n_rollout_samples") or 0 + self.n_rollout_samples = 0 + self._running = False + self._collectors: Dict[str, BattleCollector] = {} self._policies: Dict[str, "Policy.collect_function"] = {} - self._inferencers: Dict[str, "inferencer"] = {} - self._rolloutors: Dict[str, "rolloutor"] = {} - # self._transitions = TransitionList(self.env.env_num) - # self._inferencer = task.wrap(inferencer(cfg, policy, env)) - # self._rolloutor = task.wrap(rolloutor(cfg, policy, env, self._transitions)) - + self._model_updated = True task.on("league_job_actor_{}".format(task.router.node_id), self._on_league_job) task.on("learner_model", self._on_learner_model) @@ -107,74 +109,57 @@ def _on_league_job(self, job: "Job"): "Waiting for new model on actor: {}, player: {}".format(task.router.node_id, job.launch_player) ) sleep(1) - + + collector = self._get_collector(job.launch_player) policies = [] main_player: "PlayerMeta" = None for player in job.players: policies.append(self._get_policy(player)) if player.player_id == job.launch_player: main_player = player - inferencer,rolloutor = self._get_collector(player.player_id) + # inferencer,rolloutor = self._get_collector(player.player_id) assert main_player, "Can not find active player" - for p in self._policies: - p.reset() - - # initialize env - # self._envs.reset() + collector.reset_policy(policies) - # 参考StepCollector - ctx = OnlineRLContext() - ctx.env_step = 0 - ctx.env_episode = 0 - ctx.train_iter = main_player.total_agent_step - #TODO: what is ctx.collect_kwargs + def send_actor_job(episode_info: List): + job.result = [e['result'] for e in episode_info] + task.emit("actor_job", job) - old = ctx.env_step - - target_size = self.cfg.policy.collect.n_sample * self.cfg.policy.collect.unroll_len - - while True: - # model interaction with env - # collector - inferencer(ctx) - rolloutor(ctx) - if ctx.env_step - old >= target_size: - ctx.trajectories, ctx.trajectory_end_idx = self._transitions.to_trajectories() - self._transitions.clear() - break + def send_actor_data(train_data: List): + # Don't send data in evaluation mode + if job.is_eval: + return + for d in train_data: + d["adv"] = d["reward"] - # generate traj - # get traj from collector + actor_data = ActorData(env_step=collector.envstep, train_data=train_data) + task.emit("actor_data_player_{}".format(job.launch_player), actor_data) - # emit traj data - # rolloutor 实现 + ctx = OnlineRLContext() + ctx.n_episode = None + ctx.train_iter = main_player.total_agent_step + ctx.policy_kwargs = None - def send_actor_job(): - """ - Q:When send actor job? - """ - raise NotImplementedError + train_data, episode_info = collector.collect(ctx) + train_data, episode_info = train_data[0], episode_info[0] # only use main player data for training + send_actor_data(train_data) + send_actor_job(episode_info) - def send_actor_data(): - """ - Send actor traj for each iter. - """ - raise NotImplementedError - task.emit("actor_greeting", task.router.node_id) self._running = False def _get_collector(self, player_id: str): - if self._inferencers.get(player_id) and self._rolloutors.get(player_id): - return self._inferencers[player_id], self._rolloutors[player_id] + if self._collectors.get(player_id): + return self._collectors.get(player_id) cfg = self.cfg env = self.env_fn() - policy = self._policies[player_id] - - self._inferencers[player_id] = task.wrap(inferencer(cfg, policy, env)) - self._rolloutors[player_id] = task.wrap(rolloutor(cfg, policy, env, self._transitions)) - return self._inferencers[player_id], self._rolloutors[player_id] + collector = BattleCollector( + cfg.policy.collect.collector, + env + ) + self._collectors[player_id] = collector + return collector def _get_policy(self, player: "PlayerMeta") -> "Policy.collect_function": player_id = player.player_id From ac781533bf2f128203ef25295434a97d5ce06dea Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Fri, 27 May 2022 15:03:45 +0800 Subject: [PATCH 025/229] change position --- ding/framework/middleware/__init__.py | 2 +- ding/framework/middleware/collector.py | 261 +++++++++++++++++- .../middleware/functional/collector.py | 143 +--------- ding/framework/middleware/league_actor.py | 22 +- 4 files changed, 263 insertions(+), 165 deletions(-) diff --git a/ding/framework/middleware/__init__.py b/ding/framework/middleware/__init__.py index 31c9b73f0d..ab45651c01 100644 --- a/ding/framework/middleware/__init__.py +++ b/ding/framework/middleware/__init__.py @@ -1,5 +1,5 @@ from .functional import * -from .collector import StepCollector, EpisodeCollector +from .collector import StepCollector, EpisodeCollector, BattleCollector from .learner import OffPolicyLearner, HERLearner from .ckpt_handler import CkptSaver from .league_actor import LeagueActor, Job \ No newline at end of file diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index a93aee6fb8..1b0258a7e4 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -1,6 +1,5 @@ -from typing import TYPE_CHECKING, Callable, List +from typing import TYPE_CHECKING, Callable, List, Optional, Tuple from easydict import EasyDict - from ding.policy import Policy, get_random_policy from ding.envs import BaseEnvManager from ding.framework import task @@ -9,6 +8,264 @@ if TYPE_CHECKING: from ding.framework import OnlineRLContext +import torch +from collections import namedtuple +from ding.utils import EasyTimer, dicts_to_lists +from ding.torch_utils import to_tensor, to_ndarray +from ding.worker.collector.base_serial_collector import CachePool, TrajBuffer, INF, to_tensor_transitions + + +class BattleCollector(): + def __init__( + self, + cfg: EasyDict, + env: BaseEnvManager = None, + policy: List[namedtuple] = None + ): + self._deepcopy_obs = cfg.deepcopy_obs + self._transform_obs = cfg.transform_obs + self._cfg = cfg + self._timer = EasyTimer() + self._end_flag = False + self._traj_len = float("inf") + + # TODO(zms) call self.reset() to reset policy and env + self._policy = policy + self._env = env + + def reset_env(self, _env: Optional[BaseEnvManager] = None) -> None: + """ + Overview: + Reset the environment. + If _env is None, reset the old environment. + If _env is not None, replace the old environment in the collector with the new passed \ + in environment and launch. + Arguments: + - env (:obj:`Optional[BaseEnvManager]`): instance of the subclass of vectorized \ + env_manager(BaseEnvManager) + """ + if _env is not None: + self._env = _env + self._env.launch() + self._env_num = self._env.env_num + else: + self._env.reset() + + def reset_policy(self, _policy: Optional[List[namedtuple]] = None) -> None: + """ + Overview: + Reset the policy. + If _policy is None, reset the old policy. + If _policy is not None, replace the old policy in the collector with the new passed in policy. + Arguments: + - policy (:obj:`Optional[List[namedtuple]]`): the api namedtuple of collect_mode policy + """ + assert hasattr(self, '_env'), "please set env first" + if _policy is not None: + assert len(_policy) == 2, "1v1 episode collector needs 2 policy, but found {}".format(len(_policy)) + self._policy = _policy + self._default_n_episode = _policy[0].get_attribute('cfg').collect.get('n_episode', None) + self._unroll_len = _policy[0].get_attribute('unroll_len') + self._on_policy = _policy[0].get_attribute('cfg').on_policy + self._traj_len = INF + # self._logger.debug( + # 'Set default n_episode mode(n_episode({}), env_num({}), traj_len({}))'.format( + # self._default_n_episode, self._env_num, self._traj_len + # ) + # ) + for p in self._policy: + p.reset() + + def reset(self, _policy: Optional[List[namedtuple]] = None, _env: Optional[BaseEnvManager] = None) -> None: + """ + Overview: + Reset the environment and policy. + If _env is None, reset the old environment. + If _env is not None, replace the old environment in the collector with the new passed \ + in environment and launch. + If _policy is None, reset the old policy. + If _policy is not None, replace the old policy in the collector with the new passed in policy. + Arguments: + - policy (:obj:`Optional[List[namedtuple]]`): the api namedtuple of collect_mode policy + - env (:obj:`Optional[BaseEnvManager]`): instance of the subclass of vectorized \ + env_manager(BaseEnvManager) + """ + if _env is not None: + self.reset_env(_env) + if _policy is not None: + self.reset_policy(_policy) + + self._obs_pool = CachePool('obs', self._env_num, deepcopy=self._deepcopy_obs) + self._policy_output_pool = CachePool('policy_output', self._env_num) + # _traj_buffer is {env_id: {policy_id: TrajBuffer}}, is used to store traj_len pieces of transitions + self._traj_buffer = { + env_id: {policy_id: TrajBuffer(maxlen=self._traj_len) + for policy_id in range(2)} + for env_id in range(self._env_num) + } + self._env_info = {env_id: {'time': 0., 'step': 0} for env_id in range(self._env_num)} + + self._episode_info = [] + self._total_envstep_count = 0 + self._total_episode_count = 0 + self._total_duration = 0 + self._last_train_iter = 0 + self._end_flag = False + + def _reset_stat(self, env_id: int) -> None: + """ + Overview: + Reset the collector's state. Including reset the traj_buffer, obs_pool, policy_output_pool\ + and env_info. Reset these states according to env_id. You can refer to base_serial_collector\ + to get more messages. + Arguments: + - env_id (:obj:`int`): the id where we need to reset the collector's state + """ + for i in range(2): + self._traj_buffer[env_id][i].clear() + self._obs_pool.reset(env_id) + self._policy_output_pool.reset(env_id) + self._env_info[env_id] = {'time': 0., 'step': 0} + + def close(self) -> None: + """ + Overview: + Close the collector. If end_flag is False, close the environment, flush the tb_logger\ + and close the tb_logger. + """ + if self._end_flag: + return + self._end_flag = True + self._env.close() + + def __del__(self) -> None: + """ + Overview: + Execute the close command and close the collector. __del__ is automatically called to \ + destroy the collector instance when the collector finishes its work + """ + self.close() + + def __call__(self, ctx: "OnlineRLContext") -> None: + """ + Input of ctx: + - n_episode (:obj:`int`): the number of collecting data episode + - train_iter (:obj:`int`): the number of training iteration + - policy_kwargs (:obj:`dict`): the keyword args for policy forward + Output of ctx: + - return_data (:obj:`Tuple[List, List]`): A tuple with training sample(data) and episode info, \ + the former is a list containing collected episodes if not get_train_sample, \ + otherwise, return train_samples split by unroll_len. + """ + + if ctx.n_episode is None: + ### TODO(zms): self._default_n_episode comes from self.reset_policy() + if self._default_n_episode is None: + raise RuntimeError("Please specify collect n_episode") + else: + ctx.n_episode = self._default_n_episode + ### TODO(zms): self._env_num comes from self.reset_env() + assert ctx.n_episode >= self._env_num, "Please make sure n_episode >= env_num" + + if ctx.policy_kwargs is None: + ctx.policy_kwargs = {} + + collected_episode = 0 + return_data = [[] for _ in range(2)] + return_info = [[] for _ in range(2)] + ready_env_id = set() + remain_episode = ctx.n_episode + + while True: + with self._timer: + # Get current env obs. + obs = self._env.ready_obs + new_available_env_id = set(obs.keys()).difference(ready_env_id) + ready_env_id = ready_env_id.union(set(list(new_available_env_id)[:remain_episode])) + remain_episode -= min(len(new_available_env_id), remain_episode) + obs = {env_id: obs[env_id] for env_id in ready_env_id} + + # Policy forward. + ### TODO(zms): self._obs_pool comes from self.reset + self._obs_pool.update(obs) + if self._transform_obs: + obs = to_tensor(obs, dtype=torch.float32) + obs = dicts_to_lists(obs) + policy_output = [p.forward(obs[i], **ctx.policy_kwargs) for i, p in enumerate(self._policy)] + + ### TODO(zms): self._policy_output_pool comes from self.reset + self._policy_output_pool.update(policy_output) + # Interact with env. + actions = {} + for env_id in ready_env_id: + actions[env_id] = [] + for output in policy_output: + actions[env_id].append(output[env_id]['action']) + actions = to_ndarray(actions) + timesteps = self._env.step(actions) + + # TODO(nyz) this duration may be inaccurate in async env + interaction_duration = self._timer.value / len(timesteps) + + # TODO(nyz) vectorize this for loop + for env_id, timestep in timesteps.items(): + # TODO(zms): self._env_info comes from self.reset() + self._env_info[env_id]['step'] += 1 + # TODO(zms): self._total_envstep_count comes from self.reset() + self._total_envstep_count += 1 + with self._timer: + for policy_id, policy in enumerate(self._policy): + policy_timestep_data = [d[policy_id] if not isinstance(d, bool) else d for d in timestep] + policy_timestep = type(timestep)(*policy_timestep_data) + transition = self._policy[policy_id].process_transition( + # TODO(zms): self._policy_output_pool comes from self.reset() + self._obs_pool[env_id][policy_id], self._policy_output_pool[env_id][policy_id], + policy_timestep + ) + transition['collect_iter'] = ctx.train_iter + # TODO(zms): self._traj_buffer comes from self.reset() + self._traj_buffer[env_id][policy_id].append(transition) + # prepare data + if timestep.done: + # TODO(zms): to get rid of collector, "to_tensor_transitions" function should be removed and must be somewhere else. + transitions = to_tensor_transitions(self._traj_buffer[env_id][policy_id]) + if self._cfg.get_train_sample: + train_sample = self._policy[policy_id].get_train_sample(transitions) + return_data[policy_id].extend(train_sample) + else: + return_data[policy_id].append(transitions) + self._traj_buffer[env_id][policy_id].clear() + + self._env_info[env_id]['time'] += self._timer.value + interaction_duration + + # If env is done, record episode info and reset + if timestep.done: + # TODO(zms): self._total_episode_count comes from self.reset() + self._total_episode_count += 1 + info = { + 'reward0': timestep.info[0]['final_eval_reward'], + 'reward1': timestep.info[1]['final_eval_reward'], + 'time': self._env_info[env_id]['time'], + 'step': self._env_info[env_id]['step'], + } + collected_episode += 1 + # TODO(zms): self._episode_info comes from self.reset() + self._episode_info.append(info) + for i, p in enumerate(self._policy): + p.reset([env_id]) + # TODO(zms): define self._reset_stat + self._reset_stat(env_id) + ready_env_id.remove(env_id) + for policy_id in range(2): + return_info[policy_id].append(timestep.info[policy_id]) + if collected_episode >= ctx.n_episode: + break + # log + ### TODO: how to deal with log here? + # self._output_log(ctx.train_iter) + ctx.return_data = return_data + ctx.return_info = return_info + class StepCollector: """ diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 7377b14f51..7a826e5309 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -1,15 +1,9 @@ -from typing import TYPE_CHECKING, Callable, List, Tuple, Any +from typing import TYPE_CHECKING,Optional, Callable, List, Tuple, Any from easydict import EasyDict from functools import reduce -import torch import treetensor.torch as ttorch from ding.envs import BaseEnvManager from ding.policy import Policy -from ding.framework import task -from collections import namedtuple -from ding.utils import EasyTimer, dicts_to_lists -from ding.torch_utils import to_tensor, to_ndarray -from ding.worker.collector.base_serial_collector import to_tensor_transitions if TYPE_CHECKING: from ding.framework import OnlineRLContext @@ -86,141 +80,6 @@ def _inference(ctx: "OnlineRLContext"): return _inference -class BattleCollector(): - def __init__( - self, - cfg: EasyDict, - env: BaseEnvManager = None, - policy: List[namedtuple] = None - ): - self._cfg = cfg - self._transform_obs = cfg.transform_obs - self._timer = EasyTimer() - - # TODO(zms) call self.reset() to reset policy and env - self._policy = policy - self._env = env - - - def __call__(self, ctx: "OnlineRLContext") -> None: - """ - Input of ctx: - - n_episode (:obj:`int`): the number of collecting data episode - - train_iter (:obj:`int`): the number of training iteration - - policy_kwargs (:obj:`dict`): the keyword args for policy forward - Output of ctx: - - return_data (:obj:`Tuple[List, List]`): A tuple with training sample(data) and episode info, \ - the former is a list containing collected episodes if not get_train_sample, \ - otherwise, return train_samples split by unroll_len. - """ - - if ctx.n_episode is None: - ### TODO(zms): self._default_n_episode comes from self.reset_policy() - if self._default_n_episode is None: - raise RuntimeError("Please specify collect n_episode") - else: - ctx.n_episode = self._default_n_episode - ### TODO(zms): self._env_num comes from self.reset_env() - assert ctx.n_episode >= self._env_num, "Please make sure n_episode >= env_num" - - if ctx.policy_kwargs is None: - ctx.policy_kwargs = {} - - collected_episode = 0 - return_data = [[] for _ in range(2)] - return_info = [[] for _ in range(2)] - ready_env_id = set() - remain_episode = ctx.n_episode - - while True: - with self._timer: - # Get current env obs. - obs = self._env.ready_obs - new_available_env_id = set(obs.keys()).difference(ready_env_id) - ready_env_id = ready_env_id.union(set(list(new_available_env_id)[:remain_episode])) - remain_episode -= min(len(new_available_env_id), remain_episode) - obs = {env_id: obs[env_id] for env_id in ready_env_id} - - # Policy forward. - ### TODO(zms): self._obs_pool comes from self.reset - self._obs_pool.update(obs) - if self._transform_obs: - obs = to_tensor(obs, dtype=torch.float32) - obs = dicts_to_lists(obs) - policy_output = [p.forward(obs[i], **ctx.policy_kwargs) for i, p in enumerate(self._policy)] - - ### TODO(zms): self._policy_output_pool comes from self.reset - self._policy_output_pool.update(policy_output) - # Interact with env. - actions = {} - for env_id in ready_env_id: - actions[env_id] = [] - for output in policy_output: - actions[env_id].append(output[env_id]['action']) - actions = to_ndarray(actions) - timesteps = self._env.step(actions) - - # TODO(nyz) this duration may be inaccurate in async env - interaction_duration = self._timer.value / len(timesteps) - - # TODO(nyz) vectorize this for loop - for env_id, timestep in timesteps.items(): - # TODO(zms): self._env_info comes from self.reset() - self._env_info[env_id]['step'] += 1 - # TODO(zms): self._total_envstep_count comes from self.reset() - self._total_envstep_count += 1 - with self._timer: - for policy_id, policy in enumerate(self._policy): - policy_timestep_data = [d[policy_id] if not isinstance(d, bool) else d for d in timestep] - policy_timestep = type(timestep)(*policy_timestep_data) - transition = self._policy[policy_id].process_transition( - # TODO(zms): self._policy_output_pool comes from self.reset() - self._obs_pool[env_id][policy_id], self._policy_output_pool[env_id][policy_id], - policy_timestep - ) - transition['collect_iter'] = ctx.train_iter - # TODO(zms): self._traj_buffer comes from self.reset() - self._traj_buffer[env_id][policy_id].append(transition) - # prepare data - if timestep.done: - # TODO(zms): to get rid of collector, "to_tensor_transitions" function should be removed and must be somewhere else. - transitions = to_tensor_transitions(self._traj_buffer[env_id][policy_id]) - if self._cfg.get_train_sample: - train_sample = self._policy[policy_id].get_train_sample(transitions) - return_data[policy_id].extend(train_sample) - else: - return_data[policy_id].append(transitions) - self._traj_buffer[env_id][policy_id].clear() - - self._env_info[env_id]['time'] += self._timer.value + interaction_duration - - # If env is done, record episode info and reset - if timestep.done: - # TODO(zms): self._total_episode_count comes from self.reset() - self._total_episode_count += 1 - info = { - 'reward0': timestep.info[0]['final_eval_reward'], - 'reward1': timestep.info[1]['final_eval_reward'], - 'time': self._env_info[env_id]['time'], - 'step': self._env_info[env_id]['step'], - } - collected_episode += 1 - # TODO(zms): self._episode_info comes from self.reset() - self._episode_info.append(info) - for i, p in enumerate(self._policy): - p.reset([env_id]) - # TODO(zms): define self._reset_stat - self._reset_stat(env_id) - ready_env_id.remove(env_id) - for policy_id in range(2): - return_info[policy_id].append(timestep.info[policy_id]) - if collected_episode >= ctx.n_episode: - break - # log - ### TODO: how to deal with log here? - # self._output_log(ctx.train_iter) - ctx.return_data = return_data - ctx.return_info = return_info diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 757752b88d..8ec78c1efb 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -9,14 +9,12 @@ from easydict import EasyDict from ding.envs import BaseEnvManager -from .functional import inferencer, rolloutor, TransitionList - from typing import TYPE_CHECKING if TYPE_CHECKING: from ding.framework import OnlineRLContext from ding.policy import Policy from ding.framework.middleware.league_learner import LearnerModel - from ding.framework.middleware.functional.collector import BattleCollector + from ding.framework.middleware import BattleCollector @dataclass class ActorData: @@ -51,22 +49,6 @@ class Job: train_iter: int = None is_eval: bool = False -# class Agent: -# HAS_MODEL = False -# HAS_TEACHER_MODEL = False -# HAS_SUCCESSIVE_MODEL = False -# def __init__(self, cfg=None, env_id=0): -# pass - -# def reset(self, map_name, race, game_info, obs): -# pass - -# def step(self, obs): -# action = {'func_id': 0, 'skip_steps': 1, -# 'queued': False, 'unit_tags': [0], -# 'target_unit_tag': 0, 'location': [0, 0]} -# return [action] - class LeagueActor: @@ -141,7 +123,7 @@ def send_actor_data(train_data: List): ctx.train_iter = main_player.total_agent_step ctx.policy_kwargs = None - train_data, episode_info = collector.collect(ctx) + train_data, episode_info = collector(ctx) train_data, episode_info = train_data[0], episode_info[0] # only use main player data for training send_actor_data(train_data) send_actor_job(episode_info) From 609c10904d89b7fd43af1b1a4324d50d8a78e399 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Fri, 27 May 2022 16:14:09 +0800 Subject: [PATCH 026/229] input policies inside ctx --- ding/framework/middleware/collector.py | 87 ++++++++++---------------- 1 file changed, 32 insertions(+), 55 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 1b0258a7e4..468319ef91 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -14,6 +14,24 @@ from ding.torch_utils import to_tensor, to_ndarray from ding.worker.collector.base_serial_collector import CachePool, TrajBuffer, INF, to_tensor_transitions +def reset_policy(_policy: Optional[List[namedtuple]] = None): + + def _reset_policy(ctx: OnlineRLContext): + if _policy is not None: + assert len(_policy) > 1, "battle collector needs more than 1 policies" + ctx._policy = _policy + ctx._default_n_episode = _policy[0].get_attribute('cfg').collect.get('n_episode', None) + # ctx._unroll_len = _policy[0].get_attribute('unroll_len') # unuseful here + # ctx._on_policy = _policy[0].get_attribute('cfg').on_policy # unuseful here + # ctx._traj_len = INF + + for p in ctx._policy: + p.reset() + + return _reset_policy + + + class BattleCollector(): def __init__( @@ -29,11 +47,9 @@ def __init__( self._end_flag = False self._traj_len = float("inf") - # TODO(zms) call self.reset() to reset policy and env - self._policy = policy - self._env = env + self._reset(env) - def reset_env(self, _env: Optional[BaseEnvManager] = None) -> None: + def _reset_env(self, _env: Optional[BaseEnvManager] = None) -> None: """ Overview: Reset the environment. @@ -51,35 +67,10 @@ def reset_env(self, _env: Optional[BaseEnvManager] = None) -> None: else: self._env.reset() - def reset_policy(self, _policy: Optional[List[namedtuple]] = None) -> None: - """ - Overview: - Reset the policy. - If _policy is None, reset the old policy. - If _policy is not None, replace the old policy in the collector with the new passed in policy. - Arguments: - - policy (:obj:`Optional[List[namedtuple]]`): the api namedtuple of collect_mode policy - """ - assert hasattr(self, '_env'), "please set env first" - if _policy is not None: - assert len(_policy) == 2, "1v1 episode collector needs 2 policy, but found {}".format(len(_policy)) - self._policy = _policy - self._default_n_episode = _policy[0].get_attribute('cfg').collect.get('n_episode', None) - self._unroll_len = _policy[0].get_attribute('unroll_len') - self._on_policy = _policy[0].get_attribute('cfg').on_policy - self._traj_len = INF - # self._logger.debug( - # 'Set default n_episode mode(n_episode({}), env_num({}), traj_len({}))'.format( - # self._default_n_episode, self._env_num, self._traj_len - # ) - # ) - for p in self._policy: - p.reset() - - def reset(self, _policy: Optional[List[namedtuple]] = None, _env: Optional[BaseEnvManager] = None) -> None: + def _reset(self, _env: Optional[BaseEnvManager] = None) -> None: """ Overview: - Reset the environment and policy. + Reset the environment. If _env is None, reset the old environment. If _env is not None, replace the old environment in the collector with the new passed \ in environment and launch. @@ -91,9 +82,7 @@ def reset(self, _policy: Optional[List[namedtuple]] = None, _env: Optional[BaseE env_manager(BaseEnvManager) """ if _env is not None: - self.reset_env(_env) - if _policy is not None: - self.reset_policy(_policy) + self._reset_env(_env) self._obs_pool = CachePool('obs', self._env_num, deepcopy=self._deepcopy_obs) self._policy_output_pool = CachePool('policy_output', self._env_num) @@ -127,7 +116,7 @@ def _reset_stat(self, env_id: int) -> None: self._policy_output_pool.reset(env_id) self._env_info[env_id] = {'time': 0., 'step': 0} - def close(self) -> None: + def _close(self) -> None: """ Overview: Close the collector. If end_flag is False, close the environment, flush the tb_logger\ @@ -144,7 +133,7 @@ def __del__(self) -> None: Execute the close command and close the collector. __del__ is automatically called to \ destroy the collector instance when the collector finishes its work """ - self.close() + self._close() def __call__(self, ctx: "OnlineRLContext") -> None: """ @@ -159,12 +148,10 @@ def __call__(self, ctx: "OnlineRLContext") -> None: """ if ctx.n_episode is None: - ### TODO(zms): self._default_n_episode comes from self.reset_policy() - if self._default_n_episode is None: + if ctx._default_n_episode is None: raise RuntimeError("Please specify collect n_episode") else: - ctx.n_episode = self._default_n_episode - ### TODO(zms): self._env_num comes from self.reset_env() + ctx.n_episode = ctx._default_n_episode assert ctx.n_episode >= self._env_num, "Please make sure n_episode >= env_num" if ctx.policy_kwargs is None: @@ -186,14 +173,12 @@ def __call__(self, ctx: "OnlineRLContext") -> None: obs = {env_id: obs[env_id] for env_id in ready_env_id} # Policy forward. - ### TODO(zms): self._obs_pool comes from self.reset self._obs_pool.update(obs) if self._transform_obs: obs = to_tensor(obs, dtype=torch.float32) obs = dicts_to_lists(obs) - policy_output = [p.forward(obs[i], **ctx.policy_kwargs) for i, p in enumerate(self._policy)] + policy_output = [p.forward(obs[i], **ctx.policy_kwargs) for i, p in enumerate(ctx._policy)] - ### TODO(zms): self._policy_output_pool comes from self.reset self._policy_output_pool.update(policy_output) # Interact with env. actions = {} @@ -209,28 +194,23 @@ def __call__(self, ctx: "OnlineRLContext") -> None: # TODO(nyz) vectorize this for loop for env_id, timestep in timesteps.items(): - # TODO(zms): self._env_info comes from self.reset() self._env_info[env_id]['step'] += 1 - # TODO(zms): self._total_envstep_count comes from self.reset() self._total_envstep_count += 1 with self._timer: - for policy_id, policy in enumerate(self._policy): + for policy_id, policy in enumerate(ctx._policy): policy_timestep_data = [d[policy_id] if not isinstance(d, bool) else d for d in timestep] policy_timestep = type(timestep)(*policy_timestep_data) - transition = self._policy[policy_id].process_transition( - # TODO(zms): self._policy_output_pool comes from self.reset() + transition = ctx._policy[policy_id].process_transition( self._obs_pool[env_id][policy_id], self._policy_output_pool[env_id][policy_id], policy_timestep ) transition['collect_iter'] = ctx.train_iter - # TODO(zms): self._traj_buffer comes from self.reset() self._traj_buffer[env_id][policy_id].append(transition) # prepare data if timestep.done: - # TODO(zms): to get rid of collector, "to_tensor_transitions" function should be removed and must be somewhere else. transitions = to_tensor_transitions(self._traj_buffer[env_id][policy_id]) if self._cfg.get_train_sample: - train_sample = self._policy[policy_id].get_train_sample(transitions) + train_sample = ctx._policy[policy_id].get_train_sample(transitions) return_data[policy_id].extend(train_sample) else: return_data[policy_id].append(transitions) @@ -240,7 +220,6 @@ def __call__(self, ctx: "OnlineRLContext") -> None: # If env is done, record episode info and reset if timestep.done: - # TODO(zms): self._total_episode_count comes from self.reset() self._total_episode_count += 1 info = { 'reward0': timestep.info[0]['final_eval_reward'], @@ -249,11 +228,9 @@ def __call__(self, ctx: "OnlineRLContext") -> None: 'step': self._env_info[env_id]['step'], } collected_episode += 1 - # TODO(zms): self._episode_info comes from self.reset() self._episode_info.append(info) - for i, p in enumerate(self._policy): + for i, p in enumerate(ctx._policy): p.reset([env_id]) - # TODO(zms): define self._reset_stat self._reset_stat(env_id) ready_env_id.remove(env_id) for policy_id in range(2): From fa6fe8e54be14a3cbb290706f396a5d4758b9052 Mon Sep 17 00:00:00 2001 From: lixuelin Date: Fri, 27 May 2022 16:58:46 +0800 Subject: [PATCH 027/229] add event enum --- ding/framework/event_enum.py | 30 ++++++++++++------- .../middleware/league_coordinator.py | 8 ++--- .../tests/test_league_coordinator.py | 8 ++--- ding/framework/tests/test_event_num.py | 10 +++++++ 4 files changed, 38 insertions(+), 18 deletions(-) create mode 100644 ding/framework/tests/test_event_num.py diff --git a/ding/framework/event_enum.py b/ding/framework/event_enum.py index bdc8c56462..44e1e69182 100644 --- a/ding/framework/event_enum.py +++ b/ding/framework/event_enum.py @@ -1,18 +1,28 @@ +import re from enum import Enum, unique @unique class EventEnum(Enum): - COORDINATOR_DISPATCH_ACTOR_JOB = 1000 + # template event + TEMPLATE_EVENT = "example_xxx_{actor_id}_{player_id}" - LEARNER_SEND_MODEL = 2000 - LEARNER_SEND_META = 2001 + # events emited by coordinators + COORDINATOR_DISPATCH_ACTOR_JOB = "coordinator_dispatch_actor_job_{actor_id}" - ACTOR_GREETING = 3000 - ACTOR_SEND_DATA = 3001 - ACTOR_FINISH_JOB = 3002 + # events emited by learners + LEARNER_SEND_MODEL = "on_learner_send_model" + LEARNER_SEND_META = "on_learner_send_meta" - def __call__(self, node_id: int = None): - if not node_id: - return "event_{}".format(self.value) - return "event_{}_{}".format(self.value, node_id) \ No newline at end of file + # events emited by actors + ACTOR_GREETING = "actor_greeting" + ACTOR_SEND_DATA = "actor_send_meta" + ACTOR_FINISH_JOB = "actor_finish_job" + + def get_event(self, *args, **kwargs): + args_dict = {} + if args: + params = re.findall(r"\{(.*?)\}", self.value) + args_dict.update(zip(params, args)) + args_dict.update(kwargs) + return self.value.format(**args_dict) diff --git a/ding/framework/middleware/league_coordinator.py b/ding/framework/middleware/league_coordinator.py index bb037cdcb8..55283195d6 100644 --- a/ding/framework/middleware/league_coordinator.py +++ b/ding/framework/middleware/league_coordinator.py @@ -22,9 +22,9 @@ def __init__(self, league: "BaseLeague") -> None: self.league = league self._job_iter = self._job_dispatcher() self._lock = Lock() - task.on(EventEnum.ACTOR_GREETING(), self._on_actor_greeting) - task.on(EventEnum.LEARNER_SEND_META(), self._on_learner_meta) - task.on(EventEnum.ACTOR_FINISH_JOB(), self._on_actor_job) + task.on(EventEnum.ACTOR_GREETING.get_event(), self._on_actor_greeting) + task.on(EventEnum.LEARNER_SEND_META.get_event(), self._on_learner_meta) + task.on(EventEnum.ACTOR_FINISH_JOB, self._on_actor_job) def _on_actor_greeting(self, actor_id): with self._lock: @@ -32,7 +32,7 @@ def _on_actor_greeting(self, actor_id): if job.job_no > 0 and job.job_no % 10 == 0: # 1/10 turn job into eval mode job.is_eval = True job.actor_id = actor_id - task.emit(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB(actor_id), job) + task.emit(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.get_event(actor_id), job) def _on_actor_job(self, job: "Job"): self.league.update_payoff(job) diff --git a/ding/framework/middleware/tests/test_league_coordinator.py b/ding/framework/middleware/tests/test_league_coordinator.py index 7cc832dbd6..35f97ae21a 100644 --- a/ding/framework/middleware/tests/test_league_coordinator.py +++ b/ding/framework/middleware/tests/test_league_coordinator.py @@ -47,10 +47,10 @@ def _main(): # test ACTOR_GREETING res = [] actor_id = "test_node_{}".format(task.router.node_id) - task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB(actor_id), lambda job: res.append(job)) + task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.get_event(actor_id), lambda job: res.append(job)) time.sleep(1) for _ in range(3): - task.emit(EventEnum.ACTOR_GREETING(), actor_id) + task.emit(EventEnum.ACTOR_GREETING.get_event(), actor_id) time.sleep(3) assert actor_id == res[-1].actor_id elif task.router.node_id == 2: @@ -58,7 +58,7 @@ def _main(): actor_id = "test_node_{}".format(task.router.node_id) time.sleep(1) for _ in range(3): - task.emit(EventEnum.LEARNER_SEND_META(), {"meta": actor_id}) + task.emit(EventEnum.LEARNER_SEND_META.get_event(), {"meta": actor_id}) time.sleep(3) elif task.router.node_id == 3: # test ACTOR_FINISH_JOB @@ -66,7 +66,7 @@ def _main(): time.sleep(1) job = Job(-1, actor_id, False) for _ in range(3): - task.emit(EventEnum.ACTOR_FINISH_JOB(), job) + task.emit(EventEnum.ACTOR_FINISH_JOB.get_event(), job) time.sleep(3) else: raise Exception("Invalid node id {}".format(task.router.is_active)) diff --git a/ding/framework/tests/test_event_num.py b/ding/framework/tests/test_event_num.py new file mode 100644 index 0000000000..e2b272d4f9 --- /dev/null +++ b/ding/framework/tests/test_event_num.py @@ -0,0 +1,10 @@ +import py +import pytest +from ding.framework import EventEnum + + +@pytest.mark.unittest +def test_event_enum(): + assert EventEnum.TEMPLATE_EVENT.get_event(12, 34) == "example_xxx_12_34" + assert EventEnum.TEMPLATE_EVENT.get_event(12, player_id=34) == "example_xxx_12_34" + assert EventEnum.TEMPLATE_EVENT.get_event(actor_id=12, player_id=34) == "example_xxx_12_34" \ No newline at end of file From bc9ef75edd220bfaebad3c6679f538d906842af1 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Fri, 27 May 2022 20:43:03 +0800 Subject: [PATCH 028/229] change test --- .../middleware/tests/test_league_actor.py | 87 +++++++++++-------- 1 file changed, 49 insertions(+), 38 deletions(-) diff --git a/ding/framework/middleware/tests/test_league_actor.py b/ding/framework/middleware/tests/test_league_actor.py index 6818a25a7a..118c4b1971 100644 --- a/ding/framework/middleware/tests/test_league_actor.py +++ b/ding/framework/middleware/tests/test_league_actor.py @@ -1,58 +1,69 @@ -from ding.model import DQN -from ding.policy import DQNPolicy -from ding.envs import DingEnvWrapper, BaseEnvManagerV2 -from ding.data import DequeBuffer -from ding.config import compile_config -from ding.framework import task, Parallel -from ding.framework.context import OnlineRLContext -from ding.framework.middleware import LeagueActor, Job -from ding.utils import set_pkg_seed -from dizoo.classic_control.cartpole.config.cartpole_dqn_config import main_config, create_config -from dizoo.distar.envs.distar_env import DIStarEnv -from distar.ctools.utils import read_config +from time import sleep +import pytest from copy import deepcopy +from ding.envs import BaseEnvManager +from ding.framework.middleware.league_learner import LearnerModel +from ding.framework.middleware.tests.league_config import cfg +from ding.framework.middleware.league_actor import ActorData, LeagueActor, Job -distar_cfg = read_config('C:/Users/hjs/DI-engine/dizoo/distar/envs/test_distar_config.yaml') -cfg = compile_config(main_config, create_cfg=create_config, auto=True) +from ding.framework.task import Task +from ding.model import VAC +from ding.policy.ppo import PPOPolicy +from dizoo.league_demo.game_env import GameEnv -def prepare_test(): +class MockLeague: + def __init__(self): + self.active_players_ids = ["test_node_1", "test_node_2", "test_node_3"] + self.update_payoff_cnt = 0 + self.update_active_player_cnt = 0 + self.create_historical_player_cnt = 0 + self.get_job_info_cnt = 0 + def update_payoff(self, job): + self.update_payoff_cnt += 1 + # print("update_payoff: {}".format(job)) + + def update_active_player(self, meta): + self.update_active_player_cnt += 1 + # print("update_active_player: {}".format(meta)) + + def create_historical_player(self, meta): + self.create_historical_player_cnt += 1 + # print("create_historical_player: {}".format(meta)) + + def get_job_info(self, player_id): + self.get_job_info_cnt += 1 + # print("get_job_info") + return Job(231890, player_id, False) + +def prepare_test(): global cfg cfg = deepcopy(cfg) def env_fn(): - env = BaseEnvManagerV2( - env_fn=[lambda: DingEnvWrapper(DIStarEnv(distar_cfg)) for _ in range(cfg.env.collector_env_num)], - cfg=cfg.env.manager + env = BaseEnvManager( + env_fn=[lambda: GameEnv(cfg.env.env_type) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager ) env.seed(cfg.seed) return env - + def policy_fn(): - model = DQN(**cfg.policy.model) - policy = DQNPolicy(cfg.policy, model=model) + model = VAC(**cfg.policy.model) + policy = PPOPolicy(cfg.policy, model=model) return policy - - return cfg, env_fn, policy_fn + + league = BaseLeague(cfg.policy.other.league) + return cfg, env_fn, policy_fn, league + def main(): cfg, env_fn, policy_fn = prepare_test() + task.start() - with task.start(async_mode=False, ctx=OnlineRLContext()): - if task.router.node_id == 0: - collector_env = BaseEnvManagerV2( - env_fn=[lambda: DingEnvWrapper(DIStarEnv(distar_cfg)) for _ in range(cfg.env.collector_env_num)], - cfg=cfg.env.manager - ) - - set_pkg_seed(cfg.seed, use_cuda=cfg.policy.cuda) - - model = DQN(**cfg.policy.model) - policy = DQNPolicy(cfg.policy, model=model) - - task.use(LeagueActor(cfg, env_fn, policy_fn)) - elif task.router.node_id == 1: - pass + if task.router.node_id == 0: + LeagueActor() + elif task.router.node_id == 1: + pass if __name__ == "__main__": Parallel.runner(n_parallel_workers=4, protocol="tcp", topology="star")(main) \ No newline at end of file From 709425a48a14373ea371d9a34f9d6204b2e70b53 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Fri, 27 May 2022 21:12:12 +0800 Subject: [PATCH 029/229] for tets --- .../middleware/tests/league_config.py | 161 ++++++++++++++++++ .../middleware/tests/test_league_actor.py | 32 +++- 2 files changed, 186 insertions(+), 7 deletions(-) create mode 100644 ding/framework/middleware/tests/league_config.py diff --git a/ding/framework/middleware/tests/league_config.py b/ding/framework/middleware/tests/league_config.py new file mode 100644 index 0000000000..27a5d9373c --- /dev/null +++ b/ding/framework/middleware/tests/league_config.py @@ -0,0 +1,161 @@ +from easydict import EasyDict +cfg = EasyDict( + { + 'env': { + 'manager': { + 'episode_num': 100000, + 'max_retry': 1, + 'retry_type': 'reset', + 'auto_reset': True, + 'step_timeout': None, + 'reset_timeout': None, + 'retry_waiting_time': 0.1, + 'cfg_type': 'BaseEnvManagerDict', + 'shared_memory': False + }, + 'collector_env_num': 2, + 'evaluator_env_num': 10, + 'n_evaluator_episode': 100, + 'env_type': 'prisoner_dilemma', + 'stop_value': [-10.1, -5.05] + }, + 'policy': { + 'model': { + 'obs_shape': 2, + 'action_shape': 2, + 'action_space': 'discrete', + 'encoder_hidden_size_list': [32, 32], + 'critic_head_hidden_size': 32, + 'actor_head_hidden_size': 32, + 'share_encoder': False + }, + 'learn': { + 'learner': { + 'train_iterations': 1000000000, + 'dataloader': { + 'num_workers': 0 + }, + 'log_policy': False, + 'hook': { + 'load_ckpt_before_run': '', + 'log_show_after_iter': 100, + 'save_ckpt_after_iter': 10000, + 'save_ckpt_after_run': True + }, + 'cfg_type': 'BaseLearnerDict' + }, + 'multi_gpu': False, + 'epoch_per_collect': 10, + 'batch_size': 32, + 'learning_rate': 1e-05, + 'value_weight': 0.5, + 'entropy_weight': 0.0, + 'clip_ratio': 0.2, + 'adv_norm': True, + 'value_norm': True, + 'ppo_param_init': True, + 'grad_clip_type': 'clip_norm', + 'grad_clip_value': 0.5, + 'ignore_done': False, + 'update_per_collect': 3, + 'scheduler': { + 'schedule_flag': False, + 'schedule_mode': 'reduce', + 'factor': 0.005, + 'change_range': [0, 1], + 'threshold': 0.5, + 'patience': 50 + } + }, + 'collect': { + 'collector': { + 'deepcopy_obs': False, + 'transform_obs': False, + 'collect_print_freq': 100, + 'get_train_sample': True, + 'cfg_type': 'BattleEpisodeSerialCollectorDict' + }, + 'unroll_len': 1, + 'discount_factor': 1.0, + 'gae_lambda': 1.0, + 'n_episode': 128 + }, + 'eval': { + 'evaluator': { + 'eval_freq': 50, + 'cfg_type': 'BattleInteractionSerialEvaluatorDict', + 'stop_value': [-10.1, -5.05], + 'n_episode': 100 + } + }, + 'other': { + 'replay_buffer': { + 'type': 'naive', + 'replay_buffer_size': 10000, + 'deepcopy': False, + 'enable_track_used_data': False, + 'periodic_thruput_seconds': 60, + 'cfg_type': 'NaiveReplayBufferDict' + }, + 'league': { + 'player_category': ['default'], + 'path_policy': 'league_demo/policy', + 'active_players': { + 'main_player': 2 + }, + 'main_player': { + 'one_phase_step': 200, + 'branch_probs': { + 'pfsp': 0.0, + 'sp': 1.0 + }, + 'strong_win_rate': 0.7 + }, + 'main_exploiter': { + 'one_phase_step': 200, + 'branch_probs': { + 'main_players': 1.0 + }, + 'strong_win_rate': 0.7, + 'min_valid_win_rate': 0.3 + }, + 'league_exploiter': { + 'one_phase_step': 200, + 'branch_probs': { + 'pfsp': 1.0 + }, + 'strong_win_rate': 0.7, + 'mutate_prob': 0.5 + }, + 'use_pretrain': False, + 'use_pretrain_init_historical': False, + 'payoff': { + 'type': 'battle', + 'decay': 0.99, + 'min_win_rate_games': 8 + }, + 'metric': { + 'mu': 0, + 'sigma': 8.333333333333334, + 'beta': 4.166666666666667, + 'tau': 0.0, + 'draw_probability': 0.02 + } + } + }, + 'type': 'ppo', + 'cuda': False, + 'on_policy': True, + 'priority': False, + 'priority_IS_weight': False, + 'recompute_adv': True, + 'action_space': 'discrete', + 'nstep_return': False, + 'multi_agent': False, + 'transition_with_policy_data': True, + 'cfg_type': 'PPOPolicyDict' + }, + 'exp_name': 'league_demo', + 'seed': 0 + } +) diff --git a/ding/framework/middleware/tests/test_league_actor.py b/ding/framework/middleware/tests/test_league_actor.py index 118c4b1971..e8aed67fc8 100644 --- a/ding/framework/middleware/tests/test_league_actor.py +++ b/ding/framework/middleware/tests/test_league_actor.py @@ -2,15 +2,22 @@ import pytest from copy import deepcopy from ding.envs import BaseEnvManager -from ding.framework.middleware.league_learner import LearnerModel from ding.framework.middleware.tests.league_config import cfg from ding.framework.middleware.league_actor import ActorData, LeagueActor, Job -from ding.framework.task import Task +from ding.framework.task import task, Parallel from ding.model import VAC from ding.policy.ppo import PPOPolicy from dizoo.league_demo.game_env import GameEnv +from dataclasses import dataclass + +@dataclass +class LearnerModel: + player_id: str + state_dict: dict + train_iter: int = 0 + class MockLeague: def __init__(self): self.active_players_ids = ["test_node_1", "test_node_2", "test_node_3"] @@ -52,18 +59,29 @@ def policy_fn(): policy = PPOPolicy(cfg.policy, model=model) return policy - league = BaseLeague(cfg.policy.other.league) + league = MockLeague() return cfg, env_fn, policy_fn, league def main(): - cfg, env_fn, policy_fn = prepare_test() + cfg, env_fn, policy_fn, league = prepare_test() + policy = policy_fn() task.start() + ACTOR_ID = 0 + + def on_actor_greeting(actor_id): + assert actor_id == ACTOR_ID + + def on_actor_job(job_: Job): + assert job_.launch_player == job.launch_player + + def on_actor_data(actor_data): + assert isinstance(actor_data, ActorData) - if task.router.node_id == 0: - LeagueActor() + if task.router.node_id == ACTOR_ID: + league_actor = LeagueActor(cfg, env_fn, policy_fn) elif task.router.node_id == 1: - pass + task.on('actor_greeting', on_actor_greeting) if __name__ == "__main__": Parallel.runner(n_parallel_workers=4, protocol="tcp", topology="star")(main) \ No newline at end of file From 532d28eefb371a3cc4becddc03b77e775aa98a1b Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Fri, 27 May 2022 21:18:04 +0800 Subject: [PATCH 030/229] for test --- ding/framework/middleware/league_actor.py | 11 +- .../middleware/tests/test_league_actor.py | 3 +- ding/league/v2/__init__.py | 1 + ding/league/v2/base_league.py | 212 ++++++++++++++++++ 4 files changed, 216 insertions(+), 11 deletions(-) create mode 100644 ding/league/v2/__init__.py create mode 100644 ding/league/v2/base_league.py diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 8ec78c1efb..6094923529 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -12,6 +12,7 @@ from typing import TYPE_CHECKING if TYPE_CHECKING: from ding.framework import OnlineRLContext + from ding.league.v2.base_league import Job from ding.policy import Policy from ding.framework.middleware.league_learner import LearnerModel from ding.framework.middleware import BattleCollector @@ -40,16 +41,6 @@ class PlayerMeta: checkpoint: "Storage" total_agent_step: int = 0 -@dataclass -class Job: - launch_player: str - players: List["PlayerMeta"] - result: list = field(default_factory=list) - job_no: int = 0 # Serial number of job, not required - train_iter: int = None - is_eval: bool = False - - class LeagueActor: def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): diff --git a/ding/framework/middleware/tests/test_league_actor.py b/ding/framework/middleware/tests/test_league_actor.py index e8aed67fc8..eeafce34e8 100644 --- a/ding/framework/middleware/tests/test_league_actor.py +++ b/ding/framework/middleware/tests/test_league_actor.py @@ -3,9 +3,10 @@ from copy import deepcopy from ding.envs import BaseEnvManager from ding.framework.middleware.tests.league_config import cfg -from ding.framework.middleware.league_actor import ActorData, LeagueActor, Job +from ding.framework.middleware.league_actor import ActorData, LeagueActor from ding.framework.task import task, Parallel +from ding.league.v2.base_league import BaseLeague, Job from ding.model import VAC from ding.policy.ppo import PPOPolicy from dizoo.league_demo.game_env import GameEnv diff --git a/ding/league/v2/__init__.py b/ding/league/v2/__init__.py new file mode 100644 index 0000000000..0eb76f750a --- /dev/null +++ b/ding/league/v2/__init__.py @@ -0,0 +1 @@ +from .base_league import BaseLeague, Job diff --git a/ding/league/v2/base_league.py b/ding/league/v2/base_league.py new file mode 100644 index 0000000000..260f34d951 --- /dev/null +++ b/ding/league/v2/base_league.py @@ -0,0 +1,212 @@ +from dataclasses import dataclass, field +from typing import List +import copy +from easydict import EasyDict + +from ding.league.player import ActivePlayer, HistoricalPlayer, create_player +from ding.league.shared_payoff import create_payoff +from ding.utils import deep_merge_dicts +from ding.league.metric import LeagueMetricEnv +from ding.framework.storage import Storage +from typing import TYPE_CHECKING +if TYPE_CHECKING: + from ding.league import Player, PlayerMeta + + +@dataclass +class Job: + launch_player: str + players: List["PlayerMeta"] + result: list = field(default_factory=list) + job_no: int = 0 # Serial number of job, not required + train_iter: int = None + is_eval: bool = False + + +class BaseLeague: + """ + Overview: + League, proposed by Google Deepmind AlphaStar. Can manage multiple players in one league. + Interface: + get_job_info, create_historical_player, update_active_player, update_payoff + + .. note:: + In ``__init__`` method, league would also initialized players as well(in ``_init_players`` method). + """ + + @classmethod + def default_config(cls: type) -> EasyDict: + cfg = EasyDict(copy.deepcopy(cls.config)) + cfg.cfg_type = cls.__name__ + 'Dict' + return cfg + + config = dict( + league_type='baseV2', + import_names=["ding.league.v2.base_league"], + # ---player---- + # "player_category" is just a name. Depends on the env. + # For example, in StarCraft, this can be ['zerg', 'terran', 'protoss']. + player_category=['default'], + # Support different types of active players for solo and battle league. + # For solo league, supports ['solo_active_player']. + # For battle league, supports ['battle_active_player', 'main_player', 'main_exploiter', 'league_exploiter']. + # active_players=dict(), + # "use_pretrain" means whether to use pretrain model to initialize active player. + use_pretrain=False, + # "use_pretrain_init_historical" means whether to use pretrain model to initialize historical player. + # "pretrain_checkpoint_path" is the pretrain checkpoint path used in "use_pretrain" and + # "use_pretrain_init_historical". If both are False, "pretrain_checkpoint_path" can be omitted as well. + # Otherwise, "pretrain_checkpoint_path" should list paths of all player categories. + use_pretrain_init_historical=False, + pretrain_checkpoint_path=dict(default='default_cate_pretrain.pth', ), + # ---payoff--- + payoff=dict( + # Supports ['battle'] + type='battle', + decay=0.99, + min_win_rate_games=8, + ), + metric=dict( + mu=0, + sigma=25 / 3, + beta=25 / 3 / 2, + tau=0.0, + draw_probability=0.02, + ), + ) + + def __init__(self, cfg: EasyDict) -> None: + """ + Overview: + Initialization method. + Arguments: + - cfg (:obj:`EasyDict`): League config. + """ + self.cfg = deep_merge_dicts(self.default_config(), cfg) + self.active_players: List["ActivePlayer"] = [] + self.historical_players: List["HistoricalPlayer"] = [] + self.payoff = create_payoff(self.cfg.payoff) + metric_cfg = self.cfg.metric + self.metric_env = LeagueMetricEnv(metric_cfg.mu, metric_cfg.sigma, metric_cfg.tau, metric_cfg.draw_probability) + self._init_players() + + def _init_players(self) -> None: + """ + Overview: + Initialize players (active & historical) in the league. + """ + # Add different types of active players for each player category, according to ``cfg.active_players``. + for cate in self.cfg.player_category: # Player's category (Depends on the env) + for k, n in self.cfg.active_players.items(): # Active player's type + for i in range(n): # This type's active player number + name = '{}_{}_{}'.format(k, cate, i) + player = create_player( + self.cfg, k, self.cfg[k], cate, self.payoff, None, name, 0, self.metric_env.create_rating() + ) + self.active_players.append(player) + self.payoff.add_player(player) + + # Add pretrain player as the initial HistoricalPlayer for each player category. + if self.cfg.use_pretrain_init_historical: + for cate in self.cfg.player_category: + main_player_name = [k for k in self.cfg.keys() if 'main_player' in k] + assert len(main_player_name) == 1, main_player_name + main_player_name = main_player_name[0] + name = '{}_{}_0_pretrain_historical'.format(main_player_name, cate) + parent_name = '{}_{}_0'.format(main_player_name, cate) + hp = HistoricalPlayer( + self.cfg.get(main_player_name), + cate, + self.payoff, + self.cfg.pretrain_checkpoint_path[cate], + name, + 0, + self.metric_env.create_rating(), + parent_id=parent_name + ) + self.historical_players.append(hp) + self.payoff.add_player(hp) + + # Save active players' ``player_id`` + self.active_players_ids = [p.player_id for p in self.active_players] + # Validate active players are unique by ``player_id``. + assert len(self.active_players_ids) == len(set(self.active_players_ids)) + + def get_job_info(self, player_id: str = None) -> Job: + """ + Overview: + Get info dict of the job which is to be launched to an active player. + Arguments: + - player_id (:obj:`str`): The active player's id. + Returns: + - job_info (:obj:`dict`): Job info. + ReturnsKeys: + - necessary: ``launch_player`` (the active player) + """ + if player_id is None: + player_id = self.active_players_ids[0] + idx = self.active_players_ids.index(player_id) + player = self.active_players[idx] + player_job_info = player.get_job() + opponent_player = player_job_info["opponent"] + job = Job(launch_player=player_id, players=[player.meta, opponent_player.meta]) + return job + + def create_historical_player(self, player_meta: "PlayerMeta", force: bool = False) -> None: + """ + Overview: + Judge whether a player is trained enough for snapshot. If yes, call player's ``snapshot``, create a + historical player(prepare the checkpoint and add it to the shared payoff), then mutate it, and return True. + Otherwise, return False. + Arguments: + - player_id (:obj:`ActivePlayer`): The active player's id. + """ + idx = self.active_players_ids.index(player_meta.player_id) + player: "ActivePlayer" = self.active_players[idx] + if force or (player_meta.checkpoint and player.is_trained_enough()): + # Snapshot + hp = player.snapshot(self.metric_env, player_meta.checkpoint) + self.historical_players.append(hp) + self.payoff.add_player(hp) + + def update_active_player(self, player_meta: "PlayerMeta") -> None: + """ + Overview: + Update an active player's info. + Arguments: + - player_id (:obj:`str`): Player id. + - train_iter (:obj:`int`): Train iteration. + """ + idx = self.active_players_ids.index(player_meta.player_id) + player = self.active_players[idx] + if isinstance(player, ActivePlayer): + player.total_agent_step = player_meta.total_agent_step + + def update_payoff(self, job: Job) -> None: + """ + Overview: + Finish current job. Update shared payoff to record the game results. + Arguments: + - job_info (:obj:`dict`): A dict containing job result information. + """ + job_info = { + "launch_player": job.launch_player, + "player_id": list(map(lambda p: p.player_id, job.players)), + "result": job.result + } + self.payoff.update(job_info) + # Update player rating + home_id, away_id = job_info['player_id'] + home_player, away_player = self.get_player_by_id(home_id), self.get_player_by_id(away_id) + job_info_result = job_info['result'] + if isinstance(job_info_result[0], list): + job_info_result = sum(job_info_result, []) + home_player.rating, away_player.rating = self.metric_env.rate_1vs1( + home_player.rating, away_player.rating, result=job_info_result + ) + + def get_player_by_id(self, player_id: str) -> 'Player': + if 'historical' in player_id: + return [p for p in self.historical_players if p.player_id == player_id][0] + else: + return [p for p in self.active_players if p.player_id == player_id][0] From d7203dc7c7c60eabeb573f59e6c2ac5e7245cb94 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Fri, 27 May 2022 21:31:19 +0800 Subject: [PATCH 031/229] for test --- ding/framework/middleware/__init__.py | 2 +- ding/framework/middleware/league_learner.py | 7 +++ .../middleware/tests/test_league_actor.py | 58 ++++++++----------- 3 files changed, 33 insertions(+), 34 deletions(-) create mode 100644 ding/framework/middleware/league_learner.py diff --git a/ding/framework/middleware/__init__.py b/ding/framework/middleware/__init__.py index ab45651c01..e701f5e4bb 100644 --- a/ding/framework/middleware/__init__.py +++ b/ding/framework/middleware/__init__.py @@ -2,4 +2,4 @@ from .collector import StepCollector, EpisodeCollector, BattleCollector from .learner import OffPolicyLearner, HERLearner from .ckpt_handler import CkptSaver -from .league_actor import LeagueActor, Job \ No newline at end of file +from .league_actor import LeagueActor \ No newline at end of file diff --git a/ding/framework/middleware/league_learner.py b/ding/framework/middleware/league_learner.py new file mode 100644 index 0000000000..a80c861ab4 --- /dev/null +++ b/ding/framework/middleware/league_learner.py @@ -0,0 +1,7 @@ +from dataclasses import dataclass + +@dataclass +class LearnerModel: + player_id: str + state_dict: dict + train_iter: int = 0 \ No newline at end of file diff --git a/ding/framework/middleware/tests/test_league_actor.py b/ding/framework/middleware/tests/test_league_actor.py index eeafce34e8..2b00c3e2f1 100644 --- a/ding/framework/middleware/tests/test_league_actor.py +++ b/ding/framework/middleware/tests/test_league_actor.py @@ -2,6 +2,7 @@ import pytest from copy import deepcopy from ding.envs import BaseEnvManager +from ding.framework.middleware.league_learner import LearnerModel from ding.framework.middleware.tests.league_config import cfg from ding.framework.middleware.league_actor import ActorData, LeagueActor @@ -13,37 +14,6 @@ from dataclasses import dataclass -@dataclass -class LearnerModel: - player_id: str - state_dict: dict - train_iter: int = 0 - -class MockLeague: - def __init__(self): - self.active_players_ids = ["test_node_1", "test_node_2", "test_node_3"] - self.update_payoff_cnt = 0 - self.update_active_player_cnt = 0 - self.create_historical_player_cnt = 0 - self.get_job_info_cnt = 0 - - def update_payoff(self, job): - self.update_payoff_cnt += 1 - # print("update_payoff: {}".format(job)) - - def update_active_player(self, meta): - self.update_active_player_cnt += 1 - # print("update_active_player: {}".format(meta)) - - def create_historical_player(self, meta): - self.create_historical_player_cnt += 1 - # print("create_historical_player: {}".format(meta)) - - def get_job_info(self, player_id): - self.get_job_info_cnt += 1 - # print("get_job_info") - return Job(231890, player_id, False) - def prepare_test(): global cfg cfg = deepcopy(cfg) @@ -60,14 +30,17 @@ def policy_fn(): policy = PPOPolicy(cfg.policy, model=model) return policy - league = MockLeague() + league = BaseLeague(cfg.policy.other.league) return cfg, env_fn, policy_fn, league def main(): cfg, env_fn, policy_fn, league = prepare_test() policy = policy_fn() + league: BaseLeague task.start() + + job: Job = league.get_job_info() ACTOR_ID = 0 def on_actor_greeting(actor_id): @@ -81,8 +54,27 @@ def on_actor_data(actor_data): if task.router.node_id == ACTOR_ID: league_actor = LeagueActor(cfg, env_fn, policy_fn) + elif task.router.node_id == 1: task.on('actor_greeting', on_actor_greeting) + task.on("actor_job", on_actor_job) + task.on("actor_data_player_{}".format(job.launch_player), on_actor_data) + + sleep(0.3) + task.emit("league_job_actor_{}".format(task.router.node_id), job) + sleep(0.3) + assert league_actor._model_updated == False + + task.emit( + "learner_model", + LearnerModel( + player_id=league.active_players_ids[0], state_dict=policy.learn_mode.state_dict(), train_iter=0 + ) + ) + sleep(0.3) + assert league_actor._model_updated == True + + task.finish = True if __name__ == "__main__": - Parallel.runner(n_parallel_workers=4, protocol="tcp", topology="star")(main) \ No newline at end of file + Parallel.runner(n_parallel_workers=2, protocol="tcp", topology="star")(main) \ No newline at end of file From b6b506cb7e6cb9cc50c63d288885c437848cdb76 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Sat, 28 May 2022 00:08:38 +0800 Subject: [PATCH 032/229] test pass --- ding/framework/middleware/collector.py | 16 ++-- ding/framework/middleware/league_actor.py | 55 +++++++++---- .../middleware/tests/test_league_actor.py | 78 +++++++++++++------ ding/framework/storage/__init__.py | 2 + ding/framework/storage/file.py | 12 +++ ding/framework/storage/storage.py | 16 ++++ ding/framework/storage/tests/test_storage.py | 18 +++++ 7 files changed, 148 insertions(+), 49 deletions(-) create mode 100644 ding/framework/storage/__init__.py create mode 100644 ding/framework/storage/file.py create mode 100644 ding/framework/storage/storage.py create mode 100644 ding/framework/storage/tests/test_storage.py diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 468319ef91..fc01e17cc4 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -5,8 +5,8 @@ from ding.framework import task from .functional import inferencer, rolloutor, TransitionList -if TYPE_CHECKING: - from ding.framework import OnlineRLContext +# if TYPE_CHECKING: +from ding.framework import OnlineRLContext import torch from collections import namedtuple @@ -33,12 +33,11 @@ def _reset_policy(ctx: OnlineRLContext): -class BattleCollector(): +class BattleCollector: def __init__( self, cfg: EasyDict, env: BaseEnvManager = None, - policy: List[namedtuple] = None ): self._deepcopy_obs = cfg.deepcopy_obs self._transform_obs = cfg.transform_obs @@ -46,7 +45,6 @@ def __init__( self._timer = EasyTimer() self._end_flag = False self._traj_len = float("inf") - self._reset(env) def _reset_env(self, _env: Optional[BaseEnvManager] = None) -> None: @@ -146,7 +144,7 @@ def __call__(self, ctx: "OnlineRLContext") -> None: the former is a list containing collected episodes if not get_train_sample, \ otherwise, return train_samples split by unroll_len. """ - + ctx.envstep = self._total_envstep_count if ctx.n_episode is None: if ctx._default_n_episode is None: raise RuntimeError("Please specify collect n_episode") @@ -162,7 +160,6 @@ def __call__(self, ctx: "OnlineRLContext") -> None: return_info = [[] for _ in range(2)] ready_env_id = set() remain_episode = ctx.n_episode - while True: with self._timer: # Get current env obs. @@ -196,6 +193,7 @@ def __call__(self, ctx: "OnlineRLContext") -> None: for env_id, timestep in timesteps.items(): self._env_info[env_id]['step'] += 1 self._total_envstep_count += 1 + ctx.envstep = self._total_envstep_count with self._timer: for policy_id, policy in enumerate(ctx._policy): policy_timestep_data = [d[policy_id] if not isinstance(d, bool) else d for d in timestep] @@ -240,8 +238,8 @@ def __call__(self, ctx: "OnlineRLContext") -> None: # log ### TODO: how to deal with log here? # self._output_log(ctx.train_iter) - ctx.return_data = return_data - ctx.return_info = return_info + ctx.train_data = return_data + ctx.episode_info = return_info class StepCollector: diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 6094923529..2b2a07a77f 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -9,13 +9,12 @@ from easydict import EasyDict from ding.envs import BaseEnvManager -from typing import TYPE_CHECKING -if TYPE_CHECKING: - from ding.framework import OnlineRLContext - from ding.league.v2.base_league import Job - from ding.policy import Policy - from ding.framework.middleware.league_learner import LearnerModel - from ding.framework.middleware import BattleCollector +from ding.framework import OnlineRLContext +from ding.league.v2.base_league import Job +from ding.policy import Policy +from ding.framework.middleware.league_learner import LearnerModel +from ding.framework.middleware import BattleCollector +from ding.framework.middleware.collector import reset_policy @dataclass class ActorData: @@ -82,7 +81,6 @@ def _on_league_job(self, job: "Job"): "Waiting for new model on actor: {}, player: {}".format(task.router.node_id, job.launch_player) ) sleep(1) - collector = self._get_collector(job.launch_player) policies = [] main_player: "PlayerMeta" = None @@ -91,10 +89,10 @@ def _on_league_job(self, job: "Job"): if player.player_id == job.launch_player: main_player = player # inferencer,rolloutor = self._get_collector(player.player_id) - assert main_player, "Can not find active player" - collector.reset_policy(policies) + ctx = OnlineRLContext() + reset_policy(policies)(ctx) def send_actor_job(episode_info: List): job.result = [e['result'] for e in episode_info] task.emit("actor_job", job) @@ -106,16 +104,16 @@ def send_actor_data(train_data: List): for d in train_data: d["adv"] = d["reward"] - actor_data = ActorData(env_step=collector.envstep, train_data=train_data) + actor_data = ActorData(env_step=ctx.envstep, train_data=train_data) task.emit("actor_data_player_{}".format(job.launch_player), actor_data) - ctx = OnlineRLContext() + ctx.n_episode = None ctx.train_iter = main_player.total_agent_step ctx.policy_kwargs = None - train_data, episode_info = collector(ctx) - train_data, episode_info = train_data[0], episode_info[0] # only use main player data for training + collector(ctx) + train_data, episode_info = ctx.train_data[0], ctx.episode_info[0] # only use main player data for training send_actor_data(train_data) send_actor_job(episode_info) @@ -151,8 +149,35 @@ def __call__(self): sleep(3) # used for test +# if __name__ == '__main__': +# actor = LeagueActor() + + if __name__ == '__main__': - actor = LeagueActor() + from copy import deepcopy + from ding.framework.middleware.tests.league_config import cfg + from dizoo.league_demo.game_env import GameEnv + + def prepare_test(): + global cfg + cfg = deepcopy(cfg) + + def env_fn(): + env = BaseEnvManager( + env_fn=[lambda: GameEnv(cfg.env.env_type) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager + ) + env.seed(cfg.seed) + return env + + return cfg, env_fn + + cfg, env_fn = prepare_test() + collector = BattleCollector( + cfg.policy.collect.collector, + env_fn() + ) + ctx = OnlineRLContext() + reset_policy(None)(ctx) diff --git a/ding/framework/middleware/tests/test_league_actor.py b/ding/framework/middleware/tests/test_league_actor.py index 2b00c3e2f1..0670257fe9 100644 --- a/ding/framework/middleware/tests/test_league_actor.py +++ b/ding/framework/middleware/tests/test_league_actor.py @@ -4,10 +4,11 @@ from ding.envs import BaseEnvManager from ding.framework.middleware.league_learner import LearnerModel from ding.framework.middleware.tests.league_config import cfg -from ding.framework.middleware.league_actor import ActorData, LeagueActor +from ding.framework.middleware.league_actor import ActorData, LeagueActor, PlayerMeta +from ding.framework.storage import FileStorage from ding.framework.task import task, Parallel -from ding.league.v2.base_league import BaseLeague, Job +from ding.league.v2.base_league import Job from ding.model import VAC from ding.policy.ppo import PPOPolicy from dizoo.league_demo.game_env import GameEnv @@ -30,51 +31,78 @@ def policy_fn(): policy = PPOPolicy(cfg.policy, model=model) return policy - league = BaseLeague(cfg.policy.other.league) - return cfg, env_fn, policy_fn, league + return cfg, env_fn, policy_fn -def main(): - cfg, env_fn, policy_fn, league = prepare_test() +def test_league_actor(): + cfg, env_fn, policy_fn = prepare_test() policy = policy_fn() - league: BaseLeague task.start() - job: Job = league.get_job_info() + job = Job( + launch_player='main_player_default_0', + players=[ + PlayerMeta( + player_id='main_player_default_0', + checkpoint=FileStorage(path = None), + total_agent_step=0 + ), + PlayerMeta( + player_id='main_player_default_1', + checkpoint=FileStorage(path = None), + total_agent_step=0) + ] + ) ACTOR_ID = 0 - - def on_actor_greeting(actor_id): - assert actor_id == ACTOR_ID - - def on_actor_job(job_: Job): - assert job_.launch_player == job.launch_player - - def on_actor_data(actor_data): - assert isinstance(actor_data, ActorData) if task.router.node_id == ACTOR_ID: + sleep(2) league_actor = LeagueActor(cfg, env_fn, policy_fn) + league_actor() elif task.router.node_id == 1: + + testcases = { + "on_actor_greeting": False, + "on_actor_job": False, + "on_actor_data": False, + } + + def on_actor_greeting(actor_id): + assert actor_id == ACTOR_ID + task.emit("league_job_actor_{}".format(ACTOR_ID), job) + testcases["on_actor_greeting"] = True + + def on_actor_job(job_: Job): + assert job_.launch_player == job.launch_player + testcases["on_actor_job"] = True + + + def on_actor_data(actor_data): + assert isinstance(actor_data, ActorData) + testcases["on_actor_data"] = True + task.on('actor_greeting', on_actor_greeting) task.on("actor_job", on_actor_job) task.on("actor_data_player_{}".format(job.launch_player), on_actor_data) sleep(0.3) - task.emit("league_job_actor_{}".format(task.router.node_id), job) - sleep(0.3) - assert league_actor._model_updated == False + # assert league_actor._model_updated == False task.emit( "learner_model", LearnerModel( - player_id=league.active_players_ids[0], state_dict=policy.learn_mode.state_dict(), train_iter=0 + player_id='main_player_default_0', state_dict=policy.learn_mode.state_dict(), train_iter=0 ) ) - sleep(0.3) - assert league_actor._model_updated == True + sleep(5) + # assert league_actor._model_updated == True - task.finish = True + try: + print(testcases) + assert all(testcases.values()) + finally: + task.finish = True if __name__ == "__main__": - Parallel.runner(n_parallel_workers=2, protocol="tcp", topology="star")(main) \ No newline at end of file + Parallel.runner(n_parallel_workers=2, protocol="tcp", topology="mesh")(test_league_actor) \ No newline at end of file diff --git a/ding/framework/storage/__init__.py b/ding/framework/storage/__init__.py new file mode 100644 index 0000000000..6d8c388953 --- /dev/null +++ b/ding/framework/storage/__init__.py @@ -0,0 +1,2 @@ +from .storage import Storage +from .file import FileStorage diff --git a/ding/framework/storage/file.py b/ding/framework/storage/file.py new file mode 100644 index 0000000000..18bcc2c39d --- /dev/null +++ b/ding/framework/storage/file.py @@ -0,0 +1,12 @@ +from typing import Any +from ding.framework.storage import Storage +from ding.utils import read_file, save_file + + +class FileStorage(Storage): + + def save(self, data: Any) -> None: + save_file(self.path, data) + + def load(self) -> Any: + return read_file(self.path) diff --git a/ding/framework/storage/storage.py b/ding/framework/storage/storage.py new file mode 100644 index 0000000000..6ba9e81c9d --- /dev/null +++ b/ding/framework/storage/storage.py @@ -0,0 +1,16 @@ +from abc import abstractmethod +from typing import Any + + +class Storage: + + def __init__(self, path: str) -> None: + self.path = path + + @abstractmethod + def save(self, data: Any) -> None: + raise NotImplementedError + + @abstractmethod + def load(self) -> Any: + raise NotImplementedError diff --git a/ding/framework/storage/tests/test_storage.py b/ding/framework/storage/tests/test_storage.py new file mode 100644 index 0000000000..53eebe3fa2 --- /dev/null +++ b/ding/framework/storage/tests/test_storage.py @@ -0,0 +1,18 @@ +import tempfile +import pytest +import os +from os import path +from ding.framework.storage import FileStorage + + +@pytest.mark.unittest +def test_file_storage(): + path_ = path.join(tempfile.gettempdir(), "test_storage.txt") + try: + storage = FileStorage(path=path_) + storage.save("test") + content = storage.load() + assert content == "test" + finally: + if path.exists(path_): + os.remove(path_) From 9023855b706478d5a82e1deecab3f794e5c7ef81 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Sat, 28 May 2022 16:12:34 +0800 Subject: [PATCH 033/229] correctly use task --- ding/framework/middleware/league_actor.py | 66 +++++------ .../middleware/tests/test_league_actor.py | 103 ++++++++--------- .../tests/test_league_actor_one_process.py | 108 ++++++++++++++++++ 3 files changed, 193 insertions(+), 84 deletions(-) create mode 100644 ding/framework/middleware/tests/test_league_actor_one_process.py diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 2b2a07a77f..ab7730f17c 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -91,8 +91,7 @@ def _on_league_job(self, job: "Job"): # inferencer,rolloutor = self._get_collector(player.player_id) assert main_player, "Can not find active player" - ctx = OnlineRLContext() - reset_policy(policies)(ctx) + reset_policy(policies)( self.ctx) def send_actor_job(episode_info: List): job.result = [e['result'] for e in episode_info] task.emit("actor_job", job) @@ -104,16 +103,16 @@ def send_actor_data(train_data: List): for d in train_data: d["adv"] = d["reward"] - actor_data = ActorData(env_step=ctx.envstep, train_data=train_data) + actor_data = ActorData(env_step=self.ctx.envstep, train_data=train_data) task.emit("actor_data_player_{}".format(job.launch_player), actor_data) - ctx.n_episode = None - ctx.train_iter = main_player.total_agent_step - ctx.policy_kwargs = None + self.ctx.n_episode = None + self.ctx.train_iter = main_player.total_agent_step + self.ctx.policy_kwargs = None - collector(ctx) - train_data, episode_info = ctx.train_data[0], ctx.episode_info[0] # only use main player data for training + collector(self.ctx) + train_data, episode_info = self.ctx.train_data[0], self.ctx.episode_info[0] # only use main player data for training send_actor_data(train_data) send_actor_job(episode_info) @@ -143,7 +142,8 @@ def _get_policy(self, player: "PlayerMeta") -> "Policy.collect_function": return policy - def __call__(self): + def __call__(self, ctx: "OnlineRLContext"): + self.ctx = ctx if not self._running: task.emit("actor_greeting", task.router.node_id) sleep(3) @@ -153,31 +153,31 @@ def __call__(self): # actor = LeagueActor() -if __name__ == '__main__': - from copy import deepcopy - from ding.framework.middleware.tests.league_config import cfg - from dizoo.league_demo.game_env import GameEnv - - def prepare_test(): - global cfg - cfg = deepcopy(cfg) - - def env_fn(): - env = BaseEnvManager( - env_fn=[lambda: GameEnv(cfg.env.env_type) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager - ) - env.seed(cfg.seed) - return env - - return cfg, env_fn +# if __name__ == '__main__': +# from copy import deepcopy +# from ding.framework.middleware.tests.league_config import cfg +# from dizoo.league_demo.game_env import GameEnv + +# def prepare_test(): +# global cfg +# cfg = deepcopy(cfg) + +# def env_fn(): +# env = BaseEnvManager( +# env_fn=[lambda: GameEnv(cfg.env.env_type) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager +# ) +# env.seed(cfg.seed) +# return env + +# return cfg, env_fn - cfg, env_fn = prepare_test() +# cfg, env_fn = prepare_test() - collector = BattleCollector( - cfg.policy.collect.collector, - env_fn() - ) - ctx = OnlineRLContext() - reset_policy(None)(ctx) +# collector = BattleCollector( +# cfg.policy.collect.collector, +# env_fn() +# ) +# ctx = OnlineRLContext() +# reset_policy(None)(ctx) diff --git a/ding/framework/middleware/tests/test_league_actor.py b/ding/framework/middleware/tests/test_league_actor.py index 0670257fe9..6b4e49c324 100644 --- a/ding/framework/middleware/tests/test_league_actor.py +++ b/ding/framework/middleware/tests/test_league_actor.py @@ -37,8 +37,6 @@ def policy_fn(): def test_league_actor(): cfg, env_fn, policy_fn = prepare_test() policy = policy_fn() - task.start() - job = Job( launch_player='main_player_default_0', players=[ @@ -54,55 +52,58 @@ def test_league_actor(): ] ) ACTOR_ID = 0 - - if task.router.node_id == ACTOR_ID: - sleep(2) - league_actor = LeagueActor(cfg, env_fn, policy_fn) - league_actor() - - elif task.router.node_id == 1: - - testcases = { - "on_actor_greeting": False, - "on_actor_job": False, - "on_actor_data": False, - } - - def on_actor_greeting(actor_id): - assert actor_id == ACTOR_ID - task.emit("league_job_actor_{}".format(ACTOR_ID), job) - testcases["on_actor_greeting"] = True - - def on_actor_job(job_: Job): - assert job_.launch_player == job.launch_player - testcases["on_actor_job"] = True - - - def on_actor_data(actor_data): - assert isinstance(actor_data, ActorData) - testcases["on_actor_data"] = True - - task.on('actor_greeting', on_actor_greeting) - task.on("actor_job", on_actor_job) - task.on("actor_data_player_{}".format(job.launch_player), on_actor_data) - - sleep(0.3) - # assert league_actor._model_updated == False - - task.emit( - "learner_model", - LearnerModel( - player_id='main_player_default_0', state_dict=policy.learn_mode.state_dict(), train_iter=0 - ) - ) - sleep(5) - # assert league_actor._model_updated == True - - try: - print(testcases) - assert all(testcases.values()) - finally: - task.finish = True + + with task.start(async_mode=True): + if task.router.node_id == ACTOR_ID: + sleep(2) + league_actor = LeagueActor(cfg, env_fn, policy_fn) + task.use(league_actor) + + elif task.router.node_id == 1: + def test_actor(): + testcases = { + "on_actor_greeting": False, + "on_actor_job": False, + "on_actor_data": False, + } + + def on_actor_greeting(actor_id): + assert actor_id == ACTOR_ID + task.emit("league_job_actor_{}".format(ACTOR_ID), job) + testcases["on_actor_greeting"] = True + + def on_actor_job(job_: Job): + assert job_.launch_player == job.launch_player + testcases["on_actor_job"] = True + + def on_actor_data(actor_data): + assert isinstance(actor_data, ActorData) + testcases["on_actor_data"] = True + + task.on('actor_greeting', on_actor_greeting) + task.on("actor_job", on_actor_job) + task.on("actor_data_player_{}".format(job.launch_player), on_actor_data) + + def _test_actor(ctx): + sleep(0.3) + + task.emit( + "learner_model", + LearnerModel( + player_id='main_player_default_0', state_dict=policy.learn_mode.state_dict(), train_iter=0 + ) + ) + sleep(5) + try: + print(testcases) + assert all(testcases.values()) + finally: + task.finish = True + return _test_actor + + task.use(test_actor()) + + task.run() if __name__ == "__main__": Parallel.runner(n_parallel_workers=2, protocol="tcp", topology="mesh")(test_league_actor) \ No newline at end of file diff --git a/ding/framework/middleware/tests/test_league_actor_one_process.py b/ding/framework/middleware/tests/test_league_actor_one_process.py new file mode 100644 index 0000000000..3d7ab4241e --- /dev/null +++ b/ding/framework/middleware/tests/test_league_actor_one_process.py @@ -0,0 +1,108 @@ +from time import sleep +import pytest +from copy import deepcopy +from ding.envs import BaseEnvManager +from ding.framework.middleware.league_learner import LearnerModel +from ding.framework.middleware.tests.league_config import cfg +from ding.framework.middleware.league_actor import ActorData, LeagueActor, PlayerMeta +from ding.framework.storage import FileStorage + +from ding.framework.task import task, Parallel +from ding.framework import OnlineRLContext +from ding.league.v2.base_league import Job +from ding.model import VAC +from ding.policy.ppo import PPOPolicy +from dizoo.league_demo.game_env import GameEnv + +from dataclasses import dataclass + +def prepare_test(): + global cfg + cfg = deepcopy(cfg) + + def env_fn(): + env = BaseEnvManager( + env_fn=[lambda: GameEnv(cfg.env.env_type) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager + ) + env.seed(cfg.seed) + return env + + def policy_fn(): + model = VAC(**cfg.policy.model) + policy = PPOPolicy(cfg.policy, model=model) + return policy + + return cfg, env_fn, policy_fn + + +@pytest.mark.unittest +def test_league_actor(): + cfg, env_fn, policy_fn = prepare_test() + policy = policy_fn() + with task.start(async_mode=True): + league_actor = LeagueActor(cfg=cfg, env_fn=env_fn, policy_fn=policy_fn) + + def test_actor(): + job = Job( + launch_player='main_player_default_0', + players=[ + PlayerMeta( + player_id='main_player_default_0', + checkpoint=FileStorage(path = None), + total_agent_step=0 + ), + PlayerMeta( + player_id='main_player_default_1', + checkpoint=FileStorage(path = None), + total_agent_step=0) + ] + ) + testcases = { + "on_actor_greeting": False, + "on_actor_job": False, + "on_actor_data": False, + } + + def on_actor_greeting(actor_id): + assert actor_id == task.router.node_id + testcases["on_actor_greeting"] = True + + def on_actor_job(job_: Job): + assert job_.launch_player == job.launch_player + testcases["on_actor_job"] = True + + def on_actor_data(actor_data): + assert isinstance(actor_data, ActorData) + testcases["on_actor_data"] = True + + task.on("actor_greeting", on_actor_greeting) + task.on("actor_job", on_actor_job) + task.on("actor_data_player_{}".format(job.launch_player), on_actor_data) + + def _test_actor(ctx): + sleep(0.3) + task.emit("league_job_actor_{}".format(task.router.node_id), job) + sleep(0.3) + assert league_actor._model_updated == False + + task.emit( + "learner_model", + LearnerModel( + player_id='main_player_default_0', state_dict=policy.learn_mode.state_dict(), train_iter=0 + ) + ) + sleep(0.3) + assert league_actor._model_updated == True + try: + assert all(testcases.values()) + finally: + task.finish = True + + return _test_actor + + task.use(test_actor()) + task.use(league_actor) + task.run() + +if __name__ == "__main__": + test_league_actor() \ No newline at end of file From 1465a52c822ee2af046f58aa74249ba6929177ad Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Sat, 28 May 2022 16:32:50 +0800 Subject: [PATCH 034/229] change a bit --- ding/framework/middleware/collector.py | 9 +- ding/framework/middleware/league_actor.py | 9 +- .../middleware/tests/test_league_actor.py | 87 +++++++++---------- .../tests/test_league_actor_one_process.py | 1 + 4 files changed, 54 insertions(+), 52 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index fc01e17cc4..da138a7ff7 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -14,13 +14,12 @@ from ding.torch_utils import to_tensor, to_ndarray from ding.worker.collector.base_serial_collector import CachePool, TrajBuffer, INF, to_tensor_transitions -def reset_policy(_policy: Optional[List[namedtuple]] = None): +def reset_policy(): def _reset_policy(ctx: OnlineRLContext): - if _policy is not None: - assert len(_policy) > 1, "battle collector needs more than 1 policies" - ctx._policy = _policy - ctx._default_n_episode = _policy[0].get_attribute('cfg').collect.get('n_episode', None) + if ctx._policy is not None: + assert len(ctx._policy) > 1, "battle collector needs more than 1 policies" + ctx._default_n_episode = ctx._policy[0].get_attribute('cfg').collect.get('n_episode', None) # ctx._unroll_len = _policy[0].get_attribute('unroll_len') # unuseful here # ctx._on_policy = _policy[0].get_attribute('cfg').on_policy # unuseful here # ctx._traj_len = INF diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index ab7730f17c..9bfdc79481 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -54,6 +54,7 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self._model_updated = True task.on("league_job_actor_{}".format(task.router.node_id), self._on_league_job) task.on("learner_model", self._on_learner_model) + self._policy_reseter = task.wrap(reset_policy()) def _on_learner_model(self, learner_model: "LearnerModel"): """ @@ -91,7 +92,9 @@ def _on_league_job(self, job: "Job"): # inferencer,rolloutor = self._get_collector(player.player_id) assert main_player, "Can not find active player" - reset_policy(policies)( self.ctx) + self.ctx._policy = policies + self._policy_reseter(self.ctx) + def send_actor_job(episode_info: List): job.result = [e['result'] for e in episode_info] task.emit("actor_job", job) @@ -124,10 +127,10 @@ def _get_collector(self, player_id: str): return self._collectors.get(player_id) cfg = self.cfg env = self.env_fn() - collector = BattleCollector( + collector = task.wrap(BattleCollector( cfg.policy.collect.collector, env - ) + )) self._collectors[player_id] = collector return collector diff --git a/ding/framework/middleware/tests/test_league_actor.py b/ding/framework/middleware/tests/test_league_actor.py index 6b4e49c324..77c228b10e 100644 --- a/ding/framework/middleware/tests/test_league_actor.py +++ b/ding/framework/middleware/tests/test_league_actor.py @@ -54,53 +54,52 @@ def test_league_actor(): ACTOR_ID = 0 with task.start(async_mode=True): - if task.router.node_id == ACTOR_ID: - sleep(2) - league_actor = LeagueActor(cfg, env_fn, policy_fn) - task.use(league_actor) - - elif task.router.node_id == 1: - def test_actor(): - testcases = { - "on_actor_greeting": False, - "on_actor_job": False, - "on_actor_data": False, - } - - def on_actor_greeting(actor_id): - assert actor_id == ACTOR_ID - task.emit("league_job_actor_{}".format(ACTOR_ID), job) - testcases["on_actor_greeting"] = True + league_actor = LeagueActor(cfg, env_fn, policy_fn) + + def test_actor(): + testcases = { + "on_actor_greeting": False, + "on_actor_job": False, + "on_actor_data": False, + } + + def on_actor_greeting(actor_id): + assert actor_id == ACTOR_ID + task.emit("league_job_actor_{}".format(ACTOR_ID), job) + testcases["on_actor_greeting"] = True + + def on_actor_job(job_: Job): + assert job_.launch_player == job.launch_player + testcases["on_actor_job"] = True + + def on_actor_data(actor_data): + assert isinstance(actor_data, ActorData) + testcases["on_actor_data"] = True - def on_actor_job(job_: Job): - assert job_.launch_player == job.launch_player - testcases["on_actor_job"] = True - - def on_actor_data(actor_data): - assert isinstance(actor_data, ActorData) - testcases["on_actor_data"] = True - - task.on('actor_greeting', on_actor_greeting) - task.on("actor_job", on_actor_job) - task.on("actor_data_player_{}".format(job.launch_player), on_actor_data) - - def _test_actor(ctx): - sleep(0.3) - - task.emit( - "learner_model", - LearnerModel( - player_id='main_player_default_0', state_dict=policy.learn_mode.state_dict(), train_iter=0 - ) + task.on('actor_greeting', on_actor_greeting) + task.on("actor_job", on_actor_job) + task.on("actor_data_player_{}".format(job.launch_player), on_actor_data) + + def _test_actor(ctx): + sleep(0.3) + + task.emit( + "learner_model", + LearnerModel( + player_id='main_player_default_0', state_dict=policy.learn_mode.state_dict(), train_iter=0 ) - sleep(5) - try: - print(testcases) - assert all(testcases.values()) - finally: - task.finish = True - return _test_actor + ) + sleep(5) + try: + print(testcases) + assert all(testcases.values()) + finally: + task.finish = True + return _test_actor + if task.router.node_id == ACTOR_ID: + task.use(league_actor) + elif task.router.node_id == 1: task.use(test_actor()) task.run() diff --git a/ding/framework/middleware/tests/test_league_actor_one_process.py b/ding/framework/middleware/tests/test_league_actor_one_process.py index 3d7ab4241e..1afae06eef 100644 --- a/ding/framework/middleware/tests/test_league_actor_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_one_process.py @@ -94,6 +94,7 @@ def _test_actor(ctx): sleep(0.3) assert league_actor._model_updated == True try: + print(testcases) assert all(testcases.values()) finally: task.finish = True From 579c386b43c6caf581457103f9e0fcd89735afa9 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Sat, 28 May 2022 19:43:25 +0800 Subject: [PATCH 035/229] simplify init --- ding/framework/middleware/collector.py | 131 ++++++------------ .../middleware/tests/test_league_actor.py | 2 +- 2 files changed, 47 insertions(+), 86 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index da138a7ff7..617483551e 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -20,9 +20,6 @@ def _reset_policy(ctx: OnlineRLContext): if ctx._policy is not None: assert len(ctx._policy) > 1, "battle collector needs more than 1 policies" ctx._default_n_episode = ctx._policy[0].get_attribute('cfg').collect.get('n_episode', None) - # ctx._unroll_len = _policy[0].get_attribute('unroll_len') # unuseful here - # ctx._on_policy = _policy[0].get_attribute('cfg').on_policy # unuseful here - # ctx._traj_len = INF for p in ctx._policy: p.reset() @@ -36,67 +33,31 @@ class BattleCollector: def __init__( self, cfg: EasyDict, - env: BaseEnvManager = None, + env: BaseEnvManager, ): - self._deepcopy_obs = cfg.deepcopy_obs - self._transform_obs = cfg.transform_obs - self._cfg = cfg + self.cfg = cfg self._timer = EasyTimer() - self._end_flag = False - self._traj_len = float("inf") - self._reset(env) - - def _reset_env(self, _env: Optional[BaseEnvManager] = None) -> None: - """ - Overview: - Reset the environment. - If _env is None, reset the old environment. - If _env is not None, replace the old environment in the collector with the new passed \ - in environment and launch. - Arguments: - - env (:obj:`Optional[BaseEnvManager]`): instance of the subclass of vectorized \ - env_manager(BaseEnvManager) - """ - if _env is not None: - self._env = _env - self._env.launch() - self._env_num = self._env.env_num - else: - self._env.reset() - - def _reset(self, _env: Optional[BaseEnvManager] = None) -> None: - """ - Overview: - Reset the environment. - If _env is None, reset the old environment. - If _env is not None, replace the old environment in the collector with the new passed \ - in environment and launch. - If _policy is None, reset the old policy. - If _policy is not None, replace the old policy in the collector with the new passed in policy. - Arguments: - - policy (:obj:`Optional[List[namedtuple]]`): the api namedtuple of collect_mode policy - - env (:obj:`Optional[BaseEnvManager]`): instance of the subclass of vectorized \ - env_manager(BaseEnvManager) - """ - if _env is not None: - self._reset_env(_env) + self.end_flag = False + self.traj_len = float("inf") + # self._reset(env) + self.env = env + self.env.launch() + self.env_num = self.env.env_num - self._obs_pool = CachePool('obs', self._env_num, deepcopy=self._deepcopy_obs) - self._policy_output_pool = CachePool('policy_output', self._env_num) + self.obs_pool = CachePool('obs', self.env_num, deepcopy=self.cfg.deepcopy_obs) + self.policy_output_pool = CachePool('policy_output', self.env_num) # _traj_buffer is {env_id: {policy_id: TrajBuffer}}, is used to store traj_len pieces of transitions - self._traj_buffer = { - env_id: {policy_id: TrajBuffer(maxlen=self._traj_len) + self.traj_buffer = { + env_id: {policy_id: TrajBuffer(maxlen=self.traj_len) for policy_id in range(2)} - for env_id in range(self._env_num) + for env_id in range(self.env_num) } - self._env_info = {env_id: {'time': 0., 'step': 0} for env_id in range(self._env_num)} - - self._episode_info = [] - self._total_envstep_count = 0 - self._total_episode_count = 0 - self._total_duration = 0 - self._last_train_iter = 0 - self._end_flag = False + self.env_info = {env_id: {'time': 0., 'step': 0} for env_id in range(self.env_num)} + + self.episode_info = [] + self.total_envstep_count = 0 + self.total_episode_count = 0 + self.end_flag = False def _reset_stat(self, env_id: int) -> None: """ @@ -108,10 +69,10 @@ def _reset_stat(self, env_id: int) -> None: - env_id (:obj:`int`): the id where we need to reset the collector's state """ for i in range(2): - self._traj_buffer[env_id][i].clear() - self._obs_pool.reset(env_id) - self._policy_output_pool.reset(env_id) - self._env_info[env_id] = {'time': 0., 'step': 0} + self.traj_buffer[env_id][i].clear() + self.obs_pool.reset(env_id) + self.policy_output_pool.reset(env_id) + self.env_info[env_id] = {'time': 0., 'step': 0} def _close(self) -> None: """ @@ -119,10 +80,10 @@ def _close(self) -> None: Close the collector. If end_flag is False, close the environment, flush the tb_logger\ and close the tb_logger. """ - if self._end_flag: + if self.end_flag: return - self._end_flag = True - self._env.close() + self.end_flag = True + self.env.close() def __del__(self) -> None: """ @@ -143,13 +104,13 @@ def __call__(self, ctx: "OnlineRLContext") -> None: the former is a list containing collected episodes if not get_train_sample, \ otherwise, return train_samples split by unroll_len. """ - ctx.envstep = self._total_envstep_count + ctx.envstep = self.total_envstep_count if ctx.n_episode is None: if ctx._default_n_episode is None: raise RuntimeError("Please specify collect n_episode") else: ctx.n_episode = ctx._default_n_episode - assert ctx.n_episode >= self._env_num, "Please make sure n_episode >= env_num" + assert ctx.n_episode >= self.env_num, "Please make sure n_episode >= env_num" if ctx.policy_kwargs is None: ctx.policy_kwargs = {} @@ -162,20 +123,20 @@ def __call__(self, ctx: "OnlineRLContext") -> None: while True: with self._timer: # Get current env obs. - obs = self._env.ready_obs + obs = self.env.ready_obs new_available_env_id = set(obs.keys()).difference(ready_env_id) ready_env_id = ready_env_id.union(set(list(new_available_env_id)[:remain_episode])) remain_episode -= min(len(new_available_env_id), remain_episode) obs = {env_id: obs[env_id] for env_id in ready_env_id} # Policy forward. - self._obs_pool.update(obs) - if self._transform_obs: + self.obs_pool.update(obs) + if self.cfg.transform_obs: obs = to_tensor(obs, dtype=torch.float32) obs = dicts_to_lists(obs) policy_output = [p.forward(obs[i], **ctx.policy_kwargs) for i, p in enumerate(ctx._policy)] - self._policy_output_pool.update(policy_output) + self.policy_output_pool.update(policy_output) # Interact with env. actions = {} for env_id in ready_env_id: @@ -183,49 +144,49 @@ def __call__(self, ctx: "OnlineRLContext") -> None: for output in policy_output: actions[env_id].append(output[env_id]['action']) actions = to_ndarray(actions) - timesteps = self._env.step(actions) + timesteps = self.env.step(actions) # TODO(nyz) this duration may be inaccurate in async env interaction_duration = self._timer.value / len(timesteps) # TODO(nyz) vectorize this for loop for env_id, timestep in timesteps.items(): - self._env_info[env_id]['step'] += 1 - self._total_envstep_count += 1 - ctx.envstep = self._total_envstep_count + self.env_info[env_id]['step'] += 1 + self.total_envstep_count += 1 + ctx.envstep = self.total_envstep_count with self._timer: for policy_id, policy in enumerate(ctx._policy): policy_timestep_data = [d[policy_id] if not isinstance(d, bool) else d for d in timestep] policy_timestep = type(timestep)(*policy_timestep_data) transition = ctx._policy[policy_id].process_transition( - self._obs_pool[env_id][policy_id], self._policy_output_pool[env_id][policy_id], + self.obs_pool[env_id][policy_id], self.policy_output_pool[env_id][policy_id], policy_timestep ) transition['collect_iter'] = ctx.train_iter - self._traj_buffer[env_id][policy_id].append(transition) + self.traj_buffer[env_id][policy_id].append(transition) # prepare data if timestep.done: - transitions = to_tensor_transitions(self._traj_buffer[env_id][policy_id]) - if self._cfg.get_train_sample: + transitions = to_tensor_transitions(self.traj_buffer[env_id][policy_id]) + if self.cfg.get_train_sample: train_sample = ctx._policy[policy_id].get_train_sample(transitions) return_data[policy_id].extend(train_sample) else: return_data[policy_id].append(transitions) - self._traj_buffer[env_id][policy_id].clear() + self.traj_buffer[env_id][policy_id].clear() - self._env_info[env_id]['time'] += self._timer.value + interaction_duration + self.env_info[env_id]['time'] += self._timer.value + interaction_duration # If env is done, record episode info and reset if timestep.done: - self._total_episode_count += 1 + self.total_episode_count += 1 info = { 'reward0': timestep.info[0]['final_eval_reward'], 'reward1': timestep.info[1]['final_eval_reward'], - 'time': self._env_info[env_id]['time'], - 'step': self._env_info[env_id]['step'], + 'time': self.env_info[env_id]['time'], + 'step': self.env_info[env_id]['step'], } collected_episode += 1 - self._episode_info.append(info) + self.episode_info.append(info) for i, p in enumerate(ctx._policy): p.reset([env_id]) self._reset_stat(env_id) diff --git a/ding/framework/middleware/tests/test_league_actor.py b/ding/framework/middleware/tests/test_league_actor.py index 77c228b10e..648466c65b 100644 --- a/ding/framework/middleware/tests/test_league_actor.py +++ b/ding/framework/middleware/tests/test_league_actor.py @@ -89,7 +89,7 @@ def _test_actor(ctx): player_id='main_player_default_0', state_dict=policy.learn_mode.state_dict(), train_iter=0 ) ) - sleep(5) + sleep(10) try: print(testcases) assert all(testcases.values()) From b404024f9a4f9fd4fd425a25dc65adb0f8de5428 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Sat, 28 May 2022 20:34:47 +0800 Subject: [PATCH 036/229] change a bit --- ding/framework/middleware/collector.py | 46 +++++++++++------------ ding/framework/middleware/league_actor.py | 2 +- 2 files changed, 22 insertions(+), 26 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 617483551e..8e22c51cb6 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -17,11 +17,12 @@ def reset_policy(): def _reset_policy(ctx: OnlineRLContext): - if ctx._policy is not None: - assert len(ctx._policy) > 1, "battle collector needs more than 1 policies" - ctx._default_n_episode = ctx._policy[0].get_attribute('cfg').collect.get('n_episode', None) + if ctx.policies is not None: + assert len(ctx.policies) > 1, "battle collector needs more than 1 policies" + ctx._default_n_episode = ctx.policies[0].get_attribute('cfg').collect.get('n_episode', None) + ctx.agent_num = len(ctx.policies) - for p in ctx._policy: + for p in ctx.policies: p.reset() return _reset_policy @@ -46,7 +47,7 @@ def __init__( self.obs_pool = CachePool('obs', self.env_num, deepcopy=self.cfg.deepcopy_obs) self.policy_output_pool = CachePool('policy_output', self.env_num) - # _traj_buffer is {env_id: {policy_id: TrajBuffer}}, is used to store traj_len pieces of transitions + # traj_buffer is {env_id: {policy_id: TrajBuffer}}, is used to store traj_len pieces of transitions self.traj_buffer = { env_id: {policy_id: TrajBuffer(maxlen=self.traj_len) for policy_id in range(2)} @@ -59,7 +60,7 @@ def __init__( self.total_episode_count = 0 self.end_flag = False - def _reset_stat(self, env_id: int) -> None: + def _reset_stat(self, env_id: int, agent_num: int) -> None: """ Overview: Reset the collector's state. Including reset the traj_buffer, obs_pool, policy_output_pool\ @@ -68,7 +69,7 @@ def _reset_stat(self, env_id: int) -> None: Arguments: - env_id (:obj:`int`): the id where we need to reset the collector's state """ - for i in range(2): + for i in range(agent_num): self.traj_buffer[env_id][i].clear() self.obs_pool.reset(env_id) self.policy_output_pool.reset(env_id) @@ -100,7 +101,7 @@ def __call__(self, ctx: "OnlineRLContext") -> None: - train_iter (:obj:`int`): the number of training iteration - policy_kwargs (:obj:`dict`): the keyword args for policy forward Output of ctx: - - return_data (:obj:`Tuple[List, List]`): A tuple with training sample(data) and episode info, \ + - ctx.train_data (:obj:`Tuple[List, List]`): A tuple with training sample(data) and episode info, \ the former is a list containing collected episodes if not get_train_sample, \ otherwise, return train_samples split by unroll_len. """ @@ -116,8 +117,8 @@ def __call__(self, ctx: "OnlineRLContext") -> None: ctx.policy_kwargs = {} collected_episode = 0 - return_data = [[] for _ in range(2)] - return_info = [[] for _ in range(2)] + ctx.train_data = [[] for _ in range(ctx.agent_num)] + ctx.train_info = [[] for _ in range(ctx.agent_num)] ready_env_id = set() remain_episode = ctx.n_episode while True: @@ -134,7 +135,7 @@ def __call__(self, ctx: "OnlineRLContext") -> None: if self.cfg.transform_obs: obs = to_tensor(obs, dtype=torch.float32) obs = dicts_to_lists(obs) - policy_output = [p.forward(obs[i], **ctx.policy_kwargs) for i, p in enumerate(ctx._policy)] + policy_output = [p.forward(obs[i], **ctx.policy_kwargs) for i, p in enumerate(ctx.policies)] self.policy_output_pool.update(policy_output) # Interact with env. @@ -155,10 +156,10 @@ def __call__(self, ctx: "OnlineRLContext") -> None: self.total_envstep_count += 1 ctx.envstep = self.total_envstep_count with self._timer: - for policy_id, policy in enumerate(ctx._policy): + for policy_id, _ in enumerate(ctx.policies): policy_timestep_data = [d[policy_id] if not isinstance(d, bool) else d for d in timestep] policy_timestep = type(timestep)(*policy_timestep_data) - transition = ctx._policy[policy_id].process_transition( + transition = ctx.policies[policy_id].process_transition( self.obs_pool[env_id][policy_id], self.policy_output_pool[env_id][policy_id], policy_timestep ) @@ -168,10 +169,10 @@ def __call__(self, ctx: "OnlineRLContext") -> None: if timestep.done: transitions = to_tensor_transitions(self.traj_buffer[env_id][policy_id]) if self.cfg.get_train_sample: - train_sample = ctx._policy[policy_id].get_train_sample(transitions) - return_data[policy_id].extend(train_sample) + train_sample = ctx.policies[policy_id].get_train_sample(transitions) + ctx.train_data[policy_id].extend(train_sample) else: - return_data[policy_id].append(transitions) + ctx.train_data[policy_id].append(transitions) self.traj_buffer[env_id][policy_id].clear() self.env_info[env_id]['time'] += self._timer.value + interaction_duration @@ -187,19 +188,14 @@ def __call__(self, ctx: "OnlineRLContext") -> None: } collected_episode += 1 self.episode_info.append(info) - for i, p in enumerate(ctx._policy): + for i, p in enumerate(ctx.policies): p.reset([env_id]) - self._reset_stat(env_id) + self._reset_stat(env_id, ctx.agent_num) ready_env_id.remove(env_id) - for policy_id in range(2): - return_info[policy_id].append(timestep.info[policy_id]) + for policy_id in range(ctx.agent_num): + ctx.train_info[policy_id].append(timestep.info[policy_id]) if collected_episode >= ctx.n_episode: break - # log - ### TODO: how to deal with log here? - # self._output_log(ctx.train_iter) - ctx.train_data = return_data - ctx.episode_info = return_info class StepCollector: diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 9bfdc79481..522f95f853 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -92,7 +92,7 @@ def _on_league_job(self, job: "Job"): # inferencer,rolloutor = self._get_collector(player.player_id) assert main_player, "Can not find active player" - self.ctx._policy = policies + self.ctx.policies = policies self._policy_reseter(self.ctx) def send_actor_job(episode_info: List): From ffcc50b80d43c722aca0996cb7c4093a45596f28 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Sat, 28 May 2022 20:37:46 +0800 Subject: [PATCH 037/229] change a bit --- ding/framework/middleware/collector.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 8e22c51cb6..5c2c7127a2 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -118,7 +118,7 @@ def __call__(self, ctx: "OnlineRLContext") -> None: collected_episode = 0 ctx.train_data = [[] for _ in range(ctx.agent_num)] - ctx.train_info = [[] for _ in range(ctx.agent_num)] + ctx.episode_info = [[] for _ in range(ctx.agent_num)] ready_env_id = set() remain_episode = ctx.n_episode while True: @@ -193,7 +193,7 @@ def __call__(self, ctx: "OnlineRLContext") -> None: self._reset_stat(env_id, ctx.agent_num) ready_env_id.remove(env_id) for policy_id in range(ctx.agent_num): - ctx.train_info[policy_id].append(timestep.info[policy_id]) + ctx.episode_info[policy_id].append(timestep.info[policy_id]) if collected_episode >= ctx.n_episode: break From a55fe17312c15a217a6a9f752553afecb89d9dd6 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Sat, 28 May 2022 20:50:18 +0800 Subject: [PATCH 038/229] change a bit --- ding/framework/middleware/collector.py | 7 +++---- ding/framework/middleware/league_actor.py | 8 ++++---- 2 files changed, 7 insertions(+), 8 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 5c2c7127a2..9bc6205997 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -14,9 +14,8 @@ from ding.torch_utils import to_tensor, to_ndarray from ding.worker.collector.base_serial_collector import CachePool, TrajBuffer, INF, to_tensor_transitions -def reset_policy(): - - def _reset_policy(ctx: OnlineRLContext): +def policy_resetter(): + def _policy_resetter(ctx: OnlineRLContext): if ctx.policies is not None: assert len(ctx.policies) > 1, "battle collector needs more than 1 policies" ctx._default_n_episode = ctx.policies[0].get_attribute('cfg').collect.get('n_episode', None) @@ -25,7 +24,7 @@ def _reset_policy(ctx: OnlineRLContext): for p in ctx.policies: p.reset() - return _reset_policy + return _policy_resetter diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 522f95f853..07c78f9014 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -14,7 +14,7 @@ from ding.policy import Policy from ding.framework.middleware.league_learner import LearnerModel from ding.framework.middleware import BattleCollector -from ding.framework.middleware.collector import reset_policy +from ding.framework.middleware.collector import policy_resetter @dataclass class ActorData: @@ -54,7 +54,7 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self._model_updated = True task.on("league_job_actor_{}".format(task.router.node_id), self._on_league_job) task.on("learner_model", self._on_learner_model) - self._policy_reseter = task.wrap(reset_policy()) + self._policy_resetter = task.wrap(policy_resetter()) def _on_learner_model(self, learner_model: "LearnerModel"): """ @@ -93,7 +93,7 @@ def _on_league_job(self, job: "Job"): assert main_player, "Can not find active player" self.ctx.policies = policies - self._policy_reseter(self.ctx) + self._policy_resetter(self.ctx) def send_actor_job(episode_info: List): job.result = [e['result'] for e in episode_info] @@ -182,5 +182,5 @@ def __call__(self, ctx: "OnlineRLContext"): # env_fn() # ) # ctx = OnlineRLContext() -# reset_policy(None)(ctx) +# policy_resetter(None)(ctx) From 8084daee4cc9321af9cf3ff7bdae526b0c695d7b Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Sat, 28 May 2022 20:58:33 +0800 Subject: [PATCH 039/229] change a bit --- ding/framework/middleware/collector.py | 28 +++++++++++------------ ding/framework/middleware/league_actor.py | 7 +++--- 2 files changed, 18 insertions(+), 17 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 9bc6205997..f4fdc84863 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -20,6 +20,13 @@ def _policy_resetter(ctx: OnlineRLContext): assert len(ctx.policies) > 1, "battle collector needs more than 1 policies" ctx._default_n_episode = ctx.policies[0].get_attribute('cfg').collect.get('n_episode', None) ctx.agent_num = len(ctx.policies) + ctx.traj_len = float("inf") + # traj_buffer is {env_id: {policy_id: TrajBuffer}}, is used to store traj_len pieces of transitions + ctx.traj_buffer = { + env_id: {policy_id: TrajBuffer(maxlen=ctx.traj_len) + for policy_id in range(ctx.agent_num)} + for env_id in range(ctx.env_num) + } for p in ctx.policies: p.reset() @@ -38,7 +45,6 @@ def __init__( self.cfg = cfg self._timer = EasyTimer() self.end_flag = False - self.traj_len = float("inf") # self._reset(env) self.env = env self.env.launch() @@ -46,12 +52,6 @@ def __init__( self.obs_pool = CachePool('obs', self.env_num, deepcopy=self.cfg.deepcopy_obs) self.policy_output_pool = CachePool('policy_output', self.env_num) - # traj_buffer is {env_id: {policy_id: TrajBuffer}}, is used to store traj_len pieces of transitions - self.traj_buffer = { - env_id: {policy_id: TrajBuffer(maxlen=self.traj_len) - for policy_id in range(2)} - for env_id in range(self.env_num) - } self.env_info = {env_id: {'time': 0., 'step': 0} for env_id in range(self.env_num)} self.episode_info = [] @@ -59,7 +59,7 @@ def __init__( self.total_episode_count = 0 self.end_flag = False - def _reset_stat(self, env_id: int, agent_num: int) -> None: + def _reset_stat(self, env_id: int, ctx: OnlineRLContext) -> None: """ Overview: Reset the collector's state. Including reset the traj_buffer, obs_pool, policy_output_pool\ @@ -68,8 +68,8 @@ def _reset_stat(self, env_id: int, agent_num: int) -> None: Arguments: - env_id (:obj:`int`): the id where we need to reset the collector's state """ - for i in range(agent_num): - self.traj_buffer[env_id][i].clear() + for i in range(ctx.agent_num): + ctx.traj_buffer[env_id][i].clear() self.obs_pool.reset(env_id) self.policy_output_pool.reset(env_id) self.env_info[env_id] = {'time': 0., 'step': 0} @@ -163,16 +163,16 @@ def __call__(self, ctx: "OnlineRLContext") -> None: policy_timestep ) transition['collect_iter'] = ctx.train_iter - self.traj_buffer[env_id][policy_id].append(transition) + ctx.traj_buffer[env_id][policy_id].append(transition) # prepare data if timestep.done: - transitions = to_tensor_transitions(self.traj_buffer[env_id][policy_id]) + transitions = to_tensor_transitions(ctx.traj_buffer[env_id][policy_id]) if self.cfg.get_train_sample: train_sample = ctx.policies[policy_id].get_train_sample(transitions) ctx.train_data[policy_id].extend(train_sample) else: ctx.train_data[policy_id].append(transitions) - self.traj_buffer[env_id][policy_id].clear() + ctx.traj_buffer[env_id][policy_id].clear() self.env_info[env_id]['time'] += self._timer.value + interaction_duration @@ -189,7 +189,7 @@ def __call__(self, ctx: "OnlineRLContext") -> None: self.episode_info.append(info) for i, p in enumerate(ctx.policies): p.reset([env_id]) - self._reset_stat(env_id, ctx.agent_num) + self._reset_stat(env_id, ctx) ready_env_id.remove(env_id) for policy_id in range(ctx.agent_num): ctx.episode_info[policy_id].append(timestep.info[policy_id]) diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 07c78f9014..8fd61da5a5 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -44,7 +44,8 @@ class LeagueActor: def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.cfg = cfg - self.env_fn = env_fn + self.env = env_fn() + self.env_num = self.env.env_num self.policy_fn = policy_fn # self.n_rollout_samples = self.cfg.policy.collect.get("n_rollout_samples") or 0 self.n_rollout_samples = 0 @@ -93,6 +94,7 @@ def _on_league_job(self, job: "Job"): assert main_player, "Can not find active player" self.ctx.policies = policies + self.ctx.env_num = self.env_num self._policy_resetter(self.ctx) def send_actor_job(episode_info: List): @@ -126,10 +128,9 @@ def _get_collector(self, player_id: str): if self._collectors.get(player_id): return self._collectors.get(player_id) cfg = self.cfg - env = self.env_fn() collector = task.wrap(BattleCollector( cfg.policy.collect.collector, - env + self.env )) self._collectors[player_id] = collector return collector From da46b22d338949955625e5881f6fbf5df1af9fd9 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Sat, 28 May 2022 21:50:11 +0800 Subject: [PATCH 040/229] change a bit --- ding/framework/middleware/collector.py | 88 +++++++++++++++----------- 1 file changed, 50 insertions(+), 38 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index f4fdc84863..d6c8843936 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -34,6 +34,33 @@ def _policy_resetter(ctx: OnlineRLContext): return _policy_resetter +def battle_inferencer(cfg: EasyDict, env: BaseEnvManager, obs_pool: CachePool, policy_output_pool:CachePool): + def _battle_inferencer(ctx: "OnlineRLContext"): + # Get current env obs. + obs = env.ready_obs + new_available_env_id = set(obs.keys()).difference(ctx.ready_env_id) + ctx.ready_env_id = ctx.ready_env_id.union(set(list(new_available_env_id)[:ctx.remain_episode])) + ctx.remain_episode -= min(len(new_available_env_id), ctx.remain_episode) + obs = {env_id: obs[env_id] for env_id in ctx.ready_env_id} + + # Policy forward. + obs_pool.update(obs) + if cfg.transform_obs: + obs = to_tensor(obs, dtype=torch.float32) + obs = dicts_to_lists(obs) + policy_output = [p.forward(obs[i], **ctx.policy_kwargs) for i, p in enumerate(ctx.policies)] + policy_output_pool.update(policy_output) + + # Interact with env. + actions = {} + for env_id in ctx.ready_env_id: + actions[env_id] = [] + for output in policy_output: + actions[env_id].append(output[env_id]['action']) + actions = to_ndarray(actions) + ctx.timesteps = env.step(actions) + + return _battle_inferencer class BattleCollector: @@ -47,7 +74,6 @@ def __init__( self.end_flag = False # self._reset(env) self.env = env - self.env.launch() self.env_num = self.env.env_num self.obs_pool = CachePool('obs', self.env_num, deepcopy=self.cfg.deepcopy_obs) @@ -58,6 +84,8 @@ def __init__( self.total_envstep_count = 0 self.total_episode_count = 0 self.end_flag = False + + self._battle_inferencer = task.wrap(battle_inferencer(self.cfg, self.env, self.obs_pool, self.policy_output_pool)) def _reset_stat(self, env_id: int, ctx: OnlineRLContext) -> None: """ @@ -100,7 +128,7 @@ def __call__(self, ctx: "OnlineRLContext") -> None: - train_iter (:obj:`int`): the number of training iteration - policy_kwargs (:obj:`dict`): the keyword args for policy forward Output of ctx: - - ctx.train_data (:obj:`Tuple[List, List]`): A tuple with training sample(data) and episode info, \ + - return_data (:obj:`Tuple[List, List]`): A tuple with training sample(data) and episode info, \ the former is a list containing collected episodes if not get_train_sample, \ otherwise, return train_samples split by unroll_len. """ @@ -115,42 +143,23 @@ def __call__(self, ctx: "OnlineRLContext") -> None: if ctx.policy_kwargs is None: ctx.policy_kwargs = {} - collected_episode = 0 - ctx.train_data = [[] for _ in range(ctx.agent_num)] - ctx.episode_info = [[] for _ in range(ctx.agent_num)] - ready_env_id = set() - remain_episode = ctx.n_episode + if self.env.closed: + self.env.launch() + + ctx.collected_episode = 0 + return_data = [[] for _ in range(ctx.agent_num)] + return_info = [[] for _ in range(ctx.agent_num)] + ctx.ready_env_id = set() + ctx.remain_episode = ctx.n_episode while True: with self._timer: - # Get current env obs. - obs = self.env.ready_obs - new_available_env_id = set(obs.keys()).difference(ready_env_id) - ready_env_id = ready_env_id.union(set(list(new_available_env_id)[:remain_episode])) - remain_episode -= min(len(new_available_env_id), remain_episode) - obs = {env_id: obs[env_id] for env_id in ready_env_id} - - # Policy forward. - self.obs_pool.update(obs) - if self.cfg.transform_obs: - obs = to_tensor(obs, dtype=torch.float32) - obs = dicts_to_lists(obs) - policy_output = [p.forward(obs[i], **ctx.policy_kwargs) for i, p in enumerate(ctx.policies)] - - self.policy_output_pool.update(policy_output) - # Interact with env. - actions = {} - for env_id in ready_env_id: - actions[env_id] = [] - for output in policy_output: - actions[env_id].append(output[env_id]['action']) - actions = to_ndarray(actions) - timesteps = self.env.step(actions) + self._battle_inferencer(ctx) # TODO(nyz) this duration may be inaccurate in async env - interaction_duration = self._timer.value / len(timesteps) + interaction_duration = self._timer.value / len(ctx.timesteps) # TODO(nyz) vectorize this for loop - for env_id, timestep in timesteps.items(): + for env_id, timestep in ctx.timesteps.items(): self.env_info[env_id]['step'] += 1 self.total_envstep_count += 1 ctx.envstep = self.total_envstep_count @@ -169,9 +178,9 @@ def __call__(self, ctx: "OnlineRLContext") -> None: transitions = to_tensor_transitions(ctx.traj_buffer[env_id][policy_id]) if self.cfg.get_train_sample: train_sample = ctx.policies[policy_id].get_train_sample(transitions) - ctx.train_data[policy_id].extend(train_sample) + return_data[policy_id].extend(train_sample) else: - ctx.train_data[policy_id].append(transitions) + return_data[policy_id].append(transitions) ctx.traj_buffer[env_id][policy_id].clear() self.env_info[env_id]['time'] += self._timer.value + interaction_duration @@ -185,16 +194,19 @@ def __call__(self, ctx: "OnlineRLContext") -> None: 'time': self.env_info[env_id]['time'], 'step': self.env_info[env_id]['step'], } - collected_episode += 1 + ctx.collected_episode += 1 self.episode_info.append(info) for i, p in enumerate(ctx.policies): p.reset([env_id]) self._reset_stat(env_id, ctx) - ready_env_id.remove(env_id) + ctx.ready_env_id.remove(env_id) for policy_id in range(ctx.agent_num): - ctx.episode_info[policy_id].append(timestep.info[policy_id]) - if collected_episode >= ctx.n_episode: + return_info[policy_id].append(timestep.info[policy_id]) + if ctx.collected_episode >= ctx.n_episode: break + + ctx.train_data = return_data + ctx.episode_info = return_info class StepCollector: From 65b87625229cb50146d7325532ab043bcc1346d6 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Sun, 29 May 2022 00:02:11 +0800 Subject: [PATCH 041/229] change a bit --- ding/framework/middleware/collector.py | 59 +++++++++++++---------- ding/framework/middleware/league_actor.py | 50 ++++--------------- 2 files changed, 44 insertions(+), 65 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index d6c8843936..f62a0c2bbb 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -62,12 +62,37 @@ def _battle_inferencer(ctx: "OnlineRLContext"): return _battle_inferencer +def battle_rolloutor(cfg: EasyDict, obs_pool: CachePool, policy_output_pool:CachePool): + def _battle_rolloutor(ctx: "OnlineRLContext"): + timestep = ctx.timestep + env_id = ctx.env_id + for policy_id, _ in enumerate(ctx.policies): + policy_timestep_data = [d[policy_id] if not isinstance(d, bool) else d for d in timestep] + policy_timestep = type(timestep)(*policy_timestep_data) + transition = ctx.policies[policy_id].process_transition( + obs_pool[env_id][policy_id], policy_output_pool[env_id][policy_id], + policy_timestep + ) + transition['collect_iter'] = ctx.train_iter + ctx.traj_buffer[env_id][policy_id].append(transition) + # If env is done, prepare data + if timestep.done: + transitions = to_tensor_transitions(ctx.traj_buffer[env_id][policy_id]) + if cfg.get_train_sample: + train_sample = ctx.policies[policy_id].get_train_sample(transitions) + ctx.train_data[policy_id].extend(train_sample) + else: + ctx.train_data[policy_id].append(transitions) + ctx.traj_buffer[env_id][policy_id].clear() + return _battle_rolloutor + class BattleCollector: def __init__( self, cfg: EasyDict, env: BaseEnvManager, + n_rollout_samples: int ): self.cfg = cfg self._timer = EasyTimer() @@ -84,8 +109,10 @@ def __init__( self.total_envstep_count = 0 self.total_episode_count = 0 self.end_flag = False + self.n_rollout_samples = n_rollout_samples self._battle_inferencer = task.wrap(battle_inferencer(self.cfg, self.env, self.obs_pool, self.policy_output_pool)) + self._battle_rolloutor = task.wrap(battle_rolloutor(self.cfg, self.obs_pool, self.policy_output_pool)) def _reset_stat(self, env_id: int, ctx: OnlineRLContext) -> None: """ @@ -128,7 +155,7 @@ def __call__(self, ctx: "OnlineRLContext") -> None: - train_iter (:obj:`int`): the number of training iteration - policy_kwargs (:obj:`dict`): the keyword args for policy forward Output of ctx: - - return_data (:obj:`Tuple[List, List]`): A tuple with training sample(data) and episode info, \ + - ctx.train_data (:obj:`Tuple[List, List]`): A tuple with training sample(data) and episode info, \ the former is a list containing collected episodes if not get_train_sample, \ otherwise, return train_samples split by unroll_len. """ @@ -147,8 +174,8 @@ def __call__(self, ctx: "OnlineRLContext") -> None: self.env.launch() ctx.collected_episode = 0 - return_data = [[] for _ in range(ctx.agent_num)] - return_info = [[] for _ in range(ctx.agent_num)] + ctx.train_data = [[] for _ in range(ctx.agent_num)] + ctx.episode_info = [[] for _ in range(ctx.agent_num)] ctx.ready_env_id = set() ctx.remain_episode = ctx.n_episode while True: @@ -163,25 +190,10 @@ def __call__(self, ctx: "OnlineRLContext") -> None: self.env_info[env_id]['step'] += 1 self.total_envstep_count += 1 ctx.envstep = self.total_envstep_count + ctx.env_id = env_id + ctx.timestep = timestep with self._timer: - for policy_id, _ in enumerate(ctx.policies): - policy_timestep_data = [d[policy_id] if not isinstance(d, bool) else d for d in timestep] - policy_timestep = type(timestep)(*policy_timestep_data) - transition = ctx.policies[policy_id].process_transition( - self.obs_pool[env_id][policy_id], self.policy_output_pool[env_id][policy_id], - policy_timestep - ) - transition['collect_iter'] = ctx.train_iter - ctx.traj_buffer[env_id][policy_id].append(transition) - # prepare data - if timestep.done: - transitions = to_tensor_transitions(ctx.traj_buffer[env_id][policy_id]) - if self.cfg.get_train_sample: - train_sample = ctx.policies[policy_id].get_train_sample(transitions) - return_data[policy_id].extend(train_sample) - else: - return_data[policy_id].append(transitions) - ctx.traj_buffer[env_id][policy_id].clear() + self._battle_rolloutor(ctx) self.env_info[env_id]['time'] += self._timer.value + interaction_duration @@ -201,13 +213,10 @@ def __call__(self, ctx: "OnlineRLContext") -> None: self._reset_stat(env_id, ctx) ctx.ready_env_id.remove(env_id) for policy_id in range(ctx.agent_num): - return_info[policy_id].append(timestep.info[policy_id]) + ctx.episode_info[policy_id].append(timestep.info[policy_id]) if ctx.collected_episode >= ctx.n_episode: break - ctx.train_data = return_data - ctx.episode_info = return_info - class StepCollector: """ diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 8fd61da5a5..847143c746 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -47,7 +47,7 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.env = env_fn() self.env_num = self.env.env_num self.policy_fn = policy_fn - # self.n_rollout_samples = self.cfg.policy.collect.get("n_rollout_samples") or 0 + self.n_rollout_samples = self.cfg.policy.collect.get("n_rollout_samples") or 0 self.n_rollout_samples = 0 self._running = False self._collectors: Dict[str, BattleCollector] = {} @@ -63,11 +63,10 @@ def _on_learner_model(self, learner_model: "LearnerModel"): """ player_meta = PlayerMeta(player_id=learner_model.player_id, checkpoint=None) policy = self._get_policy(player_meta) + # update policy model policy.load_state_dict(learner_model.state_dict) self._model_updated = True - # update policy model - def _on_league_job(self, job: "Job"): """ Deal with job distributed by coordinator. Load historical model, generate traj and emit data. @@ -111,10 +110,12 @@ def send_actor_data(train_data: List): actor_data = ActorData(env_step=self.ctx.envstep, train_data=train_data) task.emit("actor_data_player_{}".format(job.launch_player), actor_data) - - self.ctx.n_episode = None - self.ctx.train_iter = main_player.total_agent_step - self.ctx.policy_kwargs = None + if self.n_rollout_samples > 0: + pass + else: + self.ctx.n_episode = None + self.ctx.train_iter = main_player.total_agent_step + self.ctx.policy_kwargs = None collector(self.ctx) train_data, episode_info = self.ctx.train_data[0], self.ctx.episode_info[0] # only use main player data for training @@ -130,7 +131,8 @@ def _get_collector(self, player_id: str): cfg = self.cfg collector = task.wrap(BattleCollector( cfg.policy.collect.collector, - self.env + self.env, + self.n_rollout_samples )) self._collectors[player_id] = collector return collector @@ -152,36 +154,4 @@ def __call__(self, ctx: "OnlineRLContext"): task.emit("actor_greeting", task.router.node_id) sleep(3) -# used for test -# if __name__ == '__main__': -# actor = LeagueActor() - - -# if __name__ == '__main__': -# from copy import deepcopy -# from ding.framework.middleware.tests.league_config import cfg -# from dizoo.league_demo.game_env import GameEnv - -# def prepare_test(): -# global cfg -# cfg = deepcopy(cfg) - -# def env_fn(): -# env = BaseEnvManager( -# env_fn=[lambda: GameEnv(cfg.env.env_type) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager -# ) -# env.seed(cfg.seed) -# return env - -# return cfg, env_fn - -# cfg, env_fn = prepare_test() - - -# collector = BattleCollector( -# cfg.policy.collect.collector, -# env_fn() -# ) -# ctx = OnlineRLContext() -# policy_resetter(None)(ctx) From ad9632c03c0e9c746e8f9151e8dd0d59f5fb8eab Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Sun, 29 May 2022 00:06:17 +0800 Subject: [PATCH 042/229] change position of policy_resetter, battle_rolloutor, battle_inferencer --- ding/framework/middleware/collector.py | 81 +------------------ .../middleware/functional/__init__.py | 2 +- .../middleware/functional/collector.py | 80 +++++++++++++++++- ding/framework/middleware/league_actor.py | 2 +- 4 files changed, 83 insertions(+), 82 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index f62a0c2bbb..4975798a38 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -3,88 +3,13 @@ from ding.policy import Policy, get_random_policy from ding.envs import BaseEnvManager from ding.framework import task -from .functional import inferencer, rolloutor, TransitionList +from .functional import inferencer, rolloutor, TransitionList, battle_inferencer, battle_rolloutor # if TYPE_CHECKING: from ding.framework import OnlineRLContext -import torch -from collections import namedtuple -from ding.utils import EasyTimer, dicts_to_lists -from ding.torch_utils import to_tensor, to_ndarray -from ding.worker.collector.base_serial_collector import CachePool, TrajBuffer, INF, to_tensor_transitions - -def policy_resetter(): - def _policy_resetter(ctx: OnlineRLContext): - if ctx.policies is not None: - assert len(ctx.policies) > 1, "battle collector needs more than 1 policies" - ctx._default_n_episode = ctx.policies[0].get_attribute('cfg').collect.get('n_episode', None) - ctx.agent_num = len(ctx.policies) - ctx.traj_len = float("inf") - # traj_buffer is {env_id: {policy_id: TrajBuffer}}, is used to store traj_len pieces of transitions - ctx.traj_buffer = { - env_id: {policy_id: TrajBuffer(maxlen=ctx.traj_len) - for policy_id in range(ctx.agent_num)} - for env_id in range(ctx.env_num) - } - - for p in ctx.policies: - p.reset() - - return _policy_resetter - - -def battle_inferencer(cfg: EasyDict, env: BaseEnvManager, obs_pool: CachePool, policy_output_pool:CachePool): - def _battle_inferencer(ctx: "OnlineRLContext"): - # Get current env obs. - obs = env.ready_obs - new_available_env_id = set(obs.keys()).difference(ctx.ready_env_id) - ctx.ready_env_id = ctx.ready_env_id.union(set(list(new_available_env_id)[:ctx.remain_episode])) - ctx.remain_episode -= min(len(new_available_env_id), ctx.remain_episode) - obs = {env_id: obs[env_id] for env_id in ctx.ready_env_id} - - # Policy forward. - obs_pool.update(obs) - if cfg.transform_obs: - obs = to_tensor(obs, dtype=torch.float32) - obs = dicts_to_lists(obs) - policy_output = [p.forward(obs[i], **ctx.policy_kwargs) for i, p in enumerate(ctx.policies)] - policy_output_pool.update(policy_output) - - # Interact with env. - actions = {} - for env_id in ctx.ready_env_id: - actions[env_id] = [] - for output in policy_output: - actions[env_id].append(output[env_id]['action']) - actions = to_ndarray(actions) - ctx.timesteps = env.step(actions) - - return _battle_inferencer - -def battle_rolloutor(cfg: EasyDict, obs_pool: CachePool, policy_output_pool:CachePool): - def _battle_rolloutor(ctx: "OnlineRLContext"): - timestep = ctx.timestep - env_id = ctx.env_id - for policy_id, _ in enumerate(ctx.policies): - policy_timestep_data = [d[policy_id] if not isinstance(d, bool) else d for d in timestep] - policy_timestep = type(timestep)(*policy_timestep_data) - transition = ctx.policies[policy_id].process_transition( - obs_pool[env_id][policy_id], policy_output_pool[env_id][policy_id], - policy_timestep - ) - transition['collect_iter'] = ctx.train_iter - ctx.traj_buffer[env_id][policy_id].append(transition) - # If env is done, prepare data - if timestep.done: - transitions = to_tensor_transitions(ctx.traj_buffer[env_id][policy_id]) - if cfg.get_train_sample: - train_sample = ctx.policies[policy_id].get_train_sample(transitions) - ctx.train_data[policy_id].extend(train_sample) - else: - ctx.train_data[policy_id].append(transitions) - ctx.traj_buffer[env_id][policy_id].clear() - return _battle_rolloutor +from ding.utils import EasyTimer +from ding.worker.collector.base_serial_collector import CachePool class BattleCollector: diff --git a/ding/framework/middleware/functional/__init__.py b/ding/framework/middleware/functional/__init__.py index defdc3f4c4..de028e8834 100644 --- a/ding/framework/middleware/functional/__init__.py +++ b/ding/framework/middleware/functional/__init__.py @@ -1,7 +1,7 @@ from .trainer import trainer, multistep_trainer from .data_processor import offpolicy_data_fetcher, data_pusher, offline_data_fetcher, offline_data_saver, \ sqil_data_pusher -from .collector import inferencer, rolloutor, TransitionList +from .collector import inferencer, rolloutor, TransitionList, policy_resetter, battle_inferencer, battle_rolloutor from .evaluator import interaction_evaluator from .termination_checker import termination_checker from .pace_controller import pace_controller diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 7a826e5309..adc344cf16 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -4,9 +4,13 @@ import treetensor.torch as ttorch from ding.envs import BaseEnvManager from ding.policy import Policy +import torch +from ding.utils import dicts_to_lists +from ding.torch_utils import to_tensor, to_ndarray +from ding.worker.collector.base_serial_collector import CachePool, TrajBuffer, to_tensor_transitions -if TYPE_CHECKING: - from ding.framework import OnlineRLContext +# if TYPE_CHECKING: +from ding.framework import OnlineRLContext class TransitionList: @@ -133,3 +137,75 @@ def _rollout(ctx: "OnlineRLContext"): # TODO log return _rollout + +def policy_resetter(): + def _policy_resetter(ctx: OnlineRLContext): + if ctx.policies is not None: + assert len(ctx.policies) > 1, "battle collector needs more than 1 policies" + ctx._default_n_episode = ctx.policies[0].get_attribute('cfg').collect.get('n_episode', None) + ctx.agent_num = len(ctx.policies) + ctx.traj_len = float("inf") + # traj_buffer is {env_id: {policy_id: TrajBuffer}}, is used to store traj_len pieces of transitions + ctx.traj_buffer = { + env_id: {policy_id: TrajBuffer(maxlen=ctx.traj_len) + for policy_id in range(ctx.agent_num)} + for env_id in range(ctx.env_num) + } + + for p in ctx.policies: + p.reset() + + return _policy_resetter + + +def battle_inferencer(cfg: EasyDict, env: BaseEnvManager, obs_pool: CachePool, policy_output_pool:CachePool): + def _battle_inferencer(ctx: "OnlineRLContext"): + # Get current env obs. + obs = env.ready_obs + new_available_env_id = set(obs.keys()).difference(ctx.ready_env_id) + ctx.ready_env_id = ctx.ready_env_id.union(set(list(new_available_env_id)[:ctx.remain_episode])) + ctx.remain_episode -= min(len(new_available_env_id), ctx.remain_episode) + obs = {env_id: obs[env_id] for env_id in ctx.ready_env_id} + + # Policy forward. + obs_pool.update(obs) + if cfg.transform_obs: + obs = to_tensor(obs, dtype=torch.float32) + obs = dicts_to_lists(obs) + policy_output = [p.forward(obs[i], **ctx.policy_kwargs) for i, p in enumerate(ctx.policies)] + policy_output_pool.update(policy_output) + + # Interact with env. + actions = {} + for env_id in ctx.ready_env_id: + actions[env_id] = [] + for output in policy_output: + actions[env_id].append(output[env_id]['action']) + actions = to_ndarray(actions) + ctx.timesteps = env.step(actions) + + return _battle_inferencer + +def battle_rolloutor(cfg: EasyDict, obs_pool: CachePool, policy_output_pool:CachePool): + def _battle_rolloutor(ctx: "OnlineRLContext"): + timestep = ctx.timestep + env_id = ctx.env_id + for policy_id, _ in enumerate(ctx.policies): + policy_timestep_data = [d[policy_id] if not isinstance(d, bool) else d for d in timestep] + policy_timestep = type(timestep)(*policy_timestep_data) + transition = ctx.policies[policy_id].process_transition( + obs_pool[env_id][policy_id], policy_output_pool[env_id][policy_id], + policy_timestep + ) + transition['collect_iter'] = ctx.train_iter + ctx.traj_buffer[env_id][policy_id].append(transition) + # If env is done, prepare data + if timestep.done: + transitions = to_tensor_transitions(ctx.traj_buffer[env_id][policy_id]) + if cfg.get_train_sample: + train_sample = ctx.policies[policy_id].get_train_sample(transitions) + ctx.train_data[policy_id].extend(train_sample) + else: + ctx.train_data[policy_id].append(transitions) + ctx.traj_buffer[env_id][policy_id].clear() + return _battle_rolloutor \ No newline at end of file diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 847143c746..6a814de5a9 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -14,7 +14,7 @@ from ding.policy import Policy from ding.framework.middleware.league_learner import LearnerModel from ding.framework.middleware import BattleCollector -from ding.framework.middleware.collector import policy_resetter +from ding.framework.middleware.functional import policy_resetter @dataclass class ActorData: From 192e6e4e436ef9d67095ede4bd84fc9be58b0ebf Mon Sep 17 00:00:00 2001 From: lixuelin Date: Mon, 30 May 2022 10:12:28 +0800 Subject: [PATCH 043/229] polish stdim & infonce loss --- ding/policy/command_mode_policy_instance.py | 7 ++- ding/policy/dqn.py | 59 +++++++++++++++---- ding/torch_utils/loss/__init__.py | 1 - .../loss/tests/test_contrastive_loss.py | 9 +-- .../serial/pong/pong_dqn_stdim_config.py | 5 +- .../config/cartpole_dqn_stdim_config.py | 5 +- 6 files changed, 64 insertions(+), 22 deletions(-) diff --git a/ding/policy/command_mode_policy_instance.py b/ding/policy/command_mode_policy_instance.py index 51455a4d11..17661aed6e 100644 --- a/ding/policy/command_mode_policy_instance.py +++ b/ding/policy/command_mode_policy_instance.py @@ -2,7 +2,7 @@ from ding.rl_utils import get_epsilon_greedy_fn from .base_policy import CommandModePolicy -from .dqn import DQNPolicy +from .dqn import DQNPolicy, DQNSTDIMPolicy from .c51 import C51Policy from .qrdqn import QRDQNPolicy from .iqn import IQNPolicy @@ -92,6 +92,11 @@ class DQNCommandModePolicy(DQNPolicy, EpsCommandModePolicy): pass +@POLICY_REGISTRY.register('dqn_stdim_command') +class DQNSTDIMCommandModePolicy(DQNSTDIMPolicy, EpsCommandModePolicy): + pass + + @POLICY_REGISTRY.register('dqfd_command') class DQFDCommandModePolicy(DQFDPolicy, EpsCommandModePolicy): pass diff --git a/ding/policy/dqn.py b/ding/policy/dqn.py index d3f28f440f..4de1dcedcb 100644 --- a/ding/policy/dqn.py +++ b/ding/policy/dqn.py @@ -4,13 +4,14 @@ import torch from ding.torch_utils import Adam, to_device +from ding.torch_utils.loss.contrastive_loss import ContrastiveLoss from ding.rl_utils import q_nstep_td_data, q_nstep_td_error, get_nstep_return_data, get_train_sample from ding.model import model_wrap from ding.utils import POLICY_REGISTRY from ding.utils.data import default_collate, default_decollate + from .base_policy import Policy from .common_utils import default_preprocess_learn -from ding.torch_utils import ContrastiveLoss @POLICY_REGISTRY.register('dqn') @@ -393,7 +394,7 @@ class DQNSTDIMPolicy(DQNPolicy): == ==================== ======== ============== ======================================== ======================= ID Symbol Type Default Value Description Other(Shape) == ==================== ======== ============== ======================================== ======================= - 1 ``type`` str dqn | RL policy register name, refer to | This arg is optional, + 1 ``type`` str dqn_stdim | RL policy register name, refer to | This arg is optional, | registry ``POLICY_REGISTRY`` | a placeholder 2 ``cuda`` bool False | Whether to use cuda for network | This arg can be diff- | erent from modes @@ -437,14 +438,14 @@ class DQNSTDIMPolicy(DQNPolicy): | decay from start | value to end value | during decay length. - 20 | ``loss_ratio`` float 0.01 | the ratio of auxiliary loss to main | any real value, - | loss | typically in + 20 | ``aux_loss_ratio`` float 0.05 | the ratio of the auxiliary loss to | any real value, + | the TD loss | typically in | [-0.1, 0.1]. == ==================== ======== ============== ======================================== ======================= """ config = dict( - type='dqn', + type='dqn_stdim', # (bool) Whether use cuda in policy cuda=False, # (bool) Whether learning policy is the same as collecting data policy(on-policy) @@ -499,18 +500,17 @@ class DQNSTDIMPolicy(DQNPolicy): ), replay_buffer=dict(replay_buffer_size=10000, ), ), - loss_ratio=0.01, + aux_loss_ratio=0.05, ) def _init_learn(self) -> None: super()._init_learn() - self._main_encoder = self._model.encoder x_size, y_size = self._get_encoding_size() self._aux_model = ContrastiveLoss(x_size, y_size, **self._cfg.aux_model) if self._cuda: self._aux_model.cuda() self._aux_optimizer = Adam(self._aux_model.parameters(), lr=self._cfg.learn.learning_rate) - self._aux_ratio = self._cfg.loss_ratio + self._aux_ratio = self._cfg.aux_loss_ratio def _get_encoding_size(self): obs = self._cfg.model.obs_shape @@ -526,7 +526,7 @@ def _get_encoding_size(self): def _aux_encode(self, data): x = data["obs"] - y = self._main_encoder(data["obs"]) + y = self._model.encoder(data["obs"]) return x, y def _forward_learn(self, data: Dict[str, Any]) -> Dict[str, Any]: @@ -583,14 +583,14 @@ def _forward_learn(self, data: Dict[str, Any]) -> Dict[str, Any]: q_value, target_q_value, data['action'], target_q_action, data['reward'], data['done'], data['weight'] ) value_gamma = data.get('value_gamma') - loss, td_error_per_sample = q_nstep_td_error(data_n, self._gamma, nstep=self._nstep, value_gamma=value_gamma) + bellman_loss, td_error_per_sample = q_nstep_td_error(data_n, self._gamma, nstep=self._nstep, value_gamma=value_gamma) # ====================== # Compute auxiliary loss # ====================== x, y = self._aux_encode(data) aux_loss_eval = self._aux_model.forward(x, y) * self._aux_ratio - loss += aux_loss_eval + loss = aux_loss_eval + bellman_loss # ==================== # Q-learning update @@ -607,10 +607,45 @@ def _forward_learn(self, data: Dict[str, Any]) -> Dict[str, Any]: self._target_model.update(self._learn_model.state_dict()) return { 'cur_lr': self._optimizer.defaults['lr'], - 'total_loss': loss.item(), + 'bellman_loss': bellman_loss.item(), 'aux_loss': aux_loss_eval.item(), + 'total_loss': loss.item(), 'q_value': q_value.mean().item(), 'priority': td_error_per_sample.abs().tolist(), # Only discrete action satisfying len(data['action'])==1 can return this and draw histogram on tensorboard. # '[histogram]action_distribution': data['action'], } + + def _monitor_vars_learn(self) -> List[str]: + return ['cur_lr', 'bellman_loss', 'aux_loss', 'total_loss', 'q_value'] + + def _state_dict_learn(self) -> Dict[str, Any]: + """ + Overview: + Return the state_dict of learn mode, usually including model and optimizer. + Returns: + - state_dict (:obj:`Dict[str, Any]`): the dict of current policy learn state, for saving and restoring. + """ + return { + 'model': self._learn_model.state_dict(), + 'target_model': self._target_model.state_dict(), + 'optimizer': self._optimizer.state_dict(), + 'aux_optimizer': self._aux_optimizer.state_dict(), + } + + def _load_state_dict_learn(self, state_dict: Dict[str, Any]) -> None: + """ + Overview: + Load the state_dict variable into policy learn mode. + Arguments: + - state_dict (:obj:`Dict[str, Any]`): the dict of policy learn state saved before. + + .. tip:: + If you want to only load some parts of model, you can simply set the ``strict`` argument in \ + load_state_dict to ``False``, or refer to ``ding.torch_utils.checkpoint_helper`` for more \ + complicated operation. + """ + self._learn_model.load_state_dict(state_dict['model']) + self._target_model.load_state_dict(state_dict['target_model']) + self._optimizer.load_state_dict(state_dict['optimizer']) + self._aux_optimizer.load_state_dict(state_dict['aux_optimizer']) diff --git a/ding/torch_utils/loss/__init__.py b/ding/torch_utils/loss/__init__.py index 8668e53b98..e2795e2747 100644 --- a/ding/torch_utils/loss/__init__.py +++ b/ding/torch_utils/loss/__init__.py @@ -1,3 +1,2 @@ from .cross_entropy_loss import LabelSmoothCELoss, SoftFocalLoss, build_ce_criterion from .multi_logits_loss import MultiLogitsLoss -from .contrastive_loss import ContrastiveLoss diff --git a/ding/torch_utils/loss/tests/test_contrastive_loss.py b/ding/torch_utils/loss/tests/test_contrastive_loss.py index 8cbdec8f03..83eeb182d3 100644 --- a/ding/torch_utils/loss/tests/test_contrastive_loss.py +++ b/ding/torch_utils/loss/tests/test_contrastive_loss.py @@ -2,18 +2,19 @@ import numpy as np import torch from torch.utils.data import TensorDataset, DataLoader -from ding.torch_utils import ContrastiveLoss +from ding.torch_utils.loss.contrastive_loss import ContrastiveLoss -@pytest.mark.unittest -@pytest.mark.parametrize('noise', [0.1, 1.0, 3.0]) +@pytest.mark.benchmark +@pytest.mark.parametrize('noise', [0.1, 1.0]) @pytest.mark.parametrize('dims', [ [16], + [3, 16, 16] ]) def test_infonce_loss(noise, dims): print_loss = False batch_size = 128 - N_batch = 10 + N_batch = 3 x_dim = [batch_size * N_batch] + dims encode_shape = 16 diff --git a/dizoo/atari/config/serial/pong/pong_dqn_stdim_config.py b/dizoo/atari/config/serial/pong/pong_dqn_stdim_config.py index 2f91944bee..7ce8b78cb3 100644 --- a/dizoo/atari/config/serial/pong/pong_dqn_stdim_config.py +++ b/dizoo/atari/config/serial/pong/pong_dqn_stdim_config.py @@ -24,7 +24,8 @@ loss_type = 'infonce', temperature = 1.0, ), - loss_ratio = 0.05, + # the ratio of the auxiliary loss to the TD loss + aux_loss_ratio = 0.05, nstep=3, discount_factor=0.99, learn=dict( @@ -54,7 +55,7 @@ import_names=['dizoo.atari.envs.atari_env'], ), env_manager=dict(type='subprocess'), - policy=dict(type='dqn'), + policy=dict(type='dqn_stdim'), ) pong_dqn_stdim_create_config = EasyDict(pong_dqn_stdim_create_config) create_config = pong_dqn_stdim_create_config diff --git a/dizoo/classic_control/cartpole/config/cartpole_dqn_stdim_config.py b/dizoo/classic_control/cartpole/config/cartpole_dqn_stdim_config.py index 0695d91475..816c3721ce 100644 --- a/dizoo/classic_control/cartpole/config/cartpole_dqn_stdim_config.py +++ b/dizoo/classic_control/cartpole/config/cartpole_dqn_stdim_config.py @@ -24,7 +24,8 @@ loss_type = 'infonce', temperature = 1.0, ), - loss_ratio = 0.05, + # the ratio of the auxiliary loss to the TD loss + aux_loss_ratio = 0.05, nstep=1, discount_factor=0.97, learn=dict( @@ -52,7 +53,7 @@ import_names=['dizoo.classic_control.cartpole.envs.cartpole_env'], ), env_manager=dict(type='base'), - policy=dict(type='dqn'), + policy=dict(type='dqn_stdim'), replay_buffer=dict( type='deque', import_names=['ding.data.buffer.deque_buffer_wrapper'] From 46ee7cf7ace7cd9e575831fc45a84622daca80d8 Mon Sep 17 00:00:00 2001 From: lixuelin Date: Mon, 30 May 2022 11:46:47 +0800 Subject: [PATCH 044/229] polish EventEnum --- ding/framework/event_enum.py | 22 +++++++++---------- ding/framework/event_loop.py | 13 +++++++++++ .../middleware/league_coordinator.py | 8 +++---- .../tests/test_league_coordinator.py | 20 ++++++++--------- 4 files changed, 37 insertions(+), 26 deletions(-) diff --git a/ding/framework/event_enum.py b/ding/framework/event_enum.py index bdc8c56462..c0ea7f9dcb 100644 --- a/ding/framework/event_enum.py +++ b/ding/framework/event_enum.py @@ -2,17 +2,15 @@ @unique -class EventEnum(Enum): - COORDINATOR_DISPATCH_ACTOR_JOB = 1000 +class EventEnum(str, Enum): + # events emited by coordinators + COORDINATOR_DISPATCH_ACTOR_JOB = "on_coordinator_dispatch_actor_job_{actor_id}" - LEARNER_SEND_MODEL = 2000 - LEARNER_SEND_META = 2001 + # events emited by learners + LEARNER_SEND_MODEL = "on_learner_send_model" + LEARNER_SEND_META = "on_learner_send_meta" - ACTOR_GREETING = 3000 - ACTOR_SEND_DATA = 3001 - ACTOR_FINISH_JOB = 3002 - - def __call__(self, node_id: int = None): - if not node_id: - return "event_{}".format(self.value) - return "event_{}_{}".format(self.value, node_id) \ No newline at end of file + # events emited by actors + ACTOR_GREETING = "on_actor_greeting" + ACTOR_SEND_DATA = "on_actor_send_meta" + ACTOR_FINISH_JOB = "on_actor_finish_job" diff --git a/ding/framework/event_loop.py b/ding/framework/event_loop.py index b5f58720a1..a4665ca01b 100644 --- a/ding/framework/event_loop.py +++ b/ding/framework/event_loop.py @@ -1,3 +1,4 @@ +import re from collections import defaultdict from typing import Callable, Optional from concurrent.futures import ThreadPoolExecutor @@ -23,6 +24,12 @@ def on(self, event: str, fn: Callable) -> None: - event (:obj:`str`): Event name. - fn (:obj:`Callable`): The function. """ + # check if the event name contains unfilled parameters. + params = re.findall(r"\{(.*?)\}", event) + if params: + raise ValueError( + "Event name missing parameters: {}. Please use String.format() to fill up".format(", ".join(params)) + ) self._listeners[event].append(fn) def off(self, event: str, fn: Optional[Callable] = None) -> None: @@ -65,6 +72,12 @@ def emit(self, event: str, *args, **kwargs) -> None: """ if self._exception: raise self._exception + # check if the event name contains unfilled parameters. + params = re.findall(r"\{(.*?)\}", event) + if params: + raise ValueError( + "Event name missing parameters: {}. Please use String.format() to fill up".format(", ".join(params)) + ) if self._active: self._thread_pool.submit(self._trigger, event, *args, **kwargs) diff --git a/ding/framework/middleware/league_coordinator.py b/ding/framework/middleware/league_coordinator.py index bb037cdcb8..ab995b5341 100644 --- a/ding/framework/middleware/league_coordinator.py +++ b/ding/framework/middleware/league_coordinator.py @@ -22,9 +22,9 @@ def __init__(self, league: "BaseLeague") -> None: self.league = league self._job_iter = self._job_dispatcher() self._lock = Lock() - task.on(EventEnum.ACTOR_GREETING(), self._on_actor_greeting) - task.on(EventEnum.LEARNER_SEND_META(), self._on_learner_meta) - task.on(EventEnum.ACTOR_FINISH_JOB(), self._on_actor_job) + task.on(EventEnum.ACTOR_GREETING, self._on_actor_greeting) + task.on(EventEnum.LEARNER_SEND_META, self._on_learner_meta) + task.on(EventEnum.ACTOR_FINISH_JOB, self._on_actor_job) def _on_actor_greeting(self, actor_id): with self._lock: @@ -32,7 +32,7 @@ def _on_actor_greeting(self, actor_id): if job.job_no > 0 and job.job_no % 10 == 0: # 1/10 turn job into eval mode job.is_eval = True job.actor_id = actor_id - task.emit(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB(actor_id), job) + task.emit(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=actor_id), job) def _on_actor_job(self, job: "Job"): self.league.update_payoff(job) diff --git a/ding/framework/middleware/tests/test_league_coordinator.py b/ding/framework/middleware/tests/test_league_coordinator.py index 7cc832dbd6..af75cfd846 100644 --- a/ding/framework/middleware/tests/test_league_coordinator.py +++ b/ding/framework/middleware/tests/test_league_coordinator.py @@ -38,7 +38,7 @@ def _main(): league = MockLeague() coordinator = LeagueCoordinator(league) coordinator(None) - time.sleep(5) + time.sleep(3) assert league.update_payoff_cnt == 3 assert league.update_active_player_cnt == 3 assert league.create_historical_player_cnt == 3 @@ -47,26 +47,26 @@ def _main(): # test ACTOR_GREETING res = [] actor_id = "test_node_{}".format(task.router.node_id) - task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB(actor_id), lambda job: res.append(job)) - time.sleep(1) + task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=actor_id), lambda job: res.append(job)) + time.sleep(0.1) for _ in range(3): - task.emit(EventEnum.ACTOR_GREETING(), actor_id) - time.sleep(3) + task.emit(EventEnum.ACTOR_GREETING, actor_id) + time.sleep(2) assert actor_id == res[-1].actor_id elif task.router.node_id == 2: # test LEARNER_SEND_META actor_id = "test_node_{}".format(task.router.node_id) - time.sleep(1) + time.sleep(0.1) for _ in range(3): - task.emit(EventEnum.LEARNER_SEND_META(), {"meta": actor_id}) - time.sleep(3) + task.emit(EventEnum.LEARNER_SEND_META, {"meta": actor_id}) + time.sleep(2) elif task.router.node_id == 3: # test ACTOR_FINISH_JOB actor_id = "test_node_{}".format(task.router.node_id) - time.sleep(1) + time.sleep(0.1) job = Job(-1, actor_id, False) for _ in range(3): - task.emit(EventEnum.ACTOR_FINISH_JOB(), job) + task.emit(EventEnum.ACTOR_FINISH_JOB, job) time.sleep(3) else: raise Exception("Invalid node id {}".format(task.router.is_active)) From 474524e68a578bb72ce17a5e651fb238123c3ffd Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Sun, 29 May 2022 01:00:02 +0800 Subject: [PATCH 045/229] simplify the code --- ding/framework/middleware/collector.py | 16 ++++------------ 1 file changed, 4 insertions(+), 12 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 4975798a38..3c4ded6168 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -53,17 +53,6 @@ def _reset_stat(self, env_id: int, ctx: OnlineRLContext) -> None: self.obs_pool.reset(env_id) self.policy_output_pool.reset(env_id) self.env_info[env_id] = {'time': 0., 'step': 0} - - def _close(self) -> None: - """ - Overview: - Close the collector. If end_flag is False, close the environment, flush the tb_logger\ - and close the tb_logger. - """ - if self.end_flag: - return - self.end_flag = True - self.env.close() def __del__(self) -> None: """ @@ -71,7 +60,10 @@ def __del__(self) -> None: Execute the close command and close the collector. __del__ is automatically called to \ destroy the collector instance when the collector finishes its work """ - self._close() + if self.end_flag: + return + self.end_flag = True + self.env.close() def __call__(self, ctx: "OnlineRLContext") -> None: """ From 9d91063e344c2c516d2258cc0c9fdeccf29cc4e7 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Sun, 29 May 2022 01:06:33 +0800 Subject: [PATCH 046/229] for multiple policies --- ding/framework/middleware/collector.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 3c4ded6168..dece33dc4c 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -1,3 +1,4 @@ +from distutils.log import info from typing import TYPE_CHECKING, Callable, List, Optional, Tuple from easydict import EasyDict from ding.policy import Policy, get_random_policy @@ -118,11 +119,11 @@ def __call__(self, ctx: "OnlineRLContext") -> None: if timestep.done: self.total_episode_count += 1 info = { - 'reward0': timestep.info[0]['final_eval_reward'], - 'reward1': timestep.info[1]['final_eval_reward'], 'time': self.env_info[env_id]['time'], 'step': self.env_info[env_id]['step'], } + for policy_id in range(ctx.agent_num): + info['reward'+str(policy_id)] = timestep.info[policy_id]['final_eval_reward'] ctx.collected_episode += 1 self.episode_info.append(info) for i, p in enumerate(ctx.policies): From 6ca4ae246c96b5bae95e481490773935cec0e218 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Sun, 29 May 2022 01:16:31 +0800 Subject: [PATCH 047/229] change a bit --- ding/framework/middleware/functional/collector.py | 4 ++-- ding/framework/middleware/league_actor.py | 3 +-- 2 files changed, 3 insertions(+), 4 deletions(-) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index adc344cf16..295ffb2af9 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -138,7 +138,7 @@ def _rollout(ctx: "OnlineRLContext"): return _rollout -def policy_resetter(): +def policy_resetter(env_num:int): def _policy_resetter(ctx: OnlineRLContext): if ctx.policies is not None: assert len(ctx.policies) > 1, "battle collector needs more than 1 policies" @@ -149,7 +149,7 @@ def _policy_resetter(ctx: OnlineRLContext): ctx.traj_buffer = { env_id: {policy_id: TrajBuffer(maxlen=ctx.traj_len) for policy_id in range(ctx.agent_num)} - for env_id in range(ctx.env_num) + for env_id in range(env_num) } for p in ctx.policies: diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 6a814de5a9..95a6cfd5f6 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -55,7 +55,7 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self._model_updated = True task.on("league_job_actor_{}".format(task.router.node_id), self._on_league_job) task.on("learner_model", self._on_learner_model) - self._policy_resetter = task.wrap(policy_resetter()) + self._policy_resetter = task.wrap(policy_resetter(self.env_num)) def _on_learner_model(self, learner_model: "LearnerModel"): """ @@ -93,7 +93,6 @@ def _on_league_job(self, job: "Job"): assert main_player, "Can not find active player" self.ctx.policies = policies - self.ctx.env_num = self.env_num self._policy_resetter(self.ctx) def send_actor_job(episode_info: List): From 2d85ccf9509d8bfd2841ffc86ca7762c42cd8af3 Mon Sep 17 00:00:00 2001 From: lixuelin Date: Mon, 30 May 2022 14:39:06 +0800 Subject: [PATCH 048/229] fix style --- ding/policy/dqn.py | 4 +++- ding/torch_utils/loss/tests/test_contrastive_loss.py | 5 +---- 2 files changed, 4 insertions(+), 5 deletions(-) diff --git a/ding/policy/dqn.py b/ding/policy/dqn.py index 4de1dcedcb..a69bcabdc8 100644 --- a/ding/policy/dqn.py +++ b/ding/policy/dqn.py @@ -583,7 +583,9 @@ def _forward_learn(self, data: Dict[str, Any]) -> Dict[str, Any]: q_value, target_q_value, data['action'], target_q_action, data['reward'], data['done'], data['weight'] ) value_gamma = data.get('value_gamma') - bellman_loss, td_error_per_sample = q_nstep_td_error(data_n, self._gamma, nstep=self._nstep, value_gamma=value_gamma) + bellman_loss, td_error_per_sample = q_nstep_td_error( + data_n, self._gamma, nstep=self._nstep, value_gamma=value_gamma + ) # ====================== # Compute auxiliary loss diff --git a/ding/torch_utils/loss/tests/test_contrastive_loss.py b/ding/torch_utils/loss/tests/test_contrastive_loss.py index 83eeb182d3..8737ada4d1 100644 --- a/ding/torch_utils/loss/tests/test_contrastive_loss.py +++ b/ding/torch_utils/loss/tests/test_contrastive_loss.py @@ -7,10 +7,7 @@ @pytest.mark.benchmark @pytest.mark.parametrize('noise', [0.1, 1.0]) -@pytest.mark.parametrize('dims', [ - [16], - [3, 16, 16] -]) +@pytest.mark.parametrize('dims', [[16], [3, 16, 16]]) def test_infonce_loss(noise, dims): print_loss = False batch_size = 128 From 157b9b3ab63a2a1e1922b538f969e8e306cbf0b4 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Mon, 30 May 2022 14:52:54 +0800 Subject: [PATCH 049/229] revert to drop the streaming type code --- ding/framework/middleware/league_actor.py | 14 ++++++++------ 1 file changed, 8 insertions(+), 6 deletions(-) diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 95a6cfd5f6..b2af5cb039 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -109,12 +109,14 @@ def send_actor_data(train_data: List): actor_data = ActorData(env_step=self.ctx.envstep, train_data=train_data) task.emit("actor_data_player_{}".format(job.launch_player), actor_data) - if self.n_rollout_samples > 0: - pass - else: - self.ctx.n_episode = None - self.ctx.train_iter = main_player.total_agent_step - self.ctx.policy_kwargs = None + self.ctx.n_episode = None + self.ctx.train_iter = main_player.total_agent_step + self.ctx.policy_kwargs = None + + # if self.n_rollout_samples > 0: + # pass + # else: + # pass collector(self.ctx) train_data, episode_info = self.ctx.train_data[0], self.ctx.episode_info[0] # only use main player data for training From a13b5e6e9d564368739c2fc1909220f6587aa2dc Mon Sep 17 00:00:00 2001 From: lixuelin Date: Mon, 30 May 2022 15:23:49 +0800 Subject: [PATCH 050/229] fix codecov --- .coveragerc | 1 + ding/policy/dqn.py | 2 ++ ding/torch_utils/loss/contrastive_loss.py | 5 ----- ding/torch_utils/loss/tests/test_contrastive_loss.py | 9 ++++++--- 4 files changed, 9 insertions(+), 8 deletions(-) diff --git a/.coveragerc b/.coveragerc index d187aa2739..119f51e515 100644 --- a/.coveragerc +++ b/.coveragerc @@ -21,3 +21,4 @@ omit = ding/scripts/tests/test_parallel_socket.py ding/data/buffer/tests/test_benchmark.py ding/example/* + ding/torch_utils/loss/tests/* diff --git a/ding/policy/dqn.py b/ding/policy/dqn.py index a69bcabdc8..5788e121e1 100644 --- a/ding/policy/dqn.py +++ b/ding/policy/dqn.py @@ -577,6 +577,8 @@ def _forward_learn(self, data: Dict[str, Any]) -> Dict[str, Any]: aux_loss_learn = self._aux_model.forward(x_no_grad, y_no_grad) self._aux_optimizer.zero_grad() aux_loss_learn.backward() + if self._cfg.learn.multi_gpu: + self.sync_gradients(self._aux_model) self._aux_optimizer.step() data_n = q_nstep_td_data( diff --git a/ding/torch_utils/loss/contrastive_loss.py b/ding/torch_utils/loss/contrastive_loss.py index 0ef3eb073f..78d8575160 100644 --- a/ding/torch_utils/loss/contrastive_loss.py +++ b/ding/torch_utils/loss/contrastive_loss.py @@ -97,8 +97,3 @@ def forward(self, x: torch.Tensor, y: torch.Tensor): # The positive score is the first element of the log softmax. loss = -pred_log[:, :, 0, :].mean() return loss - - def __call__(self, x: torch.Tensor, y: torch.Tensor): - with torch.no_grad(): - out = self.forward(x, y) - return out diff --git a/ding/torch_utils/loss/tests/test_contrastive_loss.py b/ding/torch_utils/loss/tests/test_contrastive_loss.py index 8737ada4d1..785f703bc2 100644 --- a/ding/torch_utils/loss/tests/test_contrastive_loss.py +++ b/ding/torch_utils/loss/tests/test_contrastive_loss.py @@ -7,18 +7,21 @@ @pytest.mark.benchmark @pytest.mark.parametrize('noise', [0.1, 1.0]) -@pytest.mark.parametrize('dims', [[16], [3, 16, 16]]) +@pytest.mark.parametrize('dims', [16, [1, 16, 16], [1, 40, 40]]) def test_infonce_loss(noise, dims): print_loss = False batch_size = 128 N_batch = 3 - x_dim = [batch_size * N_batch] + dims + if isinstance(dims, int): + x_dim = [batch_size * N_batch, dims] + else: + x_dim = [batch_size * N_batch] + dims encode_shape = 16 x = np.random.normal(0, 1, size=x_dim) y = x ** 2 + noise * np.random.normal(0, 1, size=x_dim) - estimator = ContrastiveLoss(x.shape[1:], y.shape[1:], encode_shape=encode_shape) + estimator = ContrastiveLoss(dims, dims, encode_shape=encode_shape) dataset = TensorDataset(torch.Tensor(x), torch.Tensor(y)) dataloader = DataLoader(dataset, batch_size=batch_size) optimizer = torch.optim.Adam(estimator.parameters(), lr=3e-4) From ecd01196ca674e106f8c2f42134d32a1dbbd66cc Mon Sep 17 00:00:00 2001 From: lixuelin Date: Mon, 30 May 2022 18:12:35 +0800 Subject: [PATCH 051/229] fix import --- ding/policy/dqn.py | 3 +-- ding/torch_utils/loss/__init__.py | 1 + ding/torch_utils/loss/contrastive_loss.py | 6 ++++-- 3 files changed, 6 insertions(+), 4 deletions(-) diff --git a/ding/policy/dqn.py b/ding/policy/dqn.py index 5788e121e1..cf5c271299 100644 --- a/ding/policy/dqn.py +++ b/ding/policy/dqn.py @@ -3,8 +3,7 @@ import copy import torch -from ding.torch_utils import Adam, to_device -from ding.torch_utils.loss.contrastive_loss import ContrastiveLoss +from ding.torch_utils import Adam, to_device, ContrastiveLoss from ding.rl_utils import q_nstep_td_data, q_nstep_td_error, get_nstep_return_data, get_train_sample from ding.model import model_wrap from ding.utils import POLICY_REGISTRY diff --git a/ding/torch_utils/loss/__init__.py b/ding/torch_utils/loss/__init__.py index e2795e2747..8668e53b98 100644 --- a/ding/torch_utils/loss/__init__.py +++ b/ding/torch_utils/loss/__init__.py @@ -1,2 +1,3 @@ from .cross_entropy_loss import LabelSmoothCELoss, SoftFocalLoss, build_ce_criterion from .multi_logits_loss import MultiLogitsLoss +from .contrastive_loss import ContrastiveLoss diff --git a/ding/torch_utils/loss/contrastive_loss.py b/ding/torch_utils/loss/contrastive_loss.py index 78d8575160..ed17eebcb1 100644 --- a/ding/torch_utils/loss/contrastive_loss.py +++ b/ding/torch_utils/loss/contrastive_loss.py @@ -1,9 +1,9 @@ from typing import Union -from ding.utils import SequenceType + import torch import torch.nn as nn import torch.nn.functional as F -from ding.model import ConvEncoder, FCEncoder +from ding.utils import SequenceType class ContrastiveLoss(nn.Module): @@ -44,6 +44,8 @@ def __init__( self._temperature = temperature def _get_encoder(self, obs: Union[int, SequenceType], heads: int): + from ding.model import ConvEncoder, FCEncoder + if isinstance(obs, int): obs = [obs] assert len(obs) in [1, 3] From 4d54abfefcd4f6141ecd5be7ac0111d5a83b8b42 Mon Sep 17 00:00:00 2001 From: lixuelin Date: Mon, 30 May 2022 18:58:16 +0800 Subject: [PATCH 052/229] add readme --- README.md | 20 +++++++++++++------ ding/policy/dqn.py | 4 ++-- .../config/cartpole_dqn_stdim_config.py | 4 ++-- 3 files changed, 18 insertions(+), 10 deletions(-) diff --git a/README.md b/README.md index bedd7fb091..05c57fcdd8 100644 --- a/README.md +++ b/README.md @@ -74,12 +74,19 @@ Have fun with exploration and exploitation. ## Outline -* [Installation](#installation) -* [Quick Start](#quick-start) -* [Feature/Algorithm Versatility](#algorithm-versatility) -* [Feature/Environment Versatility](#environment-versatility) -* [Feedback & Contribution](feedback-and-contribution) -* [License](#license) +- [Introduction to DI-engine (beta)](#introduction-to-di-engine-beta) +- [Outline](#outline) +- [Installation](#installation) +- [Quick Start](#quick-start) +- [Feature](#feature) + - [Algorithm Versatility](#algorithm-versatility) + - [Environment Versatility](#environment-versatility) +- [Feedback and Contribution](#feedback-and-contribution) +- [Supporters](#supporters) + - [↳ Stargazers](#-stargazers) + - [↳ Forkers](#-forkers) +- [Citation](#citation) +- [License](#license) ## Installation @@ -164,6 +171,7 @@ ding -m serial -e cartpole -p dqn -s 0 | 35 | [MBPO](https://arxiv.org/pdf/1906.08253.pdf) | ![mbrl](https://img.shields.io/badge/-ModelBasedRL-lightblue) | [model/template/model_based/mbpo](https://github.com/opendilab/DI-engine/blob/main/ding/model/template/model_based/mbpo.py) | python3 -u sac_halfcheetah_mopo_default_config.py | | 36 | [PER](https://arxiv.org/pdf/1511.05952.pdf) | ![other](https://img.shields.io/badge/-other-lightgrey) | [worker/replay_buffer](https://github.com/opendilab/DI-engine/blob/main/ding/worker/replay_buffer/advanced_buffer.py) | `rainbow demo` | | 37 | [GAE](https://arxiv.org/pdf/1506.02438.pdf) | ![other](https://img.shields.io/badge/-other-lightgrey) | [rl_utils/gae](https://github.com/opendilab/DI-engine/blob/main/ding/rl_utils/gae.py) | `ppo demo` | +| 38 | [ST-DIM](https://arxiv.org/pdf/1906.08226.pdf) | ![other](https://img.shields.io/badge/-other-lightgrey) | [torch_utils/loss/contrastive_loss](https://github.com/opendilab/DI-engine/blob/main/ding/torch_utils/loss/contrastive_loss.py) | ding -m serial -c cartpole_dqn_stdim_config.py -s 0 | ![discrete](https://img.shields.io/badge/-discrete-brightgreen) means discrete action space, which is only label in normal DRL algorithms (1-18) diff --git a/ding/policy/dqn.py b/ding/policy/dqn.py index cf5c271299..6198c6c9a5 100644 --- a/ding/policy/dqn.py +++ b/ding/policy/dqn.py @@ -524,8 +524,8 @@ def _get_encoding_size(self): return x.size()[1:], y.size()[1:] def _aux_encode(self, data): - x = data["obs"] - y = self._model.encoder(data["obs"]) + x = self._model.encoder(data["obs"]) + y = self._model.encoder(data["next_obs"]) return x, y def _forward_learn(self, data: Dict[str, Any]) -> Dict[str, Any]: diff --git a/dizoo/classic_control/cartpole/config/cartpole_dqn_stdim_config.py b/dizoo/classic_control/cartpole/config/cartpole_dqn_stdim_config.py index 816c3721ce..25f9bea89e 100644 --- a/dizoo/classic_control/cartpole/config/cartpole_dqn_stdim_config.py +++ b/dizoo/classic_control/cartpole/config/cartpole_dqn_stdim_config.py @@ -7,11 +7,11 @@ evaluator_env_num=5, n_evaluator_episode=5, stop_value=195, - replay_path='cartpole_dqn_seed0/video', + replay_path='cartpole_dqn_stdim_seed0/video', ), policy=dict( cuda=False, - load_path='cartpole_dqn_seed0/ckpt/ckpt_best.pth.tar', # necessary for eval + load_path='cartpole_dqn_stdim_seed0/ckpt/ckpt_best.pth.tar', # necessary for eval model=dict( obs_shape=4, action_shape=2, From 65525c1f26f8bae4feb0c8d818609af21b4c7f50 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Mon, 30 May 2022 20:21:53 +0800 Subject: [PATCH 053/229] drop useless codes --- ding/framework/middleware/collector.py | 24 ++----------------- .../tests/test_league_actor_one_process.py | 2 +- 2 files changed, 3 insertions(+), 23 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index dece33dc4c..dea3b6b9d7 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -9,7 +9,6 @@ # if TYPE_CHECKING: from ding.framework import OnlineRLContext -from ding.utils import EasyTimer from ding.worker.collector.base_serial_collector import CachePool @@ -21,7 +20,6 @@ def __init__( n_rollout_samples: int ): self.cfg = cfg - self._timer = EasyTimer() self.end_flag = False # self._reset(env) self.env = env @@ -29,9 +27,7 @@ def __init__( self.obs_pool = CachePool('obs', self.env_num, deepcopy=self.cfg.deepcopy_obs) self.policy_output_pool = CachePool('policy_output', self.env_num) - self.env_info = {env_id: {'time': 0., 'step': 0} for env_id in range(self.env_num)} - self.episode_info = [] self.total_envstep_count = 0 self.total_episode_count = 0 self.end_flag = False @@ -53,7 +49,6 @@ def _reset_stat(self, env_id: int, ctx: OnlineRLContext) -> None: ctx.traj_buffer[env_id][i].clear() self.obs_pool.reset(env_id) self.policy_output_pool.reset(env_id) - self.env_info[env_id] = {'time': 0., 'step': 0} def __del__(self) -> None: """ @@ -97,35 +92,20 @@ def __call__(self, ctx: "OnlineRLContext") -> None: ctx.ready_env_id = set() ctx.remain_episode = ctx.n_episode while True: - with self._timer: - self._battle_inferencer(ctx) - - # TODO(nyz) this duration may be inaccurate in async env - interaction_duration = self._timer.value / len(ctx.timesteps) + self._battle_inferencer(ctx) # TODO(nyz) vectorize this for loop for env_id, timestep in ctx.timesteps.items(): - self.env_info[env_id]['step'] += 1 self.total_envstep_count += 1 ctx.envstep = self.total_envstep_count ctx.env_id = env_id ctx.timestep = timestep - with self._timer: - self._battle_rolloutor(ctx) - - self.env_info[env_id]['time'] += self._timer.value + interaction_duration + self._battle_rolloutor(ctx) # If env is done, record episode info and reset if timestep.done: self.total_episode_count += 1 - info = { - 'time': self.env_info[env_id]['time'], - 'step': self.env_info[env_id]['step'], - } - for policy_id in range(ctx.agent_num): - info['reward'+str(policy_id)] = timestep.info[policy_id]['final_eval_reward'] ctx.collected_episode += 1 - self.episode_info.append(info) for i, p in enumerate(ctx.policies): p.reset([env_id]) self._reset_stat(env_id, ctx) diff --git a/ding/framework/middleware/tests/test_league_actor_one_process.py b/ding/framework/middleware/tests/test_league_actor_one_process.py index 1afae06eef..9f940e130e 100644 --- a/ding/framework/middleware/tests/test_league_actor_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_one_process.py @@ -91,7 +91,7 @@ def _test_actor(ctx): player_id='main_player_default_0', state_dict=policy.learn_mode.state_dict(), train_iter=0 ) ) - sleep(0.3) + sleep(5) assert league_actor._model_updated == True try: print(testcases) From a1b090825626798528394cbd871fb12019b0f674 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Mon, 30 May 2022 21:02:41 +0800 Subject: [PATCH 054/229] change rolloutor --- ding/framework/middleware/collector.py | 39 ++----------- .../middleware/functional/collector.py | 58 ++++++++++++------- 2 files changed, 40 insertions(+), 57 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index dea3b6b9d7..e48487fec9 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -29,26 +29,11 @@ def __init__( self.policy_output_pool = CachePool('policy_output', self.env_num) self.total_envstep_count = 0 - self.total_episode_count = 0 self.end_flag = False self.n_rollout_samples = n_rollout_samples self._battle_inferencer = task.wrap(battle_inferencer(self.cfg, self.env, self.obs_pool, self.policy_output_pool)) - self._battle_rolloutor = task.wrap(battle_rolloutor(self.cfg, self.obs_pool, self.policy_output_pool)) - - def _reset_stat(self, env_id: int, ctx: OnlineRLContext) -> None: - """ - Overview: - Reset the collector's state. Including reset the traj_buffer, obs_pool, policy_output_pool\ - and env_info. Reset these states according to env_id. You can refer to base_serial_collector\ - to get more messages. - Arguments: - - env_id (:obj:`int`): the id where we need to reset the collector's state - """ - for i in range(ctx.agent_num): - ctx.traj_buffer[env_id][i].clear() - self.obs_pool.reset(env_id) - self.policy_output_pool.reset(env_id) + self._battle_rolloutor = task.wrap(battle_rolloutor(self.cfg, self.env, self.obs_pool, self.policy_output_pool)) def __del__(self) -> None: """ @@ -93,25 +78,9 @@ def __call__(self, ctx: "OnlineRLContext") -> None: ctx.remain_episode = ctx.n_episode while True: self._battle_inferencer(ctx) - - # TODO(nyz) vectorize this for loop - for env_id, timestep in ctx.timesteps.items(): - self.total_envstep_count += 1 - ctx.envstep = self.total_envstep_count - ctx.env_id = env_id - ctx.timestep = timestep - self._battle_rolloutor(ctx) - - # If env is done, record episode info and reset - if timestep.done: - self.total_episode_count += 1 - ctx.collected_episode += 1 - for i, p in enumerate(ctx.policies): - p.reset([env_id]) - self._reset_stat(env_id, ctx) - ctx.ready_env_id.remove(env_id) - for policy_id in range(ctx.agent_num): - ctx.episode_info[policy_id].append(timestep.info[policy_id]) + self._battle_rolloutor(ctx) + self.total_envstep_count = ctx.envstep + if ctx.collected_episode >= ctx.n_episode: break diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 295ffb2af9..a7f0524b7e 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -181,31 +181,45 @@ def _battle_inferencer(ctx: "OnlineRLContext"): actions[env_id] = [] for output in policy_output: actions[env_id].append(output[env_id]['action']) - actions = to_ndarray(actions) - ctx.timesteps = env.step(actions) + ctx.actions = to_ndarray(actions) return _battle_inferencer -def battle_rolloutor(cfg: EasyDict, obs_pool: CachePool, policy_output_pool:CachePool): +def battle_rolloutor(cfg: EasyDict, env: BaseEnvManager, obs_pool: CachePool, policy_output_pool:CachePool): def _battle_rolloutor(ctx: "OnlineRLContext"): - timestep = ctx.timestep - env_id = ctx.env_id - for policy_id, _ in enumerate(ctx.policies): - policy_timestep_data = [d[policy_id] if not isinstance(d, bool) else d for d in timestep] - policy_timestep = type(timestep)(*policy_timestep_data) - transition = ctx.policies[policy_id].process_transition( - obs_pool[env_id][policy_id], policy_output_pool[env_id][policy_id], - policy_timestep - ) - transition['collect_iter'] = ctx.train_iter - ctx.traj_buffer[env_id][policy_id].append(transition) - # If env is done, prepare data + timesteps = env.step(ctx.actions) + for env_id, timestep in timesteps.items(): + # TODO: self.total_envstep_count += 1 + ctx.envstep += 1 + for policy_id, _ in enumerate(ctx.policies): + policy_timestep_data = [d[policy_id] if not isinstance(d, bool) else d for d in timestep] + policy_timestep = type(timestep)(*policy_timestep_data) + transition = ctx.policies[policy_id].process_transition( + obs_pool[env_id][policy_id], policy_output_pool[env_id][policy_id], + policy_timestep + ) + transition['collect_iter'] = ctx.train_iter + ctx.traj_buffer[env_id][policy_id].append(transition) + # If env is done, prepare data + if timestep.done: + transitions = to_tensor_transitions(ctx.traj_buffer[env_id][policy_id]) + if cfg.get_train_sample: + train_sample = ctx.policies[policy_id].get_train_sample(transitions) + ctx.train_data[policy_id].extend(train_sample) + else: + ctx.train_data[policy_id].append(transitions) + ctx.traj_buffer[env_id][policy_id].clear() + if timestep.done: - transitions = to_tensor_transitions(ctx.traj_buffer[env_id][policy_id]) - if cfg.get_train_sample: - train_sample = ctx.policies[policy_id].get_train_sample(transitions) - ctx.train_data[policy_id].extend(train_sample) - else: - ctx.train_data[policy_id].append(transitions) - ctx.traj_buffer[env_id][policy_id].clear() + ctx.collected_episode += 1 + for i, p in enumerate(ctx.policies): + p.reset([env_id]) + for i in range(ctx.agent_num): + ctx.traj_buffer[env_id][i].clear() + obs_pool.reset(env_id) + policy_output_pool.reset(env_id) + ctx.ready_env_id.remove(env_id) + for policy_id in range(ctx.agent_num): + ctx.episode_info[policy_id].append(timestep.info[policy_id]) + return _battle_rolloutor \ No newline at end of file From 68191a9720f7df916c26f617a7d2fc5858624310 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Mon, 30 May 2022 22:21:05 +0800 Subject: [PATCH 055/229] move on_league_job in call --- ding/framework/middleware/league_actor.py | 126 ++++++++++-------- .../middleware/tests/test_league_actor.py | 5 +- 2 files changed, 70 insertions(+), 61 deletions(-) diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index b2af5cb039..44fb47a052 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -15,6 +15,7 @@ from ding.framework.middleware.league_learner import LearnerModel from ding.framework.middleware import BattleCollector from ding.framework.middleware.functional import policy_resetter +from queue import Queue @dataclass class ActorData: @@ -49,13 +50,14 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.policy_fn = policy_fn self.n_rollout_samples = self.cfg.policy.collect.get("n_rollout_samples") or 0 self.n_rollout_samples = 0 - self._running = False + # self._running = False self._collectors: Dict[str, BattleCollector] = {} self._policies: Dict[str, "Policy.collect_function"] = {} self._model_updated = True task.on("league_job_actor_{}".format(task.router.node_id), self._on_league_job) task.on("learner_model", self._on_learner_model) self._policy_resetter = task.wrap(policy_resetter(self.env_num)) + self.job_queue = Queue() def _on_learner_model(self, learner_model: "LearnerModel"): """ @@ -71,60 +73,7 @@ def _on_league_job(self, job: "Job"): """ Deal with job distributed by coordinator. Load historical model, generate traj and emit data. """ - self._running = True - - # Wait new active model for 10 seconds - for _ in range(10): - if self._model_updated: - self._model_updated = False - break - logging.info( - "Waiting for new model on actor: {}, player: {}".format(task.router.node_id, job.launch_player) - ) - sleep(1) - collector = self._get_collector(job.launch_player) - policies = [] - main_player: "PlayerMeta" = None - for player in job.players: - policies.append(self._get_policy(player)) - if player.player_id == job.launch_player: - main_player = player - # inferencer,rolloutor = self._get_collector(player.player_id) - assert main_player, "Can not find active player" - - self.ctx.policies = policies - self._policy_resetter(self.ctx) - - def send_actor_job(episode_info: List): - job.result = [e['result'] for e in episode_info] - task.emit("actor_job", job) - - def send_actor_data(train_data: List): - # Don't send data in evaluation mode - if job.is_eval: - return - for d in train_data: - d["adv"] = d["reward"] - - actor_data = ActorData(env_step=self.ctx.envstep, train_data=train_data) - task.emit("actor_data_player_{}".format(job.launch_player), actor_data) - - self.ctx.n_episode = None - self.ctx.train_iter = main_player.total_agent_step - self.ctx.policy_kwargs = None - - # if self.n_rollout_samples > 0: - # pass - # else: - # pass - - collector(self.ctx) - train_data, episode_info = self.ctx.train_data[0], self.ctx.episode_info[0] # only use main player data for training - send_actor_data(train_data) - send_actor_job(episode_info) - - task.emit("actor_greeting", task.router.node_id) - self._running = False + self.job_queue.put(job) def _get_collector(self, player_id: str): if self._collectors.get(player_id): @@ -150,9 +99,68 @@ def _get_policy(self, player: "PlayerMeta") -> "Policy.collect_function": return policy def __call__(self, ctx: "OnlineRLContext"): - self.ctx = ctx - if not self._running: - task.emit("actor_greeting", task.router.node_id) - sleep(3) + # if not self._running: + # task.emit("actor_greeting", task.router.node_id) + + while True: + if self.job_queue.empty(): + task.emit("actor_greeting", task.router.node_id) + + job = self.job_queue.get() + # self._running = True + + # Wait new active model for 10 seconds + for _ in range(10): + if self._model_updated: + self._model_updated = False + break + logging.info( + "Waiting for new model on actor: {}, player: {}".format(task.router.node_id, job.launch_player) + ) + sleep(1) + + collector = self._get_collector(job.launch_player) + policies = [] + main_player: "PlayerMeta" = None + for player in job.players: + policies.append(self._get_policy(player)) + if player.player_id == job.launch_player: + main_player = player + # inferencer,rolloutor = self._get_collector(player.player_id) + assert main_player, "Can not find active player" + + ctx.policies = policies + self._policy_resetter(ctx) + + def send_actor_job(episode_info: List): + job.result = [e['result'] for e in episode_info] + task.emit("actor_job", job) + + def send_actor_data(train_data: List): + # Don't send data in evaluation mode + if job.is_eval: + return + for d in train_data: + d["adv"] = d["reward"] + + actor_data = ActorData(env_step=ctx.envstep, train_data=train_data) + task.emit("actor_data_player_{}".format(job.launch_player), actor_data) + + ctx.n_episode = None + ctx.train_iter = main_player.total_agent_step + ctx.policy_kwargs = None + + # if self.n_rollout_samples > 0: + # pass + # else: + # pass + + collector(ctx) + train_data, episode_info = ctx.train_data[0], ctx.episode_info[0] # only use main player data for training + send_actor_data(train_data) + send_actor_job(episode_info) + + # task.emit("actor_greeting", task.router.node_id) + # self._running = False diff --git a/ding/framework/middleware/tests/test_league_actor.py b/ding/framework/middleware/tests/test_league_actor.py index 648466c65b..dfd59d3461 100644 --- a/ding/framework/middleware/tests/test_league_actor.py +++ b/ding/framework/middleware/tests/test_league_actor.py @@ -65,7 +65,6 @@ def test_actor(): def on_actor_greeting(actor_id): assert actor_id == ACTOR_ID - task.emit("league_job_actor_{}".format(ACTOR_ID), job) testcases["on_actor_greeting"] = True def on_actor_job(job_: Job): @@ -82,6 +81,8 @@ def on_actor_data(actor_data): def _test_actor(ctx): sleep(0.3) + task.emit("league_job_actor_{}".format(ACTOR_ID), job) + sleep(0.3) task.emit( "learner_model", @@ -89,7 +90,7 @@ def _test_actor(ctx): player_id='main_player_default_0', state_dict=policy.learn_mode.state_dict(), train_iter=0 ) ) - sleep(10) + sleep(5) try: print(testcases) assert all(testcases.values()) From 59f2a6e4a40f2213de25fff1a98b82f228aec3f1 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 31 May 2022 11:21:04 +0800 Subject: [PATCH 056/229] change __call__ --- ding/framework/middleware/league_actor.py | 116 ++++++++++------------ 1 file changed, 55 insertions(+), 61 deletions(-) diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 44fb47a052..d627c5425c 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -15,7 +15,7 @@ from ding.framework.middleware.league_learner import LearnerModel from ding.framework.middleware import BattleCollector from ding.framework.middleware.functional import policy_resetter -from queue import Queue +import queue @dataclass class ActorData: @@ -57,7 +57,7 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): task.on("league_job_actor_{}".format(task.router.node_id), self._on_league_job) task.on("learner_model", self._on_learner_model) self._policy_resetter = task.wrap(policy_resetter(self.env_num)) - self.job_queue = Queue() + self.job_queue = queue.Queue() def _on_learner_model(self, learner_model: "LearnerModel"): """ @@ -102,65 +102,59 @@ def __call__(self, ctx: "OnlineRLContext"): # if not self._running: # task.emit("actor_greeting", task.router.node_id) - while True: - if self.job_queue.empty(): - task.emit("actor_greeting", task.router.node_id) - - job = self.job_queue.get() - # self._running = True - - # Wait new active model for 10 seconds - for _ in range(10): - if self._model_updated: - self._model_updated = False - break - logging.info( - "Waiting for new model on actor: {}, player: {}".format(task.router.node_id, job.launch_player) - ) - sleep(1) + if self.job_queue.empty(): + task.emit("actor_greeting", task.router.node_id) + + try: + job = self.job_queue.get(timeout = 5) + except queue.Empty: + logging.warning("For actor_{}, no Job get from coordinator".format(task.router.node_id)) + return + + # self._running = True + + # Wait new active model for 10 seconds + for _ in range(10): + if self._model_updated: + self._model_updated = False + break + logging.info( + "Waiting for new model on actor: {}, player: {}".format(task.router.node_id, job.launch_player) + ) + sleep(1) + + collector = self._get_collector(job.launch_player) + policies = [] + main_player: "PlayerMeta" = None + for player in job.players: + policies.append(self._get_policy(player)) + if player.player_id == job.launch_player: + main_player = player + # inferencer,rolloutor = self._get_collector(player.player_id) + assert main_player, "Can not find active player" + + ctx.policies = policies + self._policy_resetter(ctx) + + ctx.n_episode = None + ctx.train_iter = main_player.total_agent_step + ctx.policy_kwargs = None + + collector(ctx) + train_data, episode_info = ctx.train_data[0], ctx.episode_info[0] # only use main player data for training - collector = self._get_collector(job.launch_player) - policies = [] - main_player: "PlayerMeta" = None - for player in job.players: - policies.append(self._get_policy(player)) - if player.player_id == job.launch_player: - main_player = player - # inferencer,rolloutor = self._get_collector(player.player_id) - assert main_player, "Can not find active player" - - ctx.policies = policies - self._policy_resetter(ctx) - - def send_actor_job(episode_info: List): - job.result = [e['result'] for e in episode_info] - task.emit("actor_job", job) - - def send_actor_data(train_data: List): - # Don't send data in evaluation mode - if job.is_eval: - return - for d in train_data: - d["adv"] = d["reward"] - - actor_data = ActorData(env_step=ctx.envstep, train_data=train_data) - task.emit("actor_data_player_{}".format(job.launch_player), actor_data) - - ctx.n_episode = None - ctx.train_iter = main_player.total_agent_step - ctx.policy_kwargs = None - - # if self.n_rollout_samples > 0: - # pass - # else: - # pass - - collector(ctx) - train_data, episode_info = ctx.train_data[0], ctx.episode_info[0] # only use main player data for training - send_actor_data(train_data) - send_actor_job(episode_info) - - # task.emit("actor_greeting", task.router.node_id) - # self._running = False + # Send actor data. Don't send data in evaluation mode + if job.is_eval: + return + for d in train_data: + d["adv"] = d["reward"] + + actor_data = ActorData(env_step=ctx.envstep, train_data=train_data) + task.emit("actor_data_player_{}".format(job.launch_player), actor_data) + + # Send actor job + job.result = [e['result'] for e in episode_info] + task.emit("actor_job", job) + From cfabb47507b4f83c5b5b9c848bbf9595ec5c9367 Mon Sep 17 00:00:00 2001 From: lixuelin Date: Tue, 31 May 2022 15:28:36 +0800 Subject: [PATCH 057/229] add league coordinator --- .../middleware/league_coordinator.py | 22 ++++++++----------- .../tests/test_league_coordinator.py | 2 +- 2 files changed, 10 insertions(+), 14 deletions(-) diff --git a/ding/framework/middleware/league_coordinator.py b/ding/framework/middleware/league_coordinator.py index efc894c844..f5996a3388 100644 --- a/ding/framework/middleware/league_coordinator.py +++ b/ding/framework/middleware/league_coordinator.py @@ -13,16 +13,22 @@ class LeagueCoordinator: def __init__(self, league: "BaseLeague") -> None: self.league = league - self._job_iter = self._job_dispatcher() self._lock = Lock() + self._total_send_jobs = 0 + self._eval_frequency = 10 + task.on(EventEnum.ACTOR_GREETING, self._on_actor_greeting) task.on(EventEnum.LEARNER_SEND_META, self._on_learner_meta) task.on(EventEnum.ACTOR_FINISH_JOB, self._on_actor_job) def _on_actor_greeting(self, actor_id): with self._lock: - job: "Job" = next(self._job_iter) - if job.job_no > 0 and job.job_no % 10 == 0: # 1/10 turn job into eval mode + player_num = len(self.league.active_players_ids) + player_id = self.league.active_players_ids[self._total_send_jobs % player_num] + job = self.league.get_job_info(player_id) + job.job_no = self._total_send_jobs + self._total_send_jobs += 1 + if job.job_no > 0 and job.job_no % self._eval_frequency == 0: job.is_eval = True job.actor_id = actor_id task.emit(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=actor_id), job) @@ -36,13 +42,3 @@ def _on_learner_meta(self, player_meta: "PlayerMeta"): def __call__(self, ctx: "Context") -> None: sleep(1) - - def _job_dispatcher(self) -> "Job": - i = 0 - while True: - player_num = len(self.league.active_players_ids) - player_id = self.league.active_players_ids[i % player_num] - job = self.league.get_job_info(player_id) - job.job_no = i - i += 1 - yield job diff --git a/ding/framework/middleware/tests/test_league_coordinator.py b/ding/framework/middleware/tests/test_league_coordinator.py index d810df27b1..6c8cd1c7d8 100644 --- a/ding/framework/middleware/tests/test_league_coordinator.py +++ b/ding/framework/middleware/tests/test_league_coordinator.py @@ -28,7 +28,7 @@ def create_historical_player(self, meta): def get_job_info(self, player_id): self.get_job_info_cnt += 1 - return Job(player_id=player_id, players=[]) + return Job(launch_player=player_id, players=[]) def _main(): From 0ff864dba1ef6bbf790e178679a93dce6f26f2e2 Mon Sep 17 00:00:00 2001 From: zhumengshen <744762298@qq.com> Date: Tue, 31 May 2022 07:31:39 +0000 Subject: [PATCH 058/229] reformatting --- ding/framework/middleware/__init__.py | 2 +- ding/framework/middleware/collector.py | 18 +++++------ .../middleware/functional/collector.py | 24 +++++++------- ding/framework/middleware/league_actor.py | 25 +++++++-------- ding/framework/middleware/league_learner.py | 3 +- .../middleware/tests/test_league_actor.py | 31 +++++++++---------- .../tests/test_league_actor_one_process.py | 23 ++++++-------- 7 files changed, 58 insertions(+), 68 deletions(-) diff --git a/ding/framework/middleware/__init__.py b/ding/framework/middleware/__init__.py index e701f5e4bb..be4be50d6f 100644 --- a/ding/framework/middleware/__init__.py +++ b/ding/framework/middleware/__init__.py @@ -2,4 +2,4 @@ from .collector import StepCollector, EpisodeCollector, BattleCollector from .learner import OffPolicyLearner, HERLearner from .ckpt_handler import CkptSaver -from .league_actor import LeagueActor \ No newline at end of file +from .league_actor import LeagueActor diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index e48487fec9..bd412dc75e 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -13,12 +13,8 @@ class BattleCollector: - def __init__( - self, - cfg: EasyDict, - env: BaseEnvManager, - n_rollout_samples: int - ): + + def __init__(self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int): self.cfg = cfg self.end_flag = False # self._reset(env) @@ -32,7 +28,9 @@ def __init__( self.end_flag = False self.n_rollout_samples = n_rollout_samples - self._battle_inferencer = task.wrap(battle_inferencer(self.cfg, self.env, self.obs_pool, self.policy_output_pool)) + self._battle_inferencer = task.wrap( + battle_inferencer(self.cfg, self.env, self.obs_pool, self.policy_output_pool) + ) self._battle_rolloutor = task.wrap(battle_rolloutor(self.cfg, self.env, self.obs_pool, self.policy_output_pool)) def __del__(self) -> None: @@ -67,7 +65,7 @@ def __call__(self, ctx: "OnlineRLContext") -> None: if ctx.policy_kwargs is None: ctx.policy_kwargs = {} - + if self.env.closed: self.env.launch() @@ -80,10 +78,10 @@ def __call__(self, ctx: "OnlineRLContext") -> None: self._battle_inferencer(ctx) self._battle_rolloutor(ctx) self.total_envstep_count = ctx.envstep - + if ctx.collected_episode >= ctx.n_episode: break - + class StepCollector: """ diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index a7f0524b7e..4b3650660c 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -1,4 +1,4 @@ -from typing import TYPE_CHECKING,Optional, Callable, List, Tuple, Any +from typing import TYPE_CHECKING, Optional, Callable, List, Tuple, Any from easydict import EasyDict from functools import reduce import treetensor.torch as ttorch @@ -85,8 +85,6 @@ def _inference(ctx: "OnlineRLContext"): return _inference - - def rolloutor(cfg: EasyDict, policy: Policy, env: BaseEnvManager, transitions: TransitionList) -> Callable: """ Overview: @@ -138,7 +136,9 @@ def _rollout(ctx: "OnlineRLContext"): return _rollout -def policy_resetter(env_num:int): + +def policy_resetter(env_num: int): + def _policy_resetter(ctx: OnlineRLContext): if ctx.policies is not None: assert len(ctx.policies) > 1, "battle collector needs more than 1 policies" @@ -148,7 +148,7 @@ def _policy_resetter(ctx: OnlineRLContext): # traj_buffer is {env_id: {policy_id: TrajBuffer}}, is used to store traj_len pieces of transitions ctx.traj_buffer = { env_id: {policy_id: TrajBuffer(maxlen=ctx.traj_len) - for policy_id in range(ctx.agent_num)} + for policy_id in range(ctx.agent_num)} for env_id in range(env_num) } @@ -158,7 +158,8 @@ def _policy_resetter(ctx: OnlineRLContext): return _policy_resetter -def battle_inferencer(cfg: EasyDict, env: BaseEnvManager, obs_pool: CachePool, policy_output_pool:CachePool): +def battle_inferencer(cfg: EasyDict, env: BaseEnvManager, obs_pool: CachePool, policy_output_pool: CachePool): + def _battle_inferencer(ctx: "OnlineRLContext"): # Get current env obs. obs = env.ready_obs @@ -185,7 +186,9 @@ def _battle_inferencer(ctx: "OnlineRLContext"): return _battle_inferencer -def battle_rolloutor(cfg: EasyDict, env: BaseEnvManager, obs_pool: CachePool, policy_output_pool:CachePool): + +def battle_rolloutor(cfg: EasyDict, env: BaseEnvManager, obs_pool: CachePool, policy_output_pool: CachePool): + def _battle_rolloutor(ctx: "OnlineRLContext"): timesteps = env.step(ctx.actions) for env_id, timestep in timesteps.items(): @@ -195,8 +198,7 @@ def _battle_rolloutor(ctx: "OnlineRLContext"): policy_timestep_data = [d[policy_id] if not isinstance(d, bool) else d for d in timestep] policy_timestep = type(timestep)(*policy_timestep_data) transition = ctx.policies[policy_id].process_transition( - obs_pool[env_id][policy_id], policy_output_pool[env_id][policy_id], - policy_timestep + obs_pool[env_id][policy_id], policy_output_pool[env_id][policy_id], policy_timestep ) transition['collect_iter'] = ctx.train_iter ctx.traj_buffer[env_id][policy_id].append(transition) @@ -221,5 +223,5 @@ def _battle_rolloutor(ctx: "OnlineRLContext"): ctx.ready_env_id.remove(env_id) for policy_id in range(ctx.agent_num): ctx.episode_info[policy_id].append(timestep.info[policy_id]) - - return _battle_rolloutor \ No newline at end of file + + return _battle_rolloutor diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index d627c5425c..39a64eb6c8 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -2,7 +2,7 @@ from time import sleep import logging -from typing import Dict, List, Any, Callable +from typing import Dict, List, Any, Callable from dataclasses import dataclass, field from abc import abstractmethod @@ -17,11 +17,13 @@ from ding.framework.middleware.functional import policy_resetter import queue + @dataclass class ActorData: train_data: Any env_step: int = 0 + class Storage: def __init__(self, path: str) -> None: @@ -35,12 +37,14 @@ def save(self, data: Any) -> None: def load(self) -> Any: raise NotImplementedError + @dataclass class PlayerMeta: player_id: str checkpoint: "Storage" total_agent_step: int = 0 + class LeagueActor: def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): @@ -74,16 +78,12 @@ def _on_league_job(self, job: "Job"): Deal with job distributed by coordinator. Load historical model, generate traj and emit data. """ self.job_queue.put(job) - + def _get_collector(self, player_id: str): if self._collectors.get(player_id): return self._collectors.get(player_id) cfg = self.cfg - collector = task.wrap(BattleCollector( - cfg.policy.collect.collector, - self.env, - self.n_rollout_samples - )) + collector = task.wrap(BattleCollector(cfg.policy.collect.collector, self.env, self.n_rollout_samples)) self._collectors[player_id] = collector return collector @@ -106,7 +106,7 @@ def __call__(self, ctx: "OnlineRLContext"): task.emit("actor_greeting", task.router.node_id) try: - job = self.job_queue.get(timeout = 5) + job = self.job_queue.get(timeout=5) except queue.Empty: logging.warning("For actor_{}, no Job get from coordinator".format(task.router.node_id)) return @@ -122,7 +122,7 @@ def __call__(self, ctx: "OnlineRLContext"): "Waiting for new model on actor: {}, player: {}".format(task.router.node_id, job.launch_player) ) sleep(1) - + collector = self._get_collector(job.launch_player) policies = [] main_player: "PlayerMeta" = None @@ -139,10 +139,10 @@ def __call__(self, ctx: "OnlineRLContext"): ctx.n_episode = None ctx.train_iter = main_player.total_agent_step ctx.policy_kwargs = None - + collector(ctx) train_data, episode_info = ctx.train_data[0], ctx.episode_info[0] # only use main player data for training - + # Send actor data. Don't send data in evaluation mode if job.is_eval: return @@ -155,6 +155,3 @@ def __call__(self, ctx: "OnlineRLContext"): # Send actor job job.result = [e['result'] for e in episode_info] task.emit("actor_job", job) - - - diff --git a/ding/framework/middleware/league_learner.py b/ding/framework/middleware/league_learner.py index a80c861ab4..adcdd158b6 100644 --- a/ding/framework/middleware/league_learner.py +++ b/ding/framework/middleware/league_learner.py @@ -1,7 +1,8 @@ from dataclasses import dataclass + @dataclass class LearnerModel: player_id: str state_dict: dict - train_iter: int = 0 \ No newline at end of file + train_iter: int = 0 diff --git a/ding/framework/middleware/tests/test_league_actor.py b/ding/framework/middleware/tests/test_league_actor.py index dfd59d3461..e5acaf6e19 100644 --- a/ding/framework/middleware/tests/test_league_actor.py +++ b/ding/framework/middleware/tests/test_league_actor.py @@ -15,6 +15,7 @@ from dataclasses import dataclass + def prepare_test(): global cfg cfg = deepcopy(cfg) @@ -34,22 +35,15 @@ def policy_fn(): return cfg, env_fn, policy_fn -def test_league_actor(): +def _main(): cfg, env_fn, policy_fn = prepare_test() policy = policy_fn() job = Job( - launch_player='main_player_default_0', + launch_player='main_player_default_0', players=[ - PlayerMeta( - player_id='main_player_default_0', - checkpoint=FileStorage(path = None), - total_agent_step=0 - ), - PlayerMeta( - player_id='main_player_default_1', - checkpoint=FileStorage(path = None), - total_agent_step=0) - ] + PlayerMeta(player_id='main_player_default_0', checkpoint=FileStorage(path=None), total_agent_step=0), + PlayerMeta(player_id='main_player_default_1', checkpoint=FileStorage(path=None), total_agent_step=0) + ] ) ACTOR_ID = 0 @@ -66,15 +60,15 @@ def test_actor(): def on_actor_greeting(actor_id): assert actor_id == ACTOR_ID testcases["on_actor_greeting"] = True - + def on_actor_job(job_: Job): assert job_.launch_player == job.launch_player testcases["on_actor_job"] = True - + def on_actor_data(actor_data): assert isinstance(actor_data, ActorData) testcases["on_actor_data"] = True - + task.on('actor_greeting', on_actor_greeting) task.on("actor_job", on_actor_job) task.on("actor_data_player_{}".format(job.launch_player), on_actor_data) @@ -96,6 +90,7 @@ def _test_actor(ctx): assert all(testcases.values()) finally: task.finish = True + return _test_actor if task.router.node_id == ACTOR_ID: @@ -105,5 +100,7 @@ def _test_actor(ctx): task.run() -if __name__ == "__main__": - Parallel.runner(n_parallel_workers=2, protocol="tcp", topology="mesh")(test_league_actor) \ No newline at end of file + +@pytest.mark.unittest +def test_league_actor(): + Parallel.runner(n_parallel_workers=2, protocol="tcp", topology="mesh")(_main) diff --git a/ding/framework/middleware/tests/test_league_actor_one_process.py b/ding/framework/middleware/tests/test_league_actor_one_process.py index 9f940e130e..0718ce13ca 100644 --- a/ding/framework/middleware/tests/test_league_actor_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_one_process.py @@ -16,6 +16,7 @@ from dataclasses import dataclass + def prepare_test(): global cfg cfg = deepcopy(cfg) @@ -44,18 +45,15 @@ def test_league_actor(): def test_actor(): job = Job( - launch_player='main_player_default_0', + launch_player='main_player_default_0', players=[ PlayerMeta( - player_id='main_player_default_0', - checkpoint=FileStorage(path = None), - total_agent_step=0 - ), + player_id='main_player_default_0', checkpoint=FileStorage(path=None), total_agent_step=0 + ), PlayerMeta( - player_id='main_player_default_1', - checkpoint=FileStorage(path = None), - total_agent_step=0) - ] + player_id='main_player_default_1', checkpoint=FileStorage(path=None), total_agent_step=0 + ) + ] ) testcases = { "on_actor_greeting": False, @@ -83,7 +81,7 @@ def _test_actor(ctx): sleep(0.3) task.emit("league_job_actor_{}".format(task.router.node_id), job) sleep(0.3) - assert league_actor._model_updated == False + assert league_actor._model_updated is False task.emit( "learner_model", @@ -92,7 +90,7 @@ def _test_actor(ctx): ) ) sleep(5) - assert league_actor._model_updated == True + assert league_actor._model_updated is True try: print(testcases) assert all(testcases.values()) @@ -104,6 +102,3 @@ def _test_actor(ctx): task.use(test_actor()) task.use(league_actor) task.run() - -if __name__ == "__main__": - test_league_actor() \ No newline at end of file From 6542a30549154649a7268b2d8d371bca9461ba91 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 31 May 2022 20:45:24 +0800 Subject: [PATCH 059/229] add new Enum event names inside actor and test --- ding/framework/event_enum.py | 2 +- .../middleware/functional/collector.py | 6 ++++-- ding/framework/middleware/league_actor.py | 12 ++++++------ .../middleware/tests/test_league_actor.py | 16 ++++++++++------ .../tests/test_league_actor_one_process.py | 17 ++++++++++------- 5 files changed, 31 insertions(+), 22 deletions(-) diff --git a/ding/framework/event_enum.py b/ding/framework/event_enum.py index c0ea7f9dcb..e7f555b548 100644 --- a/ding/framework/event_enum.py +++ b/ding/framework/event_enum.py @@ -12,5 +12,5 @@ class EventEnum(str, Enum): # events emited by actors ACTOR_GREETING = "on_actor_greeting" - ACTOR_SEND_DATA = "on_actor_send_meta" + ACTOR_SEND_DATA = "on_actor_send_meta_player_{player}" ACTOR_FINISH_JOB = "on_actor_finish_job" diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 4b3650660c..f637a3bf77 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -152,8 +152,10 @@ def _policy_resetter(ctx: OnlineRLContext): for env_id in range(env_num) } - for p in ctx.policies: - p.reset() + for p in ctx.policies: + p.reset() + else: + raise RuntimeError('ctx.policies should not be None') return _policy_resetter diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 39a64eb6c8..7ee6cd3af8 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -1,4 +1,4 @@ -from ding.framework import task +from ding.framework import task, EventEnum from time import sleep import logging @@ -58,8 +58,8 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self._collectors: Dict[str, BattleCollector] = {} self._policies: Dict[str, "Policy.collect_function"] = {} self._model_updated = True - task.on("league_job_actor_{}".format(task.router.node_id), self._on_league_job) - task.on("learner_model", self._on_learner_model) + task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), self._on_league_job) + task.on(EventEnum.LEARNER_SEND_MODEL, self._on_learner_model) self._policy_resetter = task.wrap(policy_resetter(self.env_num)) self.job_queue = queue.Queue() @@ -103,7 +103,7 @@ def __call__(self, ctx: "OnlineRLContext"): # task.emit("actor_greeting", task.router.node_id) if self.job_queue.empty(): - task.emit("actor_greeting", task.router.node_id) + task.emit(EventEnum.ACTOR_GREETING, task.router.node_id) try: job = self.job_queue.get(timeout=5) @@ -150,8 +150,8 @@ def __call__(self, ctx: "OnlineRLContext"): d["adv"] = d["reward"] actor_data = ActorData(env_step=ctx.envstep, train_data=train_data) - task.emit("actor_data_player_{}".format(job.launch_player), actor_data) + task.emit(EventEnum.ACTOR_SEND_DATA.format(player=job.launch_player), actor_data) # Send actor job job.result = [e['result'] for e in episode_info] - task.emit("actor_job", job) + task.emit(EventEnum.ACTOR_FINISH_JOB, job) diff --git a/ding/framework/middleware/tests/test_league_actor.py b/ding/framework/middleware/tests/test_league_actor.py index e5acaf6e19..b9876bc6ba 100644 --- a/ding/framework/middleware/tests/test_league_actor.py +++ b/ding/framework/middleware/tests/test_league_actor.py @@ -13,7 +13,7 @@ from ding.policy.ppo import PPOPolicy from dizoo.league_demo.game_env import GameEnv -from dataclasses import dataclass +from ding.framework import EventEnum def prepare_test(): @@ -69,17 +69,17 @@ def on_actor_data(actor_data): assert isinstance(actor_data, ActorData) testcases["on_actor_data"] = True - task.on('actor_greeting', on_actor_greeting) - task.on("actor_job", on_actor_job) - task.on("actor_data_player_{}".format(job.launch_player), on_actor_data) + task.on(EventEnum.ACTOR_GREETING, on_actor_greeting) + task.on(EventEnum.ACTOR_FINISH_JOB, on_actor_job) + task.on(EventEnum.ACTOR_SEND_DATA.format(player=job.launch_player), on_actor_data) def _test_actor(ctx): sleep(0.3) - task.emit("league_job_actor_{}".format(ACTOR_ID), job) + task.emit(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=ACTOR_ID), job) sleep(0.3) task.emit( - "learner_model", + EventEnum.LEARNER_SEND_MODEL, LearnerModel( player_id='main_player_default_0', state_dict=policy.learn_mode.state_dict(), train_iter=0 ) @@ -104,3 +104,7 @@ def _test_actor(ctx): @pytest.mark.unittest def test_league_actor(): Parallel.runner(n_parallel_workers=2, protocol="tcp", topology="mesh")(_main) + + +if __name__ == '__main__': + Parallel.runner(n_parallel_workers=2, protocol="tcp", topology="mesh")(_main) diff --git a/ding/framework/middleware/tests/test_league_actor_one_process.py b/ding/framework/middleware/tests/test_league_actor_one_process.py index 0718ce13ca..1adae982a9 100644 --- a/ding/framework/middleware/tests/test_league_actor_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_one_process.py @@ -7,14 +7,14 @@ from ding.framework.middleware.league_actor import ActorData, LeagueActor, PlayerMeta from ding.framework.storage import FileStorage -from ding.framework.task import task, Parallel +from ding.framework.task import task from ding.framework import OnlineRLContext from ding.league.v2.base_league import Job from ding.model import VAC from ding.policy.ppo import PPOPolicy from dizoo.league_demo.game_env import GameEnv -from dataclasses import dataclass +from ding.framework import EventEnum def prepare_test(): @@ -73,18 +73,18 @@ def on_actor_data(actor_data): assert isinstance(actor_data, ActorData) testcases["on_actor_data"] = True - task.on("actor_greeting", on_actor_greeting) - task.on("actor_job", on_actor_job) - task.on("actor_data_player_{}".format(job.launch_player), on_actor_data) + task.on(EventEnum.ACTOR_GREETING, on_actor_greeting) + task.on(EventEnum.ACTOR_FINISH_JOB, on_actor_job) + task.on(EventEnum.ACTOR_SEND_DATA.format(player=job.launch_player), on_actor_data) def _test_actor(ctx): sleep(0.3) - task.emit("league_job_actor_{}".format(task.router.node_id), job) + task.emit(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), job) sleep(0.3) assert league_actor._model_updated is False task.emit( - "learner_model", + EventEnum.LEARNER_SEND_MODEL, LearnerModel( player_id='main_player_default_0', state_dict=policy.learn_mode.state_dict(), train_iter=0 ) @@ -102,3 +102,6 @@ def _test_actor(ctx): task.use(test_actor()) task.use(league_actor) task.run() + +if __name__ == '__main__': + test_league_actor() \ No newline at end of file From c7fac3f5e7c6d195b4546824199d7290f63ecde0 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 31 May 2022 21:15:47 +0800 Subject: [PATCH 060/229] add test coordinator & actor pipeline --- .../middleware/tests/test_league_pipeline.py | 92 +++++++++++++++++++ 1 file changed, 92 insertions(+) create mode 100644 ding/framework/middleware/tests/test_league_pipeline.py diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py new file mode 100644 index 0000000000..a7fca1015c --- /dev/null +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -0,0 +1,92 @@ +from time import sleep +import pytest +from copy import deepcopy +from ding.envs import BaseEnvManager +from ding.framework.middleware.tests.league_config import cfg +from ding.framework.middleware import LeagueActor, LeagueCoordinator +from ding.framework.middleware.league_actor import PlayerMeta +from ding.framework.storage import FileStorage + +from ding.framework.task import task, Parallel +from ding.league.v2.base_league import Job +from ding.model import VAC +from ding.policy.ppo import PPOPolicy +from dizoo.league_demo.game_env import GameEnv + +from unittest.mock import patch + +def prepare_test(): + global cfg + cfg = deepcopy(cfg) + + def env_fn(): + env = BaseEnvManager( + env_fn=[lambda: GameEnv(cfg.env.env_type) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager + ) + env.seed(cfg.seed) + return env + + def policy_fn(): + model = VAC(**cfg.policy.model) + policy = PPOPolicy(cfg.policy, model=model) + return policy + + return cfg, env_fn, policy_fn + +class MockLeague: + + def __init__(self): + self.active_players_ids = ["main_player_default_0", "main_player_default_1", "main_player_default_2"] + self.update_payoff_cnt = 0 + self.update_active_player_cnt = 0 + self.create_historical_player_cnt = 0 + self.get_job_info_cnt = 0 + + def update_payoff(self, job): + self.update_payoff_cnt += 1 + + def update_active_player(self, meta): + self.update_active_player_cnt += 1 + + def create_historical_player(self, meta): + self.create_historical_player_cnt += 1 + + def get_job_info(self, player_id): + self.get_job_info_cnt += 1 + return Job( + launch_player=player_id, + players=[ + PlayerMeta(player_id='main_player_default_0', checkpoint=FileStorage(path=None), total_agent_step=0), + PlayerMeta(player_id='main_player_default_1', checkpoint=FileStorage(path=None), total_agent_step=0) + ] + ) + + +def _main(): + cfg, env_fn, policy_fn = prepare_test() + ACTOR_ID = 1 + + with task.start(async_mode=True): + league_actor = LeagueActor(cfg, env_fn, policy_fn) + league = MockLeague() + coordinator = LeagueCoordinator(league) + + if task.router.node_id == 0: + with patch("ding.league.BaseLeague", MockLeague): + task.use(coordinator) + sleep(10) + assert league.get_job_info_cnt == 1 + assert league.update_payoff_cnt == 1 + if task.router.node_id == ACTOR_ID: + task.use(league_actor) + + task.run(max_step=1) + + +@pytest.mark.unittest +def test_league_actor(): + Parallel.runner(n_parallel_workers=2, protocol="tcp", topology="mesh")(_main) + + +if __name__ == '__main__': + Parallel.runner(n_parallel_workers=2, protocol="tcp", topology="mesh")(_main) From 49ccd6c835ca19b9103f0a8e2f96fbfcd06cba44 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 1 Jun 2022 11:18:22 +0800 Subject: [PATCH 061/229] modify _on_learner_model method inside league_actor to make it thread safety --- ding/framework/middleware/league_actor.py | 34 ++++++++++--------- .../tests/test_league_actor_one_process.py | 2 -- .../middleware/tests/test_league_pipeline.py | 5 ++- 3 files changed, 22 insertions(+), 19 deletions(-) diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 7ee6cd3af8..8fc706179a 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -57,21 +57,17 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): # self._running = False self._collectors: Dict[str, BattleCollector] = {} self._policies: Dict[str, "Policy.collect_function"] = {} - self._model_updated = True task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), self._on_league_job) task.on(EventEnum.LEARNER_SEND_MODEL, self._on_learner_model) self._policy_resetter = task.wrap(policy_resetter(self.env_num)) self.job_queue = queue.Queue() + self.model_queue = queue.Queue() def _on_learner_model(self, learner_model: "LearnerModel"): """ - If get newest learner model, update this actor's model. + If get newest learner model, put it inside model_queue. """ - player_meta = PlayerMeta(player_id=learner_model.player_id, checkpoint=None) - policy = self._get_policy(player_meta) - # update policy model - policy.load_state_dict(learner_model.state_dict) - self._model_updated = True + self.model_queue.put(learner_model) def _on_league_job(self, job: "Job"): """ @@ -111,17 +107,23 @@ def __call__(self, ctx: "OnlineRLContext"): logging.warning("For actor_{}, no Job get from coordinator".format(task.router.node_id)) return - # self._running = True - - # Wait new active model for 10 seconds - for _ in range(10): - if self._model_updated: - self._model_updated = False - break + new_model = None + try: + logging.info( + "Getting new model on actor: {}, player: {}".format(task.router.node_id, job.launch_player) + ) + new_model = self.model_queue.get(timeout=10) + except queue.Empty: + logging.warning('Cannot get new model, use old model instead.') + + if new_model is not None: + player_meta = PlayerMeta(player_id=new_model.player_id, checkpoint=None) + policy = self._get_policy(player_meta) + # update policy model + policy.load_state_dict(new_model.state_dict) logging.info( - "Waiting for new model on actor: {}, player: {}".format(task.router.node_id, job.launch_player) + "Got new model on actor: {}, player: {}".format(task.router.node_id, job.launch_player) ) - sleep(1) collector = self._get_collector(job.launch_player) policies = [] diff --git a/ding/framework/middleware/tests/test_league_actor_one_process.py b/ding/framework/middleware/tests/test_league_actor_one_process.py index 1adae982a9..d5370be2d6 100644 --- a/ding/framework/middleware/tests/test_league_actor_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_one_process.py @@ -81,7 +81,6 @@ def _test_actor(ctx): sleep(0.3) task.emit(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), job) sleep(0.3) - assert league_actor._model_updated is False task.emit( EventEnum.LEARNER_SEND_MODEL, @@ -90,7 +89,6 @@ def _test_actor(ctx): ) ) sleep(5) - assert league_actor._model_updated is True try: print(testcases) assert all(testcases.values()) diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index a7fca1015c..fcfa185c5f 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -74,10 +74,11 @@ def _main(): if task.router.node_id == 0: with patch("ding.league.BaseLeague", MockLeague): task.use(coordinator) - sleep(10) + sleep(15) assert league.get_job_info_cnt == 1 assert league.update_payoff_cnt == 1 if task.router.node_id == ACTOR_ID: + # league_actor = LeagueActor() task.use(league_actor) task.run(max_step=1) @@ -90,3 +91,5 @@ def test_league_actor(): if __name__ == '__main__': Parallel.runner(n_parallel_workers=2, protocol="tcp", topology="mesh")(_main) +# replicas = 10 +# un parallel worker 改成1 \ No newline at end of file From 6a2b76c8bd4ffe087ebb6e3ca343be516c3b1c02 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 1 Jun 2022 12:06:28 +0800 Subject: [PATCH 062/229] change test_league_pipeline.py to multiple process --- ding/framework/middleware/league_actor.py | 4 +-- .../middleware/tests/test_league_pipeline.py | 28 +++++++++---------- 2 files changed, 16 insertions(+), 16 deletions(-) diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 8fc706179a..e2f0c12eb8 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -114,7 +114,7 @@ def __call__(self, ctx: "OnlineRLContext"): ) new_model = self.model_queue.get(timeout=10) except queue.Empty: - logging.warning('Cannot get new model, use old model instead.') + logging.warning('Cannot get new model, use old model instead on actor: {}, player: {}'.format(task.router.node_id, job.launch_player)) if new_model is not None: player_meta = PlayerMeta(player_id=new_model.player_id, checkpoint=None) @@ -133,7 +133,7 @@ def __call__(self, ctx: "OnlineRLContext"): if player.player_id == job.launch_player: main_player = player # inferencer,rolloutor = self._get_collector(player.player_id) - assert main_player, "Can not find active player" + assert main_player, "can not find active player, on actor: {}".format(task.router.node_id) ctx.policies = policies self._policy_resetter(ctx) diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index fcfa185c5f..42a9595c7c 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -14,6 +14,7 @@ from dizoo.league_demo.game_env import GameEnv from unittest.mock import patch +import random def prepare_test(): global cfg @@ -53,43 +54,42 @@ def create_historical_player(self, meta): def get_job_info(self, player_id): self.get_job_info_cnt += 1 + other_players = [i for i in self.active_players_ids if i != player_id] + another_palyer = random.choice(other_players) return Job( launch_player=player_id, players=[ - PlayerMeta(player_id='main_player_default_0', checkpoint=FileStorage(path=None), total_agent_step=0), - PlayerMeta(player_id='main_player_default_1', checkpoint=FileStorage(path=None), total_agent_step=0) + PlayerMeta(player_id=player_id, checkpoint=FileStorage(path=None), total_agent_step=0), + PlayerMeta(player_id=another_palyer, checkpoint=FileStorage(path=None), total_agent_step=0) ] ) +N_ACTORS = 5 def _main(): cfg, env_fn, policy_fn = prepare_test() - ACTOR_ID = 1 with task.start(async_mode=True): - league_actor = LeagueActor(cfg, env_fn, policy_fn) - league = MockLeague() - coordinator = LeagueCoordinator(league) - if task.router.node_id == 0: + league = MockLeague() + coordinator = LeagueCoordinator(league) with patch("ding.league.BaseLeague", MockLeague): task.use(coordinator) sleep(15) - assert league.get_job_info_cnt == 1 - assert league.update_payoff_cnt == 1 - if task.router.node_id == ACTOR_ID: - # league_actor = LeagueActor() - task.use(league_actor) + assert league.get_job_info_cnt == N_ACTORS + assert league.update_payoff_cnt == N_ACTORS + else: + task.use(LeagueActor(cfg, env_fn, policy_fn)) task.run(max_step=1) @pytest.mark.unittest def test_league_actor(): - Parallel.runner(n_parallel_workers=2, protocol="tcp", topology="mesh")(_main) + Parallel.runner(n_parallel_workers=N_ACTORS+1, protocol="tcp", topology="mesh")(_main) if __name__ == '__main__': - Parallel.runner(n_parallel_workers=2, protocol="tcp", topology="mesh")(_main) + Parallel.runner(n_parallel_workers=N_ACTORS+1, protocol="tcp", topology="mesh")(_main) # replicas = 10 # un parallel worker 改成1 \ No newline at end of file From aeac530791bec583a54b18f958e1a741fdbffe29 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 1 Jun 2022 15:37:06 +0800 Subject: [PATCH 063/229] fix a problem of env initialization inside the creation of collector --- ding/framework/middleware/league_actor.py | 16 ++++++++-------- .../middleware/tests/test_league_pipeline.py | 2 ++ 2 files changed, 10 insertions(+), 8 deletions(-) diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index e2f0c12eb8..b8f632b5c9 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -49,12 +49,10 @@ class LeagueActor: def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.cfg = cfg - self.env = env_fn() - self.env_num = self.env.env_num + self.env_fn = env_fn + self.env_num = env_fn().env_num self.policy_fn = policy_fn self.n_rollout_samples = self.cfg.policy.collect.get("n_rollout_samples") or 0 - self.n_rollout_samples = 0 - # self._running = False self._collectors: Dict[str, BattleCollector] = {} self._policies: Dict[str, "Policy.collect_function"] = {} task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), self._on_league_job) @@ -71,7 +69,7 @@ def _on_learner_model(self, learner_model: "LearnerModel"): def _on_league_job(self, job: "Job"): """ - Deal with job distributed by coordinator. Load historical model, generate traj and emit data. + Deal with job distributed by coordinator, put it inside job_queue. """ self.job_queue.put(job) @@ -79,7 +77,8 @@ def _get_collector(self, player_id: str): if self._collectors.get(player_id): return self._collectors.get(player_id) cfg = self.cfg - collector = task.wrap(BattleCollector(cfg.policy.collect.collector, self.env, self.n_rollout_samples)) + env = self.env_fn() + collector = task.wrap(BattleCollector(cfg.policy.collect.collector, env, self.n_rollout_samples)) self._collectors[player_id] = collector return collector @@ -102,12 +101,12 @@ def __call__(self, ctx: "OnlineRLContext"): task.emit(EventEnum.ACTOR_GREETING, task.router.node_id) try: - job = self.job_queue.get(timeout=5) + job = self.job_queue.get(timeout=10) except queue.Empty: logging.warning("For actor_{}, no Job get from coordinator".format(task.router.node_id)) return - new_model = None + new_model: "LearnerModel" = None try: logging.info( "Getting new model on actor: {}, player: {}".format(task.router.node_id, job.launch_player) @@ -116,6 +115,7 @@ def __call__(self, ctx: "OnlineRLContext"): except queue.Empty: logging.warning('Cannot get new model, use old model instead on actor: {}, player: {}'.format(task.router.node_id, job.launch_player)) + # 每次训练开始把 model_queue 清空 if new_model is not None: player_meta = PlayerMeta(player_id=new_model.player_id, checkpoint=None) policy = self._get_policy(player_meta) diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index 42a9595c7c..518b9bff65 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -73,9 +73,11 @@ def _main(): if task.router.node_id == 0: league = MockLeague() coordinator = LeagueCoordinator(league) + sleep(2) with patch("ding.league.BaseLeague", MockLeague): task.use(coordinator) sleep(15) + # print(league.get_job_info_cnt) assert league.get_job_info_cnt == N_ACTORS assert league.update_payoff_cnt == N_ACTORS else: From 0cd0e1d07fbbfe9c9f18dccb2bf04fa339fa9987 Mon Sep 17 00:00:00 2001 From: lixuelin Date: Wed, 1 Jun 2022 15:39:55 +0800 Subject: [PATCH 064/229] polish league coordinator --- .../middleware/league_coordinator.py | 6 +- .../tests/test_league_coordinator.py | 69 +++++++++---------- 2 files changed, 35 insertions(+), 40 deletions(-) diff --git a/ding/framework/middleware/league_coordinator.py b/ding/framework/middleware/league_coordinator.py index f5996a3388..8a50c9f8d1 100644 --- a/ding/framework/middleware/league_coordinator.py +++ b/ding/framework/middleware/league_coordinator.py @@ -33,12 +33,12 @@ def _on_actor_greeting(self, actor_id): job.actor_id = actor_id task.emit(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=actor_id), job) - def _on_actor_job(self, job: "Job"): - self.league.update_payoff(job) - def _on_learner_meta(self, player_meta: "PlayerMeta"): self.league.update_active_player(player_meta) self.league.create_historical_player(player_meta) + + def _on_actor_job(self, job: "Job"): + self.league.update_payoff(job) def __call__(self, ctx: "Context") -> None: sleep(1) diff --git a/ding/framework/middleware/tests/test_league_coordinator.py b/ding/framework/middleware/tests/test_league_coordinator.py index 6c8cd1c7d8..1d46539faa 100644 --- a/ding/framework/middleware/tests/test_league_coordinator.py +++ b/ding/framework/middleware/tests/test_league_coordinator.py @@ -32,45 +32,40 @@ def get_job_info(self, player_id): def _main(): - task.start() - if task.router.node_id == 0: - with patch("ding.league.BaseLeague", MockLeague): - league = MockLeague() - coordinator = LeagueCoordinator(league) + with task.start(): + if task.router.node_id == 0: + with patch("ding.league.BaseLeague", MockLeague): + league = MockLeague() + coordinator = LeagueCoordinator(league) + time.sleep(3) + assert league.update_payoff_cnt == 3 + assert league.update_active_player_cnt == 3 + assert league.create_historical_player_cnt == 3 + assert league.get_job_info_cnt == 3 + elif task.router.node_id == 1: + # test ACTOR_GREETING + res = [] + task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), + lambda job: res.append(job)) + for _ in range(3): + task.emit(EventEnum.ACTOR_GREETING, task.router.node_id) time.sleep(3) - assert league.update_payoff_cnt == 3 - assert league.update_active_player_cnt == 3 - assert league.create_historical_player_cnt == 3 - assert league.get_job_info_cnt == 3 - elif task.router.node_id == 1: - # test ACTOR_GREETING - res = [] - actor_id = "test_node_{}".format(task.router.node_id) - task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=actor_id), lambda job: res.append(job)) - time.sleep(0.1) - for _ in range(3): - task.emit(EventEnum.ACTOR_GREETING, actor_id) - time.sleep(2) - assert actor_id == res[-1].actor_id - elif task.router.node_id == 2: - # test LEARNER_SEND_META - actor_id = "test_node_{}".format(task.router.node_id) - time.sleep(0.1) - for _ in range(3): - task.emit(EventEnum.LEARNER_SEND_META, {"meta": actor_id}) - time.sleep(2) - elif task.router.node_id == 3: - # test ACTOR_FINISH_JOB - actor_id = "test_node_{}".format(task.router.node_id) - time.sleep(0.1) - job = Job(-1, actor_id, False) - for _ in range(3): - task.emit(EventEnum.ACTOR_FINISH_JOB, job) - time.sleep(3) - else: - raise Exception("Invalid node id {}".format(task.router.is_active)) + assert task.router.node_id == res[-1].actor_id + elif task.router.node_id == 2: + # test LEARNER_SEND_META + for _ in range(3): + task.emit(EventEnum.LEARNER_SEND_META, {"meta": task.router.node_id}) + time.sleep(3) + elif task.router.node_id == 3: + # test ACTOR_FINISH_JOB + job = Job(-1, task.router.node_id, False) + for _ in range(3): + task.emit(EventEnum.ACTOR_FINISH_JOB, job) + time.sleep(3) + else: + raise Exception("Invalid node id {}".format(task.router.is_active)) -@pytest.mark.unittest +@pytest.mark.lxl def test_coordinator(): Parallel.runner(n_parallel_workers=4, protocol="tcp", topology="star")(_main) From fe26bb3b49bf98b177122c2985c679d3169eb27e Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 1 Jun 2022 15:54:38 +0800 Subject: [PATCH 065/229] change "policies" to "current_policies" to make it clear --- ding/framework/middleware/league_actor.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index b8f632b5c9..d4c4b5a425 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -115,7 +115,7 @@ def __call__(self, ctx: "OnlineRLContext"): except queue.Empty: logging.warning('Cannot get new model, use old model instead on actor: {}, player: {}'.format(task.router.node_id, job.launch_player)) - # 每次训练开始把 model_queue 清空 + # TODO: 每次训练开始把 model_queue 清空 if new_model is not None: player_meta = PlayerMeta(player_id=new_model.player_id, checkpoint=None) policy = self._get_policy(player_meta) @@ -126,16 +126,16 @@ def __call__(self, ctx: "OnlineRLContext"): ) collector = self._get_collector(job.launch_player) - policies = [] + current_policies = [] main_player: "PlayerMeta" = None for player in job.players: - policies.append(self._get_policy(player)) + current_policies.append(self._get_policy(player)) if player.player_id == job.launch_player: main_player = player # inferencer,rolloutor = self._get_collector(player.player_id) assert main_player, "can not find active player, on actor: {}".format(task.router.node_id) - ctx.policies = policies + ctx.policies = current_policies self._policy_resetter(ctx) ctx.n_episode = None From bd6395b2fc049875a0cb5ca3f5df66e7a1317aed Mon Sep 17 00:00:00 2001 From: lixuelin Date: Wed, 1 Jun 2022 17:29:55 +0800 Subject: [PATCH 066/229] polish league coordinator --- ding/framework/middleware/tests/test_league_coordinator.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ding/framework/middleware/tests/test_league_coordinator.py b/ding/framework/middleware/tests/test_league_coordinator.py index 1d46539faa..2d3a8b65cc 100644 --- a/ding/framework/middleware/tests/test_league_coordinator.py +++ b/ding/framework/middleware/tests/test_league_coordinator.py @@ -66,6 +66,6 @@ def _main(): raise Exception("Invalid node id {}".format(task.router.is_active)) -@pytest.mark.lxl +@pytest.mark.unittest def test_coordinator(): Parallel.runner(n_parallel_workers=4, protocol="tcp", topology="star")(_main) From 465ce9b99f4bc80b5714cb76ef9dc6b1518162ca Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 1 Jun 2022 21:02:49 +0800 Subject: [PATCH 067/229] add streaming data collection --- ding/framework/middleware/__init__.py | 1 + ding/framework/middleware/actor_data.py | 7 +++ ding/framework/middleware/collector.py | 19 +++++- ding/framework/middleware/league_actor.py | 60 ++++--------------- .../middleware/tests/test_league_actor.py | 3 +- .../tests/test_league_actor_one_process.py | 3 +- .../middleware/tests/test_league_pipeline.py | 2 +- ding/league/player.py | 8 +++ 8 files changed, 48 insertions(+), 55 deletions(-) create mode 100644 ding/framework/middleware/actor_data.py diff --git a/ding/framework/middleware/__init__.py b/ding/framework/middleware/__init__.py index 8580fc2caf..039511d001 100644 --- a/ding/framework/middleware/__init__.py +++ b/ding/framework/middleware/__init__.py @@ -4,3 +4,4 @@ from .ckpt_handler import CkptSaver from .league_actor import LeagueActor from .league_coordinator import LeagueCoordinator +from .actor_data import ActorData diff --git a/ding/framework/middleware/actor_data.py b/ding/framework/middleware/actor_data.py new file mode 100644 index 0000000000..350022052a --- /dev/null +++ b/ding/framework/middleware/actor_data.py @@ -0,0 +1,7 @@ +from typing import Any +from dataclasses import dataclass + +@dataclass +class ActorData: + train_data: Any + env_step: int = 0 \ No newline at end of file diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index bd412dc75e..4a89fa7353 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -1,17 +1,16 @@ from distutils.log import info -from typing import TYPE_CHECKING, Callable, List, Optional, Tuple from easydict import EasyDict from ding.policy import Policy, get_random_policy from ding.envs import BaseEnvManager -from ding.framework import task +from ding.framework import task, EventEnum from .functional import inferencer, rolloutor, TransitionList, battle_inferencer, battle_rolloutor +from .actor_data import ActorData # if TYPE_CHECKING: from ding.framework import OnlineRLContext from ding.worker.collector.base_serial_collector import CachePool - class BattleCollector: def __init__(self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int): @@ -27,6 +26,7 @@ def __init__(self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int): self.total_envstep_count = 0 self.end_flag = False self.n_rollout_samples = n_rollout_samples + self.streaming_sampling_flag = n_rollout_samples > 0 self._battle_inferencer = task.wrap( battle_inferencer(self.cfg, self.env, self.obs_pool, self.policy_output_pool) @@ -79,10 +79,23 @@ def __call__(self, ctx: "OnlineRLContext") -> None: self._battle_rolloutor(ctx) self.total_envstep_count = ctx.envstep + if not ctx.job.is_eval and self.streaming_sampling_flag is True and len(ctx.train_data[0]) >= self.n_rollout_samples: + actor_data = ActorData(env_step=ctx.envstep, train_data=ctx.train_data[0]) + task.emit(EventEnum.ACTOR_SEND_DATA.format(player=ctx.job.launch_player), actor_data) + ctx.train_data = [[] for _ in range(ctx.agent_num)] + if ctx.collected_episode >= ctx.n_episode: + ctx.job.result = [e['result'] for e in ctx.episode_info[0]] + task.emit(EventEnum.ACTOR_FINISH_JOB, ctx.job) + if not ctx.job.is_eval and len(ctx.train_data[0]) > 0: + actor_data = ActorData(env_step=ctx.envstep, train_data=ctx.train_data[0]) + task.emit(EventEnum.ACTOR_SEND_DATA.format(player=ctx.job.launch_player), actor_data) + ctx.train_data = [[] for _ in range(ctx.agent_num)] break + + class StepCollector: """ Overview: diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index d4c4b5a425..90f1c8e21c 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -15,36 +15,9 @@ from ding.framework.middleware.league_learner import LearnerModel from ding.framework.middleware import BattleCollector from ding.framework.middleware.functional import policy_resetter +from ding.league.player import PlayerMeta import queue - -@dataclass -class ActorData: - train_data: Any - env_step: int = 0 - - -class Storage: - - def __init__(self, path: str) -> None: - self.path = path - - @abstractmethod - def save(self, data: Any) -> None: - raise NotImplementedError - - @abstractmethod - def load(self) -> Any: - raise NotImplementedError - - -@dataclass -class PlayerMeta: - player_id: str - checkpoint: "Storage" - total_agent_step: int = 0 - - class LeagueActor: def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): @@ -52,7 +25,8 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.env_fn = env_fn self.env_num = env_fn().env_num self.policy_fn = policy_fn - self.n_rollout_samples = self.cfg.policy.collect.get("n_rollout_samples") or 0 + # self.n_rollout_samples = self.cfg.policy.collect.get("n_rollout_samples") or 0 + self.n_rollout_samples = 64 self._collectors: Dict[str, BattleCollector] = {} self._policies: Dict[str, "Policy.collect_function"] = {} task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), self._on_league_job) @@ -101,7 +75,7 @@ def __call__(self, ctx: "OnlineRLContext"): task.emit(EventEnum.ACTOR_GREETING, task.router.node_id) try: - job = self.job_queue.get(timeout=10) + ctx.job = self.job_queue.get(timeout=10) except queue.Empty: logging.warning("For actor_{}, no Job get from coordinator".format(task.router.node_id)) return @@ -109,28 +83,28 @@ def __call__(self, ctx: "OnlineRLContext"): new_model: "LearnerModel" = None try: logging.info( - "Getting new model on actor: {}, player: {}".format(task.router.node_id, job.launch_player) + "Getting new model on actor: {}, player: {}".format(task.router.node_id, ctx.job.launch_player) ) new_model = self.model_queue.get(timeout=10) except queue.Empty: - logging.warning('Cannot get new model, use old model instead on actor: {}, player: {}'.format(task.router.node_id, job.launch_player)) + logging.warning('Cannot get new model, use old model instead on actor: {}, player: {}'.format(task.router.node_id, ctx.job.launch_player)) - # TODO: 每次训练开始把 model_queue 清空 + # TODO: 每次循环开始前把 model_queue 清空 if new_model is not None: player_meta = PlayerMeta(player_id=new_model.player_id, checkpoint=None) policy = self._get_policy(player_meta) # update policy model policy.load_state_dict(new_model.state_dict) logging.info( - "Got new model on actor: {}, player: {}".format(task.router.node_id, job.launch_player) + "Got new model on actor: {}, player: {}".format(task.router.node_id, ctx.job.launch_player) ) - collector = self._get_collector(job.launch_player) + collector = self._get_collector(ctx.job.launch_player) current_policies = [] main_player: "PlayerMeta" = None - for player in job.players: + for player in ctx.job.players: current_policies.append(self._get_policy(player)) - if player.player_id == job.launch_player: + if player.player_id == ctx.job.launch_player: main_player = player # inferencer,rolloutor = self._get_collector(player.player_id) assert main_player, "can not find active player, on actor: {}".format(task.router.node_id) @@ -143,17 +117,5 @@ def __call__(self, ctx: "OnlineRLContext"): ctx.policy_kwargs = None collector(ctx) - train_data, episode_info = ctx.train_data[0], ctx.episode_info[0] # only use main player data for training - - # Send actor data. Don't send data in evaluation mode - if job.is_eval: - return - for d in train_data: - d["adv"] = d["reward"] - actor_data = ActorData(env_step=ctx.envstep, train_data=train_data) - task.emit(EventEnum.ACTOR_SEND_DATA.format(player=job.launch_player), actor_data) - # Send actor job - job.result = [e['result'] for e in episode_info] - task.emit(EventEnum.ACTOR_FINISH_JOB, job) diff --git a/ding/framework/middleware/tests/test_league_actor.py b/ding/framework/middleware/tests/test_league_actor.py index b9876bc6ba..53772a8a30 100644 --- a/ding/framework/middleware/tests/test_league_actor.py +++ b/ding/framework/middleware/tests/test_league_actor.py @@ -4,7 +4,8 @@ from ding.envs import BaseEnvManager from ding.framework.middleware.league_learner import LearnerModel from ding.framework.middleware.tests.league_config import cfg -from ding.framework.middleware.league_actor import ActorData, LeagueActor, PlayerMeta +from ding.framework.middleware import ActorData, LeagueActor +from ding.league.player import PlayerMeta from ding.framework.storage import FileStorage from ding.framework.task import task, Parallel diff --git a/ding/framework/middleware/tests/test_league_actor_one_process.py b/ding/framework/middleware/tests/test_league_actor_one_process.py index d5370be2d6..4aaef8861d 100644 --- a/ding/framework/middleware/tests/test_league_actor_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_one_process.py @@ -4,7 +4,8 @@ from ding.envs import BaseEnvManager from ding.framework.middleware.league_learner import LearnerModel from ding.framework.middleware.tests.league_config import cfg -from ding.framework.middleware.league_actor import ActorData, LeagueActor, PlayerMeta +from ding.framework.middleware import ActorData, LeagueActor +from ding.league.player import PlayerMeta from ding.framework.storage import FileStorage from ding.framework.task import task diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index 518b9bff65..a84a4170a9 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -4,7 +4,7 @@ from ding.envs import BaseEnvManager from ding.framework.middleware.tests.league_config import cfg from ding.framework.middleware import LeagueActor, LeagueCoordinator -from ding.framework.middleware.league_actor import PlayerMeta +from ding.league.player import PlayerMeta from ding.framework.storage import FileStorage from ding.framework.task import task, Parallel diff --git a/ding/league/player.py b/ding/league/player.py index e253c0bdad..f5a7d33233 100644 --- a/ding/league/player.py +++ b/ding/league/player.py @@ -1,3 +1,4 @@ +from dataclasses import dataclass from typing import Callable, Optional, List from collections import namedtuple import numpy as np @@ -5,6 +6,13 @@ from ding.utils import import_module, PLAYER_REGISTRY from .algorithm import pfsp +from ding.framework.storage import Storage + +@dataclass +class PlayerMeta: + player_id: str + checkpoint: "Storage" + total_agent_step: int = 0 class Player: From a6e9343ac5ae33d23cfd2a9c6ea47618a4c50248 Mon Sep 17 00:00:00 2001 From: niuyazhe Date: Wed, 1 Jun 2022 21:15:49 +0800 Subject: [PATCH 068/229] demo(nyz): add distar model --- dizoo/distar/envs/__init__.py | 2 + dizoo/distar/envs/action_dict.py | 937 ++++++++++++++ dizoo/distar/envs/fake_data.py | 306 +++++ dizoo/distar/envs/meta.py | 11 + dizoo/distar/envs/static_data.py | 1152 +++++++++++++++++ dizoo/distar/model/__init__.py | 1 + .../model/actor_critic_default_config.yaml | 453 +++++++ dizoo/distar/model/encoder.py | 42 + dizoo/distar/model/head/__init__.py | 2 + dizoo/distar/model/head/action_arg_head.py | 497 +++++++ dizoo/distar/model/head/action_type_head.py | 71 + dizoo/distar/model/lstm.py | 321 +++++ dizoo/distar/model/model.py | 189 +++ dizoo/distar/model/module_utils.py | 570 ++++++++ dizoo/distar/model/obs_encoder/__init__.py | 4 + .../model/obs_encoder/entity_encoder.py | 101 ++ .../model/obs_encoder/scalar_encoder.py | 145 +++ .../model/obs_encoder/spatial_encoder.py | 99 ++ .../distar/model/obs_encoder/value_encoder.py | 84 ++ dizoo/distar/model/policy.py | 79 ++ dizoo/distar/model/tests/test_encoder.py | 31 + dizoo/distar/model/tests/test_value.py | 23 + dizoo/distar/model/value.py | 38 + 23 files changed, 5158 insertions(+) create mode 100644 dizoo/distar/envs/__init__.py create mode 100644 dizoo/distar/envs/action_dict.py create mode 100644 dizoo/distar/envs/fake_data.py create mode 100644 dizoo/distar/envs/meta.py create mode 100644 dizoo/distar/envs/static_data.py create mode 100644 dizoo/distar/model/__init__.py create mode 100644 dizoo/distar/model/actor_critic_default_config.yaml create mode 100644 dizoo/distar/model/encoder.py create mode 100644 dizoo/distar/model/head/__init__.py create mode 100644 dizoo/distar/model/head/action_arg_head.py create mode 100644 dizoo/distar/model/head/action_type_head.py create mode 100644 dizoo/distar/model/lstm.py create mode 100644 dizoo/distar/model/model.py create mode 100644 dizoo/distar/model/module_utils.py create mode 100644 dizoo/distar/model/obs_encoder/__init__.py create mode 100644 dizoo/distar/model/obs_encoder/entity_encoder.py create mode 100644 dizoo/distar/model/obs_encoder/scalar_encoder.py create mode 100644 dizoo/distar/model/obs_encoder/spatial_encoder.py create mode 100644 dizoo/distar/model/obs_encoder/value_encoder.py create mode 100644 dizoo/distar/model/policy.py create mode 100644 dizoo/distar/model/tests/test_encoder.py create mode 100644 dizoo/distar/model/tests/test_value.py create mode 100644 dizoo/distar/model/value.py diff --git a/dizoo/distar/envs/__init__.py b/dizoo/distar/envs/__init__.py new file mode 100644 index 0000000000..729cd76ef8 --- /dev/null +++ b/dizoo/distar/envs/__init__.py @@ -0,0 +1,2 @@ +from .meta import * +from .static_data import BEGIN_ACTIONS diff --git a/dizoo/distar/envs/action_dict.py b/dizoo/distar/envs/action_dict.py new file mode 100644 index 0000000000..470ed978ee --- /dev/null +++ b/dizoo/distar/envs/action_dict.py @@ -0,0 +1,937 @@ +import numpy as np +from copy import deepcopy + +ACTION_INFO_MASK = \ + { + 0: {'name': 'no_op', 'func_type': 'raw_no_op', 'ability_id': None, 'general_id': None, 'goal': 'other', 'special_goal': None, 'queued': False, 'selected_units': False, 'target_unit': False, 'target_location': False}, + 168: {'name': 'raw_move_camera', 'func_type': 'raw_move_camera', 'ability_id': None, 'general_id': None, 'goal': 'other', 'special_goal': None, 'queued': False, 'selected_units': False, 'target_unit': False, 'target_location': True}, + 2: {'name': 'Attack_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3674, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BATTLECRUISER', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MEDIVAC', 'TERRAN_MISSILETURRET', 'TERRAN_MULE', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_RAVEN', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'TERRAN_WIDOWMINE', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CHANGELING', 'ZERG_CHANGELINGMARINE', 'ZERG_CHANGELINGMARINESHIELD', 'ZERG_CHANGELINGZEALOT', 'ZERG_CHANGELINGZERGLING', 'ZERG_CHANGELINGZERGLINGWINGS', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTOR', 'ZERG_INFESTORBURROWED', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMP', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_OVERLORD', 'ZERG_OVERLORDTRANSPORT', 'ZERG_OVERSEER', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_ROACHBURROWED', 'ZERG_SPINECRAWLER', 'ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLER', 'ZERG_SPORECRAWLERUPROOTED', 'ZERG_SWARMHOSTMP', 'ZERG_ULTRALISK', 'ZERG_VIPER', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ADEPTPHASESHIFT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 57, 24, 692, 50, 53, 484, 689, 734, 51, 48, 54, 23, 268, 130, 56, 49, 45, 33, 32, 52, 691, 34, 35, 498, 9, 289, 114, 12, 15, 14, 13, 17, 16, 112, 104, 107, 111, 127, 7, 489, 693, 502, 503, 108, 106, 893, 129, 126, 688, 110, 118, 98, 139, 99, 140, 494, 109, 499, 105, 311, 801, 141, 79, 4, 76, 694, 733, 75, 83, 85, 10, 488, 82, 495, 78, 66, 84, 894, 77, 74, 496, 80, 81, 73]}, + 3: {'name': 'Attack_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3674, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BATTLECRUISER', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MEDIVAC', 'TERRAN_MISSILETURRET', 'TERRAN_MULE', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_RAVEN', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'TERRAN_WIDOWMINE', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CHANGELING', 'ZERG_CHANGELINGMARINE', 'ZERG_CHANGELINGMARINESHIELD', 'ZERG_CHANGELINGZEALOT', 'ZERG_CHANGELINGZERGLING', 'ZERG_CHANGELINGZERGLINGWINGS', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTOR', 'ZERG_INFESTORBURROWED', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMP', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_OVERLORD', 'ZERG_OVERLORDTRANSPORT', 'ZERG_OVERSEER', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_ROACHBURROWED', 'ZERG_SPINECRAWLER', 'ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLER', 'ZERG_SPORECRAWLERUPROOTED', 'ZERG_SWARMHOSTMP', 'ZERG_ULTRALISK', 'ZERG_VIPER', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ADEPTPHASESHIFT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 57, 24, 692, 50, 53, 484, 689, 734, 51, 48, 54, 23, 268, 130, 56, 49, 45, 33, 32, 52, 691, 34, 35, 498, 9, 289, 114, 12, 15, 14, 13, 17, 16, 112, 104, 107, 111, 127, 7, 489, 693, 502, 503, 108, 106, 893, 129, 126, 688, 110, 118, 98, 139, 99, 140, 494, 109, 499, 105, 311, 801, 141, 79, 4, 76, 694, 733, 75, 83, 85, 10, 488, 82, 495, 78, 66, 84, 894, 77, 74, 496, 80, 81, 73]}, + 4: {'name': 'Attack_Attack_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 23, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MISSILETURRET', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_SPINECRAWLER', 'ZERG_SPORECRAWLER', 'ZERG_ULTRALISK', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 24, 692, 50, 53, 484, 689, 734, 51, 48, 23, 130, 49, 45, 33, 32, 52, 691, 34, 35, 9, 289, 114, 112, 104, 107, 7, 489, 693, 503, 108, 126, 688, 110, 98, 99, 109, 105, 311, 141, 79, 4, 76, 83, 85, 10, 488, 78, 66, 84, 894, 77, 74, 496, 80, 73]}, + 6: {'name': 'Attack_AttackBuilding_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2048, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MISSILETURRET', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_SPINECRAWLER', 'ZERG_SPORECRAWLER', 'ZERG_ULTRALISK', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 24, 692, 50, 53, 484, 689, 734, 51, 48, 23, 130, 49, 45, 33, 32, 52, 691, 34, 35, 9, 289, 114, 112, 104, 107, 7, 489, 693, 503, 108, 126, 688, 110, 98, 99, 109, 105, 311, 141, 79, 4, 76, 83, 85, 10, 488, 78, 66, 84, 894, 77, 74, 496, 80, 73]}, + 5: {'name': 'Attack_Attack_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 23, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MISSILETURRET', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_SPINECRAWLER', 'ZERG_SPORECRAWLER', 'ZERG_ULTRALISK', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 24, 692, 50, 53, 484, 689, 734, 51, 48, 23, 130, 49, 45, 33, 32, 52, 691, 34, 35, 9, 289, 114, 112, 104, 107, 7, 489, 693, 503, 108, 126, 688, 110, 98, 99, 109, 105, 311, 141, 79, 4, 76, 83, 85, 10, 488, 78, 66, 84, 894, 77, 74, 496, 80, 73]}, + 7: {'name': 'Attack_AttackBuilding_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2048, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MISSILETURRET', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_SPINECRAWLER', 'ZERG_SPORECRAWLER', 'ZERG_ULTRALISK', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 24, 692, 50, 53, 484, 689, 734, 51, 48, 23, 130, 49, 45, 33, 32, 52, 691, 34, 35, 9, 289, 114, 112, 104, 107, 7, 489, 693, 503, 108, 126, 688, 110, 98, 99, 109, 105, 311, 141, 79, 4, 76, 83, 85, 10, 488, 78, 66, 84, 894, 77, 74, 496, 80, 73]}, + 539: {'name': 'Attack_Battlecruiser_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3771, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_BATTLECRUISER'], 'avail_unit_type_id': [57]}, + 540: {'name': 'Attack_Battlecruiser_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3771, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_BATTLECRUISER'], 'avail_unit_type_id': [57]}, + 8: {'name': 'Attack_Redirect_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1682, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MISSILETURRET', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_SPINECRAWLER', 'ZERG_SPORECRAWLER', 'ZERG_ULTRALISK', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 24, 692, 50, 53, 484, 689, 734, 51, 48, 23, 130, 49, 45, 33, 32, 52, 691, 34, 35, 9, 289, 114, 112, 104, 107, 7, 489, 693, 503, 108, 126, 688, 110, 98, 99, 109, 105, 311, 141, 79, 4, 76, 83, 85, 10, 488, 78, 66, 84, 894, 77, 74, 496, 80, 73]}, + 9: {'name': 'Attack_Redirect_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 1682, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MISSILETURRET', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_SPINECRAWLER', 'ZERG_SPORECRAWLER', 'ZERG_ULTRALISK', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 24, 692, 50, 53, 484, 689, 734, 51, 48, 23, 130, 49, 45, 33, 32, 52, 691, 34, 35, 9, 289, 114, 112, 104, 107, 7, 489, 693, 503, 108, 126, 688, 110, 98, 99, 109, 105, 311, 141, 79, 4, 76, 83, 85, 10, 488, 78, 66, 84, 894, 77, 74, 496, 80, 73]}, + 88: {'name': 'Behavior_BuildingAttackOff_quick', 'func_type': 'raw_cmd', 'ability_id': 2082, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_BANELING'], 'avail_unit_type_id': [9]}, + 87: {'name': 'Behavior_BuildingAttackOn_quick', 'func_type': 'raw_cmd', 'ability_id': 2081, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_BANELING'], 'avail_unit_type_id': [9]}, + 169: {'name': 'Behavior_CloakOff_quick', 'func_type': 'raw_cmd', 'ability_id': 3677, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_BANSHEE', 'TERRAN_GHOST'], 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True, 'target_location': False, 'avail_unit_type': ['PROTOSS_DARKTEMPLAR', 'PROTOSS_STALKER'], 'avail_unit_type_id': [76, 74]}, + 297: {'name': 'Effect_CalldownMULE_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 171, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_ORBITALCOMMAND'], 'avail_unit_type_id': [132]}, + 298: {'name': 'Effect_CalldownMULE_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 171, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_ORBITALCOMMAND'], 'avail_unit_type_id': [132]}, + 299: {'name': 'Effect_CausticSpray_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2324, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_CORRUPTOR'], 'avail_unit_type_id': [112]}, + 302: {'name': 'Effect_Charge_autocast', 'func_type': 'raw_autocast', 'ability_id': 1819, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_ZEALOT'], 'avail_unit_type_id': [73]}, + 300: {'name': 'Effect_Charge_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1819, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_ZEALOT'], 'avail_unit_type_id': [73]}, + 301: {'name': 'Effect_Charge_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 1819, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_ZEALOT'], 'avail_unit_type_id': [73]}, + 122: {'name': 'Effect_ChronoBoostEnergyCost_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3755, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_NEXUS'], 'avail_unit_type_id': [59]}, + 33: {'name': 'Effect_ChronoBoost_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 261, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_NEXUS'], 'avail_unit_type_id': [59]}, + 303: {'name': 'Effect_Contaminate_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 1825, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_OVERSEER'], 'avail_unit_type_id': [129]}, + 304: {'name': 'Effect_CorrosiveBile_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2338, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_RAVAGER'], 'avail_unit_type_id': [688]}, + 305: {'name': 'Effect_EMP_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1628, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, + 306: {'name': 'Effect_EMP_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 1628, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, + 307: {'name': 'Effect_Explode_quick', 'func_type': 'raw_cmd', 'ability_id': 42, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_BANELING', 'ZERG_BANELINGBURROWED'], 'avail_unit_type_id': [9, 115]}, + 157: {'name': 'Effect_Feedback_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 140, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_HIGHTEMPLAR'], 'avail_unit_type_id': [75]}, + 79: {'name': 'Effect_ForceField_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1526, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, + 308: {'name': 'Effect_FungalGrowth_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 74, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_INFESTOR', 'ZERG_INFESTORBURROWED'], 'avail_unit_type_id': [111, 127]}, + 309: {'name': 'Effect_FungalGrowth_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 74, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_INFESTOR', 'ZERG_INFESTORBURROWED'], 'avail_unit_type_id': [111, 127]}, + 310: {'name': 'Effect_GhostSnipe_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2714, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, + 32: {'name': 'Effect_GravitonBeam_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 173, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_PHOENIX'], 'avail_unit_type_id': [78]}, + 20: {'name': 'Effect_GuardianShield_quick', 'func_type': 'raw_cmd', 'ability_id': 76, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, + 312: {'name': 'Effect_Heal_autocast', 'func_type': 'raw_autocast', 'ability_id': 386, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_MEDIVAC'], 'avail_unit_type_id': [54]}, + 311: {'name': 'Effect_Heal_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 386, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_MEDIVAC'], 'avail_unit_type_id': [54]}, + 313: {'name': 'Effect_ImmortalBarrier_autocast', 'func_type': 'raw_autocast', 'ability_id': 2328, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_IMMORTAL'], 'avail_unit_type_id': [83]}, + 91: {'name': 'Effect_ImmortalBarrier_quick', 'func_type': 'raw_cmd', 'ability_id': 2328, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_IMMORTAL'], 'avail_unit_type_id': [83]}, + 314: {'name': 'Effect_InfestedTerrans_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 247, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_INFESTOR', 'ZERG_INFESTORBURROWED'], 'avail_unit_type_id': [111, 127]}, + 315: {'name': 'Effect_InjectLarva_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 251, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_QUEEN'], 'avail_unit_type_id': [126]}, + 316: {'name': 'Effect_InterferenceMatrix_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3747, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_RAVEN'], 'avail_unit_type_id': [56]}, + 317: {'name': 'Effect_KD8Charge_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2588, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_REAPER'], 'avail_unit_type_id': [49]}, + 538: {'name': 'Effect_KD8Charge_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2588, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_REAPER'], 'avail_unit_type_id': [49]}, + 318: {'name': 'Effect_LockOn_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2350, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_CYCLONE'], 'avail_unit_type_id': [692]}, + 541: {'name': 'Effect_LockOn_autocast', 'func_type': 'raw_autocast', 'ability_id': 2350, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_CYCLONE'], 'avail_unit_type_id': [692]}, + 319: {'name': 'Effect_LocustSwoop_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2387, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_LOCUSTMPFLYING'], 'avail_unit_type_id': [693]}, + 110: {'name': 'Effect_MassRecall_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3686, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE'], 'avail_unit_type_id': [10, 488]}, + 136: {'name': 'Effect_MassRecall_Mothership_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2368, 'general_id': 3686, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_MOTHERSHIP'], 'avail_unit_type_id': [10]}, + 162: {'name': 'Effect_MassRecall_Nexus_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3757, 'general_id': 3686, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_NEXUS'], 'avail_unit_type_id': [59]}, + 137: {'name': 'Effect_MassRecall_StrategicRecall_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 142, 'general_id': 3686, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_MOTHERSHIP'], 'avail_unit_type_id': [10]}, + 320: {'name': 'Effect_MedivacIgniteAfterburners_quick', 'func_type': 'raw_cmd', 'ability_id': 2116, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_MEDIVAC'], 'avail_unit_type_id': [54]}, + 321: {'name': 'Effect_NeuralParasite_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 249, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_INFESTOR', 'ZERG_INFESTORBURROWED'], 'avail_unit_type_id': [111, 127]}, + 322: {'name': 'Effect_NukeCalldown_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1622, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, + 90: {'name': 'Effect_OracleRevelation_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2146, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_ORACLE'], 'avail_unit_type_id': [495]}, + 323: {'name': 'Effect_ParasiticBomb_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2542, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_VIPER'], 'avail_unit_type_id': [499]}, + 65: {'name': 'Effect_PsiStorm_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1036, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_HIGHTEMPLAR'], 'avail_unit_type_id': [75]}, + 167: {'name': 'Effect_PurificationNova_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2346, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_DISRUPTOR'], 'avail_unit_type_id': [694]}, + 324: {'name': 'Effect_Repair_autocast', 'func_type': 'raw_autocast', 'ability_id': 3685, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_MULE', 'TERRAN_SCV', 'TERRAN_REPAIRDRONE'], 'avail_unit_type_id': [268, 45, 1913]}, + 108: {'name': 'Effect_Repair_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3685, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_MULE', 'TERRAN_SCV', 'TERRAN_REPAIRDRONE'], 'avail_unit_type_id': [268, 45, 1913]}, + 109: {'name': 'Effect_Repair_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3685, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_MULE', 'TERRAN_SCV', 'TERRAN_REPAIRDRONE'], 'avail_unit_type_id': [268, 45, 1913]}, + 326: {'name': 'Effect_Repair_Mule_autocast', 'func_type': 'raw_autocast', 'ability_id': 78, 'general_id': 3685, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_MULE'], 'avail_unit_type_id': [268]}, + 325: {'name': 'Effect_Repair_Mule_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 78, 'general_id': 3685, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_MULE'], 'avail_unit_type_id': [268]}, + 328: {'name': 'Effect_Repair_RepairDrone_autocast', 'func_type': 'raw_autocast', 'ability_id': 3751, 'general_id': 3685, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_REPAIRDRONE'], 'avail_unit_type_id': [1913]}, + 327: {'name': 'Effect_Repair_RepairDrone_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3751, 'general_id': 3685, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_REPAIRDRONE'], 'avail_unit_type_id': [1913]}, + 330: {'name': 'Effect_Repair_SCV_autocast', 'func_type': 'raw_autocast', 'ability_id': 316, 'general_id': 3685, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_SCV'], 'avail_unit_type_id': [45]}, + 329: {'name': 'Effect_Repair_SCV_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 316, 'general_id': 3685, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_SCV'], 'avail_unit_type_id': [45]}, + 331: {'name': 'Effect_Restore_autocast', 'func_type': 'raw_autocast', 'ability_id': 3765, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SHIELDBATTERY'], 'avail_unit_type_id': [1910]}, + 161: {'name': 'Effect_Restore_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3765, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_SHIELDBATTERY'], 'avail_unit_type_id': [1910]}, + 332: {'name': 'Effect_Salvage_quick', 'func_type': 'raw_cmd', 'ability_id': 32, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_BUNKER'], 'avail_unit_type_id': [24]}, + 333: {'name': 'Effect_Scan_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 399, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_ORBITALCOMMAND'], 'avail_unit_type_id': [132]}, + 113: {'name': 'Effect_ShadowStride_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2700, 'general_id': 3687, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_DARKTEMPLAR'], 'avail_unit_type_id': [76]}, + 334: {'name': 'Effect_SpawnChangeling_quick', 'func_type': 'raw_cmd', 'ability_id': 181, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_OVERSEER'], 'avail_unit_type_id': [129]}, + 335: {'name': 'Effect_SpawnLocusts_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2704, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_SWARMHOSTBURROWEDMP', 'ZERG_SWARMHOSTMP'], 'avail_unit_type_id': [493, 494]}, + 336: {'name': 'Effect_SpawnLocusts_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2704, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_SWARMHOSTBURROWEDMP', 'ZERG_SWARMHOSTMP'], 'avail_unit_type_id': [493, 494]}, + 337: {'name': 'Effect_Spray_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3684, 'general_id': 0, 'goal': 'effect', 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['PROTOSS_OBSERVER'], 'avail_unit_type_id': [82]}, + 409: {'name': 'Morph_ThorExplosiveMode_quick', 'func_type': 'raw_cmd', 'ability_id': 2364, 'general_id': 0, 'goal': 'other', 'special_goal': 'morph', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_THORAP'], 'avail_unit_type_id': [691]}, + 410: {'name': 'Morph_ThorHighImpactMode_quick', 'func_type': 'raw_cmd', 'ability_id': 2362, 'general_id': 0, 'goal': 'other', 'special_goal': 'morph', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_THOR'], 'avail_unit_type_id': [52]}, + 411: {'name': 'Morph_Unsiege_quick', 'func_type': 'raw_cmd', 'ability_id': 390, 'general_id': 0, 'goal': 'other', 'special_goal': 'morph', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_SIEGETANKSIEGED'], 'avail_unit_type_id': [32]}, + 412: {'name': 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73]}, + 545: {'name': 'Move_Battlecruiser_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3776, 'general_id': 3794, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_BATTLECRUISER'], 'avail_unit_type_id': [57]}, + 546: {'name': 'Move_Battlecruiser_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3776, 'general_id': 3794, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_BATTLECRUISER'], 'avail_unit_type_id': [57]}, + 547: {'name': 'Move_Move_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 16, 'general_id': 3794, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_BANSHEE', 'TERRAN_BARRACKSFLYING', 'TERRAN_COMMANDCENTERFLYING', 'TERRAN_CYCLONE', 'TERRAN_FACTORYFLYING', 'TERRAN_GHOST', 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73]}, + 548: {'name': 'Move_Move_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 16, 'general_id': 3794, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_BANSHEE', 'TERRAN_BARRACKSFLYING', 'TERRAN_COMMANDCENTERFLYING', 'TERRAN_CYCLONE', 'TERRAN_FACTORYFLYING', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MEDIVAC', 'TERRAN_MULE', 'TERRAN_ORBITALCOMMANDFLYING', 'TERRAN_RAVEN', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_STARPORTFLYING', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'TERRAN_WIDOWMINE', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_BROODLORDCOCOON', 'ZERG_CHANGELING', 'ZERG_CHANGELINGMARINE', 'ZERG_CHANGELINGMARINESHIELD', 'ZERG_CHANGELINGZEALOT', 'ZERG_CHANGELINGZERGLING', 'ZERG_CHANGELINGZERGLINGWINGS', 'ZERG_CORRUPTOR', 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'ZERG_MUTALISK', 'ZERG_OVERLORD', 'ZERG_OVERLORDCOCOON', 'ZERG_OVERLORDTRANSPORT', 'ZERG_OVERSEER', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_ROACHBURROWED', 'ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLERUPROOTED', 'ZERG_SWARMHOSTMP', 'ZERG_TRANSPORTOVERLORDCOCOON', 'ZERG_ULTRALISK', 'ZERG_VIPER', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ADEPTPHASESHIFT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PROBE', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [55, 46, 57, 36, 692, 43, 50, 53, 484, 689, 51, 48, 54, 268, 134, 56, 49, 45, 33, 44, 52, 691, 34, 35, 498, 9, 289, 114, 113, 12, 15, 14, 13, 17, 16, 112, 104, 107, 150, 111, 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'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_BANSHEE', 'TERRAN_BARRACKSFLYING', 'TERRAN_COMMANDCENTERFLYING', 'TERRAN_CYCLONE', 'TERRAN_FACTORYFLYING', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MEDIVAC', 'TERRAN_MULE', 'TERRAN_ORBITALCOMMANDFLYING', 'TERRAN_RAVEN', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_STARPORTFLYING', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'TERRAN_WIDOWMINE', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_BROODLORDCOCOON', 'ZERG_CHANGELING', 'ZERG_CHANGELINGMARINE', 'ZERG_CHANGELINGMARINESHIELD', 'ZERG_CHANGELINGZEALOT', 'ZERG_CHANGELINGZERGLING', 'ZERG_CHANGELINGZERGLINGWINGS', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTEDTERRANSEGG', 'ZERG_INFESTOR', 'ZERG_INFESTORBURROWED', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 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'ZERG_BROODLORDCOCOON', 'ZERG_CHANGELING', 'ZERG_CHANGELINGMARINE', 'ZERG_CHANGELINGMARINESHIELD', 'ZERG_CHANGELINGZEALOT', 'ZERG_CHANGELINGZERGLING', 'ZERG_CHANGELINGZERGLINGWINGS', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTEDTERRANSEGG', 'ZERG_INFESTOR', 'ZERG_INFESTORBURROWED', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMP', 'ZERG_MUTALISK', 'ZERG_OVERLORD', 'ZERG_OVERLORDCOCOON', 'ZERG_OVERLORDTRANSPORT', 'ZERG_OVERSEER', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_ROACHBURROWED', 'ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLERUPROOTED', 'ZERG_SWARMHOSTMP', 'ZERG_TRANSPORTOVERLORDCOCOON', 'ZERG_ULTRALISK', 'ZERG_VIPER', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ADEPTPHASESHIFT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PROBE', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [55, 46, 36, 692, 43, 50, 53, 484, 689, 51, 48, 54, 268, 134, 56, 49, 45, 33, 44, 52, 691, 34, 35, 498, 9, 289, 114, 113, 12, 15, 14, 13, 17, 16, 112, 104, 107, 150, 111, 127, 7, 489, 693, 502, 108, 106, 128, 893, 129, 126, 688, 110, 118, 139, 140, 494, 892, 109, 499, 105, 311, 801, 141, 79, 4, 76, 694, 733, 75, 83, 85, 10, 488, 82, 495, 78, 84, 77, 74, 496, 80, 81, 73]}, + 415: {'name': 'Rally_Building_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 195, 'general_id': 3673, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_BARRACKS', 'TERRAN_BUNKER', 'TERRAN_FACTORY', 'TERRAN_STARPORT', 'ZERG_NYDUSCANAL', 'ZERG_NYDUSNETWORK', 'ZERG_RAVAGERCOCOON', 'PROTOSS_GATEWAY', 'PROTOSS_ROBOTICSFACILITY', 'PROTOSS_STARGATE'], 'avail_unit_type_id': [21, 24, 27, 28, 142, 95, 687, 62, 71, 67]}, + 416: {'name': 'Rally_Building_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 195, 'general_id': 3673, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_BARRACKS', 'TERRAN_BUNKER', 'TERRAN_FACTORY', 'TERRAN_STARPORT', 'ZERG_NYDUSCANAL', 'ZERG_NYDUSNETWORK', 'ZERG_RAVAGERCOCOON', 'PROTOSS_GATEWAY', 'PROTOSS_ROBOTICSFACILITY', 'PROTOSS_STARGATE'], 'avail_unit_type_id': [21, 24, 27, 28, 142, 95, 687, 62, 71, 67]}, + 417: {'name': 'Rally_CommandCenter_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 203, 'general_id': 3690, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_COMMANDCENTER', 'TERRAN_ORBITALCOMMAND', 'TERRAN_PLANETARYFORTRESS'], 'avail_unit_type_id': [18, 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'ZerglingBurrowed'], 'target_type_name': []}, + 3: {'action_name': 'Attack_unit', 'selected_type': [311, 801, 1955, 79, 4, 76, 694, 733, 75, 83, 10, 488, 82, 1911, 495, 78, 66, 84, 894, 77, 1910, 74, 496, 80, 81, 136, 73, 31, 55, 57, 24, 692, 50, 144, 53, 484, 689, 734, 268, 51, 48, 54, 23, 130, 11, 56, 49, 1913, 45, 33, 32, 52, 691, 34, 35, 498, 500, 9, 115, 8, 114, 113, 289, 12, 15, 14, 13, 17, 16, 103, 112, 104, 116, 107, 117, 94, 7, 120, 150, 111, 127, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 98, 139, 99, 140, 494, 493, 109, 131, 499, 105, 119], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 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'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 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'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 12: {'action_name': 'Smart_unit', 'selected_type': [311, 801, 1955, 79, 4, 76, 694, 733, 62, 75, 83, 10, 488, 59, 82, 1911, 495, 78, 66, 84, 894, 71, 77, 1910, 74, 67, 496, 80, 81, 136, 73, 31, 55, 21, 46, 57, 24, 18, 36, 692, 27, 43, 50, 144, 53, 484, 689, 734, 268, 51, 48, 54, 23, 132, 134, 130, 11, 56, 49, 1913, 45, 33, 32, 28, 44, 52, 691, 34, 35, 498, 500, 9, 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'Barracks', 'BarracksFlying', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'Factory', 'FactoryFlying', 'Ghost', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reaper', 'RepairDrone', 'SCV', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 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'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 13: {'action_name': 'Move_pt', 'selected_type': [311, 801, 1955, 79, 4, 76, 694, 733, 75, 83, 10, 488, 82, 1911, 495, 78, 84, 894, 77, 1910, 74, 496, 80, 81, 136, 73, 31, 55, 46, 57, 36, 692, 43, 50, 144, 53, 484, 689, 734, 268, 51, 48, 54, 23, 134, 11, 56, 49, 1913, 45, 33, 32, 44, 52, 691, 34, 35, 498, 500, 9, 115, 8, 114, 113, 289, 12, 15, 14, 13, 17, 16, 103, 112, 104, 116, 107, 117, 94, 7, 120, 150, 111, 127, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 98, 139, 99, 140, 494, 493, 109, 131, 499, 105, 119], 'target_type': [], 'selected_type_name': ['Adept', 'AdeptPhaseShift', 'AssimilatorRich', 'Carrier', 'Colossus', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'HighTemplar', 'Immortal', 'Mothership', 'MothershipCore', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'Probe', 'PylonOvercharged', 'Sentry', 'ShieldBattery', 'Stalker', 'Tempest', 'VoidRay', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'AutoTurret', 'Banshee', 'BarracksFlying', 'Battlecruiser', 'CommandCenterFlying', 'Cyclone', 'FactoryFlying', 'Ghost', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'OrbitalCommandFlying', 'PointDefenseDrone', 'Raven', 'Reaper', 'RepairDrone', 'SCV', 'SiegeTank', 'SiegeTankSieged', 'StarportFlying', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': []}, + 14: {'action_name': 'Move_unit', 'selected_type': [311, 801, 1955, 79, 4, 76, 694, 733, 75, 83, 10, 488, 82, 1911, 495, 78, 84, 894, 77, 1910, 74, 496, 80, 81, 136, 73, 31, 55, 46, 57, 36, 692, 43, 50, 144, 53, 484, 689, 734, 268, 51, 48, 54, 23, 134, 11, 56, 49, 1913, 45, 33, 32, 44, 52, 691, 34, 35, 498, 500, 9, 115, 8, 114, 113, 289, 12, 15, 14, 13, 17, 16, 103, 112, 104, 116, 107, 117, 94, 7, 120, 150, 111, 127, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 98, 139, 99, 140, 494, 493, 109, 131, 499, 105, 119], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Adept', 'AdeptPhaseShift', 'AssimilatorRich', 'Carrier', 'Colossus', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'HighTemplar', 'Immortal', 'Mothership', 'MothershipCore', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'Probe', 'PylonOvercharged', 'Sentry', 'ShieldBattery', 'Stalker', 'Tempest', 'VoidRay', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'AutoTurret', 'Banshee', 'BarracksFlying', 'Battlecruiser', 'CommandCenterFlying', 'Cyclone', 'FactoryFlying', 'Ghost', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'OrbitalCommandFlying', 'PointDefenseDrone', 'Raven', 'Reaper', 'RepairDrone', 'SCV', 'SiegeTank', 'SiegeTankSieged', 'StarportFlying', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 15: {'action_name': 'Patrol_pt', 'selected_type': [311, 801, 1955, 79, 4, 76, 694, 733, 75, 83, 10, 488, 82, 1911, 495, 78, 84, 894, 77, 1910, 74, 496, 80, 81, 136, 73, 31, 55, 46, 57, 36, 692, 43, 50, 144, 53, 484, 689, 734, 268, 51, 48, 54, 23, 134, 11, 56, 49, 1913, 45, 33, 32, 44, 52, 691, 34, 35, 498, 500, 9, 115, 8, 114, 113, 289, 12, 15, 14, 13, 17, 16, 103, 112, 104, 116, 107, 117, 94, 7, 120, 150, 111, 127, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 98, 139, 99, 140, 494, 493, 109, 131, 499, 105, 119], 'target_type': [], 'selected_type_name': ['Adept', 'AdeptPhaseShift', 'AssimilatorRich', 'Carrier', 'Colossus', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'HighTemplar', 'Immortal', 'Mothership', 'MothershipCore', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'Probe', 'PylonOvercharged', 'Sentry', 'ShieldBattery', 'Stalker', 'Tempest', 'VoidRay', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'AutoTurret', 'Banshee', 'BarracksFlying', 'Battlecruiser', 'CommandCenterFlying', 'Cyclone', 'FactoryFlying', 'Ghost', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'OrbitalCommandFlying', 'PointDefenseDrone', 'Raven', 'Reaper', 'RepairDrone', 'SCV', 'SiegeTank', 'SiegeTankSieged', 'StarportFlying', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': []}, + 16: {'action_name': 'Patrol_unit', 'selected_type': [311, 801, 1955, 79, 4, 76, 694, 733, 75, 83, 10, 488, 82, 1911, 495, 78, 84, 894, 77, 1910, 74, 496, 80, 81, 136, 73, 31, 55, 46, 57, 36, 692, 43, 50, 144, 53, 484, 689, 734, 268, 51, 48, 54, 23, 134, 11, 56, 49, 1913, 45, 33, 32, 44, 52, 691, 34, 35, 498, 500, 9, 115, 8, 114, 113, 289, 12, 15, 14, 13, 17, 16, 103, 112, 104, 116, 107, 117, 94, 7, 120, 150, 111, 127, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 98, 139, 99, 140, 494, 493, 109, 131, 499, 105, 119], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Adept', 'AdeptPhaseShift', 'AssimilatorRich', 'Carrier', 'Colossus', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'HighTemplar', 'Immortal', 'Mothership', 'MothershipCore', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'Probe', 'PylonOvercharged', 'Sentry', 'ShieldBattery', 'Stalker', 'Tempest', 'VoidRay', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'AutoTurret', 'Banshee', 'BarracksFlying', 'Battlecruiser', 'CommandCenterFlying', 'Cyclone', 'FactoryFlying', 'Ghost', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'OrbitalCommandFlying', 'PointDefenseDrone', 'Raven', 'Reaper', 'RepairDrone', 'SCV', 'SiegeTank', 'SiegeTankSieged', 'StarportFlying', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 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'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BanelingNest', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'BroodlingEscort', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'CreepTumor', 'CreepTumorBurrowed', 'CreepTumorQueen', 'Drone', 'DroneBurrowed', 'EvolutionChamber', 'Extractor', 'ExtractorRich', 'GreaterSpire', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'HydraliskDen', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Larva', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpawningPool', 'SpineCrawler', 'SpineCrawlerUprooted', 'Spire', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'UltraliskCavern', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': []}, + 107: {'action_name': 'Rally_Units_unit', 'selected_type': [311, 801, 141, 61, 1955, 79, 4, 72, 69, 76, 694, 733, 64, 135, 63, 62, 75, 83, 85, 10, 488, 59, 82, 1911, 495, 78, 66, 84, 60, 894, 70, 71, 77, 1910, 74, 67, 732, 496, 68, 65, 80, 133, 81, 136, 73, 29, 31, 55, 21, 46, 38, 37, 57, 24, 18, 36, 692, 22, 27, 43, 40, 39, 30, 50, 26, 144, 145, 53, 484, 830, 689, 734, 268, 51, 48, 54, 23, 58, 132, 134, 130, 11, 56, 6, 49, 20, 1960, 1913, 45, 25, 33, 32, 28, 44, 42, 41, 19, 47, 5, 52, 691, 34, 35, 498, 500, 9, 115, 8, 96, 114, 113, 289, 143, 12, 15, 14, 13, 17, 16, 103, 112, 87, 137, 138, 104, 116, 90, 88, 1956, 102, 86, 101, 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485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Adept', 'AdeptPhaseShift', 'Archon', 'Assimilator', 'AssimilatorRich', 'Carrier', 'Colossus', 'CyberneticsCore', 'DarkShrine', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'FleetBeacon', 'ForceField', 'Forge', 'Gateway', 'HighTemplar', 'Immortal', 'Interceptor', 'Mothership', 'MothershipCore', 'Nexus', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'Pylon', 'PylonOvercharged', 'RoboticsBay', 'RoboticsFacility', 'Sentry', 'ShieldBattery', 'Stalker', 'Stargate', 'StasisTrap', 'Tempest', 'TemplarArchive', 'TwilightCouncil', 'VoidRay', 'WarpGate', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'Armory', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'BarracksReactor', 'BarracksTechLab', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'EngineeringBay', 'Factory', 'FactoryFlying', 'FactoryReactor', 'FactoryTechLab', 'FusionCore', 'Ghost', 'GhostAcademy', 'GhostAlternate', 'GhostNova', 'Hellion', 'Hellbat', 'KD8Charge', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'Nuke', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reactor', 'Reaper', 'Refinery', 'RefineryRich', 'RepairDrone', 'SCV', 'SensorTower', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'StarportReactor', 'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BanelingNest', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'BroodlingEscort', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'CreepTumor', 'CreepTumorBurrowed', 'CreepTumorQueen', 'Drone', 'DroneBurrowed', 'EvolutionChamber', 'Extractor', 'ExtractorRich', 'GreaterSpire', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'HydraliskDen', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Larva', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpawningPool', 'SpineCrawler', 'SpineCrawlerUprooted', 'Spire', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'UltraliskCavern', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 109: {'action_name': 'Effect_Repair_unit', 'selected_type': [268, 45], 'target_type': [29, 31, 55, 21, 46, 38, 37, 57, 24, 18, 36, 692, 22, 27, 43, 40, 39, 30, 26, 144, 53, 484, 689, 734, 268, 54, 23, 132, 134, 130, 11, 56, 6, 49, 20, 1960, 1913, 45, 25, 33, 32, 28, 44, 42, 41, 19, 47, 5, 52, 691, 34, 35, 498, 500], 'selected_type_name': ['MULE', 'SCV'], 'target_type_name': ['Armory', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'BarracksReactor', 'BarracksTechLab', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'EngineeringBay', 'Factory', 'FactoryFlying', 'FactoryReactor', 'FactoryTechLab', 'FusionCore', 'GhostAcademy', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Medivac', 'MissileTurret', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reactor', 'Reaper', 'Refinery', 'RefineryRich', 'RepairDrone', 'SCV', 'SensorTower', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'StarportReactor', 'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed']}, + 110: {'action_name': 'Effect_MassRecall_pt', 'selected_type': [10, 59], 'target_type': [], 'selected_type_name': ['Mothership', 'Nexus'], 'target_type_name': []}, + 111: {'action_name': 'Effect_Blink_pt', 'selected_type': [74, 76], 'target_type': [], 'selected_type_name': ['Stalker', 'DarkTemplar'], 'target_type_name': []}, + 114: {'action_name': 'Rally_Workers_pt', 'selected_type': [59, 18, 132, 130, 86, 100, 101], 'target_type': [], 'selected_type_name': ['Nexus', 'CommandCenter', 'OrbitalCommand', 'PlanetaryFortress', 'Hatchery', 'Lair', 'Hive'], 'target_type_name': []}, + 115: {'action_name': 'Rally_Workers_unit', 'selected_type': [59, 18, 132, 130, 86, 100, 101], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Nexus', 'CommandCenter', 'OrbitalCommand', 'PlanetaryFortress', 'Hatchery', 'Lair', 'Hive'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 116: {'action_name': 'Research_ProtossAirArmor_quick', 'selected_type': [72], 'target_type': [], 'selected_type_name': ['CyberneticsCore'], 'target_type_name': []}, + 117: {'action_name': 'Research_ProtossAirWeapons_quick', 'selected_type': [72], 'target_type': [], 'selected_type_name': ['CyberneticsCore'], 'target_type_name': []}, + 118: {'action_name': 'Research_ProtossGroundArmor_quick', 'selected_type': [63], 'target_type': [], 'selected_type_name': ['Forge'], 'target_type_name': []}, + 119: {'action_name': 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'Immortal', 'Interceptor', 'Mothership', 'MothershipCore', 'Nexus', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'Pylon', 'PylonOvercharged', 'RoboticsBay', 'RoboticsFacility', 'Sentry', 'ShieldBattery', 'Stalker', 'Stargate', 'StasisTrap', 'Tempest', 'TemplarArchive', 'TwilightCouncil', 'VoidRay', 'WarpGate', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'Armory', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'BarracksReactor', 'BarracksTechLab', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'EngineeringBay', 'Factory', 'FactoryFlying', 'FactoryReactor', 'FactoryTechLab', 'FusionCore', 'Ghost', 'GhostAcademy', 'GhostAlternate', 'GhostNova', 'Hellion', 'Hellbat', 'KD8Charge', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'Nuke', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reactor', 'Reaper', 'Refinery', 'RefineryRich', 'RepairDrone', 'SCV', 'SensorTower', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'StarportReactor', 'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BanelingNest', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'BroodlingEscort', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'CreepTumor', 'CreepTumorBurrowed', 'CreepTumorQueen', 'Drone', 'DroneBurrowed', 'EvolutionChamber', 'Extractor', 'ExtractorRich', 'GreaterSpire', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'HydraliskDen', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Larva', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpawningPool', 'SpineCrawler', 'SpineCrawlerUprooted', 'Spire', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'UltraliskCavern', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': []}, + 157: {'action_name': 'Effect_Feedback_unit', 'selected_type': [75], 'target_type': [129, 75, 111, 499, 1912, 126, 127, 78, 10, 77, 144, 56, 495, 50, 54, 55, 125], 'selected_type_name': ['HighTemplar'], 'target_type_name': ['Overseer', 'HighTemplar', 'Infestor', 'Viper', 'OverseerOversightMode', 'Queen', 'InfestorBurrowed', 'Phoenix', 'Mothership', 'Sentry', 'GhostAlternate', 'Raven', 'Oracle', 'Ghost', 'Medivac', 'Banshee', 'QueenBurrowed']}, 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[56], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 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'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 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'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 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'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 295: {'action_name': 'Effect_AutoTurret_pt', 'selected_type': [56], 'target_type': [], 'selected_type_name': ['Raven'], 'target_type_name': []}, + 296: {'action_name': 'Effect_BlindingCloud_pt', 'selected_type': [499], 'target_type': [], 'selected_type_name': ['Viper'], 'target_type_name': []}, + 297: {'action_name': 'Effect_CalldownMULE_pt', 'selected_type': [132], 'target_type': [], 'selected_type_name': ['OrbitalCommand'], 'target_type_name': []}, + 298: {'action_name': 'Effect_CalldownMULE_unit', 'selected_type': [132], 'target_type': [665, 666, 483, 341, 146, 147, 884, 885, 796, 797, 1961], 'selected_type_name': ['OrbitalCommand'], 'target_type_name': ['LabMineralField', 'LabMineralField750', 'MineralField750', 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'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 301: {'action_name': 'Effect_Charge_unit', 'selected_type': [73], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 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'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 303: {'action_name': 'Effect_Contaminate_unit', 'selected_type': [1912, 129], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 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'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 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'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 304: {'action_name': 'Effect_CorrosiveBile_pt', 'selected_type': [688], 'target_type': [], 'selected_type_name': ['Ravager'], 'target_type_name': []}, + 305: {'action_name': 'Effect_EMP_pt', 'selected_type': [144, 50], 'target_type': [], 'selected_type_name': ['GhostAlternate', 'Ghost'], 'target_type_name': []}, + 307: {'action_name': 'Effect_Explode_quick', 'selected_type': [9, 115], 'target_type': [], 'selected_type_name': ['Baneling', 'BanelingBurrowed'], 'target_type_name': []}, + 308: {'action_name': 'Effect_FungalGrowth_pt', 'selected_type': [111], 'target_type': [], 'selected_type_name': ['Infestor'], 'target_type_name': []}, + 310: {'action_name': 'Effect_GhostSnipe_unit', 'selected_type': [144, 145, 50], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 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'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 311: {'action_name': 'Effect_Heal_unit', 'selected_type': [54], 'target_type': [48, 51, 49], 'selected_type_name': ['Medivac'], 'target_type_name': ['Marine', 'Marauder', 'Reaper']}, + 314: {'action_name': 'Effect_InfestedTerrans_pt', 'selected_type': [111, 127], 'target_type': [], 'selected_type_name': ['Infestor', 'InfestorBurrowed'], 'target_type_name': []}, + 315: {'action_name': 'Effect_InjectLarva_unit', 'selected_type': [126], 'target_type': [100, 101, 86], 'selected_type_name': ['Queen'], 'target_type_name': ['Lair', 'Hive', 'Hatchery']}, + 316: {'action_name': 'Effect_InterferenceMatrix_unit', 'selected_type': [56], 'target_type': [311, 801, 141, 61, 1955, 79, 4, 72, 69, 76, 694, 733, 64, 135, 63, 62, 75, 83, 85, 10, 488, 59, 82, 1911, 495, 78, 66, 84, 60, 894, 70, 71, 77, 1910, 74, 67, 732, 496, 68, 65, 80, 133, 81, 136, 73, 29, 31, 55, 21, 46, 38, 37, 57, 24, 18, 36, 692, 22, 27, 43, 40, 39, 30, 50, 26, 144, 145, 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104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Cyclone'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 319: {'action_name': 'Effect_LocustSwoop_pt', 'selected_type': [693], 'target_type': [], 'selected_type_name': ['LocustFlying'], 'target_type_name': []}, + 320: {'action_name': 'Effect_MedivacIgniteAfterburners_quick', 'selected_type': [54], 'target_type': [], 'selected_type_name': ['Medivac'], 'target_type_name': []}, + 321: {'action_name': 'Effect_NeuralParasite_unit', 'selected_type': [111, 127], 'target_type': [311, 801, 141, 61, 1955, 79, 4, 72, 69, 76, 694, 733, 64, 135, 63, 62, 75, 83, 85, 10, 488, 59, 82, 1911, 495, 78, 66, 84, 60, 894, 70, 71, 77, 1910, 74, 67, 732, 496, 68, 65, 80, 133, 81, 136, 73, 29, 31, 55, 21, 46, 38, 37, 57, 24, 18, 36, 692, 22, 27, 43, 40, 39, 30, 50, 26, 144, 145, 53, 484, 830, 689, 734, 268, 51, 48, 54, 23, 58, 132, 134, 130, 11, 56, 6, 49, 20, 1960, 1913, 45, 25, 33, 32, 28, 44, 42, 41, 19, 47, 5, 52, 691, 34, 35, 498, 500, 9, 115, 8, 96, 114, 113, 289, 143, 12, 15, 14, 13, 17, 16, 103, 112, 87, 137, 138, 104, 116, 90, 88, 1956, 102, 86, 101, 107, 117, 91, 94, 7, 120, 150, 111, 127, 100, 151, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 89, 98, 139, 92, 99, 140, 494, 493, 109, 131, 93, 499, 105, 119], 'selected_type_name': ['Infestor', 'InfestorBurrowed'], 'target_type_name': ['Adept', 'AdeptPhaseShift', 'Archon', 'Assimilator', 'AssimilatorRich', 'Carrier', 'Colossus', 'CyberneticsCore', 'DarkShrine', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'FleetBeacon', 'ForceField', 'Forge', 'Gateway', 'HighTemplar', 'Immortal', 'Interceptor', 'Mothership', 'MothershipCore', 'Nexus', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'Pylon', 'PylonOvercharged', 'RoboticsBay', 'RoboticsFacility', 'Sentry', 'ShieldBattery', 'Stalker', 'Stargate', 'StasisTrap', 'Tempest', 'TemplarArchive', 'TwilightCouncil', 'VoidRay', 'WarpGate', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'Armory', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'BarracksReactor', 'BarracksTechLab', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'EngineeringBay', 'Factory', 'FactoryFlying', 'FactoryReactor', 'FactoryTechLab', 'FusionCore', 'Ghost', 'GhostAcademy', 'GhostAlternate', 'GhostNova', 'Hellion', 'Hellbat', 'KD8Charge', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'Nuke', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reactor', 'Reaper', 'Refinery', 'RefineryRich', 'RepairDrone', 'SCV', 'SensorTower', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'StarportReactor', 'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BanelingNest', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'BroodlingEscort', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'CreepTumor', 'CreepTumorBurrowed', 'CreepTumorQueen', 'Drone', 'DroneBurrowed', 'EvolutionChamber', 'Extractor', 'ExtractorRich', 'GreaterSpire', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'HydraliskDen', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Larva', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpawningPool', 'SpineCrawler', 'SpineCrawlerUprooted', 'Spire', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'UltraliskCavern', 'Viper', 'Zergling', 'ZerglingBurrowed']}, + 322: {'action_name': 'Effect_NukeCalldown_pt', 'selected_type': [144, 145, 50], 'target_type': [], 'selected_type_name': ['GhostAlternate', 'GhostNova', 'Ghost'], 'target_type_name': []}, + 323: {'action_name': 'Effect_ParasiticBomb_unit', 'selected_type': [499], 'target_type': [311, 801, 141, 61, 1955, 79, 4, 72, 69, 76, 694, 733, 64, 135, 63, 62, 75, 83, 85, 10, 488, 59, 82, 1911, 495, 78, 66, 84, 60, 894, 70, 71, 77, 1910, 74, 67, 732, 496, 68, 65, 80, 133, 81, 136, 73, 29, 31, 55, 21, 46, 38, 37, 57, 24, 18, 36, 692, 22, 27, 43, 40, 39, 30, 50, 26, 144, 145, 53, 484, 830, 689, 734, 268, 51, 48, 54, 23, 58, 132, 134, 130, 11, 56, 6, 49, 20, 1960, 1913, 45, 25, 33, 32, 28, 44, 42, 41, 19, 47, 5, 52, 691, 34, 35, 498, 500, 9, 115, 8, 96, 114, 113, 289, 143, 12, 15, 14, 13, 17, 16, 103, 112, 87, 137, 138, 104, 116, 90, 88, 1956, 102, 86, 101, 107, 117, 91, 94, 7, 120, 150, 111, 127, 100, 151, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 89, 98, 139, 92, 99, 140, 494, 493, 109, 131, 93, 499, 105, 119], 'selected_type_name': ['Viper'], 'target_type_name': ['Adept', 'AdeptPhaseShift', 'Archon', 'Assimilator', 'AssimilatorRich', 'Carrier', 'Colossus', 'CyberneticsCore', 'DarkShrine', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'FleetBeacon', 'ForceField', 'Forge', 'Gateway', 'HighTemplar', 'Immortal', 'Interceptor', 'Mothership', 'MothershipCore', 'Nexus', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'Pylon', 'PylonOvercharged', 'RoboticsBay', 'RoboticsFacility', 'Sentry', 'ShieldBattery', 'Stalker', 'Stargate', 'StasisTrap', 'Tempest', 'TemplarArchive', 'TwilightCouncil', 'VoidRay', 'WarpGate', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'Armory', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'BarracksReactor', 'BarracksTechLab', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'EngineeringBay', 'Factory', 'FactoryFlying', 'FactoryReactor', 'FactoryTechLab', 'FusionCore', 'Ghost', 'GhostAcademy', 'GhostAlternate', 'GhostNova', 'Hellion', 'Hellbat', 'KD8Charge', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'Nuke', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reactor', 'Reaper', 'Refinery', 'RefineryRich', 'RepairDrone', 'SCV', 'SensorTower', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'StarportReactor', 'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BanelingNest', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'BroodlingEscort', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'CreepTumor', 'CreepTumorBurrowed', 'CreepTumorQueen', 'Drone', 'DroneBurrowed', 'EvolutionChamber', 'Extractor', 'ExtractorRich', 'GreaterSpire', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'HydraliskDen', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Larva', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpawningPool', 'SpineCrawler', 'SpineCrawlerUprooted', 'Spire', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'UltraliskCavern', 'Viper', 'Zergling', 'ZerglingBurrowed']}, + 332: {'action_name': 'Effect_Salvage_quick', 'selected_type': [24], 'target_type': [], 'selected_type_name': ['Bunker'], 'target_type_name': []}, + 333: {'action_name': 'Effect_Scan_pt', 'selected_type': [132], 'target_type': [], 'selected_type_name': ['OrbitalCommand'], 'target_type_name': []}, + 334: {'action_name': 'Effect_SpawnChangeling_quick', 'selected_type': [1912, 129], 'target_type': [], 'selected_type_name': ['OverseerOversightMode', 'Overseer'], 'target_type_name': []}, + 335: {'action_name': 'Effect_SpawnLocusts_pt', 'selected_type': [493, 494], 'target_type': [], 'selected_type_name': ['SwarmHostBurrowed', 'SwarmHost'], 'target_type_name': []}, + 337: {'action_name': 'Effect_Spray_pt', 'selected_type': [104, 84, 45], 'target_type': [], 'selected_type_name': ['Drone', 'Probe', 'SCV'], 'target_type_name': []}, + 341: {'action_name': 'Effect_Stim_quick', 'selected_type': [48, 24, 51], 'target_type': [], 'selected_type_name': ['Marine', 'Bunker', 'Marauder'], 'target_type_name': []}, + 346: {'action_name': 'Effect_SupplyDrop_unit', 'selected_type': [132], 'target_type': [19, 47], 'selected_type_name': ['OrbitalCommand'], 'target_type_name': ['SupplyDepot', 'SupplyDepotLowered']}, + 347: {'action_name': 'Effect_TacticalJump_pt', 'selected_type': [57], 'target_type': [], 'selected_type_name': ['Battlecruiser'], 'target_type_name': []}, + 348: {'action_name': 'Effect_TimeWarp_pt', 'selected_type': [10], 'target_type': [], 'selected_type_name': ['Mothership'], 'target_type_name': []}, + 349: {'action_name': 'Effect_Transfusion_unit', 'selected_type': [126], 'target_type': [9, 115, 8, 96, 114, 113, 289, 143, 12, 15, 14, 13, 17, 16, 103, 112, 87, 137, 138, 104, 116, 90, 88, 1956, 102, 86, 101, 107, 117, 91, 94, 7, 120, 150, 111, 127, 100, 151, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 89, 98, 139, 92, 99, 140, 494, 493, 109, 131, 93, 499, 105, 119], 'selected_type_name': ['Queen'], 'target_type_name': ['Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BanelingNest', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'BroodlingEscort', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'CreepTumor', 'CreepTumorBurrowed', 'CreepTumorQueen', 'Drone', 'DroneBurrowed', 'EvolutionChamber', 'Extractor', 'ExtractorRich', 'GreaterSpire', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'HydraliskDen', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Larva', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpawningPool', 'SpineCrawler', 'SpineCrawlerUprooted', 'Spire', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 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'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 538: {'action_name': 'Effect_KD8Charge_unit', 'selected_type': [49], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 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732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Reaper'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 553: {'action_name': 'Research_AnabolicSynthesis_quick', 'selected_type': [93], 'target_type': [], 'selected_type_name': ['UltraliskCavern'], 'target_type_name': []}, + 554: {'action_name': 'Research_CycloneLockOnDamage_quick', 'selected_type': [39], 'target_type': [], 'selected_type_name': ['FactoryTechLab'], 'target_type_name': []}, + 556: {'action_name': 'UnloadUnit_quick', 'selected_type': [81, 136, 24, 18, 54, 142, 95, 893, 36, 130], 'target_type': [], 'selected_type_name': ['WarpPrism', 'WarpPrismPhasing', 'Bunker', 'CommandCenter', 'Medivac', 'NydusCanal', 'NydusNetwork', 'OverlordTransport', 'CommandCenterFlying', 'PlanetaryFortress'], 'target_type_name': []}, + 24: {'action_name': 'Hallucination_HighTemplar_quick', 'selected_type': [77], 'target_type': [], 'selected_type_name': ['Sentry'], 'target_type_name': []}, + 93: {'action_name': 'Hallucination_Adept_quick', 'selected_type': [77], 'target_type': [], 'selected_type_name': ['Sentry'], 'target_type_name': []}, + 200: {'action_name': 'Build_Interceptors_autocast', 'selected_type': [79], 'target_type': [], 'selected_type_name': ['Carrier'], 'target_type_name': []}, + 247: {'action_name': 'BurrowUp_autocast', 'selected_type': [115, 117, 119], 'target_type': [], 'selected_type_name': ['BanelingBurrowed', 'HydraliskBurrowed', 'ZerglingBurrowed'], 'target_type_name': []}, + 302: {'action_name': 'Effect_Charge_autocast', 'selected_type': [73], 'target_type': [], 'selected_type_name': ['Zealot'], 'target_type_name': []}, + 312: {'action_name': 'Effect_Heal_autocast', 'selected_type': [54], 'target_type': [], 'selected_type_name': ['Medivac'], 'target_type_name': []}, + 324: {'action_name': 'Effect_Repair_autocast', 'selected_type': [268, 45], 'target_type': [], 'selected_type_name': ['MULE', 'SCV'], 'target_type_name': []}, + 331: {'action_name': 'Effect_Restore_autocast', 'selected_type': [1910], 'target_type': [], 'selected_type_name': ['ShieldBattery'], 'target_type_name': []}, + 541: {'action_name': 'Effect_LockOn_autocast', 'selected_type': [692], 'target_type': [], 'selected_type_name': ['Cyclone'], 'target_type_name': []}, + 544: {'action_name': 'Morph_WarpGate_autocast', 'selected_type': [62], 'target_type': [], 'selected_type_name': ['Gateway'], 'target_type_name': []}, + 112: {'action_name': 'Effect_Blink_unit', 'selected_type': [74, 76], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 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'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 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72, 133, 59, 62, 63], 'selected_type_name': ['Nexus'], 'target_type_name': ['FleetBeacon', 'TwilightCouncil', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'WarpGate', 'Nexus', 'Gateway', 'Forge']}, + 306: {'action_name': 'Effect_EMP_unit', 'selected_type': [144, 145, 50], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 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'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 309: {'action_name': 'Effect_FungalGrowth_unit', 'selected_type': [111], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 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'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 313: {'action_name': 'Effect_ImmortalBarrier_autocast', 'selected_type': [83], 'target_type': [], 'selected_type_name': ['Immortal'], 'target_type_name': []}, + 91: {'action_name': 'Effect_ImmortalBarrier_quick', 'selected_type': [83], 'target_type': [], 'selected_type_name': ['Immortal'], 'target_type_name': []}, + 108: {'action_name': 'Effect_Repair_pt', 'selected_type': [268, 45], 'target_type': [], 'selected_type_name': ['MULE', 'SCV'], 'target_type_name': []}, + 336: {'action_name': 'Effect_SpawnLocusts_unit', 'selected_type': [493, 494], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 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'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 353: {'action_name': 'Effect_WidowMineAttack_autocast', 'selected_type': [498, 500], 'target_type': [], 'selected_type_name': ['WidowMine', 'WidowMineBurrowed'], 'target_type_name': []}, + 351: {'action_name': 'Effect_WidowMineAttack_pt', 'selected_type': [498, 500], 'target_type': [], 'selected_type_name': ['WidowMine', 'WidowMineBurrowed'], 'target_type_name': []}, + 352: {'action_name': 'Effect_WidowMineAttack_unit', 'selected_type': [498, 500], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['WidowMine', 'WidowMineBurrowed'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 392: {'action_name': 'Morph_LurkerDen_quick', 'selected_type': [91], 'target_type': [], 'selected_type_name': ['HydraliskDen'], 'target_type_name': []}, + 393: {'action_name': 'Morph_Mothership_quick', 'selected_type': [488], 'target_type': [], 'selected_type_name': ['MothershipCore'], 'target_type_name': []}, + 435: {'action_name': 'Research_CycloneRapidFireLaunchers_quick', 'selected_type': [39], 'target_type': [], 'selected_type_name': ['FactoryTechLab'], 'target_type_name': []}, + 563: {'action_name': 'Research_EnhancedShockwaves_quick', 'selected_type': [26], 'target_type': [], 'selected_type_name': ['GhostAcademy'], 'target_type_name': []}, + 18: {'action_name': 'Research_InterceptorGravitonCatapult_quick', 'selected_type': [64], 'target_type': [], 'selected_type_name': ['FleetBeacon'], 'target_type_name': []}, + 443: {'action_name': 'Research_NeosteelFrame_quick', 'selected_type': [22], 'target_type': [], 'selected_type_name': ['EngineeringBay'], 'target_type_name': []}, + 449: {'action_name': 'Research_RavenRecalibratedExplosives_quick', 'selected_type': [41], 'target_type': [], 'selected_type_name': ['StarportTechLab'], 'target_type_name': []}, + 513: {'action_name': 'Train_MothershipCore_quick', 'selected_type': [59], 'target_type': [], 'selected_type_name': ['Nexus'], 'target_type_name': []}, +} + +def get_general(general_id): + return {k: v for k, v in ACTION_INFO_MASK.items() if v['ability_id'] == general_id} + + +def merge_judge(target_general_action, val): + ret = [] + for k, v in target_general_action.items(): + if v['target_unit'] != val['target_unit']: + continue + if v['target_location'] != val['target_location']: + continue + if v['func_type'] != val['func_type']: + continue + ret.append(k) + try: + assert(len(ret) == 1) + except AssertionError: + print(target_general_action) + print(val) + print(ret) + return ret[0] + + +GENERAL_ACTION_INFO_MASK = {} +ACT_TO_GENERAL_ACT = {} +ACT_TO_GENERAL_ACT_ARRAY = np.full(max(ACTION_INFO_MASK.keys()) + 1, -1, dtype=np.int) +for k, v in ACTION_INFO_MASK.items(): + general_id = v['general_id'] + if general_id is None or general_id == 0: + GENERAL_ACTION_INFO_MASK[k] = v + ACT_TO_GENERAL_ACT[k] = k + ACT_TO_GENERAL_ACT_ARRAY[k] = k + else: + target_general_action = get_general(general_id) + action_id = merge_judge(target_general_action, v) + ACT_TO_GENERAL_ACT[k] = action_id + ACT_TO_GENERAL_ACT_ARRAY[k] = action_id diff --git a/dizoo/distar/envs/fake_data.py b/dizoo/distar/envs/fake_data.py new file mode 100644 index 0000000000..1b98ddbda7 --- /dev/null +++ b/dizoo/distar/envs/fake_data.py @@ -0,0 +1,306 @@ +from typing import Sequence +import torch + +from .meta import MAX_DELAY, MAX_ENTITY_NUM, NUM_ACTIONS, ENTITY_TYPE_NUM, NUM_UPGRADES, NUM_CUMULATIVE_STAT_ACTIONS, \ + NUM_BEGINNING_ORDER_ACTIONS, NUM_UNIT_MIX_ABILITIES, NUM_QUEUE_ACTION, NUM_BUFFS, NUM_ADDON +#from distar.ctools.data.collate_fn import default_collate_with_dim + +currTrainCount_MAX = 5 +H, W = 152, 160 + + +def hidden_state(): + return [(torch.zeros(size=(128, )), torch.zeros(size=(128, ))) for _ in range(1)] + + +def spatial_info(): + return { + 'height_map': torch.rand(H, W), + 'visibility_map': torch.randint(0, 4, size=(H, W), dtype=torch.float), + 'creep': torch.randint(0, 2, size=(H, W), dtype=torch.float), + 'player_relative': torch.randint(0, 5, size=(H, W), dtype=torch.float), + 'alerts': torch.randint(0, 2, size=(H, W), dtype=torch.float), + 'pathable': torch.randint(0, 2, size=(H, W), dtype=torch.float), + 'buildable': torch.randint(0, 2, size=(H, W), dtype=torch.float), + 'effect_PsiStorm': torch.randint(0, min(H, W), size=(2, ), dtype=torch.float), + 'effect_NukeDot': torch.randint(0, min(H, W), size=(2, ), dtype=torch.float), + 'effect_LiberatorDefenderZone': torch.randint(0, min(H, W), size=(2, ), dtype=torch.float), + 'effect_BlindingCloud': torch.randint(0, min(H, W), size=(2, ), dtype=torch.float), + 'effect_CorrosiveBile': torch.randint(0, min(H, W), size=(2, ), dtype=torch.float), + 'effect_LurkerSpines': torch.randint(0, min(H, W), size=(2, ), dtype=torch.float), + } + + +def entity_info(): + data = { + 'unit_type': torch.randint(0, ENTITY_TYPE_NUM, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'alliance': torch.randint(0, 5, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'cargo_space_taken': torch.randint(0, 9, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'build_progress': torch.rand(MAX_ENTITY_NUM), + 'health_ratio': torch.rand(MAX_ENTITY_NUM), + 'shield_ratio': torch.rand(MAX_ENTITY_NUM), + 'energy_ratio': torch.rand(MAX_ENTITY_NUM), + 'display_type': torch.randint(0, 5, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'x': torch.randint(0, 11, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'y': torch.randint(0, 11, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'cloak': torch.randint(0, 5, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'is_blip': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'is_powered': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'mineral_contents': torch.rand(MAX_ENTITY_NUM), + 'vespene_contents': torch.rand(MAX_ENTITY_NUM), + 'cargo_space_max': torch.randint(0, 9, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'assigned_harvesters': torch.randint(0, 24, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'weapon_cooldown': torch.randint(0, 32, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'order_length': torch.randint(0, 9, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'order_id_0': torch.randint(0, NUM_ACTIONS, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'order_id_1': torch.randint(0, NUM_QUEUE_ACTION, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'is_hallucination': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'buff_id_0': torch.randint(0, NUM_BUFFS, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'buff_id_1': torch.randint(0, NUM_BUFFS, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'addon_unit_type': torch.randint(0, NUM_ADDON, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'is_active': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'order_progress_0': torch.rand(MAX_ENTITY_NUM), + 'order_progress_1': torch.rand(MAX_ENTITY_NUM), + 'order_id_2': torch.randint(0, NUM_QUEUE_ACTION, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'order_id_3': torch.randint(0, NUM_QUEUE_ACTION, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'is_in_cargo': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'attack_upgrade_level': torch.randint(0, 4, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'armor_upgrade_level': torch.randint(0, 4, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'shield_upgrade_level': torch.randint(0, 4, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'last_selected_units': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'last_targeted_unit': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + } + return data + + +def scalar_info(): + data = { + 'home_race': torch.randint(0, 4, size=(), dtype=torch.float), + 'away_race': torch.randint(0, 4, size=(), dtype=torch.float), + 'agent_statistics': torch.rand(10), + 'time': torch.randint(0, 100, size=(), dtype=torch.float), + 'unit_counts_bow': torch.randint(0, 10, size=(ENTITY_TYPE_NUM, ), dtype=torch.float), + 'beginning_build_order': torch.randint(0, 20, size=(20, ), dtype=torch.float), + 'cumulative_stat': torch.randint(0, 2, size=(NUM_CUMULATIVE_STAT_ACTIONS, ), dtype=torch.float), + 'last_delay': torch.randint(0, MAX_DELAY, size=(), dtype=torch.float), + 'last_queued': torch.randint(0, 2, size=(), dtype=torch.float), + 'last_action_type': torch.randint(0, NUM_ACTIONS, size=(), dtype=torch.float), + 'upgrades': torch.randint(0, 2, size=(NUM_UPGRADES, ), dtype=torch.float), + 'beginning_order': torch.randint(0, NUM_BEGINNING_ORDER_ACTIONS, size=(20, ), dtype=torch.float), + 'bo_location': torch.randint(0, 100*100, size=(20, ), dtype=torch.float), + 'unit_type_bool': torch.randint(0, 2, size=(ENTITY_TYPE_NUM, ), dtype=torch.float), + 'enemy_unit_type_bool': torch.randint(0, 2, size=(ENTITY_TYPE_NUM, ), dtype=torch.float), + 'unit_order_type': torch.randint(0, 2, size=(NUM_UNIT_MIX_ABILITIES, ), dtype=torch.float) + } + return data + + +def action_info(): + data = { + 'action_type': torch.randint(0, NUM_ACTIONS, size=(), dtype=torch.long), + 'delay': torch.randint(0, MAX_DELAY, size=(), dtype=torch.long), + 'selected_units': torch.randint(0, 5, size=(MAX_SELECTED_UNITS_NUM, ), dtype=torch.long), + 'target_unit': torch.randint(0, MAX_ENTITY_NUM, size=(), dtype=torch.long), + 'target_location': torch.randint(0, SPATIAL_SIZE, size=(), dtype=torch.long) + } + return data + + +def action_mask(): + data = { + 'action_type': torch.randint(0, 1, size=(), dtype=torch.long), + 'delay': torch.randint(0, 1, size=(), dtype=torch.long), + 'selected_units': torch.randint(0, 1, size=(), dtype=torch.long), + 'target_unit': torch.randint(0, 1, size=(), dtype=torch.long), + 'target_location': torch.randint(0, 1, size=(), dtype=torch.long) + } + return data + + +def action_logp(): + data = { + 'action_type': torch.rand(size=()) + 2, + 'delay': torch.rand(size=()) + 2, + 'selected_units': torch.rand(size=(MAX_SELECTED_UNITS_NUM, )) + 2, + 'target_unit': torch.rand(size=()) + 2, + 'target_location': torch.rand(size=()) + 2 + } + return data + + +def action_logits(): + data = { + 'action_type': torch.rand(size=(NUM_ACTIONS + 1, )) - 1, + 'delay': torch.rand(size=(MAX_DELAY, )) - 1, + 'selected_units': torch.rand(size=(MAX_SELECTED_UNITS_NUM, MAX_ENTITY_NUM + 1)) - 1, + 'target_unit': torch.rand(size=(MAX_ENTITY_NUM, )) - 1, + 'target_location': torch.rand(size=(16384, )) - 1 + } + + mask = dict() + mask['selected_units_logits_mask'] = data['selected_units'].sum(0) + mask['target_units_logits_mask'] = data['target_unit'] + mask['actions_mask'] = {k: val.sum() for k, val in data.items()} + mask['selected_units_mask'] = data['selected_units'].sum(-1) + + return data, mask + + +def fake_step_data(): + data = ( + spatial_info(), + entity_info(), + scalar_info(), + action_info(), + action_mask(), + torch.randint(5, 100, size=(1, ), dtype=torch.long), # entity num + torch.randint(0, MAX_SELECTED_UNITS_NUM, size=(), dtype=torch.long), # selected_units_num + torch.randint(0, SPATIAL_SIZE, size=(512, 2), dtype=torch.long) # entity location + ) + return data + + +def fake_inference_data(): + data = ( + spatial_info(), + entity_info(), + scalar_info(), + torch.randint(5, 100, size=(1, ), dtype=torch.long), # entity_num + torch.randint(0, SPATIAL_SIZE, size=(512, 2), dtype=torch.long), # entity_location + ) + return data + + +def rl_step_data(): + teacher_action_logits, mask = action_logits() + data = { + 'spatial_info': spatial_info(), + 'entity_info': entity_info(), + 'scalar_info': scalar_info(), + 'entity_num': torch.randint(5, 100, size=(1, ), dtype=torch.long), + 'selected_units_num': torch.randint(0, MAX_SELECTED_UNITS_NUM, size=(), dtype=torch.long), + 'entity_location': torch.randint(0, SPATIAL_SIZE, size=(512, 2), dtype=torch.long), + 'hidden_state': [(torch.zeros(size=(128, )), torch.zeros(size=(128, ))) for _ in range(1)], # hidden state + 'action_info': action_info(), + 'behaviour_logp': action_logp(), + 'teacher_logit': teacher_action_logits, + 'reward': { + 'winloss': torch.randint(-1, 1, size=(), dtype=torch.float), + 'build_order': torch.randint(-1, 1, size=(), dtype=torch.float), + 'built_unit': torch.randint(-1, 1, size=(), dtype=torch.float), + 'effect': torch.randint(-1, 1, size=(), dtype=torch.float), + 'upgrade': torch.randint(-1, 1, size=(), dtype=torch.float), + 'battle': torch.randint(-1, 1, size=(), dtype=torch.float), + }, + 'step': torch.randint(100, 1000, size=(), dtype=torch.long), + 'mask': mask, + } + return data + + +def transfer_data(data, cuda=False, share_memory=False, device=None): + assert cuda or share_memory + new_data = [] + for d in data: + if isinstance(d, torch.Tensor): + if cuda: + d = d.to(device) + if share_memory: + d.share_memory_() + new_data.append(d) + elif isinstance(d, dict): + if cuda: + d = {k: v.to(device) for k, v in d.items()} + if share_memory: + d = {k: v.share_memory_() for k, v in d.items()} + new_data.append(d) + return tuple(new_data) + + +def fake_step_data_share_memory(): + data = fake_step_data() + data = transfer_data(data) + return data + + +def fake_rl_data_batch(batch_size=1): + list_step_data = [] + # list_hidden_state = [] + for i in range(batch_size): + step_data = rl_step_data() + # hidden_state = step_data.pop('hidden_state') + list_step_data.append(step_data) + # list_hidden_state.append(hidden_state) + + step_data_batch = default_collate_with_dim(list_step_data) + # hidden_state_batch = default_collate_with_dim(list_hidden_state,dim=0) + batch = step_data_batch + # batch['hidden_state'] = hidden_state_batch + return batch + + +def fake_rl_data_batch_with_last(unroll_len=3): + list_step_data = [] + # list_hidden_state = [] + for i in range(unroll_len): + step_data = rl_step_data() + # hidden_state = step_data.pop('hidden_state') + list_step_data.append(step_data) + # list_hidden_state.append(hidden_state) + last_step_data = { + 'spatial_info': spatial_info(), + 'entity_info': entity_info(), + 'scalar_info': scalar_info(), + 'entity_num': torch.randint(5, 100, size=(1, ), dtype=torch.long), + # 'selected_units_num': torch.randint(0, MAX_SELECTED_UNITS_NUM, size=(), dtype=torch.long), + 'entity_location': torch.randint(0, SPATIAL_SIZE, size=(512, 2), dtype=torch.long), + 'hidden_state': [(torch.zeros(size=(128, )), torch.zeros(size=(128, ))) for _ in range(1)], # hidden state + } + list_step_data.append(last_step_data) + step_data_batch = default_collate_with_dim(list_step_data) + # hidden_state_batch = default_collate_with_dim(list_hidden_state,dim=0) + batch = step_data_batch + # batch['hidden_state'] = hidden_state_batch + return batch + + +def fake_rl_learner_data_batch(batch_size=6, unroll_len=4): + data_batch_list = [fake_rl_data_batch_with_last(unroll_len) for _ in range(batch_size)] + data_batch = default_collate_with_dim(data_batch_list, dim=1) + return data_batch + + +def flat(data): + if isinstance(data, torch.Tensor): + return torch.flatten(data, start_dim=0, end_dim=1) # (1, (T+1) * B) + elif isinstance(data, dict): + new_data = {} + for k, val in data.items(): + new_data[k] = flat(val) + return new_data + elif isinstance(data, Sequence): + new_data = [flat(v) for v in data] + return new_data + else: + print(type(data)) + + +def rl_learner_forward_data(batch_size=6, unroll_len=4): + data = fake_rl_learner_data_batch(batch_size, unroll_len) + new_data = {} + for k, val in data.items(): + if k in [ + 'spatial_info', + 'entity_info', + 'scalar_info', + 'entity_num', # 'action_info' + # 'selected_units_num', + 'entity_location', + 'hidden_state', + ]: + new_data[k] = flat(val) + else: + new_data[k] = val + new_data['batch_size'] = batch_size + new_data['unroll_len'] = unroll_len + return new_data diff --git a/dizoo/distar/envs/meta.py b/dizoo/distar/envs/meta.py new file mode 100644 index 0000000000..6eb39b1661 --- /dev/null +++ b/dizoo/distar/envs/meta.py @@ -0,0 +1,11 @@ +MAX_DELAY = 64 +MAX_ENTITY_NUM = 512 +ENTITY_TYPE_NUM = 260 +NUM_ACTIONS = 327 +NUM_UPGRADES = 90 +NUM_CUMULATIVE_STAT_ACTIONS = 167 +NUM_BEGINNING_ORDER_ACTIONS = 174 +NUM_UNIT_MIX_ABILITIES = 269 +NUM_QUEUE_ACTION = 49 +NUM_BUFFS = 50 +NUM_ADDON = 9 diff --git a/dizoo/distar/envs/static_data.py b/dizoo/distar/envs/static_data.py new file mode 100644 index 0000000000..a0674c7bb1 --- /dev/null +++ b/dizoo/distar/envs/static_data.py @@ -0,0 +1,1152 @@ +# Copyright 2017 Google Inc. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS-IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Expose static data in a more useful form than the raw protos.""" + +import six +import torch +import numpy as np +from .action_dict import ACTION_INFO_MASK, GENERAL_ACTION_INFO_MASK, ACTIONS_STAT + + +class StaticData(object): + """Expose static data in a more useful form than the raw protos.""" + + def __init__(self, data): + """Takes data from RequestData.""" + self._units = {u.unit_id: u.name for u in data.units} + self._unit_stats = {u.unit_id: u for u in data.units} + self._upgrades = {a.upgrade_id: a for a in data.upgrades} + self._abilities = {a.ability_id: a for a in data.abilities} + self._general_abilities = {a.remaps_to_ability_id for a in data.abilities if a.remaps_to_ability_id} + + for a in six.itervalues(self._abilities): + a.hotkey = a.hotkey.lower() + + @property + def abilities(self): + return self._abilities + + @property + def upgrades(self): + return self._upgrades + + @property + def units(self): + return self._units + + @property + def unit_stats(self): + return self._unit_stats + + @property + def general_abilities(self): + return self._general_abilities + + +def get_reorder_lookup_array(input): + num = max(input) + # use -1 as marker for invalid entry + array = torch.full((num + 1, ), -1, dtype=torch.long) + for index, item in enumerate(input): + array[item] = index + return array + + +# List of used/available abilities found by parsing replays. +ABILITIES = [ + 0, # invalid + 1, + 4, + 6, + 7, + 16, + 17, + 18, + 19, + 23, + 26, + 28, + 30, + 32, + 36, + 38, + 42, + 44, + 46, + 74, + 76, + 78, + 80, + 110, + 140, + 142, + 144, + 146, + 148, + 150, + 152, + 154, + 156, + 158, + 160, + 162, + 164, + 166, + 167, + 169, + 171, + 173, + 174, + 181, + 195, + 199, + 203, + 207, + 211, + 212, + 216, + 217, + 247, + 249, + 250, + 251, + 253, + 255, + 261, + 263, + 265, + 295, + 296, + 298, + 299, + 304, + 305, + 306, + 307, + 308, + 309, + 312, + 313, + 314, + 315, + 316, + 318, + 319, + 320, + 321, + 322, + 323, + 324, + 326, + 327, + 328, + 329, + 331, + 333, + 348, + 380, + 382, + 383, + 386, + 388, + 390, + 392, + 393, + 394, + 396, + 397, + 399, + 401, + 403, + 405, + 407, + 408, + 410, + 413, + 415, + 416, + 417, + 419, + 421, + 422, + 451, + 452, + 454, + 455, + 484, + 485, + 487, + 488, + 517, + 518, + 520, + 522, + 524, + 554, + 556, + 558, + 560, + 561, + 562, + 563, + 591, + 594, + 595, + 596, + 597, + 614, + 620, + 621, + 622, + 623, + 624, + 626, + 650, + 651, + 652, + 653, + 654, + 655, + 656, + 657, + 658, + 710, + 730, + 731, + 732, + 761, + 764, + 766, + 768, + 769, + 790, + 793, + 799, + 803, + 804, + 805, + 820, + 822, + 855, + 856, + 857, + 861, + 862, + 863, + 864, + 865, + 866, + 880, + 881, + 882, + 883, + 884, + 885, + 886, + 887, + 889, + 890, + 891, + 892, + 893, + 894, + 895, + 911, + 913, + 914, + 916, + 917, + 919, + 920, + 921, + 922, + 946, + 948, + 950, + 954, + 955, + 976, + 977, + 978, + 979, + 994, + 1006, + 1036, + 1038, + 1039, + 1042, + 1062, + 1063, + 1064, + 1065, + 1066, + 1067, + 1068, + 1069, + 1070, + 1093, + 1094, + 1097, + 1126, + 1152, + 1154, + 1155, + 1156, + 1157, + 1158, + 1159, + 1160, + 1161, + 1162, + 1163, + 1165, + 1166, + 1167, + 1183, + 1184, + 1186, + 1187, + 1188, + 1189, + 1190, + 1191, + 1192, + 1193, + 1194, + 1216, + 1217, + 1218, + 1219, + 1220, + 1221, + 1223, + 1225, + 1252, + 1253, + 1282, + 1283, + 1312, + 1313, + 1314, + 1315, + 1316, + 1317, + 1342, + 1343, + 1344, + 1345, + 1346, + 1348, + 1351, + 1352, + 1353, + 1354, + 1356, + 1372, + 1373, + 1374, + 1376, + 1378, + 1380, + 1382, + 1384, + 1386, + 1388, + 1390, + 1392, + 1394, + 1396, + 1406, + 1408, + 1409, + 1413, + 1414, + 1416, + 1417, + 1418, + 1419, + 1433, + 1435, + 1437, + 1438, + 1440, + 1442, + 1444, + 1446, + 1448, + 1449, + 1450, + 1451, + 1454, + 1455, + 1482, + 1512, + 1514, + 1516, + 1517, + 1518, + 1520, + 1522, + 1524, + 1526, + 1528, + 1530, + 1532, + 1562, + 1563, + 1564, + 1565, + 1566, + 1567, + 1568, + 1592, + 1593, + 1594, + 1622, + 1623, + 1628, + 1632, + 1664, + 1682, + 1683, + 1684, + 1691, + 1692, + 1693, + 1694, + 1725, + 1727, + 1729, + 1730, + 1731, + 1732, + 1733, + 1763, + 1764, + 1766, + 1768, + 1819, + 1825, + 1831, + 1832, + 1833, + 1834, + 1847, + 1848, + 1853, + 1974, + 1978, + 1998, + 2014, + 2016, + 2048, + 2057, + 2063, + 2067, + 2073, + 2081, + 2082, + 2095, + 2097, + 2099, + 2108, + 2110, + 2112, + 2113, + 2114, + 2116, + 2146, + 2162, + 2244, + 2324, + 2328, + 2330, + 2331, + 2332, + 2333, + 2338, + 2340, + 2342, + 2346, + 2350, + 2354, + 2358, + 2362, + 2364, + 2365, + 2368, + 2370, + 2371, + 2373, + 2375, + 2376, + 2387, + 2389, + 2391, + 2393, + 2505, + 2535, + 2542, + 2544, + 2550, + 2552, + 2558, + 2560, + 2588, + 2594, + 2596, + 2700, + 2704, + 2708, + 2709, + 2714, + 2720, + 3707, + 3709, + 3739, + 3741, + 3743, + 3745, + 3747, + 3749, + 3751, + 3753, + 3755, + 3757, + 3765, + 3771, + 3776, + 3777, + 3778, + 3783, +] + +# 356, 503, 547, 360, 515, 193, 10, 197, 528, 495, 516, 184, 491, 190, 483, # TODO +# 498, 192, 215, 189, 437, 519, 514, 219, 198, 507, 204, 400, 349, 492, 431, +# 543, 201, 387, 442, 479, 551, 489, 425, 218, 447, 238, 220, 501, 391, 445, +# 438, 526, 350, 256, 494, 493, + +NUM_ABILITIES = len(ABILITIES) + +ABILITIES_REORDER = {item: idx for idx, item in enumerate(ABILITIES)} + +ABILITIES_REORDER_ARRAY = get_reorder_lookup_array(ABILITIES) + +# List of known unit types. It is generated by parsing replays and from: +# https://github.com/Blizzard/s2client-api/blob/master/include/sc2api/sc2_typeenums.h +UNIT_TYPES = [ + 0, + 4, + 5, + 6, + 7, + 8, + 9, + 10, + 11, + 12, + 13, + 14, + 15, + 16, + 17, + 18, + 19, + 20, + 21, + 22, + 23, + 24, + 25, + 26, + 27, + 28, + 29, + 30, + 31, + 32, + 33, + 34, + 35, + 36, + 37, + 38, + 39, + 40, + 41, + 42, + 43, + 44, + 45, + 46, + 47, + 48, + 49, + 50, + 51, + 52, + 53, + 54, + 55, + 56, + 57, + 58, + 59, + 60, + 61, + 62, + 63, + 64, + 65, + 66, + 67, + 68, + 69, + 70, + 71, + 72, + 73, + 74, + 75, + 76, + 77, + 78, + 79, + 80, + 81, + 82, + 83, + 84, + 85, + 86, + 87, + 88, + 89, + 90, + 91, + 92, + 93, + 94, + 95, + 96, + 97, + 98, + 99, + 100, + 101, + 102, + 103, + 104, + 105, + 106, + 107, + 108, + 109, + 110, + 111, + 112, + 113, + 114, + 115, + 116, + 117, + 118, + 119, + 120, + 125, + 126, + 127, + 128, + 129, + 130, + 131, + 132, + 133, + 134, + 135, + 136, + 137, + 138, + 139, + 140, + 141, + 142, + 143, + 144, + 145, + 146, + 147, + 149, + 150, + 151, + 268, + 289, + 311, + 321, + 322, + 324, + 330, + 335, + 336, + 341, + 342, + 343, + 344, + 350, + 364, + 365, + 371, + 372, + 373, + 376, + 377, + 472, + 473, + 474, + 475, + 483, + 484, + 485, + 486, + 487, + 488, + 489, + 490, + 493, + 494, + 495, + 496, + 498, + 499, + 500, + 501, + 502, + 503, + 504, + 517, + 518, + 559, + 560, + 561, + 562, + 563, + 564, + 588, + 589, + 590, + 591, + 608, + 609, + 610, + 612, + 628, + 629, + 630, + 638, + 639, + 640, + 641, + 642, + 643, + 648, + 649, + 651, + 661, + 662, + 663, + 664, + 665, + 666, + 687, + 688, + 689, + 690, + 691, + 692, + 693, + 694, + 732, + 733, + 734, + 796, + 797, + 801, + 824, + 830, + 877, + 880, + 881, + 884, + 885, + 886, + 887, + 892, + 893, + 894, + 1904, + 1908, + 1910, + 1911, + 1912, + 1913, + 1955, + 1956, + 1957, + 1958, + 1960, + 1961, +] + +UNIT_TYPES_REORDER = {item: idx for idx, item in enumerate(UNIT_TYPES)} + +NUM_UNIT_TYPES = len(UNIT_TYPES) + +UNIT_TYPES_REORDER_ARRAY = get_reorder_lookup_array(UNIT_TYPES) + +# List of used buffs found by parsing replays. +BUFFS = [ + 0, # TODO + 5, + 6, + 7, + 8, + 11, + 12, + 13, + 16, + 17, + 18, + 22, + 24, + 25, + 27, + 28, + 29, + 30, + 33, + 36, + 38, + 49, + 59, + 83, + 89, + 99, + 102, + 116, + 121, + 122, + 129, + 132, + 133, + 134, + 136, + 137, + 145, + 271, + 272, + 273, + 274, + 275, + 277, + 279, + 280, + 281, + 288, + 289, + 20, + 97, +] + +NUM_BUFFS = len(BUFFS) + +BUFFS_REORDER = {item: idx for idx, item in enumerate(BUFFS)} + +BUFFS_REORDER_ARRAY = get_reorder_lookup_array(BUFFS) + +# List of used upgrades found by parsing replays. +UPGRADES = [ + 0, + 1, + 2, + 3, + 4, + 5, + 6, + 7, + 8, + 9, + 10, + 11, + 12, + 13, + 15, + 16, + 17, + 19, + 20, + 22, + 25, + 30, + 31, + 32, + 36, + 37, + 38, + 39, + 40, + 41, + 42, + 43, + 44, + 45, + 46, + 47, + 48, + 49, + 50, + 52, + 53, + 54, + 55, + 56, + 57, + 58, + 59, + 60, + 61, + 62, + 64, + 65, + 66, + 68, + 69, + 70, + 71, + 72, + 73, + 74, + 75, + 76, + 78, + 79, + 80, + 81, + 82, + 83, + 84, + 86, + 87, + 88, + 99, + 101, + 116, + 117, + 118, + 122, + 130, + 134, + 135, + 136, + 139, + 140, + 141, + 144, + 289, + 291, + 293, + 296, +] + +NUM_UPGRADES = len(UPGRADES) + +UPGRADES_REORDER = {item: idx for idx, item in enumerate(UPGRADES)} + +UPGRADES_REORDER_ARRAY = get_reorder_lookup_array(UPGRADES) + +UPGRADES_REORDER_INV = {v: k for k, v in UPGRADES_REORDER.items()} + +UPGRADES_REORDER_INV_ARRAY = UPGRADES + +ADDON = [0, 5, 6, 37, 38, 39, 40, 41, 42] + +NUM_ADDON = len(ADDON) + +ADDON_REORDER = {item: idx for idx, item in enumerate(ADDON)} + +ADDON_REORDER_ARRAY = get_reorder_lookup_array(ADDON) + +ACTIONS = list(GENERAL_ACTION_INFO_MASK.keys()) + +NUM_ACTIONS = len(ACTIONS) + +NUM_ACTIONS_RAW = len(list(ACTION_INFO_MASK.keys())) + +# this is for the translation from distar.ctools.pysc2 ability id to distar.ctools.pysc2 raw ability id +# _FUNCTIONS: +# https://github.com/deepmind/ctools.pysc2/blob/5ca04dbf6dd0b852966418379e2d95d9ad3393f8/ctools.pysc2/lib/actions.py#L583 +# _RAW_FUNCTIONS: +# https://github.com/deepmind/ctools.pysc2/blob/5ca04dbf6dd0b852966418379e2d95d9ad3393f8/ctools.pysc2/lib/actions.py#L1186 +# ACTIONS_REORDER[ctools.pysc2_ability_id] = distar.ctools.pysc2_raw_ability_id +ACTIONS_REORDER = {item: idx for idx, item in enumerate(ACTIONS)} + +ACTIONS_REORDER_ARRAY = get_reorder_lookup_array(ACTIONS) + +ACTIONS_REORDER_INV = {v: k for k, v in ACTIONS_REORDER.items()} + +ACTIONS_REORDER_INV_ARRAY = ACTIONS + +# Begin actions: actions (raw ability ids) included in the beginning_build_order +target_list = ['unit', 'build', 'research'] +BEGIN_ACTIONS = [k for k, v in GENERAL_ACTION_INFO_MASK.items() if v['goal'] in target_list] +OLD_BEGIN_ACTIONS = [k for k, v in GENERAL_ACTION_INFO_MASK.items() if v['goal'] in target_list + ['effect']] + +removed_actions = [35, 64, 520, 222, 515, 503] +for i in removed_actions: + BEGIN_ACTIONS.remove(i) +NUM_BEGIN_ACTIONS = len(BEGIN_ACTIONS) + +OLD_BEGIN_ACTIONS_REORDER = {item: idx for idx, item in enumerate(OLD_BEGIN_ACTIONS)} + +OLD_BEGIN_ACTIONS_REORDER_INV = {v: k for k, v in OLD_BEGIN_ACTIONS_REORDER.items()} + +BUILD_ORDER_REWARD_ACTIONS = BEGIN_ACTIONS + +BEGIN_ACTIONS_REORDER_ARRAY = get_reorder_lookup_array(BEGIN_ACTIONS) + +UNIT_BUILD_ACTIONS = [k for k, v in GENERAL_ACTION_INFO_MASK.items() if v['goal'] in ['unit', 'build']] + +NUM_UNIT_BUILD_ACTIONS = len(UNIT_BUILD_ACTIONS) + +UNIT_BUILD_ACTIONS_REORDER = {item: idx for idx, item in enumerate(UNIT_BUILD_ACTIONS)} + +UNIT_BUILD_ACTIONS_REORDER_ARRAY = get_reorder_lookup_array(UNIT_BUILD_ACTIONS) + +EFFECT_ACTIONS = [k for k, v in GENERAL_ACTION_INFO_MASK.items() if v['goal'] in ['effect']] + +NUM_EFFECT_ACTIONS = len(EFFECT_ACTIONS) + +EFFECT_ACTIONS_REORDER = {item: idx for idx, item in enumerate(EFFECT_ACTIONS)} + +EFFECT_ACTIONS_REORDER_ARRAY = get_reorder_lookup_array(EFFECT_ACTIONS) + +RESEARCH_ACTIONS = [k for k, v in GENERAL_ACTION_INFO_MASK.items() if v['goal'] in ['research']] + +NUM_RESEARCH_ACTIONS = len(RESEARCH_ACTIONS) + +RESEARCH_ACTIONS_REORDER = {item: idx for idx, item in enumerate(RESEARCH_ACTIONS)} + +RESEARCH_ACTIONS_REORDER_ARRAY = get_reorder_lookup_array(RESEARCH_ACTIONS) + +ORDER_ACTIONS = [ + 425, 85, 426, 553, 427, 428, 429, 84, 430, 431, 83, 432, 433, 434, 554, 435, 436, 563, 69, 437, 67, 68, 438, 440, + 439, 441, 18, 442, 443, 444, 445, 446, 19, 447, 116, 117, 118, 119, 120, 70, 448, 449, 97, 450, 451, 452, 456, 460, + 464, 465, 469, 473, 82, 474, 478, 482, 494, 495, 486, 490, 54, 499, 500, 56, 62, 501, 502, 52, 166, 504, 505, 506, + 51, 63, 509, 510, 511, 512, 513, 21, 61, 58, 55, 64, 516, 517, 518, 520, 53, 521, 50, 59, 523, 525, 57, 76, 74, 73, + 60, 75, 72, 71, 527, 49 +] + +NUM_ORDER_ACTIONS = len(ORDER_ACTIONS) + 1 +ORDER_ACTIONS_REORDER_ARRAY = torch.zeros(max(GENERAL_ACTION_INFO_MASK.keys()) + 1, dtype=torch.long) +for idx, v in enumerate(ORDER_ACTIONS): + ORDER_ACTIONS_REORDER_ARRAY[v] = idx + 1 + + +def ger_reorder_tag(val, template): + low = 0 + high = len(template) + while low < high: + mid = (low + high) // 2 + mid_val = template[mid] + if val == mid_val: + return mid + elif val > mid_val: + low = mid + 1 + else: + high = mid + raise ValueError("unknow found val: {}".format(val)) + + +SELECTED_UNITS_MASK = torch.zeros(NUM_ACTIONS, NUM_UNIT_TYPES) +TARGET_UNITS_MASK = torch.zeros(NUM_ACTIONS, NUM_UNIT_TYPES) +for i in range(NUM_ACTIONS): + a = ACTIONS_REORDER_INV[i] + type_set = set(ACTIONS_STAT[a]['selected_type']) + reorder_type_list = [UNIT_TYPES_REORDER[i] for i in type_set] + SELECTED_UNITS_MASK[i, reorder_type_list] = 1 + type_set = set(ACTIONS_STAT[a]['target_type']) + reorder_type_list = [UNIT_TYPES_REORDER[i] for i in type_set] + TARGET_UNITS_MASK[i, reorder_type_list] = 1 + +UNIT_SPECIFIC_ABILITIES = [ + 4, 6, 7, 9, 2063, 16, 17, 18, 19, 2067, 23, 2073, 26, 28, 30, 2081, 36, 38, 40, 42, 46, 2095, 2097, 2099, 2108, + 2110, 2116, 74, 76, 78, 80, 2146, 110, 140, 142, 146, 148, 152, 154, 166, 167, 173, 181, 2244, 216, 217, 247, 249, + 251, 253, 263, 265, 2324, 2330, 2332, 2338, 2340, 2342, 295, 296, 2346, 298, 299, 2350, 2358, 2362, 316, 2364, 318, + 319, 320, 321, 322, 323, 324, 2370, 326, 2375, 2376, 327, 328, 329, 331, 333, 2383, 2385, 2387, 2393, 380, 382, 383, + 386, 388, 390, 392, 393, 394, 396, 397, 401, 403, 405, 407, 412, 413, 416, 417, 419, 421, 422, 452, 454, 455, 2505, + 485, 487, 488, 2536, 2542, 2544, 2554, 2556, 2558, 2560, 518, 520, 522, 524, 2588, 2594, 2596, 554, 556, 558, 560, + 561, 562, 563, 591, 594, 595, 596, 597, 614, 620, 621, 622, 623, 624, 626, 650, 651, 652, 653, 654, 2700, 656, 657, + 2706, 658, 2708, 2704, 2714, 2720, 710, 730, 731, 732, 761, 764, 766, 769, 790, 793, 799, 804, 805, 820, 855, 856, + 857, 861, 862, 863, 864, 865, 866, 880, 881, 882, 883, 884, 885, 886, 887, 889, 890, 891, 892, 893, 894, 895, 911, + 913, 914, 916, 917, 919, 920, 921, 922, 946, 948, 950, 954, 955, 976, 977, 978, 979, 994, 1006, 1036, 1042, 1062, + 1063, 1064, 1065, 1066, 1067, 1068, 1069, 1070, 1093, 1094, 1097, 1126, 1152, 1154, 1155, 1156, 1157, 1158, 1159, + 1160, 1161, 1162, 1163, 1165, 1166, 1167, 1183, 1184, 1186, 1187, 1188, 1189, 1190, 1191, 1192, 1193, 1194, 1216, + 1218, 1220, 1223, 1225, 1252, 1253, 1282, 1283, 1312, 1313, 1314, 1315, 1316, 1317, 1342, 1343, 1344, 1345, 1346, + 1348, 1351, 1352, 1353, 1354, 1356, 1372, 1374, 1376, 1378, 1380, 1382, 1384, 1386, 1388, 1390, 1392, 1394, 1396, + 1406, 1408, 1409, 1433, 1435, 1437, 1438, 1440, 1442, 1444, 1446, 1448, 1450, 1454, 1455, 1482, 1512, 1514, 1516, + 1518, 1520, 1522, 1524, 1526, 1528, 1530, 1532, 1562, 1563, 1564, 1565, 1566, 1567, 1568, 1592, 1593, 1594, 1622, + 1628, 1632, 3707, 3709, 1662, 1664, 3739, 1692, 1693, 1694, 3741, 3743, 3745, 3747, 3753, 3765, 3771, 1725, 1727, + 3776, 1729, 3778, 1731, 3777, 1733, 3783, 1764, 1767, 1768, 1819, 1825, 1978, 1998, 2014, 2016 +] + +# correspond to UNIT_SPECIFIC_ABILITIES +UNIT_GENERAL_ABILITIES = [ + 3665, 3665, 3665, 3665, 0, 3794, 3795, 3793, 3674, 0, 3674, 0, 3684, 3684, 3684, 0, 3688, 3689, 0, 0, 0, 3661, 3662, + 0, 3661, 3662, 0, 0, 0, 3685, 0, 0, 0, 0, 3686, 0, 0, 0, 0, 3666, 3667, 0, 0, 0, 0, 0, 0, 0, 0, 3675, 0, 0, 0, 0, 0, + 0, 3661, 3662, 3666, 3667, 0, 3666, 3667, 0, 0, 0, 3685, 0, 0, 0, 0, 0, 0, 0, 0, 3668, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, + 0, 0, 3675, 3676, 3677, 0, 0, 0, 3676, 3677, 3668, 3669, 3796, 0, 0, 0, 3668, 3668, 3664, 3663, 3679, 3678, 3682, + 3683, 3679, 3682, 3683, 0, 3679, 3682, 3683, 0, 0, 0, 0, 0, 0, 0, 3679, 3678, 3678, 0, 0, 3659, 3659, 3678, 0, 0, 0, + 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3698, 3698, 3698, 3687, 3697, 3697, 0, 3697, 0, 0, 0, 0, 0, 0, 0, + 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3701, 3701, 3701, 3699, 3699, 3699, 3700, 3700, 3700, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, + 0, 0, 0, 0, 0, 3668, 3669, 3796, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3695, 3695, 3695, 3694, + 3694, 3694, 3696, 3696, 3696, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3666, 3667, 3705, 3705, 3705, + 3704, 3704, 3704, 3706, 3706, 3706, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3703, 3703, 3703, 3702, 3702, 3702, 0, 0, 0, 0, 0, 0, + 0, 0, 0, 0, 0, 0, 3661, 3662, 3661, 3662, 3661, 3662, 3661, 3662, 3661, 3662, 3661, 3662, 3668, 3669, 3796, 3661, + 3662, 3668, 3664, 3796, 3687, 3661, 3662, 0, 0, 0, 0, 0, 3661, 3662, 0, 0, 0, 3679, 3678, 0, 0, 0, 0, 3693, 3693, + 3693, 3692, 3692, 3692, 0, 0, 0, 0, 0, 0, 0, 3659, 0, 3661, 0, 0, 0, 0, 3691, 0, 0, 0, 0, 0, 0, 3674, 3681, 3681, + 3794, 3680, 3793, 3680, 3795, 3691, 3665, 0, 0, 0, 0, 0, 0, 0, 3661, 3662 +] + +# UNIT_MIX_ABILITIES = [] +# for idx in range(len(UNIT_SPECIFIC_ABILITIES)): +# if UNIT_GENERAL_ABILITIES[idx] == 0: +# UNIT_MIX_ABILITIES.append(UNIT_SPECIFIC_ABILITIES[idx]) +# else: +# UNIT_MIX_ABILITIES.append(UNIT_GENERAL_ABILITIES[idx]) +# UNIT_MIX_ABILITIES = [0] + list(set(UNIT_MIX_ABILITIES)) # use 0 as no op + +UNIT_MIX_ABILITIES = [ + 0, 2560, 524, 1036, 2063, 1042, 2067, 1530, 2073, 1344, 2588, 1532, 1568, 2081, 1126, 40, 42, 556, 46, 558, 560, + 561, 562, 2099, 563, 1345, 1592, 1593, 1594, 2116, 1093, 1094, 1097, 74, 3659, 76, 3661, 3662, 3663, 3664, 80, 3665, + 3666, 3667, 3669, 3668, 591, 594, 595, 3674, 3675, 3676, 3677, 3678, 3679, 1628, 1632, 2146, 3682, 3684, 3685, 3686, + 3683, 3688, 3689, 614, 3687, 620, 621, 110, 622, 623, 624, 626, 3698, 3697, 3701, 3699, 3700, 3695, 3696, 3705, + 3704, 3706, 3703, 3702, 1348, 1152, 3709, 1154, 1155, 1156, 1157, 1158, 1159, 1160, 1161, 650, 651, 140, 1162, 1163, + 1165, 2704, 1166, 146, 2706, 148, 2708, 1167, 3693, 152, 3692, 154, 2714, 3694, 1354, 3739, 1692, 2720, 1693, 3741, + 3743, 3745, 3747, 3753, 173, 181, 1664, 3765, 3691, 1216, 1218, 2244, 1220, 710, 1223, 1225, 3793, 3794, 3795, 3796, + 216, 217, 730, 731, 732, 1252, 1253, 1764, 1767, 1768, 247, 249, 761, 251, 764, 766, 769, 1282, 1283, 263, 265, + 2324, 790, 793, 2330, 1819, 2332, 799, 1825, 2338, 804, 805, 2346, 2350, 820, 2358, 2362, 2364, 318, 319, 320, 321, + 322, 323, 324, 1342, 326, 2375, 2376, 327, 328, 331, 329, 333, 1351, 2383, 1352, 2385, 1353, 2387, 1356, 2393, 1372, + 880, 881, 882, 883, 884, 885, 886, 887, 1346, 889, 890, 891, 892, 893, 894, 895, 386, 388, 390, 401, 403, 916, 405, + 917, 919, 920, 921, 922, 1448, 3680, 1450, 1454, 1455, 946, 948, 950, 596, 954, 955, 597, 1978, 3681, 2505, 1482, + 1998, 976, 977, 978, 979, 1622, 994, 2536, 1516, 2542, 1006, 2544, 1518, 1520, 1526, 1528, 2554, 1343, 2556, 2558 +] diff --git a/dizoo/distar/model/__init__.py b/dizoo/distar/model/__init__.py new file mode 100644 index 0000000000..8ea35e8f96 --- /dev/null +++ b/dizoo/distar/model/__init__.py @@ -0,0 +1 @@ +#from .model import Model, alphastar_model_default_config diff --git a/dizoo/distar/model/actor_critic_default_config.yaml b/dizoo/distar/model/actor_critic_default_config.yaml new file mode 100644 index 0000000000..5cdef334e5 --- /dev/null +++ b/dizoo/distar/model/actor_critic_default_config.yaml @@ -0,0 +1,453 @@ +var1: &NUM_ADDON 9 +var2: &NUM_BUFFS 50 +var3: &NUM_UNIT_TYPES 260 +var4: &NUM_UPGRADES 90 +var5: &NUM_ACTIONS 327 +var6: &NUM_QUEUE_ACTIONS 49 +var7: &NUM_BEGINNING_ORDER_ACTIONS 174 +var8: &NUM_CUMULATIVE_STAT_ACTIONS 167 +var9: &SPATIAL_X 160 +var10: &SPATIAL_Y 152 +var11: &NUM_UNIT_MIX_ABILITIES 269 + + +learner: + use_value_feature: False +model: + spatial_x: *SPATIAL_X + spatial_y: *SPATIAL_Y + temperature: 1.0 + # ===== Tuning ===== + freeze_targets: [] + state_dict_mask: [] + use_value_network: False + enable_baselines: ['winloss', 'build_order', 'built_unit', 'effect', 'upgrade', 'battle'] + entity_reduce_type: 'selected_units_num' # ['constant', 'entity_num', 'selected_units_num'] + # ===== Value ===== + value: + encoder: + modules: + enemy_unit_counts_bow: + arc: fc + input_dim: *NUM_UNIT_TYPES + output_dim: 64 + enemy_unit_type_bool: + arc: fc + input_dim: *NUM_UNIT_TYPES + output_dim: 64 + enemy_agent_statistics: + arc: fc + input_dim: 10 + output_dim: 64 + enemy_upgrades: + arc: fc + input_dim: *NUM_UPGRADES + output_dim: 32 + unit_alliance: + arc: one_hot + num_embeddings: 2 + embedding_dim: 16 + unit_type: + arc: one_hot + num_embeddings: *NUM_UNIT_TYPES + embedding_dim: 48 + beginning_order: + arc: transformer + action_one_hot_dim: *NUM_BEGINNING_ORDER_ACTIONS + binary_dim: 10 + head_dim: 8 + output_dim: 64 + activation: 'relu' + cumulative_stat: + arc: fc + input_dim: *NUM_CUMULATIVE_STAT_ACTIONS + output_dim: 128 + scatter: + scatter_input_dim: 64 + scatter_dim: 8 + scatter_type: add + spatial: + input_dim: 10 # 8 + 2 + project_dim: 16 + down_channels: [16, 32, 32] + resblock_num: 4 + spatial_fc_dim: 128 + + winloss: + name: winloss + cum_stat_keys: ['unit_build', 'research'] + param: + name: 'winloss' + input_dim: 384 #1920 + activation: 'relu' + norm_type: 'LN' + res_dim: 256 + res_num: 16 + atan: True + build_order: + name: build_order + cum_stat_keys: ['unit_build', 'effect', 'research'] + param: + name: 'build_order' + input_dim: 384 #2016 + activation: 'relu' + norm_type: 'LN' + res_dim: 256 + res_num: 16 + atan: False + built_unit: + name: built_unit + cum_stat_keys: ['unit_build'] + param: + name: 'built_unit' + input_dim: 384 #1824 + activation: 'relu' + norm_type: 'LN' + res_dim: 256 + res_num: 16 + atan: False + effect: + name: effect + cum_stat_keys: ['effect'] + param: + name: 'effect' + input_dim: 384 #1824 + activation: 'relu' + norm_type: 'LN' + res_dim: 256 + res_num: 16 + atan: False + upgrade: + name: upgrade + cum_stat_keys: ['research'] + param: + name: 'upgrade' + input_dim: 384 #1824 + activation: 'relu' + norm_type: 'LN' + res_dim: 256 + res_num: 16 + atan: False + battle: + name: battle + cum_stat_keys: ['unit_build', 'effect', 'research'] + param: + name: 'battle' + input_dim: 384 #2016 + activation: 'relu' + norm_type: 'LN' + res_dim: 256 + res_num: 16 + atan: False + # ===== Encoder ===== + encoder: + obs_encoder: + encoder_names: [scalar_encoder, spatial_encoder, entity_encoder] + scalar_encoder: + module: + agent_statistics: + arc: fc + input_dim: 10 + output_dim: 64 + baseline_feature: True + home_race: + arc: one_hot + num_embeddings: 5 + embedding_dim: 32 + scalar_context: True + away_race: + arc: one_hot + num_embeddings: 5 + embedding_dim: 32 + scalar_context: True + upgrades: + arc: fc + input_dim: *NUM_UPGRADES + output_dim: 128 + baseline_feature: True + time: + arc: identity + output_dim: 32 + unit_counts_bow: + arc: fc + input_dim: *NUM_UNIT_TYPES + output_dim: 128 + baseline_feature: True + last_delay: + arc: one_hot + num_embeddings: 128 + embedding_dim: 64 + last_queued: + arc: one_hot + num_embeddings: 2 + embedding_dim: 32 + last_action_type: + arc: one_hot + num_embeddings: *NUM_ACTIONS + embedding_dim: 128 + cumulative_stat: + arc: fc + input_dim: *NUM_CUMULATIVE_STAT_ACTIONS + output_dim: 128 + scalar_context: True + baseline_feature: True + beginning_order: + arc: transformer + action_one_hot_dim: *NUM_BEGINNING_ORDER_ACTIONS + binary_dim: 10 + head_dim: 8 + output_dim: 64 + scalar_context: True + activation: 'relu' + baseline_feature: True + unit_type_bool: + arc: fc + input_dim: *NUM_UNIT_TYPES + output_dim: 64 + scalar_context: True + enemy_unit_type_bool: + arc: fc + input_dim: *NUM_UNIT_TYPES + output_dim: 64 + scalar_context: True + unit_order_type: + arc: fc + input_dim: *NUM_UNIT_MIX_ABILITIES + output_dim: 64 + scalar_context: True + activation: 'relu' + output_dim: 1024 + spatial_encoder: + module: + height_map: + arc: other + visibility_map: + arc: one_hot + num_embeddings: 4 + creep: + arc: one_hot + num_embeddings: 2 + player_relative: + arc: one_hot + num_embeddings: 5 + alerts: + arc: one_hot + num_embeddings: 2 + pathable: + arc: one_hot + num_embeddings: 2 + buildable: + arc: one_hot + num_embeddings: 2 + effect_PsiStorm: + arc: scatter + effect_NukeDot: + arc: scatter + effect_LiberatorDefenderZone: + arc: scatter + effect_BlindingCloud: + arc: scatter + effect_CorrosiveBile: + arc: scatter + effect_LurkerSpines: + arc: scatter + input_dim: 56 + resblock_num: 4 + fc_dim: 256 + project_dim: 32 + downsample_type: 'maxpool' + down_channels: [64, 128, 128] + activation: 'relu' + norm_type: 'none' + head_type: 'fc' + entity_encoder: + module: + unit_type: + arc: one_hot + num_embeddings: *NUM_UNIT_TYPES + alliance: + arc: one_hot + num_embeddings: 5 + cargo_space_taken: + arc: one_hot + num_embeddings: 9 + build_progress: + arc: unsqueeze + health_ratio: + arc: unsqueeze + shield_ratio: + arc: unsqueeze + energy_ratio: + arc: unsqueeze + display_type: + arc: one_hot + num_embeddings: 5 + x: + arc: binary + num_embeddings: 11 + y: + arc: binary + num_embeddings: 11 + cloak: + arc: one_hot + num_embeddings: 5 + is_blip: + arc: one_hot + num_embeddings: 2 + is_powered: + arc: one_hot + num_embeddings: 2 + mineral_contents: + arc: unsqueeze + vespene_contents: + arc: unsqueeze + cargo_space_max: + arc: one_hot + num_embeddings: 9 + assigned_harvesters: + arc: one_hot + num_embeddings: 24 + weapon_cooldown: + arc: one_hot + num_embeddings: 32 + order_length: + arc: one_hot + num_embeddings: 9 + order_id_0: + arc: one_hot + num_embeddings: *NUM_ACTIONS + order_id_1: + arc: one_hot + num_embeddings: *NUM_QUEUE_ACTIONS + is_hallucination: + arc: one_hot + num_embeddings: 2 + buff_id_0: + arc: one_hot + num_embeddings: *NUM_BUFFS + buff_id_1: + arc: one_hot + num_embeddings: *NUM_BUFFS + addon_unit_type: + arc: one_hot + num_embeddings: *NUM_ADDON + is_active: + arc: one_hot + num_embeddings: 2 + order_progress_0: + arc: unsqueeze + order_progress_1: + arc: unsqueeze + order_id_2: + arc: one_hot + num_embeddings: *NUM_QUEUE_ACTIONS + order_id_3: + arc: one_hot + num_embeddings: *NUM_QUEUE_ACTIONS + is_in_cargo: + arc: one_hot + num_embeddings: 2 + attack_upgrade_level: + arc: one_hot + num_embeddings: 4 + armor_upgrade_level: + arc: one_hot + num_embeddings: 4 + shield_upgrade_level: + arc: one_hot + num_embeddings: 4 + last_selected_units: + arc: one_hot + num_embeddings: 2 + last_targeted_unit: + arc: one_hot + num_embeddings: 2 + input_dim: 997 # cat all entity info + head_dim: 128 + hidden_dim: 1024 + output_dim: 256 + head_num: 2 + mlp_num: 2 + layer_num: 3 + dropout_ratio: 0 + activation: 'relu' + ln_type: 'post' + use_score_cumulative: False + scatter: + input_dim: 256 # entity_encoder.output_dim + output_dim: 32 + scatter_type: 'add' + core_lstm: + lstm_type: 'normal' + input_size: 1536 # spatial_encoder.fc_dim + entity_encoder.output_dim + scalar_encoder.output_dim + hidden_size: 384 + num_layers: 3 + dropout: 0.0 + score_cumulative: + input_dim: 13 + output_dim: 64 + activation: 'relu' + # ===== Policy ===== + policy: + head: + head_names: [action_type_head, delay_head, queued_head, selected_units_head, target_unit_head, location_head] + action_type_head: + input_dim: 384 # core.hidden_size + res_dim: 256 + res_num: 2 + action_num: *NUM_ACTIONS + action_map_dim: 256 # scalar context + gate_dim: 1024 + context_dim: 448 + activation: 'relu' + norm_type: 'LN' + ln_type: 'normal' + use_mask: False + delay_head: + input_dim: 1024 # action_type_head.gate_dim + decode_dim: 256 + delay_dim: 128 + delay_map_dim: 256 + activation: 'relu' + queued_head: + input_dim: 1024 # action_type_head.gate_dim + decode_dim: 256 + queued_dim: 2 + queued_map_dim: 256 + activation: 'relu' + selected_units_head: + lstm_type: 'pytorch' + lstm_norm_type: 'none' + lstm_dropout: 0. + input_dim: 1024 # action_type_head.gate_dim + entity_embedding_dim: 256 # entity_encoder.output_dim + key_dim: 32 + unit_type_dim: 259 + func_dim: 256 + hidden_dim: 32 + num_layers: 1 + max_entity_num: 64 + activation: 'relu' + target_unit_head: + input_dim: 1024 # action_type_head.gate_dim + entity_embedding_dim: 256 # entity_encoder.output_dim + key_dim: 32 + unit_type_dim: 259 + func_dim: 256 + activation: 'relu' + embedding_norm: True + location_head: + input_dim: 1024 + project_dim: 1024 + upsample_type: 'bilinear' + upsample_dims: [64, 32, 1] # len(upsample_dims)-len(down_channels)+1 = ratio + res_dim: 128 + res_num: 4 + film: False + gate: True + unet: False + reshape_size: [16, 16] + reshape_channel: 4 # entity_encoder.gate_dim / reshape_size + map_skip_dim: 128 # spatial_encoder.down_channels[-1] + activation: 'relu' + # loc_type: 'alphastar' diff --git a/dizoo/distar/model/encoder.py b/dizoo/distar/model/encoder.py new file mode 100644 index 0000000000..f6d849f901 --- /dev/null +++ b/dizoo/distar/model/encoder.py @@ -0,0 +1,42 @@ +import collections + +import torch +import torch.nn as nn +from typing import Dict +from torch import Tensor + +from ding.torch_utils import fc_block, ScatterConnection + +from .obs_encoder import ScalarEncoder, SpatialEncoder, EntityEncoder +from .lstm import script_lnlstm + + +class Encoder(nn.Module): + + def __init__(self, cfg): + super(Encoder, self).__init__() + self.whole_cfg = cfg + self.cfg = cfg.model.encoder + self.encoder = nn.ModuleDict() + self.scalar_encoder = ScalarEncoder(self.whole_cfg) + self.spatial_encoder = SpatialEncoder(self.whole_cfg) + self.entity_encoder = EntityEncoder(self.whole_cfg) + self.scatter_project = fc_block(self.cfg.scatter.input_dim, self.cfg.scatter.output_dim, activation=nn.ReLU()) + self.scatter_dim = self.cfg.scatter.output_dim + self.scatter_connection = ScatterConnection(self.cfg.scatter.scatter_type) + + def forward( + self, spatial_info: Dict[str, Tensor], entity_info: Dict[str, Tensor], scalar_info: Dict[str, Tensor], + entity_num: Tensor + ): + embedded_scalar, scalar_context, baseline_feature = self.scalar_encoder(scalar_info) + entity_embeddings, embedded_entity, entity_mask = self.entity_encoder(entity_info, entity_num) + entity_location = torch.cat([entity_info['y'].unsqueeze(dim=-1), entity_info['x'].unsqueeze(dim=-1)], dim=-1) + shape = spatial_info['height_map'].shape[-2:] + project_embeddings = self.scatter_project(entity_embeddings) + project_embeddings = project_embeddings * entity_mask.unsqueeze(dim=2) + + scatter_map = self.scatter_connection(project_embeddings, shape, entity_location) + embedded_spatial, map_skip = self.spatial_encoder(spatial_info, scatter_map) + lstm_input = torch.cat([embedded_scalar, embedded_entity, embedded_spatial], dim=-1) + return lstm_input, scalar_context, baseline_feature, entity_embeddings, map_skip diff --git a/dizoo/distar/model/head/__init__.py b/dizoo/distar/model/head/__init__.py new file mode 100644 index 0000000000..94e44e0486 --- /dev/null +++ b/dizoo/distar/model/head/__init__.py @@ -0,0 +1,2 @@ +from .action_arg_head import DelayHead, SelectedUnitsHead, TargetUnitHead, LocationHead, QueuedHead +from .action_type_head import ActionTypeHead diff --git a/dizoo/distar/model/head/action_arg_head.py b/dizoo/distar/model/head/action_arg_head.py new file mode 100644 index 0000000000..34d36b086e --- /dev/null +++ b/dizoo/distar/model/head/action_arg_head.py @@ -0,0 +1,497 @@ +''' +Copyright 2020 Sensetime X-lab. All Rights Reserved + +Main Function: + 1. Implementation for action_type_head, including basic processes. + 2. Implementation for delay_head, including basic processes. + 3. Implementation for queue_type_head, including basic processes. + 4. Implementation for selected_units_type_head, including basic processes. + 5. Implementation for target_unit_head, including basic processes. + 6. Implementation for location_head, including basic processes. +''' +from typing import Optional, List +from torch import Tensor +import math + +import torch +import torch.nn as nn +import torch.nn.functional as F +from ding.torch_utils import fc_block, conv2d_block, deconv2d_block, build_activation, ResBlock, NearestUpsample, \ + BilinearUpsample, sequence_mask, GatedResBlock, FiLMedResBlock, AttentionPool +from dizoo.distar.envs import MAX_ENTITY_NUM, MAX_SELECTED_UNITS_NUM +from ..lstm import script_lnlstm, script_lstm + + +class DelayHead(nn.Module): + + def __init__(self, cfg): + super(DelayHead, self).__init__() + self.whole_cfg = cfg + self.cfg = self.whole_cfg.model.policy.head.delay_head + self.act = build_activation(self.cfg.activation) + self.fc1 = fc_block(self.cfg.input_dim, self.cfg.decode_dim, activation=self.act, norm_type=None) + self.fc2 = fc_block(self.cfg.decode_dim, self.cfg.decode_dim, activation=self.act, norm_type=None) + self.fc3 = fc_block(self.cfg.decode_dim, self.cfg.delay_dim, activation=None, norm_type=None) # regression + self.embed_fc1 = fc_block(self.cfg.delay_dim, self.cfg.delay_map_dim, activation=self.act, norm_type=None) + self.embed_fc2 = fc_block(self.cfg.delay_map_dim, self.cfg.input_dim, activation=None, norm_type=None) + + self.delay_dim = self.cfg.delay_dim + + def forward(self, embedding, delay: Optional[torch.Tensor] = None): + x = self.fc1(embedding) + x = self.fc2(x) + x = self.fc3(x) + if delay is None: + p = F.softmax(x, dim=1) + delay = torch.multinomial(p, 1)[:, 0] + + delay_encode = torch.nn.functional.one_hot(delay.long(), self.delay_dim).float() + embedding_delay = self.embed_fc1(delay_encode) + embedding_delay = self.embed_fc2(embedding_delay) # get autoregressive_embedding + + return x, delay, embedding + embedding_delay + + +class QueuedHead(nn.Module): + + def __init__(self, cfg): + super(QueuedHead, self).__init__() + self.whole_cfg = cfg + self.cfg = self.whole_cfg.model.policy.head.queued_head + self.act = build_activation(self.cfg.activation) + # to get queued logits + self.fc1 = fc_block(self.cfg.input_dim, self.cfg.decode_dim, activation=self.act, norm_type=None) + self.fc2 = fc_block(self.cfg.decode_dim, self.cfg.decode_dim, activation=self.act, norm_type=None) + self.fc3 = fc_block(self.cfg.decode_dim, self.cfg.queued_dim, activation=None, norm_type=None) + + # to get autoregressive_embedding + self.embed_fc1 = fc_block(self.cfg.queued_dim, self.cfg.queued_map_dim, activation=self.act, norm_type=None) + self.embed_fc2 = fc_block(self.cfg.queued_map_dim, self.cfg.input_dim, activation=None, norm_type=None) + + self.queued_dim = self.cfg.queued_dim + + def forward(self, embedding, queued=None): + x = self.fc1(embedding) + x = self.fc2(x) + x = self.fc3(x) + x.div_(self.whole_cfg.model.temperature) + if queued is None: + p = F.softmax(x, dim=1) + queued = torch.multinomial(p, 1)[:, 0] + + queued_one_hot = torch.nn.functional.one_hot(queued.long(), self.queued_dim).float() + embedding_queued = self.embed_fc1(queued_one_hot) + embedding_queued = self.embed_fc2(embedding_queued) # get autoregressive_embedding + + return x, queued, embedding + embedding_queued + + +class SelectedUnitsHead(nn.Module): + + def __init__(self, cfg): + super(SelectedUnitsHead, self).__init__() + self.whole_cfg = cfg + self.cfg = self.whole_cfg.model.policy.head.selected_units_head + self.act = build_activation(self.cfg.activation) + self.key_fc = fc_block(self.cfg.entity_embedding_dim, self.cfg.key_dim, activation=None, norm_type=None) + self.query_fc1 = fc_block(self.cfg.input_dim, self.cfg.func_dim, activation=self.act) + self.query_fc2 = fc_block(self.cfg.func_dim, self.cfg.key_dim, activation=None) + self.embed_fc1 = fc_block(self.cfg.key_dim, self.cfg.func_dim, activation=self.act, norm_type=None) + self.embed_fc2 = fc_block(self.cfg.func_dim, self.cfg.input_dim, activation=None, norm_type=None) + + self.max_select_num = MAX_SELECTED_UNITS_NUM + self.max_entity_num = MAX_ENTITY_NUM + self.key_dim = self.cfg.key_dim + + self.num_layers = self.cfg.num_layers + self.test_iou = self.cfg.get('test_iou', False) + + self.lstm = script_lnlstm(self.cfg.key_dim, self.cfg.hidden_dim, self.cfg.num_layers) + self.end_embedding = torch.nn.Parameter(torch.FloatTensor(1, self.key_dim)) + stdv = 1. / math.sqrt(self.end_embedding.size(1)) + self.end_embedding.data.uniform_(-stdv, stdv) + if self.whole_cfg.model.entity_reduce_type == 'attention_pool': + self.attention_pool = AttentionPool(key_dim=self.cfg.key_dim, head_num=2, output_dim=self.cfg.input_dim) + elif self.whole_cfg.model.entity_reduce_type == 'attention_pool_add_num': + self.attention_pool = AttentionPool( + key_dim=self.cfg.key_dim, head_num=2, output_dim=self.cfg.input_dim, max_num=MAX_SELECTED_UNITS_NUM + 1 + ) + self.extra_units = self.whole_cfg.get('agent', {}).get('extra_units', False) + + def _get_key_mask(self, entity_embedding, entity_num): + bs = entity_embedding.shape[0] + padding_end = torch.zeros(1, self.end_embedding.shape[1]).repeat(bs, 1, + 1).to(entity_embedding.device) # b, 1, c + key = self.key_fc(entity_embedding) # b, n, c + key = torch.cat([key, padding_end], dim=1) + end_embeddings = torch.ones(key.shape, dtype=key.dtype, device=key.device) * self.end_embedding.squeeze(dim=0) + flag = torch.ones(key.shape[:2], dtype=torch.bool, device=key.device).unsqueeze(dim=2) + flag[torch.arange(bs), entity_num] = 0 + end_embeddings = end_embeddings * ~flag + key = key * flag + key = key + end_embeddings + reduce_type = self.whole_cfg.model.entity_reduce_type + if reduce_type == 'entity_num': + key_reduce = torch.div(key, entity_num.reshape(-1, 1, 1)) + key_embeddings = self.embed_fc(key_reduce) + elif reduce_type == 'constant': + key_reduce = torch.div(key, 512) + key_embeddings = self.embed_fc(key_reduce) + elif reduce_type == 'selected_units_num' or 'attention' in reduce_type: + key_embeddings = key + else: + raise NotImplementedError + + new_entity_num = entity_num + 1 # add end entity + mask = sequence_mask(new_entity_num, max_len=entity_embedding.shape[1] + 1) + return key, mask, key_embeddings + + def _get_pred_with_logit(self, logit): + logit.div_(self.whole_cfg.model.temperature) + p = F.softmax(logit, dim=-1) + units = torch.multinomial(p, 1)[:, 0] + return units + + def _query( + self, + key: Tensor, + entity_num: Tensor, + autoregressive_embedding: Tensor, + logits_mask: Tensor, + key_embeddings: Tensor, + selected_units_num: Optional[Tensor] = None, + selected_units: Optional[Tensor] = None, + su_mask: Tensor = None + ): + ae = autoregressive_embedding + bs = ae.shape[0] + end_flag = torch.zeros(bs, dtype=torch.bool).to(ae.device) + results_list, logits_list = [], [] + state = [ + (torch.zeros(ae.shape[0], 32, device=ae.device), torch.zeros(ae.shape[0], 32, device=ae.device)) + for _ in range(self.num_layers) + ] + logits_mask[torch.arange(bs), entity_num] = torch.tensor([0], dtype=torch.bool, device=ae.device) + + result: Optional[Tensor] = None + results: Optional[Tensor] = None + extra_units = torch.zeros(bs, MAX_ENTITY_NUM + 1, device=ae.device) + if selected_units is not None and selected_units_num is not None: # train + bs = selected_units.shape[0] + seq_len = selected_units_num.max() + queries = [] + selected_mask = sequence_mask(selected_units_num) # b, s + if self.test_iou: + iou_ae = ae.detach().clone() + iou_logits_mask = logits_mask.detach().clone() + iou_state = [ + (torch.zeros(ae.shape[0], 32, device=ae.device), torch.zeros(ae.shape[0], 32, device=ae.device)) + for _ in range(self.num_layers) + ] + logits_mask = logits_mask.repeat(max(seq_len, 1), 1, 1) # b, n -> s, b, n + logits_mask[0, torch.arange(bs), entity_num] = 0 # end flag is not available at first selection + selected_units_one_hot = torch.zeros(*key_embeddings.shape[:2], device=ae.device).unsqueeze(dim=2) + for i in range(max(seq_len, 1)): + if i > 0: + logits_mask[i] = logits_mask[i - 1] + if i == 1: # enable end flag + logits_mask[i, torch.arange(bs), entity_num] = 1 + logits_mask[i, torch.arange(bs), selected_units[:, i - 1]] = 0 # mask selected units + lstm_input = self.query_fc2(self.query_fc1(ae)).unsqueeze(0) + lstm_output, state = self.lstm(lstm_input, state) + queries.append(lstm_output) + reduce_type = self.whole_cfg.model.entity_reduce_type + if reduce_type == 'selected_units_num' or 'attention' in reduce_type: + new_selected_units_one_hot = selected_units_one_hot.clone() # inplace operation can not backward + end_flag[selected_units[:, i] == entity_num] = 1 + new_selected_units_one_hot[torch.arange(bs)[~end_flag], selected_units[:, i][~end_flag], :] = 1 + if self.whole_cfg.model.entity_reduce_type == 'selected_units_num': + selected_units_emebedding = (key_embeddings * new_selected_units_one_hot).sum(dim=1) + S = selected_units_num + selected_units_emebedding[S != 0] = \ + selected_units_emebedding[S != 0] / new_selected_units_one_hot.sum(dim=1)[S != 0] + selected_units_emebedding = self.embed_fc2(self.embed_fc1(selected_units_emebedding)) + ae = autoregressive_embedding + selected_units_emebedding + elif self.whole_cfg.model.entity_reduce_type == 'attention_pool': + ae = autoregressive_embedding + self.attention_pool( + key_embeddings, mask=new_selected_units_one_hot + ) + elif self.whole_cfg.model.entity_reduce_type == 'attention_pool_add_num': + ae = autoregressive_embedding + self.attention_pool( + key_embeddings, + num=new_selected_units_one_hot.sum(dim=1).squeeze(dim=1), + mask=new_selected_units_one_hot, + ) + selected_units_one_hot = new_selected_units_one_hot.clone() + else: + ae = ae + key_embeddings[torch.arange(bs), + selected_units[:, i]] * (i + 1 < selected_units_num).unsqueeze(1) + + queries = torch.cat(queries, dim=0).unsqueeze(dim=2) # s, b, 1, -1 + key = key.unsqueeze(dim=0) # 1, b, n, -1 + query_result = queries * key + logits = query_result.sum(dim=3) # s, b, n + logits = logits.masked_fill(~logits_mask, -1e9) + logits = logits.permute(1, 0, 2).contiguous() + if self.test_iou: + with torch.no_grad(): + selected_units_one_hot = torch.zeros(*key_embeddings.shape[:2], device=ae.device).unsqueeze(dim=2) + selected_units_num = torch.ones(bs, dtype=torch.long, device=ae.device) * seq_len + key = key.squeeze(dim=0) + for i in range(seq_len): + if i > 0: + if i == 1: # end flag can be selected at second selection + iou_logits_mask[torch.arange(bs), + entity_num] = torch.tensor([1], dtype=torch.bool, device=ae.device) + if result is not None: + iou_logits_mask[torch.arange(bs), result.detach()] = torch.tensor( + [0], dtype=torch.bool, device=ae.device + ) # mask selected units + lstm_input = self.query_fc2(self.query_fc1(iou_ae)).unsqueeze(0) + lstm_output, iou_state = self.lstm(lstm_input, iou_state) + queries = lstm_output.permute(1, 0, 2) # b, 1, c + query_result = queries * key + step_logits = query_result.sum(dim=2) # b, n + step_logits = step_logits.masked_fill(~iou_logits_mask, -1e9) + step_logits = step_logits.div(1) + result = self._get_pred_with_logit(step_logits) + selected_units_num[(result == entity_num) * ~(end_flag)] = torch.tensor(i + 1).to(result.device) + end_flag[result == entity_num] = torch.tensor([1], dtype=torch.bool, device=ae.device) + results_list.append(result) + reduce_type = self.whole_cfg.model.entity_reduce_type + if reduce_type == 'selected_units_num' or 'attention' in reduce_type: + selected_units_one_hot[torch.arange(bs)[~end_flag], result[~end_flag], :] = 1 + if self.whole_cfg.model.entity_reduce_type == 'selected_units_num': + selected_units_emebedding = (key_embeddings * selected_units_one_hot + ).sum(dim=1) / selected_units_one_hot.sum(dim=1) + selected_units_emebedding = self.embed_fc2(self.embed_fc1(selected_units_emebedding)) + iou_ae = autoregressive_embedding + selected_units_emebedding + elif self.whole_cfg.model.entity_reduce_type == 'attention_pool': + iou_ae = autoregressive_embedding + self.attention_pool( + key_embeddings, mask=selected_units_one_hot + ) + elif self.whole_cfg.model.entity_reduce_type == 'attention_pool_add_num': + iou_ae = autoregressive_embedding + self.attention_pool( + key_embeddings, + num=selected_units_one_hot.sum(dim=1).squeeze(dim=1), + mask=selected_units_one_hot, + ) + else: + iou_ae = iou_ae + key_embeddings[torch.arange(bs), result] * ~end_flag.unsqueeze(dim=1) + results = torch.stack(results_list, dim=0) + results = results.transpose(1, 0).contiguous() + + else: + selected_units_num = torch.ones(bs, dtype=torch.long, device=ae.device) * self.max_select_num + end_flag[~su_mask] = 1 + selected_units_num[~su_mask] = 0 + selected_units_one_hot = torch.zeros(*key_embeddings.shape[:2], device=ae.device).unsqueeze(dim=2) + for i in range(self.max_select_num): + if i > 0: + if i == 1: # end flag can be selected at second selection + logits_mask[torch.arange(bs), + entity_num] = torch.tensor([1], dtype=torch.bool, device=ae.device) + if result is not None: + logits_mask[torch.arange(bs), result.detach()] = torch.tensor( + [0], dtype=torch.bool, device=ae.device + ) # mask selected units + lstm_input = self.query_fc2(self.query_fc1(ae)).unsqueeze(0) + lstm_output, state = self.lstm(lstm_input, state) + queries = lstm_output.permute(1, 0, 2) # b, 1, c + query_result = queries * key + step_logits = query_result.sum(dim=2) # b, n + step_logits = step_logits.masked_fill(~logits_mask, -1e9) + step_logits = step_logits.div(1) + result = self._get_pred_with_logit(step_logits) + selected_units_num[(result == entity_num) * ~(end_flag)] = torch.tensor(i + 1).to(result.device) + end_flag[result == entity_num] = torch.tensor([1], dtype=torch.bool, device=ae.device) + results_list.append(result) + logits_list.append(step_logits) + reduce_type = self.whole_cfg.model.entity_reduce_type + if reduce_type == 'selected_units_num' or 'attention' in reduce_type: + selected_units_one_hot[torch.arange(bs)[~end_flag], result[~end_flag], :] = 1 + if self.whole_cfg.model.entity_reduce_type == 'selected_units_num': + selected_units_emebedding = (key_embeddings * selected_units_one_hot).sum(dim=1) + slected_num = selected_units_one_hot.sum(dim=1).squeeze(dim=1) + selected_units_emebedding[slected_num != 0] = selected_units_emebedding[ + slected_num != 0] / slected_num[slected_num != 0].unsqueeze(dim=1) + selected_units_emebedding = self.embed_fc2(self.embed_fc1(selected_units_emebedding)) + ae = autoregressive_embedding + selected_units_emebedding + elif self.whole_cfg.model.entity_reduce_type == 'attention_pool': + ae = autoregressive_embedding + self.attention_pool(key_embeddings, mask=selected_units_one_hot) + elif self.whole_cfg.model.entity_reduce_type == 'attention_pool_add_num': + ae = autoregressive_embedding + self.attention_pool( + key_embeddings, + num=selected_units_one_hot.sum(dim=1).squeeze(dim=1), + mask=selected_units_one_hot, + ) + else: + ae = ae + key_embeddings[torch.arange(bs), result] * ~end_flag.unsqueeze(dim=1) + if end_flag.all(): + break + if self.extra_units: + end_flag_logit = step_logits[torch.arange(bs), entity_num] + extra_units = ((step_logits > end_flag_logit.unsqueeze(dim=1)) * ~end_flag.unsqueeze(dim=1)).float() + results = torch.stack(results_list, dim=0) + results = results.transpose(1, 0).contiguous() + logits = torch.stack(logits_list, dim=0) + logits = logits.transpose(1, 0).contiguous() + return logits, results, ae, selected_units_num, extra_units + + def forward( + self, + embedding, + entity_embedding, + entity_num, + selected_units_num: Optional[Tensor] = None, + selected_units: Optional[Tensor] = None, + su_mask: Optional[Tensor] = None + ): + key, mask, key_embeddings = self._get_key_mask(entity_embedding, entity_num) + logits, units, embedding, selected_units_num, extra_units = self._query( + key, entity_num, embedding, mask, key_embeddings, selected_units_num, selected_units, su_mask + ) + return logits, units, embedding, selected_units_num, extra_units + + +class TargetUnitHead(nn.Module): + + def __init__(self, cfg): + super(TargetUnitHead, self).__init__() + self.whole_cfg = cfg + self.cfg = self.whole_cfg.model.policy.head.target_unit_head + self.act = build_activation(self.cfg.activation) + self.key_fc = fc_block(self.cfg.entity_embedding_dim, self.cfg.key_dim, activation=None, norm_type=None) + self.query_fc1 = fc_block(self.cfg.input_dim, self.cfg.key_dim, activation=self.act, norm_type=None) + self.query_fc2 = fc_block(self.cfg.key_dim, self.cfg.key_dim, activation=None, norm_type=None) + self.key_dim = self.cfg.key_dim + self.max_entity_num = MAX_ENTITY_NUM + + def forward(self, embedding, entity_embedding, entity_num, target_unit: Optional[torch.Tensor] = None): + key = self.key_fc(entity_embedding) + mask = sequence_mask(entity_num, max_len=entity_embedding.shape[1]) + + query = self.query_fc2(self.query_fc1(embedding)) + + logits = query.unsqueeze(1) * key + logits = logits.sum(dim=2) # b, n, -1 + logits.masked_fill_(~mask, value=-1e9) + + logits.div_(self.whole_cfg.model.temperature) + if target_unit is None: + p = F.softmax(logits, dim=1) + target_unit = torch.multinomial(p, 1)[:, 0] + return logits, target_unit + + +class LocationHead(nn.Module): + + def __init__(self, cfg): + super(LocationHead, self).__init__() + self.whole_cfg = cfg + self.cfg = self.whole_cfg.model.policy.head.location_head + self.act = build_activation(self.cfg.activation) + self.reshape_size = self.cfg.reshape_size + self.reshape_channel = self.cfg.reshape_channel + + self.conv1 = conv2d_block( + self.cfg.map_skip_dim + self.cfg.reshape_channel, + self.cfg.res_dim, + 1, + 1, + 0, + activation=build_activation(self.cfg.activation), + norm_type=None + ) + self.res = nn.ModuleList() + self.res_act = nn.ModuleList() + self.res_dim = self.cfg.res_dim + self.use_film = self.cfg.get('film', False) + self.use_gate = self.cfg.get('gate', False) + self.use_unet = self.cfg.get('unet', False) + self.project_embed = fc_block( + self.cfg.input_dim, + self.whole_cfg.model.spatial_y // 8 * self.whole_cfg.model.spatial_x // 8 * 4, + activation=build_activation(self.cfg.activation) + ) + if self.use_film: + self.film_fc = fc_block(self.cfg.input_dim, self.res_dim, activation=build_activation(self.cfg.activation)) + self.film_gamma = nn.ModuleList() + self.film_beta = nn.ModuleList() + self.film = nn.ModuleList() + + self.res = nn.ModuleList() + for i in range(self.cfg.res_num): + if self.use_gate: + self.res.append( + GatedResBlock( + self.res_dim, + self.res_dim, + 3, + 1, + 1, + activation=build_activation(self.cfg.activation), + norm_type=None + ) + ) + else: + self.res.append(ResBlock(self.dim, build_activation(self.cfg.activation), norm_type=None)) + if self.use_film: + self.film_gamma.append(nn.Linear(self.res_dim, self.res_dim)) + self.film_beta.append(nn.Linear(self.res_dim, self.res_dim)) + self.film.append(FiLMedResBlock(self.res_dim, with_cond=[True])) + torch.nn.init.xavier_uniform_(self.film_gamma[i].weight) + torch.nn.init.xavier_uniform_(self.film_beta[i].weight) + + self.upsample = nn.ModuleList() # upsample list + dims = [self.res_dim] + self.cfg.upsample_dims + assert (self.cfg.upsample_type in ['deconv', 'nearest', 'bilinear']) + for i in range(len(self.cfg.upsample_dims)): + if i == len(self.cfg.upsample_dims) - 1: + activation = None + else: + activation = build_activation(self.cfg.activation) + if self.cfg.upsample_type == 'deconv': + self.upsample.append( + deconv2d_block(dims[i], dims[i + 1], 4, 2, 1, activation=activation, norm_type=None) + ) + else: + self.upsample.append(conv2d_block(dims[i], dims[i + 1], 3, 1, 1, activation=activation, norm_type=None)) + + def forward(self, embedding, map_skip: List[Tensor], location=None): + projected_embedding = self.project_embed(embedding) + reshape_embedding = projected_embedding.reshape( + projected_embedding.shape[0], self.reshape_channel, self.whole_cfg.model.spatial_y // 8, + self.whole_cfg.model.spatial_x // 8 + ) + cat_feature = torch.cat([reshape_embedding, map_skip[-1]], dim=1) + + x1 = self.act(cat_feature) + x = self.conv1(x1) + if self.use_film: + film_embedding = self.film_fc(embedding) + + # reverse cat_feature instead of reversing resblock + for i in range(self.cfg.res_num): + x = x + map_skip[len(map_skip) - i - 1] + if self.use_gate: + x = self.res[i](x, x) + else: + x = self.res[i](x) + if self.use_film: + x = self.film[i](x, gammas=self.film_gamma[i](film_embedding), betas=self.film_beta[i](film_embedding)) + for i, layer in enumerate(self.upsample): + if self.cfg.upsample_type == 'nearest': + x = F.interpolate(x, scale_factor=2., mode='nearest') + elif self.cfg.upsample_type == 'bilinear': + x = F.interpolate(x, scale_factor=2., mode='bilinear') + if self.use_unet: + x = x + map_skip[len(map_skip) - self.cfg.res_num - i - 1] + x = layer(x) + + logits_flatten = x.view(x.shape[0], -1) + logits_flatten.div_(self.whole_cfg.model.temperature) + p = F.softmax(logits_flatten, dim=1) + if location is None: + location = torch.multinomial(p, 1)[:, 0] + return logits_flatten, location diff --git a/dizoo/distar/model/head/action_type_head.py b/dizoo/distar/model/head/action_type_head.py new file mode 100644 index 0000000000..98eaa250e1 --- /dev/null +++ b/dizoo/distar/model/head/action_type_head.py @@ -0,0 +1,71 @@ +''' +Copyright 2020 Sensetime X-lab. All Rights Reserved + +Main Function: + 1. Implementation for action_type_head, including basic processes. +''' +from typing import Optional, List, Tuple +from torch import Tensor +import torch +import torch.nn as nn +import torch.nn.functional as F +from ding.torch_utils import ResFCBlock, fc_block, build_activation +from dizoo.distar.envs import ACTION_RACE_MASK + + +class ActionTypeHead(nn.Module): + __constants__ = ['mask_action'] + + def __init__(self, cfg): + super(ActionTypeHead, self).__init__() + self.whole_cfg = cfg + self.cfg = self.whole_cfg.model.policy.head.action_type_head + self.act = build_activation(self.cfg.activation) # use relu as default + self.project = fc_block(self.cfg.input_dim, self.cfg.res_dim, activation=self.act, norm_type=None) + # self.project = fc_block(self.cfg.input_dim, self.cfg.res_dim) + blocks = [ResFCBlock(self.cfg.res_dim, self.act, self.cfg.norm_type) for _ in range(self.cfg.res_num)] + self.res = nn.Sequential(*blocks) + self.weight_norm = self.cfg.get('weight_norm', False) + self.drop_Z = torch.nn.Dropout(p=self.cfg.get('drop_ratio', 0.0)) + self.drop_ratio = self.cfg.get('drop_ratio', 0.0) + self.action_fc = build_activation('glu')(self.cfg.res_dim, self.cfg.action_num, self.cfg.context_dim) + + self.action_map_fc1 = fc_block( + self.cfg.action_num, self.cfg.action_map_dim, activation=self.act, norm_type=None + ) + self.action_map_fc2 = fc_block( + self.cfg.action_map_dim, self.cfg.action_map_dim, activation=None, norm_type=None + ) + self.glu1 = build_activation('glu')(self.cfg.action_map_dim, self.cfg.gate_dim, self.cfg.context_dim) + self.glu2 = build_activation('glu')(self.cfg.input_dim, self.cfg.gate_dim, self.cfg.context_dim) + self.action_num = self.cfg.action_num + if self.whole_cfg.common.type == 'play': + self.use_mask = True + else: + self.use_mask = False + self.race = 'zerg' + + def forward(self, + lstm_output, + scalar_context, + action_type: Optional[torch.Tensor] = None) -> Tuple[Tensor, Tensor, Tensor]: + x = self.project(lstm_output) + x = self.res(x) + x = self.action_fc(x, scalar_context) + x.div_(self.whole_cfg.model.temperature) + if self.use_mask: + mask = ACTION_RACE_MASK[self.race].to(x.device) + x = x.masked_fill(~mask.unsqueeze(dim=0), -1e9) + if action_type is None: + p = F.softmax(x, dim=1) + action_type = torch.multinomial(p, 1)[:, 0] + + # one-hot version of action_type + action_one_hot = torch.nn.functional.one_hot(action_type.long(), self.action_num).float() + embedding1 = self.action_map_fc1(action_one_hot) + embedding1 = self.action_map_fc2(embedding1) + embedding1 = self.glu1(embedding1, scalar_context) + embedding2 = self.glu2(lstm_output, scalar_context) + embedding = embedding1 + embedding2 + + return x, action_type, embedding diff --git a/dizoo/distar/model/lstm.py b/dizoo/distar/model/lstm.py new file mode 100644 index 0000000000..8671a8ff05 --- /dev/null +++ b/dizoo/distar/model/lstm.py @@ -0,0 +1,321 @@ +from collections import namedtuple +from typing import List, Tuple +from torch import Tensor +from torch.nn import Parameter +import warnings +import numbers +import torch +import torch.nn as nn +import torch.jit as jit +warnings.filterwarnings( + "ignore", + message=r"'layers' was found in ScriptModule constants, but it is a non-constant submodule. Consider removing it." +) + + +def script_lstm(input_size, hidden_size, num_layers, dropout=False, bidirectional=False): + '''Returns a ScriptModule that mimics a PyTorch native LSTM.''' + + if bidirectional: + stack_type = StackedLSTM2 + layer_type = BidirLSTMLayer + dirs = 2 + elif dropout: + stack_type = StackedLSTMWithDropout + layer_type = LSTMLayer + dirs = 1 + else: + stack_type = StackedLSTM + layer_type = LSTMLayer + dirs = 1 + + return stack_type( + num_layers, + layer_type, + first_layer_args=[LSTMCell, input_size, hidden_size], + other_layer_args=[LSTMCell, hidden_size * dirs, hidden_size] + ) + + +def script_lnlstm( + input_size, + hidden_size, + num_layers, + bias=True, + batch_first=False, + dropout=False, + bidirectional=False, + decompose_layernorm=False +): + '''Returns a ScriptModule that mimics a PyTorch native LSTM.''' + + # The following are not implemented. + assert bias + assert not batch_first + assert not dropout + + if bidirectional: + stack_type = StackedLSTM2 + layer_type = BidirLSTMLayer + dirs = 2 + else: + stack_type = StackedLSTM + layer_type = LSTMLayer + dirs = 1 + + return stack_type( + num_layers, + layer_type, + first_layer_args=[LayerNormLSTMCell, input_size, hidden_size, decompose_layernorm], + other_layer_args=[LayerNormLSTMCell, hidden_size * dirs, hidden_size, decompose_layernorm] + ) + + +LSTMState = namedtuple('LSTMState', ['hx', 'cx']) + + +def reverse(lst: List[Tensor]) -> List[Tensor]: + return lst[::-1] + + +class LSTMCell(nn.Module): + + def __init__(self, input_size, hidden_size): + super(LSTMCell, self).__init__() + self.input_size = input_size + self.hidden_size = hidden_size + self.weight_ih = Parameter(torch.randn(4 * hidden_size, input_size)) + self.weight_hh = Parameter(torch.randn(4 * hidden_size, hidden_size)) + self.bias_ih = Parameter(torch.randn(4 * hidden_size)) + self.bias_hh = Parameter(torch.randn(4 * hidden_size)) + + def forward(self, input: Tensor, state: Tuple[Tensor, Tensor]) -> Tuple[Tensor, Tuple[Tensor, Tensor]]: + hx, cx = state + gates = (torch.mm(input, self.weight_ih.t()) + self.bias_ih + torch.mm(hx, self.weight_hh.t()) + self.bias_hh) + ingate, forgetgate, cellgate, outgate = gates.chunk(4, 1) + + ingate = torch.sigmoid(ingate) + forgetgate = torch.sigmoid(forgetgate) + cellgate = torch.tanh(cellgate) + outgate = torch.sigmoid(outgate) + + cy = (forgetgate * cx) + (ingate * cellgate) + hy = outgate * torch.tanh(cy) + + return hy, (hy, cy) + + +class LayerNorm(nn.Module): + + def __init__(self, normalized_shape): + super(LayerNorm, self).__init__() + if isinstance(normalized_shape, numbers.Integral): + normalized_shape = (normalized_shape, ) + normalized_shape = torch.Size(normalized_shape) + + # XXX: This is true for our LSTM / NLP use case and helps simplify code + assert len(normalized_shape) == 1 + + self.weight = Parameter(torch.ones(normalized_shape)) + self.bias = Parameter(torch.zeros(normalized_shape)) + self.normalized_shape = normalized_shape + + def compute_layernorm_stats(self, input): + mu = input.mean(-1, keepdim=True) + sigma = input.std(-1, keepdim=True, unbiased=False) + return mu, sigma + + def forward(self, input): + mu, sigma = self.compute_layernorm_stats(input) + return (input - mu) / sigma * self.weight + self.bias + + +class LayerNormLSTMCell(nn.Module): + + def __init__(self, input_size, hidden_size, decompose_layernorm=False): + super(LayerNormLSTMCell, self).__init__() + self.input_size = input_size + self.hidden_size = hidden_size + self.weight_ih = Parameter(torch.randn(4 * hidden_size, input_size)) + self.weight_hh = Parameter(torch.randn(4 * hidden_size, hidden_size)) + # The layernorms provide learnable biases + + if decompose_layernorm: + ln = LayerNorm + else: + ln = nn.LayerNorm + + self.layernorm_i = ln(4 * hidden_size) + self.layernorm_h = ln(4 * hidden_size) + self.layernorm_c = ln(hidden_size) + + def forward(self, input: Tensor, state: Tuple[Tensor, Tensor]) -> Tuple[Tensor, Tuple[Tensor, Tensor]]: + hx, cx = state + igates = self.layernorm_i(torch.mm(input, self.weight_ih.t())) + hgates = self.layernorm_h(torch.mm(hx, self.weight_hh.t())) + gates = igates + hgates + ingate, forgetgate, cellgate, outgate = gates.chunk(4, 1) + + ingate = torch.sigmoid(ingate) + forgetgate = torch.sigmoid(forgetgate) + cellgate = torch.tanh(cellgate) + outgate = torch.sigmoid(outgate) + + cy = self.layernorm_c((forgetgate * cx) + (ingate * cellgate)) + hy = outgate * torch.tanh(cy) + + return hy, (hy, cy) + + +class LSTMLayer(nn.Module): + + def __init__(self, cell, *cell_args): + super(LSTMLayer, self).__init__() + self.cell = cell(*cell_args) + + def forward(self, input: Tensor, state: Tuple[Tensor, Tensor]) -> Tuple[Tensor, Tuple[Tensor, Tensor]]: + inputs = input.unbind(0) + outputs = torch.jit.annotate(List[Tensor], []) + for i in range(len(inputs)): + out, state = self.cell(inputs[i], state) + outputs += [out] + return torch.stack(outputs), state + + +class ReverseLSTMLayer(nn.Module): + + def __init__(self, cell, *cell_args): + super(ReverseLSTMLayer, self).__init__() + self.cell = cell(*cell_args) + + def forward(self, input: Tensor, state: Tuple[Tensor, Tensor]) -> Tuple[Tensor, Tuple[Tensor, Tensor]]: + inputs = reverse(input.unbind(0)) + outputs = jit.annotate(List[Tensor], []) + for i in range(len(inputs)): + out, state = self.cell(inputs[i], state) + outputs += [out] + return torch.stack(reverse(outputs)), state + + +class BidirLSTMLayer(nn.Module): + __constants__ = ['directions'] + + def __init__(self, cell, *cell_args): + super(BidirLSTMLayer, self).__init__() + self.directions = nn.ModuleList([ + LSTMLayer(cell, *cell_args), + ReverseLSTMLayer(cell, *cell_args), + ]) + + def forward(self, input: Tensor, states: List[Tuple[Tensor, Tensor]]) -> Tuple[Tensor, List[Tuple[Tensor, Tensor]]]: + # List[LSTMState]: [forward LSTMState, backward LSTMState] + outputs = jit.annotate(List[Tensor], []) + output_states = jit.annotate(List[Tuple[Tensor, Tensor]], []) + # XXX: enumerate https://github.com/pytorch/pytorch/issues/14471 + i = 0 + for direction in self.directions: + state = states[i] + out, out_state = direction(input, state) + outputs += [out] + output_states += [out_state] + i += 1 + return torch.cat(outputs, -1), output_states + + +def init_stacked_lstm(num_layers, layer, first_layer_args, other_layer_args): + layers = [layer(*first_layer_args)] + [layer(*other_layer_args) for _ in range(num_layers - 1)] + return nn.ModuleList(layers) + + +class StackedLSTM(nn.Module): + __constants__ = ['layers'] # Necessary for iterating through self.layers + + def __init__(self, num_layers, layer, first_layer_args, other_layer_args): + super(StackedLSTM, self).__init__() + self.layers = init_stacked_lstm(num_layers, layer, first_layer_args, other_layer_args) + + def forward(self, input: Tensor, states: List[Tuple[Tensor, Tensor]]) -> Tuple[Tensor, List[Tuple[Tensor, Tensor]]]: + # List[LSTMState]: One state per layer + output_states = jit.annotate(List[Tuple[Tensor, Tensor]], []) + output = input + # XXX: enumerate https://github.com/pytorch/pytorch/issues/14471 + i = 0 + for rnn_layer in self.layers: + state = states[i] + output, out_state = rnn_layer(output, state) + output_states += [out_state] + i += 1 + return output, output_states + + +# Differs from StackedLSTM in that its forward method takes +# List[List[Tuple[Tensor,Tensor]]]. It would be nice to subclass StackedLSTM +# except we don't support overriding script methods. +# https://github.com/pytorch/pytorch/issues/10733 +class StackedLSTM2(nn.Module): + __constants__ = ['layers'] # Necessary for iterating through self.layers + + def __init__(self, num_layers, layer, first_layer_args, other_layer_args): + super(StackedLSTM2, self).__init__() + self.layers = init_stacked_lstm(num_layers, layer, first_layer_args, other_layer_args) + + def forward(self, input: Tensor, + states: List[List[Tuple[Tensor, Tensor]]]) -> Tuple[Tensor, List[List[Tuple[Tensor, Tensor]]]]: + # List[List[LSTMState]]: The outer list is for layers, + # inner list is for directions. + output_states = jit.annotate(List[List[Tuple[Tensor, Tensor]]], []) + output = input + # XXX: enumerate https://github.com/pytorch/pytorch/issues/14471 + i = 0 + for rnn_layer in self.layers: + state = states[i] + output, out_state = rnn_layer(output, state) + output_states += [out_state] + i += 1 + return output, output_states + + +class StackedLSTMWithDropout(nn.Module): + # Necessary for iterating through self.layers and dropout support + __constants__ = ['layers', 'num_layers'] + + def __init__(self, num_layers, layer, first_layer_args, other_layer_args): + super(StackedLSTMWithDropout, self).__init__() + self.layers = init_stacked_lstm(num_layers, layer, first_layer_args, other_layer_args) + # Introduces a Dropout layer on the outputs of each LSTM layer except + # the last layer, with dropout probability = 0.4. + self.num_layers = num_layers + + if (num_layers == 1): + warnings.warn( + "dropout lstm adds dropout layers after all but last " + "recurrent layer, it expects num_layers greater than " + "1, but got num_layers = 1" + ) + + self.dropout_layer = nn.Dropout(0.4) + + def forward(self, input: Tensor, states: List[Tuple[Tensor, Tensor]]) -> Tuple[Tensor, List[Tuple[Tensor, Tensor]]]: + # List[LSTMState]: One state per layer + output_states = jit.annotate(List[Tuple[Tensor, Tensor]], []) + output = input + # XXX: enumerate https://github.com/pytorch/pytorch/issues/14471 + i = 0 + for rnn_layer in self.layers: + state = states[i] + output, out_state = rnn_layer(output, state) + # Apply the dropout layer except the last layer + if i < self.num_layers - 1: + output = self.dropout_layer(output) + output_states += [out_state] + i += 1 + return output, output_states + + +def test_script_stacked_lnlstm(seq_len, batch, input_size, hidden_size, num_layers): + inp = torch.randn(seq_len, batch, input_size) + states = [LSTMState(torch.randn(batch, hidden_size), torch.randn(batch, hidden_size)) for _ in range(num_layers)] + rnn = script_lnlstm(input_size, hidden_size, num_layers) + + # just a smoke test + out, out_state = rnn(inp, states) diff --git a/dizoo/distar/model/model.py b/dizoo/distar/model/model.py new file mode 100644 index 0000000000..74ef6a208b --- /dev/null +++ b/dizoo/distar/model/model.py @@ -0,0 +1,189 @@ +from collections import OrderedDict +from typing import Dict, Tuple, List +from torch import Tensor + +import os.path as osp +import torch +import torch.nn as nn + +from ding.utils import read_yaml_config, deep_merge_dicts, default_collate +from ding.torch_utils import detach_grad +from dizoo.distar.envs import MAX_SELECTED_UNITS_NUM +from .encoder import Encoder +from .obs_encoder.value_encoder import ValueEncoder +from .lstm import script_lnlstm +from .policy import Policy +from .value import ValueBaseline + +alphastar_model_default_config = read_yaml_config(osp.join(osp.dirname(__file__), "actor_critic_default_config.yaml")) + + +class Model(nn.Module): + + def __init__(self, cfg={}, use_value_network=False, temperature=None): + super(Model, self).__init__() + self.whole_cfg = deep_merge_dicts(alphastar_model_default_config, cfg) + if temperature is not None: + self.whole_cfg.model.temperature = temperature + self.cfg = self.whole_cfg.model + self.encoder = Encoder(self.whole_cfg) + self.policy = Policy(self.whole_cfg) + self._use_value_feature = self.whole_cfg.learner.get('use_value_feature', False) + if use_value_network: + if self._use_value_feature: + self.value_encoder = ValueEncoder(self.whole_cfg) + self.value_networks = nn.ModuleDict() + for k, v in self.cfg.value.items(): + if k in self.cfg.enable_baselines: + # creating a ValueBaseline network for each baseline, to be used in _critic_forward + self.value_networks[v.name] = ValueBaseline(v.param, self._use_value_feature) + # name of needed cumulative stat items + self.only_update_baseline = self.cfg.get('only_update_baseline', False) + self.core_lstm = script_lnlstm( + self.cfg.encoder.core_lstm.input_size, self.cfg.encoder.core_lstm.hidden_size, + self.cfg.encoder.core_lstm.num_layers + ) + + def forward( + self, + spatial_info: Tensor, + entity_info: Dict[str, Tensor], + scalar_info: Dict[str, Tensor], + entity_num: Tensor, + hidden_state: List[Tuple[Tensor, Tensor]], + ): + lstm_input, scalar_context, baseline_feature, entity_embeddings, map_skip = \ + self.encoder(spatial_info, entity_info, scalar_info, entity_num) + lstm_output, out_state = self.core_lstm(lstm_input.unsqueeze(dim=0), hidden_state) + action_info, selected_units_num, logit, extra_units = self.policy( + lstm_output.squeeze(dim=0), entity_embeddings, map_skip, scalar_context, entity_num + ) + return action_info, selected_units_num, out_state + + def compute_logp_action( + self, spatial_info: Tensor, entity_info: Dict[str, Tensor], scalar_info: Dict[str, Tensor], entity_num: Tensor, + hidden_state: List[Tuple[Tensor, Tensor]], **kwargs + ): + lstm_input, scalar_context, baseline_feature, entity_embeddings, map_skip = \ + self.encoder(spatial_info, entity_info, scalar_info, entity_num) + lstm_output, out_state = self.core_lstm(lstm_input.unsqueeze(dim=0), hidden_state) + action_info, selected_units_num, logit, extra_units = self.policy( + lstm_output.squeeze(dim=0), entity_embeddings, map_skip, scalar_context, entity_num + ) + log_action_probs = {} + for k, action in action_info.items(): + dist = torch.distributions.Categorical(logits=logit[k]) + action_log_probs = dist.log_prob(action) + log_action_probs[k] = action_log_probs + return { + 'action_info': action_info, + 'action_logp': log_action_probs, + 'selected_units_num': selected_units_num, + 'entity_num': entity_num, + 'hidden_state': out_state, + 'logit': logit, + 'extra_units': extra_units + } + + def compute_teacher_logit( + self, spatial_info: Tensor, entity_info: Dict[str, Tensor], scalar_info: Dict[str, Tensor], entity_num: Tensor, + hidden_state: List[Tuple[Tensor, Tensor]], selected_units_num, action_info: Dict[str, Tensor], **kwargs + ): + lstm_input, scalar_context, baseline_feature, entity_embeddings, map_skip = \ + self.encoder(spatial_info, entity_info, scalar_info, entity_num) + lstm_output, out_state = self.core_lstm(lstm_input.unsqueeze(dim=0), hidden_state) + action_info, selected_units_num, logit = self.policy.train_forward( + lstm_output.squeeze(dim=0), entity_embeddings, map_skip, scalar_context, entity_num, action_info, + selected_units_num + ) + return { + 'logit': logit, + 'hidden_state': out_state, + 'entity_num': entity_num, + 'selected_units_num': selected_units_num + } + + def rl_learner_forward( + self, spatial_info, entity_info, scalar_info, entity_num, hidden_state, action_info, selected_units_num, + behaviour_logp, teacher_logit, mask, reward, step, batch_size, unroll_len, **kwargs + ): + flat_action_info = {} + for k, val in action_info.items(): + flat_action_info[k] = torch.flatten(val, start_dim=0, end_dim=1) + flat_selected_units_num = torch.flatten(selected_units_num, start_dim=0, end_dim=1) + + lstm_input, scalar_context, baseline_feature, entity_embeddings, map_skip = \ + self.encoder(spatial_info, entity_info, scalar_info, entity_num) + hidden_size = hidden_state[0][0].shape[-1] + + hidden_state = [ + [hidden_state[i][j].view(-1, batch_size, hidden_size)[0, :, :] for j in range(len(hidden_state[i]))] + for i in range(len(hidden_state)) + ] + lstm_output, out_state = self.core_lstm(lstm_input.view(-1, batch_size, lstm_input.shape[-1]), hidden_state) + lstm_output = lstm_output.view(-1, lstm_output.shape[-1]) + + policy_lstm_input = lstm_output.squeeze(dim=0)[:-batch_size] + policy_entity_embeddings = entity_embeddings[:-batch_size] + policy_map_skip = [map[:-batch_size] for map in map_skip] + policy_scalar_context = scalar_context[:-batch_size] + policy_entity_num = entity_num[:-batch_size] + _, _, logits = self.policy.train_forward( + policy_lstm_input, policy_entity_embeddings, policy_map_skip, policy_scalar_context, policy_entity_num, + flat_action_info, flat_selected_units_num + ) + + # logits['selected_units'] = logits['selected_units'].mean(dim=1) + critic_input = lstm_output.squeeze(0) + # add state info + if self.only_update_baseline: + critic_input = detach_grad(critic_input) + baseline_feature = detach_grad(baseline_feature) + if self._use_value_feature: + value_feature = kwargs['value_feature'] + value_feature = self.value_encoder(value_feature) + critic_input = torch.cat([critic_input, value_feature, baseline_feature], dim=1) + baseline_values = {} + for k, v in self.value_networks.items(): + baseline_values[k] = v(critic_input) + for k, val in logits.items(): + logits[k] = val.view(unroll_len, batch_size, *val.shape[1:]) + for k, val in baseline_values.items(): + baseline_values[k] = val.view(unroll_len + 1, batch_size) + outputs = {} + outputs['unroll_len'] = unroll_len + outputs['batch_size'] = batch_size + outputs['selected_units_num'] = selected_units_num + logits['selected_units'] = torch.nn.functional.pad( + logits['selected_units'], ( + 0, + 0, + 0, + MAX_SELECTED_UNITS_NUM - logits['selected_units'].shape[2], + ), 'constant', -1e9 + ) + outputs['target_logit'] = logits + outputs['value'] = baseline_values + outputs['action_log_prob'] = behaviour_logp + outputs['teacher_logit'] = teacher_logit + outputs['mask'] = mask + outputs['action'] = action_info + outputs['reward'] = reward + outputs['step'] = step + + return outputs + + def sl_train( + self, spatial_info, entity_info, scalar_info, entity_num, selected_units_num, traj_lens, hidden_state, + action_info, **kwargs + ): + batch_size = len(traj_lens) + lstm_input, scalar_context, baseline_feature, entity_embeddings, map_skip = \ + self.encoder(spatial_info, entity_info, scalar_info, entity_num) + lstm_input = lstm_input.view(-1, lstm_input.shape[0] // batch_size, lstm_input.shape[-1]).permute(1, 0, 2) + lstm_output, out_state = self.core_lstm(lstm_input, hidden_state) + lstm_output = lstm_output.permute(1, 0, 2).contiguous().view(-1, lstm_output.shape[-1]) + action_info, selected_units_num, logits = self.policy.train_forward( + lstm_output, entity_embeddings, map_skip, scalar_context, entity_num, action_info, selected_units_num + ) + return logits, action_info, out_state diff --git a/dizoo/distar/model/module_utils.py b/dizoo/distar/model/module_utils.py new file mode 100644 index 0000000000..d28d311dfd --- /dev/null +++ b/dizoo/distar/model/module_utils.py @@ -0,0 +1,570 @@ +import torch +import torch.nn as nn +import torch.nn.functional as F +import math +from torch.nn.init import kaiming_normal_, kaiming_uniform_ +from distar.ctools.torch_utils import conv2d_block, sequence_mask, fc_block, build_normalization +from typing import Optional, Dict, Tuple +from torch import Tensor + + +def scatter_connection(shape, project_embeddings, entity_location, scatter_dim, scatter_type='add'): + B, H, W = shape + device = entity_location.device + entity_num = entity_location.shape[1] + index = entity_location.view(-1, 2).long() + bias = torch.arange(B).unsqueeze(1).repeat(1, entity_num).view(-1).to(device) + bias *= H * W + index[:, 0].clamp_(0, W - 1) + index[:, 1].clamp_(0, H - 1) + index = index[:, 1] * W + index[:, 0] # entity_location: (x, y), spatial_info: (y, x) + index += bias + index = index.repeat(scatter_dim, 1) + # flat scatter map and project embeddings + scatter_map = torch.zeros(scatter_dim, B * H * W, device=device) + project_embeddings = project_embeddings.view(-1, scatter_dim).permute(1, 0) + if scatter_type == 'cover': + scatter_map.scatter_(dim=1, index=index, src=project_embeddings) + elif scatter_type == 'add': + scatter_map.scatter_add_(dim=1, index=index, src=project_embeddings) + else: + raise NotImplementedError + scatter_map = scatter_map.reshape(scatter_dim, B, H, W) + scatter_map = scatter_map.permute(1, 0, 2, 3) + return scatter_map + + +class AttentionPool(nn.Module): + + def __init__(self, key_dim, head_num, output_dim, max_num=None): + super(AttentionPool, self).__init__() + self.queries = torch.nn.Parameter(torch.zeros(1, 1, head_num, key_dim)) + torch.nn.init.xavier_uniform_(self.queries) + self.head_num = head_num + self.add_num = False + if max_num is not None: + self.add_num = True + self.num_ebed = torch.nn.Embedding(num_embeddings=max_num, embedding_dim=output_dim) + self.embed_fc = fc_block(key_dim * self.head_num, output_dim) + + def forward(self, x, num=None, mask=None): + assert len(x.shape) == 3 # batch size, tokens, channels + x_with_head = x.unsqueeze(dim=2) # add head dim + score = x_with_head * self.queries + score = score.sum(dim=3) # b, t, h + if mask is not None: + assert len(mask.shape) == 3 and mask.shape[-1] == 1 + mask = mask.repeat(1, 1, self.head_num) + score.masked_fill_(~mask.bool(), value=-1e9) + score = F.softmax(score, dim=1) + x = x.unsqueeze(dim=3).repeat(1, 1, 1, self.head_num) # b, t, c, h + score = score.unsqueeze(dim=2) # b, t, 1, h + x = x * score + x = x.sum(dim=1) # b, c, h + x = x.view(x.shape[0], -1) # b, c * h + x = self.embed_fc(x) # b, c + if self.add_num: + x = x + F.relu(self.num_ebed(num.long())) + x = F.relu(x) + return x + + +class Attention(nn.Module): + + def __init__(self, input_dim, head_dim, output_dim, head_num, dropout): + super(Attention, self).__init__() + self.head_num = head_num + self.head_dim = head_dim + self.dropout = dropout + self.attention_pre = fc_block(input_dim, head_dim * head_num * 3) # query, key, value + self.project = fc_block(head_dim * head_num, output_dim) + + def split(self, x, T: bool = False): + B, N = x.shape[:2] + x = x.view(B, N, self.head_num, self.head_dim) + x = x.permute(0, 2, 1, 3).contiguous() # B, head_num, N, head_dim + if T: + x = x.permute(0, 1, 3, 2).contiguous() + return x + + def forward(self, x, mask: Optional[torch.Tensor] = None): + """ + Overview: + x: [batch_size, seq_len, embeddding_size] + """ + assert (len(x.shape) == 3) + B, N = x.shape[:2] + x = self.attention_pre(x) + query, key, value = torch.chunk(x, 3, dim=2) + query, key, value = self.split(query), self.split(key, T=True), self.split(value) + + score = torch.matmul(query, key) # B, head_num, N, N + score /= math.sqrt(self.head_dim) + if mask is not None: + score.masked_fill_(~mask, value=-1e9) + + score = F.softmax(score, dim=-1) + if self.dropout: + score = self.dropout(score) + attention = torch.matmul(score, value) # B, head_num, N, head_dim + + attention = attention.permute(0, 2, 1, 3).contiguous() # B, N, head_num, head_dim + attention = self.project(attention.view(B, N, -1)) # B, N, output_dim + return attention + + +class TransformerLayer(nn.Module): + + def __init__(self, input_dim, head_dim, hidden_dim, output_dim, head_num, mlp_num, dropout, activation, ln_type): + super(TransformerLayer, self).__init__() + self.attention = Attention(input_dim, head_dim, output_dim, head_num, dropout) + self.layernorm1 = build_normalization('LN')(output_dim) + self.dropout = dropout + layers = [] + dims = [output_dim] + [hidden_dim] * (mlp_num - 1) + [output_dim] + for i in range(mlp_num): + layers.append(fc_block(dims[i], dims[i + 1], activation=activation)) + if self.dropout: + layers.append(self.dropout) + self.mlp = nn.Sequential(*layers) + self.layernorm2 = build_normalization('LN')(output_dim) + self.ln_type = ln_type + + def forward(self, x, mask: Optional[torch.Tensor] = None): + if self.ln_type == 'post': + a = self.attention(x, mask) + if self.dropout: + a = self.dropout(a) + x = self.layernorm1(x + a) + m = self.mlp(x) + if self.dropout: + m = self.dropout(m) + x = self.layernorm2(x + m) + elif self.ln_type == 'pre': + a = self.attention(self.layernorm1(x), mask) + if self.dropout: + a = self.dropout(a) + x = x + a + m = self.mlp(self.layernorm2(x)) + if self.dropout: + m = self.dropout(m) + x = x + m + else: + raise NotImplementedError(self.ln_type) + return x, mask + + +class Transformer(nn.Module): + ''' + Note: + Input has passed through embedding + ''' + + def __init__( + self, + input_dim, + head_dim=128, + hidden_dim=1024, + output_dim=256, + head_num=2, + mlp_num=2, + layer_num=3, + pad_val=0, + dropout_ratio=0.0, + activation=nn.ReLU(), + ln_type='pre' + ): + super(Transformer, self).__init__() + self.embedding = fc_block(input_dim, output_dim, activation=activation) + self.pad_val = pad_val + self.act = activation + layers = [] + dims = [output_dim] + [output_dim] * layer_num + if dropout_ratio > 0: + self.dropout = nn.Dropout(dropout_ratio) + else: + self.dropout = None + for i in range(layer_num): + layers.append( + TransformerLayer( + dims[i], head_dim, hidden_dim, dims[i + 1], head_num, mlp_num, self.dropout, self.act, ln_type + ) + ) + self.layers = nn.ModuleList(layers) + + def forward(self, x, mask: Optional[torch.Tensor] = None): + if mask is not None: + mask = mask.unsqueeze(dim=1).repeat(1, mask.shape[1], 1).unsqueeze(dim=1) + x = self.embedding(x) + if self.dropout: + x = self.dropout(x) + for m in self.layers: + x, mask = m(x, mask) + return x + + +class GatedResBlock(nn.Module): + ''' + Gated Residual Block with conv2d_block by songgl at 2020.10.23 + ''' + + def __init__(self, in_channels, out_channels, kernel_size, stride, padding, activation=nn.ReLU(), norm_type='BN'): + super(GatedResBlock, self).__init__() + assert (stride == 1) + assert (in_channels == out_channels) + self.act = activation + self.conv1 = conv2d_block(in_channels, out_channels, 3, 1, 1, activation=self.act, norm_type=norm_type) + self.conv2 = conv2d_block(out_channels, out_channels, 3, 1, 1, activation=None, norm_type=norm_type) + self.GateWeightG = nn.Sequential( + conv2d_block(out_channels, out_channels, 1, 1, 0, activation=self.act, norm_type=None), + conv2d_block(out_channels, out_channels, 1, 1, 0, activation=self.act, norm_type=None), + conv2d_block(out_channels, out_channels, 1, 1, 0, activation=self.act, norm_type=None), + conv2d_block(out_channels, out_channels, 1, 1, 0, activation=None, norm_type=None) + ) + self.UpdateSP = nn.Parameter(torch.zeros(1)) + nn.init.constant_(self.UpdateSP, 0.1) + + def forward(self, x, NoiseMap): + residual = x + x = self.conv1(x) + x = self.conv2(x) + x = torch.tanh(x * torch.sigmoid(self.GateWeightG(NoiseMap))) * self.UpdateSP + x = self.act(x + residual) + #x = x + residual + return x + + +class FiLM(nn.Module): + """ + A Feature-wise Linear Modulation Layer from + 'FiLM: Visual Reasoning with a General Conditioning Layer' + """ + + def forward(self, x, gammas, betas): + gammas = gammas.unsqueeze(2).unsqueeze(3).expand_as(x) + betas = betas.unsqueeze(2).unsqueeze(3).expand_as(x) + return (gammas * x) + betas + + +class FiLMedResBlock(nn.Module): + + def __init__( + self, + in_dim, + out_dim=None, + with_residual=True, + with_batchnorm=False, + with_cond=[False], + dropout=0, + num_extra_channels=0, + extra_channel_freq=1, + with_input_proj=3, + num_cond_maps=0, + kernel_size=3, + batchnorm_affine=False, + num_layers=1, + condition_method='conv-film', + debug_every=float('inf') + ): + if out_dim is None: + out_dim = in_dim + super(FiLMedResBlock, self).__init__() + self.with_residual = with_residual + self.with_batchnorm = with_batchnorm + self.with_cond = with_cond + self.dropout = dropout + self.extra_channel_freq = 0 if num_extra_channels == 0 else extra_channel_freq + self.with_input_proj = with_input_proj # Kernel size of input projection + self.num_cond_maps = num_cond_maps + self.kernel_size = kernel_size + self.batchnorm_affine = batchnorm_affine + self.num_layers = num_layers + self.condition_method = condition_method + self.debug_every = debug_every + self.film = None + self.bn1 = None + self.drop = None + + if self.with_input_proj % 2 == 0: + raise (NotImplementedError) + if self.kernel_size % 2 == 0: + raise (NotImplementedError) + if self.num_layers >= 2: + raise (NotImplementedError) + + if self.condition_method == 'block-input-film' and self.with_cond[0]: + self.film = FiLM() + if self.with_input_proj: + self.input_proj = nn.Conv2d( + in_dim + (num_extra_channels if self.extra_channel_freq >= 1 else 0), + in_dim, + kernel_size=self.with_input_proj, + padding=self.with_input_proj // 2 + ) + + self.conv1 = nn.Conv2d( + in_dim + self.num_cond_maps + (num_extra_channels if self.extra_channel_freq >= 2 else 0), + out_dim, + kernel_size=self.kernel_size, + padding=self.kernel_size // 2 + ) + if self.condition_method == 'conv-film' and self.with_cond[0]: + self.film = FiLM() + if self.with_batchnorm: + self.bn1 = nn.BatchNorm2d(out_dim, affine=((not self.with_cond[0]) or self.batchnorm_affine)) + if self.condition_method == 'bn-film' and self.with_cond[0]: + self.film = FiLM() + if dropout > 0: + self.drop = nn.Dropout2d(p=self.dropout) + if ((self.condition_method == 'relu-film' or self.condition_method == 'block-output-film') + and self.with_cond[0]): + self.film = FiLM() + + self.init_modules(self.modules()) + + def init_modules(self, modules, init='normal'): + if init.lower() == 'normal': + init_params = kaiming_normal_ + elif init.lower() == 'uniform': + init_params = kaiming_uniform_ + else: + return + for m in modules: + if isinstance(m, (nn.Conv2d, nn.Linear)): + init_params(m.weight) + + def forward( + self, + x, + gammas: Optional[torch.Tensor] = None, + betas: Optional[torch.Tensor] = None, + extra_channels: Optional[torch.Tensor] = None, + cond_maps: Optional[torch.Tensor] = None + ): + + if self.film is not None: + if self.condition_method == 'block-input-film' and self.with_cond[0]: + x = self.film(x, gammas, betas) + + # ResBlock input projection + if self.with_input_proj: + if extra_channels is not None and self.extra_channel_freq >= 1: + x = torch.cat([x, extra_channels], 1) + x = F.relu(self.input_proj(x)) + out = x + + # ResBlock body + if cond_maps is not None: + out = torch.cat([out, cond_maps], 1) + if extra_channels is not None and self.extra_channel_freq >= 2: + out = torch.cat([out, extra_channels], 1) + out = self.conv1(out) + if self.film is not None: + if self.condition_method == 'conv-film' and self.with_cond[0]: + out = self.film(out, gammas, betas) + if self.bn1 is not None: + if self.with_batchnorm: + out = self.bn1(out) + if self.film is not None: + if self.condition_method == 'bn-film' and self.with_cond[0]: + out = self.film(out, gammas, betas) + if self.drop is not None: + if self.dropout > 0: + out = self.drop(out) + # out = F.relu(out) + if self.film is not None: + if self.condition_method == 'relu-film' and self.with_cond[0]: + out = self.film(out, gammas, betas) + + # ResBlock remainder + if self.with_residual: + out = F.relu(x + out) + if self.film is not None: + if self.condition_method == 'block-output-film' and self.with_cond[0]: + out = self.film(out, gammas, betas) + return out + + +class LSTMForwardWrapper(object): + + def _before_forward(self, inputs, prev_state): + assert hasattr(self, 'num_layers') + assert hasattr(self, 'hidden_size') + seq_len, batch_size = inputs.shape[:2] + if prev_state is None: + num_directions = 1 + zeros = torch.zeros( + num_directions * self.num_layers, + batch_size, + self.hidden_size, + dtype=inputs.dtype, + device=inputs.device + ) + prev_state = (zeros, zeros) + elif isinstance(prev_state, list) and len(prev_state) == 2 and isinstance(prev_state[0], torch.Tensor): + pass + elif isinstance(prev_state, list) and len(prev_state) == batch_size: + num_directions = 1 + zeros = torch.zeros( + num_directions * self.num_layers, 1, self.hidden_size, dtype=inputs.dtype, device=inputs.device + ) + state = [] + for prev in prev_state: + if prev is None: + state.append([zeros, zeros]) + else: + state.append(prev) + state = list(zip(*state)) + prev_state = [torch.cat(t, dim=1) for t in state] + return prev_state + + def _after_forward(self, next_state, list_next_state: bool = False): + if list_next_state: + h, c = [torch.stack(t, dim=0) for t in zip(*next_state)] + batch_size = h.shape[1] + next_state = [torch.chunk(h, batch_size, dim=1), torch.chunk(c, batch_size, dim=1)] + next_state = list(zip(*next_state)) + else: + next_state = [torch.stack(t, dim=0) for t in zip(*next_state)] + return next_state + + +class LSTM(nn.Module): + + def __init__(self, input_size, hidden_size, num_layers, norm_type=None, bias=True, dropout=0.): + super(LSTM, self).__init__() + self.input_size = input_size + self.hidden_size = hidden_size + self.num_layers = num_layers + + norm_func = build_normalization(norm_type) + #self.norm = nn.ModuleList([norm_func(hidden_size) for _ in range(4 * num_layers)]) + self.norm_A = nn.ModuleList([norm_func(hidden_size * 4) for _ in range(2 * num_layers)]) + self.norm_B = nn.ModuleList([norm_func(hidden_size) for _ in range(1 * num_layers)]) + self.wx = nn.ParameterList() + self.wh = nn.ParameterList() + dims = [input_size] + [hidden_size] * 3 + for l in range(num_layers): + self.wx.append(nn.Parameter(torch.zeros(dims[l], dims[l + 1] * 4))) + self.wh.append(nn.Parameter(torch.zeros(hidden_size, hidden_size * 4))) + if bias: + self.bias = nn.Parameter(torch.zeros(num_layers, hidden_size * 4)) + else: + self.bias = None + self.use_dropout = dropout > 0. + if self.use_dropout: + self.dropout = nn.Dropout(dropout) + self._init() + + def _init(self): + gain = math.sqrt(1. / self.hidden_size) + for l in range(self.num_layers): + torch.nn.init.uniform_(self.wx[l], -gain, gain) + torch.nn.init.uniform_(self.wh[l], -gain, gain) + if self.bias is not None: + torch.nn.init.uniform_(self.bias[l], -gain, gain) + + # for i in range(len(self.norm_A)): + # torch.nn.init.constant_(self.norm_A[i].weight, 0) + # torch.nn.init.constant_(self.norm_A[i].bias, 1) + # for i in range(len(self.norm_B)): + # torch.nn.init.constant_(self.norm_A[i].weight, 0) + # torch.nn.init.constant_(self.norm_A[i].bias, 1) + + def forward( + self, inputs, prev_state: Tuple[Tensor, Tensor], list_next_state: bool = False, forget_bias: float = 1.0 + ): + ''' + Input: + inputs: tensor of size [seq_len, batch_size, input_size] + prev_state: None or tensor of size [num_directions*num_layers, batch_size, hidden_size] + list_next_state: whether return next_state with list format + ''' + seq_len, batch_size = inputs.shape[:2] + + H, C = prev_state + x = inputs + next_state = [] + for l in range(self.num_layers): + h, c = H[l], C[l] + new_x = [] + for s in range(seq_len): + if self.use_dropout: + gate = self.norm_A[l * 2](torch.matmul(self.dropout(x[s]), self.wx[l]) + ) + self.norm_A[l * 2 + 1](torch.matmul(h, self.wh[l])) + else: + gate = self.norm_A[l * 2](torch.matmul(x[s], self.wx[l]) + ) + self.norm_A[l * 2 + 1](torch.matmul(h, self.wh[l])) + if self.bias is not None: + gate += self.bias[l] + gate = list(torch.chunk(gate, 4, dim=1)) + # for i in range(4): + # gate[i] = self.norm[l * 4 + i](gate[i]) + i, f, o, u = gate + i = torch.sigmoid(i) + f = torch.sigmoid(f + forget_bias) + o = torch.sigmoid(o) + u = torch.tanh(u) + c = f * c + i * u + cc = self.norm_B[l](c) + h = o * torch.tanh(cc) + # if self.use_dropout and l != self.num_layers - 1: # layer input dropout + # h = self.dropout(h) + new_x.append(h) + next_state.append((h, c)) + x = torch.stack(new_x, dim=0) + return x, next_state + + +class PytorchLSTM(nn.LSTM, LSTMForwardWrapper): + + def forward(self, inputs, prev_state, list_next_state: bool = False): + prev_state = self._before_forward(inputs, prev_state) + output, next_state = nn.LSTM.forward(self, inputs, prev_state) + next_state = self._after_forward(next_state, list_next_state) + return output, next_state + + def _after_forward(self, next_state, list_next_state: bool = False): + if list_next_state: + h, c = next_state + batch_size = h.shape[1] + next_state = [torch.chunk(h, batch_size, dim=1), torch.chunk(c, batch_size, dim=1)] + return list(zip(*next_state)) + else: + return next_state + + +def get_lstm(lstm_type, input_size, hidden_size, num_layers, norm_type, dropout=0.): + assert lstm_type in ['normal', 'pytorch'] + if lstm_type == 'normal': + return LSTM(input_size, hidden_size, num_layers, norm_type, dropout=dropout) + elif lstm_type == 'pytorch': + return PytorchLSTM(input_size, hidden_size, num_layers, dropout=dropout) + + +class GLU(nn.Module): + + def __init__(self, input_dim, output_dim, context_dim, input_type='fc'): + super(GLU, self).__init__() + assert (input_type in ['fc', 'conv2d']) + if input_type == 'fc': + self.layer1 = fc_block(context_dim, input_dim) + self.layer2 = fc_block(input_dim, output_dim) + elif input_type == 'conv2d': + self.layer1 = conv2d_block(context_dim, input_dim, 1, 1, 0) + self.layer2 = conv2d_block(input_dim, output_dim, 1, 1, 0) + + def forward(self, x, context): + gate = self.layer1(context) + gate = torch.sigmoid(gate) + x = gate * x + x = self.layer2(x) + return x + + +def build_activation(activation): + act_func = {'relu': nn.ReLU(inplace=True), 'glu': GLU, 'prelu': nn.PReLU(init=0.0)} + if activation in act_func.keys(): + return act_func[activation] + else: + raise KeyError("invalid key for activation: {}".format(activation)) diff --git a/dizoo/distar/model/obs_encoder/__init__.py b/dizoo/distar/model/obs_encoder/__init__.py new file mode 100644 index 0000000000..6a6dc1103e --- /dev/null +++ b/dizoo/distar/model/obs_encoder/__init__.py @@ -0,0 +1,4 @@ +from .scalar_encoder import ScalarEncoder +from .spatial_encoder import SpatialEncoder +from .entity_encoder import EntityEncoder +from .value_encoder import ValueEncoder diff --git a/dizoo/distar/model/obs_encoder/entity_encoder.py b/dizoo/distar/model/obs_encoder/entity_encoder.py new file mode 100644 index 0000000000..56ecf6d24d --- /dev/null +++ b/dizoo/distar/model/obs_encoder/entity_encoder.py @@ -0,0 +1,101 @@ +import torch +import torch.nn as nn +from typing import Dict +from torch import Tensor + +from ding.torch_utils import fc_block, build_activation, sequence_mask, Transformer +from dizoo.distar.envs import MAX_ENTITY_NUM + + +def get_binary_embed_mat(bit_num): + location_embedding = [] + for n in range(2 ** bit_num): + s = '0' * (bit_num - len(bin(n)[2:])) + bin(n)[2:] + location_embedding.append(list(int(i) for i in s)) + return torch.tensor(location_embedding).float() + + +class EntityEncoder(nn.Module): + r''' + B=batch size EN=any number of entities ID=input_dim OS=output_size=256 + (B*EN*ID) (EN'*OS) (EN'*OS) (EN'*OS) (B*EN*OS) + x -> combine -> Transformer -> act -> entity_fc -> split -> entity_embeddings + batch | (B*EN*OS) (B*OS) (B*OS) + \-> split -> mean -> embed_fc -> embedded_entity + ''' + + def __init__(self, cfg): + super(EntityEncoder, self).__init__() + self.encode_modules = nn.ModuleDict() + self.whole_cfg = cfg + self.cfg = self.whole_cfg.model.encoder.obs_encoder.entity_encoder + for k, item in self.cfg.module.items(): + if item['arc'] == 'one_hot': + self.encode_modules[k] = nn.Embedding.from_pretrained( + torch.eye(item['num_embeddings']), freeze=True, padding_idx=None + ) + if item['arc'] == 'binary': + self.encode_modules[k] = torch.nn.Embedding.from_pretrained( + get_binary_embed_mat(item['num_embeddings']), freeze=True, padding_idx=None + ) + self.act = build_activation(self.cfg.activation) + self.transformer = Transformer( + input_dim=self.cfg.input_dim, + head_dim=self.cfg.head_dim, + hidden_dim=self.cfg.hidden_dim, + output_dim=self.cfg.output_dim, + head_num=self.cfg.head_num, + mlp_num=self.cfg.mlp_num, + layer_num=self.cfg.layer_num, + dropout_ratio=self.cfg.dropout_ratio, + activation=self.act, + ) + self.entity_fc = fc_block(self.cfg.output_dim, self.cfg.output_dim, activation=self.act) + self.embed_fc = fc_block(self.cfg.output_dim, self.cfg.output_dim, activation=self.act) + if self.whole_cfg.model.entity_reduce_type == 'attention_pool': + from ding.torch_utils import AttentionPool + self.attention_pool = AttentionPool(key_dim=self.cfg.output_dim, head_num=2, output_dim=self.cfg.output_dim) + elif self.whole_cfg.model.entity_reduce_type == 'attention_pool_add_num': + from ding.torch_utils import AttentionPool + self.attention_pool = AttentionPool( + key_dim=self.cfg.output_dim, head_num=2, output_dim=self.cfg.output_dim, max_num=MAX_ENTITY_NUM + 1 + ) + + def forward(self, x: Dict[str, Tensor], entity_num): + entity_embedding = [] + for k, item in self.cfg.module.items(): + assert k in x.keys(), '{} not in {}'.format(k, x.keys()) + if item['arc'] == 'one_hot': + # check data + over_cross_data = x[k] >= item['num_embeddings'] + # if over_cross_data.any(): + # print(k, x[k][over_cross_data]) + lower_cross_data = x[k] < 0 + if lower_cross_data.any(): + print(k, x[k][lower_cross_data]) + raise RuntimeError + clipped_data = x[k].long().clamp_(max=item['num_embeddings'] - 1) + entity_embedding.append(self.encode_modules[k](clipped_data)) + elif item['arc'] == 'binary': + entity_embedding.append(self.encode_modules[k](x[k].long())) + elif item['arc'] == 'unsqueeze': + entity_embedding.append(x[k].float().unsqueeze(dim=-1)) + x = torch.cat(entity_embedding, dim=-1) + mask = sequence_mask(entity_num, max_len=x.shape[1]) + x = self.transformer(x, mask=mask) + entity_embeddings = self.entity_fc(self.act(x)) + + if self.whole_cfg.model.entity_reduce_type in ['entity_num', 'selected_units_num']: + x_mask = x * mask.unsqueeze(dim=2) + embedded_entity = x_mask.sum(dim=1) / entity_num.unsqueeze(dim=-1) + elif self.whole_cfg.model.entity_reduce_type == 'constant': + x_mask = x * mask.unsqueeze(dim=2) + embedded_entity = x_mask.sum(dim=1) / 512 + elif self.whole_cfg.model.entity_reduce_type == 'attention_pool': + embedded_entity = self.attention_pool(x, mask=mask.unsqueeze(dim=2)) + elif self.whole_cfg.model.entity_reduce_type == 'attention_pool_add_num': + embedded_entity = self.attention_pool(x, num=entity_num, mask=mask.unsqueeze(dim=2)) + else: + raise NotImplementedError + embedded_entity = self.embed_fc(embedded_entity) + return entity_embeddings, embedded_entity, mask diff --git a/dizoo/distar/model/obs_encoder/scalar_encoder.py b/dizoo/distar/model/obs_encoder/scalar_encoder.py new file mode 100644 index 0000000000..83fcae8d03 --- /dev/null +++ b/dizoo/distar/model/obs_encoder/scalar_encoder.py @@ -0,0 +1,145 @@ +from typing import Dict +from torch import Tensor +import torch +import torch.nn as nn +import torch.nn.functional as F +from ding.torch_utils import fc_block, build_activation, Transformer +from .entity_encoder import get_binary_embed_mat + + +def compute_denominator(x: torch.Tensor, dim: int) -> torch.Tensor: + x = x // 2 * 2 + x = torch.div(x, dim) + x = torch.pow(10000., x) + x = torch.div(1., x) + return x + + +class BeginningBuildOrderEncoder(nn.Module): + + def __init__(self, cfg, bo_cfg): + super(BeginningBuildOrderEncoder, self).__init__() + self.whole_cfg = cfg + self.cfg = bo_cfg + self.output_dim = self.cfg.output_dim + self.input_dim = self.cfg.action_one_hot_dim + 20 + self.cfg.binary_dim * 2 + self.act = build_activation(self.cfg.activation) + self.transformer = Transformer( + input_dim=self.input_dim, + head_dim=self.cfg.head_dim, + hidden_dim=self.cfg.output_dim * 2, + output_dim=self.cfg.output_dim + ) + self.embedd_fc = fc_block(self.cfg.output_dim, self.output_dim, activation=self.act) + self.action_one_hot = nn.Embedding.from_pretrained( + torch.eye(self.cfg.action_one_hot_dim), freeze=True, padding_idx=None + ) + self.order_one_hot = nn.Embedding.from_pretrained(torch.eye(20), freeze=True, padding_idx=None) + self.location_binary = nn.Embedding.from_pretrained( + get_binary_embed_mat(self.cfg.binary_dim), freeze=True, padding_idx=None + ) + + def _add_seq_info(self, x): + indices_one_hot = torch.zeros(size=(x.shape[1], x.shape[1]), device=x.device) + indices = torch.arange(x.shape[1], device=x.device).unsqueeze(dim=1) + indices_one_hot = indices_one_hot.scatter_(dim=-1, index=indices, value=1.) + indices_one_hot = indices_one_hot.unsqueeze(0).repeat(x.shape[0], 1, 1) # expand to batch dim + return torch.cat([x, indices_one_hot], dim=2) + + def forward(self, x, bo_location): + x = self.action_one_hot(x.long()) + x = self._add_seq_info(x) + location_x = bo_location % self.whole_cfg.model.spatial_x + location_y = bo_location // self.whole_cfg.model.spatial_x + location_x = self.location_binary(location_x.long()) + location_y = self.location_binary(location_y.long()) + x = torch.cat([x, location_x, location_y], dim=2) + assert len(x.shape) == 3 + x = self.transformer(x) + x = x.mean(dim=1) + x = self.embedd_fc(x) + return x + + +class ScalarEncoder(nn.Module): + + def __init__(self, cfg): + super(ScalarEncoder, self).__init__() + self.whole_cfg = cfg + self.cfg = self.whole_cfg.model.encoder.obs_encoder.scalar_encoder + self.act = build_activation(self.cfg.activation) + self.keys = [] + self.scalar_context_keys = [] + self.baseline_feature_keys = [] + self.one_hot_keys = [] + + self.encode_modules = nn.ModuleDict() + + for k, item in self.cfg.module.items(): + if k == 'time': + continue + if item['arc'] == 'one_hot': + encoder = nn.Embedding(num_embeddings=item['num_embeddings'], embedding_dim=item['embedding_dim']) + torch.nn.init.xavier_uniform_(encoder.weight) + self.encode_modules[k] = encoder + self.one_hot_keys.append(k) + elif item['arc'] == 'fc': + encoder = fc_block(item['input_dim'], item['output_dim'], activation=self.act) + self.encode_modules[k] = encoder + if 'scalar_context' in item.keys() and item['scalar_context']: + self.scalar_context_keys.append(k) + if 'baseline_feature' in item.keys() and item['baseline_feature']: + self.baseline_feature_keys.append(k) + + self.position_array = torch.nn.Parameter( + compute_denominator( + torch.arange(0, self.cfg.module.time.output_dim, dtype=torch.float), self.cfg.module.time.output_dim + ), + requires_grad=False + ) + self.time_embedding_dim = self.cfg.module.time.output_dim + bo_cfg = self.whole_cfg.model.encoder.obs_encoder.scalar_encoder.module.beginning_order + self.encode_modules['beginning_order'] = BeginningBuildOrderEncoder(self.whole_cfg, bo_cfg) + + def time_encoder(self, x: Tensor): + v = torch.zeros(size=(x.shape[0], self.time_embedding_dim), dtype=torch.float, device=x.device) + assert len(x.shape) == 1 + x = x.unsqueeze(dim=1) + v[:, 0::2] = torch.sin(x * self.position_array[0::2]) # even + v[:, 1::2] = torch.cos(x * self.position_array[1::2]) # odd + return v + + def forward(self, x: Dict[str, Tensor]): + embedded_scalar = [] + scalar_context = [] + baseline_feature = [] + + for key, item in self.cfg.module.items(): + assert key in x.keys(), key + if key == 'time': + continue + elif item['arc'] == 'one_hot': + # check data + over_cross_data = x[key] >= item['num_embeddings'] + if over_cross_data.any(): + print(key, x[key][over_cross_data]) + + x[key] = x[key].clamp_(max=item['num_embeddings'] - 1) + embedding = self.encode_modules[key](x[key].long()) + embedding = self.act(embedding) + elif key == 'beginning_order': + embedding = self.encode_modules[key](x[key].float(), x['bo_location'].long()) + else: + embedding = self.encode_modules[key](x[key].float()) + embedded_scalar.append(embedding) + if key in self.scalar_context_keys: + scalar_context.append(embedding) + if key in self.baseline_feature_keys: + baseline_feature.append(embedding) + time_embedding = self.time_encoder(x['time']) + embedded_scalar.append(time_embedding) + embedded_scalar = torch.cat(embedded_scalar, dim=1) + scalar_context = torch.cat(scalar_context, dim=1) + baseline_feature = torch.cat(baseline_feature, dim=1) + + return embedded_scalar, scalar_context, baseline_feature diff --git a/dizoo/distar/model/obs_encoder/spatial_encoder.py b/dizoo/distar/model/obs_encoder/spatial_encoder.py new file mode 100644 index 0000000000..f4dcabf728 --- /dev/null +++ b/dizoo/distar/model/obs_encoder/spatial_encoder.py @@ -0,0 +1,99 @@ +import math +from collections.abc import Sequence +import torch +import torch.nn as nn +import torch.nn.functional as F +from ding.torch_utils import conv2d_block, fc_block, build_activation, ResBlock, same_shape + + +class SpatialEncoder(nn.Module): + __constants__ = ['head_type'] + + def __init__(self, cfg): + super(SpatialEncoder, self).__init__() + self.whole_cfg = cfg + self.cfg = self.whole_cfg.model.encoder.obs_encoder.spatial_encoder + self.act = build_activation(self.cfg.activation) + if self.cfg.norm_type == 'none': + self.norm = None + else: + self.norm = self.cfg.norm_type + self.project = conv2d_block( + self.cfg.input_dim, self.cfg.project_dim, 1, 1, 0, activation=self.act, norm_type=self.norm + ) + dims = [self.cfg.project_dim] + self.cfg.down_channels + self.down_channels = self.cfg.down_channels + self.encode_modules = nn.ModuleDict() + self.downsample = nn.ModuleList() + for k, item in self.cfg.module.items(): + if item['arc'] == 'one_hot': + self.encode_modules[k] = nn.Embedding.from_pretrained( + torch.eye(item['num_embeddings']), freeze=True, padding_idx=None + ) + for i in range(len(self.down_channels)): + if self.cfg.downsample_type == 'conv2d': + self.downsample.append( + conv2d_block(dims[i], dims[i + 1], 4, 2, 1, activation=self.act, norm_type=self.norm) + ) + elif self.cfg.downsample_type in ['avgpool', 'maxpool']: + self.downsample.append( + conv2d_block(dims[i], dims[i + 1], 3, 1, 1, activation=self.act, norm_type=self.norm) + ) + else: + raise KeyError("invalid downsample module type :{}".format(type(self.cfg.downsample_type))) + self.res = nn.ModuleList() + self.head_type = self.cfg.get('head_type', 'pool') + dim = dims[-1] + self.resblock_num = self.cfg.resblock_num + for i in range(self.cfg.resblock_num): + self.res.append(ResBlock(dim, self.act, norm_type=self.norm)) + if self.head_type == 'fc': + self.fc = fc_block( + dim * self.whole_cfg.model.spatial_y // 8 * self.whole_cfg.model.spatial_x // 8, + self.cfg.fc_dim, + activation=self.act + ) + else: + self.gap = nn.AdaptiveAvgPool2d((1, 1)) + self.fc = fc_block(dim, self.cfg.fc_dim, activation=self.act) + + def forward(self, x, scatter_map): + embeddings = [] + for k, item in self.cfg.module.items(): + if item['arc'] == 'one_hot': + embedding = self.encode_modules[k](x[k].long()) + embedding = embedding.permute(0, 3, 1, 2) + embeddings.append(embedding) + elif item['arc'] == 'other': + assert k == 'height_map' + embeddings.append(x[k].unsqueeze(dim=1).float() / 256) + elif item['arc'] == 'scatter': + bs, shape_x, shape_y = x[k].shape[0], self.whole_cfg.model.spatial_x, self.whole_cfg.model.spatial_y + embedding = torch.zeros(bs * shape_y * shape_x, device=x[k].device) + bias = torch.arange(bs, device=x[k].device).unsqueeze(dim=1) * shape_y * shape_x + x[k] = x[k] + bias + x[k] = x[k].view(-1) + embedding[x[k].long()] = 1. + embedding = embedding.view(bs, 1, shape_y, shape_x) + embeddings.append(embedding) + embeddings.append(scatter_map) + x = torch.cat(embeddings, dim=1) + x = self.project(x) + map_skip = [] + for i in range(len(self.downsample)): + map_skip.append(x) + if self.cfg.downsample_type == 'avgpool': + x = torch.nn.functional.avg_pool2d(x, 2, 2) + elif self.cfg.downsample_type == 'maxpool': + x = torch.nn.functional.max_pool2d(x, 2, 2) + x = self.downsample[i](x) + for block in self.res: + map_skip.append(x) + x = block(x) + if isinstance(x, torch.Tensor): + if self.head_type != 'fc': + x = self.gap(x) + + x = x.view(x.shape[0], -1) + x = self.fc(x) + return x, map_skip diff --git a/dizoo/distar/model/obs_encoder/value_encoder.py b/dizoo/distar/model/obs_encoder/value_encoder.py new file mode 100644 index 0000000000..81e42ac838 --- /dev/null +++ b/dizoo/distar/model/obs_encoder/value_encoder.py @@ -0,0 +1,84 @@ +import torch +import torch.nn as nn +import torch.nn.functional as F +from ding.torch_utils import fc_block, build_activation, conv2d_block, ResBlock, same_shape, sequence_mask, \ + Transformer, scatter_connection +from dizoo.distar.envs import BEGIN_ACTIONS +from .spatial_encoder import SpatialEncoder +from .scalar_encoder import BeginningBuildOrderEncoder + + +class ValueEncoder(nn.Module): + + def __init__(self, cfg): + super(ValueEncoder, self).__init__() + self.whole_cfg = cfg + self.cfg = cfg.model.value.encoder + self.act = build_activation('relu') + self.encode_modules = nn.ModuleDict() + for k, item in self.cfg.modules.items(): + if item['arc'] == 'fc': + self.encode_modules[k] = fc_block(item['input_dim'], item['output_dim'], activation=self.act) + elif item['arc'] == 'one_hot': + self.encode_modules[k] = nn.Embedding( + num_embeddings=item['num_embeddings'], embedding_dim=item['embedding_dim'] + ) + + bo_cfg = self.cfg.modules.beginning_order + self.encode_modules['beginning_order'] = BeginningBuildOrderEncoder(self.whole_cfg, bo_cfg) + self.scatter_project = fc_block( + self.cfg.scatter.scatter_input_dim, self.cfg.scatter.scatter_dim, activation=self.act + ) + self.scatter_type = self.cfg.scatter.scatter_type + self.scatter_dim = self.cfg.scatter.scatter_dim + + self.project = conv2d_block( + self.cfg.spatial.input_dim, self.cfg.spatial.project_dim, 1, 1, 0, activation=self.act + ) + down_layers = [] + dims = [self.cfg.spatial.project_dim] + self.cfg.spatial.down_channels + for i in range(len(self.cfg.spatial.down_channels)): + down_layers.append(nn.MaxPool2d(2, 2)) + down_layers.append(conv2d_block(dims[i], dims[i + 1], 3, 1, 1, activation=self.act)) + self.downsample = nn.Sequential(*down_layers) + dim = dims[-1] + self.resblock_num = self.cfg.spatial.resblock_num + self.res = nn.ModuleList() + for i in range(self.resblock_num): + self.res.append(ResBlock(dim, self.act, norm_type=None)) + self.spatial_fc = fc_block( + dim * self.whole_cfg.model.spatial_y // 8 * self.whole_cfg.model.spatial_x // 8, + self.cfg.spatial.spatial_fc_dim, + activation=self.act + ) + + def forward(self, x): + spatial_embedding = [] + fc_embedding = [] + for k, item in self.cfg.modules.items(): + if item['arc'] == 'fc': + embedding = self.encode_modules[k](x[k].float()) + fc_embedding.append(embedding) + if item['arc'] == 'one_hot': + embedding = self.encode_modules[k](x[k].long()) + spatial_embedding.append(embedding) + + bo_embedding = self.encode_modules['beginning_order'](x['beginning_order'].float(), x['bo_location'].long()) + fc_embedding = torch.cat(fc_embedding, dim=-1) + spatial_embedding = torch.cat(spatial_embedding, dim=-1) + project_embedding = self.scatter_project(spatial_embedding) + unit_mask = sequence_mask(x['total_unit_count'], max_len=project_embedding.shape[1]) + project_embedding = project_embedding * unit_mask.unsqueeze(dim=2) + entity_location = torch.cat([x['unit_x'].unsqueeze(dim=-1), x['unit_y'].unsqueeze(dim=-1)], dim=-1) + b, c, h, w = x['own_units_spatial'].shape + scatter_map = scatter_connection( + (b, h, w), project_embedding, entity_location, self.scatter_dim, self.scatter_type + ) + spatial_x = torch.cat([scatter_map, x['own_units_spatial'].float(), x['enemy_units_spatial'].float()], dim=1) + spatial_x = self.project(spatial_x) + spatial_x = self.downsample(spatial_x) + for i in range(self.resblock_num): + spatial_x = self.res[i](spatial_x) + spatial_x = self.spatial_fc(spatial_x.view(spatial_x.shape[0], -1)) + x = torch.cat([fc_embedding, spatial_x, bo_embedding], dim=-1) + return x diff --git a/dizoo/distar/model/policy.py b/dizoo/distar/model/policy.py new file mode 100644 index 0000000000..46587ed652 --- /dev/null +++ b/dizoo/distar/model/policy.py @@ -0,0 +1,79 @@ +from typing import List, Dict, Optional +from torch import Tensor +import torch +import torch.nn as nn + +from dizoo.distar.envs import SELECTED_UNITS_MASK +from .head import DelayHead, QueuedHead, SelectedUnitsHead, TargetUnitHead, LocationHead, ActionTypeHead + + +class Policy(nn.Module): + + def __init__(self, cfg): + super(Policy, self).__init__() + self.whole_cfg = cfg + self.cfg = cfg.model.policy + self.action_type_head = ActionTypeHead(self.whole_cfg) + self.delay_head = DelayHead(self.whole_cfg) + self.queued_head = QueuedHead(self.whole_cfg) + self.selected_units_head = SelectedUnitsHead(self.whole_cfg) + self.target_unit_head = TargetUnitHead(self.whole_cfg) + self.location_head = LocationHead(self.whole_cfg) + + def forward( + self, lstm_output: Tensor, entity_embeddings: Tensor, map_skip: List[Tensor], scalar_context: Tensor, + entity_num: Tensor + ): + action = torch.jit.annotate(Dict[str, Tensor], {}) + logit = torch.jit.annotate(Dict[str, Tensor], {}) + + # action type + logit['action_type'], action['action_type'], embeddings = self.action_type_head(lstm_output, scalar_context) + + #action arg delay + logit['delay'], action['delay'], embeddings = self.delay_head(embeddings) + + logit['queued'], action['queued'], embeddings = self.queued_head(embeddings) + + # selected_units_head cannot be compiled to onnx due to indice + su_mask = SELECTED_UNITS_MASK[action['action_type']] + logit['selected_units'], action['selected_units' + ], embeddings, selected_units_num, extra_units = self.selected_units_head( + embeddings, entity_embeddings, entity_num, None, None, su_mask + ) + + logit['target_unit'], action['target_unit'] = self.target_unit_head(embeddings, entity_embeddings, entity_num) + + logit['target_location'], action['target_location'] = self.location_head(embeddings, map_skip) + + return action, selected_units_num, logit, extra_units + + def train_forward( + self, lstm_output, entity_embeddings, map_skip: List[Tensor], scalar_context, entity_num, action_info, + selected_units_num + ): + action = torch.jit.annotate(Dict[str, Tensor], {}) + logit = torch.jit.annotate(Dict[str, Tensor], {}) + + # action type + logit['action_type'], action['action_type'], embeddings = self.action_type_head( + lstm_output, scalar_context, action_info['action_type'] + ) + + #action arg delay + logit['delay'], action['delay'], embeddings = self.delay_head(embeddings, action_info['delay']) + + logit['queued'], action['queued'], embeddings = self.queued_head(embeddings, action_info['queued']) + + logit['selected_units'], action['selected_units'], embeddings, selected_units_num, _ = self.selected_units_head( + embeddings, entity_embeddings, entity_num, selected_units_num, action_info['selected_units'] + ) + + logit['target_unit'], action['target_unit'] = self.target_unit_head( + embeddings, entity_embeddings, entity_num, action_info['target_unit'] + ) + + logit['target_location'], action['target_location'] = self.location_head( + embeddings, map_skip, action_info['target_location'] + ) + return action, selected_units_num, logit diff --git a/dizoo/distar/model/tests/test_encoder.py b/dizoo/distar/model/tests/test_encoder.py new file mode 100644 index 0000000000..1e64a0701b --- /dev/null +++ b/dizoo/distar/model/tests/test_encoder.py @@ -0,0 +1,31 @@ +from easydict import EasyDict +import pytest +import torch +from ding.utils import read_yaml_config +from ding.utils.data import default_collate +from dizoo.distar.model.encoder import Encoder +from dizoo.distar.envs.fake_data import scalar_info, entity_info, spatial_info + + +@pytest.mark.envtest +def test_encoder(): + B, M = 4, 512 + cfg = read_yaml_config('../actor_critic_default_config.yaml') + cfg = EasyDict(cfg) + encoder = Encoder(cfg) + print(encoder) + + spatial_info_data = default_collate([spatial_info() for _ in range(B)]) + entity_info_data = default_collate([entity_info() for _ in range(B)]) + scalar_info_data = default_collate([scalar_info() for _ in range(B)]) + entity_num = torch.randint(M // 2, M, size=(B, )) + entity_num[-1] = M + + lstm_input, scalar_context, baseline_feature, entity_embeddings, map_skip = encoder( + spatial_info_data, entity_info_data, scalar_info_data, entity_num + ) + assert lstm_input.shape == (B, 1536) + assert scalar_context.shape == (B, 448) + assert baseline_feature.shape == (B, 512) + assert entity_embeddings.shape == (B, 512, 256) + assert isinstance(map_skip, list) and len(map_skip) == 7 diff --git a/dizoo/distar/model/tests/test_value.py b/dizoo/distar/model/tests/test_value.py new file mode 100644 index 0000000000..fcaa0bbaf7 --- /dev/null +++ b/dizoo/distar/model/tests/test_value.py @@ -0,0 +1,23 @@ +import pytest +import torch +from dizoo.distar.model.value import ValueBaseline + + +@pytest.mark.envtest +def test_value_baseline(): + + class CFG: + + def __init__(self): + self.activation = 'relu' + self.norm_type = 'LN' + self.input_dim = 1024 + self.res_dim = 256 + self.res_num = 16 + self.use_value_feature = False + self.atan = True + + model = ValueBaseline(CFG()) + inputs = torch.randn(4, 1024) + output = model(inputs) + assert (output.shape == (4, )) diff --git a/dizoo/distar/model/value.py b/dizoo/distar/model/value.py new file mode 100644 index 0000000000..501b8ebbc8 --- /dev/null +++ b/dizoo/distar/model/value.py @@ -0,0 +1,38 @@ +import torch +import torch.nn as nn +import torch.nn.functional as F +import numpy as np +from ding.torch_utils import fc_block, build_activation, ResFCBlock + + +class ValueBaseline(nn.Module): + ''' + Network to be applied on each baseline input, parameters for the current baseline are defined in the cfg + + input_dim res_dim res_dim 1 + x -> fc (norm & act) -> ResFCBlock*res_num -> fc (no norm no act) -> atan act -> value + ''' + + def __init__(self, cfg): + super(ValueBaseline, self).__init__() + self.act = build_activation(cfg.activation) + if cfg.use_value_feature: + input_dim = cfg.input_dim + 1056 + else: + input_dim = cfg.input_dim + self.project = fc_block(input_dim, cfg.res_dim, activation=self.act, norm_type=None) + blocks = [ResFCBlock(cfg.res_dim, self.act, cfg.norm_type) for _ in range(cfg.res_num)] + self.res = nn.Sequential(*blocks) + self.value_fc = fc_block(cfg.res_dim, 1, activation=None, norm_type=None, init_gain=0.1) + self.atan = cfg.atan + self.PI = np.pi + + def forward(self, x): + x = self.project(x) + x = self.res(x) + x = self.value_fc(x) + + x = x.squeeze(1) + if self.atan: + x = (2.0 / self.PI) * torch.atan((self.PI / 2.0) * x) + return x From 8093b72aa1aaa34d083a88a29728463a3e0dd80c Mon Sep 17 00:00:00 2001 From: niuyazhe Date: Wed, 1 Jun 2022 21:16:41 +0800 Subject: [PATCH 069/229] feature(nyz): polish encoder and value related modules (ci skip) --- ding/torch_utils/network/nn_module.py | 11 ++++-- ding/torch_utils/network/res_block.py | 38 +++++++++++++------ ding/torch_utils/network/rnn.py | 12 +++--- .../torch_utils/network/scatter_connection.py | 4 +- ding/utils/__init__.py | 2 +- ding/utils/default_helper.py | 22 ++++++++++- 6 files changed, 65 insertions(+), 24 deletions(-) diff --git a/ding/torch_utils/network/nn_module.py b/ding/torch_utils/network/nn_module.py index ebc32f9e43..5387e58b58 100644 --- a/ding/torch_utils/network/nn_module.py +++ b/ding/torch_utils/network/nn_module.py @@ -1,9 +1,9 @@ +from typing import Union, Tuple, List, Callable, Optional import math import torch import torch.nn as nn import torch.nn.functional as F from torch.nn.init import xavier_normal_, kaiming_normal_, orthogonal_ -from typing import Union, Tuple, List, Callable from ding.compatibility import torch_gt_131 from .normalization import build_normalization @@ -214,7 +214,8 @@ def fc_block( activation: nn.Module = None, norm_type: str = None, use_dropout: bool = False, - dropout_probability: float = 0.5 + dropout_probability: float = 0.5, + init_gain: Optional[float] = None, ) -> nn.Sequential: r""" Overview: @@ -228,6 +229,7 @@ def fc_block( - norm_type (:obj:`str`): type of the normalization - use_dropout (:obj:`bool`) : whether to use dropout in the fully-connected block - dropout_probability (:obj:`float`) : probability of an element to be zeroed in the dropout. Default: 0.5 + - init_gain (:obj:`float`): FC initialization gain argument, if specified, use xavier with init_gain. Returns: - block (:obj:`nn.Sequential`): a sequential list containing the torch layers of the fully-connected block @@ -237,7 +239,10 @@ def fc_block( """ block = [] block.append(nn.Linear(in_channels, out_channels)) - if norm_type is not None: + if init_gain is not None: + torch.nn.init.xavier_uniform_(block[-1].weight, init_gain) + torch.nn.init.constant_(block[-1].bias, 0.0) + if norm_type is not None and norm_type != 'none': block.append(build_normalization(norm_type, dim=1)(out_channels)) if activation is not None: block.append(activation) diff --git a/ding/torch_utils/network/res_block.py b/ding/torch_utils/network/res_block.py index c9187a8f44..3dcdafa40f 100644 --- a/ding/torch_utils/network/res_block.py +++ b/ding/torch_utils/network/res_block.py @@ -1,7 +1,7 @@ import torch.nn as nn import torch -from .nn_module import conv2d_block, fc_block +from .nn_module import conv2d_block, fc_block, build_normalization class ResBlock(nn.Module): @@ -78,19 +78,28 @@ class ResFCBlock(nn.Module): forward ''' - def __init__(self, in_channels: int, activation: nn.Module = nn.ReLU(), norm_type: str = 'BN'): + def __init__( + self, in_channels: int, activation: nn.Module = nn.ReLU(), norm_type: str = 'BN', final_norm: bool = False + ): r""" Overview: Init the Residual Block Arguments: - in_channels (:obj:`int`): Number of channels in the input tensor - activation (:obj:`nn.Module`): the optional activation function - - norm_type (:obj:`str`): type of the normalization, defalut set to 'BN' + - norm_type (:obj:`str`): type of the normalization, default set to 'BN' + - final_norm (:obj:`bool`): Whether to add norm in final residual output. """ super(ResFCBlock, self).__init__() self.act = activation - self.fc1 = fc_block(in_channels, in_channels, activation=self.act, norm_type=norm_type) - self.fc2 = fc_block(in_channels, in_channels, activation=None, norm_type=norm_type) + self.final_norm = final_norm + if final_norm: + self.fc1 = fc_block(in_channels, in_channels, activation=self.act, norm_type=None) + self.fc2 = fc_block(in_channels, in_channels, activation=None, norm_type=None) + self.norm = build_normalization(norm_type)(in_channels) + else: + self.fc1 = fc_block(in_channels, in_channels, activation=self.act, norm_type=norm_type) + self.fc2 = fc_block(in_channels, in_channels, activation=None, norm_type=norm_type) def forward(self, x: torch.Tensor) -> torch.Tensor: r""" @@ -99,10 +108,17 @@ def forward(self, x: torch.Tensor) -> torch.Tensor: Arguments: - x (:obj:`torch.Tensor`): the input tensor Returns: - - x(:obj:`torch.Tensor`): the resblock output tensor + - x (:obj:`torch.Tensor`): the resblock output tensor """ - residual = x - x = self.fc1(x) - x = self.fc2(x) - x = self.act(x + residual) - return x + if self.final_norm: + residual = x + x = self.fc1(x) + x = self.fc2(x) + x = self.norm(x + residual) + return x + else: + residual = x + x = self.fc1(x) + x = self.fc2(x) + x = self.act(x + residual) + return x diff --git a/ding/torch_utils/network/rnn.py b/ding/torch_utils/network/rnn.py index 0f87ffbcb4..45d3dab5bd 100644 --- a/ding/torch_utils/network/rnn.py +++ b/ding/torch_utils/network/rnn.py @@ -21,15 +21,15 @@ def is_sequence(data): def sequence_mask(lengths: torch.Tensor, max_len: Optional[int] = None) -> torch.BoolTensor: - r""" + """ Overview: - create a mask for a batch sequences with different lengths + Create a mask for a batch sequences with different lengths. Arguments: - - lengths (:obj:`torch.Tensor`): lengths in each different sequences, shape could be (n, 1) or (n) - - max_len (:obj:`int`): the padding size, if max_len is None, the padding size is the \ - max length of sequences + - lengths (:obj:`torch.Tensor`): Lengths in each different sequences, shape could be (n, 1) or (n). + - max_len (:obj:`int`): The padding size, if max_len is None, the padding size is the \ + max length of sequences. Returns: - - masks (:obj:`torch.BoolTensor`): mask has the same device as lengths + - masks (:obj:`torch.BoolTensor`): Mask has the same device as lengths. """ if len(lengths.shape) == 1: lengths = lengths.unsqueeze(dim=1) diff --git a/ding/torch_utils/network/scatter_connection.py b/ding/torch_utils/network/scatter_connection.py index e0385fa240..5b2f3b4ee5 100644 --- a/ding/torch_utils/network/scatter_connection.py +++ b/ding/torch_utils/network/scatter_connection.py @@ -77,11 +77,13 @@ def forward(self, x: torch.Tensor, spatial_size: Tuple[int, int], location: torc device = x.device B, M, N = x.shape H, W = spatial_size - index = location.view(-1, 2) + index = location.view(-1, 2).long() bias = torch.arange(B).mul_(H * W).unsqueeze(1).repeat(1, M).view(-1).to(device) + index = index[:, 0] * W + index[:, 1] index += bias index = index.repeat(N, 1) + x = x.view(-1, N).permute(1, 0) output = torch.zeros(N, B * H * W, device=device) if self.scatter_type == 'cover': diff --git a/ding/utils/__init__.py b/ding/utils/__init__.py index 5fac3c401e..608773c1af 100644 --- a/ding/utils/__init__.py +++ b/ding/utils/__init__.py @@ -3,7 +3,7 @@ from .compression_helper import get_data_compressor, get_data_decompressor from .default_helper import override, dicts_to_lists, lists_to_dicts, squeeze, default_get, error_wrapper, list_split, \ LimitedSpaceContainer, deep_merge_dicts, set_pkg_seed, flatten_dict, one_time_warning, split_data_generator, \ - RunningMeanStd, make_key_as_identifier + RunningMeanStd, make_key_as_identifier, read_yaml_config from .design_helper import SingletonMetaclass from .file_helper import read_file, save_file, remove_file from .import_helper import try_import_ceph, try_import_mc, try_import_link, import_module, try_import_redis, \ diff --git a/ding/utils/default_helper.py b/ding/utils/default_helper.py index 1de84385d1..1f8cba81bb 100644 --- a/ding/utils/default_helper.py +++ b/ding/utils/default_helper.py @@ -1,10 +1,13 @@ from typing import Union, Mapping, List, NamedTuple, Tuple, Callable, Optional, Any, Dict +from functools import lru_cache # in python3.9, we can change to cache +from easydict import EasyDict +import os import copy -from ditk import logging import random -from functools import lru_cache # in python3.9, we can change to cache import numpy as np import torch +import yaml +from ditk import logging def lists_to_dicts( @@ -569,3 +572,18 @@ def legalization(s: str) -> str: new_k = legalization(k) new_data[new_k] = data[k] return new_data + + +def read_yaml_config(path: str) -> EasyDict: + """ + Overview: + Read yaml configuration from given path. + Arguments: + - path (:obj:`str`): Path of source yaml. + Returns: + - cfg (:obj:`EasyDict`): Config data from this file with dict type. + """ + assert os.path.exists(path), path + with open(path, "r") as f: + config = yaml.safe_load(f) + return EasyDict(config) From 83abc64c57a9eb05825159906a4c076479fe6081 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 1 Jun 2022 22:15:49 +0800 Subject: [PATCH 070/229] add locker and model_dict --- ding/framework/middleware/league_actor.py | 34 ++++++++++------------- 1 file changed, 15 insertions(+), 19 deletions(-) diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 90f1c8e21c..ba59c57b46 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -16,6 +16,7 @@ from ding.framework.middleware import BattleCollector from ding.framework.middleware.functional import policy_resetter from ding.league.player import PlayerMeta +from threading import Lock import queue class LeagueActor: @@ -33,13 +34,15 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): task.on(EventEnum.LEARNER_SEND_MODEL, self._on_learner_model) self._policy_resetter = task.wrap(policy_resetter(self.env_num)) self.job_queue = queue.Queue() - self.model_queue = queue.Queue() + self.model_dict = {} + self.model_dict_lock = Lock() def _on_learner_model(self, learner_model: "LearnerModel"): """ If get newest learner model, put it inside model_queue. """ - self.model_queue.put(learner_model) + with self.model_dict_lock: + self.model_dict[learner_model.player_id] = learner_model def _on_league_job(self, job: "Job"): """ @@ -79,25 +82,18 @@ def __call__(self, ctx: "OnlineRLContext"): except queue.Empty: logging.warning("For actor_{}, no Job get from coordinator".format(task.router.node_id)) return - - new_model: "LearnerModel" = None - try: - logging.info( - "Getting new model on actor: {}, player: {}".format(task.router.node_id, ctx.job.launch_player) - ) - new_model = self.model_queue.get(timeout=10) - except queue.Empty: - logging.warning('Cannot get new model, use old model instead on actor: {}, player: {}'.format(task.router.node_id, ctx.job.launch_player)) + job_player_id_list = [player.player_id for player in ctx.job.players] + # TODO: 每次循环开始前把 model_queue 清空 - if new_model is not None: - player_meta = PlayerMeta(player_id=new_model.player_id, checkpoint=None) - policy = self._get_policy(player_meta) - # update policy model - policy.load_state_dict(new_model.state_dict) - logging.info( - "Got new model on actor: {}, player: {}".format(task.router.node_id, ctx.job.launch_player) - ) + with self.model_dict_lock: + for player_id, learner_model in self.model_dict.items(): + if learner_model is not None and player_id in job_player_id_list: + player_meta = PlayerMeta(player_id=player_id, checkpoint=None) + policy = self._get_policy(player_meta) + # update policy model + policy.load_state_dict(learner_model.state_dict) + self.model_dict[player_id] = None collector = self._get_collector(ctx.job.launch_player) current_policies = [] From 604ed59a078ae5fe93defa3c3e2e13b005a6665b Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 1 Jun 2022 23:40:06 +0800 Subject: [PATCH 071/229] change name of vars and add BattleContext --- ding/framework/context.py | 8 +++++ ding/framework/middleware/collector.py | 4 +-- .../middleware/functional/collector.py | 31 +++++++++---------- ding/framework/middleware/league_actor.py | 18 +++++------ 4 files changed, 33 insertions(+), 28 deletions(-) diff --git a/ding/framework/context.py b/ding/framework/context.py index 949e0e7d01..5f5016f93f 100644 --- a/ding/framework/context.py +++ b/ding/framework/context.py @@ -75,3 +75,11 @@ def __init__(self, *args, **kwargs) -> None: self.last_eval_iter = -1 self.keep('train_iter', 'last_eval_iter') + +class BattleContext(Context): + def __init__(self, *args, **kwargs) -> None: + super().__init__(*args, **kwargs) + self.__dict__ = self + + self.all_policies = [] + self.keep('all_policies') \ No newline at end of file diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 4a89fa7353..898b293bde 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -7,7 +7,7 @@ from .actor_data import ActorData # if TYPE_CHECKING: -from ding.framework import OnlineRLContext +from ding.framework import OnlineRLContext, BattleContext from ding.worker.collector.base_serial_collector import CachePool @@ -44,7 +44,7 @@ def __del__(self) -> None: self.end_flag = True self.env.close() - def __call__(self, ctx: "OnlineRLContext") -> None: + def __call__(self, ctx: "BattleContext") -> None: """ Input of ctx: - n_episode (:obj:`int`): the number of collecting data episode diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index f637a3bf77..440cfdd1bb 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -10,7 +10,7 @@ from ding.worker.collector.base_serial_collector import CachePool, TrajBuffer, to_tensor_transitions # if TYPE_CHECKING: -from ding.framework import OnlineRLContext +from ding.framework import OnlineRLContext, BattleContext class TransitionList: @@ -139,11 +139,11 @@ def _rollout(ctx: "OnlineRLContext"): def policy_resetter(env_num: int): - def _policy_resetter(ctx: OnlineRLContext): - if ctx.policies is not None: - assert len(ctx.policies) > 1, "battle collector needs more than 1 policies" - ctx._default_n_episode = ctx.policies[0].get_attribute('cfg').collect.get('n_episode', None) - ctx.agent_num = len(ctx.policies) + def _policy_resetter(ctx: "BattleContext"): + if ctx.current_policies is not None: + assert len(ctx.current_policies) > 1, "battle collector needs more than 1 policies" + ctx._default_n_episode = ctx.current_policies[0].get_attribute('cfg').collect.get('n_episode', None) + ctx.agent_num = len(ctx.current_policies) ctx.traj_len = float("inf") # traj_buffer is {env_id: {policy_id: TrajBuffer}}, is used to store traj_len pieces of transitions ctx.traj_buffer = { @@ -152,17 +152,17 @@ def _policy_resetter(ctx: OnlineRLContext): for env_id in range(env_num) } - for p in ctx.policies: + for p in ctx.current_policies: p.reset() else: - raise RuntimeError('ctx.policies should not be None') + raise RuntimeError('ctx.current_policies should not be None') return _policy_resetter def battle_inferencer(cfg: EasyDict, env: BaseEnvManager, obs_pool: CachePool, policy_output_pool: CachePool): - def _battle_inferencer(ctx: "OnlineRLContext"): + def _battle_inferencer(ctx: "BattleContext"): # Get current env obs. obs = env.ready_obs new_available_env_id = set(obs.keys()).difference(ctx.ready_env_id) @@ -175,7 +175,7 @@ def _battle_inferencer(ctx: "OnlineRLContext"): if cfg.transform_obs: obs = to_tensor(obs, dtype=torch.float32) obs = dicts_to_lists(obs) - policy_output = [p.forward(obs[i], **ctx.policy_kwargs) for i, p in enumerate(ctx.policies)] + policy_output = [p.forward(obs[i], **ctx.policy_kwargs) for i, p in enumerate(ctx.current_policies)] policy_output_pool.update(policy_output) # Interact with env. @@ -191,15 +191,14 @@ def _battle_inferencer(ctx: "OnlineRLContext"): def battle_rolloutor(cfg: EasyDict, env: BaseEnvManager, obs_pool: CachePool, policy_output_pool: CachePool): - def _battle_rolloutor(ctx: "OnlineRLContext"): + def _battle_rolloutor(ctx: "BattleContext"): timesteps = env.step(ctx.actions) for env_id, timestep in timesteps.items(): - # TODO: self.total_envstep_count += 1 ctx.envstep += 1 - for policy_id, _ in enumerate(ctx.policies): + for policy_id, _ in enumerate(ctx.current_policies): policy_timestep_data = [d[policy_id] if not isinstance(d, bool) else d for d in timestep] policy_timestep = type(timestep)(*policy_timestep_data) - transition = ctx.policies[policy_id].process_transition( + transition = ctx.current_policies[policy_id].process_transition( obs_pool[env_id][policy_id], policy_output_pool[env_id][policy_id], policy_timestep ) transition['collect_iter'] = ctx.train_iter @@ -208,7 +207,7 @@ def _battle_rolloutor(ctx: "OnlineRLContext"): if timestep.done: transitions = to_tensor_transitions(ctx.traj_buffer[env_id][policy_id]) if cfg.get_train_sample: - train_sample = ctx.policies[policy_id].get_train_sample(transitions) + train_sample = ctx.current_policies[policy_id].get_train_sample(transitions) ctx.train_data[policy_id].extend(train_sample) else: ctx.train_data[policy_id].append(transitions) @@ -216,7 +215,7 @@ def _battle_rolloutor(ctx: "OnlineRLContext"): if timestep.done: ctx.collected_episode += 1 - for i, p in enumerate(ctx.policies): + for i, p in enumerate(ctx.current_policies): p.reset([env_id]) for i in range(ctx.agent_num): ctx.traj_buffer[env_id][i].clear() diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index ba59c57b46..77635d516e 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -9,7 +9,7 @@ from easydict import EasyDict from ding.envs import BaseEnvManager -from ding.framework import OnlineRLContext +from ding.framework import BattleContext from ding.league.v2.base_league import Job from ding.policy import Policy from ding.framework.middleware.league_learner import LearnerModel @@ -29,7 +29,7 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): # self.n_rollout_samples = self.cfg.policy.collect.get("n_rollout_samples") or 0 self.n_rollout_samples = 64 self._collectors: Dict[str, BattleCollector] = {} - self._policies: Dict[str, "Policy.collect_function"] = {} + self.all_policies: Dict[str, "Policy.collect_function"] = {} task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), self._on_league_job) task.on(EventEnum.LEARNER_SEND_MODEL, self._on_learner_model) self._policy_resetter = task.wrap(policy_resetter(self.env_num)) @@ -61,16 +61,16 @@ def _get_collector(self, player_id: str): def _get_policy(self, player: "PlayerMeta") -> "Policy.collect_function": player_id = player.player_id - if self._policies.get(player_id): - return self._policies.get(player_id) + if self.all_policies.get(player_id): + return self.all_policies.get(player_id) policy: "Policy.collect_function" = self.policy_fn().collect_mode - self._policies[player_id] = policy + self.all_policies[player_id] = policy if "historical" in player.player_id: policy.load_state_dict(player.checkpoint.load()) return policy - def __call__(self, ctx: "OnlineRLContext"): + def __call__(self, ctx: "BattleContext"): # if not self._running: # task.emit("actor_greeting", task.router.node_id) @@ -85,7 +85,6 @@ def __call__(self, ctx: "OnlineRLContext"): job_player_id_list = [player.player_id for player in ctx.job.players] - # TODO: 每次循环开始前把 model_queue 清空 with self.model_dict_lock: for player_id, learner_model in self.model_dict.items(): if learner_model is not None and player_id in job_player_id_list: @@ -96,16 +95,15 @@ def __call__(self, ctx: "OnlineRLContext"): self.model_dict[player_id] = None collector = self._get_collector(ctx.job.launch_player) - current_policies = [] + ctx.current_policies = [] main_player: "PlayerMeta" = None for player in ctx.job.players: - current_policies.append(self._get_policy(player)) + ctx.current_policies.append(self._get_policy(player)) if player.player_id == ctx.job.launch_player: main_player = player # inferencer,rolloutor = self._get_collector(player.player_id) assert main_player, "can not find active player, on actor: {}".format(task.router.node_id) - ctx.policies = current_policies self._policy_resetter(ctx) ctx.n_episode = None From 2ad937d1b67ed93f8340dd64227fa1279337106c Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 1 Jun 2022 23:41:30 +0800 Subject: [PATCH 072/229] debugging --- ding/framework/__init__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ding/framework/__init__.py b/ding/framework/__init__.py index 990b258f6f..f79c44a515 100644 --- a/ding/framework/__init__.py +++ b/ding/framework/__init__.py @@ -1,4 +1,4 @@ -from .context import Context, OnlineRLContext, OfflineRLContext +from .context import Context, OnlineRLContext, OfflineRLContext, BattleContext from .task import Task, task from .parallel import Parallel from .event_loop import EventLoop From bfd149d9d62675a83f4f6567568dd53c642f2101 Mon Sep 17 00:00:00 2001 From: lixl-st <101248619+lixl-st@users.noreply.github.com> Date: Thu, 2 Jun 2022 12:02:37 +0800 Subject: [PATCH 073/229] update quick colab link --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 05c57fcdd8..7c283dc652 100644 --- a/README.md +++ b/README.md @@ -115,7 +115,7 @@ The detailed documentation are hosted on [doc](https://di-engine-docs.readthedoc [3 Minutes Kickoff](https://di-engine-docs.readthedocs.io/en/latest/quick_start/index.html) -[3 Minutes Kickoff (colab)](https://colab.research.google.com/drive/1J29voOD2v9_FXjW-EyTVfRxY_Op_ygef#scrollTo=MIaKQqaZCpGz) +[3 Minutes Kickoff (colab)](https://colab.research.google.com/drive/1K3DGi3dOT9fhFqa6bBtinwCDdWkOM3zE?usp=sharing) [3 分钟上手中文版 (kaggle)](https://www.kaggle.com/fallinx/di-engine/) From 1071dd1378c2c7fc43d2ca8cba1793fec925931d Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Thu, 2 Jun 2022 15:13:19 +0800 Subject: [PATCH 074/229] drop commit "add BattleContext, policy_getter, policy_updater, modify policy_resetter", fix conflicts --- ding/framework/context.py | 3 --- ding/framework/middleware/__init__.py | 1 - ding/framework/middleware/collector.py | 17 ++++---------- .../middleware/functional/__init__.py | 3 ++- .../middleware/{ => functional}/actor_data.py | 0 .../middleware/functional/collector.py | 23 +++++++++++++++++++ ding/framework/middleware/league_actor.py | 15 ++++++++---- .../middleware/tests/test_league_actor.py | 3 ++- .../tests/test_league_actor_one_process.py | 3 ++- 9 files changed, 44 insertions(+), 24 deletions(-) rename ding/framework/middleware/{ => functional}/actor_data.py (100%) diff --git a/ding/framework/context.py b/ding/framework/context.py index 5f5016f93f..d5dd2da9a9 100644 --- a/ding/framework/context.py +++ b/ding/framework/context.py @@ -80,6 +80,3 @@ class BattleContext(Context): def __init__(self, *args, **kwargs) -> None: super().__init__(*args, **kwargs) self.__dict__ = self - - self.all_policies = [] - self.keep('all_policies') \ No newline at end of file diff --git a/ding/framework/middleware/__init__.py b/ding/framework/middleware/__init__.py index 039511d001..8580fc2caf 100644 --- a/ding/framework/middleware/__init__.py +++ b/ding/framework/middleware/__init__.py @@ -4,4 +4,3 @@ from .ckpt_handler import CkptSaver from .league_actor import LeagueActor from .league_coordinator import LeagueCoordinator -from .actor_data import ActorData diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 898b293bde..e80e540bb1 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -3,8 +3,7 @@ from ding.policy import Policy, get_random_policy from ding.envs import BaseEnvManager from ding.framework import task, EventEnum -from .functional import inferencer, rolloutor, TransitionList, battle_inferencer, battle_rolloutor -from .actor_data import ActorData +from .functional import inferencer, rolloutor, TransitionList, battle_inferencer, battle_rolloutor, job_data_sender # if TYPE_CHECKING: from ding.framework import OnlineRLContext, BattleContext @@ -32,6 +31,8 @@ def __init__(self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int): battle_inferencer(self.cfg, self.env, self.obs_pool, self.policy_output_pool) ) self._battle_rolloutor = task.wrap(battle_rolloutor(self.cfg, self.env, self.obs_pool, self.policy_output_pool)) + self._job_data_sender = task.wrap(job_data_sender(self.streaming_sampling_flag, self.n_rollout_samples)) + def __del__(self) -> None: """ @@ -77,20 +78,12 @@ def __call__(self, ctx: "BattleContext") -> None: while True: self._battle_inferencer(ctx) self._battle_rolloutor(ctx) + self.total_envstep_count = ctx.envstep - if not ctx.job.is_eval and self.streaming_sampling_flag is True and len(ctx.train_data[0]) >= self.n_rollout_samples: - actor_data = ActorData(env_step=ctx.envstep, train_data=ctx.train_data[0]) - task.emit(EventEnum.ACTOR_SEND_DATA.format(player=ctx.job.launch_player), actor_data) - ctx.train_data = [[] for _ in range(ctx.agent_num)] + self._job_data_sender(ctx) if ctx.collected_episode >= ctx.n_episode: - ctx.job.result = [e['result'] for e in ctx.episode_info[0]] - task.emit(EventEnum.ACTOR_FINISH_JOB, ctx.job) - if not ctx.job.is_eval and len(ctx.train_data[0]) > 0: - actor_data = ActorData(env_step=ctx.envstep, train_data=ctx.train_data[0]) - task.emit(EventEnum.ACTOR_SEND_DATA.format(player=ctx.job.launch_player), actor_data) - ctx.train_data = [[] for _ in range(ctx.agent_num)] break diff --git a/ding/framework/middleware/functional/__init__.py b/ding/framework/middleware/functional/__init__.py index de028e8834..4997ff1da3 100644 --- a/ding/framework/middleware/functional/__init__.py +++ b/ding/framework/middleware/functional/__init__.py @@ -1,7 +1,7 @@ from .trainer import trainer, multistep_trainer from .data_processor import offpolicy_data_fetcher, data_pusher, offline_data_fetcher, offline_data_saver, \ sqil_data_pusher -from .collector import inferencer, rolloutor, TransitionList, policy_resetter, battle_inferencer, battle_rolloutor +from .collector import inferencer, rolloutor, TransitionList, policy_resetter, battle_inferencer, battle_rolloutor, job_data_sender from .evaluator import interaction_evaluator from .termination_checker import termination_checker from .pace_controller import pace_controller @@ -10,3 +10,4 @@ from .explorer import eps_greedy_handler, eps_greedy_masker from .advantage_estimator import gae_estimator from .enhancer import reward_estimator, her_data_enhancer, nstep_reward_enhancer +from .actor_data import ActorData diff --git a/ding/framework/middleware/actor_data.py b/ding/framework/middleware/functional/actor_data.py similarity index 100% rename from ding/framework/middleware/actor_data.py rename to ding/framework/middleware/functional/actor_data.py diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 440cfdd1bb..eb700c856e 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -8,6 +8,10 @@ from ding.utils import dicts_to_lists from ding.torch_utils import to_tensor, to_ndarray from ding.worker.collector.base_serial_collector import CachePool, TrajBuffer, to_tensor_transitions +from threading import Lock +from ding.league.player import PlayerMeta +from ding.framework import task, EventEnum +from .actor_data import ActorData # if TYPE_CHECKING: from ding.framework import OnlineRLContext, BattleContext @@ -159,6 +163,25 @@ def _policy_resetter(ctx: "BattleContext"): return _policy_resetter +def job_data_sender(streaming_sampling_flag: bool, n_rollout_samples: int): + + def _job_data_sender(ctx: "BattleContext"): + if not ctx.job.is_eval and streaming_sampling_flag is True and len(ctx.train_data[0]) >= n_rollout_samples: + actor_data = ActorData(env_step=ctx.envstep, train_data=ctx.train_data[0]) + task.emit(EventEnum.ACTOR_SEND_DATA.format(player=ctx.job.launch_player), actor_data) + ctx.train_data = [[] for _ in range(ctx.agent_num)] + + if ctx.collected_episode >= ctx.n_episode: + ctx.job.result = [e['result'] for e in ctx.episode_info[0]] + task.emit(EventEnum.ACTOR_FINISH_JOB, ctx.job) + if not ctx.job.is_eval and len(ctx.train_data[0]) > 0: + actor_data = ActorData(env_step=ctx.envstep, train_data=ctx.train_data[0]) + task.emit(EventEnum.ACTOR_SEND_DATA.format(player=ctx.job.launch_player), actor_data) + ctx.train_data = [[] for _ in range(ctx.agent_num)] + + return _job_data_sender + + def battle_inferencer(cfg: EasyDict, env: BaseEnvManager, obs_pool: CachePool, policy_output_pool: CachePool): diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 77635d516e..8fb1a67941 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -70,17 +70,22 @@ def _get_policy(self, player: "PlayerMeta") -> "Policy.collect_function": return policy - def __call__(self, ctx: "BattleContext"): - # if not self._running: - # task.emit("actor_greeting", task.router.node_id) - + def _get_job(self): if self.job_queue.empty(): task.emit(EventEnum.ACTOR_GREETING, task.router.node_id) + job = None try: - ctx.job = self.job_queue.get(timeout=10) + job = self.job_queue.get(timeout=10) except queue.Empty: logging.warning("For actor_{}, no Job get from coordinator".format(task.router.node_id)) + + return job + + def __call__(self, ctx: "BattleContext"): + + ctx.job = self._get_job() + if ctx.job is None: return job_player_id_list = [player.player_id for player in ctx.job.players] diff --git a/ding/framework/middleware/tests/test_league_actor.py b/ding/framework/middleware/tests/test_league_actor.py index 53772a8a30..d71b9b0f3f 100644 --- a/ding/framework/middleware/tests/test_league_actor.py +++ b/ding/framework/middleware/tests/test_league_actor.py @@ -4,7 +4,8 @@ from ding.envs import BaseEnvManager from ding.framework.middleware.league_learner import LearnerModel from ding.framework.middleware.tests.league_config import cfg -from ding.framework.middleware import ActorData, LeagueActor +from ding.framework.middleware import LeagueActor +from ding.framework.middleware.functional import ActorData from ding.league.player import PlayerMeta from ding.framework.storage import FileStorage diff --git a/ding/framework/middleware/tests/test_league_actor_one_process.py b/ding/framework/middleware/tests/test_league_actor_one_process.py index 4aaef8861d..e97610bcf1 100644 --- a/ding/framework/middleware/tests/test_league_actor_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_one_process.py @@ -4,7 +4,8 @@ from ding.envs import BaseEnvManager from ding.framework.middleware.league_learner import LearnerModel from ding.framework.middleware.tests.league_config import cfg -from ding.framework.middleware import ActorData, LeagueActor +from ding.framework.middleware import LeagueActor +from ding.framework.middleware.functional import ActorData from ding.league.player import PlayerMeta from ding.framework.storage import FileStorage From 310c2797ab0f8953fc081cf1b19bb4fb30db63ee Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Thu, 2 Jun 2022 16:29:11 +0800 Subject: [PATCH 075/229] change the logic of update model --- ding/framework/middleware/league_actor.py | 19 +++++++++++-------- 1 file changed, 11 insertions(+), 8 deletions(-) diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 8fb1a67941..9b6da663c6 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -90,16 +90,19 @@ def __call__(self, ctx: "BattleContext"): job_player_id_list = [player.player_id for player in ctx.job.players] - with self.model_dict_lock: - for player_id, learner_model in self.model_dict.items(): - if learner_model is not None and player_id in job_player_id_list: - player_meta = PlayerMeta(player_id=player_id, checkpoint=None) - policy = self._get_policy(player_meta) - # update policy model - policy.load_state_dict(learner_model.state_dict) - self.model_dict[player_id] = None + for player_id in job_player_id_list: + if player_id not in self.model_dict.keys() or self.model_dict[player_id] == None: + continue + else: + learner_model = self.model_dict[player_id] + player_meta = PlayerMeta(player_id=player_id, checkpoint=None) + policy = self._get_policy(player_meta) + # update policy model + policy.load_state_dict(learner_model.state_dict) + self.model_dict[player_id] = None collector = self._get_collector(ctx.job.launch_player) + ctx.current_policies = [] main_player: "PlayerMeta" = None for player in ctx.job.players: From d8a385dbc79bf807612f0bc2c7a68df93244baef Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Thu, 2 Jun 2022 17:36:48 +0800 Subject: [PATCH 076/229] add actor._get_current_policies and collector._update_policies --- ding/framework/middleware/collector.py | 22 ++++++++++++++- ding/framework/middleware/league_actor.py | 33 +++++++++-------------- 2 files changed, 33 insertions(+), 22 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index e80e540bb1..4d219f03f2 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -4,6 +4,7 @@ from ding.envs import BaseEnvManager from ding.framework import task, EventEnum from .functional import inferencer, rolloutor, TransitionList, battle_inferencer, battle_rolloutor, job_data_sender +from typing import Dict # if TYPE_CHECKING: from ding.framework import OnlineRLContext, BattleContext @@ -12,7 +13,7 @@ class BattleCollector: - def __init__(self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int): + def __init__(self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int, model_dict: Dict, all_policies: Dict): self.cfg = cfg self.end_flag = False # self._reset(env) @@ -26,6 +27,8 @@ def __init__(self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int): self.end_flag = False self.n_rollout_samples = n_rollout_samples self.streaming_sampling_flag = n_rollout_samples > 0 + self.model_dict = model_dict + self.all_policies = all_policies self._battle_inferencer = task.wrap( battle_inferencer(self.cfg, self.env, self.obs_pool, self.policy_output_pool) @@ -44,6 +47,22 @@ def __del__(self) -> None: return self.end_flag = True self.env.close() + + def _update_policies(self, job) -> None: + job_player_id_list = [player.player_id for player in job.players] + + for player_id in job_player_id_list: + if self.model_dict.get(player_id) is None: + continue + else: + learner_model = self.model_dict.get(player_id) + policy = self.all_policies.get(player_id) + assert policy, "for player{}, policy should have been initialized already" + # update policy model + policy.load_state_dict(learner_model.state_dict) + self.model_dict[player_id] = None + + def __call__(self, ctx: "BattleContext") -> None: """ @@ -76,6 +95,7 @@ def __call__(self, ctx: "BattleContext") -> None: ctx.ready_env_id = set() ctx.remain_episode = ctx.n_episode while True: + self._update_policies(ctx.job) self._battle_inferencer(ctx) self._battle_rolloutor(ctx) diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 9b6da663c6..26e9c5c6b2 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -55,7 +55,7 @@ def _get_collector(self, player_id: str): return self._collectors.get(player_id) cfg = self.cfg env = self.env_fn() - collector = task.wrap(BattleCollector(cfg.policy.collect.collector, env, self.n_rollout_samples)) + collector = task.wrap(BattleCollector(cfg.policy.collect.collector, env, self.n_rollout_samples, self.model_dict, self.all_policies)) self._collectors[player_id] = collector return collector @@ -82,34 +82,25 @@ def _get_job(self): return job + def _get_current_policies(self, job): + current_policies = [] + main_player: "PlayerMeta" = None + for player in job.players: + current_policies.append(self._get_policy(player)) + if player.player_id == job.launch_player: + main_player = player + return main_player, current_policies + + def __call__(self, ctx: "BattleContext"): ctx.job = self._get_job() if ctx.job is None: return - job_player_id_list = [player.player_id for player in ctx.job.players] - - for player_id in job_player_id_list: - if player_id not in self.model_dict.keys() or self.model_dict[player_id] == None: - continue - else: - learner_model = self.model_dict[player_id] - player_meta = PlayerMeta(player_id=player_id, checkpoint=None) - policy = self._get_policy(player_meta) - # update policy model - policy.load_state_dict(learner_model.state_dict) - self.model_dict[player_id] = None - collector = self._get_collector(ctx.job.launch_player) - ctx.current_policies = [] - main_player: "PlayerMeta" = None - for player in ctx.job.players: - ctx.current_policies.append(self._get_policy(player)) - if player.player_id == ctx.job.launch_player: - main_player = player - # inferencer,rolloutor = self._get_collector(player.player_id) + main_player, ctx.current_policies = self._get_current_policies(ctx.job) assert main_player, "can not find active player, on actor: {}".format(task.router.node_id) self._policy_resetter(ctx) From 07950981a77fe9797250486c05fb31f2c5822fe7 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Mon, 6 Jun 2022 11:08:53 +0800 Subject: [PATCH 077/229] change variable names --- ding/framework/middleware/collector.py | 6 +++--- ding/framework/middleware/functional/collector.py | 2 +- ding/framework/middleware/league_actor.py | 2 +- 3 files changed, 5 insertions(+), 5 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 4d219f03f2..5b52e407eb 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -69,7 +69,7 @@ def __call__(self, ctx: "BattleContext") -> None: Input of ctx: - n_episode (:obj:`int`): the number of collecting data episode - train_iter (:obj:`int`): the number of training iteration - - policy_kwargs (:obj:`dict`): the keyword args for policy forward + - collect_kwargs (:obj:`dict`): the keyword args for policy forward Output of ctx: - ctx.train_data (:obj:`Tuple[List, List]`): A tuple with training sample(data) and episode info, \ the former is a list containing collected episodes if not get_train_sample, \ @@ -83,8 +83,8 @@ def __call__(self, ctx: "BattleContext") -> None: ctx.n_episode = ctx._default_n_episode assert ctx.n_episode >= self.env_num, "Please make sure n_episode >= env_num" - if ctx.policy_kwargs is None: - ctx.policy_kwargs = {} + if ctx.collect_kwargs is None: + ctx.collect_kwargs = {} if self.env.closed: self.env.launch() diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index eb700c856e..4af6e82dd9 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -198,7 +198,7 @@ def _battle_inferencer(ctx: "BattleContext"): if cfg.transform_obs: obs = to_tensor(obs, dtype=torch.float32) obs = dicts_to_lists(obs) - policy_output = [p.forward(obs[i], **ctx.policy_kwargs) for i, p in enumerate(ctx.current_policies)] + policy_output = [p.forward(obs[i], **ctx.collect_kwargs) for i, p in enumerate(ctx.current_policies)] policy_output_pool.update(policy_output) # Interact with env. diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 26e9c5c6b2..5562e2b4a7 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -107,7 +107,7 @@ def __call__(self, ctx: "BattleContext"): ctx.n_episode = None ctx.train_iter = main_player.total_agent_step - ctx.policy_kwargs = None + ctx.collect_kwargs = None collector(ctx) From ab7b5565d3d46a0361b99e5fc2c67d0ef623b8c2 Mon Sep 17 00:00:00 2001 From: lixuelin Date: Mon, 6 Jun 2022 14:48:05 +0800 Subject: [PATCH 078/229] add league policy --- ding/framework/middleware/league_learner.py | 68 +++++++++++++++++++ .../tests/test_league_coordinator.py | 4 ++ .../middleware/tests/test_league_pipeline.py | 2 +- 3 files changed, 73 insertions(+), 1 deletion(-) diff --git a/ding/framework/middleware/league_learner.py b/ding/framework/middleware/league_learner.py index adcdd158b6..103f2877cc 100644 --- a/ding/framework/middleware/league_learner.py +++ b/ding/framework/middleware/league_learner.py @@ -1,4 +1,16 @@ from dataclasses import dataclass +from time import sleep +from os import path as osp +from ding.framework import task, EventEnum +from ding.framework.storage import Storage, FileStorage +from ding.league.player import PlayerMeta +from ding.worker.learner.base_learner import BaseLearner +from typing import TYPE_CHECKING, Callable, Optional +from threading import Lock +if TYPE_CHECKING: + from ding.framework import Context + from ding.framework.middleware.league_actor import ActorData + from ding.league import ActivePlayer @dataclass @@ -6,3 +18,59 @@ class LearnerModel: player_id: str state_dict: dict train_iter: int = 0 + +@dataclass +class LearnerModel: + player_id: str + state_dict: dict + train_iter: int = 0 + +class LeagueLearner: + + def __init__(self, cfg: dict, policy_fn: Callable, player: "ActivePlayer") -> None: + self.cfg = cfg + self.policy_fn = policy_fn + self.player = player + self.player_id = player.player_id + self.checkpoint_prefix = cfg.policy.other.league.path_policy + self._learner = self._get_learner() + task.on(EventEnum.ACTOR_SEND_DATA.format(player=self.player_id), self._on_actor_data) + self._lock = Lock() + + def _on_actor_data(self, actor_data: "ActorData"): + with self._lock: + cfg = self.cfg + for _ in range(cfg.policy.learn.update_per_collect): + self._learner.train(actor_data.train_data, actor_data.env_step) + + self.player.total_agent_step = self._learner.train_iter + checkpoint = self._save_checkpoint() if self.player.is_trained_enough() else None + task.emit( + EventEnum.LEARNER_SEND_META, + PlayerMeta(player_id=self.player_id, checkpoint=checkpoint, total_agent_step=self._learner.train_iter) + ) + + learner_model = LearnerModel( + player_id=self.player_id, state_dict=self._learner.policy.state_dict(), train_iter=self._learner.train_iter + ) + task.emit(EventEnum.LEARNER_SEND_MODEL, learner_model) + + def _get_learner(self) -> BaseLearner: + policy = self.policy_fn().learn_mode + learner = BaseLearner( + self.cfg.policy.learn.learner, + policy, + exp_name=self.cfg.exp_name, + instance_name=self.player_id + '_learner' + ) + return learner + + def _save_checkpoint(self) -> Optional[Storage]: + storage = FileStorage( + path=osp.join(self.checkpoint_prefix, "{}_{}_ckpt.pth".format(self.player_id, self._learner.train_iter)) + ) + storage.save(self._learner.policy.state_dict()) + return storage + + def __call__(self, _: "Context") -> None: + sleep(1) diff --git a/ding/framework/middleware/tests/test_league_coordinator.py b/ding/framework/middleware/tests/test_league_coordinator.py index 2d3a8b65cc..bdaba250a1 100644 --- a/ding/framework/middleware/tests/test_league_coordinator.py +++ b/ding/framework/middleware/tests/test_league_coordinator.py @@ -69,3 +69,7 @@ def _main(): @pytest.mark.unittest def test_coordinator(): Parallel.runner(n_parallel_workers=4, protocol="tcp", topology="star")(_main) + + +if __name__ == "__main__": + Parallel.runner(n_parallel_workers=4, protocol="tcp", topology="star")(_main) diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index a84a4170a9..680298a46f 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -64,7 +64,7 @@ def get_job_info(self, player_id): ] ) -N_ACTORS = 5 +N_ACTORS = 3 def _main(): cfg, env_fn, policy_fn = prepare_test() From 1137a17ee8a626266b09910043b2a92a0e22331a Mon Sep 17 00:00:00 2001 From: lixuelin Date: Mon, 6 Jun 2022 14:52:49 +0800 Subject: [PATCH 079/229] reformat --- ding/framework/context.py | 2 ++ ding/framework/middleware/collector.py | 14 ++++++-------- .../middleware/functional/actor_data.py | 3 ++- .../framework/middleware/functional/collector.py | 6 +++--- ding/framework/middleware/league_actor.py | 16 +++++++++------- ding/framework/middleware/league_coordinator.py | 4 ++-- ding/framework/middleware/league_learner.py | 2 ++ .../tests/test_league_actor_one_process.py | 3 ++- .../middleware/tests/test_league_coordinator.py | 8 +++++--- .../middleware/tests/test_league_pipeline.py | 12 ++++++++---- ding/league/player.py | 1 + 11 files changed, 42 insertions(+), 29 deletions(-) diff --git a/ding/framework/context.py b/ding/framework/context.py index d5dd2da9a9..7111490ea2 100644 --- a/ding/framework/context.py +++ b/ding/framework/context.py @@ -76,7 +76,9 @@ def __init__(self, *args, **kwargs) -> None: self.keep('train_iter', 'last_eval_iter') + class BattleContext(Context): + def __init__(self, *args, **kwargs) -> None: super().__init__(*args, **kwargs) self.__dict__ = self diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 4d219f03f2..d4c7c76fad 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -11,9 +11,12 @@ from ding.worker.collector.base_serial_collector import CachePool + class BattleCollector: - def __init__(self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int, model_dict: Dict, all_policies: Dict): + def __init__( + self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int, model_dict: Dict, all_policies: Dict + ): self.cfg = cfg self.end_flag = False # self._reset(env) @@ -36,7 +39,6 @@ def __init__(self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int, m self._battle_rolloutor = task.wrap(battle_rolloutor(self.cfg, self.env, self.obs_pool, self.policy_output_pool)) self._job_data_sender = task.wrap(job_data_sender(self.streaming_sampling_flag, self.n_rollout_samples)) - def __del__(self) -> None: """ Overview: @@ -47,9 +49,9 @@ def __del__(self) -> None: return self.end_flag = True self.env.close() - + def _update_policies(self, job) -> None: - job_player_id_list = [player.player_id for player in job.players] + job_player_id_list = [player.player_id for player in job.players] for player_id in job_player_id_list: if self.model_dict.get(player_id) is None: @@ -62,8 +64,6 @@ def _update_policies(self, job) -> None: policy.load_state_dict(learner_model.state_dict) self.model_dict[player_id] = None - - def __call__(self, ctx: "BattleContext") -> None: """ Input of ctx: @@ -107,8 +107,6 @@ def __call__(self, ctx: "BattleContext") -> None: break - - class StepCollector: """ Overview: diff --git a/ding/framework/middleware/functional/actor_data.py b/ding/framework/middleware/functional/actor_data.py index 350022052a..2540e1862c 100644 --- a/ding/framework/middleware/functional/actor_data.py +++ b/ding/framework/middleware/functional/actor_data.py @@ -1,7 +1,8 @@ from typing import Any from dataclasses import dataclass + @dataclass class ActorData: train_data: Any - env_step: int = 0 \ No newline at end of file + env_step: int = 0 diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index eb700c856e..92081a4541 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -163,8 +163,9 @@ def _policy_resetter(ctx: "BattleContext"): return _policy_resetter + def job_data_sender(streaming_sampling_flag: bool, n_rollout_samples: int): - + def _job_data_sender(ctx: "BattleContext"): if not ctx.job.is_eval and streaming_sampling_flag is True and len(ctx.train_data[0]) >= n_rollout_samples: actor_data = ActorData(env_step=ctx.envstep, train_data=ctx.train_data[0]) @@ -178,9 +179,8 @@ def _job_data_sender(ctx: "BattleContext"): actor_data = ActorData(env_step=ctx.envstep, train_data=ctx.train_data[0]) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=ctx.job.launch_player), actor_data) ctx.train_data = [[] for _ in range(ctx.agent_num)] - - return _job_data_sender + return _job_data_sender def battle_inferencer(cfg: EasyDict, env: BaseEnvManager, obs_pool: CachePool, policy_output_pool: CachePool): diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 26e9c5c6b2..70007d14d8 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -19,6 +19,7 @@ from threading import Lock import queue + class LeagueActor: def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): @@ -55,7 +56,11 @@ def _get_collector(self, player_id: str): return self._collectors.get(player_id) cfg = self.cfg env = self.env_fn() - collector = task.wrap(BattleCollector(cfg.policy.collect.collector, env, self.n_rollout_samples, self.model_dict, self.all_policies)) + collector = task.wrap( + BattleCollector( + cfg.policy.collect.collector, env, self.n_rollout_samples, self.model_dict, self.all_policies + ) + ) self._collectors[player_id] = collector return collector @@ -79,8 +84,8 @@ def _get_job(self): job = self.job_queue.get(timeout=10) except queue.Empty: logging.warning("For actor_{}, no Job get from coordinator".format(task.router.node_id)) - - return job + + return job def _get_current_policies(self, job): current_policies = [] @@ -91,13 +96,12 @@ def _get_current_policies(self, job): main_player = player return main_player, current_policies - def __call__(self, ctx: "BattleContext"): ctx.job = self._get_job() if ctx.job is None: return - + collector = self._get_collector(ctx.job.launch_player) main_player, ctx.current_policies = self._get_current_policies(ctx.job) @@ -110,5 +114,3 @@ def __call__(self, ctx: "BattleContext"): ctx.policy_kwargs = None collector(ctx) - - diff --git a/ding/framework/middleware/league_coordinator.py b/ding/framework/middleware/league_coordinator.py index 8a50c9f8d1..8db9d9c4e5 100644 --- a/ding/framework/middleware/league_coordinator.py +++ b/ding/framework/middleware/league_coordinator.py @@ -16,7 +16,7 @@ def __init__(self, league: "BaseLeague") -> None: self._lock = Lock() self._total_send_jobs = 0 self._eval_frequency = 10 - + task.on(EventEnum.ACTOR_GREETING, self._on_actor_greeting) task.on(EventEnum.LEARNER_SEND_META, self._on_learner_meta) task.on(EventEnum.ACTOR_FINISH_JOB, self._on_actor_job) @@ -36,7 +36,7 @@ def _on_actor_greeting(self, actor_id): def _on_learner_meta(self, player_meta: "PlayerMeta"): self.league.update_active_player(player_meta) self.league.create_historical_player(player_meta) - + def _on_actor_job(self, job: "Job"): self.league.update_payoff(job) diff --git a/ding/framework/middleware/league_learner.py b/ding/framework/middleware/league_learner.py index 103f2877cc..2e82fee82a 100644 --- a/ding/framework/middleware/league_learner.py +++ b/ding/framework/middleware/league_learner.py @@ -19,12 +19,14 @@ class LearnerModel: state_dict: dict train_iter: int = 0 + @dataclass class LearnerModel: player_id: str state_dict: dict train_iter: int = 0 + class LeagueLearner: def __init__(self, cfg: dict, policy_fn: Callable, player: "ActivePlayer") -> None: diff --git a/ding/framework/middleware/tests/test_league_actor_one_process.py b/ding/framework/middleware/tests/test_league_actor_one_process.py index e97610bcf1..821557a1b7 100644 --- a/ding/framework/middleware/tests/test_league_actor_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_one_process.py @@ -103,5 +103,6 @@ def _test_actor(ctx): task.use(league_actor) task.run() + if __name__ == '__main__': - test_league_actor() \ No newline at end of file + test_league_actor() diff --git a/ding/framework/middleware/tests/test_league_coordinator.py b/ding/framework/middleware/tests/test_league_coordinator.py index bdaba250a1..8a95ca1278 100644 --- a/ding/framework/middleware/tests/test_league_coordinator.py +++ b/ding/framework/middleware/tests/test_league_coordinator.py @@ -45,8 +45,10 @@ def _main(): elif task.router.node_id == 1: # test ACTOR_GREETING res = [] - task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), - lambda job: res.append(job)) + task.on( + EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), + lambda job: res.append(job) + ) for _ in range(3): task.emit(EventEnum.ACTOR_GREETING, task.router.node_id) time.sleep(3) @@ -63,7 +65,7 @@ def _main(): task.emit(EventEnum.ACTOR_FINISH_JOB, job) time.sleep(3) else: - raise Exception("Invalid node id {}".format(task.router.is_active)) + raise Exception("Invalid node id {}".format(task.router.is_active)) @pytest.mark.unittest diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index 680298a46f..8b2d0f5c75 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -16,6 +16,7 @@ from unittest.mock import patch import random + def prepare_test(): global cfg cfg = deepcopy(cfg) @@ -34,6 +35,7 @@ def policy_fn(): return cfg, env_fn, policy_fn + class MockLeague: def __init__(self): @@ -57,15 +59,17 @@ def get_job_info(self, player_id): other_players = [i for i in self.active_players_ids if i != player_id] another_palyer = random.choice(other_players) return Job( - launch_player=player_id, + launch_player=player_id, players=[ PlayerMeta(player_id=player_id, checkpoint=FileStorage(path=None), total_agent_step=0), PlayerMeta(player_id=another_palyer, checkpoint=FileStorage(path=None), total_agent_step=0) ] ) + N_ACTORS = 3 + def _main(): cfg, env_fn, policy_fn = prepare_test() @@ -88,10 +92,10 @@ def _main(): @pytest.mark.unittest def test_league_actor(): - Parallel.runner(n_parallel_workers=N_ACTORS+1, protocol="tcp", topology="mesh")(_main) + Parallel.runner(n_parallel_workers=N_ACTORS + 1, protocol="tcp", topology="mesh")(_main) if __name__ == '__main__': - Parallel.runner(n_parallel_workers=N_ACTORS+1, protocol="tcp", topology="mesh")(_main) + Parallel.runner(n_parallel_workers=N_ACTORS + 1, protocol="tcp", topology="mesh")(_main) # replicas = 10 -# un parallel worker 改成1 \ No newline at end of file +# un parallel worker 改成1 diff --git a/ding/league/player.py b/ding/league/player.py index f5a7d33233..c9f2b28402 100644 --- a/ding/league/player.py +++ b/ding/league/player.py @@ -8,6 +8,7 @@ from .algorithm import pfsp from ding.framework.storage import Storage + @dataclass class PlayerMeta: player_id: str From e9d3b4794c90ca5f3b8495870500de59b3b3e676 Mon Sep 17 00:00:00 2001 From: niuyazhe Date: Mon, 6 Jun 2022 20:23:41 +0800 Subject: [PATCH 080/229] polish(nyz): polish and test distar head --- ding/torch_utils/__init__.py | 2 +- ding/torch_utils/data_helper.py | 14 +- ding/torch_utils/network/__init__.py | 5 +- ding/torch_utils/network/nn_module.py | 35 + ding/torch_utils/network/res_block.py | 26 + .../torch_utils/network/script_lstm.py | 157 +- dizoo/distar/envs/__init__.py | 2 +- dizoo/distar/envs/action_dict.py | 937 ----------- dizoo/distar/envs/meta.py | 1 + dizoo/distar/envs/static_data.py | 1473 ++++++++++++++++- .../model/actor_critic_default_config.yaml | 7 +- dizoo/distar/model/head/action_arg_head.py | 90 +- dizoo/distar/model/head/action_type_head.py | 11 +- dizoo/distar/model/model.py | 15 +- dizoo/distar/model/module_utils.py | 570 ------- dizoo/distar/model/policy.py | 2 +- dizoo/distar/model/tests/test_head.py | 119 ++ 17 files changed, 1717 insertions(+), 1749 deletions(-) rename dizoo/distar/model/lstm.py => ding/torch_utils/network/script_lstm.py (72%) delete mode 100644 dizoo/distar/envs/action_dict.py delete mode 100644 dizoo/distar/model/module_utils.py create mode 100644 dizoo/distar/model/tests/test_head.py diff --git a/ding/torch_utils/__init__.py b/ding/torch_utils/__init__.py index ca48761136..fdc5eeed8d 100644 --- a/ding/torch_utils/__init__.py +++ b/ding/torch_utils/__init__.py @@ -1,6 +1,6 @@ from .checkpoint_helper import build_checkpoint_helper, CountVar, auto_checkpoint from .data_helper import to_device, to_tensor, to_ndarray, to_list, to_dtype, same_shape, tensor_to_list, \ - build_log_buffer, CudaFetcher, get_tensor_data, unsqueeze, get_null_data + build_log_buffer, CudaFetcher, get_tensor_data, unsqueeze, get_null_data, detach_grad from .distribution import CategoricalPd, CategoricalPdPytorch from .metric import levenshtein_distance, hamming_distance from .network import * diff --git a/ding/torch_utils/data_helper.py b/ding/torch_utils/data_helper.py index 9e0b8e7861..a0dd8ba07b 100644 --- a/ding/torch_utils/data_helper.py +++ b/ding/torch_utils/data_helper.py @@ -1,4 +1,4 @@ -from typing import Iterable, Any, Optional, List +from typing import Iterable, Any, Optional, List, Mapping from collections.abc import Sequence import numbers import time @@ -397,3 +397,15 @@ def get_null_data(template: Any, num: int) -> List[Any]: data['reward'].zero_() ret.append(data) return ret + + +def detach_grad(data): + if isinstance(data, Sequence): + for i in range(len(data)): + data[i] = detach_grad(data[i]) + elif isinstance(data, Mapping): + for k in data.keys(): + data[k] = detach_grad(data[k]) + elif isinstance(data, torch.Tensor): + data = data.detach() + return data diff --git a/ding/torch_utils/network/__init__.py b/ding/torch_utils/network/__init__.py index fd661c078a..d22ae36740 100644 --- a/ding/torch_utils/network/__init__.py +++ b/ding/torch_utils/network/__init__.py @@ -1,7 +1,7 @@ from .activation import build_activation, Swish -from .res_block import ResBlock, ResFCBlock +from .res_block import ResBlock, ResFCBlock, GatedConvResBlock from .nn_module import fc_block, conv2d_block, one_hot, deconv2d_block, BilinearUpsample, NearestUpsample, \ - binary_encode, NoiseLinearLayer, noise_block, MLP, Flatten + binary_encode, NoiseLinearLayer, noise_block, MLP, Flatten, AttentionPool from .normalization import build_normalization from .rnn import get_lstm, sequence_mask from .soft_argmax import SoftArgmax @@ -10,3 +10,4 @@ from .resnet import resnet18, ResNet from .gumbel_softmax import GumbelSoftmax from .gtrxl import GTrXL, GRUGatingUnit +from .script_lstm import script_lstm diff --git a/ding/torch_utils/network/nn_module.py b/ding/torch_utils/network/nn_module.py index 5387e58b58..0cf7e4ec6a 100644 --- a/ding/torch_utils/network/nn_module.py +++ b/ding/torch_utils/network/nn_module.py @@ -592,6 +592,41 @@ def noise_block( return sequential_pack(block) +class AttentionPool(nn.Module): + + def __init__(self, key_dim, head_num, output_dim, max_num=None): + super(AttentionPool, self).__init__() + self.queries = torch.nn.Parameter(torch.zeros(1, 1, head_num, key_dim)) + torch.nn.init.xavier_uniform_(self.queries) + self.head_num = head_num + self.add_num = False + if max_num is not None: + self.add_num = True + self.num_ebed = torch.nn.Embedding(num_embeddings=max_num, embedding_dim=output_dim) + self.embed_fc = fc_block(key_dim * self.head_num, output_dim) + + def forward(self, x, num=None, mask=None): + assert len(x.shape) == 3 # batch size, tokens, channels + x_with_head = x.unsqueeze(dim=2) # add head dim + score = x_with_head * self.queries + score = score.sum(dim=3) # b, t, h + if mask is not None: + assert len(mask.shape) == 3 and mask.shape[-1] == 1 + mask = mask.repeat(1, 1, self.head_num) + score.masked_fill_(~mask.bool(), value=-1e9) + score = F.softmax(score, dim=1) + x = x.unsqueeze(dim=3).repeat(1, 1, 1, self.head_num) # b, t, c, h + score = score.unsqueeze(dim=2) # b, t, 1, h + x = x * score + x = x.sum(dim=1) # b, c, h + x = x.view(x.shape[0], -1) # b, c * h + x = self.embed_fc(x) # b, c + if self.add_num: + x = x + F.relu(self.num_ebed(num.long())) + x = F.relu(x) + return x + + class NaiveFlatten(nn.Module): def __init__(self, start_dim: int = 1, end_dim: int = -1) -> None: diff --git a/ding/torch_utils/network/res_block.py b/ding/torch_utils/network/res_block.py index 3dcdafa40f..5e71edde39 100644 --- a/ding/torch_utils/network/res_block.py +++ b/ding/torch_utils/network/res_block.py @@ -122,3 +122,29 @@ def forward(self, x: torch.Tensor) -> torch.Tensor: x = self.fc2(x) x = self.act(x + residual) return x + + +class GatedConvResBlock(nn.Module): + + def __init__(self, in_channels, out_channels, kernel_size, stride, padding, activation=nn.ReLU(), norm_type='BN'): + super(GatedConvResBlock, self).__init__() + assert (stride == 1), stride + assert (in_channels == out_channels), '{}/{}'.format(in_channels, out_channels) + self.act = activation + self.conv1 = conv2d_block(in_channels, out_channels, 3, 1, 1, activation=self.act, norm_type=norm_type) + self.conv2 = conv2d_block(out_channels, out_channels, 3, 1, 1, activation=None, norm_type=norm_type) + self.gate = nn.Sequential( + conv2d_block(out_channels, out_channels, 1, 1, 0, activation=self.act, norm_type=None), + conv2d_block(out_channels, out_channels, 1, 1, 0, activation=self.act, norm_type=None), + conv2d_block(out_channels, out_channels, 1, 1, 0, activation=self.act, norm_type=None), + conv2d_block(out_channels, out_channels, 1, 1, 0, activation=None, norm_type=None) + ) + self.update_sp = nn.Parameter(torch.full((1, ), fill_value=0.1)) + + def forward(self, x, noise_map): + residual = x + x = self.conv1(x) + x = self.conv2(x) + x = torch.tanh(x * torch.sigmoid(self.gate(noise_map))) * self.update_sp + x = self.act(x + residual) + return x diff --git a/dizoo/distar/model/lstm.py b/ding/torch_utils/network/script_lstm.py similarity index 72% rename from dizoo/distar/model/lstm.py rename to ding/torch_utils/network/script_lstm.py index 8671a8ff05..dc695e0961 100644 --- a/dizoo/distar/model/lstm.py +++ b/ding/torch_utils/network/script_lstm.py @@ -1,81 +1,10 @@ -from collections import namedtuple from typing import List, Tuple -from torch import Tensor -from torch.nn import Parameter -import warnings import numbers import torch import torch.nn as nn import torch.jit as jit -warnings.filterwarnings( - "ignore", - message=r"'layers' was found in ScriptModule constants, but it is a non-constant submodule. Consider removing it." -) - - -def script_lstm(input_size, hidden_size, num_layers, dropout=False, bidirectional=False): - '''Returns a ScriptModule that mimics a PyTorch native LSTM.''' - - if bidirectional: - stack_type = StackedLSTM2 - layer_type = BidirLSTMLayer - dirs = 2 - elif dropout: - stack_type = StackedLSTMWithDropout - layer_type = LSTMLayer - dirs = 1 - else: - stack_type = StackedLSTM - layer_type = LSTMLayer - dirs = 1 - - return stack_type( - num_layers, - layer_type, - first_layer_args=[LSTMCell, input_size, hidden_size], - other_layer_args=[LSTMCell, hidden_size * dirs, hidden_size] - ) - - -def script_lnlstm( - input_size, - hidden_size, - num_layers, - bias=True, - batch_first=False, - dropout=False, - bidirectional=False, - decompose_layernorm=False -): - '''Returns a ScriptModule that mimics a PyTorch native LSTM.''' - - # The following are not implemented. - assert bias - assert not batch_first - assert not dropout - - if bidirectional: - stack_type = StackedLSTM2 - layer_type = BidirLSTMLayer - dirs = 2 - else: - stack_type = StackedLSTM - layer_type = LSTMLayer - dirs = 1 - - return stack_type( - num_layers, - layer_type, - first_layer_args=[LayerNormLSTMCell, input_size, hidden_size, decompose_layernorm], - other_layer_args=[LayerNormLSTMCell, hidden_size * dirs, hidden_size, decompose_layernorm] - ) - - -LSTMState = namedtuple('LSTMState', ['hx', 'cx']) - - -def reverse(lst: List[Tensor]) -> List[Tensor]: - return lst[::-1] +from torch import Tensor +from ditk import logging class LSTMCell(nn.Module): @@ -84,10 +13,10 @@ def __init__(self, input_size, hidden_size): super(LSTMCell, self).__init__() self.input_size = input_size self.hidden_size = hidden_size - self.weight_ih = Parameter(torch.randn(4 * hidden_size, input_size)) - self.weight_hh = Parameter(torch.randn(4 * hidden_size, hidden_size)) - self.bias_ih = Parameter(torch.randn(4 * hidden_size)) - self.bias_hh = Parameter(torch.randn(4 * hidden_size)) + self.weight_ih = nn.Parameter(torch.randn(4 * hidden_size, input_size)) + self.weight_hh = nn.Parameter(torch.randn(4 * hidden_size, hidden_size)) + self.bias_ih = nn.Parameter(torch.randn(4 * hidden_size)) + self.bias_hh = nn.Parameter(torch.randn(4 * hidden_size)) def forward(self, input: Tensor, state: Tuple[Tensor, Tensor]) -> Tuple[Tensor, Tuple[Tensor, Tensor]]: hx, cx = state @@ -105,45 +34,16 @@ def forward(self, input: Tensor, state: Tuple[Tensor, Tensor]) -> Tuple[Tensor, return hy, (hy, cy) -class LayerNorm(nn.Module): - - def __init__(self, normalized_shape): - super(LayerNorm, self).__init__() - if isinstance(normalized_shape, numbers.Integral): - normalized_shape = (normalized_shape, ) - normalized_shape = torch.Size(normalized_shape) - - # XXX: This is true for our LSTM / NLP use case and helps simplify code - assert len(normalized_shape) == 1 - - self.weight = Parameter(torch.ones(normalized_shape)) - self.bias = Parameter(torch.zeros(normalized_shape)) - self.normalized_shape = normalized_shape - - def compute_layernorm_stats(self, input): - mu = input.mean(-1, keepdim=True) - sigma = input.std(-1, keepdim=True, unbiased=False) - return mu, sigma - - def forward(self, input): - mu, sigma = self.compute_layernorm_stats(input) - return (input - mu) / sigma * self.weight + self.bias - - class LayerNormLSTMCell(nn.Module): - def __init__(self, input_size, hidden_size, decompose_layernorm=False): + def __init__(self, input_size, hidden_size): super(LayerNormLSTMCell, self).__init__() self.input_size = input_size self.hidden_size = hidden_size - self.weight_ih = Parameter(torch.randn(4 * hidden_size, input_size)) - self.weight_hh = Parameter(torch.randn(4 * hidden_size, hidden_size)) - # The layernorms provide learnable biases + self.weight_ih = nn.Parameter(torch.randn(4 * hidden_size, input_size)) + self.weight_hh = nn.Parameter(torch.randn(4 * hidden_size, hidden_size)) - if decompose_layernorm: - ln = LayerNorm - else: - ln = nn.LayerNorm + ln = nn.LayerNorm self.layernorm_i = ln(4 * hidden_size) self.layernorm_h = ln(4 * hidden_size) @@ -182,6 +82,10 @@ def forward(self, input: Tensor, state: Tuple[Tensor, Tensor]) -> Tuple[Tensor, return torch.stack(outputs), state +def reverse(lst: List[Tensor]) -> List[Tensor]: + return lst[::-1] + + class ReverseLSTMLayer(nn.Module): def __init__(self, cell, *cell_args): @@ -287,7 +191,7 @@ def __init__(self, num_layers, layer, first_layer_args, other_layer_args): self.num_layers = num_layers if (num_layers == 1): - warnings.warn( + logging.warning( "dropout lstm adds dropout layers after all but last " "recurrent layer, it expects num_layers greater than " "1, but got num_layers = 1" @@ -312,10 +216,29 @@ def forward(self, input: Tensor, states: List[Tuple[Tensor, Tensor]]) -> Tuple[T return output, output_states -def test_script_stacked_lnlstm(seq_len, batch, input_size, hidden_size, num_layers): - inp = torch.randn(seq_len, batch, input_size) - states = [LSTMState(torch.randn(batch, hidden_size), torch.randn(batch, hidden_size)) for _ in range(num_layers)] - rnn = script_lnlstm(input_size, hidden_size, num_layers) +def script_lstm(input_size, hidden_size, num_layers, dropout=False, bidirectional=False, LN=False): + '''Returns a ScriptModule that mimics a PyTorch native LSTM.''' - # just a smoke test - out, out_state = rnn(inp, states) + if bidirectional: + stack_type = StackedLSTM2 + layer_type = BidirLSTMLayer + dirs = 2 + elif dropout: + stack_type = StackedLSTMWithDropout + layer_type = LSTMLayer + dirs = 1 + else: + stack_type = StackedLSTM + layer_type = LSTMLayer + dirs = 1 + if LN: + cell = LayerNormLSTMCell + else: + cell = LSTMCell + + return stack_type( + num_layers, + layer_type, + first_layer_args=[cell, input_size, hidden_size], + other_layer_args=[cell, hidden_size * dirs, hidden_size] + ) diff --git a/dizoo/distar/envs/__init__.py b/dizoo/distar/envs/__init__.py index 729cd76ef8..66f1c31e80 100644 --- a/dizoo/distar/envs/__init__.py +++ b/dizoo/distar/envs/__init__.py @@ -1,2 +1,2 @@ from .meta import * -from .static_data import BEGIN_ACTIONS +from .static_data import BEGIN_ACTIONS, ACTION_RACE_MASK, SELECTED_UNITS_MASK diff --git a/dizoo/distar/envs/action_dict.py b/dizoo/distar/envs/action_dict.py deleted file mode 100644 index 470ed978ee..0000000000 --- a/dizoo/distar/envs/action_dict.py +++ /dev/null @@ -1,937 +0,0 @@ -import numpy as np -from copy import deepcopy - -ACTION_INFO_MASK = \ - { - 0: {'name': 'no_op', 'func_type': 'raw_no_op', 'ability_id': None, 'general_id': None, 'goal': 'other', 'special_goal': None, 'queued': False, 'selected_units': False, 'target_unit': False, 'target_location': False}, - 168: {'name': 'raw_move_camera', 'func_type': 'raw_move_camera', 'ability_id': None, 'general_id': None, 'goal': 'other', 'special_goal': None, 'queued': False, 'selected_units': False, 'target_unit': False, 'target_location': True}, - 2: {'name': 'Attack_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3674, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BATTLECRUISER', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MEDIVAC', 'TERRAN_MISSILETURRET', 'TERRAN_MULE', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_RAVEN', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'TERRAN_WIDOWMINE', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CHANGELING', 'ZERG_CHANGELINGMARINE', 'ZERG_CHANGELINGMARINESHIELD', 'ZERG_CHANGELINGZEALOT', 'ZERG_CHANGELINGZERGLING', 'ZERG_CHANGELINGZERGLINGWINGS', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTOR', 'ZERG_INFESTORBURROWED', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMP', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_OVERLORD', 'ZERG_OVERLORDTRANSPORT', 'ZERG_OVERSEER', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_ROACHBURROWED', 'ZERG_SPINECRAWLER', 'ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLER', 'ZERG_SPORECRAWLERUPROOTED', 'ZERG_SWARMHOSTMP', 'ZERG_ULTRALISK', 'ZERG_VIPER', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ADEPTPHASESHIFT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 57, 24, 692, 50, 53, 484, 689, 734, 51, 48, 54, 23, 268, 130, 56, 49, 45, 33, 32, 52, 691, 34, 35, 498, 9, 289, 114, 12, 15, 14, 13, 17, 16, 112, 104, 107, 111, 127, 7, 489, 693, 502, 503, 108, 106, 893, 129, 126, 688, 110, 118, 98, 139, 99, 140, 494, 109, 499, 105, 311, 801, 141, 79, 4, 76, 694, 733, 75, 83, 85, 10, 488, 82, 495, 78, 66, 84, 894, 77, 74, 496, 80, 81, 73]}, - 3: {'name': 'Attack_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3674, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BATTLECRUISER', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MEDIVAC', 'TERRAN_MISSILETURRET', 'TERRAN_MULE', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_RAVEN', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'TERRAN_WIDOWMINE', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CHANGELING', 'ZERG_CHANGELINGMARINE', 'ZERG_CHANGELINGMARINESHIELD', 'ZERG_CHANGELINGZEALOT', 'ZERG_CHANGELINGZERGLING', 'ZERG_CHANGELINGZERGLINGWINGS', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTOR', 'ZERG_INFESTORBURROWED', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMP', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_OVERLORD', 'ZERG_OVERLORDTRANSPORT', 'ZERG_OVERSEER', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_ROACHBURROWED', 'ZERG_SPINECRAWLER', 'ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLER', 'ZERG_SPORECRAWLERUPROOTED', 'ZERG_SWARMHOSTMP', 'ZERG_ULTRALISK', 'ZERG_VIPER', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ADEPTPHASESHIFT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 57, 24, 692, 50, 53, 484, 689, 734, 51, 48, 54, 23, 268, 130, 56, 49, 45, 33, 32, 52, 691, 34, 35, 498, 9, 289, 114, 12, 15, 14, 13, 17, 16, 112, 104, 107, 111, 127, 7, 489, 693, 502, 503, 108, 106, 893, 129, 126, 688, 110, 118, 98, 139, 99, 140, 494, 109, 499, 105, 311, 801, 141, 79, 4, 76, 694, 733, 75, 83, 85, 10, 488, 82, 495, 78, 66, 84, 894, 77, 74, 496, 80, 81, 73]}, - 4: {'name': 'Attack_Attack_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 23, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MISSILETURRET', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_SPINECRAWLER', 'ZERG_SPORECRAWLER', 'ZERG_ULTRALISK', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 24, 692, 50, 53, 484, 689, 734, 51, 48, 23, 130, 49, 45, 33, 32, 52, 691, 34, 35, 9, 289, 114, 112, 104, 107, 7, 489, 693, 503, 108, 126, 688, 110, 98, 99, 109, 105, 311, 141, 79, 4, 76, 83, 85, 10, 488, 78, 66, 84, 894, 77, 74, 496, 80, 73]}, - 6: {'name': 'Attack_AttackBuilding_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2048, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MISSILETURRET', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_SPINECRAWLER', 'ZERG_SPORECRAWLER', 'ZERG_ULTRALISK', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 24, 692, 50, 53, 484, 689, 734, 51, 48, 23, 130, 49, 45, 33, 32, 52, 691, 34, 35, 9, 289, 114, 112, 104, 107, 7, 489, 693, 503, 108, 126, 688, 110, 98, 99, 109, 105, 311, 141, 79, 4, 76, 83, 85, 10, 488, 78, 66, 84, 894, 77, 74, 496, 80, 73]}, - 5: {'name': 'Attack_Attack_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 23, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MISSILETURRET', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_SPINECRAWLER', 'ZERG_SPORECRAWLER', 'ZERG_ULTRALISK', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 24, 692, 50, 53, 484, 689, 734, 51, 48, 23, 130, 49, 45, 33, 32, 52, 691, 34, 35, 9, 289, 114, 112, 104, 107, 7, 489, 693, 503, 108, 126, 688, 110, 98, 99, 109, 105, 311, 141, 79, 4, 76, 83, 85, 10, 488, 78, 66, 84, 894, 77, 74, 496, 80, 73]}, - 7: {'name': 'Attack_AttackBuilding_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2048, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MISSILETURRET', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_SPINECRAWLER', 'ZERG_SPORECRAWLER', 'ZERG_ULTRALISK', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 24, 692, 50, 53, 484, 689, 734, 51, 48, 23, 130, 49, 45, 33, 32, 52, 691, 34, 35, 9, 289, 114, 112, 104, 107, 7, 489, 693, 503, 108, 126, 688, 110, 98, 99, 109, 105, 311, 141, 79, 4, 76, 83, 85, 10, 488, 78, 66, 84, 894, 77, 74, 496, 80, 73]}, - 539: {'name': 'Attack_Battlecruiser_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3771, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_BATTLECRUISER'], 'avail_unit_type_id': [57]}, - 540: {'name': 'Attack_Battlecruiser_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3771, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_BATTLECRUISER'], 'avail_unit_type_id': [57]}, - 8: {'name': 'Attack_Redirect_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1682, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MISSILETURRET', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_SPINECRAWLER', 'ZERG_SPORECRAWLER', 'ZERG_ULTRALISK', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 24, 692, 50, 53, 484, 689, 734, 51, 48, 23, 130, 49, 45, 33, 32, 52, 691, 34, 35, 9, 289, 114, 112, 104, 107, 7, 489, 693, 503, 108, 126, 688, 110, 98, 99, 109, 105, 311, 141, 79, 4, 76, 83, 85, 10, 488, 78, 66, 84, 894, 77, 74, 496, 80, 73]}, - 9: {'name': 'Attack_Redirect_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 1682, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MISSILETURRET', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_SPINECRAWLER', 'ZERG_SPORECRAWLER', 'ZERG_ULTRALISK', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 24, 692, 50, 53, 484, 689, 734, 51, 48, 23, 130, 49, 45, 33, 32, 52, 691, 34, 35, 9, 289, 114, 112, 104, 107, 7, 489, 693, 503, 108, 126, 688, 110, 98, 99, 109, 105, 311, 141, 79, 4, 76, 83, 85, 10, 488, 78, 66, 84, 894, 77, 74, 496, 80, 73]}, - 88: {'name': 'Behavior_BuildingAttackOff_quick', 'func_type': 'raw_cmd', 'ability_id': 2082, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_BANELING'], 'avail_unit_type_id': [9]}, - 87: {'name': 'Behavior_BuildingAttackOn_quick', 'func_type': 'raw_cmd', 'ability_id': 2081, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_BANELING'], 'avail_unit_type_id': [9]}, - 169: {'name': 'Behavior_CloakOff_quick', 'func_type': 'raw_cmd', 'ability_id': 3677, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_BANSHEE', 'TERRAN_GHOST'], 'avail_unit_type_id': [55, 50]}, - 170: {'name': 'Behavior_CloakOff_Banshee_quick', 'func_type': 'raw_cmd', 'ability_id': 393, 'general_id': 3677, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_BANSHEE'], 'avail_unit_type_id': [55]}, - 171: {'name': 'Behavior_CloakOff_Ghost_quick', 'func_type': 'raw_cmd', 'ability_id': 383, 'general_id': 3677, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, - 172: {'name': 'Behavior_CloakOn_quick', 'func_type': 'raw_cmd', 'ability_id': 3676, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_BANSHEE', 'TERRAN_GHOST'], 'avail_unit_type_id': [55, 50]}, - 173: {'name': 'Behavior_CloakOn_Banshee_quick', 'func_type': 'raw_cmd', 'ability_id': 392, 'general_id': 3676, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_BANSHEE'], 'avail_unit_type_id': [55]}, - 174: {'name': 'Behavior_CloakOn_Ghost_quick', 'func_type': 'raw_cmd', 'ability_id': 382, 'general_id': 3676, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, - 175: {'name': 'Behavior_GenerateCreepOff_quick', 'func_type': 'raw_cmd', 'ability_id': 1693, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_OVERLORD', 'ZERG_OVERLORDTRANSPORT'], 'avail_unit_type_id': [106, 893]}, - 176: {'name': 'Behavior_GenerateCreepOn_quick', 'func_type': 'raw_cmd', 'ability_id': 1692, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_OVERLORD', 'ZERG_OVERLORDTRANSPORT'], 'avail_unit_type_id': [106, 893]}, - 178: {'name': 'Behavior_HoldFireOff_Ghost_quick', 'func_type': 'raw_cmd', 'ability_id': 38, 'general_id': 3689, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, - 179: {'name': 'Behavior_HoldFireOff_Lurker_quick', 'func_type': 'raw_cmd', 'ability_id': 2552, 'general_id': 3689, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_LURKERMP'], 'avail_unit_type_id': [502]}, - 177: {'name': 'Behavior_HoldFireOff_quick', 'func_type': 'raw_cmd', 'ability_id': 3689, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_GHOST', 'ZERG_LURKERMPBURROWED'], 'avail_unit_type_id': [50, 503]}, - 181: {'name': 'Behavior_HoldFireOn_Ghost_quick', 'func_type': 'raw_cmd', 'ability_id': 36, 'general_id': 3688, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, - 182: {'name': 'Behavior_HoldFireOn_Lurker_quick', 'func_type': 'raw_cmd', 'ability_id': 2550, 'general_id': 3688, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': 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183: {'name': 'Build_Armory_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 331, 'general_id': 0, 'goal': 'build', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_SCV'], 'avail_unit_type_id': [45]}, - 36: {'name': 'Build_Assimilator_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 882, 'general_id': 0, 'goal': 'build', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_PROBE'], 'avail_unit_type_id': [84]}, - 184: {'name': 'Build_BanelingNest_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1162, 'general_id': 0, 'goal': 'build', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_DRONE'], 'avail_unit_type_id': [104]}, - 185: {'name': 'Build_Barracks_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 321, 'general_id': 0, 'goal': 'build', 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'avail_unit_type': ['ZERG_CREEPTUMORBURROWED', 'ZERG_QUEEN'], 'avail_unit_type_id': [137, 126]}, - 189: {'name': 'Build_CreepTumor_Queen_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1694, 'general_id': 3691, 'goal': 'build', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_QUEEN'], 'avail_unit_type_id': [126]}, - 190: {'name': 'Build_CreepTumor_Tumor_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1733, 'general_id': 3691, 'goal': 'build', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_CREEPTUMORBURROWED'], 'avail_unit_type_id': [137]}, - 47: {'name': 'Build_CyberneticsCore_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 894, 'general_id': 0, 'goal': 'build', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_PROBE'], 'avail_unit_type_id': [84]}, - 44: {'name': 'Build_DarkShrine_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 891, 'general_id': 0, 'goal': 'build', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_PROBE'], 'avail_unit_type_id': [84]}, - 191: {'name': 'Build_EngineeringBay_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 322, 'general_id': 0, 'goal': 'build', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_SCV'], 'avail_unit_type_id': [45]}, - 192: {'name': 'Build_EvolutionChamber_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1156, 'general_id': 0, 'goal': 'build', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_DRONE'], 'avail_unit_type_id': [104]}, - 193: {'name': 'Build_Extractor_unit', 'func_type': 'raw_cmd_unit', 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True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_INFESTOR', 'ZERG_INFESTORBURROWED'], 'avail_unit_type_id': [111, 127]}, - 288: {'name': 'Cancel_Nuke_quick', 'func_type': 'raw_cmd', 'ability_id': 1623, 'general_id': 3659, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, - 130: {'name': 'Cancel_Queue1_quick', 'func_type': 'raw_cmd', 'ability_id': 304, 'general_id': 3671, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': [], 'avail_unit_type_id': []}, - 131: {'name': 'Cancel_Queue5_quick', 'func_type': 'raw_cmd', 'ability_id': 306, 'general_id': 3671, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': [], 'avail_unit_type_id': []}, - 289: {'name': 'Cancel_QueueAddOn_quick', 'func_type': 'raw_cmd', 'ability_id': 312, 'general_id': 3671, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_BARRACKS', 'TERRAN_FACTORY', 'TERRAN_STARPORT'], 'avail_unit_type_id': [21, 27, 28]}, - 132: {'name': 'Cancel_QueueCancelToSelection_quick', 'func_type': 'raw_cmd', 'ability_id': 308, 'general_id': 3671, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': [], 'avail_unit_type_id': []}, - 134: {'name': 'Cancel_QueuePassiveCancelToSelection_quick', 'func_type': 'raw_cmd', 'ability_id': 1833, 'general_id': 3671, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': [], 'avail_unit_type_id': []}, - 133: {'name': 'Cancel_QueuePassive_quick', 'func_type': 'raw_cmd', 'ability_id': 1831, 'general_id': 3671, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': [], 'avail_unit_type_id': []}, - 290: {'name': 'Cancel_SpineCrawlerRoot_quick', 'func_type': 'raw_cmd', 'ability_id': 1730, 'general_id': 3659, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_SPINECRAWLERUPROOTED'], 'avail_unit_type_id': [139]}, - 291: {'name': 'Cancel_SporeCrawlerRoot_quick', 'func_type': 'raw_cmd', 'ability_id': 1732, 'general_id': 3659, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_SPORECRAWLERUPROOTED'], 'avail_unit_type_id': [140]}, - 292: {'name': 'Cancel_StarportAddOn_quick', 'func_type': 'raw_cmd', 'ability_id': 517, 'general_id': 3659, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_STARPORTREACTOR', 'TERRAN_STARPORTTECHLAB'], 'avail_unit_type_id': [42, 41]}, - 127: {'name': 'Cancel_StasisTrap_quick', 'func_type': 'raw_cmd', 'ability_id': 2535, 'general_id': 3659, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_ORACLE'], 'avail_unit_type_id': [495]}, - 128: {'name': 'Cancel_VoidRayPrismaticAlignment_quick', 'func_type': 'raw_cmd', 'ability_id': 3707, 'general_id': 3659, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_VOIDRAY'], 'avail_unit_type_id': [80]}, - 293: {'name': 'Effect_Abduct_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2067, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_VIPER'], 'avail_unit_type_id': [499]}, - 96: {'name': 'Effect_AdeptPhaseShift_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2544, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_ADEPT'], 'avail_unit_type_id': [311]}, - 294: {'name': 'Effect_AntiArmorMissile_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3753, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_RAVEN'], 'avail_unit_type_id': [56]}, - 295: {'name': 'Effect_AutoTurret_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1764, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_RAVEN'], 'avail_unit_type_id': [56]}, - 296: {'name': 'Effect_BlindingCloud_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2063, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_VIPER'], 'avail_unit_type_id': [499]}, - 111: {'name': 'Effect_Blink_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3687, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_DARKTEMPLAR', 'PROTOSS_STALKER'], 'avail_unit_type_id': [76, 74]}, - 135: {'name': 'Effect_Blink_Stalker_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1442, 'general_id': 3687, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_STALKER'], 'avail_unit_type_id': [74]}, - 112: {'name': 'Effect_Blink_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3687, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_DARKTEMPLAR', 'PROTOSS_STALKER'], 'avail_unit_type_id': [76, 74]}, - 297: {'name': 'Effect_CalldownMULE_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 171, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_ORBITALCOMMAND'], 'avail_unit_type_id': [132]}, - 298: {'name': 'Effect_CalldownMULE_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 171, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_ORBITALCOMMAND'], 'avail_unit_type_id': [132]}, - 299: {'name': 'Effect_CausticSpray_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2324, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_CORRUPTOR'], 'avail_unit_type_id': [112]}, - 302: {'name': 'Effect_Charge_autocast', 'func_type': 'raw_autocast', 'ability_id': 1819, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_ZEALOT'], 'avail_unit_type_id': [73]}, - 300: {'name': 'Effect_Charge_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1819, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_ZEALOT'], 'avail_unit_type_id': [73]}, - 301: {'name': 'Effect_Charge_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 1819, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_ZEALOT'], 'avail_unit_type_id': [73]}, - 122: {'name': 'Effect_ChronoBoostEnergyCost_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3755, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_NEXUS'], 'avail_unit_type_id': [59]}, - 33: {'name': 'Effect_ChronoBoost_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 261, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_NEXUS'], 'avail_unit_type_id': [59]}, - 303: {'name': 'Effect_Contaminate_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 1825, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_OVERSEER'], 'avail_unit_type_id': [129]}, - 304: {'name': 'Effect_CorrosiveBile_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2338, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_RAVAGER'], 'avail_unit_type_id': [688]}, - 305: {'name': 'Effect_EMP_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1628, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, - 306: {'name': 'Effect_EMP_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 1628, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, - 307: {'name': 'Effect_Explode_quick', 'func_type': 'raw_cmd', 'ability_id': 42, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_BANELING', 'ZERG_BANELINGBURROWED'], 'avail_unit_type_id': [9, 115]}, - 157: {'name': 'Effect_Feedback_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 140, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_HIGHTEMPLAR'], 'avail_unit_type_id': [75]}, - 79: {'name': 'Effect_ForceField_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1526, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 308: {'name': 'Effect_FungalGrowth_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 74, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_INFESTOR', 'ZERG_INFESTORBURROWED'], 'avail_unit_type_id': [111, 127]}, - 309: {'name': 'Effect_FungalGrowth_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 74, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_INFESTOR', 'ZERG_INFESTORBURROWED'], 'avail_unit_type_id': [111, 127]}, - 310: {'name': 'Effect_GhostSnipe_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2714, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, - 32: {'name': 'Effect_GravitonBeam_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 173, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_PHOENIX'], 'avail_unit_type_id': [78]}, - 20: {'name': 'Effect_GuardianShield_quick', 'func_type': 'raw_cmd', 'ability_id': 76, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 312: {'name': 'Effect_Heal_autocast', 'func_type': 'raw_autocast', 'ability_id': 386, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_MEDIVAC'], 'avail_unit_type_id': [54]}, - 311: {'name': 'Effect_Heal_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 386, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_MEDIVAC'], 'avail_unit_type_id': [54]}, - 313: {'name': 'Effect_ImmortalBarrier_autocast', 'func_type': 'raw_autocast', 'ability_id': 2328, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_IMMORTAL'], 'avail_unit_type_id': [83]}, - 91: {'name': 'Effect_ImmortalBarrier_quick', 'func_type': 'raw_cmd', 'ability_id': 2328, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_IMMORTAL'], 'avail_unit_type_id': [83]}, - 314: {'name': 'Effect_InfestedTerrans_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 247, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_INFESTOR', 'ZERG_INFESTORBURROWED'], 'avail_unit_type_id': [111, 127]}, - 315: {'name': 'Effect_InjectLarva_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 251, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_QUEEN'], 'avail_unit_type_id': [126]}, - 316: {'name': 'Effect_InterferenceMatrix_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3747, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_RAVEN'], 'avail_unit_type_id': [56]}, - 317: {'name': 'Effect_KD8Charge_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2588, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_REAPER'], 'avail_unit_type_id': [49]}, - 538: {'name': 'Effect_KD8Charge_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2588, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_REAPER'], 'avail_unit_type_id': [49]}, - 318: {'name': 'Effect_LockOn_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2350, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_CYCLONE'], 'avail_unit_type_id': [692]}, - 541: {'name': 'Effect_LockOn_autocast', 'func_type': 'raw_autocast', 'ability_id': 2350, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_CYCLONE'], 'avail_unit_type_id': [692]}, - 319: {'name': 'Effect_LocustSwoop_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2387, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_LOCUSTMPFLYING'], 'avail_unit_type_id': [693]}, - 110: {'name': 'Effect_MassRecall_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3686, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE'], 'avail_unit_type_id': [10, 488]}, - 136: {'name': 'Effect_MassRecall_Mothership_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2368, 'general_id': 3686, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_MOTHERSHIP'], 'avail_unit_type_id': [10]}, - 162: {'name': 'Effect_MassRecall_Nexus_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3757, 'general_id': 3686, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_NEXUS'], 'avail_unit_type_id': [59]}, - 137: {'name': 'Effect_MassRecall_StrategicRecall_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 142, 'general_id': 3686, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_MOTHERSHIP'], 'avail_unit_type_id': [10]}, - 320: {'name': 'Effect_MedivacIgniteAfterburners_quick', 'func_type': 'raw_cmd', 'ability_id': 2116, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_MEDIVAC'], 'avail_unit_type_id': [54]}, - 321: {'name': 'Effect_NeuralParasite_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 249, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_INFESTOR', 'ZERG_INFESTORBURROWED'], 'avail_unit_type_id': [111, 127]}, - 322: {'name': 'Effect_NukeCalldown_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1622, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, - 90: {'name': 'Effect_OracleRevelation_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2146, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_ORACLE'], 'avail_unit_type_id': [495]}, - 323: {'name': 'Effect_ParasiticBomb_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2542, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_VIPER'], 'avail_unit_type_id': [499]}, - 65: {'name': 'Effect_PsiStorm_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1036, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_HIGHTEMPLAR'], 'avail_unit_type_id': [75]}, - 167: {'name': 'Effect_PurificationNova_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2346, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_DISRUPTOR'], 'avail_unit_type_id': [694]}, - 324: {'name': 'Effect_Repair_autocast', 'func_type': 'raw_autocast', 'ability_id': 3685, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_MULE', 'TERRAN_SCV', 'TERRAN_REPAIRDRONE'], 'avail_unit_type_id': [268, 45, 1913]}, - 108: {'name': 'Effect_Repair_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3685, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_MULE', 'TERRAN_SCV', 'TERRAN_REPAIRDRONE'], 'avail_unit_type_id': [268, 45, 1913]}, - 109: {'name': 'Effect_Repair_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3685, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_MULE', 'TERRAN_SCV', 'TERRAN_REPAIRDRONE'], 'avail_unit_type_id': [268, 45, 1913]}, - 326: {'name': 'Effect_Repair_Mule_autocast', 'func_type': 'raw_autocast', 'ability_id': 78, 'general_id': 3685, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_MULE'], 'avail_unit_type_id': [268]}, - 325: {'name': 'Effect_Repair_Mule_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 78, 'general_id': 3685, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_MULE'], 'avail_unit_type_id': [268]}, - 328: {'name': 'Effect_Repair_RepairDrone_autocast', 'func_type': 'raw_autocast', 'ability_id': 3751, 'general_id': 3685, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_REPAIRDRONE'], 'avail_unit_type_id': [1913]}, - 327: {'name': 'Effect_Repair_RepairDrone_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3751, 'general_id': 3685, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_REPAIRDRONE'], 'avail_unit_type_id': [1913]}, - 330: {'name': 'Effect_Repair_SCV_autocast', 'func_type': 'raw_autocast', 'ability_id': 316, 'general_id': 3685, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_SCV'], 'avail_unit_type_id': [45]}, - 329: {'name': 'Effect_Repair_SCV_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 316, 'general_id': 3685, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_SCV'], 'avail_unit_type_id': [45]}, - 331: {'name': 'Effect_Restore_autocast', 'func_type': 'raw_autocast', 'ability_id': 3765, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SHIELDBATTERY'], 'avail_unit_type_id': [1910]}, - 161: {'name': 'Effect_Restore_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3765, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_SHIELDBATTERY'], 'avail_unit_type_id': [1910]}, - 332: {'name': 'Effect_Salvage_quick', 'func_type': 'raw_cmd', 'ability_id': 32, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_BUNKER'], 'avail_unit_type_id': [24]}, - 333: {'name': 'Effect_Scan_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 399, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_ORBITALCOMMAND'], 'avail_unit_type_id': [132]}, - 113: {'name': 'Effect_ShadowStride_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2700, 'general_id': 3687, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_DARKTEMPLAR'], 'avail_unit_type_id': [76]}, - 334: {'name': 'Effect_SpawnChangeling_quick', 'func_type': 'raw_cmd', 'ability_id': 181, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_OVERSEER'], 'avail_unit_type_id': [129]}, - 335: {'name': 'Effect_SpawnLocusts_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2704, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_SWARMHOSTBURROWEDMP', 'ZERG_SWARMHOSTMP'], 'avail_unit_type_id': [493, 494]}, - 336: {'name': 'Effect_SpawnLocusts_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2704, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_SWARMHOSTBURROWEDMP', 'ZERG_SWARMHOSTMP'], 'avail_unit_type_id': [493, 494]}, - 337: {'name': 'Effect_Spray_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3684, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_SCV', 'ZERG_DRONE', 'PROTOSS_PROBE'], 'avail_unit_type_id': [45, 104, 84]}, - 338: {'name': 'Effect_Spray_Protoss_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 30, 'general_id': 3684, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_PROBE'], 'avail_unit_type_id': [84]}, - 339: {'name': 'Effect_Spray_Terran_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 26, 'general_id': 3684, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_SCV'], 'avail_unit_type_id': [45]}, - 340: {'name': 'Effect_Spray_Zerg_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 28, 'general_id': 3684, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_DRONE'], 'avail_unit_type_id': [104]}, - 341: {'name': 'Effect_Stim_quick', 'func_type': 'raw_cmd', 'ability_id': 3675, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_BUNKER', 'TERRAN_MARAUDER', 'TERRAN_MARINE'], 'avail_unit_type_id': [24, 51, 48]}, - 342: {'name': 'Effect_Stim_Marauder_quick', 'func_type': 'raw_cmd', 'ability_id': 253, 'general_id': 3675, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_MARAUDER'], 'avail_unit_type_id': [51]}, - 343: {'name': 'Effect_Stim_Marauder_Redirect_quick', 'func_type': 'raw_cmd', 'ability_id': 1684, 'general_id': 3675, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_MARAUDER'], 'avail_unit_type_id': [51]}, - 344: {'name': 'Effect_Stim_Marine_quick', 'func_type': 'raw_cmd', 'ability_id': 380, 'general_id': 3675, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_MARINE'], 'avail_unit_type_id': [48]}, - 345: {'name': 'Effect_Stim_Marine_Redirect_quick', 'func_type': 'raw_cmd', 'ability_id': 1683, 'general_id': 3675, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_MARINE'], 'avail_unit_type_id': [48]}, - 346: {'name': 'Effect_SupplyDrop_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 255, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_ORBITALCOMMAND'], 'avail_unit_type_id': [132]}, - 347: {'name': 'Effect_TacticalJump_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2358, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_BATTLECRUISER'], 'avail_unit_type_id': [57]}, - 348: {'name': 'Effect_TimeWarp_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2244, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE'], 'avail_unit_type_id': [10, 488]}, - 349: {'name': 'Effect_Transfusion_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 1664, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_QUEEN'], 'avail_unit_type_id': [126]}, - 350: {'name': 'Effect_ViperConsume_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2073, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_VIPER'], 'avail_unit_type_id': [499]}, - 94: {'name': 'Effect_VoidRayPrismaticAlignment_quick', 'func_type': 'raw_cmd', 'ability_id': 2393, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_VOIDRAY'], 'avail_unit_type_id': [80]}, - 353: {'name': 'Effect_WidowMineAttack_autocast', 'func_type': 'raw_autocast', 'ability_id': 2099, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_WIDOWMINEBURROWED'], 'avail_unit_type_id': [500]}, - 351: {'name': 'Effect_WidowMineAttack_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2099, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_WIDOWMINEBURROWED'], 'avail_unit_type_id': [500]}, - 352: {'name': 'Effect_WidowMineAttack_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2099, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_WIDOWMINEBURROWED'], 'avail_unit_type_id': [500]}, - 537: {'name': 'Effect_YamatoGun_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 401, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_BATTLECRUISER'], 'avail_unit_type_id': [57]}, - 93: {'name': 'Hallucination_Adept_quick', 'func_type': 'raw_cmd', 'ability_id': 2391, 'general_id': 0, 'goal': 'effect', 'special_goal': 'hallucination', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 22: {'name': 'Hallucination_Archon_quick', 'func_type': 'raw_cmd', 'ability_id': 146, 'general_id': 0, 'goal': 'effect', 'special_goal': 'hallucination', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 23: {'name': 'Hallucination_Colossus_quick', 'func_type': 'raw_cmd', 'ability_id': 148, 'general_id': 0, 'goal': 'effect', 'special_goal': 'hallucination', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 92: {'name': 'Hallucination_Disruptor_quick', 'func_type': 'raw_cmd', 'ability_id': 2389, 'general_id': 0, 'goal': 'effect', 'special_goal': 'hallucination', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 24: {'name': 'Hallucination_HighTemplar_quick', 'func_type': 'raw_cmd', 'ability_id': 150, 'general_id': 0, 'goal': 'effect', 'special_goal': 'hallucination', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 25: {'name': 'Hallucination_Immortal_quick', 'func_type': 'raw_cmd', 'ability_id': 152, 'general_id': 0, 'goal': 'effect', 'special_goal': 'hallucination', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 89: {'name': 'Hallucination_Oracle_quick', 'func_type': 'raw_cmd', 'ability_id': 2114, 'general_id': 0, 'goal': 'effect', 'special_goal': 'hallucination', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 26: {'name': 'Hallucination_Phoenix_quick', 'func_type': 'raw_cmd', 'ability_id': 154, 'general_id': 0, 'goal': 'effect', 'special_goal': 'hallucination', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 27: {'name': 'Hallucination_Probe_quick', 'func_type': 'raw_cmd', 'ability_id': 156, 'general_id': 0, 'goal': 'effect', 'special_goal': 'hallucination', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 28: {'name': 'Hallucination_Stalker_quick', 'func_type': 'raw_cmd', 'ability_id': 158, 'general_id': 0, 'goal': 'effect', 'special_goal': 'hallucination', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 29: {'name': 'Hallucination_VoidRay_quick', 'func_type': 'raw_cmd', 'ability_id': 160, 'general_id': 0, 'goal': 'effect', 'special_goal': 'hallucination', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 30: {'name': 'Hallucination_WarpPrism_quick', 'func_type': 'raw_cmd', 'ability_id': 162, 'general_id': 0, 'goal': 'effect', 'special_goal': 'hallucination', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 31: {'name': 'Hallucination_Zealot_quick', 'func_type': 'raw_cmd', 'ability_id': 164, 'general_id': 0, 'goal': 'effect', 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'ZERG_MUTALISK', 'ZERG_OVERLORD', 'ZERG_OVERLORDCOCOON', 'ZERG_OVERLORDTRANSPORT', 'ZERG_OVERSEER', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_ROACHBURROWED', 'ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLERUPROOTED', 'ZERG_SWARMHOSTMP', 'ZERG_TRANSPORTOVERLORDCOCOON', 'ZERG_ULTRALISK', 'ZERG_VIPER', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ADEPTPHASESHIFT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PROBE', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [55, 46, 36, 692, 43, 50, 53, 484, 689, 51, 48, 54, 268, 134, 56, 49, 45, 33, 44, 52, 691, 34, 35, 498, 9, 289, 114, 113, 12, 15, 14, 13, 17, 16, 112, 104, 107, 150, 111, 127, 7, 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'ZERG_BROODLORDCOCOON', 'ZERG_CHANGELING', 'ZERG_CHANGELINGMARINE', 'ZERG_CHANGELINGMARINESHIELD', 'ZERG_CHANGELINGZEALOT', 'ZERG_CHANGELINGZERGLING', 'ZERG_CHANGELINGZERGLINGWINGS', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTEDTERRANSEGG', 'ZERG_INFESTOR', 'ZERG_INFESTORBURROWED', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMP', 'ZERG_MUTALISK', 'ZERG_OVERLORD', 'ZERG_OVERLORDCOCOON', 'ZERG_OVERLORDTRANSPORT', 'ZERG_OVERSEER', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_ROACHBURROWED', 'ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLERUPROOTED', 'ZERG_SWARMHOSTMP', 'ZERG_TRANSPORTOVERLORDCOCOON', 'ZERG_ULTRALISK', 'ZERG_VIPER', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ADEPTPHASESHIFT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PROBE', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [55, 46, 36, 692, 43, 50, 53, 484, 689, 51, 48, 54, 268, 134, 56, 49, 45, 33, 44, 52, 691, 34, 35, 498, 9, 289, 114, 113, 12, 15, 14, 13, 17, 16, 112, 104, 107, 150, 111, 127, 7, 489, 693, 502, 108, 106, 128, 893, 129, 126, 688, 110, 118, 139, 140, 494, 892, 109, 499, 105, 311, 801, 141, 79, 4, 76, 694, 733, 75, 83, 85, 10, 488, 82, 495, 78, 84, 77, 74, 496, 80, 81, 73]}, - 15: {'name': 'Patrol_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3795, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_BANSHEE', 'TERRAN_BARRACKSFLYING', 'TERRAN_BATTLECRUISER', 'TERRAN_COMMANDCENTERFLYING', 'TERRAN_CYCLONE', 'TERRAN_FACTORYFLYING', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MEDIVAC', 'TERRAN_MULE', 'TERRAN_ORBITALCOMMANDFLYING', 'TERRAN_RAVEN', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_STARPORTFLYING', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'TERRAN_WIDOWMINE', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_BROODLORDCOCOON', 'ZERG_CHANGELING', 'ZERG_CHANGELINGMARINE', 'ZERG_CHANGELINGMARINESHIELD', 'ZERG_CHANGELINGZEALOT', 'ZERG_CHANGELINGZERGLING', 'ZERG_CHANGELINGZERGLINGWINGS', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTEDTERRANSEGG', 'ZERG_INFESTOR', 'ZERG_INFESTORBURROWED', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMP', 'ZERG_MUTALISK', 'ZERG_OVERLORD', 'ZERG_OVERLORDCOCOON', 'ZERG_OVERLORDTRANSPORT', 'ZERG_OVERSEER', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_ROACHBURROWED', 'ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLERUPROOTED', 'ZERG_SWARMHOSTMP', 'ZERG_TRANSPORTOVERLORDCOCOON', 'ZERG_ULTRALISK', 'ZERG_VIPER', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ADEPTPHASESHIFT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PROBE', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [55, 46, 57, 36, 692, 43, 50, 53, 484, 689, 51, 48, 54, 268, 134, 56, 49, 45, 33, 44, 52, 691, 34, 35, 498, 9, 289, 114, 113, 12, 15, 14, 13, 17, 16, 112, 104, 107, 150, 111, 127, 7, 489, 693, 502, 108, 106, 128, 893, 129, 126, 688, 110, 118, 139, 140, 494, 892, 109, 499, 105, 311, 801, 141, 79, 4, 76, 694, 733, 75, 83, 85, 10, 488, 82, 495, 78, 84, 77, 74, 496, 80, 81, 73]}, - 16: {'name': 'Patrol_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3795, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_BANSHEE', 'TERRAN_BARRACKSFLYING', 'TERRAN_BATTLECRUISER', 'TERRAN_COMMANDCENTERFLYING', 'TERRAN_CYCLONE', 'TERRAN_FACTORYFLYING', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MEDIVAC', 'TERRAN_MULE', 'TERRAN_ORBITALCOMMANDFLYING', 'TERRAN_RAVEN', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_STARPORTFLYING', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'TERRAN_WIDOWMINE', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_BROODLORDCOCOON', 'ZERG_CHANGELING', 'ZERG_CHANGELINGMARINE', 'ZERG_CHANGELINGMARINESHIELD', 'ZERG_CHANGELINGZEALOT', 'ZERG_CHANGELINGZERGLING', 'ZERG_CHANGELINGZERGLINGWINGS', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTEDTERRANSEGG', 'ZERG_INFESTOR', 'ZERG_INFESTORBURROWED', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMP', 'ZERG_MUTALISK', 'ZERG_OVERLORD', 'ZERG_OVERLORDCOCOON', 'ZERG_OVERLORDTRANSPORT', 'ZERG_OVERSEER', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_ROACHBURROWED', 'ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLERUPROOTED', 'ZERG_SWARMHOSTMP', 'ZERG_TRANSPORTOVERLORDCOCOON', 'ZERG_ULTRALISK', 'ZERG_VIPER', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ADEPTPHASESHIFT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PROBE', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [55, 46, 57, 36, 692, 43, 50, 53, 484, 689, 51, 48, 54, 268, 134, 56, 49, 45, 33, 44, 52, 691, 34, 35, 498, 9, 289, 114, 113, 12, 15, 14, 13, 17, 16, 112, 104, 107, 150, 111, 127, 7, 489, 693, 502, 108, 106, 128, 893, 129, 126, 688, 110, 118, 139, 140, 494, 892, 109, 499, 105, 311, 801, 141, 79, 4, 76, 694, 733, 75, 83, 85, 10, 488, 82, 495, 78, 84, 77, 74, 496, 80, 81, 73]}, - 549: {'name': 'Patrol_Battlecruiser_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3777, 'general_id': 3795, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_BATTLECRUISER'], 'avail_unit_type_id': [57]}, - 550: {'name': 'Patrol_Battlecruiser_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3777, 'general_id': 3795, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_BATTLECRUISER'], 'avail_unit_type_id': [57]}, - 551: {'name': 'Patrol_Patrol_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 17, 'general_id': 3795, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_BANSHEE', 'TERRAN_BARRACKSFLYING', 'TERRAN_COMMANDCENTERFLYING', 'TERRAN_CYCLONE', 'TERRAN_FACTORYFLYING', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MEDIVAC', 'TERRAN_MULE', 'TERRAN_ORBITALCOMMANDFLYING', 'TERRAN_RAVEN', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_STARPORTFLYING', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'TERRAN_WIDOWMINE', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_BROODLORDCOCOON', 'ZERG_CHANGELING', 'ZERG_CHANGELINGMARINE', 'ZERG_CHANGELINGMARINESHIELD', 'ZERG_CHANGELINGZEALOT', 'ZERG_CHANGELINGZERGLING', 'ZERG_CHANGELINGZERGLINGWINGS', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTEDTERRANSEGG', 'ZERG_INFESTOR', 'ZERG_INFESTORBURROWED', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMP', 'ZERG_MUTALISK', 'ZERG_OVERLORD', 'ZERG_OVERLORDCOCOON', 'ZERG_OVERLORDTRANSPORT', 'ZERG_OVERSEER', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_ROACHBURROWED', 'ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLERUPROOTED', 'ZERG_SWARMHOSTMP', 'ZERG_TRANSPORTOVERLORDCOCOON', 'ZERG_ULTRALISK', 'ZERG_VIPER', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ADEPTPHASESHIFT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PROBE', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [55, 46, 36, 692, 43, 50, 53, 484, 689, 51, 48, 54, 268, 134, 56, 49, 45, 33, 44, 52, 691, 34, 35, 498, 9, 289, 114, 113, 12, 15, 14, 13, 17, 16, 112, 104, 107, 150, 111, 127, 7, 489, 693, 502, 108, 106, 128, 893, 129, 126, 688, 110, 118, 139, 140, 494, 892, 109, 499, 105, 311, 801, 141, 79, 4, 76, 694, 733, 75, 83, 85, 10, 488, 82, 495, 78, 84, 77, 74, 496, 80, 81, 73]}, - 552: {'name': 'Patrol_Patrol_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 17, 'general_id': 3795, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_BANSHEE', 'TERRAN_BARRACKSFLYING', 'TERRAN_COMMANDCENTERFLYING', 'TERRAN_CYCLONE', 'TERRAN_FACTORYFLYING', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MEDIVAC', 'TERRAN_MULE', 'TERRAN_ORBITALCOMMANDFLYING', 'TERRAN_RAVEN', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_STARPORTFLYING', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'TERRAN_WIDOWMINE', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_BROODLORDCOCOON', 'ZERG_CHANGELING', 'ZERG_CHANGELINGMARINE', 'ZERG_CHANGELINGMARINESHIELD', 'ZERG_CHANGELINGZEALOT', 'ZERG_CHANGELINGZERGLING', 'ZERG_CHANGELINGZERGLINGWINGS', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTEDTERRANSEGG', 'ZERG_INFESTOR', 'ZERG_INFESTORBURROWED', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMP', 'ZERG_MUTALISK', 'ZERG_OVERLORD', 'ZERG_OVERLORDCOCOON', 'ZERG_OVERLORDTRANSPORT', 'ZERG_OVERSEER', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_ROACHBURROWED', 'ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLERUPROOTED', 'ZERG_SWARMHOSTMP', 'ZERG_TRANSPORTOVERLORDCOCOON', 'ZERG_ULTRALISK', 'ZERG_VIPER', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ADEPTPHASESHIFT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PROBE', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [55, 46, 36, 692, 43, 50, 53, 484, 689, 51, 48, 54, 268, 134, 56, 49, 45, 33, 44, 52, 691, 34, 35, 498, 9, 289, 114, 113, 12, 15, 14, 13, 17, 16, 112, 104, 107, 150, 111, 127, 7, 489, 693, 502, 108, 106, 128, 893, 129, 126, 688, 110, 118, 139, 140, 494, 892, 109, 499, 105, 311, 801, 141, 79, 4, 76, 694, 733, 75, 83, 85, 10, 488, 82, 495, 78, 84, 77, 74, 496, 80, 81, 73]}, - 415: {'name': 'Rally_Building_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 195, 'general_id': 3673, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_BARRACKS', 'TERRAN_BUNKER', 'TERRAN_FACTORY', 'TERRAN_STARPORT', 'ZERG_NYDUSCANAL', 'ZERG_NYDUSNETWORK', 'ZERG_RAVAGERCOCOON', 'PROTOSS_GATEWAY', 'PROTOSS_ROBOTICSFACILITY', 'PROTOSS_STARGATE'], 'avail_unit_type_id': [21, 24, 27, 28, 142, 95, 687, 62, 71, 67]}, - 416: {'name': 'Rally_Building_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 195, 'general_id': 3673, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_BARRACKS', 'TERRAN_BUNKER', 'TERRAN_FACTORY', 'TERRAN_STARPORT', 'ZERG_NYDUSCANAL', 'ZERG_NYDUSNETWORK', 'ZERG_RAVAGERCOCOON', 'PROTOSS_GATEWAY', 'PROTOSS_ROBOTICSFACILITY', 'PROTOSS_STARGATE'], 'avail_unit_type_id': [21, 24, 27, 28, 142, 95, 687, 62, 71, 67]}, - 417: {'name': 'Rally_CommandCenter_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 203, 'general_id': 3690, 'goal': 'other', 'special_goal': None, 'queued': True, 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'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 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'HighTemplar', 'Immortal', 'Mothership', 'MothershipCore', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'PylonOvercharged', 'Sentry', 'ShieldBattery', 'Stalker', 'Tempest', 'VoidRay', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'AutoTurret', 'Banshee', 'Battlecruiser', 'Bunker', 'Cyclone', 'Ghost', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reaper', 'RepairDrone', 'SCV', 'SiegeTank', 'SiegeTankSieged', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 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'Barracks', 'BarracksFlying', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'Factory', 'FactoryFlying', 'Ghost', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reaper', 'RepairDrone', 'SCV', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 13: {'action_name': 'Move_pt', 'selected_type': [311, 801, 1955, 79, 4, 76, 694, 733, 75, 83, 10, 488, 82, 1911, 495, 78, 84, 894, 77, 1910, 74, 496, 80, 81, 136, 73, 31, 55, 46, 57, 36, 692, 43, 50, 144, 53, 484, 689, 734, 268, 51, 48, 54, 23, 134, 11, 56, 49, 1913, 45, 33, 32, 44, 52, 691, 34, 35, 498, 500, 9, 115, 8, 114, 113, 289, 12, 15, 14, 13, 17, 16, 103, 112, 104, 116, 107, 117, 94, 7, 120, 150, 111, 127, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 98, 139, 99, 140, 494, 493, 109, 131, 499, 105, 119], 'target_type': [], 'selected_type_name': ['Adept', 'AdeptPhaseShift', 'AssimilatorRich', 'Carrier', 'Colossus', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'HighTemplar', 'Immortal', 'Mothership', 'MothershipCore', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'Probe', 'PylonOvercharged', 'Sentry', 'ShieldBattery', 'Stalker', 'Tempest', 'VoidRay', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'AutoTurret', 'Banshee', 'BarracksFlying', 'Battlecruiser', 'CommandCenterFlying', 'Cyclone', 'FactoryFlying', 'Ghost', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'OrbitalCommandFlying', 'PointDefenseDrone', 'Raven', 'Reaper', 'RepairDrone', 'SCV', 'SiegeTank', 'SiegeTankSieged', 'StarportFlying', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': []}, - 14: {'action_name': 'Move_unit', 'selected_type': [311, 801, 1955, 79, 4, 76, 694, 733, 75, 83, 10, 488, 82, 1911, 495, 78, 84, 894, 77, 1910, 74, 496, 80, 81, 136, 73, 31, 55, 46, 57, 36, 692, 43, 50, 144, 53, 484, 689, 734, 268, 51, 48, 54, 23, 134, 11, 56, 49, 1913, 45, 33, 32, 44, 52, 691, 34, 35, 498, 500, 9, 115, 8, 114, 113, 289, 12, 15, 14, 13, 17, 16, 103, 112, 104, 116, 107, 117, 94, 7, 120, 150, 111, 127, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 98, 139, 99, 140, 494, 493, 109, 131, 499, 105, 119], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Adept', 'AdeptPhaseShift', 'AssimilatorRich', 'Carrier', 'Colossus', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'HighTemplar', 'Immortal', 'Mothership', 'MothershipCore', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'Probe', 'PylonOvercharged', 'Sentry', 'ShieldBattery', 'Stalker', 'Tempest', 'VoidRay', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'AutoTurret', 'Banshee', 'BarracksFlying', 'Battlecruiser', 'CommandCenterFlying', 'Cyclone', 'FactoryFlying', 'Ghost', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'OrbitalCommandFlying', 'PointDefenseDrone', 'Raven', 'Reaper', 'RepairDrone', 'SCV', 'SiegeTank', 'SiegeTankSieged', 'StarportFlying', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 15: {'action_name': 'Patrol_pt', 'selected_type': [311, 801, 1955, 79, 4, 76, 694, 733, 75, 83, 10, 488, 82, 1911, 495, 78, 84, 894, 77, 1910, 74, 496, 80, 81, 136, 73, 31, 55, 46, 57, 36, 692, 43, 50, 144, 53, 484, 689, 734, 268, 51, 48, 54, 23, 134, 11, 56, 49, 1913, 45, 33, 32, 44, 52, 691, 34, 35, 498, 500, 9, 115, 8, 114, 113, 289, 12, 15, 14, 13, 17, 16, 103, 112, 104, 116, 107, 117, 94, 7, 120, 150, 111, 127, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 98, 139, 99, 140, 494, 493, 109, 131, 499, 105, 119], 'target_type': [], 'selected_type_name': ['Adept', 'AdeptPhaseShift', 'AssimilatorRich', 'Carrier', 'Colossus', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'HighTemplar', 'Immortal', 'Mothership', 'MothershipCore', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'Probe', 'PylonOvercharged', 'Sentry', 'ShieldBattery', 'Stalker', 'Tempest', 'VoidRay', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'AutoTurret', 'Banshee', 'BarracksFlying', 'Battlecruiser', 'CommandCenterFlying', 'Cyclone', 'FactoryFlying', 'Ghost', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'OrbitalCommandFlying', 'PointDefenseDrone', 'Raven', 'Reaper', 'RepairDrone', 'SCV', 'SiegeTank', 'SiegeTankSieged', 'StarportFlying', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': []}, - 16: {'action_name': 'Patrol_unit', 'selected_type': [311, 801, 1955, 79, 4, 76, 694, 733, 75, 83, 10, 488, 82, 1911, 495, 78, 84, 894, 77, 1910, 74, 496, 80, 81, 136, 73, 31, 55, 46, 57, 36, 692, 43, 50, 144, 53, 484, 689, 734, 268, 51, 48, 54, 23, 134, 11, 56, 49, 1913, 45, 33, 32, 44, 52, 691, 34, 35, 498, 500, 9, 115, 8, 114, 113, 289, 12, 15, 14, 13, 17, 16, 103, 112, 104, 116, 107, 117, 94, 7, 120, 150, 111, 127, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 98, 139, 99, 140, 494, 493, 109, 131, 499, 105, 119], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 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1958, 1960, 1961], 'selected_type_name': ['Adept', 'AdeptPhaseShift', 'AssimilatorRich', 'Carrier', 'Colossus', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'HighTemplar', 'Immortal', 'Mothership', 'MothershipCore', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'Probe', 'PylonOvercharged', 'Sentry', 'ShieldBattery', 'Stalker', 'Tempest', 'VoidRay', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'AutoTurret', 'Banshee', 'BarracksFlying', 'Battlecruiser', 'CommandCenterFlying', 'Cyclone', 'FactoryFlying', 'Ghost', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'OrbitalCommandFlying', 'PointDefenseDrone', 'Raven', 'Reaper', 'RepairDrone', 'SCV', 'SiegeTank', 'SiegeTankSieged', 'StarportFlying', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 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'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 17: {'action_name': 'HoldPosition_quick', 'selected_type': [311, 801, 1955, 79, 4, 76, 694, 733, 62, 75, 83, 10, 488, 59, 82, 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'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': []}, - 19: {'action_name': 'Research_PhoenixAnionPulseCrystals_quick', 'selected_type': [64], 'target_type': [], 'selected_type_name': ['FleetBeacon'], 'target_type_name': []}, - 20: {'action_name': 'Effect_GuardianShield_quick', 'selected_type': [77], 'target_type': [], 'selected_type_name': ['Sentry'], 'target_type_name': []}, - 21: {'action_name': 'Train_Mothership_quick', 'selected_type': [59], 'target_type': [], 'selected_type_name': ['Nexus'], 'target_type_name': []}, - 22: {'action_name': 'Hallucination_Archon_quick', 'selected_type': [77], 'target_type': [], 'selected_type_name': ['Sentry'], 'target_type_name': []}, - 23: {'action_name': 'Hallucination_Colossus_quick', 'selected_type': [77], 'target_type': [], 'selected_type_name': ['Sentry'], 'target_type_name': []}, - 25: {'action_name': 'Hallucination_Immortal_quick', 'selected_type': [77], 'target_type': [], 'selected_type_name': ['Sentry'], 'target_type_name': []}, - 26: {'action_name': 'Hallucination_Phoenix_quick', 'selected_type': [77], 'target_type': [], 'selected_type_name': ['Sentry'], 'target_type_name': []}, - 27: {'action_name': 'Hallucination_Probe_quick', 'selected_type': [77], 'target_type': [], 'selected_type_name': ['Sentry'], 'target_type_name': []}, - 28: {'action_name': 'Hallucination_Stalker_quick', 'selected_type': [77], 'target_type': [], 'selected_type_name': ['Sentry'], 'target_type_name': []}, - 29: {'action_name': 'Hallucination_VoidRay_quick', 'selected_type': [77], 'target_type': [], 'selected_type_name': ['Sentry'], 'target_type_name': []}, - 30: {'action_name': 'Hallucination_WarpPrism_quick', 'selected_type': [77], 'target_type': [], 'selected_type_name': ['Sentry'], 'target_type_name': []}, - 31: {'action_name': 'Hallucination_Zealot_quick', 'selected_type': [77], 'target_type': [], 'selected_type_name': ['Sentry'], 'target_type_name': []}, - 32: {'action_name': 'Effect_GravitonBeam_unit', 'selected_type': [78], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 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'Stargate', 'StasisTrap', 'Tempest', 'TemplarArchive', 'TwilightCouncil', 'VoidRay', 'WarpGate', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'Armory', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'BarracksReactor', 'BarracksTechLab', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'EngineeringBay', 'Factory', 'FactoryFlying', 'FactoryReactor', 'FactoryTechLab', 'FusionCore', 'Ghost', 'GhostAcademy', 'GhostAlternate', 'GhostNova', 'Hellion', 'Hellbat', 'KD8Charge', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'Nuke', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reactor', 'Reaper', 'Refinery', 'RefineryRich', 'RepairDrone', 'SCV', 'SensorTower', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'StarportReactor', 'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BanelingNest', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'BroodlingEscort', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'CreepTumor', 'CreepTumorBurrowed', 'CreepTumorQueen', 'Drone', 'DroneBurrowed', 'EvolutionChamber', 'Extractor', 'ExtractorRich', 'GreaterSpire', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'HydraliskDen', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Larva', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpawningPool', 'SpineCrawler', 'SpineCrawlerUprooted', 'Spire', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'UltraliskCavern', 'Viper', 'Zergling', 'ZerglingBurrowed']}, - 105: {'action_name': 'UnloadAllAt_pt', 'selected_type': [81, 136, 24, 18, 54, 142, 95, 893, 36, 130], 'target_type': [], 'selected_type_name': ['WarpPrism', 'WarpPrismPhasing', 'Bunker', 'CommandCenter', 'Medivac', 'NydusCanal', 'NydusNetwork', 'OverlordTransport', 'CommandCenterFlying', 'PlanetaryFortress'], 'target_type_name': []}, - 106: {'action_name': 'Rally_Units_pt', 'selected_type': [311, 801, 141, 61, 1955, 79, 4, 72, 69, 76, 694, 733, 64, 135, 63, 62, 75, 83, 85, 10, 488, 59, 82, 1911, 495, 78, 66, 84, 60, 894, 70, 71, 77, 1910, 74, 67, 732, 496, 68, 65, 80, 133, 81, 136, 73, 29, 31, 55, 21, 46, 38, 37, 57, 24, 18, 36, 692, 22, 27, 43, 40, 39, 30, 50, 26, 144, 145, 53, 484, 830, 689, 734, 268, 51, 48, 54, 23, 58, 132, 134, 130, 11, 56, 6, 49, 20, 1960, 1913, 45, 25, 33, 32, 28, 44, 42, 41, 19, 47, 5, 52, 691, 34, 35, 498, 500, 9, 115, 8, 96, 114, 113, 289, 143, 12, 15, 14, 13, 17, 16, 103, 112, 87, 137, 138, 104, 116, 90, 88, 1956, 102, 86, 101, 107, 117, 91, 94, 7, 120, 150, 111, 127, 100, 151, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 89, 98, 139, 92, 99, 140, 494, 493, 109, 131, 93, 499, 105, 119], 'target_type': [], 'selected_type_name': ['Adept', 'AdeptPhaseShift', 'Archon', 'Assimilator', 'AssimilatorRich', 'Carrier', 'Colossus', 'CyberneticsCore', 'DarkShrine', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'FleetBeacon', 'ForceField', 'Forge', 'Gateway', 'HighTemplar', 'Immortal', 'Interceptor', 'Mothership', 'MothershipCore', 'Nexus', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'Pylon', 'PylonOvercharged', 'RoboticsBay', 'RoboticsFacility', 'Sentry', 'ShieldBattery', 'Stalker', 'Stargate', 'StasisTrap', 'Tempest', 'TemplarArchive', 'TwilightCouncil', 'VoidRay', 'WarpGate', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'Armory', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'BarracksReactor', 'BarracksTechLab', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'EngineeringBay', 'Factory', 'FactoryFlying', 'FactoryReactor', 'FactoryTechLab', 'FusionCore', 'Ghost', 'GhostAcademy', 'GhostAlternate', 'GhostNova', 'Hellion', 'Hellbat', 'KD8Charge', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'Nuke', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reactor', 'Reaper', 'Refinery', 'RefineryRich', 'RepairDrone', 'SCV', 'SensorTower', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'StarportReactor', 'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BanelingNest', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'BroodlingEscort', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'CreepTumor', 'CreepTumorBurrowed', 'CreepTumorQueen', 'Drone', 'DroneBurrowed', 'EvolutionChamber', 'Extractor', 'ExtractorRich', 'GreaterSpire', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'HydraliskDen', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Larva', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpawningPool', 'SpineCrawler', 'SpineCrawlerUprooted', 'Spire', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'UltraliskCavern', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': []}, - 107: {'action_name': 'Rally_Units_unit', 'selected_type': [311, 801, 141, 61, 1955, 79, 4, 72, 69, 76, 694, 733, 64, 135, 63, 62, 75, 83, 85, 10, 488, 59, 82, 1911, 495, 78, 66, 84, 60, 894, 70, 71, 77, 1910, 74, 67, 732, 496, 68, 65, 80, 133, 81, 136, 73, 29, 31, 55, 21, 46, 38, 37, 57, 24, 18, 36, 692, 22, 27, 43, 40, 39, 30, 50, 26, 144, 145, 53, 484, 830, 689, 734, 268, 51, 48, 54, 23, 58, 132, 134, 130, 11, 56, 6, 49, 20, 1960, 1913, 45, 25, 33, 32, 28, 44, 42, 41, 19, 47, 5, 52, 691, 34, 35, 498, 500, 9, 115, 8, 96, 114, 113, 289, 143, 12, 15, 14, 13, 17, 16, 103, 112, 87, 137, 138, 104, 116, 90, 88, 1956, 102, 86, 101, 107, 117, 91, 94, 7, 120, 150, 111, 127, 100, 151, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 89, 98, 139, 92, 99, 140, 494, 493, 109, 131, 93, 499, 105, 119], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Adept', 'AdeptPhaseShift', 'Archon', 'Assimilator', 'AssimilatorRich', 'Carrier', 'Colossus', 'CyberneticsCore', 'DarkShrine', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'FleetBeacon', 'ForceField', 'Forge', 'Gateway', 'HighTemplar', 'Immortal', 'Interceptor', 'Mothership', 'MothershipCore', 'Nexus', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'Pylon', 'PylonOvercharged', 'RoboticsBay', 'RoboticsFacility', 'Sentry', 'ShieldBattery', 'Stalker', 'Stargate', 'StasisTrap', 'Tempest', 'TemplarArchive', 'TwilightCouncil', 'VoidRay', 'WarpGate', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'Armory', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'BarracksReactor', 'BarracksTechLab', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'EngineeringBay', 'Factory', 'FactoryFlying', 'FactoryReactor', 'FactoryTechLab', 'FusionCore', 'Ghost', 'GhostAcademy', 'GhostAlternate', 'GhostNova', 'Hellion', 'Hellbat', 'KD8Charge', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'Nuke', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reactor', 'Reaper', 'Refinery', 'RefineryRich', 'RepairDrone', 'SCV', 'SensorTower', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'StarportReactor', 'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BanelingNest', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'BroodlingEscort', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'CreepTumor', 'CreepTumorBurrowed', 'CreepTumorQueen', 'Drone', 'DroneBurrowed', 'EvolutionChamber', 'Extractor', 'ExtractorRich', 'GreaterSpire', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'HydraliskDen', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Larva', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpawningPool', 'SpineCrawler', 'SpineCrawlerUprooted', 'Spire', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'UltraliskCavern', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 109: {'action_name': 'Effect_Repair_unit', 'selected_type': [268, 45], 'target_type': [29, 31, 55, 21, 46, 38, 37, 57, 24, 18, 36, 692, 22, 27, 43, 40, 39, 30, 26, 144, 53, 484, 689, 734, 268, 54, 23, 132, 134, 130, 11, 56, 6, 49, 20, 1960, 1913, 45, 25, 33, 32, 28, 44, 42, 41, 19, 47, 5, 52, 691, 34, 35, 498, 500], 'selected_type_name': ['MULE', 'SCV'], 'target_type_name': ['Armory', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'BarracksReactor', 'BarracksTechLab', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'EngineeringBay', 'Factory', 'FactoryFlying', 'FactoryReactor', 'FactoryTechLab', 'FusionCore', 'GhostAcademy', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Medivac', 'MissileTurret', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reactor', 'Reaper', 'Refinery', 'RefineryRich', 'RepairDrone', 'SCV', 'SensorTower', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'StarportReactor', 'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed']}, - 110: {'action_name': 'Effect_MassRecall_pt', 'selected_type': [10, 59], 'target_type': [], 'selected_type_name': ['Mothership', 'Nexus'], 'target_type_name': []}, - 111: {'action_name': 'Effect_Blink_pt', 'selected_type': [74, 76], 'target_type': [], 'selected_type_name': ['Stalker', 'DarkTemplar'], 'target_type_name': []}, - 114: {'action_name': 'Rally_Workers_pt', 'selected_type': [59, 18, 132, 130, 86, 100, 101], 'target_type': [], 'selected_type_name': ['Nexus', 'CommandCenter', 'OrbitalCommand', 'PlanetaryFortress', 'Hatchery', 'Lair', 'Hive'], 'target_type_name': []}, - 115: {'action_name': 'Rally_Workers_unit', 'selected_type': [59, 18, 132, 130, 86, 100, 101], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Nexus', 'CommandCenter', 'OrbitalCommand', 'PlanetaryFortress', 'Hatchery', 'Lair', 'Hive'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 116: {'action_name': 'Research_ProtossAirArmor_quick', 'selected_type': [72], 'target_type': [], 'selected_type_name': ['CyberneticsCore'], 'target_type_name': []}, - 117: {'action_name': 'Research_ProtossAirWeapons_quick', 'selected_type': [72], 'target_type': [], 'selected_type_name': ['CyberneticsCore'], 'target_type_name': []}, - 118: {'action_name': 'Research_ProtossGroundArmor_quick', 'selected_type': [63], 'target_type': [], 'selected_type_name': ['Forge'], 'target_type_name': []}, - 119: {'action_name': 'Research_ProtossGroundWeapons_quick', 'selected_type': [63], 'target_type': [], 'selected_type_name': ['Forge'], 'target_type_name': []}, - 120: {'action_name': 'Research_ProtossShields_quick', 'selected_type': [63], 'target_type': [], 'selected_type_name': ['Forge'], 'target_type_name': []}, - 121: {'action_name': 'Morph_ObserverMode_quick', 'selected_type': [1911], 'target_type': [], 'selected_type_name': ['ObserverSurveillanceMode'], 'target_type_name': []}, - 122: {'action_name': 'Effect_ChronoBoostEnergyCost_unit', 'selected_type': [59], 'target_type': [64, 65, 67, 68, 69, 70, 71, 72, 133, 59, 62, 63], 'selected_type_name': ['Nexus'], 'target_type_name': ['FleetBeacon', 'TwilightCouncil', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'WarpGate', 'Nexus', 'Gateway', 'Forge']}, - 129: {'action_name': 'Cancel_Last_quick', 'selected_type': [311, 801, 141, 61, 1955, 79, 4, 72, 69, 76, 694, 733, 64, 135, 63, 62, 75, 83, 85, 10, 488, 59, 82, 1911, 495, 78, 66, 84, 60, 894, 70, 71, 77, 1910, 74, 67, 732, 496, 68, 65, 80, 133, 81, 136, 73, 29, 31, 55, 21, 46, 38, 37, 57, 24, 18, 36, 692, 22, 27, 43, 40, 39, 30, 50, 26, 144, 145, 53, 484, 830, 689, 734, 268, 51, 48, 54, 23, 58, 132, 134, 130, 11, 56, 6, 49, 20, 1960, 1913, 45, 25, 33, 32, 28, 44, 42, 41, 19, 47, 5, 52, 691, 34, 35, 498, 500, 9, 115, 8, 96, 114, 113, 289, 143, 12, 15, 14, 13, 17, 16, 103, 112, 87, 137, 138, 104, 116, 90, 88, 1956, 102, 86, 101, 107, 117, 91, 94, 7, 120, 150, 111, 127, 100, 151, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 89, 98, 139, 92, 99, 140, 494, 493, 109, 131, 93, 499, 105, 119], 'target_type': [], 'selected_type_name': ['Adept', 'AdeptPhaseShift', 'Archon', 'Assimilator', 'AssimilatorRich', 'Carrier', 'Colossus', 'CyberneticsCore', 'DarkShrine', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'FleetBeacon', 'ForceField', 'Forge', 'Gateway', 'HighTemplar', 'Immortal', 'Interceptor', 'Mothership', 'MothershipCore', 'Nexus', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'Pylon', 'PylonOvercharged', 'RoboticsBay', 'RoboticsFacility', 'Sentry', 'ShieldBattery', 'Stalker', 'Stargate', 'StasisTrap', 'Tempest', 'TemplarArchive', 'TwilightCouncil', 'VoidRay', 'WarpGate', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'Armory', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'BarracksReactor', 'BarracksTechLab', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'EngineeringBay', 'Factory', 'FactoryFlying', 'FactoryReactor', 'FactoryTechLab', 'FusionCore', 'Ghost', 'GhostAcademy', 'GhostAlternate', 'GhostNova', 'Hellion', 'Hellbat', 'KD8Charge', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'Nuke', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reactor', 'Reaper', 'Refinery', 'RefineryRich', 'RepairDrone', 'SCV', 'SensorTower', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'StarportReactor', 'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BanelingNest', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'BroodlingEscort', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'CreepTumor', 'CreepTumorBurrowed', 'CreepTumorQueen', 'Drone', 'DroneBurrowed', 'EvolutionChamber', 'Extractor', 'ExtractorRich', 'GreaterSpire', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'HydraliskDen', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Larva', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpawningPool', 'SpineCrawler', 'SpineCrawlerUprooted', 'Spire', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'UltraliskCavern', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': []}, - 157: {'action_name': 'Effect_Feedback_unit', 'selected_type': [75], 'target_type': [129, 75, 111, 499, 1912, 126, 127, 78, 10, 77, 144, 56, 495, 50, 54, 55, 125], 'selected_type_name': ['HighTemplar'], 'target_type_name': ['Overseer', 'HighTemplar', 'Infestor', 'Viper', 'OverseerOversightMode', 'Queen', 'InfestorBurrowed', 'Phoenix', 'Mothership', 'Sentry', 'GhostAlternate', 'Raven', 'Oracle', 'Ghost', 'Medivac', 'Banshee', 'QueenBurrowed']}, - 158: {'action_name': 'Behavior_PulsarBeamOff_quick', 'selected_type': [495], 'target_type': [], 'selected_type_name': ['Oracle'], 'target_type_name': []}, - 159: {'action_name': 'Behavior_PulsarBeamOn_quick', 'selected_type': [495], 'target_type': [], 'selected_type_name': ['Oracle'], 'target_type_name': []}, - 160: {'action_name': 'Morph_SurveillanceMode_quick', 'selected_type': [82], 'target_type': [], 'selected_type_name': ['Observer'], 'target_type_name': []}, - 161: {'action_name': 'Effect_Restore_unit', 'selected_type': [1910], 'target_type': [311, 801, 141, 61, 1955, 79, 4, 72, 69, 76, 694, 733, 64, 135, 63, 62, 75, 83, 85, 10, 488, 59, 82, 1911, 495, 78, 66, 84, 60, 894, 70, 71, 77, 1910, 74, 67, 732, 496, 68, 65, 80, 133, 81, 136, 73], 'selected_type_name': ['ShieldBattery'], 'target_type_name': ['Adept', 'AdeptPhaseShift', 'Archon', 'Assimilator', 'AssimilatorRich', 'Carrier', 'Colossus', 'CyberneticsCore', 'DarkShrine', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'FleetBeacon', 'ForceField', 'Forge', 'Gateway', 'HighTemplar', 'Immortal', 'Interceptor', 'Mothership', 'MothershipCore', 'Nexus', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'Pylon', 'PylonOvercharged', 'RoboticsBay', 'RoboticsFacility', 'Sentry', 'ShieldBattery', 'Stalker', 'Stargate', 'StasisTrap', 'Tempest', 'TemplarArchive', 'TwilightCouncil', 'VoidRay', 'WarpGate', 'WarpPrism', 'WarpPrismPhasing', 'Zealot']}, - 164: {'action_name': 'UnloadAllAt_unit', 'selected_type': [81, 136, 24, 18, 54, 142, 95, 893, 36, 130], 'target_type': [81, 136, 24, 18, 54, 142, 95, 893, 36, 130], 'selected_type_name': ['WarpPrism', 'WarpPrismPhasing', 'Bunker', 'CommandCenter', 'Medivac', 'NydusCanal', 'NydusNetwork', 'OverlordTransport', 'CommandCenterFlying', 'PlanetaryFortress'], 'target_type_name': ['WarpPrism', 'WarpPrismPhasing', 'Bunker', 'CommandCenter', 'Medivac', 'NydusCanal', 'NydusNetwork', 'OverlordTransport', 'CommandCenterFlying', 'PlanetaryFortress']}, - 166: {'action_name': 'Train_Disruptor_quick', 'selected_type': [71], 'target_type': [], 'selected_type_name': ['RoboticsFacility'], 'target_type_name': []}, - 167: {'action_name': 'Effect_PurificationNova_pt', 'selected_type': [694], 'target_type': [], 'selected_type_name': ['Disruptor'], 'target_type_name': []}, - 168: {'action_name': 'raw_move_camera', 'selected_type': [], 'target_type': [], 'selected_type_name': [], 'target_type_name': []}, - 169: {'action_name': 'Behavior_CloakOff_quick', 'selected_type': [144, 50, 55], 'target_type': [], 'selected_type_name': ['GhostAlternate', 'Ghost', 'Banshee'], 'target_type_name': []}, - 172: {'action_name': 'Behavior_CloakOn_quick', 'selected_type': [144, 145, 50, 55], 'target_type': [], 'selected_type_name': ['GhostAlternate', 'GhostNova', 'Ghost', 'Banshee'], 'target_type_name': []}, - 175: {'action_name': 'Behavior_GenerateCreepOff_quick', 'selected_type': [106, 893], 'target_type': [], 'selected_type_name': ['Overlord', 'OverlordTransport'], 'target_type_name': []}, - 176: {'action_name': 'Behavior_GenerateCreepOn_quick', 'selected_type': [106, 893], 'target_type': [], 'selected_type_name': ['Overlord', 'OverlordTransport'], 'target_type_name': []}, - 177: {'action_name': 'Behavior_HoldFireOff_quick', 'selected_type': [144, 50, 503], 'target_type': [], 'selected_type_name': ['GhostAlternate', 'Ghost', 'LurkerBurrowed'], 'target_type_name': []}, - 180: {'action_name': 'Behavior_HoldFireOn_quick', 'selected_type': [144, 50, 503], 'target_type': [], 'selected_type_name': ['GhostAlternate', 'Ghost', 'LurkerBurrowed'], 'target_type_name': []}, - 183: {'action_name': 'Build_Armory_pt', 'selected_type': [45], 'target_type': [], 'selected_type_name': ['SCV'], 'target_type_name': []}, - 184: {'action_name': 'Build_BanelingNest_pt', 'selected_type': [104], 'target_type': [], 'selected_type_name': ['Drone'], 'target_type_name': []}, - 185: {'action_name': 'Build_Barracks_pt', 'selected_type': [45], 'target_type': [], 'selected_type_name': ['SCV'], 'target_type_name': []}, - 186: {'action_name': 'Build_Bunker_pt', 'selected_type': [45], 'target_type': [], 'selected_type_name': ['SCV'], 'target_type_name': []}, - 187: {'action_name': 'Build_CommandCenter_pt', 'selected_type': [45], 'target_type': [], 'selected_type_name': ['SCV'], 'target_type_name': []}, - 188: {'action_name': 'Build_CreepTumor_pt', 'selected_type': [137, 126], 'target_type': [], 'selected_type_name': ['CreepTumorBurrowed', 'Queen'], 'target_type_name': []}, - 191: {'action_name': 'Build_EngineeringBay_pt', 'selected_type': [45], 'target_type': [], 'selected_type_name': ['SCV'], 'target_type_name': []}, - 192: {'action_name': 'Build_EvolutionChamber_pt', 'selected_type': [104], 'target_type': [], 'selected_type_name': ['Drone'], 'target_type_name': []}, - 193: {'action_name': 'Build_Extractor_unit', 'selected_type': [104], 'target_type': [344, 342, 343, 880, 881], 'selected_type_name': ['Drone'], 'target_type_name': ['RichVespeneGeyser', 'VespeneGeyser', 'SpacePlatformGeyser', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser']}, - 194: {'action_name': 'Build_Factory_pt', 'selected_type': [45], 'target_type': [], 'selected_type_name': ['SCV'], 'target_type_name': []}, - 195: {'action_name': 'Build_FusionCore_pt', 'selected_type': [45], 'target_type': [], 'selected_type_name': ['SCV'], 'target_type_name': []}, - 196: {'action_name': 'Build_GhostAcademy_pt', 'selected_type': [45], 'target_type': [], 'selected_type_name': ['SCV'], 'target_type_name': []}, - 197: {'action_name': 'Build_Hatchery_pt', 'selected_type': [104], 'target_type': [], 'selected_type_name': ['Drone'], 'target_type_name': []}, - 198: {'action_name': 'Build_HydraliskDen_pt', 'selected_type': [104], 'target_type': [], 'selected_type_name': ['Drone'], 'target_type_name': []}, - 199: {'action_name': 'Build_InfestationPit_pt', 'selected_type': [104], 'target_type': [], 'selected_type_name': ['Drone'], 'target_type_name': []}, - 201: {'action_name': 'Build_LurkerDen_pt', 'selected_type': [104], 'target_type': [], 'selected_type_name': ['Drone'], 'target_type_name': []}, - 202: {'action_name': 'Build_MissileTurret_pt', 'selected_type': [45], 'target_type': [], 'selected_type_name': ['SCV'], 'target_type_name': []}, - 203: {'action_name': 'Build_Nuke_quick', 'selected_type': [26], 'target_type': [], 'selected_type_name': ['GhostAcademy'], 'target_type_name': []}, - 204: {'action_name': 'Build_NydusNetwork_pt', 'selected_type': [104], 'target_type': [], 'selected_type_name': ['Drone'], 'target_type_name': []}, - 205: {'action_name': 'Build_NydusWorm_pt', 'selected_type': [95], 'target_type': [], 'selected_type_name': ['NydusNetwork'], 'target_type_name': []}, - 206: {'action_name': 'Build_Reactor_quick', 'selected_type': [43, 44, 46, 21, 27, 28], 'target_type': [], 'selected_type_name': ['FactoryFlying', 'StarportFlying', 'BarracksFlying', 'Barracks', 'Factory', 'Starport'], 'target_type_name': []}, - 207: {'action_name': 'Build_Reactor_pt', 'selected_type': [43, 44, 46, 21, 27, 28], 'target_type': [], 'selected_type_name': ['FactoryFlying', 'StarportFlying', 'BarracksFlying', 'Barracks', 'Factory', 'Starport'], 'target_type_name': []}, - 214: {'action_name': 'Build_Refinery_pt', 'selected_type': [45], 'target_type': [344, 342, 343, 880, 881], 'selected_type_name': ['SCV'], 'target_type_name': ['RichVespeneGeyser', 'VespeneGeyser', 'SpacePlatformGeyser', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser']}, - 215: {'action_name': 'Build_RoachWarren_pt', 'selected_type': [104], 'target_type': [], 'selected_type_name': ['Drone'], 'target_type_name': []}, - 216: {'action_name': 'Build_SensorTower_pt', 'selected_type': [45], 'target_type': [], 'selected_type_name': ['SCV'], 'target_type_name': []}, - 217: {'action_name': 'Build_SpawningPool_pt', 'selected_type': [104], 'target_type': [], 'selected_type_name': ['Drone'], 'target_type_name': []}, - 218: {'action_name': 'Build_SpineCrawler_pt', 'selected_type': [104], 'target_type': [], 'selected_type_name': ['Drone'], 'target_type_name': []}, - 219: {'action_name': 'Build_Spire_pt', 'selected_type': [104], 'target_type': [], 'selected_type_name': ['Drone'], 'target_type_name': []}, - 220: {'action_name': 'Build_SporeCrawler_pt', 'selected_type': [104], 'target_type': [], 'selected_type_name': ['Drone'], 'target_type_name': []}, - 221: {'action_name': 'Build_Starport_pt', 'selected_type': [45], 'target_type': [], 'selected_type_name': ['SCV'], 'target_type_name': []}, - 222: {'action_name': 'Build_SupplyDepot_pt', 'selected_type': [45], 'target_type': [], 'selected_type_name': ['SCV'], 'target_type_name': []}, - 223: {'action_name': 'Build_TechLab_quick', 'selected_type': [43, 44, 46, 21, 27, 28], 'target_type': [], 'selected_type_name': ['FactoryFlying', 'StarportFlying', 'BarracksFlying', 'Barracks', 'Factory', 'Starport'], 'target_type_name': []}, - 224: {'action_name': 'Build_TechLab_pt', 'selected_type': [43, 44, 46, 21, 27, 28], 'target_type': [], 'selected_type_name': ['FactoryFlying', 'StarportFlying', 'BarracksFlying', 'Barracks', 'Factory', 'Starport'], 'target_type_name': []}, - 231: {'action_name': 'Build_UltraliskCavern_pt', 'selected_type': [104], 'target_type': [], 'selected_type_name': ['Drone'], 'target_type_name': []}, - 232: {'action_name': 'BurrowDown_quick', 'selected_type': [7, 104, 105, 9, 107, 109, 110, 494, 111, 688, 498, 502, 503, 126], 'target_type': [], 'selected_type_name': ['InfestedTerran', 'Drone', 'Zergling', 'Baneling', 'Hydralisk', 'Ultralisk', 'Roach', 'SwarmHost', 'Infestor', 'Ravager', 'WidowMine', 'Lurker', 'LurkerBurrowed', 'Queen'], 'target_type_name': []}, - 246: {'action_name': 'BurrowUp_quick', 'selected_type': [131, 503, 493, 690, 115, 500, 116, 118, 119, 117, 125, 127, 120], 'target_type': [], 'selected_type_name': ['UltraliskBurrowed', 'LurkerBurrowed', 'SwarmHostBurrowed', 'RavagerBurrowed', 'BanelingBurrowed', 'WidowMineBurrowed', 'DroneBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'HydraliskBurrowed', 'QueenBurrowed', 'InfestorBurrowed', 'InfestedTerranBurrowed'], 'target_type_name': []}, - 293: {'action_name': 'Effect_Abduct_unit', 'selected_type': [499], 'target_type': [311, 801, 141, 61, 1955, 79, 4, 72, 69, 76, 694, 733, 64, 135, 63, 62, 75, 83, 85, 10, 488, 59, 82, 1911, 495, 78, 66, 84, 60, 894, 70, 71, 77, 1910, 74, 67, 732, 496, 68, 65, 80, 133, 81, 136, 73, 29, 31, 55, 21, 46, 38, 37, 57, 24, 18, 36, 692, 22, 27, 43, 40, 39, 30, 50, 26, 144, 145, 53, 484, 830, 689, 734, 268, 51, 48, 54, 23, 58, 132, 134, 130, 11, 56, 6, 49, 20, 1960, 1913, 45, 25, 33, 32, 28, 44, 42, 41, 19, 47, 5, 52, 691, 34, 35, 498, 500, 9, 115, 8, 96, 114, 113, 289, 143, 12, 15, 14, 13, 17, 16, 103, 112, 87, 137, 138, 104, 116, 90, 88, 1956, 102, 86, 101, 107, 117, 91, 94, 7, 120, 150, 111, 127, 100, 151, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 89, 98, 139, 92, 99, 140, 494, 493, 109, 131, 93, 499, 105, 119], 'selected_type_name': ['Viper'], 'target_type_name': ['Adept', 'AdeptPhaseShift', 'Archon', 'Assimilator', 'AssimilatorRich', 'Carrier', 'Colossus', 'CyberneticsCore', 'DarkShrine', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'FleetBeacon', 'ForceField', 'Forge', 'Gateway', 'HighTemplar', 'Immortal', 'Interceptor', 'Mothership', 'MothershipCore', 'Nexus', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'Pylon', 'PylonOvercharged', 'RoboticsBay', 'RoboticsFacility', 'Sentry', 'ShieldBattery', 'Stalker', 'Stargate', 'StasisTrap', 'Tempest', 'TemplarArchive', 'TwilightCouncil', 'VoidRay', 'WarpGate', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'Armory', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'BarracksReactor', 'BarracksTechLab', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'EngineeringBay', 'Factory', 'FactoryFlying', 'FactoryReactor', 'FactoryTechLab', 'FusionCore', 'Ghost', 'GhostAcademy', 'GhostAlternate', 'GhostNova', 'Hellion', 'Hellbat', 'KD8Charge', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'Nuke', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reactor', 'Reaper', 'Refinery', 'RefineryRich', 'RepairDrone', 'SCV', 'SensorTower', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'StarportReactor', 'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BanelingNest', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'BroodlingEscort', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'CreepTumor', 'CreepTumorBurrowed', 'CreepTumorQueen', 'Drone', 'DroneBurrowed', 'EvolutionChamber', 'Extractor', 'ExtractorRich', 'GreaterSpire', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'HydraliskDen', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Larva', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpawningPool', 'SpineCrawler', 'SpineCrawlerUprooted', 'Spire', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'UltraliskCavern', 'Viper', 'Zergling', 'ZerglingBurrowed']}, - 294: {'action_name': 'Effect_AntiArmorMissile_unit', 'selected_type': [56], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Raven'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 295: {'action_name': 'Effect_AutoTurret_pt', 'selected_type': [56], 'target_type': [], 'selected_type_name': ['Raven'], 'target_type_name': []}, - 296: {'action_name': 'Effect_BlindingCloud_pt', 'selected_type': [499], 'target_type': [], 'selected_type_name': ['Viper'], 'target_type_name': []}, - 297: {'action_name': 'Effect_CalldownMULE_pt', 'selected_type': [132], 'target_type': [], 'selected_type_name': ['OrbitalCommand'], 'target_type_name': []}, - 298: {'action_name': 'Effect_CalldownMULE_unit', 'selected_type': [132], 'target_type': [665, 666, 483, 341, 146, 147, 884, 885, 796, 797, 1961], 'selected_type_name': ['OrbitalCommand'], 'target_type_name': ['LabMineralField', 'LabMineralField750', 'MineralField750', 'MineralField', 'RichMineralField', 'RichMineralField750', 'PurifierMineralField', 'PurifierMineralField750', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'MineralField450']}, - 299: {'action_name': 'Effect_CausticSpray_unit', 'selected_type': [112], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 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'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 301: {'action_name': 'Effect_Charge_unit', 'selected_type': [73], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Zealot'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 303: {'action_name': 'Effect_Contaminate_unit', 'selected_type': [1912, 129], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['OverseerOversightMode', 'Overseer'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 304: {'action_name': 'Effect_CorrosiveBile_pt', 'selected_type': [688], 'target_type': [], 'selected_type_name': ['Ravager'], 'target_type_name': []}, - 305: {'action_name': 'Effect_EMP_pt', 'selected_type': [144, 50], 'target_type': [], 'selected_type_name': ['GhostAlternate', 'Ghost'], 'target_type_name': []}, - 307: {'action_name': 'Effect_Explode_quick', 'selected_type': [9, 115], 'target_type': [], 'selected_type_name': ['Baneling', 'BanelingBurrowed'], 'target_type_name': []}, - 308: {'action_name': 'Effect_FungalGrowth_pt', 'selected_type': [111], 'target_type': [], 'selected_type_name': ['Infestor'], 'target_type_name': []}, - 310: {'action_name': 'Effect_GhostSnipe_unit', 'selected_type': [144, 145, 50], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['GhostAlternate', 'GhostNova', 'Ghost'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 311: {'action_name': 'Effect_Heal_unit', 'selected_type': [54], 'target_type': [48, 51, 49], 'selected_type_name': ['Medivac'], 'target_type_name': ['Marine', 'Marauder', 'Reaper']}, - 314: {'action_name': 'Effect_InfestedTerrans_pt', 'selected_type': [111, 127], 'target_type': [], 'selected_type_name': ['Infestor', 'InfestorBurrowed'], 'target_type_name': []}, - 315: {'action_name': 'Effect_InjectLarva_unit', 'selected_type': [126], 'target_type': [100, 101, 86], 'selected_type_name': ['Queen'], 'target_type_name': ['Lair', 'Hive', 'Hatchery']}, - 316: {'action_name': 'Effect_InterferenceMatrix_unit', 'selected_type': [56], 'target_type': [311, 801, 141, 61, 1955, 79, 4, 72, 69, 76, 694, 733, 64, 135, 63, 62, 75, 83, 85, 10, 488, 59, 82, 1911, 495, 78, 66, 84, 60, 894, 70, 71, 77, 1910, 74, 67, 732, 496, 68, 65, 80, 133, 81, 136, 73, 29, 31, 55, 21, 46, 38, 37, 57, 24, 18, 36, 692, 22, 27, 43, 40, 39, 30, 50, 26, 144, 145, 53, 484, 830, 689, 734, 268, 51, 48, 54, 23, 58, 132, 134, 130, 11, 56, 6, 49, 20, 1960, 1913, 45, 25, 33, 32, 28, 44, 42, 41, 19, 47, 5, 52, 691, 34, 35, 498, 500, 9, 115, 8, 96, 114, 113, 289, 143, 12, 15, 14, 13, 17, 16, 103, 112, 87, 137, 138, 104, 116, 90, 88, 1956, 102, 86, 101, 107, 117, 91, 94, 7, 120, 150, 111, 127, 100, 151, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 89, 98, 139, 92, 99, 140, 494, 493, 109, 131, 93, 499, 105, 119], 'selected_type_name': ['Raven'], 'target_type_name': ['Adept', 'AdeptPhaseShift', 'Archon', 'Assimilator', 'AssimilatorRich', 'Carrier', 'Colossus', 'CyberneticsCore', 'DarkShrine', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'FleetBeacon', 'ForceField', 'Forge', 'Gateway', 'HighTemplar', 'Immortal', 'Interceptor', 'Mothership', 'MothershipCore', 'Nexus', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'Pylon', 'PylonOvercharged', 'RoboticsBay', 'RoboticsFacility', 'Sentry', 'ShieldBattery', 'Stalker', 'Stargate', 'StasisTrap', 'Tempest', 'TemplarArchive', 'TwilightCouncil', 'VoidRay', 'WarpGate', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'Armory', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'BarracksReactor', 'BarracksTechLab', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'EngineeringBay', 'Factory', 'FactoryFlying', 'FactoryReactor', 'FactoryTechLab', 'FusionCore', 'Ghost', 'GhostAcademy', 'GhostAlternate', 'GhostNova', 'Hellion', 'Hellbat', 'KD8Charge', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'Nuke', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reactor', 'Reaper', 'Refinery', 'RefineryRich', 'RepairDrone', 'SCV', 'SensorTower', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'StarportReactor', 'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BanelingNest', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'BroodlingEscort', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'CreepTumor', 'CreepTumorBurrowed', 'CreepTumorQueen', 'Drone', 'DroneBurrowed', 'EvolutionChamber', 'Extractor', 'ExtractorRich', 'GreaterSpire', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'HydraliskDen', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Larva', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpawningPool', 'SpineCrawler', 'SpineCrawlerUprooted', 'Spire', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'UltraliskCavern', 'Viper', 'Zergling', 'ZerglingBurrowed']}, - 317: {'action_name': 'Effect_KD8Charge_pt', 'selected_type': [49], 'target_type': [], 'selected_type_name': ['Reaper'], 'target_type_name': []}, - 318: {'action_name': 'Effect_LockOn_unit', 'selected_type': [692], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Cyclone'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 319: {'action_name': 'Effect_LocustSwoop_pt', 'selected_type': [693], 'target_type': [], 'selected_type_name': ['LocustFlying'], 'target_type_name': []}, - 320: {'action_name': 'Effect_MedivacIgniteAfterburners_quick', 'selected_type': [54], 'target_type': [], 'selected_type_name': ['Medivac'], 'target_type_name': []}, - 321: {'action_name': 'Effect_NeuralParasite_unit', 'selected_type': [111, 127], 'target_type': [311, 801, 141, 61, 1955, 79, 4, 72, 69, 76, 694, 733, 64, 135, 63, 62, 75, 83, 85, 10, 488, 59, 82, 1911, 495, 78, 66, 84, 60, 894, 70, 71, 77, 1910, 74, 67, 732, 496, 68, 65, 80, 133, 81, 136, 73, 29, 31, 55, 21, 46, 38, 37, 57, 24, 18, 36, 692, 22, 27, 43, 40, 39, 30, 50, 26, 144, 145, 53, 484, 830, 689, 734, 268, 51, 48, 54, 23, 58, 132, 134, 130, 11, 56, 6, 49, 20, 1960, 1913, 45, 25, 33, 32, 28, 44, 42, 41, 19, 47, 5, 52, 691, 34, 35, 498, 500, 9, 115, 8, 96, 114, 113, 289, 143, 12, 15, 14, 13, 17, 16, 103, 112, 87, 137, 138, 104, 116, 90, 88, 1956, 102, 86, 101, 107, 117, 91, 94, 7, 120, 150, 111, 127, 100, 151, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 89, 98, 139, 92, 99, 140, 494, 493, 109, 131, 93, 499, 105, 119], 'selected_type_name': ['Infestor', 'InfestorBurrowed'], 'target_type_name': ['Adept', 'AdeptPhaseShift', 'Archon', 'Assimilator', 'AssimilatorRich', 'Carrier', 'Colossus', 'CyberneticsCore', 'DarkShrine', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'FleetBeacon', 'ForceField', 'Forge', 'Gateway', 'HighTemplar', 'Immortal', 'Interceptor', 'Mothership', 'MothershipCore', 'Nexus', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'Pylon', 'PylonOvercharged', 'RoboticsBay', 'RoboticsFacility', 'Sentry', 'ShieldBattery', 'Stalker', 'Stargate', 'StasisTrap', 'Tempest', 'TemplarArchive', 'TwilightCouncil', 'VoidRay', 'WarpGate', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'Armory', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'BarracksReactor', 'BarracksTechLab', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'EngineeringBay', 'Factory', 'FactoryFlying', 'FactoryReactor', 'FactoryTechLab', 'FusionCore', 'Ghost', 'GhostAcademy', 'GhostAlternate', 'GhostNova', 'Hellion', 'Hellbat', 'KD8Charge', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'Nuke', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reactor', 'Reaper', 'Refinery', 'RefineryRich', 'RepairDrone', 'SCV', 'SensorTower', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'StarportReactor', 'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BanelingNest', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'BroodlingEscort', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'CreepTumor', 'CreepTumorBurrowed', 'CreepTumorQueen', 'Drone', 'DroneBurrowed', 'EvolutionChamber', 'Extractor', 'ExtractorRich', 'GreaterSpire', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'HydraliskDen', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Larva', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpawningPool', 'SpineCrawler', 'SpineCrawlerUprooted', 'Spire', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'UltraliskCavern', 'Viper', 'Zergling', 'ZerglingBurrowed']}, - 322: {'action_name': 'Effect_NukeCalldown_pt', 'selected_type': [144, 145, 50], 'target_type': [], 'selected_type_name': ['GhostAlternate', 'GhostNova', 'Ghost'], 'target_type_name': []}, - 323: {'action_name': 'Effect_ParasiticBomb_unit', 'selected_type': [499], 'target_type': [311, 801, 141, 61, 1955, 79, 4, 72, 69, 76, 694, 733, 64, 135, 63, 62, 75, 83, 85, 10, 488, 59, 82, 1911, 495, 78, 66, 84, 60, 894, 70, 71, 77, 1910, 74, 67, 732, 496, 68, 65, 80, 133, 81, 136, 73, 29, 31, 55, 21, 46, 38, 37, 57, 24, 18, 36, 692, 22, 27, 43, 40, 39, 30, 50, 26, 144, 145, 53, 484, 830, 689, 734, 268, 51, 48, 54, 23, 58, 132, 134, 130, 11, 56, 6, 49, 20, 1960, 1913, 45, 25, 33, 32, 28, 44, 42, 41, 19, 47, 5, 52, 691, 34, 35, 498, 500, 9, 115, 8, 96, 114, 113, 289, 143, 12, 15, 14, 13, 17, 16, 103, 112, 87, 137, 138, 104, 116, 90, 88, 1956, 102, 86, 101, 107, 117, 91, 94, 7, 120, 150, 111, 127, 100, 151, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 89, 98, 139, 92, 99, 140, 494, 493, 109, 131, 93, 499, 105, 119], 'selected_type_name': ['Viper'], 'target_type_name': ['Adept', 'AdeptPhaseShift', 'Archon', 'Assimilator', 'AssimilatorRich', 'Carrier', 'Colossus', 'CyberneticsCore', 'DarkShrine', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'FleetBeacon', 'ForceField', 'Forge', 'Gateway', 'HighTemplar', 'Immortal', 'Interceptor', 'Mothership', 'MothershipCore', 'Nexus', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'Pylon', 'PylonOvercharged', 'RoboticsBay', 'RoboticsFacility', 'Sentry', 'ShieldBattery', 'Stalker', 'Stargate', 'StasisTrap', 'Tempest', 'TemplarArchive', 'TwilightCouncil', 'VoidRay', 'WarpGate', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'Armory', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'BarracksReactor', 'BarracksTechLab', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'EngineeringBay', 'Factory', 'FactoryFlying', 'FactoryReactor', 'FactoryTechLab', 'FusionCore', 'Ghost', 'GhostAcademy', 'GhostAlternate', 'GhostNova', 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[21], 'target_type': [], 'selected_type_name': ['Barracks'], 'target_type_name': []}, - 519: {'action_name': 'Train_Roach_quick', 'selected_type': [151], 'target_type': [], 'selected_type_name': ['Larva'], 'target_type_name': []}, - 520: {'action_name': 'Train_SCV_quick', 'selected_type': [18, 132, 130], 'target_type': [], 'selected_type_name': ['CommandCenter', 'OrbitalCommand', 'PlanetaryFortress'], 'target_type_name': []}, - 521: {'action_name': 'Train_SiegeTank_quick', 'selected_type': [27], 'target_type': [], 'selected_type_name': ['Factory'], 'target_type_name': []}, - 522: {'action_name': 'Train_SwarmHost_quick', 'selected_type': [151], 'target_type': [], 'selected_type_name': ['Larva'], 'target_type_name': []}, - 523: {'action_name': 'Train_Thor_quick', 'selected_type': [27], 'target_type': [], 'selected_type_name': ['Factory'], 'target_type_name': []}, - 524: {'action_name': 'Train_Ultralisk_quick', 'selected_type': [151], 'target_type': [], 'selected_type_name': ['Larva'], 'target_type_name': []}, - 525: {'action_name': 'Train_VikingFighter_quick', 'selected_type': [28], 'target_type': [], 'selected_type_name': ['Starport'], 'target_type_name': []}, - 526: {'action_name': 'Train_Viper_quick', 'selected_type': [151], 'target_type': [], 'selected_type_name': ['Larva'], 'target_type_name': []}, - 527: {'action_name': 'Train_WidowMine_quick', 'selected_type': [27], 'target_type': [], 'selected_type_name': ['Factory'], 'target_type_name': []}, - 528: {'action_name': 'Train_Zergling_quick', 'selected_type': [151], 'target_type': [], 'selected_type_name': ['Larva'], 'target_type_name': []}, - 537: {'action_name': 'Effect_YamatoGun_unit', 'selected_type': [57], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 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'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 538: {'action_name': 'Effect_KD8Charge_unit', 'selected_type': [49], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 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'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 553: {'action_name': 'Research_AnabolicSynthesis_quick', 'selected_type': [93], 'target_type': [], 'selected_type_name': ['UltraliskCavern'], 'target_type_name': []}, - 554: {'action_name': 'Research_CycloneLockOnDamage_quick', 'selected_type': [39], 'target_type': [], 'selected_type_name': ['FactoryTechLab'], 'target_type_name': []}, - 556: {'action_name': 'UnloadUnit_quick', 'selected_type': [81, 136, 24, 18, 54, 142, 95, 893, 36, 130], 'target_type': [], 'selected_type_name': ['WarpPrism', 'WarpPrismPhasing', 'Bunker', 'CommandCenter', 'Medivac', 'NydusCanal', 'NydusNetwork', 'OverlordTransport', 'CommandCenterFlying', 'PlanetaryFortress'], 'target_type_name': []}, - 24: {'action_name': 'Hallucination_HighTemplar_quick', 'selected_type': [77], 'target_type': [], 'selected_type_name': ['Sentry'], 'target_type_name': []}, - 93: {'action_name': 'Hallucination_Adept_quick', 'selected_type': [77], 'target_type': [], 'selected_type_name': ['Sentry'], 'target_type_name': []}, - 200: {'action_name': 'Build_Interceptors_autocast', 'selected_type': [79], 'target_type': [], 'selected_type_name': ['Carrier'], 'target_type_name': []}, - 247: {'action_name': 'BurrowUp_autocast', 'selected_type': [115, 117, 119], 'target_type': [], 'selected_type_name': ['BanelingBurrowed', 'HydraliskBurrowed', 'ZerglingBurrowed'], 'target_type_name': []}, - 302: {'action_name': 'Effect_Charge_autocast', 'selected_type': [73], 'target_type': [], 'selected_type_name': ['Zealot'], 'target_type_name': []}, - 312: {'action_name': 'Effect_Heal_autocast', 'selected_type': [54], 'target_type': [], 'selected_type_name': ['Medivac'], 'target_type_name': []}, - 324: {'action_name': 'Effect_Repair_autocast', 'selected_type': [268, 45], 'target_type': [], 'selected_type_name': ['MULE', 'SCV'], 'target_type_name': []}, - 331: {'action_name': 'Effect_Restore_autocast', 'selected_type': [1910], 'target_type': [], 'selected_type_name': ['ShieldBattery'], 'target_type_name': []}, - 541: {'action_name': 'Effect_LockOn_autocast', 'selected_type': [692], 'target_type': [], 'selected_type_name': ['Cyclone'], 'target_type_name': []}, - 544: {'action_name': 'Morph_WarpGate_autocast', 'selected_type': [62], 'target_type': [], 'selected_type_name': ['Gateway'], 'target_type_name': []}, - 112: {'action_name': 'Effect_Blink_unit', 'selected_type': [74, 76], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Stalker', 'DarkTemplar'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 300: {'action_name': 'Effect_Charge_pt', 'selected_type': [73], 'target_type': [], 'selected_type_name': ['Zealot'], 'target_type_name': []}, - 33: {'action_name': 'Effect_ChronoBoost_unit', 'selected_type': [59], 'target_type': [64, 65, 67, 68, 69, 70, 71, 72, 133, 59, 62, 63], 'selected_type_name': ['Nexus'], 'target_type_name': ['FleetBeacon', 'TwilightCouncil', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'WarpGate', 'Nexus', 'Gateway', 'Forge']}, - 306: {'action_name': 'Effect_EMP_unit', 'selected_type': [144, 145, 50], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['GhostAlternate', 'GhostNova', 'Ghost'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 309: {'action_name': 'Effect_FungalGrowth_unit', 'selected_type': [111], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Infestor'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 313: {'action_name': 'Effect_ImmortalBarrier_autocast', 'selected_type': [83], 'target_type': [], 'selected_type_name': ['Immortal'], 'target_type_name': []}, - 91: {'action_name': 'Effect_ImmortalBarrier_quick', 'selected_type': [83], 'target_type': [], 'selected_type_name': ['Immortal'], 'target_type_name': []}, - 108: {'action_name': 'Effect_Repair_pt', 'selected_type': [268, 45], 'target_type': [], 'selected_type_name': ['MULE', 'SCV'], 'target_type_name': []}, - 336: {'action_name': 'Effect_SpawnLocusts_unit', 'selected_type': [493, 494], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['SwarmHostBurrowed', 'SwarmHost'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 353: {'action_name': 'Effect_WidowMineAttack_autocast', 'selected_type': [498, 500], 'target_type': [], 'selected_type_name': ['WidowMine', 'WidowMineBurrowed'], 'target_type_name': []}, - 351: {'action_name': 'Effect_WidowMineAttack_pt', 'selected_type': [498, 500], 'target_type': [], 'selected_type_name': ['WidowMine', 'WidowMineBurrowed'], 'target_type_name': []}, - 352: {'action_name': 'Effect_WidowMineAttack_unit', 'selected_type': [498, 500], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['WidowMine', 'WidowMineBurrowed'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 392: {'action_name': 'Morph_LurkerDen_quick', 'selected_type': [91], 'target_type': [], 'selected_type_name': ['HydraliskDen'], 'target_type_name': []}, - 393: {'action_name': 'Morph_Mothership_quick', 'selected_type': [488], 'target_type': [], 'selected_type_name': ['MothershipCore'], 'target_type_name': []}, - 435: {'action_name': 'Research_CycloneRapidFireLaunchers_quick', 'selected_type': [39], 'target_type': [], 'selected_type_name': ['FactoryTechLab'], 'target_type_name': []}, - 563: {'action_name': 'Research_EnhancedShockwaves_quick', 'selected_type': [26], 'target_type': [], 'selected_type_name': ['GhostAcademy'], 'target_type_name': []}, - 18: {'action_name': 'Research_InterceptorGravitonCatapult_quick', 'selected_type': [64], 'target_type': [], 'selected_type_name': ['FleetBeacon'], 'target_type_name': []}, - 443: {'action_name': 'Research_NeosteelFrame_quick', 'selected_type': [22], 'target_type': [], 'selected_type_name': ['EngineeringBay'], 'target_type_name': []}, - 449: {'action_name': 'Research_RavenRecalibratedExplosives_quick', 'selected_type': [41], 'target_type': [], 'selected_type_name': ['StarportTechLab'], 'target_type_name': []}, - 513: {'action_name': 'Train_MothershipCore_quick', 'selected_type': [59], 'target_type': [], 'selected_type_name': ['Nexus'], 'target_type_name': []}, -} - -def get_general(general_id): - return {k: v for k, v in ACTION_INFO_MASK.items() if v['ability_id'] == general_id} - - -def merge_judge(target_general_action, val): - ret = [] - for k, v in target_general_action.items(): - if v['target_unit'] != val['target_unit']: - continue - if v['target_location'] != val['target_location']: - continue - if v['func_type'] != val['func_type']: - continue - ret.append(k) - try: - assert(len(ret) == 1) - except AssertionError: - print(target_general_action) - print(val) - print(ret) - return ret[0] - - -GENERAL_ACTION_INFO_MASK = {} -ACT_TO_GENERAL_ACT = {} -ACT_TO_GENERAL_ACT_ARRAY = np.full(max(ACTION_INFO_MASK.keys()) + 1, -1, dtype=np.int) -for k, v in ACTION_INFO_MASK.items(): - general_id = v['general_id'] - if general_id is None or general_id == 0: - GENERAL_ACTION_INFO_MASK[k] = v - ACT_TO_GENERAL_ACT[k] = k - ACT_TO_GENERAL_ACT_ARRAY[k] = k - else: - target_general_action = get_general(general_id) - action_id = merge_judge(target_general_action, v) - ACT_TO_GENERAL_ACT[k] = action_id - ACT_TO_GENERAL_ACT_ARRAY[k] = action_id diff --git a/dizoo/distar/envs/meta.py b/dizoo/distar/envs/meta.py index 6eb39b1661..569fac51c6 100644 --- a/dizoo/distar/envs/meta.py +++ b/dizoo/distar/envs/meta.py @@ -9,3 +9,4 @@ NUM_QUEUE_ACTION = 49 NUM_BUFFS = 50 NUM_ADDON = 9 +MAX_SELECTED_UNITS_NUM = 64 diff --git a/dizoo/distar/envs/static_data.py b/dizoo/distar/envs/static_data.py index a0674c7bb1..e4ea003dc3 100644 --- a/dizoo/distar/envs/static_data.py +++ b/dizoo/distar/envs/static_data.py @@ -1,22 +1,1045 @@ -# Copyright 2017 Google Inc. All Rights Reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS-IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -"""Expose static data in a more useful form than the raw protos.""" - import six import torch import numpy as np -from .action_dict import ACTION_INFO_MASK, GENERAL_ACTION_INFO_MASK, ACTIONS_STAT +from collections import defaultdict + + +ACTION_INFO_MASK = \ + { + 0: {'name': 'no_op', 'func_type': 'raw_no_op', 'ability_id': None, 'general_id': None, 'goal': 'other', 'special_goal': None, 'queued': False, 'selected_units': False, 'target_unit': False, 'target_location': False}, + 168: {'name': 'raw_move_camera', 'func_type': 'raw_move_camera', 'ability_id': None, 'general_id': None, 'goal': 'other', 'special_goal': None, 'queued': False, 'selected_units': False, 'target_unit': False, 'target_location': True}, + 2: {'name': 'Attack_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3674, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BATTLECRUISER', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MEDIVAC', 'TERRAN_MISSILETURRET', 'TERRAN_MULE', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_RAVEN', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'TERRAN_WIDOWMINE', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CHANGELING', 'ZERG_CHANGELINGMARINE', 'ZERG_CHANGELINGMARINESHIELD', 'ZERG_CHANGELINGZEALOT', 'ZERG_CHANGELINGZERGLING', 'ZERG_CHANGELINGZERGLINGWINGS', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTOR', 'ZERG_INFESTORBURROWED', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMP', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_OVERLORD', 'ZERG_OVERLORDTRANSPORT', 'ZERG_OVERSEER', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_ROACHBURROWED', 'ZERG_SPINECRAWLER', 'ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLER', 'ZERG_SPORECRAWLERUPROOTED', 'ZERG_SWARMHOSTMP', 'ZERG_ULTRALISK', 'ZERG_VIPER', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ADEPTPHASESHIFT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 57, 24, 692, 50, 53, 484, 689, 734, 51, 48, 54, 23, 268, 130, 56, 49, 45, 33, 32, 52, 691, 34, 35, 498, 9, 289, 114, 12, 15, 14, 13, 17, 16, 112, 104, 107, 111, 127, 7, 489, 693, 502, 503, 108, 106, 893, 129, 126, 688, 110, 118, 98, 139, 99, 140, 494, 109, 499, 105, 311, 801, 141, 79, 4, 76, 694, 733, 75, 83, 85, 10, 488, 82, 495, 78, 66, 84, 894, 77, 74, 496, 80, 81, 73]}, + 3: {'name': 'Attack_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3674, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BATTLECRUISER', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MEDIVAC', 'TERRAN_MISSILETURRET', 'TERRAN_MULE', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_RAVEN', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'TERRAN_WIDOWMINE', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CHANGELING', 'ZERG_CHANGELINGMARINE', 'ZERG_CHANGELINGMARINESHIELD', 'ZERG_CHANGELINGZEALOT', 'ZERG_CHANGELINGZERGLING', 'ZERG_CHANGELINGZERGLINGWINGS', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTOR', 'ZERG_INFESTORBURROWED', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMP', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_OVERLORD', 'ZERG_OVERLORDTRANSPORT', 'ZERG_OVERSEER', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_ROACHBURROWED', 'ZERG_SPINECRAWLER', 'ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLER', 'ZERG_SPORECRAWLERUPROOTED', 'ZERG_SWARMHOSTMP', 'ZERG_ULTRALISK', 'ZERG_VIPER', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ADEPTPHASESHIFT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 57, 24, 692, 50, 53, 484, 689, 734, 51, 48, 54, 23, 268, 130, 56, 49, 45, 33, 32, 52, 691, 34, 35, 498, 9, 289, 114, 12, 15, 14, 13, 17, 16, 112, 104, 107, 111, 127, 7, 489, 693, 502, 503, 108, 106, 893, 129, 126, 688, 110, 118, 98, 139, 99, 140, 494, 109, 499, 105, 311, 801, 141, 79, 4, 76, 694, 733, 75, 83, 85, 10, 488, 82, 495, 78, 66, 84, 894, 77, 74, 496, 80, 81, 73]}, + 4: {'name': 'Attack_Attack_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 23, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MISSILETURRET', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_SPINECRAWLER', 'ZERG_SPORECRAWLER', 'ZERG_ULTRALISK', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 24, 692, 50, 53, 484, 689, 734, 51, 48, 23, 130, 49, 45, 33, 32, 52, 691, 34, 35, 9, 289, 114, 112, 104, 107, 7, 489, 693, 503, 108, 126, 688, 110, 98, 99, 109, 105, 311, 141, 79, 4, 76, 83, 85, 10, 488, 78, 66, 84, 894, 77, 74, 496, 80, 73]}, + 6: {'name': 'Attack_AttackBuilding_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2048, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MISSILETURRET', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_SPINECRAWLER', 'ZERG_SPORECRAWLER', 'ZERG_ULTRALISK', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 24, 692, 50, 53, 484, 689, 734, 51, 48, 23, 130, 49, 45, 33, 32, 52, 691, 34, 35, 9, 289, 114, 112, 104, 107, 7, 489, 693, 503, 108, 126, 688, 110, 98, 99, 109, 105, 311, 141, 79, 4, 76, 83, 85, 10, 488, 78, 66, 84, 894, 77, 74, 496, 80, 73]}, + 5: {'name': 'Attack_Attack_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 23, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MISSILETURRET', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_SPINECRAWLER', 'ZERG_SPORECRAWLER', 'ZERG_ULTRALISK', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 24, 692, 50, 53, 484, 689, 734, 51, 48, 23, 130, 49, 45, 33, 32, 52, 691, 34, 35, 9, 289, 114, 112, 104, 107, 7, 489, 693, 503, 108, 126, 688, 110, 98, 99, 109, 105, 311, 141, 79, 4, 76, 83, 85, 10, 488, 78, 66, 84, 894, 77, 74, 496, 80, 73]}, + 7: {'name': 'Attack_AttackBuilding_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2048, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MISSILETURRET', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_SPINECRAWLER', 'ZERG_SPORECRAWLER', 'ZERG_ULTRALISK', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 24, 692, 50, 53, 484, 689, 734, 51, 48, 23, 130, 49, 45, 33, 32, 52, 691, 34, 35, 9, 289, 114, 112, 104, 107, 7, 489, 693, 503, 108, 126, 688, 110, 98, 99, 109, 105, 311, 141, 79, 4, 76, 83, 85, 10, 488, 78, 66, 84, 894, 77, 74, 496, 80, 73]}, + 539: {'name': 'Attack_Battlecruiser_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3771, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_BATTLECRUISER'], 'avail_unit_type_id': [57]}, + 540: {'name': 'Attack_Battlecruiser_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3771, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_BATTLECRUISER'], 'avail_unit_type_id': [57]}, + 8: {'name': 'Attack_Redirect_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1682, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MISSILETURRET', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_SPINECRAWLER', 'ZERG_SPORECRAWLER', 'ZERG_ULTRALISK', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 24, 692, 50, 53, 484, 689, 734, 51, 48, 23, 130, 49, 45, 33, 32, 52, 691, 34, 35, 9, 289, 114, 112, 104, 107, 7, 489, 693, 503, 108, 126, 688, 110, 98, 99, 109, 105, 311, 141, 79, 4, 76, 83, 85, 10, 488, 78, 66, 84, 894, 77, 74, 496, 80, 73]}, + 9: {'name': 'Attack_Redirect_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 1682, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MISSILETURRET', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_SPINECRAWLER', 'ZERG_SPORECRAWLER', 'ZERG_ULTRALISK', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 24, 692, 50, 53, 484, 689, 734, 51, 48, 23, 130, 49, 45, 33, 32, 52, 691, 34, 35, 9, 289, 114, 112, 104, 107, 7, 489, 693, 503, 108, 126, 688, 110, 98, 99, 109, 105, 311, 141, 79, 4, 76, 83, 85, 10, 488, 78, 66, 84, 894, 77, 74, 496, 80, 73]}, + 88: {'name': 'Behavior_BuildingAttackOff_quick', 'func_type': 'raw_cmd', 'ability_id': 2082, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_BANELING'], 'avail_unit_type_id': [9]}, + 87: {'name': 'Behavior_BuildingAttackOn_quick', 'func_type': 'raw_cmd', 'ability_id': 2081, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_BANELING'], 'avail_unit_type_id': [9]}, + 169: {'name': 'Behavior_CloakOff_quick', 'func_type': 'raw_cmd', 'ability_id': 3677, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_BANSHEE', 'TERRAN_GHOST'], 'avail_unit_type_id': [55, 50]}, + 170: {'name': 'Behavior_CloakOff_Banshee_quick', 'func_type': 'raw_cmd', 'ability_id': 393, 'general_id': 3677, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_BANSHEE'], 'avail_unit_type_id': [55]}, + 171: {'name': 'Behavior_CloakOff_Ghost_quick', 'func_type': 'raw_cmd', 'ability_id': 383, 'general_id': 3677, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, + 172: {'name': 'Behavior_CloakOn_quick', 'func_type': 'raw_cmd', 'ability_id': 3676, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_BANSHEE', 'TERRAN_GHOST'], 'avail_unit_type_id': [55, 50]}, + 173: {'name': 'Behavior_CloakOn_Banshee_quick', 'func_type': 'raw_cmd', 'ability_id': 392, 'general_id': 3676, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_BANSHEE'], 'avail_unit_type_id': [55]}, + 174: {'name': 'Behavior_CloakOn_Ghost_quick', 'func_type': 'raw_cmd', 'ability_id': 382, 'general_id': 3676, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, + 175: {'name': 'Behavior_GenerateCreepOff_quick', 'func_type': 'raw_cmd', 'ability_id': 1693, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_OVERLORD', 'ZERG_OVERLORDTRANSPORT'], 'avail_unit_type_id': [106, 893]}, + 176: {'name': 'Behavior_GenerateCreepOn_quick', 'func_type': 'raw_cmd', 'ability_id': 1692, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_OVERLORD', 'ZERG_OVERLORDTRANSPORT'], 'avail_unit_type_id': [106, 893]}, + 178: {'name': 'Behavior_HoldFireOff_Ghost_quick', 'func_type': 'raw_cmd', 'ability_id': 38, 'general_id': 3689, 'goal': 'other', 'special_goal': 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['PROTOSS_DARKTEMPLAR', 'PROTOSS_STALKER'], 'avail_unit_type_id': [76, 74]}, + 135: {'name': 'Effect_Blink_Stalker_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1442, 'general_id': 3687, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_STALKER'], 'avail_unit_type_id': [74]}, + 112: {'name': 'Effect_Blink_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3687, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_DARKTEMPLAR', 'PROTOSS_STALKER'], 'avail_unit_type_id': [76, 74]}, + 297: {'name': 'Effect_CalldownMULE_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 171, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_ORBITALCOMMAND'], 'avail_unit_type_id': [132]}, + 298: {'name': 'Effect_CalldownMULE_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 171, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_ORBITALCOMMAND'], 'avail_unit_type_id': [132]}, + 299: {'name': 'Effect_CausticSpray_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2324, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_CORRUPTOR'], 'avail_unit_type_id': [112]}, + 302: {'name': 'Effect_Charge_autocast', 'func_type': 'raw_autocast', 'ability_id': 1819, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_ZEALOT'], 'avail_unit_type_id': [73]}, + 300: {'name': 'Effect_Charge_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1819, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_ZEALOT'], 'avail_unit_type_id': [73]}, + 301: {'name': 'Effect_Charge_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 1819, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_ZEALOT'], 'avail_unit_type_id': [73]}, + 122: {'name': 'Effect_ChronoBoostEnergyCost_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3755, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_NEXUS'], 'avail_unit_type_id': [59]}, + 33: {'name': 'Effect_ChronoBoost_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 261, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_NEXUS'], 'avail_unit_type_id': [59]}, + 303: {'name': 'Effect_Contaminate_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 1825, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_OVERSEER'], 'avail_unit_type_id': [129]}, + 304: {'name': 'Effect_CorrosiveBile_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2338, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_RAVAGER'], 'avail_unit_type_id': [688]}, + 305: {'name': 'Effect_EMP_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1628, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, + 306: {'name': 'Effect_EMP_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 1628, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, + 307: {'name': 'Effect_Explode_quick', 'func_type': 'raw_cmd', 'ability_id': 42, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_BANELING', 'ZERG_BANELINGBURROWED'], 'avail_unit_type_id': [9, 115]}, + 157: {'name': 'Effect_Feedback_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 140, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_HIGHTEMPLAR'], 'avail_unit_type_id': [75]}, + 79: {'name': 'Effect_ForceField_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1526, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, + 308: {'name': 'Effect_FungalGrowth_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 74, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_INFESTOR', 'ZERG_INFESTORBURROWED'], 'avail_unit_type_id': [111, 127]}, + 309: {'name': 'Effect_FungalGrowth_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 74, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_INFESTOR', 'ZERG_INFESTORBURROWED'], 'avail_unit_type_id': [111, 127]}, + 310: {'name': 'Effect_GhostSnipe_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2714, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, + 32: {'name': 'Effect_GravitonBeam_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 173, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_PHOENIX'], 'avail_unit_type_id': [78]}, + 20: {'name': 'Effect_GuardianShield_quick', 'func_type': 'raw_cmd', 'ability_id': 76, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, + 312: {'name': 'Effect_Heal_autocast', 'func_type': 'raw_autocast', 'ability_id': 386, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_MEDIVAC'], 'avail_unit_type_id': [54]}, + 311: {'name': 'Effect_Heal_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 386, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_MEDIVAC'], 'avail_unit_type_id': [54]}, + 313: {'name': 'Effect_ImmortalBarrier_autocast', 'func_type': 'raw_autocast', 'ability_id': 2328, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_IMMORTAL'], 'avail_unit_type_id': [83]}, + 91: {'name': 'Effect_ImmortalBarrier_quick', 'func_type': 'raw_cmd', 'ability_id': 2328, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_IMMORTAL'], 'avail_unit_type_id': [83]}, + 314: {'name': 'Effect_InfestedTerrans_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 247, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_INFESTOR', 'ZERG_INFESTORBURROWED'], 'avail_unit_type_id': [111, 127]}, + 315: {'name': 'Effect_InjectLarva_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 251, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_QUEEN'], 'avail_unit_type_id': [126]}, + 316: {'name': 'Effect_InterferenceMatrix_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3747, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_RAVEN'], 'avail_unit_type_id': [56]}, + 317: {'name': 'Effect_KD8Charge_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2588, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_REAPER'], 'avail_unit_type_id': [49]}, + 538: {'name': 'Effect_KD8Charge_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2588, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_REAPER'], 'avail_unit_type_id': [49]}, + 318: {'name': 'Effect_LockOn_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2350, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_CYCLONE'], 'avail_unit_type_id': [692]}, + 541: {'name': 'Effect_LockOn_autocast', 'func_type': 'raw_autocast', 'ability_id': 2350, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_CYCLONE'], 'avail_unit_type_id': [692]}, + 319: {'name': 'Effect_LocustSwoop_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2387, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_LOCUSTMPFLYING'], 'avail_unit_type_id': [693]}, + 110: {'name': 'Effect_MassRecall_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3686, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE'], 'avail_unit_type_id': [10, 488]}, + 136: {'name': 'Effect_MassRecall_Mothership_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2368, 'general_id': 3686, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_MOTHERSHIP'], 'avail_unit_type_id': [10]}, + 162: {'name': 'Effect_MassRecall_Nexus_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3757, 'general_id': 3686, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_NEXUS'], 'avail_unit_type_id': [59]}, + 137: {'name': 'Effect_MassRecall_StrategicRecall_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 142, 'general_id': 3686, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_MOTHERSHIP'], 'avail_unit_type_id': [10]}, + 320: {'name': 'Effect_MedivacIgniteAfterburners_quick', 'func_type': 'raw_cmd', 'ability_id': 2116, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_MEDIVAC'], 'avail_unit_type_id': [54]}, + 321: {'name': 'Effect_NeuralParasite_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 249, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_INFESTOR', 'ZERG_INFESTORBURROWED'], 'avail_unit_type_id': [111, 127]}, + 322: {'name': 'Effect_NukeCalldown_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1622, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, + 90: {'name': 'Effect_OracleRevelation_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2146, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_ORACLE'], 'avail_unit_type_id': [495]}, + 323: {'name': 'Effect_ParasiticBomb_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2542, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_VIPER'], 'avail_unit_type_id': [499]}, + 65: {'name': 'Effect_PsiStorm_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1036, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_HIGHTEMPLAR'], 'avail_unit_type_id': [75]}, + 167: {'name': 'Effect_PurificationNova_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2346, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_DISRUPTOR'], 'avail_unit_type_id': [694]}, + 324: {'name': 'Effect_Repair_autocast', 'func_type': 'raw_autocast', 'ability_id': 3685, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_MULE', 'TERRAN_SCV', 'TERRAN_REPAIRDRONE'], 'avail_unit_type_id': [268, 45, 1913]}, + 108: {'name': 'Effect_Repair_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3685, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_MULE', 'TERRAN_SCV', 'TERRAN_REPAIRDRONE'], 'avail_unit_type_id': [268, 45, 1913]}, + 109: {'name': 'Effect_Repair_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3685, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_MULE', 'TERRAN_SCV', 'TERRAN_REPAIRDRONE'], 'avail_unit_type_id': [268, 45, 1913]}, + 326: {'name': 'Effect_Repair_Mule_autocast', 'func_type': 'raw_autocast', 'ability_id': 78, 'general_id': 3685, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_MULE'], 'avail_unit_type_id': [268]}, + 325: {'name': 'Effect_Repair_Mule_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 78, 'general_id': 3685, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_MULE'], 'avail_unit_type_id': [268]}, + 328: {'name': 'Effect_Repair_RepairDrone_autocast', 'func_type': 'raw_autocast', 'ability_id': 3751, 'general_id': 3685, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_REPAIRDRONE'], 'avail_unit_type_id': [1913]}, + 327: {'name': 'Effect_Repair_RepairDrone_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3751, 'general_id': 3685, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_REPAIRDRONE'], 'avail_unit_type_id': [1913]}, + 330: {'name': 'Effect_Repair_SCV_autocast', 'func_type': 'raw_autocast', 'ability_id': 316, 'general_id': 3685, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_SCV'], 'avail_unit_type_id': [45]}, + 329: {'name': 'Effect_Repair_SCV_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 316, 'general_id': 3685, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_SCV'], 'avail_unit_type_id': [45]}, + 331: {'name': 'Effect_Restore_autocast', 'func_type': 'raw_autocast', 'ability_id': 3765, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SHIELDBATTERY'], 'avail_unit_type_id': [1910]}, + 161: {'name': 'Effect_Restore_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3765, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_SHIELDBATTERY'], 'avail_unit_type_id': [1910]}, + 332: {'name': 'Effect_Salvage_quick', 'func_type': 'raw_cmd', 'ability_id': 32, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_BUNKER'], 'avail_unit_type_id': [24]}, + 333: {'name': 'Effect_Scan_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 399, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_ORBITALCOMMAND'], 'avail_unit_type_id': [132]}, + 113: {'name': 'Effect_ShadowStride_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2700, 'general_id': 3687, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_DARKTEMPLAR'], 'avail_unit_type_id': [76]}, + 334: {'name': 'Effect_SpawnChangeling_quick', 'func_type': 'raw_cmd', 'ability_id': 181, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_OVERSEER'], 'avail_unit_type_id': [129]}, + 335: {'name': 'Effect_SpawnLocusts_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2704, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_SWARMHOSTBURROWEDMP', 'ZERG_SWARMHOSTMP'], 'avail_unit_type_id': [493, 494]}, + 336: {'name': 'Effect_SpawnLocusts_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2704, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_SWARMHOSTBURROWEDMP', 'ZERG_SWARMHOSTMP'], 'avail_unit_type_id': [493, 494]}, + 337: {'name': 'Effect_Spray_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3684, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_SCV', 'ZERG_DRONE', 'PROTOSS_PROBE'], 'avail_unit_type_id': [45, 104, 84]}, + 338: {'name': 'Effect_Spray_Protoss_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 30, 'general_id': 3684, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_PROBE'], 'avail_unit_type_id': [84]}, + 339: {'name': 'Effect_Spray_Terran_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 26, 'general_id': 3684, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_SCV'], 'avail_unit_type_id': [45]}, + 340: {'name': 'Effect_Spray_Zerg_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 28, 'general_id': 3684, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_DRONE'], 'avail_unit_type_id': [104]}, + 341: {'name': 'Effect_Stim_quick', 'func_type': 'raw_cmd', 'ability_id': 3675, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_BUNKER', 'TERRAN_MARAUDER', 'TERRAN_MARINE'], 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408: {'name': 'Morph_SupplyDepot_Raise_quick', 'func_type': 'raw_cmd', 'ability_id': 558, 'general_id': 0, 'goal': 'other', 'special_goal': 'morph', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_SUPPLYDEPOTLOWERED'], 'avail_unit_type_id': [47]}, + 160: {'name': 'Morph_SurveillanceMode_quick', 'func_type': 'raw_cmd', 'ability_id': 3741, 'general_id': 0, 'goal': 'other', 'special_goal': 'morph', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_OBSERVER'], 'avail_unit_type_id': [82]}, + 409: {'name': 'Morph_ThorExplosiveMode_quick', 'func_type': 'raw_cmd', 'ability_id': 2364, 'general_id': 0, 'goal': 'other', 'special_goal': 'morph', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_THORAP'], 'avail_unit_type_id': [691]}, + 410: {'name': 'Morph_ThorHighImpactMode_quick', 'func_type': 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'special_goal': 'morph', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_VIKINGFIGHTER'], 'avail_unit_type_id': [35]}, + 414: {'name': 'Morph_VikingFighterMode_quick', 'func_type': 'raw_cmd', 'ability_id': 405, 'general_id': 0, 'goal': 'other', 'special_goal': 'morph', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_VIKINGASSAULT'], 'avail_unit_type_id': [34]}, + 77: {'name': 'Morph_WarpGate_quick', 'func_type': 'raw_cmd', 'ability_id': 1518, 'general_id': 0, 'goal': 'other', 'special_goal': 'morph', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_GATEWAY'], 'avail_unit_type_id': [62]}, + 544: {'name': 'Morph_WarpGate_autocast', 'func_type': 'raw_autocast', 'ability_id': 1518, 'general_id': 0, 'goal': 'other', 'special_goal': 'morph', 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_GATEWAY'], 'avail_unit_type_id': [62]}, + 80: {'name': 'Morph_WarpPrismPhasingMode_quick', 'func_type': 'raw_cmd', 'ability_id': 1528, 'general_id': 0, 'goal': 'other', 'special_goal': 'morph', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_WARPPRISM'], 'avail_unit_type_id': [81]}, + 81: {'name': 'Morph_WarpPrismTransportMode_quick', 'func_type': 'raw_cmd', 'ability_id': 1530, 'general_id': 0, 'goal': 'other', 'special_goal': 'morph', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_WARPPRISMPHASING'], 'avail_unit_type_id': [136]}, + 13: {'name': 'Move_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3794, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_BANSHEE', 'TERRAN_BARRACKSFLYING', 'TERRAN_BATTLECRUISER', 'TERRAN_COMMANDCENTERFLYING', 'TERRAN_CYCLONE', 'TERRAN_FACTORYFLYING', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MEDIVAC', 'TERRAN_MULE', 'TERRAN_ORBITALCOMMANDFLYING', 'TERRAN_RAVEN', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_STARPORTFLYING', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'TERRAN_WIDOWMINE', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_BROODLORDCOCOON', 'ZERG_CHANGELING', 'ZERG_CHANGELINGMARINE', 'ZERG_CHANGELINGMARINESHIELD', 'ZERG_CHANGELINGZEALOT', 'ZERG_CHANGELINGZERGLING', 'ZERG_CHANGELINGZERGLINGWINGS', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTEDTERRANSEGG', 'ZERG_INFESTOR', 'ZERG_INFESTORBURROWED', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMP', 'ZERG_MUTALISK', 'ZERG_OVERLORD', 'ZERG_OVERLORDCOCOON', 'ZERG_OVERLORDTRANSPORT', 'ZERG_OVERSEER', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_ROACHBURROWED', 'ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLERUPROOTED', 'ZERG_SWARMHOSTMP', 'ZERG_TRANSPORTOVERLORDCOCOON', 'ZERG_ULTRALISK', 'ZERG_VIPER', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ADEPTPHASESHIFT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PROBE', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [55, 46, 57, 36, 692, 43, 50, 53, 484, 689, 51, 48, 54, 268, 134, 56, 49, 45, 33, 44, 52, 691, 34, 35, 498, 9, 289, 114, 113, 12, 15, 14, 13, 17, 16, 112, 104, 107, 150, 111, 127, 7, 489, 693, 502, 108, 106, 128, 893, 129, 126, 688, 110, 118, 139, 140, 494, 892, 109, 499, 105, 311, 801, 141, 79, 4, 76, 694, 733, 75, 83, 85, 10, 488, 82, 495, 78, 84, 77, 74, 496, 80, 81, 73]}, + 14: {'name': 'Move_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3794, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_BANSHEE', 'TERRAN_BARRACKSFLYING', 'TERRAN_BATTLECRUISER', 'TERRAN_COMMANDCENTERFLYING', 'TERRAN_CYCLONE', 'TERRAN_FACTORYFLYING', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MEDIVAC', 'TERRAN_MULE', 'TERRAN_ORBITALCOMMANDFLYING', 'TERRAN_RAVEN', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_STARPORTFLYING', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'TERRAN_WIDOWMINE', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_BROODLORDCOCOON', 'ZERG_CHANGELING', 'ZERG_CHANGELINGMARINE', 'ZERG_CHANGELINGMARINESHIELD', 'ZERG_CHANGELINGZEALOT', 'ZERG_CHANGELINGZERGLING', 'ZERG_CHANGELINGZERGLINGWINGS', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTEDTERRANSEGG', 'ZERG_INFESTOR', 'ZERG_INFESTORBURROWED', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMP', 'ZERG_MUTALISK', 'ZERG_OVERLORD', 'ZERG_OVERLORDCOCOON', 'ZERG_OVERLORDTRANSPORT', 'ZERG_OVERSEER', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_ROACHBURROWED', 'ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLERUPROOTED', 'ZERG_SWARMHOSTMP', 'ZERG_TRANSPORTOVERLORDCOCOON', 'ZERG_ULTRALISK', 'ZERG_VIPER', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ADEPTPHASESHIFT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PROBE', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [55, 46, 57, 36, 692, 43, 50, 53, 484, 689, 51, 48, 54, 268, 134, 56, 49, 45, 33, 44, 52, 691, 34, 35, 498, 9, 289, 114, 113, 12, 15, 14, 13, 17, 16, 112, 104, 107, 150, 111, 127, 7, 489, 693, 502, 108, 106, 128, 893, 129, 126, 688, 110, 118, 139, 140, 494, 892, 109, 499, 105, 311, 801, 141, 79, 4, 76, 694, 733, 75, 83, 85, 10, 488, 82, 495, 78, 84, 77, 74, 496, 80, 81, 73]}, + 545: {'name': 'Move_Battlecruiser_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3776, 'general_id': 3794, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_BATTLECRUISER'], 'avail_unit_type_id': [57]}, + 546: {'name': 'Move_Battlecruiser_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3776, 'general_id': 3794, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_BATTLECRUISER'], 'avail_unit_type_id': [57]}, + 547: {'name': 'Move_Move_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 16, 'general_id': 3794, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_BANSHEE', 'TERRAN_BARRACKSFLYING', 'TERRAN_COMMANDCENTERFLYING', 'TERRAN_CYCLONE', 'TERRAN_FACTORYFLYING', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MEDIVAC', 'TERRAN_MULE', 'TERRAN_ORBITALCOMMANDFLYING', 'TERRAN_RAVEN', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_STARPORTFLYING', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'TERRAN_WIDOWMINE', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_BROODLORDCOCOON', 'ZERG_CHANGELING', 'ZERG_CHANGELINGMARINE', 'ZERG_CHANGELINGMARINESHIELD', 'ZERG_CHANGELINGZEALOT', 'ZERG_CHANGELINGZERGLING', 'ZERG_CHANGELINGZERGLINGWINGS', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTEDTERRANSEGG', 'ZERG_INFESTOR', 'ZERG_INFESTORBURROWED', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMP', 'ZERG_MUTALISK', 'ZERG_OVERLORD', 'ZERG_OVERLORDCOCOON', 'ZERG_OVERLORDTRANSPORT', 'ZERG_OVERSEER', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_ROACHBURROWED', 'ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLERUPROOTED', 'ZERG_SWARMHOSTMP', 'ZERG_TRANSPORTOVERLORDCOCOON', 'ZERG_ULTRALISK', 'ZERG_VIPER', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ADEPTPHASESHIFT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PROBE', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [55, 46, 36, 692, 43, 50, 53, 484, 689, 51, 48, 54, 268, 134, 56, 49, 45, 33, 44, 52, 691, 34, 35, 498, 9, 289, 114, 113, 12, 15, 14, 13, 17, 16, 112, 104, 107, 150, 111, 127, 7, 489, 693, 502, 108, 106, 128, 893, 129, 126, 688, 110, 118, 139, 140, 494, 892, 109, 499, 105, 311, 801, 141, 79, 4, 76, 694, 733, 75, 83, 85, 10, 488, 82, 495, 78, 84, 77, 74, 496, 80, 81, 73]}, + 548: {'name': 'Move_Move_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 16, 'general_id': 3794, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_BANSHEE', 'TERRAN_BARRACKSFLYING', 'TERRAN_COMMANDCENTERFLYING', 'TERRAN_CYCLONE', 'TERRAN_FACTORYFLYING', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MEDIVAC', 'TERRAN_MULE', 'TERRAN_ORBITALCOMMANDFLYING', 'TERRAN_RAVEN', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_STARPORTFLYING', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'TERRAN_WIDOWMINE', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_BROODLORDCOCOON', 'ZERG_CHANGELING', 'ZERG_CHANGELINGMARINE', 'ZERG_CHANGELINGMARINESHIELD', 'ZERG_CHANGELINGZEALOT', 'ZERG_CHANGELINGZERGLING', 'ZERG_CHANGELINGZERGLINGWINGS', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTEDTERRANSEGG', 'ZERG_INFESTOR', 'ZERG_INFESTORBURROWED', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMP', 'ZERG_MUTALISK', 'ZERG_OVERLORD', 'ZERG_OVERLORDCOCOON', 'ZERG_OVERLORDTRANSPORT', 'ZERG_OVERSEER', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_ROACHBURROWED', 'ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLERUPROOTED', 'ZERG_SWARMHOSTMP', 'ZERG_TRANSPORTOVERLORDCOCOON', 'ZERG_ULTRALISK', 'ZERG_VIPER', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ADEPTPHASESHIFT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PROBE', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [55, 46, 36, 692, 43, 50, 53, 484, 689, 51, 48, 54, 268, 134, 56, 49, 45, 33, 44, 52, 691, 34, 35, 498, 9, 289, 114, 113, 12, 15, 14, 13, 17, 16, 112, 104, 107, 150, 111, 127, 7, 489, 693, 502, 108, 106, 128, 893, 129, 126, 688, 110, 118, 139, 140, 494, 892, 109, 499, 105, 311, 801, 141, 79, 4, 76, 694, 733, 75, 83, 85, 10, 488, 82, 495, 78, 84, 77, 74, 496, 80, 81, 73]}, + 15: {'name': 'Patrol_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3795, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_BANSHEE', 'TERRAN_BARRACKSFLYING', 'TERRAN_BATTLECRUISER', 'TERRAN_COMMANDCENTERFLYING', 'TERRAN_CYCLONE', 'TERRAN_FACTORYFLYING', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MEDIVAC', 'TERRAN_MULE', 'TERRAN_ORBITALCOMMANDFLYING', 'TERRAN_RAVEN', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_STARPORTFLYING', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'TERRAN_WIDOWMINE', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_BROODLORDCOCOON', 'ZERG_CHANGELING', 'ZERG_CHANGELINGMARINE', 'ZERG_CHANGELINGMARINESHIELD', 'ZERG_CHANGELINGZEALOT', 'ZERG_CHANGELINGZERGLING', 'ZERG_CHANGELINGZERGLINGWINGS', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTEDTERRANSEGG', 'ZERG_INFESTOR', 'ZERG_INFESTORBURROWED', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMP', 'ZERG_MUTALISK', 'ZERG_OVERLORD', 'ZERG_OVERLORDCOCOON', 'ZERG_OVERLORDTRANSPORT', 'ZERG_OVERSEER', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_ROACHBURROWED', 'ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLERUPROOTED', 'ZERG_SWARMHOSTMP', 'ZERG_TRANSPORTOVERLORDCOCOON', 'ZERG_ULTRALISK', 'ZERG_VIPER', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ADEPTPHASESHIFT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PROBE', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [55, 46, 57, 36, 692, 43, 50, 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'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reaper', 'RepairDrone', 'SCV', 'SiegeTank', 'SiegeTankSieged', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 12: {'action_name': 'Smart_unit', 'selected_type': [311, 801, 1955, 79, 4, 76, 694, 733, 62, 75, 83, 10, 488, 59, 82, 1911, 495, 78, 66, 84, 894, 71, 77, 1910, 74, 67, 496, 80, 81, 136, 73, 31, 55, 21, 46, 57, 24, 18, 36, 692, 27, 43, 50, 144, 53, 484, 689, 734, 268, 51, 48, 54, 23, 132, 134, 130, 11, 56, 49, 1913, 45, 33, 32, 28, 44, 52, 691, 34, 35, 498, 500, 9, 115, 8, 114, 113, 289, 12, 15, 14, 13, 17, 16, 103, 112, 104, 116, 86, 101, 107, 117, 94, 7, 120, 150, 111, 127, 100, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 98, 139, 99, 140, 494, 493, 109, 131, 499, 105, 119], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 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1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Adept', 'AdeptPhaseShift', 'AssimilatorRich', 'Carrier', 'Colossus', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'Gateway', 'HighTemplar', 'Immortal', 'Mothership', 'MothershipCore', 'Nexus', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'PylonOvercharged', 'RoboticsFacility', 'Sentry', 'ShieldBattery', 'Stalker', 'Stargate', 'Tempest', 'VoidRay', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'Factory', 'FactoryFlying', 'Ghost', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reaper', 'RepairDrone', 'SCV', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 13: {'action_name': 'Move_pt', 'selected_type': [311, 801, 1955, 79, 4, 76, 694, 733, 75, 83, 10, 488, 82, 1911, 495, 78, 84, 894, 77, 1910, 74, 496, 80, 81, 136, 73, 31, 55, 46, 57, 36, 692, 43, 50, 144, 53, 484, 689, 734, 268, 51, 48, 54, 23, 134, 11, 56, 49, 1913, 45, 33, 32, 44, 52, 691, 34, 35, 498, 500, 9, 115, 8, 114, 113, 289, 12, 15, 14, 13, 17, 16, 103, 112, 104, 116, 107, 117, 94, 7, 120, 150, 111, 127, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 98, 139, 99, 140, 494, 493, 109, 131, 499, 105, 119], 'target_type': [], 'selected_type_name': ['Adept', 'AdeptPhaseShift', 'AssimilatorRich', 'Carrier', 'Colossus', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'HighTemplar', 'Immortal', 'Mothership', 'MothershipCore', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'Probe', 'PylonOvercharged', 'Sentry', 'ShieldBattery', 'Stalker', 'Tempest', 'VoidRay', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'AutoTurret', 'Banshee', 'BarracksFlying', 'Battlecruiser', 'CommandCenterFlying', 'Cyclone', 'FactoryFlying', 'Ghost', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'OrbitalCommandFlying', 'PointDefenseDrone', 'Raven', 'Reaper', 'RepairDrone', 'SCV', 'SiegeTank', 'SiegeTankSieged', 'StarportFlying', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': []}, + 14: {'action_name': 'Move_unit', 'selected_type': [311, 801, 1955, 79, 4, 76, 694, 733, 75, 83, 10, 488, 82, 1911, 495, 78, 84, 894, 77, 1910, 74, 496, 80, 81, 136, 73, 31, 55, 46, 57, 36, 692, 43, 50, 144, 53, 484, 689, 734, 268, 51, 48, 54, 23, 134, 11, 56, 49, 1913, 45, 33, 32, 44, 52, 691, 34, 35, 498, 500, 9, 115, 8, 114, 113, 289, 12, 15, 14, 13, 17, 16, 103, 112, 104, 116, 107, 117, 94, 7, 120, 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496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Adept', 'AdeptPhaseShift', 'AssimilatorRich', 'Carrier', 'Colossus', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'HighTemplar', 'Immortal', 'Mothership', 'MothershipCore', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'Probe', 'PylonOvercharged', 'Sentry', 'ShieldBattery', 'Stalker', 'Tempest', 'VoidRay', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'AutoTurret', 'Banshee', 'BarracksFlying', 'Battlecruiser', 'CommandCenterFlying', 'Cyclone', 'FactoryFlying', 'Ghost', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'OrbitalCommandFlying', 'PointDefenseDrone', 'Raven', 'Reaper', 'RepairDrone', 'SCV', 'SiegeTank', 'SiegeTankSieged', 'StarportFlying', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 15: {'action_name': 'Patrol_pt', 'selected_type': [311, 801, 1955, 79, 4, 76, 694, 733, 75, 83, 10, 488, 82, 1911, 495, 78, 84, 894, 77, 1910, 74, 496, 80, 81, 136, 73, 31, 55, 46, 57, 36, 692, 43, 50, 144, 53, 484, 689, 734, 268, 51, 48, 54, 23, 134, 11, 56, 49, 1913, 45, 33, 32, 44, 52, 691, 34, 35, 498, 500, 9, 115, 8, 114, 113, 289, 12, 15, 14, 13, 17, 16, 103, 112, 104, 116, 107, 117, 94, 7, 120, 150, 111, 127, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 98, 139, 99, 140, 494, 493, 109, 131, 499, 105, 119], 'target_type': [], 'selected_type_name': ['Adept', 'AdeptPhaseShift', 'AssimilatorRich', 'Carrier', 'Colossus', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'HighTemplar', 'Immortal', 'Mothership', 'MothershipCore', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'Probe', 'PylonOvercharged', 'Sentry', 'ShieldBattery', 'Stalker', 'Tempest', 'VoidRay', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'AutoTurret', 'Banshee', 'BarracksFlying', 'Battlecruiser', 'CommandCenterFlying', 'Cyclone', 'FactoryFlying', 'Ghost', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'OrbitalCommandFlying', 'PointDefenseDrone', 'Raven', 'Reaper', 'RepairDrone', 'SCV', 'SiegeTank', 'SiegeTankSieged', 'StarportFlying', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': []}, + 16: {'action_name': 'Patrol_unit', 'selected_type': [311, 801, 1955, 79, 4, 76, 694, 733, 75, 83, 10, 488, 82, 1911, 495, 78, 84, 894, 77, 1910, 74, 496, 80, 81, 136, 73, 31, 55, 46, 57, 36, 692, 43, 50, 144, 53, 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'AutoTurret', 'Banshee', 'BarracksFlying', 'Battlecruiser', 'CommandCenterFlying', 'Cyclone', 'FactoryFlying', 'Ghost', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'OrbitalCommandFlying', 'PointDefenseDrone', 'Raven', 'Reaper', 'RepairDrone', 'SCV', 'SiegeTank', 'SiegeTankSieged', 'StarportFlying', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 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'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Larva', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpawningPool', 'SpineCrawler', 'SpineCrawlerUprooted', 'Spire', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'UltraliskCavern', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 109: {'action_name': 'Effect_Repair_unit', 'selected_type': [268, 45], 'target_type': [29, 31, 55, 21, 46, 38, 37, 57, 24, 18, 36, 692, 22, 27, 43, 40, 39, 30, 26, 144, 53, 484, 689, 734, 268, 54, 23, 132, 134, 130, 11, 56, 6, 49, 20, 1960, 1913, 45, 25, 33, 32, 28, 44, 42, 41, 19, 47, 5, 52, 691, 34, 35, 498, 500], 'selected_type_name': ['MULE', 'SCV'], 'target_type_name': ['Armory', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'BarracksReactor', 'BarracksTechLab', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'EngineeringBay', 'Factory', 'FactoryFlying', 'FactoryReactor', 'FactoryTechLab', 'FusionCore', 'GhostAcademy', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Medivac', 'MissileTurret', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reactor', 'Reaper', 'Refinery', 'RefineryRich', 'RepairDrone', 'SCV', 'SensorTower', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'StarportReactor', 'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed']}, + 110: {'action_name': 'Effect_MassRecall_pt', 'selected_type': [10, 59], 'target_type': [], 'selected_type_name': ['Mothership', 'Nexus'], 'target_type_name': []}, + 111: {'action_name': 'Effect_Blink_pt', 'selected_type': [74, 76], 'target_type': [], 'selected_type_name': ['Stalker', 'DarkTemplar'], 'target_type_name': []}, + 114: {'action_name': 'Rally_Workers_pt', 'selected_type': [59, 18, 132, 130, 86, 100, 101], 'target_type': [], 'selected_type_name': ['Nexus', 'CommandCenter', 'OrbitalCommand', 'PlanetaryFortress', 'Hatchery', 'Lair', 'Hive'], 'target_type_name': []}, + 115: {'action_name': 'Rally_Workers_unit', 'selected_type': [59, 18, 132, 130, 86, 100, 101], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 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'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 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'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 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'target_type': [], 'selected_type_name': ['OrbitalCommand'], 'target_type_name': []}, + 298: {'action_name': 'Effect_CalldownMULE_unit', 'selected_type': [132], 'target_type': [665, 666, 483, 341, 146, 147, 884, 885, 796, 797, 1961], 'selected_type_name': ['OrbitalCommand'], 'target_type_name': ['LabMineralField', 'LabMineralField750', 'MineralField750', 'MineralField', 'RichMineralField', 'RichMineralField750', 'PurifierMineralField', 'PurifierMineralField750', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'MineralField450']}, + 299: {'action_name': 'Effect_CausticSpray_unit', 'selected_type': [112], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 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'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 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'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 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'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 303: {'action_name': 'Effect_Contaminate_unit', 'selected_type': [1912, 129], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['OverseerOversightMode', 'Overseer'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 304: {'action_name': 'Effect_CorrosiveBile_pt', 'selected_type': [688], 'target_type': [], 'selected_type_name': ['Ravager'], 'target_type_name': []}, + 305: {'action_name': 'Effect_EMP_pt', 'selected_type': [144, 50], 'target_type': [], 'selected_type_name': ['GhostAlternate', 'Ghost'], 'target_type_name': []}, + 307: {'action_name': 'Effect_Explode_quick', 'selected_type': [9, 115], 'target_type': [], 'selected_type_name': ['Baneling', 'BanelingBurrowed'], 'target_type_name': []}, + 308: {'action_name': 'Effect_FungalGrowth_pt', 'selected_type': [111], 'target_type': [], 'selected_type_name': ['Infestor'], 'target_type_name': []}, + 310: {'action_name': 'Effect_GhostSnipe_unit', 'selected_type': [144, 145, 50], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['GhostAlternate', 'GhostNova', 'Ghost'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 311: {'action_name': 'Effect_Heal_unit', 'selected_type': [54], 'target_type': [48, 51, 49], 'selected_type_name': ['Medivac'], 'target_type_name': ['Marine', 'Marauder', 'Reaper']}, + 314: {'action_name': 'Effect_InfestedTerrans_pt', 'selected_type': [111, 127], 'target_type': [], 'selected_type_name': ['Infestor', 'InfestorBurrowed'], 'target_type_name': []}, + 315: {'action_name': 'Effect_InjectLarva_unit', 'selected_type': [126], 'target_type': [100, 101, 86], 'selected_type_name': ['Queen'], 'target_type_name': ['Lair', 'Hive', 'Hatchery']}, + 316: {'action_name': 'Effect_InterferenceMatrix_unit', 'selected_type': [56], 'target_type': [311, 801, 141, 61, 1955, 79, 4, 72, 69, 76, 694, 733, 64, 135, 63, 62, 75, 83, 85, 10, 488, 59, 82, 1911, 495, 78, 66, 84, 60, 894, 70, 71, 77, 1910, 74, 67, 732, 496, 68, 65, 80, 133, 81, 136, 73, 29, 31, 55, 21, 46, 38, 37, 57, 24, 18, 36, 692, 22, 27, 43, 40, 39, 30, 50, 26, 144, 145, 53, 484, 830, 689, 734, 268, 51, 48, 54, 23, 58, 132, 134, 130, 11, 56, 6, 49, 20, 1960, 1913, 45, 25, 33, 32, 28, 44, 42, 41, 19, 47, 5, 52, 691, 34, 35, 498, 500, 9, 115, 8, 96, 114, 113, 289, 143, 12, 15, 14, 13, 17, 16, 103, 112, 87, 137, 138, 104, 116, 90, 88, 1956, 102, 86, 101, 107, 117, 91, 94, 7, 120, 150, 111, 127, 100, 151, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 89, 98, 139, 92, 99, 140, 494, 493, 109, 131, 93, 499, 105, 119], 'selected_type_name': ['Raven'], 'target_type_name': ['Adept', 'AdeptPhaseShift', 'Archon', 'Assimilator', 'AssimilatorRich', 'Carrier', 'Colossus', 'CyberneticsCore', 'DarkShrine', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'FleetBeacon', 'ForceField', 'Forge', 'Gateway', 'HighTemplar', 'Immortal', 'Interceptor', 'Mothership', 'MothershipCore', 'Nexus', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'Pylon', 'PylonOvercharged', 'RoboticsBay', 'RoboticsFacility', 'Sentry', 'ShieldBattery', 'Stalker', 'Stargate', 'StasisTrap', 'Tempest', 'TemplarArchive', 'TwilightCouncil', 'VoidRay', 'WarpGate', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'Armory', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'BarracksReactor', 'BarracksTechLab', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'EngineeringBay', 'Factory', 'FactoryFlying', 'FactoryReactor', 'FactoryTechLab', 'FusionCore', 'Ghost', 'GhostAcademy', 'GhostAlternate', 'GhostNova', 'Hellion', 'Hellbat', 'KD8Charge', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'Nuke', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reactor', 'Reaper', 'Refinery', 'RefineryRich', 'RepairDrone', 'SCV', 'SensorTower', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'StarportReactor', 'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BanelingNest', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'BroodlingEscort', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'CreepTumor', 'CreepTumorBurrowed', 'CreepTumorQueen', 'Drone', 'DroneBurrowed', 'EvolutionChamber', 'Extractor', 'ExtractorRich', 'GreaterSpire', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'HydraliskDen', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Larva', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpawningPool', 'SpineCrawler', 'SpineCrawlerUprooted', 'Spire', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'UltraliskCavern', 'Viper', 'Zergling', 'ZerglingBurrowed']}, + 317: {'action_name': 'Effect_KD8Charge_pt', 'selected_type': [49], 'target_type': [], 'selected_type_name': ['Reaper'], 'target_type_name': []}, + 318: {'action_name': 'Effect_LockOn_unit', 'selected_type': [692], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Cyclone'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 319: {'action_name': 'Effect_LocustSwoop_pt', 'selected_type': [693], 'target_type': [], 'selected_type_name': ['LocustFlying'], 'target_type_name': []}, + 320: {'action_name': 'Effect_MedivacIgniteAfterburners_quick', 'selected_type': [54], 'target_type': [], 'selected_type_name': ['Medivac'], 'target_type_name': []}, + 321: {'action_name': 'Effect_NeuralParasite_unit', 'selected_type': [111, 127], 'target_type': [311, 801, 141, 61, 1955, 79, 4, 72, 69, 76, 694, 733, 64, 135, 63, 62, 75, 83, 85, 10, 488, 59, 82, 1911, 495, 78, 66, 84, 60, 894, 70, 71, 77, 1910, 74, 67, 732, 496, 68, 65, 80, 133, 81, 136, 73, 29, 31, 55, 21, 46, 38, 37, 57, 24, 18, 36, 692, 22, 27, 43, 40, 39, 30, 50, 26, 144, 145, 53, 484, 830, 689, 734, 268, 51, 48, 54, 23, 58, 132, 134, 130, 11, 56, 6, 49, 20, 1960, 1913, 45, 25, 33, 32, 28, 44, 42, 41, 19, 47, 5, 52, 691, 34, 35, 498, 500, 9, 115, 8, 96, 114, 113, 289, 143, 12, 15, 14, 13, 17, 16, 103, 112, 87, 137, 138, 104, 116, 90, 88, 1956, 102, 86, 101, 107, 117, 91, 94, 7, 120, 150, 111, 127, 100, 151, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 89, 98, 139, 92, 99, 140, 494, 493, 109, 131, 93, 499, 105, 119], 'selected_type_name': ['Infestor', 'InfestorBurrowed'], 'target_type_name': ['Adept', 'AdeptPhaseShift', 'Archon', 'Assimilator', 'AssimilatorRich', 'Carrier', 'Colossus', 'CyberneticsCore', 'DarkShrine', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'FleetBeacon', 'ForceField', 'Forge', 'Gateway', 'HighTemplar', 'Immortal', 'Interceptor', 'Mothership', 'MothershipCore', 'Nexus', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'Pylon', 'PylonOvercharged', 'RoboticsBay', 'RoboticsFacility', 'Sentry', 'ShieldBattery', 'Stalker', 'Stargate', 'StasisTrap', 'Tempest', 'TemplarArchive', 'TwilightCouncil', 'VoidRay', 'WarpGate', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'Armory', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'BarracksReactor', 'BarracksTechLab', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'EngineeringBay', 'Factory', 'FactoryFlying', 'FactoryReactor', 'FactoryTechLab', 'FusionCore', 'Ghost', 'GhostAcademy', 'GhostAlternate', 'GhostNova', 'Hellion', 'Hellbat', 'KD8Charge', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'Nuke', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reactor', 'Reaper', 'Refinery', 'RefineryRich', 'RepairDrone', 'SCV', 'SensorTower', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'StarportReactor', 'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BanelingNest', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'BroodlingEscort', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'CreepTumor', 'CreepTumorBurrowed', 'CreepTumorQueen', 'Drone', 'DroneBurrowed', 'EvolutionChamber', 'Extractor', 'ExtractorRich', 'GreaterSpire', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'HydraliskDen', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Larva', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpawningPool', 'SpineCrawler', 'SpineCrawlerUprooted', 'Spire', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'UltraliskCavern', 'Viper', 'Zergling', 'ZerglingBurrowed']}, + 322: {'action_name': 'Effect_NukeCalldown_pt', 'selected_type': [144, 145, 50], 'target_type': [], 'selected_type_name': ['GhostAlternate', 'GhostNova', 'Ghost'], 'target_type_name': []}, + 323: {'action_name': 'Effect_ParasiticBomb_unit', 'selected_type': [499], 'target_type': [311, 801, 141, 61, 1955, 79, 4, 72, 69, 76, 694, 733, 64, 135, 63, 62, 75, 83, 85, 10, 488, 59, 82, 1911, 495, 78, 66, 84, 60, 894, 70, 71, 77, 1910, 74, 67, 732, 496, 68, 65, 80, 133, 81, 136, 73, 29, 31, 55, 21, 46, 38, 37, 57, 24, 18, 36, 692, 22, 27, 43, 40, 39, 30, 50, 26, 144, 145, 53, 484, 830, 689, 734, 268, 51, 48, 54, 23, 58, 132, 134, 130, 11, 56, 6, 49, 20, 1960, 1913, 45, 25, 33, 32, 28, 44, 42, 41, 19, 47, 5, 52, 691, 34, 35, 498, 500, 9, 115, 8, 96, 114, 113, 289, 143, 12, 15, 14, 13, 17, 16, 103, 112, 87, 137, 138, 104, 116, 90, 88, 1956, 102, 86, 101, 107, 117, 91, 94, 7, 120, 150, 111, 127, 100, 151, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 89, 98, 139, 92, 99, 140, 494, 493, 109, 131, 93, 499, 105, 119], 'selected_type_name': ['Viper'], 'target_type_name': ['Adept', 'AdeptPhaseShift', 'Archon', 'Assimilator', 'AssimilatorRich', 'Carrier', 'Colossus', 'CyberneticsCore', 'DarkShrine', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'FleetBeacon', 'ForceField', 'Forge', 'Gateway', 'HighTemplar', 'Immortal', 'Interceptor', 'Mothership', 'MothershipCore', 'Nexus', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'Pylon', 'PylonOvercharged', 'RoboticsBay', 'RoboticsFacility', 'Sentry', 'ShieldBattery', 'Stalker', 'Stargate', 'StasisTrap', 'Tempest', 'TemplarArchive', 'TwilightCouncil', 'VoidRay', 'WarpGate', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'Armory', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'BarracksReactor', 'BarracksTechLab', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'EngineeringBay', 'Factory', 'FactoryFlying', 'FactoryReactor', 'FactoryTechLab', 'FusionCore', 'Ghost', 'GhostAcademy', 'GhostAlternate', 'GhostNova', 'Hellion', 'Hellbat', 'KD8Charge', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'Nuke', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reactor', 'Reaper', 'Refinery', 'RefineryRich', 'RepairDrone', 'SCV', 'SensorTower', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'StarportReactor', 'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BanelingNest', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'BroodlingEscort', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'CreepTumor', 'CreepTumorBurrowed', 'CreepTumorQueen', 'Drone', 'DroneBurrowed', 'EvolutionChamber', 'Extractor', 'ExtractorRich', 'GreaterSpire', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'HydraliskDen', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Larva', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpawningPool', 'SpineCrawler', 'SpineCrawlerUprooted', 'Spire', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'UltraliskCavern', 'Viper', 'Zergling', 'ZerglingBurrowed']}, + 332: {'action_name': 'Effect_Salvage_quick', 'selected_type': [24], 'target_type': [], 'selected_type_name': ['Bunker'], 'target_type_name': []}, + 333: {'action_name': 'Effect_Scan_pt', 'selected_type': [132], 'target_type': [], 'selected_type_name': ['OrbitalCommand'], 'target_type_name': []}, + 334: {'action_name': 'Effect_SpawnChangeling_quick', 'selected_type': [1912, 129], 'target_type': [], 'selected_type_name': ['OverseerOversightMode', 'Overseer'], 'target_type_name': []}, + 335: {'action_name': 'Effect_SpawnLocusts_pt', 'selected_type': [493, 494], 'target_type': [], 'selected_type_name': ['SwarmHostBurrowed', 'SwarmHost'], 'target_type_name': []}, + 337: {'action_name': 'Effect_Spray_pt', 'selected_type': [104, 84, 45], 'target_type': [], 'selected_type_name': ['Drone', 'Probe', 'SCV'], 'target_type_name': []}, + 341: {'action_name': 'Effect_Stim_quick', 'selected_type': [48, 24, 51], 'target_type': [], 'selected_type_name': ['Marine', 'Bunker', 'Marauder'], 'target_type_name': []}, + 346: {'action_name': 'Effect_SupplyDrop_unit', 'selected_type': [132], 'target_type': [19, 47], 'selected_type_name': ['OrbitalCommand'], 'target_type_name': ['SupplyDepot', 'SupplyDepotLowered']}, + 347: {'action_name': 'Effect_TacticalJump_pt', 'selected_type': [57], 'target_type': [], 'selected_type_name': ['Battlecruiser'], 'target_type_name': []}, + 348: {'action_name': 'Effect_TimeWarp_pt', 'selected_type': [10], 'target_type': [], 'selected_type_name': ['Mothership'], 'target_type_name': []}, + 349: {'action_name': 'Effect_Transfusion_unit', 'selected_type': [126], 'target_type': [9, 115, 8, 96, 114, 113, 289, 143, 12, 15, 14, 13, 17, 16, 103, 112, 87, 137, 138, 104, 116, 90, 88, 1956, 102, 86, 101, 107, 117, 91, 94, 7, 120, 150, 111, 127, 100, 151, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 89, 98, 139, 92, 99, 140, 494, 493, 109, 131, 93, 499, 105, 119], 'selected_type_name': ['Queen'], 'target_type_name': ['Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BanelingNest', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'BroodlingEscort', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'CreepTumor', 'CreepTumorBurrowed', 'CreepTumorQueen', 'Drone', 'DroneBurrowed', 'EvolutionChamber', 'Extractor', 'ExtractorRich', 'GreaterSpire', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'HydraliskDen', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Larva', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpawningPool', 'SpineCrawler', 'SpineCrawlerUprooted', 'Spire', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'UltraliskCavern', 'Viper', 'Zergling', 'ZerglingBurrowed']}, + 350: {'action_name': 'Effect_ViperConsume_unit', 'selected_type': [499], 'target_type': [96, 97, 98, 99, 100, 101, 1956, 504, 142, 86, 88, 89, 90, 91, 92, 94, 95, 102, 139, 93, 140], 'selected_type_name': ['Viper'], 'target_type_name': ['BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'ExtractorRich', 'LurkerDen', 'NydusCanal', 'Hatchery', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'InfestationPit', 'NydusNetwork', 'GreaterSpire', 'SpineCrawlerUprooted', 'UltraliskCavern', 'SporeCrawlerUprooted']}, + 363: {'action_name': 'Land_pt', 'selected_type': [36, 134, 43, 44, 46], 'target_type': [], 'selected_type_name': ['CommandCenterFlying', 'OrbitalCommandFlying', 'FactoryFlying', 'StarportFlying', 'BarracksFlying'], 'target_type_name': []}, + 369: {'action_name': 'Lift_quick', 'selected_type': [132, 18, 21, 27, 28], 'target_type': [], 'selected_type_name': ['OrbitalCommand', 'CommandCenter', 'Barracks', 'Factory', 'Starport'], 'target_type_name': []}, + 375: {'action_name': 'LoadAll_quick', 'selected_type': [81, 136, 24, 18, 54, 142, 95, 893, 36, 130], 'target_type': [], 'selected_type_name': ['WarpPrism', 'WarpPrismPhasing', 'Bunker', 'CommandCenter', 'Medivac', 'NydusCanal', 'NydusNetwork', 'OverlordTransport', 'CommandCenterFlying', 'PlanetaryFortress'], 'target_type_name': []}, + 383: {'action_name': 'Morph_BroodLord_quick', 'selected_type': [112], 'target_type': [], 'selected_type_name': 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131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Reaper'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 553: {'action_name': 'Research_AnabolicSynthesis_quick', 'selected_type': [93], 'target_type': [], 'selected_type_name': ['UltraliskCavern'], 'target_type_name': []}, + 554: {'action_name': 'Research_CycloneLockOnDamage_quick', 'selected_type': [39], 'target_type': [], 'selected_type_name': ['FactoryTechLab'], 'target_type_name': []}, + 556: {'action_name': 'UnloadUnit_quick', 'selected_type': [81, 136, 24, 18, 54, 142, 95, 893, 36, 130], 'target_type': [], 'selected_type_name': ['WarpPrism', 'WarpPrismPhasing', 'Bunker', 'CommandCenter', 'Medivac', 'NydusCanal', 'NydusNetwork', 'OverlordTransport', 'CommandCenterFlying', 'PlanetaryFortress'], 'target_type_name': []}, + 24: {'action_name': 'Hallucination_HighTemplar_quick', 'selected_type': [77], 'target_type': [], 'selected_type_name': ['Sentry'], 'target_type_name': []}, + 93: {'action_name': 'Hallucination_Adept_quick', 'selected_type': [77], 'target_type': [], 'selected_type_name': ['Sentry'], 'target_type_name': []}, + 200: {'action_name': 'Build_Interceptors_autocast', 'selected_type': [79], 'target_type': [], 'selected_type_name': ['Carrier'], 'target_type_name': []}, + 247: {'action_name': 'BurrowUp_autocast', 'selected_type': [115, 117, 119], 'target_type': [], 'selected_type_name': ['BanelingBurrowed', 'HydraliskBurrowed', 'ZerglingBurrowed'], 'target_type_name': []}, + 302: {'action_name': 'Effect_Charge_autocast', 'selected_type': [73], 'target_type': [], 'selected_type_name': ['Zealot'], 'target_type_name': []}, + 312: {'action_name': 'Effect_Heal_autocast', 'selected_type': [54], 'target_type': [], 'selected_type_name': ['Medivac'], 'target_type_name': []}, + 324: {'action_name': 'Effect_Repair_autocast', 'selected_type': [268, 45], 'target_type': [], 'selected_type_name': ['MULE', 'SCV'], 'target_type_name': []}, + 331: {'action_name': 'Effect_Restore_autocast', 'selected_type': [1910], 'target_type': [], 'selected_type_name': ['ShieldBattery'], 'target_type_name': []}, + 541: {'action_name': 'Effect_LockOn_autocast', 'selected_type': [692], 'target_type': [], 'selected_type_name': ['Cyclone'], 'target_type_name': []}, + 544: {'action_name': 'Morph_WarpGate_autocast', 'selected_type': [62], 'target_type': [], 'selected_type_name': ['Gateway'], 'target_type_name': []}, + 112: {'action_name': 'Effect_Blink_unit', 'selected_type': [74, 76], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Stalker', 'DarkTemplar'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 300: {'action_name': 'Effect_Charge_pt', 'selected_type': [73], 'target_type': [], 'selected_type_name': ['Zealot'], 'target_type_name': []}, + 33: {'action_name': 'Effect_ChronoBoost_unit', 'selected_type': [59], 'target_type': [64, 65, 67, 68, 69, 70, 71, 72, 133, 59, 62, 63], 'selected_type_name': ['Nexus'], 'target_type_name': ['FleetBeacon', 'TwilightCouncil', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'WarpGate', 'Nexus', 'Gateway', 'Forge']}, + 306: {'action_name': 'Effect_EMP_unit', 'selected_type': [144, 145, 50], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['GhostAlternate', 'GhostNova', 'Ghost'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 309: {'action_name': 'Effect_FungalGrowth_unit', 'selected_type': [111], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Infestor'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 313: {'action_name': 'Effect_ImmortalBarrier_autocast', 'selected_type': [83], 'target_type': [], 'selected_type_name': ['Immortal'], 'target_type_name': []}, + 91: {'action_name': 'Effect_ImmortalBarrier_quick', 'selected_type': [83], 'target_type': [], 'selected_type_name': ['Immortal'], 'target_type_name': []}, + 108: {'action_name': 'Effect_Repair_pt', 'selected_type': [268, 45], 'target_type': [], 'selected_type_name': ['MULE', 'SCV'], 'target_type_name': []}, + 336: {'action_name': 'Effect_SpawnLocusts_unit', 'selected_type': [493, 494], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 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693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['SwarmHostBurrowed', 'SwarmHost'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 353: {'action_name': 'Effect_WidowMineAttack_autocast', 'selected_type': [498, 500], 'target_type': [], 'selected_type_name': ['WidowMine', 'WidowMineBurrowed'], 'target_type_name': []}, + 351: {'action_name': 'Effect_WidowMineAttack_pt', 'selected_type': [498, 500], 'target_type': [], 'selected_type_name': ['WidowMine', 'WidowMineBurrowed'], 'target_type_name': []}, + 352: {'action_name': 'Effect_WidowMineAttack_unit', 'selected_type': [498, 500], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 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'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, + 392: {'action_name': 'Morph_LurkerDen_quick', 'selected_type': [91], 'target_type': [], 'selected_type_name': ['HydraliskDen'], 'target_type_name': []}, + 393: {'action_name': 'Morph_Mothership_quick', 'selected_type': [488], 'target_type': [], 'selected_type_name': ['MothershipCore'], 'target_type_name': []}, + 435: {'action_name': 'Research_CycloneRapidFireLaunchers_quick', 'selected_type': [39], 'target_type': [], 'selected_type_name': ['FactoryTechLab'], 'target_type_name': []}, + 563: {'action_name': 'Research_EnhancedShockwaves_quick', 'selected_type': [26], 'target_type': [], 'selected_type_name': ['GhostAcademy'], 'target_type_name': []}, + 18: {'action_name': 'Research_InterceptorGravitonCatapult_quick', 'selected_type': [64], 'target_type': [], 'selected_type_name': ['FleetBeacon'], 'target_type_name': []}, + 443: {'action_name': 'Research_NeosteelFrame_quick', 'selected_type': [22], 'target_type': [], 'selected_type_name': ['EngineeringBay'], 'target_type_name': []}, + 449: {'action_name': 'Research_RavenRecalibratedExplosives_quick', 'selected_type': [41], 'target_type': [], 'selected_type_name': ['StarportTechLab'], 'target_type_name': []}, + 513: {'action_name': 'Train_MothershipCore_quick', 'selected_type': [59], 'target_type': [], 'selected_type_name': ['Nexus'], 'target_type_name': []}, +} + +def get_general(general_id): + return {k: v for k, v in ACTION_INFO_MASK.items() if v['ability_id'] == general_id} + + +def merge_judge(target_general_action, val): + ret = [] + for k, v in target_general_action.items(): + if v['target_unit'] != val['target_unit']: + continue + if v['target_location'] != val['target_location']: + continue + if v['func_type'] != val['func_type']: + continue + ret.append(k) + try: + assert(len(ret) == 1) + except AssertionError: + print(target_general_action) + print(val) + print(ret) + return ret[0] + + +GENERAL_ACTION_INFO_MASK = {} +ACT_TO_GENERAL_ACT = {} +ACT_TO_GENERAL_ACT_ARRAY = np.full(max(ACTION_INFO_MASK.keys()) + 1, -1, dtype=np.int) +for k, v in ACTION_INFO_MASK.items(): + general_id = v['general_id'] + if general_id is None or general_id == 0: + GENERAL_ACTION_INFO_MASK[k] = v + ACT_TO_GENERAL_ACT[k] = k + ACT_TO_GENERAL_ACT_ARRAY[k] = k + else: + target_general_action = get_general(general_id) + action_id = merge_judge(target_general_action, v) + ACT_TO_GENERAL_ACT[k] = action_id + ACT_TO_GENERAL_ACT_ARRAY[k] = action_id + + +ACTION_RACE_MASK = { +'zerg': torch.tensor([False, False, True, True, True, True, False, False, True, True, + True, True, False, False, False, False, True, False, False, False, + True, False, False, False, True, True, False, False, False, False, + False, False, True, True, True, False, False, True, False, False, + False, True, True, False, False, False, False, False, True, False, + False, False, False, True, True, True, True, False, False, False, + False, False, False, False, False, True, True, True, True, True, + True, True, False, False, False, True, False, False, False, False, + True, False, False, False, False, False, True, True, False, False, + True, False, False, True, True, False, False, False, False, False, + False, False, True, True, False, False, False, False, False, True, + False, False, True, False, False, True, False, False, False, False, + False, False, False, False, False, True, True, True, True, False, + False, False, False, True, True, False, False, False, False, False, + False, False, False, False, False, False, False, False, False, False, + False, False, False, False, True, True, True, False, False, False, + True, False, True, False, True, False, False, True, True, False, + False, True, True, False, False, False, True, True, True, True, + False, True, True, False, False, False, False, False, False, False, + True, False, False, False, False, False, False, True, True, True, + True, True, True, True, True, True, False, False, True, False, + False, False, False, True, True, False, True, False, False, False, + False, False, False, False, True, False, False, True, False, False, + False, False, True, False, True, True, False, False, True, False, + False, False, False, False, False, False, False, False, False, False, + False, False, False, False, False, False, True, False, True, True, + True, True, True, True, True, True, True, True, False, True, + False, False, False, False, True, False, False, False, True, False, + False, False, False, True, False, True, False, False, False, False, + False, False, True, False, False, True, False, False, True, False, + False, True, False, False, False, False, True, False, False, True, + False, True, False, False, False, False, False, False, False, False, + False, False, True, True, True, True, True]), +'terran': torch.tensor([False, False, True, True, False, False, True, True, False, False, + True, True, False, False, True, False, False, True, True, True, + False, False, False, True, False, False, True, False, False, True, + False, True, False, False, False, False, False, False, True, False, + True, False, False, False, False, True, True, True, False, False, + False, True, False, False, False, False, False, False, True, False, + True, True, True, False, False, False, True, True, True, True, + True, False, False, True, True, False, False, False, True, True, + False, False, False, False, False, False, False, False, True, True, + False, False, False, False, False, True, False, False, True, True, + False, False, False, False, True, True, True, True, True, False, + False, True, False, True, False, False, False, False, True, True, + True, False, False, True, True, False, False, False, True, True, + True, True, False, False, False, False, True, True, True, True, + False, False, False, False, False, False, False, False, False, False, + False, False, False, True, True, True, True, True, True, True, + True, False, False, False, False, True, True, False, False, True, + True, False, False, False, False, True, False, False, False, False, + True, False, False, True, True, True, False, True, True, True, + False, True, True, False, False, False, False, True, True, True, + True, True, True, True, True, False, False, True, False, True, + True, True, False, False, False, False, False, True, True, True, + True, True, True, False, False, False, False, False, True, True, + True, False, False, True, False, False, True, False, False, False, + False, False, False, False, False, True, True, False, True, True, + True, True, True, True, True, True, False, False, False, False, + False, False, False, False, False, True, True, True, False, False, + True, True, False, False, False, True, False, False, False, True, + True, True, False, False, False, False, True, True, True, True, + False, False, False, False, False, False, False, False, False, True, + True, False, True, False, True, False, False, False, True, False, + True, False, False, False, False, False, False, False, False, False, + True, False, False, True, True, True, True]), +'protoss': torch.tensor([False, False, True, True, False, False, False, False, False, False, + False, False, True, True, False, True, False, False, False, False, + False, True, True, False, False, False, False, True, True, False, + True, False, False, False, False, True, True, False, False, True, + False, False, False, True, True, False, False, False, False, True, + True, False, True, False, False, False, False, True, False, True, + False, False, False, True, True, False, False, False, False, True, + True, False, True, False, False, False, True, True, False, False, + False, True, True, True, True, True, False, False, False, False, + False, True, True, False, False, False, True, True, False, False, + True, True, False, False, False, False, False, False, False, False, + True, False, False, False, True, False, True, True, False, False, + False, True, True, False, False, False, False, False, True, False, + False, False, True, False, False, True, False, False, False, False, + True, True, True, True, True, True, True, True, True, True, + True, True, True, False, True, True, True, False, False, False, + True, True, False, True, False, False, False, False, False, False, + False, False, False, True, True, False, False, False, False, False, + False, False, False, False, False, False, True, False, False, False, + False, False, False, True, True, True, True, True, True, True, + True, True, True, True, True, False, True, False, False, False, + False, False, True, False, False, True, False, False, False, False, + False, False, False, True, False, True, True, False, False, False, + False, True, False, False, False, False, False, True, False, True, + True, True, True, True, True, False, False, True, False, False, + False, False, False, False, False, False, False, True, False, False, + False, False, False, False, False, True, True, True, True, False, + False, False, True, True, False, False, True, True, False, False, + False, False, True, False, True, False, False, False, False, False, + True, True, False, True, True, False, True, True, False, False, + False, False, False, True, False, True, False, True, False, False, + False, False, True, True, True, True, True, True, True, True, + False, True, False, True, True, False, True])} class StaticData(object): @@ -1150,3 +2173,421 @@ def ger_reorder_tag(val, template): 917, 919, 920, 921, 922, 1448, 3680, 1450, 1454, 1455, 946, 948, 950, 596, 954, 955, 597, 1978, 3681, 2505, 1482, 1998, 976, 977, 978, 979, 1622, 994, 2536, 1516, 2542, 1006, 2544, 1518, 1520, 1526, 1528, 2554, 1343, 2556, 2558 ] +ACTIONS = [ + {'func_id': 0, 'general_ability_id': None, 'goal': 'other', 'name': 'no_op', 'queued': False, 'selected_units': False, 'target_location': False, 'target_unit': False} , + {'func_id': 168, 'general_ability_id': None, 'goal': 'other', 'name': 'raw_move_camera', 'queued': False, 'selected_units': False, 'target_location': True, 'target_unit': False} , + {'func_id': 2, 'general_ability_id': 3674, 'goal': 'other', 'name': 'Attack_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False} , + {'func_id': 3, 'general_ability_id': 3674, 'goal': 'other', 'name': 'Attack_unit', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': True} , + {'func_id': 88, 'general_ability_id': 2082, 'goal': 'other', 'name': 'Behavior_BuildingAttackOff_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , + {'func_id': 87, 'general_ability_id': 2081, 'goal': 'other', 'name': 'Behavior_BuildingAttackOn_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , + {'func_id': 169, 'general_ability_id': 3677, 'goal': 'other', 'name': 'Behavior_CloakOff_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , + {'func_id': 172, 'general_ability_id': 3676, 'goal': 'other', 'name': 'Behavior_CloakOn_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , + {'func_id': 175, 'general_ability_id': 1693, 'goal': 'other', 'name': 'Behavior_GenerateCreepOff_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , + {'func_id': 176, 'general_ability_id': 1692, 'goal': 'other', 'name': 'Behavior_GenerateCreepOn_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , + {'func_id': 177, 'general_ability_id': 3689, 'goal': 'other', 'name': 'Behavior_HoldFireOff_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , + {'func_id': 180, 'general_ability_id': 3688, 'goal': 'other', 'name': 'Behavior_HoldFireOn_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , + {'func_id': 158, 'general_ability_id': 2376, 'goal': 'other', 'name': 'Behavior_PulsarBeamOff_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , + {'func_id': 159, 'general_ability_id': 2375, 'goal': 'other', 'name': 'Behavior_PulsarBeamOn_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , + {'func_id': 183, 'general_ability_id': 331, 'goal': 'build', 'name': 'Build_Armory_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 29} , + {'func_id': 36, 'general_ability_id': 882, 'goal': 'build', 'name': 'Build_Assimilator_unit', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': True, 'game_id': 61} , + {'func_id': 184, 'general_ability_id': 1162, 'goal': 'build', 'name': 'Build_BanelingNest_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 96} , + {'func_id': 185, 'general_ability_id': 321, 'goal': 'build', 'name': 'Build_Barracks_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 21} , + {'func_id': 186, 'general_ability_id': 324, 'goal': 'build', 'name': 'Build_Bunker_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 24} , + {'func_id': 187, 'general_ability_id': 318, 'goal': 'build', 'name': 'Build_CommandCenter_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 18} , + {'func_id': 188, 'general_ability_id': 3691, 'goal': 'build', 'name': 'Build_CreepTumor_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 87} , + {'func_id': 47, 'general_ability_id': 894, 'goal': 'build', 'name': 'Build_CyberneticsCore_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 72} , + {'func_id': 44, 'general_ability_id': 891, 'goal': 'build', 'name': 'Build_DarkShrine_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 69} , + {'func_id': 191, 'general_ability_id': 322, 'goal': 'build', 'name': 'Build_EngineeringBay_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 22} , + {'func_id': 192, 'general_ability_id': 1156, 'goal': 'build', 'name': 'Build_EvolutionChamber_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 90} , + {'func_id': 193, 'general_ability_id': 1154, 'goal': 'build', 'name': 'Build_Extractor_unit', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': True, 'game_id': 88} , + {'func_id': 194, 'general_ability_id': 328, 'goal': 'build', 'name': 'Build_Factory_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 27} , + {'func_id': 39, 'general_ability_id': 885, 'goal': 'build', 'name': 'Build_FleetBeacon_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 64} , + {'func_id': 38, 'general_ability_id': 884, 'goal': 'build', 'name': 'Build_Forge_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 63} , + {'func_id': 195, 'general_ability_id': 333, 'goal': 'build', 'name': 'Build_FusionCore_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 30} , + {'func_id': 37, 'general_ability_id': 883, 'goal': 'build', 'name': 'Build_Gateway_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 62} , + {'func_id': 196, 'general_ability_id': 327, 'goal': 'build', 'name': 'Build_GhostAcademy_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 26} , + {'func_id': 197, 'general_ability_id': 1152, 'goal': 'build', 'name': 'Build_Hatchery_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 86} , + {'func_id': 198, 'general_ability_id': 1157, 'goal': 'build', 'name': 'Build_HydraliskDen_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 91} , + {'func_id': 199, 'general_ability_id': 1160, 'goal': 'build', 'name': 'Build_InfestationPit_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 94} , + {'func_id': 200, 'general_ability_id': 1042, 'goal': 'build', 'name': 'Build_Interceptors_autocast', 'queued': False, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 85} , + {'func_id': 66, 'general_ability_id': 1042, 'goal': 'build', 'name': 'Build_Interceptors_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 85} , + {'func_id': 201, 'general_ability_id': 1163, 'goal': 'build', 'name': 'Build_LurkerDen_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 504} , + {'func_id': 202, 'general_ability_id': 323, 'goal': 'build', 'name': 'Build_MissileTurret_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 23} , + {'func_id': 34, 'general_ability_id': 880, 'goal': 'build', 'name': 'Build_Nexus_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 59} , + {'func_id': 203, 'general_ability_id': 710, 'goal': 'build', 'name': 'Build_Nuke_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 58} , + {'func_id': 204, 'general_ability_id': 1161, 'goal': 'build', 'name': 'Build_NydusNetwork_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 95} , + {'func_id': 205, 'general_ability_id': 1768, 'goal': 'build', 'name': 'Build_NydusWorm_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 142} , + {'func_id': 41, 'general_ability_id': 887, 'goal': 'build', 'name': 'Build_PhotonCannon_pt', 'queued': True, 'selected_units': True, 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'goal': 'research', 'name': 'Research_TunnelingClaws_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 3} , + {'func_id': 82, 'general_ability_id': 1568, 'goal': 'research', 'name': 'Research_WarpGate_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 84} , + {'func_id': 474, 'general_ability_id': 3702, 'goal': 'research', 'name': 'Research_ZergFlyerArmor_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 71} , + {'func_id': 478, 'general_ability_id': 3703, 'goal': 'research', 'name': 'Research_ZergFlyerAttack_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 68} , + {'func_id': 482, 'general_ability_id': 3704, 'goal': 'research', 'name': 'Research_ZergGroundArmor_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 56} , + {'func_id': 494, 'general_ability_id': 1252, 'goal': 'research', 'name': 'Research_ZerglingAdrenalGlands_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 65} , + {'func_id': 495, 'general_ability_id': 1253, 'goal': 'research', 'name': 'Research_ZerglingMetabolicBoost_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 66} , + {'func_id': 486, 'general_ability_id': 3705, 'goal': 'research', 'name': 'Research_ZergMeleeWeapons_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 53} , + {'func_id': 490, 'general_ability_id': 3706, 'goal': 'research', 'name': 'Research_ZergMissileWeapons_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 59} , + {'func_id': 1, 'general_ability_id': 1, 'goal': 'other', 'name': 'Smart_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False} , + {'func_id': 12, 'general_ability_id': 1, 'goal': 'other', 'name': 'Smart_unit', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': True} , + {'func_id': 101, 'general_ability_id': 3665, 'goal': 'other', 'name': 'Stop_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , + {'func_id': 54, 'general_ability_id': 922, 'goal': 'unit', 'name': 'Train_Adept_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 311} , + {'func_id': 498, 'general_ability_id': 80, 'goal': 'unit', 'name': 'Train_Baneling_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 9} , + {'func_id': 499, 'general_ability_id': 621, 'goal': 'unit', 'name': 'Train_Banshee_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 55} , + {'func_id': 500, 'general_ability_id': 623, 'goal': 'unit', 'name': 'Train_Battlecruiser_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 57} , + {'func_id': 56, 'general_ability_id': 948, 'goal': 'unit', 'name': 'Train_Carrier_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 79} , + {'func_id': 62, 'general_ability_id': 978, 'goal': 'unit', 'name': 'Train_Colossus_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 4} , + {'func_id': 501, 'general_ability_id': 1353, 'goal': 'unit', 'name': 'Train_Corruptor_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 112} , + {'func_id': 502, 'general_ability_id': 597, 'goal': 'unit', 'name': 'Train_Cyclone_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 692} , + {'func_id': 52, 'general_ability_id': 920, 'goal': 'unit', 'name': 'Train_DarkTemplar_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 76} , + {'func_id': 166, 'general_ability_id': 994, 'goal': 'unit', 'name': 'Train_Disruptor_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 694} , + {'func_id': 503, 'general_ability_id': 1342, 'goal': 'unit', 'name': 'Train_Drone_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 104} , + {'func_id': 504, 'general_ability_id': 562, 'goal': 'unit', 'name': 'Train_Ghost_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 50} , + {'func_id': 505, 'general_ability_id': 596, 'goal': 'unit', 'name': 'Train_Hellbat_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 484} , + {'func_id': 506, 'general_ability_id': 595, 'goal': 'unit', 'name': 'Train_Hellion_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 53} , + {'func_id': 51, 'general_ability_id': 919, 'goal': 'unit', 'name': 'Train_HighTemplar_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 75} , + {'func_id': 507, 'general_ability_id': 1345, 'goal': 'unit', 'name': 'Train_Hydralisk_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 107} , + {'func_id': 63, 'general_ability_id': 979, 'goal': 'unit', 'name': 'Train_Immortal_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 83} , + {'func_id': 508, 'general_ability_id': 1352, 'goal': 'unit', 'name': 'Train_Infestor_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 111} , + {'func_id': 509, 'general_ability_id': 626, 'goal': 'unit', 'name': 'Train_Liberator_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 689} , + {'func_id': 510, 'general_ability_id': 563, 'goal': 'unit', 'name': 'Train_Marauder_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 51} , + {'func_id': 511, 'general_ability_id': 560, 'goal': 'unit', 'name': 'Train_Marine_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 48} , + {'func_id': 512, 'general_ability_id': 620, 'goal': 'unit', 'name': 'Train_Medivac_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 54} , + {'func_id': 513, 'general_ability_id': 1853, 'goal': 'unit', 'name': 'Train_MothershipCore_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 488} , + {'func_id': 21, 'general_ability_id': 110, 'goal': 'unit', 'name': 'Train_Mothership_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 10} , + {'func_id': 514, 'general_ability_id': 1346, 'goal': 'unit', 'name': 'Train_Mutalisk_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 108} , + {'func_id': 61, 'general_ability_id': 977, 'goal': 'unit', 'name': 'Train_Observer_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 82} , + {'func_id': 58, 'general_ability_id': 954, 'goal': 'unit', 'name': 'Train_Oracle_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 495} , + {'func_id': 515, 'general_ability_id': 1344, 'goal': 'unit', 'name': 'Train_Overlord_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 106} , + {'func_id': 55, 'general_ability_id': 946, 'goal': 'unit', 'name': 'Train_Phoenix_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 78} , + {'func_id': 64, 'general_ability_id': 1006, 'goal': 'unit', 'name': 'Train_Probe_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 84} , + {'func_id': 516, 'general_ability_id': 1632, 'goal': 'unit', 'name': 'Train_Queen_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 126} , + {'func_id': 517, 'general_ability_id': 622, 'goal': 'unit', 'name': 'Train_Raven_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 56} , + {'func_id': 518, 'general_ability_id': 561, 'goal': 'unit', 'name': 'Train_Reaper_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 49} , + {'func_id': 519, 'general_ability_id': 1351, 'goal': 'unit', 'name': 'Train_Roach_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 110} , + {'func_id': 520, 'general_ability_id': 524, 'goal': 'unit', 'name': 'Train_SCV_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 45} , + {'func_id': 53, 'general_ability_id': 921, 'goal': 'unit', 'name': 'Train_Sentry_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 77} , + {'func_id': 521, 'general_ability_id': 591, 'goal': 'unit', 'name': 'Train_SiegeTank_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 33} , + {'func_id': 50, 'general_ability_id': 917, 'goal': 'unit', 'name': 'Train_Stalker_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 74} , + {'func_id': 522, 'general_ability_id': 1356, 'goal': 'unit', 'name': 'Train_SwarmHost_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 494} , + {'func_id': 59, 'general_ability_id': 955, 'goal': 'unit', 'name': 'Train_Tempest_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 496} , + {'func_id': 523, 'general_ability_id': 594, 'goal': 'unit', 'name': 'Train_Thor_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 52} , + {'func_id': 524, 'general_ability_id': 1348, 'goal': 'unit', 'name': 'Train_Ultralisk_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 109} , + {'func_id': 525, 'general_ability_id': 624, 'goal': 'unit', 'name': 'Train_VikingFighter_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 35} , + {'func_id': 526, 'general_ability_id': 1354, 'goal': 'unit', 'name': 'Train_Viper_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 499} , + {'func_id': 57, 'general_ability_id': 950, 'goal': 'unit', 'name': 'Train_VoidRay_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 80} , + {'func_id': 76, 'general_ability_id': 1419, 'goal': 'unit', 'name': 'TrainWarp_Adept_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 311} , + {'func_id': 74, 'general_ability_id': 1417, 'goal': 'unit', 'name': 'TrainWarp_DarkTemplar_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 76} , + {'func_id': 73, 'general_ability_id': 1416, 'goal': 'unit', 'name': 'TrainWarp_HighTemplar_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 75} , + {'func_id': 60, 'general_ability_id': 976, 'goal': 'unit', 'name': 'Train_WarpPrism_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 81} , + {'func_id': 75, 'general_ability_id': 1418, 'goal': 'unit', 'name': 'TrainWarp_Sentry_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 77} , + {'func_id': 72, 'general_ability_id': 1414, 'goal': 'unit', 'name': 'TrainWarp_Stalker_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 74} , + {'func_id': 71, 'general_ability_id': 1413, 'goal': 'unit', 'name': 'TrainWarp_Zealot_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 73} , + {'func_id': 527, 'general_ability_id': 614, 'goal': 'unit', 'name': 'Train_WidowMine_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 498} , + {'func_id': 49, 'general_ability_id': 916, 'goal': 'unit', 'name': 'Train_Zealot_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 73} , + {'func_id': 528, 'general_ability_id': 1343, 'goal': 'unit', 'name': 'Train_Zergling_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 105} , + {'func_id': 105, 'general_ability_id': 3669, 'goal': 'other', 'name': 'UnloadAllAt_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False} , + {'func_id': 164, 'general_ability_id': 3669, 'goal': 'other', 'name': 'UnloadAllAt_unit', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': True} , + {'func_id': 100, 'general_ability_id': 3664, 'goal': 'other', 'name': 'UnloadAll_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , + {'func_id': 556, 'general_ability_id': 3796, 'goal': 'other', 'name': 'UnloadUnit_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , +] + + +NUM_UNIT_MIX_ABILITIES = len(UNIT_MIX_ABILITIES) #269 + +UNIT_ABILITY_REORDER = torch.full((max(UNIT_MIX_ABILITIES) + 1, ), fill_value=-1, dtype=torch.long) +for idx in range(len(UNIT_SPECIFIC_ABILITIES)): + if UNIT_GENERAL_ABILITIES[idx] == 0: + UNIT_ABILITY_REORDER[UNIT_SPECIFIC_ABILITIES[idx]] = UNIT_MIX_ABILITIES.index(UNIT_SPECIFIC_ABILITIES[idx]) + else: + UNIT_ABILITY_REORDER[UNIT_SPECIFIC_ABILITIES[idx]] = UNIT_MIX_ABILITIES.index(UNIT_GENERAL_ABILITIES[idx]) +UNIT_ABILITY_REORDER[0] = 0 # use 0 as no op + +FUNC_ID_TO_ACTION_TYPE_DICT = {a['func_id']: idx for idx, a in enumerate(ACTIONS)} +ABILITY_TO_GABILITY = {} +for idx in range(len(UNIT_SPECIFIC_ABILITIES)): + if UNIT_GENERAL_ABILITIES[idx] == 0: + ABILITY_TO_GABILITY[UNIT_SPECIFIC_ABILITIES[idx]] = UNIT_SPECIFIC_ABILITIES[idx] + else: + ABILITY_TO_GABILITY[UNIT_SPECIFIC_ABILITIES[idx]] = UNIT_GENERAL_ABILITIES[idx] + +GABILITY_TO_QUEUE_ACTION = {} +QUEUE_ACTIONS = [] +count = 1 # use 0 as no op +for idx, f in enumerate(ACTIONS): + if 'Train_' in f['name'] or 'Research' in f['name']: + GABILITY_TO_QUEUE_ACTION[f['general_ability_id']] = count + QUEUE_ACTIONS.append(idx) + count += 1 + else: + GABILITY_TO_QUEUE_ACTION[f['general_ability_id']] = 0 + +ABILITY_TO_QUEUE_ACTION = torch.full((max(ABILITY_TO_GABILITY.keys()) + 1, ), fill_value=-1, dtype=torch.long) +ABILITY_TO_QUEUE_ACTION[0] = 0 # use 0 as no op +for a_id, g_id in ABILITY_TO_GABILITY.items(): + if g_id in GABILITY_TO_QUEUE_ACTION.keys(): + ABILITY_TO_QUEUE_ACTION[a_id] = GABILITY_TO_QUEUE_ACTION[g_id] + else: + ABILITY_TO_QUEUE_ACTION[a_id] = 0 + +EXCLUDE_ACTIONS = [ + 'Build_Pylon_pt', 'Train_Overlord_quick', 'Build_SupplyDepot_pt', # supply action + 'Train_Drone_quick', 'Train_SCV_quick', 'Train_Probe_quick', # worker action + 'Build_CreepTumor_pt', '' +] + +BO_EXCLUDE_ACTIONS = [ +] + +CUM_EXCLUDE_ACTIONS = [ + 'Build_SpineCrawler_pt', 'Build_SporeCrawler_pt', 'Build_PhotonCannon_pt', 'Build_ShieldBattery_pt', + 'Build_Bunker_pt', 'Morph_Overseer_quick', 'Build_MissileTurret_pt' +] + +BEGINNING_ORDER_ACTIONS = [0] +CUMULATIVE_STAT_ACTIONS = [0] +for idx, f in enumerate(ACTIONS): + if f['goal'] in ['unit', 'build', 'research'] and f['name'] not in EXCLUDE_ACTIONS and f['name'] not in CUM_EXCLUDE_ACTIONS: + CUMULATIVE_STAT_ACTIONS.append(idx) + if f['goal'] in ['unit', 'build', 'research'] and f['name'] not in EXCLUDE_ACTIONS: + BEGINNING_ORDER_ACTIONS.append(idx) + +NUM_ACTIONS = len(ACTIONS) +NUM_QUEUE_ACTIONS = len(QUEUE_ACTIONS) +NUM_BEGINNING_ORDER_ACTIONS = len(BEGINNING_ORDER_ACTIONS) +NUM_CUMULATIVE_STAT_ACTIONS = len(CUMULATIVE_STAT_ACTIONS) + +SELECTED_UNITS_MASK = torch.zeros(len(ACTIONS), dtype=torch.bool) +for idx, a in enumerate(ACTIONS): + if a['selected_units']: + SELECTED_UNITS_MASK[idx] = 1 + +UNIT_BUILD_ACTIONS = [a['func_id'] for a in ACTIONS if a['goal'] == 'build'] +UNIT_TRAIN_ACTIONS = [a['func_id'] for a in ACTIONS if a['goal'] == 'unit'] + +GENERAL_ABILITY_IDS = [] +for idx, a in enumerate(ACTIONS): + GENERAL_ABILITY_IDS.append(a['general_ability_id']) +UNIT_ABILITY_TO_ACTION = {} +for idx, a in enumerate(UNIT_MIX_ABILITIES): + if a in GENERAL_ABILITY_IDS: + UNIT_ABILITY_TO_ACTION[idx] = GENERAL_ABILITY_IDS.index(a) + +UNIT_TO_CUM = defaultdict(lambda: -1) +UPGRADE_TO_CUM = defaultdict(lambda: -1) +for idx, a in enumerate(ACTIONS): + if 'game_id' in a and a['goal'] in ['unit', 'build'] and idx in CUMULATIVE_STAT_ACTIONS: + UNIT_TO_CUM[a['game_id']] = CUMULATIVE_STAT_ACTIONS.index(idx) + elif 'game_id' in a and a['goal'] in ['research'] and idx in CUMULATIVE_STAT_ACTIONS: + UPGRADE_TO_CUM[a['game_id']] = CUMULATIVE_STAT_ACTIONS.index(idx) diff --git a/dizoo/distar/model/actor_critic_default_config.yaml b/dizoo/distar/model/actor_critic_default_config.yaml index 5cdef334e5..08859163b3 100644 --- a/dizoo/distar/model/actor_critic_default_config.yaml +++ b/dizoo/distar/model/actor_critic_default_config.yaml @@ -21,6 +21,7 @@ model: freeze_targets: [] state_dict_mask: [] use_value_network: False + only_update_baseline: False enable_baselines: ['winloss', 'build_order', 'built_unit', 'effect', 'upgrade', 'battle'] entity_reduce_type: 'selected_units_num' # ['constant', 'entity_num', 'selected_units_num'] # ===== Value ===== @@ -403,6 +404,7 @@ model: norm_type: 'LN' ln_type: 'normal' use_mask: False + race: 'zerg' delay_head: input_dim: 1024 # action_type_head.gate_dim decode_dim: 256 @@ -428,6 +430,7 @@ model: num_layers: 1 max_entity_num: 64 activation: 'relu' + extra_units: True # select extra units if selected units exceed max_entity_num=64 target_unit_head: input_dim: 1024 # action_type_head.gate_dim entity_embedding_dim: 256 # entity_encoder.output_dim @@ -443,11 +446,7 @@ model: upsample_dims: [64, 32, 1] # len(upsample_dims)-len(down_channels)+1 = ratio res_dim: 128 res_num: 4 - film: False gate: True - unet: False - reshape_size: [16, 16] reshape_channel: 4 # entity_encoder.gate_dim / reshape_size map_skip_dim: 128 # spatial_encoder.down_channels[-1] activation: 'relu' - # loc_type: 'alphastar' diff --git a/dizoo/distar/model/head/action_arg_head.py b/dizoo/distar/model/head/action_arg_head.py index 34d36b086e..35f3d3b1f4 100644 --- a/dizoo/distar/model/head/action_arg_head.py +++ b/dizoo/distar/model/head/action_arg_head.py @@ -17,9 +17,8 @@ import torch.nn as nn import torch.nn.functional as F from ding.torch_utils import fc_block, conv2d_block, deconv2d_block, build_activation, ResBlock, NearestUpsample, \ - BilinearUpsample, sequence_mask, GatedResBlock, FiLMedResBlock, AttentionPool + BilinearUpsample, sequence_mask, GatedConvResBlock, AttentionPool, script_lstm from dizoo.distar.envs import MAX_ENTITY_NUM, MAX_SELECTED_UNITS_NUM -from ..lstm import script_lnlstm, script_lstm class DelayHead(nn.Module): @@ -104,9 +103,8 @@ def __init__(self, cfg): self.key_dim = self.cfg.key_dim self.num_layers = self.cfg.num_layers - self.test_iou = self.cfg.get('test_iou', False) - self.lstm = script_lnlstm(self.cfg.key_dim, self.cfg.hidden_dim, self.cfg.num_layers) + self.lstm = script_lstm(self.cfg.key_dim, self.cfg.hidden_dim, self.cfg.num_layers, LN=True) self.end_embedding = torch.nn.Parameter(torch.FloatTensor(1, self.key_dim)) stdv = 1. / math.sqrt(self.end_embedding.size(1)) self.end_embedding.data.uniform_(-stdv, stdv) @@ -116,7 +114,7 @@ def __init__(self, cfg): self.attention_pool = AttentionPool( key_dim=self.cfg.key_dim, head_num=2, output_dim=self.cfg.input_dim, max_num=MAX_SELECTED_UNITS_NUM + 1 ) - self.extra_units = self.whole_cfg.get('agent', {}).get('extra_units', False) + self.extra_units = self.cfg.extra_units # select extra units if selected units exceed max_entity_num=64 def _get_key_mask(self, entity_embedding, entity_num): bs = entity_embedding.shape[0] @@ -175,19 +173,11 @@ def _query( result: Optional[Tensor] = None results: Optional[Tensor] = None - extra_units = torch.zeros(bs, MAX_ENTITY_NUM + 1, device=ae.device) if selected_units is not None and selected_units_num is not None: # train bs = selected_units.shape[0] seq_len = selected_units_num.max() queries = [] selected_mask = sequence_mask(selected_units_num) # b, s - if self.test_iou: - iou_ae = ae.detach().clone() - iou_logits_mask = logits_mask.detach().clone() - iou_state = [ - (torch.zeros(ae.shape[0], 32, device=ae.device), torch.zeros(ae.shape[0], 32, device=ae.device)) - for _ in range(self.num_layers) - ] logits_mask = logits_mask.repeat(max(seq_len, 1), 1, 1) # b, n -> s, b, n logits_mask[0, torch.arange(bs), entity_num] = 0 # end flag is not available at first selection selected_units_one_hot = torch.zeros(*key_embeddings.shape[:2], device=ae.device).unsqueeze(dim=2) @@ -233,54 +223,8 @@ def _query( logits = query_result.sum(dim=3) # s, b, n logits = logits.masked_fill(~logits_mask, -1e9) logits = logits.permute(1, 0, 2).contiguous() - if self.test_iou: - with torch.no_grad(): - selected_units_one_hot = torch.zeros(*key_embeddings.shape[:2], device=ae.device).unsqueeze(dim=2) - selected_units_num = torch.ones(bs, dtype=torch.long, device=ae.device) * seq_len - key = key.squeeze(dim=0) - for i in range(seq_len): - if i > 0: - if i == 1: # end flag can be selected at second selection - iou_logits_mask[torch.arange(bs), - entity_num] = torch.tensor([1], dtype=torch.bool, device=ae.device) - if result is not None: - iou_logits_mask[torch.arange(bs), result.detach()] = torch.tensor( - [0], dtype=torch.bool, device=ae.device - ) # mask selected units - lstm_input = self.query_fc2(self.query_fc1(iou_ae)).unsqueeze(0) - lstm_output, iou_state = self.lstm(lstm_input, iou_state) - queries = lstm_output.permute(1, 0, 2) # b, 1, c - query_result = queries * key - step_logits = query_result.sum(dim=2) # b, n - step_logits = step_logits.masked_fill(~iou_logits_mask, -1e9) - step_logits = step_logits.div(1) - result = self._get_pred_with_logit(step_logits) - selected_units_num[(result == entity_num) * ~(end_flag)] = torch.tensor(i + 1).to(result.device) - end_flag[result == entity_num] = torch.tensor([1], dtype=torch.bool, device=ae.device) - results_list.append(result) - reduce_type = self.whole_cfg.model.entity_reduce_type - if reduce_type == 'selected_units_num' or 'attention' in reduce_type: - selected_units_one_hot[torch.arange(bs)[~end_flag], result[~end_flag], :] = 1 - if self.whole_cfg.model.entity_reduce_type == 'selected_units_num': - selected_units_emebedding = (key_embeddings * selected_units_one_hot - ).sum(dim=1) / selected_units_one_hot.sum(dim=1) - selected_units_emebedding = self.embed_fc2(self.embed_fc1(selected_units_emebedding)) - iou_ae = autoregressive_embedding + selected_units_emebedding - elif self.whole_cfg.model.entity_reduce_type == 'attention_pool': - iou_ae = autoregressive_embedding + self.attention_pool( - key_embeddings, mask=selected_units_one_hot - ) - elif self.whole_cfg.model.entity_reduce_type == 'attention_pool_add_num': - iou_ae = autoregressive_embedding + self.attention_pool( - key_embeddings, - num=selected_units_one_hot.sum(dim=1).squeeze(dim=1), - mask=selected_units_one_hot, - ) - else: - iou_ae = iou_ae + key_embeddings[torch.arange(bs), result] * ~end_flag.unsqueeze(dim=1) - results = torch.stack(results_list, dim=0) - results = results.transpose(1, 0).contiguous() - + results = selected_units + extra_units = None else: selected_units_num = torch.ones(bs, dtype=torch.long, device=ae.device) * self.max_select_num end_flag[~su_mask] = 1 @@ -391,7 +335,6 @@ def __init__(self, cfg): self.whole_cfg = cfg self.cfg = self.whole_cfg.model.policy.head.location_head self.act = build_activation(self.cfg.activation) - self.reshape_size = self.cfg.reshape_size self.reshape_channel = self.cfg.reshape_channel self.conv1 = conv2d_block( @@ -406,25 +349,18 @@ def __init__(self, cfg): self.res = nn.ModuleList() self.res_act = nn.ModuleList() self.res_dim = self.cfg.res_dim - self.use_film = self.cfg.get('film', False) - self.use_gate = self.cfg.get('gate', False) - self.use_unet = self.cfg.get('unet', False) + self.use_gate = self.cfg.gate self.project_embed = fc_block( self.cfg.input_dim, self.whole_cfg.model.spatial_y // 8 * self.whole_cfg.model.spatial_x // 8 * 4, activation=build_activation(self.cfg.activation) ) - if self.use_film: - self.film_fc = fc_block(self.cfg.input_dim, self.res_dim, activation=build_activation(self.cfg.activation)) - self.film_gamma = nn.ModuleList() - self.film_beta = nn.ModuleList() - self.film = nn.ModuleList() self.res = nn.ModuleList() for i in range(self.cfg.res_num): if self.use_gate: self.res.append( - GatedResBlock( + GatedConvResBlock( self.res_dim, self.res_dim, 3, @@ -436,12 +372,6 @@ def __init__(self, cfg): ) else: self.res.append(ResBlock(self.dim, build_activation(self.cfg.activation), norm_type=None)) - if self.use_film: - self.film_gamma.append(nn.Linear(self.res_dim, self.res_dim)) - self.film_beta.append(nn.Linear(self.res_dim, self.res_dim)) - self.film.append(FiLMedResBlock(self.res_dim, with_cond=[True])) - torch.nn.init.xavier_uniform_(self.film_gamma[i].weight) - torch.nn.init.xavier_uniform_(self.film_beta[i].weight) self.upsample = nn.ModuleList() # upsample list dims = [self.res_dim] + self.cfg.upsample_dims @@ -468,8 +398,6 @@ def forward(self, embedding, map_skip: List[Tensor], location=None): x1 = self.act(cat_feature) x = self.conv1(x1) - if self.use_film: - film_embedding = self.film_fc(embedding) # reverse cat_feature instead of reversing resblock for i in range(self.cfg.res_num): @@ -478,15 +406,11 @@ def forward(self, embedding, map_skip: List[Tensor], location=None): x = self.res[i](x, x) else: x = self.res[i](x) - if self.use_film: - x = self.film[i](x, gammas=self.film_gamma[i](film_embedding), betas=self.film_beta[i](film_embedding)) for i, layer in enumerate(self.upsample): if self.cfg.upsample_type == 'nearest': x = F.interpolate(x, scale_factor=2., mode='nearest') elif self.cfg.upsample_type == 'bilinear': x = F.interpolate(x, scale_factor=2., mode='bilinear') - if self.use_unet: - x = x + map_skip[len(map_skip) - self.cfg.res_num - i - 1] x = layer(x) logits_flatten = x.view(x.shape[0], -1) diff --git a/dizoo/distar/model/head/action_type_head.py b/dizoo/distar/model/head/action_type_head.py index 98eaa250e1..104c4e0ad8 100644 --- a/dizoo/distar/model/head/action_type_head.py +++ b/dizoo/distar/model/head/action_type_head.py @@ -22,12 +22,8 @@ def __init__(self, cfg): self.cfg = self.whole_cfg.model.policy.head.action_type_head self.act = build_activation(self.cfg.activation) # use relu as default self.project = fc_block(self.cfg.input_dim, self.cfg.res_dim, activation=self.act, norm_type=None) - # self.project = fc_block(self.cfg.input_dim, self.cfg.res_dim) blocks = [ResFCBlock(self.cfg.res_dim, self.act, self.cfg.norm_type) for _ in range(self.cfg.res_num)] self.res = nn.Sequential(*blocks) - self.weight_norm = self.cfg.get('weight_norm', False) - self.drop_Z = torch.nn.Dropout(p=self.cfg.get('drop_ratio', 0.0)) - self.drop_ratio = self.cfg.get('drop_ratio', 0.0) self.action_fc = build_activation('glu')(self.cfg.res_dim, self.cfg.action_num, self.cfg.context_dim) self.action_map_fc1 = fc_block( @@ -39,11 +35,8 @@ def __init__(self, cfg): self.glu1 = build_activation('glu')(self.cfg.action_map_dim, self.cfg.gate_dim, self.cfg.context_dim) self.glu2 = build_activation('glu')(self.cfg.input_dim, self.cfg.gate_dim, self.cfg.context_dim) self.action_num = self.cfg.action_num - if self.whole_cfg.common.type == 'play': - self.use_mask = True - else: - self.use_mask = False - self.race = 'zerg' + self.use_mask = self.cfg.use_mask + self.race = self.cfg.race def forward(self, lstm_output, diff --git a/dizoo/distar/model/model.py b/dizoo/distar/model/model.py index 74ef6a208b..f21a8d9863 100644 --- a/dizoo/distar/model/model.py +++ b/dizoo/distar/model/model.py @@ -7,11 +7,10 @@ import torch.nn as nn from ding.utils import read_yaml_config, deep_merge_dicts, default_collate -from ding.torch_utils import detach_grad +from ding.torch_utils import detach_grad, script_lstm from dizoo.distar.envs import MAX_SELECTED_UNITS_NUM from .encoder import Encoder from .obs_encoder.value_encoder import ValueEncoder -from .lstm import script_lnlstm from .policy import Policy from .value import ValueBaseline @@ -28,7 +27,7 @@ def __init__(self, cfg={}, use_value_network=False, temperature=None): self.cfg = self.whole_cfg.model self.encoder = Encoder(self.whole_cfg) self.policy = Policy(self.whole_cfg) - self._use_value_feature = self.whole_cfg.learner.get('use_value_feature', False) + self._use_value_feature = self.whole_cfg.learner.use_value_feature if use_value_network: if self._use_value_feature: self.value_encoder = ValueEncoder(self.whole_cfg) @@ -38,10 +37,12 @@ def __init__(self, cfg={}, use_value_network=False, temperature=None): # creating a ValueBaseline network for each baseline, to be used in _critic_forward self.value_networks[v.name] = ValueBaseline(v.param, self._use_value_feature) # name of needed cumulative stat items - self.only_update_baseline = self.cfg.get('only_update_baseline', False) - self.core_lstm = script_lnlstm( - self.cfg.encoder.core_lstm.input_size, self.cfg.encoder.core_lstm.hidden_size, - self.cfg.encoder.core_lstm.num_layers + self.only_update_baseline = self.cfg.only_update_baseline + self.core_lstm = script_lstm( + self.cfg.encoder.core_lstm.input_size, + self.cfg.encoder.core_lstm.hidden_size, + self.cfg.encoder.core_lstm.num_layers, + LN=True ) def forward( diff --git a/dizoo/distar/model/module_utils.py b/dizoo/distar/model/module_utils.py deleted file mode 100644 index d28d311dfd..0000000000 --- a/dizoo/distar/model/module_utils.py +++ /dev/null @@ -1,570 +0,0 @@ -import torch -import torch.nn as nn -import torch.nn.functional as F -import math -from torch.nn.init import kaiming_normal_, kaiming_uniform_ -from distar.ctools.torch_utils import conv2d_block, sequence_mask, fc_block, build_normalization -from typing import Optional, Dict, Tuple -from torch import Tensor - - -def scatter_connection(shape, project_embeddings, entity_location, scatter_dim, scatter_type='add'): - B, H, W = shape - device = entity_location.device - entity_num = entity_location.shape[1] - index = entity_location.view(-1, 2).long() - bias = torch.arange(B).unsqueeze(1).repeat(1, entity_num).view(-1).to(device) - bias *= H * W - index[:, 0].clamp_(0, W - 1) - index[:, 1].clamp_(0, H - 1) - index = index[:, 1] * W + index[:, 0] # entity_location: (x, y), spatial_info: (y, x) - index += bias - index = index.repeat(scatter_dim, 1) - # flat scatter map and project embeddings - scatter_map = torch.zeros(scatter_dim, B * H * W, device=device) - project_embeddings = project_embeddings.view(-1, scatter_dim).permute(1, 0) - if scatter_type == 'cover': - scatter_map.scatter_(dim=1, index=index, src=project_embeddings) - elif scatter_type == 'add': - scatter_map.scatter_add_(dim=1, index=index, src=project_embeddings) - else: - raise NotImplementedError - scatter_map = scatter_map.reshape(scatter_dim, B, H, W) - scatter_map = scatter_map.permute(1, 0, 2, 3) - return scatter_map - - -class AttentionPool(nn.Module): - - def __init__(self, key_dim, head_num, output_dim, max_num=None): - super(AttentionPool, self).__init__() - self.queries = torch.nn.Parameter(torch.zeros(1, 1, head_num, key_dim)) - torch.nn.init.xavier_uniform_(self.queries) - self.head_num = head_num - self.add_num = False - if max_num is not None: - self.add_num = True - self.num_ebed = torch.nn.Embedding(num_embeddings=max_num, embedding_dim=output_dim) - self.embed_fc = fc_block(key_dim * self.head_num, output_dim) - - def forward(self, x, num=None, mask=None): - assert len(x.shape) == 3 # batch size, tokens, channels - x_with_head = x.unsqueeze(dim=2) # add head dim - score = x_with_head * self.queries - score = score.sum(dim=3) # b, t, h - if mask is not None: - assert len(mask.shape) == 3 and mask.shape[-1] == 1 - mask = mask.repeat(1, 1, self.head_num) - score.masked_fill_(~mask.bool(), value=-1e9) - score = F.softmax(score, dim=1) - x = x.unsqueeze(dim=3).repeat(1, 1, 1, self.head_num) # b, t, c, h - score = score.unsqueeze(dim=2) # b, t, 1, h - x = x * score - x = x.sum(dim=1) # b, c, h - x = x.view(x.shape[0], -1) # b, c * h - x = self.embed_fc(x) # b, c - if self.add_num: - x = x + F.relu(self.num_ebed(num.long())) - x = F.relu(x) - return x - - -class Attention(nn.Module): - - def __init__(self, input_dim, head_dim, output_dim, head_num, dropout): - super(Attention, self).__init__() - self.head_num = head_num - self.head_dim = head_dim - self.dropout = dropout - self.attention_pre = fc_block(input_dim, head_dim * head_num * 3) # query, key, value - self.project = fc_block(head_dim * head_num, output_dim) - - def split(self, x, T: bool = False): - B, N = x.shape[:2] - x = x.view(B, N, self.head_num, self.head_dim) - x = x.permute(0, 2, 1, 3).contiguous() # B, head_num, N, head_dim - if T: - x = x.permute(0, 1, 3, 2).contiguous() - return x - - def forward(self, x, mask: Optional[torch.Tensor] = None): - """ - Overview: - x: [batch_size, seq_len, embeddding_size] - """ - assert (len(x.shape) == 3) - B, N = x.shape[:2] - x = self.attention_pre(x) - query, key, value = torch.chunk(x, 3, dim=2) - query, key, value = self.split(query), self.split(key, T=True), self.split(value) - - score = torch.matmul(query, key) # B, head_num, N, N - score /= math.sqrt(self.head_dim) - if mask is not None: - score.masked_fill_(~mask, value=-1e9) - - score = F.softmax(score, dim=-1) - if self.dropout: - score = self.dropout(score) - attention = torch.matmul(score, value) # B, head_num, N, head_dim - - attention = attention.permute(0, 2, 1, 3).contiguous() # B, N, head_num, head_dim - attention = self.project(attention.view(B, N, -1)) # B, N, output_dim - return attention - - -class TransformerLayer(nn.Module): - - def __init__(self, input_dim, head_dim, hidden_dim, output_dim, head_num, mlp_num, dropout, activation, ln_type): - super(TransformerLayer, self).__init__() - self.attention = Attention(input_dim, head_dim, output_dim, head_num, dropout) - self.layernorm1 = build_normalization('LN')(output_dim) - self.dropout = dropout - layers = [] - dims = [output_dim] + [hidden_dim] * (mlp_num - 1) + [output_dim] - for i in range(mlp_num): - layers.append(fc_block(dims[i], dims[i + 1], activation=activation)) - if self.dropout: - layers.append(self.dropout) - self.mlp = nn.Sequential(*layers) - self.layernorm2 = build_normalization('LN')(output_dim) - self.ln_type = ln_type - - def forward(self, x, mask: Optional[torch.Tensor] = None): - if self.ln_type == 'post': - a = self.attention(x, mask) - if self.dropout: - a = self.dropout(a) - x = self.layernorm1(x + a) - m = self.mlp(x) - if self.dropout: - m = self.dropout(m) - x = self.layernorm2(x + m) - elif self.ln_type == 'pre': - a = self.attention(self.layernorm1(x), mask) - if self.dropout: - a = self.dropout(a) - x = x + a - m = self.mlp(self.layernorm2(x)) - if self.dropout: - m = self.dropout(m) - x = x + m - else: - raise NotImplementedError(self.ln_type) - return x, mask - - -class Transformer(nn.Module): - ''' - Note: - Input has passed through embedding - ''' - - def __init__( - self, - input_dim, - head_dim=128, - hidden_dim=1024, - output_dim=256, - head_num=2, - mlp_num=2, - layer_num=3, - pad_val=0, - dropout_ratio=0.0, - activation=nn.ReLU(), - ln_type='pre' - ): - super(Transformer, self).__init__() - self.embedding = fc_block(input_dim, output_dim, activation=activation) - self.pad_val = pad_val - self.act = activation - layers = [] - dims = [output_dim] + [output_dim] * layer_num - if dropout_ratio > 0: - self.dropout = nn.Dropout(dropout_ratio) - else: - self.dropout = None - for i in range(layer_num): - layers.append( - TransformerLayer( - dims[i], head_dim, hidden_dim, dims[i + 1], head_num, mlp_num, self.dropout, self.act, ln_type - ) - ) - self.layers = nn.ModuleList(layers) - - def forward(self, x, mask: Optional[torch.Tensor] = None): - if mask is not None: - mask = mask.unsqueeze(dim=1).repeat(1, mask.shape[1], 1).unsqueeze(dim=1) - x = self.embedding(x) - if self.dropout: - x = self.dropout(x) - for m in self.layers: - x, mask = m(x, mask) - return x - - -class GatedResBlock(nn.Module): - ''' - Gated Residual Block with conv2d_block by songgl at 2020.10.23 - ''' - - def __init__(self, in_channels, out_channels, kernel_size, stride, padding, activation=nn.ReLU(), norm_type='BN'): - super(GatedResBlock, self).__init__() - assert (stride == 1) - assert (in_channels == out_channels) - self.act = activation - self.conv1 = conv2d_block(in_channels, out_channels, 3, 1, 1, activation=self.act, norm_type=norm_type) - self.conv2 = conv2d_block(out_channels, out_channels, 3, 1, 1, activation=None, norm_type=norm_type) - self.GateWeightG = nn.Sequential( - conv2d_block(out_channels, out_channels, 1, 1, 0, activation=self.act, norm_type=None), - conv2d_block(out_channels, out_channels, 1, 1, 0, activation=self.act, norm_type=None), - conv2d_block(out_channels, out_channels, 1, 1, 0, activation=self.act, norm_type=None), - conv2d_block(out_channels, out_channels, 1, 1, 0, activation=None, norm_type=None) - ) - self.UpdateSP = nn.Parameter(torch.zeros(1)) - nn.init.constant_(self.UpdateSP, 0.1) - - def forward(self, x, NoiseMap): - residual = x - x = self.conv1(x) - x = self.conv2(x) - x = torch.tanh(x * torch.sigmoid(self.GateWeightG(NoiseMap))) * self.UpdateSP - x = self.act(x + residual) - #x = x + residual - return x - - -class FiLM(nn.Module): - """ - A Feature-wise Linear Modulation Layer from - 'FiLM: Visual Reasoning with a General Conditioning Layer' - """ - - def forward(self, x, gammas, betas): - gammas = gammas.unsqueeze(2).unsqueeze(3).expand_as(x) - betas = betas.unsqueeze(2).unsqueeze(3).expand_as(x) - return (gammas * x) + betas - - -class FiLMedResBlock(nn.Module): - - def __init__( - self, - in_dim, - out_dim=None, - with_residual=True, - with_batchnorm=False, - with_cond=[False], - dropout=0, - num_extra_channels=0, - extra_channel_freq=1, - with_input_proj=3, - num_cond_maps=0, - kernel_size=3, - batchnorm_affine=False, - num_layers=1, - condition_method='conv-film', - debug_every=float('inf') - ): - if out_dim is None: - out_dim = in_dim - super(FiLMedResBlock, self).__init__() - self.with_residual = with_residual - self.with_batchnorm = with_batchnorm - self.with_cond = with_cond - self.dropout = dropout - self.extra_channel_freq = 0 if num_extra_channels == 0 else extra_channel_freq - self.with_input_proj = with_input_proj # Kernel size of input projection - self.num_cond_maps = num_cond_maps - self.kernel_size = kernel_size - self.batchnorm_affine = batchnorm_affine - self.num_layers = num_layers - self.condition_method = condition_method - self.debug_every = debug_every - self.film = None - self.bn1 = None - self.drop = None - - if self.with_input_proj % 2 == 0: - raise (NotImplementedError) - if self.kernel_size % 2 == 0: - raise (NotImplementedError) - if self.num_layers >= 2: - raise (NotImplementedError) - - if self.condition_method == 'block-input-film' and self.with_cond[0]: - self.film = FiLM() - if self.with_input_proj: - self.input_proj = nn.Conv2d( - in_dim + (num_extra_channels if self.extra_channel_freq >= 1 else 0), - in_dim, - kernel_size=self.with_input_proj, - padding=self.with_input_proj // 2 - ) - - self.conv1 = nn.Conv2d( - in_dim + self.num_cond_maps + (num_extra_channels if self.extra_channel_freq >= 2 else 0), - out_dim, - kernel_size=self.kernel_size, - padding=self.kernel_size // 2 - ) - if self.condition_method == 'conv-film' and self.with_cond[0]: - self.film = FiLM() - if self.with_batchnorm: - self.bn1 = nn.BatchNorm2d(out_dim, affine=((not self.with_cond[0]) or self.batchnorm_affine)) - if self.condition_method == 'bn-film' and self.with_cond[0]: - self.film = FiLM() - if dropout > 0: - self.drop = nn.Dropout2d(p=self.dropout) - if ((self.condition_method == 'relu-film' or self.condition_method == 'block-output-film') - and self.with_cond[0]): - self.film = FiLM() - - self.init_modules(self.modules()) - - def init_modules(self, modules, init='normal'): - if init.lower() == 'normal': - init_params = kaiming_normal_ - elif init.lower() == 'uniform': - init_params = kaiming_uniform_ - else: - return - for m in modules: - if isinstance(m, (nn.Conv2d, nn.Linear)): - init_params(m.weight) - - def forward( - self, - x, - gammas: Optional[torch.Tensor] = None, - betas: Optional[torch.Tensor] = None, - extra_channels: Optional[torch.Tensor] = None, - cond_maps: Optional[torch.Tensor] = None - ): - - if self.film is not None: - if self.condition_method == 'block-input-film' and self.with_cond[0]: - x = self.film(x, gammas, betas) - - # ResBlock input projection - if self.with_input_proj: - if extra_channels is not None and self.extra_channel_freq >= 1: - x = torch.cat([x, extra_channels], 1) - x = F.relu(self.input_proj(x)) - out = x - - # ResBlock body - if cond_maps is not None: - out = torch.cat([out, cond_maps], 1) - if extra_channels is not None and self.extra_channel_freq >= 2: - out = torch.cat([out, extra_channels], 1) - out = self.conv1(out) - if self.film is not None: - if self.condition_method == 'conv-film' and self.with_cond[0]: - out = self.film(out, gammas, betas) - if self.bn1 is not None: - if self.with_batchnorm: - out = self.bn1(out) - if self.film is not None: - if self.condition_method == 'bn-film' and self.with_cond[0]: - out = self.film(out, gammas, betas) - if self.drop is not None: - if self.dropout > 0: - out = self.drop(out) - # out = F.relu(out) - if self.film is not None: - if self.condition_method == 'relu-film' and self.with_cond[0]: - out = self.film(out, gammas, betas) - - # ResBlock remainder - if self.with_residual: - out = F.relu(x + out) - if self.film is not None: - if self.condition_method == 'block-output-film' and self.with_cond[0]: - out = self.film(out, gammas, betas) - return out - - -class LSTMForwardWrapper(object): - - def _before_forward(self, inputs, prev_state): - assert hasattr(self, 'num_layers') - assert hasattr(self, 'hidden_size') - seq_len, batch_size = inputs.shape[:2] - if prev_state is None: - num_directions = 1 - zeros = torch.zeros( - num_directions * self.num_layers, - batch_size, - self.hidden_size, - dtype=inputs.dtype, - device=inputs.device - ) - prev_state = (zeros, zeros) - elif isinstance(prev_state, list) and len(prev_state) == 2 and isinstance(prev_state[0], torch.Tensor): - pass - elif isinstance(prev_state, list) and len(prev_state) == batch_size: - num_directions = 1 - zeros = torch.zeros( - num_directions * self.num_layers, 1, self.hidden_size, dtype=inputs.dtype, device=inputs.device - ) - state = [] - for prev in prev_state: - if prev is None: - state.append([zeros, zeros]) - else: - state.append(prev) - state = list(zip(*state)) - prev_state = [torch.cat(t, dim=1) for t in state] - return prev_state - - def _after_forward(self, next_state, list_next_state: bool = False): - if list_next_state: - h, c = [torch.stack(t, dim=0) for t in zip(*next_state)] - batch_size = h.shape[1] - next_state = [torch.chunk(h, batch_size, dim=1), torch.chunk(c, batch_size, dim=1)] - next_state = list(zip(*next_state)) - else: - next_state = [torch.stack(t, dim=0) for t in zip(*next_state)] - return next_state - - -class LSTM(nn.Module): - - def __init__(self, input_size, hidden_size, num_layers, norm_type=None, bias=True, dropout=0.): - super(LSTM, self).__init__() - self.input_size = input_size - self.hidden_size = hidden_size - self.num_layers = num_layers - - norm_func = build_normalization(norm_type) - #self.norm = nn.ModuleList([norm_func(hidden_size) for _ in range(4 * num_layers)]) - self.norm_A = nn.ModuleList([norm_func(hidden_size * 4) for _ in range(2 * num_layers)]) - self.norm_B = nn.ModuleList([norm_func(hidden_size) for _ in range(1 * num_layers)]) - self.wx = nn.ParameterList() - self.wh = nn.ParameterList() - dims = [input_size] + [hidden_size] * 3 - for l in range(num_layers): - self.wx.append(nn.Parameter(torch.zeros(dims[l], dims[l + 1] * 4))) - self.wh.append(nn.Parameter(torch.zeros(hidden_size, hidden_size * 4))) - if bias: - self.bias = nn.Parameter(torch.zeros(num_layers, hidden_size * 4)) - else: - self.bias = None - self.use_dropout = dropout > 0. - if self.use_dropout: - self.dropout = nn.Dropout(dropout) - self._init() - - def _init(self): - gain = math.sqrt(1. / self.hidden_size) - for l in range(self.num_layers): - torch.nn.init.uniform_(self.wx[l], -gain, gain) - torch.nn.init.uniform_(self.wh[l], -gain, gain) - if self.bias is not None: - torch.nn.init.uniform_(self.bias[l], -gain, gain) - - # for i in range(len(self.norm_A)): - # torch.nn.init.constant_(self.norm_A[i].weight, 0) - # torch.nn.init.constant_(self.norm_A[i].bias, 1) - # for i in range(len(self.norm_B)): - # torch.nn.init.constant_(self.norm_A[i].weight, 0) - # torch.nn.init.constant_(self.norm_A[i].bias, 1) - - def forward( - self, inputs, prev_state: Tuple[Tensor, Tensor], list_next_state: bool = False, forget_bias: float = 1.0 - ): - ''' - Input: - inputs: tensor of size [seq_len, batch_size, input_size] - prev_state: None or tensor of size [num_directions*num_layers, batch_size, hidden_size] - list_next_state: whether return next_state with list format - ''' - seq_len, batch_size = inputs.shape[:2] - - H, C = prev_state - x = inputs - next_state = [] - for l in range(self.num_layers): - h, c = H[l], C[l] - new_x = [] - for s in range(seq_len): - if self.use_dropout: - gate = self.norm_A[l * 2](torch.matmul(self.dropout(x[s]), self.wx[l]) - ) + self.norm_A[l * 2 + 1](torch.matmul(h, self.wh[l])) - else: - gate = self.norm_A[l * 2](torch.matmul(x[s], self.wx[l]) - ) + self.norm_A[l * 2 + 1](torch.matmul(h, self.wh[l])) - if self.bias is not None: - gate += self.bias[l] - gate = list(torch.chunk(gate, 4, dim=1)) - # for i in range(4): - # gate[i] = self.norm[l * 4 + i](gate[i]) - i, f, o, u = gate - i = torch.sigmoid(i) - f = torch.sigmoid(f + forget_bias) - o = torch.sigmoid(o) - u = torch.tanh(u) - c = f * c + i * u - cc = self.norm_B[l](c) - h = o * torch.tanh(cc) - # if self.use_dropout and l != self.num_layers - 1: # layer input dropout - # h = self.dropout(h) - new_x.append(h) - next_state.append((h, c)) - x = torch.stack(new_x, dim=0) - return x, next_state - - -class PytorchLSTM(nn.LSTM, LSTMForwardWrapper): - - def forward(self, inputs, prev_state, list_next_state: bool = False): - prev_state = self._before_forward(inputs, prev_state) - output, next_state = nn.LSTM.forward(self, inputs, prev_state) - next_state = self._after_forward(next_state, list_next_state) - return output, next_state - - def _after_forward(self, next_state, list_next_state: bool = False): - if list_next_state: - h, c = next_state - batch_size = h.shape[1] - next_state = [torch.chunk(h, batch_size, dim=1), torch.chunk(c, batch_size, dim=1)] - return list(zip(*next_state)) - else: - return next_state - - -def get_lstm(lstm_type, input_size, hidden_size, num_layers, norm_type, dropout=0.): - assert lstm_type in ['normal', 'pytorch'] - if lstm_type == 'normal': - return LSTM(input_size, hidden_size, num_layers, norm_type, dropout=dropout) - elif lstm_type == 'pytorch': - return PytorchLSTM(input_size, hidden_size, num_layers, dropout=dropout) - - -class GLU(nn.Module): - - def __init__(self, input_dim, output_dim, context_dim, input_type='fc'): - super(GLU, self).__init__() - assert (input_type in ['fc', 'conv2d']) - if input_type == 'fc': - self.layer1 = fc_block(context_dim, input_dim) - self.layer2 = fc_block(input_dim, output_dim) - elif input_type == 'conv2d': - self.layer1 = conv2d_block(context_dim, input_dim, 1, 1, 0) - self.layer2 = conv2d_block(input_dim, output_dim, 1, 1, 0) - - def forward(self, x, context): - gate = self.layer1(context) - gate = torch.sigmoid(gate) - x = gate * x - x = self.layer2(x) - return x - - -def build_activation(activation): - act_func = {'relu': nn.ReLU(inplace=True), 'glu': GLU, 'prelu': nn.PReLU(init=0.0)} - if activation in act_func.keys(): - return act_func[activation] - else: - raise KeyError("invalid key for activation: {}".format(activation)) diff --git a/dizoo/distar/model/policy.py b/dizoo/distar/model/policy.py index 46587ed652..8c6d0de52a 100644 --- a/dizoo/distar/model/policy.py +++ b/dizoo/distar/model/policy.py @@ -60,7 +60,7 @@ def train_forward( lstm_output, scalar_context, action_info['action_type'] ) - #action arg delay + # action arg delay logit['delay'], action['delay'], embeddings = self.delay_head(embeddings, action_info['delay']) logit['queued'], action['queued'], embeddings = self.queued_head(embeddings, action_info['queued']) diff --git a/dizoo/distar/model/tests/test_head.py b/dizoo/distar/model/tests/test_head.py new file mode 100644 index 0000000000..aee499232e --- /dev/null +++ b/dizoo/distar/model/tests/test_head.py @@ -0,0 +1,119 @@ +import pytest +import torch +from easydict import EasyDict +from ding.utils import read_yaml_config +from dizoo.distar.model.head import ActionTypeHead, DelayHead, SelectedUnitsHead, TargetUnitHead, LocationHead, \ + QueuedHead +B, ENTITY = 4, 128 +total_config = EasyDict(read_yaml_config('../actor_critic_default_config.yaml')) + + +@pytest.mark.envtest +class TestHead(): + + def test_action_type_head(self): + cfg = total_config.model.policy.head.action_type_head + head = ActionTypeHead(total_config) + lstm_output = torch.randn(B, cfg.input_dim) + scalar_context = torch.randn(B, cfg.context_dim) + + logit, action_type, embedding = head(lstm_output, scalar_context) + assert logit.shape == (B, 327) + assert action_type.shape == (B, ) + assert embedding.shape == (B, cfg.gate_dim) + + logit, output_action_type, embedding = head(lstm_output, scalar_context, action_type) + assert logit.shape == (B, 327) + assert embedding.shape == (B, cfg.gate_dim) + assert output_action_type.eq(action_type).all() + + def test_delay_head(self): + cfg = total_config.model.policy.head.delay_head + head = DelayHead(total_config) + inputs = torch.randn(B, cfg.input_dim) + + logit, delay, embedding = head(inputs) + assert logit.shape == (B, cfg.delay_dim) + assert delay.shape == (B, ) + assert embedding.shape == (B, cfg.input_dim) + + logit, output_delay, embedding = head(inputs, delay) + assert logit.shape == (B, cfg.delay_dim) + assert embedding.shape == (B, cfg.input_dim) + assert output_delay.eq(delay).all() + + def test_queued_head(self): + cfg = total_config.model.policy.head.queued_head + head = QueuedHead(total_config) + inputs = torch.randn(B, cfg.input_dim) + + logit, queued, embedding = head(inputs) + assert logit.shape == (B, cfg.queued_dim) + assert queued.shape == (B, ) + assert embedding.shape == (B, cfg.input_dim) + + logit, output_queued, embedding = head(inputs, queued) + assert logit.shape == (B, cfg.queued_dim) + assert embedding.shape == (B, cfg.input_dim) + assert output_queued.eq(queued).all() + + def test_target_unit_head(self): + cfg = total_config.model.policy.head.target_unit_head + head = TargetUnitHead(total_config) + inputs = torch.randn(B, cfg.input_dim) + entity_embedding = torch.rand(B, ENTITY, cfg.entity_embedding_dim) + entity_num = torch.randint(ENTITY // 2, ENTITY, size=(B, )) + entity_num[-1] = ENTITY + + logit, target_unit = head(inputs, entity_embedding, entity_num) + assert logit.shape == (B, ENTITY) + assert target_unit.shape == (B, ) + + logit, output_target_unit = head(inputs, entity_embedding, entity_num, target_unit) + assert logit.shape == (B, ENTITY) + assert output_target_unit.eq(target_unit).all() + + def test_location_head(self): + cfg = total_config.model.policy.head.location_head + head = LocationHead(total_config) + inputs = torch.randn(B, cfg.input_dim) + Y, X = total_config.model.spatial_y, total_config.model.spatial_x + map_skip = [torch.randn(B, cfg.res_dim, Y // 8, X // 8) for _ in range(cfg.res_num)] + + logit, location = head(inputs, map_skip) + assert logit.shape == (B, Y * X) + assert location.shape == (B, ) + + logit, output_location = head(inputs, map_skip, location) + assert logit.shape == (B, Y * X) + assert output_location.eq(location).all() + + def test_selected_units_head(self): + cfg = total_config.model.policy.head.selected_units_head + head = SelectedUnitsHead(total_config) + inputs = torch.randn(B, cfg.input_dim) + entity_embedding = torch.rand(B, ENTITY, cfg.entity_embedding_dim) + entity_num = torch.randint(ENTITY // 2, ENTITY, size=(B, )) + entity_num[-1] = ENTITY + su_mask = torch.randint(0, 2, size=(B, )).bool() + su_mask[-1] = 1 + + logit, selected_units, embedding, selected_units_num, extra_units = head( + inputs, entity_embedding, entity_num, su_mask=su_mask + ) + N = selected_units_num.max() + assert embedding.shape == (B, cfg.input_dim) + assert logit.shape == (B, N, ENTITY + 1) + assert selected_units.shape == (B, N) + assert selected_units_num.shape == (B, ) + assert extra_units.shape == (B, ENTITY + 1) + + selected_units_num = selected_units_num.clamp(0, 64) + logit, output_selected_units, embedding, selected_units_num, extra_units = head( + inputs, entity_embedding, entity_num, selected_units_num, selected_units, su_mask + ) + N = selected_units_num.max() + assert embedding.shape == (B, cfg.input_dim) + assert logit.shape == (B, N, ENTITY + 1) + assert extra_units is None + assert output_selected_units.eq(selected_units).all() From fd71c467479b46603884a7d626f1fa2168cf1bc2 Mon Sep 17 00:00:00 2001 From: lixuelin Date: Tue, 7 Jun 2022 17:37:44 +0800 Subject: [PATCH 081/229] add learner to test pipeline --- ding/framework/middleware/__init__.py | 1 + .../middleware/league_coordinator.py | 2 +- ding/framework/middleware/league_learner.py | 23 ++-- ding/framework/middleware/tests/__init__.py | 3 +- .../middleware/tests/league_config.py | 4 +- .../middleware/tests/mock_for_test.py | 48 ++++++++ .../middleware/tests/test_league_learner.py | 85 +++++++++++++++ .../middleware/tests/test_league_pipeline.py | 103 +++++++----------- 8 files changed, 190 insertions(+), 79 deletions(-) create mode 100644 ding/framework/middleware/tests/test_league_learner.py diff --git a/ding/framework/middleware/__init__.py b/ding/framework/middleware/__init__.py index 8580fc2caf..62cdf16759 100644 --- a/ding/framework/middleware/__init__.py +++ b/ding/framework/middleware/__init__.py @@ -4,3 +4,4 @@ from .ckpt_handler import CkptSaver from .league_actor import LeagueActor from .league_coordinator import LeagueCoordinator +from .league_learner import LeagueLearner diff --git a/ding/framework/middleware/league_coordinator.py b/ding/framework/middleware/league_coordinator.py index 8db9d9c4e5..27bef09e23 100644 --- a/ding/framework/middleware/league_coordinator.py +++ b/ding/framework/middleware/league_coordinator.py @@ -6,7 +6,7 @@ if TYPE_CHECKING: from ding.framework import Task, Context - from ding.league import BaseLeague + from ding.league.v2 import BaseLeague class LeagueCoordinator: diff --git a/ding/framework/middleware/league_learner.py b/ding/framework/middleware/league_learner.py index 2e82fee82a..7cc805af99 100644 --- a/ding/framework/middleware/league_learner.py +++ b/ding/framework/middleware/league_learner.py @@ -1,32 +1,25 @@ +import os from dataclasses import dataclass +from threading import Lock from time import sleep -from os import path as osp +from typing import TYPE_CHECKING, Callable, Optional + from ding.framework import task, EventEnum from ding.framework.storage import Storage, FileStorage from ding.league.player import PlayerMeta from ding.worker.learner.base_learner import BaseLearner -from typing import TYPE_CHECKING, Callable, Optional -from threading import Lock + if TYPE_CHECKING: from ding.framework import Context from ding.framework.middleware.league_actor import ActorData from ding.league import ActivePlayer - @dataclass class LearnerModel: player_id: str state_dict: dict train_iter: int = 0 - -@dataclass -class LearnerModel: - player_id: str - state_dict: dict - train_iter: int = 0 - - class LeagueLearner: def __init__(self, cfg: dict, policy_fn: Callable, player: "ActivePlayer") -> None: @@ -36,8 +29,8 @@ def __init__(self, cfg: dict, policy_fn: Callable, player: "ActivePlayer") -> No self.player_id = player.player_id self.checkpoint_prefix = cfg.policy.other.league.path_policy self._learner = self._get_learner() - task.on(EventEnum.ACTOR_SEND_DATA.format(player=self.player_id), self._on_actor_data) self._lock = Lock() + task.on(EventEnum.ACTOR_SEND_DATA.format(player=self.player_id), self._on_actor_data) def _on_actor_data(self, actor_data: "ActorData"): with self._lock: @@ -68,8 +61,10 @@ def _get_learner(self) -> BaseLearner: return learner def _save_checkpoint(self) -> Optional[Storage]: + if not os.path.exists(self.checkpoint_prefix): + os.makedirs(self.checkpoint_prefix) storage = FileStorage( - path=osp.join(self.checkpoint_prefix, "{}_{}_ckpt.pth".format(self.player_id, self._learner.train_iter)) + path=os.path.join(self.checkpoint_prefix, "{}_{}_ckpt.pth".format(self.player_id, self._learner.train_iter)) ) storage.save(self._learner.policy.state_dict()) return storage diff --git a/ding/framework/middleware/tests/__init__.py b/ding/framework/middleware/tests/__init__.py index 5bb84e7fe2..54c6b9f76a 100644 --- a/ding/framework/middleware/tests/__init__.py +++ b/ding/framework/middleware/tests/__init__.py @@ -1 +1,2 @@ -from .mock_for_test import MockEnv, MockPolicy, MockHerRewardModel, CONFIG +from .mock_for_test import * +from .league_config import cfg \ No newline at end of file diff --git a/ding/framework/middleware/tests/league_config.py b/ding/framework/middleware/tests/league_config.py index 27a5d9373c..e31def9660 100644 --- a/ding/framework/middleware/tests/league_config.py +++ b/ding/framework/middleware/tests/league_config.py @@ -46,7 +46,7 @@ }, 'multi_gpu': False, 'epoch_per_collect': 10, - 'batch_size': 32, + 'batch_size': 16, 'learning_rate': 1e-05, 'value_weight': 0.5, 'entropy_weight': 0.0, @@ -99,7 +99,7 @@ }, 'league': { 'player_category': ['default'], - 'path_policy': 'league_demo/policy', + 'path_policy': 'league_demo/ckpt', 'active_players': { 'main_player': 2 }, diff --git a/ding/framework/middleware/tests/mock_for_test.py b/ding/framework/middleware/tests/mock_for_test.py index 7fa6cde7aa..0a5ef694ab 100644 --- a/ding/framework/middleware/tests/mock_for_test.py +++ b/ding/framework/middleware/tests/mock_for_test.py @@ -1,10 +1,15 @@ from typing import Union, Any, List, Callable, Dict, Optional from collections import namedtuple +import random import torch import treetensor.numpy as tnp from easydict import EasyDict from unittest.mock import Mock +from ding.league.player import PlayerMeta +from ding.league.v2 import BaseLeague, Job +from ding.framework.storage import FileStorage + obs_dim = [2, 2] action_space = 1 env_num = 2 @@ -116,3 +121,46 @@ def __init__(self) -> None: def estimate(self, episode: List[Dict[str, Any]]) -> List[Dict[str, Any]]: return [[episode[0] for _ in range(self.episode_element_size)]] + + +class MockLeague(BaseLeague): + def __init__(self, cfg) -> None: + super().__init__(cfg) + print(self.active_players) + self.update_payoff_cnt = 0 + self.update_active_player_cnt = 0 + self.create_historical_player_cnt = 0 + self.get_job_info_cnt = 0 + + def update_payoff(self, job): + self.update_payoff_cnt += 1 + + def update_active_player(self, meta): + self.update_active_player_cnt += 1 + + def create_historical_player(self, meta): + self.create_historical_player_cnt += 1 + + def get_job_info(self, player_id): + self.get_job_info_cnt += 1 + other_players = [i for i in self.active_players_ids if i != player_id] + another_palyer = random.choice(other_players) + return Job( + launch_player=player_id, + players=[ + PlayerMeta(player_id=player_id, checkpoint=FileStorage(path=None), total_agent_step=0), + PlayerMeta(player_id=another_palyer, checkpoint=FileStorage(path=None), total_agent_step=0) + ] + ) + + +class MockLogger(): + + def add_scalar(*args): + pass + + def close(*args): + pass + + def flush(*args): + pass diff --git a/ding/framework/middleware/tests/test_league_learner.py b/ding/framework/middleware/tests/test_league_learner.py new file mode 100644 index 0000000000..4918e5492b --- /dev/null +++ b/ding/framework/middleware/tests/test_league_learner.py @@ -0,0 +1,85 @@ +from copy import deepcopy +from time import sleep +import torch +import pytest + +from ding.envs import BaseEnvManager +from ding.model import VAC +from ding.policy import PPOPolicy +from ding.framework import EventEnum +from ding.framework.task import task, Parallel +from ding.framework.middleware import LeagueLearner +from ding.framework.middleware.functional.actor_data import ActorData +from ding.framework.middleware.tests import cfg, MockLeague, MockLogger +from dizoo.league_demo.game_env import GameEnv + + +def prepare_test(): + global cfg + cfg = deepcopy(cfg) + + def env_fn(): + env = BaseEnvManager( + env_fn=[lambda: GameEnv(cfg.env.env_type) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager + ) + env.seed(cfg.seed) + return env + + def policy_fn(): + model = VAC(**cfg.policy.model) + policy = PPOPolicy(cfg.policy, model=model) + return policy + + return cfg, env_fn, policy_fn + +def coordinator_mocker(): + task.on(EventEnum.LEARNER_SEND_META, lambda x: print("test:", x)) + task.on(EventEnum.LEARNER_SEND_MODEL, lambda x: print("test: send model success")) + def _coordinator_mocker(ctx): + sleep(1) + return _coordinator_mocker + +def actor_mocker(league): + def _actor_mocker(ctx): + sleep(1) + obs_size = cfg.policy.model.obs_shape + data = [{ + 'obs': torch.rand(*obs_size), + 'next_obs': torch.rand(*obs_size), + 'done': False, + 'reward': torch.rand(1), + 'logit': torch.rand(1), + 'action': torch.randint(low=0, high=2, size=(1,)), + } for _ in range(32)] + actor_data = ActorData(env_step=0, train_data=data) + n_players = len(league.active_players_ids) + player = league.active_players[(task.router.node_id + 2) % n_players] + print("actor player:", player.player_id) + task.emit(EventEnum.ACTOR_SEND_DATA.format(player=player.player_id), actor_data) + return _actor_mocker + +def _main(): + cfg, env_fn, policy_fn = prepare_test() + league = MockLeague(cfg.policy.other.league) + + with task.start(): + if task.router.node_id == 0: + task.use(coordinator_mocker()) + elif task.router.node_id <= 2: + task.use(actor_mocker(league)) + else: + n_players = len(league.active_players_ids) + player = league.active_players[task.router.node_id % n_players] + learner = LeagueLearner(cfg, policy_fn, player) + learner._learner._tb_logger = MockLogger() + task.use(learner) + task.run(max_step=5) + + +@pytest.mark.unittest +def test_league_learner(): + Parallel.runner(n_parallel_workers=5, protocol="tcp", topology="mesh")(_main) + + +if __name__ == '__main__': + Parallel.runner(n_parallel_workers=5, protocol="tcp", topology="mesh")(_main) diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index 8b2d0f5c75..2801be6974 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -1,21 +1,40 @@ +# from time import sleep +# from boto import config +# import pytest +# from copy import deepcopy + +# from ding.framework.middleware.league_learner import LeagueLearner +# from ding.framework.middleware.tests.league_config import cfg +# from ding.framework.middleware import LeagueActor, LeagueCoordinator +# from ding.league.player import PlayerMeta, create_player +# from ding.league.v2 import BaseLeague +# from ding.framework.storage import FileStorage + +# from ding.framework.task import task, Parallel +# from ding.league.v2.base_league import Job +# from ding.model import VAC +# from ding.policy.ppo import PPOPolicy +# from dizoo.league_demo.game_env import GameEnv + +from copy import deepcopy from time import sleep +import torch import pytest -from copy import deepcopy -from ding.envs import BaseEnvManager -from ding.framework.middleware.tests.league_config import cfg -from ding.framework.middleware import LeagueActor, LeagueCoordinator -from ding.league.player import PlayerMeta -from ding.framework.storage import FileStorage +import random -from ding.framework.task import task, Parallel -from ding.league.v2.base_league import Job +from ding.envs import BaseEnvManager from ding.model import VAC -from ding.policy.ppo import PPOPolicy +from ding.policy import PPOPolicy +from ding.framework import EventEnum +from ding.framework.task import task, Parallel +from ding.framework.middleware import LeagueCoordinator, LeagueActor, LeagueLearner +from ding.framework.middleware.functional.actor_data import ActorData +from ding.framework.middleware.tests import cfg, MockLeague, MockLogger from dizoo.league_demo.game_env import GameEnv -from unittest.mock import patch -import random +N_ACTORS = 2 +N_LEARNERS = 2 def prepare_test(): global cfg @@ -35,67 +54,29 @@ def policy_fn(): return cfg, env_fn, policy_fn - -class MockLeague: - - def __init__(self): - self.active_players_ids = ["main_player_default_0", "main_player_default_1", "main_player_default_2"] - self.update_payoff_cnt = 0 - self.update_active_player_cnt = 0 - self.create_historical_player_cnt = 0 - self.get_job_info_cnt = 0 - - def update_payoff(self, job): - self.update_payoff_cnt += 1 - - def update_active_player(self, meta): - self.update_active_player_cnt += 1 - - def create_historical_player(self, meta): - self.create_historical_player_cnt += 1 - - def get_job_info(self, player_id): - self.get_job_info_cnt += 1 - other_players = [i for i in self.active_players_ids if i != player_id] - another_palyer = random.choice(other_players) - return Job( - launch_player=player_id, - players=[ - PlayerMeta(player_id=player_id, checkpoint=FileStorage(path=None), total_agent_step=0), - PlayerMeta(player_id=another_palyer, checkpoint=FileStorage(path=None), total_agent_step=0) - ] - ) - - -N_ACTORS = 3 - - def _main(): cfg, env_fn, policy_fn = prepare_test() + league = MockLeague(cfg.policy.other.league) with task.start(async_mode=True): if task.router.node_id == 0: - league = MockLeague() - coordinator = LeagueCoordinator(league) - sleep(2) - with patch("ding.league.BaseLeague", MockLeague): - task.use(coordinator) - sleep(15) - # print(league.get_job_info_cnt) - assert league.get_job_info_cnt == N_ACTORS - assert league.update_payoff_cnt == N_ACTORS - else: + task.use(LeagueCoordinator(league)) + elif task.router.node_id <= N_ACTORS: task.use(LeagueActor(cfg, env_fn, policy_fn)) + else: + n_players = len(league.active_players_ids) + player = league.active_players[task.router.node_id % n_players] + learner = LeagueLearner(cfg, policy_fn, player) + learner._learner._tb_logger = MockLogger() + task.use(learner) - task.run(max_step=1) + task.run(max_step=10) @pytest.mark.unittest def test_league_actor(): - Parallel.runner(n_parallel_workers=N_ACTORS + 1, protocol="tcp", topology="mesh")(_main) + Parallel.runner(n_parallel_workers=N_ACTORS + N_LEARNERS + 1, protocol="tcp", topology="mesh")(_main) if __name__ == '__main__': - Parallel.runner(n_parallel_workers=N_ACTORS + 1, protocol="tcp", topology="mesh")(_main) -# replicas = 10 -# un parallel worker 改成1 + Parallel.runner(n_parallel_workers=N_ACTORS + N_LEARNERS + 1, protocol="tcp", topology="mesh")(_main) \ No newline at end of file From 77dc67e0eef35385e8b2ba0ee4a6292aaed610b2 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 8 Jun 2022 09:45:32 +0800 Subject: [PATCH 082/229] change vars names, get rid of cache_pool --- ding/framework/middleware/collector.py | 11 +++----- .../middleware/functional/collector.py | 27 +++++++++---------- .../middleware/tests/test_league_actor.py | 5 ++-- 3 files changed, 19 insertions(+), 24 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 5b52e407eb..67ff3576d9 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -20,9 +20,6 @@ def __init__(self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int, m self.env = env self.env_num = self.env.env_num - self.obs_pool = CachePool('obs', self.env_num, deepcopy=self.cfg.deepcopy_obs) - self.policy_output_pool = CachePool('policy_output', self.env_num) - self.total_envstep_count = 0 self.end_flag = False self.n_rollout_samples = n_rollout_samples @@ -31,9 +28,9 @@ def __init__(self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int, m self.all_policies = all_policies self._battle_inferencer = task.wrap( - battle_inferencer(self.cfg, self.env, self.obs_pool, self.policy_output_pool) + battle_inferencer(self.cfg, self.env) ) - self._battle_rolloutor = task.wrap(battle_rolloutor(self.cfg, self.env, self.obs_pool, self.policy_output_pool)) + self._battle_rolloutor = task.wrap(battle_rolloutor(self.cfg, self.env)) self._job_data_sender = task.wrap(job_data_sender(self.streaming_sampling_flag, self.n_rollout_samples)) @@ -75,7 +72,7 @@ def __call__(self, ctx: "BattleContext") -> None: the former is a list containing collected episodes if not get_train_sample, \ otherwise, return train_samples split by unroll_len. """ - ctx.envstep = self.total_envstep_count + ctx.env_step = self.total_envstep_count if ctx.n_episode is None: if ctx._default_n_episode is None: raise RuntimeError("Please specify collect n_episode") @@ -99,7 +96,7 @@ def __call__(self, ctx: "BattleContext") -> None: self._battle_inferencer(ctx) self._battle_rolloutor(ctx) - self.total_envstep_count = ctx.envstep + self.total_envstep_count = ctx.env_step self._job_data_sender(ctx) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 4af6e82dd9..78cb1eef36 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -2,6 +2,7 @@ from easydict import EasyDict from functools import reduce import treetensor.torch as ttorch +from ding import policy from ding.envs import BaseEnvManager from ding.policy import Policy import torch @@ -167,7 +168,7 @@ def job_data_sender(streaming_sampling_flag: bool, n_rollout_samples: int): def _job_data_sender(ctx: "BattleContext"): if not ctx.job.is_eval and streaming_sampling_flag is True and len(ctx.train_data[0]) >= n_rollout_samples: - actor_data = ActorData(env_step=ctx.envstep, train_data=ctx.train_data[0]) + actor_data = ActorData(env_step=ctx.env_step, train_data=ctx.train_data[0]) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=ctx.job.launch_player), actor_data) ctx.train_data = [[] for _ in range(ctx.agent_num)] @@ -175,54 +176,54 @@ def _job_data_sender(ctx: "BattleContext"): ctx.job.result = [e['result'] for e in ctx.episode_info[0]] task.emit(EventEnum.ACTOR_FINISH_JOB, ctx.job) if not ctx.job.is_eval and len(ctx.train_data[0]) > 0: - actor_data = ActorData(env_step=ctx.envstep, train_data=ctx.train_data[0]) + actor_data = ActorData(env_step=ctx.env_step, train_data=ctx.train_data[0]) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=ctx.job.launch_player), actor_data) ctx.train_data = [[] for _ in range(ctx.agent_num)] return _job_data_sender - -def battle_inferencer(cfg: EasyDict, env: BaseEnvManager, obs_pool: CachePool, policy_output_pool: CachePool): +import time +def battle_inferencer(cfg: EasyDict, env: BaseEnvManager): def _battle_inferencer(ctx: "BattleContext"): # Get current env obs. obs = env.ready_obs + # the role of remain_episode is to mask necessary rollouts, avoid processing unnecessary data new_available_env_id = set(obs.keys()).difference(ctx.ready_env_id) ctx.ready_env_id = ctx.ready_env_id.union(set(list(new_available_env_id)[:ctx.remain_episode])) ctx.remain_episode -= min(len(new_available_env_id), ctx.remain_episode) obs = {env_id: obs[env_id] for env_id in ctx.ready_env_id} # Policy forward. - obs_pool.update(obs) if cfg.transform_obs: obs = to_tensor(obs, dtype=torch.float32) obs = dicts_to_lists(obs) - policy_output = [p.forward(obs[i], **ctx.collect_kwargs) for i, p in enumerate(ctx.current_policies)] - policy_output_pool.update(policy_output) - + inference_output = [p.forward(obs[i], **ctx.collect_kwargs) for i, p in enumerate(ctx.current_policies)] + ctx.obs = obs + ctx.inference_output = inference_output # Interact with env. actions = {} for env_id in ctx.ready_env_id: actions[env_id] = [] - for output in policy_output: + for output in inference_output: actions[env_id].append(output[env_id]['action']) ctx.actions = to_ndarray(actions) return _battle_inferencer -def battle_rolloutor(cfg: EasyDict, env: BaseEnvManager, obs_pool: CachePool, policy_output_pool: CachePool): +def battle_rolloutor(cfg: EasyDict, env: BaseEnvManager): def _battle_rolloutor(ctx: "BattleContext"): timesteps = env.step(ctx.actions) for env_id, timestep in timesteps.items(): - ctx.envstep += 1 + ctx.env_step += 1 for policy_id, _ in enumerate(ctx.current_policies): policy_timestep_data = [d[policy_id] if not isinstance(d, bool) else d for d in timestep] policy_timestep = type(timestep)(*policy_timestep_data) transition = ctx.current_policies[policy_id].process_transition( - obs_pool[env_id][policy_id], policy_output_pool[env_id][policy_id], policy_timestep + ctx.obs[policy_id][env_id], ctx.inference_output[policy_id][env_id], policy_timestep ) transition['collect_iter'] = ctx.train_iter ctx.traj_buffer[env_id][policy_id].append(transition) @@ -242,8 +243,6 @@ def _battle_rolloutor(ctx: "BattleContext"): p.reset([env_id]) for i in range(ctx.agent_num): ctx.traj_buffer[env_id][i].clear() - obs_pool.reset(env_id) - policy_output_pool.reset(env_id) ctx.ready_env_id.remove(env_id) for policy_id in range(ctx.agent_num): ctx.episode_info[policy_id].append(timestep.info[policy_id]) diff --git a/ding/framework/middleware/tests/test_league_actor.py b/ding/framework/middleware/tests/test_league_actor.py index d71b9b0f3f..f585720eb8 100644 --- a/ding/framework/middleware/tests/test_league_actor.py +++ b/ding/framework/middleware/tests/test_league_actor.py @@ -62,6 +62,7 @@ def test_actor(): def on_actor_greeting(actor_id): assert actor_id == ACTOR_ID testcases["on_actor_greeting"] = True + task.emit(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=ACTOR_ID), job) def on_actor_job(job_: Job): assert job_.launch_player == job.launch_player @@ -77,8 +78,6 @@ def on_actor_data(actor_data): def _test_actor(ctx): sleep(0.3) - task.emit(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=ACTOR_ID), job) - sleep(0.3) task.emit( EventEnum.LEARNER_SEND_MODEL, @@ -86,7 +85,7 @@ def _test_actor(ctx): player_id='main_player_default_0', state_dict=policy.learn_mode.state_dict(), train_iter=0 ) ) - sleep(5) + sleep(10) try: print(testcases) assert all(testcases.values()) From f95113ab36f4ad6e96ed1be53474c476e61b2cea Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 8 Jun 2022 15:20:13 +0800 Subject: [PATCH 083/229] change the position of traj_buffers initialization --- ding/framework/middleware/collector.py | 11 +++- .../middleware/functional/collector.py | 66 ++++++++++++++----- ding/framework/middleware/league_actor.py | 3 +- 3 files changed, 59 insertions(+), 21 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 67ff3576d9..346319e3b3 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -5,6 +5,7 @@ from ding.framework import task, EventEnum from .functional import inferencer, rolloutor, TransitionList, battle_inferencer, battle_rolloutor, job_data_sender from typing import Dict +from ding.worker.collector.base_serial_collector import TrajBuffer # if TYPE_CHECKING: from ding.framework import OnlineRLContext, BattleContext @@ -30,7 +31,6 @@ def __init__(self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int, m self._battle_inferencer = task.wrap( battle_inferencer(self.cfg, self.env) ) - self._battle_rolloutor = task.wrap(battle_rolloutor(self.cfg, self.env)) self._job_data_sender = task.wrap(job_data_sender(self.streaming_sampling_flag, self.n_rollout_samples)) @@ -83,8 +83,13 @@ def __call__(self, ctx: "BattleContext") -> None: if ctx.collect_kwargs is None: ctx.collect_kwargs = {} - if self.env.closed: - self.env.launch() + # traj_buffer is {env_id: {policy_id: TrajBuffer}}, is used to store traj_len pieces of transitions + self.traj_buffer = { + env_id: {policy_id: TrajBuffer(maxlen=ctx.traj_len) + for policy_id in range(ctx.agent_num)} + for env_id in range(self.env_num) + } + self._battle_rolloutor = task.wrap(battle_rolloutor(self.cfg, self.env, self.traj_buffer)) ctx.collected_episode = 0 ctx.train_data = [[] for _ in range(ctx.agent_num)] diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 78cb1eef36..65fade9044 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -8,11 +8,10 @@ import torch from ding.utils import dicts_to_lists from ding.torch_utils import to_tensor, to_ndarray -from ding.worker.collector.base_serial_collector import CachePool, TrajBuffer, to_tensor_transitions -from threading import Lock -from ding.league.player import PlayerMeta +from ding.worker.collector.base_serial_collector import TrajBuffer, to_tensor_transitions from ding.framework import task, EventEnum from .actor_data import ActorData +from typing import Dict # if TYPE_CHECKING: from ding.framework import OnlineRLContext, BattleContext @@ -150,13 +149,6 @@ def _policy_resetter(ctx: "BattleContext"): ctx._default_n_episode = ctx.current_policies[0].get_attribute('cfg').collect.get('n_episode', None) ctx.agent_num = len(ctx.current_policies) ctx.traj_len = float("inf") - # traj_buffer is {env_id: {policy_id: TrajBuffer}}, is used to store traj_len pieces of transitions - ctx.traj_buffer = { - env_id: {policy_id: TrajBuffer(maxlen=ctx.traj_len) - for policy_id in range(ctx.agent_num)} - for env_id in range(env_num) - } - for p in ctx.current_policies: p.reset() else: @@ -187,6 +179,10 @@ def _job_data_sender(ctx: "BattleContext"): def battle_inferencer(cfg: EasyDict, env: BaseEnvManager): def _battle_inferencer(ctx: "BattleContext"): + + if env.closed: + env.launch() + # Get current env obs. obs = env.ready_obs # the role of remain_episode is to mask necessary rollouts, avoid processing unnecessary data @@ -213,36 +209,74 @@ def _battle_inferencer(ctx: "BattleContext"): return _battle_inferencer -def battle_rolloutor(cfg: EasyDict, env: BaseEnvManager): +class BattleTransitionList: + + def __init__(self, env_num: int, agent_num: int) -> None: + self.env_num = env_num + self.agent_num = agent_num + self._transitions = [[[] for _ in range(agent_num)] for _ in range(env_num)] + self._done_idx = [[] for _ in range(env_num)] + + def append(self, env_id: int, policy_id: int, transition: Any) -> None: + self._transitions[env_id].append(transition) + if transition.done: + self._done_idx[env_id].append(len(self._transitions[env_id])) + + def to_trajectories(self) -> Tuple[List[Any], List[int]]: + trajectories = sum(self._transitions, []) + lengths = [len(t) for t in self._transitions] + trajectory_end_idx = [reduce(lambda x, y: x + y, lengths[:i + 1]) for i in range(len(lengths))] + trajectory_end_idx = [t - 1 for t in trajectory_end_idx] + return trajectories, trajectory_end_idx + + def to_episodes(self) -> List[List[Any]]: + episodes = [] + for env_id in range(self.env_num): + last_idx = 0 + for done_idx in self._done_idx[env_id]: + episodes.append(self._transitions[env_id][last_idx:done_idx]) + last_idx = done_idx + return episodes + + def clear(self): + for item in self._transitions: + item.clear() + for item in self._done_idx: + item.clear() + + +def battle_rolloutor(cfg: EasyDict, env: BaseEnvManager, traj_buffer: Dict): def _battle_rolloutor(ctx: "BattleContext"): timesteps = env.step(ctx.actions) + ctx.env_step += len(timesteps) for env_id, timestep in timesteps.items(): - ctx.env_step += 1 for policy_id, _ in enumerate(ctx.current_policies): policy_timestep_data = [d[policy_id] if not isinstance(d, bool) else d for d in timestep] policy_timestep = type(timestep)(*policy_timestep_data) transition = ctx.current_policies[policy_id].process_transition( ctx.obs[policy_id][env_id], ctx.inference_output[policy_id][env_id], policy_timestep ) + # transition = ttorch.as_tensor(transition) + # transition.collect_train_iter = ttorch.as_tensor([ctx.train_iter]) transition['collect_iter'] = ctx.train_iter - ctx.traj_buffer[env_id][policy_id].append(transition) + traj_buffer[env_id][policy_id].append(transition) # If env is done, prepare data if timestep.done: - transitions = to_tensor_transitions(ctx.traj_buffer[env_id][policy_id]) + transitions = to_tensor_transitions(traj_buffer[env_id][policy_id]) if cfg.get_train_sample: train_sample = ctx.current_policies[policy_id].get_train_sample(transitions) ctx.train_data[policy_id].extend(train_sample) else: ctx.train_data[policy_id].append(transitions) - ctx.traj_buffer[env_id][policy_id].clear() + traj_buffer[env_id][policy_id].clear() if timestep.done: ctx.collected_episode += 1 for i, p in enumerate(ctx.current_policies): p.reset([env_id]) for i in range(ctx.agent_num): - ctx.traj_buffer[env_id][i].clear() + traj_buffer[env_id][i].clear() ctx.ready_env_id.remove(env_id) for policy_id in range(ctx.agent_num): ctx.episode_info[policy_id].append(timestep.info[policy_id]) diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 5562e2b4a7..fb1a3e77f5 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -26,8 +26,7 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.env_fn = env_fn self.env_num = env_fn().env_num self.policy_fn = policy_fn - # self.n_rollout_samples = self.cfg.policy.collect.get("n_rollout_samples") or 0 - self.n_rollout_samples = 64 + self.n_rollout_samples = self.cfg.policy.collect.get("n_rollout_samples") or 0 self._collectors: Dict[str, BattleCollector] = {} self.all_policies: Dict[str, "Policy.collect_function"] = {} task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), self._on_league_job) From 7d5c112c0abf6e45d34e95afc44407ce461d0c0b Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 8 Jun 2022 15:39:13 +0800 Subject: [PATCH 084/229] change a bit rolloutor --- ding/framework/middleware/functional/collector.py | 14 +++++--------- 1 file changed, 5 insertions(+), 9 deletions(-) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 65fade9044..a0b855ef55 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -218,9 +218,9 @@ def __init__(self, env_num: int, agent_num: int) -> None: self._done_idx = [[] for _ in range(env_num)] def append(self, env_id: int, policy_id: int, transition: Any) -> None: - self._transitions[env_id].append(transition) - if transition.done: - self._done_idx[env_id].append(len(self._transitions[env_id])) + self._transitions[env_id][policy_id].append(transition) + if transition.done and policy_id == 0: + self._done_idx[env_id].append(len(self._transitions[env_id][policy_id])) def to_trajectories(self) -> Tuple[List[Any], List[int]]: trajectories = sum(self._transitions, []) @@ -270,15 +270,11 @@ def _battle_rolloutor(ctx: "BattleContext"): else: ctx.train_data[policy_id].append(transitions) traj_buffer[env_id][policy_id].clear() + ctx.current_policies[policy_id].reset([env_id]) + ctx.episode_info[policy_id].append(timestep.info[policy_id]) if timestep.done: ctx.collected_episode += 1 - for i, p in enumerate(ctx.current_policies): - p.reset([env_id]) - for i in range(ctx.agent_num): - traj_buffer[env_id][i].clear() ctx.ready_env_id.remove(env_id) - for policy_id in range(ctx.agent_num): - ctx.episode_info[policy_id].append(timestep.info[policy_id]) return _battle_rolloutor From bc8c332f315bf2c3274af400f9d3dc0c0319d5e0 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 8 Jun 2022 21:33:33 +0800 Subject: [PATCH 085/229] change the style to 1.0 middleware --- ding/framework/context.py | 12 +++ ding/framework/middleware/collector.py | 50 +++------- .../middleware/functional/__init__.py | 2 +- .../middleware/functional/collector.py | 95 +------------------ ding/framework/middleware/league_actor.py | 54 +++++++---- .../middleware/tests/league_config.py | 3 +- .../middleware/tests/test_league_actor.py | 5 +- .../tests/test_league_actor_one_process.py | 3 +- .../middleware/tests/test_league_pipeline.py | 3 +- 9 files changed, 79 insertions(+), 148 deletions(-) diff --git a/ding/framework/context.py b/ding/framework/context.py index d5dd2da9a9..7ead2dd35b 100644 --- a/ding/framework/context.py +++ b/ding/framework/context.py @@ -80,3 +80,15 @@ class BattleContext(Context): def __init__(self, *args, **kwargs) -> None: super().__init__(*args, **kwargs) self.__dict__ = self + self.n_episode = None + self.train_iter = 0 + self.job = None + self.collect_kwargs = {} + self.env_episode = 0 + self.episodes = [] + self.episode_info = [] + self.ready_env_id = set() + self.agent_num = 2 + self.job_finish = False + self.traj_len = float("inf") + self.current_policies = [] diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 346319e3b3..fceb5c99fa 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -2,19 +2,17 @@ from easydict import EasyDict from ding.policy import Policy, get_random_policy from ding.envs import BaseEnvManager -from ding.framework import task, EventEnum -from .functional import inferencer, rolloutor, TransitionList, battle_inferencer, battle_rolloutor, job_data_sender +from ding.framework import task +from .functional import inferencer, rolloutor, TransitionList, battle_inferencer, battle_rolloutor from typing import Dict -from ding.worker.collector.base_serial_collector import TrajBuffer # if TYPE_CHECKING: from ding.framework import OnlineRLContext, BattleContext -from ding.worker.collector.base_serial_collector import CachePool class BattleCollector: - def __init__(self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int, model_dict: Dict, all_policies: Dict): + def __init__(self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int, model_dict: Dict, all_policies: Dict, agent_num: int): self.cfg = cfg self.end_flag = False # self._reset(env) @@ -24,15 +22,15 @@ def __init__(self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int, m self.total_envstep_count = 0 self.end_flag = False self.n_rollout_samples = n_rollout_samples - self.streaming_sampling_flag = n_rollout_samples > 0 self.model_dict = model_dict self.all_policies = all_policies + self.agent_num = agent_num self._battle_inferencer = task.wrap( battle_inferencer(self.cfg, self.env) ) - self._job_data_sender = task.wrap(job_data_sender(self.streaming_sampling_flag, self.n_rollout_samples)) - + self._transition_list = [TransitionList(self.env.env_num) for _ in range(self.agent_num)] + self._battle_rolloutor = task.wrap(battle_rolloutor(self.cfg, self.env, self._transition_list)) def __del__(self) -> None: """ @@ -59,8 +57,6 @@ def _update_policies(self, job) -> None: policy.load_state_dict(learner_model.state_dict) self.model_dict[player_id] = None - - def __call__(self, ctx: "BattleContext") -> None: """ Input of ctx: @@ -73,29 +69,7 @@ def __call__(self, ctx: "BattleContext") -> None: otherwise, return train_samples split by unroll_len. """ ctx.env_step = self.total_envstep_count - if ctx.n_episode is None: - if ctx._default_n_episode is None: - raise RuntimeError("Please specify collect n_episode") - else: - ctx.n_episode = ctx._default_n_episode - assert ctx.n_episode >= self.env_num, "Please make sure n_episode >= env_num" - - if ctx.collect_kwargs is None: - ctx.collect_kwargs = {} - - # traj_buffer is {env_id: {policy_id: TrajBuffer}}, is used to store traj_len pieces of transitions - self.traj_buffer = { - env_id: {policy_id: TrajBuffer(maxlen=ctx.traj_len) - for policy_id in range(ctx.agent_num)} - for env_id in range(self.env_num) - } - self._battle_rolloutor = task.wrap(battle_rolloutor(self.cfg, self.env, self.traj_buffer)) - - ctx.collected_episode = 0 - ctx.train_data = [[] for _ in range(ctx.agent_num)] - ctx.episode_info = [[] for _ in range(ctx.agent_num)] - ctx.ready_env_id = set() - ctx.remain_episode = ctx.n_episode + old = ctx.env_episode while True: self._update_policies(ctx.job) self._battle_inferencer(ctx) @@ -103,10 +77,14 @@ def __call__(self, ctx: "BattleContext") -> None: self.total_envstep_count = ctx.env_step - self._job_data_sender(ctx) - - if ctx.collected_episode >= ctx.n_episode: + if (self.n_rollout_samples > 0 and ctx.env_episode - old >= self.n_rollout_samples) or ctx.env_episode >= ctx.n_episode: + ctx.episodes = self._transition_list[0].to_episodes() + for transitions in self._transition_list: + transitions.clear() + if ctx.env_episode >= ctx.n_episode: + ctx.job_finish = True break + diff --git a/ding/framework/middleware/functional/__init__.py b/ding/framework/middleware/functional/__init__.py index 4997ff1da3..c17d0e8a63 100644 --- a/ding/framework/middleware/functional/__init__.py +++ b/ding/framework/middleware/functional/__init__.py @@ -1,7 +1,7 @@ from .trainer import trainer, multistep_trainer from .data_processor import offpolicy_data_fetcher, data_pusher, offline_data_fetcher, offline_data_saver, \ sqil_data_pusher -from .collector import inferencer, rolloutor, TransitionList, policy_resetter, battle_inferencer, battle_rolloutor, job_data_sender +from .collector import inferencer, rolloutor, TransitionList, battle_inferencer, battle_rolloutor from .evaluator import interaction_evaluator from .termination_checker import termination_checker from .pace_controller import pace_controller diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index a0b855ef55..e34e3f14a4 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -2,16 +2,11 @@ from easydict import EasyDict from functools import reduce import treetensor.torch as ttorch -from ding import policy from ding.envs import BaseEnvManager from ding.policy import Policy import torch from ding.utils import dicts_to_lists from ding.torch_utils import to_tensor, to_ndarray -from ding.worker.collector.base_serial_collector import TrajBuffer, to_tensor_transitions -from ding.framework import task, EventEnum -from .actor_data import ActorData -from typing import Dict # if TYPE_CHECKING: from ding.framework import OnlineRLContext, BattleContext @@ -141,41 +136,6 @@ def _rollout(ctx: "OnlineRLContext"): return _rollout -def policy_resetter(env_num: int): - - def _policy_resetter(ctx: "BattleContext"): - if ctx.current_policies is not None: - assert len(ctx.current_policies) > 1, "battle collector needs more than 1 policies" - ctx._default_n_episode = ctx.current_policies[0].get_attribute('cfg').collect.get('n_episode', None) - ctx.agent_num = len(ctx.current_policies) - ctx.traj_len = float("inf") - for p in ctx.current_policies: - p.reset() - else: - raise RuntimeError('ctx.current_policies should not be None') - - return _policy_resetter - -def job_data_sender(streaming_sampling_flag: bool, n_rollout_samples: int): - - def _job_data_sender(ctx: "BattleContext"): - if not ctx.job.is_eval and streaming_sampling_flag is True and len(ctx.train_data[0]) >= n_rollout_samples: - actor_data = ActorData(env_step=ctx.env_step, train_data=ctx.train_data[0]) - task.emit(EventEnum.ACTOR_SEND_DATA.format(player=ctx.job.launch_player), actor_data) - ctx.train_data = [[] for _ in range(ctx.agent_num)] - - if ctx.collected_episode >= ctx.n_episode: - ctx.job.result = [e['result'] for e in ctx.episode_info[0]] - task.emit(EventEnum.ACTOR_FINISH_JOB, ctx.job) - if not ctx.job.is_eval and len(ctx.train_data[0]) > 0: - actor_data = ActorData(env_step=ctx.env_step, train_data=ctx.train_data[0]) - task.emit(EventEnum.ACTOR_SEND_DATA.format(player=ctx.job.launch_player), actor_data) - ctx.train_data = [[] for _ in range(ctx.agent_num)] - - return _job_data_sender - - -import time def battle_inferencer(cfg: EasyDict, env: BaseEnvManager): def _battle_inferencer(ctx: "BattleContext"): @@ -209,43 +169,7 @@ def _battle_inferencer(ctx: "BattleContext"): return _battle_inferencer -class BattleTransitionList: - - def __init__(self, env_num: int, agent_num: int) -> None: - self.env_num = env_num - self.agent_num = agent_num - self._transitions = [[[] for _ in range(agent_num)] for _ in range(env_num)] - self._done_idx = [[] for _ in range(env_num)] - - def append(self, env_id: int, policy_id: int, transition: Any) -> None: - self._transitions[env_id][policy_id].append(transition) - if transition.done and policy_id == 0: - self._done_idx[env_id].append(len(self._transitions[env_id][policy_id])) - - def to_trajectories(self) -> Tuple[List[Any], List[int]]: - trajectories = sum(self._transitions, []) - lengths = [len(t) for t in self._transitions] - trajectory_end_idx = [reduce(lambda x, y: x + y, lengths[:i + 1]) for i in range(len(lengths))] - trajectory_end_idx = [t - 1 for t in trajectory_end_idx] - return trajectories, trajectory_end_idx - - def to_episodes(self) -> List[List[Any]]: - episodes = [] - for env_id in range(self.env_num): - last_idx = 0 - for done_idx in self._done_idx[env_id]: - episodes.append(self._transitions[env_id][last_idx:done_idx]) - last_idx = done_idx - return episodes - - def clear(self): - for item in self._transitions: - item.clear() - for item in self._done_idx: - item.clear() - - -def battle_rolloutor(cfg: EasyDict, env: BaseEnvManager, traj_buffer: Dict): +def battle_rolloutor(cfg: EasyDict, env: BaseEnvManager, transition_list: List): def _battle_rolloutor(ctx: "BattleContext"): timesteps = env.step(ctx.actions) @@ -257,24 +181,15 @@ def _battle_rolloutor(ctx: "BattleContext"): transition = ctx.current_policies[policy_id].process_transition( ctx.obs[policy_id][env_id], ctx.inference_output[policy_id][env_id], policy_timestep ) - # transition = ttorch.as_tensor(transition) - # transition.collect_train_iter = ttorch.as_tensor([ctx.train_iter]) - transition['collect_iter'] = ctx.train_iter - traj_buffer[env_id][policy_id].append(transition) - # If env is done, prepare data + transition = ttorch.as_tensor(transition) + transition.collect_train_iter = ttorch.as_tensor([ctx.train_iter]) + transition_list[policy_id].append(env_id, transition) if timestep.done: - transitions = to_tensor_transitions(traj_buffer[env_id][policy_id]) - if cfg.get_train_sample: - train_sample = ctx.current_policies[policy_id].get_train_sample(transitions) - ctx.train_data[policy_id].extend(train_sample) - else: - ctx.train_data[policy_id].append(transitions) - traj_buffer[env_id][policy_id].clear() ctx.current_policies[policy_id].reset([env_id]) ctx.episode_info[policy_id].append(timestep.info[policy_id]) if timestep.done: - ctx.collected_episode += 1 ctx.ready_env_id.remove(env_id) + ctx.env_episode += 1 return _battle_rolloutor diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index fb1a3e77f5..623ce458a6 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -1,20 +1,16 @@ from ding.framework import task, EventEnum -from time import sleep import logging -from typing import Dict, List, Any, Callable -from dataclasses import dataclass, field -from abc import abstractmethod +from typing import Dict, Callable from easydict import EasyDict -from ding.envs import BaseEnvManager from ding.framework import BattleContext from ding.league.v2.base_league import Job from ding.policy import Policy from ding.framework.middleware.league_learner import LearnerModel from ding.framework.middleware import BattleCollector -from ding.framework.middleware.functional import policy_resetter +from ding.framework.middleware.functional import ActorData from ding.league.player import PlayerMeta from threading import Lock import queue @@ -31,7 +27,6 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.all_policies: Dict[str, "Policy.collect_function"] = {} task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), self._on_league_job) task.on(EventEnum.LEARNER_SEND_MODEL, self._on_learner_model) - self._policy_resetter = task.wrap(policy_resetter(self.env_num)) self.job_queue = queue.Queue() self.model_dict = {} self.model_dict_lock = Lock() @@ -49,12 +44,12 @@ def _on_league_job(self, job: "Job"): """ self.job_queue.put(job) - def _get_collector(self, player_id: str): + def _get_collector(self, player_id: str, agent_num: int): if self._collectors.get(player_id): return self._collectors.get(player_id) cfg = self.cfg env = self.env_fn() - collector = task.wrap(BattleCollector(cfg.policy.collect.collector, env, self.n_rollout_samples, self.model_dict, self.all_policies)) + collector = task.wrap(BattleCollector(cfg.policy.collect.collector, env, self.n_rollout_samples, self.model_dict, self.all_policies, agent_num)) self._collectors[player_id] = collector return collector @@ -88,6 +83,15 @@ def _get_current_policies(self, job): current_policies.append(self._get_policy(player)) if player.player_id == job.launch_player: main_player = player + assert main_player, "can not find active player, on actor: {}".format(task.router.node_id) + + if current_policies is not None: + assert len(current_policies) > 1, "battle collector needs more than 1 policies" + for p in current_policies: + p.reset() + else: + raise RuntimeError('current_policies should not be None') + return main_player, current_policies @@ -97,17 +101,35 @@ def __call__(self, ctx: "BattleContext"): if ctx.job is None: return - collector = self._get_collector(ctx.job.launch_player) + collector = self._get_collector(ctx.job.launch_player, len(ctx.job.players)) main_player, ctx.current_policies = self._get_current_policies(ctx.job) - assert main_player, "can not find active player, on actor: {}".format(task.router.node_id) + ctx.agent_num = len(ctx.current_policies) - self._policy_resetter(ctx) + _default_n_episode = ctx.current_policies[0].get_attribute('cfg').collect.get('n_episode', None) + if ctx.n_episode is None: + if _default_n_episode is None: + raise RuntimeError("Please specify collect n_episode") + else: + ctx.n_episode = _default_n_episode + assert ctx.n_episode >= self.env_num, "Please make sure n_episode >= env_num" - ctx.n_episode = None ctx.train_iter = main_player.total_agent_step - ctx.collect_kwargs = None - - collector(ctx) + ctx.episode_info = [[] for _ in range(ctx.agent_num)] + + ctx.remain_episode = ctx.n_episode + while True: + + collector(ctx) + + if not ctx.job.is_eval: + actor_data = ActorData(env_step=ctx.env_step, train_data=ctx.episodes) + task.emit(EventEnum.ACTOR_SEND_DATA.format(player=ctx.job.launch_player), actor_data) + ctx.episodes = [] + if ctx.job_finish is True: + ctx.job.result = [e['result'] for e in ctx.episode_info[0]] + task.emit(EventEnum.ACTOR_FINISH_JOB, ctx.job) + ctx.episode_info = [[] for _ in range(ctx.agent_num)] + break diff --git a/ding/framework/middleware/tests/league_config.py b/ding/framework/middleware/tests/league_config.py index 27a5d9373c..c905a34025 100644 --- a/ding/framework/middleware/tests/league_config.py +++ b/ding/framework/middleware/tests/league_config.py @@ -78,7 +78,8 @@ 'unroll_len': 1, 'discount_factor': 1.0, 'gae_lambda': 1.0, - 'n_episode': 128 + 'n_episode': 128, + 'n_rollout_samples': 32 }, 'eval': { 'evaluator': { diff --git a/ding/framework/middleware/tests/test_league_actor.py b/ding/framework/middleware/tests/test_league_actor.py index f585720eb8..4c1da29564 100644 --- a/ding/framework/middleware/tests/test_league_actor.py +++ b/ding/framework/middleware/tests/test_league_actor.py @@ -2,6 +2,7 @@ import pytest from copy import deepcopy from ding.envs import BaseEnvManager +from ding.framework.context import BattleContext from ding.framework.middleware.league_learner import LearnerModel from ding.framework.middleware.tests.league_config import cfg from ding.framework.middleware import LeagueActor @@ -49,7 +50,7 @@ def _main(): ) ACTOR_ID = 0 - with task.start(async_mode=True): + with task.start(async_mode=True, ctx=BattleContext()): league_actor = LeagueActor(cfg, env_fn, policy_fn) def test_actor(): @@ -99,7 +100,7 @@ def _test_actor(ctx): elif task.router.node_id == 1: task.use(test_actor()) - task.run() + task.run(max_step=5) @pytest.mark.unittest diff --git a/ding/framework/middleware/tests/test_league_actor_one_process.py b/ding/framework/middleware/tests/test_league_actor_one_process.py index e97610bcf1..f7d66787e3 100644 --- a/ding/framework/middleware/tests/test_league_actor_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_one_process.py @@ -2,6 +2,7 @@ import pytest from copy import deepcopy from ding.envs import BaseEnvManager +from ding.framework.context import BattleContext from ding.framework.middleware.league_learner import LearnerModel from ding.framework.middleware.tests.league_config import cfg from ding.framework.middleware import LeagueActor @@ -42,7 +43,7 @@ def policy_fn(): def test_league_actor(): cfg, env_fn, policy_fn = prepare_test() policy = policy_fn() - with task.start(async_mode=True): + with task.start(async_mode=True, ctx = BattleContext()): league_actor = LeagueActor(cfg=cfg, env_fn=env_fn, policy_fn=policy_fn) def test_actor(): diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index a84a4170a9..b8d7bcf565 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -2,6 +2,7 @@ import pytest from copy import deepcopy from ding.envs import BaseEnvManager +from ding.framework.context import BattleContext from ding.framework.middleware.tests.league_config import cfg from ding.framework.middleware import LeagueActor, LeagueCoordinator from ding.league.player import PlayerMeta @@ -69,7 +70,7 @@ def get_job_info(self, player_id): def _main(): cfg, env_fn, policy_fn = prepare_test() - with task.start(async_mode=True): + with task.start(async_mode=True, ctx=BattleContext()): if task.router.node_id == 0: league = MockLeague() coordinator = LeagueCoordinator(league) From 1078673066c8b4c8014c304a66405400b4eafa80 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 8 Jun 2022 23:18:29 +0800 Subject: [PATCH 086/229] change a bit --- ding/framework/middleware/__init__.py | 2 +- ding/framework/middleware/collector.py | 17 ++++++----------- .../middleware/functional/collector.py | 4 ++-- ding/framework/middleware/league_actor.py | 10 ++++------ 4 files changed, 13 insertions(+), 20 deletions(-) diff --git a/ding/framework/middleware/__init__.py b/ding/framework/middleware/__init__.py index 8580fc2caf..0c50f850de 100644 --- a/ding/framework/middleware/__init__.py +++ b/ding/framework/middleware/__init__.py @@ -1,5 +1,5 @@ from .functional import * -from .collector import StepCollector, EpisodeCollector, BattleCollector +from .collector import StepCollector, EpisodeCollector, BattleEpisodeCollector from .learner import OffPolicyLearner, HERLearner from .ckpt_handler import CkptSaver from .league_actor import LeagueActor diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index fceb5c99fa..cfb7b07563 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -10,7 +10,7 @@ from ding.framework import OnlineRLContext, BattleContext -class BattleCollector: +class BattleEpisodeCollector: def __init__(self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int, model_dict: Dict, all_policies: Dict, agent_num: int): self.cfg = cfg @@ -20,17 +20,14 @@ def __init__(self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int, m self.env_num = self.env.env_num self.total_envstep_count = 0 - self.end_flag = False self.n_rollout_samples = n_rollout_samples self.model_dict = model_dict self.all_policies = all_policies self.agent_num = agent_num - self._battle_inferencer = task.wrap( - battle_inferencer(self.cfg, self.env) - ) - self._transition_list = [TransitionList(self.env.env_num) for _ in range(self.agent_num)] - self._battle_rolloutor = task.wrap(battle_rolloutor(self.cfg, self.env, self._transition_list)) + self._battle_inferencer = task.wrap(battle_inferencer(self.cfg, self.env)) + self._transitions_list = [TransitionList(self.env.env_num) for _ in range(self.agent_num)] + self._battle_rolloutor = task.wrap(battle_rolloutor(self.cfg, self.env, self._transitions_list)) def __del__(self) -> None: """ @@ -78,14 +75,12 @@ def __call__(self, ctx: "BattleContext") -> None: self.total_envstep_count = ctx.env_step if (self.n_rollout_samples > 0 and ctx.env_episode - old >= self.n_rollout_samples) or ctx.env_episode >= ctx.n_episode: - ctx.episodes = self._transition_list[0].to_episodes() - for transitions in self._transition_list: + ctx.episodes = self._transitions_list[0].to_episodes() + for transitions in self._transitions_list: transitions.clear() if ctx.env_episode >= ctx.n_episode: ctx.job_finish = True break - - diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index e34e3f14a4..ebea99e355 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -169,7 +169,7 @@ def _battle_inferencer(ctx: "BattleContext"): return _battle_inferencer -def battle_rolloutor(cfg: EasyDict, env: BaseEnvManager, transition_list: List): +def battle_rolloutor(cfg: EasyDict, env: BaseEnvManager, transitions_list: List): def _battle_rolloutor(ctx: "BattleContext"): timesteps = env.step(ctx.actions) @@ -183,7 +183,7 @@ def _battle_rolloutor(ctx: "BattleContext"): ) transition = ttorch.as_tensor(transition) transition.collect_train_iter = ttorch.as_tensor([ctx.train_iter]) - transition_list[policy_id].append(env_id, transition) + transitions_list[policy_id].append(env_id, transition) if timestep.done: ctx.current_policies[policy_id].reset([env_id]) ctx.episode_info[policy_id].append(timestep.info[policy_id]) diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 623ce458a6..fba5eef506 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -9,7 +9,7 @@ from ding.league.v2.base_league import Job from ding.policy import Policy from ding.framework.middleware.league_learner import LearnerModel -from ding.framework.middleware import BattleCollector +from ding.framework.middleware import BattleEpisodeCollector from ding.framework.middleware.functional import ActorData from ding.league.player import PlayerMeta from threading import Lock @@ -23,7 +23,7 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.env_num = env_fn().env_num self.policy_fn = policy_fn self.n_rollout_samples = self.cfg.policy.collect.get("n_rollout_samples") or 0 - self._collectors: Dict[str, BattleCollector] = {} + self._collectors: Dict[str, BattleEpisodeCollector] = {} self.all_policies: Dict[str, "Policy.collect_function"] = {} task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), self._on_league_job) task.on(EventEnum.LEARNER_SEND_MODEL, self._on_learner_model) @@ -49,7 +49,7 @@ def _get_collector(self, player_id: str, agent_num: int): return self._collectors.get(player_id) cfg = self.cfg env = self.env_fn() - collector = task.wrap(BattleCollector(cfg.policy.collect.collector, env, self.n_rollout_samples, self.model_dict, self.all_policies, agent_num)) + collector = task.wrap(BattleEpisodeCollector(cfg.policy.collect.collector, env, self.n_rollout_samples, self.model_dict, self.all_policies, agent_num)) self._collectors[player_id] = collector return collector @@ -116,13 +116,11 @@ def __call__(self, ctx: "BattleContext"): ctx.train_iter = main_player.total_agent_step ctx.episode_info = [[] for _ in range(ctx.agent_num)] - ctx.remain_episode = ctx.n_episode while True: - collector(ctx) - if not ctx.job.is_eval: + if not ctx.job.is_eval and len(ctx.episodes) > 0: actor_data = ActorData(env_step=ctx.env_step, train_data=ctx.episodes) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=ctx.job.launch_player), actor_data) ctx.episodes = [] From d3fcc5171835bb34cb43c508dcf3ff59d9ca5249 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 8 Jun 2022 23:35:08 +0800 Subject: [PATCH 087/229] change a bit --- ding/framework/middleware/collector.py | 2 +- ding/framework/middleware/league_actor.py | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index cfb7b07563..4c690303c4 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -75,8 +75,8 @@ def __call__(self, ctx: "BattleContext") -> None: self.total_envstep_count = ctx.env_step if (self.n_rollout_samples > 0 and ctx.env_episode - old >= self.n_rollout_samples) or ctx.env_episode >= ctx.n_episode: - ctx.episodes = self._transitions_list[0].to_episodes() for transitions in self._transitions_list: + ctx.episodes.append(transitions.to_episodes()) transitions.clear() if ctx.env_episode >= ctx.n_episode: ctx.job_finish = True diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index fba5eef506..578afb0782 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -120,8 +120,8 @@ def __call__(self, ctx: "BattleContext"): while True: collector(ctx) - if not ctx.job.is_eval and len(ctx.episodes) > 0: - actor_data = ActorData(env_step=ctx.env_step, train_data=ctx.episodes) + if not ctx.job.is_eval and len(ctx.episodes[0]) > 0: + actor_data = ActorData(env_step=ctx.env_step, train_data=ctx.episodes[0]) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=ctx.job.launch_player), actor_data) ctx.episodes = [] if ctx.job_finish is True: From 0dc1c5f3bb73998c946603f6bb8709a7bb504e03 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 8 Jun 2022 23:50:54 +0800 Subject: [PATCH 088/229] change variable name --- ding/framework/context.py | 2 ++ ding/framework/middleware/__init__.py | 2 +- ding/framework/middleware/collector.py | 4 ++-- ding/framework/middleware/functional/collector.py | 1 + ding/framework/middleware/league_actor.py | 2 +- 5 files changed, 7 insertions(+), 4 deletions(-) diff --git a/ding/framework/context.py b/ding/framework/context.py index 7ead2dd35b..be8ef2482f 100644 --- a/ding/framework/context.py +++ b/ding/framework/context.py @@ -92,3 +92,5 @@ def __init__(self, *args, **kwargs) -> None: self.job_finish = False self.traj_len = float("inf") self.current_policies = [] + self.env_step = 0 + self.total_envstep_count = 0 diff --git a/ding/framework/middleware/__init__.py b/ding/framework/middleware/__init__.py index 0c50f850de..ed4075492e 100644 --- a/ding/framework/middleware/__init__.py +++ b/ding/framework/middleware/__init__.py @@ -1,5 +1,5 @@ from .functional import * -from .collector import StepCollector, EpisodeCollector, BattleEpisodeCollector +from .collector import StepCollector, EpisodeCollector, BattleEpisodeCollector#, BattleStepCollector from .learner import OffPolicyLearner, HERLearner from .ckpt_handler import CkptSaver from .league_actor import LeagueActor diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 4c690303c4..a1acdc9d2f 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -65,14 +65,14 @@ def __call__(self, ctx: "BattleContext") -> None: the former is a list containing collected episodes if not get_train_sample, \ otherwise, return train_samples split by unroll_len. """ - ctx.env_step = self.total_envstep_count + ctx.total_envstep_count = self.total_envstep_count old = ctx.env_episode while True: self._update_policies(ctx.job) self._battle_inferencer(ctx) self._battle_rolloutor(ctx) - self.total_envstep_count = ctx.env_step + self.total_envstep_count = ctx.total_envstep_count if (self.n_rollout_samples > 0 and ctx.env_episode - old >= self.n_rollout_samples) or ctx.env_episode >= ctx.n_episode: for transitions in self._transitions_list: diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index ebea99e355..2b40f70358 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -173,6 +173,7 @@ def battle_rolloutor(cfg: EasyDict, env: BaseEnvManager, transitions_list: List) def _battle_rolloutor(ctx: "BattleContext"): timesteps = env.step(ctx.actions) + ctx.total_envstep_count += len(timesteps) ctx.env_step += len(timesteps) for env_id, timestep in timesteps.items(): for policy_id, _ in enumerate(ctx.current_policies): diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 578afb0782..2c61d8d8cb 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -121,7 +121,7 @@ def __call__(self, ctx: "BattleContext"): collector(ctx) if not ctx.job.is_eval and len(ctx.episodes[0]) > 0: - actor_data = ActorData(env_step=ctx.env_step, train_data=ctx.episodes[0]) + actor_data = ActorData(env_step=ctx.total_envstep_count, train_data=ctx.episodes[0]) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=ctx.job.launch_player), actor_data) ctx.episodes = [] if ctx.job_finish is True: From 5944584cafc01bc67182a7d94b1b4961df8f3318 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Thu, 9 Jun 2022 00:37:17 +0800 Subject: [PATCH 089/229] add step collector and step actor --- ding/framework/context.py | 9 ++ ding/framework/middleware/__init__.py | 4 +- ding/framework/middleware/collector.py | 75 ++++++++++ ding/framework/middleware/league_actor.py | 131 +++++++++++++++++- .../middleware/tests/league_config.py | 4 +- .../middleware/tests/test_league_actor.py | 2 +- .../tests/test_league_actor_one_process.py | 4 +- .../middleware/tests/test_league_pipeline.py | 2 +- 8 files changed, 223 insertions(+), 8 deletions(-) diff --git a/ding/framework/context.py b/ding/framework/context.py index be8ef2482f..4113ea5c7b 100644 --- a/ding/framework/context.py +++ b/ding/framework/context.py @@ -94,3 +94,12 @@ def __init__(self, *args, **kwargs) -> None: self.current_policies = [] self.env_step = 0 self.total_envstep_count = 0 + self.trajectories_list = [] + self.trajectory_end_idx_list = [] + self.trajectories = [] + self.trajectory_end_idx = None + + self.remain_episode = 0 + self.n_sample = 1 + self.unroll_len = 1 + self.train_data = None diff --git a/ding/framework/middleware/__init__.py b/ding/framework/middleware/__init__.py index ed4075492e..6b0e33141e 100644 --- a/ding/framework/middleware/__init__.py +++ b/ding/framework/middleware/__init__.py @@ -1,6 +1,6 @@ from .functional import * -from .collector import StepCollector, EpisodeCollector, BattleEpisodeCollector#, BattleStepCollector +from .collector import StepCollector, EpisodeCollector, BattleEpisodeCollector, BattleStepCollector from .learner import OffPolicyLearner, HERLearner from .ckpt_handler import CkptSaver -from .league_actor import LeagueActor +from .league_actor import LeagueActor, StepLeagueActor from .league_coordinator import LeagueCoordinator diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index a1acdc9d2f..b77895d4d8 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -83,6 +83,81 @@ def __call__(self, ctx: "BattleContext") -> None: break +class BattleStepCollector: + + def __init__(self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int, model_dict: Dict, all_policies: Dict, agent_num: int): + self.cfg = cfg + self.end_flag = False + # self._reset(env) + self.env = env + self.env_num = self.env.env_num + + self.total_envstep_count = 0 + self.n_rollout_samples = n_rollout_samples + self.model_dict = model_dict + self.all_policies = all_policies + self.agent_num = agent_num + + self._battle_inferencer = task.wrap(battle_inferencer(self.cfg, self.env)) + self._transitions_list = [TransitionList(self.env.env_num) for _ in range(self.agent_num)] + self._battle_rolloutor = task.wrap(battle_rolloutor(self.cfg, self.env, self._transitions_list)) + + def __del__(self) -> None: + """ + Overview: + Execute the close command and close the collector. __del__ is automatically called to \ + destroy the collector instance when the collector finishes its work + """ + if self.end_flag: + return + self.end_flag = True + self.env.close() + + def _update_policies(self, job) -> None: + job_player_id_list = [player.player_id for player in job.players] + + for player_id in job_player_id_list: + if self.model_dict.get(player_id) is None: + continue + else: + learner_model = self.model_dict.get(player_id) + policy = self.all_policies.get(player_id) + assert policy, "for player{}, policy should have been initialized already" + # update policy model + policy.load_state_dict(learner_model.state_dict) + self.model_dict[player_id] = None + + def __call__(self, ctx: "BattleContext") -> None: + """ + Input of ctx: + - n_episode (:obj:`int`): the number of collecting data episode + - train_iter (:obj:`int`): the number of training iteration + - collect_kwargs (:obj:`dict`): the keyword args for policy forward + Output of ctx: + - ctx.train_data (:obj:`Tuple[List, List]`): A tuple with training sample(data) and episode info, \ + the former is a list containing collected episodes if not get_train_sample, \ + otherwise, return train_samples split by unroll_len. + """ + ctx.total_envstep_count = self.total_envstep_count + old = ctx.env_step + + while True: + self._update_policies(ctx.job) + self._battle_inferencer(ctx) + self._battle_rolloutor(ctx) + + self.total_envstep_count = ctx.total_envstep_count + + if (self.n_rollout_samples > 0 and ctx.env_step - old >= self.n_rollout_samples) or ctx.env_step >= ctx.n_sample * ctx.unroll_len: + for transitions in self._transitions_list: + trajectories, trajectory_end_idx = transitions.to_trajectories() + ctx.trajectories_list.append(trajectories) + ctx.trajectory_end_idx_list.append(trajectory_end_idx) + transitions.clear() + if ctx.env_step >= ctx.n_sample * ctx.unroll_len: + ctx.job_finish = True + break + class StepCollector: """ diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 2c61d8d8cb..d47c3d5484 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -9,7 +9,7 @@ from ding.league.v2.base_league import Job from ding.policy import Policy from ding.framework.middleware.league_learner import LearnerModel -from ding.framework.middleware import BattleEpisodeCollector +from ding.framework.middleware import BattleEpisodeCollector, BattleStepCollector, gae_estimator from ding.framework.middleware.functional import ActorData from ding.league.player import PlayerMeta from threading import Lock @@ -131,3 +131,132 @@ def __call__(self, ctx: "BattleContext"): break +class StepLeagueActor: + + def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): + self.cfg = cfg + self.env_fn = env_fn + self.env_num = env_fn().env_num + self.policy_fn = policy_fn + self.n_rollout_samples = self.cfg.policy.collect.get("n_rollout_samples") or 0 + self.n_sample = self.cfg.policy.collect.get("n_sample") or 1 + self.unroll_len = self.cfg.policy.collect.get("unroll_len") or 1 + self._collectors: Dict[str, BattleEpisodeCollector] = {} + self.all_policies: Dict[str, "Policy.collect_function"] = {} + task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), self._on_league_job) + task.on(EventEnum.LEARNER_SEND_MODEL, self._on_learner_model) + self.job_queue = queue.Queue() + self.model_dict = {} + self.model_dict_lock = Lock() + + self._gae_estimator = gae_estimator(cfg, policy_fn().collect_mode) + + def _on_learner_model(self, learner_model: "LearnerModel"): + """ + If get newest learner model, put it inside model_queue. + """ + with self.model_dict_lock: + self.model_dict[learner_model.player_id] = learner_model + + def _on_league_job(self, job: "Job"): + """ + Deal with job distributed by coordinator, put it inside job_queue. + """ + self.job_queue.put(job) + + def _get_collector(self, player_id: str, agent_num: int): + if self._collectors.get(player_id): + return self._collectors.get(player_id) + cfg = self.cfg + env = self.env_fn() + collector = task.wrap(BattleStepCollector(cfg.policy.collect.collector, env, self.n_rollout_samples, self.model_dict, self.all_policies, agent_num)) + self._collectors[player_id] = collector + return collector + + def _get_policy(self, player: "PlayerMeta") -> "Policy.collect_function": + player_id = player.player_id + if self.all_policies.get(player_id): + return self.all_policies.get(player_id) + policy: "Policy.collect_function" = self.policy_fn().collect_mode + self.all_policies[player_id] = policy + if "historical" in player.player_id: + policy.load_state_dict(player.checkpoint.load()) + + return policy + + def _get_job(self): + if self.job_queue.empty(): + task.emit(EventEnum.ACTOR_GREETING, task.router.node_id) + job = None + + try: + job = self.job_queue.get(timeout=10) + except queue.Empty: + logging.warning("For actor_{}, no Job get from coordinator".format(task.router.node_id)) + + return job + + def _get_current_policies(self, job): + current_policies = [] + main_player: "PlayerMeta" = None + for player in job.players: + current_policies.append(self._get_policy(player)) + if player.player_id == job.launch_player: + main_player = player + assert main_player, "can not find active player, on actor: {}".format(task.router.node_id) + + if current_policies is not None: + assert len(current_policies) > 1, "battle collector needs more than 1 policies" + for p in current_policies: + p.reset() + else: + raise RuntimeError('current_policies should not be None') + + return main_player, current_policies + + + def __call__(self, ctx: "BattleContext"): + + ctx.job = self._get_job() + if ctx.job is None: + return + + collector = self._get_collector(ctx.job.launch_player, len(ctx.job.players)) + + main_player, ctx.current_policies = self._get_current_policies(ctx.job) + ctx.agent_num = len(ctx.current_policies) + + _default_n_episode = ctx.current_policies[0].get_attribute('cfg').collect.get('n_episode', None) + if ctx.n_episode is None: + if _default_n_episode is None: + raise RuntimeError("Please specify collect n_episode") + else: + ctx.n_episode = _default_n_episode + assert ctx.n_episode >= self.env_num, "Please make sure n_episode >= env_num" + + ctx.train_iter = main_player.total_agent_step + ctx.episode_info = [[] for _ in range(ctx.agent_num)] + ctx.remain_episode = ctx.n_episode + ctx.n_sample = self.n_sample + ctx.unroll_len = self.unroll_len + while True: + collector(ctx) + + if not ctx.job.is_eval and len(ctx.trajectories_list[0]) > 0: + ctx.trajectories = ctx.trajectories_list[0] + ctx.trajectory_end_idx = ctx.trajectory_end_idx_list[0] + self._gae_estimator(ctx) + actor_data = ActorData(env_step=ctx.total_envstep_count, train_data=ctx.train_data) + task.emit(EventEnum.ACTOR_SEND_DATA.format(player=ctx.job.launch_player), actor_data) + + ctx.trajectories_list = [] + ctx.trajectory_end_idx_list = [] + ctx.trajectories = [] + ctx.trajectory_end_idx = None + + if ctx.job_finish is True: + ctx.job.result = [e['result'] for e in ctx.episode_info[0]] + task.emit(EventEnum.ACTOR_FINISH_JOB, ctx.job) + ctx.episode_info = [[] for _ in range(ctx.agent_num)] + break + diff --git a/ding/framework/middleware/tests/league_config.py b/ding/framework/middleware/tests/league_config.py index c905a34025..a905431e19 100644 --- a/ding/framework/middleware/tests/league_config.py +++ b/ding/framework/middleware/tests/league_config.py @@ -79,7 +79,9 @@ 'discount_factor': 1.0, 'gae_lambda': 1.0, 'n_episode': 128, - 'n_rollout_samples': 32 + 'n_rollout_samples': 32, + 'n_sample': 64, + 'unroll_len': 2 }, 'eval': { 'evaluator': { diff --git a/ding/framework/middleware/tests/test_league_actor.py b/ding/framework/middleware/tests/test_league_actor.py index 4c1da29564..6d5416a554 100644 --- a/ding/framework/middleware/tests/test_league_actor.py +++ b/ding/framework/middleware/tests/test_league_actor.py @@ -5,7 +5,7 @@ from ding.framework.context import BattleContext from ding.framework.middleware.league_learner import LearnerModel from ding.framework.middleware.tests.league_config import cfg -from ding.framework.middleware import LeagueActor +from ding.framework.middleware import LeagueActor, StepLeagueActor from ding.framework.middleware.functional import ActorData from ding.league.player import PlayerMeta from ding.framework.storage import FileStorage diff --git a/ding/framework/middleware/tests/test_league_actor_one_process.py b/ding/framework/middleware/tests/test_league_actor_one_process.py index f7d66787e3..f976c0f63d 100644 --- a/ding/framework/middleware/tests/test_league_actor_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_one_process.py @@ -5,7 +5,7 @@ from ding.framework.context import BattleContext from ding.framework.middleware.league_learner import LearnerModel from ding.framework.middleware.tests.league_config import cfg -from ding.framework.middleware import LeagueActor +from ding.framework.middleware import LeagueActor, StepLeagueActor from ding.framework.middleware.functional import ActorData from ding.league.player import PlayerMeta from ding.framework.storage import FileStorage @@ -44,7 +44,7 @@ def test_league_actor(): cfg, env_fn, policy_fn = prepare_test() policy = policy_fn() with task.start(async_mode=True, ctx = BattleContext()): - league_actor = LeagueActor(cfg=cfg, env_fn=env_fn, policy_fn=policy_fn) + league_actor = StepLeagueActor(cfg=cfg, env_fn=env_fn, policy_fn=policy_fn) def test_actor(): job = Job( diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index b8d7bcf565..b8308c4810 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -4,7 +4,7 @@ from ding.envs import BaseEnvManager from ding.framework.context import BattleContext from ding.framework.middleware.tests.league_config import cfg -from ding.framework.middleware import LeagueActor, LeagueCoordinator +from ding.framework.middleware import LeagueActor, LeagueCoordinator, StepLeagueActor from ding.league.player import PlayerMeta from ding.framework.storage import FileStorage From c171d590b4befb968989ad38e7ce6897b0664aea Mon Sep 17 00:00:00 2001 From: Zhanhui Zhou Date: Sun, 5 Jun 2022 06:00:43 -0400 Subject: [PATCH 090/229] feature&optim(zzh): add DDPPO & add model-based SAC with lambda-return target & refactor MBRL pipeline (#332) * finish sac_nstep * draft ddppo * fix bugs * add multiprocessing * fix(jrn) * add configs add weight decay change from clip_norm to clip_value nan debug add 1e-6 fix numericall stable logcosh delete debug mode * temp save * temp save * finish mbsac and (WIP) create world model interface * fix * fix * grad clip * save before refactor mbsac * draft complete * add stale files * add docstring&comments * delete stale pipelines; update new configs * delete stale files * fix eval_freq in config * fix bug in termination_fn * polish * polish 1.1 * delete TanhTransform * polish 1.2 * polish 1.3 * fix test file name conflict * fix flake8 style * polish 1.4 * polish 1.5 * polish 1.6 * polish 1.7 * fix test_TanhTransform assertion * codecov * retrigger action --- README.md | 10 +- ding/config/config.py | 15 + ding/entry/__init__.py | 2 +- ding/entry/serial_entry_mbrl.py | 302 ++++++----- ding/entry/tests/test_serial_entry_mbrl.py | 29 + ding/model/template/__init__.py | 1 - ding/model/template/model_based/__init__.py | 1 - ding/model/template/model_based/mbpo.py | 424 --------------- ding/model/template/tests/test_mbpo.py | 45 -- ding/policy/command_mode_policy_instance.py | 6 + ding/policy/mbpolicy/__init__.py | 1 + ding/policy/mbpolicy/mbsac.py | 221 ++++++++ .../mbpolicy/tests/test_mbpolicy_utils.py | 36 ++ ding/policy/mbpolicy/tests/test_mbsac.py | 23 + ding/policy/mbpolicy/utils.py | 88 +++ ding/rl_utils/td.py | 33 +- ding/utils/__init__.py | 3 +- ding/utils/registry_factory.py | 2 + ding/worker/learner/base_learner.py | 7 +- ding/world_model/__init__.py | 2 + ding/world_model/base_world_model.py | 354 ++++++++++++ ding/world_model/ddppo.py | 509 ++++++++++++++++++ ding/world_model/mbpo.py | 255 +++++++++ ding/world_model/model/ensemble.py | 150 ++++++ ding/world_model/model/tests/test_ensemble.py | 29 + ding/world_model/tests/test_ddppo.py | 106 ++++ ding/world_model/tests/test_mbpo.py | 67 +++ ding/world_model/tests/test_world_model.py | 121 +++++ .../tests/test_world_model_utils.py | 19 + ding/world_model/utils.py | 25 + .../mbrl/pendulum_mbsac_ddppo_config.py | 116 ++++ .../config/mbrl/pendulum_mbsac_mbpo_config.py | 110 ++++ .../config/mbrl/pendulum_sac_ddppo_config.py | 121 +++++ .../config/mbrl/pendulum_sac_mbpo_config.py | 115 ++++ .../pendulum/envs/pendulum_env.py | 15 + .../config/ant_sac_mbpo_default_config.py | 135 ----- .../humanoid_sac_mbpo_default_config.py | 135 ----- .../mbrl/halfcheetah_mbsac_mbpo_config.py | 115 ++++ .../{ => mbrl}/halfcheetah_sac_mbpo_config.py | 89 ++- .../config/mbrl/hopper_mbsac_mbpo_config.py | 115 ++++ .../{ => mbrl}/hopper_sac_mbpo_config.py | 83 ++- .../config/mbrl/walker2d_mbsac_mbpo_config.py | 115 ++++ .../{ => mbrl}/walker2d_sac_mbpo_config.py | 87 ++- dizoo/mujoco/envs/__init__.py | 1 - dizoo/mujoco/envs/mujoco_env.py | 62 +++ dizoo/mujoco/envs/mujoco_gym_env.py | 16 +- dizoo/mujoco/envs/mujoco_model_env.py | 131 ----- 47 files changed, 3289 insertions(+), 1158 deletions(-) create mode 100644 ding/entry/tests/test_serial_entry_mbrl.py delete mode 100644 ding/model/template/model_based/__init__.py delete mode 100644 ding/model/template/model_based/mbpo.py delete mode 100644 ding/model/template/tests/test_mbpo.py create mode 100644 ding/policy/mbpolicy/__init__.py create mode 100644 ding/policy/mbpolicy/mbsac.py create mode 100644 ding/policy/mbpolicy/tests/test_mbpolicy_utils.py create mode 100644 ding/policy/mbpolicy/tests/test_mbsac.py create mode 100644 ding/policy/mbpolicy/utils.py create mode 100644 ding/world_model/__init__.py create mode 100644 ding/world_model/base_world_model.py create mode 100644 ding/world_model/ddppo.py create mode 100644 ding/world_model/mbpo.py create mode 100644 ding/world_model/model/ensemble.py create mode 100644 ding/world_model/model/tests/test_ensemble.py create mode 100644 ding/world_model/tests/test_ddppo.py create mode 100644 ding/world_model/tests/test_mbpo.py create mode 100644 ding/world_model/tests/test_world_model.py create mode 100644 ding/world_model/tests/test_world_model_utils.py create mode 100644 ding/world_model/utils.py create mode 100644 dizoo/classic_control/pendulum/config/mbrl/pendulum_mbsac_ddppo_config.py create mode 100644 dizoo/classic_control/pendulum/config/mbrl/pendulum_mbsac_mbpo_config.py create mode 100644 dizoo/classic_control/pendulum/config/mbrl/pendulum_sac_ddppo_config.py create mode 100644 dizoo/classic_control/pendulum/config/mbrl/pendulum_sac_mbpo_config.py delete mode 100644 dizoo/mujoco/config/ant_sac_mbpo_default_config.py delete mode 100644 dizoo/mujoco/config/humanoid_sac_mbpo_default_config.py create mode 100644 dizoo/mujoco/config/mbrl/halfcheetah_mbsac_mbpo_config.py rename dizoo/mujoco/config/{ => mbrl}/halfcheetah_sac_mbpo_config.py (51%) create mode 100644 dizoo/mujoco/config/mbrl/hopper_mbsac_mbpo_config.py rename dizoo/mujoco/config/{ => mbrl}/hopper_sac_mbpo_config.py (53%) create mode 100644 dizoo/mujoco/config/mbrl/walker2d_mbsac_mbpo_config.py rename dizoo/mujoco/config/{ => mbrl}/walker2d_sac_mbpo_config.py (52%) delete mode 100644 dizoo/mujoco/envs/mujoco_model_env.py diff --git a/README.md b/README.md index cfcebeb6aa..592b173849 100644 --- a/README.md +++ b/README.md @@ -169,10 +169,12 @@ ding -m serial -e cartpole -p dqn -s 0 | 32 | [ICM](https://arxiv.org/pdf/1705.05363.pdf) | ![exp](https://img.shields.io/badge/-exploration-orange) | [ICM中文文档](https://di-engine-docs.readthedocs.io/zh_CN/latest/12_policies/icm_zh.html)
[reward_model/icm](https://github.com/opendilab/DI-engine/blob/main/ding/reward_model/icm_reward_model.py) | python3 -u cartpole_ppo_icm_config.py | | 33 | [CQL](https://arxiv.org/pdf/2006.04779.pdf) | ![offline](https://img.shields.io/badge/-offlineRL-darkblue) | [policy/cql](https://github.com/opendilab/DI-engine/blob/main/ding/policy/cql.py) | python3 -u d4rl_cql_main.py | | 34 | [TD3BC](https://arxiv.org/pdf/2106.06860.pdf) | ![offline](https://img.shields.io/badge/-offlineRL-darkblue) | [policy/td3_bc](https://github.com/opendilab/DI-engine/blob/main/ding/policy/td3_bc.py) | python3 -u mujoco_td3_bc_main.py | -| 35 | [MBPO](https://arxiv.org/pdf/1906.08253.pdf) | ![mbrl](https://img.shields.io/badge/-ModelBasedRL-lightblue) | [model/template/model_based/mbpo](https://github.com/opendilab/DI-engine/blob/main/ding/model/template/model_based/mbpo.py) | python3 -u sac_halfcheetah_mopo_default_config.py | -| 36 | [PER](https://arxiv.org/pdf/1511.05952.pdf) | ![other](https://img.shields.io/badge/-other-lightgrey) | [worker/replay_buffer](https://github.com/opendilab/DI-engine/blob/main/ding/worker/replay_buffer/advanced_buffer.py) | `rainbow demo` | -| 37 | [GAE](https://arxiv.org/pdf/1506.02438.pdf) | ![other](https://img.shields.io/badge/-other-lightgrey) | [rl_utils/gae](https://github.com/opendilab/DI-engine/blob/main/ding/rl_utils/gae.py) | `ppo demo` | -| 38 | [ST-DIM](https://arxiv.org/pdf/1906.08226.pdf) | ![other](https://img.shields.io/badge/-other-lightgrey) | [torch_utils/loss/contrastive_loss](https://github.com/opendilab/DI-engine/blob/main/ding/torch_utils/loss/contrastive_loss.py) | ding -m serial -c cartpole_dqn_stdim_config.py -s 0 | +| 35 | MBSAC([SAC](https://arxiv.org/abs/1801.01290)+[VE](https://arxiv.org/abs/1803.00101)+[SVG](https://arxiv.org/abs/1510.09142)) | ![continuous](https://img.shields.io/badge/-continous-green)![mbrl](https://img.shields.io/badge/-ModelBasedRL-lightblue) | [policy/mbpolicy/mbsac](https://github.com/opendilab/DI-engine/blob/main/ding/policy/mbpolicy/mbsac.py) | python3 -u pendulum_mbsac_mbpo_config.py \ python3 -u pendulum_mbsac_ddppo_config.py | +| 36 | [MBPO](https://arxiv.org/pdf/1906.08253.pdf) | ![mbrl](https://img.shields.io/badge/-ModelBasedRL-lightblue) | [world_model/mbpo](https://github.com/opendilab/DI-engine/blob/main/ding/world_model/mbpo.py) | python3 -u pendulum_sac_mbpo_config.py | +| 37 | [DDPPO](https://openreview.net/forum?id=rzvOQrnclO0) | ![mbrl](https://img.shields.io/badge/-ModelBasedRL-lightblue) | [world_model/ddppo](https://github.com/opendilab/DI-engine/blob/main/ding/world_model/ddppo.py) | python3 -u pendulum_mbsac_ddppo_config.py | +| 38 | [PER](https://arxiv.org/pdf/1511.05952.pdf) | ![other](https://img.shields.io/badge/-other-lightgrey) | [worker/replay_buffer](https://github.com/opendilab/DI-engine/blob/main/ding/worker/replay_buffer/advanced_buffer.py) | `rainbow demo` | +| 39 | [GAE](https://arxiv.org/pdf/1506.02438.pdf) | ![other](https://img.shields.io/badge/-other-lightgrey) | [rl_utils/gae](https://github.com/opendilab/DI-engine/blob/main/ding/rl_utils/gae.py) | `ppo demo` | +| 40 | [ST-DIM](https://arxiv.org/pdf/1906.08226.pdf) | ![other](https://img.shields.io/badge/-other-lightgrey) | [torch_utils/loss/contrastive_loss](https://github.com/opendilab/DI-engine/blob/main/ding/torch_utils/loss/contrastive_loss.py) | ding -m serial -c cartpole_dqn_stdim_config.py -s 0 | ![discrete](https://img.shields.io/badge/-discrete-brightgreen) means discrete action space, which is only label in normal DRL algorithms (1-18) diff --git a/ding/config/config.py b/ding/config/config.py index ab3af8ea4c..286505382b 100644 --- a/ding/config/config.py +++ b/ding/config/config.py @@ -17,6 +17,7 @@ AdvancedReplayBuffer, get_parallel_commander_cls, get_parallel_collector_cls, get_buffer_cls, \ get_serial_collector_cls, MetricSerialEvaluator, BattleInteractionSerialEvaluator from ding.reward_model import get_reward_model_cls +from ding.world_model import get_world_model_cls from .utils import parallel_transform, parallel_transform_slurm, parallel_transform_k8s, save_config_formatted @@ -316,6 +317,7 @@ def compile_config( buffer: type = None, env: type = None, reward_model: type = None, + world_model: type = None, seed: int = 0, auto: bool = False, create_cfg: dict = None, @@ -378,6 +380,12 @@ def compile_config( reward_model_config = reward_model.default_config() else: reward_model_config = EasyDict() + if 'world_model' in create_cfg: + world_model = get_world_model_cls(create_cfg.world_model) + world_model_config = world_model.default_config() + world_model_config.update(create_cfg.world_model) + else: + world_model_config = EasyDict() else: if 'default_config' in dir(env): env_config = env.default_config() @@ -393,6 +401,11 @@ def compile_config( reward_model_config = EasyDict() else: reward_model_config = reward_model.default_config() + if world_model is None: + world_model_config = EasyDict() + else: + world_model_config = world_model.default_config() + world_model_config.update(create_cfg.world_model) policy_config.learn.learner = deep_merge_dicts( learner.default_config(), policy_config.learn.learner, @@ -409,6 +422,8 @@ def compile_config( default_config = EasyDict({'env': env_config, 'policy': policy_config}) if len(reward_model_config) > 0: default_config['reward_model'] = reward_model_config + if len(world_model_config) > 0: + default_config['world_model'] = world_model_config cfg = deep_merge_dicts(default_config, cfg) cfg.seed = seed # check important key in config diff --git a/ding/entry/__init__.py b/ding/entry/__init__.py index 7559b5d33d..a94d233f1a 100644 --- a/ding/entry/__init__.py +++ b/ding/entry/__init__.py @@ -9,7 +9,6 @@ from .serial_entry_reward_model_offpolicy import serial_pipeline_reward_model_offpolicy from .serial_entry_reward_model_onpolicy import serial_pipeline_reward_model_onpolicy from .serial_entry_bc import serial_pipeline_bc -from .serial_entry_mbrl import serial_pipeline_mbrl from .serial_entry_dqfd import serial_pipeline_dqfd from .serial_entry_r2d3 import serial_pipeline_r2d3 from .serial_entry_sqil import serial_pipeline_sqil @@ -25,3 +24,4 @@ from .serial_entry_preference_based_irl_onpolicy \ import serial_pipeline_preference_based_irl_onpolicy from .application_entry_drex_collect_data import drex_collecting_data +from .serial_entry_mbrl import serial_pipeline_dyna, serial_pipeline_dream diff --git a/ding/entry/serial_entry_mbrl.py b/ding/entry/serial_entry_mbrl.py index b2c306f37c..f1d493ed5f 100644 --- a/ding/entry/serial_entry_mbrl.py +++ b/ding/entry/serial_entry_mbrl.py @@ -1,110 +1,58 @@ from typing import Union, Optional, List, Any, Tuple -import os -import copy import torch -from ditk import logging +import os from functools import partial + from tensorboardX import SummaryWriter -from ding.envs import get_vec_env_setting, create_env_manager, create_model_env -from ding.model import create_model from ding.worker import BaseLearner, InteractionSerialEvaluator, BaseSerialCommander, create_buffer, \ - create_serial_collector + get_buffer_cls, create_serial_collector +from ding.world_model import WorldModel +from ding.worker import IBuffer +from ding.envs import get_vec_env_setting, create_env_manager from ding.config import read_config, compile_config +from ding.utils import set_pkg_seed, deep_merge_dicts from ding.policy import create_policy -from ding.utils import set_pkg_seed, read_file, save_file -from .utils import random_collect - - -def save_ckpt_fn(learner, env_model, envstep): - dirname = './{}/ckpt'.format(learner.exp_name) - if not os.path.exists(dirname): - try: - os.mkdir(dirname) - except FileExistsError: - pass - policy_prefix = 'policy_envstep_{}_'.format(envstep) - model_prefix = 'model_envstep_{}_'.format(envstep) - - def model_save_ckpt_fn(ckpt_name): - """ - Overview: - Save checkpoint in corresponding path. - Checkpoint info includes policy state_dict and iter num. - Arguments: - - engine (:obj:`BaseLearner`): the BaseLearner which needs to save checkpoint - """ - path = os.path.join(dirname, ckpt_name) - state_dict = env_model.state_dict() - save_file(path, state_dict) - learner.info('env model save ckpt in {}'.format(path)) - - def model_policy_save_ckpt_fn(ckpt_name): - model_save_ckpt_fn(model_prefix + ckpt_name) - learner.save_checkpoint(policy_prefix + ckpt_name) - - return model_policy_save_ckpt_fn - - -def serial_pipeline_mbrl( +from ding.world_model import create_world_model +from ding.entry.utils import random_collect + + +def mbrl_entry_setup( input_cfg: Union[str, Tuple[dict, dict]], seed: int = 0, env_setting: Optional[List[Any]] = None, model: Optional[torch.nn.Module] = None, - max_train_iter: Optional[int] = int(1e10), - max_env_step: Optional[int] = int(1e10), -) -> 'Policy': # noqa - """ - Overview: - Serial pipeline entry for model-based RL. - Arguments: - - input_cfg (:obj:`Union[str, Tuple[dict, dict]]`): Config in dict type. \ - ``str`` type means config file path. \ - ``Tuple[dict, dict]`` type means [user_config, create_cfg]. - - seed (:obj:`int`): Random seed. - - env_setting (:obj:`Optional[List[Any]]`): A list with 3 elements: \ - ``BaseEnv`` subclass, collector env config, and evaluator env config. - - model (:obj:`Optional[torch.nn.Module]`): Instance of torch.nn.Module. - - max_train_iter (:obj:`Optional[int]`): Maximum policy update iterations in training. - - max_env_step (:obj:`Optional[int]`): Maximum collected environment interaction steps. - Returns: - - policy (:obj:`Policy`): Converged policy. - """ - # Compile config +) -> Tuple: if isinstance(input_cfg, str): cfg, create_cfg = read_config(input_cfg) else: cfg, create_cfg = input_cfg - model_based_cfg = cfg.pop('model_based') create_cfg.policy.type = create_cfg.policy.type + '_command' env_fn = None if env_setting is None else env_setting[0] cfg = compile_config(cfg, seed=seed, env=env_fn, auto=True, create_cfg=create_cfg, save_cfg=True) - # Create logger - tb_logger = SummaryWriter(os.path.join('./{}/log/'.format(cfg.exp_name), 'serial')) - - # Create env if env_setting is None: env_fn, collector_env_cfg, evaluator_env_cfg = get_vec_env_setting(cfg.env) else: env_fn, collector_env_cfg, evaluator_env_cfg = env_setting + collector_env = create_env_manager(cfg.env.manager, [partial(env_fn, cfg=c) for c in collector_env_cfg]) evaluator_env = create_env_manager(cfg.env.manager, [partial(env_fn, cfg=c) for c in evaluator_env_cfg]) + collector_env.seed(cfg.seed) evaluator_env.seed(cfg.seed, dynamic_seed=False) + set_pkg_seed(cfg.seed, use_cuda=cfg.policy.cuda) - # Create env model - model_based_cfg.env_model.tb_logger = tb_logger - env_model = create_model(model_based_cfg.env_model) + # create logger + tb_logger = SummaryWriter(os.path.join('./{}/log/'.format(cfg.exp_name), 'serial')) - # Create model-based env - model_env = create_model_env(model_based_cfg.model_env) + # create world model + world_model = create_world_model(cfg.world_model, env_fn(cfg.env), tb_logger) - # Create policy - set_pkg_seed(cfg.seed, use_cuda=cfg.policy.cuda) + # create policy policy = create_policy(cfg.policy, model=model, enable_field=['learn', 'collect', 'eval', 'command']) - # Create worker components: learner, collector, evaluator, replay buffer, commander. + # create worker learner = BaseLearner(cfg.policy.learn.learner, policy.learn_mode, tb_logger, exp_name=cfg.exp_name) collector = create_serial_collector( cfg.policy.collect.collector, @@ -116,71 +64,181 @@ def serial_pipeline_mbrl( evaluator = InteractionSerialEvaluator( cfg.policy.eval.evaluator, evaluator_env, policy.eval_mode, tb_logger, exp_name=cfg.exp_name ) - replay_buffer = create_buffer(cfg.policy.other.replay_buffer, tb_logger=tb_logger, exp_name=cfg.exp_name) - imagine_buffer = create_buffer(model_based_cfg.imagine_buffer, tb_logger=tb_logger, exp_name=cfg.exp_name) + env_buffer = create_buffer(cfg.policy.other.replay_buffer, tb_logger=tb_logger, exp_name=cfg.exp_name) commander = BaseSerialCommander( - cfg.policy.other.commander, learner, collector, evaluator, replay_buffer, policy.command_mode + cfg.policy.other.commander, learner, collector, evaluator, env_buffer, policy.command_mode + ) + + return ( + cfg, + policy, + world_model, + env_buffer, + learner, + collector, + collector_env, + evaluator, + commander, + tb_logger, ) - # ========== - # Main loop - # ========== - # Learner's before_run hook. + +def create_img_buffer( + cfg: dict, input_cfg: Union[str, Tuple[dict, dict]], world_model: WorldModel, tb_logger: 'SummaryWriter' +) -> IBuffer: # noqa + if isinstance(input_cfg, str): + _, create_cfg = read_config(input_cfg) + else: + _, create_cfg = input_cfg + img_buffer_cfg = cfg.world_model.other.imagination_buffer + img_buffer_cfg.update(create_cfg.imagination_buffer) + buffer_cls = get_buffer_cls(img_buffer_cfg) + cfg.world_model.other.imagination_buffer.update(deep_merge_dicts(buffer_cls.default_config(), img_buffer_cfg)) + if img_buffer_cfg.type == 'elastic': + img_buffer_cfg.set_buffer_size = world_model.buffer_size_scheduler + img_buffer = create_buffer(cfg.world_model.other.imagination_buffer, tb_logger=tb_logger, exp_name=cfg.exp_name) + return img_buffer + + +def serial_pipeline_dyna( + input_cfg: Union[str, Tuple[dict, dict]], + seed: int = 0, + env_setting: Optional[List[Any]] = None, + model: Optional[torch.nn.Module] = None, + max_train_iter: Optional[int] = int(1e10), + max_env_step: Optional[int] = int(1e10), +) -> 'Policy': # noqa + """ + Overview: + Serial pipeline entry for dyna-style model-based RL. + Arguments: + - input_cfg (:obj:`Union[str, Tuple[dict, dict]]`): Config in dict type. \ + ``str`` type means config file path. \ + ``Tuple[dict, dict]`` type means [user_config, create_cfg]. + - seed (:obj:`int`): Random seed. + - env_setting (:obj:`Optional[List[Any]]`): A list with 3 elements: \ + ``BaseEnv`` subclass, collector env config, and evaluator env config. + - model (:obj:`Optional[torch.nn.Module]`): Instance of torch.nn.Module. + - max_train_iter (:obj:`Optional[int]`): Maximum policy update iterations in training. + - max_env_step (:obj:`Optional[int]`): Maximum collected environment interaction steps. + Returns: + - policy (:obj:`Policy`): Converged policy. + """ + cfg, policy, world_model, env_buffer, learner, collector, collector_env, evaluator, commander, tb_logger = \ + mbrl_entry_setup(input_cfg, seed, env_setting, model) + + img_buffer = create_img_buffer(cfg, input_cfg, world_model, tb_logger) + learner.call_hook('before_run') - # Accumulate plenty of data before the beginning of training. if cfg.policy.get('random_collect_size', 0) > 0: - random_collect(cfg.policy, policy, collector, collector_env, commander, replay_buffer) - # Train - batch_size = learner.policy.get_attribute('batch_size') - real_ratio = model_based_cfg['real_ratio'] - replay_batch_size = int(batch_size * real_ratio) - imagine_batch_size = batch_size - replay_batch_size - eval_buffer = [] + random_collect(cfg.policy, policy, collector, collector_env, commander, env_buffer) + while True: collect_kwargs = commander.step() - # Evaluate policy performance - if evaluator.should_eval(learner.train_iter): - stop, reward = evaluator.eval( - save_ckpt_fn(learner, env_model, collector.envstep), learner.train_iter, collector.envstep - ) + # eval the policy + if evaluator.should_eval(collector.envstep): + stop, reward = evaluator.eval(learner.save_checkpoint, learner.train_iter, collector.envstep) if stop: break - # Collect data by default config n_sample/n_episode - new_data = collector.collect(train_iter=learner.train_iter, policy_kwargs=collect_kwargs) - replay_buffer.push(new_data, cur_collector_envstep=collector.envstep) - eval_buffer.extend(new_data) - # Eval env_model - if env_model.should_eval(collector.envstep): - env_model.eval(eval_buffer, collector.envstep) - eval_buffer = [] - # Train env_model and use model_env to rollout - if env_model.should_train(collector.envstep): - env_model.train(replay_buffer, learner.train_iter, collector.envstep) - imagine_buffer.update(collector.envstep) - model_env.rollout( - env_model, policy.collect_mode, replay_buffer, imagine_buffer, collector.envstep, learner.train_iter + + # fill environment buffer + data = collector.collect(train_iter=learner.train_iter, policy_kwargs=collect_kwargs) + env_buffer.push(data, cur_collector_envstep=collector.envstep) + + # eval&train world model and fill imagination buffer + if world_model.should_eval(collector.envstep): + world_model.eval(env_buffer, collector.envstep, learner.train_iter) + if world_model.should_train(collector.envstep): + world_model.train(env_buffer, collector.envstep, learner.train_iter) + world_model.fill_img_buffer( + policy.collect_mode, env_buffer, img_buffer, collector.envstep, learner.train_iter ) - policy._rollout_length = model_env._set_rollout_length(collector.envstep) - # Learn policy from collected data + for i in range(cfg.policy.learn.update_per_collect): - # Learner will train ``update_per_collect`` times in one iteration. - replay_train_data = replay_buffer.sample(replay_batch_size, learner.train_iter) - imagine_batch_data = imagine_buffer.sample(imagine_batch_size, learner.train_iter) - if replay_train_data is None or imagine_batch_data is None: - break - train_data = replay_train_data + imagine_batch_data + batch_size = learner.policy.get_attribute('batch_size') + train_data = world_model.sample(env_buffer, img_buffer, batch_size, learner.train_iter) learner.train(train_data, collector.envstep) - # Priority is not support - # if learner.policy.get_attribute('priority'): - # replay_buffer.update(learner.priority_info) + if cfg.policy.on_policy: # On-policy algorithm must clear the replay buffer. - replay_buffer.clear() - imagine_buffer.clear() + env_buffer.clear() + img_buffer.clear() + + if collector.envstep >= max_env_step or learner.train_iter >= max_train_iter: + break + + learner.call_hook('after_run') + + return policy + + +def serial_pipeline_dream( + input_cfg: Union[str, Tuple[dict, dict]], + seed: int = 0, + env_setting: Optional[List[Any]] = None, + model: Optional[torch.nn.Module] = None, + max_train_iter: Optional[int] = int(1e10), + max_env_step: Optional[int] = int(1e10), +) -> 'Policy': # noqa + """ + Overview: + Serial pipeline entry for dreamer-style model-based RL. + Arguments: + - input_cfg (:obj:`Union[str, Tuple[dict, dict]]`): Config in dict type. \ + ``str`` type means config file path. \ + ``Tuple[dict, dict]`` type means [user_config, create_cfg]. + - seed (:obj:`int`): Random seed. + - env_setting (:obj:`Optional[List[Any]]`): A list with 3 elements: \ + ``BaseEnv`` subclass, collector env config, and evaluator env config. + - model (:obj:`Optional[torch.nn.Module]`): Instance of torch.nn.Module. + - max_train_iter (:obj:`Optional[int]`): Maximum policy update iterations in training. + - max_env_step (:obj:`Optional[int]`): Maximum collected environment interaction steps. + Returns: + - policy (:obj:`Policy`): Converged policy. + """ + cfg, policy, world_model, env_buffer, learner, collector, collector_env, evaluator, commander, tb_logger = \ + mbrl_entry_setup(input_cfg, seed, env_setting, model) + + learner.call_hook('before_run') + + if cfg.policy.get('random_collect_size', 0) > 0: + random_collect(cfg.policy, policy, collector, collector_env, commander, env_buffer) + + while True: + collect_kwargs = commander.step() + # eval the policy + if evaluator.should_eval(collector.envstep): + stop, reward = evaluator.eval(learner.save_checkpoint, learner.train_iter, collector.envstep) + if stop: + break + + # fill environment buffer + data = collector.collect(train_iter=learner.train_iter, policy_kwargs=collect_kwargs) + env_buffer.push(data, cur_collector_envstep=collector.envstep) + + # eval&train world model and fill imagination buffer + if world_model.should_eval(collector.envstep): + world_model.eval(env_buffer, collector.envstep, learner.train_iter) + if world_model.should_train(collector.envstep): + world_model.train(env_buffer, collector.envstep, learner.train_iter) + + update_per_collect = cfg.policy.learn.update_per_collect // world_model.rollout_length_scheduler( + collector.envstep + ) + update_per_collect = max(1, update_per_collect) + for i in range(update_per_collect): + batch_size = learner.policy.get_attribute('batch_size') + train_data = env_buffer.sample(batch_size, learner.train_iter) + # dreamer-style: use pure on-policy imagined rollout to train policy, + # which depends on the current envstep to decide the rollout length + learner.train( + train_data, collector.envstep, policy_kwargs=dict(world_model=world_model, envstep=collector.envstep) + ) + if collector.envstep >= max_env_step or learner.train_iter >= max_train_iter: break - # Learner's after_run hook. learner.call_hook('after_run') + return policy diff --git a/ding/entry/tests/test_serial_entry_mbrl.py b/ding/entry/tests/test_serial_entry_mbrl.py new file mode 100644 index 0000000000..57fff7a121 --- /dev/null +++ b/ding/entry/tests/test_serial_entry_mbrl.py @@ -0,0 +1,29 @@ +import pytest +from copy import deepcopy +from ding.entry.serial_entry_mbrl import serial_pipeline_dyna, serial_pipeline_dream + +from dizoo.classic_control.pendulum.config.mbrl.pendulum_sac_mbpo_config \ + import main_config as pendulum_sac_mbpo_main_config,\ + create_config as pendulum_sac_mbpo_create_config + +from dizoo.classic_control.pendulum.config.mbrl.pendulum_mbsac_mbpo_config \ + import main_config as pendulum_mbsac_mbpo_main_config,\ + create_config as pendulum_mbsac_mbpo_create_config + + +@pytest.mark.unittest +def test_sac_mbpo_dyna(): + config = [deepcopy(pendulum_sac_mbpo_main_config), deepcopy(pendulum_sac_mbpo_create_config)] + try: + serial_pipeline_dyna(config, seed=0, max_train_iter=1) + except Exception: + assert False, "pipeline fail" + + +@pytest.mark.unittest +def test_sac_mbpo_dream(): + config = [deepcopy(pendulum_mbsac_mbpo_main_config), deepcopy(pendulum_mbsac_mbpo_create_config)] + try: + serial_pipeline_dream(config, seed=0, max_train_iter=1) + except Exception: + assert False, "pipeline fail" diff --git a/ding/model/template/__init__.py b/ding/model/template/__init__.py index 21007aa43c..8e12e274d5 100644 --- a/ding/model/template/__init__.py +++ b/ding/model/template/__init__.py @@ -17,5 +17,4 @@ from .ngu import NGU from .qac_dist import QACDIST from .maqac import MAQAC, ContinuousMAQAC -from .model_based import EnsembleDynamicsModel from .vae import VanillaVAE diff --git a/ding/model/template/model_based/__init__.py b/ding/model/template/model_based/__init__.py deleted file mode 100644 index 21708a5cfc..0000000000 --- a/ding/model/template/model_based/__init__.py +++ /dev/null @@ -1 +0,0 @@ -from .mbpo import EnsembleDynamicsModel diff --git a/ding/model/template/model_based/mbpo.py b/ding/model/template/model_based/mbpo.py deleted file mode 100644 index c6034d5ee0..0000000000 --- a/ding/model/template/model_based/mbpo.py +++ /dev/null @@ -1,424 +0,0 @@ -import math -import copy -import itertools - -import numpy as np -import torch -import torch.nn as nn -import torch.nn.functional as F - -from ding.utils import MODEL_REGISTRY -from ding.torch_utils import Swish -from ding.utils.data import default_collate - - -class StandardScaler(nn.Module): - - def __init__(self, input_size): - super(StandardScaler, self).__init__() - self.register_buffer('std', torch.ones(1, input_size)) - self.register_buffer('mu', torch.zeros(1, input_size)) - - def fit(self, data): - std, mu = torch.std_mean(data, dim=0, keepdim=True) - std[std < 1e-12] = 1 - self.std.data.mul_(0.0).add_(std) - self.mu.data.mul_(0.0).add_(mu) - - def transform(self, data): - return (data - self.mu) / self.std - - def inverse_transform(self, data): - return self.std * data + self.mu - - -def init_weights(m): - - def truncated_normal_init(t, mean=0.0, std=0.01): - torch.nn.init.normal_(t, mean=mean, std=std) - while True: - cond = torch.logical_or(t < mean - 2 * std, t > mean + 2 * std) - if not torch.sum(cond): - break - t = torch.where(cond, torch.nn.init.normal_(torch.ones(t.shape), mean=mean, std=std), t) - return t - - if isinstance(m, nn.Linear) or isinstance(m, EnsembleFC): - input_dim = m.in_features - truncated_normal_init(m.weight, std=1 / (2 * np.sqrt(input_dim))) - m.bias.data.fill_(0.0) - - -class EnsembleFC(nn.Module): - __constants__ = ['in_features', 'out_features'] - in_features: int - out_features: int - ensemble_size: int - weight: torch.Tensor - - def __init__(self, in_features: int, out_features: int, ensemble_size: int, weight_decay: float = 0.) -> None: - super(EnsembleFC, self).__init__() - self.in_features = in_features - self.out_features = out_features - self.ensemble_size = ensemble_size - self.weight = nn.Parameter(torch.Tensor(ensemble_size, in_features, out_features)) - self.weight_decay = weight_decay - self.bias = nn.Parameter(torch.Tensor(ensemble_size, 1, out_features)) - - def forward(self, input: torch.Tensor) -> torch.Tensor: - assert input.shape[0] == self.ensemble_size and len(input.shape) == 3 - return torch.bmm(input, self.weight) + self.bias # w times x + b - - def extra_repr(self) -> str: - return 'in_features={}, out_features={}'.format(self.in_features, self.out_features) - - -class EnsembleModel(nn.Module): - - def __init__( - self, - state_size, - action_size, - reward_size, - ensemble_size, - hidden_size=200, - learning_rate=1e-3, - use_decay=False - ): - super(EnsembleModel, self).__init__() - - self.use_decay = use_decay - self.hidden_size = hidden_size - self.output_dim = state_size + reward_size - - self.nn1 = EnsembleFC(state_size + action_size, hidden_size, ensemble_size, weight_decay=0.000025) - self.nn2 = EnsembleFC(hidden_size, hidden_size, ensemble_size, weight_decay=0.00005) - self.nn3 = EnsembleFC(hidden_size, hidden_size, ensemble_size, weight_decay=0.000075) - self.nn4 = EnsembleFC(hidden_size, hidden_size, ensemble_size, weight_decay=0.000075) - self.nn5 = EnsembleFC(hidden_size, self.output_dim * 2, ensemble_size, weight_decay=0.0001) - self.max_logvar = nn.Parameter(torch.ones(1, self.output_dim).float() * 0.5, requires_grad=False) - self.min_logvar = nn.Parameter(torch.ones(1, self.output_dim).float() * -10, requires_grad=False) - self.swish = Swish() - - self.apply(init_weights) - - self.optimizer = torch.optim.Adam(self.parameters(), lr=learning_rate) - - def forward(self, x, ret_log_var=False): - nn1_output = self.swish(self.nn1(x)) - nn2_output = self.swish(self.nn2(nn1_output)) - nn3_output = self.swish(self.nn3(nn2_output)) - nn4_output = self.swish(self.nn4(nn3_output)) - nn5_output = self.nn5(nn4_output) - - mean, logvar = nn5_output.chunk(2, dim=2) - logvar = self.max_logvar - F.softplus(self.max_logvar - logvar) - logvar = self.min_logvar + F.softplus(logvar - self.min_logvar) - - if ret_log_var: - return mean, logvar - else: - return mean, torch.exp(logvar) - - def get_decay_loss(self): - decay_loss = 0. - for m in self.children(): - if isinstance(m, EnsembleFC): - decay_loss += m.weight_decay * torch.sum(torch.square(m.weight)) / 2. - return decay_loss - - def loss(self, mean, logvar, labels): - """ - mean, logvar: Ensemble_size x N x dim - labels: Ensemble_size x N x dim - """ - assert len(mean.shape) == len(logvar.shape) == len(labels.shape) == 3 - inv_var = torch.exp(-logvar) - # Average over batch and dim, sum over ensembles. - mse_loss_inv = (torch.pow(mean - labels, 2) * inv_var).mean(dim=(1, 2)) - var_loss = logvar.mean(dim=(1, 2)) - mse_loss = torch.pow(mean - labels, 2).mean(dim=(1, 2)) - total_loss = mse_loss_inv.sum() + var_loss.sum() - return total_loss, mse_loss - - def train(self, loss): - self.optimizer.zero_grad() - - loss += 0.01 * torch.sum(self.max_logvar) - 0.01 * torch.sum(self.min_logvar) - if self.use_decay: - loss += self.get_decay_loss() - - loss.backward() - - self.optimizer.step() - - -@MODEL_REGISTRY.register('mbpo') -class EnsembleDynamicsModel(nn.Module): - - def __init__( - self, - network_size, - elite_size, - state_size, - action_size, - reward_size=1, - hidden_size=200, - use_decay=False, - batch_size=256, - holdout_ratio=0.2, - max_epochs_since_update=5, - train_freq=250, - eval_freq=20, - cuda=True, - tb_logger=None - ): - super(EnsembleDynamicsModel, self).__init__() - self._cuda = cuda - self.tb_logger = tb_logger - - self.network_size = network_size - self.elite_size = elite_size - self.state_size = state_size - self.action_size = action_size - self.reward_size = reward_size - - self.ensemble_model = EnsembleModel( - state_size, action_size, reward_size, network_size, hidden_size, use_decay=use_decay - ) - self.scaler = StandardScaler(state_size + action_size) - if self._cuda: - self.cuda() - - self.last_train_step = 0 - self.last_eval_step = 0 - self.train_freq = train_freq - self.eval_freq = eval_freq - self.ensemble_mse_losses = [] - self.model_variances = [] - - self._max_epochs_since_update = max_epochs_since_update - self.batch_size = batch_size - self.holdout_ratio = holdout_ratio - self.elite_model_idxes = [] - - def should_eval(self, envstep): - """ - Overview: - Determine whether you need to start the evaluation mode, if the number of training has reached\ - the maximum number of times to start the evaluator, return True - """ - if (envstep - self.last_eval_step) < self.eval_freq or self.last_train_step == 0: - return False - return True - - def should_train(self, envstep): - """ - Overview: - Determine whether you need to start the evaluation mode, if the number of training has reached\ - the maximum number of times to start the evaluator, return True - """ - if (envstep - self.last_train_step) < self.train_freq: - return False - return True - - def eval(self, data, envstep): - # load data - data = default_collate(data) - data['done'] = data['done'].float() - data['weight'] = data.get('weight', None) - obs = data['obs'] - action = data['action'] - reward = data['reward'] - next_obs = data['next_obs'] - if len(reward.shape) == 1: - reward = reward.unsqueeze(1) - - # build eval samples - inputs = torch.cat([obs, action], dim=1) - labels = torch.cat([reward, next_obs - obs], dim=1) - if self._cuda: - inputs = inputs.cuda() - labels = labels.cuda() - - # normalize - inputs = self.scaler.transform(inputs) - - # repeat for ensemble - inputs = inputs[None, :, :].repeat(self.network_size, 1, 1) - labels = labels[None, :, :].repeat(self.network_size, 1, 1) - - # eval - with torch.no_grad(): - mean, logvar = self.ensemble_model(inputs, ret_log_var=True) - loss, mse_loss = self.ensemble_model.loss(mean, logvar, labels) - ensemble_mse_loss = torch.pow(mean.mean(0) - labels[0], 2) - model_variance = mean.var(0) - self.tb_logger.add_scalar('env_model_step/eval_mse_loss', mse_loss.mean().item(), envstep) - self.tb_logger.add_scalar('env_model_step/eval_ensemble_mse_loss', ensemble_mse_loss.mean().item(), envstep) - self.tb_logger.add_scalar('env_model_step/eval_model_variances', model_variance.mean().item(), envstep) - - self.last_eval_step = envstep - - def train(self, buffer, train_iter, envstep): - # load data - data = buffer.sample(buffer.count(), train_iter) - data = default_collate(data) - data['done'] = data['done'].float() - data['weight'] = data.get('weight', None) - obs = data['obs'] - action = data['action'] - reward = data['reward'] - next_obs = data['next_obs'] - if len(reward.shape) == 1: - reward = reward.unsqueeze(1) - # build train samples - inputs = torch.cat([obs, action], dim=1) - labels = torch.cat([reward, next_obs - obs], dim=1) - if self._cuda: - inputs = inputs.cuda() - labels = labels.cuda() - # train - logvar = self._train(inputs, labels) - self.last_train_step = envstep - # log - if self.tb_logger is not None: - for k, v in logvar.items(): - self.tb_logger.add_scalar('env_model_step/' + k, v, envstep) - - def _train(self, inputs, labels): - #split - num_holdout = int(inputs.shape[0] * self.holdout_ratio) - train_inputs, train_labels = inputs[num_holdout:], labels[num_holdout:] - holdout_inputs, holdout_labels = inputs[:num_holdout], labels[:num_holdout] - - #normalize - self.scaler.fit(train_inputs) - train_inputs = self.scaler.transform(train_inputs) - holdout_inputs = self.scaler.transform(holdout_inputs) - - #repeat for ensemble - holdout_inputs = holdout_inputs[None, :, :].repeat(self.network_size, 1, 1) - holdout_labels = holdout_labels[None, :, :].repeat(self.network_size, 1, 1) - - self._epochs_since_update = 0 - self._snapshots = {i: (-1, 1e10) for i in range(self.network_size)} - self._save_states() - for epoch in itertools.count(): - - train_idx = torch.stack([torch.randperm(train_inputs.shape[0]) - for _ in range(self.network_size)]).to(train_inputs.device) - self.mse_loss = [] - for start_pos in range(0, train_inputs.shape[0], self.batch_size): - idx = train_idx[:, start_pos:start_pos + self.batch_size] - train_input = train_inputs[idx] - train_label = train_labels[idx] - mean, logvar = self.ensemble_model(train_input, ret_log_var=True) - loss, mse_loss = self.ensemble_model.loss(mean, logvar, train_label) - self.ensemble_model.train(loss) - self.mse_loss.append(mse_loss.mean().item()) - self.mse_loss = sum(self.mse_loss) / len(self.mse_loss) - - with torch.no_grad(): - holdout_mean, holdout_logvar = self.ensemble_model(holdout_inputs, ret_log_var=True) - _, holdout_mse_loss = self.ensemble_model.loss(holdout_mean, holdout_logvar, holdout_labels) - self.curr_holdout_mse_loss = holdout_mse_loss.mean().item() - break_train = self._save_best(epoch, holdout_mse_loss) - if break_train: - break - - self._load_states() - with torch.no_grad(): - holdout_mean, holdout_logvar = self.ensemble_model(holdout_inputs, ret_log_var=True) - _, holdout_mse_loss = self.ensemble_model.loss(holdout_mean, holdout_logvar, holdout_labels) - sorted_loss, sorted_loss_idx = holdout_mse_loss.sort() - sorted_loss = sorted_loss.detach().cpu().numpy().tolist() - sorted_loss_idx = sorted_loss_idx.detach().cpu().numpy().tolist() - self.elite_model_idxes = sorted_loss_idx[:self.elite_size] - self.top_holdout_mse_loss = sorted_loss[0] - self.middle_holdout_mse_loss = sorted_loss[self.network_size // 2] - self.bottom_holdout_mse_loss = sorted_loss[-1] - self.best_holdout_mse_loss = holdout_mse_loss.mean().item() - return { - 'mse_loss': self.mse_loss, - 'curr_holdout_mse_loss': self.curr_holdout_mse_loss, - 'best_holdout_mse_loss': self.best_holdout_mse_loss, - 'top_holdout_mse_loss': self.top_holdout_mse_loss, - 'middle_holdout_mse_loss': self.middle_holdout_mse_loss, - 'bottom_holdout_mse_loss': self.bottom_holdout_mse_loss, - } - - def _save_states(self, ): - self._states = copy.deepcopy(self.state_dict()) - - def _save_state(self, id): - state_dict = self.state_dict() - for k, v in state_dict.items(): - if 'weight' in k or 'bias' in k: - self._states[k].data[id] = copy.deepcopy(v.data[id]) - - def _load_states(self): - self.load_state_dict(self._states) - - def _save_best(self, epoch, holdout_losses): - updated = False - for i in range(len(holdout_losses)): - current = holdout_losses[i] - _, best = self._snapshots[i] - improvement = (best - current) / best - if improvement > 0.01: - self._snapshots[i] = (epoch, current) - self._save_state(i) - # self._save_state(i) - updated = True - # improvement = (best - current) / best - - if updated: - self._epochs_since_update = 0 - else: - self._epochs_since_update += 1 - if self._epochs_since_update > self._max_epochs_since_update: - return True - else: - return False - - def batch_predict(self, obs, action): - # to predict a batch - # norm and repeat for ensemble - inputs = self.scaler.transform(torch.cat([obs, action], dim=-1)).unsqueeze(0).repeat(self.network_size, 1, 1) - # predict - outputs, _ = self.ensemble_model(inputs, ret_log_var=False) - outputs = outputs.mean(0) - return outputs[:, 0], outputs[:, 1:] + obs - - def predict(self, obs, act, batch_size=8192, deterministic=True): - # to predict the whole buffer and return cpu tensor - # form inputs - if self._cuda: - obs = obs.cuda() - act = act.cuda() - inputs = torch.cat([obs, act], dim=1) - inputs = self.scaler.transform(inputs) - # predict - ensemble_mean, ensemble_var = [], [] - for i in range(0, inputs.shape[0], batch_size): - input = inputs[i:i + batch_size].unsqueeze(0).repeat(self.network_size, 1, 1) - b_mean, b_var = self.ensemble_model(input, ret_log_var=False) - ensemble_mean.append(b_mean) - ensemble_var.append(b_var) - ensemble_mean = torch.cat(ensemble_mean, 1) - ensemble_var = torch.cat(ensemble_var, 1) - ensemble_mean[:, :, 1:] += obs.unsqueeze(0) - ensemble_std = ensemble_var.sqrt() - # sample from the predicted distribution - if deterministic: - ensemble_sample = ensemble_mean - else: - ensemble_sample = ensemble_mean + torch.randn(**ensemble_mean.shape).to(ensemble_mean) * ensemble_std - # sample from ensemble - model_idxes = torch.from_numpy(np.random.choice(self.elite_model_idxes, size=len(obs))).to(inputs.device) - batch_idxes = torch.arange(len(obs)).to(inputs.device) - sample = ensemble_sample[model_idxes, batch_idxes] - rewards, next_obs = sample[:, :1], sample[:, 1:] - - return rewards.detach().cpu(), next_obs.detach().cpu() diff --git a/ding/model/template/tests/test_mbpo.py b/ding/model/template/tests/test_mbpo.py deleted file mode 100644 index 445a931758..0000000000 --- a/ding/model/template/tests/test_mbpo.py +++ /dev/null @@ -1,45 +0,0 @@ -import pytest -from itertools import product -import torch -from ding.model.template.model_based import EnsembleDynamicsModel -from ding.torch_utils import is_differentiable - -# constants -network_size = 3 -elite_size = 2 -hidden_size = 20 -# arguments -state_size = [16] -action_size = [16] -reward_size = [1, 2] -args = list(product(*[state_size, action_size, reward_size])) - - -@pytest.mark.unittest -class TestMBPO: - - def output_check(self, model, outputs): - if isinstance(outputs, torch.Tensor): - loss = outputs.sum() - elif isinstance(outputs, list): - loss = sum([t.sum() for t in outputs]) - elif isinstance(outputs, dict): - loss = sum([v.sum() for v in outputs.values()]) - is_differentiable(loss, model) - - @pytest.mark.parametrize('state_size, action_size, reward_size', args) - def test_mbpo(self, state_size, action_size, reward_size): - states = torch.rand(1280, state_size) - actions = torch.rand(1280, action_size) - - next_states = states + actions.mean(1, keepdim=True) - rewards = next_states.mean(1, keepdim=True).repeat(1, reward_size) - - inputs = torch.cat([states, actions], dim=1) - labels = torch.cat([rewards, next_states], dim=1) - - model = EnsembleDynamicsModel( - network_size, elite_size, state_size, action_size, reward_size, hidden_size, use_decay=True, cuda=False - ) - - model._train(inputs[:640], labels[:640]) diff --git a/ding/policy/command_mode_policy_instance.py b/ding/policy/command_mode_policy_instance.py index 7e659d485c..e883049166 100644 --- a/ding/policy/command_mode_policy_instance.py +++ b/ding/policy/command_mode_policy_instance.py @@ -22,6 +22,7 @@ from .td3_vae import TD3VAEPolicy from .td3_bc import TD3BCPolicy from .sac import SACPolicy, SACDiscretePolicy +from .mbpolicy.mbsac import MBSACPolicy from .qmix import QMIXPolicy from .wqmix import WQMIXPolicy from .collaq import CollaQPolicy @@ -246,6 +247,11 @@ class SACCommandModePolicy(SACPolicy, DummyCommandModePolicy): pass +@POLICY_REGISTRY.register('mbsac_command') +class MBSACCommandModePolicy(MBSACPolicy, DummyCommandModePolicy): + pass + + @POLICY_REGISTRY.register('cql_command') class CQLCommandModePolicy(CQLPolicy, DummyCommandModePolicy): pass diff --git a/ding/policy/mbpolicy/__init__.py b/ding/policy/mbpolicy/__init__.py new file mode 100644 index 0000000000..7d528cd15b --- /dev/null +++ b/ding/policy/mbpolicy/__init__.py @@ -0,0 +1 @@ +from .mbsac import MBSACPolicy diff --git a/ding/policy/mbpolicy/mbsac.py b/ding/policy/mbpolicy/mbsac.py new file mode 100644 index 0000000000..37c3777d22 --- /dev/null +++ b/ding/policy/mbpolicy/mbsac.py @@ -0,0 +1,221 @@ +from typing import Dict, Any, List +from functools import partial +import copy + +import torch +from torch import Tensor +from torch import nn +from torch.distributions import Normal, Independent, TransformedDistribution, TanhTransform +from easydict import EasyDict + +from ding.torch_utils import to_device +from ding.utils import POLICY_REGISTRY, deep_merge_dicts +from ding.policy import SACPolicy +from ding.rl_utils import generalized_lambda_returns +from ding.policy.common_utils import default_preprocess_learn + +from .utils import q_evaluation + + +@POLICY_REGISTRY.register('mbsac') +class MBSACPolicy(SACPolicy): + """ + Overview: + Model based SAC with value expansion (arXiv: 1803.00101)\ + and value gradient (arXiv: 1510.09142) w.r.t lambda-return. + + Config: + == ==================== ======== ============= ================================== + ID Symbol Type Default Value Description + == ==================== ======== ============= ================================== + 1 ``learn._lambda`` float 0.8 | Lambda for TD-lambda return. + 2 ``learn.grad_clip` float 100.0 | Max norm of gradients. + 3 ``learn.sample_state`` bool True | Whether to sample states or tra- + | nsitions from environment buffer. + == ==================== ======== ============= ================================== + + .. note:: + For other configs, please refer to ding.policy.sac.SACPolicy. + """ + + config = dict( + learn=dict( + # (float) Lambda for TD-lambda return. + lambda_=0.8, + # (float) Max norm of gradients. + grad_clip=100, + # (bool) Whether to sample states or transitions from environment buffer. + sample_state=True, + ) + ) + + @classmethod + def default_config(cls: type) -> EasyDict: + cfg = copy.deepcopy(cls.config) + cfg = EasyDict(deep_merge_dicts(super().config, cfg)) + cfg.cfg_type = cls.__name__ + 'Dict' + return cfg + + def _init_learn(self) -> None: + super()._init_learn() + + self._lambda = self._cfg.learn.lambda_ + self._grad_clip = self._cfg.learn.grad_clip + self._sample_state = self._cfg.learn.sample_state + + self._target_model.requires_grad_(False) + + # TODO: auto alpha + self._auto_alpha = False + + # TODO: TanhTransform leads to NaN + def actor_fn(obs: Tensor): + # (mu, sigma) = self._learn_model.forward( + # obs, mode='compute_actor')['logit'] + # # enforce action bounds + # dist = TransformedDistribution( + # Independent(Normal(mu, sigma), 1), [TanhTransform()]) + # action = dist.rsample() + # log_prob = dist.log_prob(action) + # return action, -self._alpha.detach() * log_prob + (mu, sigma) = self._learn_model.forward(obs, mode='compute_actor')['logit'] + dist = Independent(Normal(mu, sigma), 1) + pred = dist.rsample() + action = torch.tanh(pred) + + log_prob = dist.log_prob( + pred + ) + 2 * (pred + torch.nn.functional.softplus(-2. * pred) - torch.log(torch.tensor(2.))).sum(-1) + return action, -self._alpha.detach() * log_prob + + self._actor_fn = actor_fn + + def critic_fn(obss: Tensor, actions: Tensor, model: nn.Module): + eval_data = {'obs': obss, 'action': actions} + q_values = model.forward(eval_data, mode='compute_critic')['q_value'] + return q_values + + self._critic_fn = critic_fn + + def _forward_learn(self, data: dict, world_model, envstep) -> Dict[str, Any]: + # preprocess data + data = default_preprocess_learn( + data, + use_priority=self._priority, + use_priority_IS_weight=self._cfg.priority_IS_weight, + ignore_done=self._cfg.learn.ignore_done, + use_nstep=False + ) + if self._cuda: + data = to_device(data, self._device) + + if len(data['action'].shape) == 1: + data['action'] = data['action'].unsqueeze(1) + + self._learn_model.train() + self._target_model.train() + + # TODO: use treetensor + # rollout length is determined by world_model.rollout_length_scheduler + if self._sample_state: + # data['reward'], ... are not used + obss, actions, rewards, aug_rewards, dones = \ + world_model.rollout(data['obs'], self._actor_fn, envstep) + else: + obss, actions, rewards, aug_rewards, dones = \ + world_model.rollout(data['next_obs'], self._actor_fn, envstep) + obss = torch.concat([data['obs'][None, :], obss]) + actions = torch.concat([data['action'][None, :], actions]) + rewards = torch.concat([data['reward'][None, :], rewards]) + aug_rewards = torch.concat([torch.zeros_like(data['reward'])[None, :], aug_rewards]) + dones = torch.concat([data['done'][None, :], dones]) + + # (T+1, B) + target_q_values = q_evaluation(obss, actions, partial(self._critic_fn, model=self._target_model)) + if self._twin_critic: + target_q_values = torch.min(target_q_values[0], target_q_values[1]) + aug_rewards + else: + target_q_values = target_q_values + aug_rewards + + # (T, B) + lambda_return = generalized_lambda_returns(target_q_values, rewards, self._gamma, self._lambda, dones[1:]) + + # (T, B) + # If S_t terminates, we should not consider loss from t+1,... + weight = (1 - dones[:-1].detach()).cumprod(dim=0) + + # (T+1, B) + q_values = q_evaluation(obss.detach(), actions.detach(), partial(self._critic_fn, model=self._learn_model)) + if self._twin_critic: + critic_loss = 0.5 * torch.square(q_values[0][:-1] - lambda_return.detach()) \ + + 0.5 * torch.square(q_values[1][:-1] - lambda_return.detach()) + else: + critic_loss = 0.5 * torch.square(q_values[:-1] - lambda_return.detach()) + + # value expansion loss + critic_loss = (critic_loss * weight).mean() + + # value gradient loss + policy_loss = -(lambda_return * weight).mean() + + # alpha_loss = None + + loss_dict = { + 'critic_loss': critic_loss, + 'policy_loss': policy_loss, + # 'alpha_loss': alpha_loss.detach(), + } + + norm_dict = self._update(loss_dict) + + # ============= + # after update + # ============= + self._forward_learn_cnt += 1 + # target update + self._target_model.update(self._learn_model.state_dict()) + + return { + 'cur_lr_q': self._optimizer_q.defaults['lr'], + 'cur_lr_p': self._optimizer_policy.defaults['lr'], + 'alpha': self._alpha.item(), + 'target_q_value': target_q_values.detach().mean().item(), + **norm_dict, + **loss_dict, + } + + def _update(self, loss_dict): + # update critic + self._optimizer_q.zero_grad() + loss_dict['critic_loss'].backward() + critic_norm = nn.utils.clip_grad_norm_(self._model.critic.parameters(), self._grad_clip) + self._optimizer_q.step() + # update policy + self._optimizer_policy.zero_grad() + loss_dict['policy_loss'].backward() + policy_norm = nn.utils.clip_grad_norm_(self._model.actor.parameters(), self._grad_clip) + self._optimizer_policy.step() + # update temperature + # self._alpha_optim.zero_grad() + # loss_dict['alpha_loss'].backward() + # self._alpha_optim.step() + return {'policy_norm': policy_norm, 'critic_norm': critic_norm} + + def _monitor_vars_learn(self) -> List[str]: + r""" + Overview: + Return variables' name if variables are to used in monitor. + Returns: + - vars (:obj:`List[str]`): Variables' name list. + """ + alpha_loss = ['alpha_loss'] if self._auto_alpha else [] + return [ + 'policy_loss', + 'critic_loss', + 'policy_norm', + 'critic_norm', + 'cur_lr_q', + 'cur_lr_p', + 'alpha', + 'target_q_value', + ] + alpha_loss diff --git a/ding/policy/mbpolicy/tests/test_mbpolicy_utils.py b/ding/policy/mbpolicy/tests/test_mbpolicy_utils.py new file mode 100644 index 0000000000..74636f45dc --- /dev/null +++ b/ding/policy/mbpolicy/tests/test_mbpolicy_utils.py @@ -0,0 +1,36 @@ +import pytest +import torch +from ding.policy.mbpolicy.utils import flatten_batch, unflatten_batch, q_evaluation + + +@pytest.mark.unittest +def test_flatten_unflattent_batch(): + T, B, C, H, W = 10, 20, 3, 255, 255 + data = torch.randn(T, B, C, H, W) + data, batch_dim = flatten_batch(data, nonbatch_dims=3) + assert data.shape == (T * B, C, H, W) and batch_dim == (T, B) + data = unflatten_batch(data, batch_dim) + assert data.shape == (T, B, C, H, W) + + T, B, N = 10, 20, 100 + data = torch.randn(T, B, N) + data, batch_dim = flatten_batch(data, nonbatch_dims=1) + assert data.shape == (T * B, N) and batch_dim == (T, B) + data = unflatten_batch(data, batch_dim) + assert data.shape == (T, B, N) + + +@pytest.mark.unittest +def test_q_evaluation(): + T, B, O, A = 10, 20, 100, 30 + obss = torch.randn(T, B, O) + actions = torch.randn(T, B, A) + + def fake_q_fn(obss, actions): + # obss: flatten_B * O + # actions: flatten_B * A + # return: flatten_B + return obss.sum(-1) + + q_value = q_evaluation(obss, actions, fake_q_fn) + assert q_value.shape == (T, B) diff --git a/ding/policy/mbpolicy/tests/test_mbsac.py b/ding/policy/mbpolicy/tests/test_mbsac.py new file mode 100644 index 0000000000..ab32ead675 --- /dev/null +++ b/ding/policy/mbpolicy/tests/test_mbsac.py @@ -0,0 +1,23 @@ +import pytest +import torch +from torch.distributions import Normal, Independent, TransformedDistribution, TanhTransform +from ding.policy.mbpolicy import MBSACPolicy + + +@pytest.mark.unittest +def test_TanhTransform(): + mu, sigma = torch.randn(3, 3), torch.ones(3, 3) + + dist = Independent(Normal(mu, sigma), 1) + pred = dist.rsample() + action = torch.tanh(pred) + + log_prob_1 = dist.log_prob(pred + ) + 2 * (pred + torch.nn.functional.softplus(-2. * pred) - + torch.log(torch.tensor(2.))).sum(-1) + + tanh_dist = TransformedDistribution(Independent(Normal(mu, sigma), 1), [TanhTransform()]) + + log_prob_2 = tanh_dist.log_prob(action) + + assert (log_prob_1 - log_prob_2).mean().abs() < 1e-5 diff --git a/ding/policy/mbpolicy/utils.py b/ding/policy/mbpolicy/utils.py new file mode 100644 index 0000000000..391401ca09 --- /dev/null +++ b/ding/policy/mbpolicy/utils.py @@ -0,0 +1,88 @@ +from typing import Callable, Tuple, Union + +from torch import Tensor, Size + + +def flatten_batch(x: Tensor, nonbatch_dims=1) -> Tuple[Tensor, Size]: + """ + Overview: + Flatten the first (dim - nonbatch_dims) dimensions of a tensor as batch dimension. + (T, B, X) => (T*B, X) + Arguments: + - x (:obj:`torch.Tensor`): the tensor to flatten + - nonbatch_dims (:obj:`int`): the number of dimensions that is not flattened as\ + batch dimension.z + Returns: + - x (:obj:`torch.Tensor`): the flattened tensor + - batch_dim: the flattened dimension of the original tensor, which can be used to\ + reverse the operation. + + Examples:: + + >>> x = torch.ones(10, 20, 4, 8) + >>> x, batch_dim = flatten_batch(x, 2) + >>> x.shape == (200, 4, 8) + >>> batch_dim == (10, 20) + """ + if nonbatch_dims > 0: + batch_dim = x.shape[:-nonbatch_dims] + x = x.view(-1, *(x.shape[-nonbatch_dims:])) + return x, batch_dim + else: + batch_dim = x.shape + x = x.view(-1) + return x, batch_dim + + +def unflatten_batch(x: Tensor, batch_dim: Union[Size, Tuple]) -> Tensor: + """ + Overview: + Unflatten the batch dimension of a tensor. + (T*B, X) => (T, B, X) + Arguments: + - x (:obj:`torch.Tensor`): the tensor to unflatten + - batch_dim (:obj:`torch.Size`): the dimensions that are flattened + Returns: + - x (:obj:`torch.Tensor`): the original unflattened tensor + + Examples:: + + >>> x = torch.ones(10, 20, 4, 8) + >>> x, batch_dim = flatten_batch(x, 2) + >>> x.shape == (200, 4, 8) + >>> batch_dim == (10, 20) + >>> x = unflatten_batch(x, batch_dim) + >>> x.shape == (10, 20, 4, 8) + """ + return x.view(*batch_dim, *x.shape[1:]) + + +def q_evaluation(obss: Tensor, actions: Tensor, q_critic_fn: Callable[[Tensor, Tensor], + Tensor]) -> Union[Tensor, Tuple[Tensor, Tensor]]: + """ + Overview: + Evaluate observation&action pairs along the trajectory + Arguments: + - obss (:obj:`torch.Tensor`): the observations along the trajectory + - actions (:obj:`torch.Size`): the actions along the trajectory + - q_critic_fn (:obj:`Callable`): the unified API Q(S_t, A_t) + Returns: + - q_value (:obj:`torch.Tensor`): the action-value function evaluated along the trajectory + Shapes: + N: time step + B: batch size + O: observation dimension + A: action dimension + + - obss: [N, B, O] + - actions: [N, B, A] + - q_value: [N, B] + + """ + obss, dim = flatten_batch(obss, 1) + actions, _ = flatten_batch(actions, 1) + q_values = q_critic_fn(obss, actions) + # twin critic + if isinstance(q_values, list): + return [unflatten_batch(q_values[0], dim), unflatten_batch(q_values[1], dim)] + return unflatten_batch(q_values, dim) diff --git a/ding/rl_utils/td.py b/ding/rl_utils/td.py index e72b519370..443ddcf00c 100644 --- a/ding/rl_utils/td.py +++ b/ding/rl_utils/td.py @@ -999,7 +999,11 @@ def td_lambda_error(data: namedtuple, gamma: float = 0.9, lambda_: float = 0.8) def generalized_lambda_returns( - bootstrap_values: torch.Tensor, rewards: torch.Tensor, gammas: float, lambda_: float + bootstrap_values: torch.Tensor, + rewards: torch.Tensor, + gammas: float, + lambda_: float, + done: Optional[torch.Tensor] = None ) -> torch.Tensor: r""" Overview: @@ -1014,6 +1018,8 @@ def generalized_lambda_returns( discount factor for each step (from 0 to T-1), of size [T_traj, batchsize] - lambda (:obj:`torch.Tensor` or :obj:`float`): determining the mix of bootstrapping vs further accumulation of multistep returns at each timestep, of size [T_traj, batchsize] + - done (:obj:`torch.Tensor` or :obj:`float`): + whether the episode done at current step (from 0 to T-1), of size [T_traj, batchsize] Returns: - return (:obj:`torch.Tensor`): Computed lambda return value for each state from 0 to T-1, of size [T_traj, batchsize] @@ -1023,11 +1029,15 @@ def generalized_lambda_returns( if not isinstance(lambda_, torch.Tensor): lambda_ = lambda_ * torch.ones_like(rewards) bootstrap_values_tp1 = bootstrap_values[1:, :] - return multistep_forward_view(bootstrap_values_tp1, rewards, gammas, lambda_) + return multistep_forward_view(bootstrap_values_tp1, rewards, gammas, lambda_, done) def multistep_forward_view( - bootstrap_values: torch.Tensor, rewards: torch.Tensor, gammas: float, lambda_: float + bootstrap_values: torch.Tensor, + rewards: torch.Tensor, + gammas: float, + lambda_: float, + done: Optional[torch.Tensor] = None ) -> torch.Tensor: r""" Overview: @@ -1041,9 +1051,6 @@ def multistep_forward_view( ``` Assuming the first dim of input tensors correspond to the index in batch - There is no special handling for terminal state value, - if some state has reached the terminal, just fill in zeros for values and rewards beyond terminal - (including the terminal state, which is, bootstrap_values[terminal] should also be 0) Arguments: - bootstrap_values (:obj:`torch.Tensor`): estimation of the value at *step 1 to T*, of size [T_traj, batchsize] - rewards (:obj:`torch.Tensor`): the returns from 0 to T-1, of size [T_traj, batchsize] @@ -1051,17 +1058,23 @@ def multistep_forward_view( - lambda (:obj:`torch.Tensor`): determining the mix of bootstrapping vs further accumulation of \ multistep returns at each timestep of size [T_traj, batchsize], the element for T-1 is ignored \ and effectively set to 0, as there is no information about future rewards. + - done (:obj:`torch.Tensor` or :obj:`float`): + whether the episode done at current step (from 0 to T-1), of size [T_traj, batchsize] Returns: - ret (:obj:`torch.Tensor`): Computed lambda return value \ for each state from 0 to T-1, of size [T_traj, batchsize] """ result = torch.empty_like(rewards) + if done is None: + done = torch.zeros_like(rewards) # Forced cutoff at the last one - result[-1, :] = rewards[-1, :] + gammas[-1, :] * bootstrap_values[-1, :] + result[-1, :] = rewards[-1, :] + (1 - done[-1, :]) * gammas[-1, :] * bootstrap_values[-1, :] discounts = gammas * lambda_ for t in reversed(range(rewards.size()[0] - 1)): - result[t, :] = rewards[t, :] \ - + discounts[t, :] * result[t + 1, :] \ - + (gammas[t, :] - discounts[t, :]) * bootstrap_values[t, :] + result[t, :] = rewards[t, :] + (1 - done[t, :]) * \ + ( + discounts[t, :] * result[t + 1, :] + + (gammas[t, :] - discounts[t, :]) * bootstrap_values[t, :] + ) return result diff --git a/ding/utils/__init__.py b/ding/utils/__init__.py index 608773c1af..b4229c4982 100644 --- a/ding/utils/__init__.py +++ b/ding/utils/__init__.py @@ -19,7 +19,8 @@ from .registry_factory import registries, POLICY_REGISTRY, ENV_REGISTRY, LEARNER_REGISTRY, COMM_LEARNER_REGISTRY, \ SERIAL_COLLECTOR_REGISTRY, PARALLEL_COLLECTOR_REGISTRY, COMM_COLLECTOR_REGISTRY, \ COMMANDER_REGISTRY, LEAGUE_REGISTRY, PLAYER_REGISTRY, MODEL_REGISTRY, ENV_MANAGER_REGISTRY, ENV_WRAPPER_REGISTRY, \ - REWARD_MODEL_REGISTRY, BUFFER_REGISTRY, DATASET_REGISTRY, SERIAL_EVALUATOR_REGISTRY, MQ_REGISTRY + REWARD_MODEL_REGISTRY, BUFFER_REGISTRY, DATASET_REGISTRY, SERIAL_EVALUATOR_REGISTRY, MQ_REGISTRY, \ + WORLD_MODEL_REGISTRY from .scheduler_helper import Scheduler from .segment_tree import SumSegmentTree, MinSegmentTree, SegmentTree from .slurm_helper import find_free_port_slurm, node_to_host, node_to_partition diff --git a/ding/utils/registry_factory.py b/ding/utils/registry_factory.py index 51e56f9375..b60ad917c8 100644 --- a/ding/utils/registry_factory.py +++ b/ding/utils/registry_factory.py @@ -18,6 +18,7 @@ DATASET_REGISTRY = Registry() SERIAL_EVALUATOR_REGISTRY = Registry() MQ_REGISTRY = Registry() +WORLD_MODEL_REGISTRY = Registry() registries = { 'policy': POLICY_REGISTRY, @@ -38,4 +39,5 @@ 'dataset': DATASET_REGISTRY, 'serial_evaluator': SERIAL_EVALUATOR_REGISTRY, 'message_queue': MQ_REGISTRY, + 'world_model': WORLD_MODEL_REGISTRY, } diff --git a/ding/worker/learner/base_learner.py b/ding/worker/learner/base_learner.py index ac89d763ac..0ceac89eea 100644 --- a/ding/worker/learner/base_learner.py +++ b/ding/worker/learner/base_learner.py @@ -177,7 +177,7 @@ def register_hook(self, hook: LearnerHook) -> None: """ add_learner_hook(self._hooks, hook) - def train(self, data: dict, envstep: int = -1) -> None: + def train(self, data: dict, envstep: int = -1, policy_kwargs: Optional[dict] = None) -> None: """ Overview: Given training data, implement network update for one iteration and update related variables. @@ -198,8 +198,11 @@ def train(self, data: dict, envstep: int = -1) -> None: assert hasattr(self, '_policy'), "please set learner policy" self.call_hook('before_iter') + if policy_kwargs is None: + policy_kwargs = {} + # Forward - log_vars = self._policy.forward(data) + log_vars = self._policy.forward(data, **policy_kwargs) # Update replay buffer's priority info if isinstance(log_vars, dict): diff --git a/ding/world_model/__init__.py b/ding/world_model/__init__.py new file mode 100644 index 0000000000..45cb5bea35 --- /dev/null +++ b/ding/world_model/__init__.py @@ -0,0 +1,2 @@ +from .base_world_model import WorldModel, DynaWorldModel, DreamWorldModel, HybridWorldModel, \ + get_world_model_cls, create_world_model diff --git a/ding/world_model/base_world_model.py b/ding/world_model/base_world_model.py new file mode 100644 index 0000000000..29f228d4c8 --- /dev/null +++ b/ding/world_model/base_world_model.py @@ -0,0 +1,354 @@ +from typing import Tuple, Callable +from collections import namedtuple +from abc import ABC, abstractmethod + +import torch +from torch import Tensor, nn +from easydict import EasyDict + +from ding.worker import IBuffer +from ding.envs import BaseEnv +from ding.utils import deep_merge_dicts +from ding.world_model.utils import get_rollout_length_scheduler + +from ding.utils import import_module, WORLD_MODEL_REGISTRY + + +def get_world_model_cls(cfg): + import_module(cfg.get('import_names', [])) + return WORLD_MODEL_REGISTRY.get(cfg.type) + + +def create_world_model(cfg, *args, **kwargs): + import_module(cfg.get('import_names', [])) + return WORLD_MODEL_REGISTRY.build(cfg.type, cfg, *args, **kwargs) + + +class WorldModel(ABC): + """ + Overview: + Abstract baseclass for world model. + + Interfaces: + should_train, should_eval, train, eval, step + """ + + config = dict( + train_freq=250, # w.r.t environment step + eval_freq=250, # w.r.t environment step + cuda=True, + rollout_length_scheduler=dict( + type='linear', + rollout_start_step=20000, + rollout_end_step=150000, + rollout_length_min=1, + rollout_length_max=25, + ) + ) + + def __init__(self, cfg: dict, env: BaseEnv, tb_logger: 'SummaryWriter'): # noqa + self.cfg = cfg + self.env = env + self.tb_logger = tb_logger + + self._cuda = cfg.cuda + self.train_freq = cfg.train_freq + self.eval_freq = cfg.eval_freq + self.rollout_length_scheduler = get_rollout_length_scheduler(cfg.rollout_length_scheduler) + + self.last_train_step = 0 + self.last_eval_step = 0 + + @classmethod + def default_config(cls: type) -> EasyDict: + # can not call default_config() recursively + # because config will be overwritten by subclasses + merge_cfg = EasyDict(cfg_type=cls.__name__ + 'Dict') + while cls != ABC: + merge_cfg = deep_merge_dicts(merge_cfg, cls.config) + cls = cls.__base__ + return merge_cfg + + def should_train(self, envstep: int): + """ + Overview: + Check whether need to train world model. + """ + return (envstep - self.last_train_step) >= self.train_freq + + def should_eval(self, envstep: int): + """ + Overview: + Check whether need to evaluate world model. + """ + return (envstep - self.last_eval_step) >= self.eval_freq and self.last_train_step != 0 + + @abstractmethod + def train(self, env_buffer: IBuffer, envstep: int, train_iter: int): + """ + Overview: + Train world model using data from env_buffer. + Arguments: + - env_buffer (:obj:`IBuffer`): the buffer which collects real environment steps + - envstep (:obj:`int`): the current number of environment steps in real environment + - train_iter (:obj:`int`): the current number of policy training iterations + """ + raise NotImplementedError + + @abstractmethod + def eval(self, env_buffer: IBuffer, envstep: int, train_iter: int): + """ + Overview: + Evaluate world model using data from env_buffer. + Arguments: + - env_buffer (:obj:`IBuffer`): the buffer that collects real environment steps + - envstep (:obj:`int`): the current number of environment steps in real environment + - train_iter (:obj:`int`): the current number of policy training iterations + """ + raise NotImplementedError + + @abstractmethod + def step(self, obs: Tensor, action: Tensor) -> Tuple[Tensor, Tensor, Tensor]: + """ + Overview: + Take one step in world model. + Arguments: + - obs (:obj:`torch.Tensor`): current observations S_t + - action (:obj:`torch.Tensor`): current actions A_t + Returns: + - reward (:obj:`torch.Tensor`): rewards R_t + - next_obs (:obj:`torch.Tensor`): next observations S_t+1 + - done (:obj:`torch.Tensor`): whether the episodes ends + Shapes: + B: batch size + O: observation dimension + A: action dimension + + - obs: [B, O] + - action: [B, A] + - reward: [B, ] + - next_obs: [B, O] + - done: [B, ] + """ + raise NotImplementedError + + +class DynaWorldModel(WorldModel, ABC): + """ + Overview: + Dyna-style world model (summarized in arXiv: 1907.02057) which stores and\ + reuses imagination rollout in the imagination buffer. + + Interfaces: + sample, fill_img_buffer, should_train, should_eval, train, eval, step + """ + + config = dict( + other=dict( + real_ratio=0.05, + rollout_retain=4, + rollout_batch_size=100000, + imagination_buffer=dict( + type='elastic', + replay_buffer_size=6000000, + deepcopy=False, + enable_track_used_data=False, + # set_buffer_size=set_buffer_size, + periodic_thruput_seconds=60, + ), + ) + ) + + def __init__(self, cfg: dict, env: BaseEnv, tb_logger: 'SummaryWriter'): # noqa + super().__init__(cfg, env, tb_logger) + self.real_ratio = cfg.other.real_ratio + self.rollout_batch_size = cfg.other.rollout_batch_size + self.rollout_retain = cfg.other.rollout_retain + self.buffer_size_scheduler = \ + lambda x: self.rollout_length_scheduler(x) * self.rollout_batch_size * self.rollout_retain + + def sample(self, env_buffer: IBuffer, img_buffer: IBuffer, batch_size: int, train_iter: int) -> dict: + """ + Overview: + Sample from the combination of environment buffer and imagination buffer with\ + certain ratio to generate batched data for policy training. + Arguments: + - policy (:obj:`namedtuple`): policy in collect mode + - env_buffer (:obj:`IBuffer`): the buffer that collects real environment steps + - img_buffer (:obj:`IBuffer`): the buffer that collects imagination steps + - batch_size (:obj:`int`): the batch size for policy training + - train_iter (:obj:`int`): the current number of policy training iterations + Returns: + - data (:obj:`int`): the training data for policy training + """ + env_batch_size = int(batch_size * self.real_ratio) + img_batch_size = batch_size - env_batch_size + env_data = env_buffer.sample(env_batch_size, train_iter) + img_data = img_buffer.sample(img_batch_size, train_iter) + train_data = env_data + img_data + return train_data + + def fill_img_buffer( + self, policy: namedtuple, env_buffer: IBuffer, img_buffer: IBuffer, envstep: int, train_iter: int + ): + """ + Overview: + Sample from the env_buffer, rollouts to generate new data, and push them into the img_buffer. + Arguments: + - policy (:obj:`namedtuple`): policy in collect mode + - env_buffer (:obj:`IBuffer`): the buffer that collects real environment steps + - img_buffer (:obj:`IBuffer`): the buffer that collects imagination steps + - envstep (:obj:`int`): the current number of environment steps in real environment + - train_iter (:obj:`int`): the current number of policy training iterations + """ + from ding.torch_utils import to_tensor + from ding.envs import BaseEnvTimestep + from ding.worker.collector.base_serial_collector import to_tensor_transitions + + def step(obs, act): + # This function has the same input and output format as env manager's step + data_id = list(obs.keys()) + obs = torch.stack([obs[id] for id in data_id], dim=0) + act = torch.stack([act[id] for id in data_id], dim=0) + with torch.no_grad(): + rewards, next_obs, terminals = self.step(obs, act) + # terminals = self.termination_fn(next_obs) + timesteps = { + id: BaseEnvTimestep(n, r, d, {}) + for id, n, r, d in zip(data_id, + next_obs.cpu().numpy(), + rewards.cpu().numpy(), + terminals.cpu().numpy()) + } + return timesteps + + # set rollout length + rollout_length = self.rollout_length_scheduler(envstep) + # load data + data = env_buffer.sample(self.rollout_batch_size, train_iter, replace=True) + obs = {id: data[id]['obs'] for id in range(len(data))} + # rollout + buffer = [[] for id in range(len(obs))] + new_data = [] + for i in range(rollout_length): + # get action + obs = to_tensor(obs, dtype=torch.float32) + policy_output = policy.forward(obs) + actions = {id: output['action'] for id, output in policy_output.items()} + # predict next obs and reward + # timesteps = self.step(obs, actions, env_model) + timesteps = step(obs, actions) + obs_new = {} + for id, timestep in timesteps.items(): + transition = policy.process_transition(obs[id], policy_output[id], timestep) + transition['collect_iter'] = train_iter + buffer[id].append(transition) + if not timestep.done: + obs_new[id] = timestep.obs + if timestep.done or i + 1 == rollout_length: + transitions = to_tensor_transitions(buffer[id]) + train_sample = policy.get_train_sample(transitions) + new_data.extend(train_sample) + if len(obs_new) == 0: + break + obs = obs_new + + img_buffer.push(new_data, cur_collector_envstep=envstep) + + +class DreamWorldModel(WorldModel, ABC): + """ + Overview: + Dreamer-style world model which uses each imagination rollout only once\ + and backpropagate through time(rollout) to optimize policy. + + Interfaces: + rollout, should_train, should_eval, train, eval, step + """ + + def rollout(self, obs: Tensor, actor_fn: Callable[[Tensor], Tuple[Tensor, Tensor]], + envstep: int) -> Tuple[Tensor, Tensor, Tensor, Tensor, Tensor]: + """ + Overview: + Generate batched imagination rollouts starting from the current observations. + This function is useful for value gradients where the policy is optimized by BPTT. + Arguments: + - obs (:obj:`Tensor`): the current observations S_t + - actor_fn (:obj:`Callable`): the unified API (A_t, H_t) = pi(S_t) + - envstep (:obj:`int`): the current number of environment steps in real environment + Returns: + - obss (:obj:`Tensor`): S_t, ... S_t+n + - actions (:obj:`Tensor`): A_t, ..., A_t+n + - rewards (:obj:`Tensor`): R_t, ..., R_t+n-1 + - aug_rewards (:obj:`Tensor`): H_t', ..., H_t+n, this can be entropy bonus as in SAC,\ + otherwise it should be a zero tensor + - dones (:obj:`Tensor`): done_t, ..., done_t+n + Shapes: + N: time step + B: batch size + O: observation dimension + A: action dimension + + - obss: [N+1, B, O], where obss[0] are the real observations + - actions: [N+1, B, A] + - rewards: [N, B] + - aug_rewards: [N+1, B] + - dones: [N+1, B] + + .. note:: + - The rollout length is determined by rollout length scheduler. + + - actor_fn's inputs and outputs shape are similar to WorldModel.step() + """ + horizon = self.rollout_length_scheduler(envstep) + device = 'cuda' if self._cuda else 'cpu' + if isinstance(self, nn.Module): + # Rollouts should propagate gradients only to policy, + # so make sure that the world model is not updated by rollout. + self.requires_grad_(False) + obss = [obs] + actions = [] + rewards = [] + aug_rewards = [] # -temperature*logprob + dones = [torch.zeros_like(obs.sum(-1), device=device)] + for _ in range(horizon): + action, aug_reward = actor_fn(obs) + # done: probability of termination + reward, obs, done = self.step(obs, action) + if len(reward.shape) == 2: + reward = reward.squeeze(1) + if len(done.shape) == 2: + done = done.squeeze(1) + reward = reward + aug_reward + obss.append(obs) + actions.append(action) + rewards.append(reward) + aug_rewards.append(aug_reward) + dones.append(done) + action, aug_reward = actor_fn(obs) + actions.append(action) + aug_rewards.append(aug_reward) + if isinstance(self, nn.Module): + self.requires_grad_(True) + return ( + torch.stack(obss), + torch.stack(actions), + # rewards is an empty list when horizon=0 + torch.stack(rewards) if rewards else torch.tensor(rewards, device=device), + torch.stack(aug_rewards), + torch.stack(dones) + ) + + +class HybridWorldModel(DynaWorldModel, DreamWorldModel, ABC): + """ + Overview: + The hybrid model that combines reused and on-the-fly rollouts. + + Interfaces: + rollout, sample, fill_img_buffer, should_train, should_eval, train, eval, step + """ + + def __init__(self, cfg: dict, env: BaseEnv, tb_logger: 'SummaryWriter'): # noqa + DynaWorldModel.__init__(self, cfg, env, tb_logger) + DreamWorldModel.__init__(self, cfg, env, tb_logger) diff --git a/ding/world_model/ddppo.py b/ding/world_model/ddppo.py new file mode 100644 index 0000000000..3c2cfca675 --- /dev/null +++ b/ding/world_model/ddppo.py @@ -0,0 +1,509 @@ +import itertools +import numpy as np +import multiprocessing +import copy +import torch +from torch import nn + +from scipy.spatial import KDTree +from ding.utils import WORLD_MODEL_REGISTRY +from ding.utils.data import default_collate +from ding.world_model.base_world_model import HybridWorldModel +from ding.world_model.model.ensemble import EnsembleModel, StandardScaler + + +#======================= Helper functions ======================= +def get_neighbor_index(data, k): + """ + data: [B, N] + k: int + + ret: [B, k] + """ + data = data.cpu().numpy() + tree = KDTree(data) + global tree_query + + # tree_query = lambda datapoint: tree.query(datapoint, k=k+1)[1][1:] + def tree_query(datapoint): + return tree.query(datapoint, k=k + 1)[1][1:] + + # TODO: multiprocessing + pool = multiprocessing.Pool(processes=multiprocessing.cpu_count()) + nn_index = torch.from_numpy(np.array(list(pool.map(tree_query, data)), dtype=np.int32)).to(torch.long) + pool.close() + return nn_index + + +def get_batch_jacobian(net, x, noutputs): # x: b, in dim, noutpouts: out dim + x = x.unsqueeze(1) # b, 1 ,in_dim + n = x.size()[0] + x = x.repeat(1, noutputs, 1) # b, out_dim, in_dim + x.requires_grad_(True) + y = net(x) + upstream_gradient = torch.eye(noutputs).reshape(1, noutputs, noutputs).repeat(n, 1, 1).to(x.device) + re = torch.autograd.grad(y, x, upstream_gradient, create_graph=True)[0] + + return re + + +class EnsembleGradientModel(EnsembleModel): + + def train(self, loss, loss_reg, reg): + self.optimizer.zero_grad() + + loss += 0.01 * torch.sum(self.max_logvar) - 0.01 * torch.sum(self.min_logvar) + loss += reg * loss_reg + if self.use_decay: + loss += self.get_decay_loss() + + loss.backward() + + self.optimizer.step() + + +# TODO: derive from MBPO instead of implementing from scratch +@WORLD_MODEL_REGISTRY.register('ddppo') +class DDPPOWorldMode(HybridWorldModel, nn.Module): + """rollout model + gradient model""" + config = dict( + model=dict( + ensemble_size=7, + elite_size=5, + state_size=None, # has to be specified + action_size=None, # has to be specified + reward_size=1, + hidden_size=200, + use_decay=False, + batch_size=256, + holdout_ratio=0.2, + max_epochs_since_update=5, + deterministic_rollout=True, + # parameters for DDPPO + gradient_model=True, + k=3, + reg=1, + neighbor_pool_size=10000, + train_freq_gradient_model=250 + ), + ) + + def __init__(self, cfg, env, tb_logger): + HybridWorldModel.__init__(self, cfg, env, tb_logger) + nn.Module.__init__(self) + + cfg = cfg.model + self.ensemble_size = cfg.ensemble_size + self.elite_size = cfg.elite_size + self.state_size = cfg.state_size + self.action_size = cfg.action_size + self.reward_size = cfg.reward_size + self.hidden_size = cfg.hidden_size + self.use_decay = cfg.use_decay + self.batch_size = cfg.batch_size + self.holdout_ratio = cfg.holdout_ratio + self.max_epochs_since_update = cfg.max_epochs_since_update + self.deterministic_rollout = cfg.deterministic_rollout + # parameters for DDPPO + self.gradient_model = cfg.gradient_model + self.k = cfg.k + self.reg = cfg.reg + self.neighbor_pool_size = cfg.neighbor_pool_size + self.train_freq_gradient_model = cfg.train_freq_gradient_model + + self.rollout_model = EnsembleModel( + self.state_size, + self.action_size, + self.reward_size, + self.ensemble_size, + self.hidden_size, + use_decay=self.use_decay + ) + self.scaler = StandardScaler(self.state_size + self.action_size) + + self.ensemble_mse_losses = [] + self.model_variances = [] + self.elite_model_idxes = [] + + if self.gradient_model: + self.gradient_model = EnsembleGradientModel( + self.state_size, + self.action_size, + self.reward_size, + self.ensemble_size, + self.hidden_size, + use_decay=self.use_decay + ) + self.elite_model_idxes_gradient_model = [] + + self.last_train_step_gradient_model = 0 + + if self._cuda: + self.cuda() + + def step(self, obs, act, batch_size=8192): + + class Predict(torch.autograd.Function): + # TODO: align rollout_model elites with gradient_model elites + # use different model for forward and backward + @staticmethod + def forward(ctx, x): + ctx.save_for_backward(x) + mean, var = self.rollout_model(x, ret_log_var=False) + return torch.concat([mean, var], dim=-1) + + @staticmethod + def backward(ctx, grad_out): + x, = ctx.saved_tensors + with torch.enable_grad(): + x = x.detach() + x.requires_grad_(True) + mean, var = self.gradient_model(x, ret_log_var=False) + y = torch.concat([mean, var], dim=-1) + return torch.autograd.grad(y, x, grad_outputs=grad_out, create_graph=True) + + if len(act.shape) == 1: + act = act.unsqueeze(1) + if self._cuda: + obs = obs.cuda() + act = act.cuda() + inputs = torch.cat([obs, act], dim=1) + inputs = self.scaler.transform(inputs) + # predict + ensemble_mean, ensemble_var = [], [] + for i in range(0, inputs.shape[0], batch_size): + input = inputs[i:i + batch_size].unsqueeze(0).repeat(self.ensemble_size, 1, 1) + if not torch.is_grad_enabled() or not self.gradient_model: + b_mean, b_var = self.rollout_model(input, ret_log_var=False) + else: + # use gradient model to compute gradients during backward pass + output = Predict.apply(input) + b_mean, b_var = output.chunk(2, dim=2) + ensemble_mean.append(b_mean) + ensemble_var.append(b_var) + ensemble_mean = torch.cat(ensemble_mean, 1) + ensemble_var = torch.cat(ensemble_var, 1) + ensemble_mean[:, :, 1:] += obs.unsqueeze(0) + ensemble_std = ensemble_var.sqrt() + # sample from the predicted distribution + if self.deterministic_rollout: + ensemble_sample = ensemble_mean + else: + ensemble_sample = ensemble_mean + torch.randn_like(ensemble_mean).to(ensemble_mean) * ensemble_std + # sample from ensemble + model_idxes = torch.from_numpy(np.random.choice(self.elite_model_idxes, size=len(obs))).to(inputs.device) + batch_idxes = torch.arange(len(obs)).to(inputs.device) + sample = ensemble_sample[model_idxes, batch_idxes] + rewards, next_obs = sample[:, :1], sample[:, 1:] + + return rewards, next_obs, self.env.termination_fn(next_obs) + + def eval(self, env_buffer, envstep, train_iter): + data = env_buffer.sample(self.eval_freq, train_iter) + data = default_collate(data) + data['done'] = data['done'].float() + data['weight'] = data.get('weight', None) + obs = data['obs'] + action = data['action'] + reward = data['reward'] + next_obs = data['next_obs'] + if len(reward.shape) == 1: + reward = reward.unsqueeze(1) + if len(action.shape) == 1: + action = action.unsqueeze(1) + + # build eval samples + inputs = torch.cat([obs, action], dim=1) + labels = torch.cat([reward, next_obs - obs], dim=1) + if self._cuda: + inputs = inputs.cuda() + labels = labels.cuda() + + # normalize + inputs = self.scaler.transform(inputs) + + # repeat for ensemble + inputs = inputs.unsqueeze(0).repeat(self.ensemble_size, 1, 1) + labels = labels.unsqueeze(0).repeat(self.ensemble_size, 1, 1) + + # eval + with torch.no_grad(): + mean, logvar = self.rollout_model(inputs, ret_log_var=True) + loss, mse_loss = self.rollout_model.loss(mean, logvar, labels) + ensemble_mse_loss = torch.pow(mean.mean(0) - labels[0], 2) + model_variance = mean.var(0) + self.tb_logger.add_scalar('env_model_step/eval_mse_loss', mse_loss.mean().item(), envstep) + self.tb_logger.add_scalar('env_model_step/eval_ensemble_mse_loss', ensemble_mse_loss.mean().item(), envstep) + self.tb_logger.add_scalar('env_model_step/eval_model_variances', model_variance.mean().item(), envstep) + + self.last_eval_step = envstep + + def train(self, env_buffer, envstep, train_iter): + + def train_sample(data) -> tuple: + data = default_collate(data) + data['done'] = data['done'].float() + data['weight'] = data.get('weight', None) + obs = data['obs'] + action = data['action'] + reward = data['reward'] + next_obs = data['next_obs'] + if len(reward.shape) == 1: + reward = reward.unsqueeze(1) + if len(action.shape) == 1: + action = action.unsqueeze(1) + # build train samples + inputs = torch.cat([obs, action], dim=1) + labels = torch.cat([reward, next_obs - obs], dim=1) + if self._cuda: + inputs = inputs.cuda() + labels = labels.cuda() + return inputs, labels + + logvar = dict() + + data = env_buffer.sample(env_buffer.count(), train_iter) + inputs, labels = train_sample(data) + logvar.update(self._train_rollout_model(inputs, labels)) + + if self.gradient_model: + # update neighbor pool + if (envstep - self.last_train_step_gradient_model) >= self.train_freq_gradient_model: + n = min(env_buffer.count(), self.neighbor_pool_size) + self.neighbor_pool = env_buffer.sample(n, train_iter, sample_range=slice(-n, None)) + inputs_reg, labels_reg = train_sample(self.neighbor_pool) + logvar.update(self._train_gradient_model(inputs, labels, inputs_reg, labels_reg)) + self.last_train_step_gradient_model = envstep + + self.last_train_step = envstep + + # log + if self.tb_logger is not None: + for k, v in logvar.items(): + self.tb_logger.add_scalar('env_model_step/' + k, v, envstep) + + def _train_rollout_model(self, inputs, labels): + #split + num_holdout = int(inputs.shape[0] * self.holdout_ratio) + train_inputs, train_labels = inputs[num_holdout:], labels[num_holdout:] + holdout_inputs, holdout_labels = inputs[:num_holdout], labels[:num_holdout] + + #normalize + self.scaler.fit(train_inputs) + train_inputs = self.scaler.transform(train_inputs) + holdout_inputs = self.scaler.transform(holdout_inputs) + + #repeat for ensemble + holdout_inputs = holdout_inputs.unsqueeze(0).repeat(self.ensemble_size, 1, 1) + holdout_labels = holdout_labels.unsqueeze(0).repeat(self.ensemble_size, 1, 1) + + self._epochs_since_update = 0 + self._snapshots = {i: (-1, 1e10) for i in range(self.ensemble_size)} + self._save_states() + for epoch in itertools.count(): + + train_idx = torch.stack([torch.randperm(train_inputs.shape[0]) + for _ in range(self.ensemble_size)]).to(train_inputs.device) + self.mse_loss = [] + for start_pos in range(0, train_inputs.shape[0], self.batch_size): + idx = train_idx[:, start_pos:start_pos + self.batch_size] + train_input = train_inputs[idx] + train_label = train_labels[idx] + mean, logvar = self.rollout_model(train_input, ret_log_var=True) + loss, mse_loss = self.rollout_model.loss(mean, logvar, train_label) + self.rollout_model.train(loss) + self.mse_loss.append(mse_loss.mean().item()) + self.mse_loss = sum(self.mse_loss) / len(self.mse_loss) + + with torch.no_grad(): + holdout_mean, holdout_logvar = self.rollout_model(holdout_inputs, ret_log_var=True) + _, holdout_mse_loss = self.rollout_model.loss(holdout_mean, holdout_logvar, holdout_labels) + self.curr_holdout_mse_loss = holdout_mse_loss.mean().item() + break_train = self._save_best(epoch, holdout_mse_loss) + if break_train: + break + + self._load_states() + with torch.no_grad(): + holdout_mean, holdout_logvar = self.rollout_model(holdout_inputs, ret_log_var=True) + _, holdout_mse_loss = self.rollout_model.loss(holdout_mean, holdout_logvar, holdout_labels) + sorted_loss, sorted_loss_idx = holdout_mse_loss.sort() + sorted_loss = sorted_loss.detach().cpu().numpy().tolist() + sorted_loss_idx = sorted_loss_idx.detach().cpu().numpy().tolist() + self.elite_model_idxes = sorted_loss_idx[:self.elite_size] + self.top_holdout_mse_loss = sorted_loss[0] + self.middle_holdout_mse_loss = sorted_loss[self.ensemble_size // 2] + self.bottom_holdout_mse_loss = sorted_loss[-1] + self.best_holdout_mse_loss = holdout_mse_loss.mean().item() + return { + 'rollout_model/mse_loss': self.mse_loss, + 'rollout_model/curr_holdout_mse_loss': self.curr_holdout_mse_loss, + 'rollout_model/best_holdout_mse_loss': self.best_holdout_mse_loss, + 'rollout_model/top_holdout_mse_loss': self.top_holdout_mse_loss, + 'rollout_model/middle_holdout_mse_loss': self.middle_holdout_mse_loss, + 'rollout_model/bottom_holdout_mse_loss': self.bottom_holdout_mse_loss, + } + + def _get_jacobian(self, model, train_input_reg): + """ + train_input_reg: [ensemble_size, B, state_size+action_size] + + ret: [ensemble_size, B, state_size+reward_size, state_size+action_size] + """ + + def func(x): + x = x.view(self.ensemble_size, -1, self.state_size + self.action_size) + state = x[:, :, :self.state_size] + x = self.scaler.transform(x) + y, _ = model(x) + # y[:, :, self.reward_size:] += state, inplace operation leads to error + null = torch.zeros_like(y) + null[:, :, self.reward_size:] += state + y = y + null + + return y.view(-1, self.state_size + self.reward_size, self.state_size + self.reward_size) + + # reshape input + train_input_reg = train_input_reg.view(-1, self.state_size + self.action_size) + jacobian = get_batch_jacobian(func, train_input_reg, self.state_size + self.reward_size) + + # reshape jacobian + return jacobian.view( + self.ensemble_size, -1, self.state_size + self.reward_size, self.state_size + self.action_size + ) + + def _train_gradient_model(self, inputs, labels, inputs_reg, labels_reg): + #split + num_holdout = int(inputs.shape[0] * self.holdout_ratio) + train_inputs, train_labels = inputs[num_holdout:], labels[num_holdout:] + holdout_inputs, holdout_labels = inputs[:num_holdout], labels[:num_holdout] + + #normalize + # self.scaler.fit(train_inputs) + train_inputs = self.scaler.transform(train_inputs) + holdout_inputs = self.scaler.transform(holdout_inputs) + + #repeat for ensemble + holdout_inputs = holdout_inputs.unsqueeze(0).repeat(self.ensemble_size, 1, 1) + holdout_labels = holdout_labels.unsqueeze(0).repeat(self.ensemble_size, 1, 1) + + #no split and normalization on regulation data + train_inputs_reg, train_labels_reg = inputs_reg, labels_reg + + neighbor_index = get_neighbor_index(train_inputs_reg, self.k) + neighbor_inputs = train_inputs_reg[neighbor_index] # [N, k, state_size+action_size] + neighbor_labels = train_labels_reg[neighbor_index] # [N, k, state_size+reward_size] + neighbor_inputs_distance = (neighbor_inputs - train_inputs_reg.unsqueeze(1)) # [N, k, state_size+action_size] + neighbor_labels_distance = (neighbor_labels - train_labels_reg.unsqueeze(1)) # [N, k, state_size+reward_size] + + self._epochs_since_update = 0 + self._snapshots = {i: (-1, 1e10) for i in range(self.ensemble_size)} + self._save_states() + for epoch in itertools.count(): + + train_idx = torch.stack([torch.randperm(train_inputs.shape[0]) + for _ in range(self.ensemble_size)]).to(train_inputs.device) + + train_idx_reg = torch.stack([torch.randperm(train_inputs_reg.shape[0]) + for _ in range(self.ensemble_size)]).to(train_inputs_reg.device) + + self.mse_loss = [] + self.grad_loss = [] + for start_pos in range(0, train_inputs.shape[0], self.batch_size): + idx = train_idx[:, start_pos:start_pos + self.batch_size] + train_input = train_inputs[idx] + train_label = train_labels[idx] + mean, logvar = self.gradient_model(train_input, ret_log_var=True) + loss, mse_loss = self.gradient_model.loss(mean, logvar, train_label) + + # regulation loss + if start_pos % train_inputs_reg.shape[0] < (start_pos + self.batch_size) % train_inputs_reg.shape[0]: + idx_reg = train_idx_reg[:, start_pos % train_inputs_reg.shape[0]:(start_pos + self.batch_size) % + train_inputs_reg.shape[0]] + else: + idx_reg = train_idx_reg[:, 0:(start_pos + self.batch_size) % train_inputs_reg.shape[0]] + + train_input_reg = train_inputs_reg[idx_reg] + neighbor_input_distance = neighbor_inputs_distance[idx_reg + ] # [ensemble_size, B, k, state_size+action_size] + neighbor_label_distance = neighbor_labels_distance[idx_reg + ] # [ensemble_size, B, k, state_size+reward_size] + + jacobian = self._get_jacobian(self.gradient_model, train_input_reg).unsqueeze(2).repeat_interleave( + self.k, dim=2 + ) # [ensemble_size, B, k(repeat), state_size+reward_size, state_size+action_size] + + directional_derivative = (jacobian @ neighbor_input_distance.unsqueeze(-1)).squeeze( + -1 + ) # [ensemble_size, B, k, state_size+reward_size] + + loss_reg = torch.pow((neighbor_label_distance - directional_derivative), + 2).sum(0).mean() # sumed over network + + self.gradient_model.train(loss, loss_reg, self.reg) + self.mse_loss.append(mse_loss.mean().item()) + self.grad_loss.append(loss_reg.item()) + + self.mse_loss = sum(self.mse_loss) / len(self.mse_loss) + self.grad_loss = sum(self.grad_loss) / len(self.grad_loss) + + with torch.no_grad(): + holdout_mean, holdout_logvar = self.gradient_model(holdout_inputs, ret_log_var=True) + _, holdout_mse_loss = self.gradient_model.loss(holdout_mean, holdout_logvar, holdout_labels) + self.curr_holdout_mse_loss = holdout_mse_loss.mean().item() + break_train = self._save_best(epoch, holdout_mse_loss) + if break_train: + break + + self._load_states() + with torch.no_grad(): + holdout_mean, holdout_logvar = self.gradient_model(holdout_inputs, ret_log_var=True) + _, holdout_mse_loss = self.gradient_model.loss(holdout_mean, holdout_logvar, holdout_labels) + sorted_loss, sorted_loss_idx = holdout_mse_loss.sort() + sorted_loss = sorted_loss.detach().cpu().numpy().tolist() + sorted_loss_idx = sorted_loss_idx.detach().cpu().numpy().tolist() + self.elite_model_idxes_gradient_model = sorted_loss_idx[:self.elite_size] + self.top_holdout_mse_loss = sorted_loss[0] + self.middle_holdout_mse_loss = sorted_loss[self.ensemble_size // 2] + self.bottom_holdout_mse_loss = sorted_loss[-1] + self.best_holdout_mse_loss = holdout_mse_loss.mean().item() + return { + 'gradient_model/mse_loss': self.mse_loss, + 'gradient_model/grad_loss': self.grad_loss, + 'gradient_model/curr_holdout_mse_loss': self.curr_holdout_mse_loss, + 'gradient_model/best_holdout_mse_loss': self.best_holdout_mse_loss, + 'gradient_model/top_holdout_mse_loss': self.top_holdout_mse_loss, + 'gradient_model/middle_holdout_mse_loss': self.middle_holdout_mse_loss, + 'gradient_model/bottom_holdout_mse_loss': self.bottom_holdout_mse_loss, + } + + def _save_states(self, ): + self._states = copy.deepcopy(self.state_dict()) + + def _save_state(self, id): + state_dict = self.state_dict() + for k, v in state_dict.items(): + if 'weight' in k or 'bias' in k: + self._states[k].data[id] = copy.deepcopy(v.data[id]) + + def _load_states(self): + self.load_state_dict(self._states) + + def _save_best(self, epoch, holdout_losses): + updated = False + for i in range(len(holdout_losses)): + current = holdout_losses[i] + _, best = self._snapshots[i] + improvement = (best - current) / best + if improvement > 0.01: + self._snapshots[i] = (epoch, current) + self._save_state(i) + # self._save_state(i) + updated = True + # improvement = (best - current) / best + + if updated: + self._epochs_since_update = 0 + else: + self._epochs_since_update += 1 + return self._epochs_since_update > self.max_epochs_since_update diff --git a/ding/world_model/mbpo.py b/ding/world_model/mbpo.py new file mode 100644 index 0000000000..c748192500 --- /dev/null +++ b/ding/world_model/mbpo.py @@ -0,0 +1,255 @@ +import itertools +import numpy as np +import copy +import torch +from torch import nn + +from ding.utils import WORLD_MODEL_REGISTRY +from ding.utils.data import default_collate +from ding.world_model.base_world_model import HybridWorldModel +from ding.world_model.model.ensemble import EnsembleModel, StandardScaler + + +@WORLD_MODEL_REGISTRY.register('mbpo') +class MBPOWorldModel(HybridWorldModel, nn.Module): + config = dict( + model=dict( + ensemble_size=7, + elite_size=5, + state_size=None, + action_size=None, + reward_size=1, + hidden_size=200, + use_decay=False, + batch_size=256, + holdout_ratio=0.2, + max_epochs_since_update=5, + deterministic_rollout=True, + ), + ) + + def __init__(self, cfg, env, tb_logger): + HybridWorldModel.__init__(self, cfg, env, tb_logger) + nn.Module.__init__(self) + + cfg = cfg.model + self.ensemble_size = cfg.ensemble_size + self.elite_size = cfg.elite_size + self.state_size = cfg.state_size + self.action_size = cfg.action_size + self.reward_size = cfg.reward_size + self.hidden_size = cfg.hidden_size + self.use_decay = cfg.use_decay + self.batch_size = cfg.batch_size + self.holdout_ratio = cfg.holdout_ratio + self.max_epochs_since_update = cfg.max_epochs_since_update + self.deterministic_rollout = cfg.deterministic_rollout + + self.ensemble_model = EnsembleModel( + self.state_size, + self.action_size, + self.reward_size, + self.ensemble_size, + self.hidden_size, + use_decay=self.use_decay + ) + self.scaler = StandardScaler(self.state_size + self.action_size) + + if self._cuda: + self.cuda() + + self.ensemble_mse_losses = [] + self.model_variances = [] + self.elite_model_idxes = [] + + def step(self, obs, act, batch_size=8192): + if len(act.shape) == 1: + act = act.unsqueeze(1) + if self._cuda: + obs = obs.cuda() + act = act.cuda() + inputs = torch.cat([obs, act], dim=1) + inputs = self.scaler.transform(inputs) + # predict + ensemble_mean, ensemble_var = [], [] + for i in range(0, inputs.shape[0], batch_size): + input = inputs[i:i + batch_size].unsqueeze(0).repeat(self.ensemble_size, 1, 1) + b_mean, b_var = self.ensemble_model(input, ret_log_var=False) + ensemble_mean.append(b_mean) + ensemble_var.append(b_var) + ensemble_mean = torch.cat(ensemble_mean, 1) + ensemble_var = torch.cat(ensemble_var, 1) + ensemble_mean[:, :, 1:] += obs.unsqueeze(0) + ensemble_std = ensemble_var.sqrt() + # sample from the predicted distribution + if self.deterministic_rollout: + ensemble_sample = ensemble_mean + else: + ensemble_sample = ensemble_mean + torch.randn_like(ensemble_mean).to(ensemble_mean) * ensemble_std + # sample from ensemble + model_idxes = torch.from_numpy(np.random.choice(self.elite_model_idxes, size=len(obs))).to(inputs.device) + batch_idxes = torch.arange(len(obs)).to(inputs.device) + sample = ensemble_sample[model_idxes, batch_idxes] + rewards, next_obs = sample[:, :1], sample[:, 1:] + + return rewards, next_obs, self.env.termination_fn(next_obs) + + def eval(self, env_buffer, envstep, train_iter): + data = env_buffer.sample(self.eval_freq, train_iter) + data = default_collate(data) + data['done'] = data['done'].float() + data['weight'] = data.get('weight', None) + obs = data['obs'] + action = data['action'] + reward = data['reward'] + next_obs = data['next_obs'] + if len(reward.shape) == 1: + reward = reward.unsqueeze(1) + if len(action.shape) == 1: + action = action.unsqueeze(1) + + # build eval samples + inputs = torch.cat([obs, action], dim=1) + labels = torch.cat([reward, next_obs - obs], dim=1) + if self._cuda: + inputs = inputs.cuda() + labels = labels.cuda() + + # normalize + inputs = self.scaler.transform(inputs) + + # repeat for ensemble + inputs = inputs.unsqueeze(0).repeat(self.ensemble_size, 1, 1) + labels = labels.unsqueeze(0).repeat(self.ensemble_size, 1, 1) + + # eval + with torch.no_grad(): + mean, logvar = self.ensemble_model(inputs, ret_log_var=True) + loss, mse_loss = self.ensemble_model.loss(mean, logvar, labels) + ensemble_mse_loss = torch.pow(mean.mean(0) - labels[0], 2) + model_variance = mean.var(0) + self.tb_logger.add_scalar('env_model_step/eval_mse_loss', mse_loss.mean().item(), envstep) + self.tb_logger.add_scalar('env_model_step/eval_ensemble_mse_loss', ensemble_mse_loss.mean().item(), envstep) + self.tb_logger.add_scalar('env_model_step/eval_model_variances', model_variance.mean().item(), envstep) + + self.last_eval_step = envstep + + def train(self, env_buffer, envstep, train_iter): + data = env_buffer.sample(env_buffer.count(), train_iter) + data = default_collate(data) + data['done'] = data['done'].float() + data['weight'] = data.get('weight', None) + obs = data['obs'] + action = data['action'] + reward = data['reward'] + next_obs = data['next_obs'] + if len(reward.shape) == 1: + reward = reward.unsqueeze(1) + if len(action.shape) == 1: + action = action.unsqueeze(1) + # build train samples + inputs = torch.cat([obs, action], dim=1) + labels = torch.cat([reward, next_obs - obs], dim=1) + if self._cuda: + inputs = inputs.cuda() + labels = labels.cuda() + # train + logvar = self._train(inputs, labels) + self.last_train_step = envstep + # log + if self.tb_logger is not None: + for k, v in logvar.items(): + self.tb_logger.add_scalar('env_model_step/' + k, v, envstep) + + def _train(self, inputs, labels): + #split + num_holdout = int(inputs.shape[0] * self.holdout_ratio) + train_inputs, train_labels = inputs[num_holdout:], labels[num_holdout:] + holdout_inputs, holdout_labels = inputs[:num_holdout], labels[:num_holdout] + + #normalize + self.scaler.fit(train_inputs) + train_inputs = self.scaler.transform(train_inputs) + holdout_inputs = self.scaler.transform(holdout_inputs) + + #repeat for ensemble + holdout_inputs = holdout_inputs.unsqueeze(0).repeat(self.ensemble_size, 1, 1) + holdout_labels = holdout_labels.unsqueeze(0).repeat(self.ensemble_size, 1, 1) + + self._epochs_since_update = 0 + self._snapshots = {i: (-1, 1e10) for i in range(self.ensemble_size)} + self._save_states() + for epoch in itertools.count(): + + train_idx = torch.stack([torch.randperm(train_inputs.shape[0]) + for _ in range(self.ensemble_size)]).to(train_inputs.device) + self.mse_loss = [] + for start_pos in range(0, train_inputs.shape[0], self.batch_size): + idx = train_idx[:, start_pos:start_pos + self.batch_size] + train_input = train_inputs[idx] + train_label = train_labels[idx] + mean, logvar = self.ensemble_model(train_input, ret_log_var=True) + loss, mse_loss = self.ensemble_model.loss(mean, logvar, train_label) + self.ensemble_model.train(loss) + self.mse_loss.append(mse_loss.mean().item()) + self.mse_loss = sum(self.mse_loss) / len(self.mse_loss) + + with torch.no_grad(): + holdout_mean, holdout_logvar = self.ensemble_model(holdout_inputs, ret_log_var=True) + _, holdout_mse_loss = self.ensemble_model.loss(holdout_mean, holdout_logvar, holdout_labels) + self.curr_holdout_mse_loss = holdout_mse_loss.mean().item() + break_train = self._save_best(epoch, holdout_mse_loss) + if break_train: + break + + self._load_states() + with torch.no_grad(): + holdout_mean, holdout_logvar = self.ensemble_model(holdout_inputs, ret_log_var=True) + _, holdout_mse_loss = self.ensemble_model.loss(holdout_mean, holdout_logvar, holdout_labels) + sorted_loss, sorted_loss_idx = holdout_mse_loss.sort() + sorted_loss = sorted_loss.detach().cpu().numpy().tolist() + sorted_loss_idx = sorted_loss_idx.detach().cpu().numpy().tolist() + self.elite_model_idxes = sorted_loss_idx[:self.elite_size] + self.top_holdout_mse_loss = sorted_loss[0] + self.middle_holdout_mse_loss = sorted_loss[self.ensemble_size // 2] + self.bottom_holdout_mse_loss = sorted_loss[-1] + self.best_holdout_mse_loss = holdout_mse_loss.mean().item() + return { + 'mse_loss': self.mse_loss, + 'curr_holdout_mse_loss': self.curr_holdout_mse_loss, + 'best_holdout_mse_loss': self.best_holdout_mse_loss, + 'top_holdout_mse_loss': self.top_holdout_mse_loss, + 'middle_holdout_mse_loss': self.middle_holdout_mse_loss, + 'bottom_holdout_mse_loss': self.bottom_holdout_mse_loss, + } + + def _save_states(self, ): + self._states = copy.deepcopy(self.state_dict()) + + def _save_state(self, id): + state_dict = self.state_dict() + for k, v in state_dict.items(): + if 'weight' in k or 'bias' in k: + self._states[k].data[id] = copy.deepcopy(v.data[id]) + + def _load_states(self): + self.load_state_dict(self._states) + + def _save_best(self, epoch, holdout_losses): + updated = False + for i in range(len(holdout_losses)): + current = holdout_losses[i] + _, best = self._snapshots[i] + improvement = (best - current) / best + if improvement > 0.01: + self._snapshots[i] = (epoch, current) + self._save_state(i) + # self._save_state(i) + updated = True + # improvement = (best - current) / best + + if updated: + self._epochs_since_update = 0 + else: + self._epochs_since_update += 1 + return self._epochs_since_update > self.max_epochs_since_update diff --git a/ding/world_model/model/ensemble.py b/ding/world_model/model/ensemble.py new file mode 100644 index 0000000000..87433fd8c5 --- /dev/null +++ b/ding/world_model/model/ensemble.py @@ -0,0 +1,150 @@ +import numpy as np +import torch +import torch.nn as nn +import torch.nn.functional as F + +from ding.torch_utils import Swish + + +class StandardScaler(nn.Module): + + def __init__(self, input_size: int): + super(StandardScaler, self).__init__() + self.register_buffer('std', torch.ones(1, input_size)) + self.register_buffer('mu', torch.zeros(1, input_size)) + + def fit(self, data: torch.Tensor): + std, mu = torch.std_mean(data, dim=0, keepdim=True) + std[std < 1e-12] = 1 + self.std.data.mul_(0.0).add_(std) + self.mu.data.mul_(0.0).add_(mu) + + def transform(self, data: torch.Tensor): + return (data - self.mu) / self.std + + def inverse_transform(self, data: torch.Tensor): + return self.std * data + self.mu + + +class EnsembleFC(nn.Module): + __constants__ = ['in_features', 'out_features'] + in_features: int + out_features: int + ensemble_size: int + weight: torch.Tensor + + def __init__(self, in_features: int, out_features: int, ensemble_size: int, weight_decay: float = 0.) -> None: + super(EnsembleFC, self).__init__() + self.in_features = in_features + self.out_features = out_features + self.ensemble_size = ensemble_size + self.weight = nn.Parameter(torch.zeros(ensemble_size, in_features, out_features)) + self.weight_decay = weight_decay + self.bias = nn.Parameter(torch.zeros(ensemble_size, 1, out_features)) + + def forward(self, input: torch.Tensor) -> torch.Tensor: + assert input.shape[0] == self.ensemble_size and len(input.shape) == 3 + return torch.bmm(input, self.weight) + self.bias # w times x + b + + def extra_repr(self) -> str: + return 'in_features={}, out_features={}, ensemble_size={}, weight_decay={}'.format( + self.in_features, self.out_features, self.ensemble_size, self.weight_decay + ) + + +class EnsembleModel(nn.Module): + + def __init__( + self, + state_size, + action_size, + reward_size, + ensemble_size, + hidden_size=200, + learning_rate=1e-3, + use_decay=False + ): + super(EnsembleModel, self).__init__() + + self.use_decay = use_decay + self.hidden_size = hidden_size + self.output_dim = state_size + reward_size + + self.nn1 = EnsembleFC(state_size + action_size, hidden_size, ensemble_size, weight_decay=0.000025) + self.nn2 = EnsembleFC(hidden_size, hidden_size, ensemble_size, weight_decay=0.00005) + self.nn3 = EnsembleFC(hidden_size, hidden_size, ensemble_size, weight_decay=0.000075) + self.nn4 = EnsembleFC(hidden_size, hidden_size, ensemble_size, weight_decay=0.000075) + self.nn5 = EnsembleFC(hidden_size, self.output_dim * 2, ensemble_size, weight_decay=0.0001) + self.max_logvar = nn.Parameter(torch.ones(1, self.output_dim).float() * 0.5, requires_grad=False) + self.min_logvar = nn.Parameter(torch.ones(1, self.output_dim).float() * -10, requires_grad=False) + self.swish = Swish() + + def init_weights(m: nn.Module): + + def truncated_normal_init(t, mean: float = 0.0, std: float = 0.01): + torch.nn.init.normal_(t, mean=mean, std=std) + while True: + cond = torch.logical_or(t < mean - 2 * std, t > mean + 2 * std) + if not torch.sum(cond): + break + t = torch.where(cond, torch.nn.init.normal_(torch.ones(t.shape), mean=mean, std=std), t) + return t + + if isinstance(m, nn.Linear) or isinstance(m, EnsembleFC): + input_dim = m.in_features + truncated_normal_init(m.weight, std=1 / (2 * np.sqrt(input_dim))) + m.bias.data.fill_(0.0) + + self.apply(init_weights) + + self.optimizer = torch.optim.Adam(self.parameters(), lr=learning_rate) + + def forward(self, x: torch.Tensor, ret_log_var: bool = False): + x = self.swish(self.nn1(x)) + x = self.swish(self.nn2(x)) + x = self.swish(self.nn3(x)) + x = self.swish(self.nn4(x)) + x = self.nn5(x) + + mean, logvar = x.chunk(2, dim=2) + logvar = self.max_logvar - F.softplus(self.max_logvar - logvar) + logvar = self.min_logvar + F.softplus(logvar - self.min_logvar) + + if ret_log_var: + return mean, logvar + else: + return mean, torch.exp(logvar) + + def get_decay_loss(self): + decay_loss = 0. + for m in self.modules(): + if isinstance(m, EnsembleFC): + decay_loss += m.weight_decay * torch.sum(torch.square(m.weight)) / 2. + return decay_loss + + def loss(self, mean: torch.Tensor, logvar: torch.Tensor, labels: torch.Tensor): + """ + mean, logvar: Ensemble_size x N x dim + labels: Ensemble_size x N x dim + """ + assert len(mean.shape) == len(logvar.shape) == len(labels.shape) == 3 + inv_var = torch.exp(-logvar) + # Average over batch and dim, sum over ensembles. + mse_loss_inv = (torch.pow(mean - labels, 2) * inv_var).mean(dim=(1, 2)) + var_loss = logvar.mean(dim=(1, 2)) + with torch.no_grad(): + # Used only for logging. + mse_loss = torch.pow(mean - labels, 2).mean(dim=(1, 2)) + total_loss = mse_loss_inv.sum() + var_loss.sum() + return total_loss, mse_loss + + def train(self, loss: torch.Tensor): + self.optimizer.zero_grad() + + loss += 0.01 * torch.sum(self.max_logvar) - 0.01 * torch.sum(self.min_logvar) + if self.use_decay: + loss += self.get_decay_loss() + + loss.backward() + + self.optimizer.step() diff --git a/ding/world_model/model/tests/test_ensemble.py b/ding/world_model/model/tests/test_ensemble.py new file mode 100644 index 0000000000..8dcaf9395f --- /dev/null +++ b/ding/world_model/model/tests/test_ensemble.py @@ -0,0 +1,29 @@ +import pytest +import torch +from itertools import product +from ding.world_model.model.ensemble import EnsembleFC, EnsembleModel + +# arguments +state_size = [16] +action_size = [16, 1] +reward_size = [1] +args = list(product(*[state_size, action_size, reward_size])) + + +@pytest.mark.unittest +def test_EnsembleFC(): + in_dim, out_dim, ensemble_size, B = 4, 8, 7, 64 + fc = EnsembleFC(in_dim, out_dim, ensemble_size) + x = torch.randn(ensemble_size, B, in_dim) + y = fc(x) + assert y.shape == (ensemble_size, B, out_dim) + + +@pytest.mark.parametrize('state_size, action_size, reward_size', args) +def test_EnsembleModel(state_size, action_size, reward_size): + ensemble_size, B = 7, 64 + model = EnsembleModel(state_size, action_size, reward_size, ensemble_size) + x = torch.randn(ensemble_size, B, state_size + action_size) + y = model(x) + assert len(y) == 2 + assert y[0].shape == y[1].shape == (ensemble_size, B, state_size + reward_size) diff --git a/ding/world_model/tests/test_ddppo.py b/ding/world_model/tests/test_ddppo.py new file mode 100644 index 0000000000..0f9f67bd18 --- /dev/null +++ b/ding/world_model/tests/test_ddppo.py @@ -0,0 +1,106 @@ +import pytest +import torch +from torch import nn + +from itertools import product +from easydict import EasyDict +from ding.world_model.ddppo import DDPPOWorldMode, get_batch_jacobian, get_neighbor_index +from ding.utils import deep_merge_dicts + +# arguments +state_size = [16] +action_size = [16, 1] +reward_size = [1] +args = list(product(*[state_size, action_size, reward_size])) + + +@pytest.mark.unittest +class TestDDPPO: + + def get_world_model(self, state_size, action_size, reward_size): + cfg = DDPPOWorldMode.default_config() + cfg = deep_merge_dicts( + cfg, dict(cuda=False, model=dict(state_size=state_size, action_size=action_size, reward_size=reward_size)) + ) + fake_env = EasyDict(termination_fn=lambda obs: torch.zeros_like(obs.sum(-1)).bool()) + return DDPPOWorldMode(cfg, fake_env, None) + + def test_get_neighbor_index(self): + k = 2 + data = torch.tensor([[0, 0, 0], [0, 0, 1], [0, 0, -1], [5, 0, 0], [5, 0, 1], [5, 0, -1]]) + idx = get_neighbor_index(data, k) + target_idx = torch.tensor([[2, 1], [0, 2], [0, 1], [5, 4], [3, 5], [3, 4]]) + assert (idx - target_idx).sum() == 0 + + def test_get_batch_jacobian(self): + B, in_dim, out_dim = 64, 4, 8 + net = nn.Linear(in_dim, out_dim) + x = torch.randn(B, in_dim) + jacobian = get_batch_jacobian(net, x, out_dim) + assert jacobian.shape == (B, out_dim, in_dim) + + @pytest.mark.parametrize('state_size, action_size, reward_size', args) + def test_get_jacobian(self, state_size, action_size, reward_size): + B, ensemble_size = 64, 7 + model = self.get_world_model(state_size, action_size, reward_size) + train_input_reg = torch.randn(ensemble_size, B, state_size + action_size) + jacobian = model._get_jacobian(model.gradient_model, train_input_reg) + assert jacobian.shape == (ensemble_size, B, state_size + reward_size, state_size + action_size) + assert jacobian.requires_grad + + @pytest.mark.parametrize('state_size, action_size, reward_size', args) + def test_step(self, state_size, action_size, reward_size): + states = torch.rand(128, state_size) + actions = torch.rand(128, action_size) + model = self.get_world_model(state_size, action_size, reward_size) + model.elite_model_idxes = [0, 1] + rewards, next_obs, dones = model.step(states, actions) + assert rewards.shape == (128, reward_size) + assert next_obs.shape == (128, state_size) + assert dones.shape == (128, ) + + @pytest.mark.parametrize('state_size, action_size, reward_size', args) + def test_train_rollout_model(self, state_size, action_size, reward_size): + states = torch.rand(1280, state_size) + actions = torch.rand(1280, action_size) + + next_states = states + actions.mean(1, keepdim=True) + rewards = next_states.mean(1, keepdim=True).repeat(1, reward_size) + + inputs = torch.cat([states, actions], dim=1) + labels = torch.cat([rewards, next_states], dim=1) + + model = self.get_world_model(state_size, action_size, reward_size) + model._train_rollout_model(inputs[:64], labels[:64]) + + @pytest.mark.parametrize('state_size, action_size, reward_size', args) + def test_train_graident_model(self, state_size, action_size, reward_size): + states = torch.rand(1280, state_size) + actions = torch.rand(1280, action_size) + + next_states = states + actions.mean(1, keepdim=True) + rewards = next_states.mean(1, keepdim=True).repeat(1, reward_size) + + inputs = torch.cat([states, actions], dim=1) + labels = torch.cat([rewards, next_states], dim=1) + + model = self.get_world_model(state_size, action_size, reward_size) + model._train_gradient_model(inputs[:64], labels[:64], inputs[:64], labels[:64]) + + @pytest.mark.parametrize('state_size, action_size, reward_size', args[:1]) + def test_others(self, state_size, action_size, reward_size): + states = torch.rand(1280, state_size) + actions = torch.rand(1280, action_size) + + next_states = states + actions.mean(1, keepdim=True) + rewards = next_states.mean(1, keepdim=True).repeat(1, reward_size) + + inputs = torch.cat([states, actions], dim=1) + labels = torch.cat([rewards, next_states], dim=1) + + model = self.get_world_model(state_size, action_size, reward_size) + model._train_rollout_model(inputs[:64], labels[:64]) + model._train_gradient_model(inputs[:64], labels[:64], inputs[:64], labels[:64]) + model._save_states() + model._load_states() + model._save_best(0, [1, 2, 3]) diff --git a/ding/world_model/tests/test_mbpo.py b/ding/world_model/tests/test_mbpo.py new file mode 100644 index 0000000000..2720719d29 --- /dev/null +++ b/ding/world_model/tests/test_mbpo.py @@ -0,0 +1,67 @@ +import pytest +import torch + +from itertools import product +from easydict import EasyDict +from ding.world_model.mbpo import MBPOWorldModel +from ding.utils import deep_merge_dicts + +# arguments +state_size = [16] +action_size = [16, 1] +reward_size = [1] +args = list(product(*[state_size, action_size, reward_size])) + + +@pytest.mark.unittest +class TestMBPO: + + def get_world_model(self, state_size, action_size, reward_size): + cfg = MBPOWorldModel.default_config() + cfg = deep_merge_dicts( + cfg, dict(cuda=False, model=dict(state_size=state_size, action_size=action_size, reward_size=reward_size)) + ) + fake_env = EasyDict(termination_fn=lambda obs: torch.zeros_like(obs.sum(-1)).bool()) + return MBPOWorldModel(cfg, fake_env, None) + + @pytest.mark.parametrize('state_size, action_size, reward_size', args) + def test_step(self, state_size, action_size, reward_size): + states = torch.rand(128, state_size) + actions = torch.rand(128, action_size) + model = self.get_world_model(state_size, action_size, reward_size) + model.elite_model_idxes = [0, 1] + rewards, next_obs, dones = model.step(states, actions) + assert rewards.shape == (128, reward_size) + assert next_obs.shape == (128, state_size) + assert dones.shape == (128, ) + + @pytest.mark.parametrize('state_size, action_size, reward_size', args) + def test_train(self, state_size, action_size, reward_size): + states = torch.rand(1280, state_size) + actions = torch.rand(1280, action_size) + + next_states = states + actions.mean(1, keepdim=True) + rewards = next_states.mean(1, keepdim=True).repeat(1, reward_size) + + inputs = torch.cat([states, actions], dim=1) + labels = torch.cat([rewards, next_states], dim=1) + + model = self.get_world_model(state_size, action_size, reward_size) + model._train(inputs[:64], labels[:64]) + + @pytest.mark.parametrize('state_size, action_size, reward_size', args[:1]) + def test_others(self, state_size, action_size, reward_size): + states = torch.rand(1280, state_size) + actions = torch.rand(1280, action_size) + + next_states = states + actions.mean(1, keepdim=True) + rewards = next_states.mean(1, keepdim=True).repeat(1, reward_size) + + inputs = torch.cat([states, actions], dim=1) + labels = torch.cat([rewards, next_states], dim=1) + + model = self.get_world_model(state_size, action_size, reward_size) + model._train(inputs[:64], labels[:64]) + model._save_states() + model._load_states() + model._save_best(0, [1, 2, 3]) diff --git a/ding/world_model/tests/test_world_model.py b/ding/world_model/tests/test_world_model.py new file mode 100644 index 0000000000..1e56904ed0 --- /dev/null +++ b/ding/world_model/tests/test_world_model.py @@ -0,0 +1,121 @@ +import pytest +import torch +from easydict import EasyDict +from ding.world_model.base_world_model import DreamWorldModel, DynaWorldModel +from ding.worker.replay_buffer import NaiveReplayBuffer, EpisodeReplayBuffer + + +@pytest.mark.unittest +class TestDynaWorldModel: + + @pytest.mark.parametrize('buffer_type', [NaiveReplayBuffer, EpisodeReplayBuffer]) + def test_fill_img_buffer(self, buffer_type): + env_buffer = buffer_type(buffer_type.default_config(), None, 'exp_name', 'instance_name') + img_buffer = buffer_type(buffer_type.default_config(), None, 'exp_name', 'instance_name') + fake_config = EasyDict( + train_freq=250, # w.r.t environment step + eval_freq=250, # w.r.t environment step + cuda=False, + rollout_length_scheduler=dict( + type='linear', + rollout_start_step=20000, + rollout_end_step=150000, + rollout_length_min=1, + rollout_length_max=25, + ), + other=dict( + real_ratio=0.05, + rollout_retain=4, + rollout_batch_size=100000, + imagination_buffer=dict( + type='elastic', + replay_buffer_size=6000000, + deepcopy=False, + enable_track_used_data=False, + # set_buffer_size=set_buffer_size, + periodic_thruput_seconds=60, + ), + ), + ) + T, B, O, A = 25, 20, 100, 30 + + class FakeModel(DynaWorldModel): + + def train(self, env_buffer, envstep, train_iter): + pass + + def eval(self, env_buffer, envstep, train_iter): + pass + + def step(self, obs, action): + return (torch.zeros(B), torch.rand(B, O), obs.sum(-1) > 0) + + from ding.policy import SACPolicy + from ding.model import QAC + + policy_config = SACPolicy.default_config() + policy_config.model.update(dict(obs_shape=2, action_shape=2)) + model = QAC(**policy_config.model) + policy = SACPolicy(policy_config, model=model).collect_mode + + fake_model = FakeModel(fake_config, None, None) + + env_buffer.push( + [ + { + 'obs': torch.randn(2), + 'next_obs': torch.randn(2), + 'action': torch.randn(2), + 'reward': torch.randn(1), + 'done': False, + 'collect_iter': 0 + } + ] * 20, 0 + ) + + super(FakeModel, fake_model).fill_img_buffer(policy, env_buffer, img_buffer, 0, 0) + + +@pytest.mark.unittest +class TestDreamWorldModel: + + def test_rollout(self): + fake_config = EasyDict( + train_freq=250, # w.r.t environment step + eval_freq=250, # w.r.t environment step + cuda=False, + rollout_length_scheduler=dict( + type='linear', + rollout_start_step=20000, + rollout_end_step=150000, + rollout_length_min=1, + rollout_length_max=25, + ) + ) + envstep = 150000 + T, B, O, A = 25, 20, 100, 30 + + class FakeModel(DreamWorldModel): + + def train(self, env_buffer, envstep, train_iter): + pass + + def eval(self, env_buffer, envstep, train_iter): + pass + + def step(self, obs, action): + return (torch.zeros(B), torch.rand(B, O), obs.sum(-1) > 0) + + def fake_policy_fn(obs): + return torch.randn(B, A), torch.zeros(B) + + fake_model = FakeModel(fake_config, None, None) + + obs = torch.rand(B, O) + obss, actions, rewards, aug_rewards, dones = \ + super(FakeModel, fake_model).rollout(obs, fake_policy_fn, envstep) + assert obss.shape == (T + 1, B, O) + assert actions.shape == (T + 1, B, A) + assert rewards.shape == (T, B) + assert aug_rewards.shape == (T + 1, B) + assert dones.shape == (T + 1, B) diff --git a/ding/world_model/tests/test_world_model_utils.py b/ding/world_model/tests/test_world_model_utils.py new file mode 100644 index 0000000000..26ba5e7f5e --- /dev/null +++ b/ding/world_model/tests/test_world_model_utils.py @@ -0,0 +1,19 @@ +import pytest +from easydict import EasyDict +from ding.world_model.utils import get_rollout_length_scheduler + + +@pytest.mark.unittest +def test_get_rollout_length_scheduler(): + fake_cfg = EasyDict( + type='linear', + rollout_start_step=20000, + rollout_end_step=150000, + rollout_length_min=1, + rollout_length_max=25, + ) + scheduler = get_rollout_length_scheduler(fake_cfg) + assert scheduler(0) == 1 + assert scheduler(19999) == 1 + assert scheduler(150000) == 25 + assert scheduler(1500000) == 25 diff --git a/ding/world_model/utils.py b/ding/world_model/utils.py new file mode 100644 index 0000000000..15172699f9 --- /dev/null +++ b/ding/world_model/utils.py @@ -0,0 +1,25 @@ +from easydict import EasyDict +from typing import Callable + + +def get_rollout_length_scheduler(cfg: EasyDict) -> Callable[[int], int]: + """ + Overview: + Get the rollout length scheduler that adapts rollout length based\ + on the current environment steps. + Returns: + - scheduler (:obj:`Callble`): The function that takes envstep and\ + return the current rollout length. + """ + if cfg.type == 'linear': + x0 = cfg.rollout_start_step + x1 = cfg.rollout_end_step + y0 = cfg.rollout_length_min + y1 = cfg.rollout_length_max + w = (y1 - y0) / (x1 - x0) + b = y0 + return lambda x: int(min(max(w * (x - x0) + b, y0), y1)) + elif cfg.type == 'constant': + return lambda x: cfg.rollout_length + else: + raise KeyError("not implemented key: {}".format(cfg.type)) diff --git a/dizoo/classic_control/pendulum/config/mbrl/pendulum_mbsac_ddppo_config.py b/dizoo/classic_control/pendulum/config/mbrl/pendulum_mbsac_ddppo_config.py new file mode 100644 index 0000000000..b722ff7f6c --- /dev/null +++ b/dizoo/classic_control/pendulum/config/mbrl/pendulum_mbsac_ddppo_config.py @@ -0,0 +1,116 @@ +from easydict import EasyDict + +from ding.entry import serial_pipeline_dream + +# environment hypo +env_id = 'Pendulum-v0' +obs_shape = 3 +action_shape = 1 + +# gpu +cuda = False + +main_config = dict( + exp_name='pendulum_mbsac_ddppo_seed0', + env=dict( + env_id=env_id, # only for backward compatibility + collector_env_num=10, + evaluator_env_num=5, + # (bool) Scale output action into legal range. + act_scale=True, + n_evaluator_episode=5, + stop_value=-250, + ), + policy=dict( + cuda=cuda, + # backward compatibility: it is better to + # put random_collect_size in policy.other + random_collect_size=1000, + model=dict( + obs_shape=obs_shape, + action_shape=action_shape, + twin_critic=True, + action_space='reparameterization', + actor_head_hidden_size=128, + critic_head_hidden_size=128, + ), + learn=dict( + lambda_=0.8, + sample_state=False, + update_per_collect=1, + batch_size=128, + learning_rate_q=0.001, + learning_rate_policy=0.001, + learning_rate_alpha=0.0003, + ignore_done=True, + target_theta=0.005, + discount_factor=0.99, + auto_alpha=True, + value_network=False, + ), + collect=dict( + n_sample=1, + unroll_len=1, + ), + command=dict(), + eval=dict(evaluator=dict(eval_freq=100, )), + other=dict( + # environment buffer + replay_buffer=dict(replay_buffer_size=100000, ), + ), + ), + world_model=dict( + eval_freq=100, # w.r.t envstep + train_freq=100, # w.r.t envstep + cuda=cuda, + rollout_length_scheduler=dict( + type='linear', + rollout_start_step=2000, + rollout_end_step=15000, + rollout_length_min=3, + rollout_length_max=3, + ), + model=dict( + gradient_model=True, + k=3, + reg=50, + neighbor_pool_size=1000, + train_freq_gradient_model=500, + # + ensemble_size=5, + elite_size=3, + state_size=obs_shape, + action_size=action_shape, + reward_size=1, + hidden_size=100, + use_decay=True, + batch_size=64, + holdout_ratio=0.1, + max_epochs_since_update=5, + deterministic_rollout=True, + ), + ), +) + +main_config = EasyDict(main_config) + +create_config = dict( + env=dict( + type='mbpendulum', + import_names=['dizoo.classic_control.pendulum.envs.pendulum_env'], + ), + env_manager=dict(type='base'), + policy=dict( + type='mbsac', + import_names=['ding.policy.mbpolicy.mbsac'], + ), + replay_buffer=dict(type='naive', ), + world_model=dict( + type='ddppo', + import_names=['ding.world_model.ddppo'], + ), +) +create_config = EasyDict(create_config) + +if __name__ == '__main__': + serial_pipeline_dream((main_config, create_config), seed=0) diff --git a/dizoo/classic_control/pendulum/config/mbrl/pendulum_mbsac_mbpo_config.py b/dizoo/classic_control/pendulum/config/mbrl/pendulum_mbsac_mbpo_config.py new file mode 100644 index 0000000000..06f30b93be --- /dev/null +++ b/dizoo/classic_control/pendulum/config/mbrl/pendulum_mbsac_mbpo_config.py @@ -0,0 +1,110 @@ +from easydict import EasyDict + +from ding.entry import serial_pipeline_dream + +# environment hypo +env_id = 'Pendulum-v0' +obs_shape = 3 +action_shape = 1 + +# gpu +cuda = False + +main_config = dict( + exp_name='pendulum_mbsac_mbpo_seed0', + env=dict( + env_id=env_id, # only for backward compatibility + collector_env_num=10, + evaluator_env_num=5, + # (bool) Scale output action into legal range. + act_scale=True, + n_evaluator_episode=5, + stop_value=-250, + ), + policy=dict( + cuda=cuda, + # backward compatibility: it is better to + # put random_collect_size in policy.other + random_collect_size=1000, + model=dict( + obs_shape=obs_shape, + action_shape=action_shape, + twin_critic=True, + action_space='reparameterization', + actor_head_hidden_size=128, + critic_head_hidden_size=128, + ), + learn=dict( + lambda_=0.8, + sample_state=False, + update_per_collect=1, + batch_size=128, + learning_rate_q=0.001, + learning_rate_policy=0.001, + learning_rate_alpha=0.0003, + ignore_done=True, + target_theta=0.005, + discount_factor=0.99, + auto_alpha=True, + value_network=False, + ), + collect=dict( + n_sample=1, + unroll_len=1, + ), + command=dict(), + eval=dict(evaluator=dict(eval_freq=100, )), + other=dict( + # environment buffer + replay_buffer=dict(replay_buffer_size=100000, ), + ), + ), + world_model=dict( + eval_freq=100, # w.r.t envstep + train_freq=100, # w.r.t envstep + cuda=cuda, + rollout_length_scheduler=dict( + type='linear', + rollout_start_step=2000, + rollout_end_step=15000, + rollout_length_min=3, + rollout_length_max=3, + ), + model=dict( + ensemble_size=5, + elite_size=3, + state_size=obs_shape, + action_size=action_shape, + reward_size=1, + hidden_size=100, + use_decay=True, + batch_size=64, + holdout_ratio=0.1, + max_epochs_since_update=5, + deterministic_rollout=True, + ), + ), +) + +main_config = EasyDict(main_config) + +create_config = dict( + env=dict( + type='mbpendulum', + import_names=['dizoo.classic_control.pendulum.envs.pendulum_env'], + ), + env_manager=dict(type='base'), + policy=dict( + type='mbsac', + import_names=['ding.policy.mbpolicy.mbsac'], + ), + replay_buffer=dict(type='naive', ), + world_model=dict( + type='mbpo', + import_names=['ding.world_model.mbpo'], + ), +) +create_config = EasyDict(create_config) + +if __name__ == '__main__': + serial_pipeline_dream((main_config, create_config), seed=0) diff --git a/dizoo/classic_control/pendulum/config/mbrl/pendulum_sac_ddppo_config.py b/dizoo/classic_control/pendulum/config/mbrl/pendulum_sac_ddppo_config.py new file mode 100644 index 0000000000..4eb551261d --- /dev/null +++ b/dizoo/classic_control/pendulum/config/mbrl/pendulum_sac_ddppo_config.py @@ -0,0 +1,121 @@ +from easydict import EasyDict + +from ding.entry import serial_pipeline_dyna + +# environment hypo +env_id = 'Pendulum-v0' +obs_shape = 3 +action_shape = 1 + +# gpu +cuda = False + +main_config = dict( + exp_name='pendulum_sac_ddppo_seed0', + env=dict( + env_id=env_id, # only for backward compatibility + collector_env_num=10, + evaluator_env_num=5, + # (bool) Scale output action into legal range. + act_scale=True, + n_evaluator_episode=5, + stop_value=-250, + ), + policy=dict( + cuda=cuda, + # backward compatibility: it is better to + # put random_collect_size in policy.other + random_collect_size=1000, + model=dict( + obs_shape=obs_shape, + action_shape=action_shape, + twin_critic=True, + action_space='reparameterization', + actor_head_hidden_size=128, + critic_head_hidden_size=128, + ), + learn=dict( + update_per_collect=1, + batch_size=128, + learning_rate_q=0.001, + learning_rate_policy=0.001, + learning_rate_alpha=0.0003, + ignore_done=True, + target_theta=0.005, + discount_factor=0.99, + auto_alpha=True, + value_network=False, + ), + collect=dict( + n_sample=1, + unroll_len=1, + ), + command=dict(), + eval=dict(evaluator=dict(eval_freq=100, )), + other=dict( + # environment buffer + replay_buffer=dict(replay_buffer_size=100000, ), + ), + ), + world_model=dict( + eval_freq=100, # w.r.t envstep + train_freq=100, # w.r.t envstep + cuda=cuda, + rollout_length_scheduler=dict( + type='linear', + rollout_start_step=2000, + rollout_end_step=15000, + rollout_length_min=1, + rollout_length_max=1, + ), + model=dict( + gradient_model=True, + k=3, + reg=50, + neighbor_pool_size=1000, + train_freq_gradient_model=500, + # + ensemble_size=5, + elite_size=3, + state_size=obs_shape, + action_size=action_shape, + reward_size=1, + hidden_size=100, + use_decay=True, + batch_size=64, + holdout_ratio=0.1, + max_epochs_since_update=5, + deterministic_rollout=True, + ), + other=dict( + rollout_batch_size=10000, + rollout_retain=4, + real_ratio=0.05, + imagination_buffer=dict(replay_buffer_size=600000, ), + ), + ), +) + +main_config = EasyDict(main_config) + +create_config = dict( + env=dict( + type='mbpendulum', + import_names=['dizoo.classic_control.pendulum.envs.pendulum_env'], + ), + env_manager=dict(type='base'), + policy=dict( + type='sac', + import_names=['ding.policy.sac'], + ), + replay_buffer=dict(type='naive', ), + imagination_buffer=dict(type='elastic', ), + world_model=dict( + type='ddppo', + import_names=['ding.world_model.ddppo'], + ), +) +create_config = EasyDict(create_config) + +if __name__ == '__main__': + serial_pipeline_dyna((main_config, create_config), seed=0) diff --git a/dizoo/classic_control/pendulum/config/mbrl/pendulum_sac_mbpo_config.py b/dizoo/classic_control/pendulum/config/mbrl/pendulum_sac_mbpo_config.py new file mode 100644 index 0000000000..9e1fddd426 --- /dev/null +++ b/dizoo/classic_control/pendulum/config/mbrl/pendulum_sac_mbpo_config.py @@ -0,0 +1,115 @@ +from easydict import EasyDict + +from ding.entry import serial_pipeline_dyna + +# environment hypo +env_id = 'Pendulum-v0' +obs_shape = 3 +action_shape = 1 + +# gpu +cuda = False + +main_config = dict( + exp_name='pendulum_sac_mbpo_seed0', + env=dict( + env_id=env_id, # only for backward compatibility + collector_env_num=10, + evaluator_env_num=5, + # (bool) Scale output action into legal range. + act_scale=True, + n_evaluator_episode=5, + stop_value=-250, + ), + policy=dict( + cuda=cuda, + # backward compatibility: it is better to + # put random_collect_size in policy.other + random_collect_size=1000, + model=dict( + obs_shape=obs_shape, + action_shape=action_shape, + twin_critic=True, + action_space='reparameterization', + actor_head_hidden_size=128, + critic_head_hidden_size=128, + ), + learn=dict( + update_per_collect=1, + batch_size=128, + learning_rate_q=0.001, + learning_rate_policy=0.001, + learning_rate_alpha=0.0003, + ignore_done=True, + target_theta=0.005, + discount_factor=0.99, + auto_alpha=True, + value_network=False, + ), + collect=dict( + n_sample=1, + unroll_len=1, + ), + command=dict(), + eval=dict(evaluator=dict(eval_freq=100, )), + other=dict( + # environment buffer + replay_buffer=dict(replay_buffer_size=100000, ), + ), + ), + world_model=dict( + eval_freq=100, # w.r.t envstep + train_freq=100, # w.r.t envstep + cuda=cuda, + rollout_length_scheduler=dict( + type='linear', + rollout_start_step=2000, + rollout_end_step=15000, + rollout_length_min=1, + rollout_length_max=1, + ), + model=dict( + ensemble_size=5, + elite_size=3, + state_size=obs_shape, + action_size=action_shape, + reward_size=1, + hidden_size=100, + use_decay=True, + batch_size=64, + holdout_ratio=0.1, + max_epochs_since_update=5, + deterministic_rollout=True, + ), + other=dict( + rollout_batch_size=10000, + rollout_retain=4, + real_ratio=0.05, + imagination_buffer=dict(replay_buffer_size=600000, ), + ), + ), +) + +main_config = EasyDict(main_config) + +create_config = dict( + env=dict( + type='mbpendulum', + import_names=['dizoo.classic_control.pendulum.envs.pendulum_env'], + ), + env_manager=dict(type='base'), + policy=dict( + type='sac', + import_names=['ding.policy.sac'], + ), + replay_buffer=dict(type='naive', ), + imagination_buffer=dict(type='elastic', ), + world_model=dict( + type='mbpo', + import_names=['ding.world_model.mbpo'], + ), +) +create_config = EasyDict(create_config) + +if __name__ == '__main__': + serial_pipeline_dyna((main_config, create_config), seed=0) diff --git a/dizoo/classic_control/pendulum/envs/pendulum_env.py b/dizoo/classic_control/pendulum/envs/pendulum_env.py index 2eca5ea892..a1abbeae79 100644 --- a/dizoo/classic_control/pendulum/envs/pendulum_env.py +++ b/dizoo/classic_control/pendulum/envs/pendulum_env.py @@ -1,5 +1,6 @@ from typing import Any, Union, Optional import gym +import torch import numpy as np from ding.envs import BaseEnv, BaseEnvTimestep from ding.envs.common.common_function import affine_transform @@ -89,3 +90,17 @@ def reward_space(self) -> gym.spaces.Space: def __repr__(self) -> str: return "DI-engine Pendulum Env({})".format(self._cfg.env_id) + + +@ENV_REGISTRY.register('mbpendulum') +class MBPendulumEnv(PendulumEnv): + def termination_fn(self, next_obs: torch.Tensor) -> torch.Tensor: + """ + Overview: + This function determines whether each state is a terminated state + .. note:: + Done is always false for pendulum, according to\ + . + """ + done = torch.zeros_like(next_obs.sum(-1)).bool() + return done diff --git a/dizoo/mujoco/config/ant_sac_mbpo_default_config.py b/dizoo/mujoco/config/ant_sac_mbpo_default_config.py deleted file mode 100644 index 145af6b0bf..0000000000 --- a/dizoo/mujoco/config/ant_sac_mbpo_default_config.py +++ /dev/null @@ -1,135 +0,0 @@ -from easydict import EasyDict -from ding.entry import serial_pipeline_mbrl - -# environment hypo -env_id = 'AntTruncatedObs-v2' -obs_shape = 27 -action_shape = 8 - -# gpu -cuda = True - -# model training hypo -rollout_batch_size = 100000 -rollout_retain = 4 -rollout_start_step = 20000 -rollout_end_step = 150000 -rollout_length_min = 1 -rollout_length_max = 25 - -x0 = rollout_start_step -y0 = rollout_length_min -y1 = rollout_length_max -w = (rollout_length_max - rollout_length_min) / (rollout_end_step - rollout_start_step) -b = rollout_length_min -set_rollout_length = lambda x: int(min(max(w * (x - x0) + b, y0), y1)) -set_buffer_size = lambda x: set_rollout_length(x) * rollout_batch_size * rollout_retain - -main_config = dict( - exp_name='ant_sac_mbpo_seed0', - env=dict( - env_id=env_id, - norm_obs=dict(use_norm=False, ), - norm_reward=dict(use_norm=False, ), - collector_env_num=1, - evaluator_env_num=8, - use_act_scale=True, - n_evaluator_episode=8, - stop_value=100000, - ), - policy=dict( - cuda=cuda, - random_collect_size=10000, - model=dict( - obs_shape=obs_shape, - action_shape=action_shape, - twin_critic=True, - action_space='reparameterization', - actor_head_hidden_size=256, - critic_head_hidden_size=256, - ), - learn=dict( - update_per_collect=20, - batch_size=256, - learning_rate_q=3e-4, - learning_rate_policy=3e-4, - learning_rate_alpha=3e-4, - ignore_done=False, - target_theta=0.005, - discount_factor=0.99, - alpha=0.2, - reparameterization=True, - auto_alpha=False, - ), - collect=dict( - n_sample=1, - unroll_len=1, - ), - command=dict(), - eval=dict(evaluator=dict(eval_freq=5000, )), - other=dict(replay_buffer=dict(replay_buffer_size=1000000, periodic_thruput_seconds=60), ), - ), - model_based=dict( - real_ratio=0.05, - imagine_buffer=dict( - type='elastic', - replay_buffer_size=6000000, - deepcopy=False, - enable_track_used_data=False, - set_buffer_size=set_buffer_size, - periodic_thruput_seconds=60, - ), - env_model=dict( - type='mbpo', - import_names=['ding.model.template.model_based.mbpo'], - network_size=7, - elite_size=5, - state_size=obs_shape, - action_size=action_shape, - reward_size=1, - hidden_size=200, - use_decay=True, - batch_size=256, - holdout_ratio=0.1, - max_epochs_since_update=5, - eval_freq=250, - train_freq=250, - cuda=cuda, - ), - model_env=dict( - type='mujoco_model', - import_names=['dizoo.mujoco.envs.mujoco_model_env'], - env_id=env_id, - rollout_batch_size=rollout_batch_size, - set_rollout_length=set_rollout_length, - ), - ), -) - -main_config = EasyDict(main_config) - -create_config = dict( - env=dict( - type='mujoco', - import_names=['dizoo.mujoco.envs.mujoco_env'], - ), - env_manager=dict(type='subprocess'), - policy=dict( - type='sac', - import_names=['ding.policy.sac'], - ), - replay_buffer=dict(type='naive', ), -) -create_config = EasyDict(create_config) - -if __name__ == '__main__': - import argparse - import copy - parser = argparse.ArgumentParser() - parser.add_argument('--seed', type=int, default=0) - args = parser.parse_args() - params = vars(args) - seed = params['seed'] - main_config.exp_name = f'ant_sac_mbpo_seed{seed}' - serial_pipeline_mbrl((copy.deepcopy(main_config), copy.deepcopy(create_config)), - seed=seed, max_env_step=400000) \ No newline at end of file diff --git a/dizoo/mujoco/config/humanoid_sac_mbpo_default_config.py b/dizoo/mujoco/config/humanoid_sac_mbpo_default_config.py deleted file mode 100644 index 11f0198ce4..0000000000 --- a/dizoo/mujoco/config/humanoid_sac_mbpo_default_config.py +++ /dev/null @@ -1,135 +0,0 @@ -from easydict import EasyDict -from ding.entry import serial_pipeline_mbrl - -# environment hypo -env_id = 'HumanoidTruncatedObs-v2' -obs_shape = 45 -action_shape = 17 - -# gpu -cuda = True - -# model training hypo -rollout_batch_size = 100000 -rollout_retain = 4 -rollout_start_step = 20000 -rollout_end_step = 450000 -rollout_length_min = 1 -rollout_length_max = 25 - -x0 = rollout_start_step -y0 = rollout_length_min -y1 = rollout_length_max -w = (rollout_length_max - rollout_length_min) / (rollout_end_step - rollout_start_step) -b = rollout_length_min -set_rollout_length = lambda x: int(min(max(w * (x - x0) + b, y0), y1)) -set_buffer_size = lambda x: set_rollout_length(x) * rollout_batch_size * rollout_retain - -main_config = dict( - exp_name='humanoid_sac_mbpo_seed0', - env=dict( - env_id=env_id, - norm_obs=dict(use_norm=False, ), - norm_reward=dict(use_norm=False, ), - collector_env_num=1, - evaluator_env_num=8, - use_act_scale=True, - n_evaluator_episode=8, - stop_value=100000, - ), - policy=dict( - cuda=cuda, - random_collect_size=10000, - model=dict( - obs_shape=obs_shape, - action_shape=action_shape, - twin_critic=True, - action_space='reparameterization', - actor_head_hidden_size=512, - critic_head_hidden_size=512, - ), - learn=dict( - update_per_collect=20, - batch_size=256, - learning_rate_q=3e-4, - learning_rate_policy=3e-4, - learning_rate_alpha=3e-4, - ignore_done=False, - target_theta=0.005, - discount_factor=0.99, - alpha=0.2, - reparameterization=True, - auto_alpha=False, - ), - collect=dict( - n_sample=1, - unroll_len=1, - ), - command=dict(), - eval=dict(evaluator=dict(eval_freq=5000, )), - other=dict(replay_buffer=dict(replay_buffer_size=1000000, periodic_thruput_seconds=60), ), - ), - model_based=dict( - real_ratio=0.05, - imagine_buffer=dict( - type='elastic', - replay_buffer_size=6000000, - deepcopy=False, - enable_track_used_data=False, - set_buffer_size=set_buffer_size, - periodic_thruput_seconds=60, - ), - env_model=dict( - type='mbpo', - import_names=['ding.model.template.model_based.mbpo'], - network_size=7, - elite_size=5, - state_size=obs_shape, - action_size=action_shape, - reward_size=1, - hidden_size=400, - use_decay=True, - batch_size=256, - holdout_ratio=0.1, - max_epochs_since_update=5, - eval_freq=250, - train_freq=250, - cuda=cuda, - ), - model_env=dict( - type='mujoco_model', - import_names=['dizoo.mujoco.envs.mujoco_model_env'], - env_id=env_id, - rollout_batch_size=rollout_batch_size, - set_rollout_length=set_rollout_length, - ), - ), -) - -main_config = EasyDict(main_config) - -create_config = dict( - env=dict( - type='mujoco', - import_names=['dizoo.mujoco.envs.mujoco_env'], - ), - env_manager=dict(type='subprocess'), - policy=dict( - type='sac', - import_names=['ding.policy.sac'], - ), - replay_buffer=dict(type='naive', ), -) -create_config = EasyDict(create_config) - -if __name__ == '__main__': - import argparse - import copy - parser = argparse.ArgumentParser() - parser.add_argument('--seed', type=int, default=0) - args = parser.parse_args() - params = vars(args) - seed = params['seed'] - main_config.exp_name = f'humanoid_sac_mbpo_seed{seed}' - serial_pipeline_mbrl((copy.deepcopy(main_config), copy.deepcopy(create_config)), - seed=seed, max_env_step=400000) diff --git a/dizoo/mujoco/config/mbrl/halfcheetah_mbsac_mbpo_config.py b/dizoo/mujoco/config/mbrl/halfcheetah_mbsac_mbpo_config.py new file mode 100644 index 0000000000..754e5a74d7 --- /dev/null +++ b/dizoo/mujoco/config/mbrl/halfcheetah_mbsac_mbpo_config.py @@ -0,0 +1,115 @@ +from easydict import EasyDict + +from ding.entry import serial_pipeline_dream + +# environment hypo +env_id = 'HalfCheetah-v3' +obs_shape = 17 +action_shape = 6 + +# gpu +cuda = True + +main_config = dict( + exp_name='halfcheetach_mbsac_mbpo_seed0', + env=dict( + env_id=env_id, + norm_obs=dict(use_norm=False, ), + norm_reward=dict(use_norm=False, ), + collector_env_num=1, + evaluator_env_num=8, + use_act_scale=True, + n_evaluator_episode=8, + stop_value=100000, + ), + policy=dict( + cuda=cuda, + # it is better to put random_collect_size in policy.other + random_collect_size=10000, + model=dict( + obs_shape=obs_shape, + action_shape=action_shape, + twin_critic=True, + action_space='reparameterization', + actor_head_hidden_size=256, + critic_head_hidden_size=256, + ), + learn=dict( + lambda_=0.8, + sample_state=False, + update_per_collect=40, + batch_size=256, + learning_rate_q=3e-4, + learning_rate_policy=3e-4, + learning_rate_alpha=3e-4, + ignore_done=False, + target_theta=0.005, + discount_factor=0.99, + alpha=0.2, + reparameterization=True, + auto_alpha=False, + ), + collect=dict( + n_sample=1, + unroll_len=1, + ), + command=dict(), + eval=dict(evaluator=dict(eval_freq=500, )), # w.r.t envstep + other=dict( + # environment buffer + replay_buffer=dict( + replay_buffer_size=1000000, + periodic_thruput_seconds=60 + ), + ), + ), + world_model=dict( + eval_freq=250, # w.r.t envstep + train_freq=250, # w.r.t envstep + cuda=cuda, + rollout_length_scheduler=dict( + type='linear', + rollout_start_step=20000, + rollout_end_step=40000, + rollout_length_min=1, + rollout_length_max=3, + ), + model=dict( + ensemble_size=7, + elite_size=5, + state_size=obs_shape, # has to be specified + action_size=action_shape, # has to be specified + reward_size=1, + hidden_size=200, + use_decay=True, + batch_size=256, + holdout_ratio=0.1, + max_epochs_since_update=5, + deterministic_rollout=True, + ), + ), +) + +main_config = EasyDict(main_config) + +create_config = dict( + env=dict( + type='mbmujoco', + import_names=['dizoo.mujoco.envs.mujoco_env'], + ), + env_manager=dict(type='subprocess'), + policy=dict( + type='mbsac', + import_names=['ding.policy.mbpolicy.mbsac'], + ), + replay_buffer=dict(type='naive', ), + world_model=dict( + type='mbpo', + import_names=['ding.world_model.mbpo'], + ), +) +create_config = EasyDict(create_config) + + +if __name__ == '__main__': + serial_pipeline_dream((main_config, create_config), seed=0, max_env_step=100000) diff --git a/dizoo/mujoco/config/halfcheetah_sac_mbpo_config.py b/dizoo/mujoco/config/mbrl/halfcheetah_sac_mbpo_config.py similarity index 51% rename from dizoo/mujoco/config/halfcheetah_sac_mbpo_config.py rename to dizoo/mujoco/config/mbrl/halfcheetah_sac_mbpo_config.py index 9b11caaa63..f1260df418 100644 --- a/dizoo/mujoco/config/halfcheetah_sac_mbpo_config.py +++ b/dizoo/mujoco/config/mbrl/halfcheetah_sac_mbpo_config.py @@ -1,5 +1,7 @@ from easydict import EasyDict +from ding.entry import serial_pipeline_dyna + # environment hypo env_id = 'HalfCheetah-v3' obs_shape = 17 @@ -8,24 +10,8 @@ # gpu cuda = True -# model training hypo -rollout_batch_size = 100000 -rollout_retain = 4 -rollout_start_step = 20000 -rollout_end_step = 150000 -rollout_length_min = 1 -rollout_length_max = 1 - -x0 = rollout_start_step -y0 = rollout_length_min -y1 = rollout_length_max -w = (rollout_length_max - rollout_length_min) / (rollout_end_step - rollout_start_step) -b = rollout_length_min -set_rollout_length = lambda x: int(min(max(w * (x - x0) + b, y0), y1)) -set_buffer_size = lambda x: set_rollout_length(x) * rollout_batch_size * rollout_retain - main_config = dict( - exp_name='halfcheetach_mbpo_sac_seed0', + exp_name='halfcheetach_sac_mbpo_seed0', env=dict( env_id=env_id, norm_obs=dict(use_norm=False, ), @@ -35,10 +21,10 @@ use_act_scale=True, n_evaluator_episode=8, stop_value=100000, - manager=dict(shared_memory=False, ), ), policy=dict( cuda=cuda, + # it is better to put random_collect_size in policy.other random_collect_size=10000, model=dict( obs_shape=obs_shape, @@ -66,42 +52,44 @@ unroll_len=1, ), command=dict(), - eval=dict(evaluator=dict(eval_freq=5000, )), - other=dict(replay_buffer=dict(replay_buffer_size=1000000, periodic_thruput_seconds=60), ), + eval=dict(evaluator=dict(eval_freq=500, )), # w.r.t envstep + other=dict( + # environment buffer + replay_buffer=dict( + replay_buffer_size=1000000, + periodic_thruput_seconds=60 + ), + ), ), - model_based=dict( - real_ratio=0.05, - imagine_buffer=dict( - type='elastic', - replay_buffer_size=6000000, - deepcopy=False, - enable_track_used_data=False, - set_buffer_size=set_buffer_size, - periodic_thruput_seconds=60, + world_model=dict( + eval_freq=250, # w.r.t envstep + train_freq=250, # w.r.t envstep + cuda=cuda, + rollout_length_scheduler=dict( + type='linear', + rollout_start_step=20000, + rollout_end_step=150000, + rollout_length_min=1, + rollout_length_max=1, ), - env_model=dict( - type='mbpo', - import_names=['ding.model.template.model_based.mbpo'], - network_size=7, + model=dict( + ensemble_size=7, elite_size=5, - state_size=obs_shape, - action_size=action_shape, + state_size=obs_shape, # has to be specified + action_size=action_shape, # has to be specified reward_size=1, - hidden_size=200, + hidden_size=400, use_decay=True, batch_size=256, holdout_ratio=0.1, max_epochs_since_update=5, - eval_freq=250, - train_freq=250, - cuda=cuda, + deterministic_rollout=True, ), - model_env=dict( - type='mujoco_model', - import_names=['dizoo.mujoco.envs.mujoco_model_env'], - env_id=env_id, - rollout_batch_size=rollout_batch_size, - set_rollout_length=set_rollout_length, + other=dict( + rollout_batch_size=100000, + rollout_retain=4, + real_ratio=0.05, + imagination_buffer=dict(replay_buffer_size=6000000, ), ), ), ) @@ -110,7 +98,7 @@ create_config = dict( env=dict( - type='mujoco', + type='mbmujoco', import_names=['dizoo.mujoco.envs.mujoco_env'], ), env_manager=dict(type='subprocess'), @@ -119,9 +107,14 @@ import_names=['ding.policy.sac'], ), replay_buffer=dict(type='naive', ), + imagination_buffer=dict(type='elastic', ), + world_model=dict( + type='mbpo', + import_names=['ding.world_model.mbpo'], + ), ) create_config = EasyDict(create_config) + if __name__ == '__main__': - from ding.entry import serial_pipeline_mbrl - serial_pipeline_mbrl((main_config, create_config), seed=0) + serial_pipeline_dyna((main_config, create_config), seed=0, max_env_step=100000) diff --git a/dizoo/mujoco/config/mbrl/hopper_mbsac_mbpo_config.py b/dizoo/mujoco/config/mbrl/hopper_mbsac_mbpo_config.py new file mode 100644 index 0000000000..f6fb8d2148 --- /dev/null +++ b/dizoo/mujoco/config/mbrl/hopper_mbsac_mbpo_config.py @@ -0,0 +1,115 @@ +from easydict import EasyDict + +from ding.entry import serial_pipeline_dream + +# environment hypo +env_id = 'Hopper-v2' +obs_shape = 11 +action_shape = 3 + +# gpu +cuda = True + +main_config = dict( + exp_name='hopper_mbsac_mbpo_seed0', + env=dict( + env_id=env_id, + norm_obs=dict(use_norm=False, ), + norm_reward=dict(use_norm=False, ), + collector_env_num=1, + evaluator_env_num=8, + use_act_scale=True, + n_evaluator_episode=8, + stop_value=100000, + ), + policy=dict( + cuda=cuda, + # it is better to put random_collect_size in policy.other + random_collect_size=10000, + model=dict( + obs_shape=obs_shape, + action_shape=action_shape, + twin_critic=True, + action_space='reparameterization', + actor_head_hidden_size=256, + critic_head_hidden_size=256, + ), + learn=dict( + lambda_=0.8, + sample_state=False, + update_per_collect=20, + batch_size=256, + learning_rate_q=3e-4, + learning_rate_policy=3e-4, + learning_rate_alpha=3e-4, + ignore_done=False, + target_theta=0.005, + discount_factor=0.99, + alpha=0.2, + reparameterization=True, + auto_alpha=False, + ), + collect=dict( + n_sample=1, + unroll_len=1, + ), + command=dict(), + eval=dict(evaluator=dict(eval_freq=500, )), # w.r.t envstep + other=dict( + # environment buffer + replay_buffer=dict( + replay_buffer_size=1000000, + periodic_thruput_seconds=60 + ), + ), + ), + world_model=dict( + eval_freq=250, # w.r.t envstep + train_freq=250, # w.r.t envstep + cuda=cuda, + rollout_length_scheduler=dict( + type='linear', + rollout_start_step=20000, + rollout_end_step=40000, + rollout_length_min=1, + rollout_length_max=3, + ), + model=dict( + ensemble_size=7, + elite_size=5, + state_size=obs_shape, # has to be specified + action_size=action_shape, # has to be specified + reward_size=1, + hidden_size=200, + use_decay=True, + batch_size=256, + holdout_ratio=0.1, + max_epochs_since_update=5, + deterministic_rollout=True, + ), + ), +) + +main_config = EasyDict(main_config) + +create_config = dict( + env=dict( + type='mbmujoco', + import_names=['dizoo.mujoco.envs.mujoco_env'], + ), + env_manager=dict(type='subprocess'), + policy=dict( + type='mbsac', + import_names=['ding.policy.mbpolicy.mbsac'], + ), + replay_buffer=dict(type='naive', ), + world_model=dict( + type='mbpo', + import_names=['ding.world_model.mbpo'], + ), +) +create_config = EasyDict(create_config) + + +if __name__ == '__main__': + serial_pipeline_dream((main_config, create_config), seed=0, max_env_step=100000) diff --git a/dizoo/mujoco/config/hopper_sac_mbpo_config.py b/dizoo/mujoco/config/mbrl/hopper_sac_mbpo_config.py similarity index 53% rename from dizoo/mujoco/config/hopper_sac_mbpo_config.py rename to dizoo/mujoco/config/mbrl/hopper_sac_mbpo_config.py index b4ed9ab4ab..1de119adb5 100644 --- a/dizoo/mujoco/config/hopper_sac_mbpo_config.py +++ b/dizoo/mujoco/config/mbrl/hopper_sac_mbpo_config.py @@ -1,5 +1,7 @@ from easydict import EasyDict +from ding.entry import serial_pipeline_dyna + # environment hypo env_id = 'Hopper-v2' obs_shape = 11 @@ -8,22 +10,6 @@ # gpu cuda = True -# model training hypo -rollout_batch_size = 100000 -rollout_retain = 4 -rollout_start_step = 20000 -rollout_end_step = 150000 -rollout_length_min = 1 -rollout_length_max = 15 - -x0 = rollout_start_step -y0 = rollout_length_min -y1 = rollout_length_max -w = (rollout_length_max - rollout_length_min) / (rollout_end_step - rollout_start_step) -b = rollout_length_min -set_rollout_length = lambda x: int(min(max(w * (x - x0) + b, y0), y1)) -set_buffer_size = lambda x: set_rollout_length(x) * rollout_batch_size * rollout_retain - main_config = dict( exp_name='hopper_sac_mbpo_seed0', env=dict( @@ -38,6 +24,7 @@ ), policy=dict( cuda=cuda, + # it is better to put random_collect_size in policy.other random_collect_size=10000, model=dict( obs_shape=obs_shape, @@ -65,42 +52,44 @@ unroll_len=1, ), command=dict(), - eval=dict(evaluator=dict(eval_freq=5000, )), - other=dict(replay_buffer=dict(replay_buffer_size=1000000, periodic_thruput_seconds=60), ), + eval=dict(evaluator=dict(eval_freq=500, )), # w.r.t envstep + other=dict( + # environment buffer + replay_buffer=dict( + replay_buffer_size=1000000, + periodic_thruput_seconds=60 + ), + ), ), - model_based=dict( - real_ratio=0.05, - imagine_buffer=dict( - type='elastic', - replay_buffer_size=6000000, - deepcopy=False, - enable_track_used_data=False, - set_buffer_size=set_buffer_size, - periodic_thruput_seconds=60, + world_model=dict( + eval_freq=250, # w.r.t envstep + train_freq=250, # w.r.t envstep + cuda=cuda, + rollout_length_scheduler=dict( + type='linear', + rollout_start_step=20000, + rollout_end_step=150000, + rollout_length_min=1, + rollout_length_max=15, ), - env_model=dict( - type='mbpo', - import_names=['ding.model.template.model_based.mbpo'], - network_size=7, + model=dict( + ensemble_size=7, elite_size=5, - state_size=obs_shape, - action_size=action_shape, + state_size=obs_shape, # has to be specified + action_size=action_shape, # has to be specified reward_size=1, hidden_size=200, use_decay=True, batch_size=256, holdout_ratio=0.1, max_epochs_since_update=5, - eval_freq=250, - train_freq=250, - cuda=cuda, + deterministic_rollout=True, ), - model_env=dict( - type='mujoco_model', - import_names=['dizoo.mujoco.envs.mujoco_model_env'], - env_id=env_id, - rollout_batch_size=rollout_batch_size, - set_rollout_length=set_rollout_length, + other=dict( + rollout_batch_size=100000, + rollout_retain=4, + real_ratio=0.05, + imagination_buffer=dict(replay_buffer_size=6000000, ), ), ), ) @@ -109,7 +98,7 @@ create_config = dict( env=dict( - type='mujoco', + type='mbmujoco', import_names=['dizoo.mujoco.envs.mujoco_env'], ), env_manager=dict(type='subprocess'), @@ -118,10 +107,14 @@ import_names=['ding.policy.sac'], ), replay_buffer=dict(type='naive', ), + imagination_buffer=dict(type='elastic', ), + world_model=dict( + type='mbpo', + import_names=['ding.world_model.mbpo'], + ), ) create_config = EasyDict(create_config) if __name__ == '__main__': - from ding.entry import serial_pipeline_mbrl - serial_pipeline_mbrl((main_config, create_config), seed=0) + serial_pipeline_dyna((main_config, create_config), seed=0, max_env_step=100000) diff --git a/dizoo/mujoco/config/mbrl/walker2d_mbsac_mbpo_config.py b/dizoo/mujoco/config/mbrl/walker2d_mbsac_mbpo_config.py new file mode 100644 index 0000000000..061018a068 --- /dev/null +++ b/dizoo/mujoco/config/mbrl/walker2d_mbsac_mbpo_config.py @@ -0,0 +1,115 @@ +from easydict import EasyDict + +from ding.entry import serial_pipeline_dream + +# environment hypo +env_id = 'Walker2d-v2' +obs_shape = 17 +action_shape = 6 + +# gpu +cuda = True + +main_config = dict( + exp_name='walker2d_mbsac_mbpo_seed0', + env=dict( + env_id=env_id, + norm_obs=dict(use_norm=False, ), + norm_reward=dict(use_norm=False, ), + collector_env_num=4, + evaluator_env_num=8, + use_act_scale=True, + n_evaluator_episode=8, + stop_value=100000, + ), + policy=dict( + cuda=cuda, + # it is better to put random_collect_size in policy.other + random_collect_size=10000, + model=dict( + obs_shape=obs_shape, + action_shape=action_shape, + twin_critic=True, + action_space='reparameterization', + actor_head_hidden_size=256, + critic_head_hidden_size=256, + ), + learn=dict( + lambda_=0.8, + sample_state=False, + update_per_collect=20, + batch_size=512, + learning_rate_q=3e-4, + learning_rate_policy=3e-4, + learning_rate_alpha=3e-4, + ignore_done=False, + target_theta=0.005, + discount_factor=0.99, + alpha=0.2, + reparameterization=True, + auto_alpha=False, + ), + collect=dict( + n_sample=8, + unroll_len=1, + ), + command=dict(), + eval=dict(evaluator=dict(eval_freq=500, )), # w.r.t envstep + other=dict( + # environment buffer + replay_buffer=dict( + replay_buffer_size=1000000, + periodic_thruput_seconds=60 + ), + ), + ), + world_model=dict( + eval_freq=250, # w.r.t envstep + train_freq=250, # w.r.t envstep + cuda=cuda, + rollout_length_scheduler=dict( + type='linear', + rollout_start_step=30000, + rollout_end_step=100000, + rollout_length_min=1, + rollout_length_max=3, + ), + model=dict( + ensemble_size=7, + elite_size=5, + state_size=obs_shape, # has to be specified + action_size=action_shape, # has to be specified + reward_size=1, + hidden_size=200, + use_decay=True, + batch_size=512, + holdout_ratio=0.1, + max_epochs_since_update=5, + deterministic_rollout=True, + ), + ), +) + +main_config = EasyDict(main_config) + +create_config = dict( + env=dict( + type='mbmujoco', + import_names=['dizoo.mujoco.envs.mujoco_env'], + ), + env_manager=dict(type='subprocess'), + policy=dict( + type='mbsac', + import_names=['ding.policy.mbpolicy.mbsac'], + ), + replay_buffer=dict(type='naive', ), + world_model=dict( + type='mbpo', + import_names=['ding.world_model.mbpo'], + ), +) +create_config = EasyDict(create_config) + + +if __name__ == '__main__': + serial_pipeline_dream((main_config, create_config), seed=0, max_env_step=300000) diff --git a/dizoo/mujoco/config/walker2d_sac_mbpo_config.py b/dizoo/mujoco/config/mbrl/walker2d_sac_mbpo_config.py similarity index 52% rename from dizoo/mujoco/config/walker2d_sac_mbpo_config.py rename to dizoo/mujoco/config/mbrl/walker2d_sac_mbpo_config.py index fef96c7b68..b27600e346 100644 --- a/dizoo/mujoco/config/walker2d_sac_mbpo_config.py +++ b/dizoo/mujoco/config/mbrl/walker2d_sac_mbpo_config.py @@ -1,5 +1,7 @@ from easydict import EasyDict +from ding.entry import serial_pipeline_dyna + # environment hypo env_id = 'Walker2d-v2' obs_shape = 17 @@ -8,22 +10,6 @@ # gpu cuda = True -# model training hypo -rollout_batch_size = 100000 -rollout_retain = 4 -rollout_start_step = 20000 -rollout_end_step = 150000 -rollout_length_min = 1 -rollout_length_max = 1 - -x0 = rollout_start_step -y0 = rollout_length_min -y1 = rollout_length_max -w = (rollout_length_max - rollout_length_min) / (rollout_end_step - rollout_start_step) -b = rollout_length_min -set_rollout_length = lambda x: int(min(max(w * (x - x0) + b, y0), y1)) -set_buffer_size = lambda x: set_rollout_length(x) * rollout_batch_size * rollout_retain - main_config = dict( exp_name='walker2d_sac_mbpo_seed0', env=dict( @@ -38,6 +24,7 @@ ), policy=dict( cuda=cuda, + # it is better to put random_collect_size in policy.other random_collect_size=10000, model=dict( obs_shape=obs_shape, @@ -49,7 +36,7 @@ ), learn=dict( update_per_collect=20, - batch_size=2048, + batch_size=512, learning_rate_q=3e-4, learning_rate_policy=3e-4, learning_rate_alpha=3e-4, @@ -65,42 +52,44 @@ unroll_len=1, ), command=dict(), - eval=dict(evaluator=dict(eval_freq=5000, )), - other=dict(replay_buffer=dict(replay_buffer_size=1000000, periodic_thruput_seconds=60), ), + eval=dict(evaluator=dict(eval_freq=500, )), # w.r.t envstep + other=dict( + # environment buffer + replay_buffer=dict( + replay_buffer_size=1000000, + periodic_thruput_seconds=60 + ), + ), ), - model_based=dict( - real_ratio=0.05, - imagine_buffer=dict( - type='elastic', - replay_buffer_size=6000000, - deepcopy=False, - enable_track_used_data=False, - set_buffer_size=set_buffer_size, - periodic_thruput_seconds=60, + world_model=dict( + eval_freq=250, # w.r.t envstep + train_freq=250, # w.r.t envstep + cuda=cuda, + rollout_length_scheduler=dict( + type='linear', + rollout_start_step=20000, + rollout_end_step=150000, + rollout_length_min=1, + rollout_length_max=1, ), - env_model=dict( - type='mbpo', - import_names=['ding.model.template.model_based.mbpo'], - network_size=7, + model=dict( + ensemble_size=7, elite_size=5, - state_size=obs_shape, - action_size=action_shape, + state_size=obs_shape, # has to be specified + action_size=action_shape, # has to be specified reward_size=1, hidden_size=200, use_decay=True, - batch_size=2048, + batch_size=512, holdout_ratio=0.1, max_epochs_since_update=5, - eval_freq=250, - train_freq=250, - cuda=cuda, + deterministic_rollout=True, ), - model_env=dict( - type='mujoco_model', - import_names=['dizoo.mujoco.envs.mujoco_model_env'], - env_id=env_id, - rollout_batch_size=rollout_batch_size, - set_rollout_length=set_rollout_length, + other=dict( + rollout_batch_size=100000, + rollout_retain=4, + real_ratio=0.05, + imagination_buffer=dict(replay_buffer_size=6000000, ), ), ), ) @@ -109,7 +98,7 @@ create_config = dict( env=dict( - type='mujoco', + type='mbmujoco', import_names=['dizoo.mujoco.envs.mujoco_env'], ), env_manager=dict(type='subprocess'), @@ -118,10 +107,14 @@ import_names=['ding.policy.sac'], ), replay_buffer=dict(type='naive', ), + imagination_buffer=dict(type='elastic', ), + world_model=dict( + type='mbpo', + import_names=['ding.world_model.mbpo'], + ), ) create_config = EasyDict(create_config) if __name__ == '__main__': - from ding.entry import serial_pipeline_mbrl - serial_pipeline_mbrl((main_config, create_config), seed=0) + serial_pipeline_dyna((main_config, create_config), seed=0, max_env_step=300000) diff --git a/dizoo/mujoco/envs/__init__.py b/dizoo/mujoco/envs/__init__.py index e42e50a495..fac36665b9 100644 --- a/dizoo/mujoco/envs/__init__.py +++ b/dizoo/mujoco/envs/__init__.py @@ -1,2 +1 @@ from .mujoco_env import MujocoEnv -from .mujoco_model_env import MujocoModelEnv diff --git a/dizoo/mujoco/envs/mujoco_env.py b/dizoo/mujoco/envs/mujoco_env.py index fb530d1d2f..f656e5793a 100644 --- a/dizoo/mujoco/envs/mujoco_env.py +++ b/dizoo/mujoco/envs/mujoco_env.py @@ -3,6 +3,7 @@ import numpy as np from easydict import EasyDict import gym +import torch from ding.envs import BaseEnv, BaseEnvTimestep from ding.envs.common.common_function import affine_transform @@ -119,3 +120,64 @@ def action_space(self) -> gym.spaces.Space: @property def reward_space(self) -> gym.spaces.Space: return self._reward_space + + +@ENV_REGISTRY.register('mbmujoco') +class MBMujocoEnv(MujocoEnv): + def termination_fn(self, next_obs: torch.Tensor) -> torch.Tensor: + """ + Overview: + This function determines whether each state is a terminated state. + .. note:: + This is a collection of termination functions for mujocos used in MBPO (arXiv: 1906.08253),\ + directly copied from MBPO repo https://github.com/jannerm/mbpo/tree/master/mbpo/static. + """ + assert len(next_obs.shape) == 2 + if self._cfg.env_id == "Hopper-v2": + height = next_obs[:, 0] + angle = next_obs[:, 1] + not_done = torch.isfinite(next_obs).all(-1) \ + * (torch.abs(next_obs[:, 1:]) < 100).all(-1) \ + * (height > .7) \ + * (torch.abs(angle) < .2) + + done = ~not_done + return done + elif self._cfg.env_id == "Walker2d-v2": + height = next_obs[:, 0] + angle = next_obs[:, 1] + not_done = (height > 0.8) \ + * (height < 2.0) \ + * (angle > -1.0) \ + * (angle < 1.0) + done = ~not_done + return done + elif 'walker_' in self._cfg.env_id: + torso_height = next_obs[:, -2] + torso_ang = next_obs[:, -1] + if 'walker_7' in self._cfg.env_id or 'walker_5' in self._cfg.env_id: + offset = 0. + else: + offset = 0.26 + not_done = (torso_height > 0.8 - offset) \ + * (torso_height < 2.0 - offset) \ + * (torso_ang > -1.0) \ + * (torso_ang < 1.0) + done = ~not_done + return done + elif self._cfg.env_id == "HalfCheetah-v3": + done = torch.zeros_like(next_obs.sum(-1)).bool() + return done + elif self._cfg.env_id in ['Ant-v2', 'AntTruncatedObs-v2']: + x = next_obs[:, 0] + not_done = torch.isfinite(next_obs).all(axis=-1) \ + * (x >= 0.2) \ + * (x <= 1.0) + done = ~not_done + return done + elif self._cfg.env_id in ['Humanoid-v2', 'HumanoidTruncatedObs-v2']: + z = next_obs[:,0] + done = (z < 1.0) + (z > 2.0) + return done + else: + raise KeyError("not implemented env_id: {}".format(self._cfg.env_id)) diff --git a/dizoo/mujoco/envs/mujoco_gym_env.py b/dizoo/mujoco/envs/mujoco_gym_env.py index a25f5e0ca4..331ab5796c 100644 --- a/dizoo/mujoco/envs/mujoco_gym_env.py +++ b/dizoo/mujoco/envs/mujoco_gym_env.py @@ -19,9 +19,12 @@ def register(gym_env): @gym_env_register('AntTruncatedObs-v2') class AntTruncatedObsEnv(AntEnv): """ + Overview: + Modified ant with observation dim truncated to 27, which is used in MBPO (arXiv: 1906.08253). + .. note:: External forces (sim.data.cfrc_ext) are removed from the observation. - Otherwise identical to Ant-v2 from - https://github.com/openai/gym/blob/master/gym/envs/mujoco/ant.py + Otherwise identical to Ant-v2 from\ + . """ def _get_obs(self): return np.concatenate([ @@ -33,10 +36,13 @@ def _get_obs(self): @gym_env_register('HumanoidTruncatedObs-v2') class HumanoidTruncatedObsEnv(HumanoidEnv): """ - COM inertia (cinert), COM velocity (cvel), actuator forces (qfrc_actuator), + Overview: + Modified humanoid with observation dim truncated to 45, which is used in MBPO (arXiv: 1906.08253). + .. note:: + COM inertia (cinert), COM velocity (cvel), actuator forces (qfrc_actuator),\ and external forces (cfrc_ext) are removed from the observation. - Otherwise identical to Humanoid-v2 from - https://github.com/openai/gym/blob/master/gym/envs/mujoco/humanoid.py + Otherwise identical to Humanoid-v2 from\ + . """ def _get_obs(self): data = self.sim.data diff --git a/dizoo/mujoco/envs/mujoco_model_env.py b/dizoo/mujoco/envs/mujoco_model_env.py deleted file mode 100644 index b037823f25..0000000000 --- a/dizoo/mujoco/envs/mujoco_model_env.py +++ /dev/null @@ -1,131 +0,0 @@ -from typing import Any, Union, List, Callable, Dict -import copy -import torch -import torch.nn as nn -import numpy as np - -from ding.envs import BaseEnv, BaseEnvTimestep -from ding.envs.common.common_function import affine_transform -from ding.torch_utils import to_tensor, to_ndarray, to_list -from .mujoco_wrappers import wrap_mujoco -from ding.utils import ENV_REGISTRY -from ding.worker.collector.base_serial_collector import to_tensor_transitions - - -@ENV_REGISTRY.register('mujoco_model') -class MujocoModelEnv(object): - - def __init__(self, env_id: str, set_rollout_length: Callable, rollout_batch_size: int = 100000): - self.env_id = env_id - self.rollout_batch_size = rollout_batch_size - self._set_rollout_length = set_rollout_length - - def termination_fn(self, next_obs: torch.Tensor) -> torch.Tensor: - # This function determines whether each state is a terminated state - assert len(next_obs.shape) == 2 - if self.env_id == "Hopper-v2": - height = next_obs[:, 0] - angle = next_obs[:, 1] - not_done = torch.isfinite(next_obs).all(-1) \ - * (torch.abs(next_obs[:, 1:]) < 100).all(-1) \ - * (height > .7) \ - * (torch.abs(angle) < .2) - - done = ~not_done - return done - elif self.env_id == "Walker2d-v2": - height = next_obs[:, 0] - angle = next_obs[:, 1] - not_done = (height > 0.8) \ - * (height < 2.0) \ - * (angle > -1.0) \ - * (angle < 1.0) - done = ~not_done - return done - elif 'walker_' in self.env_id: - torso_height = next_obs[:, -2] - torso_ang = next_obs[:, -1] - if 'walker_7' in self.env_id or 'walker_5' in self.env_id: - offset = 0. - else: - offset = 0.26 - not_done = (torso_height > 0.8 - offset) \ - * (torso_height < 2.0 - offset) \ - * (torso_ang > -1.0) \ - * (torso_ang < 1.0) - done = ~not_done - return done - elif self.env_id == "HalfCheetah-v3": - done = torch.zeros_like(next_obs.sum(-1)).bool() - return done - elif self.env_id in ['Ant-v2', 'AntTruncatedObs-v2']: - x = next_obs[:, 0] - not_done = np.isfinite(next_obs).all(axis=-1) \ - * (x >= 0.2) \ - * (x <= 1.0) - done = ~not_done - return done - elif self.env_id in ['Humanoid-v2', 'HumanoidTruncatedObs-v2']: - z = next_obs[:,0] - done = (z < 1.0) + (z > 2.0) - return done - - - def rollout( - self, - env_model: nn.Module, - policy: 'Policy', # noqa - replay_buffer: 'IBuffer', # noqa - imagine_buffer: 'IBuffer', # noqa - envstep: int, - cur_learner_iter: int - ) -> None: - """ - Overview: - This function samples from the replay_buffer, rollouts to generate new data, - and push them into the imagine_buffer - """ - # set rollout length - rollout_length = self._set_rollout_length(envstep) - # load data - data = replay_buffer.sample(self.rollout_batch_size, cur_learner_iter, replace=True) - obs = {id: data[id]['obs'] for id in range(len(data))} - # rollout - buffer = [[] for id in range(len(obs))] - new_data = [] - for i in range(rollout_length): - # get action - obs = to_tensor(obs, dtype=torch.float32) - policy_output = policy.forward(obs) - actions = {id: output['action'] for id, output in policy_output.items()} - # predict next obs and reward - timesteps = self.step(obs, actions, env_model) - obs_new = {} - for id, timestep in timesteps.items(): - transition = policy.process_transition(obs[id], policy_output[id], timestep) - transition['collect_iter'] = cur_learner_iter - buffer[id].append(transition) - if not timestep.done: - obs_new[id] = timestep.obs - if timestep.done or i + 1 == rollout_length: - transitions = to_tensor_transitions(buffer[id]) - train_sample = policy.get_train_sample(transitions) - new_data.extend(train_sample) - if len(obs_new) == 0: - break - obs = obs_new - - imagine_buffer.push(new_data, cur_collector_envstep=envstep) - - def step(self, obs: Dict, act: Dict, env_model: nn.Module) -> Dict: - # This function has the same input and output format as env manager's step - data_id = list(obs.keys()) - obs = torch.stack([obs[id] for id in data_id], dim=0) - act = torch.stack([act[id] for id in data_id], dim=0) - rewards, next_obs = env_model.predict(obs, act) - terminals = self.termination_fn(next_obs) - timesteps = { - id: BaseEnvTimestep(n, r, d, {}) - for id, n, r, d in zip(data_id, next_obs.numpy(), rewards.numpy(), terminals.numpy()) - } - return timesteps From 285942388f79a11cc38f476879fc4f7a1f5f8579 Mon Sep 17 00:00:00 2001 From: lixuelin Date: Thu, 9 Jun 2022 14:15:40 +0800 Subject: [PATCH 091/229] add league learner --- ding/framework/middleware/collector.py | 1 + ding/framework/middleware/league_actor.py | 4 ++++ ding/framework/middleware/league_coordinator.py | 7 +++++++ ding/framework/middleware/league_learner.py | 8 ++++++++ ding/framework/middleware/tests/mock_for_test.py | 1 - ding/framework/middleware/tests/test_league_learner.py | 4 +++- ding/framework/middleware/tests/test_league_pipeline.py | 7 ++++--- dizoo/distar/envs/fake_data.py | 5 ++--- dizoo/distar/envs/meta.py | 2 ++ 9 files changed, 31 insertions(+), 8 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index d4c7c76fad..36d07d79a6 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -1,5 +1,6 @@ from distutils.log import info from easydict import EasyDict +from ding import policy from ding.policy import Policy, get_random_policy from ding.envs import BaseEnvManager from ding.framework import task, EventEnum diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 70007d14d8..51ea83db8e 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -37,11 +37,13 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.job_queue = queue.Queue() self.model_dict = {} self.model_dict_lock = Lock() + self._step = 0 def _on_learner_model(self, learner_model: "LearnerModel"): """ If get newest learner model, put it inside model_queue. """ + print("receive model from learner") with self.model_dict_lock: self.model_dict[learner_model.player_id] = learner_model @@ -114,3 +116,5 @@ def __call__(self, ctx: "BattleContext"): ctx.policy_kwargs = None collector(ctx) + logging.info("{} Step: {}".format(self.__class__, self._step)) + self._step += 1 diff --git a/ding/framework/middleware/league_coordinator.py b/ding/framework/middleware/league_coordinator.py index 27bef09e23..7880f9d47b 100644 --- a/ding/framework/middleware/league_coordinator.py +++ b/ding/framework/middleware/league_coordinator.py @@ -1,8 +1,10 @@ +from collections import defaultdict from time import sleep from threading import Lock from dataclasses import dataclass from typing import TYPE_CHECKING from ding.framework import task, EventEnum +import logging if TYPE_CHECKING: from ding.framework import Task, Context @@ -16,6 +18,7 @@ def __init__(self, league: "BaseLeague") -> None: self._lock = Lock() self._total_send_jobs = 0 self._eval_frequency = 10 + self._step = 0 task.on(EventEnum.ACTOR_GREETING, self._on_actor_greeting) task.on(EventEnum.LEARNER_SEND_META, self._on_learner_meta) @@ -34,11 +37,15 @@ def _on_actor_greeting(self, actor_id): task.emit(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=actor_id), job) def _on_learner_meta(self, player_meta: "PlayerMeta"): + print("on_learner_meta {}".format(player_meta)) self.league.update_active_player(player_meta) self.league.create_historical_player(player_meta) def _on_actor_job(self, job: "Job"): + print("on_actor_job {}".format(job.launch_player)) # right self.league.update_payoff(job) def __call__(self, ctx: "Context") -> None: sleep(1) + logging.info("{} Step: {}".format(self.__class__, self._step)) + self._step += 1 diff --git a/ding/framework/middleware/league_learner.py b/ding/framework/middleware/league_learner.py index 7cc805af99..211db688a7 100644 --- a/ding/framework/middleware/league_learner.py +++ b/ding/framework/middleware/league_learner.py @@ -1,4 +1,5 @@ import os +import logging from dataclasses import dataclass from threading import Lock from time import sleep @@ -31,20 +32,25 @@ def __init__(self, cfg: dict, policy_fn: Callable, player: "ActivePlayer") -> No self._learner = self._get_learner() self._lock = Lock() task.on(EventEnum.ACTOR_SEND_DATA.format(player=self.player_id), self._on_actor_data) + self._step = 0 def _on_actor_data(self, actor_data: "ActorData"): + print("receive data from actor!") with self._lock: cfg = self.cfg for _ in range(cfg.policy.learn.update_per_collect): + print("train model") self._learner.train(actor_data.train_data, actor_data.env_step) self.player.total_agent_step = self._learner.train_iter + print("save checkpoint") checkpoint = self._save_checkpoint() if self.player.is_trained_enough() else None task.emit( EventEnum.LEARNER_SEND_META, PlayerMeta(player_id=self.player_id, checkpoint=checkpoint, total_agent_step=self._learner.train_iter) ) + print("pack model") learner_model = LearnerModel( player_id=self.player_id, state_dict=self._learner.policy.state_dict(), train_iter=self._learner.train_iter ) @@ -71,3 +77,5 @@ def _save_checkpoint(self) -> Optional[Storage]: def __call__(self, _: "Context") -> None: sleep(1) + logging.info("{} Step: {}".format(self.__class__, self._step)) + self._step += 1 diff --git a/ding/framework/middleware/tests/mock_for_test.py b/ding/framework/middleware/tests/mock_for_test.py index 0a5ef694ab..adef35b4b7 100644 --- a/ding/framework/middleware/tests/mock_for_test.py +++ b/ding/framework/middleware/tests/mock_for_test.py @@ -126,7 +126,6 @@ def estimate(self, episode: List[Dict[str, Any]]) -> List[Dict[str, Any]]: class MockLeague(BaseLeague): def __init__(self, cfg) -> None: super().__init__(cfg) - print(self.active_players) self.update_payoff_cnt = 0 self.update_active_player_cnt = 0 self.create_historical_player_cnt = 0 diff --git a/ding/framework/middleware/tests/test_league_learner.py b/ding/framework/middleware/tests/test_league_learner.py index 4918e5492b..1fed2b66f7 100644 --- a/ding/framework/middleware/tests/test_league_learner.py +++ b/ding/framework/middleware/tests/test_league_learner.py @@ -2,6 +2,7 @@ from time import sleep import torch import pytest +import logging from ding.envs import BaseEnvManager from ding.model import VAC @@ -13,6 +14,7 @@ from ding.framework.middleware.tests import cfg, MockLeague, MockLogger from dizoo.league_demo.game_env import GameEnv +logging.getLogger().setLevel(logging.INFO) def prepare_test(): global cfg @@ -73,7 +75,7 @@ def _main(): learner = LeagueLearner(cfg, policy_fn, player) learner._learner._tb_logger = MockLogger() task.use(learner) - task.run(max_step=5) + task.run(max_step=3) @pytest.mark.unittest diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index 2801be6974..7d24682869 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -59,6 +59,7 @@ def _main(): league = MockLeague(cfg.policy.other.league) with task.start(async_mode=True): + print("node id:", task.router.node_id) if task.router.node_id == 0: task.use(LeagueCoordinator(league)) elif task.router.node_id <= N_ACTORS: @@ -70,13 +71,13 @@ def _main(): learner._learner._tb_logger = MockLogger() task.use(learner) - task.run(max_step=10) + task.run(max_step=120) @pytest.mark.unittest def test_league_actor(): - Parallel.runner(n_parallel_workers=N_ACTORS + N_LEARNERS + 1, protocol="tcp", topology="mesh")(_main) + Parallel.runner(n_parallel_workers=N_ACTORS+N_LEARNERS+1, protocol="tcp", topology="mesh")(_main) if __name__ == '__main__': - Parallel.runner(n_parallel_workers=N_ACTORS + N_LEARNERS + 1, protocol="tcp", topology="mesh")(_main) \ No newline at end of file + Parallel.runner(n_parallel_workers=N_ACTORS+N_LEARNERS+1, protocol="tcp", topology="mesh")(_main) \ No newline at end of file diff --git a/dizoo/distar/envs/fake_data.py b/dizoo/distar/envs/fake_data.py index 1b98ddbda7..b0c8b7098e 100644 --- a/dizoo/distar/envs/fake_data.py +++ b/dizoo/distar/envs/fake_data.py @@ -1,9 +1,8 @@ from typing import Sequence import torch -from .meta import MAX_DELAY, MAX_ENTITY_NUM, NUM_ACTIONS, ENTITY_TYPE_NUM, NUM_UPGRADES, NUM_CUMULATIVE_STAT_ACTIONS, \ - NUM_BEGINNING_ORDER_ACTIONS, NUM_UNIT_MIX_ABILITIES, NUM_QUEUE_ACTION, NUM_BUFFS, NUM_ADDON -#from distar.ctools.data.collate_fn import default_collate_with_dim +from .meta import * +# from distar.ctools.data.collate_fn import default_collate_with_dim currTrainCount_MAX = 5 H, W = 152, 160 diff --git a/dizoo/distar/envs/meta.py b/dizoo/distar/envs/meta.py index 6eb39b1661..6a702554da 100644 --- a/dizoo/distar/envs/meta.py +++ b/dizoo/distar/envs/meta.py @@ -9,3 +9,5 @@ NUM_QUEUE_ACTION = 49 NUM_BUFFS = 50 NUM_ADDON = 9 +MAX_SELECTED_UNITS_NUM = 20 # tmp +SPATIAL_SIZE = 20 # tmp From db3afc28a8eaec9cb1b42fd639793ff896ad1772 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Thu, 9 Jun 2022 17:26:35 +0800 Subject: [PATCH 092/229] change the distar_env to fit BaseEnvManager, write test_distar_env_with_manager.py to test. change config to get self-play --- dizoo/distar/envs/distar_env.py | 131 ++++++++++-------- dizoo/distar/envs/test_distar_config.yaml | 2 +- .../envs/test_distar_env_with_manager.py | 93 +++++++++++++ 3 files changed, 165 insertions(+), 61 deletions(-) create mode 100644 dizoo/distar/envs/test_distar_env_with_manager.py diff --git a/dizoo/distar/envs/distar_env.py b/dizoo/distar/envs/distar_env.py index 4b5c2fa394..45530766b6 100644 --- a/dizoo/distar/envs/distar_env.py +++ b/dizoo/distar/envs/distar_env.py @@ -1,6 +1,6 @@ from distar.envs.env import SC2Env -from ding.envs import BaseEnv +from ding.envs import BaseEnv, BaseEnvTimestep from distar.agent.default.lib.actions import ACTIONS, NUM_ACTIONS from distar.agent.default.lib.features import MAX_DELAY, SPATIAL_SIZE, MAX_SELECTED_UNITS_NUM from distar.pysc2.lib.action_dict import ACTIONS_STAT @@ -13,15 +13,23 @@ def __init__(self,cfg): super(DIStarEnv, self).__init__(cfg) def reset(self): - return super(DIStarEnv,self).reset() + observations, game_info, map_name = super(DIStarEnv,self).reset() + return observations def close(self): super(DIStarEnv,self).close() - def step(self,actions): + def step(self, actions): # In DI-engine, the return of BaseEnv.step is ('obs', 'reward', 'done', 'info') # Here in DI-star, the return is ({'raw_obs': self._obs[agent_idx], 'opponent_obs': opponent_obs, 'action_result': self._action_result[agent_idx]}, reward, episode_complete) - return super(DIStarEnv,self).step(actions) + next_observations, reward, done = super(DIStarEnv,self).step(actions) + timestep = BaseEnvTimestep( + obs = next_observations, + reward = reward, + done = done, + info = None + ) + return timestep def seed(self, seed, dynamic_seed=False): self._random_seed = seed @@ -37,63 +45,66 @@ def action_space(self): pass def random_action(self, obs): - raw = obs[0]['raw_obs'].observation.raw_data - - all_unit_types = set() - self_unit_types = set() - - for u in raw.units: - # Here we select the units except “buildings that are in building progress” for simplification - if u.build_progress == 1: - all_unit_types.add(u.unit_type) - if u.alliance == 1: - self_unit_types.add(u.unit_type) - - avail_actions = [ - {0: {'exist_selected_types':[], 'exist_target_types':[]}}, - {168:{'exist_selected_types':[], 'exist_target_types':[]}} - ] # no_op and raw_move_camera don't have seleted_units - - for action_id, action in ACTIONS_STAT.items(): - exist_selected_types = list(self_unit_types.intersection(set(action['selected_type']))) - exist_target_types = list(all_unit_types.intersection(set(action['target_type']))) - - # if an action should have target, but we don't have valid target in this observation, then discard this action - if len(action['target_type']) != 0 and len(exist_target_types) == 0: - continue - - if len(exist_selected_types) > 0: - avail_actions.append({action_id: {'exist_selected_types':exist_selected_types, 'exist_target_types':exist_target_types}}) - - current_action = random.choice(avail_actions) - func_id, exist_types = current_action.popitem() - - if func_id not in [0, 168]: - correspond_selected_units = [u.tag for u in raw.units if u.unit_type in exist_types['exist_selected_types'] and u.build_progress == 1] - correspond_targets = [u.tag for u in raw.units if u.unit_type in exist_types['exist_target_types'] and u.build_progress == 1] - - num_selected_unit = random.randint(0, min(MAX_SELECTED_UNITS_NUM, len(correspond_selected_units))) - - unit_tags = random.sample(correspond_selected_units, num_selected_unit) - target_unit_tag = random.choice(correspond_targets) if len(correspond_targets) > 0 else None - - else: - unit_tags = [] - target_unit_tag = None + return_action = {} + for policy_id in obs.keys(): + raw = obs[policy_id]['raw_obs'].observation.raw_data + + all_unit_types = set() + self_unit_types = set() + + for u in raw.units: + # Here we select the units except “buildings that are in building progress” for simplification + if u.build_progress == 1: + all_unit_types.add(u.unit_type) + if u.alliance == 1: + self_unit_types.add(u.unit_type) + + avail_actions = [ + {0: {'exist_selected_types':[], 'exist_target_types':[]}}, + {168:{'exist_selected_types':[], 'exist_target_types':[]}} + ] # no_op and raw_move_camera don't have seleted_units + + for action_id, action in ACTIONS_STAT.items(): + exist_selected_types = list(self_unit_types.intersection(set(action['selected_type']))) + exist_target_types = list(all_unit_types.intersection(set(action['target_type']))) + + # if an action should have target, but we don't have valid target in this observation, then discard this action + if len(action['target_type']) != 0 and len(exist_target_types) == 0: + continue + + if len(exist_selected_types) > 0: + avail_actions.append({action_id: {'exist_selected_types':exist_selected_types, 'exist_target_types':exist_target_types}}) - data = { - 'func_id': func_id, - 'skip_steps': random.randint(0, MAX_DELAY - 1), - # 'skip_steps': 8, - 'queued': random.randint(0, 1), - 'unit_tags': unit_tags, - 'target_unit_tag': target_unit_tag, - 'location': ( - random.randint(0, SPATIAL_SIZE[0] - 1), - random.randint(0, SPATIAL_SIZE[1] - 1) - ) - } - return {0:[data]} + current_action = random.choice(avail_actions) + func_id, exist_types = current_action.popitem() + + if func_id not in [0, 168]: + correspond_selected_units = [u.tag for u in raw.units if u.unit_type in exist_types['exist_selected_types'] and u.build_progress == 1] + correspond_targets = [u.tag for u in raw.units if u.unit_type in exist_types['exist_target_types'] and u.build_progress == 1] + + num_selected_unit = random.randint(0, min(MAX_SELECTED_UNITS_NUM, len(correspond_selected_units))) + + unit_tags = random.sample(correspond_selected_units, num_selected_unit) + target_unit_tag = random.choice(correspond_targets) if len(correspond_targets) > 0 else None + + else: + unit_tags = [] + target_unit_tag = None + + data = { + 'func_id': func_id, + 'skip_steps': random.randint(0, MAX_DELAY - 1), + # 'skip_steps': 8, + 'queued': random.randint(0, 1), + 'unit_tags': unit_tags, + 'target_unit_tag': target_unit_tag, + 'location': ( + random.randint(0, SPATIAL_SIZE[0] - 1), + random.randint(0, SPATIAL_SIZE[1] - 1) + ) + } + return_action[policy_id] = [data] + return return_action @property diff --git a/dizoo/distar/envs/test_distar_config.yaml b/dizoo/distar/envs/test_distar_config.yaml index a3322baa54..18247e5a54 100644 --- a/dizoo/distar/envs/test_distar_config.yaml +++ b/dizoo/distar/envs/test_distar_config.yaml @@ -2,7 +2,7 @@ actor: job_type: 'train' # ['train', 'eval', 'train_test', 'eval_test'] env: map_name: 'KingsCove' - player_ids: ['agent1', 'bot10'] + player_ids: ['agent1', 'agent2'] races: ['zerg', 'zerg'] map_size_resolutions: [True, True] # if True, ignore minimap_resolutions minimap_resolutions: [[160, 152], [160, 152]] diff --git a/dizoo/distar/envs/test_distar_env_with_manager.py b/dizoo/distar/envs/test_distar_env_with_manager.py new file mode 100644 index 0000000000..c65f8b7a80 --- /dev/null +++ b/dizoo/distar/envs/test_distar_env_with_manager.py @@ -0,0 +1,93 @@ +import os +from re import L +import shutil +import argparse + +from distar.ctools.utils import read_config, deep_merge_dicts +from distar.actor import Actor +import torch +import random +import time +from ding.envs import BaseEnvManager +from dizoo.distar.envs import DIStarEnv +import traceback + +from easydict import EasyDict +env_cfg = EasyDict( + { + 'env': { + 'manager': { + 'episode_num': 100000, + 'max_retry': 1, + 'retry_type': 'reset', + 'auto_reset': True, + 'step_timeout': None, + 'reset_timeout': None, + 'retry_waiting_time': 0.1, + 'cfg_type': 'BaseEnvManagerDict', + 'shared_memory': False + } + } + } +) + +class TestDIstarEnv: + def __init__(self): + + cfg = read_config('C:/Users/hjs/DI-engine/dizoo/distar/envs/test_distar_config.yaml') + self._whole_cfg = cfg + self._whole_cfg.env.map_name = 'KingsCove' + self._agent_env = DIStarEnv(self._whole_cfg) + + def _inference_loop(self, job={}): + + + torch.set_num_threads(1) + + # self._env = DIStarEnv(self._whole_cfg) + self._env = BaseEnvManager( + env_fn=[lambda: DIStarEnv(self._whole_cfg) for _ in range(1)], cfg=env_cfg.env.manager + ) + self._env.seed(1) + + with torch.no_grad(): + for episode in range(2): + self._env.launch() + try: + for env_step in range(10): + obs = self._env.ready_obs + # print(obs) + obs = {env_id: obs[env_id] for env_id in range(1)} + actions = {} + for env_id in range(1): + observations = obs[env_id] + print(type(observations)) + actions[env_id] = self._agent_env.random_action(observations) + # print(actions) + timesteps = self._env.step(actions) + print(actions) + + except Exception as e: + print('[EPISODE LOOP ERROR]', e, flush=True) + print(''.join(traceback.format_tb(e.__traceback__)), flush=True) + self._env.close() + + self._env.close() + +if __name__ == '__main__': + + ## main + if os.path.exists(r'C:\Program Files (x86)\StarCraft II'): + sc2path = r'C:\Program Files (x86)\StarCraft II' + elif os.path.exists('/Applications/StarCraft II'): + sc2path = '/Applications/StarCraft II' + else: + assert 'SC2PATH' in os.environ.keys(), 'please add StarCraft2 installation path to your environment variables!' + sc2path = os.environ['SC2PATH'] + assert os.path.exists(sc2path), 'SC2PATH: {} does not exist!'.format(sc2path) + if not os.path.exists(os.path.join(sc2path, 'Maps/Ladder2019Season2')): + shutil.copytree(os.path.join(os.path.dirname(__file__), '../envs/maps/Ladder2019Season2'), os.path.join(sc2path, 'Maps/Ladder2019Season2')) + + ## actor_run + actor = TestDIstarEnv() + actor._inference_loop() \ No newline at end of file From 3dc0b1230c4232cb3a4206ebb02db456833db5b5 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Fri, 10 Jun 2022 15:50:57 +0800 Subject: [PATCH 093/229] arrage tests --- dizoo/distar/envs/test_distar_env2.py | 333 ------------------ .../envs/{ => tests}/test_distar_config.yaml | 0 .../test_distar_env_data.py} | 2 +- .../{ => tests}/test_distar_env_time_space.py | 2 +- .../test_distar_env_with_manager.py | 3 +- 5 files changed, 3 insertions(+), 337 deletions(-) delete mode 100644 dizoo/distar/envs/test_distar_env2.py rename dizoo/distar/envs/{ => tests}/test_distar_config.yaml (100%) rename dizoo/distar/envs/{test_distar_env.py => tests/test_distar_env_data.py} (93%) rename dizoo/distar/envs/{ => tests}/test_distar_env_time_space.py (95%) rename dizoo/distar/envs/{ => tests}/test_distar_env_with_manager.py (92%) diff --git a/dizoo/distar/envs/test_distar_env2.py b/dizoo/distar/envs/test_distar_env2.py deleted file mode 100644 index 5bc284ab3b..0000000000 --- a/dizoo/distar/envs/test_distar_env2.py +++ /dev/null @@ -1,333 +0,0 @@ -import os -import shutil -import argparse - -import os -import time -import traceback -import uuid -from collections import defaultdict -import torch -import torch.multiprocessing as mp -import random -import json -import platform - -from distar.agent.import_helper import import_module -from distar.ctools.utils import read_config, deep_merge_dicts -from distar.ctools.utils.log_helper import TextLogger, VariableRecord -from distar.ctools.worker.actor.actor_comm import ActorComm -from distar.actor import Actor -import torch -import random -import time - -from distar.ctools.worker.league.player import FRAC_ID -from distar_env import DIStarEnv -import traceback - -default_config = read_config('C:/Users/hjs/DI-star/distar/actor/actor_default_config.yaml') - -class TestDIstarEnv: - def __init__(self,cfg): - cfg = deep_merge_dicts(default_config, cfg) - self._whole_cfg = cfg - self._cfg = cfg.actor - self._job_type = cfg.actor.job_type - self._league_job_type = cfg.actor.get('league_job_type','test') - self._actor_uid = str(uuid.uuid1()) - self._gpu_batch_inference = self._cfg.get('gpu_batch_inference', False) - self._logger = TextLogger( - path=os.path.join(os.getcwd(), 'experiments', self._whole_cfg.common.experiment_name, 'actor_log'), - name=self._actor_uid) - if self._job_type == 'train': - self._comm = ActorComm(self._whole_cfg, self._actor_uid, self._logger) - self.max_job_duration = self._whole_cfg.communication.actor_ask_for_job_interval * random.uniform(0.7 , 1.3) - self._setup_agents() - - self._whole_cfg.env.map_name = 'KingsCove' - - def _setup_agents(self): - self.agents = [] - if self._job_type == 'train': - # comm setup agents - self._comm.ask_for_job(self) - else: - self.models = {} - map_names = [] - for idx, player_id in enumerate(self._cfg.player_ids): - if 'bot' in player_id: - continue - Agent = import_module(self._cfg.agents.get(player_id, 'default'), 'Agent') - agent = Agent(self._whole_cfg) - agent.player_id = player_id - agent.side_id = idx - self.agents.append(agent) - agent.side_id = idx - if agent.HAS_MODEL: - if player_id not in self.models.keys(): - if self._cfg.use_cuda: - assert 'test' in self._job_type, 'only test mode support gpu' - agent.model = agent.model.cuda() - else: - agent.model = agent.model.eval().share_memory() - if not self._cfg.fake_model: - state_dict = torch.load(self._cfg.model_paths[player_id], map_location='cpu') - if 'map_name' in state_dict: - map_names.append(state_dict['map_name']) - agent._fake_reward_prob = state_dict['fake_reward_prob'] - agent._z_path = state_dict['z_path'] - agent.z_idx = state_dict['z_idx'] - model_state_dict = {k: v for k, v in state_dict['model'].items() if - 'value_networks' not in k} - agent.model.load_state_dict(model_state_dict, strict=False) - self.models[player_id] = agent.model - else: - agent.model = self.models[player_id] - if len(map_names) == 1: - self._whole_cfg.env.map_name = map_names[0] - if len(map_names) == 2: - if not(map_names[0] == 'random' and map_names[1] != 'random'): - self._whole_cfg.env.map_name = 'NewRepugnancy' - if self._job_type == 'train_test': - teacher_models = {} - for idx, teacher_player_id in enumerate(self._cfg.teacher_player_ids): - if 'bot' in self._cfg.player_ids[idx]: - continue - agent = self.agents[idx] - agent.teacher_player_id = teacher_player_id - if agent.HAS_TEACHER_MODEL: - if teacher_player_id not in teacher_models.keys(): - if self._cfg.use_cuda: - agent.teacher_model = agent.teacher_model.cuda() - else: - agent.teacher_model = agent.teacher_model.eval() - if not self._cfg.fake_model: - state_dict = torch.load(self._cfg.teacher_model_paths[teacher_player_id], - map_location='cpu') - model_state_dict = {k: v for k, v in state_dict['model'].items() if - 'value_networks' not in k} - agent.teacher_model.load_state_dict(model_state_dict) - teacher_models[teacher_player_id] = agent.teacher_model - else: - agent.teacher_model = teacher_models[teacher_player_id] - - def _inference_loop(self, env_id=0, job={}, result_queue=None, pipe_c=None): - torch.set_num_threads(1) - frac_ids = job.get('frac_ids',[]) - env_info = job.get('env_info', {}) - races = [] - for frac_id in frac_ids: - races.append(random.choice(FRAC_ID[frac_id])) - if len(races) >0: - env_info['races']=races - mergerd_whole_cfg = deep_merge_dicts(self._whole_cfg, {'env': env_info}) - self._env = DIStarEnv(mergerd_whole_cfg) - - iter_count = 0 - if env_id == 0: - variable_record = VariableRecord(self._cfg.print_freq) - variable_record.register_var('agent_time') - variable_record.register_var('agent_time_per_agent') - variable_record.register_var('env_time') - if 'train' in self._job_type: - variable_record.register_var('post_process_time') - variable_record.register_var('post_process_per_agent') - variable_record.register_var('send_data_time') - variable_record.register_var('send_data_per_agent') - variable_record.register_var('send_data_per_agent') - variable_record.register_var('update_model_time') - - with torch.no_grad(): - episode_count = 0 - while episode_count < self._cfg.episode_num: - try: - game_start = time.time() - game_iters = 0 - observations, game_info, map_name = self._env.reset() - for idx in observations.keys(): - self.agents[idx].env_id = env_id - race = self._whole_cfg.env.races[idx] - self.agents[idx].reset(map_name, race, game_info[idx], observations[idx]) - - for iter in range(50): # one episode loop - # agent step - # if iter % 5 == 1: - # actions = {0: [{'func_id': 503, 'skip_steps': 0, 'queued': 0, 'unit_tags': [4350279681, 4350541825, 4350803969], - # 'target_unit_tag': 4309123073, 'location': (127, 17)}]} - # elif iter % 5 == 2: - # actions = {0: [{'func_id': 503, 'skip_steps': 9, 'queued': 0, - # 'unit_tags': [4346085377, 4346347521, 4346609665], 'target_unit_tag': 4345823233, 'location': (17, 121)}]} - # elif iter % 5 == 3: - # actions = {0: [{'func_id': 12, 'skip_steps': 8, 'queued': 0, - # 'unit_tags': [4350279681, 4350541825, 4350803969], 'target_unit_tag': 4309123073, 'location': (139, 16)}]} - # elif iter % 5 == 4: - # actions = {0: [{'func_id': 515, 'skip_steps': 3, 'queued': 0, - # 'unit_tags': [4350541825, 4350803969, 4358930433], 'target_unit_tag': 4309123073, 'location': (127, 15)}]} - # else: - # actions = {0: [{'func_id': 1, 'skip_steps': 10, 'queued': 0, - # 'unit_tags': [4354211841], 'target_unit_tag': 4350017537, 'location': (126, 27)}]} - - # agent step - agent_start_time = time.time() - agent_count = 0 - actions = {} - - players_obs = observations - for player_index, obs in players_obs.items(): - player_id = self.agents[player_index].player_id - if self._job_type == 'train': - self.agents[player_index]._model_last_iter = self._comm.model_last_iter_dict[player_id].item() - actions[player_index] = self.agents[player_index].step(obs) - agent_count += 1 - agent_time = time.time() - agent_start_time - - - # env step - env_start_time = time.time() - next_observations, reward, done = self._env.step(actions) - # print('reward: ', reward) - # print('next_observations', next_observations) - # print('done: ', done) - env_time = time.time() - env_start_time - next_players_obs = next_observations - time.sleep(1) - - # collect data - if 'train' in self._job_type: - post_process_time = 0 - post_process_count = 0 - send_data_time = 0 - send_data_count = 0 - for player_index, obs in next_players_obs.items(): - if self._job_type == 'train_test' or self.agents[player_index].player_id in self._comm.job[ - 'send_data_players']: - post_process_start_time = time.time() - traj_data = self.agents[player_index].collect_data(next_players_obs[player_index], - reward[player_index], done, player_index) - post_process_time += time.time() - post_process_start_time - post_process_count += 1 - if traj_data is not None and self._job_type == 'train': - send_data_start_time = time.time() - self._comm.send_data(traj_data, self.agents[player_index].player_id) - send_data_time += time.time() - send_data_start_time - send_data_count += 1 - else: - self.agents[player_index].update_fake_reward(next_players_obs[player_index]) - - # update log - iter_count += 1 - game_iters += 1 - if env_id == 0: - if 'train' in self._job_type: - variable_record.update_var( - {'agent_time': agent_time, - 'agent_time_per_agent': agent_time / (agent_count + 1e-6), - 'env_time': env_time, - }) - if post_process_count > 0: - variable_record.update_var( - {'post_process_time': post_process_time, - 'post_process_per_agent': post_process_time / post_process_count, - }) - if send_data_count > 0: - variable_record.update_var({ - 'send_data_time': send_data_time, - 'send_data_per_agent': send_data_time / send_data_count, - }) - - else: - variable_record.update_var({'agent_time': agent_time, - 'agent_time_per_agent': agent_time / (agent_count + 1e-6), - 'env_time': env_time, }) - self.iter_after_hook(iter_count, variable_record) - - if not done: - observations = next_observations - else: - players_obs = observations - if 'test' in self._whole_cfg and self._whole_cfg.test.get('tb_stat', False): - if not os.path.exists(self._env._result_dir): - os.makedirs(self._env._result_dir) - data = self.agents[0].get_stat_data() - path = os.path.join(self._env._result_dir, '{}_{}_{}_.json'.format(env_id, episode_count, player_index)) - with open(path, 'w') as f: - json.dump(data, f) - - if self._job_type == 'train': - player_idx = random.sample(players_obs.keys(), 1)[0] - game_steps = players_obs[player_idx]['raw_obs'].observation.game_loop - result_info = defaultdict(dict) - - for player_index in range(len(self.agents)): - player_id = self.agents[player_index].player_id - side_id = self.agents[player_index].side_id - race = self.agents[player_index].race - agent_iters = self.agents[player_index].iter_count - result_info[side_id]['race'] = race - result_info[side_id]['player_id'] = player_id - result_info[side_id]['opponent_id'] = self.agents[player_index].opponent_id - result_info[side_id]['winloss'] = reward[player_index] - result_info[side_id]['agent_iters'] = agent_iters - result_info[side_id].update(self.agents[player_index].get_unit_num_info()) - result_info[side_id].update(self.agents[player_index].get_stat_data()) - game_duration = time.time() - game_start - result_info['game_steps'] = game_steps - result_info['game_iters'] = game_iters - result_info['game_duration'] = game_duration - self._comm.send_result(result_info) - break - - except Exception as e: - print('[EPISODE LOOP ERROR]', e, flush=True) - print(''.join(traceback.format_tb(e.__traceback__)), flush=True) - self._env.close() - self._env.close() - if result_queue is not None: - print(os.getpid(), 'done') - result_queue.put('done') - time.sleep(1000000) - else: - return - def iter_after_hook(self, iter_count, variable_record): - if iter_count % self._cfg.print_freq == 0: - if hasattr(self,'_comm'): - variable_record.update_var({'update_model_time':self._comm._avg_update_model_time.item() }) - self._logger.info( - 'ACTOR({}):\n{}TimeStep{}{} {}'.format( - self._actor_uid, '=' * 35, iter_count, '=' * 35, - variable_record.get_vars_text() - ) - ) - -if __name__ == '__main__': - - ## main - if os.path.exists(r'C:\Program Files (x86)\StarCraft II'): - sc2path = r'C:\Program Files (x86)\StarCraft II' - elif os.path.exists('/Applications/StarCraft II'): - sc2path = '/Applications/StarCraft II' - else: - assert 'SC2PATH' in os.environ.keys(), 'please add StarCraft2 installation path to your environment variables!' - sc2path = os.environ['SC2PATH'] - assert os.path.exists(sc2path), 'SC2PATH: {} does not exist!'.format(sc2path) - if not os.path.exists(os.path.join(sc2path, 'Maps/Ladder2019Season2')): - shutil.copytree(os.path.join(os.path.dirname(__file__), '../envs/maps/Ladder2019Season2'), os.path.join(sc2path, 'Maps/Ladder2019Season2')) - - parser = argparse.ArgumentParser(description="rl_train") - parser.add_argument("--config", default='C:/Users/hjs/DI-star/distar/bin/user_config.yaml') - parser.add_argument("--type", default=None) - parser.add_argument("--task", default='bot') - parser.add_argument("--player_id", default='MP0') - parser.add_argument("--gpu_batch_inference", default='false') - parser.add_argument("--init_method", type=str, default=None) - parser.add_argument("--rank", type=int, default=0) - parser.add_argument("--world_size", type=int, default=1) - args = parser.parse_args() - config = read_config(args.config) - config.common.type = 'rl' - config.actor.traj_len = config.learner.data.trajectory_length - - ## actor_run - actor = TestDIstarEnv(config) - actor._inference_loop() \ No newline at end of file diff --git a/dizoo/distar/envs/test_distar_config.yaml b/dizoo/distar/envs/tests/test_distar_config.yaml similarity index 100% rename from dizoo/distar/envs/test_distar_config.yaml rename to dizoo/distar/envs/tests/test_distar_config.yaml diff --git a/dizoo/distar/envs/test_distar_env.py b/dizoo/distar/envs/tests/test_distar_env_data.py similarity index 93% rename from dizoo/distar/envs/test_distar_env.py rename to dizoo/distar/envs/tests/test_distar_env_data.py index 6e25788431..38f1dc83a6 100644 --- a/dizoo/distar/envs/test_distar_env.py +++ b/dizoo/distar/envs/tests/test_distar_env_data.py @@ -11,7 +11,7 @@ class TestDIstarEnv: def __init__(self): - cfg = read_config('C:/Users/hjs/DI-engine/dizoo/distar/envs/test_distar_config.yaml') + cfg = read_config('./test_distar_config.yaml') self._whole_cfg = cfg self._whole_cfg.env.map_name = 'KingsCove' diff --git a/dizoo/distar/envs/test_distar_env_time_space.py b/dizoo/distar/envs/tests/test_distar_env_time_space.py similarity index 95% rename from dizoo/distar/envs/test_distar_env_time_space.py rename to dizoo/distar/envs/tests/test_distar_env_time_space.py index d2f784a119..3cc3612e45 100644 --- a/dizoo/distar/envs/test_distar_env_time_space.py +++ b/dizoo/distar/envs/tests/test_distar_env_time_space.py @@ -12,7 +12,7 @@ class TestDIstarEnv: def __init__(self): - cfg = read_config('C:/Users/hjs/DI-star/ding-test/envs/test_distar_config.yaml') + cfg = read_config('./test_distar_config.yaml') self._whole_cfg = cfg self._whole_cfg.env.map_name = 'KingsCove' self._total_iters = 0 diff --git a/dizoo/distar/envs/test_distar_env_with_manager.py b/dizoo/distar/envs/tests/test_distar_env_with_manager.py similarity index 92% rename from dizoo/distar/envs/test_distar_env_with_manager.py rename to dizoo/distar/envs/tests/test_distar_env_with_manager.py index c65f8b7a80..78f8154ba6 100644 --- a/dizoo/distar/envs/test_distar_env_with_manager.py +++ b/dizoo/distar/envs/tests/test_distar_env_with_manager.py @@ -34,7 +34,7 @@ class TestDIstarEnv: def __init__(self): - cfg = read_config('C:/Users/hjs/DI-engine/dizoo/distar/envs/test_distar_config.yaml') + cfg = read_config('./test_distar_config.yaml') self._whole_cfg = cfg self._whole_cfg.env.map_name = 'KingsCove' self._agent_env = DIStarEnv(self._whole_cfg) @@ -61,7 +61,6 @@ def _inference_loop(self, job={}): actions = {} for env_id in range(1): observations = obs[env_id] - print(type(observations)) actions[env_id] = self._agent_env.random_action(observations) # print(actions) timesteps = self._env.step(actions) From 9b4deaace760ad2117e1b3ff61337c6e7055fda2 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Fri, 10 Jun 2022 15:52:31 +0800 Subject: [PATCH 094/229] format context and league_actor --- ding/framework/context.py | 30 ++++++++++++++--------- ding/framework/middleware/league_actor.py | 2 +- 2 files changed, 19 insertions(+), 13 deletions(-) diff --git a/ding/framework/context.py b/ding/framework/context.py index 4113ea5c7b..47582b9c64 100644 --- a/ding/framework/context.py +++ b/ding/framework/context.py @@ -80,26 +80,32 @@ class BattleContext(Context): def __init__(self, *args, **kwargs) -> None: super().__init__(*args, **kwargs) self.__dict__ = self + # collect target paras self.n_episode = None + self.n_sample = 1 + self.unroll_len = 1 + + #collect process paras + self.env_episode = 0 + self.env_step = 0 + self.total_envstep_count = 0 self.train_iter = 0 - self.job = None self.collect_kwargs = {} - self.env_episode = 0 - self.episodes = [] - self.episode_info = [] - self.ready_env_id = set() self.agent_num = 2 - self.job_finish = False self.traj_len = float("inf") self.current_policies = [] - self.env_step = 0 - self.total_envstep_count = 0 + self.ready_env_id = set() + self.remain_episode = 0 + + #job paras + self.job = None + self.job_finish = False + + #Return data paras + self.episodes = [] + self.episode_info = [] self.trajectories_list = [] self.trajectory_end_idx_list = [] self.trajectories = [] self.trajectory_end_idx = None - - self.remain_episode = 0 - self.n_sample = 1 - self.unroll_len = 1 self.train_data = None diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index d47c3d5484..b9760873fc 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -104,7 +104,6 @@ def __call__(self, ctx: "BattleContext"): collector = self._get_collector(ctx.job.launch_player, len(ctx.job.players)) main_player, ctx.current_policies = self._get_current_policies(ctx.job) - ctx.agent_num = len(ctx.current_policies) _default_n_episode = ctx.current_policies[0].get_attribute('cfg').collect.get('n_episode', None) if ctx.n_episode is None: @@ -114,6 +113,7 @@ def __call__(self, ctx: "BattleContext"): ctx.n_episode = _default_n_episode assert ctx.n_episode >= self.env_num, "Please make sure n_episode >= env_num" + ctx.agent_num = len(ctx.current_policies) ctx.train_iter = main_player.total_agent_step ctx.episode_info = [[] for _ in range(ctx.agent_num)] ctx.remain_episode = ctx.n_episode From c65fecfc731c44384b7ca1d70b7cf34978a8f0ab Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Fri, 10 Jun 2022 16:16:18 +0800 Subject: [PATCH 095/229] make old test runnable --- .../distar/envs/tests/test_distar_env_data.py | 13 +++++----- .../envs/tests/test_distar_env_time_space.py | 25 ++++++++++--------- 2 files changed, 20 insertions(+), 18 deletions(-) diff --git a/dizoo/distar/envs/tests/test_distar_env_data.py b/dizoo/distar/envs/tests/test_distar_env_data.py index 38f1dc83a6..85caa88973 100644 --- a/dizoo/distar/envs/tests/test_distar_env_data.py +++ b/dizoo/distar/envs/tests/test_distar_env_data.py @@ -8,6 +8,9 @@ import random import time +from dizoo.distar.envs import DIStarEnv +import traceback + class TestDIstarEnv: def __init__(self): @@ -16,8 +19,6 @@ def __init__(self): self._whole_cfg.env.map_name = 'KingsCove' def _inference_loop(self, job={}): - from dizoo.distar.envs import DIStarEnv - import traceback torch.set_num_threads(1) @@ -26,15 +27,15 @@ def _inference_loop(self, job={}): with torch.no_grad(): for _ in range(5): try: - observations, game_info, map_name = self._env.reset() + observations = self._env.reset() for iter in range(1000): # one episode loop # agent step actions = self._env.random_action(observations) # env step - next_observations, reward, done = self._env.step(actions) - if not done: - observations = next_observations + timestep = self._env.step(actions) + if not timestep.done: + observations = timestep.obs else: break diff --git a/dizoo/distar/envs/tests/test_distar_env_time_space.py b/dizoo/distar/envs/tests/test_distar_env_time_space.py index 3cc3612e45..6d99173aa5 100644 --- a/dizoo/distar/envs/tests/test_distar_env_time_space.py +++ b/dizoo/distar/envs/tests/test_distar_env_time_space.py @@ -9,6 +9,9 @@ import time import sys +from dizoo.distar.envs import DIStarEnv +import traceback + class TestDIstarEnv: def __init__(self): @@ -20,8 +23,6 @@ def __init__(self): self._total_space = 0 def _inference_loop(self, job={}): - from distar_env import DIStarEnv - import traceback torch.set_num_threads(1) @@ -30,32 +31,32 @@ def _inference_loop(self, job={}): with torch.no_grad(): for _ in range(5): try: - observations, game_info, map_name = self._env.reset() + observations = self._env.reset() for iter in range(1000): # one episode loop # agent step actions = self._env.random_action(observations) # env step before_step_time = time.time() - next_observations, reward, done = self._env.step(actions) + timestep = self._env.step(actions) after_step_time = time.time() self._total_time += after_step_time - before_step_time self._total_iters += 1 - self._total_space += sys.getsizeof((actions,observations,next_observations,reward,done)) + self._total_space += sys.getsizeof((actions,observations,timestep.obs,timestep.reward,timestep.done)) print('observations: ', sys.getsizeof(observations), ' Byte') print('actions: ', sys.getsizeof(actions), ' Byte') - print('reward: ', sys.getsizeof(reward), ' Byte') - print('done: ', sys.getsizeof(done), ' Byte') - print('total: ', sys.getsizeof((actions,observations,next_observations,reward,done)),' Byte') + print('reward: ', sys.getsizeof(timestep.reward), ' Byte') + print('done: ', sys.getsizeof(timestep.done), ' Byte') + print('total: ', sys.getsizeof((actions,observations,timestep.obs,timestep.reward,timestep.done)),' Byte') print(type(observations)) # dict - print(type(reward)) # list - print(type(done)) # bool + print(type(timestep.reward)) # list + print(type(timestep.done)) # bool print(type(actions)) # dict - if not done: - observations = next_observations + if not timestep.done: + observations = timestep.obs else: break From cd189550d87b0d7a4f5266be80a343daa1cd9c81 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Thu, 9 Jun 2022 17:26:35 +0800 Subject: [PATCH 096/229] change the distar_env to fit BaseEnvManager, write test_distar_env_with_manager.py to test. change config to get self-play --- dizoo/distar/envs/distar_env.py | 131 ++++++++++-------- dizoo/distar/envs/test_distar_config.yaml | 2 +- .../envs/test_distar_env_with_manager.py | 93 +++++++++++++ 3 files changed, 165 insertions(+), 61 deletions(-) create mode 100644 dizoo/distar/envs/test_distar_env_with_manager.py diff --git a/dizoo/distar/envs/distar_env.py b/dizoo/distar/envs/distar_env.py index 4b5c2fa394..45530766b6 100644 --- a/dizoo/distar/envs/distar_env.py +++ b/dizoo/distar/envs/distar_env.py @@ -1,6 +1,6 @@ from distar.envs.env import SC2Env -from ding.envs import BaseEnv +from ding.envs import BaseEnv, BaseEnvTimestep from distar.agent.default.lib.actions import ACTIONS, NUM_ACTIONS from distar.agent.default.lib.features import MAX_DELAY, SPATIAL_SIZE, MAX_SELECTED_UNITS_NUM from distar.pysc2.lib.action_dict import ACTIONS_STAT @@ -13,15 +13,23 @@ def __init__(self,cfg): super(DIStarEnv, self).__init__(cfg) def reset(self): - return super(DIStarEnv,self).reset() + observations, game_info, map_name = super(DIStarEnv,self).reset() + return observations def close(self): super(DIStarEnv,self).close() - def step(self,actions): + def step(self, actions): # In DI-engine, the return of BaseEnv.step is ('obs', 'reward', 'done', 'info') # Here in DI-star, the return is ({'raw_obs': self._obs[agent_idx], 'opponent_obs': opponent_obs, 'action_result': self._action_result[agent_idx]}, reward, episode_complete) - return super(DIStarEnv,self).step(actions) + next_observations, reward, done = super(DIStarEnv,self).step(actions) + timestep = BaseEnvTimestep( + obs = next_observations, + reward = reward, + done = done, + info = None + ) + return timestep def seed(self, seed, dynamic_seed=False): self._random_seed = seed @@ -37,63 +45,66 @@ def action_space(self): pass def random_action(self, obs): - raw = obs[0]['raw_obs'].observation.raw_data - - all_unit_types = set() - self_unit_types = set() - - for u in raw.units: - # Here we select the units except “buildings that are in building progress” for simplification - if u.build_progress == 1: - all_unit_types.add(u.unit_type) - if u.alliance == 1: - self_unit_types.add(u.unit_type) - - avail_actions = [ - {0: {'exist_selected_types':[], 'exist_target_types':[]}}, - {168:{'exist_selected_types':[], 'exist_target_types':[]}} - ] # no_op and raw_move_camera don't have seleted_units - - for action_id, action in ACTIONS_STAT.items(): - exist_selected_types = list(self_unit_types.intersection(set(action['selected_type']))) - exist_target_types = list(all_unit_types.intersection(set(action['target_type']))) - - # if an action should have target, but we don't have valid target in this observation, then discard this action - if len(action['target_type']) != 0 and len(exist_target_types) == 0: - continue - - if len(exist_selected_types) > 0: - avail_actions.append({action_id: {'exist_selected_types':exist_selected_types, 'exist_target_types':exist_target_types}}) - - current_action = random.choice(avail_actions) - func_id, exist_types = current_action.popitem() - - if func_id not in [0, 168]: - correspond_selected_units = [u.tag for u in raw.units if u.unit_type in exist_types['exist_selected_types'] and u.build_progress == 1] - correspond_targets = [u.tag for u in raw.units if u.unit_type in exist_types['exist_target_types'] and u.build_progress == 1] - - num_selected_unit = random.randint(0, min(MAX_SELECTED_UNITS_NUM, len(correspond_selected_units))) - - unit_tags = random.sample(correspond_selected_units, num_selected_unit) - target_unit_tag = random.choice(correspond_targets) if len(correspond_targets) > 0 else None - - else: - unit_tags = [] - target_unit_tag = None + return_action = {} + for policy_id in obs.keys(): + raw = obs[policy_id]['raw_obs'].observation.raw_data + + all_unit_types = set() + self_unit_types = set() + + for u in raw.units: + # Here we select the units except “buildings that are in building progress” for simplification + if u.build_progress == 1: + all_unit_types.add(u.unit_type) + if u.alliance == 1: + self_unit_types.add(u.unit_type) + + avail_actions = [ + {0: {'exist_selected_types':[], 'exist_target_types':[]}}, + {168:{'exist_selected_types':[], 'exist_target_types':[]}} + ] # no_op and raw_move_camera don't have seleted_units + + for action_id, action in ACTIONS_STAT.items(): + exist_selected_types = list(self_unit_types.intersection(set(action['selected_type']))) + exist_target_types = list(all_unit_types.intersection(set(action['target_type']))) + + # if an action should have target, but we don't have valid target in this observation, then discard this action + if len(action['target_type']) != 0 and len(exist_target_types) == 0: + continue + + if len(exist_selected_types) > 0: + avail_actions.append({action_id: {'exist_selected_types':exist_selected_types, 'exist_target_types':exist_target_types}}) - data = { - 'func_id': func_id, - 'skip_steps': random.randint(0, MAX_DELAY - 1), - # 'skip_steps': 8, - 'queued': random.randint(0, 1), - 'unit_tags': unit_tags, - 'target_unit_tag': target_unit_tag, - 'location': ( - random.randint(0, SPATIAL_SIZE[0] - 1), - random.randint(0, SPATIAL_SIZE[1] - 1) - ) - } - return {0:[data]} + current_action = random.choice(avail_actions) + func_id, exist_types = current_action.popitem() + + if func_id not in [0, 168]: + correspond_selected_units = [u.tag for u in raw.units if u.unit_type in exist_types['exist_selected_types'] and u.build_progress == 1] + correspond_targets = [u.tag for u in raw.units if u.unit_type in exist_types['exist_target_types'] and u.build_progress == 1] + + num_selected_unit = random.randint(0, min(MAX_SELECTED_UNITS_NUM, len(correspond_selected_units))) + + unit_tags = random.sample(correspond_selected_units, num_selected_unit) + target_unit_tag = random.choice(correspond_targets) if len(correspond_targets) > 0 else None + + else: + unit_tags = [] + target_unit_tag = None + + data = { + 'func_id': func_id, + 'skip_steps': random.randint(0, MAX_DELAY - 1), + # 'skip_steps': 8, + 'queued': random.randint(0, 1), + 'unit_tags': unit_tags, + 'target_unit_tag': target_unit_tag, + 'location': ( + random.randint(0, SPATIAL_SIZE[0] - 1), + random.randint(0, SPATIAL_SIZE[1] - 1) + ) + } + return_action[policy_id] = [data] + return return_action @property diff --git a/dizoo/distar/envs/test_distar_config.yaml b/dizoo/distar/envs/test_distar_config.yaml index a3322baa54..18247e5a54 100644 --- a/dizoo/distar/envs/test_distar_config.yaml +++ b/dizoo/distar/envs/test_distar_config.yaml @@ -2,7 +2,7 @@ actor: job_type: 'train' # ['train', 'eval', 'train_test', 'eval_test'] env: map_name: 'KingsCove' - player_ids: ['agent1', 'bot10'] + player_ids: ['agent1', 'agent2'] races: ['zerg', 'zerg'] map_size_resolutions: [True, True] # if True, ignore minimap_resolutions minimap_resolutions: [[160, 152], [160, 152]] diff --git a/dizoo/distar/envs/test_distar_env_with_manager.py b/dizoo/distar/envs/test_distar_env_with_manager.py new file mode 100644 index 0000000000..c65f8b7a80 --- /dev/null +++ b/dizoo/distar/envs/test_distar_env_with_manager.py @@ -0,0 +1,93 @@ +import os +from re import L +import shutil +import argparse + +from distar.ctools.utils import read_config, deep_merge_dicts +from distar.actor import Actor +import torch +import random +import time +from ding.envs import BaseEnvManager +from dizoo.distar.envs import DIStarEnv +import traceback + +from easydict import EasyDict +env_cfg = EasyDict( + { + 'env': { + 'manager': { + 'episode_num': 100000, + 'max_retry': 1, + 'retry_type': 'reset', + 'auto_reset': True, + 'step_timeout': None, + 'reset_timeout': None, + 'retry_waiting_time': 0.1, + 'cfg_type': 'BaseEnvManagerDict', + 'shared_memory': False + } + } + } +) + +class TestDIstarEnv: + def __init__(self): + + cfg = read_config('C:/Users/hjs/DI-engine/dizoo/distar/envs/test_distar_config.yaml') + self._whole_cfg = cfg + self._whole_cfg.env.map_name = 'KingsCove' + self._agent_env = DIStarEnv(self._whole_cfg) + + def _inference_loop(self, job={}): + + + torch.set_num_threads(1) + + # self._env = DIStarEnv(self._whole_cfg) + self._env = BaseEnvManager( + env_fn=[lambda: DIStarEnv(self._whole_cfg) for _ in range(1)], cfg=env_cfg.env.manager + ) + self._env.seed(1) + + with torch.no_grad(): + for episode in range(2): + self._env.launch() + try: + for env_step in range(10): + obs = self._env.ready_obs + # print(obs) + obs = {env_id: obs[env_id] for env_id in range(1)} + actions = {} + for env_id in range(1): + observations = obs[env_id] + print(type(observations)) + actions[env_id] = self._agent_env.random_action(observations) + # print(actions) + timesteps = self._env.step(actions) + print(actions) + + except Exception as e: + print('[EPISODE LOOP ERROR]', e, flush=True) + print(''.join(traceback.format_tb(e.__traceback__)), flush=True) + self._env.close() + + self._env.close() + +if __name__ == '__main__': + + ## main + if os.path.exists(r'C:\Program Files (x86)\StarCraft II'): + sc2path = r'C:\Program Files (x86)\StarCraft II' + elif os.path.exists('/Applications/StarCraft II'): + sc2path = '/Applications/StarCraft II' + else: + assert 'SC2PATH' in os.environ.keys(), 'please add StarCraft2 installation path to your environment variables!' + sc2path = os.environ['SC2PATH'] + assert os.path.exists(sc2path), 'SC2PATH: {} does not exist!'.format(sc2path) + if not os.path.exists(os.path.join(sc2path, 'Maps/Ladder2019Season2')): + shutil.copytree(os.path.join(os.path.dirname(__file__), '../envs/maps/Ladder2019Season2'), os.path.join(sc2path, 'Maps/Ladder2019Season2')) + + ## actor_run + actor = TestDIstarEnv() + actor._inference_loop() \ No newline at end of file From 6a3d4334d1b537ffea8800c0675b3634d3ef38eb Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Fri, 10 Jun 2022 15:50:57 +0800 Subject: [PATCH 097/229] arrage tests --- dizoo/distar/envs/test_distar_env2.py | 333 ------------------ .../envs/{ => tests}/test_distar_config.yaml | 0 .../test_distar_env_data.py} | 2 +- .../{ => tests}/test_distar_env_time_space.py | 2 +- .../test_distar_env_with_manager.py | 3 +- 5 files changed, 3 insertions(+), 337 deletions(-) delete mode 100644 dizoo/distar/envs/test_distar_env2.py rename dizoo/distar/envs/{ => tests}/test_distar_config.yaml (100%) rename dizoo/distar/envs/{test_distar_env.py => tests/test_distar_env_data.py} (93%) rename dizoo/distar/envs/{ => tests}/test_distar_env_time_space.py (95%) rename dizoo/distar/envs/{ => tests}/test_distar_env_with_manager.py (92%) diff --git a/dizoo/distar/envs/test_distar_env2.py b/dizoo/distar/envs/test_distar_env2.py deleted file mode 100644 index 5bc284ab3b..0000000000 --- a/dizoo/distar/envs/test_distar_env2.py +++ /dev/null @@ -1,333 +0,0 @@ -import os -import shutil -import argparse - -import os -import time -import traceback -import uuid -from collections import defaultdict -import torch -import torch.multiprocessing as mp -import random -import json -import platform - -from distar.agent.import_helper import import_module -from distar.ctools.utils import read_config, deep_merge_dicts -from distar.ctools.utils.log_helper import TextLogger, VariableRecord -from distar.ctools.worker.actor.actor_comm import ActorComm -from distar.actor import Actor -import torch -import random -import time - -from distar.ctools.worker.league.player import FRAC_ID -from distar_env import DIStarEnv -import traceback - -default_config = read_config('C:/Users/hjs/DI-star/distar/actor/actor_default_config.yaml') - -class TestDIstarEnv: - def __init__(self,cfg): - cfg = deep_merge_dicts(default_config, cfg) - self._whole_cfg = cfg - self._cfg = cfg.actor - self._job_type = cfg.actor.job_type - self._league_job_type = cfg.actor.get('league_job_type','test') - self._actor_uid = str(uuid.uuid1()) - self._gpu_batch_inference = self._cfg.get('gpu_batch_inference', False) - self._logger = TextLogger( - path=os.path.join(os.getcwd(), 'experiments', self._whole_cfg.common.experiment_name, 'actor_log'), - name=self._actor_uid) - if self._job_type == 'train': - self._comm = ActorComm(self._whole_cfg, self._actor_uid, self._logger) - self.max_job_duration = self._whole_cfg.communication.actor_ask_for_job_interval * random.uniform(0.7 , 1.3) - self._setup_agents() - - self._whole_cfg.env.map_name = 'KingsCove' - - def _setup_agents(self): - self.agents = [] - if self._job_type == 'train': - # comm setup agents - self._comm.ask_for_job(self) - else: - self.models = {} - map_names = [] - for idx, player_id in enumerate(self._cfg.player_ids): - if 'bot' in player_id: - continue - Agent = import_module(self._cfg.agents.get(player_id, 'default'), 'Agent') - agent = Agent(self._whole_cfg) - agent.player_id = player_id - agent.side_id = idx - self.agents.append(agent) - agent.side_id = idx - if agent.HAS_MODEL: - if player_id not in self.models.keys(): - if self._cfg.use_cuda: - assert 'test' in self._job_type, 'only test mode support gpu' - agent.model = agent.model.cuda() - else: - agent.model = agent.model.eval().share_memory() - if not self._cfg.fake_model: - state_dict = torch.load(self._cfg.model_paths[player_id], map_location='cpu') - if 'map_name' in state_dict: - map_names.append(state_dict['map_name']) - agent._fake_reward_prob = state_dict['fake_reward_prob'] - agent._z_path = state_dict['z_path'] - agent.z_idx = state_dict['z_idx'] - model_state_dict = {k: v for k, v in state_dict['model'].items() if - 'value_networks' not in k} - agent.model.load_state_dict(model_state_dict, strict=False) - self.models[player_id] = agent.model - else: - agent.model = self.models[player_id] - if len(map_names) == 1: - self._whole_cfg.env.map_name = map_names[0] - if len(map_names) == 2: - if not(map_names[0] == 'random' and map_names[1] != 'random'): - self._whole_cfg.env.map_name = 'NewRepugnancy' - if self._job_type == 'train_test': - teacher_models = {} - for idx, teacher_player_id in enumerate(self._cfg.teacher_player_ids): - if 'bot' in self._cfg.player_ids[idx]: - continue - agent = self.agents[idx] - agent.teacher_player_id = teacher_player_id - if agent.HAS_TEACHER_MODEL: - if teacher_player_id not in teacher_models.keys(): - if self._cfg.use_cuda: - agent.teacher_model = agent.teacher_model.cuda() - else: - agent.teacher_model = agent.teacher_model.eval() - if not self._cfg.fake_model: - state_dict = torch.load(self._cfg.teacher_model_paths[teacher_player_id], - map_location='cpu') - model_state_dict = {k: v for k, v in state_dict['model'].items() if - 'value_networks' not in k} - agent.teacher_model.load_state_dict(model_state_dict) - teacher_models[teacher_player_id] = agent.teacher_model - else: - agent.teacher_model = teacher_models[teacher_player_id] - - def _inference_loop(self, env_id=0, job={}, result_queue=None, pipe_c=None): - torch.set_num_threads(1) - frac_ids = job.get('frac_ids',[]) - env_info = job.get('env_info', {}) - races = [] - for frac_id in frac_ids: - races.append(random.choice(FRAC_ID[frac_id])) - if len(races) >0: - env_info['races']=races - mergerd_whole_cfg = deep_merge_dicts(self._whole_cfg, {'env': env_info}) - self._env = DIStarEnv(mergerd_whole_cfg) - - iter_count = 0 - if env_id == 0: - variable_record = VariableRecord(self._cfg.print_freq) - variable_record.register_var('agent_time') - variable_record.register_var('agent_time_per_agent') - variable_record.register_var('env_time') - if 'train' in self._job_type: - variable_record.register_var('post_process_time') - variable_record.register_var('post_process_per_agent') - variable_record.register_var('send_data_time') - variable_record.register_var('send_data_per_agent') - variable_record.register_var('send_data_per_agent') - variable_record.register_var('update_model_time') - - with torch.no_grad(): - episode_count = 0 - while episode_count < self._cfg.episode_num: - try: - game_start = time.time() - game_iters = 0 - observations, game_info, map_name = self._env.reset() - for idx in observations.keys(): - self.agents[idx].env_id = env_id - race = self._whole_cfg.env.races[idx] - self.agents[idx].reset(map_name, race, game_info[idx], observations[idx]) - - for iter in range(50): # one episode loop - # agent step - # if iter % 5 == 1: - # actions = {0: [{'func_id': 503, 'skip_steps': 0, 'queued': 0, 'unit_tags': [4350279681, 4350541825, 4350803969], - # 'target_unit_tag': 4309123073, 'location': (127, 17)}]} - # elif iter % 5 == 2: - # actions = {0: [{'func_id': 503, 'skip_steps': 9, 'queued': 0, - # 'unit_tags': [4346085377, 4346347521, 4346609665], 'target_unit_tag': 4345823233, 'location': (17, 121)}]} - # elif iter % 5 == 3: - # actions = {0: [{'func_id': 12, 'skip_steps': 8, 'queued': 0, - # 'unit_tags': [4350279681, 4350541825, 4350803969], 'target_unit_tag': 4309123073, 'location': (139, 16)}]} - # elif iter % 5 == 4: - # actions = {0: [{'func_id': 515, 'skip_steps': 3, 'queued': 0, - # 'unit_tags': [4350541825, 4350803969, 4358930433], 'target_unit_tag': 4309123073, 'location': (127, 15)}]} - # else: - # actions = {0: [{'func_id': 1, 'skip_steps': 10, 'queued': 0, - # 'unit_tags': [4354211841], 'target_unit_tag': 4350017537, 'location': (126, 27)}]} - - # agent step - agent_start_time = time.time() - agent_count = 0 - actions = {} - - players_obs = observations - for player_index, obs in players_obs.items(): - player_id = self.agents[player_index].player_id - if self._job_type == 'train': - self.agents[player_index]._model_last_iter = self._comm.model_last_iter_dict[player_id].item() - actions[player_index] = self.agents[player_index].step(obs) - agent_count += 1 - agent_time = time.time() - agent_start_time - - - # env step - env_start_time = time.time() - next_observations, reward, done = self._env.step(actions) - # print('reward: ', reward) - # print('next_observations', next_observations) - # print('done: ', done) - env_time = time.time() - env_start_time - next_players_obs = next_observations - time.sleep(1) - - # collect data - if 'train' in self._job_type: - post_process_time = 0 - post_process_count = 0 - send_data_time = 0 - send_data_count = 0 - for player_index, obs in next_players_obs.items(): - if self._job_type == 'train_test' or self.agents[player_index].player_id in self._comm.job[ - 'send_data_players']: - post_process_start_time = time.time() - traj_data = self.agents[player_index].collect_data(next_players_obs[player_index], - reward[player_index], done, player_index) - post_process_time += time.time() - post_process_start_time - post_process_count += 1 - if traj_data is not None and self._job_type == 'train': - send_data_start_time = time.time() - self._comm.send_data(traj_data, self.agents[player_index].player_id) - send_data_time += time.time() - send_data_start_time - send_data_count += 1 - else: - self.agents[player_index].update_fake_reward(next_players_obs[player_index]) - - # update log - iter_count += 1 - game_iters += 1 - if env_id == 0: - if 'train' in self._job_type: - variable_record.update_var( - {'agent_time': agent_time, - 'agent_time_per_agent': agent_time / (agent_count + 1e-6), - 'env_time': env_time, - }) - if post_process_count > 0: - variable_record.update_var( - {'post_process_time': post_process_time, - 'post_process_per_agent': post_process_time / post_process_count, - }) - if send_data_count > 0: - variable_record.update_var({ - 'send_data_time': send_data_time, - 'send_data_per_agent': send_data_time / send_data_count, - }) - - else: - variable_record.update_var({'agent_time': agent_time, - 'agent_time_per_agent': agent_time / (agent_count + 1e-6), - 'env_time': env_time, }) - self.iter_after_hook(iter_count, variable_record) - - if not done: - observations = next_observations - else: - players_obs = observations - if 'test' in self._whole_cfg and self._whole_cfg.test.get('tb_stat', False): - if not os.path.exists(self._env._result_dir): - os.makedirs(self._env._result_dir) - data = self.agents[0].get_stat_data() - path = os.path.join(self._env._result_dir, '{}_{}_{}_.json'.format(env_id, episode_count, player_index)) - with open(path, 'w') as f: - json.dump(data, f) - - if self._job_type == 'train': - player_idx = random.sample(players_obs.keys(), 1)[0] - game_steps = players_obs[player_idx]['raw_obs'].observation.game_loop - result_info = defaultdict(dict) - - for player_index in range(len(self.agents)): - player_id = self.agents[player_index].player_id - side_id = self.agents[player_index].side_id - race = self.agents[player_index].race - agent_iters = self.agents[player_index].iter_count - result_info[side_id]['race'] = race - result_info[side_id]['player_id'] = player_id - result_info[side_id]['opponent_id'] = self.agents[player_index].opponent_id - result_info[side_id]['winloss'] = reward[player_index] - result_info[side_id]['agent_iters'] = agent_iters - result_info[side_id].update(self.agents[player_index].get_unit_num_info()) - result_info[side_id].update(self.agents[player_index].get_stat_data()) - game_duration = time.time() - game_start - result_info['game_steps'] = game_steps - result_info['game_iters'] = game_iters - result_info['game_duration'] = game_duration - self._comm.send_result(result_info) - break - - except Exception as e: - print('[EPISODE LOOP ERROR]', e, flush=True) - print(''.join(traceback.format_tb(e.__traceback__)), flush=True) - self._env.close() - self._env.close() - if result_queue is not None: - print(os.getpid(), 'done') - result_queue.put('done') - time.sleep(1000000) - else: - return - def iter_after_hook(self, iter_count, variable_record): - if iter_count % self._cfg.print_freq == 0: - if hasattr(self,'_comm'): - variable_record.update_var({'update_model_time':self._comm._avg_update_model_time.item() }) - self._logger.info( - 'ACTOR({}):\n{}TimeStep{}{} {}'.format( - self._actor_uid, '=' * 35, iter_count, '=' * 35, - variable_record.get_vars_text() - ) - ) - -if __name__ == '__main__': - - ## main - if os.path.exists(r'C:\Program Files (x86)\StarCraft II'): - sc2path = r'C:\Program Files (x86)\StarCraft II' - elif os.path.exists('/Applications/StarCraft II'): - sc2path = '/Applications/StarCraft II' - else: - assert 'SC2PATH' in os.environ.keys(), 'please add StarCraft2 installation path to your environment variables!' - sc2path = os.environ['SC2PATH'] - assert os.path.exists(sc2path), 'SC2PATH: {} does not exist!'.format(sc2path) - if not os.path.exists(os.path.join(sc2path, 'Maps/Ladder2019Season2')): - shutil.copytree(os.path.join(os.path.dirname(__file__), '../envs/maps/Ladder2019Season2'), os.path.join(sc2path, 'Maps/Ladder2019Season2')) - - parser = argparse.ArgumentParser(description="rl_train") - parser.add_argument("--config", default='C:/Users/hjs/DI-star/distar/bin/user_config.yaml') - parser.add_argument("--type", default=None) - parser.add_argument("--task", default='bot') - parser.add_argument("--player_id", default='MP0') - parser.add_argument("--gpu_batch_inference", default='false') - parser.add_argument("--init_method", type=str, default=None) - parser.add_argument("--rank", type=int, default=0) - parser.add_argument("--world_size", type=int, default=1) - args = parser.parse_args() - config = read_config(args.config) - config.common.type = 'rl' - config.actor.traj_len = config.learner.data.trajectory_length - - ## actor_run - actor = TestDIstarEnv(config) - actor._inference_loop() \ No newline at end of file diff --git a/dizoo/distar/envs/test_distar_config.yaml b/dizoo/distar/envs/tests/test_distar_config.yaml similarity index 100% rename from dizoo/distar/envs/test_distar_config.yaml rename to dizoo/distar/envs/tests/test_distar_config.yaml diff --git a/dizoo/distar/envs/test_distar_env.py b/dizoo/distar/envs/tests/test_distar_env_data.py similarity index 93% rename from dizoo/distar/envs/test_distar_env.py rename to dizoo/distar/envs/tests/test_distar_env_data.py index 6e25788431..38f1dc83a6 100644 --- a/dizoo/distar/envs/test_distar_env.py +++ b/dizoo/distar/envs/tests/test_distar_env_data.py @@ -11,7 +11,7 @@ class TestDIstarEnv: def __init__(self): - cfg = read_config('C:/Users/hjs/DI-engine/dizoo/distar/envs/test_distar_config.yaml') + cfg = read_config('./test_distar_config.yaml') self._whole_cfg = cfg self._whole_cfg.env.map_name = 'KingsCove' diff --git a/dizoo/distar/envs/test_distar_env_time_space.py b/dizoo/distar/envs/tests/test_distar_env_time_space.py similarity index 95% rename from dizoo/distar/envs/test_distar_env_time_space.py rename to dizoo/distar/envs/tests/test_distar_env_time_space.py index d2f784a119..3cc3612e45 100644 --- a/dizoo/distar/envs/test_distar_env_time_space.py +++ b/dizoo/distar/envs/tests/test_distar_env_time_space.py @@ -12,7 +12,7 @@ class TestDIstarEnv: def __init__(self): - cfg = read_config('C:/Users/hjs/DI-star/ding-test/envs/test_distar_config.yaml') + cfg = read_config('./test_distar_config.yaml') self._whole_cfg = cfg self._whole_cfg.env.map_name = 'KingsCove' self._total_iters = 0 diff --git a/dizoo/distar/envs/test_distar_env_with_manager.py b/dizoo/distar/envs/tests/test_distar_env_with_manager.py similarity index 92% rename from dizoo/distar/envs/test_distar_env_with_manager.py rename to dizoo/distar/envs/tests/test_distar_env_with_manager.py index c65f8b7a80..78f8154ba6 100644 --- a/dizoo/distar/envs/test_distar_env_with_manager.py +++ b/dizoo/distar/envs/tests/test_distar_env_with_manager.py @@ -34,7 +34,7 @@ class TestDIstarEnv: def __init__(self): - cfg = read_config('C:/Users/hjs/DI-engine/dizoo/distar/envs/test_distar_config.yaml') + cfg = read_config('./test_distar_config.yaml') self._whole_cfg = cfg self._whole_cfg.env.map_name = 'KingsCove' self._agent_env = DIStarEnv(self._whole_cfg) @@ -61,7 +61,6 @@ def _inference_loop(self, job={}): actions = {} for env_id in range(1): observations = obs[env_id] - print(type(observations)) actions[env_id] = self._agent_env.random_action(observations) # print(actions) timesteps = self._env.step(actions) From e3c95ffe2117f78620b7ce7e8bdb368157500a74 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Fri, 10 Jun 2022 16:16:18 +0800 Subject: [PATCH 098/229] make old test runnable --- .../distar/envs/tests/test_distar_env_data.py | 13 +++++----- .../envs/tests/test_distar_env_time_space.py | 25 ++++++++++--------- 2 files changed, 20 insertions(+), 18 deletions(-) diff --git a/dizoo/distar/envs/tests/test_distar_env_data.py b/dizoo/distar/envs/tests/test_distar_env_data.py index 38f1dc83a6..85caa88973 100644 --- a/dizoo/distar/envs/tests/test_distar_env_data.py +++ b/dizoo/distar/envs/tests/test_distar_env_data.py @@ -8,6 +8,9 @@ import random import time +from dizoo.distar.envs import DIStarEnv +import traceback + class TestDIstarEnv: def __init__(self): @@ -16,8 +19,6 @@ def __init__(self): self._whole_cfg.env.map_name = 'KingsCove' def _inference_loop(self, job={}): - from dizoo.distar.envs import DIStarEnv - import traceback torch.set_num_threads(1) @@ -26,15 +27,15 @@ def _inference_loop(self, job={}): with torch.no_grad(): for _ in range(5): try: - observations, game_info, map_name = self._env.reset() + observations = self._env.reset() for iter in range(1000): # one episode loop # agent step actions = self._env.random_action(observations) # env step - next_observations, reward, done = self._env.step(actions) - if not done: - observations = next_observations + timestep = self._env.step(actions) + if not timestep.done: + observations = timestep.obs else: break diff --git a/dizoo/distar/envs/tests/test_distar_env_time_space.py b/dizoo/distar/envs/tests/test_distar_env_time_space.py index 3cc3612e45..6d99173aa5 100644 --- a/dizoo/distar/envs/tests/test_distar_env_time_space.py +++ b/dizoo/distar/envs/tests/test_distar_env_time_space.py @@ -9,6 +9,9 @@ import time import sys +from dizoo.distar.envs import DIStarEnv +import traceback + class TestDIstarEnv: def __init__(self): @@ -20,8 +23,6 @@ def __init__(self): self._total_space = 0 def _inference_loop(self, job={}): - from distar_env import DIStarEnv - import traceback torch.set_num_threads(1) @@ -30,32 +31,32 @@ def _inference_loop(self, job={}): with torch.no_grad(): for _ in range(5): try: - observations, game_info, map_name = self._env.reset() + observations = self._env.reset() for iter in range(1000): # one episode loop # agent step actions = self._env.random_action(observations) # env step before_step_time = time.time() - next_observations, reward, done = self._env.step(actions) + timestep = self._env.step(actions) after_step_time = time.time() self._total_time += after_step_time - before_step_time self._total_iters += 1 - self._total_space += sys.getsizeof((actions,observations,next_observations,reward,done)) + self._total_space += sys.getsizeof((actions,observations,timestep.obs,timestep.reward,timestep.done)) print('observations: ', sys.getsizeof(observations), ' Byte') print('actions: ', sys.getsizeof(actions), ' Byte') - print('reward: ', sys.getsizeof(reward), ' Byte') - print('done: ', sys.getsizeof(done), ' Byte') - print('total: ', sys.getsizeof((actions,observations,next_observations,reward,done)),' Byte') + print('reward: ', sys.getsizeof(timestep.reward), ' Byte') + print('done: ', sys.getsizeof(timestep.done), ' Byte') + print('total: ', sys.getsizeof((actions,observations,timestep.obs,timestep.reward,timestep.done)),' Byte') print(type(observations)) # dict - print(type(reward)) # list - print(type(done)) # bool + print(type(timestep.reward)) # list + print(type(timestep.done)) # bool print(type(actions)) # dict - if not done: - observations = next_observations + if not timestep.done: + observations = timestep.obs else: break From 80277600a2ca359be99be54b5393f7f72a73de2b Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Mon, 13 Jun 2022 11:55:38 +0800 Subject: [PATCH 099/229] change random_action to a classmethod --- dizoo/distar/envs/distar_env.py | 5 +++-- dizoo/distar/envs/tests/test_distar_env_data.py | 2 +- .../envs/tests/test_distar_env_time_space.py | 2 +- .../envs/tests/test_distar_env_with_manager.py | 14 +++++++------- 4 files changed, 12 insertions(+), 11 deletions(-) diff --git a/dizoo/distar/envs/distar_env.py b/dizoo/distar/envs/distar_env.py index 45530766b6..ff9751f614 100644 --- a/dizoo/distar/envs/distar_env.py +++ b/dizoo/distar/envs/distar_env.py @@ -43,8 +43,9 @@ def observation_space(self): def action_space(self): #TODO pass - - def random_action(self, obs): + + @classmethod + def random_action(cls, obs): return_action = {} for policy_id in obs.keys(): raw = obs[policy_id]['raw_obs'].observation.raw_data diff --git a/dizoo/distar/envs/tests/test_distar_env_data.py b/dizoo/distar/envs/tests/test_distar_env_data.py index 85caa88973..afbf4cbfff 100644 --- a/dizoo/distar/envs/tests/test_distar_env_data.py +++ b/dizoo/distar/envs/tests/test_distar_env_data.py @@ -31,7 +31,7 @@ def _inference_loop(self, job={}): for iter in range(1000): # one episode loop # agent step - actions = self._env.random_action(observations) + actions = DIStarEnv.random_action(observations) # env step timestep = self._env.step(actions) if not timestep.done: diff --git a/dizoo/distar/envs/tests/test_distar_env_time_space.py b/dizoo/distar/envs/tests/test_distar_env_time_space.py index 6d99173aa5..b664490b92 100644 --- a/dizoo/distar/envs/tests/test_distar_env_time_space.py +++ b/dizoo/distar/envs/tests/test_distar_env_time_space.py @@ -35,7 +35,7 @@ def _inference_loop(self, job={}): for iter in range(1000): # one episode loop # agent step - actions = self._env.random_action(observations) + actions = DIStarEnv.random_action(observations) # env step before_step_time = time.time() timestep = self._env.step(actions) diff --git a/dizoo/distar/envs/tests/test_distar_env_with_manager.py b/dizoo/distar/envs/tests/test_distar_env_with_manager.py index 78f8154ba6..da5b9ae219 100644 --- a/dizoo/distar/envs/tests/test_distar_env_with_manager.py +++ b/dizoo/distar/envs/tests/test_distar_env_with_manager.py @@ -31,6 +31,8 @@ } ) +ENV_NUMBER = 2 + class TestDIstarEnv: def __init__(self): @@ -41,12 +43,11 @@ def __init__(self): def _inference_loop(self, job={}): - torch.set_num_threads(1) # self._env = DIStarEnv(self._whole_cfg) self._env = BaseEnvManager( - env_fn=[lambda: DIStarEnv(self._whole_cfg) for _ in range(1)], cfg=env_cfg.env.manager + env_fn=[lambda: DIStarEnv(self._whole_cfg) for _ in range(ENV_NUMBER)], cfg=env_cfg.env.manager ) self._env.seed(1) @@ -54,15 +55,14 @@ def _inference_loop(self, job={}): for episode in range(2): self._env.launch() try: - for env_step in range(10): + for env_step in range(1000): obs = self._env.ready_obs # print(obs) - obs = {env_id: obs[env_id] for env_id in range(1)} + obs = {env_id: obs[env_id] for env_id in range(ENV_NUMBER)} actions = {} - for env_id in range(1): + for env_id in range(ENV_NUMBER): observations = obs[env_id] - actions[env_id] = self._agent_env.random_action(observations) - # print(actions) + actions[env_id] = DIStarEnv.random_action(observations) timesteps = self._env.step(actions) print(actions) From cbe964c71cb7b55ce975cb4ff8453967193f2716 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Mon, 13 Jun 2022 17:22:05 +0800 Subject: [PATCH 100/229] change a bit DI-star env --- dizoo/distar/envs/distar_env.py | 120 +++++++++--------- .../distar/envs/tests/test_distar_env_data.py | 10 +- .../envs/tests/test_distar_env_time_space.py | 9 +- .../tests/test_distar_env_with_manager.py | 12 +- 4 files changed, 72 insertions(+), 79 deletions(-) diff --git a/dizoo/distar/envs/distar_env.py b/dizoo/distar/envs/distar_env.py index ff9751f614..4b3518d836 100644 --- a/dizoo/distar/envs/distar_env.py +++ b/dizoo/distar/envs/distar_env.py @@ -23,11 +23,14 @@ def step(self, actions): # In DI-engine, the return of BaseEnv.step is ('obs', 'reward', 'done', 'info') # Here in DI-star, the return is ({'raw_obs': self._obs[agent_idx], 'opponent_obs': opponent_obs, 'action_result': self._action_result[agent_idx]}, reward, episode_complete) next_observations, reward, done = super(DIStarEnv,self).step(actions) + info = {} + for policy_id in next_observations.keys(): + info[policy_id] = None timestep = BaseEnvTimestep( obs = next_observations, reward = reward, done = done, - info = None + info = info ) return timestep @@ -46,66 +49,63 @@ def action_space(self): @classmethod def random_action(cls, obs): - return_action = {} - for policy_id in obs.keys(): - raw = obs[policy_id]['raw_obs'].observation.raw_data - - all_unit_types = set() - self_unit_types = set() - - for u in raw.units: - # Here we select the units except “buildings that are in building progress” for simplification - if u.build_progress == 1: - all_unit_types.add(u.unit_type) - if u.alliance == 1: - self_unit_types.add(u.unit_type) - - avail_actions = [ - {0: {'exist_selected_types':[], 'exist_target_types':[]}}, - {168:{'exist_selected_types':[], 'exist_target_types':[]}} - ] # no_op and raw_move_camera don't have seleted_units - - for action_id, action in ACTIONS_STAT.items(): - exist_selected_types = list(self_unit_types.intersection(set(action['selected_type']))) - exist_target_types = list(all_unit_types.intersection(set(action['target_type']))) - - # if an action should have target, but we don't have valid target in this observation, then discard this action - if len(action['target_type']) != 0 and len(exist_target_types) == 0: - continue - - if len(exist_selected_types) > 0: - avail_actions.append({action_id: {'exist_selected_types':exist_selected_types, 'exist_target_types':exist_target_types}}) + raw = obs['raw_obs'].observation.raw_data + + all_unit_types = set() + self_unit_types = set() + + for u in raw.units: + # Here we select the units except “buildings that are in building progress” for simplification + if u.build_progress == 1: + all_unit_types.add(u.unit_type) + if u.alliance == 1: + self_unit_types.add(u.unit_type) + + avail_actions = [ + {0: {'exist_selected_types':[], 'exist_target_types':[]}}, + {168:{'exist_selected_types':[], 'exist_target_types':[]}} + ] # no_op and raw_move_camera don't have seleted_units + + for action_id, action in ACTIONS_STAT.items(): + exist_selected_types = list(self_unit_types.intersection(set(action['selected_type']))) + exist_target_types = list(all_unit_types.intersection(set(action['target_type']))) + + # if an action should have target, but we don't have valid target in this observation, then discard this action + if len(action['target_type']) != 0 and len(exist_target_types) == 0: + continue + + if len(exist_selected_types) > 0: + avail_actions.append({action_id: {'exist_selected_types':exist_selected_types, 'exist_target_types':exist_target_types}}) + + current_action = random.choice(avail_actions) + func_id, exist_types = current_action.popitem() + + if func_id not in [0, 168]: + correspond_selected_units = [u.tag for u in raw.units if u.unit_type in exist_types['exist_selected_types'] and u.build_progress == 1] + correspond_targets = [u.tag for u in raw.units if u.unit_type in exist_types['exist_target_types'] and u.build_progress == 1] + + num_selected_unit = random.randint(0, min(MAX_SELECTED_UNITS_NUM, len(correspond_selected_units))) + + unit_tags = random.sample(correspond_selected_units, num_selected_unit) + target_unit_tag = random.choice(correspond_targets) if len(correspond_targets) > 0 else None + + else: + unit_tags = [] + target_unit_tag = None - current_action = random.choice(avail_actions) - func_id, exist_types = current_action.popitem() - - if func_id not in [0, 168]: - correspond_selected_units = [u.tag for u in raw.units if u.unit_type in exist_types['exist_selected_types'] and u.build_progress == 1] - correspond_targets = [u.tag for u in raw.units if u.unit_type in exist_types['exist_target_types'] and u.build_progress == 1] - - num_selected_unit = random.randint(0, min(MAX_SELECTED_UNITS_NUM, len(correspond_selected_units))) - - unit_tags = random.sample(correspond_selected_units, num_selected_unit) - target_unit_tag = random.choice(correspond_targets) if len(correspond_targets) > 0 else None - - else: - unit_tags = [] - target_unit_tag = None - - data = { - 'func_id': func_id, - 'skip_steps': random.randint(0, MAX_DELAY - 1), - # 'skip_steps': 8, - 'queued': random.randint(0, 1), - 'unit_tags': unit_tags, - 'target_unit_tag': target_unit_tag, - 'location': ( - random.randint(0, SPATIAL_SIZE[0] - 1), - random.randint(0, SPATIAL_SIZE[1] - 1) - ) - } - return_action[policy_id] = [data] - return return_action + data = { + 'func_id': func_id, + 'skip_steps': random.randint(0, MAX_DELAY - 1), + # 'skip_steps': 8, + 'queued': random.randint(0, 1), + 'unit_tags': unit_tags, + 'target_unit_tag': target_unit_tag, + 'location': ( + random.randint(0, SPATIAL_SIZE[0] - 1), + random.randint(0, SPATIAL_SIZE[1] - 1) + ) + } + return [data] @property diff --git a/dizoo/distar/envs/tests/test_distar_env_data.py b/dizoo/distar/envs/tests/test_distar_env_data.py index afbf4cbfff..d3816b01f6 100644 --- a/dizoo/distar/envs/tests/test_distar_env_data.py +++ b/dizoo/distar/envs/tests/test_distar_env_data.py @@ -1,12 +1,8 @@ import os import shutil -import argparse -from distar.ctools.utils import read_config, deep_merge_dicts -from distar.actor import Actor +from distar.ctools.utils import read_config import torch -import random -import time from dizoo.distar.envs import DIStarEnv import traceback @@ -31,7 +27,9 @@ def _inference_loop(self, job={}): for iter in range(1000): # one episode loop # agent step - actions = DIStarEnv.random_action(observations) + actions = {} + for player_index, player_obs in observations.items(): + actions[player_index] = DIStarEnv.random_action(player_obs) # env step timestep = self._env.step(actions) if not timestep.done: diff --git a/dizoo/distar/envs/tests/test_distar_env_time_space.py b/dizoo/distar/envs/tests/test_distar_env_time_space.py index b664490b92..d4be5613d4 100644 --- a/dizoo/distar/envs/tests/test_distar_env_time_space.py +++ b/dizoo/distar/envs/tests/test_distar_env_time_space.py @@ -1,11 +1,8 @@ import os import shutil -import argparse -from distar.ctools.utils import read_config, deep_merge_dicts -from distar.actor import Actor +from distar.ctools.utils import read_config import torch -import random import time import sys @@ -35,7 +32,9 @@ def _inference_loop(self, job={}): for iter in range(1000): # one episode loop # agent step - actions = DIStarEnv.random_action(observations) + actions = {} + for player_index, player_obs in observations.items(): + actions[player_index] = DIStarEnv.random_action(player_obs) # env step before_step_time = time.time() timestep = self._env.step(actions) diff --git a/dizoo/distar/envs/tests/test_distar_env_with_manager.py b/dizoo/distar/envs/tests/test_distar_env_with_manager.py index da5b9ae219..ab8efdfa64 100644 --- a/dizoo/distar/envs/tests/test_distar_env_with_manager.py +++ b/dizoo/distar/envs/tests/test_distar_env_with_manager.py @@ -1,13 +1,8 @@ import os -from re import L import shutil -import argparse -from distar.ctools.utils import read_config, deep_merge_dicts -from distar.actor import Actor +from distar.ctools.utils import read_config import torch -import random -import time from ding.envs import BaseEnvManager from dizoo.distar.envs import DIStarEnv import traceback @@ -39,7 +34,6 @@ def __init__(self): cfg = read_config('./test_distar_config.yaml') self._whole_cfg = cfg self._whole_cfg.env.map_name = 'KingsCove' - self._agent_env = DIStarEnv(self._whole_cfg) def _inference_loop(self, job={}): @@ -62,7 +56,9 @@ def _inference_loop(self, job={}): actions = {} for env_id in range(ENV_NUMBER): observations = obs[env_id] - actions[env_id] = DIStarEnv.random_action(observations) + actions[env_id] = {} + for player_index, player_obs in observations.items(): + actions[env_id][player_index] = DIStarEnv.random_action(player_obs) timesteps = self._env.step(actions) print(actions) From fa07d12e65415cc31b61376036c3adb0df13349a Mon Sep 17 00:00:00 2001 From: lixuelin Date: Mon, 13 Jun 2022 17:31:19 +0800 Subject: [PATCH 101/229] add mock policy --- ding/framework/middleware/league_learner.py | 4 +- .../middleware/tests/league_config.py | 4 +- .../middleware/tests/mock_for_test.py | 39 ++++++++++++++++++ .../middleware/tests/test_league_pipeline.py | 41 +++++-------------- dizoo/distar/envs/distar_env.py | 9 ++-- 5 files changed, 59 insertions(+), 38 deletions(-) diff --git a/ding/framework/middleware/league_learner.py b/ding/framework/middleware/league_learner.py index 211db688a7..e48d3cc3f1 100644 --- a/ding/framework/middleware/league_learner.py +++ b/ding/framework/middleware/league_learner.py @@ -31,10 +31,10 @@ def __init__(self, cfg: dict, policy_fn: Callable, player: "ActivePlayer") -> No self.checkpoint_prefix = cfg.policy.other.league.path_policy self._learner = self._get_learner() self._lock = Lock() - task.on(EventEnum.ACTOR_SEND_DATA.format(player=self.player_id), self._on_actor_data) + task.on(EventEnum.ACTOR_SEND_DATA.format(player=self.player_id), self._on_actor_send_data) self._step = 0 - def _on_actor_data(self, actor_data: "ActorData"): + def _on_actor_send_data(self, actor_data: "ActorData"): print("receive data from actor!") with self._lock: cfg = self.cfg diff --git a/ding/framework/middleware/tests/league_config.py b/ding/framework/middleware/tests/league_config.py index e31def9660..985c03ea54 100644 --- a/ding/framework/middleware/tests/league_config.py +++ b/ding/framework/middleware/tests/league_config.py @@ -13,8 +13,8 @@ 'cfg_type': 'BaseEnvManagerDict', 'shared_memory': False }, - 'collector_env_num': 2, - 'evaluator_env_num': 10, + 'collector_env_num': 1, + 'evaluator_env_num': 1, 'n_evaluator_episode': 100, 'env_type': 'prisoner_dilemma', 'stop_value': [-10.1, -5.05] diff --git a/ding/framework/middleware/tests/mock_for_test.py b/ding/framework/middleware/tests/mock_for_test.py index adef35b4b7..1ba504f296 100644 --- a/ding/framework/middleware/tests/mock_for_test.py +++ b/ding/framework/middleware/tests/mock_for_test.py @@ -5,10 +5,15 @@ import treetensor.numpy as tnp from easydict import EasyDict from unittest.mock import Mock +from copy import deepcopy +from ding.torch_utils import to_device from ding.league.player import PlayerMeta from ding.league.v2 import BaseLeague, Job from ding.framework.storage import FileStorage +from ding.policy import PPOPolicy +from dizoo.distar.envs.distar_env import DIStarEnv + obs_dim = [2, 2] action_space = 1 @@ -163,3 +168,37 @@ def close(*args): def flush(*args): pass + + +class DIStarMockPolicy(PPOPolicy): + def _mock_data(self, data): + print("Data: ", data) + mock_data = {} + for id, val in data.items(): + assert isinstance(val, dict) + assert 'obs' in val + assert 'next_obs' in val + assert 'action' in val + assert 'reward' in val + mock_data[id] = deepcopy(val) + mock_data[id]['obs'] = torch.rand(16) + mock_data[id]['next_obs'] = torch.rand(16) + mock_data[id]['action'] = torch.rand(4) + return mock_data, data + + def _forward_learn(self, data: Dict[str, Any]) -> Dict[str, Any]: + print("Call forward_learn:") + mock_data, original_data = self._mock_data(data) + return super()._forward_learn(mock_data) + + def _forward_collect(self, data: Dict[int, Any]) -> Dict[int, Any]: + print("Call forward_collect:") + mock_data, original_data = self._mock_data(data) + output = super()._forward_collect(mock_data) + for id in output.keys(): + output[id]['action'] = DIStarEnv.random_action(original_data[id]['obs']) + return output + + # def _forward_eval(self, data: Dict[int, Any]) -> Dict[int, Any]: + # data = {i: torch.rand(self.policy.model.obs_shape) for i in range(self.cfg.env.collector_env_num)} + # return super()._forward_eval(data) diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index 7d24682869..deedddf5cb 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -1,55 +1,36 @@ -# from time import sleep -# from boto import config -# import pytest -# from copy import deepcopy - -# from ding.framework.middleware.league_learner import LeagueLearner -# from ding.framework.middleware.tests.league_config import cfg -# from ding.framework.middleware import LeagueActor, LeagueCoordinator -# from ding.league.player import PlayerMeta, create_player -# from ding.league.v2 import BaseLeague -# from ding.framework.storage import FileStorage - -# from ding.framework.task import task, Parallel -# from ding.league.v2.base_league import Job -# from ding.model import VAC -# from ding.policy.ppo import PPOPolicy -# from dizoo.league_demo.game_env import GameEnv - from copy import deepcopy from time import sleep -import torch import pytest -import random +import os from ding.envs import BaseEnvManager from ding.model import VAC -from ding.policy import PPOPolicy -from ding.framework import EventEnum from ding.framework.task import task, Parallel from ding.framework.middleware import LeagueCoordinator, LeagueActor, LeagueLearner from ding.framework.middleware.functional.actor_data import ActorData from ding.framework.middleware.tests import cfg, MockLeague, MockLogger -from dizoo.league_demo.game_env import GameEnv +from dizoo.distar.envs.distar_env import DIStarEnv +from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy +from distar.ctools.utils import read_config - -N_ACTORS = 2 -N_LEARNERS = 2 +N_ACTORS = 1 +N_LEARNERS = 1 def prepare_test(): global cfg cfg = deepcopy(cfg) + env_cfg = read_config(os.path.join(os.path.dirname(__file__), '../../../../dizoo/distar/envs/tests/test_distar_config.yaml')) def env_fn(): env = BaseEnvManager( - env_fn=[lambda: GameEnv(cfg.env.env_type) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager + env_fn=[lambda: DIStarEnv(env_cfg) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager ) env.seed(cfg.seed) return env def policy_fn(): model = VAC(**cfg.policy.model) - policy = PPOPolicy(cfg.policy, model=model) + policy = DIStarMockPolicy(cfg.policy, model=model) return policy return cfg, env_fn, policy_fn @@ -71,7 +52,7 @@ def _main(): learner._learner._tb_logger = MockLogger() task.use(learner) - task.run(max_step=120) + task.run(max_step=300) @pytest.mark.unittest @@ -80,4 +61,4 @@ def test_league_actor(): if __name__ == '__main__': - Parallel.runner(n_parallel_workers=N_ACTORS+N_LEARNERS+1, protocol="tcp", topology="mesh")(_main) \ No newline at end of file + Parallel.runner(n_parallel_workers=N_ACTORS+N_LEARNERS+1, protocol="tcp", topology="mesh")(_main) diff --git a/dizoo/distar/envs/distar_env.py b/dizoo/distar/envs/distar_env.py index 45530766b6..7c3d6e4dca 100644 --- a/dizoo/distar/envs/distar_env.py +++ b/dizoo/distar/envs/distar_env.py @@ -7,9 +7,9 @@ import torch import random -class DIStarEnv(SC2Env,BaseEnv): +class DIStarEnv(SC2Env, BaseEnv): - def __init__(self,cfg): + def __init__(self, cfg): super(DIStarEnv, self).__init__(cfg) def reset(self): @@ -22,7 +22,7 @@ def close(self): def step(self, actions): # In DI-engine, the return of BaseEnv.step is ('obs', 'reward', 'done', 'info') # Here in DI-star, the return is ({'raw_obs': self._obs[agent_idx], 'opponent_obs': opponent_obs, 'action_result': self._action_result[agent_idx]}, reward, episode_complete) - next_observations, reward, done = super(DIStarEnv,self).step(actions) + next_observations, reward, done = super(DIStarEnv, self).step(actions) timestep = BaseEnvTimestep( obs = next_observations, reward = reward, @@ -44,7 +44,8 @@ def action_space(self): #TODO pass - def random_action(self, obs): + @classmethod + def random_action(cls, obs): return_action = {} for policy_id in obs.keys(): raw = obs[policy_id]['raw_obs'].observation.raw_data From 7ad26effa4ba64ba9f898a1d0e8959c84c326f7e Mon Sep 17 00:00:00 2001 From: lixuelin Date: Mon, 13 Jun 2022 17:49:43 +0800 Subject: [PATCH 102/229] reformat --- ding/framework/middleware/league_learner.py | 5 +++- ding/framework/middleware/tests/__init__.py | 2 +- .../middleware/tests/mock_for_test.py | 3 +- .../middleware/tests/test_league_learner.py | 28 +++++++++++++------ .../middleware/tests/test_league_pipeline.py | 10 +++++-- 5 files changed, 34 insertions(+), 14 deletions(-) diff --git a/ding/framework/middleware/league_learner.py b/ding/framework/middleware/league_learner.py index e48d3cc3f1..eba816ce0c 100644 --- a/ding/framework/middleware/league_learner.py +++ b/ding/framework/middleware/league_learner.py @@ -15,12 +15,14 @@ from ding.framework.middleware.league_actor import ActorData from ding.league import ActivePlayer + @dataclass class LearnerModel: player_id: str state_dict: dict train_iter: int = 0 + class LeagueLearner: def __init__(self, cfg: dict, policy_fn: Callable, player: "ActivePlayer") -> None: @@ -70,7 +72,8 @@ def _save_checkpoint(self) -> Optional[Storage]: if not os.path.exists(self.checkpoint_prefix): os.makedirs(self.checkpoint_prefix) storage = FileStorage( - path=os.path.join(self.checkpoint_prefix, "{}_{}_ckpt.pth".format(self.player_id, self._learner.train_iter)) + path=os.path. + join(self.checkpoint_prefix, "{}_{}_ckpt.pth".format(self.player_id, self._learner.train_iter)) ) storage.save(self._learner.policy.state_dict()) return storage diff --git a/ding/framework/middleware/tests/__init__.py b/ding/framework/middleware/tests/__init__.py index 54c6b9f76a..8fc101ec04 100644 --- a/ding/framework/middleware/tests/__init__.py +++ b/ding/framework/middleware/tests/__init__.py @@ -1,2 +1,2 @@ from .mock_for_test import * -from .league_config import cfg \ No newline at end of file +from .league_config import cfg diff --git a/ding/framework/middleware/tests/mock_for_test.py b/ding/framework/middleware/tests/mock_for_test.py index 1ba504f296..9bd5637017 100644 --- a/ding/framework/middleware/tests/mock_for_test.py +++ b/ding/framework/middleware/tests/mock_for_test.py @@ -14,7 +14,6 @@ from ding.policy import PPOPolicy from dizoo.distar.envs.distar_env import DIStarEnv - obs_dim = [2, 2] action_space = 1 env_num = 2 @@ -129,6 +128,7 @@ def estimate(self, episode: List[Dict[str, Any]]) -> List[Dict[str, Any]]: class MockLeague(BaseLeague): + def __init__(self, cfg) -> None: super().__init__(cfg) self.update_payoff_cnt = 0 @@ -171,6 +171,7 @@ def flush(*args): class DIStarMockPolicy(PPOPolicy): + def _mock_data(self, data): print("Data: ", data) mock_data = {} diff --git a/ding/framework/middleware/tests/test_league_learner.py b/ding/framework/middleware/tests/test_league_learner.py index 1fed2b66f7..81dfa12075 100644 --- a/ding/framework/middleware/tests/test_league_learner.py +++ b/ding/framework/middleware/tests/test_league_learner.py @@ -16,6 +16,7 @@ logging.getLogger().setLevel(logging.INFO) + def prepare_test(): global cfg cfg = deepcopy(cfg) @@ -34,32 +35,43 @@ def policy_fn(): return cfg, env_fn, policy_fn + def coordinator_mocker(): task.on(EventEnum.LEARNER_SEND_META, lambda x: print("test:", x)) task.on(EventEnum.LEARNER_SEND_MODEL, lambda x: print("test: send model success")) + def _coordinator_mocker(ctx): sleep(1) + return _coordinator_mocker + def actor_mocker(league): + def _actor_mocker(ctx): sleep(1) obs_size = cfg.policy.model.obs_shape - data = [{ - 'obs': torch.rand(*obs_size), - 'next_obs': torch.rand(*obs_size), - 'done': False, - 'reward': torch.rand(1), - 'logit': torch.rand(1), - 'action': torch.randint(low=0, high=2, size=(1,)), - } for _ in range(32)] + if isinstance(obs_size, int): + obs_size = [obs_size] + data = [ + { + 'obs': torch.rand(*obs_size), + 'next_obs': torch.rand(*obs_size), + 'done': False, + 'reward': torch.rand(1), + 'logit': torch.rand(1), + 'action': torch.randint(low=0, high=2, size=(1, )), + } for _ in range(32) + ] actor_data = ActorData(env_step=0, train_data=data) n_players = len(league.active_players_ids) player = league.active_players[(task.router.node_id + 2) % n_players] print("actor player:", player.player_id) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=player.player_id), actor_data) + return _actor_mocker + def _main(): cfg, env_fn, policy_fn = prepare_test() league = MockLeague(cfg.policy.other.league) diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index deedddf5cb..5fa85c95a0 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -16,10 +16,13 @@ N_ACTORS = 1 N_LEARNERS = 1 + def prepare_test(): global cfg cfg = deepcopy(cfg) - env_cfg = read_config(os.path.join(os.path.dirname(__file__), '../../../../dizoo/distar/envs/tests/test_distar_config.yaml')) + env_cfg = read_config( + os.path.join(os.path.dirname(__file__), '../../../../dizoo/distar/envs/tests/test_distar_config.yaml') + ) def env_fn(): env = BaseEnvManager( @@ -35,6 +38,7 @@ def policy_fn(): return cfg, env_fn, policy_fn + def _main(): cfg, env_fn, policy_fn = prepare_test() league = MockLeague(cfg.policy.other.league) @@ -57,8 +61,8 @@ def _main(): @pytest.mark.unittest def test_league_actor(): - Parallel.runner(n_parallel_workers=N_ACTORS+N_LEARNERS+1, protocol="tcp", topology="mesh")(_main) + Parallel.runner(n_parallel_workers=N_ACTORS + N_LEARNERS + 1, protocol="tcp", topology="mesh")(_main) if __name__ == '__main__': - Parallel.runner(n_parallel_workers=N_ACTORS+N_LEARNERS+1, protocol="tcp", topology="mesh")(_main) + Parallel.runner(n_parallel_workers=N_ACTORS + N_LEARNERS + 1, protocol="tcp", topology="mesh")(_main) From 56ed8e10845024c991cc55667c26c9292b4e4fc3 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Mon, 13 Jun 2022 19:26:06 +0800 Subject: [PATCH 103/229] fix a bug --- dizoo/distar/envs/distar_env.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/dizoo/distar/envs/distar_env.py b/dizoo/distar/envs/distar_env.py index 4b3518d836..9ccbd6d22b 100644 --- a/dizoo/distar/envs/distar_env.py +++ b/dizoo/distar/envs/distar_env.py @@ -24,7 +24,7 @@ def step(self, actions): # Here in DI-star, the return is ({'raw_obs': self._obs[agent_idx], 'opponent_obs': opponent_obs, 'action_result': self._action_result[agent_idx]}, reward, episode_complete) next_observations, reward, done = super(DIStarEnv,self).step(actions) info = {} - for policy_id in next_observations.keys(): + for policy_id in range(self._num_agents): info[policy_id] = None timestep = BaseEnvTimestep( obs = next_observations, From b93426097fcda275a6539882c015e2e9db44b1dd Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Mon, 13 Jun 2022 19:27:13 +0800 Subject: [PATCH 104/229] modification to run DI-star in pipeline --- ding/framework/middleware/collector.py | 4 +- .../middleware/functional/__init__.py | 2 +- .../middleware/functional/collector.py | 66 +++++++ .../middleware/tests/league_config.py | 2 +- .../middleware/tests/test_distar_config.yaml | 16 ++ .../test_league_actor_distar_one_process.py | 172 ++++++++++++++++++ .../tests/test_league_actor_one_process.py | 1 - 7 files changed, 259 insertions(+), 4 deletions(-) create mode 100644 ding/framework/middleware/tests/test_distar_config.yaml create mode 100644 ding/framework/middleware/tests/test_league_actor_distar_one_process.py diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index b77895d4d8..1454e8a5f8 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -3,7 +3,9 @@ from ding.policy import Policy, get_random_policy from ding.envs import BaseEnvManager from ding.framework import task -from .functional import inferencer, rolloutor, TransitionList, battle_inferencer, battle_rolloutor +from .functional import inferencer, rolloutor, TransitionList, battle_rolloutor +from .functional import battle_inferencer_for_distar as battle_inferencer +from .functional import battle_rolloutor_for_distar as battle_rolloutor from typing import Dict # if TYPE_CHECKING: diff --git a/ding/framework/middleware/functional/__init__.py b/ding/framework/middleware/functional/__init__.py index c17d0e8a63..df97581c45 100644 --- a/ding/framework/middleware/functional/__init__.py +++ b/ding/framework/middleware/functional/__init__.py @@ -1,7 +1,7 @@ from .trainer import trainer, multistep_trainer from .data_processor import offpolicy_data_fetcher, data_pusher, offline_data_fetcher, offline_data_saver, \ sqil_data_pusher -from .collector import inferencer, rolloutor, TransitionList, battle_inferencer, battle_rolloutor +from .collector import inferencer, rolloutor, TransitionList, battle_inferencer, battle_rolloutor, battle_inferencer_for_distar, battle_rolloutor_for_distar from .evaluator import interaction_evaluator from .termination_checker import termination_checker from .pace_controller import pace_controller diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 2b40f70358..47f0aaf696 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -194,3 +194,69 @@ def _battle_rolloutor(ctx: "BattleContext"): ctx.env_episode += 1 return _battle_rolloutor + + +def battle_inferencer_for_distar(cfg: EasyDict, env: BaseEnvManager): + + def _battle_inferencer(ctx: "BattleContext"): + + if env.closed: + env.launch() + + # Get current env obs. + obs = env.ready_obs + # the role of remain_episode is to mask necessary rollouts, avoid processing unnecessary data + new_available_env_id = set(obs.keys()).difference(ctx.ready_env_id) + ctx.ready_env_id = ctx.ready_env_id.union(set(list(new_available_env_id)[:ctx.remain_episode])) + ctx.remain_episode -= min(len(new_available_env_id), ctx.remain_episode) + obs = {env_id: obs[env_id] for env_id in ctx.ready_env_id} + + ctx.obs = obs + + # Policy forward. + inference_output = {} + actions = {} + for env_id in ctx.ready_env_id: + observations = obs[env_id] + inference_output[env_id] = {} + actions[env_id] = {} + for policy_id, policy_obs in observations.items(): + output = ctx.current_policies[policy_id].forward(policy_obs) + inference_output[env_id][policy_id] = output + actions[env_id][policy_id] = output['action'] + print(actions) + ctx.inference_output = inference_output + ctx.actions = actions + + return _battle_inferencer + +from ding.envs import BaseEnvTimestep +def battle_rolloutor_for_distar(cfg: EasyDict, env: BaseEnvManager, transitions_list: List): + + def _battle_rolloutor(ctx: "BattleContext"): + timesteps = env.step(ctx.actions) + ctx.total_envstep_count += len(timesteps) + ctx.env_step += len(timesteps) + for env_id, timestep in timesteps.items(): + for policy_id in ctx.obs[env_id].keys(): + policy_timestep = BaseEnvTimestep( + obs = timestep.obs.get(policy_id) if timestep.obs.get(policy_id) is not None else None, + reward = timestep.reward[policy_id], + done = timestep.done, + info = {} + ) + transition = ctx.current_policies[policy_id].process_transition( + ctx.obs[env_id][policy_id], ctx.inference_output[env_id][policy_id], policy_timestep + ) + transition = EasyDict(transition) + transition.collect_train_iter = ttorch.as_tensor([ctx.train_iter]) + transitions_list[policy_id].append(env_id, transition) + if timestep.done: + ctx.current_policies[policy_id].reset([env_id]) + ctx.episode_info[policy_id].append(timestep.info[policy_id]) + + if timestep.done: + ctx.ready_env_id.remove(env_id) + ctx.env_episode += 1 + + return _battle_rolloutor \ No newline at end of file diff --git a/ding/framework/middleware/tests/league_config.py b/ding/framework/middleware/tests/league_config.py index a905431e19..ed23c58acc 100644 --- a/ding/framework/middleware/tests/league_config.py +++ b/ding/framework/middleware/tests/league_config.py @@ -13,7 +13,7 @@ 'cfg_type': 'BaseEnvManagerDict', 'shared_memory': False }, - 'collector_env_num': 2, + 'collector_env_num': 1, 'evaluator_env_num': 10, 'n_evaluator_episode': 100, 'env_type': 'prisoner_dilemma', diff --git a/ding/framework/middleware/tests/test_distar_config.yaml b/ding/framework/middleware/tests/test_distar_config.yaml new file mode 100644 index 0000000000..18247e5a54 --- /dev/null +++ b/ding/framework/middleware/tests/test_distar_config.yaml @@ -0,0 +1,16 @@ +actor: + job_type: 'train' # ['train', 'eval', 'train_test', 'eval_test'] +env: + map_name: 'KingsCove' + player_ids: ['agent1', 'agent2'] + races: ['zerg', 'zerg'] + map_size_resolutions: [True, True] # if True, ignore minimap_resolutions + minimap_resolutions: [[160, 152], [160, 152]] + realtime: False + replay_dir: '.' + random_seed: 'none' + game_steps_per_episode: 100000 + update_bot_obs: False + save_replay_episodes: 1 + update_both_obs: False + version: '4.10.0' \ No newline at end of file diff --git a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py new file mode 100644 index 0000000000..faa1f3c396 --- /dev/null +++ b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py @@ -0,0 +1,172 @@ +from time import sleep +import pytest +from copy import deepcopy +from ding.envs import BaseEnvManager +from ding.framework.context import BattleContext +from ding.framework.middleware.league_learner import LearnerModel +from ding.framework.middleware.tests.league_config import cfg +from ding.framework.middleware import LeagueActor +from ding.framework.middleware.functional import ActorData +from ding.league.player import PlayerMeta +from ding.framework.storage import FileStorage +from easydict import EasyDict + +from ding.framework.task import task +from ding.league.v2.base_league import Job +from dizoo.distar.envs.distar_env import DIStarEnv +from unittest.mock import Mock, patch + +from ding.framework import EventEnum +from typing import Dict, Any, List, Optional +from collections import namedtuple +from distar.ctools.utils import read_config +import treetensor.torch as ttorch +from easydict import EasyDict + +class LearnMode: + def __init__(self) -> None: + pass + + def state_dict(self): + return {} + +class CollectMode: + def __init__(self) -> None: + self._cfg = EasyDict(dict( + collect = dict( + n_episode = 64 + ) + )) + + def load_state_dict(self, state_dict): + return + + def forward(self, data: Dict): + return_data = {} + return_data['action'] = DIStarEnv.random_action(data) + return_data['logit'] = [1] + return_data['value'] = [0] + + return return_data + + def process_transition(self, obs: Any, model_output: dict, timestep: namedtuple) -> dict: + transition = { + 'obs': obs, + 'next_obs': timestep.obs, + 'action': model_output['action'], + 'logit': model_output['logit'], + 'value': model_output['value'], + 'reward': timestep.reward, + 'done': timestep.done, + } + return transition + + def reset(self, data_id: Optional[List[int]] = None) -> None: + pass + + def get_attribute(self, name: str) -> Any: + if hasattr(self, '_get_' + name): + return getattr(self, '_get_' + name)() + elif hasattr(self, '_' + name): + return getattr(self, '_' + name) + else: + raise NotImplementedError + + +class MockActorDIstarPolicy(): + + def __init__(self): + + self.learn_mode = LearnMode() + self.collect_mode = CollectMode() + + +def prepare_test(): + global cfg + cfg = deepcopy(cfg) + + env_cfg = read_config('./test_distar_config.yaml') + env_cfg.env.map_name = 'KingsCove' + + def env_fn(): + env = BaseEnvManager( + env_fn=[lambda: DIStarEnv(env_cfg) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager + ) + env.seed(cfg.seed) + return env + + def policy_fn(): + policy = MockActorDIstarPolicy() + return policy + + return cfg, env_fn, policy_fn + + + +@pytest.mark.unittest +def test_league_actor(): + cfg, env_fn, policy_fn = prepare_test() + policy = policy_fn() + with task.start(async_mode=True, ctx = BattleContext()): + league_actor = LeagueActor(cfg=cfg, env_fn=env_fn, policy_fn=policy_fn) + + def test_actor(): + job = Job( + launch_player='main_player_default_0', + players=[ + PlayerMeta( + player_id='main_player_default_0', checkpoint=FileStorage(path=None), total_agent_step=0 + ), + PlayerMeta( + player_id='main_player_default_1', checkpoint=FileStorage(path=None), total_agent_step=0 + ) + ] + ) + testcases = { + "on_actor_greeting": False, + "on_actor_job": False, + "on_actor_data": False, + } + + def on_actor_greeting(actor_id): + assert actor_id == task.router.node_id + testcases["on_actor_greeting"] = True + + def on_actor_job(job_: Job): + assert job_.launch_player == job.launch_player + testcases["on_actor_job"] = True + + def on_actor_data(actor_data): + assert isinstance(actor_data, ActorData) + testcases["on_actor_data"] = True + + task.on(EventEnum.ACTOR_GREETING, on_actor_greeting) + task.on(EventEnum.ACTOR_FINISH_JOB, on_actor_job) + task.on(EventEnum.ACTOR_SEND_DATA.format(player=job.launch_player), on_actor_data) + + def _test_actor(ctx): + sleep(0.3) + task.emit(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), job) + sleep(0.3) + + task.emit( + EventEnum.LEARNER_SEND_MODEL, + LearnerModel( + player_id='main_player_default_0', state_dict=policy.learn_mode.state_dict(), train_iter=0 + ) + ) + sleep(150) + # try: + # print(testcases) + # assert all(testcases.values()) + # finally: + # task.finish = True + + return _test_actor + + task.use(test_actor()) + task.use(league_actor) + task.run() + +if __name__ == '__main__': + test_league_actor() \ No newline at end of file diff --git a/ding/framework/middleware/tests/test_league_actor_one_process.py b/ding/framework/middleware/tests/test_league_actor_one_process.py index f976c0f63d..124a0b312b 100644 --- a/ding/framework/middleware/tests/test_league_actor_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_one_process.py @@ -11,7 +11,6 @@ from ding.framework.storage import FileStorage from ding.framework.task import task -from ding.framework import OnlineRLContext from ding.league.v2.base_league import Job from ding.model import VAC from ding.policy.ppo import PPOPolicy From 3518a03ffa84ffc0f62986633d9e59e4614f0533 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Mon, 13 Jun 2022 20:00:27 +0800 Subject: [PATCH 105/229] fix conflicts --- ...nfig.yaml~HEAD => test_distar_config.yaml} | 0 .../tests/test_distar_config.yaml~dev-distar | 16 -------- .../tests/test_distar_env_with_manager.py | 39 ------------------- 3 files changed, 55 deletions(-) rename dizoo/distar/envs/tests/{test_distar_config.yaml~HEAD => test_distar_config.yaml} (100%) delete mode 100644 dizoo/distar/envs/tests/test_distar_config.yaml~dev-distar diff --git a/dizoo/distar/envs/tests/test_distar_config.yaml~HEAD b/dizoo/distar/envs/tests/test_distar_config.yaml similarity index 100% rename from dizoo/distar/envs/tests/test_distar_config.yaml~HEAD rename to dizoo/distar/envs/tests/test_distar_config.yaml diff --git a/dizoo/distar/envs/tests/test_distar_config.yaml~dev-distar b/dizoo/distar/envs/tests/test_distar_config.yaml~dev-distar deleted file mode 100644 index 18247e5a54..0000000000 --- a/dizoo/distar/envs/tests/test_distar_config.yaml~dev-distar +++ /dev/null @@ -1,16 +0,0 @@ -actor: - job_type: 'train' # ['train', 'eval', 'train_test', 'eval_test'] -env: - map_name: 'KingsCove' - player_ids: ['agent1', 'agent2'] - races: ['zerg', 'zerg'] - map_size_resolutions: [True, True] # if True, ignore minimap_resolutions - minimap_resolutions: [[160, 152], [160, 152]] - realtime: False - replay_dir: '.' - random_seed: 'none' - game_steps_per_episode: 100000 - update_bot_obs: False - save_replay_episodes: 1 - update_both_obs: False - version: '4.10.0' \ No newline at end of file diff --git a/dizoo/distar/envs/tests/test_distar_env_with_manager.py b/dizoo/distar/envs/tests/test_distar_env_with_manager.py index 4d35e80e4a..ab8efdfa64 100644 --- a/dizoo/distar/envs/tests/test_distar_env_with_manager.py +++ b/dizoo/distar/envs/tests/test_distar_env_with_manager.py @@ -1,20 +1,8 @@ import os -<<<<<<< HEAD import shutil from distar.ctools.utils import read_config import torch -======= -from re import L -import shutil -import argparse - -from distar.ctools.utils import read_config, deep_merge_dicts -from distar.actor import Actor -import torch -import random -import time ->>>>>>> dev-distar from ding.envs import BaseEnvManager from dizoo.distar.envs import DIStarEnv import traceback @@ -38,37 +26,22 @@ } ) -<<<<<<< HEAD ENV_NUMBER = 2 -======= ->>>>>>> dev-distar class TestDIstarEnv: def __init__(self): cfg = read_config('./test_distar_config.yaml') self._whole_cfg = cfg self._whole_cfg.env.map_name = 'KingsCove' -<<<<<<< HEAD - - def _inference_loop(self, job={}): - -======= - self._agent_env = DIStarEnv(self._whole_cfg) def _inference_loop(self, job={}): - ->>>>>>> dev-distar torch.set_num_threads(1) # self._env = DIStarEnv(self._whole_cfg) self._env = BaseEnvManager( -<<<<<<< HEAD env_fn=[lambda: DIStarEnv(self._whole_cfg) for _ in range(ENV_NUMBER)], cfg=env_cfg.env.manager -======= - env_fn=[lambda: DIStarEnv(self._whole_cfg) for _ in range(1)], cfg=env_cfg.env.manager ->>>>>>> dev-distar ) self._env.seed(1) @@ -76,7 +49,6 @@ def _inference_loop(self, job={}): for episode in range(2): self._env.launch() try: -<<<<<<< HEAD for env_step in range(1000): obs = self._env.ready_obs # print(obs) @@ -87,17 +59,6 @@ def _inference_loop(self, job={}): actions[env_id] = {} for player_index, player_obs in observations.items(): actions[env_id][player_index] = DIStarEnv.random_action(player_obs) -======= - for env_step in range(10): - obs = self._env.ready_obs - # print(obs) - obs = {env_id: obs[env_id] for env_id in range(1)} - actions = {} - for env_id in range(1): - observations = obs[env_id] - actions[env_id] = self._agent_env.random_action(observations) - # print(actions) ->>>>>>> dev-distar timesteps = self._env.step(actions) print(actions) From 9ae914a84c015d83edffe18f508a8e942dce317e Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Mon, 13 Jun 2022 20:37:45 +0800 Subject: [PATCH 106/229] change mocks --- ding/framework/middleware/collector.py | 3 +- .../middleware/functional/__init__.py | 2 +- .../middleware/functional/collector.py | 66 -------------- .../middleware/tests/mock_for_test.py | 85 +++++++++++++++++-- .../test_league_actor_distar_one_process.py | 36 ++++---- 5 files changed, 97 insertions(+), 95 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 21c8597828..d53ab16a45 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -5,8 +5,7 @@ from ding.envs import BaseEnvManager from ding.framework import task from .functional import inferencer, rolloutor, TransitionList, battle_rolloutor -from .functional import battle_inferencer_for_distar as battle_inferencer -from .functional import battle_rolloutor_for_distar as battle_rolloutor +from .functional import battle_inferencer, battle_rolloutor from typing import Dict # if TYPE_CHECKING: diff --git a/ding/framework/middleware/functional/__init__.py b/ding/framework/middleware/functional/__init__.py index df97581c45..c17d0e8a63 100644 --- a/ding/framework/middleware/functional/__init__.py +++ b/ding/framework/middleware/functional/__init__.py @@ -1,7 +1,7 @@ from .trainer import trainer, multistep_trainer from .data_processor import offpolicy_data_fetcher, data_pusher, offline_data_fetcher, offline_data_saver, \ sqil_data_pusher -from .collector import inferencer, rolloutor, TransitionList, battle_inferencer, battle_rolloutor, battle_inferencer_for_distar, battle_rolloutor_for_distar +from .collector import inferencer, rolloutor, TransitionList, battle_inferencer, battle_rolloutor from .evaluator import interaction_evaluator from .termination_checker import termination_checker from .pace_controller import pace_controller diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 47f0aaf696..2b40f70358 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -194,69 +194,3 @@ def _battle_rolloutor(ctx: "BattleContext"): ctx.env_episode += 1 return _battle_rolloutor - - -def battle_inferencer_for_distar(cfg: EasyDict, env: BaseEnvManager): - - def _battle_inferencer(ctx: "BattleContext"): - - if env.closed: - env.launch() - - # Get current env obs. - obs = env.ready_obs - # the role of remain_episode is to mask necessary rollouts, avoid processing unnecessary data - new_available_env_id = set(obs.keys()).difference(ctx.ready_env_id) - ctx.ready_env_id = ctx.ready_env_id.union(set(list(new_available_env_id)[:ctx.remain_episode])) - ctx.remain_episode -= min(len(new_available_env_id), ctx.remain_episode) - obs = {env_id: obs[env_id] for env_id in ctx.ready_env_id} - - ctx.obs = obs - - # Policy forward. - inference_output = {} - actions = {} - for env_id in ctx.ready_env_id: - observations = obs[env_id] - inference_output[env_id] = {} - actions[env_id] = {} - for policy_id, policy_obs in observations.items(): - output = ctx.current_policies[policy_id].forward(policy_obs) - inference_output[env_id][policy_id] = output - actions[env_id][policy_id] = output['action'] - print(actions) - ctx.inference_output = inference_output - ctx.actions = actions - - return _battle_inferencer - -from ding.envs import BaseEnvTimestep -def battle_rolloutor_for_distar(cfg: EasyDict, env: BaseEnvManager, transitions_list: List): - - def _battle_rolloutor(ctx: "BattleContext"): - timesteps = env.step(ctx.actions) - ctx.total_envstep_count += len(timesteps) - ctx.env_step += len(timesteps) - for env_id, timestep in timesteps.items(): - for policy_id in ctx.obs[env_id].keys(): - policy_timestep = BaseEnvTimestep( - obs = timestep.obs.get(policy_id) if timestep.obs.get(policy_id) is not None else None, - reward = timestep.reward[policy_id], - done = timestep.done, - info = {} - ) - transition = ctx.current_policies[policy_id].process_transition( - ctx.obs[env_id][policy_id], ctx.inference_output[env_id][policy_id], policy_timestep - ) - transition = EasyDict(transition) - transition.collect_train_iter = ttorch.as_tensor([ctx.train_iter]) - transitions_list[policy_id].append(env_id, transition) - if timestep.done: - ctx.current_policies[policy_id].reset([env_id]) - ctx.episode_info[policy_id].append(timestep.info[policy_id]) - - if timestep.done: - ctx.ready_env_id.remove(env_id) - ctx.env_episode += 1 - - return _battle_rolloutor \ No newline at end of file diff --git a/ding/framework/middleware/tests/mock_for_test.py b/ding/framework/middleware/tests/mock_for_test.py index 9bd5637017..4be1fd1f42 100644 --- a/ding/framework/middleware/tests/mock_for_test.py +++ b/ding/framework/middleware/tests/mock_for_test.py @@ -1,4 +1,4 @@ -from typing import Union, Any, List, Callable, Dict, Optional +from typing import TYPE_CHECKING, Union, Any, List, Callable, Dict, Optional from collections import namedtuple import random import torch @@ -13,6 +13,11 @@ from ding.framework.storage import FileStorage from ding.policy import PPOPolicy from dizoo.distar.envs.distar_env import DIStarEnv +from ding.envs import BaseEnvManager +import treetensor.torch as ttorch + +if TYPE_CHECKING: + from ding.framework import BattleContext obs_dim = [2, 2] action_space = 1 @@ -194,12 +199,80 @@ def _forward_learn(self, data: Dict[str, Any]) -> Dict[str, Any]: def _forward_collect(self, data: Dict[int, Any]) -> Dict[int, Any]: print("Call forward_collect:") - mock_data, original_data = self._mock_data(data) - output = super()._forward_collect(mock_data) - for id in output.keys(): - output[id]['action'] = DIStarEnv.random_action(original_data[id]['obs']) - return output + return_data = {} + return_data['action'] = DIStarEnv.random_action(data) + return_data['logit'] = [1] + return_data['value'] = [0] + + return return_data # def _forward_eval(self, data: Dict[int, Any]) -> Dict[int, Any]: # data = {i: torch.rand(self.policy.model.obs_shape) for i in range(self.cfg.env.collector_env_num)} # return super()._forward_eval(data) + + +def battle_inferencer_for_distar(cfg: EasyDict, env: BaseEnvManager): + + def _battle_inferencer(ctx: "BattleContext"): + + if env.closed: + env.launch() + + # Get current env obs. + obs = env.ready_obs + # the role of remain_episode is to mask necessary rollouts, avoid processing unnecessary data + new_available_env_id = set(obs.keys()).difference(ctx.ready_env_id) + ctx.ready_env_id = ctx.ready_env_id.union(set(list(new_available_env_id)[:ctx.remain_episode])) + ctx.remain_episode -= min(len(new_available_env_id), ctx.remain_episode) + obs = {env_id: obs[env_id] for env_id in ctx.ready_env_id} + + ctx.obs = obs + + # Policy forward. + inference_output = {} + actions = {} + for env_id in ctx.ready_env_id: + observations = obs[env_id] + inference_output[env_id] = {} + actions[env_id] = {} + for policy_id, policy_obs in observations.items(): + output = ctx.current_policies[policy_id].forward(policy_obs) + inference_output[env_id][policy_id] = output + actions[env_id][policy_id] = output['action'] + print(actions) + ctx.inference_output = inference_output + ctx.actions = actions + + return _battle_inferencer + + +from ding.envs import BaseEnvTimestep +def battle_rolloutor_for_distar(cfg: EasyDict, env: BaseEnvManager, transitions_list: List): + + def _battle_rolloutor(ctx: "BattleContext"): + timesteps = env.step(ctx.actions) + ctx.total_envstep_count += len(timesteps) + ctx.env_step += len(timesteps) + for env_id, timestep in timesteps.items(): + for policy_id in ctx.obs[env_id].keys(): + policy_timestep = BaseEnvTimestep( + obs = timestep.obs.get(policy_id) if timestep.obs.get(policy_id) is not None else None, + reward = timestep.reward[policy_id], + done = timestep.done, + info = {} + ) + transition = ctx.current_policies[policy_id].process_transition( + ctx.obs[env_id][policy_id], ctx.inference_output[env_id][policy_id], policy_timestep + ) + transition = EasyDict(transition) + transition.collect_train_iter = ttorch.as_tensor([ctx.train_iter]) + transitions_list[policy_id].append(env_id, transition) + if timestep.done: + ctx.current_policies[policy_id].reset([env_id]) + ctx.episode_info[policy_id].append(timestep.info[policy_id]) + + if timestep.done: + ctx.ready_env_id.remove(env_id) + ctx.env_episode += 1 + + return _battle_rolloutor diff --git a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py index faa1f3c396..95e12bd633 100644 --- a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py @@ -20,8 +20,10 @@ from typing import Dict, Any, List, Optional from collections import namedtuple from distar.ctools.utils import read_config -import treetensor.torch as ttorch from easydict import EasyDict +from ding.model import VAC + +from ding.framework.middleware.tests.mock_for_test import battle_inferencer_for_distar, battle_rolloutor_for_distar, DIStarMockPolicy class LearnMode: def __init__(self) -> None: @@ -71,14 +73,6 @@ def get_attribute(self, name: str) -> Any: return getattr(self, '_' + name) else: raise NotImplementedError - - -class MockActorDIstarPolicy(): - - def __init__(self): - - self.learn_mode = LearnMode() - self.collect_mode = CollectMode() def prepare_test(): @@ -96,19 +90,18 @@ def env_fn(): return env def policy_fn(): - policy = MockActorDIstarPolicy() + model = VAC(**cfg.policy.model) + policy = DIStarMockPolicy(cfg.policy, model=model) return policy return cfg, env_fn, policy_fn - @pytest.mark.unittest def test_league_actor(): cfg, env_fn, policy_fn = prepare_test() policy = policy_fn() with task.start(async_mode=True, ctx = BattleContext()): - league_actor = LeagueActor(cfg=cfg, env_fn=env_fn, policy_fn=policy_fn) def test_actor(): job = Job( @@ -156,17 +149,20 @@ def _test_actor(ctx): ) ) sleep(150) - # try: - # print(testcases) - # assert all(testcases.values()) - # finally: - # task.finish = True + try: + print(testcases) + assert all(testcases.values()) + finally: + task.finish = True return _test_actor - task.use(test_actor()) - task.use(league_actor) - task.run() + with patch("ding.framework.middleware.collector.battle_inferencer", battle_inferencer_for_distar): + with patch("ding.framework.middleware.collector.battle_rolloutor", battle_rolloutor_for_distar): + league_actor = LeagueActor(cfg=cfg, env_fn=env_fn, policy_fn=policy_fn) + task.use(test_actor()) + task.use(league_actor) + task.run() if __name__ == '__main__': test_league_actor() \ No newline at end of file From 2d050d3cd96fbe53d8391229e7f932e2dca2246b Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Mon, 13 Jun 2022 22:06:49 +0800 Subject: [PATCH 107/229] one_process test pass, multiple_process test failed because cannot pickle data --- ding/framework/middleware/league_actor.py | 6 ++-- .../middleware/tests/mock_for_test.py | 1 - .../test_league_actor_distar_one_process.py | 5 +-- .../middleware/tests/test_league_pipeline.py | 36 ++++++++++--------- 4 files changed, 26 insertions(+), 22 deletions(-) diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 0b4fa9d958..7ffa9ac7d8 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -246,9 +246,11 @@ def __call__(self, ctx: "BattleContext"): if not ctx.job.is_eval and len(ctx.trajectories_list[0]) > 0: ctx.trajectories = ctx.trajectories_list[0] ctx.trajectory_end_idx = ctx.trajectory_end_idx_list[0] - self._gae_estimator(ctx) - actor_data = ActorData(env_step=ctx.total_envstep_count, train_data=ctx.train_data) + # self._gae_estimator(ctx) + # actor_data = ActorData(env_step=ctx.total_envstep_count, train_data=ctx.train_data) + actor_data = ActorData(env_step=ctx.total_envstep_count, train_data=ctx.trajectories) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=ctx.job.launch_player), actor_data) + print('sending data') ctx.trajectories_list = [] ctx.trajectory_end_idx_list = [] diff --git a/ding/framework/middleware/tests/mock_for_test.py b/ding/framework/middleware/tests/mock_for_test.py index 4be1fd1f42..a08f85c906 100644 --- a/ding/framework/middleware/tests/mock_for_test.py +++ b/ding/framework/middleware/tests/mock_for_test.py @@ -239,7 +239,6 @@ def _battle_inferencer(ctx: "BattleContext"): output = ctx.current_policies[policy_id].forward(policy_obs) inference_output[env_id][policy_id] = output actions[env_id][policy_id] = output['action'] - print(actions) ctx.inference_output = inference_output ctx.actions = actions diff --git a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py index 95e12bd633..b10330baab 100644 --- a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py @@ -5,7 +5,7 @@ from ding.framework.context import BattleContext from ding.framework.middleware.league_learner import LearnerModel from ding.framework.middleware.tests.league_config import cfg -from ding.framework.middleware import LeagueActor +from ding.framework.middleware import LeagueActor, StepLeagueActor from ding.framework.middleware.functional import ActorData from ding.league.player import PlayerMeta from ding.framework.storage import FileStorage @@ -130,6 +130,7 @@ def on_actor_job(job_: Job): testcases["on_actor_job"] = True def on_actor_data(actor_data): + print('got actor_data') assert isinstance(actor_data, ActorData) testcases["on_actor_data"] = True @@ -159,7 +160,7 @@ def _test_actor(ctx): with patch("ding.framework.middleware.collector.battle_inferencer", battle_inferencer_for_distar): with patch("ding.framework.middleware.collector.battle_rolloutor", battle_rolloutor_for_distar): - league_actor = LeagueActor(cfg=cfg, env_fn=env_fn, policy_fn=policy_fn) + league_actor = StepLeagueActor(cfg=cfg, env_fn=env_fn, policy_fn=policy_fn) task.use(test_actor()) task.use(league_actor) task.run() diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index 473d895b82..502eff8dc6 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -5,7 +5,7 @@ from ding.envs import BaseEnvManager from ding.framework.context import BattleContext from ding.framework.middleware.tests.league_config import cfg -from ding.framework.middleware import LeagueActor, LeagueCoordinator +from ding.framework.middleware import LeagueActor, StepLeagueActor, LeagueCoordinator from ding.envs import BaseEnvManager from ding.model import VAC @@ -13,8 +13,9 @@ from ding.framework.middleware import LeagueCoordinator, LeagueActor, LeagueLearner from ding.framework.middleware.tests import cfg, MockLeague, MockLogger from dizoo.distar.envs.distar_env import DIStarEnv -from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy +from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, battle_inferencer_for_distar, battle_rolloutor_for_distar from distar.ctools.utils import read_config +from unittest.mock import patch import os N_ACTORS = 1 @@ -24,9 +25,8 @@ def prepare_test(): global cfg cfg = deepcopy(cfg) - env_cfg = read_config( - os.path.join(os.path.dirname(__file__), '../../../../dizoo/distar/envs/tests/test_distar_config.yaml') - ) + env_cfg = read_config('./test_distar_config.yaml') + env_cfg.env.map_name = 'KingsCove' def env_fn(): env = BaseEnvManager( @@ -48,19 +48,21 @@ def _main(): league = MockLeague(cfg.policy.other.league) with task.start(async_mode=True, ctx=BattleContext()): - print("node id:", task.router.node_id) - if task.router.node_id == 0: - task.use(LeagueCoordinator(league)) - elif task.router.node_id <= N_ACTORS: - task.use(LeagueActor(cfg, env_fn, policy_fn)) - else: - n_players = len(league.active_players_ids) - player = league.active_players[task.router.node_id % n_players] - learner = LeagueLearner(cfg, policy_fn, player) - learner._learner._tb_logger = MockLogger() - task.use(learner) + with patch("ding.framework.middleware.collector.battle_inferencer", battle_inferencer_for_distar): + with patch("ding.framework.middleware.collector.battle_rolloutor", battle_rolloutor_for_distar): + print("node id:", task.router.node_id) + if task.router.node_id == 0: + task.use(LeagueCoordinator(league)) + elif task.router.node_id <= N_ACTORS: + task.use(StepLeagueActor(cfg, env_fn, policy_fn)) + else: + n_players = len(league.active_players_ids) + player = league.active_players[task.router.node_id % n_players] + learner = LeagueLearner(cfg, policy_fn, player) + learner._learner._tb_logger = MockLogger() + task.use(learner) - task.run(max_step=300) + task.run(max_step=300) @pytest.mark.unittest From 82af279e4957020cc3bbc6c81aa2281937bdc171 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Mon, 13 Jun 2022 23:20:35 +0800 Subject: [PATCH 108/229] change config --- .../middleware/tests/mock_for_test.py | 30 ++++---- .../test_league_actor_distar_one_process.py | 1 - .../middleware/tests/test_league_pipeline.py | 1 - .../tests/test_league_pipeline_one_process.py | 72 +++++++++++++++++++ .../distar/envs/tests/test_distar_env_data.py | 1 - .../envs/tests/test_distar_env_time_space.py | 1 - .../tests/test_distar_env_with_manager.py | 1 - 7 files changed, 86 insertions(+), 21 deletions(-) create mode 100644 ding/framework/middleware/tests/test_league_pipeline_one_process.py diff --git a/ding/framework/middleware/tests/mock_for_test.py b/ding/framework/middleware/tests/mock_for_test.py index a08f85c906..1abd780500 100644 --- a/ding/framework/middleware/tests/mock_for_test.py +++ b/ding/framework/middleware/tests/mock_for_test.py @@ -177,25 +177,23 @@ def flush(*args): class DIStarMockPolicy(PPOPolicy): - def _mock_data(self, data): - print("Data: ", data) - mock_data = {} - for id, val in data.items(): - assert isinstance(val, dict) - assert 'obs' in val - assert 'next_obs' in val - assert 'action' in val - assert 'reward' in val - mock_data[id] = deepcopy(val) - mock_data[id]['obs'] = torch.rand(16) - mock_data[id]['next_obs'] = torch.rand(16) - mock_data[id]['action'] = torch.rand(4) - return mock_data, data + def _mock_data(self, data_list): + for data in data_list: + assert isinstance(data, dict) + assert 'obs' in data + assert 'next_obs' in data + assert 'action' in data + assert 'reward' in data + data['obs'] = torch.rand(16) + data['next_obs'] = torch.rand(16) + data['action'] = torch.rand(4) + return data_list def _forward_learn(self, data: Dict[str, Any]) -> Dict[str, Any]: print("Call forward_learn:") - mock_data, original_data = self._mock_data(data) - return super()._forward_learn(mock_data) + data = self._mock_data(data) + # return super()._forward_learn(data) + return def _forward_collect(self, data: Dict[int, Any]) -> Dict[int, Any]: print("Call forward_collect:") diff --git a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py index b10330baab..ffae695425 100644 --- a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py @@ -80,7 +80,6 @@ def prepare_test(): cfg = deepcopy(cfg) env_cfg = read_config('./test_distar_config.yaml') - env_cfg.env.map_name = 'KingsCove' def env_fn(): env = BaseEnvManager( diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index 502eff8dc6..8eb4e72032 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -26,7 +26,6 @@ def prepare_test(): global cfg cfg = deepcopy(cfg) env_cfg = read_config('./test_distar_config.yaml') - env_cfg.env.map_name = 'KingsCove' def env_fn(): env = BaseEnvManager( diff --git a/ding/framework/middleware/tests/test_league_pipeline_one_process.py b/ding/framework/middleware/tests/test_league_pipeline_one_process.py new file mode 100644 index 0000000000..64628e7387 --- /dev/null +++ b/ding/framework/middleware/tests/test_league_pipeline_one_process.py @@ -0,0 +1,72 @@ +from copy import deepcopy +from time import sleep +import pytest +from copy import deepcopy +from ding.envs import BaseEnvManager +from ding.framework.context import BattleContext +from ding.framework.middleware.tests.league_config import cfg +from ding.framework.middleware import LeagueActor, StepLeagueActor, LeagueCoordinator + +from ding.envs import BaseEnvManager +from ding.model import VAC +from ding.framework.task import task, Parallel +from ding.framework.middleware import LeagueCoordinator, LeagueActor, LeagueLearner +from ding.framework.middleware.tests import cfg, MockLeague, MockLogger +from dizoo.distar.envs.distar_env import DIStarEnv +from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, battle_inferencer_for_distar, battle_rolloutor_for_distar +from distar.ctools.utils import read_config +from unittest.mock import patch +import os + +def prepare_test(): + global cfg + cfg = deepcopy(cfg) + env_cfg = read_config('./test_distar_config.yaml') + + def env_fn(): + env = BaseEnvManager( + env_fn=[lambda: DIStarEnv(env_cfg) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager + ) + env.seed(cfg.seed) + return env + + def policy_fn(): + model = VAC(**cfg.policy.model) + policy = DIStarMockPolicy(cfg.policy, model=model) + return policy + + return cfg, env_fn, policy_fn + + +def _main(): + cfg, env_fn, policy_fn = prepare_test() + league = MockLeague(cfg.policy.other.league) + n_players = len(league.active_players_ids) + print(n_players) + + with task.start(async_mode=True, ctx=BattleContext()): + with patch("ding.framework.middleware.collector.battle_inferencer", battle_inferencer_for_distar): + with patch("ding.framework.middleware.collector.battle_rolloutor", battle_rolloutor_for_distar): + player_0 = league.active_players[0] + learner_0 = LeagueLearner(cfg, policy_fn, player_0) + learner_0._learner._tb_logger = MockLogger() + + player_1 = league.active_players[1] + learner_1 = LeagueLearner(cfg, policy_fn, player_1) + learner_1._learner._tb_logger = MockLogger() + + task.use(LeagueCoordinator(league)) + task.use(StepLeagueActor(cfg, env_fn, policy_fn)) + task.use(learner_0) + task.use(learner_1) + + task.run(max_step=300) + + +@pytest.mark.unittest +def test_league_actor(): + _main() + + +if __name__ == '__main__': + _main() diff --git a/dizoo/distar/envs/tests/test_distar_env_data.py b/dizoo/distar/envs/tests/test_distar_env_data.py index 6a9e932881..05c09d4002 100644 --- a/dizoo/distar/envs/tests/test_distar_env_data.py +++ b/dizoo/distar/envs/tests/test_distar_env_data.py @@ -15,7 +15,6 @@ def __init__(self): cfg = read_config('./test_distar_config.yaml') self._whole_cfg = cfg - self._whole_cfg.env.map_name = 'KingsCove' def _inference_loop(self, job={}): diff --git a/dizoo/distar/envs/tests/test_distar_env_time_space.py b/dizoo/distar/envs/tests/test_distar_env_time_space.py index d4be5613d4..9252c88597 100644 --- a/dizoo/distar/envs/tests/test_distar_env_time_space.py +++ b/dizoo/distar/envs/tests/test_distar_env_time_space.py @@ -14,7 +14,6 @@ def __init__(self): cfg = read_config('./test_distar_config.yaml') self._whole_cfg = cfg - self._whole_cfg.env.map_name = 'KingsCove' self._total_iters = 0 self._total_time = 0 self._total_space = 0 diff --git a/dizoo/distar/envs/tests/test_distar_env_with_manager.py b/dizoo/distar/envs/tests/test_distar_env_with_manager.py index ab8efdfa64..930d5e99f7 100644 --- a/dizoo/distar/envs/tests/test_distar_env_with_manager.py +++ b/dizoo/distar/envs/tests/test_distar_env_with_manager.py @@ -33,7 +33,6 @@ def __init__(self): cfg = read_config('./test_distar_config.yaml') self._whole_cfg = cfg - self._whole_cfg.env.map_name = 'KingsCove' def _inference_loop(self, job={}): From 1e78af8787d7caec9cfc21337db51a335d66bd79 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 14 Jun 2022 21:32:02 +0800 Subject: [PATCH 109/229] transform transitions so they could be sent, and write responding tests. change the finish condition of BattleStepCollector to env_episode. add env.close. And other modifications --- ding/framework/middleware/collector.py | 6 +- ding/framework/middleware/league_actor.py | 11 +- .../middleware/league_coordinator.py | 8 +- ding/framework/middleware/league_learner.py | 17 ++- .../middleware/tests/league_config.py | 3 +- .../middleware/tests/mock_for_test.py | 125 +++++++++++++++++- .../test_league_actor_distar_one_process.py | 14 +- .../middleware/tests/test_league_pipeline.py | 13 +- .../tests/test_league_pipeline_one_process.py | 12 +- dizoo/distar/envs/distar_env.py | 23 +++- 10 files changed, 196 insertions(+), 36 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index d53ab16a45..7824a53f8f 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -84,6 +84,7 @@ def __call__(self, ctx: "BattleContext") -> None: transitions.clear() if ctx.env_episode >= ctx.n_episode: ctx.job_finish = True + self.env.close() break @@ -152,14 +153,15 @@ def __call__(self, ctx: "BattleContext") -> None: self.total_envstep_count = ctx.total_envstep_count - if (self.n_rollout_samples > 0 and ctx.env_step - old >= self.n_rollout_samples) or ctx.env_step >= ctx.n_sample * ctx.unroll_len: + if (self.n_rollout_samples > 0 and ctx.env_step - old >= self.n_rollout_samples) or ctx.env_episode >= ctx.n_episode: for transitions in self._transitions_list: trajectories, trajectory_end_idx = transitions.to_trajectories() ctx.trajectories_list.append(trajectories) ctx.trajectory_end_idx_list.append(trajectory_end_idx) transitions.clear() - if ctx.env_step >= ctx.n_sample * ctx.unroll_len: + if ctx.env_episode >= ctx.n_episode: ctx.job_finish = True + self.env.close() break diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 7ffa9ac7d8..4179e11759 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -36,7 +36,7 @@ def _on_learner_model(self, learner_model: "LearnerModel"): """ If get newest learner model, put it inside model_queue. """ - print("receive model from learner") + print("Actor receive model from learner \n") with self.model_dict_lock: self.model_dict[learner_model.player_id] = learner_model @@ -150,12 +150,13 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.model_dict = {} self.model_dict_lock = Lock() - self._gae_estimator = gae_estimator(cfg, policy_fn().collect_mode) + # self._gae_estimator = gae_estimator(cfg, policy_fn().collect_mode) def _on_learner_model(self, learner_model: "LearnerModel"): """ If get newest learner model, put it inside model_queue. """ + print('Actor got model \n') with self.model_dict_lock: self.model_dict[learner_model.player_id] = learner_model @@ -221,7 +222,8 @@ def __call__(self, ctx: "BattleContext"): ctx.job = self._get_job() if ctx.job is None: return - + print('For actor, a job begin \n') + collector = self._get_collector(ctx.job.launch_player, len(ctx.job.players)) main_player, ctx.current_policies = self._get_current_policies(ctx.job) @@ -250,7 +252,7 @@ def __call__(self, ctx: "BattleContext"): # actor_data = ActorData(env_step=ctx.total_envstep_count, train_data=ctx.train_data) actor_data = ActorData(env_step=ctx.total_envstep_count, train_data=ctx.trajectories) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=ctx.job.launch_player), actor_data) - print('sending data') + print('Actor send data\n') ctx.trajectories_list = [] ctx.trajectory_end_idx_list = [] @@ -261,4 +263,5 @@ def __call__(self, ctx: "BattleContext"): ctx.job.result = [e['result'] for e in ctx.episode_info[0]] task.emit(EventEnum.ACTOR_FINISH_JOB, ctx.job) ctx.episode_info = [[] for _ in range(ctx.agent_num)] + print('Actor job finish, send job\n') break diff --git a/ding/framework/middleware/league_coordinator.py b/ding/framework/middleware/league_coordinator.py index 7880f9d47b..7d4be1cda3 100644 --- a/ding/framework/middleware/league_coordinator.py +++ b/ding/framework/middleware/league_coordinator.py @@ -25,6 +25,7 @@ def __init__(self, league: "BaseLeague") -> None: task.on(EventEnum.ACTOR_FINISH_JOB, self._on_actor_job) def _on_actor_greeting(self, actor_id): + print('coordinator recieve actor greeting\n') with self._lock: player_num = len(self.league.active_players_ids) player_id = self.league.active_players_ids[self._total_send_jobs % player_num] @@ -34,18 +35,21 @@ def _on_actor_greeting(self, actor_id): if job.job_no > 0 and job.job_no % self._eval_frequency == 0: job.is_eval = True job.actor_id = actor_id + print('coordinator emit job\n') task.emit(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=actor_id), job) def _on_learner_meta(self, player_meta: "PlayerMeta"): + print('coordinator recieve learner meta\n') print("on_learner_meta {}".format(player_meta)) self.league.update_active_player(player_meta) self.league.create_historical_player(player_meta) def _on_actor_job(self, job: "Job"): + print('coordinator recieve actor finished job\n') print("on_actor_job {}".format(job.launch_player)) # right self.league.update_payoff(job) def __call__(self, ctx: "Context") -> None: sleep(1) - logging.info("{} Step: {}".format(self.__class__, self._step)) - self._step += 1 + # logging.info("{} Step: {}".format(self.__class__, self._step)) + # self._step += 1 diff --git a/ding/framework/middleware/league_learner.py b/ding/framework/middleware/league_learner.py index eba816ce0c..52f98fc654 100644 --- a/ding/framework/middleware/league_learner.py +++ b/ding/framework/middleware/league_learner.py @@ -37,16 +37,20 @@ def __init__(self, cfg: dict, policy_fn: Callable, player: "ActivePlayer") -> No self._step = 0 def _on_actor_send_data(self, actor_data: "ActorData"): - print("receive data from actor!") + print("learner receive data from actor! \n") with self._lock: cfg = self.cfg for _ in range(cfg.policy.learn.update_per_collect): - print("train model") - self._learner.train(actor_data.train_data, actor_data.env_step) + pass + # print("train model") + # prinst(actor_data.train_data) + # self._learner.train(actor_data.train_data, actor_data.env_step) self.player.total_agent_step = self._learner.train_iter - print("save checkpoint") + # print("save checkpoint") checkpoint = self._save_checkpoint() if self.player.is_trained_enough() else None + + print('learner send player meta\n') task.emit( EventEnum.LEARNER_SEND_META, PlayerMeta(player_id=self.player_id, checkpoint=checkpoint, total_agent_step=self._learner.train_iter) @@ -56,6 +60,7 @@ def _on_actor_send_data(self, actor_data: "ActorData"): learner_model = LearnerModel( player_id=self.player_id, state_dict=self._learner.policy.state_dict(), train_iter=self._learner.train_iter ) + print('learner send model\n') task.emit(EventEnum.LEARNER_SEND_MODEL, learner_model) def _get_learner(self) -> BaseLearner: @@ -80,5 +85,5 @@ def _save_checkpoint(self) -> Optional[Storage]: def __call__(self, _: "Context") -> None: sleep(1) - logging.info("{} Step: {}".format(self.__class__, self._step)) - self._step += 1 + # logging.info("{} Step: {}".format(self.__class__, self._step)) + # self._step += 1 diff --git a/ding/framework/middleware/tests/league_config.py b/ding/framework/middleware/tests/league_config.py index 02eab837e9..3d1e6b5b1d 100644 --- a/ding/framework/middleware/tests/league_config.py +++ b/ding/framework/middleware/tests/league_config.py @@ -75,10 +75,9 @@ 'get_train_sample': True, 'cfg_type': 'BattleEpisodeSerialCollectorDict' }, - 'unroll_len': 1, 'discount_factor': 1.0, 'gae_lambda': 1.0, - 'n_episode': 128, + 'n_episode': 1, 'n_rollout_samples': 32, 'n_sample': 64, 'unroll_len': 2 diff --git a/ding/framework/middleware/tests/mock_for_test.py b/ding/framework/middleware/tests/mock_for_test.py index 1abd780500..1d13c37f84 100644 --- a/ding/framework/middleware/tests/mock_for_test.py +++ b/ding/framework/middleware/tests/mock_for_test.py @@ -194,19 +194,93 @@ def _forward_learn(self, data: Dict[str, Any]) -> Dict[str, Any]: data = self._mock_data(data) # return super()._forward_learn(data) return + + # def _forward_eval(self, data: Dict[int, Any]) -> Dict[int, Any]: + # data = {i: torch.rand(self.policy.model.obs_shape) for i in range(self.cfg.env.collector_env_num)} + # return super()._forward_eval(data) + + +from distar.agent.default.lib.features import Features +class DIstarCollectMode: + + def __init__(self) -> None: + self._cfg = EasyDict(dict( + collect = dict( + n_episode = 1 + ) + )) + self._feature = None + self._race = 'zerg' + + def load_state_dict(self, state_dict): + return + + def get_attribute(self, name: str) -> Any: + if hasattr(self, '_get_' + name): + return getattr(self, '_get_' + name)() + elif hasattr(self, '_' + name): + return getattr(self, '_' + name) + else: + raise NotImplementedError + + def reset(self, data_id: Optional[List[int]] = None) -> None: + pass + + def _pre_process(self, obs): + agent_obs = self._feature.transform_obs(obs['raw_obs'], padding_spatial=True) + self._game_info = agent_obs.pop('game_info') + self._game_step = self._game_info['game_loop'] - def _forward_collect(self, data: Dict[int, Any]) -> Dict[int, Any]: - print("Call forward_collect:") + last_selected_units = torch.zeros(agent_obs['entity_num'], dtype=torch.int8) + last_targeted_unit = torch.zeros(agent_obs['entity_num'], dtype=torch.int8) + + agent_obs['entity_info']['last_selected_units'] = last_selected_units + agent_obs['entity_info']['last_targeted_unit'] = last_targeted_unit + + self._observation = agent_obs + + + def forward(self, policy_obs: Dict[int, Any]) -> Dict[int, Any]: + # print("Call forward_collect:") + self._pre_process(policy_obs) return_data = {} - return_data['action'] = DIStarEnv.random_action(data) + return_data['action'] = DIStarEnv.random_action(policy_obs) return_data['logit'] = [1] return_data['value'] = [0] return return_data + + def process_transition(self, obs: Any, model_output: dict, timestep: namedtuple) -> dict: + next_obs = timestep.obs + reward = timestep.reward + done = timestep.done + agent_obs = self._observation + step_data = { + 'obs': { + 'map_name': 'KingsCove', + 'spatial_info': agent_obs['spatial_info'], + # 'spatial_info_ref': spatial_info_ref, + 'entity_info': agent_obs['entity_info'], + 'scalar_info': agent_obs['scalar_info'], + 'entity_num': agent_obs['entity_num'], + 'step': torch.tensor(self._game_step, dtype=torch.float) + }, + 'next_obs': {}, + 'logit': model_output['logit'], + 'action': model_output['action'], + 'value': model_output['value'], + # 'successive_logit': deepcopy(teacher_output['logit']), + 'reward': reward, + 'done': done + } + return step_data - # def _forward_eval(self, data: Dict[int, Any]) -> Dict[int, Any]: - # data = {i: torch.rand(self.policy.model.obs_shape) for i in range(self.cfg.env.collector_env_num)} - # return super()._forward_eval(data) + +class DIStarMockPolicyCollect: + + def __init__(self): + + self.collect_mode = DIstarCollectMode() def battle_inferencer_for_distar(cfg: EasyDict, env: BaseEnvManager): @@ -216,6 +290,13 @@ def _battle_inferencer(ctx: "BattleContext"): if env.closed: env.launch() + # TODO: Just for distar + races = ['zerg', 'zerg'] + for policy_index, p in enumerate(ctx.current_policies): + if p._feature is None: + p._feature = Features(env._envs[0].game_info[policy_index], env.ready_obs[0][policy_index]['raw_obs']) + p._race = races[policy_index] + # Get current env obs. obs = env.ready_obs # the role of remain_episode is to mask necessary rollouts, avoid processing unnecessary data @@ -273,3 +354,35 @@ def _battle_rolloutor(ctx: "BattleContext"): ctx.env_episode += 1 return _battle_rolloutor + + +from ding.envs import BaseEnvTimestep +def battle_rolloutor_for_distar_2(cfg: EasyDict, env: BaseEnvManager, transitions_list: List): + + def _battle_rolloutor(ctx: "BattleContext"): + timesteps = env.step(ctx.actions) + ctx.total_envstep_count += len(timesteps) + ctx.env_step += len(timesteps) + for env_id, timestep in timesteps.items(): + for policy_id, _ in timestep.obs.items(): + policy_timestep = BaseEnvTimestep( + obs = timestep.obs.get(policy_id), + reward = timestep.reward[policy_id], + done = timestep.done, + info = {} + ) + transition = ctx.current_policies[policy_id].process_transition( + None, None, policy_timestep + ) + transition = EasyDict(transition) + transition.collect_train_iter = ttorch.as_tensor([ctx.train_iter]) + transitions_list[policy_id].append(env_id, transition) + if timestep.done: + ctx.current_policies[policy_id].reset([env_id]) + ctx.episode_info[policy_id].append(timestep.info[policy_id]) + + if timestep.done: + ctx.ready_env_id.remove(env_id) + ctx.env_episode += 1 + + return _battle_rolloutor \ No newline at end of file diff --git a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py index ffae695425..a62285569a 100644 --- a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py @@ -23,7 +23,7 @@ from easydict import EasyDict from ding.model import VAC -from ding.framework.middleware.tests.mock_for_test import battle_inferencer_for_distar, battle_rolloutor_for_distar, DIStarMockPolicy +from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicyCollect, battle_inferencer_for_distar, battle_rolloutor_for_distar, DIStarMockPolicy class LearnMode: def __init__(self) -> None: @@ -92,13 +92,17 @@ def policy_fn(): model = VAC(**cfg.policy.model) policy = DIStarMockPolicy(cfg.policy, model=model) return policy + + def collect_policy_fn(): + policy = DIStarMockPolicyCollect() + return policy - return cfg, env_fn, policy_fn + return cfg, env_fn, policy_fn, collect_policy_fn @pytest.mark.unittest def test_league_actor(): - cfg, env_fn, policy_fn = prepare_test() + cfg, env_fn, policy_fn, collect_policy_fn = prepare_test() policy = policy_fn() with task.start(async_mode=True, ctx = BattleContext()): @@ -148,7 +152,7 @@ def _test_actor(ctx): player_id='main_player_default_0', state_dict=policy.learn_mode.state_dict(), train_iter=0 ) ) - sleep(150) + sleep(100) try: print(testcases) assert all(testcases.values()) @@ -159,7 +163,7 @@ def _test_actor(ctx): with patch("ding.framework.middleware.collector.battle_inferencer", battle_inferencer_for_distar): with patch("ding.framework.middleware.collector.battle_rolloutor", battle_rolloutor_for_distar): - league_actor = StepLeagueActor(cfg=cfg, env_fn=env_fn, policy_fn=policy_fn) + league_actor = StepLeagueActor(cfg=cfg, env_fn=env_fn, policy_fn=collect_policy_fn) task.use(test_actor()) task.use(league_actor) task.run() diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index 8eb4e72032..ffbc7f8fa8 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -13,7 +13,7 @@ from ding.framework.middleware import LeagueCoordinator, LeagueActor, LeagueLearner from ding.framework.middleware.tests import cfg, MockLeague, MockLogger from dizoo.distar.envs.distar_env import DIStarEnv -from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, battle_inferencer_for_distar, battle_rolloutor_for_distar +from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, DIStarMockPolicyCollect, battle_inferencer_for_distar, battle_rolloutor_for_distar from distar.ctools.utils import read_config from unittest.mock import patch import os @@ -39,11 +39,16 @@ def policy_fn(): policy = DIStarMockPolicy(cfg.policy, model=model) return policy - return cfg, env_fn, policy_fn + def collect_policy_fn(): + policy = DIStarMockPolicyCollect() + return policy + + return cfg, env_fn, policy_fn, collect_policy_fn + def _main(): - cfg, env_fn, policy_fn = prepare_test() + cfg, env_fn, policy_fn, collect_policy_fn = prepare_test() league = MockLeague(cfg.policy.other.league) with task.start(async_mode=True, ctx=BattleContext()): @@ -53,7 +58,7 @@ def _main(): if task.router.node_id == 0: task.use(LeagueCoordinator(league)) elif task.router.node_id <= N_ACTORS: - task.use(StepLeagueActor(cfg, env_fn, policy_fn)) + task.use(StepLeagueActor(cfg, env_fn, collect_policy_fn)) else: n_players = len(league.active_players_ids) player = league.active_players[task.router.node_id % n_players] diff --git a/ding/framework/middleware/tests/test_league_pipeline_one_process.py b/ding/framework/middleware/tests/test_league_pipeline_one_process.py index 64628e7387..9c741bb14b 100644 --- a/ding/framework/middleware/tests/test_league_pipeline_one_process.py +++ b/ding/framework/middleware/tests/test_league_pipeline_one_process.py @@ -13,7 +13,7 @@ from ding.framework.middleware import LeagueCoordinator, LeagueActor, LeagueLearner from ding.framework.middleware.tests import cfg, MockLeague, MockLogger from dizoo.distar.envs.distar_env import DIStarEnv -from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, battle_inferencer_for_distar, battle_rolloutor_for_distar +from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, DIStarMockPolicyCollect, battle_inferencer_for_distar, battle_rolloutor_for_distar from distar.ctools.utils import read_config from unittest.mock import patch import os @@ -34,12 +34,16 @@ def policy_fn(): model = VAC(**cfg.policy.model) policy = DIStarMockPolicy(cfg.policy, model=model) return policy + + def collect_policy_fn(): + policy = DIStarMockPolicyCollect() + return policy - return cfg, env_fn, policy_fn + return cfg, env_fn, policy_fn, collect_policy_fn def _main(): - cfg, env_fn, policy_fn = prepare_test() + cfg, env_fn, policy_fn, collect_policy_fn = prepare_test() league = MockLeague(cfg.policy.other.league) n_players = len(league.active_players_ids) print(n_players) @@ -56,7 +60,7 @@ def _main(): learner_1._learner._tb_logger = MockLogger() task.use(LeagueCoordinator(league)) - task.use(StepLeagueActor(cfg, env_fn, policy_fn)) + task.use(StepLeagueActor(cfg, env_fn, collect_policy_fn)) task.use(learner_0) task.use(learner_1) diff --git a/dizoo/distar/envs/distar_env.py b/dizoo/distar/envs/distar_env.py index 79b05fc97b..1a830c47c8 100644 --- a/dizoo/distar/envs/distar_env.py +++ b/dizoo/distar/envs/distar_env.py @@ -10,9 +10,14 @@ class DIStarEnv(SC2Env, BaseEnv): def __init__(self, cfg): super(DIStarEnv, self).__init__(cfg) + self._game_info = None + self._map_name = None def reset(self): observations, game_info, map_name = super(DIStarEnv,self).reset() + # print(game_info) + self.game_info = game_info + self.map_name = map_name return observations def close(self): @@ -24,7 +29,7 @@ def step(self, actions): next_observations, reward, done = super(DIStarEnv,self).step(actions) info = {} for policy_id in range(self._num_agents): - info[policy_id] = None + info[policy_id] = {'result': None} timestep = BaseEnvTimestep( obs = next_observations, reward = reward, @@ -35,6 +40,22 @@ def step(self, actions): def seed(self, seed, dynamic_seed=False): self._random_seed = seed + + @property + def game_info(self): + return self._game_info + + @game_info.setter + def game_info(self, new_game_info): + self._game_info = new_game_info + + @property + def map_name(self): + return self._map_name + + @map_name.setter + def map_name(self, new_map_name): + self._map_name = new_map_name @property def observation_space(self): From ece3a6456189d6717531489eb7451da77682a345 Mon Sep 17 00:00:00 2001 From: niuyazhe Date: Tue, 14 Jun 2022 22:04:41 +0800 Subject: [PATCH 110/229] feature(nyz): add distar policy learn part --- ding/rl_utils/__init__.py | 6 +- ding/rl_utils/steve.py | 74 ++++++ ding/rl_utils/test_steve.py | 42 +++ ding/rl_utils/tests/test_upgo.py | 7 +- ding/rl_utils/upgo.py | 43 ++- ding/rl_utils/vtrace.py | 28 +- ding/torch_utils/__init__.py | 2 +- ding/torch_utils/data_helper.py | 17 ++ dizoo/distar/model/model.py | 8 +- dizoo/distar/policy/distar_policy.py | 384 +++++++++++++++++++++++++++ dizoo/distar/policy/utils.py | 90 +++++++ 11 files changed, 656 insertions(+), 45 deletions(-) create mode 100644 ding/rl_utils/steve.py create mode 100644 ding/rl_utils/test_steve.py create mode 100644 dizoo/distar/policy/distar_policy.py create mode 100644 dizoo/distar/policy/utils.py diff --git a/ding/rl_utils/__init__.py b/ding/rl_utils/__init__.py index 16d0458365..1b0d61e708 100644 --- a/ding/rl_utils/__init__.py +++ b/ding/rl_utils/__init__.py @@ -11,11 +11,11 @@ nstep_return_data, nstep_return, iqn_nstep_td_data, iqn_nstep_td_error, qrdqn_nstep_td_data, qrdqn_nstep_td_error,\ q_nstep_sql_td_error, dqfd_nstep_td_error, dqfd_nstep_td_data, q_v_1step_td_error, q_v_1step_td_data,\ dqfd_nstep_td_error_with_rescale -from .vtrace import vtrace_loss, compute_importance_weights -from .upgo import upgo_loss +from .upgo import upgo_data, upgo_error from .adder import get_gae, get_gae_with_default_last_value, get_nstep_return_data, get_train_sample from .value_rescale import value_transform, value_inv_transform -from .vtrace import vtrace_data, vtrace_error +from .vtrace import vtrace_data, vtrace_error, vtrace_loss, vtrace_data_with_rho, vtrace_error_with_rho, \ + compute_importance_weights from .beta_function import beta_function_map from .retrace import compute_q_retraces from .acer import acer_policy_error, acer_value_error, acer_trust_region_update diff --git a/ding/rl_utils/steve.py b/ding/rl_utils/steve.py new file mode 100644 index 0000000000..23077bda63 --- /dev/null +++ b/ding/rl_utils/steve.py @@ -0,0 +1,74 @@ +from typing import List, Callable +import torch + + +def steve_target( + obs, reward, done, q_fn, rew_fn, policy_fn, transition_fn, done_fn, rollout_step, discount_factor, ensemble_num +) -> torch.Tensor: + """ + Shapes: + - obs (:obj:`torch.Tensor`): :math:`(B, N1)`, where N1 is obs shape + - reward (:obj:`torch.Tensor`): :math:`(B, )` + - done (:obj:`torch.Tensor`): :math:`(B, )` + - return_ (:obj:`torch.Tensor`): :math:`(B, )` + """ + # tile first data + ensemble_q_num, ensemble_r_num, ensemble_d_num = ensemble_num + obs = obs.unsqueeze(1).repeat(1, ensemble_q_num, 1) + reward = reward.unsqueeze(1).repeat(1, ensemble_r_num) + done = done.unsqueeze(1).repeat(1, ensemble_d_num) + + with torch.no_grad(): + device = reward.device + # real data + action = policy_fn(obs) + q_value = q_fn(obs, action) + q_list, r_list, d_list = [q_value], [reward], [done] + # imagination data + for i in range(rollout_step): + next_obs = transition_fn(obs, action) + reward = rew_fn(obs, action, next_obs) + done = done_fn(obs, action, next_obs) + obs = next_obs + action = policy_fn(obs) + q_value = q_fn(obs, action) + + q_list.append(q_value) + r_list.append(reward) + d_list.append(done) + + q_value = torch.stack(q_list, dim=1) # B, H, M + reward = torch.stack(r_list, dim=1) # B, H, N + done = torch.stack(d_list, dim=1) # B, H, L + + H = rollout_step + 1 + + time_factor = torch.full((1, H), discount_factor).to(device) ** torch.arange(float(H)) + upper_tri = torch.triu(torch.randn(H, H)).to(device) + reward_coeff = (upper_tri * time_factor).unsqueeze(0).unsqueeze(-1).unsqueeze(-1) # 1, H, H, 1, 1 + value_coeff = (time_factor ** discount_factor).unsqueeze(-1).unsqueeze(-1) # 1, H, 1, 1 + + # (B, 1, L) cat (B, H-1, L) + reward_done = torch.cat([torch.ones_like(done[:, 0]).unsqueeze(1), torch.cumprod(done[:, :-1], dim=1)], dim=1) + reward_done = reward_done.unsqueeze(1).unsqueeze(-2) + value_done = done.unsqueeze(-2) + + # (B, 1, H, N, 1) x (1, H, H, 1, 1) x (B, 1, H, 1, L) + reward = reward.unsqueeze(1).unsqueeze(-1) * reward_coeff * reward_done + # (B, H, N, L) + cum_reward = torch.sum(reward, dim=2) # sum in the second H + # (B, H, M, 1) x (1, H, 1, 1) x (B, H, 1, L) = B, H, M, L + q_value = q_value.unsqueeze(-1) * value_coeff * value_done + # (B, H, 1, N, L) + (B, H, M, 1, L) = B, H, M, N, L + target = cum_reward.unsqueeze(-3) + q_value.unsqueeze(-2) + + target = target.view(target.shape[0], H, -1) # B, H, MxNxL + target_mean = target.mean(-1) + target_var = target.var(-1) + target_confidence = 1. / (target_var + 1e-8) # B, H + target_confidence = torch.clamp(target_confidence, 0, 100) # for some special case + # norm + target_confidence /= target_confidence.sum(dim=1, keepdim=True) + + return_ = (target_mean * target_confidence).sum(dim=1) + return return_ diff --git a/ding/rl_utils/test_steve.py b/ding/rl_utils/test_steve.py new file mode 100644 index 0000000000..acfa74f7d0 --- /dev/null +++ b/ding/rl_utils/test_steve.py @@ -0,0 +1,42 @@ +import pytest +import torch +from .steve import steve_target + + +@pytest.mark.unittest +def test_steve_target(): + B = 2 + M, N, L = 3, 4, 5 + obs_tplus1 = torch.randn(B, 16) + reward_t = torch.randn(B, ) + done_t = torch.randint(0, 2, size=(B, )).float() + + def q_fn(obs, action): + return torch.randn(obs.shape[0], M) + + def rew_fn(obs, action, next_obs): + return torch.randn(obs.shape[0], N) + + def policy_fn(obs): + return torch.randn(obs.shape[0], ) + + def transition_fn(obs, action): + return torch.randn(obs.shape[0], L, obs.shape[1]) + + def done_fn(obs, action, next_obs): + return torch.randint(0, 2, size=(obs.shape[0], L)).float() + + return_ = steve_target( + obs_tplus1, + reward_t, + done_t, + q_fn, + rew_fn, + policy_fn, + transition_fn, + done_fn, + rollout_step=6, + discount_factor=0.99, + ensemble_num=(M, N, L) + ) + assert return_.shape == (B, ) diff --git a/ding/rl_utils/tests/test_upgo.py b/ding/rl_utils/tests/test_upgo.py index 5bd96d9c7e..075cfa2d54 100644 --- a/ding/rl_utils/tests/test_upgo.py +++ b/ding/rl_utils/tests/test_upgo.py @@ -1,6 +1,6 @@ import pytest import torch -from ding.rl_utils.upgo import upgo_loss, upgo_returns, tb_cross_entropy +from ding.rl_utils.upgo import upgo_data, upgo_error, upgo_returns, tb_cross_entropy @pytest.mark.unittest @@ -31,7 +31,10 @@ def test_upgo(): # upgo loss rhos = torch.randn(T, B) - loss = upgo_loss(logit, rhos, action, rewards, bootstrap_values) + dist = torch.distributions.Categorical(logits=logit) + log_prob = dist.log_prob(action) + data = upgo_data(log_prob, rhos, bootstrap_values, rewards, torch.ones_like(rewards)) + loss = upgo_error(data) assert logit.requires_grad assert bootstrap_values.requires_grad for t in [logit, bootstrap_values]: diff --git a/ding/rl_utils/upgo.py b/ding/rl_utils/upgo.py index 366d67ada4..ca333f475e 100644 --- a/ding/rl_utils/upgo.py +++ b/ding/rl_utils/upgo.py @@ -1,6 +1,6 @@ import torch import torch.nn.functional as F -from ding.hpc_rl import hpc_wrapper +from collections import namedtuple from .td import generalized_lambda_returns @@ -48,40 +48,29 @@ def upgo_returns(rewards: torch.Tensor, bootstrap_values: torch.Tensor) -> torch return generalized_lambda_returns(bootstrap_values, rewards, 1.0, lambdas) -@hpc_wrapper( - shape_fn=lambda args: args[0].shape, - namedtuple_data=True, - include_args=5, - include_kwargs=['target_output', 'rhos', 'action', 'rewards', 'bootstrap_values'] -) -def upgo_loss( - target_output: torch.Tensor, - rhos: torch.Tensor, - action: torch.Tensor, - rewards: torch.Tensor, - bootstrap_values: torch.Tensor, - mask=None -) -> torch.Tensor: - r""" +upgo_data = namedtuple('upgo_data', ['target_log_prob', 'rhos', 'bootstrap_values', 'rewards', 'weights']) + + +def upgo_error(data: namedtuple, ) -> torch.Tensor: + """ Overview: - Computing UPGO loss given constant gamma and lambda. There is no special handling for terminal state value, + Computing UPGO loss given constant gamma and lambda. There is no special handling for terminal state value, \ if the last state in trajectory is the terminal, just pass a 0 as bootstrap_terminal_value. Arguments: - - target_output (:obj:`torch.Tensor`): the output computed by the target policy network, \ + - target_log_prob (:obj:`torch.Tensor`): The output computed by the target policy network, \ of size [T_traj, batchsize, n_output] - - rhos (:obj:`torch.Tensor`): the importance sampling ratio, of size [T_traj, batchsize] - - action (:obj:`torch.Tensor`): the action taken, of size [T_traj, batchsize] - - rewards (:obj:`torch.Tensor`): the returns from time step 0 to T-1, of size [T_traj, batchsize] - - bootstrap_values (:obj:`torch.Tensor`): estimation of the state value at step 0 to T, \ + - rhos (:obj:`torch.Tensor`): The importance sampling ratio, of size [T_traj, batchsize] + - bootstrap_values (:obj:`torch.Tensor`): The estimation of the state value at step 0 to T, \ of size [T_traj+1, batchsize] + - rewards (:obj:`torch.Tensor`): The returns from time step 0 to T-1, of size [T_traj, batchsize] + - weights (:obj:`torch.Tensor`): Data weights per sample, of size [T_traj, batchsize]. Returns: - - loss (:obj:`torch.Tensor`): Computed importance sampled UPGO loss, averaged over the samples, of size [] + - loss (:obj:`torch.Tensor`): Computed importance sampled UPGO loss, averaged over the samples, 0-dim tensor. """ + target_log_prob, rhos, bootstrap_values, rewards, weights = data # discard the value at T as it should be considered in the next slice with torch.no_grad(): returns = upgo_returns(rewards, bootstrap_values) advantages = rhos * (returns - bootstrap_values[:-1]) - metric = tb_cross_entropy(target_output, action, mask) - assert (metric.shape == action.shape[:2]) - losses = advantages * metric - return -losses.mean() + loss = -advantages * target_log_prob * weights + return loss.mean() diff --git a/ding/rl_utils/vtrace.py b/ding/rl_utils/vtrace.py index b8c262e1a0..ef2761dbe0 100644 --- a/ding/rl_utils/vtrace.py +++ b/ding/rl_utils/vtrace.py @@ -69,13 +69,13 @@ def shape_fn_vtrace(args, kwargs): include_kwargs=['data', 'gamma', 'lambda_', 'rho_clip_ratio', 'c_clip_ratio', 'rho_pg_clip_ratio'] ) def vtrace_error( - data: namedtuple, - gamma: float = 0.99, - lambda_: float = 0.95, - rho_clip_ratio: float = 1.0, - c_clip_ratio: float = 1.0, - rho_pg_clip_ratio: float = 1.0 -): + data: namedtuple, + gamma: float = 0.99, + lambda_: float = 0.95, + rho_clip_ratio: float = 1.0, + c_clip_ratio: float = 1.0, + rho_pg_clip_ratio: float = 1.0 +) -> namedtuple: """ Overview: Implementation of vtrace(IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner\ @@ -124,3 +124,17 @@ def vtrace_error( value_loss = (F.mse_loss(value[:-1], return_, reduction='none') * weight).mean() entropy_loss = (dist_target.entropy() * weight).mean() return vtrace_loss(pg_loss, value_loss, entropy_loss) + + +vtrace_data_with_rho = namedtuple('vtrace_data_with_rho', ['target_log_prob', 'rho', 'value', 'reward', 'weight']) + + +def vtrace_error_with_rho(data: namedtuple, gamma: float = 0.99, lambda_: float = 0.95) -> torch.Tensor: + target_log_prob, rho, value, reward, weight = data + with torch.no_grad(): + return_ = vtrace_nstep_return(rho, rho, reward, value, gamma, lambda_) + # pg_rhos = torch.clamp(IS, max=rho_pg_clip_ratio) + return_t_plus_1 = torch.cat([return_[1:], value[-1:]], 0) + adv = vtrace_advantage(rho, reward, return_t_plus_1, value[:-1], gamma) + loss = -adv * target_log_prob * weight + return loss.mean() diff --git a/ding/torch_utils/__init__.py b/ding/torch_utils/__init__.py index fdc5eeed8d..b78d0f08b2 100644 --- a/ding/torch_utils/__init__.py +++ b/ding/torch_utils/__init__.py @@ -1,6 +1,6 @@ from .checkpoint_helper import build_checkpoint_helper, CountVar, auto_checkpoint from .data_helper import to_device, to_tensor, to_ndarray, to_list, to_dtype, same_shape, tensor_to_list, \ - build_log_buffer, CudaFetcher, get_tensor_data, unsqueeze, get_null_data, detach_grad + build_log_buffer, CudaFetcher, get_tensor_data, unsqueeze, get_null_data, detach_grad, flatten from .distribution import CategoricalPd, CategoricalPdPytorch from .metric import levenshtein_distance, hamming_distance from .network import * diff --git a/ding/torch_utils/data_helper.py b/ding/torch_utils/data_helper.py index a0dd8ba07b..e87e88c770 100644 --- a/ding/torch_utils/data_helper.py +++ b/ding/torch_utils/data_helper.py @@ -408,4 +408,21 @@ def detach_grad(data): data[k] = detach_grad(data[k]) elif isinstance(data, torch.Tensor): data = data.detach() + else: + raise TypeError("not support data type: {}".format(type(data))) return data + + +def flatten(data): + if isinstance(data, torch.Tensor): + return torch.flatten(data, start_dim=0, end_dim=1) # (1, (T+1) * B) + elif isinstance(data, dict): + new_data = {} + for k, val in data.items(): + new_data[k] = flatten(val) + return new_data + elif isinstance(data, Sequence): + new_data = [flatten(v) for v in data] + return new_data + else: + raise TypeError("not support data type: {}".format(type(data))) diff --git a/dizoo/distar/model/model.py b/dizoo/distar/model/model.py index f21a8d9863..01b8236bda 100644 --- a/dizoo/distar/model/model.py +++ b/dizoo/distar/model/model.py @@ -19,11 +19,9 @@ class Model(nn.Module): - def __init__(self, cfg={}, use_value_network=False, temperature=None): + def __init__(self, cfg={}, use_value_network=False): super(Model, self).__init__() self.whole_cfg = deep_merge_dicts(alphastar_model_default_config, cfg) - if temperature is not None: - self.whole_cfg.model.temperature = temperature self.cfg = self.whole_cfg.model self.encoder = Encoder(self.whole_cfg) self.policy = Policy(self.whole_cfg) @@ -104,7 +102,7 @@ def compute_teacher_logit( 'selected_units_num': selected_units_num } - def rl_learner_forward( + def rl_learn_forward( self, spatial_info, entity_info, scalar_info, entity_num, hidden_state, action_info, selected_units_num, behaviour_logp, teacher_logit, mask, reward, step, batch_size, unroll_len, **kwargs ): @@ -174,7 +172,7 @@ def rl_learner_forward( return outputs - def sl_train( + def sl_learn_forward( self, spatial_info, entity_info, scalar_info, entity_num, selected_units_num, traj_lens, hidden_state, action_info, **kwargs ): diff --git a/dizoo/distar/policy/distar_policy.py b/dizoo/distar/policy/distar_policy.py new file mode 100644 index 0000000000..7226be1745 --- /dev/null +++ b/dizoo/distar/policy/distar_policy.py @@ -0,0 +1,384 @@ +from typing import Dict +import os.path as osp +import torch +import torch.nn.functional as F +from torch.optim import Adam + +from ding.policy import Policy +from ding.torch_utils import to_device +from ding.rl_utils import td_lambda_data, td_lambda_error, vtrace_data_with_rho, vtrace_error_with_rho, \ + upgo_data, upgo_error +from ding.utils import EasyTimer +from dizoo.distar.model import Model +from .utils import collate_fn_learn + +EPS = 1e-9 + + +def entropy_error(target_policy_probs_dict, target_policy_log_probs_dict, mask, head_weights_dict): + total_entropy_loss = 0. + entropy_dict = {} + for head_type in ['action_type', 'queued', 'delay', 'selected_units', 'target_unit', 'target_location']: + ent = -target_policy_probs_dict[head_type] * target_policy_log_probs_dict[head_type] + if head_type == 'selected_units': + ent = ent.sum(dim=-1) / ( + EPS + torch.log(mask['selected_units_logits_mask'].float().sum(dim=-1) + 1).unsqueeze(-1) + ) # normalize + ent = (ent * mask['selected_units_mask']).sum(-1) + ent = ent.div(mask['selected_units_mask'].sum(-1) + EPS) + elif head_type == 'target_unit': + # normalize by unit + ent = ent.sum(dim=-1) / (EPS + torch.log(mask['target_units_logits_mask'].float().sum(dim=-1) + 1)) + else: + ent = ent.sum(dim=-1) / torch.log(torch.FloatTensor([ent.shape[-1]]).to(ent.device)) + if head_type not in ['action_type', 'delay']: + ent = ent * mask['actions_mask'][head_type] + entropy = ent.mean() + entropy_dict['entropy/' + head_type] = entropy.item() + total_entropy_loss += (-entropy * head_weights_dict[head_type]) + return total_entropy_loss, entropy_dict + + +def kl_error( + target_policy_log_probs_dict, teacher_policy_logits_dict, mask, game_steps, action_type_kl_steps, head_weights_dict +): + total_kl_loss = 0. + kl_loss_dict = {} + + for head_type in ['action_type', 'queued', 'delay', 'selected_units', 'target_unit', 'target_location']: + target_policy_log_probs = target_policy_log_probs_dict[head_type] + teacher_policy_logits = teacher_policy_logits_dict[head_type] + + teacher_policy_log_probs = F.log_softmax(teacher_policy_logits, dim=-1) + teacher_policy_probs = torch.exp(teacher_policy_log_probs) + kl = teacher_policy_probs * (teacher_policy_log_probs - target_policy_log_probs) + + kl = kl.sum(dim=-1) + if head_type == 'selected_units': + kl = (kl * mask['selected_units_mask']).sum(-1) + if head_type not in ['action_type', 'delay']: + kl = kl * mask['actions_mask'][head_type] + if head_type == 'action_type': + flag = game_steps < action_type_kl_steps + action_type_kl = kl * flag * mask['cum_action_mask'] + action_type_kl_loss = action_type_kl.mean() + kl_loss_dict['kl/extra_at'] = action_type_kl_loss.item() + kl_loss = kl.mean() + total_kl_loss += (kl_loss * head_weights_dict[head_type]) + kl_loss_dict['kl/' + head_type] = kl_loss.item() + return total_kl_loss, action_type_kl_loss, kl_loss_dict + + +class DIStarPolicy(Policy): + config = dict( + cuda=True, + multi_gpu=False, + learning_rate=1e-5, + model=dict(), + loss_weights=dict( + baseline=dict( + winloss=10.0, + build_order=0.0, + built_unit=0.0, + effect=0.0, + upgrade=0.0, + battle=0.0, + ), + vtrace=dict( + winloss=1.0, + build_order=0.0, + built_unit=0.0, + effect=0.0, + upgrade=0.0, + battle=0.0, + ), + upgo=dict(winloss=1.0, ), + kl=0.02, + action_type_kl=0.1, + entropy=0.0001, + ), + vtrace_head_weights=dict( + action_type=1.0, + delay=1.0, + select_unit_num_logits=1.0, + selected_units=0.01, + target_unit=1.0, + target_location=1.0, + ), + upgo_head_weights=dict( + action_type=1.0, + delay=1.0, + select_unit_num_logits=1.0, + selected_units=0.01, + target_unit=1.0, + target_location=1.0, + ), + entropy_head_weights=dict( + action_type=1.0, + delay=1.0, + select_unit_num_logits=1.0, + selected_units=0.01, + target_unit=1.0, + target_location=1.0, + ), + kl_head_weights=dict( + action_type=1.0, + delay=1.0, + select_unit_num_logits=1.0, + selected_units=0.01, + target_unit=1.0, + target_location=1.0, + ), + kl=dict(action_type_kl_steps=2400, ), + gammas=dict( + baseline=dict( + winloss=1.0, + build_order=1.0, + built_unit=1.0, + effect=1.0, + upgrade=1.0, + battle=0.997, + ), + pg=dict( + winloss=1.0, + build_order=1.0, + built_unit=1.0, + effect=1.0, + upgrade=1.0, + battle=0.997, + ), + ), + grad_clip=dict(threshold=1.0, ) + ) + + def _init_learn(self): + self.learn_model = Model(self._cfg.model, use_value_network=True) + self.head_types = ['action_type', 'delay', 'queued', 'target_unit', 'selected_units', 'target_location'] + # policy parameters + self.gammas = self._cfg.gammas + self.loss_weights = self._cfg.loss_weights + self.action_type_kl_steps = self._cfg.kl.action_type_kl_steps + self.vtrace_head_weights = self._cfg.vtrace_head_weights + self.upgo_head_weights = self._cfg.upgo_head_weights + self.entropy_head_weights = self._cfg.entropy_head_weights + self.kl_head_weights = self._cfg.kl_head_weights + + # optimizer + self.optimizer = Adam( + self.learn_model.parameters(), + lr=self._cfg.learning_rate, + betas=(0, 0.99), + eps=1e-5, + ) + # utils + self.timer = EasyTimer(cuda=self._cfg.cuda) + + def _forward_learn(self, inputs: Dict): + # =========== + # pre-process + # =========== + inputs = collate_fn_learn(inputs) + if self._cfg.cuda: + inputs = to_device(inputs) + + # ============= + # model forward + # ============= + # create loss show dict + loss_info_dict = {} + with self.timer: + model_output = self.learn_model.rl_learn_forward(**inputs) + loss_info_dict['model_forward_time'] = self.timer.value + + # =========== + # preparation + # =========== + target_policy_logits_dict = model_output['target_logit'] # shape (T,B) + baseline_values_dict = model_output['value'] # shape (T+1,B) + behaviour_action_log_probs_dict = model_output['action_log_prob'] # shape (T,B) + teacher_policy_logits_dict = model_output['teacher_logit'] # shape (T,B) + masks_dict = model_output['mask'] # shape (T,B) + actions_dict = model_output['action'] # shape (T,B) + rewards_dict = model_output['reward'] # shape (T,B) + game_steps = model_output['step'] # shape (T,B) target_action_log_prob + + flag = rewards_dict['winloss'][-1] == 0 + for filed in baseline_values_dict.keys(): + baseline_values_dict[filed][-1] *= flag + + # create preparation info dict + target_policy_probs_dict = {} + target_policy_log_probs_dict = {} + target_action_log_probs_dict = {} + clipped_rhos_dict = {} + + # ============================================================ + # get distribution info for behaviour policy and target policy + # ============================================================ + for head_type in self.head_types: + # take info from correspondent input dict + target_policy_logits = target_policy_logits_dict[head_type] + actions = actions_dict[head_type] + # compute target log_probs, probs(for entropy,kl), target_action_log_probs, log_rhos(for pg_loss, upgo_loss) + pi_target = torch.distributions.Categorical(logits=target_policy_logits) + target_policy_probs = pi_target.probs + target_policy_log_probs = pi_target.logits + target_action_log_probs = pi_target.log_prob(actions) + behaviour_action_log_probs = behaviour_action_log_probs_dict[head_type] + + with torch.no_grad(): + log_rhos = target_action_log_probs - behaviour_action_log_probs + if head_type == 'selected_units': + log_rhos *= masks_dict['selected_units_mask'] + log_rhos = log_rhos.sum(dim=-1) + rhos = torch.exp(log_rhos) + clipped_rhos = rhos.clamp_(max=1) + # save preparation results to correspondent dict + target_policy_probs_dict[head_type] = target_policy_probs + target_policy_log_probs_dict[head_type] = target_policy_log_probs + if head_type == 'selected_units': + target_action_log_probs.masked_fill_(~masks_dict['selected_units_mask'], 0) + target_action_log_probs = target_action_log_probs.sum(-1) + target_action_log_probs_dict[head_type] = target_action_log_probs + # log_rhos_dict[head_type] = log_rhos + clipped_rhos_dict[head_type] = clipped_rhos + + # ==================== + # vtrace loss + # ==================== + total_vtrace_loss = 0. + vtrace_loss_dict = {} + + for field, baseline in baseline_values_dict.items(): + baseline_value = baseline_values_dict[field] + reward = rewards_dict[field] + for head_type in self.head_types: + weight = self.vtrace_head_weights[head_type] + if head_type not in ['action_type', 'delay']: + weight = weight * masks_dict['actions_mask'][head_type] + if field in ['build_order', 'built_unit', 'effect']: + weight = weight * masks_dict[field + '_mask'] + + data_item = vtrace_data_with_rho( + target_action_log_probs_dict[head_type], clipped_rhos_dict[head_type], baseline_value, reward, + weight + ) + vtrace_loss_item = vtrace_error_with_rho(data_item, gamma=1.0, lambda_=1.0) + + vtrace_loss_dict['vtrace/' + field + '/' + head_type] = vtrace_loss_item.item() + total_vtrace_loss += self.loss_weights.vtrace[field] * self.vtrace_head_weights[head_type + ] * vtrace_loss_item + + loss_info_dict.update(vtrace_loss_dict) + + # =========== + # upgo loss + # =========== + upgo_loss_dict = {} + total_upgo_loss = 0. + for head_type in self.head_types: + weight = self.upgo_head_weights[head_type] + if head_type not in ['action_type', 'delay']: + weight = weight * masks_dict['actions_mask'][head_type] + + data_item = upgo_data( + target_action_log_probs_dict[head_type], clipped_rhos_dict[head_type], baseline_values_dict['winloss'], + rewards_dict['winloss'], weight + ) + upgo_loss_item = upgo_error(data_item) + + total_upgo_loss += upgo_loss_item + upgo_loss_dict['upgo/' + head_type] = upgo_loss_item.item() + total_upgo_loss *= self.loss_weights.upgo.winloss + loss_info_dict.update(upgo_loss_dict) + + # =========== + # critic loss + # =========== + total_critic_loss = 0. + # field is from ['winloss', 'build_order', 'built_unit', 'effect', 'upgrade', 'battle'] + for field, baseline in baseline_values_dict.items(): + reward = rewards_dict[field] + # Notice: in general, we need to include done when we consider discount factor, but in our implementation + # of alphastar, traj_data(with size equal to unroll-len) sent from actor comes from the same episode. + # If the game is draw, we don't consider it is actually done + if field in ['build_order', 'built_unit', 'effect']: + weight = masks_dict[[field + '_mask']] + else: + weight = None + + field_data = td_lambda_data(baseline, reward, weight) + critic_loss = td_lambda_error(baseline, reward, masks_dict, gamma=self.gammas.baseline[field]) + + total_critic_loss += self.loss_weights.baseline[field] * critic_loss + loss_info_dict['td' + field] = critic_loss.item() + loss_info_dict['reward/' + field] = reward.float().mean().item() + loss_info_dict['value/' + field] = baseline.mean().item() + loss_info_dict['reward/battle'] = rewards_dict['battle'].float().mean().item() + + # ============ + # entropy loss + # ============ + total_entropy_loss, entropy_dict = \ + entropy_error(target_policy_probs_dict, target_policy_log_probs_dict, masks_dict, + head_weights_dict=self.entropy_head_weights) + + total_entropy_loss *= self.loss_weights.entropy + loss_info_dict.update(entropy_dict) + + # ======= + # kl loss + # ======= + total_kl_loss, action_type_kl_loss, kl_loss_dict = \ + kl_error(target_policy_log_probs_dict, teacher_policy_logits_dict, masks_dict, game_steps, + action_type_kl_steps=self.action_type_kl_steps, head_weights_dict=self.kl_head_weights) + total_kl_loss *= self.loss_weights.kl + action_type_kl_loss *= self.loss_weights.action_type_kl + loss_info_dict.update(kl_loss_dict) + + # ====== + # update + # ====== + total_loss = ( + total_vtrace_loss + total_upgo_loss + total_critic_loss + total_entropy_loss + total_kl_loss + + action_type_kl_loss + ) + with self.timer: + self.optimizer.zero_grad() + total_loss.backward() + if self._cfg.multi_gpu: + self.sync_gradients() + gradient = torch.nn.utils.clip_grad_norm_(self.learn_model.parameters(), self._cfg.grad_clip.threshold, 2) + self.optimizer.step() + + loss_info_dict['backward_time'] = self.timer.value + loss_info_dict['total_loss'] = total_loss + loss_info_dict['gradient'] = gradient + return loss_info_dict + + def _monitor_var_learn(self): + ret = ['total_loss', 'kl/extra_at', 'gradient', 'backward_time', 'model_forward_time'] + for k1 in ['winloss', 'build_order', 'built_unit', 'effect', 'upgrade', 'battle', 'upgo', 'kl', 'entropy']: + for k2 in ['reward', 'value', 'td', 'action_type', 'delay', 'queued', 'selected_units', 'target_unit', + 'target_location']: + ret.append(k1 + '/' + k2) + return ret + + def _state_dict(self) -> Dict: + return { + 'model': self.learn_model.state_dict(), + 'optimizer': self.optimizer.state_dict(), + } + + def _load_state_dict_learn(self, _state_dict: Dict) -> None: + self.learn_model.load_state_dict(_state_dict['model']) + self.optimizer.load_state_dict(_state_dict['optimizer']) + + def _init_collect(self): + pass + + def _forward_collect(self, data): + pass + + _init_eval = _init_collect + _forward_eval = _forward_collect diff --git a/dizoo/distar/policy/utils.py b/dizoo/distar/policy/utils.py new file mode 100644 index 0000000000..48a4c6f0b3 --- /dev/null +++ b/dizoo/distar/policy/utils.py @@ -0,0 +1,90 @@ +import torch +from ding.torch_utils import flatten, sequence_mask +from ding.utils import default_collate +from dizoo.distar.envs import MAX_SELECTED_UNITS_NUM + +MASK_INF = -1e9 + + +def padding_entity_info(traj_data, max_entity_num): + traj_data.pop('map_name', None) + entity_padding_num = max_entity_num - len(traj_data['entity_info']['x']) + if 'entity_embeddings' in traj_data.keys(): + traj_data['entity_embeddings'] = torch.nn.functional.pad( + traj_data['entity_embeddings'], (0, 0, 0, entity_padding_num), 'constant', 0 + ) + + for k in traj_data['entity_info'].keys(): + traj_data['entity_info'][k] = torch.nn.functional.pad( + traj_data['entity_info'][k], (0, entity_padding_num), 'constant', 0 + ) + if 'action_info' in traj_data: + su_padding_num = MAX_SELECTED_UNITS_NUM - traj_data['teacher_logit']['selected_units'].shape[0] + + traj_data['mask']['selected_units_mask'] = sequence_mask( + traj_data['selected_units_num'].unsqueeze(dim=0), max_len=MAX_SELECTED_UNITS_NUM + ).squeeze(dim=0) + traj_data['action_info']['selected_units'] = torch.nn.functional.pad( + traj_data['action_info']['selected_units'], + (0, MAX_SELECTED_UNITS_NUM - traj_data['action_info']['selected_units'].shape[-1]), 'constant', 0 + ) + + traj_data['behaviour_logp']['selected_units'] = torch.nn.functional.pad( + traj_data['behaviour_logp']['selected_units'], ( + 0, + su_padding_num, + ), 'constant', MASK_INF + ) + + traj_data['teacher_logit']['selected_units'] = torch.nn.functional.pad( + traj_data['teacher_logit']['selected_units'], ( + 0, + entity_padding_num, + 0, + su_padding_num, + ), 'constant', MASK_INF + ) + traj_data['teacher_logit']['target_unit'] = torch.nn.functional.pad( + traj_data['teacher_logit']['target_unit'], (0, entity_padding_num), 'constant', MASK_INF + ) + + traj_data['mask']['selected_units_logits_mask'] = sequence_mask( + traj_data['entity_num'].unsqueeze(dim=0) + 1, max_len=max_entity_num + 1 + ).squeeze(dim=0) + traj_data['mask']['target_units_logits_mask'] = sequence_mask( + traj_data['entity_num'].unsqueeze(dim=0), max_len=max_entity_num + ).squeeze(dim=0) + + return traj_data + + +def collate_fn_learn(traj_batch): + # data list of list, with shape batch_size, unroll_len + # find max_entity_num in data_batch + max_entity_num = max( + [len(traj_data['entity_info']['x']) for traj_data_list in traj_batch for traj_data in traj_data_list] + ) + + # padding entity_info in observatin, target_unit, selected_units, mask + traj_batch = [ + [padding_entity_info(traj_data, max_entity_num) for traj_data in traj_data_list] + for traj_data_list in traj_batch + ] + + data = [default_collate(traj_data_list) for traj_data_list in traj_batch] + + batch_size = len(data) + unroll_len = len(data[0]['step']) + data = default_collate(data, dim=1) + + new_data = {} + for k, val in data.items(): + if k in ['spatial_info', 'entity_info', 'scalar_info', 'entity_num', 'entity_location', 'hidden_state', + 'value_feature']: + new_data[k] = flatten(val) + else: + new_data[k] = val + new_data['aux_type'] = batch_size + new_data['batch_size'] = batch_size + new_data['unroll_len'] = unroll_len + return new_data From e9e8ebb8203c301c5cd7751c8aa5a2affeed7164 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 14 Jun 2022 22:36:00 +0800 Subject: [PATCH 111/229] change format --- ding/framework/middleware/collector.py | 33 ++++---- ding/framework/middleware/league_actor.py | 36 +++++---- .../middleware/league_coordinator.py | 2 + .../middleware/tests/mock_for_test.py | 66 ++++------------ .../test_league_actor_distar_one_process.py | 26 +++--- .../middleware/tests/test_league_pipeline.py | 8 +- .../tests/test_league_pipeline_one_process.py | 14 ++-- dizoo/distar/envs/distar_env.py | 79 +++++++++++-------- .../tests/test_distar_env_with_manager.py | 16 ++-- 9 files changed, 131 insertions(+), 149 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 7824a53f8f..cfac1ff2ce 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -1,21 +1,19 @@ -from distutils.log import info from easydict import EasyDict -from ding import policy -from ding.policy import Policy, get_random_policy +from ding.policy import get_random_policy from ding.envs import BaseEnvManager from ding.framework import task -from .functional import inferencer, rolloutor, TransitionList, battle_rolloutor -from .functional import battle_inferencer, battle_rolloutor -from typing import Dict +from .functional import inferencer, rolloutor, TransitionList, battle_inferencer, battle_rolloutor +from typing import Dict, TYPE_CHECKING -# if TYPE_CHECKING: -from ding.framework import OnlineRLContext, BattleContext +if TYPE_CHECKING: + from ding.framework import OnlineRLContext, BattleContext class BattleEpisodeCollector: def __init__( - self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int, model_dict: Dict, all_policies: Dict, agent_num: int + self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int, model_dict: Dict, all_policies: Dict, + agent_num: int ): self.cfg = cfg self.end_flag = False @@ -78,7 +76,8 @@ def __call__(self, ctx: "BattleContext") -> None: self.total_envstep_count = ctx.total_envstep_count - if (self.n_rollout_samples > 0 and ctx.env_episode - old >= self.n_rollout_samples) or ctx.env_episode >= ctx.n_episode: + if (self.n_rollout_samples > 0 + and ctx.env_episode - old >= self.n_rollout_samples) or ctx.env_episode >= ctx.n_episode: for transitions in self._transitions_list: ctx.episodes.append(transitions.to_episodes()) transitions.clear() @@ -90,7 +89,10 @@ def __call__(self, ctx: "BattleContext") -> None: class BattleStepCollector: - def __init__(self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int, model_dict: Dict, all_policies: Dict, agent_num: int): + def __init__( + self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int, model_dict: Dict, all_policies: Dict, + agent_num: int + ): self.cfg = cfg self.end_flag = False # self._reset(env) @@ -117,9 +119,9 @@ def __del__(self) -> None: return self.end_flag = True self.env.close() - + def _update_policies(self, job) -> None: - job_player_id_list = [player.player_id for player in job.players] + job_player_id_list = [player.player_id for player in job.players] for player_id in job_player_id_list: if self.model_dict.get(player_id) is None: @@ -145,7 +147,7 @@ def __call__(self, ctx: "BattleContext") -> None: """ ctx.total_envstep_count = self.total_envstep_count old = ctx.env_step - + while True: self._update_policies(ctx.job) self._battle_inferencer(ctx) @@ -153,7 +155,8 @@ def __call__(self, ctx: "BattleContext") -> None: self.total_envstep_count = ctx.total_envstep_count - if (self.n_rollout_samples > 0 and ctx.env_step - old >= self.n_rollout_samples) or ctx.env_episode >= ctx.n_episode: + if (self.n_rollout_samples > 0 + and ctx.env_step - old >= self.n_rollout_samples) or ctx.env_episode >= ctx.n_episode: for transitions in self._transitions_list: trajectories, trajectory_end_idx = transitions.to_trajectories() ctx.trajectories_list.append(trajectories) diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 4179e11759..164eb424ab 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -1,19 +1,20 @@ from ding.framework import task, EventEnum import logging -from typing import Dict, Callable +from typing import TYPE_CHECKING, Dict, Callable -from easydict import EasyDict - -from ding.framework import BattleContext -from ding.league.v2.base_league import Job from ding.policy import Policy -from ding.framework.middleware.league_learner import LearnerModel -from ding.framework.middleware import BattleEpisodeCollector, BattleStepCollector, gae_estimator +from ding.framework.middleware import BattleEpisodeCollector, BattleStepCollector from ding.framework.middleware.functional import ActorData from ding.league.player import PlayerMeta from threading import Lock import queue +from easydict import EasyDict + +if TYPE_CHECKING: + from ding.league.v2.base_league import Job + from ding.framework import BattleContext + from ding.framework.middleware.league_learner import LearnerModel class LeagueActor: @@ -51,7 +52,11 @@ def _get_collector(self, player_id: str, agent_num: int): return self._collectors.get(player_id) cfg = self.cfg env = self.env_fn() - collector = task.wrap(BattleEpisodeCollector(cfg.policy.collect.collector, env, self.n_rollout_samples, self.model_dict, self.all_policies, agent_num)) + collector = task.wrap( + BattleEpisodeCollector( + cfg.policy.collect.collector, env, self.n_rollout_samples, self.model_dict, self.all_policies, agent_num + ) + ) self._collectors[player_id] = collector return collector @@ -101,7 +106,7 @@ def __call__(self, ctx: "BattleContext"): ctx.job = self._get_job() if ctx.job is None: return - + collector = self._get_collector(ctx.job.launch_player, len(ctx.job.players)) main_player, ctx.current_policies = self._get_current_policies(ctx.job) @@ -171,7 +176,11 @@ def _get_collector(self, player_id: str, agent_num: int): return self._collectors.get(player_id) cfg = self.cfg env = self.env_fn() - collector = task.wrap(BattleStepCollector(cfg.policy.collect.collector, env, self.n_rollout_samples, self.model_dict, self.all_policies, agent_num)) + collector = task.wrap( + BattleStepCollector( + cfg.policy.collect.collector, env, self.n_rollout_samples, self.model_dict, self.all_policies, agent_num + ) + ) self._collectors[player_id] = collector return collector @@ -195,8 +204,8 @@ def _get_job(self): job = self.job_queue.get(timeout=10) except queue.Empty: logging.warning("For actor_{}, no Job get from coordinator".format(task.router.node_id)) - - return job + + return job def _get_current_policies(self, job): current_policies = [] @@ -216,7 +225,6 @@ def _get_current_policies(self, job): return main_player, current_policies - def __call__(self, ctx: "BattleContext"): ctx.job = self._get_job() @@ -240,7 +248,7 @@ def __call__(self, ctx: "BattleContext"): ctx.train_iter = main_player.total_agent_step ctx.episode_info = [[] for _ in range(ctx.agent_num)] ctx.remain_episode = ctx.n_episode - ctx.n_sample = self.n_sample + ctx.n_sample = self.n_sample ctx.unroll_len = self.unroll_len while True: collector(ctx) diff --git a/ding/framework/middleware/league_coordinator.py b/ding/framework/middleware/league_coordinator.py index 7d4be1cda3..cbe3813e73 100644 --- a/ding/framework/middleware/league_coordinator.py +++ b/ding/framework/middleware/league_coordinator.py @@ -9,6 +9,8 @@ if TYPE_CHECKING: from ding.framework import Task, Context from ding.league.v2 import BaseLeague + from ding.league.player import PlayerMeta + from ding.league.v2.base_league import Job class LeagueCoordinator: diff --git a/ding/framework/middleware/tests/mock_for_test.py b/ding/framework/middleware/tests/mock_for_test.py index 1d13c37f84..420c548775 100644 --- a/ding/framework/middleware/tests/mock_for_test.py +++ b/ding/framework/middleware/tests/mock_for_test.py @@ -5,7 +5,6 @@ import treetensor.numpy as tnp from easydict import EasyDict from unittest.mock import Mock -from copy import deepcopy from ding.torch_utils import to_device from ding.league.player import PlayerMeta @@ -15,6 +14,8 @@ from dizoo.distar.envs.distar_env import DIStarEnv from ding.envs import BaseEnvManager import treetensor.torch as ttorch +from ding.envs import BaseEnvTimestep +from distar.agent.default.lib.features import Features if TYPE_CHECKING: from ding.framework import BattleContext @@ -194,27 +195,22 @@ def _forward_learn(self, data: Dict[str, Any]) -> Dict[str, Any]: data = self._mock_data(data) # return super()._forward_learn(data) return - + # def _forward_eval(self, data: Dict[int, Any]) -> Dict[int, Any]: # data = {i: torch.rand(self.policy.model.obs_shape) for i in range(self.cfg.env.collector_env_num)} # return super()._forward_eval(data) -from distar.agent.default.lib.features import Features class DIstarCollectMode: def __init__(self) -> None: - self._cfg = EasyDict(dict( - collect = dict( - n_episode = 1 - ) - )) + self._cfg = EasyDict(dict(collect=dict(n_episode=1))) self._feature = None self._race = 'zerg' - + def load_state_dict(self, state_dict): return - + def get_attribute(self, name: str) -> Any: if hasattr(self, '_get_' + name): return getattr(self, '_get_' + name)() @@ -239,7 +235,6 @@ def _pre_process(self, obs): self._observation = agent_obs - def forward(self, policy_obs: Dict[int, Any]) -> Dict[int, Any]: # print("Call forward_collect:") self._pre_process(policy_obs) @@ -249,7 +244,7 @@ def forward(self, policy_obs: Dict[int, Any]) -> Dict[int, Any]: return_data['value'] = [0] return return_data - + def process_transition(self, obs: Any, model_output: dict, timestep: namedtuple) -> dict: next_obs = timestep.obs reward = timestep.reward @@ -264,7 +259,7 @@ def process_transition(self, obs: Any, model_output: dict, timestep: namedtuple) 'scalar_info': agent_obs['scalar_info'], 'entity_num': agent_obs['entity_num'], 'step': torch.tensor(self._game_step, dtype=torch.float) - }, + }, 'next_obs': {}, 'logit': model_output['logit'], 'action': model_output['action'], @@ -289,14 +284,14 @@ def _battle_inferencer(ctx: "BattleContext"): if env.closed: env.launch() - + # TODO: Just for distar races = ['zerg', 'zerg'] for policy_index, p in enumerate(ctx.current_policies): if p._feature is None: p._feature = Features(env._envs[0].game_info[policy_index], env.ready_obs[0][policy_index]['raw_obs']) p._race = races[policy_index] - + # Get current env obs. obs = env.ready_obs # the role of remain_episode is to mask necessary rollouts, avoid processing unnecessary data @@ -324,7 +319,6 @@ def _battle_inferencer(ctx: "BattleContext"): return _battle_inferencer -from ding.envs import BaseEnvTimestep def battle_rolloutor_for_distar(cfg: EasyDict, env: BaseEnvManager, transitions_list: List): def _battle_rolloutor(ctx: "BattleContext"): @@ -334,10 +328,10 @@ def _battle_rolloutor(ctx: "BattleContext"): for env_id, timestep in timesteps.items(): for policy_id in ctx.obs[env_id].keys(): policy_timestep = BaseEnvTimestep( - obs = timestep.obs.get(policy_id) if timestep.obs.get(policy_id) is not None else None, - reward = timestep.reward[policy_id], - done = timestep.done, - info = {} + obs=timestep.obs.get(policy_id) if timestep.obs.get(policy_id) is not None else None, + reward=timestep.reward[policy_id], + done=timestep.done, + info={} ) transition = ctx.current_policies[policy_id].process_transition( ctx.obs[env_id][policy_id], ctx.inference_output[env_id][policy_id], policy_timestep @@ -354,35 +348,3 @@ def _battle_rolloutor(ctx: "BattleContext"): ctx.env_episode += 1 return _battle_rolloutor - - -from ding.envs import BaseEnvTimestep -def battle_rolloutor_for_distar_2(cfg: EasyDict, env: BaseEnvManager, transitions_list: List): - - def _battle_rolloutor(ctx: "BattleContext"): - timesteps = env.step(ctx.actions) - ctx.total_envstep_count += len(timesteps) - ctx.env_step += len(timesteps) - for env_id, timestep in timesteps.items(): - for policy_id, _ in timestep.obs.items(): - policy_timestep = BaseEnvTimestep( - obs = timestep.obs.get(policy_id), - reward = timestep.reward[policy_id], - done = timestep.done, - info = {} - ) - transition = ctx.current_policies[policy_id].process_transition( - None, None, policy_timestep - ) - transition = EasyDict(transition) - transition.collect_train_iter = ttorch.as_tensor([ctx.train_iter]) - transitions_list[policy_id].append(env_id, transition) - if timestep.done: - ctx.current_policies[policy_id].reset([env_id]) - ctx.episode_info[policy_id].append(timestep.info[policy_id]) - - if timestep.done: - ctx.ready_env_id.remove(env_id) - ctx.env_episode += 1 - - return _battle_rolloutor \ No newline at end of file diff --git a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py index a62285569a..6977630eb8 100644 --- a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py @@ -20,29 +20,28 @@ from typing import Dict, Any, List, Optional from collections import namedtuple from distar.ctools.utils import read_config -from easydict import EasyDict from ding.model import VAC -from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicyCollect, battle_inferencer_for_distar, battle_rolloutor_for_distar, DIStarMockPolicy +from ding.framework.middleware.tests import DIStarMockPolicyCollect, battle_inferencer_for_distar, battle_rolloutor_for_distar, DIStarMockPolicy + class LearnMode: + def __init__(self) -> None: pass def state_dict(self): return {} + class CollectMode: + def __init__(self) -> None: - self._cfg = EasyDict(dict( - collect = dict( - n_episode = 64 - ) - )) + self._cfg = EasyDict(dict(collect=dict(n_episode=64))) def load_state_dict(self, state_dict): return - + def forward(self, data: Dict): return_data = {} return_data['action'] = DIStarEnv.random_action(data) @@ -50,7 +49,7 @@ def forward(self, data: Dict): return_data['value'] = [0] return return_data - + def process_transition(self, obs: Any, model_output: dict, timestep: namedtuple) -> dict: transition = { 'obs': obs, @@ -62,10 +61,10 @@ def process_transition(self, obs: Any, model_output: dict, timestep: namedtuple) 'done': timestep.done, } return transition - + def reset(self, data_id: Optional[List[int]] = None) -> None: pass - + def get_attribute(self, name: str) -> Any: if hasattr(self, '_get_' + name): return getattr(self, '_get_' + name)() @@ -92,7 +91,7 @@ def policy_fn(): model = VAC(**cfg.policy.model) policy = DIStarMockPolicy(cfg.policy, model=model) return policy - + def collect_policy_fn(): policy = DIStarMockPolicyCollect() return policy @@ -104,7 +103,7 @@ def collect_policy_fn(): def test_league_actor(): cfg, env_fn, policy_fn, collect_policy_fn = prepare_test() policy = policy_fn() - with task.start(async_mode=True, ctx = BattleContext()): + with task.start(async_mode=True, ctx=BattleContext()): def test_actor(): job = Job( @@ -168,5 +167,6 @@ def _test_actor(ctx): task.use(league_actor) task.run() + if __name__ == '__main__': test_league_actor() \ No newline at end of file diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index ffbc7f8fa8..6f14c38463 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -1,22 +1,17 @@ from copy import deepcopy from time import sleep import pytest -from copy import deepcopy from ding.envs import BaseEnvManager from ding.framework.context import BattleContext -from ding.framework.middleware.tests.league_config import cfg -from ding.framework.middleware import LeagueActor, StepLeagueActor, LeagueCoordinator +from ding.framework.middleware import StepLeagueActor, LeagueCoordinator, LeagueLearner -from ding.envs import BaseEnvManager from ding.model import VAC from ding.framework.task import task, Parallel -from ding.framework.middleware import LeagueCoordinator, LeagueActor, LeagueLearner from ding.framework.middleware.tests import cfg, MockLeague, MockLogger from dizoo.distar.envs.distar_env import DIStarEnv from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, DIStarMockPolicyCollect, battle_inferencer_for_distar, battle_rolloutor_for_distar from distar.ctools.utils import read_config from unittest.mock import patch -import os N_ACTORS = 1 N_LEARNERS = 1 @@ -46,7 +41,6 @@ def collect_policy_fn(): return cfg, env_fn, policy_fn, collect_policy_fn - def _main(): cfg, env_fn, policy_fn, collect_policy_fn = prepare_test() league = MockLeague(cfg.policy.other.league) diff --git a/ding/framework/middleware/tests/test_league_pipeline_one_process.py b/ding/framework/middleware/tests/test_league_pipeline_one_process.py index 9c741bb14b..8c217b0578 100644 --- a/ding/framework/middleware/tests/test_league_pipeline_one_process.py +++ b/ding/framework/middleware/tests/test_league_pipeline_one_process.py @@ -1,23 +1,19 @@ from copy import deepcopy -from time import sleep import pytest -from copy import deepcopy from ding.envs import BaseEnvManager from ding.framework.context import BattleContext -from ding.framework.middleware.tests.league_config import cfg -from ding.framework.middleware import LeagueActor, StepLeagueActor, LeagueCoordinator +from ding.framework.middleware import StepLeagueActor, LeagueCoordinator, LeagueLearner -from ding.envs import BaseEnvManager from ding.model import VAC -from ding.framework.task import task, Parallel -from ding.framework.middleware import LeagueCoordinator, LeagueActor, LeagueLearner +from ding.framework.task import task from ding.framework.middleware.tests import cfg, MockLeague, MockLogger from dizoo.distar.envs.distar_env import DIStarEnv -from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, DIStarMockPolicyCollect, battle_inferencer_for_distar, battle_rolloutor_for_distar +from ding.framework.middleware.tests import DIStarMockPolicy, DIStarMockPolicyCollect, battle_inferencer_for_distar, battle_rolloutor_for_distar from distar.ctools.utils import read_config from unittest.mock import patch import os + def prepare_test(): global cfg cfg = deepcopy(cfg) @@ -34,7 +30,7 @@ def policy_fn(): model = VAC(**cfg.policy.model) policy = DIStarMockPolicy(cfg.policy, model=model) return policy - + def collect_policy_fn(): policy = DIStarMockPolicyCollect() return policy diff --git a/dizoo/distar/envs/distar_env.py b/dizoo/distar/envs/distar_env.py index 1a830c47c8..f34ee527b1 100644 --- a/dizoo/distar/envs/distar_env.py +++ b/dizoo/distar/envs/distar_env.py @@ -6,6 +6,7 @@ import torch import random + class DIStarEnv(SC2Env, BaseEnv): def __init__(self, cfg): @@ -14,28 +15,23 @@ def __init__(self, cfg): self._map_name = None def reset(self): - observations, game_info, map_name = super(DIStarEnv,self).reset() + observations, game_info, map_name = super(DIStarEnv, self).reset() # print(game_info) self.game_info = game_info self.map_name = map_name return observations def close(self): - super(DIStarEnv,self).close() + super(DIStarEnv, self).close() def step(self, actions): # In DI-engine, the return of BaseEnv.step is ('obs', 'reward', 'done', 'info') # Here in DI-star, the return is ({'raw_obs': self._obs[agent_idx], 'opponent_obs': opponent_obs, 'action_result': self._action_result[agent_idx]}, reward, episode_complete) - next_observations, reward, done = super(DIStarEnv,self).step(actions) + next_observations, reward, done = super(DIStarEnv, self).step(actions) info = {} for policy_id in range(self._num_agents): info[policy_id] = {'result': None} - timestep = BaseEnvTimestep( - obs = next_observations, - reward = reward, - done = done, - info = info - ) + timestep = BaseEnvTimestep(obs=next_observations, reward=reward, done=done, info=info) return timestep def seed(self, seed, dynamic_seed=False): @@ -44,19 +40,19 @@ def seed(self, seed, dynamic_seed=False): @property def game_info(self): return self._game_info - + @game_info.setter def game_info(self, new_game_info): self._game_info = new_game_info - + @property def map_name(self): return self._map_name - + @map_name.setter def map_name(self, new_map_name): self._map_name = new_map_name - + @property def observation_space(self): #TODO @@ -66,25 +62,34 @@ def observation_space(self): def action_space(self): #TODO pass - + @classmethod def random_action(cls, obs): raw = obs['raw_obs'].observation.raw_data all_unit_types = set() self_unit_types = set() - + for u in raw.units: # Here we select the units except “buildings that are in building progress” for simplification if u.build_progress == 1: all_unit_types.add(u.unit_type) if u.alliance == 1: self_unit_types.add(u.unit_type) - + avail_actions = [ - {0: {'exist_selected_types':[], 'exist_target_types':[]}}, - {168:{'exist_selected_types':[], 'exist_target_types':[]}} - ] # no_op and raw_move_camera don't have seleted_units + { + 0: { + 'exist_selected_types': [], + 'exist_target_types': [] + } + }, { + 168: { + 'exist_selected_types': [], + 'exist_target_types': [] + } + } + ] # no_op and raw_move_camera don't have seleted_units for action_id, action in ACTIONS_STAT.items(): exist_selected_types = list(self_unit_types.intersection(set(action['selected_type']))) @@ -95,39 +100,46 @@ def random_action(cls, obs): continue if len(exist_selected_types) > 0: - avail_actions.append({action_id: {'exist_selected_types':exist_selected_types, 'exist_target_types':exist_target_types}}) - + avail_actions.append( + { + action_id: { + 'exist_selected_types': exist_selected_types, + 'exist_target_types': exist_target_types + } + } + ) + current_action = random.choice(avail_actions) func_id, exist_types = current_action.popitem() if func_id not in [0, 168]: - correspond_selected_units = [u.tag for u in raw.units if u.unit_type in exist_types['exist_selected_types'] and u.build_progress == 1] - correspond_targets = [u.tag for u in raw.units if u.unit_type in exist_types['exist_target_types'] and u.build_progress == 1] + correspond_selected_units = [ + u.tag for u in raw.units if u.unit_type in exist_types['exist_selected_types'] and u.build_progress == 1 + ] + correspond_targets = [ + u.tag for u in raw.units if u.unit_type in exist_types['exist_target_types'] and u.build_progress == 1 + ] num_selected_unit = random.randint(0, min(MAX_SELECTED_UNITS_NUM, len(correspond_selected_units))) - unit_tags = random.sample(correspond_selected_units, num_selected_unit) + unit_tags = random.sample(correspond_selected_units, num_selected_unit) target_unit_tag = random.choice(correspond_targets) if len(correspond_targets) > 0 else None else: unit_tags = [] target_unit_tag = None - + data = { - 'func_id': func_id, + 'func_id': func_id, 'skip_steps': random.randint(0, MAX_DELAY - 1), # 'skip_steps': 8, 'queued': random.randint(0, 1), - 'unit_tags': unit_tags, - 'target_unit_tag': target_unit_tag, - 'location': ( - random.randint(0, SPATIAL_SIZE[0] - 1), - random.randint(0, SPATIAL_SIZE[1] - 1) - ) + 'unit_tags': unit_tags, + 'target_unit_tag': target_unit_tag, + 'location': (random.randint(0, SPATIAL_SIZE[0] - 1), random.randint(0, SPATIAL_SIZE[1] - 1)) } return [data] - @property def reward_space(self): @@ -137,6 +149,7 @@ def reward_space(self): def __repr__(self): return "DI-engine DI-star Env" + # if __name__ == '__main__': # no_target_unit_actions = sorted([action['func_id'] for action in ACTIONS if action['target_unit'] == False]) # no_target_unit_actions_dict = sorted([action_id for action_id, action in ACTIONS_STAT.items() if len(action['target_type']) == 0]) diff --git a/dizoo/distar/envs/tests/test_distar_env_with_manager.py b/dizoo/distar/envs/tests/test_distar_env_with_manager.py index 930d5e99f7..6741db2eda 100644 --- a/dizoo/distar/envs/tests/test_distar_env_with_manager.py +++ b/dizoo/distar/envs/tests/test_distar_env_with_manager.py @@ -28,7 +28,9 @@ ENV_NUMBER = 2 + class TestDIstarEnv: + def __init__(self): cfg = read_config('./test_distar_config.yaml') @@ -60,17 +62,16 @@ def _inference_loop(self, job={}): actions[env_id][player_index] = DIStarEnv.random_action(player_obs) timesteps = self._env.step(actions) print(actions) - + except Exception as e: print('[EPISODE LOOP ERROR]', e, flush=True) print(''.join(traceback.format_tb(e.__traceback__)), flush=True) self._env.close() - + self._env.close() -if __name__ == '__main__': - ## main +if __name__ == '__main__': if os.path.exists(r'C:\Program Files (x86)\StarCraft II'): sc2path = r'C:\Program Files (x86)\StarCraft II' elif os.path.exists('/Applications/StarCraft II'): @@ -80,8 +81,11 @@ def _inference_loop(self, job={}): sc2path = os.environ['SC2PATH'] assert os.path.exists(sc2path), 'SC2PATH: {} does not exist!'.format(sc2path) if not os.path.exists(os.path.join(sc2path, 'Maps/Ladder2019Season2')): - shutil.copytree(os.path.join(os.path.dirname(__file__), '../envs/maps/Ladder2019Season2'), os.path.join(sc2path, 'Maps/Ladder2019Season2')) + shutil.copytree( + os.path.join(os.path.dirname(__file__), '../envs/maps/Ladder2019Season2'), + os.path.join(sc2path, 'Maps/Ladder2019Season2') + ) - ## actor_run + # actor_run actor = TestDIstarEnv() actor._inference_loop() \ No newline at end of file From ffe8f7c63a921062b168dfe048b39230acb375f2 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 15 Jun 2022 17:05:54 +0800 Subject: [PATCH 112/229] change print to show node_id; change format --- ding/framework/middleware/collector.py | 4 ++-- ding/framework/middleware/league_actor.py | 13 +++++++------ ding/framework/middleware/league_coordinator.py | 13 ++++++++----- ding/framework/middleware/league_learner.py | 13 ++++++++----- .../middleware/tests/test_league_pipeline.py | 6 +++--- 5 files changed, 28 insertions(+), 21 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index cfac1ff2ce..20e2f7e823 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -82,8 +82,8 @@ def __call__(self, ctx: "BattleContext") -> None: ctx.episodes.append(transitions.to_episodes()) transitions.clear() if ctx.env_episode >= ctx.n_episode: - ctx.job_finish = True self.env.close() + ctx.job_finish = True break @@ -163,8 +163,8 @@ def __call__(self, ctx: "BattleContext") -> None: ctx.trajectory_end_idx_list.append(trajectory_end_idx) transitions.clear() if ctx.env_episode >= ctx.n_episode: - ctx.job_finish = True self.env.close() + ctx.job_finish = True break diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 164eb424ab..b630b5abaa 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -37,7 +37,7 @@ def _on_learner_model(self, learner_model: "LearnerModel"): """ If get newest learner model, put it inside model_queue. """ - print("Actor receive model from learner \n") + print("Actor {} receive model from learner \n".format(task.router.node_id), flush=True) with self.model_dict_lock: self.model_dict[learner_model.player_id] = learner_model @@ -161,7 +161,7 @@ def _on_learner_model(self, learner_model: "LearnerModel"): """ If get newest learner model, put it inside model_queue. """ - print('Actor got model \n') + print('Actor {} recieved model \n'.format(task.router.node_id), flush=True) with self.model_dict_lock: self.model_dict[learner_model.player_id] = learner_model @@ -203,7 +203,7 @@ def _get_job(self): try: job = self.job_queue.get(timeout=10) except queue.Empty: - logging.warning("For actor_{}, no Job get from coordinator".format(task.router.node_id)) + logging.warning("For actor {}, no Job get from coordinator".format(task.router.node_id)) return job @@ -230,7 +230,7 @@ def __call__(self, ctx: "BattleContext"): ctx.job = self._get_job() if ctx.job is None: return - print('For actor, a job begin \n') + print('For actor {}, a job begin \n'.format(task.router.node_id), flush=True) collector = self._get_collector(ctx.job.launch_player, len(ctx.job.players)) @@ -256,11 +256,12 @@ def __call__(self, ctx: "BattleContext"): if not ctx.job.is_eval and len(ctx.trajectories_list[0]) > 0: ctx.trajectories = ctx.trajectories_list[0] ctx.trajectory_end_idx = ctx.trajectory_end_idx_list[0] + print('actor {}, len trajectories {}'.format(task.router.node_id, len(ctx.trajectories)), flush=True) # self._gae_estimator(ctx) # actor_data = ActorData(env_step=ctx.total_envstep_count, train_data=ctx.train_data) actor_data = ActorData(env_step=ctx.total_envstep_count, train_data=ctx.trajectories) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=ctx.job.launch_player), actor_data) - print('Actor send data\n') + print('Actor {} send data\n'.format(task.router.node_id), flush=True) ctx.trajectories_list = [] ctx.trajectory_end_idx_list = [] @@ -271,5 +272,5 @@ def __call__(self, ctx: "BattleContext"): ctx.job.result = [e['result'] for e in ctx.episode_info[0]] task.emit(EventEnum.ACTOR_FINISH_JOB, ctx.job) ctx.episode_info = [[] for _ in range(ctx.agent_num)] - print('Actor job finish, send job\n') + print('Actor {} job finish, send job\n'.format(task.router.node_id), flush=True) break diff --git a/ding/framework/middleware/league_coordinator.py b/ding/framework/middleware/league_coordinator.py index cbe3813e73..43300d8711 100644 --- a/ding/framework/middleware/league_coordinator.py +++ b/ding/framework/middleware/league_coordinator.py @@ -27,7 +27,7 @@ def __init__(self, league: "BaseLeague") -> None: task.on(EventEnum.ACTOR_FINISH_JOB, self._on_actor_job) def _on_actor_greeting(self, actor_id): - print('coordinator recieve actor greeting\n') + print('coordinator recieve actor greeting\n', flush=True) with self._lock: player_num = len(self.league.active_players_ids) player_id = self.league.active_players_ids[self._total_send_jobs % player_num] @@ -37,20 +37,23 @@ def _on_actor_greeting(self, actor_id): if job.job_no > 0 and job.job_no % self._eval_frequency == 0: job.is_eval = True job.actor_id = actor_id - print('coordinator emit job\n') + print('coordinator emit job\n', flush=True) task.emit(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=actor_id), job) def _on_learner_meta(self, player_meta: "PlayerMeta"): - print('coordinator recieve learner meta\n') - print("on_learner_meta {}".format(player_meta)) + print('coordinator recieve learner meta\n', flush=True) + # print("on_learner_meta {}".format(player_meta)) self.league.update_active_player(player_meta) self.league.create_historical_player(player_meta) def _on_actor_job(self, job: "Job"): - print('coordinator recieve actor finished job\n') + print('coordinator recieve actor finished job\n', flush=True) print("on_actor_job {}".format(job.launch_player)) # right self.league.update_payoff(job) + def __del__(self): + print('task finished, coordinator closed', flush=True) + def __call__(self, ctx: "Context") -> None: sleep(1) # logging.info("{} Step: {}".format(self.__class__, self._step)) diff --git a/ding/framework/middleware/league_learner.py b/ding/framework/middleware/league_learner.py index 52f98fc654..af7ec59039 100644 --- a/ding/framework/middleware/league_learner.py +++ b/ding/framework/middleware/league_learner.py @@ -37,30 +37,30 @@ def __init__(self, cfg: dict, policy_fn: Callable, player: "ActivePlayer") -> No self._step = 0 def _on_actor_send_data(self, actor_data: "ActorData"): - print("learner receive data from actor! \n") + print("learner receive data from actor! \n", flush=True) with self._lock: cfg = self.cfg for _ in range(cfg.policy.learn.update_per_collect): pass # print("train model") - # prinst(actor_data.train_data) + # print(actor_data.train_data) # self._learner.train(actor_data.train_data, actor_data.env_step) self.player.total_agent_step = self._learner.train_iter # print("save checkpoint") checkpoint = self._save_checkpoint() if self.player.is_trained_enough() else None - print('learner send player meta\n') + print('learner send player meta\n', flush=True) task.emit( EventEnum.LEARNER_SEND_META, PlayerMeta(player_id=self.player_id, checkpoint=checkpoint, total_agent_step=self._learner.train_iter) ) - print("pack model") + # print("pack model") learner_model = LearnerModel( player_id=self.player_id, state_dict=self._learner.policy.state_dict(), train_iter=self._learner.train_iter ) - print('learner send model\n') + print('learner send model\n', flush=True) task.emit(EventEnum.LEARNER_SEND_MODEL, learner_model) def _get_learner(self) -> BaseLearner: @@ -83,6 +83,9 @@ def _save_checkpoint(self) -> Optional[Storage]: storage.save(self._learner.policy.state_dict()) return storage + def __del__(self): + print('task finished, learner closed', flush=True) + def __call__(self, _: "Context") -> None: sleep(1) # logging.info("{} Step: {}".format(self.__class__, self._step)) diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index 6f14c38463..2afe43e56d 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -13,8 +13,8 @@ from distar.ctools.utils import read_config from unittest.mock import patch -N_ACTORS = 1 -N_LEARNERS = 1 +N_ACTORS = 2 +N_LEARNERS = 2 def prepare_test(): @@ -60,7 +60,7 @@ def _main(): learner._learner._tb_logger = MockLogger() task.use(learner) - task.run(max_step=300) + task.run() @pytest.mark.unittest From b6c24b76a572631b9a72ee7d7170b4078b1265a5 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 15 Jun 2022 17:15:58 +0800 Subject: [PATCH 113/229] handle exception during reset SC2 env --- dizoo/distar/envs/distar_env.py | 15 ++++++++++----- 1 file changed, 10 insertions(+), 5 deletions(-) diff --git a/dizoo/distar/envs/distar_env.py b/dizoo/distar/envs/distar_env.py index f34ee527b1..88512666f9 100644 --- a/dizoo/distar/envs/distar_env.py +++ b/dizoo/distar/envs/distar_env.py @@ -15,11 +15,16 @@ def __init__(self, cfg): self._map_name = None def reset(self): - observations, game_info, map_name = super(DIStarEnv, self).reset() - # print(game_info) - self.game_info = game_info - self.map_name = map_name - return observations + while True: + try: + observations, game_info, map_name = super(DIStarEnv, self).reset() + # print(game_info) + self.game_info = game_info + self.map_name = map_name + return observations + except Exception as e: + print("during reset SC2 env, an error happend: ", e, flush=True) + self.close() def close(self): super(DIStarEnv, self).close() From 78bed49622e216fe71c3afd2031753cff50ce170 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 15 Jun 2022 17:53:49 +0800 Subject: [PATCH 114/229] rolloutor handle error during step --- ding/framework/context.py | 4 ++++ ding/framework/middleware/functional/collector.py | 9 ++++++++- ding/framework/middleware/tests/mock_for_test.py | 11 +++++++++++ 3 files changed, 23 insertions(+), 1 deletion(-) diff --git a/ding/framework/context.py b/ding/framework/context.py index 4fa242c0be..e2b38fbc19 100644 --- a/ding/framework/context.py +++ b/ding/framework/context.py @@ -103,6 +103,10 @@ def __init__(self, *args, **kwargs) -> None: self.job = None self.job_finish = False + #data + self.obs = None + self.actions = None + #Return data paras self.episodes = [] self.episode_info = [] diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 2b40f70358..c02b5b254b 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -46,6 +46,13 @@ def clear(self): for item in self._done_idx: item.clear() + def clear(self, env_id: int) -> None: + self._transitions[env_id].clear() + self._done_idx[env_id].clear() + + def length(self, env_id: int) -> int: + return len(self._transitions[env_id]) + def inferencer(cfg: EasyDict, policy: Policy, env: BaseEnvManager) -> Callable: """ @@ -142,7 +149,7 @@ def _battle_inferencer(ctx: "BattleContext"): if env.closed: env.launch() - + # Get current env obs. obs = env.ready_obs # the role of remain_episode is to mask necessary rollouts, avoid processing unnecessary data diff --git a/ding/framework/middleware/tests/mock_for_test.py b/ding/framework/middleware/tests/mock_for_test.py index 420c548775..4d028eb257 100644 --- a/ding/framework/middleware/tests/mock_for_test.py +++ b/ding/framework/middleware/tests/mock_for_test.py @@ -323,6 +323,17 @@ def battle_rolloutor_for_distar(cfg: EasyDict, env: BaseEnvManager, transitions_ def _battle_rolloutor(ctx: "BattleContext"): timesteps = env.step(ctx.actions) + error_env_id_list = [] + for env_id, timestep in timesteps.items(): + if timestep.info.get('step_error'): + error_env_id_list.append(env_id) + ctx.total_envstep_count -= transitions_list[0].length(env_id) + ctx.env_step -= transitions_list[0].length(env_id) + for transitions in transitions_list: + transitions.clear(env_id) + for error_env_id in error_env_id_list: + del timesteps[error_env_id] + ctx.total_envstep_count += len(timesteps) ctx.env_step += len(timesteps) for env_id, timestep in timesteps.items(): From 2ad48501ab082d17b5e7d58589c4b6dc62e90cc9 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 15 Jun 2022 17:55:24 +0800 Subject: [PATCH 115/229] add test for step exception --- .../tests/test_handle_step_exception.py | 37 +++++++++++++++++++ 1 file changed, 37 insertions(+) create mode 100644 ding/framework/middleware/tests/test_handle_step_exception.py diff --git a/ding/framework/middleware/tests/test_handle_step_exception.py b/ding/framework/middleware/tests/test_handle_step_exception.py new file mode 100644 index 0000000000..0ebbd460fc --- /dev/null +++ b/ding/framework/middleware/tests/test_handle_step_exception.py @@ -0,0 +1,37 @@ +from ding.framework.context import BattleContext +from ding.framework.middleware.functional.collector import TransitionList +from ding.framework.middleware.tests import battle_rolloutor_for_distar +import pytest +from unittest.mock import Mock +from ding.envs import BaseEnvTimestep +from easydict import EasyDict + + +class MockEnvManager(Mock): + + def step(self, actions): + timesteps = {} + for env_id in actions.keys(): + timesteps[env_id] = BaseEnvTimestep(obs=[1], reward=[1, 1], done=False, info={'step_error': True}) + return timesteps + + +@pytest.mark.unittest +def test_handle_step_exception(): + ctx = BattleContext() + ctx.total_envstep_count = 10 + ctx.env_step = 20 + transitions_list = [TransitionList(env_num=2)] + for _ in range(5): + transitions_list[0].append(env_id=0, transition=BaseEnvTimestep(obs=[1], reward=[1, 1], done=False, info={})) + transitions_list[0].append(env_id=1, transition=BaseEnvTimestep(obs=[1], reward=[1, 1], done=False, info={})) + + ctx.actions = {0: {}} + ctx.obs = {0: {0: {}}} + rolloutor = battle_rolloutor_for_distar(cfg=EasyDict(), env=MockEnvManager(), transitions_list=transitions_list) + rolloutor(ctx) + + assert ctx.total_envstep_count == 5 + assert ctx.env_step == 15 + assert transitions_list[0].length(0) == 0 + assert transitions_list[0].length(1) == 5 From 72dfa38b7f033901a3e29c9fc4105fcaa34470ec Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 15 Jun 2022 22:02:19 +0800 Subject: [PATCH 116/229] fix a bug of TransitionList, and simpify BattleContext --- ding/framework/context.py | 7 +------ ding/framework/middleware/functional/collector.py | 2 +- ding/framework/middleware/league_actor.py | 15 +++++---------- ding/framework/middleware/tests/mock_for_test.py | 2 +- .../tests/test_handle_step_exception.py | 4 ++++ 5 files changed, 12 insertions(+), 18 deletions(-) diff --git a/ding/framework/context.py b/ding/framework/context.py index e2b38fbc19..0dfb23d20c 100644 --- a/ding/framework/context.py +++ b/ding/framework/context.py @@ -84,9 +84,7 @@ def __init__(self, *args, **kwargs) -> None: self.__dict__ = self # collect target paras self.n_episode = None - self.n_sample = 1 - self.unroll_len = 1 - + #collect process paras self.env_episode = 0 self.env_step = 0 @@ -94,7 +92,6 @@ def __init__(self, *args, **kwargs) -> None: self.train_iter = 0 self.collect_kwargs = {} self.agent_num = 2 - self.traj_len = float("inf") self.current_policies = [] self.ready_env_id = set() self.remain_episode = 0 @@ -112,6 +109,4 @@ def __init__(self, *args, **kwargs) -> None: self.episode_info = [] self.trajectories_list = [] self.trajectory_end_idx_list = [] - self.trajectories = [] - self.trajectory_end_idx = None self.train_data = None diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index c02b5b254b..6cc9fc86e2 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -46,7 +46,7 @@ def clear(self): for item in self._done_idx: item.clear() - def clear(self, env_id: int) -> None: + def clear_env_transitions(self, env_id: int) -> None: self._transitions[env_id].clear() self._done_idx[env_id].clear() diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index b630b5abaa..da0bb01079 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -248,25 +248,20 @@ def __call__(self, ctx: "BattleContext"): ctx.train_iter = main_player.total_agent_step ctx.episode_info = [[] for _ in range(ctx.agent_num)] ctx.remain_episode = ctx.n_episode - ctx.n_sample = self.n_sample - ctx.unroll_len = self.unroll_len + while True: collector(ctx) if not ctx.job.is_eval and len(ctx.trajectories_list[0]) > 0: - ctx.trajectories = ctx.trajectories_list[0] - ctx.trajectory_end_idx = ctx.trajectory_end_idx_list[0] - print('actor {}, len trajectories {}'.format(task.router.node_id, len(ctx.trajectories)), flush=True) - # self._gae_estimator(ctx) - # actor_data = ActorData(env_step=ctx.total_envstep_count, train_data=ctx.train_data) - actor_data = ActorData(env_step=ctx.total_envstep_count, train_data=ctx.trajectories) + trajectories = ctx.trajectories_list[0] + trajectory_end_idx = ctx.trajectory_end_idx_list[0] + print('actor {}, len trajectories {}'.format(task.router.node_id, len(trajectories)), flush=True) + actor_data = ActorData(env_step=ctx.total_envstep_count, train_data=trajectories) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=ctx.job.launch_player), actor_data) print('Actor {} send data\n'.format(task.router.node_id), flush=True) ctx.trajectories_list = [] ctx.trajectory_end_idx_list = [] - ctx.trajectories = [] - ctx.trajectory_end_idx = None if ctx.job_finish is True: ctx.job.result = [e['result'] for e in ctx.episode_info[0]] diff --git a/ding/framework/middleware/tests/mock_for_test.py b/ding/framework/middleware/tests/mock_for_test.py index 4d028eb257..6d3c21ed05 100644 --- a/ding/framework/middleware/tests/mock_for_test.py +++ b/ding/framework/middleware/tests/mock_for_test.py @@ -330,7 +330,7 @@ def _battle_rolloutor(ctx: "BattleContext"): ctx.total_envstep_count -= transitions_list[0].length(env_id) ctx.env_step -= transitions_list[0].length(env_id) for transitions in transitions_list: - transitions.clear(env_id) + transitions.clear_env_transitions(env_id) for error_env_id in error_env_id_list: del timesteps[error_env_id] diff --git a/ding/framework/middleware/tests/test_handle_step_exception.py b/ding/framework/middleware/tests/test_handle_step_exception.py index 0ebbd460fc..ce70cb7b46 100644 --- a/ding/framework/middleware/tests/test_handle_step_exception.py +++ b/ding/framework/middleware/tests/test_handle_step_exception.py @@ -35,3 +35,7 @@ def test_handle_step_exception(): assert ctx.env_step == 15 assert transitions_list[0].length(0) == 0 assert transitions_list[0].length(1) == 5 + + +if __name__ == '__main__': + test_handle_step_exception() \ No newline at end of file From f6ec222aaa591f6b23cca264ad4b20ebeeca0e3d Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 15 Jun 2022 22:05:11 +0800 Subject: [PATCH 117/229] change a bit --- ding/framework/middleware/tests/test_handle_step_exception.py | 4 ---- 1 file changed, 4 deletions(-) diff --git a/ding/framework/middleware/tests/test_handle_step_exception.py b/ding/framework/middleware/tests/test_handle_step_exception.py index ce70cb7b46..0ebbd460fc 100644 --- a/ding/framework/middleware/tests/test_handle_step_exception.py +++ b/ding/framework/middleware/tests/test_handle_step_exception.py @@ -35,7 +35,3 @@ def test_handle_step_exception(): assert ctx.env_step == 15 assert transitions_list[0].length(0) == 0 assert transitions_list[0].length(1) == 5 - - -if __name__ == '__main__': - test_handle_step_exception() \ No newline at end of file From b6129edd709cd8ab96540071fd50c9170cdf37d4 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 15 Jun 2022 22:11:23 +0800 Subject: [PATCH 118/229] change var agent_num --- ding/framework/context.py | 1 - ding/framework/middleware/league_actor.py | 30 ++++++++++++++--------- 2 files changed, 18 insertions(+), 13 deletions(-) diff --git a/ding/framework/context.py b/ding/framework/context.py index 0dfb23d20c..87e38ece44 100644 --- a/ding/framework/context.py +++ b/ding/framework/context.py @@ -91,7 +91,6 @@ def __init__(self, *args, **kwargs) -> None: self.total_envstep_count = 0 self.train_iter = 0 self.collect_kwargs = {} - self.agent_num = 2 self.current_policies = [] self.ready_env_id = set() self.remain_episode = 0 diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index da0bb01079..883aec9c88 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -33,6 +33,8 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.model_dict = {} self.model_dict_lock = Lock() + self.agent_num = 2 + def _on_learner_model(self, learner_model: "LearnerModel"): """ If get newest learner model, put it inside model_queue. @@ -47,14 +49,15 @@ def _on_league_job(self, job: "Job"): """ self.job_queue.put(job) - def _get_collector(self, player_id: str, agent_num: int): + def _get_collector(self, player_id: str): if self._collectors.get(player_id): return self._collectors.get(player_id) cfg = self.cfg env = self.env_fn() collector = task.wrap( BattleEpisodeCollector( - cfg.policy.collect.collector, env, self.n_rollout_samples, self.model_dict, self.all_policies, agent_num + cfg.policy.collect.collector, env, self.n_rollout_samples, self.model_dict, self.all_policies, + self.agent_num ) ) self._collectors[player_id] = collector @@ -107,7 +110,8 @@ def __call__(self, ctx: "BattleContext"): if ctx.job is None: return - collector = self._get_collector(ctx.job.launch_player, len(ctx.job.players)) + self.agent_num = len(ctx.job.players) + collector = self._get_collector(ctx.job.launch_player) main_player, ctx.current_policies = self._get_current_policies(ctx.job) @@ -119,9 +123,8 @@ def __call__(self, ctx: "BattleContext"): ctx.n_episode = _default_n_episode assert ctx.n_episode >= self.env_num, "Please make sure n_episode >= env_num" - ctx.agent_num = len(ctx.current_policies) ctx.train_iter = main_player.total_agent_step - ctx.episode_info = [[] for _ in range(ctx.agent_num)] + ctx.episode_info = [[] for _ in range(self.agent_num)] ctx.remain_episode = ctx.n_episode while True: collector(ctx) @@ -133,7 +136,7 @@ def __call__(self, ctx: "BattleContext"): if ctx.job_finish is True: ctx.job.result = [e['result'] for e in ctx.episode_info[0]] task.emit(EventEnum.ACTOR_FINISH_JOB, ctx.job) - ctx.episode_info = [[] for _ in range(ctx.agent_num)] + ctx.episode_info = [[] for _ in range(self.agent_num)] break @@ -155,6 +158,8 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.model_dict = {} self.model_dict_lock = Lock() + self.agent_num = 2 + # self._gae_estimator = gae_estimator(cfg, policy_fn().collect_mode) def _on_learner_model(self, learner_model: "LearnerModel"): @@ -171,14 +176,15 @@ def _on_league_job(self, job: "Job"): """ self.job_queue.put(job) - def _get_collector(self, player_id: str, agent_num: int): + def _get_collector(self, player_id: str): if self._collectors.get(player_id): return self._collectors.get(player_id) cfg = self.cfg env = self.env_fn() collector = task.wrap( BattleStepCollector( - cfg.policy.collect.collector, env, self.n_rollout_samples, self.model_dict, self.all_policies, agent_num + cfg.policy.collect.collector, env, self.n_rollout_samples, self.model_dict, self.all_policies, + self.agent_num ) ) self._collectors[player_id] = collector @@ -231,11 +237,11 @@ def __call__(self, ctx: "BattleContext"): if ctx.job is None: return print('For actor {}, a job begin \n'.format(task.router.node_id), flush=True) + self.agent_num = len(ctx.job.players) - collector = self._get_collector(ctx.job.launch_player, len(ctx.job.players)) + collector = self._get_collector(ctx.job.launch_player) main_player, ctx.current_policies = self._get_current_policies(ctx.job) - ctx.agent_num = len(ctx.current_policies) _default_n_episode = ctx.current_policies[0].get_attribute('cfg').collect.get('n_episode', None) if ctx.n_episode is None: @@ -246,7 +252,7 @@ def __call__(self, ctx: "BattleContext"): assert ctx.n_episode >= self.env_num, "Please make sure n_episode >= env_num" ctx.train_iter = main_player.total_agent_step - ctx.episode_info = [[] for _ in range(ctx.agent_num)] + ctx.episode_info = [[] for _ in range(self.agent_num)] ctx.remain_episode = ctx.n_episode while True: @@ -266,6 +272,6 @@ def __call__(self, ctx: "BattleContext"): if ctx.job_finish is True: ctx.job.result = [e['result'] for e in ctx.episode_info[0]] task.emit(EventEnum.ACTOR_FINISH_JOB, ctx.job) - ctx.episode_info = [[] for _ in range(ctx.agent_num)] + ctx.episode_info = [[] for _ in range(self.agent_num)] print('Actor {} job finish, send job\n'.format(task.router.node_id), flush=True) break From c16e9e74b9a09174c30636f03d10c9af43563f8f Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 15 Jun 2022 22:27:30 +0800 Subject: [PATCH 119/229] make n_episode more clear --- ding/framework/middleware/league_actor.py | 16 ++-------------- ding/framework/middleware/tests/league_config.py | 2 +- 2 files changed, 3 insertions(+), 15 deletions(-) diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 883aec9c88..d83fd552d6 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -115,12 +115,7 @@ def __call__(self, ctx: "BattleContext"): main_player, ctx.current_policies = self._get_current_policies(ctx.job) - _default_n_episode = ctx.current_policies[0].get_attribute('cfg').collect.get('n_episode', None) - if ctx.n_episode is None: - if _default_n_episode is None: - raise RuntimeError("Please specify collect n_episode") - else: - ctx.n_episode = _default_n_episode + ctx.n_episode = self.cfg.policy.collect.get("n_episode") or 1 assert ctx.n_episode >= self.env_num, "Please make sure n_episode >= env_num" ctx.train_iter = main_player.total_agent_step @@ -148,8 +143,6 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.env_num = env_fn().env_num self.policy_fn = policy_fn self.n_rollout_samples = self.cfg.policy.collect.get("n_rollout_samples") or 0 - self.n_sample = self.cfg.policy.collect.get("n_sample") or 1 - self.unroll_len = self.cfg.policy.collect.get("unroll_len") or 1 self._collectors: Dict[str, BattleEpisodeCollector] = {} self.all_policies: Dict[str, "Policy.collect_function"] = {} task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), self._on_league_job) @@ -243,12 +236,7 @@ def __call__(self, ctx: "BattleContext"): main_player, ctx.current_policies = self._get_current_policies(ctx.job) - _default_n_episode = ctx.current_policies[0].get_attribute('cfg').collect.get('n_episode', None) - if ctx.n_episode is None: - if _default_n_episode is None: - raise RuntimeError("Please specify collect n_episode") - else: - ctx.n_episode = _default_n_episode + ctx.n_episode = self.cfg.policy.collect.get("n_episode") or 1 assert ctx.n_episode >= self.env_num, "Please make sure n_episode >= env_num" ctx.train_iter = main_player.total_agent_step diff --git a/ding/framework/middleware/tests/league_config.py b/ding/framework/middleware/tests/league_config.py index 3d1e6b5b1d..f8a08c6069 100644 --- a/ding/framework/middleware/tests/league_config.py +++ b/ding/framework/middleware/tests/league_config.py @@ -77,7 +77,7 @@ }, 'discount_factor': 1.0, 'gae_lambda': 1.0, - 'n_episode': 1, + 'n_episode': 2, 'n_rollout_samples': 32, 'n_sample': 64, 'unroll_len': 2 From 6fa1209e97d974b9436f982c8e897a1fe5de9abd Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 15 Jun 2022 22:40:58 +0800 Subject: [PATCH 120/229] get rid of ctx.job --- ding/framework/context.py | 2 +- ding/framework/middleware/collector.py | 16 ++++------ ding/framework/middleware/league_actor.py | 38 ++++++++++++----------- 3 files changed, 27 insertions(+), 29 deletions(-) diff --git a/ding/framework/context.py b/ding/framework/context.py index 87e38ece44..f5f830f784 100644 --- a/ding/framework/context.py +++ b/ding/framework/context.py @@ -96,7 +96,7 @@ def __init__(self, *args, **kwargs) -> None: self.remain_episode = 0 #job paras - self.job = None + self.player_id_list = [] self.job_finish = False #data diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 20e2f7e823..49d560a4d5 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -42,10 +42,8 @@ def __del__(self) -> None: self.end_flag = True self.env.close() - def _update_policies(self, job) -> None: - job_player_id_list = [player.player_id for player in job.players] - - for player_id in job_player_id_list: + def _update_policies(self, player_id_list) -> None: + for player_id in player_id_list: if self.model_dict.get(player_id) is None: continue else: @@ -70,7 +68,7 @@ def __call__(self, ctx: "BattleContext") -> None: ctx.total_envstep_count = self.total_envstep_count old = ctx.env_episode while True: - self._update_policies(ctx.job) + self._update_policies(ctx.player_id_list) self._battle_inferencer(ctx) self._battle_rolloutor(ctx) @@ -120,10 +118,8 @@ def __del__(self) -> None: self.end_flag = True self.env.close() - def _update_policies(self, job) -> None: - job_player_id_list = [player.player_id for player in job.players] - - for player_id in job_player_id_list: + def _update_policies(self, player_id_list) -> None: + for player_id in player_id_list: if self.model_dict.get(player_id) is None: continue else: @@ -149,7 +145,7 @@ def __call__(self, ctx: "BattleContext") -> None: old = ctx.env_step while True: - self._update_policies(ctx.job) + self._update_policies(ctx.player_id_list) self._battle_inferencer(ctx) self._battle_rolloutor(ctx) diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index d83fd552d6..3edfbfc0a3 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -106,14 +106,15 @@ def _get_current_policies(self, job): def __call__(self, ctx: "BattleContext"): - ctx.job = self._get_job() - if ctx.job is None: + job = self._get_job() + if job is None: return - self.agent_num = len(ctx.job.players) - collector = self._get_collector(ctx.job.launch_player) + ctx.player_id_list = [player.player_id for player in job.players] + self.agent_num = len(job.players) + collector = self._get_collector(job.launch_player) - main_player, ctx.current_policies = self._get_current_policies(ctx.job) + main_player, ctx.current_policies = self._get_current_policies(job) ctx.n_episode = self.cfg.policy.collect.get("n_episode") or 1 assert ctx.n_episode >= self.env_num, "Please make sure n_episode >= env_num" @@ -124,13 +125,13 @@ def __call__(self, ctx: "BattleContext"): while True: collector(ctx) - if not ctx.job.is_eval and len(ctx.episodes[0]) > 0: + if not job.is_eval and len(ctx.episodes[0]) > 0: actor_data = ActorData(env_step=ctx.total_envstep_count, train_data=ctx.episodes[0]) - task.emit(EventEnum.ACTOR_SEND_DATA.format(player=ctx.job.launch_player), actor_data) + task.emit(EventEnum.ACTOR_SEND_DATA.format(player=job.launch_player), actor_data) ctx.episodes = [] if ctx.job_finish is True: - ctx.job.result = [e['result'] for e in ctx.episode_info[0]] - task.emit(EventEnum.ACTOR_FINISH_JOB, ctx.job) + job.result = [e['result'] for e in ctx.episode_info[0]] + task.emit(EventEnum.ACTOR_FINISH_JOB, job) ctx.episode_info = [[] for _ in range(self.agent_num)] break @@ -226,15 +227,16 @@ def _get_current_policies(self, job): def __call__(self, ctx: "BattleContext"): - ctx.job = self._get_job() - if ctx.job is None: + job = self._get_job() + if job is None: return print('For actor {}, a job begin \n'.format(task.router.node_id), flush=True) - self.agent_num = len(ctx.job.players) - collector = self._get_collector(ctx.job.launch_player) + ctx.player_id_list = [player.player_id for player in job.players] + self.agent_num = len(job.players) + collector = self._get_collector(job.launch_player) - main_player, ctx.current_policies = self._get_current_policies(ctx.job) + main_player, ctx.current_policies = self._get_current_policies(job) ctx.n_episode = self.cfg.policy.collect.get("n_episode") or 1 assert ctx.n_episode >= self.env_num, "Please make sure n_episode >= env_num" @@ -246,20 +248,20 @@ def __call__(self, ctx: "BattleContext"): while True: collector(ctx) - if not ctx.job.is_eval and len(ctx.trajectories_list[0]) > 0: + if not job.is_eval and len(ctx.trajectories_list[0]) > 0: trajectories = ctx.trajectories_list[0] trajectory_end_idx = ctx.trajectory_end_idx_list[0] print('actor {}, len trajectories {}'.format(task.router.node_id, len(trajectories)), flush=True) actor_data = ActorData(env_step=ctx.total_envstep_count, train_data=trajectories) - task.emit(EventEnum.ACTOR_SEND_DATA.format(player=ctx.job.launch_player), actor_data) + task.emit(EventEnum.ACTOR_SEND_DATA.format(player=job.launch_player), actor_data) print('Actor {} send data\n'.format(task.router.node_id), flush=True) ctx.trajectories_list = [] ctx.trajectory_end_idx_list = [] if ctx.job_finish is True: - ctx.job.result = [e['result'] for e in ctx.episode_info[0]] - task.emit(EventEnum.ACTOR_FINISH_JOB, ctx.job) + job.result = [e['result'] for e in ctx.episode_info[0]] + task.emit(EventEnum.ACTOR_FINISH_JOB, job) ctx.episode_info = [[] for _ in range(self.agent_num)] print('Actor {} job finish, send job\n'.format(task.router.node_id), flush=True) break From 09b71459ade0ec4923bb4e79f213d01b597fe352 Mon Sep 17 00:00:00 2001 From: niuyazhe Date: Wed, 15 Jun 2022 23:27:55 +0800 Subject: [PATCH 121/229] polish(nyz): remove whole_cfg in distar model and fix bugs --- dizoo/distar/model/__init__.py | 2 +- .../model/actor_critic_default_config.yaml | 20 +++++--- dizoo/distar/model/encoder.py | 10 ++-- dizoo/distar/model/head/action_arg_head.py | 50 ++++++++----------- dizoo/distar/model/head/action_type_head.py | 5 +- dizoo/distar/model/model.py | 28 ++++++----- .../model/obs_encoder/entity_encoder.py | 15 +++--- .../model/obs_encoder/scalar_encoder.py | 16 +++--- .../model/obs_encoder/spatial_encoder.py | 9 ++-- .../distar/model/obs_encoder/value_encoder.py | 2 +- dizoo/distar/model/policy.py | 15 +++--- dizoo/distar/model/tests/test_head.py | 14 +++--- 12 files changed, 90 insertions(+), 96 deletions(-) diff --git a/dizoo/distar/model/__init__.py b/dizoo/distar/model/__init__.py index 8ea35e8f96..3b4d86ebbc 100644 --- a/dizoo/distar/model/__init__.py +++ b/dizoo/distar/model/__init__.py @@ -1 +1 @@ -#from .model import Model, alphastar_model_default_config +from .model import Model diff --git a/dizoo/distar/model/actor_critic_default_config.yaml b/dizoo/distar/model/actor_critic_default_config.yaml index 08859163b3..05edf693e4 100644 --- a/dizoo/distar/model/actor_critic_default_config.yaml +++ b/dizoo/distar/model/actor_critic_default_config.yaml @@ -11,21 +11,16 @@ var10: &SPATIAL_Y 152 var11: &NUM_UNIT_MIX_ABILITIES 269 -learner: - use_value_feature: False model: - spatial_x: *SPATIAL_X - spatial_y: *SPATIAL_Y - temperature: 1.0 # ===== Tuning ===== freeze_targets: [] state_dict_mask: [] use_value_network: False only_update_baseline: False enable_baselines: ['winloss', 'build_order', 'built_unit', 'effect', 'upgrade', 'battle'] - entity_reduce_type: 'selected_units_num' # ['constant', 'entity_num', 'selected_units_num'] # ===== Value ===== value: + use_value_feature: False encoder: modules: enemy_unit_counts_bow: @@ -195,6 +190,7 @@ model: beginning_order: arc: transformer action_one_hot_dim: *NUM_BEGINNING_ORDER_ACTIONS + spatial_x: *SPATIAL_X binary_dim: 10 head_dim: 8 output_dim: 64 @@ -261,6 +257,8 @@ model: activation: 'relu' norm_type: 'none' head_type: 'fc' + spatial_x: *SPATIAL_X + spatial_y: *SPATIAL_Y entity_encoder: module: unit_type: @@ -373,7 +371,7 @@ model: dropout_ratio: 0 activation: 'relu' ln_type: 'post' - use_score_cumulative: False + entity_reduce_type: 'selected_units_num' # ['constant', 'entity_num', 'selected_units_num'] scatter: input_dim: 256 # entity_encoder.output_dim output_dim: 32 @@ -405,6 +403,7 @@ model: ln_type: 'normal' use_mask: False race: 'zerg' + temperature: 1.0 delay_head: input_dim: 1024 # action_type_head.gate_dim decode_dim: 256 @@ -417,6 +416,7 @@ model: queued_dim: 2 queued_map_dim: 256 activation: 'relu' + temperature: 1.0 selected_units_head: lstm_type: 'pytorch' lstm_norm_type: 'none' @@ -431,6 +431,8 @@ model: max_entity_num: 64 activation: 'relu' extra_units: True # select extra units if selected units exceed max_entity_num=64 + entity_reduce_type: 'selected_units_num' + temperature: 1.0 target_unit_head: input_dim: 1024 # action_type_head.gate_dim entity_embedding_dim: 256 # entity_encoder.output_dim @@ -439,6 +441,7 @@ model: func_dim: 256 activation: 'relu' embedding_norm: True + temperature: 1.0 location_head: input_dim: 1024 project_dim: 1024 @@ -450,3 +453,6 @@ model: reshape_channel: 4 # entity_encoder.gate_dim / reshape_size map_skip_dim: 128 # spatial_encoder.down_channels[-1] activation: 'relu' + spatial_x: *SPATIAL_X + spatial_y: *SPATIAL_Y + temperature: 1.0 diff --git a/dizoo/distar/model/encoder.py b/dizoo/distar/model/encoder.py index f6d849f901..bd341f70f5 100644 --- a/dizoo/distar/model/encoder.py +++ b/dizoo/distar/model/encoder.py @@ -8,19 +8,17 @@ from ding.torch_utils import fc_block, ScatterConnection from .obs_encoder import ScalarEncoder, SpatialEncoder, EntityEncoder -from .lstm import script_lnlstm class Encoder(nn.Module): def __init__(self, cfg): super(Encoder, self).__init__() - self.whole_cfg = cfg - self.cfg = cfg.model.encoder + self.cfg = cfg.encoder self.encoder = nn.ModuleDict() - self.scalar_encoder = ScalarEncoder(self.whole_cfg) - self.spatial_encoder = SpatialEncoder(self.whole_cfg) - self.entity_encoder = EntityEncoder(self.whole_cfg) + self.scalar_encoder = ScalarEncoder(self.cfg.obs_encoder.scalar_encoder) + self.spatial_encoder = SpatialEncoder(self.cfg.obs_encoder.spatial_encoder) + self.entity_encoder = EntityEncoder(self.cfg.obs_encoder.entity_encoder) self.scatter_project = fc_block(self.cfg.scatter.input_dim, self.cfg.scatter.output_dim, activation=nn.ReLU()) self.scatter_dim = self.cfg.scatter.output_dim self.scatter_connection = ScatterConnection(self.cfg.scatter.scatter_type) diff --git a/dizoo/distar/model/head/action_arg_head.py b/dizoo/distar/model/head/action_arg_head.py index 35f3d3b1f4..1c7e7b61fc 100644 --- a/dizoo/distar/model/head/action_arg_head.py +++ b/dizoo/distar/model/head/action_arg_head.py @@ -25,8 +25,7 @@ class DelayHead(nn.Module): def __init__(self, cfg): super(DelayHead, self).__init__() - self.whole_cfg = cfg - self.cfg = self.whole_cfg.model.policy.head.delay_head + self.cfg = cfg self.act = build_activation(self.cfg.activation) self.fc1 = fc_block(self.cfg.input_dim, self.cfg.decode_dim, activation=self.act, norm_type=None) self.fc2 = fc_block(self.cfg.decode_dim, self.cfg.decode_dim, activation=self.act, norm_type=None) @@ -55,8 +54,7 @@ class QueuedHead(nn.Module): def __init__(self, cfg): super(QueuedHead, self).__init__() - self.whole_cfg = cfg - self.cfg = self.whole_cfg.model.policy.head.queued_head + self.cfg = cfg self.act = build_activation(self.cfg.activation) # to get queued logits self.fc1 = fc_block(self.cfg.input_dim, self.cfg.decode_dim, activation=self.act, norm_type=None) @@ -73,7 +71,7 @@ def forward(self, embedding, queued=None): x = self.fc1(embedding) x = self.fc2(x) x = self.fc3(x) - x.div_(self.whole_cfg.model.temperature) + x.div_(self.cfg.temperature) if queued is None: p = F.softmax(x, dim=1) queued = torch.multinomial(p, 1)[:, 0] @@ -89,8 +87,7 @@ class SelectedUnitsHead(nn.Module): def __init__(self, cfg): super(SelectedUnitsHead, self).__init__() - self.whole_cfg = cfg - self.cfg = self.whole_cfg.model.policy.head.selected_units_head + self.cfg = cfg self.act = build_activation(self.cfg.activation) self.key_fc = fc_block(self.cfg.entity_embedding_dim, self.cfg.key_dim, activation=None, norm_type=None) self.query_fc1 = fc_block(self.cfg.input_dim, self.cfg.func_dim, activation=self.act) @@ -108,9 +105,9 @@ def __init__(self, cfg): self.end_embedding = torch.nn.Parameter(torch.FloatTensor(1, self.key_dim)) stdv = 1. / math.sqrt(self.end_embedding.size(1)) self.end_embedding.data.uniform_(-stdv, stdv) - if self.whole_cfg.model.entity_reduce_type == 'attention_pool': + if self.cfg.entity_reduce_type == 'attention_pool': self.attention_pool = AttentionPool(key_dim=self.cfg.key_dim, head_num=2, output_dim=self.cfg.input_dim) - elif self.whole_cfg.model.entity_reduce_type == 'attention_pool_add_num': + elif self.cfg.entity_reduce_type == 'attention_pool_add_num': self.attention_pool = AttentionPool( key_dim=self.cfg.key_dim, head_num=2, output_dim=self.cfg.input_dim, max_num=MAX_SELECTED_UNITS_NUM + 1 ) @@ -128,7 +125,7 @@ def _get_key_mask(self, entity_embedding, entity_num): end_embeddings = end_embeddings * ~flag key = key * flag key = key + end_embeddings - reduce_type = self.whole_cfg.model.entity_reduce_type + reduce_type = self.cfg.entity_reduce_type if reduce_type == 'entity_num': key_reduce = torch.div(key, entity_num.reshape(-1, 1, 1)) key_embeddings = self.embed_fc(key_reduce) @@ -145,7 +142,7 @@ def _get_key_mask(self, entity_embedding, entity_num): return key, mask, key_embeddings def _get_pred_with_logit(self, logit): - logit.div_(self.whole_cfg.model.temperature) + logit.div_(self.cfg.temperature) p = F.softmax(logit, dim=-1) units = torch.multinomial(p, 1)[:, 0] return units @@ -190,23 +187,23 @@ def _query( lstm_input = self.query_fc2(self.query_fc1(ae)).unsqueeze(0) lstm_output, state = self.lstm(lstm_input, state) queries.append(lstm_output) - reduce_type = self.whole_cfg.model.entity_reduce_type + reduce_type = self.cfg.entity_reduce_type if reduce_type == 'selected_units_num' or 'attention' in reduce_type: new_selected_units_one_hot = selected_units_one_hot.clone() # inplace operation can not backward end_flag[selected_units[:, i] == entity_num] = 1 new_selected_units_one_hot[torch.arange(bs)[~end_flag], selected_units[:, i][~end_flag], :] = 1 - if self.whole_cfg.model.entity_reduce_type == 'selected_units_num': + if reduce_type == 'selected_units_num': selected_units_emebedding = (key_embeddings * new_selected_units_one_hot).sum(dim=1) S = selected_units_num selected_units_emebedding[S != 0] = \ selected_units_emebedding[S != 0] / new_selected_units_one_hot.sum(dim=1)[S != 0] selected_units_emebedding = self.embed_fc2(self.embed_fc1(selected_units_emebedding)) ae = autoregressive_embedding + selected_units_emebedding - elif self.whole_cfg.model.entity_reduce_type == 'attention_pool': + elif reduce_type == 'attention_pool': ae = autoregressive_embedding + self.attention_pool( key_embeddings, mask=new_selected_units_one_hot ) - elif self.whole_cfg.model.entity_reduce_type == 'attention_pool_add_num': + elif reduce_type == 'attention_pool_add_num': ae = autoregressive_embedding + self.attention_pool( key_embeddings, num=new_selected_units_one_hot.sum(dim=1).squeeze(dim=1), @@ -251,19 +248,19 @@ def _query( end_flag[result == entity_num] = torch.tensor([1], dtype=torch.bool, device=ae.device) results_list.append(result) logits_list.append(step_logits) - reduce_type = self.whole_cfg.model.entity_reduce_type + reduce_type = self.cfg.entity_reduce_type if reduce_type == 'selected_units_num' or 'attention' in reduce_type: selected_units_one_hot[torch.arange(bs)[~end_flag], result[~end_flag], :] = 1 - if self.whole_cfg.model.entity_reduce_type == 'selected_units_num': + if reduce_type == 'selected_units_num': selected_units_emebedding = (key_embeddings * selected_units_one_hot).sum(dim=1) slected_num = selected_units_one_hot.sum(dim=1).squeeze(dim=1) selected_units_emebedding[slected_num != 0] = selected_units_emebedding[ slected_num != 0] / slected_num[slected_num != 0].unsqueeze(dim=1) selected_units_emebedding = self.embed_fc2(self.embed_fc1(selected_units_emebedding)) ae = autoregressive_embedding + selected_units_emebedding - elif self.whole_cfg.model.entity_reduce_type == 'attention_pool': + elif reduce_type == 'attention_pool': ae = autoregressive_embedding + self.attention_pool(key_embeddings, mask=selected_units_one_hot) - elif self.whole_cfg.model.entity_reduce_type == 'attention_pool_add_num': + elif reduce_type == 'attention_pool_add_num': ae = autoregressive_embedding + self.attention_pool( key_embeddings, num=selected_units_one_hot.sum(dim=1).squeeze(dim=1), @@ -302,8 +299,7 @@ class TargetUnitHead(nn.Module): def __init__(self, cfg): super(TargetUnitHead, self).__init__() - self.whole_cfg = cfg - self.cfg = self.whole_cfg.model.policy.head.target_unit_head + self.cfg = cfg self.act = build_activation(self.cfg.activation) self.key_fc = fc_block(self.cfg.entity_embedding_dim, self.cfg.key_dim, activation=None, norm_type=None) self.query_fc1 = fc_block(self.cfg.input_dim, self.cfg.key_dim, activation=self.act, norm_type=None) @@ -321,7 +317,7 @@ def forward(self, embedding, entity_embedding, entity_num, target_unit: Optional logits = logits.sum(dim=2) # b, n, -1 logits.masked_fill_(~mask, value=-1e9) - logits.div_(self.whole_cfg.model.temperature) + logits.div_(self.cfg.temperature) if target_unit is None: p = F.softmax(logits, dim=1) target_unit = torch.multinomial(p, 1)[:, 0] @@ -332,8 +328,7 @@ class LocationHead(nn.Module): def __init__(self, cfg): super(LocationHead, self).__init__() - self.whole_cfg = cfg - self.cfg = self.whole_cfg.model.policy.head.location_head + self.cfg = cfg self.act = build_activation(self.cfg.activation) self.reshape_channel = self.cfg.reshape_channel @@ -352,7 +347,7 @@ def __init__(self, cfg): self.use_gate = self.cfg.gate self.project_embed = fc_block( self.cfg.input_dim, - self.whole_cfg.model.spatial_y // 8 * self.whole_cfg.model.spatial_x // 8 * 4, + self.cfg.spatial_y // 8 * self.cfg.spatial_x // 8 * 4, activation=build_activation(self.cfg.activation) ) @@ -391,8 +386,7 @@ def __init__(self, cfg): def forward(self, embedding, map_skip: List[Tensor], location=None): projected_embedding = self.project_embed(embedding) reshape_embedding = projected_embedding.reshape( - projected_embedding.shape[0], self.reshape_channel, self.whole_cfg.model.spatial_y // 8, - self.whole_cfg.model.spatial_x // 8 + projected_embedding.shape[0], self.reshape_channel, self.cfg.spatial_y // 8, self.cfg.spatial_x // 8 ) cat_feature = torch.cat([reshape_embedding, map_skip[-1]], dim=1) @@ -414,7 +408,7 @@ def forward(self, embedding, map_skip: List[Tensor], location=None): x = layer(x) logits_flatten = x.view(x.shape[0], -1) - logits_flatten.div_(self.whole_cfg.model.temperature) + logits_flatten.div_(self.cfg.temperature) p = F.softmax(logits_flatten, dim=1) if location is None: location = torch.multinomial(p, 1)[:, 0] diff --git a/dizoo/distar/model/head/action_type_head.py b/dizoo/distar/model/head/action_type_head.py index 104c4e0ad8..d16c2cdd3b 100644 --- a/dizoo/distar/model/head/action_type_head.py +++ b/dizoo/distar/model/head/action_type_head.py @@ -18,8 +18,7 @@ class ActionTypeHead(nn.Module): def __init__(self, cfg): super(ActionTypeHead, self).__init__() - self.whole_cfg = cfg - self.cfg = self.whole_cfg.model.policy.head.action_type_head + self.cfg = cfg self.act = build_activation(self.cfg.activation) # use relu as default self.project = fc_block(self.cfg.input_dim, self.cfg.res_dim, activation=self.act, norm_type=None) blocks = [ResFCBlock(self.cfg.res_dim, self.act, self.cfg.norm_type) for _ in range(self.cfg.res_num)] @@ -45,7 +44,7 @@ def forward(self, x = self.project(lstm_output) x = self.res(x) x = self.action_fc(x, scalar_context) - x.div_(self.whole_cfg.model.temperature) + x.div_(self.cfg.temperature) if self.use_mask: mask = ACTION_RACE_MASK[self.race].to(x.device) x = x.masked_fill(~mask.unsqueeze(dim=0), -1e9) diff --git a/dizoo/distar/model/model.py b/dizoo/distar/model/model.py index 01b8236bda..d47e3cab83 100644 --- a/dizoo/distar/model/model.py +++ b/dizoo/distar/model/model.py @@ -6,7 +6,8 @@ import torch import torch.nn as nn -from ding.utils import read_yaml_config, deep_merge_dicts, default_collate +from ding.utils import read_yaml_config, deep_merge_dicts +from ding.utils.data import default_collate from ding.torch_utils import detach_grad, script_lstm from dizoo.distar.envs import MAX_SELECTED_UNITS_NUM from .encoder import Encoder @@ -19,21 +20,23 @@ class Model(nn.Module): - def __init__(self, cfg={}, use_value_network=False): + def __init__(self, cfg, use_value_network=False): super(Model, self).__init__() - self.whole_cfg = deep_merge_dicts(alphastar_model_default_config, cfg) - self.cfg = self.whole_cfg.model - self.encoder = Encoder(self.whole_cfg) - self.policy = Policy(self.whole_cfg) - self._use_value_feature = self.whole_cfg.learner.use_value_feature - if use_value_network: - if self._use_value_feature: - self.value_encoder = ValueEncoder(self.whole_cfg) + self.cfg = deep_merge_dicts(alphastar_model_default_config, cfg).model + self.encoder = Encoder(self.cfg) + self.policy = Policy(self.cfg) + self.use_value_network = use_value_network + if self.use_value_network: + self.use_value_feature = self.cfg.value.use_value_feature + if self.use_value_feature: + self.value_encoder = ValueEncoder(self.cfg.value) self.value_networks = nn.ModuleDict() for k, v in self.cfg.value.items(): if k in self.cfg.enable_baselines: # creating a ValueBaseline network for each baseline, to be used in _critic_forward - self.value_networks[v.name] = ValueBaseline(v.param, self._use_value_feature) + value_cfg = v.param + value_cfg['use_value_feature'] = self.use_value_feature + self.value_networks[v.name] = ValueBaseline(value_cfg) # name of needed cumulative stat items self.only_update_baseline = self.cfg.only_update_baseline self.core_lstm = script_lstm( @@ -106,6 +109,7 @@ def rl_learn_forward( self, spatial_info, entity_info, scalar_info, entity_num, hidden_state, action_info, selected_units_num, behaviour_logp, teacher_logit, mask, reward, step, batch_size, unroll_len, **kwargs ): + assert self.use_value_network flat_action_info = {} for k, val in action_info.items(): flat_action_info[k] = torch.flatten(val, start_dim=0, end_dim=1) @@ -138,7 +142,7 @@ def rl_learn_forward( if self.only_update_baseline: critic_input = detach_grad(critic_input) baseline_feature = detach_grad(baseline_feature) - if self._use_value_feature: + if self.use_value_feature: value_feature = kwargs['value_feature'] value_feature = self.value_encoder(value_feature) critic_input = torch.cat([critic_input, value_feature, baseline_feature], dim=1) diff --git a/dizoo/distar/model/obs_encoder/entity_encoder.py b/dizoo/distar/model/obs_encoder/entity_encoder.py index 56ecf6d24d..93ffb7fe29 100644 --- a/dizoo/distar/model/obs_encoder/entity_encoder.py +++ b/dizoo/distar/model/obs_encoder/entity_encoder.py @@ -27,8 +27,7 @@ class EntityEncoder(nn.Module): def __init__(self, cfg): super(EntityEncoder, self).__init__() self.encode_modules = nn.ModuleDict() - self.whole_cfg = cfg - self.cfg = self.whole_cfg.model.encoder.obs_encoder.entity_encoder + self.cfg = cfg for k, item in self.cfg.module.items(): if item['arc'] == 'one_hot': self.encode_modules[k] = nn.Embedding.from_pretrained( @@ -52,10 +51,10 @@ def __init__(self, cfg): ) self.entity_fc = fc_block(self.cfg.output_dim, self.cfg.output_dim, activation=self.act) self.embed_fc = fc_block(self.cfg.output_dim, self.cfg.output_dim, activation=self.act) - if self.whole_cfg.model.entity_reduce_type == 'attention_pool': + if self.cfg.entity_reduce_type == 'attention_pool': from ding.torch_utils import AttentionPool self.attention_pool = AttentionPool(key_dim=self.cfg.output_dim, head_num=2, output_dim=self.cfg.output_dim) - elif self.whole_cfg.model.entity_reduce_type == 'attention_pool_add_num': + elif self.cfg.entity_reduce_type == 'attention_pool_add_num': from ding.torch_utils import AttentionPool self.attention_pool = AttentionPool( key_dim=self.cfg.output_dim, head_num=2, output_dim=self.cfg.output_dim, max_num=MAX_ENTITY_NUM + 1 @@ -85,15 +84,15 @@ def forward(self, x: Dict[str, Tensor], entity_num): x = self.transformer(x, mask=mask) entity_embeddings = self.entity_fc(self.act(x)) - if self.whole_cfg.model.entity_reduce_type in ['entity_num', 'selected_units_num']: + if self.cfg.entity_reduce_type in ['entity_num', 'selected_units_num']: x_mask = x * mask.unsqueeze(dim=2) embedded_entity = x_mask.sum(dim=1) / entity_num.unsqueeze(dim=-1) - elif self.whole_cfg.model.entity_reduce_type == 'constant': + elif self.cfg.entity_reduce_type == 'constant': x_mask = x * mask.unsqueeze(dim=2) embedded_entity = x_mask.sum(dim=1) / 512 - elif self.whole_cfg.model.entity_reduce_type == 'attention_pool': + elif self.cfg.entity_reduce_type == 'attention_pool': embedded_entity = self.attention_pool(x, mask=mask.unsqueeze(dim=2)) - elif self.whole_cfg.model.entity_reduce_type == 'attention_pool_add_num': + elif self.cfg.entity_reduce_type == 'attention_pool_add_num': embedded_entity = self.attention_pool(x, num=entity_num, mask=mask.unsqueeze(dim=2)) else: raise NotImplementedError diff --git a/dizoo/distar/model/obs_encoder/scalar_encoder.py b/dizoo/distar/model/obs_encoder/scalar_encoder.py index 83fcae8d03..3bad5cb933 100644 --- a/dizoo/distar/model/obs_encoder/scalar_encoder.py +++ b/dizoo/distar/model/obs_encoder/scalar_encoder.py @@ -17,10 +17,9 @@ def compute_denominator(x: torch.Tensor, dim: int) -> torch.Tensor: class BeginningBuildOrderEncoder(nn.Module): - def __init__(self, cfg, bo_cfg): + def __init__(self, cfg): super(BeginningBuildOrderEncoder, self).__init__() - self.whole_cfg = cfg - self.cfg = bo_cfg + self.cfg = cfg self.output_dim = self.cfg.output_dim self.input_dim = self.cfg.action_one_hot_dim + 20 + self.cfg.binary_dim * 2 self.act = build_activation(self.cfg.activation) @@ -49,8 +48,8 @@ def _add_seq_info(self, x): def forward(self, x, bo_location): x = self.action_one_hot(x.long()) x = self._add_seq_info(x) - location_x = bo_location % self.whole_cfg.model.spatial_x - location_y = bo_location // self.whole_cfg.model.spatial_x + location_x = bo_location % self.cfg.spatial_x + location_y = bo_location // self.cfg.spatial_x location_x = self.location_binary(location_x.long()) location_y = self.location_binary(location_y.long()) x = torch.cat([x, location_x, location_y], dim=2) @@ -65,8 +64,7 @@ class ScalarEncoder(nn.Module): def __init__(self, cfg): super(ScalarEncoder, self).__init__() - self.whole_cfg = cfg - self.cfg = self.whole_cfg.model.encoder.obs_encoder.scalar_encoder + self.cfg = cfg self.act = build_activation(self.cfg.activation) self.keys = [] self.scalar_context_keys = [] @@ -98,8 +96,8 @@ def __init__(self, cfg): requires_grad=False ) self.time_embedding_dim = self.cfg.module.time.output_dim - bo_cfg = self.whole_cfg.model.encoder.obs_encoder.scalar_encoder.module.beginning_order - self.encode_modules['beginning_order'] = BeginningBuildOrderEncoder(self.whole_cfg, bo_cfg) + bo_cfg = self.cfg.module.beginning_order + self.encode_modules['beginning_order'] = BeginningBuildOrderEncoder(bo_cfg) def time_encoder(self, x: Tensor): v = torch.zeros(size=(x.shape[0], self.time_embedding_dim), dtype=torch.float, device=x.device) diff --git a/dizoo/distar/model/obs_encoder/spatial_encoder.py b/dizoo/distar/model/obs_encoder/spatial_encoder.py index f4dcabf728..95549eef07 100644 --- a/dizoo/distar/model/obs_encoder/spatial_encoder.py +++ b/dizoo/distar/model/obs_encoder/spatial_encoder.py @@ -11,8 +11,7 @@ class SpatialEncoder(nn.Module): def __init__(self, cfg): super(SpatialEncoder, self).__init__() - self.whole_cfg = cfg - self.cfg = self.whole_cfg.model.encoder.obs_encoder.spatial_encoder + self.cfg = cfg self.act = build_activation(self.cfg.activation) if self.cfg.norm_type == 'none': self.norm = None @@ -49,9 +48,7 @@ def __init__(self, cfg): self.res.append(ResBlock(dim, self.act, norm_type=self.norm)) if self.head_type == 'fc': self.fc = fc_block( - dim * self.whole_cfg.model.spatial_y // 8 * self.whole_cfg.model.spatial_x // 8, - self.cfg.fc_dim, - activation=self.act + dim * self.cfg.spatial_y // 8 * self.cfg.spatial_x // 8, self.cfg.fc_dim, activation=self.act ) else: self.gap = nn.AdaptiveAvgPool2d((1, 1)) @@ -68,7 +65,7 @@ def forward(self, x, scatter_map): assert k == 'height_map' embeddings.append(x[k].unsqueeze(dim=1).float() / 256) elif item['arc'] == 'scatter': - bs, shape_x, shape_y = x[k].shape[0], self.whole_cfg.model.spatial_x, self.whole_cfg.model.spatial_y + bs, shape_x, shape_y = x[k].shape[0], self.cfg.spatial_x, self.cfg.spatial_y embedding = torch.zeros(bs * shape_y * shape_x, device=x[k].device) bias = torch.arange(bs, device=x[k].device).unsqueeze(dim=1) * shape_y * shape_x x[k] = x[k] + bias diff --git a/dizoo/distar/model/obs_encoder/value_encoder.py b/dizoo/distar/model/obs_encoder/value_encoder.py index 81e42ac838..a8183c3233 100644 --- a/dizoo/distar/model/obs_encoder/value_encoder.py +++ b/dizoo/distar/model/obs_encoder/value_encoder.py @@ -47,7 +47,7 @@ def __init__(self, cfg): for i in range(self.resblock_num): self.res.append(ResBlock(dim, self.act, norm_type=None)) self.spatial_fc = fc_block( - dim * self.whole_cfg.model.spatial_y // 8 * self.whole_cfg.model.spatial_x // 8, + dim * self.cfg.spatial_y // 8 * self.cfg.spatial_x // 8, self.cfg.spatial.spatial_fc_dim, activation=self.act ) diff --git a/dizoo/distar/model/policy.py b/dizoo/distar/model/policy.py index 8c6d0de52a..45b7d24604 100644 --- a/dizoo/distar/model/policy.py +++ b/dizoo/distar/model/policy.py @@ -11,14 +11,13 @@ class Policy(nn.Module): def __init__(self, cfg): super(Policy, self).__init__() - self.whole_cfg = cfg - self.cfg = cfg.model.policy - self.action_type_head = ActionTypeHead(self.whole_cfg) - self.delay_head = DelayHead(self.whole_cfg) - self.queued_head = QueuedHead(self.whole_cfg) - self.selected_units_head = SelectedUnitsHead(self.whole_cfg) - self.target_unit_head = TargetUnitHead(self.whole_cfg) - self.location_head = LocationHead(self.whole_cfg) + self.cfg = cfg.policy + self.action_type_head = ActionTypeHead(self.cfg.head.action_type_head) + self.delay_head = DelayHead(self.cfg.head.delay_head) + self.queued_head = QueuedHead(self.cfg.head.queued_head) + self.selected_units_head = SelectedUnitsHead(self.cfg.head.selected_units_head) + self.target_unit_head = TargetUnitHead(self.cfg.head.target_unit_head) + self.location_head = LocationHead(self.cfg.head.location_head) def forward( self, lstm_output: Tensor, entity_embeddings: Tensor, map_skip: List[Tensor], scalar_context: Tensor, diff --git a/dizoo/distar/model/tests/test_head.py b/dizoo/distar/model/tests/test_head.py index aee499232e..4408f39df5 100644 --- a/dizoo/distar/model/tests/test_head.py +++ b/dizoo/distar/model/tests/test_head.py @@ -13,7 +13,7 @@ class TestHead(): def test_action_type_head(self): cfg = total_config.model.policy.head.action_type_head - head = ActionTypeHead(total_config) + head = ActionTypeHead(cfg) lstm_output = torch.randn(B, cfg.input_dim) scalar_context = torch.randn(B, cfg.context_dim) @@ -29,7 +29,7 @@ def test_action_type_head(self): def test_delay_head(self): cfg = total_config.model.policy.head.delay_head - head = DelayHead(total_config) + head = DelayHead(cfg) inputs = torch.randn(B, cfg.input_dim) logit, delay, embedding = head(inputs) @@ -44,7 +44,7 @@ def test_delay_head(self): def test_queued_head(self): cfg = total_config.model.policy.head.queued_head - head = QueuedHead(total_config) + head = QueuedHead(cfg) inputs = torch.randn(B, cfg.input_dim) logit, queued, embedding = head(inputs) @@ -59,7 +59,7 @@ def test_queued_head(self): def test_target_unit_head(self): cfg = total_config.model.policy.head.target_unit_head - head = TargetUnitHead(total_config) + head = TargetUnitHead(cfg) inputs = torch.randn(B, cfg.input_dim) entity_embedding = torch.rand(B, ENTITY, cfg.entity_embedding_dim) entity_num = torch.randint(ENTITY // 2, ENTITY, size=(B, )) @@ -75,9 +75,9 @@ def test_target_unit_head(self): def test_location_head(self): cfg = total_config.model.policy.head.location_head - head = LocationHead(total_config) + head = LocationHead(cfg) inputs = torch.randn(B, cfg.input_dim) - Y, X = total_config.model.spatial_y, total_config.model.spatial_x + Y, X = cfg.spatial_y, cfg.spatial_x map_skip = [torch.randn(B, cfg.res_dim, Y // 8, X // 8) for _ in range(cfg.res_num)] logit, location = head(inputs, map_skip) @@ -90,7 +90,7 @@ def test_location_head(self): def test_selected_units_head(self): cfg = total_config.model.policy.head.selected_units_head - head = SelectedUnitsHead(total_config) + head = SelectedUnitsHead(cfg) inputs = torch.randn(B, cfg.input_dim) entity_embedding = torch.rand(B, ENTITY, cfg.entity_embedding_dim) entity_num = torch.randint(ENTITY // 2, ENTITY, size=(B, )) From 6d653a196246c0742f13355f419deb676f0257a7 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Thu, 16 Jun 2022 13:31:30 +0800 Subject: [PATCH 122/229] add timer --- ding/envs/env_manager/base_env_manager.py | 2 ++ ding/framework/middleware/league_actor.py | 36 +++++++++++++++++++ .../middleware/tests/league_config.py | 2 +- .../middleware/tests/mock_for_test.py | 1 + .../middleware/tests/test_league_pipeline.py | 1 + 5 files changed, 41 insertions(+), 1 deletion(-) diff --git a/ding/envs/env_manager/base_env_manager.py b/ding/envs/env_manager/base_env_manager.py index b335db8dd2..991f4b588b 100644 --- a/ding/envs/env_manager/base_env_manager.py +++ b/ding/envs/env_manager/base_env_manager.py @@ -77,7 +77,9 @@ def default_config(cls: type) -> EasyDict: config = dict( episode_num=float("inf"), max_retry=1, + # inf retry_type='reset', + # renew auto_reset=True, step_timeout=None, reset_timeout=None, diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 3edfbfc0a3..39228ecc36 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -2,6 +2,7 @@ import logging from typing import TYPE_CHECKING, Dict, Callable +from ding.league import player from ding.policy import Policy from ding.framework.middleware import BattleEpisodeCollector, BattleStepCollector @@ -10,6 +11,7 @@ from threading import Lock import queue from easydict import EasyDict +import time if TYPE_CHECKING: from ding.league.v2.base_league import Job @@ -34,6 +36,7 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.model_dict_lock = Lock() self.agent_num = 2 + self.collect_time = {} def _on_learner_model(self, learner_model: "LearnerModel"): """ @@ -61,6 +64,7 @@ def _get_collector(self, player_id: str): ) ) self._collectors[player_id] = collector + self.collect_time[player_id] = 0 return collector def _get_policy(self, player: "PlayerMeta") -> "Policy.collect_function": @@ -123,12 +127,27 @@ def __call__(self, ctx: "BattleContext"): ctx.episode_info = [[] for _ in range(self.agent_num)] ctx.remain_episode = ctx.n_episode while True: + old_envstep = ctx.total_envstep_count + time_begin = time.time() collector(ctx) if not job.is_eval and len(ctx.episodes[0]) > 0: actor_data = ActorData(env_step=ctx.total_envstep_count, train_data=ctx.episodes[0]) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=job.launch_player), actor_data) ctx.episodes = [] + time_end = time.time() + self.collect_time[job.launch_player] += time_end - time_begin + total_collect_speed = ctx.total_envstep_count / self.collect_time[job.launch_player] if self.collect_time[ + job.launch_player] != 0 else 0 + envstep_passed = ctx.total_envstep_count - old_envstep + real_time_speed = envstep_passed / (time_end - time_begin) + print( + 'in actor {}, total_env_step:{}, current job env_step: {}, total_collect_speed: {} env_step/s, real-time collect speed: {} env_step/s' + .format( + task.router.node_id, ctx.total_envstep_count, ctx.env_step, total_collect_speed, real_time_speed + ) + ) + if ctx.job_finish is True: job.result = [e['result'] for e in ctx.episode_info[0]] task.emit(EventEnum.ACTOR_FINISH_JOB, job) @@ -154,6 +173,8 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.agent_num = 2 + self.collect_time = {} + # self._gae_estimator = gae_estimator(cfg, policy_fn().collect_mode) def _on_learner_model(self, learner_model: "LearnerModel"): @@ -182,6 +203,7 @@ def _get_collector(self, player_id: str): ) ) self._collectors[player_id] = collector + self.collect_time[player_id] = 0 return collector def _get_policy(self, player: "PlayerMeta") -> "Policy.collect_function": @@ -246,6 +268,8 @@ def __call__(self, ctx: "BattleContext"): ctx.remain_episode = ctx.n_episode while True: + time_begin = time.time() + old_envstep = ctx.total_envstep_count collector(ctx) if not job.is_eval and len(ctx.trajectories_list[0]) > 0: @@ -258,6 +282,18 @@ def __call__(self, ctx: "BattleContext"): ctx.trajectories_list = [] ctx.trajectory_end_idx_list = [] + time_end = time.time() + self.collect_time[job.launch_player] += time_end - time_begin + total_collect_speed = ctx.total_envstep_count / self.collect_time[job.launch_player] if self.collect_time[ + job.launch_player] != 0 else 0 + envstep_passed = ctx.total_envstep_count - old_envstep + real_time_speed = envstep_passed / (time_end - time_begin) + print( + 'in actor {}, total_env_step: {}, current job env_step: {}, total_collect_speed: {} env_step/s, real-time collect speed: {} env_step/s' + .format( + task.router.node_id, ctx.total_envstep_count, ctx.env_step, total_collect_speed, real_time_speed + ) + ) if ctx.job_finish is True: job.result = [e['result'] for e in ctx.episode_info[0]] diff --git a/ding/framework/middleware/tests/league_config.py b/ding/framework/middleware/tests/league_config.py index f8a08c6069..3d1e6b5b1d 100644 --- a/ding/framework/middleware/tests/league_config.py +++ b/ding/framework/middleware/tests/league_config.py @@ -77,7 +77,7 @@ }, 'discount_factor': 1.0, 'gae_lambda': 1.0, - 'n_episode': 2, + 'n_episode': 1, 'n_rollout_samples': 32, 'n_sample': 64, 'unroll_len': 2 diff --git a/ding/framework/middleware/tests/mock_for_test.py b/ding/framework/middleware/tests/mock_for_test.py index 6d3c21ed05..789bd28460 100644 --- a/ding/framework/middleware/tests/mock_for_test.py +++ b/ding/framework/middleware/tests/mock_for_test.py @@ -323,6 +323,7 @@ def battle_rolloutor_for_distar(cfg: EasyDict, env: BaseEnvManager, transitions_ def _battle_rolloutor(ctx: "BattleContext"): timesteps = env.step(ctx.actions) + # TODO: change this part to only modify the part of current episode, not influence previous episode error_env_id_list = [] for env_id, timestep in timesteps.items(): if timestep.info.get('step_error'): diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index 2afe43e56d..ad5b927d9c 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -23,6 +23,7 @@ def prepare_test(): env_cfg = read_config('./test_distar_config.yaml') def env_fn(): + # subprocess env manager env = BaseEnvManager( env_fn=[lambda: DIStarEnv(env_cfg) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager ) From 5d422d6f22874ace9ca62291de6e14fb801b7969 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Thu, 16 Jun 2022 13:58:00 +0800 Subject: [PATCH 123/229] add log --- ding/framework/middleware/league_actor.py | 4 ++-- ding/framework/middleware/league_coordinator.py | 10 +++++----- ding/framework/middleware/league_learner.py | 8 ++++---- 3 files changed, 11 insertions(+), 11 deletions(-) diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 39228ecc36..66b978f545 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -181,7 +181,7 @@ def _on_learner_model(self, learner_model: "LearnerModel"): """ If get newest learner model, put it inside model_queue. """ - print('Actor {} recieved model \n'.format(task.router.node_id), flush=True) + print('Actor {} recieved model {} \n'.format(task.router.node_id, learner_model.player_id), flush=True) with self.model_dict_lock: self.model_dict[learner_model.player_id] = learner_model @@ -252,7 +252,7 @@ def __call__(self, ctx: "BattleContext"): job = self._get_job() if job is None: return - print('For actor {}, a job begin \n'.format(task.router.node_id), flush=True) + print('For actor {}, a job {} begin \n'.format(task.router.node_id, job.launch_player), flush=True) ctx.player_id_list = [player.player_id for player in job.players] self.agent_num = len(job.players) diff --git a/ding/framework/middleware/league_coordinator.py b/ding/framework/middleware/league_coordinator.py index 43300d8711..ec85766a8d 100644 --- a/ding/framework/middleware/league_coordinator.py +++ b/ding/framework/middleware/league_coordinator.py @@ -27,7 +27,7 @@ def __init__(self, league: "BaseLeague") -> None: task.on(EventEnum.ACTOR_FINISH_JOB, self._on_actor_job) def _on_actor_greeting(self, actor_id): - print('coordinator recieve actor greeting\n', flush=True) + print('coordinator recieve actor {} greeting\n'.format(actor_id), flush=True) with self._lock: player_num = len(self.league.active_players_ids) player_id = self.league.active_players_ids[self._total_send_jobs % player_num] @@ -37,22 +37,22 @@ def _on_actor_greeting(self, actor_id): if job.job_no > 0 and job.job_no % self._eval_frequency == 0: job.is_eval = True job.actor_id = actor_id - print('coordinator emit job\n', flush=True) + print('coordinator emit job (main_player: {}) to actor {}\n'.format(job.launch_player, actor_id), flush=True) task.emit(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=actor_id), job) def _on_learner_meta(self, player_meta: "PlayerMeta"): - print('coordinator recieve learner meta\n', flush=True) + print('coordinator recieve learner meta for player{}\n'.format(player_meta.player_id), flush=True) # print("on_learner_meta {}".format(player_meta)) self.league.update_active_player(player_meta) self.league.create_historical_player(player_meta) def _on_actor_job(self, job: "Job"): - print('coordinator recieve actor finished job\n', flush=True) + print('coordinator recieve actor finished job, palyer {}\n'.format(job.launch_player), flush=True) print("on_actor_job {}".format(job.launch_player)) # right self.league.update_payoff(job) def __del__(self): - print('task finished, coordinator closed', flush=True) + print('task finished, coordinator {} closed'.format(task.router.node_id), flush=True) def __call__(self, ctx: "Context") -> None: sleep(1) diff --git a/ding/framework/middleware/league_learner.py b/ding/framework/middleware/league_learner.py index af7ec59039..cb02eb25e6 100644 --- a/ding/framework/middleware/league_learner.py +++ b/ding/framework/middleware/league_learner.py @@ -37,7 +37,7 @@ def __init__(self, cfg: dict, policy_fn: Callable, player: "ActivePlayer") -> No self._step = 0 def _on_actor_send_data(self, actor_data: "ActorData"): - print("learner receive data from actor! \n", flush=True) + print("learner {} receive data from actor! \n".format(task.router.node_id), flush=True) with self._lock: cfg = self.cfg for _ in range(cfg.policy.learn.update_per_collect): @@ -50,7 +50,7 @@ def _on_actor_send_data(self, actor_data: "ActorData"): # print("save checkpoint") checkpoint = self._save_checkpoint() if self.player.is_trained_enough() else None - print('learner send player meta\n', flush=True) + print('learner {} send player meta {}\n'.format(task.router.node_id, self.player_id), flush=True) task.emit( EventEnum.LEARNER_SEND_META, PlayerMeta(player_id=self.player_id, checkpoint=checkpoint, total_agent_step=self._learner.train_iter) @@ -60,7 +60,7 @@ def _on_actor_send_data(self, actor_data: "ActorData"): learner_model = LearnerModel( player_id=self.player_id, state_dict=self._learner.policy.state_dict(), train_iter=self._learner.train_iter ) - print('learner send model\n', flush=True) + print('learner {} send model\n'.format(task.router.node_id), flush=True) task.emit(EventEnum.LEARNER_SEND_MODEL, learner_model) def _get_learner(self) -> BaseLearner: @@ -84,7 +84,7 @@ def _save_checkpoint(self) -> Optional[Storage]: return storage def __del__(self): - print('task finished, learner closed', flush=True) + print('task finished, learner {} closed\n'.format(task.router.node_id), flush=True) def __call__(self, _: "Context") -> None: sleep(1) From 17469058760fbd4d4c1a3786470cb5e305bd8efe Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Fri, 17 Jun 2022 14:07:19 +0800 Subject: [PATCH 124/229] add walltime data, change ActorData Structure --- ding/framework/middleware/functional/__init__.py | 2 +- ding/framework/middleware/functional/actor_data.py | 11 ++++++++++- ding/framework/middleware/league_actor.py | 11 +++++++++-- 3 files changed, 20 insertions(+), 4 deletions(-) diff --git a/ding/framework/middleware/functional/__init__.py b/ding/framework/middleware/functional/__init__.py index c17d0e8a63..d357380d62 100644 --- a/ding/framework/middleware/functional/__init__.py +++ b/ding/framework/middleware/functional/__init__.py @@ -10,4 +10,4 @@ from .explorer import eps_greedy_handler, eps_greedy_masker from .advantage_estimator import gae_estimator from .enhancer import reward_estimator, her_data_enhancer, nstep_reward_enhancer -from .actor_data import ActorData +from .actor_data import ActorData, ActorDataMeta diff --git a/ding/framework/middleware/functional/actor_data.py b/ding/framework/middleware/functional/actor_data.py index 2540e1862c..07563075e9 100644 --- a/ding/framework/middleware/functional/actor_data.py +++ b/ding/framework/middleware/functional/actor_data.py @@ -2,7 +2,16 @@ from dataclasses import dataclass +@dataclass +class ActorDataMeta: + palyer_total_env_step: int = 0 + actor_id: int = 0 + env_id: int = 0 + send_wall_time: float = 0.0 + + @dataclass class ActorData: + meta: ActorDataMeta + # TODO make train data a list in which each env_id has a list train_data: Any - env_step: int = 0 diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 66b978f545..1e7f490e69 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -6,7 +6,7 @@ from ding.policy import Policy from ding.framework.middleware import BattleEpisodeCollector, BattleStepCollector -from ding.framework.middleware.functional import ActorData +from ding.framework.middleware.functional import ActorData, ActorDataMeta from ding.league.player import PlayerMeta from threading import Lock import queue @@ -276,7 +276,14 @@ def __call__(self, ctx: "BattleContext"): trajectories = ctx.trajectories_list[0] trajectory_end_idx = ctx.trajectory_end_idx_list[0] print('actor {}, len trajectories {}'.format(task.router.node_id, len(trajectories)), flush=True) - actor_data = ActorData(env_step=ctx.total_envstep_count, train_data=trajectories) + meta_data = ActorDataMeta( + player_total_env_step=ctx.total_envstep_count, + actor_id=task.router.node_id, + # TODO transfer env_id to train_data, each env has a trajectory or not + env_id=0, + send_wall_time=time.time() + ) + actor_data = ActorData(meta=meta_data, train_data=trajectories) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=job.launch_player), actor_data) print('Actor {} send data\n'.format(task.router.node_id), flush=True) From a30e23b3238061bc27e1b20581f4404e2a62748e Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Fri, 17 Jun 2022 19:13:16 +0800 Subject: [PATCH 125/229] battle_transition_list, need to change list to deque --- .../middleware/functional/__init__.py | 2 +- .../middleware/functional/collector.py | 68 +++++++++++ .../middleware/tests/test_collector.py | 108 ++++++++++++++++++ 3 files changed, 177 insertions(+), 1 deletion(-) diff --git a/ding/framework/middleware/functional/__init__.py b/ding/framework/middleware/functional/__init__.py index d357380d62..1b73b61a39 100644 --- a/ding/framework/middleware/functional/__init__.py +++ b/ding/framework/middleware/functional/__init__.py @@ -1,7 +1,7 @@ from .trainer import trainer, multistep_trainer from .data_processor import offpolicy_data_fetcher, data_pusher, offline_data_fetcher, offline_data_saver, \ sqil_data_pusher -from .collector import inferencer, rolloutor, TransitionList, battle_inferencer, battle_rolloutor +from .collector import inferencer, rolloutor, TransitionList, BattleTransitionList, battle_inferencer, battle_rolloutor from .evaluator import interaction_evaluator from .termination_checker import termination_checker from .pace_controller import pace_controller diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 6cc9fc86e2..bfb4681141 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -54,6 +54,74 @@ def length(self, env_id: int) -> int: return len(self._transitions[env_id]) +class BattleTransitionList: + + def __init__(self, env_num: int, unroll_len: int) -> None: + self.env_num = env_num + self._transitions = [[] for _ in range(env_num)] + self._done_episode = [[] for _ in range(env_num)] + self._unroll_len = unroll_len + + def get_trajectories(self, env_id: int): + trajectories = [] + if len(self._transitions[env_id]) == 0: + return None + while len(self._transitions[env_id]) > 0: + if self._done_episode[env_id][0] is False: + break + trajectories += self._cut_trajectory_from_episode(self._transitions[env_id][0]) + self._transitions[env_id][0].clear() + self._transitions[env_id] = self._transitions[env_id][1:] + self._done_episode[env_id] = self._done_episode[env_id][1:] + + if len(self._transitions[env_id]) == 1 and self._done_episode[env_id][0] is False: + tail_idx = max( + 0, ((len(self._transitions[env_id][0]) - self._unroll_len) // self._unroll_len) * self._unroll_len + ) + trajectories += self._cut_trajectory_from_episode(self._transitions[env_id][0][:tail_idx]) + self._transitions[env_id][0] = self._transitions[env_id][0][tail_idx:] + + return trajectories + + def _cut_trajectory_from_episode(self, episode: list): + return_episode = [] + i = 0 + num_complele_trajectory, num_tail_transitions = divmod(len(episode), self._unroll_len) + for i in range(num_complele_trajectory): + trajectory = episode[i * self._unroll_len:(i + 1) * self._unroll_len] + return_episode.append(trajectory) + + if num_tail_transitions > 0: + trajectory = episode[-self._unroll_len:] + if len(trajectory) < self._unroll_len: + initial_elements = [] + for _ in range(self._unroll_len - len(trajectory)): + initial_elements.append(trajectory[0]) + trajectory = initial_elements + trajectory + return_episode.append(trajectory) + + return return_episode # list of trajectories + + def clear_newest_transition(self, env_id: int) -> None: + self._transitions[env_id][-1].clear() + self._transitions[env_id] = self._transitions[env_id][:-1] + self._done_episode[env_id] = self._done_episode[env_id][:-1] + + def append(self, env_id: int, transition: Any) -> None: + if len(self._done_episode[env_id]) == 0 or self._done_episode[env_id][-1] is True: + self._transitions[env_id].append([]) + self._done_episode[env_id].append(False) + self._transitions[env_id][-1].append(transition) + if transition.done: + self._done_episode[env_id][-1] = True + + def clear(self): + for item in self._transitions: + item.clear() + for item in self._done_idx: + item.clear() + + def inferencer(cfg: EasyDict, policy: Policy, env: BaseEnvManager) -> Callable: """ Overview: diff --git a/ding/framework/middleware/tests/test_collector.py b/ding/framework/middleware/tests/test_collector.py index 16c577ae2b..3b0f60ba21 100644 --- a/ding/framework/middleware/tests/test_collector.py +++ b/ding/framework/middleware/tests/test_collector.py @@ -84,3 +84,111 @@ def test_episode_collector(): collector = EpisodeCollector(cfg, policy, env, random_collect_size=8) collector(ctx) assert len(ctx.episodes) == 16 + + +from ding.framework.middleware import BattleTransitionList +from easydict import EasyDict + + +@pytest.mark.unittest +def test_battle_transition_list(): + env_num = 2 + unroll_len = 32 + transition_list = BattleTransitionList(env_num, unroll_len) + len_env_0 = 48 + len_env_1 = 72 + + for i in range(len_env_0): + timestep = EasyDict({'obs': i, 'done': False}) + transition_list.append(env_id=0, transition=timestep) + + for i in range(len_env_1): + timestep = EasyDict({'obs': i, 'done': False}) + transition_list.append(env_id=1, transition=timestep) + + transition_list.append(env_id=0, transition=EasyDict({'obs': len_env_0, 'done': True})) + transition_list.append(env_id=1, transition=EasyDict({'obs': len_env_1, 'done': True})) + + len_env_0_2 = 12 + len_env_1_2 = 72 + + for i in range(len_env_0_2): + timestep = EasyDict({'obs': i, 'done': False}) + transition_list.append(env_id=0, transition=timestep) + transition_list.append(env_id=0, transition=EasyDict({'obs': len_env_0_2, 'done': True})) + for i in range(len_env_1_2): + timestep = EasyDict({'obs': i, 'done': False}) + transition_list.append(env_id=1, transition=timestep) + + env_0_result = transition_list.get_trajectories(env_id=0) + env_1_result = transition_list.get_trajectories(env_id=1) + + print(env_0_result) + print(env_1_result) + + # print(env_0_result) + assert len(env_0_result) == 3 + # print(env_1_result) + assert len(env_1_result) == 4 + + for trajectory in env_0_result: + assert len(trajectory) == unroll_len + for trajectory in env_1_result: + assert len(trajectory) == unroll_len + #env_0 + i = 0 + for trajectory in env_0_result[:-2]: + assert len(trajectory) == unroll_len + for transition in trajectory: + assert transition.obs == i + i += 1 + + trajectory = env_0_result[-2] + assert len(trajectory) == unroll_len + + i = len_env_0 - unroll_len + 1 + for transition in trajectory: + assert transition.obs == i + i += 1 + + trajectory = env_0_result[-1] + assert len(trajectory) == unroll_len + test_number = 0 + for i, transition in enumerate(trajectory): + if i < unroll_len - len_env_0_2 - 1: + assert transition.obs == 0 + else: + assert transition.obs == test_number + test_number += 1 + + #env_1 + i = 0 + for trajectory in env_1_result[:2]: + assert len(trajectory) == unroll_len + for transition in trajectory: + assert transition.obs == i + i += 1 + + trajectory = env_1_result[2] + assert len(trajectory) == unroll_len + + i = len_env_1 - unroll_len + 1 + for transition in trajectory: + assert transition.obs == i + i += 1 + + trajectory = env_1_result[3] + assert len(trajectory) == unroll_len + i = 0 + for transition in trajectory: + assert transition.obs == i + i += 1 + + # print(env_0_result) + # print(env_1_result) + print(transition_list._transitions[0]) + print(transition_list._transitions[1]) + + +if __name__ == '__main__': + test_battle_transition_list() \ No newline at end of file From d7a25637a9826b0edff04d2572aec431feebcbf1 Mon Sep 17 00:00:00 2001 From: niuyazhe Date: Sun, 19 Jun 2022 22:43:34 +0800 Subject: [PATCH 126/229] test(nyz): add distar policy learn unittest --- ding/policy/base_policy.py | 9 +- ding/torch_utils/network/rnn.py | 2 - ding/utils/data/collate_fn.py | 24 +- dizoo/distar/envs/__init__.py | 1 + dizoo/distar/envs/fake_data.py | 302 +++++++--------------- dizoo/distar/envs/meta.py | 3 +- dizoo/distar/policy/__init__.py | 1 + dizoo/distar/policy/distar_policy.py | 57 +++- dizoo/distar/policy/test_distar_policy.py | 15 ++ dizoo/distar/policy/utils.py | 6 +- 10 files changed, 178 insertions(+), 242 deletions(-) create mode 100644 dizoo/distar/policy/__init__.py create mode 100644 dizoo/distar/policy/test_distar_policy.py diff --git a/ding/policy/base_policy.py b/ding/policy/base_policy.py index a30b080015..52491ed5cb 100644 --- a/ding/policy/base_policy.py +++ b/ding/policy/base_policy.py @@ -69,7 +69,7 @@ def __init__( assert set(self._enable_field).issubset(self.total_field), self._enable_field if len(set(self._enable_field).intersection(set(['learn', 'collect', 'eval']))) > 0: - model = self._create_model(cfg, model) + model = self._create_model(cfg, model, enable_field) self._cuda = cfg.cuda and torch.cuda.is_available() # now only support multi-gpu for only enable learn mode if len(set(self._enable_field).intersection(set(['learn']))) > 0: @@ -117,7 +117,12 @@ def hook(*ignore): grad_acc = p_tmp.grad_fn.next_functions[0][0] grad_acc.register_hook(make_hook(name, p)) - def _create_model(self, cfg: dict, model: Optional[torch.nn.Module] = None) -> torch.nn.Module: + def _create_model( + self, + cfg: dict, + model: Optional[torch.nn.Module] = None, + enable_field: Optional[List[str]] = None + ) -> torch.nn.Module: if model is None: model_cfg = cfg.model if 'type' not in model_cfg: diff --git a/ding/torch_utils/network/rnn.py b/ding/torch_utils/network/rnn.py index 45d3dab5bd..bbe3bb627c 100644 --- a/ding/torch_utils/network/rnn.py +++ b/ding/torch_utils/network/rnn.py @@ -36,8 +36,6 @@ def sequence_mask(lengths: torch.Tensor, max_len: Optional[int] = None) -> torch bz = lengths.numel() if max_len is None: max_len = lengths.max() - else: - max_len = min(max_len, lengths.max()) return torch.arange(0, max_len).type_as(lengths).repeat(bz, 1).lt(lengths).to(lengths.device) diff --git a/ding/utils/data/collate_fn.py b/ding/utils/data/collate_fn.py index 0b7fcda9cb..3b534a1980 100644 --- a/ding/utils/data/collate_fn.py +++ b/ding/utils/data/collate_fn.py @@ -26,7 +26,9 @@ def ttorch_collate(x): def default_collate(batch: Sequence, + dim: int = 0, cat_1dim: bool = True, + allow_key_mismatch: bool = False, ignore_prefix: list = ['collate_ignore']) -> Union[torch.Tensor, Mapping, Sequence]: """ Overview: @@ -71,10 +73,10 @@ def default_collate(batch: Sequence, out = elem.new(storage) if elem.shape == (1, ) and cat_1dim: # reshape (B, 1) -> (B) - return torch.cat(batch, 0, out=out) + return torch.cat(batch, dim, out=out) # return torch.stack(batch, 0, out=out) else: - return torch.stack(batch, 0, out=out) + return torch.stack(batch, dim, out=out) elif isinstance(elem, ttorch.Tensor): ret = ttorch.stack(batch).json() for k in ret: @@ -87,7 +89,7 @@ def default_collate(batch: Sequence, # array of string classes and object if np_str_obj_array_pattern.search(elem.dtype.str) is not None: raise TypeError(default_collate_err_msg_format.format(elem.dtype)) - return default_collate([torch.as_tensor(b) for b in batch], cat_1dim=cat_1dim) + return default_collate([torch.as_tensor(b) for b in batch], dim=dim, cat_1dim=cat_1dim) elif elem.shape == (): # scalars return torch.as_tensor(batch) elif isinstance(elem, float): @@ -100,16 +102,22 @@ def default_collate(batch: Sequence, elif isinstance(elem, container_abcs.Mapping): ret = {} for key in elem: - if any([key.startswith(t) for t in ignore_prefix]): - ret[key] = [d[key] for d in batch] + if allow_key_mismatch: + if any([key.startswith(t) for t in ignore_prefix]): + ret[key] = [d[key] for d in batch if key in d.keys()] + else: + ret[key] = default_collate([d[key] for d in batch if key in d.keys()], dim=dim, cat_1dim=cat_1dim) else: - ret[key] = default_collate([d[key] for d in batch], cat_1dim=cat_1dim) + if any([key.startswith(t) for t in ignore_prefix]): + ret[key] = [d[key] for d in batch] + else: + ret[key] = default_collate([d[key] for d in batch], dim=dim, cat_1dim=cat_1dim) return ret elif isinstance(elem, tuple) and hasattr(elem, '_fields'): # namedtuple - return elem_type(*(default_collate(samples, cat_1dim=cat_1dim) for samples in zip(*batch))) + return elem_type(*(default_collate(samples, dim=dim, cat_1dim=cat_1dim) for samples in zip(*batch))) elif isinstance(elem, container_abcs.Sequence): transposed = zip(*batch) - return [default_collate(samples, cat_1dim=cat_1dim) for samples in transposed] + return [default_collate(samples, dim=dim, cat_1dim=cat_1dim) for samples in transposed] raise TypeError(default_collate_err_msg_format.format(elem_type)) diff --git a/dizoo/distar/envs/__init__.py b/dizoo/distar/envs/__init__.py index 66f1c31e80..1c80372f03 100644 --- a/dizoo/distar/envs/__init__.py +++ b/dizoo/distar/envs/__init__.py @@ -1,2 +1,3 @@ from .meta import * from .static_data import BEGIN_ACTIONS, ACTION_RACE_MASK, SELECTED_UNITS_MASK +from .fake_data import get_fake_rl_trajectory diff --git a/dizoo/distar/envs/fake_data.py b/dizoo/distar/envs/fake_data.py index 1b98ddbda7..ec910eaa72 100644 --- a/dizoo/distar/envs/fake_data.py +++ b/dizoo/distar/envs/fake_data.py @@ -1,18 +1,13 @@ from typing import Sequence import torch +from ding.utils.data import default_collate from .meta import MAX_DELAY, MAX_ENTITY_NUM, NUM_ACTIONS, ENTITY_TYPE_NUM, NUM_UPGRADES, NUM_CUMULATIVE_STAT_ACTIONS, \ - NUM_BEGINNING_ORDER_ACTIONS, NUM_UNIT_MIX_ABILITIES, NUM_QUEUE_ACTION, NUM_BUFFS, NUM_ADDON -#from distar.ctools.data.collate_fn import default_collate_with_dim + NUM_BEGINNING_ORDER_ACTIONS, NUM_UNIT_MIX_ABILITIES, NUM_QUEUE_ACTION, NUM_BUFFS, NUM_ADDON, MAX_SELECTED_UNITS_NUM -currTrainCount_MAX = 5 H, W = 152, 160 -def hidden_state(): - return [(torch.zeros(size=(128, )), torch.zeros(size=(128, ))) for _ in range(1)] - - def spatial_info(): return { 'height_map': torch.rand(H, W), @@ -33,42 +28,42 @@ def spatial_info(): def entity_info(): data = { - 'unit_type': torch.randint(0, ENTITY_TYPE_NUM, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'alliance': torch.randint(0, 5, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'cargo_space_taken': torch.randint(0, 9, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'build_progress': torch.rand(MAX_ENTITY_NUM), - 'health_ratio': torch.rand(MAX_ENTITY_NUM), - 'shield_ratio': torch.rand(MAX_ENTITY_NUM), - 'energy_ratio': torch.rand(MAX_ENTITY_NUM), - 'display_type': torch.randint(0, 5, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'x': torch.randint(0, 11, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'y': torch.randint(0, 11, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'cloak': torch.randint(0, 5, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'is_blip': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'is_powered': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'mineral_contents': torch.rand(MAX_ENTITY_NUM), - 'vespene_contents': torch.rand(MAX_ENTITY_NUM), - 'cargo_space_max': torch.randint(0, 9, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'assigned_harvesters': torch.randint(0, 24, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'weapon_cooldown': torch.randint(0, 32, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'order_length': torch.randint(0, 9, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'order_id_0': torch.randint(0, NUM_ACTIONS, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'order_id_1': torch.randint(0, NUM_QUEUE_ACTION, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'is_hallucination': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'buff_id_0': torch.randint(0, NUM_BUFFS, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'buff_id_1': torch.randint(0, NUM_BUFFS, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'addon_unit_type': torch.randint(0, NUM_ADDON, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'is_active': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'order_progress_0': torch.rand(MAX_ENTITY_NUM), - 'order_progress_1': torch.rand(MAX_ENTITY_NUM), - 'order_id_2': torch.randint(0, NUM_QUEUE_ACTION, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'order_id_3': torch.randint(0, NUM_QUEUE_ACTION, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'is_in_cargo': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'attack_upgrade_level': torch.randint(0, 4, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'armor_upgrade_level': torch.randint(0, 4, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'shield_upgrade_level': torch.randint(0, 4, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'last_selected_units': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'last_targeted_unit': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'unit_type': torch.randint(0, ENTITY_TYPE_NUM, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'alliance': torch.randint(0, 5, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'cargo_space_taken': torch.randint(0, 9, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'build_progress': torch.rand(MAX_ENTITY_NUM), + 'health_ratio': torch.rand(MAX_ENTITY_NUM), + 'shield_ratio': torch.rand(MAX_ENTITY_NUM), + 'energy_ratio': torch.rand(MAX_ENTITY_NUM), + 'display_type': torch.randint(0, 5, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'x': torch.randint(0, 11, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'y': torch.randint(0, 11, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'cloak': torch.randint(0, 5, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'is_blip': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'is_powered': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'mineral_contents': torch.rand(MAX_ENTITY_NUM), + 'vespene_contents': torch.rand(MAX_ENTITY_NUM), + 'cargo_space_max': torch.randint(0, 9, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'assigned_harvesters': torch.randint(0, 24, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'weapon_cooldown': torch.randint(0, 32, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'order_length': torch.randint(0, 9, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'order_id_0': torch.randint(0, NUM_ACTIONS, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'order_id_1': torch.randint(0, NUM_QUEUE_ACTION, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'is_hallucination': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'buff_id_0': torch.randint(0, NUM_BUFFS, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'buff_id_1': torch.randint(0, NUM_BUFFS, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'addon_unit_type': torch.randint(0, NUM_ADDON, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'is_active': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'order_progress_0': torch.rand(MAX_ENTITY_NUM), + 'order_progress_1': torch.rand(MAX_ENTITY_NUM), + 'order_id_2': torch.randint(0, NUM_QUEUE_ACTION, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'order_id_3': torch.randint(0, NUM_QUEUE_ACTION, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'is_in_cargo': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'attack_upgrade_level': torch.randint(0, 4, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'armor_upgrade_level': torch.randint(0, 4, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'shield_upgrade_level': torch.randint(0, 4, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'last_selected_units': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'last_targeted_unit': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), } return data @@ -87,7 +82,7 @@ def scalar_info(): 'last_action_type': torch.randint(0, NUM_ACTIONS, size=(), dtype=torch.float), 'upgrades': torch.randint(0, 2, size=(NUM_UPGRADES, ), dtype=torch.float), 'beginning_order': torch.randint(0, NUM_BEGINNING_ORDER_ACTIONS, size=(20, ), dtype=torch.float), - 'bo_location': torch.randint(0, 100*100, size=(20, ), dtype=torch.float), + 'bo_location': torch.randint(0, 100 * 100, size=(20, ), dtype=torch.float), 'unit_type_bool': torch.randint(0, 2, size=(ENTITY_TYPE_NUM, ), dtype=torch.float), 'enemy_unit_type_bool': torch.randint(0, 2, size=(ENTITY_TYPE_NUM, ), dtype=torch.float), 'unit_order_type': torch.randint(0, 2, size=(NUM_UNIT_MIX_ABILITIES, ), dtype=torch.float) @@ -95,95 +90,69 @@ def scalar_info(): return data -def action_info(): - data = { - 'action_type': torch.randint(0, NUM_ACTIONS, size=(), dtype=torch.long), - 'delay': torch.randint(0, MAX_DELAY, size=(), dtype=torch.long), - 'selected_units': torch.randint(0, 5, size=(MAX_SELECTED_UNITS_NUM, ), dtype=torch.long), - 'target_unit': torch.randint(0, MAX_ENTITY_NUM, size=(), dtype=torch.long), - 'target_location': torch.randint(0, SPATIAL_SIZE, size=(), dtype=torch.long) +def get_mask(action): + mask = { + 'action_type': torch.ones(1, dtype=torch.long).squeeze(), + 'delay': torch.ones(1, dtype=torch.long).squeeze(), + 'queued': torch.ones(1, dtype=torch.long).squeeze(), + 'selected_units': torch.randint(0, 2, size=(), dtype=torch.long), + 'target_unit': torch.randint(0, 2, size=(), dtype=torch.long), + 'target_location': torch.randint(0, 2, size=(), dtype=torch.long) } - return data + selected_units_logits_mask = torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.long) + target_units_logits_mask = torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.long) + target_units_logits_mask[action['target_unit']] = 1 - -def action_mask(): - data = { - 'action_type': torch.randint(0, 1, size=(), dtype=torch.long), - 'delay': torch.randint(0, 1, size=(), dtype=torch.long), - 'selected_units': torch.randint(0, 1, size=(), dtype=torch.long), - 'target_unit': torch.randint(0, 1, size=(), dtype=torch.long), - 'target_location': torch.randint(0, 1, size=(), dtype=torch.long) + return { + 'actions_mask': mask, + 'selected_units_logits_mask': selected_units_logits_mask, + 'target_units_logits_mask': target_units_logits_mask, } - return data -def action_logp(): +def action_info(): data = { - 'action_type': torch.rand(size=()) + 2, - 'delay': torch.rand(size=()) + 2, - 'selected_units': torch.rand(size=(MAX_SELECTED_UNITS_NUM, )) + 2, - 'target_unit': torch.rand(size=()) + 2, - 'target_location': torch.rand(size=()) + 2 + 'action_type': torch.randint(0, NUM_ACTIONS, size=(), dtype=torch.long), + 'delay': torch.randint(0, MAX_DELAY, size=(), dtype=torch.long), + 'queued': torch.randint(0, 2, size=(), dtype=torch.long), + 'selected_units': torch.randint(0, 5, size=(MAX_SELECTED_UNITS_NUM, ), dtype=torch.long), + 'target_unit': torch.randint(0, MAX_ENTITY_NUM, size=(), dtype=torch.long), + 'target_location': torch.randint(0, H, size=(), dtype=torch.long) } - return data + mask = get_mask(data) + return data, mask -def action_logits(): +def action_logits(logp=False, action=None): data = { - 'action_type': torch.rand(size=(NUM_ACTIONS + 1, )) - 1, - 'delay': torch.rand(size=(MAX_DELAY, )) - 1, - 'selected_units': torch.rand(size=(MAX_SELECTED_UNITS_NUM, MAX_ENTITY_NUM + 1)) - 1, - 'target_unit': torch.rand(size=(MAX_ENTITY_NUM, )) - 1, - 'target_location': torch.rand(size=(16384, )) - 1 + 'action_type': torch.rand(size=(NUM_ACTIONS, )) - 0.5, + 'delay': torch.rand(size=(MAX_DELAY, )) - 0.5, + 'queued': torch.rand(size=(2, )) - 0.5, + 'selected_units': torch.rand(size=(MAX_SELECTED_UNITS_NUM, MAX_ENTITY_NUM + 1)) - 0.5, + 'target_unit': torch.rand(size=(MAX_ENTITY_NUM, )) - 0.5, + 'target_location': torch.rand(size=(H * W, )) - 0.5 } - - mask = dict() - mask['selected_units_logits_mask'] = data['selected_units'].sum(0) - mask['target_units_logits_mask'] = data['target_unit'] - mask['actions_mask'] = {k: val.sum() for k, val in data.items()} - mask['selected_units_mask'] = data['selected_units'].sum(-1) - - return data, mask - - -def fake_step_data(): - data = ( - spatial_info(), - entity_info(), - scalar_info(), - action_info(), - action_mask(), - torch.randint(5, 100, size=(1, ), dtype=torch.long), # entity num - torch.randint(0, MAX_SELECTED_UNITS_NUM, size=(), dtype=torch.long), # selected_units_num - torch.randint(0, SPATIAL_SIZE, size=(512, 2), dtype=torch.long) # entity location - ) - return data - - -def fake_inference_data(): - data = ( - spatial_info(), - entity_info(), - scalar_info(), - torch.randint(5, 100, size=(1, ), dtype=torch.long), # entity_num - torch.randint(0, SPATIAL_SIZE, size=(512, 2), dtype=torch.long), # entity_location - ) + if logp: + for k in data: + dist = torch.distributions.Categorical(logits=data[k]) + data[k] = dist.log_prob(action[k]) return data -def rl_step_data(): - teacher_action_logits, mask = action_logits() +def rl_step_data(last=False): + action, mask = action_info() + teacher_action_logits = action_logits() data = { 'spatial_info': spatial_info(), 'entity_info': entity_info(), 'scalar_info': scalar_info(), 'entity_num': torch.randint(5, 100, size=(1, ), dtype=torch.long), 'selected_units_num': torch.randint(0, MAX_SELECTED_UNITS_NUM, size=(), dtype=torch.long), - 'entity_location': torch.randint(0, SPATIAL_SIZE, size=(512, 2), dtype=torch.long), - 'hidden_state': [(torch.zeros(size=(128, )), torch.zeros(size=(128, ))) for _ in range(1)], # hidden state - 'action_info': action_info(), - 'behaviour_logp': action_logp(), - 'teacher_logit': teacher_action_logits, + 'entity_location': torch.randint(0, H, size=(512, 2), dtype=torch.long), + 'hidden_state': [(torch.zeros(size=(384, )), torch.zeros(size=(384, ))) for _ in range(3)], + 'action_info': action, + 'behaviour_logp': action_logits(logp=True, action=action), + 'teacher_logit': action_logits(logp=False), 'reward': { 'winloss': torch.randint(-1, 1, size=(), dtype=torch.float), 'build_order': torch.randint(-1, 1, size=(), dtype=torch.float), @@ -195,112 +164,21 @@ def rl_step_data(): 'step': torch.randint(100, 1000, size=(), dtype=torch.long), 'mask': mask, } + if last: + for k in ['mask', 'action_info', 'teacher_logit', 'behaviour_logp', 'selected_units_num', 'reward', 'step']: + data.pop(k) return data -def transfer_data(data, cuda=False, share_memory=False, device=None): - assert cuda or share_memory - new_data = [] - for d in data: - if isinstance(d, torch.Tensor): - if cuda: - d = d.to(device) - if share_memory: - d.share_memory_() - new_data.append(d) - elif isinstance(d, dict): - if cuda: - d = {k: v.to(device) for k, v in d.items()} - if share_memory: - d = {k: v.share_memory_() for k, v in d.items()} - new_data.append(d) - return tuple(new_data) - - -def fake_step_data_share_memory(): - data = fake_step_data() - data = transfer_data(data) - return data - - -def fake_rl_data_batch(batch_size=1): - list_step_data = [] - # list_hidden_state = [] - for i in range(batch_size): - step_data = rl_step_data() - # hidden_state = step_data.pop('hidden_state') - list_step_data.append(step_data) - # list_hidden_state.append(hidden_state) - - step_data_batch = default_collate_with_dim(list_step_data) - # hidden_state_batch = default_collate_with_dim(list_hidden_state,dim=0) - batch = step_data_batch - # batch['hidden_state'] = hidden_state_batch - return batch - - -def fake_rl_data_batch_with_last(unroll_len=3): +def fake_rl_data_batch_with_last(unroll_len=4): list_step_data = [] - # list_hidden_state = [] for i in range(unroll_len): step_data = rl_step_data() - # hidden_state = step_data.pop('hidden_state') list_step_data.append(step_data) - # list_hidden_state.append(hidden_state) - last_step_data = { - 'spatial_info': spatial_info(), - 'entity_info': entity_info(), - 'scalar_info': scalar_info(), - 'entity_num': torch.randint(5, 100, size=(1, ), dtype=torch.long), - # 'selected_units_num': torch.randint(0, MAX_SELECTED_UNITS_NUM, size=(), dtype=torch.long), - 'entity_location': torch.randint(0, SPATIAL_SIZE, size=(512, 2), dtype=torch.long), - 'hidden_state': [(torch.zeros(size=(128, )), torch.zeros(size=(128, ))) for _ in range(1)], # hidden state - } - list_step_data.append(last_step_data) - step_data_batch = default_collate_with_dim(list_step_data) - # hidden_state_batch = default_collate_with_dim(list_hidden_state,dim=0) - batch = step_data_batch - # batch['hidden_state'] = hidden_state_batch - return batch + list_step_data.append(rl_step_data(last=True)) # last step + return list_step_data -def fake_rl_learner_data_batch(batch_size=6, unroll_len=4): - data_batch_list = [fake_rl_data_batch_with_last(unroll_len) for _ in range(batch_size)] - data_batch = default_collate_with_dim(data_batch_list, dim=1) +def get_fake_rl_trajectory(batch_size=3, unroll_len=4): + data_batch = [fake_rl_data_batch_with_last(unroll_len) for _ in range(batch_size)] return data_batch - - -def flat(data): - if isinstance(data, torch.Tensor): - return torch.flatten(data, start_dim=0, end_dim=1) # (1, (T+1) * B) - elif isinstance(data, dict): - new_data = {} - for k, val in data.items(): - new_data[k] = flat(val) - return new_data - elif isinstance(data, Sequence): - new_data = [flat(v) for v in data] - return new_data - else: - print(type(data)) - - -def rl_learner_forward_data(batch_size=6, unroll_len=4): - data = fake_rl_learner_data_batch(batch_size, unroll_len) - new_data = {} - for k, val in data.items(): - if k in [ - 'spatial_info', - 'entity_info', - 'scalar_info', - 'entity_num', # 'action_info' - # 'selected_units_num', - 'entity_location', - 'hidden_state', - ]: - new_data[k] = flat(val) - else: - new_data[k] = val - new_data['batch_size'] = batch_size - new_data['unroll_len'] = unroll_len - return new_data diff --git a/dizoo/distar/envs/meta.py b/dizoo/distar/envs/meta.py index 569fac51c6..7cae00865e 100644 --- a/dizoo/distar/envs/meta.py +++ b/dizoo/distar/envs/meta.py @@ -1,5 +1,6 @@ -MAX_DELAY = 64 +MAX_DELAY = 128 MAX_ENTITY_NUM = 512 +MAX_SELECTED_UNITS_NUM = 64 ENTITY_TYPE_NUM = 260 NUM_ACTIONS = 327 NUM_UPGRADES = 90 diff --git a/dizoo/distar/policy/__init__.py b/dizoo/distar/policy/__init__.py new file mode 100644 index 0000000000..061c38a426 --- /dev/null +++ b/dizoo/distar/policy/__init__.py @@ -0,0 +1 @@ +from .distar_policy import DIStarPolicy diff --git a/dizoo/distar/policy/distar_policy.py b/dizoo/distar/policy/distar_policy.py index 7226be1745..dd223d714a 100644 --- a/dizoo/distar/policy/distar_policy.py +++ b/dizoo/distar/policy/distar_policy.py @@ -1,9 +1,11 @@ -from typing import Dict +from typing import Dict, Optional, List +from easydict import EasyDict import os.path as osp import torch import torch.nn.functional as F from torch.optim import Adam +from ding.model import model_wrap from ding.policy import Policy from ding.torch_utils import to_device from ding.rl_utils import td_lambda_data, td_lambda_error, vtrace_data_with_rho, vtrace_error_with_rho, \ @@ -60,7 +62,7 @@ def kl_error( kl = kl * mask['actions_mask'][head_type] if head_type == 'action_type': flag = game_steps < action_type_kl_steps - action_type_kl = kl * flag * mask['cum_action_mask'] + action_type_kl = kl * flag action_type_kl_loss = action_type_kl.mean() kl_loss_dict['kl/extra_at'] = action_type_kl_loss.item() kl_loss = kl.mean() @@ -71,10 +73,12 @@ def kl_error( class DIStarPolicy(Policy): config = dict( + type='distar', + on_policy=False, cuda=True, - multi_gpu=False, learning_rate=1e-5, model=dict(), + learn=dict(multi_gpu=False, ), loss_weights=dict( baseline=dict( winloss=10.0, @@ -100,6 +104,7 @@ class DIStarPolicy(Policy): vtrace_head_weights=dict( action_type=1.0, delay=1.0, + queued=1.0, select_unit_num_logits=1.0, selected_units=0.01, target_unit=1.0, @@ -108,6 +113,7 @@ class DIStarPolicy(Policy): upgo_head_weights=dict( action_type=1.0, delay=1.0, + queued=1.0, select_unit_num_logits=1.0, selected_units=0.01, target_unit=1.0, @@ -116,6 +122,7 @@ class DIStarPolicy(Policy): entropy_head_weights=dict( action_type=1.0, delay=1.0, + queued=1.0, select_unit_num_logits=1.0, selected_units=0.01, target_unit=1.0, @@ -124,6 +131,7 @@ class DIStarPolicy(Policy): kl_head_weights=dict( action_type=1.0, delay=1.0, + queued=1.0, select_unit_num_logits=1.0, selected_units=0.01, target_unit=1.0, @@ -151,8 +159,22 @@ class DIStarPolicy(Policy): grad_clip=dict(threshold=1.0, ) ) + def _create_model( + self, + cfg: EasyDict, + model: Optional[torch.nn.Module] = None, + enable_field: Optional[List[str]] = None + ) -> torch.nn.Module: + assert model is None, "not implemented user-defined model" + assert len(enable_field) == 1, "only support distributed enable policy" + field = enable_field[0] + if field == 'learn': + return Model(self._cfg.model, use_value_network=True) + else: + raise KeyError("invalid policy mode: {}".format(field)) + def _init_learn(self): - self.learn_model = Model(self._cfg.model, use_value_network=True) + self.learn_model = model_wrap(self._model, 'base') self.head_types = ['action_type', 'delay', 'queued', 'target_unit', 'selected_units', 'target_location'] # policy parameters self.gammas = self._cfg.gammas @@ -179,7 +201,7 @@ def _forward_learn(self, inputs: Dict): # =========== inputs = collate_fn_learn(inputs) if self._cfg.cuda: - inputs = to_device(inputs) + inputs = to_device(inputs, self._device) # ============= # model forward @@ -256,8 +278,8 @@ def _forward_learn(self, inputs: Dict): weight = self.vtrace_head_weights[head_type] if head_type not in ['action_type', 'delay']: weight = weight * masks_dict['actions_mask'][head_type] - if field in ['build_order', 'built_unit', 'effect']: - weight = weight * masks_dict[field + '_mask'] + # if field in ['build_order', 'built_unit', 'effect']: + # weight = weight * masks_dict[field + '_mask'] data_item = vtrace_data_with_rho( target_action_log_probs_dict[head_type], clipped_rhos_dict[head_type], baseline_value, reward, @@ -302,16 +324,17 @@ def _forward_learn(self, inputs: Dict): # Notice: in general, we need to include done when we consider discount factor, but in our implementation # of alphastar, traj_data(with size equal to unroll-len) sent from actor comes from the same episode. # If the game is draw, we don't consider it is actually done - if field in ['build_order', 'built_unit', 'effect']: - weight = masks_dict[[field + '_mask']] - else: - weight = None + # if field in ['build_order', 'built_unit', 'effect']: + # weight = masks_dict[[field + '_mask']] + # else: + # weight = None + weight = None field_data = td_lambda_data(baseline, reward, weight) - critic_loss = td_lambda_error(baseline, reward, masks_dict, gamma=self.gammas.baseline[field]) + critic_loss = td_lambda_error(field_data, gamma=self.gammas.baseline[field]) total_critic_loss += self.loss_weights.baseline[field] * critic_loss - loss_info_dict['td' + field] = critic_loss.item() + loss_info_dict['td/' + field] = critic_loss.item() loss_info_dict['reward/' + field] = reward.float().mean().item() loss_info_dict['value/' + field] = baseline.mean().item() loss_info_dict['reward/battle'] = rewards_dict['battle'].float().mean().item() @@ -346,7 +369,7 @@ def _forward_learn(self, inputs: Dict): with self.timer: self.optimizer.zero_grad() total_loss.backward() - if self._cfg.multi_gpu: + if self._cfg.learn.multi_gpu: self.sync_gradients() gradient = torch.nn.utils.clip_grad_norm_(self.learn_model.parameters(), self._cfg.grad_clip.threshold, 2) self.optimizer.step() @@ -380,5 +403,11 @@ def _init_collect(self): def _forward_collect(self, data): pass + def _process_transition(self): + pass + + def _get_train_sample(self): + pass + _init_eval = _init_collect _forward_eval = _forward_collect diff --git a/dizoo/distar/policy/test_distar_policy.py b/dizoo/distar/policy/test_distar_policy.py new file mode 100644 index 0000000000..c2d9c08272 --- /dev/null +++ b/dizoo/distar/policy/test_distar_policy.py @@ -0,0 +1,15 @@ +import pytest + +from dizoo.distar.policy import DIStarPolicy +from dizoo.distar.envs import get_fake_rl_trajectory + + +@pytest.mark.envtest +class TestDIStarPolicy: + + def test_forward_learn(self): + policy = DIStarPolicy(DIStarPolicy.default_config(), enable_field=['learn']) + policy = policy.learn_mode + data = get_fake_rl_trajectory(batch_size=3) + output = policy.forward(data) + print(output) diff --git a/dizoo/distar/policy/utils.py b/dizoo/distar/policy/utils.py index 48a4c6f0b3..f0581bc210 100644 --- a/dizoo/distar/policy/utils.py +++ b/dizoo/distar/policy/utils.py @@ -1,6 +1,6 @@ import torch from ding.torch_utils import flatten, sequence_mask -from ding.utils import default_collate +from ding.utils.data import default_collate from dizoo.distar.envs import MAX_SELECTED_UNITS_NUM MASK_INF = -1e9 @@ -65,13 +65,13 @@ def collate_fn_learn(traj_batch): [len(traj_data['entity_info']['x']) for traj_data_list in traj_batch for traj_data in traj_data_list] ) - # padding entity_info in observatin, target_unit, selected_units, mask + # padding entity_info in observation, target_unit, selected_units, mask traj_batch = [ [padding_entity_info(traj_data, max_entity_num) for traj_data in traj_data_list] for traj_data_list in traj_batch ] - data = [default_collate(traj_data_list) for traj_data_list in traj_batch] + data = [default_collate(traj_data_list, allow_key_mismatch=True) for traj_data_list in traj_batch] batch_size = len(data) unroll_len = len(data[0]['step']) From b4dcce0f1e70ce5f4d1f480a0737e4aa4797cdd1 Mon Sep 17 00:00:00 2001 From: lixuelin Date: Mon, 20 Jun 2022 10:25:51 +0800 Subject: [PATCH 127/229] merge --- ding/framework/middleware/__init__.py | 2 +- ding/framework/middleware/league_learner.py | 38 ++++++++++++++++++- .../middleware/tests/league_config.py | 2 +- .../middleware/tests/mock_for_test.py | 30 ++++++--------- .../middleware/tests/test_league_pipeline.py | 9 ++--- dizoo/distar/model/model.py | 1 - dizoo/distar/policy/distar_policy.py | 2 +- 7 files changed, 55 insertions(+), 29 deletions(-) diff --git a/ding/framework/middleware/__init__.py b/ding/framework/middleware/__init__.py index 16427614ca..0530a281c0 100644 --- a/ding/framework/middleware/__init__.py +++ b/ding/framework/middleware/__init__.py @@ -4,4 +4,4 @@ from .ckpt_handler import CkptSaver from .league_actor import LeagueActor, StepLeagueActor from .league_coordinator import LeagueCoordinator -from .league_learner import LeagueLearner +from .league_learner import LeagueLearner, OffPolicyLeagueLearner diff --git a/ding/framework/middleware/league_learner.py b/ding/framework/middleware/league_learner.py index cb02eb25e6..cea9a03897 100644 --- a/ding/framework/middleware/league_learner.py +++ b/ding/framework/middleware/league_learner.py @@ -1,16 +1,18 @@ import os -import logging from dataclasses import dataclass from threading import Lock from time import sleep from typing import TYPE_CHECKING, Callable, Optional +from ding.data.buffer.deque_buffer import DequeBuffer from ding.framework import task, EventEnum +from ding.framework.middleware import OffPolicyLearner, CkptSaver, data_pusher from ding.framework.storage import Storage, FileStorage from ding.league.player import PlayerMeta from ding.worker.learner.base_learner import BaseLearner if TYPE_CHECKING: + from ding.data import Buffer from ding.framework import Context from ding.framework.middleware.league_actor import ActorData from ding.league import ActivePlayer @@ -23,6 +25,40 @@ class LearnerModel: train_iter: int = 0 +class OffPolicyLeagueLearner: + + def __init__(self, cfg: dict, policy_fn: Callable, player: "ActivePlayer") -> None: + self._buffer = DequeBuffer(size=10000) + self._policy = policy_fn().learn_mode + self.player_id = player.player_id + task.on(EventEnum.ACTOR_SEND_DATA.format(player=self.player_id), self._push_data) + self._learner = OffPolicyLearner(cfg, self._policy, self._buffer) + # self._ckpt_handler = CkptSaver(cfg, self._policy, train_freq=100) + + def _push_data(self, data: "ActorData"): + print("wait for lock") + print("push data into the buffer!") + self._buffer.push(data.train_data) + + def __call__(self, ctx: "OnlineRLContext"): + print("num of objects in buffer:", self._buffer.count()) + self._learner(ctx) + checkpoint = None + + sleep(2) + print('learner send player meta\n', flush=True) + task.emit( + EventEnum.LEARNER_SEND_META, + PlayerMeta(player_id=self.player_id, checkpoint=checkpoint, total_agent_step=0) + ) + + learner_model = LearnerModel( + player_id=self.player_id, state_dict=self._policy.state_dict(), train_iter=0 + ) + print('learner send model\n', flush=True) + task.emit(EventEnum.LEARNER_SEND_MODEL, learner_model) + + class LeagueLearner: def __init__(self, cfg: dict, policy_fn: Callable, player: "ActivePlayer") -> None: diff --git a/ding/framework/middleware/tests/league_config.py b/ding/framework/middleware/tests/league_config.py index 3d1e6b5b1d..19f3173acc 100644 --- a/ding/framework/middleware/tests/league_config.py +++ b/ding/framework/middleware/tests/league_config.py @@ -80,7 +80,7 @@ 'n_episode': 1, 'n_rollout_samples': 32, 'n_sample': 64, - 'unroll_len': 2 + 'unroll_len': 1 }, 'eval': { 'evaluator': { diff --git a/ding/framework/middleware/tests/mock_for_test.py b/ding/framework/middleware/tests/mock_for_test.py index 789bd28460..7aa73dcf35 100644 --- a/ding/framework/middleware/tests/mock_for_test.py +++ b/ding/framework/middleware/tests/mock_for_test.py @@ -10,8 +10,8 @@ from ding.league.player import PlayerMeta from ding.league.v2 import BaseLeague, Job from ding.framework.storage import FileStorage -from ding.policy import PPOPolicy from dizoo.distar.envs.distar_env import DIStarEnv +from dizoo.distar.policy.distar_policy import DIStarPolicy from ding.envs import BaseEnvManager import treetensor.torch as ttorch from ding.envs import BaseEnvTimestep @@ -176,29 +176,21 @@ def flush(*args): pass -class DIStarMockPolicy(PPOPolicy): - - def _mock_data(self, data_list): - for data in data_list: - assert isinstance(data, dict) - assert 'obs' in data - assert 'next_obs' in data - assert 'action' in data - assert 'reward' in data - data['obs'] = torch.rand(16) - data['next_obs'] = torch.rand(16) - data['action'] = torch.rand(4) - return data_list +class DIStarMockPolicy(DIStarPolicy): def _forward_learn(self, data: Dict[str, Any]) -> Dict[str, Any]: print("Call forward_learn:") - data = self._mock_data(data) - # return super()._forward_learn(data) + return super()._forward_learn(data) + + def _forward_collect(self, data: Dict[int, Any]) -> Dict[int, Any]: + return DIStarEnv.random_action(data) + + def _get_train_sample(self, data: list) -> Union[None, List[Any]]: return + + def _process_transition(self, obs: Any, model_output: dict, timestep: namedtuple) -> dict: + return dict() - # def _forward_eval(self, data: Dict[int, Any]) -> Dict[int, Any]: - # data = {i: torch.rand(self.policy.model.obs_shape) for i in range(self.cfg.env.collector_env_num)} - # return super()._forward_eval(data) class DIstarCollectMode: diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index ad5b927d9c..48e42b1241 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -3,7 +3,7 @@ import pytest from ding.envs import BaseEnvManager from ding.framework.context import BattleContext -from ding.framework.middleware import StepLeagueActor, LeagueCoordinator, LeagueLearner +from ding.framework.middleware import StepLeagueActor, LeagueCoordinator, LeagueLearner, OffPolicyLeagueLearner from ding.model import VAC from ding.framework.task import task, Parallel @@ -13,8 +13,8 @@ from distar.ctools.utils import read_config from unittest.mock import patch -N_ACTORS = 2 -N_LEARNERS = 2 +N_ACTORS = 1 +N_LEARNERS = 1 def prepare_test(): @@ -57,8 +57,7 @@ def _main(): else: n_players = len(league.active_players_ids) player = league.active_players[task.router.node_id % n_players] - learner = LeagueLearner(cfg, policy_fn, player) - learner._learner._tb_logger = MockLogger() + learner = OffPolicyLeagueLearner(cfg, policy_fn, player) task.use(learner) task.run() diff --git a/dizoo/distar/model/model.py b/dizoo/distar/model/model.py index d47e3cab83..0e0a874483 100644 --- a/dizoo/distar/model/model.py +++ b/dizoo/distar/model/model.py @@ -7,7 +7,6 @@ import torch.nn as nn from ding.utils import read_yaml_config, deep_merge_dicts -from ding.utils.data import default_collate from ding.torch_utils import detach_grad, script_lstm from dizoo.distar.envs import MAX_SELECTED_UNITS_NUM from .encoder import Encoder diff --git a/dizoo/distar/policy/distar_policy.py b/dizoo/distar/policy/distar_policy.py index dd223d714a..e09029059f 100644 --- a/dizoo/distar/policy/distar_policy.py +++ b/dizoo/distar/policy/distar_policy.py @@ -11,7 +11,7 @@ from ding.rl_utils import td_lambda_data, td_lambda_error, vtrace_data_with_rho, vtrace_error_with_rho, \ upgo_data, upgo_error from ding.utils import EasyTimer -from dizoo.distar.model import Model +from dizoo.distar.model.model import Model from .utils import collate_fn_learn EPS = 1e-9 From ca0987ba38a496027c173021a71d2f2a70da4f5e Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Mon, 20 Jun 2022 13:54:47 +0800 Subject: [PATCH 128/229] change a bit --- .../middleware/tests/test_collector.py | 6 +-- .../test_league_actor_distar_one_process.py | 52 +------------------ .../middleware/tests/test_league_pipeline.py | 3 +- .../tests/test_league_pipeline_one_process.py | 3 +- 4 files changed, 8 insertions(+), 56 deletions(-) diff --git a/ding/framework/middleware/tests/test_collector.py b/ding/framework/middleware/tests/test_collector.py index 3b0f60ba21..1c0f43e3f4 100644 --- a/ding/framework/middleware/tests/test_collector.py +++ b/ding/framework/middleware/tests/test_collector.py @@ -6,6 +6,8 @@ from ding.framework.middleware import TransitionList, inferencer, rolloutor from ding.framework.middleware import StepCollector, EpisodeCollector from ding.framework.middleware.tests import MockPolicy, MockEnv, CONFIG +from ding.framework.middleware import BattleTransitionList +from easydict import EasyDict @pytest.mark.unittest @@ -86,10 +88,6 @@ def test_episode_collector(): assert len(ctx.episodes) == 16 -from ding.framework.middleware import BattleTransitionList -from easydict import EasyDict - - @pytest.mark.unittest def test_battle_transition_list(): env_num = 2 diff --git a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py index 6977630eb8..21c8ea154a 100644 --- a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py @@ -22,56 +22,8 @@ from distar.ctools.utils import read_config from ding.model import VAC -from ding.framework.middleware.tests import DIStarMockPolicyCollect, battle_inferencer_for_distar, battle_rolloutor_for_distar, DIStarMockPolicy - - -class LearnMode: - - def __init__(self) -> None: - pass - - def state_dict(self): - return {} - - -class CollectMode: - - def __init__(self) -> None: - self._cfg = EasyDict(dict(collect=dict(n_episode=64))) - - def load_state_dict(self, state_dict): - return - - def forward(self, data: Dict): - return_data = {} - return_data['action'] = DIStarEnv.random_action(data) - return_data['logit'] = [1] - return_data['value'] = [0] - - return return_data - - def process_transition(self, obs: Any, model_output: dict, timestep: namedtuple) -> dict: - transition = { - 'obs': obs, - 'next_obs': timestep.obs, - 'action': model_output['action'], - 'logit': model_output['logit'], - 'value': model_output['value'], - 'reward': timestep.reward, - 'done': timestep.done, - } - return transition - - def reset(self, data_id: Optional[List[int]] = None) -> None: - pass - - def get_attribute(self, name: str) -> Any: - if hasattr(self, '_get_' + name): - return getattr(self, '_get_' + name)() - elif hasattr(self, '_' + name): - return getattr(self, '_' + name) - else: - raise NotImplementedError +from ding.framework.middleware.tests import DIStarMockPolicy, DIStarMockPolicyCollect, \ + battle_inferencer_for_distar, battle_rolloutor_for_distar def prepare_test(): diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index ad5b927d9c..78a8f895a3 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -9,7 +9,8 @@ from ding.framework.task import task, Parallel from ding.framework.middleware.tests import cfg, MockLeague, MockLogger from dizoo.distar.envs.distar_env import DIStarEnv -from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, DIStarMockPolicyCollect, battle_inferencer_for_distar, battle_rolloutor_for_distar +from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, DIStarMockPolicyCollect, \ + battle_inferencer_for_distar, battle_rolloutor_for_distar from distar.ctools.utils import read_config from unittest.mock import patch diff --git a/ding/framework/middleware/tests/test_league_pipeline_one_process.py b/ding/framework/middleware/tests/test_league_pipeline_one_process.py index 8c217b0578..f92530b0fc 100644 --- a/ding/framework/middleware/tests/test_league_pipeline_one_process.py +++ b/ding/framework/middleware/tests/test_league_pipeline_one_process.py @@ -8,7 +8,8 @@ from ding.framework.task import task from ding.framework.middleware.tests import cfg, MockLeague, MockLogger from dizoo.distar.envs.distar_env import DIStarEnv -from ding.framework.middleware.tests import DIStarMockPolicy, DIStarMockPolicyCollect, battle_inferencer_for_distar, battle_rolloutor_for_distar +from ding.framework.middleware.tests import DIStarMockPolicy, DIStarMockPolicyCollect, \ + battle_inferencer_for_distar, battle_rolloutor_for_distar from distar.ctools.utils import read_config from unittest.mock import patch import os From 006132fcede8bb54757ed66134d20f5946045922 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Mon, 20 Jun 2022 15:31:29 +0800 Subject: [PATCH 129/229] change a bit --- .../middleware/functional/actor_data.py | 2 +- .../middleware/functional/collector.py | 2 +- .../middleware/tests/test_collector.py | 21 +++++++++---------- .../test_league_actor_distar_one_process.py | 13 ++++++------ .../middleware/tests/test_league_pipeline.py | 5 ++++- 5 files changed, 23 insertions(+), 20 deletions(-) diff --git a/ding/framework/middleware/functional/actor_data.py b/ding/framework/middleware/functional/actor_data.py index 07563075e9..6e22d9a3b3 100644 --- a/ding/framework/middleware/functional/actor_data.py +++ b/ding/framework/middleware/functional/actor_data.py @@ -4,7 +4,7 @@ @dataclass class ActorDataMeta: - palyer_total_env_step: int = 0 + player_total_env_step: int = 0 actor_id: int = 0 env_id: int = 0 send_wall_time: float = 0.0 diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index bfb4681141..4488935d8c 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -118,7 +118,7 @@ def append(self, env_id: int, transition: Any) -> None: def clear(self): for item in self._transitions: item.clear() - for item in self._done_idx: + for item in self._done_episode: item.clear() diff --git a/ding/framework/middleware/tests/test_collector.py b/ding/framework/middleware/tests/test_collector.py index 1c0f43e3f4..9b2f75c6ee 100644 --- a/ding/framework/middleware/tests/test_collector.py +++ b/ding/framework/middleware/tests/test_collector.py @@ -100,11 +100,12 @@ def test_battle_transition_list(): timestep = EasyDict({'obs': i, 'done': False}) transition_list.append(env_id=0, transition=timestep) + transition_list.append(env_id=0, transition=EasyDict({'obs': len_env_0, 'done': True})) + for i in range(len_env_1): timestep = EasyDict({'obs': i, 'done': False}) transition_list.append(env_id=1, transition=timestep) - transition_list.append(env_id=0, transition=EasyDict({'obs': len_env_0, 'done': True})) transition_list.append(env_id=1, transition=EasyDict({'obs': len_env_1, 'done': True})) len_env_0_2 = 12 @@ -113,7 +114,9 @@ def test_battle_transition_list(): for i in range(len_env_0_2): timestep = EasyDict({'obs': i, 'done': False}) transition_list.append(env_id=0, transition=timestep) + transition_list.append(env_id=0, transition=EasyDict({'obs': len_env_0_2, 'done': True})) + for i in range(len_env_1_2): timestep = EasyDict({'obs': i, 'done': False}) transition_list.append(env_id=1, transition=timestep) @@ -135,22 +138,18 @@ def test_battle_transition_list(): assert len(trajectory) == unroll_len #env_0 i = 0 - for trajectory in env_0_result[:-2]: - assert len(trajectory) == unroll_len - for transition in trajectory: - assert transition.obs == i - i += 1 - - trajectory = env_0_result[-2] - assert len(trajectory) == unroll_len + trajectory = env_0_result[0] + for transition in trajectory: + assert transition.obs == i + i += 1 + trajectory = env_0_result[1] i = len_env_0 - unroll_len + 1 for transition in trajectory: assert transition.obs == i i += 1 - trajectory = env_0_result[-1] - assert len(trajectory) == unroll_len + trajectory = env_0_result[2] test_number = 0 for i, transition in enumerate(trajectory): if i < unroll_len - len_env_0_2 - 1: diff --git a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py index 21c8ea154a..9d8828aa3c 100644 --- a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py @@ -1,24 +1,22 @@ from time import sleep import pytest from copy import deepcopy -from ding.envs import BaseEnvManager +from ding.envs import BaseEnvManager, EnvSupervisor from ding.framework.context import BattleContext from ding.framework.middleware.league_learner import LearnerModel from ding.framework.middleware.tests.league_config import cfg -from ding.framework.middleware import LeagueActor, StepLeagueActor +from ding.framework.middleware import StepLeagueActor from ding.framework.middleware.functional import ActorData from ding.league.player import PlayerMeta from ding.framework.storage import FileStorage -from easydict import EasyDict from ding.framework.task import task from ding.league.v2.base_league import Job from dizoo.distar.envs.distar_env import DIStarEnv -from unittest.mock import Mock, patch +from unittest.mock import patch +from ding.framework.supervisor import ChildType from ding.framework import EventEnum -from typing import Dict, Any, List, Optional -from collections import namedtuple from distar.ctools.utils import read_config from ding.model import VAC @@ -36,6 +34,9 @@ def env_fn(): env = BaseEnvManager( env_fn=[lambda: DIStarEnv(env_cfg) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager ) + # env = EnvSupervisor( + # env_fn=[lambda: DIStarEnv(env_cfg) for _ in range(cfg.env.collector_env_num)], **cfg.env.manager + # ) env.seed(cfg.seed) return env diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index 78a8f895a3..bc0f8b99db 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -1,7 +1,7 @@ from copy import deepcopy from time import sleep import pytest -from ding.envs import BaseEnvManager +from ding.envs import BaseEnvManager, EnvSupervisor from ding.framework.context import BattleContext from ding.framework.middleware import StepLeagueActor, LeagueCoordinator, LeagueLearner @@ -28,6 +28,9 @@ def env_fn(): env = BaseEnvManager( env_fn=[lambda: DIStarEnv(env_cfg) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager ) + # env = EnvSupervisor( + # env_fn=[lambda: DIStarEnv(env_cfg) for _ in range(cfg.env.collector_env_num)], **cfg.env.manager + # ) env.seed(cfg.seed) return env From c664f60a1279f2edd2e47e295be3a78bd53b0f4d Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Mon, 20 Jun 2022 17:46:05 +0800 Subject: [PATCH 130/229] add comment to BattleTransitionList --- .../middleware/functional/collector.py | 40 ++++++++++++++----- .../middleware/tests/test_collector.py | 17 ++++++-- 2 files changed, 42 insertions(+), 15 deletions(-) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 4488935d8c..08d10b822a 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -10,6 +10,7 @@ # if TYPE_CHECKING: from ding.framework import OnlineRLContext, BattleContext +from collections import deque class TransitionList: @@ -57,24 +58,32 @@ def length(self, env_id: int) -> int: class BattleTransitionList: def __init__(self, env_num: int, unroll_len: int) -> None: + # for each env, we have a deque to buffer episodes, + # and a deque to tell each episode is finished or not self.env_num = env_num - self._transitions = [[] for _ in range(env_num)] - self._done_episode = [[] for _ in range(env_num)] + self._transitions = [deque() for _ in range(env_num)] + self._done_episode = [deque() for _ in range(env_num)] self._unroll_len = unroll_len def get_trajectories(self, env_id: int): trajectories = [] if len(self._transitions[env_id]) == 0: - return None + # if we have no episode for this env, we return an empty list + return trajectories while len(self._transitions[env_id]) > 0: + # Every time we check if oldest episode is done, + # if is done, we cut the episode to trajectories + # and finally drop this episode if self._done_episode[env_id][0] is False: break - trajectories += self._cut_trajectory_from_episode(self._transitions[env_id][0]) - self._transitions[env_id][0].clear() - self._transitions[env_id] = self._transitions[env_id][1:] - self._done_episode[env_id] = self._done_episode[env_id][1:] + oldest_episode = self._transitions[env_id].popleft() + self._done_episode[env_id].popleft() + trajectories += self._cut_trajectory_from_episode(oldest_episode) + oldest_episode.clear() if len(self._transitions[env_id]) == 1 and self._done_episode[env_id][0] is False: + # If last episode is not done, we only cut the trajectories till the Trajectory(t-1) (not including) + # This is because we need Trajectory(t-1) to fill up Trajectory(t) if in Trajectory(t) this episode is done tail_idx = max( 0, ((len(self._transitions[env_id][0]) - self._unroll_len) // self._unroll_len) * self._unroll_len ) @@ -84,6 +93,10 @@ def get_trajectories(self, env_id: int): return trajectories def _cut_trajectory_from_episode(self, episode: list): + # first we cut complete trajectories (list of transitions whose length equal to unroll_len) + # then we gather the transitions in the tail of episode, and fill up the trajectory with the tail transitions in Trajectory(t-1) + # If we don't have Trajectory(t-1), i.e. the length of the whole episode is smaller than unroll_len, we fill up the trajectory + # with the first element of episode. return_episode = [] i = 0 num_complele_trajectory, num_tail_transitions = divmod(len(episode), self._unroll_len) @@ -102,12 +115,17 @@ def _cut_trajectory_from_episode(self, episode: list): return return_episode # list of trajectories - def clear_newest_transition(self, env_id: int) -> None: - self._transitions[env_id][-1].clear() - self._transitions[env_id] = self._transitions[env_id][:-1] - self._done_episode[env_id] = self._done_episode[env_id][:-1] + def clear_newest_episode(self, env_id: int) -> None: + # Use it when env.step raise some error + if self._done_episode[env_id][-1] is False: + newest_episode = self._transitions[env_id].pop() + newest_episode.clear() + self._done_episode[env_id].pop() + else: + return def append(self, env_id: int, transition: Any) -> None: + # If previous episode is done, we create a new episode if len(self._done_episode[env_id]) == 0 or self._done_episode[env_id][-1] is True: self._transitions[env_id].append([]) self._done_episode[env_id].append(False) diff --git a/ding/framework/middleware/tests/test_collector.py b/ding/framework/middleware/tests/test_collector.py index 9b2f75c6ee..341576ced2 100644 --- a/ding/framework/middleware/tests/test_collector.py +++ b/ding/framework/middleware/tests/test_collector.py @@ -8,6 +8,7 @@ from ding.framework.middleware.tests import MockPolicy, MockEnv, CONFIG from ding.framework.middleware import BattleTransitionList from easydict import EasyDict +import copy @pytest.mark.unittest @@ -121,11 +122,13 @@ def test_battle_transition_list(): timestep = EasyDict({'obs': i, 'done': False}) transition_list.append(env_id=1, transition=timestep) + transition_list_2 = copy.deepcopy(transition_list) + env_0_result = transition_list.get_trajectories(env_id=0) env_1_result = transition_list.get_trajectories(env_id=1) - print(env_0_result) - print(env_1_result) + # print(env_0_result) + # print(env_1_result) # print(env_0_result) assert len(env_0_result) == 3 @@ -183,8 +186,14 @@ def test_battle_transition_list(): # print(env_0_result) # print(env_1_result) - print(transition_list._transitions[0]) - print(transition_list._transitions[1]) + # print(transition_list._transitions[0]) + # print(transition_list._transitions[1]) + + transition_list_2.clear_newest_episode(env_id=0) + transition_list_2.clear_newest_episode(env_id=1) + + assert len(transition_list_2._transitions[0]) == 2 + assert len(transition_list_2._transitions[1]) == 1 if __name__ == '__main__': From 78bfd975f9fe8e68ffad507cf5172e56e089c778 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 21 Jun 2022 00:22:17 +0800 Subject: [PATCH 131/229] change a bit --- ding/framework/context.py | 1 - ding/framework/middleware/functional/__init__.py | 2 +- ding/framework/middleware/functional/actor_data.py | 14 +++++++++----- ding/framework/middleware/functional/collector.py | 11 ++--------- ding/framework/middleware/tests/league_config.py | 2 +- ding/framework/middleware/tests/test_collector.py | 6 ++---- 6 files changed, 15 insertions(+), 21 deletions(-) diff --git a/ding/framework/context.py b/ding/framework/context.py index f5f830f784..46d58c20c4 100644 --- a/ding/framework/context.py +++ b/ding/framework/context.py @@ -107,5 +107,4 @@ def __init__(self, *args, **kwargs) -> None: self.episodes = [] self.episode_info = [] self.trajectories_list = [] - self.trajectory_end_idx_list = [] self.train_data = None diff --git a/ding/framework/middleware/functional/__init__.py b/ding/framework/middleware/functional/__init__.py index 1b73b61a39..01d87b71ca 100644 --- a/ding/framework/middleware/functional/__init__.py +++ b/ding/framework/middleware/functional/__init__.py @@ -10,4 +10,4 @@ from .explorer import eps_greedy_handler, eps_greedy_masker from .advantage_estimator import gae_estimator from .enhancer import reward_estimator, her_data_enhancer, nstep_reward_enhancer -from .actor_data import ActorData, ActorDataMeta +from .actor_data import ActorData, ActorDataMeta, ActorEnvTrajectories diff --git a/ding/framework/middleware/functional/actor_data.py b/ding/framework/middleware/functional/actor_data.py index 6e22d9a3b3..9cf7051e5f 100644 --- a/ding/framework/middleware/functional/actor_data.py +++ b/ding/framework/middleware/functional/actor_data.py @@ -1,17 +1,21 @@ -from typing import Any -from dataclasses import dataclass +from typing import Any, List +from dataclasses import dataclass, field @dataclass class ActorDataMeta: player_total_env_step: int = 0 actor_id: int = 0 - env_id: int = 0 send_wall_time: float = 0.0 +@dataclass +class ActorEnvTrajectories: + env_id: int = 0 + trajectories: List = field(default_factory=[]) + + @dataclass class ActorData: meta: ActorDataMeta - # TODO make train data a list in which each env_id has a list - train_data: Any + train_data: List = field(default_factory=[]) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 08d10b822a..def1e0ea0e 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -47,13 +47,6 @@ def clear(self): for item in self._done_idx: item.clear() - def clear_env_transitions(self, env_id: int) -> None: - self._transitions[env_id].clear() - self._done_idx[env_id].clear() - - def length(self, env_id: int) -> int: - return len(self._transitions[env_id]) - class BattleTransitionList: @@ -65,7 +58,7 @@ def __init__(self, env_num: int, unroll_len: int) -> None: self._done_episode = [deque() for _ in range(env_num)] self._unroll_len = unroll_len - def get_trajectories(self, env_id: int): + def get_env_trajectories(self, env_id: int, only_finished: bool = False): trajectories = [] if len(self._transitions[env_id]) == 0: # if we have no episode for this env, we return an empty list @@ -81,7 +74,7 @@ def get_trajectories(self, env_id: int): trajectories += self._cut_trajectory_from_episode(oldest_episode) oldest_episode.clear() - if len(self._transitions[env_id]) == 1 and self._done_episode[env_id][0] is False: + if not only_finished and len(self._transitions[env_id]) == 1 and self._done_episode[env_id][0] is False: # If last episode is not done, we only cut the trajectories till the Trajectory(t-1) (not including) # This is because we need Trajectory(t-1) to fill up Trajectory(t) if in Trajectory(t) this episode is done tail_idx = max( diff --git a/ding/framework/middleware/tests/league_config.py b/ding/framework/middleware/tests/league_config.py index 3d1e6b5b1d..bcb4ae8821 100644 --- a/ding/framework/middleware/tests/league_config.py +++ b/ding/framework/middleware/tests/league_config.py @@ -80,7 +80,7 @@ 'n_episode': 1, 'n_rollout_samples': 32, 'n_sample': 64, - 'unroll_len': 2 + 'unroll_len': 64 }, 'eval': { 'evaluator': { diff --git a/ding/framework/middleware/tests/test_collector.py b/ding/framework/middleware/tests/test_collector.py index 341576ced2..6d231afa09 100644 --- a/ding/framework/middleware/tests/test_collector.py +++ b/ding/framework/middleware/tests/test_collector.py @@ -124,15 +124,13 @@ def test_battle_transition_list(): transition_list_2 = copy.deepcopy(transition_list) - env_0_result = transition_list.get_trajectories(env_id=0) - env_1_result = transition_list.get_trajectories(env_id=1) + env_0_result = transition_list.get_env_trajectories(env_id=0) + env_1_result = transition_list.get_env_trajectories(env_id=1) # print(env_0_result) # print(env_1_result) - # print(env_0_result) assert len(env_0_result) == 3 - # print(env_1_result) assert len(env_1_result) == 4 for trajectory in env_0_result: From b64a3ec269b49319018a9f4ed737918655a2af16 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 21 Jun 2022 03:12:29 +0800 Subject: [PATCH 132/229] add BattleTransitionList into league_actors, but have some unexpected actions --- ding/framework/middleware/collector.py | 21 ++++++++------- .../middleware/functional/actor_data.py | 2 +- .../middleware/functional/collector.py | 10 +++++++ ding/framework/middleware/league_actor.py | 27 ++++++++++++------- .../test_league_actor_distar_one_process.py | 12 ++++----- 5 files changed, 45 insertions(+), 27 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 49d560a4d5..08f5435c9c 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -2,7 +2,7 @@ from ding.policy import get_random_policy from ding.envs import BaseEnvManager from ding.framework import task -from .functional import inferencer, rolloutor, TransitionList, battle_inferencer, battle_rolloutor +from .functional import inferencer, rolloutor, TransitionList, BattleTransitionList, battle_inferencer, battle_rolloutor from typing import Dict, TYPE_CHECKING if TYPE_CHECKING: @@ -88,8 +88,7 @@ def __call__(self, ctx: "BattleContext") -> None: class BattleStepCollector: def __init__( - self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int, model_dict: Dict, all_policies: Dict, - agent_num: int + self, cfg: EasyDict, env: BaseEnvManager, unroll_len: int, model_dict: Dict, all_policies: Dict, agent_num: int ): self.cfg = cfg self.end_flag = False @@ -98,13 +97,15 @@ def __init__( self.env_num = self.env.env_num self.total_envstep_count = 0 - self.n_rollout_samples = n_rollout_samples + self.unroll_len = unroll_len self.model_dict = model_dict self.all_policies = all_policies self.agent_num = agent_num self._battle_inferencer = task.wrap(battle_inferencer(self.cfg, self.env)) - self._transitions_list = [TransitionList(self.env.env_num) for _ in range(self.agent_num)] + self._transitions_list = [ + BattleTransitionList(self.env.env_num, self.unroll_len) for _ in range(self.agent_num) + ] self._battle_rolloutor = task.wrap(battle_rolloutor(self.cfg, self.env, self._transitions_list)) def __del__(self) -> None: @@ -151,16 +152,16 @@ def __call__(self, ctx: "BattleContext") -> None: self.total_envstep_count = ctx.total_envstep_count - if (self.n_rollout_samples > 0 - and ctx.env_step - old >= self.n_rollout_samples) or ctx.env_episode >= ctx.n_episode: + only_finished = True if ctx.env_episode >= ctx.n_episode else False + if (self.unroll_len > 0 and ctx.env_step - old >= self.unroll_len) or ctx.env_episode >= ctx.n_episode: for transitions in self._transitions_list: - trajectories, trajectory_end_idx = transitions.to_trajectories() + trajectories = transitions.to_trajectories(only_finished=only_finished) ctx.trajectories_list.append(trajectories) - ctx.trajectory_end_idx_list.append(trajectory_end_idx) - transitions.clear() if ctx.env_episode >= ctx.n_episode: self.env.close() ctx.job_finish = True + for transitions in self._transitions_list: + transitions.clear() break diff --git a/ding/framework/middleware/functional/actor_data.py b/ding/framework/middleware/functional/actor_data.py index 9cf7051e5f..dc62b2081f 100644 --- a/ding/framework/middleware/functional/actor_data.py +++ b/ding/framework/middleware/functional/actor_data.py @@ -18,4 +18,4 @@ class ActorEnvTrajectories: @dataclass class ActorData: meta: ActorDataMeta - train_data: List = field(default_factory=[]) + train_data: List[ActorEnvTrajectories] = field(default_factory=[]) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index def1e0ea0e..8b4ca0e310 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -1,6 +1,7 @@ from typing import TYPE_CHECKING, Optional, Callable, List, Tuple, Any from easydict import EasyDict from functools import reduce +from more_itertools import only import treetensor.torch as ttorch from ding.envs import BaseEnvManager from ding.policy import Policy @@ -11,6 +12,7 @@ # if TYPE_CHECKING: from ding.framework import OnlineRLContext, BattleContext from collections import deque +from ding.framework.middleware.functional.actor_data import ActorEnvTrajectories class TransitionList: @@ -85,6 +87,14 @@ def get_env_trajectories(self, env_id: int, only_finished: bool = False): return trajectories + def to_trajectories(self, only_finished: bool = False): + all_env_data = [] + for env_id in range(self.env_num): + trajectories = self.get_env_trajectories(env_id, only_finished=only_finished) + if len(trajectories) > 0: + all_env_data.append(ActorEnvTrajectories(env_id=env_id, trajectories=trajectories)) + return all_env_data + def _cut_trajectory_from_episode(self, episode: list): # first we cut complete trajectories (list of transitions whose length equal to unroll_len) # then we gather the transitions in the tail of episode, and fill up the trajectory with the tail transitions in Trajectory(t-1) diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 1e7f490e69..ec67c5c9b8 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -134,7 +134,7 @@ def __call__(self, ctx: "BattleContext"): if not job.is_eval and len(ctx.episodes[0]) > 0: actor_data = ActorData(env_step=ctx.total_envstep_count, train_data=ctx.episodes[0]) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=job.launch_player), actor_data) - ctx.episodes = [] + ctx.episodes = [] time_end = time.time() self.collect_time[job.launch_player] += time_end - time_begin total_collect_speed = ctx.total_envstep_count / self.collect_time[job.launch_player] if self.collect_time[ @@ -162,7 +162,7 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.env_fn = env_fn self.env_num = env_fn().env_num self.policy_fn = policy_fn - self.n_rollout_samples = self.cfg.policy.collect.get("n_rollout_samples") or 0 + self.unroll_len = self.cfg.policy.collect.get("unroll_len") or 0 self._collectors: Dict[str, BattleEpisodeCollector] = {} self.all_policies: Dict[str, "Policy.collect_function"] = {} task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), self._on_league_job) @@ -198,8 +198,7 @@ def _get_collector(self, player_id: str): env = self.env_fn() collector = task.wrap( BattleStepCollector( - cfg.policy.collect.collector, env, self.n_rollout_samples, self.model_dict, self.all_policies, - self.agent_num + cfg.policy.collect.collector, env, self.unroll_len, self.model_dict, self.all_policies, self.agent_num ) ) self._collectors[player_id] = collector @@ -272,23 +271,31 @@ def __call__(self, ctx: "BattleContext"): old_envstep = ctx.total_envstep_count collector(ctx) + # print(ctx.trajectories_list) + # ctx.trajectories_list[0] for policy_id 0 + # ctx.trajectories_list[0][0] for first env + print(len(ctx.trajectories_list[0])) + if len(ctx.trajectories_list[0]) > 0: + print(len(ctx.trajectories_list[0][0].trajectories)) + for traj in ctx.trajectories_list[0][0].trajectories: + assert len(traj) == self.unroll_len + if ctx.job_finish is True: + print('we finish the job !') + assert len(ctx.trajectories_list[0][0].trajectories) > 0 + if not job.is_eval and len(ctx.trajectories_list[0]) > 0: trajectories = ctx.trajectories_list[0] - trajectory_end_idx = ctx.trajectory_end_idx_list[0] - print('actor {}, len trajectories {}'.format(task.router.node_id, len(trajectories)), flush=True) + print('actor {}, {} envs send traj '.format(task.router.node_id, len(trajectories)), flush=True) meta_data = ActorDataMeta( player_total_env_step=ctx.total_envstep_count, actor_id=task.router.node_id, - # TODO transfer env_id to train_data, each env has a trajectory or not - env_id=0, send_wall_time=time.time() ) actor_data = ActorData(meta=meta_data, train_data=trajectories) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=job.launch_player), actor_data) print('Actor {} send data\n'.format(task.router.node_id), flush=True) - ctx.trajectories_list = [] - ctx.trajectory_end_idx_list = [] + ctx.trajectories_list = [] time_end = time.time() self.collect_time[job.launch_player] += time_end - time_begin total_collect_speed = ctx.total_envstep_count / self.collect_time[job.launch_player] if self.collect_time[ diff --git a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py index 9d8828aa3c..a1b5cb578a 100644 --- a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py @@ -104,12 +104,12 @@ def _test_actor(ctx): player_id='main_player_default_0', state_dict=policy.learn_mode.state_dict(), train_iter=0 ) ) - sleep(100) - try: - print(testcases) - assert all(testcases.values()) - finally: - task.finish = True + # sleep(100) + # try: + # print(testcases) + # assert all(testcases.values()) + # finally: + # task.finish = True return _test_actor From 8d30256d4deecc2d9f573549acc32a29e926a1c9 Mon Sep 17 00:00:00 2001 From: lixuelin Date: Tue, 21 Jun 2022 11:08:07 +0800 Subject: [PATCH 133/229] add league learner exchanger --- ding/framework/context.py | 3 + ding/framework/middleware/__init__.py | 2 +- .../middleware/league_coordinator.py | 2 - ding/framework/middleware/league_learner.py | 44 ++++++++++++++- .../middleware/tests/league_config.py | 4 +- .../middleware/tests/mock_for_test.py | 6 -- .../middleware/tests/test_league_learner.py | 55 +++++++++---------- .../middleware/tests/test_league_pipeline.py | 6 +- dizoo/distar/envs/__init__.py | 2 +- dizoo/distar/policy/distar_policy.py | 12 ++-- 10 files changed, 82 insertions(+), 54 deletions(-) diff --git a/ding/framework/context.py b/ding/framework/context.py index f5f830f784..c1fbfb593a 100644 --- a/ding/framework/context.py +++ b/ding/framework/context.py @@ -102,6 +102,7 @@ def __init__(self, *args, **kwargs) -> None: #data self.obs = None self.actions = None + self.trajectories = None #Return data paras self.episodes = [] @@ -109,3 +110,5 @@ def __init__(self, *args, **kwargs) -> None: self.trajectories_list = [] self.trajectory_end_idx_list = [] self.train_data = None + + self.keep('env_step', 'env_episode', 'train_iter', 'last_eval_iter') diff --git a/ding/framework/middleware/__init__.py b/ding/framework/middleware/__init__.py index 0530a281c0..62001ea92e 100644 --- a/ding/framework/middleware/__init__.py +++ b/ding/framework/middleware/__init__.py @@ -4,4 +4,4 @@ from .ckpt_handler import CkptSaver from .league_actor import LeagueActor, StepLeagueActor from .league_coordinator import LeagueCoordinator -from .league_learner import LeagueLearner, OffPolicyLeagueLearner +from .league_learner import * diff --git a/ding/framework/middleware/league_coordinator.py b/ding/framework/middleware/league_coordinator.py index ec85766a8d..d9e735b272 100644 --- a/ding/framework/middleware/league_coordinator.py +++ b/ding/framework/middleware/league_coordinator.py @@ -56,5 +56,3 @@ def __del__(self): def __call__(self, ctx: "Context") -> None: sleep(1) - # logging.info("{} Step: {}".format(self.__class__, self._step)) - # self._step += 1 diff --git a/ding/framework/middleware/league_learner.py b/ding/framework/middleware/league_learner.py index cea9a03897..2c0de6d5cc 100644 --- a/ding/framework/middleware/league_learner.py +++ b/ding/framework/middleware/league_learner.py @@ -1,5 +1,6 @@ import os from dataclasses import dataclass +from collections import deque from threading import Lock from time import sleep from typing import TYPE_CHECKING, Callable, Optional @@ -25,6 +26,44 @@ class LearnerModel: train_iter: int = 0 +class LeagueLearnerExchanger: + + def __init__(self, cfg: dict, policy: "Policy", player: "ActivePlayer") -> None: + self.cfg = cfg + self._cache = deque(maxlen=1000) + self.player = player + self.player_id = player.player_id + self.policy = policy + self.prefix = '{}/ckpt'.format(cfg.exp_name) + task.on(EventEnum.ACTOR_SEND_DATA.format(player=self.player_id), self._push_data) + + def _push_data(self, data: "ActorData"): + print("push data into the cache!") + self._cache.append(data.train_data) + + def __call__(self, ctx: "Context"): + ctx.trajectories = list(self._cache) + self._cache.clear() + sleep(1) + yield + print("Learner: save model, ctx.train_iter:", ctx.train_iter) + self.player.total_agent_step = ctx.train_iter + if self.player.is_trained_enough(): + storage = FileStorage( + path=os.path.join(self.prefix, "{}_{}_ckpt.pth".format(self.player_id, ctx.train_iter)) + ) + storage.save(self.policy.state_dict()) + task.emit( + EventEnum.LEARNER_SEND_META, + PlayerMeta(player_id=self.player_id, checkpoint=storage, total_agent_step=ctx.train_iter) + ) + + learner_model = LearnerModel( + player_id=self.player_id, state_dict=self.policy.state_dict(), train_iter=ctx.train_iter + ) + task.emit(EventEnum.LEARNER_SEND_MODEL, learner_model) + + class OffPolicyLeagueLearner: def __init__(self, cfg: dict, policy_fn: Callable, player: "ActivePlayer") -> None: @@ -36,11 +75,10 @@ def __init__(self, cfg: dict, policy_fn: Callable, player: "ActivePlayer") -> No # self._ckpt_handler = CkptSaver(cfg, self._policy, train_freq=100) def _push_data(self, data: "ActorData"): - print("wait for lock") print("push data into the buffer!") self._buffer.push(data.train_data) - def __call__(self, ctx: "OnlineRLContext"): + def __call__(self, ctx: "Context"): print("num of objects in buffer:", self._buffer.count()) self._learner(ctx) checkpoint = None @@ -53,7 +91,7 @@ def __call__(self, ctx: "OnlineRLContext"): ) learner_model = LearnerModel( - player_id=self.player_id, state_dict=self._policy.state_dict(), train_iter=0 + player_id=self.player_id, state_dict=self._policy.state_dict(), train_iter=ctx.train_iter # self._policy.state_dict() ) print('learner send model\n', flush=True) task.emit(EventEnum.LEARNER_SEND_MODEL, learner_model) diff --git a/ding/framework/middleware/tests/league_config.py b/ding/framework/middleware/tests/league_config.py index 19f3173acc..af8758364d 100644 --- a/ding/framework/middleware/tests/league_config.py +++ b/ding/framework/middleware/tests/league_config.py @@ -46,7 +46,7 @@ }, 'multi_gpu': False, 'epoch_per_collect': 10, - 'batch_size': 16, + 'batch_size': 4, 'learning_rate': 1e-05, 'value_weight': 0.5, 'entropy_weight': 0.0, @@ -106,7 +106,7 @@ 'main_player': 2 }, 'main_player': { - 'one_phase_step': 200, + 'one_phase_step': 10, # 20 'branch_probs': { 'pfsp': 0.0, 'sp': 1.0 diff --git a/ding/framework/middleware/tests/mock_for_test.py b/ding/framework/middleware/tests/mock_for_test.py index 7aa73dcf35..b9cb8e32a3 100644 --- a/ding/framework/middleware/tests/mock_for_test.py +++ b/ding/framework/middleware/tests/mock_for_test.py @@ -184,12 +184,6 @@ def _forward_learn(self, data: Dict[str, Any]) -> Dict[str, Any]: def _forward_collect(self, data: Dict[int, Any]) -> Dict[int, Any]: return DIStarEnv.random_action(data) - - def _get_train_sample(self, data: list) -> Union[None, List[Any]]: - return - - def _process_transition(self, obs: Any, model_output: dict, timestep: namedtuple) -> dict: - return dict() diff --git a/ding/framework/middleware/tests/test_league_learner.py b/ding/framework/middleware/tests/test_league_learner.py index 81dfa12075..89c9d2a56d 100644 --- a/ding/framework/middleware/tests/test_league_learner.py +++ b/ding/framework/middleware/tests/test_league_learner.py @@ -5,14 +5,18 @@ import logging from ding.envs import BaseEnvManager -from ding.model import VAC -from ding.policy import PPOPolicy +from ding.data import DequeBuffer +from ding.framework.context import BattleContext from ding.framework import EventEnum from ding.framework.task import task, Parallel -from ding.framework.middleware import LeagueLearner +from ding.framework.middleware import OffPolicyLeagueLearner, data_pusher,\ + OffPolicyLearner, LeagueLearnerExchanger from ding.framework.middleware.functional.actor_data import ActorData from ding.framework.middleware.tests import cfg, MockLeague, MockLogger -from dizoo.league_demo.game_env import GameEnv +from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy +from dizoo.distar.envs.distar_env import DIStarEnv +from distar.ctools.utils import read_config +from dizoo.distar.envs import fake_rl_data_batch_with_last logging.getLogger().setLevel(logging.INFO) @@ -20,17 +24,18 @@ def prepare_test(): global cfg cfg = deepcopy(cfg) + env_cfg = read_config('./test_distar_config.yaml') def env_fn(): + # subprocess env manager env = BaseEnvManager( - env_fn=[lambda: GameEnv(cfg.env.env_type) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager + env_fn=[lambda: DIStarEnv(env_cfg) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager ) env.seed(cfg.seed) return env def policy_fn(): - model = VAC(**cfg.policy.model) - policy = PPOPolicy(cfg.policy, model=model) + policy = DIStarMockPolicy(DIStarMockPolicy.default_config(), enable_field=['learn']) return policy return cfg, env_fn, policy_fn @@ -41,7 +46,7 @@ def coordinator_mocker(): task.on(EventEnum.LEARNER_SEND_MODEL, lambda x: print("test: send model success")) def _coordinator_mocker(ctx): - sleep(1) + sleep(10) return _coordinator_mocker @@ -49,25 +54,14 @@ def _coordinator_mocker(ctx): def actor_mocker(league): def _actor_mocker(ctx): - sleep(1) - obs_size = cfg.policy.model.obs_shape - if isinstance(obs_size, int): - obs_size = [obs_size] - data = [ - { - 'obs': torch.rand(*obs_size), - 'next_obs': torch.rand(*obs_size), - 'done': False, - 'reward': torch.rand(1), - 'logit': torch.rand(1), - 'action': torch.randint(low=0, high=2, size=(1, )), - } for _ in range(32) - ] - actor_data = ActorData(env_step=0, train_data=data) n_players = len(league.active_players_ids) player = league.active_players[(task.router.node_id + 2) % n_players] print("actor player:", player.player_id) - task.emit(EventEnum.ACTOR_SEND_DATA.format(player=player.player_id), actor_data) + for _ in range(3): + data = fake_rl_data_batch_with_last() + actor_data = ActorData(env_step=0, train_data=data) + task.emit(EventEnum.ACTOR_SEND_DATA.format(player=player.player_id), actor_data) + sleep(9) return _actor_mocker @@ -76,18 +70,21 @@ def _main(): cfg, env_fn, policy_fn = prepare_test() league = MockLeague(cfg.policy.other.league) - with task.start(): + with task.start(async_mode=True, ctx=BattleContext()): if task.router.node_id == 0: task.use(coordinator_mocker()) elif task.router.node_id <= 2: task.use(actor_mocker(league)) else: + buffer_ = DequeBuffer(size=cfg.policy.other.replay_buffer.replay_buffer_size) n_players = len(league.active_players_ids) + print("League: n_players: ", n_players) player = league.active_players[task.router.node_id % n_players] - learner = LeagueLearner(cfg, policy_fn, player) - learner._learner._tb_logger = MockLogger() - task.use(learner) - task.run(max_step=3) + policy = policy_fn() + task.use(LeagueLearnerExchanger(cfg, policy.learn_mode, player)) + task.use(data_pusher(cfg, buffer_)) + task.use(OffPolicyLearner(cfg, policy.learn_mode, buffer_)) + task.run(max_step=200) @pytest.mark.unittest diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index 48e42b1241..db1024c809 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -31,8 +31,7 @@ def env_fn(): return env def policy_fn(): - model = VAC(**cfg.policy.model) - policy = DIStarMockPolicy(cfg.policy, model=model) + policy = DIStarMockPolicy(DIStarMockPolicy.default_config(), enable_field=['learn']) return policy def collect_policy_fn(): @@ -57,8 +56,7 @@ def _main(): else: n_players = len(league.active_players_ids) player = league.active_players[task.router.node_id % n_players] - learner = OffPolicyLeagueLearner(cfg, policy_fn, player) - task.use(learner) + task.use(OffPolicyLeagueLearner(cfg, policy_fn, player)) task.run() diff --git a/dizoo/distar/envs/__init__.py b/dizoo/distar/envs/__init__.py index 8061a4940d..ff6a693dce 100644 --- a/dizoo/distar/envs/__init__.py +++ b/dizoo/distar/envs/__init__.py @@ -1,4 +1,4 @@ from .distar_env import DIStarEnv from .meta import * from .static_data import BEGIN_ACTIONS, ACTION_RACE_MASK, SELECTED_UNITS_MASK -from .fake_data import get_fake_rl_trajectory +from .fake_data import get_fake_rl_trajectory, fake_rl_data_batch_with_last diff --git a/dizoo/distar/policy/distar_policy.py b/dizoo/distar/policy/distar_policy.py index e09029059f..5abbdd0902 100644 --- a/dizoo/distar/policy/distar_policy.py +++ b/dizoo/distar/policy/distar_policy.py @@ -174,7 +174,7 @@ def _create_model( raise KeyError("invalid policy mode: {}".format(field)) def _init_learn(self): - self.learn_model = model_wrap(self._model, 'base') + self._learn_model = model_wrap(self._model, 'base') self.head_types = ['action_type', 'delay', 'queued', 'target_unit', 'selected_units', 'target_location'] # policy parameters self.gammas = self._cfg.gammas @@ -187,7 +187,7 @@ def _init_learn(self): # optimizer self.optimizer = Adam( - self.learn_model.parameters(), + self._learn_model.parameters(), lr=self._cfg.learning_rate, betas=(0, 0.99), eps=1e-5, @@ -209,7 +209,7 @@ def _forward_learn(self, inputs: Dict): # create loss show dict loss_info_dict = {} with self.timer: - model_output = self.learn_model.rl_learn_forward(**inputs) + model_output = self._learn_model.rl_learn_forward(**inputs) loss_info_dict['model_forward_time'] = self.timer.value # =========== @@ -371,7 +371,7 @@ def _forward_learn(self, inputs: Dict): total_loss.backward() if self._cfg.learn.multi_gpu: self.sync_gradients() - gradient = torch.nn.utils.clip_grad_norm_(self.learn_model.parameters(), self._cfg.grad_clip.threshold, 2) + gradient = torch.nn.utils.clip_grad_norm_(self._learn_model.parameters(), self._cfg.grad_clip.threshold, 2) self.optimizer.step() loss_info_dict['backward_time'] = self.timer.value @@ -389,12 +389,12 @@ def _monitor_var_learn(self): def _state_dict(self) -> Dict: return { - 'model': self.learn_model.state_dict(), + 'model': self._learn_model.state_dict(), 'optimizer': self.optimizer.state_dict(), } def _load_state_dict_learn(self, _state_dict: Dict) -> None: - self.learn_model.load_state_dict(_state_dict['model']) + self._learn_model.load_state_dict(_state_dict['model']) self.optimizer.load_state_dict(_state_dict['optimizer']) def _init_collect(self): From 0bd6e4ac2cfe25ead1a9dcc898574718830c7ab6 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 21 Jun 2022 16:43:15 +0800 Subject: [PATCH 134/229] deal with step error --- ding/framework/context.py | 1 + .../middleware/functional/collector.py | 5 +- .../middleware/tests/mock_for_test.py | 87 ++++--------------- .../test_league_actor_distar_one_process.py | 41 +++++---- dizoo/distar/envs/distar_env.py | 15 ++-- 5 files changed, 52 insertions(+), 97 deletions(-) diff --git a/ding/framework/context.py b/ding/framework/context.py index 46d58c20c4..ad5134625b 100644 --- a/ding/framework/context.py +++ b/ding/framework/context.py @@ -102,6 +102,7 @@ def __init__(self, *args, **kwargs) -> None: #data self.obs = None self.actions = None + self.inference_output = {} #Return data paras self.episodes = [] diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 8b4ca0e310..af64f68dc7 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -120,12 +120,13 @@ def _cut_trajectory_from_episode(self, episode: list): def clear_newest_episode(self, env_id: int) -> None: # Use it when env.step raise some error + len_newest_episode = 0 if self._done_episode[env_id][-1] is False: newest_episode = self._transitions[env_id].pop() + len_newest_episode = len(newest_episode) newest_episode.clear() self._done_episode[env_id].pop() - else: - return + return len_newest_episode def append(self, env_id: int, transition: Any) -> None: # If previous episode is done, we create a new episode diff --git a/ding/framework/middleware/tests/mock_for_test.py b/ding/framework/middleware/tests/mock_for_test.py index 789bd28460..16b9ef23a5 100644 --- a/ding/framework/middleware/tests/mock_for_test.py +++ b/ding/framework/middleware/tests/mock_for_test.py @@ -15,7 +15,7 @@ from ding.envs import BaseEnvManager import treetensor.torch as ttorch from ding.envs import BaseEnvTimestep -from distar.agent.default.lib.features import Features +from dizoo.distar.envs.fake_data import rl_step_data if TYPE_CHECKING: from ding.framework import BattleContext @@ -205,7 +205,6 @@ class DIstarCollectMode: def __init__(self) -> None: self._cfg = EasyDict(dict(collect=dict(n_episode=1))) - self._feature = None self._race = 'zerg' def load_state_dict(self, state_dict): @@ -222,22 +221,8 @@ def get_attribute(self, name: str) -> Any: def reset(self, data_id: Optional[List[int]] = None) -> None: pass - def _pre_process(self, obs): - agent_obs = self._feature.transform_obs(obs['raw_obs'], padding_spatial=True) - self._game_info = agent_obs.pop('game_info') - self._game_step = self._game_info['game_loop'] - - last_selected_units = torch.zeros(agent_obs['entity_num'], dtype=torch.int8) - last_targeted_unit = torch.zeros(agent_obs['entity_num'], dtype=torch.int8) - - agent_obs['entity_info']['last_selected_units'] = last_selected_units - agent_obs['entity_info']['last_targeted_unit'] = last_targeted_unit - - self._observation = agent_obs - def forward(self, policy_obs: Dict[int, Any]) -> Dict[int, Any]: # print("Call forward_collect:") - self._pre_process(policy_obs) return_data = {} return_data['action'] = DIStarEnv.random_action(policy_obs) return_data['logit'] = [1] @@ -245,29 +230,9 @@ def forward(self, policy_obs: Dict[int, Any]) -> Dict[int, Any]: return return_data - def process_transition(self, obs: Any, model_output: dict, timestep: namedtuple) -> dict: - next_obs = timestep.obs - reward = timestep.reward - done = timestep.done - agent_obs = self._observation - step_data = { - 'obs': { - 'map_name': 'KingsCove', - 'spatial_info': agent_obs['spatial_info'], - # 'spatial_info_ref': spatial_info_ref, - 'entity_info': agent_obs['entity_info'], - 'scalar_info': agent_obs['scalar_info'], - 'entity_num': agent_obs['entity_num'], - 'step': torch.tensor(self._game_step, dtype=torch.float) - }, - 'next_obs': {}, - 'logit': model_output['logit'], - 'action': model_output['action'], - 'value': model_output['value'], - # 'successive_logit': deepcopy(teacher_output['logit']), - 'reward': reward, - 'done': done - } + def process_transition(self, timestep) -> dict: + step_data = rl_step_data() + step_data['done'] = timestep.done return step_data @@ -285,13 +250,6 @@ def _battle_inferencer(ctx: "BattleContext"): if env.closed: env.launch() - # TODO: Just for distar - races = ['zerg', 'zerg'] - for policy_index, p in enumerate(ctx.current_policies): - if p._feature is None: - p._feature = Features(env._envs[0].game_info[policy_index], env.ready_obs[0][policy_index]['raw_obs']) - p._race = races[policy_index] - # Get current env obs. obs = env.ready_obs # the role of remain_episode is to mask necessary rollouts, avoid processing unnecessary data @@ -323,31 +281,24 @@ def battle_rolloutor_for_distar(cfg: EasyDict, env: BaseEnvManager, transitions_ def _battle_rolloutor(ctx: "BattleContext"): timesteps = env.step(ctx.actions) - # TODO: change this part to only modify the part of current episode, not influence previous episode - error_env_id_list = [] - for env_id, timestep in timesteps.items(): - if timestep.info.get('step_error'): - error_env_id_list.append(env_id) - ctx.total_envstep_count -= transitions_list[0].length(env_id) - ctx.env_step -= transitions_list[0].length(env_id) - for transitions in transitions_list: - transitions.clear_env_transitions(env_id) - for error_env_id in error_env_id_list: - del timesteps[error_env_id] + # for env_id, timestep in timesteps.items(): ctx.total_envstep_count += len(timesteps) ctx.env_step += len(timesteps) - for env_id, timestep in timesteps.items(): - for policy_id in ctx.obs[env_id].keys(): - policy_timestep = BaseEnvTimestep( - obs=timestep.obs.get(policy_id) if timestep.obs.get(policy_id) is not None else None, - reward=timestep.reward[policy_id], - done=timestep.done, - info={} - ) - transition = ctx.current_policies[policy_id].process_transition( - ctx.obs[env_id][policy_id], ctx.inference_output[env_id][policy_id], policy_timestep - ) + # for env_id, timestep in timesteps.items(): + # TODO(zms): make sure a standard + for env_id, timestep in enumerate(timesteps): + if timestep.info.get('abnormal'): + # TODO(zms): cannot get exact env_step of a episode because for each observation, + # in most cases only one of two policies has a obs. + # ctx.total_envstep_count -= transitions_list[0].length(env_id) + # ctx.env_step -= transitions_list[0].length(env_id) + for transitions in transitions_list: + transitions.clear_newest_episode(env_id) + continue + + for policy_id, _ in enumerate(ctx.current_policies): + transition = ctx.current_policies[policy_id].process_transition(timestep) transition = EasyDict(transition) transition.collect_train_iter = ttorch.as_tensor([ctx.train_iter]) transitions_list[policy_id].append(env_id, transition) diff --git a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py index a1b5cb578a..3f20b6a776 100644 --- a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py @@ -23,40 +23,45 @@ from ding.framework.middleware.tests import DIStarMockPolicy, DIStarMockPolicyCollect, \ battle_inferencer_for_distar, battle_rolloutor_for_distar +cfg = deepcopy(cfg) +env_cfg = read_config('./test_distar_config.yaml') -def prepare_test(): - global cfg - cfg = deepcopy(cfg) - env_cfg = read_config('./test_distar_config.yaml') +class PrepareTest(): - def env_fn(): - env = BaseEnvManager( - env_fn=[lambda: DIStarEnv(env_cfg) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager - ) - # env = EnvSupervisor( - # env_fn=[lambda: DIStarEnv(env_cfg) for _ in range(cfg.env.collector_env_num)], **cfg.env.manager + @classmethod + def get_env_fn(cls): + return DIStarEnv(env_cfg) + + @classmethod + def get_env_supervisor(cls): + # env = BaseEnvManager( + # env_fn=[lambda: DIStarEnv(env_cfg) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager # ) + env = EnvSupervisor( + type_=ChildType.THREAD, + env_fn=[cls.get_env_fn for _ in range(cfg.env.collector_env_num)], + **cfg.env.manager + ) env.seed(cfg.seed) return env - def policy_fn(): + @classmethod + def policy_fn(cls): model = VAC(**cfg.policy.model) policy = DIStarMockPolicy(cfg.policy, model=model) return policy - def collect_policy_fn(): + @classmethod + def collect_policy_fn(cls): policy = DIStarMockPolicyCollect() return policy - return cfg, env_fn, policy_fn, collect_policy_fn - @pytest.mark.unittest def test_league_actor(): - cfg, env_fn, policy_fn, collect_policy_fn = prepare_test() - policy = policy_fn() with task.start(async_mode=True, ctx=BattleContext()): + policy = PrepareTest.policy_fn() def test_actor(): job = Job( @@ -115,7 +120,9 @@ def _test_actor(ctx): with patch("ding.framework.middleware.collector.battle_inferencer", battle_inferencer_for_distar): with patch("ding.framework.middleware.collector.battle_rolloutor", battle_rolloutor_for_distar): - league_actor = StepLeagueActor(cfg=cfg, env_fn=env_fn, policy_fn=collect_policy_fn) + league_actor = StepLeagueActor( + cfg=cfg, env_fn=PrepareTest.get_env_supervisor, policy_fn=PrepareTest.collect_policy_fn + ) task.use(test_actor()) task.use(league_actor) task.run() diff --git a/dizoo/distar/envs/distar_env.py b/dizoo/distar/envs/distar_env.py index 88512666f9..f34ee527b1 100644 --- a/dizoo/distar/envs/distar_env.py +++ b/dizoo/distar/envs/distar_env.py @@ -15,16 +15,11 @@ def __init__(self, cfg): self._map_name = None def reset(self): - while True: - try: - observations, game_info, map_name = super(DIStarEnv, self).reset() - # print(game_info) - self.game_info = game_info - self.map_name = map_name - return observations - except Exception as e: - print("during reset SC2 env, an error happend: ", e, flush=True) - self.close() + observations, game_info, map_name = super(DIStarEnv, self).reset() + # print(game_info) + self.game_info = game_info + self.map_name = map_name + return observations def close(self): super(DIStarEnv, self).close() From 338a2a2c3f82d1da966122db8efe625361cd8850 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 21 Jun 2022 17:07:59 +0800 Subject: [PATCH 135/229] change a bit env_supervisor so it could run DI-star env --- ding/envs/env_manager/base_env_manager.py | 2 -- ding/envs/env_manager/env_supervisor.py | 28 ++++++++++++------- .../middleware/tests/league_config.py | 7 +++-- 3 files changed, 22 insertions(+), 15 deletions(-) diff --git a/ding/envs/env_manager/base_env_manager.py b/ding/envs/env_manager/base_env_manager.py index 991f4b588b..b335db8dd2 100644 --- a/ding/envs/env_manager/base_env_manager.py +++ b/ding/envs/env_manager/base_env_manager.py @@ -77,9 +77,7 @@ def default_config(cls: type) -> EasyDict: config = dict( episode_num=float("inf"), max_retry=1, - # inf retry_type='reset', - # renew auto_reset=True, step_timeout=None, reset_timeout=None, diff --git a/ding/envs/env_manager/env_supervisor.py b/ding/envs/env_manager/env_supervisor.py index b3e1c17fcf..919e7e6ca2 100644 --- a/ding/envs/env_manager/env_supervisor.py +++ b/ding/envs/env_manager/env_supervisor.py @@ -61,6 +61,7 @@ def __init__( episode_num: int = float("inf"), shared_memory: bool = True, copy_on_get: bool = True, + return_original_data: bool = False, **kwargs ) -> None: """ @@ -78,6 +79,7 @@ def __init__( - retry_waiting_time (:obj:`Optional[float]`): Wait time on each retry. - shared_memory (:obj:`bool`): Use shared memory in multiprocessing. - copy_on_get (:obj:`bool`): Use copy on get in multiprocessing. + - return_original_data (:obj:`bool`): Return original observation or processed observation. """ if kwargs: logging.warning("Unknown parameters on env supervisor: {}".format(kwargs)) @@ -122,6 +124,7 @@ def __init__( self._retry_waiting_time = retry_waiting_time self._env_replay_path = None self._episode_num = episode_num + self._return_original_data = return_original_data self._init_states() def _init_states(self): @@ -255,6 +258,9 @@ def ready_obs(self) -> tnp.array: >>> timesteps = env_manager.step(action) """ active_env = [i for i, s in self._env_states.items() if s == EnvState.RUN] + # TODO(zms): change it here or in env? + if self._return_original_data: + return {i: self._ready_obs[i] for i in active_env} active_env.sort() obs = [self._ready_obs.get(i) for i in active_env] if len(obs) == 0: @@ -409,16 +415,18 @@ def _recv_step_callback( remain_payloads[p.req_id] = p # make the type and content of key as similar as identifier, # in order to call them as attribute (e.g. timestep.xxx), such as ``TimeLimit.truncated`` in cartpole info - info = make_key_as_identifier(info) - payload.data = tnp.array( - { - 'obs': obs, - 'reward': reward, - 'done': done, - 'info': info, - 'env_id': payload.proc_id - } - ) + # TODO(zms): change it here or in DI-star env? + if not self._return_original_data: + info = make_key_as_identifier(info) + payload.data = tnp.array( + { + 'obs': obs, + 'reward': reward, + 'done': done, + 'info': info, + 'env_id': payload.proc_id + } + ) self._ready_obs[payload.proc_id] = obs return payload diff --git a/ding/framework/middleware/tests/league_config.py b/ding/framework/middleware/tests/league_config.py index bcb4ae8821..dab2606a08 100644 --- a/ding/framework/middleware/tests/league_config.py +++ b/ding/framework/middleware/tests/league_config.py @@ -4,14 +4,15 @@ 'env': { 'manager': { 'episode_num': 100000, - 'max_retry': 1, - 'retry_type': 'reset', + 'max_retry': 1000, + 'retry_type': 'renew', 'auto_reset': True, 'step_timeout': None, 'reset_timeout': None, 'retry_waiting_time': 0.1, 'cfg_type': 'BaseEnvManagerDict', - 'shared_memory': False + 'shared_memory': False, + 'return_original_data': True }, 'collector_env_num': 1, 'evaluator_env_num': 1, From 65e3fb1d203fb6eeabe17926a33c64de87eb1b3d Mon Sep 17 00:00:00 2001 From: lixuelin Date: Tue, 21 Jun 2022 19:04:05 +0800 Subject: [PATCH 136/229] polish pipeline & add distar example --- ding/example/distar.py | 87 ++++++++++ .../middleware/league_coordinator.py | 6 +- ding/framework/middleware/league_learner.py | 15 +- .../middleware/tests/league_config.py | 2 +- .../middleware/tests/mock_for_test.py | 1 - .../test_league_actor_distar_one_process.py | 2 +- .../tests/test_league_actor_one_process.py | 2 +- .../middleware/tests/test_league_learner.py | 11 +- .../middleware/tests/test_league_pipeline.py | 90 ++++++---- ding/league/player.py | 40 +++-- ding/utils/data/collate_fn.py | 12 +- dizoo/distar/config/__init__.py | 1 + dizoo/distar/config/distar_config.py | 164 ++++++++++++++++++ 13 files changed, 364 insertions(+), 69 deletions(-) create mode 100644 ding/example/distar.py create mode 100644 dizoo/distar/config/__init__.py create mode 100644 dizoo/distar/config/distar_config.py diff --git a/ding/example/distar.py b/ding/example/distar.py new file mode 100644 index 0000000000..b7bae5fc36 --- /dev/null +++ b/ding/example/distar.py @@ -0,0 +1,87 @@ +import logging +import pytest +from easydict import EasyDict +from copy import deepcopy +from ding.data import DequeBuffer +from ding.envs import BaseEnvManager +from ding.framework.context import BattleContext +from ding.framework.middleware import StepLeagueActor, LeagueCoordinator, LeagueLearnerExchanger, data_pusher, OffPolicyLearner +from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, DIStarMockPolicyCollect, battle_inferencer_for_distar, battle_rolloutor_for_distar +from ding.framework.task import task, Parallel +from ding.league.v2 import BaseLeague +from dizoo.distar.config import distar_cfg +from dizoo.distar.envs.distar_env import DIStarEnv +from unittest.mock import patch + +env_cfg = dict( + actor=dict(job_type='train', ), + env=dict( + map_name='KingsCove', + player_ids=['agent1', 'agent2'], + races=['zerg', 'zerg'], + map_size_resolutions=[True, True], # if True, ignore minimap_resolutions + minimap_resolutions=[[160, 152], [160, 152]], + realtime=False, + replay_dir='.', + random_seed='none', + game_steps_per_episode=100000, + update_bot_obs=False, + save_replay_episodes=1, + update_both_obs=False, + version='4.10.0', + ), +) + + +def prepare_test(): + global distar_cfg, env_cfg + env_cfg = EasyDict(env_cfg) + cfg = deepcopy(distar_cfg) + + def env_fn(): + # subprocess env manager + env = BaseEnvManager( + env_fn=[lambda: DIStarEnv(env_cfg) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager + ) + env.seed(cfg.seed) + return env + + def policy_fn(): + policy = DIStarMockPolicy(DIStarMockPolicy.default_config(), enable_field=['learn']) + return policy + + def collect_policy_fn(): + policy = DIStarMockPolicyCollect() + return policy + + return cfg, env_fn, policy_fn, collect_policy_fn + + +def main(): + logging.getLogger().setLevel(logging.INFO) + cfg, env_fn, policy_fn, collect_policy_fn = prepare_test() + league = BaseLeague(cfg.policy.other.league) + N_PLAYERS = len(league.active_players_ids) + print("League: n_players =", N_PLAYERS) + + with task.start(async_mode=True, ctx=BattleContext()),\ + patch("ding.framework.middleware.collector.battle_inferencer", battle_inferencer_for_distar),\ + patch("ding.framework.middleware.collector.battle_rolloutor", battle_rolloutor_for_distar): + print("node id:", task.router.node_id) + if task.router.node_id == 0: + task.use(LeagueCoordinator(cfg, league)) + elif task.router.node_id <= N_PLAYERS: + buffer_ = DequeBuffer(size=cfg.policy.other.replay_buffer.replay_buffer_size) + player = league.active_players[task.router.node_id % N_PLAYERS] + policy = policy_fn() + task.use(LeagueLearnerExchanger(cfg, policy.learn_mode, player)) + task.use(data_pusher(cfg, buffer_)) + task.use(OffPolicyLearner(cfg, policy.learn_mode, buffer_)) + else: + task.use(StepLeagueActor(cfg, env_fn, collect_policy_fn)) + + task.run() + + +if __name__ == "__main__": + Parallel.runner(n_parallel_workers=4, protocol="tcp", topology="mesh")(main) diff --git a/ding/framework/middleware/league_coordinator.py b/ding/framework/middleware/league_coordinator.py index d9e735b272..6b9243cb99 100644 --- a/ding/framework/middleware/league_coordinator.py +++ b/ding/framework/middleware/league_coordinator.py @@ -7,6 +7,7 @@ import logging if TYPE_CHECKING: + from easydict import EasyDict from ding.framework import Task, Context from ding.league.v2 import BaseLeague from ding.league.player import PlayerMeta @@ -15,12 +16,11 @@ class LeagueCoordinator: - def __init__(self, league: "BaseLeague") -> None: + def __init__(self, cfg: "EasyDict", league: "BaseLeague") -> None: self.league = league self._lock = Lock() self._total_send_jobs = 0 self._eval_frequency = 10 - self._step = 0 task.on(EventEnum.ACTOR_GREETING, self._on_actor_greeting) task.on(EventEnum.LEARNER_SEND_META, self._on_learner_meta) @@ -42,13 +42,11 @@ def _on_actor_greeting(self, actor_id): def _on_learner_meta(self, player_meta: "PlayerMeta"): print('coordinator recieve learner meta for player{}\n'.format(player_meta.player_id), flush=True) - # print("on_learner_meta {}".format(player_meta)) self.league.update_active_player(player_meta) self.league.create_historical_player(player_meta) def _on_actor_job(self, job: "Job"): print('coordinator recieve actor finished job, palyer {}\n'.format(job.launch_player), flush=True) - print("on_actor_job {}".format(job.launch_player)) # right self.league.update_payoff(job) def __del__(self): diff --git a/ding/framework/middleware/league_learner.py b/ding/framework/middleware/league_learner.py index 2c0de6d5cc..679c3992d9 100644 --- a/ding/framework/middleware/league_learner.py +++ b/ding/framework/middleware/league_learner.py @@ -13,7 +13,7 @@ from ding.worker.learner.base_learner import BaseLearner if TYPE_CHECKING: - from ding.data import Buffer + from ding.policy import Policy from ding.framework import Context from ding.framework.middleware.league_actor import ActorData from ding.league import ActivePlayer @@ -36,12 +36,13 @@ def __init__(self, cfg: dict, policy: "Policy", player: "ActivePlayer") -> None: self.policy = policy self.prefix = '{}/ckpt'.format(cfg.exp_name) task.on(EventEnum.ACTOR_SEND_DATA.format(player=self.player_id), self._push_data) - + def _push_data(self, data: "ActorData"): - print("push data into the cache!") + print("learner {} receive data from actor! \n".format(task.router.node_id), flush=True) self._cache.append(data.train_data) def __call__(self, ctx: "Context"): + print("push data into the ctx") ctx.trajectories = list(self._cache) self._cache.clear() sleep(1) @@ -73,7 +74,7 @@ def __init__(self, cfg: dict, policy_fn: Callable, player: "ActivePlayer") -> No task.on(EventEnum.ACTOR_SEND_DATA.format(player=self.player_id), self._push_data) self._learner = OffPolicyLearner(cfg, self._policy, self._buffer) # self._ckpt_handler = CkptSaver(cfg, self._policy, train_freq=100) - + def _push_data(self, data: "ActorData"): print("push data into the buffer!") self._buffer.push(data.train_data) @@ -91,7 +92,9 @@ def __call__(self, ctx: "Context"): ) learner_model = LearnerModel( - player_id=self.player_id, state_dict=self._policy.state_dict(), train_iter=ctx.train_iter # self._policy.state_dict() + player_id=self.player_id, + state_dict=self._policy.state_dict(), + train_iter=ctx.train_iter # self._policy.state_dict() ) print('learner send model\n', flush=True) task.emit(EventEnum.LEARNER_SEND_MODEL, learner_model) @@ -162,5 +165,3 @@ def __del__(self): def __call__(self, _: "Context") -> None: sleep(1) - # logging.info("{} Step: {}".format(self.__class__, self._step)) - # self._step += 1 diff --git a/ding/framework/middleware/tests/league_config.py b/ding/framework/middleware/tests/league_config.py index af8758364d..07a9afd5cc 100644 --- a/ding/framework/middleware/tests/league_config.py +++ b/ding/framework/middleware/tests/league_config.py @@ -46,7 +46,7 @@ }, 'multi_gpu': False, 'epoch_per_collect': 10, - 'batch_size': 4, + 'batch_size': 16, 'learning_rate': 1e-05, 'value_weight': 0.5, 'entropy_weight': 0.0, diff --git a/ding/framework/middleware/tests/mock_for_test.py b/ding/framework/middleware/tests/mock_for_test.py index b9cb8e32a3..37f6c9cde2 100644 --- a/ding/framework/middleware/tests/mock_for_test.py +++ b/ding/framework/middleware/tests/mock_for_test.py @@ -186,7 +186,6 @@ def _forward_collect(self, data: Dict[int, Any]) -> Dict[int, Any]: return DIStarEnv.random_action(data) - class DIstarCollectMode: def __init__(self) -> None: diff --git a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py index 6977630eb8..823bed0d30 100644 --- a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py @@ -169,4 +169,4 @@ def _test_actor(ctx): if __name__ == '__main__': - test_league_actor() \ No newline at end of file + test_league_actor() diff --git a/ding/framework/middleware/tests/test_league_actor_one_process.py b/ding/framework/middleware/tests/test_league_actor_one_process.py index 3d4cf7125f..90ff5b3420 100644 --- a/ding/framework/middleware/tests/test_league_actor_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_one_process.py @@ -42,7 +42,7 @@ def policy_fn(): def test_league_actor(): cfg, env_fn, policy_fn = prepare_test() policy = policy_fn() - with task.start(async_mode=True, ctx = BattleContext()): + with task.start(async_mode=True, ctx=BattleContext()): league_actor = StepLeagueActor(cfg=cfg, env_fn=env_fn, policy_fn=policy_fn) def test_actor(): diff --git a/ding/framework/middleware/tests/test_league_learner.py b/ding/framework/middleware/tests/test_league_learner.py index 89c9d2a56d..07b7414800 100644 --- a/ding/framework/middleware/tests/test_league_learner.py +++ b/ding/framework/middleware/tests/test_league_learner.py @@ -9,14 +9,15 @@ from ding.framework.context import BattleContext from ding.framework import EventEnum from ding.framework.task import task, Parallel -from ding.framework.middleware import OffPolicyLeagueLearner, data_pusher,\ +from ding.framework.middleware import data_pusher,\ OffPolicyLearner, LeagueLearnerExchanger from ding.framework.middleware.functional.actor_data import ActorData from ding.framework.middleware.tests import cfg, MockLeague, MockLogger from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy +from ding.league.v2 import BaseLeague from dizoo.distar.envs.distar_env import DIStarEnv -from distar.ctools.utils import read_config from dizoo.distar.envs import fake_rl_data_batch_with_last +from distar.ctools.utils import read_config logging.getLogger().setLevel(logging.INFO) @@ -57,7 +58,7 @@ def _actor_mocker(ctx): n_players = len(league.active_players_ids) player = league.active_players[(task.router.node_id + 2) % n_players] print("actor player:", player.player_id) - for _ in range(3): + for _ in range(24): data = fake_rl_data_batch_with_last() actor_data = ActorData(env_step=0, train_data=data) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=player.player_id), actor_data) @@ -68,7 +69,7 @@ def _actor_mocker(ctx): def _main(): cfg, env_fn, policy_fn = prepare_test() - league = MockLeague(cfg.policy.other.league) + league = BaseLeague(cfg.policy.other.league) with task.start(async_mode=True, ctx=BattleContext()): if task.router.node_id == 0: @@ -84,7 +85,7 @@ def _main(): task.use(LeagueLearnerExchanger(cfg, policy.learn_mode, player)) task.use(data_pusher(cfg, buffer_)) task.use(OffPolicyLearner(cfg, policy.learn_mode, buffer_)) - task.run(max_step=200) + task.run(max_step=30) @pytest.mark.unittest diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index db1024c809..bf8e5db502 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -1,26 +1,42 @@ -from copy import deepcopy -from time import sleep +import logging import pytest +from easydict import EasyDict +from copy import deepcopy +from ding.data import DequeBuffer from ding.envs import BaseEnvManager from ding.framework.context import BattleContext -from ding.framework.middleware import StepLeagueActor, LeagueCoordinator, LeagueLearner, OffPolicyLeagueLearner - -from ding.model import VAC +from ding.framework.middleware import StepLeagueActor, LeagueCoordinator, LeagueLearnerExchanger, data_pusher, OffPolicyLearner +from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, DIStarMockPolicyCollect, battle_inferencer_for_distar, battle_rolloutor_for_distar from ding.framework.task import task, Parallel -from ding.framework.middleware.tests import cfg, MockLeague, MockLogger +from ding.league.v2 import BaseLeague +from dizoo.distar.config import distar_cfg from dizoo.distar.envs.distar_env import DIStarEnv -from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, DIStarMockPolicyCollect, battle_inferencer_for_distar, battle_rolloutor_for_distar -from distar.ctools.utils import read_config from unittest.mock import patch -N_ACTORS = 1 -N_LEARNERS = 1 +env_cfg = dict( + actor=dict(job_type='train', ), + env=dict( + map_name='KingsCove', + player_ids=['agent1', 'agent2'], + races=['zerg', 'zerg'], + map_size_resolutions=[True, True], # if True, ignore minimap_resolutions + minimap_resolutions=[[160, 152], [160, 152]], + realtime=False, + replay_dir='.', + random_seed='none', + game_steps_per_episode=100000, + update_bot_obs=False, + save_replay_episodes=1, + update_both_obs=False, + version='4.10.0', + ), +) def prepare_test(): - global cfg - cfg = deepcopy(cfg) - env_cfg = read_config('./test_distar_config.yaml') + global distar_cfg, env_cfg + env_cfg = EasyDict(env_cfg) + cfg = deepcopy(distar_cfg) def env_fn(): # subprocess env manager @@ -41,30 +57,36 @@ def collect_policy_fn(): return cfg, env_fn, policy_fn, collect_policy_fn -def _main(): +def main(): + logging.getLogger().setLevel(logging.INFO) cfg, env_fn, policy_fn, collect_policy_fn = prepare_test() - league = MockLeague(cfg.policy.other.league) - - with task.start(async_mode=True, ctx=BattleContext()): - with patch("ding.framework.middleware.collector.battle_inferencer", battle_inferencer_for_distar): - with patch("ding.framework.middleware.collector.battle_rolloutor", battle_rolloutor_for_distar): - print("node id:", task.router.node_id) - if task.router.node_id == 0: - task.use(LeagueCoordinator(league)) - elif task.router.node_id <= N_ACTORS: - task.use(StepLeagueActor(cfg, env_fn, collect_policy_fn)) - else: - n_players = len(league.active_players_ids) - player = league.active_players[task.router.node_id % n_players] - task.use(OffPolicyLeagueLearner(cfg, policy_fn, player)) - - task.run() + league = BaseLeague(cfg.policy.other.league) + N_PLAYERS = len(league.active_players_ids) + print("League: n_players =", N_PLAYERS) + + with task.start(async_mode=True, ctx=BattleContext()),\ + patch("ding.framework.middleware.collector.battle_inferencer", battle_inferencer_for_distar),\ + patch("ding.framework.middleware.collector.battle_rolloutor", battle_rolloutor_for_distar): + print("node id:", task.router.node_id) + if task.router.node_id == 0: + task.use(LeagueCoordinator(cfg, league)) + elif task.router.node_id <= N_PLAYERS: + buffer_ = DequeBuffer(size=cfg.policy.other.replay_buffer.replay_buffer_size) + player = league.active_players[task.router.node_id % N_PLAYERS] + policy = policy_fn() + task.use(LeagueLearnerExchanger(cfg, policy.learn_mode, player)) + task.use(data_pusher(cfg, buffer_)) + task.use(OffPolicyLearner(cfg, policy.learn_mode, buffer_)) + else: + task.use(StepLeagueActor(cfg, env_fn, collect_policy_fn)) + + task.run() @pytest.mark.unittest -def test_league_actor(): - Parallel.runner(n_parallel_workers=N_ACTORS + N_LEARNERS + 1, protocol="tcp", topology="mesh")(_main) +def test_league_pipeline(): + Parallel.runner(n_parallel_workers=4, protocol="tcp", topology="mesh")(main) -if __name__ == '__main__': - Parallel.runner(n_parallel_workers=N_ACTORS + N_LEARNERS + 1, protocol="tcp", topology="mesh")(_main) +if __name__ == "__main__": + Parallel.runner(n_parallel_workers=4, protocol="tcp", topology="mesh")(main) diff --git a/ding/league/player.py b/ding/league/player.py index c9f2b28402..61b1916a9a 100644 --- a/ding/league/player.py +++ b/ding/league/player.py @@ -1,4 +1,5 @@ from dataclasses import dataclass +import traceback from typing import Callable, Optional, List from collections import namedtuple import numpy as np @@ -6,7 +7,13 @@ from ding.utils import import_module, PLAYER_REGISTRY from .algorithm import pfsp -from ding.framework.storage import Storage +from ding.framework.storage import FileStorage +from typing import TYPE_CHECKING +if TYPE_CHECKING: + from ding.league.shared_payoff import BattleSharedPayoff + from ding.league.metric import LeagueMetricEnv + from ding.league.metric import PlayerRating + from ding.framework.storage import Storage @dataclass @@ -31,11 +38,11 @@ def __init__( self, cfg: EasyDict, category: str, - init_payoff: 'BattleSharedPayoff', # noqa + init_payoff: 'BattleSharedPayoff', checkpoint_path: str, player_id: str, total_agent_step: int, - rating: 'PlayerRating', # noqa + rating: 'PlayerRating', ) -> None: """ Overview: @@ -55,6 +62,7 @@ def __init__( self._category = category self._payoff = init_payoff self._checkpoint_path = checkpoint_path + self.checkpoint = FileStorage(path=checkpoint_path) assert isinstance(player_id, str) self._player_id = player_id assert isinstance(total_agent_step, int), (total_agent_step, type(total_agent_step)) @@ -66,7 +74,7 @@ def category(self) -> str: return self._category @property - def payoff(self) -> 'BattleSharedPayoff': # noqa + def payoff(self) -> 'BattleSharedPayoff': return self._payoff @property @@ -86,13 +94,17 @@ def total_agent_step(self, step: int) -> None: self._total_agent_step = step @property - def rating(self) -> 'PlayerRating': # noqa + def rating(self) -> 'PlayerRating': return self._rating @rating.setter - def rating(self, _rating: 'PlayerRating') -> None: # noqa + def rating(self, _rating: 'PlayerRating') -> None: self._rating = _rating + @property + def meta(self) -> PlayerMeta: + return PlayerMeta(player_id=self.player_id, checkpoint=self.checkpoint, total_agent_step=self.total_agent_step) + @PLAYER_REGISTRY.register('historical_player') class HistoricalPlayer(Player): @@ -188,7 +200,9 @@ def is_trained_enough(self, select_fn: Optional[Callable] = None) -> bool: else: return False - def snapshot(self, metric_env: 'LeagueMetricEnv') -> HistoricalPlayer: # noqa + def snapshot( + self, metric_env: 'LeagueMetricEnv', checkpoint: Optional["Storage"] = None + ) -> HistoricalPlayer: # noqa """ Overview: Generate a snapshot historical player from the current player, called in league's ``_snapshot``. @@ -201,8 +215,11 @@ def snapshot(self, metric_env: 'LeagueMetricEnv') -> HistoricalPlayer: # noqa This method only generates a historical player object, but without saving the checkpoint, which should be done by league. """ - path = self.checkpoint_path.split('.pth')[0] + '_{}'.format(self._total_agent_step) + '.pth' - return HistoricalPlayer( + if checkpoint: + path = checkpoint.path + else: + path = self.checkpoint_path.split('.pth')[0] + '_{}'.format(self._total_agent_step) + '.pth' + hp = HistoricalPlayer( self._cfg, self.category, self.payoff, @@ -212,6 +229,9 @@ def snapshot(self, metric_env: 'LeagueMetricEnv') -> HistoricalPlayer: # noqa metric_env.create_rating(mu=self.rating.mu), parent_id=self.player_id ) + if checkpoint: + hp.checkpoint = checkpoint + return hp def mutate(self, info: dict) -> Optional[str]: """ @@ -349,4 +369,4 @@ def create_player(cfg: EasyDict, player_type: str, *args, **kwargs) -> Player: player_mapping's values """ import_module(cfg.get('import_names', [])) - return PLAYER_REGISTRY.build(player_type, *args, **kwargs) + return PLAYER_REGISTRY.build(player_type, *args, **kwargs) \ No newline at end of file diff --git a/ding/utils/data/collate_fn.py b/ding/utils/data/collate_fn.py index 3b534a1980..a70c40e1d5 100644 --- a/ding/utils/data/collate_fn.py +++ b/ding/utils/data/collate_fn.py @@ -25,11 +25,13 @@ def ttorch_collate(x): return x -def default_collate(batch: Sequence, - dim: int = 0, - cat_1dim: bool = True, - allow_key_mismatch: bool = False, - ignore_prefix: list = ['collate_ignore']) -> Union[torch.Tensor, Mapping, Sequence]: +def default_collate( + batch: Sequence, + dim: int = 0, + cat_1dim: bool = True, + allow_key_mismatch: bool = False, + ignore_prefix: list = ['collate_ignore'] +) -> Union[torch.Tensor, Mapping, Sequence]: """ Overview: Put each data field into a tensor with outer dimension batch size. diff --git a/dizoo/distar/config/__init__.py b/dizoo/distar/config/__init__.py new file mode 100644 index 0000000000..a05f2cbff3 --- /dev/null +++ b/dizoo/distar/config/__init__.py @@ -0,0 +1 @@ +from .distar_config import distar_cfg \ No newline at end of file diff --git a/dizoo/distar/config/distar_config.py b/dizoo/distar/config/distar_config.py new file mode 100644 index 0000000000..575efd3260 --- /dev/null +++ b/dizoo/distar/config/distar_config.py @@ -0,0 +1,164 @@ +from easydict import EasyDict + +distar_cfg = EasyDict( + { + 'env': { + 'manager': { + 'episode_num': 100000, + 'max_retry': 1, + 'retry_type': 'reset', + 'auto_reset': True, + 'step_timeout': None, + 'reset_timeout': None, + 'retry_waiting_time': 0.1, + 'cfg_type': 'BaseEnvManagerDict', + 'shared_memory': False + }, + 'collector_env_num': 1, + 'evaluator_env_num': 1, + 'n_evaluator_episode': 100, + 'env_type': 'prisoner_dilemma', + 'stop_value': [-10.1, -5.05] + }, + 'policy': { + 'model': { + 'obs_shape': 2, + 'action_shape': 2, + 'action_space': 'discrete', + 'encoder_hidden_size_list': [32, 32], + 'critic_head_hidden_size': 32, + 'actor_head_hidden_size': 32, + 'share_encoder': False + }, + 'learn': { + 'learner': { + 'train_iterations': 1000000000, + 'dataloader': { + 'num_workers': 0 + }, + 'log_policy': False, + 'hook': { + 'load_ckpt_before_run': '', + 'log_show_after_iter': 100, + 'save_ckpt_after_iter': 10000, + 'save_ckpt_after_run': True + }, + 'cfg_type': 'BaseLearnerDict' + }, + 'multi_gpu': False, + 'epoch_per_collect': 10, + 'batch_size': 16, + 'learning_rate': 1e-05, + 'value_weight': 0.5, + 'entropy_weight': 0.0, + 'clip_ratio': 0.2, + 'adv_norm': True, + 'value_norm': True, + 'ppo_param_init': True, + 'grad_clip_type': 'clip_norm', + 'grad_clip_value': 0.5, + 'ignore_done': False, + 'update_per_collect': 3, + 'scheduler': { + 'schedule_flag': False, + 'schedule_mode': 'reduce', + 'factor': 0.005, + 'change_range': [0, 1], + 'threshold': 0.5, + 'patience': 50 + } + }, + 'collect': { + 'collector': { + 'deepcopy_obs': False, + 'transform_obs': False, + 'collect_print_freq': 100, + 'get_train_sample': True, + 'cfg_type': 'BattleEpisodeSerialCollectorDict' + }, + 'discount_factor': 1.0, + 'gae_lambda': 1.0, + 'n_episode': 1, + 'n_rollout_samples': 32, + 'n_sample': 64, + 'unroll_len': 1 + }, + 'eval': { + 'evaluator': { + 'eval_freq': 50, + 'cfg_type': 'BattleInteractionSerialEvaluatorDict', + 'stop_value': [-10.1, -5.05], + 'n_episode': 100 + } + }, + 'other': { + 'replay_buffer': { + 'type': 'naive', + 'replay_buffer_size': 10000, + 'deepcopy': False, + 'enable_track_used_data': False, + 'periodic_thruput_seconds': 60, + 'cfg_type': 'NaiveReplayBufferDict' + }, + 'league': { + 'player_category': ['default'], + 'path_policy': 'league_demo/ckpt', + 'active_players': { + 'main_player': 2 + }, + 'main_player': { + 'one_phase_step': 10, # 20 + 'branch_probs': { + 'pfsp': 0.0, + 'sp': 1.0 + }, + 'strong_win_rate': 0.7 + }, + 'main_exploiter': { + 'one_phase_step': 200, + 'branch_probs': { + 'main_players': 1.0 + }, + 'strong_win_rate': 0.7, + 'min_valid_win_rate': 0.3 + }, + 'league_exploiter': { + 'one_phase_step': 200, + 'branch_probs': { + 'pfsp': 1.0 + }, + 'strong_win_rate': 0.7, + 'mutate_prob': 0.5 + }, + 'use_pretrain': False, + 'use_pretrain_init_historical': False, + 'payoff': { + 'type': 'battle', + 'decay': 0.99, + 'min_win_rate_games': 8 + }, + 'metric': { + 'mu': 0, + 'sigma': 8.333333333333334, + 'beta': 4.166666666666667, + 'tau': 0.0, + 'draw_probability': 0.02 + } + } + }, + 'type': 'ppo', + 'cuda': False, + 'on_policy': True, + 'priority': False, + 'priority_IS_weight': False, + 'recompute_adv': True, + 'action_space': 'discrete', + 'nstep_return': False, + 'multi_agent': False, + 'transition_with_policy_data': True, + 'cfg_type': 'PPOPolicyDict' + }, + 'exp_name': 'league_demo', + 'seed': 0 + } +) \ No newline at end of file From 805d2191b5aa0f4de3287d9a680f13d80cb49574 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 21 Jun 2022 19:15:32 +0800 Subject: [PATCH 137/229] make pipelines run in supervisor --- .../middleware/league_coordinator.py | 2 +- .../test_league_actor_distar_one_process.py | 3 -- .../middleware/tests/test_league_pipeline.py | 41 ++++++++++--------- .../tests/test_league_pipeline_one_process.py | 39 ++++++++++-------- dizoo/distar/envs/distar_env.py | 13 ------ 5 files changed, 46 insertions(+), 52 deletions(-) diff --git a/ding/framework/middleware/league_coordinator.py b/ding/framework/middleware/league_coordinator.py index ec85766a8d..927be65ac7 100644 --- a/ding/framework/middleware/league_coordinator.py +++ b/ding/framework/middleware/league_coordinator.py @@ -48,7 +48,7 @@ def _on_learner_meta(self, player_meta: "PlayerMeta"): def _on_actor_job(self, job: "Job"): print('coordinator recieve actor finished job, palyer {}\n'.format(job.launch_player), flush=True) - print("on_actor_job {}".format(job.launch_player)) # right + print("on_actor_job {}\n".format(job.launch_player)) # right self.league.update_payoff(job) def __del__(self): diff --git a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py index 3f20b6a776..ae1eff9c9a 100644 --- a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py @@ -35,9 +35,6 @@ def get_env_fn(cls): @classmethod def get_env_supervisor(cls): - # env = BaseEnvManager( - # env_fn=[lambda: DIStarEnv(env_cfg) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager - # ) env = EnvSupervisor( type_=ChildType.THREAD, env_fn=[cls.get_env_fn for _ in range(cfg.env.collector_env_num)], diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index bc0f8b99db..65e39efdf1 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -4,6 +4,7 @@ from ding.envs import BaseEnvManager, EnvSupervisor from ding.framework.context import BattleContext from ding.framework.middleware import StepLeagueActor, LeagueCoordinator, LeagueLearner +from ding.framework.supervisor import ChildType from ding.model import VAC from ding.framework.task import task, Parallel @@ -14,40 +15,42 @@ from distar.ctools.utils import read_config from unittest.mock import patch -N_ACTORS = 2 +N_ACTORS = 1 N_LEARNERS = 2 +cfg = deepcopy(cfg) +env_cfg = read_config('./test_distar_config.yaml') -def prepare_test(): - global cfg - cfg = deepcopy(cfg) - env_cfg = read_config('./test_distar_config.yaml') - def env_fn(): - # subprocess env manager - env = BaseEnvManager( - env_fn=[lambda: DIStarEnv(env_cfg) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager +class PrepareTest(): + + @classmethod + def get_env_fn(cls): + return DIStarEnv(env_cfg) + + @classmethod + def get_env_supervisor(cls): + env = EnvSupervisor( + type_=ChildType.THREAD, + env_fn=[cls.get_env_fn for _ in range(cfg.env.collector_env_num)], + **cfg.env.manager ) - # env = EnvSupervisor( - # env_fn=[lambda: DIStarEnv(env_cfg) for _ in range(cfg.env.collector_env_num)], **cfg.env.manager - # ) env.seed(cfg.seed) return env - def policy_fn(): + @classmethod + def policy_fn(cls): model = VAC(**cfg.policy.model) policy = DIStarMockPolicy(cfg.policy, model=model) return policy - def collect_policy_fn(): + @classmethod + def collect_policy_fn(cls): policy = DIStarMockPolicyCollect() return policy - return cfg, env_fn, policy_fn, collect_policy_fn - def _main(): - cfg, env_fn, policy_fn, collect_policy_fn = prepare_test() league = MockLeague(cfg.policy.other.league) with task.start(async_mode=True, ctx=BattleContext()): @@ -57,11 +60,11 @@ def _main(): if task.router.node_id == 0: task.use(LeagueCoordinator(league)) elif task.router.node_id <= N_ACTORS: - task.use(StepLeagueActor(cfg, env_fn, collect_policy_fn)) + task.use(StepLeagueActor(cfg, PrepareTest.get_env_supervisor, PrepareTest.collect_policy_fn)) else: n_players = len(league.active_players_ids) player = league.active_players[task.router.node_id % n_players] - learner = LeagueLearner(cfg, policy_fn, player) + learner = LeagueLearner(cfg, PrepareTest.policy_fn, player) learner._learner._tb_logger = MockLogger() task.use(learner) diff --git a/ding/framework/middleware/tests/test_league_pipeline_one_process.py b/ding/framework/middleware/tests/test_league_pipeline_one_process.py index f92530b0fc..825a86b2cb 100644 --- a/ding/framework/middleware/tests/test_league_pipeline_one_process.py +++ b/ding/framework/middleware/tests/test_league_pipeline_one_process.py @@ -1,8 +1,9 @@ from copy import deepcopy import pytest -from ding.envs import BaseEnvManager +from ding.envs import BaseEnvManager, EnvSupervisor from ding.framework.context import BattleContext from ding.framework.middleware import StepLeagueActor, LeagueCoordinator, LeagueLearner +from ding.framework.supervisor import ChildType from ding.model import VAC from ding.framework.task import task @@ -14,33 +15,39 @@ from unittest.mock import patch import os +cfg = deepcopy(cfg) +env_cfg = read_config('./test_distar_config.yaml') -def prepare_test(): - global cfg - cfg = deepcopy(cfg) - env_cfg = read_config('./test_distar_config.yaml') - def env_fn(): - env = BaseEnvManager( - env_fn=[lambda: DIStarEnv(env_cfg) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager +class PrepareTest(): + + @classmethod + def get_env_fn(cls): + return DIStarEnv(env_cfg) + + @classmethod + def get_env_supervisor(cls): + env = EnvSupervisor( + type_=ChildType.THREAD, + env_fn=[cls.get_env_fn for _ in range(cfg.env.collector_env_num)], + **cfg.env.manager ) env.seed(cfg.seed) return env - def policy_fn(): + @classmethod + def policy_fn(cls): model = VAC(**cfg.policy.model) policy = DIStarMockPolicy(cfg.policy, model=model) return policy - def collect_policy_fn(): + @classmethod + def collect_policy_fn(cls): policy = DIStarMockPolicyCollect() return policy - return cfg, env_fn, policy_fn, collect_policy_fn - def _main(): - cfg, env_fn, policy_fn, collect_policy_fn = prepare_test() league = MockLeague(cfg.policy.other.league) n_players = len(league.active_players_ids) print(n_players) @@ -49,15 +56,15 @@ def _main(): with patch("ding.framework.middleware.collector.battle_inferencer", battle_inferencer_for_distar): with patch("ding.framework.middleware.collector.battle_rolloutor", battle_rolloutor_for_distar): player_0 = league.active_players[0] - learner_0 = LeagueLearner(cfg, policy_fn, player_0) + learner_0 = LeagueLearner(cfg, PrepareTest.policy_fn, player_0) learner_0._learner._tb_logger = MockLogger() player_1 = league.active_players[1] - learner_1 = LeagueLearner(cfg, policy_fn, player_1) + learner_1 = LeagueLearner(cfg, PrepareTest.policy_fn, player_1) learner_1._learner._tb_logger = MockLogger() task.use(LeagueCoordinator(league)) - task.use(StepLeagueActor(cfg, env_fn, collect_policy_fn)) + task.use(StepLeagueActor(cfg, PrepareTest.get_env_supervisor, PrepareTest.collect_policy_fn)) task.use(learner_0) task.use(learner_1) diff --git a/dizoo/distar/envs/distar_env.py b/dizoo/distar/envs/distar_env.py index f34ee527b1..1dbb7b50c7 100644 --- a/dizoo/distar/envs/distar_env.py +++ b/dizoo/distar/envs/distar_env.py @@ -11,14 +11,9 @@ class DIStarEnv(SC2Env, BaseEnv): def __init__(self, cfg): super(DIStarEnv, self).__init__(cfg) - self._game_info = None - self._map_name = None def reset(self): observations, game_info, map_name = super(DIStarEnv, self).reset() - # print(game_info) - self.game_info = game_info - self.map_name = map_name return observations def close(self): @@ -41,18 +36,10 @@ def seed(self, seed, dynamic_seed=False): def game_info(self): return self._game_info - @game_info.setter - def game_info(self, new_game_info): - self._game_info = new_game_info - @property def map_name(self): return self._map_name - @map_name.setter - def map_name(self, new_map_name): - self._map_name = new_map_name - @property def observation_space(self): #TODO From 87ac3ce85824cf177f35b34b25571facb3628e07 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 21 Jun 2022 19:36:23 +0800 Subject: [PATCH 138/229] reformat --- ding/framework/middleware/tests/test_league_pipeline.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index d8b08f0396..ff772e29f9 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -6,8 +6,8 @@ from ding.envs import BaseEnvManager, EnvSupervisor from ding.framework.supervisor import ChildType from ding.framework.context import BattleContext -from ding.framework.middleware import StepLeagueActor, LeagueCoordinator, LeagueLearnerExchanger, data_pusher, OffPolicyLearner -from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, DIStarMockPolicyCollect, battle_inferencer_for_distar, battle_rolloutor_for_distar +from ding.framework.middleware import StepLeagueActor, LeagueCoordinator, \ + LeagueLearnerExchanger, data_pusher, OffPolicyLearner from ding.framework.task import task, Parallel from ding.league.v2 import BaseLeague from dizoo.distar.config import distar_cfg From 53bfdf596fbe63ca87319a959699992ad6a2ade6 Mon Sep 17 00:00:00 2001 From: niuyazhe Date: Tue, 21 Jun 2022 23:00:52 +0800 Subject: [PATCH 139/229] feature(nyz): add basic distar policy collect(ci skip) --- dizoo/distar/envs/__init__.py | 3 +- dizoo/distar/envs/fake_data.py | 10 +- dizoo/distar/envs/meta.py | 3 +- dizoo/distar/envs/stat.py | 789 +++++++++++++++++++++++++++ dizoo/distar/policy/distar_policy.py | 203 ++++--- dizoo/distar/policy/utils.py | 56 ++ 6 files changed, 993 insertions(+), 71 deletions(-) create mode 100644 dizoo/distar/envs/stat.py diff --git a/dizoo/distar/envs/__init__.py b/dizoo/distar/envs/__init__.py index 1c80372f03..be5986556a 100644 --- a/dizoo/distar/envs/__init__.py +++ b/dizoo/distar/envs/__init__.py @@ -1,3 +1,4 @@ from .meta import * -from .static_data import BEGIN_ACTIONS, ACTION_RACE_MASK, SELECTED_UNITS_MASK +from .static_data import BEGIN_ACTIONS, ACTION_RACE_MASK, SELECTED_UNITS_MASK, ACTIONS +from .stat import Stat from .fake_data import get_fake_rl_trajectory diff --git a/dizoo/distar/envs/fake_data.py b/dizoo/distar/envs/fake_data.py index ec910eaa72..9dfdf2c56a 100644 --- a/dizoo/distar/envs/fake_data.py +++ b/dizoo/distar/envs/fake_data.py @@ -2,7 +2,7 @@ import torch from ding.utils.data import default_collate -from .meta import MAX_DELAY, MAX_ENTITY_NUM, NUM_ACTIONS, ENTITY_TYPE_NUM, NUM_UPGRADES, NUM_CUMULATIVE_STAT_ACTIONS, \ +from .meta import MAX_DELAY, MAX_ENTITY_NUM, NUM_ACTIONS, NUM_UNIT_TYPES, NUM_UPGRADES, NUM_CUMULATIVE_STAT_ACTIONS, \ NUM_BEGINNING_ORDER_ACTIONS, NUM_UNIT_MIX_ABILITIES, NUM_QUEUE_ACTION, NUM_BUFFS, NUM_ADDON, MAX_SELECTED_UNITS_NUM H, W = 152, 160 @@ -28,7 +28,7 @@ def spatial_info(): def entity_info(): data = { - 'unit_type': torch.randint(0, ENTITY_TYPE_NUM, size=(MAX_ENTITY_NUM, ), dtype=torch.float), + 'unit_type': torch.randint(0, NUM_UNIT_TYPES, size=(MAX_ENTITY_NUM, ), dtype=torch.float), 'alliance': torch.randint(0, 5, size=(MAX_ENTITY_NUM, ), dtype=torch.float), 'cargo_space_taken': torch.randint(0, 9, size=(MAX_ENTITY_NUM, ), dtype=torch.float), 'build_progress': torch.rand(MAX_ENTITY_NUM), @@ -74,7 +74,7 @@ def scalar_info(): 'away_race': torch.randint(0, 4, size=(), dtype=torch.float), 'agent_statistics': torch.rand(10), 'time': torch.randint(0, 100, size=(), dtype=torch.float), - 'unit_counts_bow': torch.randint(0, 10, size=(ENTITY_TYPE_NUM, ), dtype=torch.float), + 'unit_counts_bow': torch.randint(0, 10, size=(NUM_UNIT_TYPES, ), dtype=torch.float), 'beginning_build_order': torch.randint(0, 20, size=(20, ), dtype=torch.float), 'cumulative_stat': torch.randint(0, 2, size=(NUM_CUMULATIVE_STAT_ACTIONS, ), dtype=torch.float), 'last_delay': torch.randint(0, MAX_DELAY, size=(), dtype=torch.float), @@ -83,8 +83,8 @@ def scalar_info(): 'upgrades': torch.randint(0, 2, size=(NUM_UPGRADES, ), dtype=torch.float), 'beginning_order': torch.randint(0, NUM_BEGINNING_ORDER_ACTIONS, size=(20, ), dtype=torch.float), 'bo_location': torch.randint(0, 100 * 100, size=(20, ), dtype=torch.float), - 'unit_type_bool': torch.randint(0, 2, size=(ENTITY_TYPE_NUM, ), dtype=torch.float), - 'enemy_unit_type_bool': torch.randint(0, 2, size=(ENTITY_TYPE_NUM, ), dtype=torch.float), + 'unit_type_bool': torch.randint(0, 2, size=(NUM_UNIT_TYPES, ), dtype=torch.float), + 'enemy_unit_type_bool': torch.randint(0, 2, size=(NUM_UNIT_TYPES, ), dtype=torch.float), 'unit_order_type': torch.randint(0, 2, size=(NUM_UNIT_MIX_ABILITIES, ), dtype=torch.float) } return data diff --git a/dizoo/distar/envs/meta.py b/dizoo/distar/envs/meta.py index 7cae00865e..bb11787f79 100644 --- a/dizoo/distar/envs/meta.py +++ b/dizoo/distar/envs/meta.py @@ -1,7 +1,7 @@ MAX_DELAY = 128 MAX_ENTITY_NUM = 512 MAX_SELECTED_UNITS_NUM = 64 -ENTITY_TYPE_NUM = 260 +NUM_UNIT_TYPES = 260 NUM_ACTIONS = 327 NUM_UPGRADES = 90 NUM_CUMULATIVE_STAT_ACTIONS = 167 @@ -10,4 +10,3 @@ NUM_QUEUE_ACTION = 49 NUM_BUFFS = 50 NUM_ADDON = 9 -MAX_SELECTED_UNITS_NUM = 64 diff --git a/dizoo/distar/envs/stat.py b/dizoo/distar/envs/stat.py new file mode 100644 index 0000000000..cebc3a028c --- /dev/null +++ b/dizoo/distar/envs/stat.py @@ -0,0 +1,789 @@ +from collections import defaultdict +import torch +from .static_data import ACTIONS + + +class Stat(object): + + def __init__(self, race_id): + self._unit_num = defaultdict(int) + self._unit_num['max_unit_num'] = 0 + self._race_id = race_id + for k, v in unit_dict[race_id].items(): + self._unit_num[v] = 0 + self._action_success_count = defaultdict(int) + + def update(self, last_action_type, action_result, observation, game_step): + if action_result < 1: + return + if action_result == 1: + self.count_unit_num(last_action_type) + entity_info, entity_num = observation['entity_info'], observation['entity_num'] + try: + if (entity_info['alliance'][:entity_num] == 1).sum() > 10: + self.success_rate_calc(last_action_type, action_result) + except Exception as e: + print('ERROR_ stat.py', e, entity_info['alliance'], entity_num) + + def success_rate_calc(self, last_action_type, action_result): + action_name = ACTIONS[last_action_type]['name'] + error_msg = action_result_dict[action_result] + self._action_success_count['rate/{}/{}'.format(action_name, error_msg)] += 1 + self._action_success_count['rate/{}/{}'.format(action_name, 'count')] += 1 + + def get_stat_data(self): + data = {} + for k, v in self._unit_num.items(): + if k != 'max_unit_num': + data['units/' + k] = v / self._unit_num['max_unit_num'] + for k, v in self._action_success_count.items(): + action_type = k.split('rate/')[1].split('/')[0] + if 'count' in k: + data[k] = v + else: + data[k] = v / (self._action_success_count['rate/{}/{}'.format(action_type, 'count')] + 1e-6) + return data + + def count_unit_num(self, last_action_type): + unit_name = self.get_build_unit_name(last_action_type, self._race_id) + if not unit_name: + return + self._unit_num[unit_name] += 1 + self._unit_num['max_unit_num'] = max(self._unit_num[unit_name], self._unit_num['max_unit_num']) + + @staticmethod + def get_build_unit_name(action_type, race_id): + action_type = ACTIONS[action_type]['func_id'] + unit_name = unit_dict[race_id].get(action_type, False) + return unit_name + + def set_race_id(self, race_id: int): + self._race_id = race_id + + @property + def unit_num(self): + return self._unit_num + + +unit_dict = { + 'zerg': { + 383: 'BroodLord', + 391: 'Lurker', + 395: 'OverlordTransport', + 396: 'Overseer', + 400: 'Ravager', + 498: 'Baneling', + 501: 'Corruptor', + 503: 'Drone', + 507: 'Hydralisk', + 508: 'Infestor', + 514: 'Mutalisk', + 515: 'Overlord', + 516: 'Queen', + 519: 'Roach', + 522: 'SwarmHost', + 524: 'Ultralisk', + 526: 'Viper', + 528: 'Zergling' + }, + 'terran': { + 499: 'Banshee', + 500: 'Battlecruiser', + 502: 'Cyclone', + 504: 'Ghost', + 505: 'Hellbat', + 506: 'Hellion', + 509: 'Liberator', + 510: 'Marauder', + 511: 'Marine', + 512: 'Medivac', + 517: 'Raven', + 518: 'Reaper', + 520: 'SCV', + 521: 'SiegeTank', + 523: 'Thor', + 525: 'VikingFighter', + 527: 'WidowMine' + }, + 'protoss': { + 86: 'Archon', + 393: 'Mothership', + 54: 'Adept', + 56: 'Carrier', + 62: 'Colossus', + 52: 'DarkTemplar', + 166: 'Disruptor', + 51: 'HighTemplar', + 63: 'Immortal', + 513: 'MothershipCore', + 21: 'Mothership', + 61: 'Observer', + 58: 'Oracle', + 55: 'Phoenix', + 64: 'Probe', + 53: 'Sentry', + 50: 'Stalker', + 59: 'Tempest', + 57: 'VoidRay', + 76: 'Adept', + 74: 'DarkTemplar', + 73: 'HighTemplar', + 60: 'WarpPrism', + 75: 'Sentry', + 72: 'Stalker', + 71: 'Zealot', + 49: 'Zealot' + } +} + +cum_dict = [ + { + 'race': ['zerg', 'terran', 'protoss'], + 'name': 'no_op' + }, { + 'race': ['terran'], + 'name': 'Armory' + }, { + 'race': ['protoss'], + 'name': 'Assimilator' + }, { + 'race': ['zerg'], + 'name': 'BanelingNest' + }, { + 'race': ['terran'], + 'name': 'Barracks' + }, { + 'race': ['terran'], + 'name': 'CommandCenter' + }, { + 'race': ['protoss'], + 'name': 'CyberneticsCore' + }, { + 'race': ['protoss'], + 'name': 'DarkShrine' + }, { + 'race': ['terran'], + 'name': 'EngineeringBay' + }, { + 'race': ['zerg'], + 'name': 'EvolutionChamber' + }, { + 'race': ['zerg'], + 'name': 'Extractor' + }, { + 'race': ['terran'], + 'name': 'Factory' + }, { + 'race': ['protoss'], + 'name': 'FleetBeacon' + }, { + 'race': ['protoss'], + 'name': 'Forge' + }, { + 'race': ['terran'], + 'name': 'FusionCore' + }, { + 'race': ['protoss'], + 'name': 'Gateway' + }, { + 'race': ['terran'], + 'name': 'GhostAcademy' + }, { + 'race': ['zerg'], + 'name': 'Hatchery' + }, { + 'race': ['zerg'], + 'name': 'HydraliskDen' + }, { + 'race': ['zerg'], + 'name': 'InfestationPit' + }, { + 'race': ['protoss'], + 'name': 'Interceptors' + }, { + 'race': ['protoss'], + 'name': 'Interceptors' + }, { + 'race': ['zerg'], + 'name': 'LurkerDen' + }, { + 'race': ['protoss'], + 'name': 'Nexus' + }, { + 'race': ['terran'], + 'name': 'Nuke' + }, { + 'race': ['zerg'], + 'name': 'NydusNetwork' + }, { + 'race': ['zerg'], + 'name': 'NydusWorm' + }, { + 'race': ['terran'], + 'name': 'Reactor' + }, { + 'race': ['terran'], + 'name': 'Reactor' + }, { + 'race': ['terran'], + 'name': 'Refinery' + }, { + 'race': ['zerg'], + 'name': 'RoachWarren' + }, { + 'race': ['protoss'], + 'name': 'RoboticsBay' + }, { + 'race': ['protoss'], + 'name': 'RoboticsFacility' + }, { + 'race': ['terran'], + 'name': 'SensorTower' + }, { + 'race': ['zerg'], + 'name': 'SpawningPool' + }, { + 'race': ['zerg'], + 'name': 'Spire' + }, { + 'race': ['protoss'], + 'name': 'Stargate' + }, { + 'race': ['terran'], + 'name': 'Starport' + }, { + 'race': ['protoss'], + 'name': 'StasisTrap' + }, { + 'race': ['terran'], + 'name': 'TechLab' + }, { + 'race': ['terran'], + 'name': 'TechLab' + }, { + 'race': ['protoss'], + 'name': 'TemplarArchive' + }, { + 'race': ['protoss'], + 'name': 'TwilightCouncil' + }, { + 'race': ['zerg'], + 'name': 'UltraliskCavern' + }, { + 'race': ['protoss'], + 'name': 'Archon' + }, { + 'race': ['zerg'], + 'name': 'BroodLord' + }, { + 'race': ['zerg'], + 'name': 'GreaterSpire' + }, { + 'race': ['zerg'], + 'name': 'Hive' + }, { + 'race': ['zerg'], + 'name': 'Lair' + }, { + 'race': ['zerg'], + 'name': 'LurkerDen' + }, { + 'race': ['zerg'], + 'name': 'Lurker' + }, { + 'race': ['protoss'], + 'name': 'Mothership' + }, { + 'race': ['terran'], + 'name': 'OrbitalCommand' + }, { + 'race': ['zerg'], + 'name': 'OverlordTransport' + }, { + 'race': ['terran'], + 'name': 'PlanetaryFortress' + }, { + 'race': ['zerg'], + 'name': 'Ravager' + }, { + 'race': ['zerg'], + 'name': 'Research_AdaptiveTalons' + }, { + 'race': ['protoss'], + 'name': 'Research_AdeptResonatingGlaives' + }, { + 'race': ['terran'], + 'name': 'Research_AdvancedBallistics' + }, { + 'race': ['zerg'], + 'name': 'Research_AnabolicSynthesis' + }, { + 'race': ['terran'], + 'name': 'Research_BansheeCloakingField' + }, { + 'race': ['terran'], + 'name': 'Research_BansheeHyperflightRotors' + }, { + 'race': ['terran'], + 'name': 'Research_BattlecruiserWeaponRefit' + }, { + 'race': ['protoss'], + 'name': 'Research_Blink' + }, { + 'race': ['zerg'], + 'name': 'Research_Burrow' + }, { + 'race': ['zerg'], + 'name': 'Research_CentrifugalHooks' + }, { + 'race': ['protoss'], + 'name': 'Research_Charge' + }, { + 'race': ['zerg'], + 'name': 'Research_ChitinousPlating' + }, { + 'race': ['terran'], + 'name': 'Research_CombatShield' + }, { + 'race': ['terran'], + 'name': 'Research_ConcussiveShells' + }, { + 'race': ['terran'], + 'name': 'Research_CycloneLockOnDamage' + }, { + 'race': ['terran'], + 'name': 'Research_CycloneRapidFireLaunchers' + }, { + 'race': ['terran'], + 'name': 'Research_DrillingClaws' + }, { + 'race': ['terran'], + 'name': 'Research_EnhancedShockwaves' + }, { + 'race': ['protoss'], + 'name': 'Research_ExtendedThermalLance' + }, { + 'race': ['zerg'], + 'name': 'Research_GlialRegeneration' + }, { + 'race': ['protoss'], + 'name': 'Research_GraviticBooster' + }, { + 'race': ['protoss'], + 'name': 'Research_GraviticDrive' + }, { + 'race': ['zerg'], + 'name': 'Research_GroovedSpines' + }, { + 'race': ['terran'], + 'name': 'Research_HighCapacityFuelTanks' + }, { + 'race': ['terran'], + 'name': 'Research_HiSecAutoTracking' + }, { + 'race': ['terran'], + 'name': 'Research_InfernalPreigniter' + }, { + 'race': ['protoss'], + 'name': 'Research_InterceptorGravitonCatapult' + }, { + 'race': ['zerg'], + 'name': 'Research_MuscularAugments' + }, { + 'race': ['terran'], + 'name': 'Research_NeosteelFrame' + }, { + 'race': ['zerg'], + 'name': 'Research_NeuralParasite' + }, { + 'race': ['zerg'], + 'name': 'Research_PathogenGlands' + }, { + 'race': ['terran'], + 'name': 'Research_PersonalCloaking' + }, { + 'race': ['protoss'], + 'name': 'Research_PhoenixAnionPulseCrystals' + }, { + 'race': ['zerg'], + 'name': 'Research_PneumatizedCarapace' + }, { + 'race': ['protoss'], + 'name': 'Research_ProtossAirArmor' + }, { + 'race': ['protoss'], + 'name': 'Research_ProtossAirWeapons' + }, { + 'race': ['protoss'], + 'name': 'Research_ProtossGroundArmor' + }, { + 'race': ['protoss'], + 'name': 'Research_ProtossGroundWeapons' + }, { + 'race': ['protoss'], + 'name': 'Research_ProtossShields' + }, { + 'race': ['protoss'], + 'name': 'Research_PsiStorm' + }, { + 'race': ['terran'], + 'name': 'Research_RavenCorvidReactor' + }, { + 'race': ['terran'], + 'name': 'Research_RavenRecalibratedExplosives' + }, { + 'race': ['protoss'], + 'name': 'Research_ShadowStrike' + }, { + 'race': ['terran'], + 'name': 'Research_SmartServos' + }, { + 'race': ['terran'], + 'name': 'Research_Stimpack' + }, { + 'race': ['terran'], + 'name': 'Research_TerranInfantryArmor' + }, { + 'race': ['terran'], + 'name': 'Research_TerranInfantryWeapons' + }, { + 'race': ['terran'], + 'name': 'Research_TerranShipWeapons' + }, { + 'race': ['terran'], + 'name': 'Research_TerranStructureArmorUpgrade' + }, { + 'race': ['terran'], + 'name': 'Research_TerranVehicleAndShipPlating' + }, { + 'race': ['terran'], + 'name': 'Research_TerranVehicleWeapons' + }, { + 'race': ['zerg'], + 'name': 'Research_TunnelingClaws' + }, { + 'race': ['protoss'], + 'name': 'Research_WarpGate' + }, { + 'race': ['zerg'], + 'name': 'Research_ZergFlyerArmor' + }, { + 'race': ['zerg'], + 'name': 'Research_ZergFlyerAttack' + }, { + 'race': ['zerg'], + 'name': 'Research_ZergGroundArmor' + }, { + 'race': ['zerg'], + 'name': 'Research_ZerglingAdrenalGlands' + }, { + 'race': ['zerg'], + 'name': 'Research_ZerglingMetabolicBoost' + }, { + 'race': ['zerg'], + 'name': 'Research_ZergMeleeWeapons' + }, { + 'race': ['zerg'], + 'name': 'Research_ZergMissileWeapons' + }, { + 'race': ['protoss'], + 'name': 'Adept' + }, { + 'race': ['zerg'], + 'name': 'Baneling' + }, { + 'race': ['terran'], + 'name': 'Banshee' + }, { + 'race': ['terran'], + 'name': 'Battlecruiser' + }, { + 'race': ['protoss'], + 'name': 'Carrier' + }, { + 'race': ['protoss'], + 'name': 'Colossus' + }, { + 'race': ['zerg'], + 'name': 'Corruptor' + }, { + 'race': ['terran'], + 'name': 'Cyclone' + }, { + 'race': ['protoss'], + 'name': 'DarkTemplar' + }, { + 'race': ['protoss'], + 'name': 'Disruptor' + }, { + 'race': ['terran'], + 'name': 'Ghost' + }, { + 'race': ['terran'], + 'name': 'Hellbat' + }, { + 'race': ['terran'], + 'name': 'Hellion' + }, { + 'race': ['protoss'], + 'name': 'HighTemplar' + }, { + 'race': ['zerg'], + 'name': 'Hydralisk' + }, { + 'race': ['protoss'], + 'name': 'Immortal' + }, { + 'race': ['zerg'], + 'name': 'Infestor' + }, { + 'race': ['terran'], + 'name': 'Liberator' + }, { + 'race': ['terran'], + 'name': 'Marauder' + }, { + 'race': ['terran'], + 'name': 'Marine' + }, { + 'race': ['terran'], + 'name': 'Medivac' + }, { + 'race': ['protoss'], + 'name': 'MothershipCore' + }, { + 'race': ['protoss'], + 'name': 'Mothership' + }, { + 'race': ['zerg'], + 'name': 'Mutalisk' + }, { + 'race': ['protoss'], + 'name': 'Observer' + }, { + 'race': ['protoss'], + 'name': 'Oracle' + }, { + 'race': ['protoss'], + 'name': 'Phoenix' + }, { + 'race': ['zerg'], + 'name': 'Queen' + }, { + 'race': ['terran'], + 'name': 'Raven' + }, { + 'race': ['terran'], + 'name': 'Reaper' + }, { + 'race': ['zerg'], + 'name': 'Roach' + }, { + 'race': ['protoss'], + 'name': 'Sentry' + }, { + 'race': ['terran'], + 'name': 'SiegeTank' + }, { + 'race': ['protoss'], + 'name': 'Stalker' + }, { + 'race': ['zerg'], + 'name': 'SwarmHost' + }, { + 'race': ['protoss'], + 'name': 'Tempest' + }, { + 'race': ['terran'], + 'name': 'Thor' + }, { + 'race': ['zerg'], + 'name': 'Ultralisk' + }, { + 'race': ['terran'], + 'name': 'VikingFighter' + }, { + 'race': ['zerg'], + 'name': 'Viper' + }, { + 'race': ['protoss'], + 'name': 'VoidRay' + }, { + 'race': ['protoss'], + 'name': 'Adept' + }, { + 'race': ['protoss'], + 'name': 'DarkTemplar' + }, { + 'race': ['protoss'], + 'name': 'HighTemplar' + }, { + 'race': ['protoss'], + 'name': 'WarpPrism' + }, { + 'race': ['protoss'], + 'name': 'Sentry' + }, { + 'race': ['protoss'], + 'name': 'Stalker' + }, { + 'race': ['protoss'], + 'name': 'Zealot' + }, { + 'race': ['terran'], + 'name': 'WidowMine' + }, { + 'race': ['protoss'], + 'name': 'Zealot' + }, { + 'race': ['zerg'], + 'name': 'Zergling' + } +] + +action_result_dict = [ + '', 'Success', 'ERROR_NotSupported', 'ERROR_Error', 'ERROR_CantQueueThatOrder', 'ERROR_Retry', 'ERROR_Cooldown', + 'ERROR_QueueIsFull', 'ERROR_RallyQueueIsFull', 'ERROR_NotEnoughMinerals', 'ERROR_NotEnoughVespene', + 'ERROR_NotEnoughTerrazine', 'ERROR_NotEnoughCustom', 'ERROR_NotEnoughFood', 'ERROR_FoodUsageImpossible', + 'ERROR_NotEnoughLife', 'ERROR_NotEnoughShields', 'ERROR_NotEnoughEnergy', 'ERROR_LifeSuppressed', + 'ERROR_ShieldsSuppressed', 'ERROR_EnergySuppressed', 'ERROR_NotEnoughCharges', 'ERROR_CantAddMoreCharges', + 'ERROR_TooMuchMinerals', 'ERROR_TooMuchVespene', 'ERROR_TooMuchTerrazine', 'ERROR_TooMuchCustom', + 'ERROR_TooMuchFood', 'ERROR_TooMuchLife', 'ERROR_TooMuchShields', 'ERROR_TooMuchEnergy', + 'ERROR_MustTargetUnitWithLife', 'ERROR_MustTargetUnitWithShields', 'ERROR_MustTargetUnitWithEnergy', + 'ERROR_CantTrade', 'ERROR_CantSpend', 'ERROR_CantTargetThatUnit', 'ERROR_CouldntAllocateUnit', 'ERROR_UnitCantMove', + 'ERROR_TransportIsHoldingPosition', 'ERROR_BuildTechRequirementsNotMet', 'ERROR_CantFindPlacementLocation', + 'ERROR_CantBuildOnThat', 'ERROR_CantBuildTooCloseToDropOff', 'ERROR_CantBuildLocationInvalid', + 'ERROR_CantSeeBuildLocation', 'ERROR_CantBuildTooCloseToCreepSource', 'ERROR_CantBuildTooCloseToResources', + 'ERROR_CantBuildTooFarFromWater', 'ERROR_CantBuildTooFarFromCreepSource', + 'ERROR_CantBuildTooFarFromBuildPowerSource', 'ERROR_CantBuildOnDenseTerrain', + 'ERROR_CantTrainTooFarFromTrainPowerSource', 'ERROR_CantLandLocationInvalid', 'ERROR_CantSeeLandLocation', + 'ERROR_CantLandTooCloseToCreepSource', 'ERROR_CantLandTooCloseToResources', 'ERROR_CantLandTooFarFromWater', + 'ERROR_CantLandTooFarFromCreepSource', 'ERROR_CantLandTooFarFromBuildPowerSource', + 'ERROR_CantLandTooFarFromTrainPowerSource', 'ERROR_CantLandOnDenseTerrain', 'ERROR_AddOnTooFarFromBuilding', + 'ERROR_MustBuildRefineryFirst', 'ERROR_BuildingIsUnderConstruction', 'ERROR_CantFindDropOff', + 'ERROR_CantLoadOtherPlayersUnits', 'ERROR_NotEnoughRoomToLoadUnit', 'ERROR_CantUnloadUnitsThere', + 'ERROR_CantWarpInUnitsThere', 'ERROR_CantLoadImmobileUnits', 'ERROR_CantRechargeImmobileUnits', + 'ERROR_CantRechargeUnderConstructionUnits', 'ERROR_CantLoadThatUnit', 'ERROR_NoCargoToUnload', + 'ERROR_LoadAllNoTargetsFound', 'ERROR_NotWhileOccupied', 'ERROR_CantAttackWithoutAmmo', 'ERROR_CantHoldAnyMoreAmmo', + 'ERROR_TechRequirementsNotMet', 'ERROR_MustLockdownUnitFirst', 'ERROR_MustTargetUnit', 'ERROR_MustTargetInventory', + 'ERROR_MustTargetVisibleUnit', 'ERROR_MustTargetVisibleLocation', 'ERROR_MustTargetWalkableLocation', + 'ERROR_MustTargetPawnableUnit', 'ERROR_YouCantControlThatUnit', 'ERROR_YouCantIssueCommandsToThatUnit', + 'ERROR_MustTargetResources', 'ERROR_RequiresHealTarget', 'ERROR_RequiresRepairTarget', 'ERROR_NoItemsToDrop', + 'ERROR_CantHoldAnyMoreItems', 'ERROR_CantHoldThat', 'ERROR_TargetHasNoInventory', 'ERROR_CantDropThisItem', + 'ERROR_CantMoveThisItem', 'ERROR_CantPawnThisUnit', 'ERROR_MustTargetCaster', 'ERROR_CantTargetCaster', + 'ERROR_MustTargetOuter', 'ERROR_CantTargetOuter', 'ERROR_MustTargetYourOwnUnits', 'ERROR_CantTargetYourOwnUnits', + 'ERROR_MustTargetFriendlyUnits', 'ERROR_CantTargetFriendlyUnits', 'ERROR_MustTargetNeutralUnits', + 'ERROR_CantTargetNeutralUnits', 'ERROR_MustTargetEnemyUnits', 'ERROR_CantTargetEnemyUnits', + 'ERROR_MustTargetAirUnits', 'ERROR_CantTargetAirUnits', 'ERROR_MustTargetGroundUnits', + 'ERROR_CantTargetGroundUnits', 'ERROR_MustTargetStructures', 'ERROR_CantTargetStructures', + 'ERROR_MustTargetLightUnits', 'ERROR_CantTargetLightUnits', 'ERROR_MustTargetArmoredUnits', + 'ERROR_CantTargetArmoredUnits', 'ERROR_MustTargetBiologicalUnits', 'ERROR_CantTargetBiologicalUnits', + 'ERROR_MustTargetHeroicUnits', 'ERROR_CantTargetHeroicUnits', 'ERROR_MustTargetRoboticUnits', + 'ERROR_CantTargetRoboticUnits', 'ERROR_MustTargetMechanicalUnits', 'ERROR_CantTargetMechanicalUnits', + 'ERROR_MustTargetPsionicUnits', 'ERROR_CantTargetPsionicUnits', 'ERROR_MustTargetMassiveUnits', + 'ERROR_CantTargetMassiveUnits', 'ERROR_MustTargetMissile', 'ERROR_CantTargetMissile', 'ERROR_MustTargetWorkerUnits', + 'ERROR_CantTargetWorkerUnits', 'ERROR_MustTargetEnergyCapableUnits', 'ERROR_CantTargetEnergyCapableUnits', + 'ERROR_MustTargetShieldCapableUnits', 'ERROR_CantTargetShieldCapableUnits', 'ERROR_MustTargetFlyers', + 'ERROR_CantTargetFlyers', 'ERROR_MustTargetBuriedUnits', 'ERROR_CantTargetBuriedUnits', + 'ERROR_MustTargetCloakedUnits', 'ERROR_CantTargetCloakedUnits', 'ERROR_MustTargetUnitsInAStasisField', + 'ERROR_CantTargetUnitsInAStasisField', 'ERROR_MustTargetUnderConstructionUnits', + 'ERROR_CantTargetUnderConstructionUnits', 'ERROR_MustTargetDeadUnits', 'ERROR_CantTargetDeadUnits', + 'ERROR_MustTargetRevivableUnits', 'ERROR_CantTargetRevivableUnits', 'ERROR_MustTargetHiddenUnits', + 'ERROR_CantTargetHiddenUnits', 'ERROR_CantRechargeOtherPlayersUnits', 'ERROR_MustTargetHallucinations', + 'ERROR_CantTargetHallucinations', 'ERROR_MustTargetInvulnerableUnits', 'ERROR_CantTargetInvulnerableUnits', + 'ERROR_MustTargetDetectedUnits', 'ERROR_CantTargetDetectedUnits', 'ERROR_CantTargetUnitWithEnergy', + 'ERROR_CantTargetUnitWithShields', 'ERROR_MustTargetUncommandableUnits', 'ERROR_CantTargetUncommandableUnits', + 'ERROR_MustTargetPreventDefeatUnits', 'ERROR_CantTargetPreventDefeatUnits', 'ERROR_MustTargetPreventRevealUnits', + 'ERROR_CantTargetPreventRevealUnits', 'ERROR_MustTargetPassiveUnits', 'ERROR_CantTargetPassiveUnits', + 'ERROR_MustTargetStunnedUnits', 'ERROR_CantTargetStunnedUnits', 'ERROR_MustTargetSummonedUnits', + 'ERROR_CantTargetSummonedUnits', 'ERROR_MustTargetUser1', 'ERROR_CantTargetUser1', + 'ERROR_MustTargetUnstoppableUnits', 'ERROR_CantTargetUnstoppableUnits', 'ERROR_MustTargetResistantUnits', + 'ERROR_CantTargetResistantUnits', 'ERROR_MustTargetDazedUnits', 'ERROR_CantTargetDazedUnits', 'ERROR_CantLockdown', + 'ERROR_CantMindControl', 'ERROR_MustTargetDestructibles', 'ERROR_CantTargetDestructibles', 'ERROR_MustTargetItems', + 'ERROR_CantTargetItems', 'ERROR_NoCalldownAvailable', 'ERROR_WaypointListFull', 'ERROR_MustTargetRace', + 'ERROR_CantTargetRace', 'ERROR_MustTargetSimilarUnits', 'ERROR_CantTargetSimilarUnits', + 'ERROR_CantFindEnoughTargets', 'ERROR_AlreadySpawningLarva', 'ERROR_CantTargetExhaustedResources', + 'ERROR_CantUseMinimap', 'ERROR_CantUseInfoPanel', 'ERROR_OrderQueueIsFull', 'ERROR_CantHarvestThatResource', + 'ERROR_HarvestersNotRequired', 'ERROR_AlreadyTargeted', 'ERROR_CantAttackWeaponsDisabled', + 'ERROR_CouldntReachTarget', 'ERROR_TargetIsOutOfRange', 'ERROR_TargetIsTooClose', 'ERROR_TargetIsOutOfArc', + 'ERROR_CantFindTeleportLocation', 'ERROR_InvalidItemClass', 'ERROR_CantFindCancelOrder' +] +NUM_ACTION_RESULT = 214 + +ACTION_RACE_MASK = { + 'zerg': torch.tensor( + [ + False, False, True, True, True, True, False, False, True, True, True, True, False, False, False, False, + True, False, False, False, True, False, False, False, True, True, False, False, False, False, False, False, + True, True, True, False, False, True, False, False, False, True, True, False, False, False, False, False, + True, False, False, False, False, True, True, True, True, False, False, False, False, False, False, False, + False, True, True, True, True, True, True, True, False, False, False, True, False, False, False, False, + True, False, False, False, False, False, True, True, False, False, True, False, False, True, True, False, + False, False, False, False, False, False, True, True, False, False, False, False, False, True, False, False, + True, False, False, True, False, False, False, False, False, False, False, False, False, True, True, True, + True, False, False, False, False, True, True, False, False, False, False, False, False, False, False, False, + False, False, False, False, False, False, False, False, False, False, True, True, True, False, False, False, + True, False, True, False, True, False, False, True, True, False, False, True, True, False, False, False, + True, True, True, True, False, True, True, False, False, False, False, False, False, False, True, False, + False, False, False, False, False, True, True, True, True, True, True, True, True, True, False, False, True, + False, False, False, False, True, True, False, True, False, False, False, False, False, False, False, True, + False, False, True, False, False, False, False, True, False, True, True, False, False, True, False, False, + False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, + True, False, True, True, True, True, True, True, True, True, True, True, False, True, False, False, False, + False, True, False, False, False, True, False, False, False, False, True, False, True, False, False, False, + False, False, False, True, False, False, True, False, False, True, False, False, True, False, False, False, + False, True, False, False, True, False, True, False, False, False, False, False, False, False, False, False, + False, True, True, True, True, True + ] + ), + 'terran': torch.tensor( + [ + False, False, True, True, False, False, True, True, False, False, True, True, False, False, True, False, + False, True, True, True, False, False, False, True, False, False, True, False, False, True, False, True, + False, False, False, False, False, False, True, False, True, False, False, False, False, True, True, True, + False, False, False, True, False, False, False, False, False, False, True, False, True, True, True, False, + False, False, True, True, True, True, True, False, False, True, True, False, False, False, True, True, + False, False, False, False, False, False, False, False, True, True, False, False, False, False, False, True, + False, False, True, True, False, False, False, False, True, True, True, True, True, False, False, True, + False, True, False, False, False, False, True, True, True, False, False, True, True, False, False, False, + True, True, True, True, False, False, False, False, True, True, True, True, False, False, False, False, + False, False, False, False, False, False, False, False, False, True, True, True, True, True, True, True, + True, False, False, False, False, True, True, False, False, True, True, False, False, False, False, True, + False, False, False, False, True, False, False, True, True, True, False, True, True, True, False, True, + True, False, False, False, False, True, True, True, True, True, True, True, True, False, False, True, False, + True, True, True, False, False, False, False, False, True, True, True, True, True, True, False, False, + False, False, False, True, True, True, False, False, True, False, False, True, False, False, False, False, + False, False, False, False, True, True, False, True, True, True, True, True, True, True, True, False, False, + False, False, False, False, False, False, False, True, True, True, False, False, True, True, False, False, + False, True, False, False, False, True, True, True, False, False, False, False, True, True, True, True, + False, False, False, False, False, False, False, False, False, True, True, False, True, False, True, False, + False, False, True, False, True, False, False, False, False, False, False, False, False, False, True, False, + False, True, True, True, True + ] + ), + 'protoss': torch.tensor( + [ + False, False, True, True, False, False, False, False, False, False, False, False, True, True, False, True, + False, False, False, False, False, True, True, False, False, False, False, True, True, False, True, False, + False, False, False, True, True, False, False, True, False, False, False, True, True, False, False, False, + False, True, True, False, True, False, False, False, False, True, False, True, False, False, False, True, + True, False, False, False, False, True, True, False, True, False, False, False, True, True, False, False, + False, True, True, True, True, True, False, False, False, False, False, True, True, False, False, False, + True, True, False, False, True, True, False, False, False, False, False, False, False, False, True, False, + False, False, True, False, True, True, False, False, False, True, True, False, False, False, False, False, + True, False, False, False, True, False, False, True, False, False, False, False, True, True, True, True, + True, True, True, True, True, True, True, True, True, False, True, True, True, False, False, False, True, + True, False, True, False, False, False, False, False, False, False, False, False, True, True, False, False, + False, False, False, False, False, False, False, False, False, True, False, False, False, False, False, + False, True, True, True, True, True, True, True, True, True, True, True, True, False, True, False, False, + False, False, False, True, False, False, True, False, False, False, False, False, False, False, True, False, + True, True, False, False, False, False, True, False, False, False, False, False, True, False, True, True, + True, True, True, True, False, False, True, False, False, False, False, False, False, False, False, False, + True, False, False, False, False, False, False, False, True, True, True, True, False, False, False, True, + True, False, False, True, True, False, False, False, False, True, False, True, False, False, False, False, + False, True, True, False, True, True, False, True, True, False, False, False, False, False, True, False, + True, False, True, False, False, False, False, True, True, True, True, True, True, True, True, False, True, + False, True, True, False, True + ] + ) +} diff --git a/dizoo/distar/policy/distar_policy.py b/dizoo/distar/policy/distar_policy.py index dd223d714a..7a0dba799a 100644 --- a/dizoo/distar/policy/distar_policy.py +++ b/dizoo/distar/policy/distar_policy.py @@ -2,7 +2,6 @@ from easydict import EasyDict import os.path as osp import torch -import torch.nn.functional as F from torch.optim import Adam from ding.model import model_wrap @@ -11,64 +10,10 @@ from ding.rl_utils import td_lambda_data, td_lambda_error, vtrace_data_with_rho, vtrace_error_with_rho, \ upgo_data, upgo_error from ding.utils import EasyTimer +from ding.utils.data import default_collate, default_decollate from dizoo.distar.model import Model -from .utils import collate_fn_learn - -EPS = 1e-9 - - -def entropy_error(target_policy_probs_dict, target_policy_log_probs_dict, mask, head_weights_dict): - total_entropy_loss = 0. - entropy_dict = {} - for head_type in ['action_type', 'queued', 'delay', 'selected_units', 'target_unit', 'target_location']: - ent = -target_policy_probs_dict[head_type] * target_policy_log_probs_dict[head_type] - if head_type == 'selected_units': - ent = ent.sum(dim=-1) / ( - EPS + torch.log(mask['selected_units_logits_mask'].float().sum(dim=-1) + 1).unsqueeze(-1) - ) # normalize - ent = (ent * mask['selected_units_mask']).sum(-1) - ent = ent.div(mask['selected_units_mask'].sum(-1) + EPS) - elif head_type == 'target_unit': - # normalize by unit - ent = ent.sum(dim=-1) / (EPS + torch.log(mask['target_units_logits_mask'].float().sum(dim=-1) + 1)) - else: - ent = ent.sum(dim=-1) / torch.log(torch.FloatTensor([ent.shape[-1]]).to(ent.device)) - if head_type not in ['action_type', 'delay']: - ent = ent * mask['actions_mask'][head_type] - entropy = ent.mean() - entropy_dict['entropy/' + head_type] = entropy.item() - total_entropy_loss += (-entropy * head_weights_dict[head_type]) - return total_entropy_loss, entropy_dict - - -def kl_error( - target_policy_log_probs_dict, teacher_policy_logits_dict, mask, game_steps, action_type_kl_steps, head_weights_dict -): - total_kl_loss = 0. - kl_loss_dict = {} - - for head_type in ['action_type', 'queued', 'delay', 'selected_units', 'target_unit', 'target_location']: - target_policy_log_probs = target_policy_log_probs_dict[head_type] - teacher_policy_logits = teacher_policy_logits_dict[head_type] - - teacher_policy_log_probs = F.log_softmax(teacher_policy_logits, dim=-1) - teacher_policy_probs = torch.exp(teacher_policy_log_probs) - kl = teacher_policy_probs * (teacher_policy_log_probs - target_policy_log_probs) - - kl = kl.sum(dim=-1) - if head_type == 'selected_units': - kl = (kl * mask['selected_units_mask']).sum(-1) - if head_type not in ['action_type', 'delay']: - kl = kl * mask['actions_mask'][head_type] - if head_type == 'action_type': - flag = game_steps < action_type_kl_steps - action_type_kl = kl * flag - action_type_kl_loss = action_type_kl.mean() - kl_loss_dict['kl/extra_at'] = action_type_kl_loss.item() - kl_loss = kl.mean() - total_kl_loss += (kl_loss * head_weights_dict[head_type]) - kl_loss_dict['kl/' + head_type] = kl_loss.item() - return total_kl_loss, action_type_kl_loss, kl_loss_dict +from dizoo.distar.envs import NUM_UNIT_TYPES, ACTIONS, Stat +from .utils import collate_fn_learn, kl_error, entropy_error class DIStarPolicy(Policy): @@ -78,6 +23,7 @@ class DIStarPolicy(Policy): cuda=True, learning_rate=1e-5, model=dict(), + # learn learn=dict(multi_gpu=False, ), loss_weights=dict( baseline=dict( @@ -156,7 +102,12 @@ class DIStarPolicy(Policy): battle=0.997, ), ), - grad_clip=dict(threshold=1.0, ) + grad_clip=dict(threshold=1.0, ), + # collect + use_value_feature=True, # whether to use value feature, this must be False when play against bot + zero_z_exceed_loop=True, # set Z to 0 if game passes the game loop in Z + zero_z_value=1, + extra_units=True, # selcet extra units if selected units exceed 64 ) def _create_model( @@ -170,6 +121,8 @@ def _create_model( field = enable_field[0] if field == 'learn': return Model(self._cfg.model, use_value_network=True) + elif field == 'collect': # disable value network + return Model(self._cfg.model) else: raise KeyError("invalid policy mode: {}".format(field)) @@ -398,13 +351,137 @@ def _load_state_dict_learn(self, _state_dict: Dict) -> None: self.optimizer.load_state_dict(_state_dict['optimizer']) def _init_collect(self): - pass + self.collect_model = model_wrap(self._model, 'base') + self._reset_collect() + + def _reset_collect(self, env_id=0): + self.stat = Stat('zerg') # TODO + self.target_z_loop = 43200 # TODO + self.exceed_loop_flag = False + self.hidden_state = None + self.last_action_type = torch.tensor(0, dtype=torch.long) + self.last_delay = torch.tensor(0, dtype=torch.long) + self.last_queued = torch.tensor(0, dtype=torch.long) + self.last_selected_unit_tags = None + self.last_targeted_unit_tag = None + self.last_location = None # [x, y] + self.enemy_unit_type_bool = torch.zeros(NUM_UNIT_TYPES, dtype=torch.uint8) + + self.target_building_order = None # TODO + self.target_bo_location = None + self.target_cumulative_stat = None + + self.map_size = None # TODO def _forward_collect(self, data): - pass + game_info = data.pop('game_info') + obs = self._data_preprocess_collect(data, game_info) + obs = default_collate([obs]) + if self._cfg.cuda: + obs = to_device(obs, self._device) - def _process_transition(self): - pass + with torch.no_grad(): + policy_output = self.collect_model.compute_logp_action(**obs) + + if self._cfg.cuda: + policy_output = to_device(policy_output, self._device) + policy_output = default_decollate(policy_output)[0] + policy_output = self._data_postprocess_collect(policy_output, game_info) + return policy_output + + def _data_preprocess_collect(self, data, game_info): + transform_obs = None + if self._cfg.use_value_feature: + obs = transform_obs(data['raw_obs'], opponent_obs=data['opponent_obs']) + else: + raise NotImplementedError + + game_step = game_info['game_loop'] + if self._cfg.zero_z_exceed_loop and game_step > self._target_z_loop: + self._exceed_loop_flag = True + + last_selected_units = torch.zeros(obs['entity_num'], dtype=torch.int8) + last_targeted_unit = torch.zeros(obs['entity_num'], dtype=torch.int8) + tags = game_info['tags'] + if self.last_selected_unit_tags is not None: + for t in self.last_selected_unit_tags: + if t in tags: + last_selected_units[tags.index(t)] = 1 + if self.last_targeted_unit_tag is None: + if self.last_targeted_unit_tag in tags: + last_targeted_unit[tags.index(self.last_targeted_unit_tag)] = 1 + obs['entity_info']['last_selected_units'] = last_selected_units + obs['entity_info']['last_targeted_unit'] = last_targeted_unit + + obs['hidden_state'] = self.hidden_state + + obs['scalar_info']['last_action_type'] = self.last_action_type + obs['scalar_info']['last_delay'] = self.last_delay + obs['scalar_info']['last_queued'] = self.last_queued + obs['scalar_info']['enemy_unit_type_bool'] = ( + self.enemy_unit_type_bool | obs['scalar_info']['enemy_unit_type_bool'] + ).to(torch.uint8) + obs['scalar_info']['beginning_order'] = self.target_building_order * (~self.exceed_loop_flag) + obs['scalar_info']['bo_location'] = self.target_bo_location * (~self.exceed_loop_flag) + if self.exceed_loop_flag: + obs['scalar_info']['cumulative_stat'] = self.target_cumulative_stat * 0 + self._cfg.zero_z_value + else: + obs['scalar_info']['cumulative_stat'] = self.target_cumulative_stat + + # update stat + self.stat.update(self.last_action_type, data['action_result'][0], obs, game_step) + return obs + + def _data_postprocess_collect(self, data, game_info): + self.hidden_state = data['hidden_state'] + + self.last_action_type = data['action_info']['action_type'] + self.last_delay = data['action_info']['delay'] + self.last_queued = data['action_info']['queued'] + action_type = self.last_action_type.item() + action_attr = ACTIONS[action_type] + + # transform into env format action + tags = game_info['tags'] + raw_action = {} + raw_action['func_id'] = action_attr['func_id'] + raw_action['skip_steps'] = self.last_delay.item() + raw_action['queued'] = self.queued.item() + + unit_tags = [] + for i in range(data['selected_units_num'] - 1): # remove end flag + unit_tags.append(tags[data['action_info']['selected_units'][i].item()]) + if self._cfg.extra_units: + extra_units = torch.nonzero(data['extra_units']).squeeze(dim=1).tolist() + for unit_index in extra_units: + unit_tags.append(tags[unit_index]) + raw_action['unit_tags'] = unit_tags + if action_attr['selected_units']: + self.last_selected_unit_tags = unit_tags + else: + self.last_selected_unit_tags = None + + raw_action['target_unit_tag'] = tags[data['action_info']['target_unit'].item()] + if action_attr['target_unit']: + self.last_targeted_unit_tag = raw_action['target_unit_tag'] + else: + self.last_targeted_unit_tag = None + + x = data['action_info']['target_location'].item() % self.map_size.x + y = data['action_info']['target_location'].item() // self.map_size.x + inverse_y = max(self.map_size.y - y, 0) + raw_action['location'] = (x, inverse_y) + self.last_location = data['action_info']['target_location'] + + data['action'] = raw_action + + return data + + def _process_transition(self, obs, policy_output, timestep): + return { + 'obs': obs, + 'action': policy_output['action_info'], + } def _get_train_sample(self): pass diff --git a/dizoo/distar/policy/utils.py b/dizoo/distar/policy/utils.py index f0581bc210..b503323c6a 100644 --- a/dizoo/distar/policy/utils.py +++ b/dizoo/distar/policy/utils.py @@ -1,9 +1,11 @@ import torch +import torch.nn.functional as F from ding.torch_utils import flatten, sequence_mask from ding.utils.data import default_collate from dizoo.distar.envs import MAX_SELECTED_UNITS_NUM MASK_INF = -1e9 +EPS = 1e-9 def padding_entity_info(traj_data, max_entity_num): @@ -88,3 +90,57 @@ def collate_fn_learn(traj_batch): new_data['batch_size'] = batch_size new_data['unroll_len'] = unroll_len return new_data + + +def entropy_error(target_policy_probs_dict, target_policy_log_probs_dict, mask, head_weights_dict): + total_entropy_loss = 0. + entropy_dict = {} + for head_type in ['action_type', 'queued', 'delay', 'selected_units', 'target_unit', 'target_location']: + ent = -target_policy_probs_dict[head_type] * target_policy_log_probs_dict[head_type] + if head_type == 'selected_units': + ent = ent.sum(dim=-1) / ( + EPS + torch.log(mask['selected_units_logits_mask'].float().sum(dim=-1) + 1).unsqueeze(-1) + ) # normalize + ent = (ent * mask['selected_units_mask']).sum(-1) + ent = ent.div(mask['selected_units_mask'].sum(-1) + EPS) + elif head_type == 'target_unit': + # normalize by unit + ent = ent.sum(dim=-1) / (EPS + torch.log(mask['target_units_logits_mask'].float().sum(dim=-1) + 1)) + else: + ent = ent.sum(dim=-1) / torch.log(torch.FloatTensor([ent.shape[-1]]).to(ent.device)) + if head_type not in ['action_type', 'delay']: + ent = ent * mask['actions_mask'][head_type] + entropy = ent.mean() + entropy_dict['entropy/' + head_type] = entropy.item() + total_entropy_loss += (-entropy * head_weights_dict[head_type]) + return total_entropy_loss, entropy_dict + + +def kl_error( + target_policy_log_probs_dict, teacher_policy_logits_dict, mask, game_steps, action_type_kl_steps, head_weights_dict +): + total_kl_loss = 0. + kl_loss_dict = {} + + for head_type in ['action_type', 'queued', 'delay', 'selected_units', 'target_unit', 'target_location']: + target_policy_log_probs = target_policy_log_probs_dict[head_type] + teacher_policy_logits = teacher_policy_logits_dict[head_type] + + teacher_policy_log_probs = F.log_softmax(teacher_policy_logits, dim=-1) + teacher_policy_probs = torch.exp(teacher_policy_log_probs) + kl = teacher_policy_probs * (teacher_policy_log_probs - target_policy_log_probs) + + kl = kl.sum(dim=-1) + if head_type == 'selected_units': + kl = (kl * mask['selected_units_mask']).sum(-1) + if head_type not in ['action_type', 'delay']: + kl = kl * mask['actions_mask'][head_type] + if head_type == 'action_type': + flag = game_steps < action_type_kl_steps + action_type_kl = kl * flag + action_type_kl_loss = action_type_kl.mean() + kl_loss_dict['kl/extra_at'] = action_type_kl_loss.item() + kl_loss = kl.mean() + total_kl_loss += (kl_loss * head_weights_dict[head_type]) + kl_loss_dict['kl/' + head_type] = kl_loss.item() + return total_kl_loss, action_type_kl_loss, kl_loss_dict From d467140e58a7319cc3046ac6c9f17ec1e0e542b0 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 21 Jun 2022 23:10:34 +0800 Subject: [PATCH 140/229] change init to make test_pipeline runnable --- ding/rl_utils/__init__.py | 2 +- ding/torch_utils/network/__init__.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/ding/rl_utils/__init__.py b/ding/rl_utils/__init__.py index a4c96bd566..f0eb990a52 100644 --- a/ding/rl_utils/__init__.py +++ b/ding/rl_utils/__init__.py @@ -13,7 +13,7 @@ q_nstep_sql_td_error, dqfd_nstep_td_error, dqfd_nstep_td_data, q_v_1step_td_error, q_v_1step_td_data,\ dqfd_nstep_td_error_with_rescale, discount_cumsum from .vtrace import vtrace_loss, compute_importance_weights -from .upgo import upgo_loss +from .upgo import upgo_data, upgo_error from .adder import get_gae, get_gae_with_default_last_value, get_nstep_return_data, get_train_sample from .value_rescale import value_transform, value_inv_transform from .vtrace import vtrace_data, vtrace_error, vtrace_loss, vtrace_data_with_rho, vtrace_error_with_rho, \ diff --git a/ding/torch_utils/network/__init__.py b/ding/torch_utils/network/__init__.py index 03197bf0f7..56926e7180 100644 --- a/ding/torch_utils/network/__init__.py +++ b/ding/torch_utils/network/__init__.py @@ -1,7 +1,7 @@ from .activation import build_activation, Swish from .res_block import ResBlock, ResFCBlock, GatedConvResBlock from .nn_module import fc_block, conv2d_block, one_hot, deconv2d_block, BilinearUpsample, NearestUpsample, \ - binary_encode, NoiseLinearLayer, noise_block, MLP, Flatten, normed_linear, normed_conv2d + binary_encode, NoiseLinearLayer, noise_block, MLP, Flatten, normed_linear, normed_conv2d, AttentionPool from .normalization import build_normalization from .rnn import get_lstm, sequence_mask from .soft_argmax import SoftArgmax From 7ea23f67a302d3850c8b222efdb381f4182921d5 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 21 Jun 2022 23:13:05 +0800 Subject: [PATCH 141/229] adjust league_learner but cannot run --- ding/framework/middleware/league_learner.py | 5 +++++ .../middleware/tests/test_league_learner.py | 19 +++++++++++++++++-- .../middleware/tests/test_league_pipeline.py | 2 +- dizoo/distar/config/distar_config.py | 11 ++++++----- 4 files changed, 29 insertions(+), 8 deletions(-) diff --git a/ding/framework/middleware/league_learner.py b/ding/framework/middleware/league_learner.py index 679c3992d9..f0c172e776 100644 --- a/ding/framework/middleware/league_learner.py +++ b/ding/framework/middleware/league_learner.py @@ -39,6 +39,11 @@ def __init__(self, cfg: dict, policy: "Policy", player: "ActivePlayer") -> None: def _push_data(self, data: "ActorData"): print("learner {} receive data from actor! \n".format(task.router.node_id), flush=True) + + # for env_trajectories in data.train_data: + # for traj in env_trajectories.trajectories: + # print(len(traj)) + # self._cache.append(traj) self._cache.append(data.train_data) def __call__(self, ctx: "Context"): diff --git a/ding/framework/middleware/tests/test_league_learner.py b/ding/framework/middleware/tests/test_league_learner.py index 07b7414800..2cea66a445 100644 --- a/ding/framework/middleware/tests/test_league_learner.py +++ b/ding/framework/middleware/tests/test_league_learner.py @@ -1,4 +1,5 @@ from copy import deepcopy +from dataclasses import dataclass from time import sleep import torch import pytest @@ -11,13 +12,15 @@ from ding.framework.task import task, Parallel from ding.framework.middleware import data_pusher,\ OffPolicyLearner, LeagueLearnerExchanger -from ding.framework.middleware.functional.actor_data import ActorData +from ding.framework.middleware.functional.actor_data import ActorData, ActorDataMeta, ActorEnvTrajectories from ding.framework.middleware.tests import cfg, MockLeague, MockLogger from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy from ding.league.v2 import BaseLeague from dizoo.distar.envs.distar_env import DIStarEnv from dizoo.distar.envs import fake_rl_data_batch_with_last from distar.ctools.utils import read_config +import time +from typing import Any logging.getLogger().setLevel(logging.INFO) @@ -52,6 +55,12 @@ def _coordinator_mocker(ctx): return _coordinator_mocker +@dataclass +class TestActorData: + env_step: int + train_data: Any + + def actor_mocker(league): def _actor_mocker(ctx): @@ -59,8 +68,14 @@ def _actor_mocker(ctx): player = league.active_players[(task.router.node_id + 2) % n_players] print("actor player:", player.player_id) for _ in range(24): + # meta = ActorDataMeta(player_total_env_step=0, actor_id=0, send_wall_time=time.time()) + # data = fake_rl_data_batch_with_last() + # actor_data = ActorData(meta=ActorDataMeta, train_data=ActorEnvTrajectories(env_id=0, trajectories=[data])) + data = fake_rl_data_batch_with_last() - actor_data = ActorData(env_step=0, train_data=data) + actor_data = TestActorData(env_step=0, train_data=data) + task.emit(EventEnum.ACTOR_SEND_DATA.format(player=player.player_id), actor_data) + task.emit(EventEnum.ACTOR_SEND_DATA.format(player=player.player_id), actor_data) sleep(9) diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index ff772e29f9..3d067bfcef 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -88,7 +88,7 @@ def main(): task.use(data_pusher(cfg, buffer_)) task.use(OffPolicyLearner(cfg, policy.learn_mode, buffer_)) else: - task.use(StepLeagueActor(cfg, PrepareTest.env_fn, PrepareTest.collect_policy_fn)) + task.use(StepLeagueActor(cfg, PrepareTest.get_env_supervisor, PrepareTest.collect_policy_fn)) task.run() diff --git a/dizoo/distar/config/distar_config.py b/dizoo/distar/config/distar_config.py index 575efd3260..0eec475ff7 100644 --- a/dizoo/distar/config/distar_config.py +++ b/dizoo/distar/config/distar_config.py @@ -5,14 +5,15 @@ 'env': { 'manager': { 'episode_num': 100000, - 'max_retry': 1, - 'retry_type': 'reset', + 'max_retry': 1000, + 'retry_type': 'renew', 'auto_reset': True, 'step_timeout': None, 'reset_timeout': None, 'retry_waiting_time': 0.1, 'cfg_type': 'BaseEnvManagerDict', - 'shared_memory': False + 'shared_memory': False, + 'return_original_data': True }, 'collector_env_num': 1, 'evaluator_env_num': 1, @@ -81,7 +82,7 @@ 'n_episode': 1, 'n_rollout_samples': 32, 'n_sample': 64, - 'unroll_len': 1 + 'unroll_len': 64 }, 'eval': { 'evaluator': { @@ -161,4 +162,4 @@ 'exp_name': 'league_demo', 'seed': 0 } -) \ No newline at end of file +) From 20d4c2b0f63531a7b904958f1551d39670994c1c Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 22 Jun 2022 11:56:22 +0800 Subject: [PATCH 142/229] add notes in conference --- ding/framework/middleware/collector.py | 2 ++ .../middleware/functional/collector.py | 3 +++ ding/framework/middleware/league_actor.py | 3 ++- .../middleware/tests/league_config.py | 4 +-- .../middleware/tests/mock_for_test.py | 26 ++++++++++++++++++- dizoo/distar/config/distar_config.py | 4 +-- dizoo/distar/envs/distar_env.py | 4 +++ 7 files changed, 40 insertions(+), 6 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 08f5435c9c..4012ef698a 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -43,6 +43,7 @@ def __del__(self) -> None: self.env.close() def _update_policies(self, player_id_list) -> None: + # TODO(zms): update train_iter for player_id in player_id_list: if self.model_dict.get(player_id) is None: continue @@ -120,6 +121,7 @@ def __del__(self) -> None: self.env.close() def _update_policies(self, player_id_list) -> None: + # TODO: 60 秒 没有更新 就阻塞，更新才返回 for player_id in player_id_list: if self.model_dict.get(player_id) is None: continue diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index af64f68dc7..fadcee92bd 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -59,6 +59,7 @@ def __init__(self, env_num: int, unroll_len: int) -> None: self._transitions = [deque() for _ in range(env_num)] self._done_episode = [deque() for _ in range(env_num)] self._unroll_len = unroll_len + # TODO(zms): last transition + 1 def get_env_trajectories(self, env_id: int, only_finished: bool = False): trajectories = [] @@ -85,6 +86,8 @@ def get_env_trajectories(self, env_id: int, only_finished: bool = False): trajectories += self._cut_trajectory_from_episode(self._transitions[env_id][0][:tail_idx]) self._transitions[env_id][0] = self._transitions[env_id][0][tail_idx:] + # 少于 64 直接删 + return trajectories def to_trajectories(self, only_finished: bool = False): diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index ec67c5c9b8..04dd8338b2 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -162,6 +162,7 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.env_fn = env_fn self.env_num = env_fn().env_num self.policy_fn = policy_fn + # TODO('self.unroll_len = self.cfg.policy.collect.unroll_len') self.unroll_len = self.cfg.policy.collect.get("unroll_len") or 0 self._collectors: Dict[str, BattleEpisodeCollector] = {} self.all_policies: Dict[str, "Policy.collect_function"] = {} @@ -282,7 +283,7 @@ def __call__(self, ctx: "BattleContext"): if ctx.job_finish is True: print('we finish the job !') assert len(ctx.trajectories_list[0][0].trajectories) > 0 - + # TODO(zms): 判断是不是main_player if not job.is_eval and len(ctx.trajectories_list[0]) > 0: trajectories = ctx.trajectories_list[0] print('actor {}, {} envs send traj '.format(task.router.node_id, len(trajectories)), flush=True) diff --git a/ding/framework/middleware/tests/league_config.py b/ding/framework/middleware/tests/league_config.py index 491b6215ee..7fea5fa746 100644 --- a/ding/framework/middleware/tests/league_config.py +++ b/ding/framework/middleware/tests/league_config.py @@ -79,9 +79,9 @@ 'discount_factor': 1.0, 'gae_lambda': 1.0, 'n_episode': 1, - 'n_rollout_samples': 32, + 'n_rollout_samples': 64, 'n_sample': 64, - 'unroll_len': 64 + 'unroll_len': 1 }, 'eval': { 'evaluator': { diff --git a/ding/framework/middleware/tests/mock_for_test.py b/ding/framework/middleware/tests/mock_for_test.py index 821f444cb6..eb508ea8e8 100644 --- a/ding/framework/middleware/tests/mock_for_test.py +++ b/ding/framework/middleware/tests/mock_for_test.py @@ -237,7 +237,18 @@ def _battle_inferencer(ctx: "BattleContext"): # Get current env obs. obs = env.ready_obs + # { + # env_id: { + # policy_id:{ + # 'raw_obs': + # 'opponent_obs': + # 'action_result': + # } + # } + # } + # the role of remain_episode is to mask necessary rollouts, avoid processing unnecessary data + # 如果每个 actor 只有一个 env, 下面这部分代码可以全部去掉 new_available_env_id = set(obs.keys()).difference(ctx.ready_env_id) ctx.ready_env_id = ctx.ready_env_id.union(set(list(new_available_env_id)[:ctx.remain_episode])) ctx.remain_episode -= min(len(new_available_env_id), ctx.remain_episode) @@ -253,9 +264,19 @@ def _battle_inferencer(ctx: "BattleContext"): inference_output[env_id] = {} actions[env_id] = {} for policy_id, policy_obs in observations.items(): + # policy.forward output = ctx.current_policies[policy_id].forward(policy_obs) inference_output[env_id][policy_id] = output actions[env_id][policy_id] = output['action'] + # aciton[env_id][policy_id] = { + # 'func_id': func_id, + # 'skip_steps': random.randint(0, MAX_DELAY - 1), + # # 'skip_steps': 8, + # 'queued': random.randint(0, 1), + # 'unit_tags': unit_tags, + # 'target_unit_tag': target_unit_tag, + # 'location': (random.randint(0, SPATIAL_SIZE[0] - 1), random.randint(0, SPATIAL_SIZE[1] - 1)) + # } ctx.inference_output = inference_output ctx.actions = actions @@ -266,18 +287,21 @@ def battle_rolloutor_for_distar(cfg: EasyDict, env: BaseEnvManager, transitions_ def _battle_rolloutor(ctx: "BattleContext"): timesteps = env.step(ctx.actions) - # for env_id, timestep in timesteps.items(): + # ctx.total_envstep_count += len(timesteps) ctx.env_step += len(timesteps) # for env_id, timestep in timesteps.items(): # TODO(zms): make sure a standard + # 这里 timestep 是 一个 env_num 长的 list，但是每次step真的会返回所有 env 的 timestep 吗？（需要确认）是就用 dict，否就用 list for env_id, timestep in enumerate(timesteps): if timestep.info.get('abnormal'): # TODO(zms): cannot get exact env_step of a episode because for each observation, # in most cases only one of two policies has a obs. # ctx.total_envstep_count -= transitions_list[0].length(env_id) # ctx.env_step -= transitions_list[0].length(env_id) + + # TODO(zms): 如果要有available_env_id 的话，这里也要更新 for transitions in transitions_list: transitions.clear_newest_episode(env_id) continue diff --git a/dizoo/distar/config/distar_config.py b/dizoo/distar/config/distar_config.py index 0eec475ff7..ff54b36afa 100644 --- a/dizoo/distar/config/distar_config.py +++ b/dizoo/distar/config/distar_config.py @@ -80,9 +80,9 @@ 'discount_factor': 1.0, 'gae_lambda': 1.0, 'n_episode': 1, - 'n_rollout_samples': 32, + 'n_rollout_samples': 64, 'n_sample': 64, - 'unroll_len': 64 + 'unroll_len': 1 }, 'eval': { 'evaluator': { diff --git a/dizoo/distar/envs/distar_env.py b/dizoo/distar/envs/distar_env.py index 1dbb7b50c7..cf78177401 100644 --- a/dizoo/distar/envs/distar_env.py +++ b/dizoo/distar/envs/distar_env.py @@ -23,6 +23,10 @@ def step(self, actions): # In DI-engine, the return of BaseEnv.step is ('obs', 'reward', 'done', 'info') # Here in DI-star, the return is ({'raw_obs': self._obs[agent_idx], 'opponent_obs': opponent_obs, 'action_result': self._action_result[agent_idx]}, reward, episode_complete) next_observations, reward, done = super(DIStarEnv, self).step(actions) + # next_observations 和 observations 格式一样 + # reward 是 list [policy reward 1, policy reard 2] + # done 是 一个 bool 值 + # TODO(zms): final_eval_reward 这局赢没赢 info = {} for policy_id in range(self._num_agents): info[policy_id] = {'result': None} From 2e7fb1a6889a77fde0c2961ad0bc755fb36b6170 Mon Sep 17 00:00:00 2001 From: lixuelin Date: Wed, 22 Jun 2022 13:53:27 +0800 Subject: [PATCH 143/229] merge --- ding/example/distar.py | 4 +-- ding/framework/middleware/league_learner.py | 17 ++++++------- .../middleware/tests/test_league_learner.py | 25 +++++++------------ .../middleware/tests/test_league_pipeline.py | 14 +++++------ 4 files changed, 26 insertions(+), 34 deletions(-) diff --git a/ding/example/distar.py b/ding/example/distar.py index b7bae5fc36..de51043fbc 100644 --- a/ding/example/distar.py +++ b/ding/example/distar.py @@ -5,7 +5,7 @@ from ding.data import DequeBuffer from ding.envs import BaseEnvManager from ding.framework.context import BattleContext -from ding.framework.middleware import StepLeagueActor, LeagueCoordinator, LeagueLearnerExchanger, data_pusher, OffPolicyLearner +from ding.framework.middleware import StepLeagueActor, LeagueCoordinator, LeagueLearnerCommunicator, data_pusher, OffPolicyLearner from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, DIStarMockPolicyCollect, battle_inferencer_for_distar, battle_rolloutor_for_distar from ding.framework.task import task, Parallel from ding.league.v2 import BaseLeague @@ -74,7 +74,7 @@ def main(): buffer_ = DequeBuffer(size=cfg.policy.other.replay_buffer.replay_buffer_size) player = league.active_players[task.router.node_id % N_PLAYERS] policy = policy_fn() - task.use(LeagueLearnerExchanger(cfg, policy.learn_mode, player)) + task.use(LeagueLearnerCommunicator(cfg, policy.learn_mode, player)) task.use(data_pusher(cfg, buffer_)) task.use(OffPolicyLearner(cfg, policy.learn_mode, buffer_)) else: diff --git a/ding/framework/middleware/league_learner.py b/ding/framework/middleware/league_learner.py index f0c172e776..53118f40c2 100644 --- a/ding/framework/middleware/league_learner.py +++ b/ding/framework/middleware/league_learner.py @@ -26,7 +26,7 @@ class LearnerModel: train_iter: int = 0 -class LeagueLearnerExchanger: +class LeagueLearnerCommunicator: def __init__(self, cfg: dict, policy: "Policy", player: "ActivePlayer") -> None: self.cfg = cfg @@ -38,16 +38,15 @@ def __init__(self, cfg: dict, policy: "Policy", player: "ActivePlayer") -> None: task.on(EventEnum.ACTOR_SEND_DATA.format(player=self.player_id), self._push_data) def _push_data(self, data: "ActorData"): - print("learner {} receive data from actor! \n".format(task.router.node_id), flush=True) - - # for env_trajectories in data.train_data: - # for traj in env_trajectories.trajectories: - # print(len(traj)) - # self._cache.append(traj) - self._cache.append(data.train_data) + for env_trajectories in data.train_data: + self._cache.extend(env_trajectories.trajectories) + # if isinstance(data.train_data, list): + # self._cache.extend(data.train_data) + # else: + # self._cache.append(data.train_data) def __call__(self, ctx: "Context"): - print("push data into the ctx") + print("Learner: push data into the ctx") ctx.trajectories = list(self._cache) self._cache.clear() sleep(1) diff --git a/ding/framework/middleware/tests/test_league_learner.py b/ding/framework/middleware/tests/test_league_learner.py index 2cea66a445..087d31fbef 100644 --- a/ding/framework/middleware/tests/test_league_learner.py +++ b/ding/framework/middleware/tests/test_league_learner.py @@ -5,19 +5,18 @@ import pytest import logging -from ding.envs import BaseEnvManager from ding.data import DequeBuffer +from ding.envs import BaseEnvManager from ding.framework.context import BattleContext from ding.framework import EventEnum from ding.framework.task import task, Parallel -from ding.framework.middleware import data_pusher,\ - OffPolicyLearner, LeagueLearnerExchanger -from ding.framework.middleware.functional.actor_data import ActorData, ActorDataMeta, ActorEnvTrajectories -from ding.framework.middleware.tests import cfg, MockLeague, MockLogger +from ding.framework.middleware import data_pusher, OffPolicyLearner, LeagueLearnerCommunicator +from ding.framework.middleware.functional.actor_data import ActorData from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy from ding.league.v2 import BaseLeague +from dizoo.distar.config import distar_cfg +from dizoo.distar.envs import get_fake_rl_trajectory from dizoo.distar.envs.distar_env import DIStarEnv -from dizoo.distar.envs import fake_rl_data_batch_with_last from distar.ctools.utils import read_config import time from typing import Any @@ -27,7 +26,7 @@ def prepare_test(): global cfg - cfg = deepcopy(cfg) + cfg = deepcopy(distar_cfg) env_cfg = read_config('./test_distar_config.yaml') def env_fn(): @@ -66,17 +65,11 @@ def actor_mocker(league): def _actor_mocker(ctx): n_players = len(league.active_players_ids) player = league.active_players[(task.router.node_id + 2) % n_players] - print("actor player:", player.player_id) + print("Actor: actor player:", player.player_id) for _ in range(24): - # meta = ActorDataMeta(player_total_env_step=0, actor_id=0, send_wall_time=time.time()) - # data = fake_rl_data_batch_with_last() - # actor_data = ActorData(meta=ActorDataMeta, train_data=ActorEnvTrajectories(env_id=0, trajectories=[data])) - - data = fake_rl_data_batch_with_last() + data = get_fake_rl_trajectory() actor_data = TestActorData(env_step=0, train_data=data) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=player.player_id), actor_data) - - task.emit(EventEnum.ACTOR_SEND_DATA.format(player=player.player_id), actor_data) sleep(9) return _actor_mocker @@ -97,7 +90,7 @@ def _main(): print("League: n_players: ", n_players) player = league.active_players[task.router.node_id % n_players] policy = policy_fn() - task.use(LeagueLearnerExchanger(cfg, policy.learn_mode, player)) + task.use(LeagueLearnerCommunicator(cfg, policy.learn_mode, player)) task.use(data_pusher(cfg, buffer_)) task.use(OffPolicyLearner(cfg, policy.learn_mode, buffer_)) task.run(max_step=30) diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index 3d067bfcef..5fe6d64817 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -6,15 +6,14 @@ from ding.envs import BaseEnvManager, EnvSupervisor from ding.framework.supervisor import ChildType from ding.framework.context import BattleContext -from ding.framework.middleware import StepLeagueActor, LeagueCoordinator, \ - LeagueLearnerExchanger, data_pusher, OffPolicyLearner +from ding.framework.middleware import StepLeagueActor, LeagueCoordinator, LeagueLearnerCommunicator, data_pusher, OffPolicyLearner +from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, DIStarMockPolicyCollect, battle_inferencer_for_distar, battle_rolloutor_for_distar from ding.framework.task import task, Parallel from ding.league.v2 import BaseLeague from dizoo.distar.config import distar_cfg from dizoo.distar.envs.distar_env import DIStarEnv from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, DIStarMockPolicyCollect, \ battle_inferencer_for_distar, battle_rolloutor_for_distar -from distar.ctools.utils import read_config from unittest.mock import patch env_cfg = dict( @@ -36,7 +35,6 @@ ), ) env_cfg = EasyDict(env_cfg) - cfg = deepcopy(distar_cfg) @@ -69,7 +67,6 @@ def collect_policy_fn(cls): def main(): logging.getLogger().setLevel(logging.INFO) - # cfg, env_fn, policy_fn, collect_policy_fn = prepare_test() league = BaseLeague(cfg.policy.other.league) N_PLAYERS = len(league.active_players_ids) print("League: n_players =", N_PLAYERS) @@ -81,10 +78,13 @@ def main(): if task.router.node_id == 0: task.use(LeagueCoordinator(cfg, league)) elif task.router.node_id <= N_PLAYERS: - buffer_ = DequeBuffer(size=cfg.policy.other.replay_buffer.replay_buffer_size) + cfg.policy.collect.unroll_len = 1 player = league.active_players[task.router.node_id % N_PLAYERS] + + buffer_ = DequeBuffer(size=cfg.policy.other.replay_buffer.replay_buffer_size) policy = PrepareTest.policy_fn() - task.use(LeagueLearnerExchanger(cfg, policy.learn_mode, player)) + + task.use(LeagueLearnerCommunicator(cfg, policy.learn_mode, player)) task.use(data_pusher(cfg, buffer_)) task.use(OffPolicyLearner(cfg, policy.learn_mode, buffer_)) else: From eafdf9cd94c47aa6f1206331029234aa40befa7c Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 22 Jun 2022 14:17:36 +0800 Subject: [PATCH 144/229] change commit position --- ding/framework/middleware/functional/collector.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index fadcee92bd..a4d12eb02e 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -86,8 +86,6 @@ def get_env_trajectories(self, env_id: int, only_finished: bool = False): trajectories += self._cut_trajectory_from_episode(self._transitions[env_id][0][:tail_idx]) self._transitions[env_id][0] = self._transitions[env_id][0][tail_idx:] - # 少于 64 直接删 - return trajectories def to_trajectories(self, only_finished: bool = False): @@ -113,6 +111,7 @@ def _cut_trajectory_from_episode(self, episode: list): if num_tail_transitions > 0: trajectory = episode[-self._unroll_len:] if len(trajectory) < self._unroll_len: + # TODO(zms): 少于 64 直接删 initial_elements = [] for _ in range(self._unroll_len - len(trajectory)): initial_elements.append(trajectory[0]) From a0612436b30ae2ce6fdb172eccceaab972c1dfb0 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 22 Jun 2022 15:33:27 +0800 Subject: [PATCH 145/229] add z infos --- dizoo/distar/envs/__init__.py | 2 +- dizoo/distar/envs/static_data.py | 6 ++ dizoo/distar/policy/distar_policy.py | 68 +++++++++++++++++-- dizoo/distar/policy/z_files/12D.json | 1 + dizoo/distar/policy/z_files/1758k.json | 1 + dizoo/distar/policy/z_files/3map.json | 1 + .../policy/z_files/7map_filter_spine.json | 1 + .../distar/policy/z_files/NewRepugnancy.json | 1 + dizoo/distar/policy/z_files/filter.json | 1 + dizoo/distar/policy/z_files/lurker.json | 1 + dizoo/distar/policy/z_files/mutalisk.json | 1 + dizoo/distar/policy/z_files/nydus.json | 1 + dizoo/distar/policy/z_files/perfect_z.json | 1 + dizoo/distar/policy/z_files/stairs.json | 1 + dizoo/distar/policy/z_files/worker_rush.json | 1 + 15 files changed, 81 insertions(+), 7 deletions(-) create mode 100644 dizoo/distar/policy/z_files/12D.json create mode 100644 dizoo/distar/policy/z_files/1758k.json create mode 100644 dizoo/distar/policy/z_files/3map.json create mode 100644 dizoo/distar/policy/z_files/7map_filter_spine.json create mode 100644 dizoo/distar/policy/z_files/NewRepugnancy.json create mode 100644 dizoo/distar/policy/z_files/filter.json create mode 100644 dizoo/distar/policy/z_files/lurker.json create mode 100644 dizoo/distar/policy/z_files/mutalisk.json create mode 100644 dizoo/distar/policy/z_files/nydus.json create mode 100644 dizoo/distar/policy/z_files/perfect_z.json create mode 100644 dizoo/distar/policy/z_files/stairs.json create mode 100644 dizoo/distar/policy/z_files/worker_rush.json diff --git a/dizoo/distar/envs/__init__.py b/dizoo/distar/envs/__init__.py index dd1dabfe48..a639510e3c 100644 --- a/dizoo/distar/envs/__init__.py +++ b/dizoo/distar/envs/__init__.py @@ -1,5 +1,5 @@ from .distar_env import DIStarEnv from .meta import * -from .static_data import BEGIN_ACTIONS, ACTION_RACE_MASK, SELECTED_UNITS_MASK, ACTIONS +from .static_data import RACE_DICT, BEGIN_ACTIONS, ACTION_RACE_MASK, SELECTED_UNITS_MASK, ACTIONS from .stat import Stat from .fake_data import get_fake_rl_trajectory, fake_rl_data_batch_with_last diff --git a/dizoo/distar/envs/static_data.py b/dizoo/distar/envs/static_data.py index e4ea003dc3..824497efae 100644 --- a/dizoo/distar/envs/static_data.py +++ b/dizoo/distar/envs/static_data.py @@ -3,6 +3,12 @@ import numpy as np from collections import defaultdict +RACE_DICT = { + 1: 'terran', + 2: 'zerg', + 3: 'protoss', + 4: 'random', +} ACTION_INFO_MASK = \ { diff --git a/dizoo/distar/policy/distar_policy.py b/dizoo/distar/policy/distar_policy.py index 3101e69755..e200ab2dca 100644 --- a/dizoo/distar/policy/distar_policy.py +++ b/dizoo/distar/policy/distar_policy.py @@ -12,8 +12,13 @@ from ding.utils import EasyTimer from ding.utils.data import default_collate, default_decollate from dizoo.distar.model import Model -from dizoo.distar.envs import NUM_UNIT_TYPES, ACTIONS, Stat +from dizoo.distar.envs import NUM_UNIT_TYPES, ACTIONS, RACE_DICT, NUM_CUMULATIVE_STAT_ACTIONS, Stat from .utils import collate_fn_learn, kl_error, entropy_error +import os +import json +import random +from copy import deepcopy +from s2clientprotocol import sc2api_pb2 as sc_pb class DIStarPolicy(Policy): @@ -108,6 +113,7 @@ class DIStarPolicy(Policy): zero_z_exceed_loop=True, # set Z to 0 if game passes the game loop in Z zero_z_value=1, extra_units=True, # selcet extra units if selected units exceed 64 + z_path='7map_filter_spine.json' ) def _create_model( @@ -352,9 +358,12 @@ def _load_state_dict_learn(self, _state_dict: Dict) -> None: def _init_collect(self): self.collect_model = model_wrap(self._model, 'base') + self.z_path = self._cfg.z_path + # TODO(zms): in _setup_agents, load state_dict to set up z_idx + self.z_idx = None self._reset_collect() - def _reset_collect(self, env_id=0): + def _reset_collect(self, game_info, obs, map_name='KingsCove', env_id=0): self.stat = Stat('zerg') # TODO self.target_z_loop = 43200 # TODO self.exceed_loop_flag = False @@ -366,12 +375,59 @@ def _reset_collect(self, env_id=0): self.last_targeted_unit_tag = None self.last_location = None # [x, y] self.enemy_unit_type_bool = torch.zeros(NUM_UNIT_TYPES, dtype=torch.uint8) + self.map_name = map_name + self.map_size = None # TODO + self.requested_races = { + info.player_id: info.race_requested + for info in game_info.player_info if info.type != sc_pb.Observer + } - self.target_building_order = None # TODO - self.target_bo_location = None - self.target_cumulative_stat = None + # init Z + raw_ob = obs['raw_obs'] + location = [] + for i in raw_ob.observation.raw_data.units: + if i.unit_type == 59 or i.unit_type == 18 or i.unit_type == 86: + location.append([i.pos.x, i.pos.y]) + assert len(location) == 1, 'no fog of war, check game version!' + self.born_location = deepcopy(location[0]) + born_location = location[0] + born_location[0] = int(born_location[0]) + # TODO(zms): map_size from Features + born_location[1] = int(self.map_size.y - born_location[1]) + born_location_str = str(born_location[0] + born_location[1] * 160) + self.z_path = os.path.join(os.path.dirname(__file__), 'lib', self.z_path) + with open(self.z_path, 'r') as f: + self.z_data = json.load(f) + z_data = self.z_data + + z_type = None + idx = None + raw_ob = obs['raw_obs'] + # TODO(zms): requested_races from Features + race = RACE_DICT[self.requested_races[raw_ob.observation.player_common.player_id]] + opponent_id = 1 if raw_ob.observation.player_common.player_id == 2 else 2 + opponent_race = RACE_DICT[self.requested_races[opponent_id]] + if race == opponent_race: + mix_race = race + else: + mix_race = race + opponent_race + if self.z_idx is not None: + idx, z_type = random.choice(self.z_idx[self.map_name][mix_race][born_location_str]) + z = z_data[self.map_name][mix_race][born_location_str][idx] + else: + z = random.choice(z_data[self.map_name][mix_race][born_location_str]) - self.map_size = None # TODO + if len(z) == 5: + self.target_building_order, target_cumulative_stat, bo_location, self._target_z_loop, z_type = z + else: + self.target_building_order, target_cumulative_stat, bo_location, self._target_z_loop = z + # TODO(zms): other attributes like use_bo_reward + self.target_building_order = torch.tensor(self.target_building_order, dtype=torch.long) + self.target_bo_location = torch.tensor(bo_location, dtype=torch.long) + self.target_cumulative_stat = torch.zeros(NUM_CUMULATIVE_STAT_ACTIONS, dtype=torch.float) + self.target_cumulative_stat.scatter_( + index=torch.tensor(target_cumulative_stat, dtype=torch.long), dim=0, value=1. + ) def _forward_collect(self, data): game_info = data.pop('game_info') diff --git a/dizoo/distar/policy/z_files/12D.json b/dizoo/distar/policy/z_files/12D.json new file mode 100644 index 0000000000..c1af4fc25f --- /dev/null +++ b/dizoo/distar/policy/z_files/12D.json @@ -0,0 +1 @@ +{"NewRepugnancy": {"zerg": {"16176": [[[38, 173, 173, 173, 173, 173, 173, 173, 39, 39, 173, 39, 0, 0, 0, 0, 0, 0, 0, 0], [34, 166], [15692, 0, 0, 0, 0, 0, 0, 0, 4934, 4934, 0, 4772, 0, 0, 0, 0, 0, 0, 0, 0], 3718], [[38, 173, 173, 173, 173, 173, 173, 39, 173, 39, 39, 39, 173, 0, 0, 0, 0, 0, 0, 0], [34, 166], [15692, 0, 0, 0, 0, 0, 0, 2844, 0, 2844, 4451, 4773, 0, 0, 0, 0, 0, 0, 0, 0], 4037], [[18, 11, 38, 150, 150, 173, 173, 173, 120, 173, 3, 150, 124, 124, 124, 124, 124, 173, 173, 173], [3, 10, 17, 34, 113, 117, 143, 166], [12496, 0, 16980, 0, 0, 0, 0, 0, 0, 0, 16501, 0, 0, 0, 0, 0, 0, 0, 0, 0], 4835], [[18, 38, 11, 173, 173, 150, 173, 173, 173, 173, 173, 173, 0, 0, 0, 0, 0, 0, 0, 0], [10, 17, 34, 143, 166], [12496, 17612, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 3585], [[18, 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b/dizoo/distar/policy/z_files/stairs.json new file mode 100644 index 0000000000..460d201a8b --- /dev/null +++ b/dizoo/distar/policy/z_files/stairs.json @@ -0,0 +1 @@ +{"NewRepugnancy": {"zerg": {"3015": [[[18, 11, 38, 150, 150, 120, 18, 173, 173, 3, 173, 10, 150, 122, 54, 11, 11, 33, 11, 82], [3, 9, 10, 17, 30, 34, 48, 55, 75, 113, 115, 117, 143, 146, 166], [7015, 0, 3819, 0, 0, 0, 11177, 0, 0, 7325, 0, 7806, 0, 0, 0, 0, 0, 7185, 0, 0], 14588], [[18, 38, 11, 150, 150, 120, 18, 3, 173, 173, 173, 173, 150, 173, 124, 124, 173, 173, 173, 124], [3, 10, 17, 34, 113, 143, 117, 166], [7015, 3010, 0, 0, 0, 0, 11177, 6527, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 8000], [[18, 11, 38, 150, 150, 120, 18, 3, 173, 173, 173, 173, 150, 124, 124, 11, 173, 173, 33, 124], [3, 10, 17, 34, 113, 143, 117, 166, 30, 146, 55], [7015, 0, 3975, 0, 0, 0, 11177, 7327, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6219, 0], 12000]], "16176": [[[18, 11, 38, 150, 150, 173, 120, 173, 173, 18, 3, 10, 150, 11, 122, 54, 11, 33, 11, 153], [3, 9, 10, 17, 30, 34, 48, 55, 75, 113, 115, 117, 143, 146, 166], [12496, 0, 15692, 0, 0, 0, 0, 0, 0, 8334, 12346, 12346, 0, 0, 0, 0, 0, 13454, 0, 0], 14588], [[18, 11, 38, 150, 150, 120, 18, 3, 173, 173, 173, 173, 173, 173, 173, 150, 124, 124, 124, 124], [3, 10, 17, 34, 113, 143, 117, 166], [12496, 0, 15372, 0, 0, 0, 8334, 11705, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 8000], [[18, 11, 38, 150, 173, 150, 173, 120, 18, 3, 150, 173, 173, 173, 173, 173, 173, 124, 124, 124], [3, 10, 17, 34, 113, 143, 117, 166, 30, 146, 55], [12496, 0, 16981, 0, 0, 0, 0, 0, 15087, 11702, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 12000]]}}} \ No newline at end of file diff --git a/dizoo/distar/policy/z_files/worker_rush.json b/dizoo/distar/policy/z_files/worker_rush.json new file mode 100644 index 0000000000..34d55a30a6 --- /dev/null +++ b/dizoo/distar/policy/z_files/worker_rush.json @@ -0,0 +1 @@ +{"KingsCove": {"zerg": {"20772": [[[38, 173, 173, 173, 173, 173, 39, 173, 18, 173, 173, 150, 150, 0, 0, 0, 0, 0, 0, 0], [17, 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"NewRepugnancy": {"zerg": {"3015": [[[38, 173, 173, 173, 173, 39, 173, 173, 173, 39, 173, 39, 39, 0, 0, 0, 0, 0, 0, 0], [34, 166], [3819, 0, 0, 0, 0, 16028, 0, 0, 0, 14580, 0, 15544, 15058, 0, 0, 0, 0, 0, 0, 0], 3977], [[38, 173, 173, 173, 173, 173, 173, 39, 173, 39, 39, 39, 173, 0, 0, 0, 0, 0, 0, 0], [34, 166], [1899, 0, 0, 0, 0, 0, 0, 14418, 0, 14742, 15542, 15062, 0, 0, 0, 0, 0, 0, 0, 0], 5384]], "16176": [[[38, 173, 173, 173, 173, 173, 39, 173, 39, 39, 39, 173, 173, 0, 0, 0, 0, 0, 0, 0], [34, 166], [15692, 0, 0, 0, 0, 0, 2844, 0, 2844, 4451, 4773, 0, 0, 0, 0, 0, 0, 0, 0, 0], 4037], [[38, 173, 173, 39, 173, 173, 173, 39, 173, 173, 173, 0, 0, 0, 0, 0, 0, 0, 0, 0], [34, 166], [15692, 0, 0, 3324, 0, 0, 0, 4134, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 3450], [[38, 173, 173, 39, 173, 173, 173, 39, 173, 39, 39, 173, 173, 0, 0, 0, 0, 0, 0, 0], [34, 166], [15692, 0, 0, 3645, 0, 0, 0, 4935, 0, 4937, 4615, 0, 0, 0, 0, 0, 0, 0, 0, 0], 4354]]}}, "CyberForest": {"zerg": {"2577": [[[38, 173, 173, 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173, 173, 173, 173, 124, 124, 124], [3, 9, 10, 17, 34, 35, 111, 113, 114, 117, 143, 166], [6573, 0, 3371, 0, 0, 0, 11054, 0, 7540, 8014, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 9652], [[18, 11, 38, 150, 150, 120, 18, 173, 173, 3, 173, 173, 173, 173, 173, 150, 10, 124, 124, 54], [3, 9, 10, 17, 18, 19, 22, 25, 26, 30, 34, 48, 50, 55, 75, 78, 83, 89, 111, 113, 115, 117, 130, 143, 146, 166], [6573, 0, 3211, 0, 0, 0, 11054, 0, 0, 8014, 0, 0, 0, 0, 0, 0, 8017, 0, 0, 0], 16657], [[18, 11, 38, 150, 150, 120, 18, 3, 173, 173, 173, 173, 150, 124, 124, 124, 124, 173, 173, 173], [3, 9, 10, 17, 18, 19, 22, 25, 26, 30, 34, 48, 50, 56, 75, 78, 83, 89, 111, 113, 115, 117, 130, 143, 146, 166], [6573, 0, 3211, 0, 0, 0, 11054, 7858, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 24908], [[11, 18, 11, 38, 150, 150, 173, 120, 18, 3, 173, 173, 173, 173, 173, 173, 173, 124, 124, 124], [3, 9, 10, 17, 25, 26, 30, 34, 35, 48, 55, 75, 89, 109, 110, 113, 115, 117, 139, 143, 146, 166], [0, 6573, 0, 3371, 0, 0, 0, 0, 11054, 7853, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 22792], [[18, 38, 11, 150, 150, 150, 10, 33, 54, 122, 11, 11, 10, 18, 82, 60, 60, 11, 153, 153], [9, 10, 17, 30, 34, 48, 75, 89, 111, 115, 143, 146], [6573, 3211, 0, 0, 0, 0, 7853, 7700, 0, 0, 0, 0, 7697, 11054, 0, 0, 0, 0, 0, 0], 12799], [[18, 11, 38, 150, 150, 120, 18, 150, 3, 173, 173, 173, 173, 150, 173, 173, 173, 173, 124, 124], [3, 9, 10, 17, 25, 26, 30, 34, 48, 113, 115, 117, 143, 146, 166], [6573, 0, 3211, 0, 0, 0, 11054, 0, 7853, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 9772], [[11, 38, 173, 173, 173, 120, 173, 3, 173, 173, 150, 173, 173, 124, 124, 124, 124, 124, 18, 124], [3, 10, 17, 30, 34, 113, 117, 143, 166], [0, 2086, 0, 0, 0, 0, 0, 3211, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6573, 0], 10660], [[18, 11, 38, 150, 150, 120, 10, 150, 33, 121, 173, 173, 173, 173, 173, 173, 173, 18, 173, 54], [9, 10, 17, 18, 19, 22, 30, 34, 47, 48, 50, 56, 112, 113, 114, 115, 130, 143, 166], [6573, 0, 3211, 0, 0, 0, 7697, 0, 8014, 0, 0, 0, 0, 0, 0, 0, 0, 11054, 0, 0], 14021], [[18, 11, 38, 173, 173, 173, 173, 173, 150, 150, 173, 120, 173, 54, 11, 11, 173, 40, 11, 18], [3, 10, 17, 34, 35, 48, 110, 113, 139, 143, 166], [6573, 0, 3211, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1451, 0, 11054], 11907], [[18, 11, 38, 150, 150, 120, 18, 3, 173, 150, 173, 173, 173, 173, 10, 124, 124, 121, 33, 11], [3, 9, 10, 17, 19, 30, 34, 35, 47, 48, 65, 110, 111, 113, 114, 117, 139, 143, 166], [6573, 0, 2580, 0, 0, 0, 11054, 7700, 0, 0, 0, 0, 0, 0, 8014, 0, 0, 0, 7536, 0], 14345], [[18, 11, 38, 150, 150, 173, 173, 120, 18, 3, 173, 173, 173, 173, 173, 173, 10, 124, 124, 124], [3, 9, 10, 17, 34, 35, 48, 113, 114, 117, 139, 143, 166], [6573, 0, 3211, 0, 0, 0, 0, 0, 11054, 8175, 0, 0, 0, 0, 0, 0, 8018, 0, 0, 0], 10900], [[18, 11, 38, 150, 150, 120, 18, 3, 173, 150, 173, 173, 10, 11, 11, 122, 33, 54, 11, 11], [3, 9, 10, 17, 18, 22, 30, 34, 48, 55, 64, 75, 78, 89, 107, 111, 113, 115, 130, 143, 146, 166], [6573, 0, 3211, 0, 0, 0, 11054, 8175, 0, 0, 0, 0, 7700, 0, 0, 0, 7696, 0, 0, 0], 15895], [[18, 11, 38, 150, 150, 120, 18, 3, 173, 173, 150, 173, 173, 173, 10, 173, 173, 173, 122, 124], [3, 9, 10, 17, 18, 19, 22, 25, 26, 30, 34, 47, 48, 50, 55, 56, 64, 75, 78, 83, 89, 107, 111, 113, 115, 117, 130, 143, 146, 166], [6573, 0, 3211, 0, 0, 0, 11054, 7853, 0, 0, 0, 0, 0, 0, 7700, 0, 0, 0, 0, 0], 26616], [[18, 11, 38, 150, 150, 120, 173, 173, 173, 18, 150, 150, 3, 10, 150, 173, 173, 173, 173, 173], [3, 9, 10, 17, 19, 30, 34, 48, 55, 75, 89, 113, 114, 115, 143, 146, 155, 166], [6573, 0, 3211, 0, 0, 0, 0, 0, 0, 11054, 0, 0, 8175, 8175, 0, 0, 0, 0, 0, 0], 17804], [[18, 11, 38, 150, 150, 120, 173, 173, 18, 10, 3, 173, 173, 173, 173, 118, 124, 173, 173, 124], [3, 9, 10, 17, 18, 19, 22, 30, 34, 47, 50, 55, 56, 75, 78, 83, 89, 111, 113, 115, 117, 130, 143, 146, 155, 166], [6573, 0, 978, 0, 0, 0, 0, 0, 11054, 1131, 8017, 0, 0, 0, 0, 0, 0, 0, 0, 0], 17829], [[18, 11, 11, 38, 150, 150, 120, 18, 173, 173, 150, 3, 173, 124, 173, 173, 173, 173, 124, 150], [3, 9, 10, 17, 25, 26, 30, 34, 75, 111, 113, 115, 117, 143, 146, 166], [6573, 0, 0, 1450, 0, 0, 0, 11054, 0, 0, 0, 7374, 0, 0, 0, 0, 0, 0, 0, 0], 15989], [[18, 18, 11, 38, 173, 150, 150, 150, 120, 173, 3, 173, 173, 173, 10, 124, 124, 10, 33, 173], [3, 9, 10, 17, 19, 30, 34, 35, 43, 48, 59, 65, 67, 75, 89, 109, 110, 111, 112, 113, 114, 117, 139, 143, 146, 153, 166], [6573, 11054, 0, 3530, 0, 0, 0, 0, 0, 0, 8175, 0, 0, 0, 8179, 0, 0, 7700, 7700, 0], 22425]]}}} \ No newline at end of file From f44f54daa4812e6f0842d3996aa1f8cb2a7f9d9e Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Thu, 23 Jun 2022 01:30:57 +0800 Subject: [PATCH 146/229] adjust codes to run the pipeline --- .../middleware/functional/collector.py | 5 + ding/framework/middleware/league_actor.py | 6 +- ding/framework/middleware/league_learner.py | 16 +- ding/framework/middleware/tests/__init__.py | 1 - .../middleware/tests/league_config.py | 164 ------------------ .../middleware/tests/test_league_learner.py | 24 +-- .../middleware/tests/test_league_pipeline.py | 3 +- dizoo/distar/config/distar_config.py | 2 +- dizoo/distar/policy/utils.py | 2 +- 9 files changed, 32 insertions(+), 191 deletions(-) delete mode 100644 ding/framework/middleware/tests/league_config.py diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index a4d12eb02e..3f677f626e 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -13,6 +13,7 @@ from ding.framework import OnlineRLContext, BattleContext from collections import deque from ding.framework.middleware.functional.actor_data import ActorEnvTrajectories +from dizoo.distar.envs.fake_data import rl_step_data class TransitionList: @@ -106,6 +107,8 @@ def _cut_trajectory_from_episode(self, episode: list): num_complele_trajectory, num_tail_transitions = divmod(len(episode), self._unroll_len) for i in range(num_complele_trajectory): trajectory = episode[i * self._unroll_len:(i + 1) * self._unroll_len] + # TODO(zms): 测试专用，之后去掉 + trajectory.append(rl_step_data(last=True)) return_episode.append(trajectory) if num_tail_transitions > 0: @@ -116,6 +119,8 @@ def _cut_trajectory_from_episode(self, episode: list): for _ in range(self._unroll_len - len(trajectory)): initial_elements.append(trajectory[0]) trajectory = initial_elements + trajectory + # TODO(zms): 测试专用，之后去掉 + trajectory.append(rl_step_data(last=True)) return_episode.append(trajectory) return return_episode # list of trajectories diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 04dd8338b2..43f8677873 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -275,11 +275,9 @@ def __call__(self, ctx: "BattleContext"): # print(ctx.trajectories_list) # ctx.trajectories_list[0] for policy_id 0 # ctx.trajectories_list[0][0] for first env - print(len(ctx.trajectories_list[0])) if len(ctx.trajectories_list[0]) > 0: - print(len(ctx.trajectories_list[0][0].trajectories)) for traj in ctx.trajectories_list[0][0].trajectories: - assert len(traj) == self.unroll_len + assert len(traj) == self.unroll_len + 1 if ctx.job_finish is True: print('we finish the job !') assert len(ctx.trajectories_list[0][0].trajectories) > 0 @@ -311,7 +309,7 @@ def __call__(self, ctx: "BattleContext"): ) if ctx.job_finish is True: - job.result = [e['result'] for e in ctx.episode_info[0]] + job.result = None task.emit(EventEnum.ACTOR_FINISH_JOB, job) ctx.episode_info = [[] for _ in range(self.agent_num)] print('Actor {} job finish, send job\n'.format(task.router.node_id), flush=True) diff --git a/ding/framework/middleware/league_learner.py b/ding/framework/middleware/league_learner.py index f0c172e776..fceaf68018 100644 --- a/ding/framework/middleware/league_learner.py +++ b/ding/framework/middleware/league_learner.py @@ -39,22 +39,22 @@ def __init__(self, cfg: dict, policy: "Policy", player: "ActivePlayer") -> None: def _push_data(self, data: "ActorData"): print("learner {} receive data from actor! \n".format(task.router.node_id), flush=True) - - # for env_trajectories in data.train_data: - # for traj in env_trajectories.trajectories: - # print(len(traj)) - # self._cache.append(traj) - self._cache.append(data.train_data) + for env_trajectories in data.train_data: + for traj in env_trajectories.trajectories: + self._cache.append(traj) + # self._cache.append(data.train_data) def __call__(self, ctx: "Context"): - print("push data into the ctx") + # print("push data into the ctx") ctx.trajectories = list(self._cache) self._cache.clear() sleep(1) yield - print("Learner: save model, ctx.train_iter:", ctx.train_iter) + # print("Learner: save model, ctx.train_iter:", ctx.train_iter) self.player.total_agent_step = ctx.train_iter if self.player.is_trained_enough(): + print('trained enough!') + print('----------------------------------------------------------------------------------') storage = FileStorage( path=os.path.join(self.prefix, "{}_{}_ckpt.pth".format(self.player_id, ctx.train_iter)) ) diff --git a/ding/framework/middleware/tests/__init__.py b/ding/framework/middleware/tests/__init__.py index 8fc101ec04..8e6f536af1 100644 --- a/ding/framework/middleware/tests/__init__.py +++ b/ding/framework/middleware/tests/__init__.py @@ -1,2 +1 @@ from .mock_for_test import * -from .league_config import cfg diff --git a/ding/framework/middleware/tests/league_config.py b/ding/framework/middleware/tests/league_config.py deleted file mode 100644 index 7fea5fa746..0000000000 --- a/ding/framework/middleware/tests/league_config.py +++ /dev/null @@ -1,164 +0,0 @@ -from easydict import EasyDict -cfg = EasyDict( - { - 'env': { - 'manager': { - 'episode_num': 100000, - 'max_retry': 1000, - 'retry_type': 'renew', - 'auto_reset': True, - 'step_timeout': None, - 'reset_timeout': None, - 'retry_waiting_time': 0.1, - 'cfg_type': 'BaseEnvManagerDict', - 'shared_memory': False, - 'return_original_data': True - }, - 'collector_env_num': 1, - 'evaluator_env_num': 1, - 'n_evaluator_episode': 100, - 'env_type': 'prisoner_dilemma', - 'stop_value': [-10.1, -5.05] - }, - 'policy': { - 'model': { - 'obs_shape': 2, - 'action_shape': 2, - 'action_space': 'discrete', - 'encoder_hidden_size_list': [32, 32], - 'critic_head_hidden_size': 32, - 'actor_head_hidden_size': 32, - 'share_encoder': False - }, - 'learn': { - 'learner': { - 'train_iterations': 1000000000, - 'dataloader': { - 'num_workers': 0 - }, - 'log_policy': False, - 'hook': { - 'load_ckpt_before_run': '', - 'log_show_after_iter': 100, - 'save_ckpt_after_iter': 10000, - 'save_ckpt_after_run': True - }, - 'cfg_type': 'BaseLearnerDict' - }, - 'multi_gpu': False, - 'epoch_per_collect': 10, - 'batch_size': 16, - 'learning_rate': 1e-05, - 'value_weight': 0.5, - 'entropy_weight': 0.0, - 'clip_ratio': 0.2, - 'adv_norm': True, - 'value_norm': True, - 'ppo_param_init': True, - 'grad_clip_type': 'clip_norm', - 'grad_clip_value': 0.5, - 'ignore_done': False, - 'update_per_collect': 3, - 'scheduler': { - 'schedule_flag': False, - 'schedule_mode': 'reduce', - 'factor': 0.005, - 'change_range': [0, 1], - 'threshold': 0.5, - 'patience': 50 - } - }, - 'collect': { - 'collector': { - 'deepcopy_obs': False, - 'transform_obs': False, - 'collect_print_freq': 100, - 'get_train_sample': True, - 'cfg_type': 'BattleEpisodeSerialCollectorDict' - }, - 'discount_factor': 1.0, - 'gae_lambda': 1.0, - 'n_episode': 1, - 'n_rollout_samples': 64, - 'n_sample': 64, - 'unroll_len': 1 - }, - 'eval': { - 'evaluator': { - 'eval_freq': 50, - 'cfg_type': 'BattleInteractionSerialEvaluatorDict', - 'stop_value': [-10.1, -5.05], - 'n_episode': 100 - } - }, - 'other': { - 'replay_buffer': { - 'type': 'naive', - 'replay_buffer_size': 10000, - 'deepcopy': False, - 'enable_track_used_data': False, - 'periodic_thruput_seconds': 60, - 'cfg_type': 'NaiveReplayBufferDict' - }, - 'league': { - 'player_category': ['default'], - 'path_policy': 'league_demo/ckpt', - 'active_players': { - 'main_player': 2 - }, - 'main_player': { - 'one_phase_step': 10, # 20 - 'branch_probs': { - 'pfsp': 0.0, - 'sp': 1.0 - }, - 'strong_win_rate': 0.7 - }, - 'main_exploiter': { - 'one_phase_step': 200, - 'branch_probs': { - 'main_players': 1.0 - }, - 'strong_win_rate': 0.7, - 'min_valid_win_rate': 0.3 - }, - 'league_exploiter': { - 'one_phase_step': 200, - 'branch_probs': { - 'pfsp': 1.0 - }, - 'strong_win_rate': 0.7, - 'mutate_prob': 0.5 - }, - 'use_pretrain': False, - 'use_pretrain_init_historical': False, - 'payoff': { - 'type': 'battle', - 'decay': 0.99, - 'min_win_rate_games': 8 - }, - 'metric': { - 'mu': 0, - 'sigma': 8.333333333333334, - 'beta': 4.166666666666667, - 'tau': 0.0, - 'draw_probability': 0.02 - } - } - }, - 'type': 'ppo', - 'cuda': False, - 'on_policy': True, - 'priority': False, - 'priority_IS_weight': False, - 'recompute_adv': True, - 'action_space': 'discrete', - 'nstep_return': False, - 'multi_agent': False, - 'transition_with_policy_data': True, - 'cfg_type': 'PPOPolicyDict' - }, - 'exp_name': 'league_demo', - 'seed': 0 - } -) diff --git a/ding/framework/middleware/tests/test_league_learner.py b/ding/framework/middleware/tests/test_league_learner.py index 2cea66a445..643e8901ec 100644 --- a/ding/framework/middleware/tests/test_league_learner.py +++ b/ding/framework/middleware/tests/test_league_learner.py @@ -13,7 +13,7 @@ from ding.framework.middleware import data_pusher,\ OffPolicyLearner, LeagueLearnerExchanger from ding.framework.middleware.functional.actor_data import ActorData, ActorDataMeta, ActorEnvTrajectories -from ding.framework.middleware.tests import cfg, MockLeague, MockLogger +from dizoo.distar.config import distar_cfg from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy from ding.league.v2 import BaseLeague from dizoo.distar.envs.distar_env import DIStarEnv @@ -26,8 +26,8 @@ def prepare_test(): - global cfg - cfg = deepcopy(cfg) + global distar_cfg + cfg = deepcopy(distar_cfg) env_cfg = read_config('./test_distar_config.yaml') def env_fn(): @@ -68,12 +68,12 @@ def _actor_mocker(ctx): player = league.active_players[(task.router.node_id + 2) % n_players] print("actor player:", player.player_id) for _ in range(24): - # meta = ActorDataMeta(player_total_env_step=0, actor_id=0, send_wall_time=time.time()) - # data = fake_rl_data_batch_with_last() - # actor_data = ActorData(meta=ActorDataMeta, train_data=ActorEnvTrajectories(env_id=0, trajectories=[data])) - + meta = ActorDataMeta(player_total_env_step=0, actor_id=0, send_wall_time=time.time()) data = fake_rl_data_batch_with_last() - actor_data = TestActorData(env_step=0, train_data=data) + actor_data = ActorData(meta=meta, train_data=[ActorEnvTrajectories(env_id=0, trajectories=[data])]) + + # data = fake_rl_data_batch_with_last() + # actor_data = TestActorData(env_step=0, train_data=data) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=player.player_id), actor_data) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=player.player_id), actor_data) @@ -83,15 +83,17 @@ def _actor_mocker(ctx): def _main(): + logging.disable(logging.WARNING) cfg, env_fn, policy_fn = prepare_test() league = BaseLeague(cfg.policy.other.league) with task.start(async_mode=True, ctx=BattleContext()): if task.router.node_id == 0: task.use(coordinator_mocker()) - elif task.router.node_id <= 2: + elif task.router.node_id <= 1: task.use(actor_mocker(league)) else: + cfg.policy.collect.unroll_len = 1 buffer_ = DequeBuffer(size=cfg.policy.other.replay_buffer.replay_buffer_size) n_players = len(league.active_players_ids) print("League: n_players: ", n_players) @@ -105,8 +107,8 @@ def _main(): @pytest.mark.unittest def test_league_learner(): - Parallel.runner(n_parallel_workers=5, protocol="tcp", topology="mesh")(_main) + Parallel.runner(n_parallel_workers=4, protocol="tcp", topology="mesh")(_main) if __name__ == '__main__': - Parallel.runner(n_parallel_workers=5, protocol="tcp", topology="mesh")(_main) + Parallel.runner(n_parallel_workers=4, protocol="tcp", topology="mesh")(_main) diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index 3d067bfcef..95cb441a88 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -68,7 +68,7 @@ def collect_policy_fn(cls): def main(): - logging.getLogger().setLevel(logging.INFO) + logging.disable(logging.WARNING) # cfg, env_fn, policy_fn, collect_policy_fn = prepare_test() league = BaseLeague(cfg.policy.other.league) N_PLAYERS = len(league.active_players_ids) @@ -81,6 +81,7 @@ def main(): if task.router.node_id == 0: task.use(LeagueCoordinator(cfg, league)) elif task.router.node_id <= N_PLAYERS: + cfg.policy.collect.unroll_len = 1 buffer_ = DequeBuffer(size=cfg.policy.other.replay_buffer.replay_buffer_size) player = league.active_players[task.router.node_id % N_PLAYERS] policy = PrepareTest.policy_fn() diff --git a/dizoo/distar/config/distar_config.py b/dizoo/distar/config/distar_config.py index ff54b36afa..0b532f2da3 100644 --- a/dizoo/distar/config/distar_config.py +++ b/dizoo/distar/config/distar_config.py @@ -82,7 +82,7 @@ 'n_episode': 1, 'n_rollout_samples': 64, 'n_sample': 64, - 'unroll_len': 1 + 'unroll_len': 4 }, 'eval': { 'evaluator': { diff --git a/dizoo/distar/policy/utils.py b/dizoo/distar/policy/utils.py index b503323c6a..393fd6e2c5 100644 --- a/dizoo/distar/policy/utils.py +++ b/dizoo/distar/policy/utils.py @@ -9,7 +9,7 @@ def padding_entity_info(traj_data, max_entity_num): - traj_data.pop('map_name', None) + # traj_data.pop('map_name', None) entity_padding_num = max_entity_num - len(traj_data['entity_info']['x']) if 'entity_embeddings' in traj_data.keys(): traj_data['entity_embeddings'] = torch.nn.functional.pad( From 9c0d6f3953d92877db635998f4c8e5b3494660a5 Mon Sep 17 00:00:00 2001 From: niuyazhe Date: Thu, 23 Jun 2022 17:03:43 +0800 Subject: [PATCH 147/229] polish(nyz): polish parse_new_game and add transform_obs --- dizoo/distar/envs/__init__.py | 2 +- dizoo/distar/envs/distar_env.py | 569 ++++++++++++++++++++++++++- dizoo/distar/envs/fake_data.py | 5 +- dizoo/distar/envs/meta.py | 4 + dizoo/distar/policy/distar_policy.py | 64 +-- 5 files changed, 571 insertions(+), 73 deletions(-) diff --git a/dizoo/distar/envs/__init__.py b/dizoo/distar/envs/__init__.py index a639510e3c..5837c285ba 100644 --- a/dizoo/distar/envs/__init__.py +++ b/dizoo/distar/envs/__init__.py @@ -1,4 +1,4 @@ -from .distar_env import DIStarEnv +from .distar_env import DIStarEnv, parse_new_game, transform_obs from .meta import * from .static_data import RACE_DICT, BEGIN_ACTIONS, ACTION_RACE_MASK, SELECTED_UNITS_MASK, ACTIONS from .stat import Stat diff --git a/dizoo/distar/envs/distar_env.py b/dizoo/distar/envs/distar_env.py index cf78177401..c61f3c8454 100644 --- a/dizoo/distar/envs/distar_env.py +++ b/dizoo/distar/envs/distar_env.py @@ -1,10 +1,32 @@ -from distar.envs.env import SC2Env +from typing import Optional, List +from copy import deepcopy +from collections import defaultdict +from s2clientprotocol import sc2api_pb2 as sc_pb +from pysc2.lib import named_array, colors +from pysc2.lib.features import Effects, ScoreCategories, FeatureType, Feature +from torch import int8, uint8, int16, int32, float32, float16, int64 -from ding.envs import BaseEnv, BaseEnvTimestep -from distar.agent.default.lib.features import MAX_DELAY, SPATIAL_SIZE, MAX_SELECTED_UNITS_NUM -from distar.pysc2.lib.action_dict import ACTIONS_STAT -import torch +import six +import collections +import enum +import json import random +import numpy as np +import torch +import os.path as osp + +from ding.envs import BaseEnv, BaseEnvTimestep +try: + from distar.envs.env import SC2Env +except ImportError: + + class SC2Env: + pass +from .meta import MAX_DELAY, MAX_SELECTED_UNITS_NUM, DEFAULT_SPATIAL_SIZE, MAX_ENTITY_NUM, NUM_UPGRADES, NUM_ACTIONS, \ + NUM_UNIT_TYPES, NUM_UNIT_MIX_ABILITIES, EFFECT_LENGTH, UPGRADE_LENGTH, BEGINNING_ORDER_LENGTH +from .static_data import ACTIONS_STAT, RACE_DICT, UNIT_TYPES_REORDER_ARRAY, UPGRADES_REORDER_ARRAY, \ + CUMULATIVE_STAT_ACTIONS, UNIT_ABILITY_REORDER, ABILITY_TO_QUEUE_ACTION, BUFFS_REORDER_ARRAY, \ + ADDON_REORDER_ARRAY class DIStarEnv(SC2Env, BaseEnv): @@ -21,7 +43,8 @@ def close(self): def step(self, actions): # In DI-engine, the return of BaseEnv.step is ('obs', 'reward', 'done', 'info') - # Here in DI-star, the return is ({'raw_obs': self._obs[agent_idx], 'opponent_obs': opponent_obs, 'action_result': self._action_result[agent_idx]}, reward, episode_complete) + # Here in DI-star, the return is ({'raw_obs': self._obs[agent_idx], 'opponent_obs': opponent_obs, + # 'action_result': self._action_result[agent_idx]}, reward, episode_complete) next_observations, reward, done = super(DIStarEnv, self).step(actions) # next_observations 和 observations 格式一样 # reward 是 list [policy reward 1, policy reard 2] @@ -86,7 +109,8 @@ def random_action(cls, obs): exist_selected_types = list(self_unit_types.intersection(set(action['selected_type']))) exist_target_types = list(all_unit_types.intersection(set(action['target_type']))) - # if an action should have target, but we don't have valid target in this observation, then discard this action + # if an action should have target, but we don't have valid target in this observation, + # then discard this action if len(action['target_type']) != 0 and len(exist_target_types) == 0: continue @@ -127,13 +151,14 @@ def random_action(cls, obs): 'queued': random.randint(0, 1), 'unit_tags': unit_tags, 'target_unit_tag': target_unit_tag, - 'location': (random.randint(0, SPATIAL_SIZE[0] - 1), random.randint(0, SPATIAL_SIZE[1] - 1)) + 'location': ( + random.randint(0, DEFAULT_SPATIAL_SIZE[0] - 1), random.randint(0, DEFAULT_SPATIAL_SIZE[1] - 1) + ) } return [data] @property def reward_space(self): - #TODO pass @@ -141,9 +166,523 @@ def __repr__(self): return "DI-engine DI-star Env" -# if __name__ == '__main__': -# no_target_unit_actions = sorted([action['func_id'] for action in ACTIONS if action['target_unit'] == False]) -# no_target_unit_actions_dict = sorted([action_id for action_id, action in ACTIONS_STAT.items() if len(action['target_type']) == 0]) -# print(no_target_unit_actions) -# print(no_target_unit_actions_dict) -# assert no_target_unit_actions == no_target_unit_actions_dict +def parse_new_game(data, z_path: str, z_idx: Optional[None] = List): + # init Z + z_path = osp.join(osp.dirname(__file__), '../envs', z_path) + with open(z_path, 'r') as f: + z_data = json.load(f) + + raw_ob = data['raw_obs'] + game_info = data['game_info'] + map_size = data['map_size'] + map_name = data['map_name'] + requested_races = { + info.player_id: info.race_requested + for info in game_info.player_info if info.type != sc_pb.Observer + } + location = [] + for i in raw_ob.observation.raw_data.units: + if i.unit_type == 59 or i.unit_type == 18 or i.unit_type == 86: + location.append([i.pos.x, i.pos.y]) + assert len(location) == 1, 'no fog of war, check game version!' + born_location = deepcopy(location[0]) + born_location = location[0] + born_location[0] = int(born_location[0]) + born_location[1] = int(map_size.y - born_location[1]) + born_location_str = str(born_location[0] + born_location[1] * 160) + + z_type = None + idx = None + race = RACE_DICT[requested_races[raw_ob.observation.player_common.player_id]] + opponent_id = 1 if raw_ob.observation.player_common.player_id == 2 else 2 + opponent_race = RACE_DICT[requested_races[opponent_id]] + if race == opponent_race: + mix_race = race + else: + mix_race = race + opponent_race + if z_idx is not None: + idx, z_type = random.choice(z_idx[map_name][mix_race][born_location_str]) + z = z_data[map_name][mix_race][born_location_str][idx] + else: + z = random.choice(z_data[map_name][mix_race][born_location_str]) + + if len(z) == 5: + target_building_order, target_cumulative_stat, bo_location, target_z_loop, z_type = z + else: + target_building_order, target_cumulative_stat, bo_location, target_z_loop = z + return race, map_size, target_building_order, target_cumulative_stat, bo_location, target_z_loop + + +class FeatureUnit(enum.IntEnum): + """Indices for the `feature_unit` observations.""" + unit_type = 0 + alliance = 1 + cargo_space_taken = 2 + build_progress = 3 + health_max = 4 + shield_max = 5 + energy_max = 6 + display_type = 7 + owner = 8 + x = 9 + y = 10 + cloak = 11 + is_blip = 12 + is_powered = 13 + mineral_contents = 14 + vespene_contents = 15 + cargo_space_max = 16 + assigned_harvesters = 17 + weapon_cooldown = 18 + order_length = 19 # If zero, the unit is idle. + order_id_0 = 20 + order_id_1 = 21 + # tag = 22 # Unique identifier for a unit (only populated for raw units). + is_hallucination = 22 + buff_id_0 = 23 + buff_id_1 = 24 + addon_unit_type = 25 + is_active = 26 + order_progress_0 = 27 + order_progress_1 = 28 + order_id_2 = 29 + order_id_3 = 30 + is_in_cargo = 31 + attack_upgrade_level = 32 + armor_upgrade_level = 33 + shield_upgrade_level = 34 + health = 35 + shield = 36 + energy = 37 + + +class MinimapFeatures(collections.namedtuple( + "MinimapFeatures", + ["height_map", "visibility_map", "creep", "player_relative", "alerts", "pathable", "buildable"])): + """The set of minimap feature layers.""" + __slots__ = () + + def __new__(cls, **kwargs): + feats = {} + for name, (scale, type_, palette) in six.iteritems(kwargs): + feats[name] = Feature( + index=MinimapFeatures._fields.index(name), + name=name, + layer_set="minimap_renders", + full_name="minimap " + name, + scale=scale, + type=type_, + palette=palette(scale) if callable(palette) else palette, + clip=False + ) + return super(MinimapFeatures, cls).__new__(cls, **feats) # pytype: disable=missing-parameter + + +MINIMAP_FEATURES = MinimapFeatures( + height_map=(256, FeatureType.SCALAR, colors.height_map), + visibility_map=(4, FeatureType.CATEGORICAL, colors.VISIBILITY_PALETTE), + creep=(2, FeatureType.CATEGORICAL, colors.CREEP_PALETTE), + player_relative=(5, FeatureType.CATEGORICAL, colors.PLAYER_RELATIVE_PALETTE), + alerts=(2, FeatureType.CATEGORICAL, colors.winter), + pathable=(2, FeatureType.CATEGORICAL, colors.winter), + buildable=(2, FeatureType.CATEGORICAL, colors.winter), +) + +SPATIAL_INFO = [ + ('height_map', uint8), ('visibility_map', uint8), ('creep', uint8), ('player_relative', uint8), ('alerts', uint8), + ('pathable', uint8), ('buildable', uint8), ('effect_PsiStorm', int16), ('effect_NukeDot', int16), + ('effect_LiberatorDefenderZone', int16), ('effect_BlindingCloud', int16), ('effect_CorrosiveBile', int16), + ('effect_LurkerSpines', int16) +] + +# (name, dtype, size) +SCALAR_INFO = [ + ('home_race', uint8, ()), ('away_race', uint8, ()), ('upgrades', int16, (NUM_UPGRADES, )), ('time', float32, ()), + ('unit_counts_bow', uint8, (NUM_UNIT_TYPES, )), ('agent_statistics', float32, (10, )), + ('cumulative_stat', uint8, (len(CUMULATIVE_STAT_ACTIONS), )), + ('beginning_order', int16, (BEGINNING_ORDER_LENGTH, )), ('last_queued', int16, ()), ('last_delay', int16, ()), + ('last_action_type', int16, ()), ('bo_location', int16, (BEGINNING_ORDER_LENGTH, )), + ('unit_order_type', uint8, (NUM_UNIT_MIX_ABILITIES, )), ('unit_type_bool', uint8, (NUM_UNIT_TYPES, )), + ('enemy_unit_type_bool', uint8, (NUM_UNIT_TYPES, )) +] + +ENTITY_INFO = [ + ('unit_type', int16), ('alliance', uint8), ('cargo_space_taken', uint8), ('build_progress', float16), + ('health_ratio', float16), ('shield_ratio', float16), ('energy_ratio', float16), ('display_type', uint8), + ('x', uint8), ('y', uint8), ('cloak', uint8), ('is_blip', uint8), ('is_powered', uint8), + ('mineral_contents', float16), ('vespene_contents', float16), ('cargo_space_max', uint8), + ('assigned_harvesters', uint8), ('weapon_cooldown', uint8), ('order_length', uint8), ('order_id_0', int16), + ('order_id_1', int16), ('is_hallucination', uint8), ('buff_id_0', uint8), ('buff_id_1', uint8), + ('addon_unit_type', uint8), ('is_active', uint8), ('order_progress_0', float16), ('order_progress_1', float16), + ('order_id_2', int16), ('order_id_3', int16), ('is_in_cargo', uint8), ('attack_upgrade_level', uint8), + ('armor_upgrade_level', uint8), ('shield_upgrade_level', uint8), ('last_selected_units', int8), + ('last_targeted_unit', int8) +] + +ACTION_INFO = { + 'action_type': torch.tensor(0, dtype=torch.long), + 'delay': torch.tensor(0, dtype=torch.long), + 'queued': torch.tensor(0, dtype=torch.long), + 'selected_units': torch.zeros((MAX_SELECTED_UNITS_NUM, ), dtype=torch.long), + 'target_unit': torch.tensor(0, dtype=torch.long), + 'target_location': torch.tensor(0, dtype=torch.long) +} + +ACTION_LOGP = { + 'action_type': torch.tensor(0, dtype=torch.float), + 'delay': torch.tensor(0, dtype=torch.float), + 'queued': torch.tensor(0, dtype=torch.float), + 'selected_units': torch.zeros((MAX_SELECTED_UNITS_NUM, ), dtype=torch.float), + 'target_unit': torch.tensor(0, dtype=torch.float), + 'target_location': torch.tensor(0, dtype=torch.float) +} + +ACTION_LOGIT = { + 'action_type': torch.zeros(NUM_ACTIONS, dtype=torch.float), + 'delay': torch.zeros(MAX_DELAY + 1, dtype=torch.float), + 'queued': torch.zeros(2, dtype=torch.float), + 'selected_units': torch.zeros((MAX_SELECTED_UNITS_NUM, MAX_ENTITY_NUM + 1), dtype=torch.float), + 'target_unit': torch.zeros(MAX_ENTITY_NUM, dtype=torch.float), + 'target_location': torch.zeros(DEFAULT_SPATIAL_SIZE[0] * DEFAULT_SPATIAL_SIZE[1], dtype=torch.float) +} + + +def compute_battle_score(obs): + if obs is None: + return 0. + score_details = obs.observation.score.score_details + killed_mineral, killed_vespene = 0., 0. + for s in ScoreCategories: + killed_mineral += getattr(score_details.killed_minerals, s.name) + killed_vespene += getattr(score_details.killed_vespene, s.name) + battle_score = killed_mineral + 1.5 * killed_vespene + return battle_score + + +def transform_obs(self, obs, padding_spatial=False, opponent_obs=None): + spatial_info = defaultdict(list) + scalar_info = {} + entity_info = dict() + game_info = {} + + raw = obs.observation.raw_data + # spatial info + for f in MINIMAP_FEATURES: + d = f.unpack(obs.observation).copy() + d = torch.from_numpy(d) + padding_y = DEFAULT_SPATIAL_SIZE[0] - d.shape[0] + padding_x = DEFAULT_SPATIAL_SIZE[1] - d.shape[1] + if (padding_y != 0 or padding_x != 0) and padding_spatial: + d = torch.nn.functional.pad(d, (0, padding_x, 0, padding_y), 'constant', 0) + spatial_info[f.name] = d + for e in raw.effects: + name = Effects(e.effect_id).name + if name in ['LiberatorDefenderZone', 'LurkerSpines'] and e.owner == 1: + continue + for p in e.pos: + location = int(p.x) + int(self.map_size.y - p.y) * DEFAULT_SPATIAL_SIZE[1] + spatial_info['effect_' + name].append(location) + for k, _ in SPATIAL_INFO: + if 'effect' in k: + padding_num = EFFECT_LENGTH - len(spatial_info[k]) + if padding_num > 0: + spatial_info[k] += [0] * padding_num + else: + spatial_info[k] = spatial_info[k][:EFFECT_LENGTH] + spatial_info[k] = torch.as_tensor(spatial_info[k], dtype=int16) + + # entity info + tag_types = {} # Only populate the cache if it's needed. + + def get_addon_type(tag): + if not tag_types: + for u in raw.units: + tag_types[u.tag] = u.unit_type + return tag_types.get(tag, 0) + + tags = [] + units = [] + for u in raw.units: + tags.append(u.tag) + units.append( + [ + u.unit_type, + u.alliance, # Self = 1, Ally = 2, Neutral = 3, Enemy = 4 + u.cargo_space_taken, + u.build_progress, + u.health_max, + u.shield_max, + u.energy_max, + u.display_type, # Visible = 1, Snapshot = 2, Hidden = 3 + u.owner, # 1-15, 16 = neutral + u.pos.x, + u.pos.y, + u.cloak, # Cloaked = 1, CloakedDetected = 2, NotCloaked = 3 + u.is_blip, + u.is_powered, + u.mineral_contents, + u.vespene_contents, + # Not populated for enemies or neutral + u.cargo_space_max, + u.assigned_harvesters, + u.weapon_cooldown, + len(u.orders), + u.orders[0].ability_id if len(u.orders) > 0 else 0, + u.orders[1].ability_id if len(u.orders) > 1 else 0, + u.is_hallucination, + u.buff_ids[0] if len(u.buff_ids) >= 1 else 0, + u.buff_ids[1] if len(u.buff_ids) >= 2 else 0, + get_addon_type(u.add_on_tag) if u.add_on_tag else 0, + u.is_active, + u.orders[0].progress if len(u.orders) >= 1 else 0, + u.orders[1].progress if len(u.orders) >= 2 else 0, + u.orders[2].ability_id if len(u.orders) > 2 else 0, + u.orders[3].ability_id if len(u.orders) > 3 else 0, + 0, + u.attack_upgrade_level, + u.armor_upgrade_level, + u.shield_upgrade_level, + u.health, + u.shield, + u.energy, + ] + ) + for v in u.passengers: + tags.append(v.tag) + units.append( + [ + v.unit_type, + u.alliance, # Self = 1, Ally = 2, Neutral = 3, Enemy = 4 + 0, + 0, + v.health_max, + v.shield_max, + v.energy_max, + 0, # Visible = 1, Snapshot = 2, Hidden = 3 + u.owner, # 1-15, 16 = neutral + u.pos.x, + u.pos.y, + 0, # Cloaked = 1, CloakedDetected = 2, NotCloaked = 3 + 0, + 0, + 0, + 0, + # Not populated for enemies or neutral + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 1, + 0, + 0, + 0, + v.health, + v.shield, + v.energy, + ] + ) + units = units[:MAX_ENTITY_NUM] + tags = tags[:MAX_ENTITY_NUM] + raw_entity_info = named_array.NamedNumpyArray(units, [None, FeatureUnit], dtype=np.float32) + + for k, dtype in ENTITY_INFO: + if 'last' in k: + pass + elif k == 'unit_type': + entity_info[k] = UNIT_TYPES_REORDER_ARRAY[raw_entity_info[:, 'unit_type']].short() + elif 'order_id' in k: + order_idx = int(k.split('_')[-1]) + if order_idx == 0: + entity_info[k] = UNIT_ABILITY_REORDER[raw_entity_info[:, k]].short() + invalid_actions = entity_info[k] == -1 + if invalid_actions.any(): + print('[ERROR] invalid unit ability', raw_entity_info[invalid_actions, k]) + else: + entity_info[k] = ABILITY_TO_QUEUE_ACTION[raw_entity_info[:, k]].short() + invalid_actions = entity_info[k] == -1 + if invalid_actions.any(): + print('[ERROR] invalid queue ability', raw_entity_info[invalid_actions, k]) + elif 'buff_id' in k: + entity_info[k] = BUFFS_REORDER_ARRAY[raw_entity_info[:, k]].short() + elif k == 'addon_unit_type': + entity_info[k] = ADDON_REORDER_ARRAY[raw_entity_info[:, k]].short() + elif k == 'cargo_space_taken': + entity_info[k] = torch.as_tensor(raw_entity_info[:, 'cargo_space_taken'], dtype=dtype).clamp_(min=0, max=8) + elif k == 'cargo_space_max': + entity_info[k] = torch.as_tensor(raw_entity_info[:, 'cargo_space_max'], dtype=dtype).clamp_(min=0, max=8) + elif k == 'health_ratio': + entity_info[k] = torch.as_tensor( + raw_entity_info[:, 'health'], dtype=dtype + ) / (torch.as_tensor(raw_entity_info[:, 'health_max'], dtype=dtype) + 1e-6) + elif k == 'shield_ratio': + entity_info[k] = torch.as_tensor( + raw_entity_info[:, 'shield'], dtype=dtype + ) / (torch.as_tensor(raw_entity_info[:, 'shield_max'], dtype=dtype) + 1e-6) + elif k == 'energy_ratio': + entity_info[k] = torch.as_tensor( + raw_entity_info[:, 'energy'], dtype=dtype + ) / (torch.as_tensor(raw_entity_info[:, 'energy_max'], dtype=dtype) + 1e-6) + elif k == 'mineral_contents': + entity_info[k] = torch.as_tensor(raw_entity_info[:, 'mineral_contents'], dtype=dtype) / 1800 + elif k == 'vespene_contents': + entity_info[k] = torch.as_tensor(raw_entity_info[:, 'vespene_contents'], dtype=dtype) / 2500 + elif k == 'y': + entity_info[k] = torch.as_tensor(self.map_size.y - raw_entity_info[:, 'y'], dtype=dtype) + else: + entity_info[k] = torch.as_tensor(raw_entity_info[:, k], dtype=dtype) + + # scalar info + scalar_info['time'] = torch.tensor(obs.observation.game_loop, dtype=torch.float) + player = obs.observation.player_common + scalar_info['agent_statistics'] = torch.tensor( + [ + player.minerals, player.vespene, player.food_used, player.food_cap, player.food_army, player.food_workers, + player.idle_worker_count, player.army_count, player.warp_gate_count, player.larva_count + ], + dtype=torch.float + ) + scalar_info['agent_statistics'] = torch.log(scalar_info['agent_statistics'] + 1) + + scalar_info["home_race"] = torch.tensor(self._requested_races[player.player_id], dtype=torch.uint8) + for player_id, race in self._requested_races.items(): + if player_id != player.player_id: + scalar_info["away_race"] = torch.tensor(race, dtype=torch.uint8) + + upgrades = torch.zeros(NUM_UPGRADES, dtype=torch.uint8) + raw_upgrades = UPGRADES_REORDER_ARRAY[raw.player.upgrade_ids[:UPGRADE_LENGTH]] + upgrades.scatter_(dim=0, index=raw_upgrades, value=1.) + scalar_info["upgrades"] = upgrades + + unit_counts_bow = torch.zeros(NUM_UNIT_TYPES, dtype=torch.uint8) + scalar_info['unit_type_bool'] = torch.zeros(NUM_UNIT_TYPES, dtype=uint8) + own_unit_types = entity_info['unit_type'][entity_info['alliance'] == 1] + scalar_info['unit_counts_bow'] = torch.scatter_add( + unit_counts_bow, dim=0, index=own_unit_types.long(), src=torch.ones_like(own_unit_types, dtype=torch.uint8) + ) + scalar_info['unit_type_bool'] = (scalar_info['unit_counts_bow'] > 0).to(uint8) + + scalar_info['unit_order_type'] = torch.zeros(NUM_UNIT_MIX_ABILITIES, dtype=uint8) + own_unit_orders = entity_info['order_id_0'][entity_info['alliance'] == 1] + scalar_info['unit_order_type'].scatter_(0, own_unit_orders.long(), torch.ones_like(own_unit_orders, dtype=uint8)) + + enemy_unit_types = entity_info['unit_type'][entity_info['alliance'] == 4] + enemy_unit_type_bool = torch.zeros(NUM_UNIT_TYPES, dtype=torch.uint8) + scalar_info['enemy_unit_type_bool'] = torch.scatter( + enemy_unit_type_bool, + dim=0, + index=enemy_unit_types.long(), + src=torch.ones_like(enemy_unit_types, dtype=torch.uint8) + ) + + # game info + game_info['map_name'] = self._map_name + game_info['action_result'] = [o.result for o in obs.action_errors] + game_info['game_loop'] = obs.observation.game_loop + game_info['tags'] = tags + game_info['battle_score'] = compute_battle_score(obs) + game_info['opponent_battle_score'] = 0. + ret = { + 'spatial_info': spatial_info, + 'scalar_info': scalar_info, + 'entity_num': torch.tensor(len(entity_info['unit_type']), dtype=torch.long), + 'entity_info': entity_info, + 'game_info': game_info, + } + + # value feature + if opponent_obs: + raw = opponent_obs.observation.raw_data + enemy_unit_counts_bow = torch.zeros(NUM_UNIT_TYPES, dtype=torch.uint8) + enemy_x = [] + enemy_y = [] + enemy_unit_type = [] + unit_alliance = [] + for u in raw.units: + if u.alliance == 1: + enemy_x.append(u.pos.x) + enemy_y.append(u.pos.y) + enemy_unit_type.append(u.unit_type) + unit_alliance.append(1) + enemy_unit_type = UNIT_TYPES_REORDER_ARRAY[enemy_unit_type].short() + enemy_unit_counts_bow = torch.scatter_add( + enemy_unit_counts_bow, + dim=0, + index=enemy_unit_type.long(), + src=torch.ones_like(enemy_unit_type, dtype=torch.uint8) + ) + enemy_unit_type_bool = (enemy_unit_counts_bow > 0).to(uint8) + + unit_type = torch.cat([enemy_unit_type, own_unit_types], dim=0) + enemy_x = torch.as_tensor(enemy_x, dtype=uint8) + unit_x = torch.cat([enemy_x, entity_info['x'][entity_info['alliance'] == 1]], dim=0) + + enemy_y = torch.as_tensor(enemy_y, dtype=float32) + enemy_y = torch.as_tensor(self.map_size.y - enemy_y, dtype=uint8) + unit_y = torch.cat([enemy_y, entity_info['y'][entity_info['alliance'] == 1]], dim=0) + total_unit_count = len(unit_y) + unit_alliance += [0] * (total_unit_count - len(unit_alliance)) + unit_alliance = torch.as_tensor(unit_alliance, dtype=torch.bool) + + padding_num = MAX_ENTITY_NUM - total_unit_count + if padding_num > 0: + unit_x = torch.nn.functional.pad(unit_x, (0, padding_num), 'constant', 0) + unit_y = torch.nn.functional.pad(unit_y, (0, padding_num), 'constant', 0) + unit_type = torch.nn.functional.pad(unit_type, (0, padding_num), 'constant', 0) + unit_alliance = torch.nn.functional.pad(unit_alliance, (0, padding_num), 'constant', 0) + else: + unit_x = unit_x[:MAX_ENTITY_NUM] + unit_y = unit_y[:MAX_ENTITY_NUM] + unit_type = unit_type[:MAX_ENTITY_NUM] + unit_alliance = unit_alliance[:MAX_ENTITY_NUM] + + total_unit_count = torch.tensor(total_unit_count, dtype=torch.long) + + player = opponent_obs.observation.player_common + enemy_agent_statistics = torch.tensor( + [ + player.minerals, player.vespene, player.food_used, player.food_cap, player.food_army, + player.food_workers, player.idle_worker_count, player.army_count, player.warp_gate_count, + player.larva_count + ], + dtype=torch.float + ) + enemy_agent_statistics = torch.log(enemy_agent_statistics + 1) + enemy_raw_upgrades = UPGRADES_REORDER_ARRAY[raw.player.upgrade_ids[:UPGRADE_LENGTH]] + enemy_upgrades = torch.zeros(NUM_UPGRADES, dtype=torch.uint8) + enemy_upgrades.scatter_(dim=0, index=enemy_raw_upgrades, value=1.) + + d = MINIMAP_FEATURES.player_relative.unpack(opponent_obs.observation).copy() + d = torch.from_numpy(d) + padding_y = DEFAULT_SPATIAL_SIZE[0] - d.shape[0] + padding_x = DEFAULT_SPATIAL_SIZE[1] - d.shape[1] + if (padding_y != 0 or padding_x != 0) and padding_spatial: + d = torch.nn.functional.pad(d, (0, padding_x, 0, padding_y), 'constant', 0) + enemy_units_spatial = d == 1 + own_units_spatial = ret['spatial_info']['player_relative'] == 1 + value_feature = { + 'unit_type': unit_type, + 'enemy_unit_counts_bow': enemy_unit_counts_bow, + 'enemy_unit_type_bool': enemy_unit_type_bool, + 'unit_x': unit_x, + 'unit_y': unit_y, + 'unit_alliance': unit_alliance, + 'total_unit_count': total_unit_count, + 'enemy_agent_statistics': enemy_agent_statistics, + 'enemy_upgrades': enemy_upgrades, + 'own_units_spatial': own_units_spatial.unsqueeze(dim=0), + 'enemy_units_spatial': enemy_units_spatial.unsqueeze(dim=0) + } + ret['value_feature'] = value_feature + game_info['opponent_battle_score'] = compute_battle_score(opponent_obs) + return ret diff --git a/dizoo/distar/envs/fake_data.py b/dizoo/distar/envs/fake_data.py index 9dfdf2c56a..569ce70031 100644 --- a/dizoo/distar/envs/fake_data.py +++ b/dizoo/distar/envs/fake_data.py @@ -3,9 +3,10 @@ from ding.utils.data import default_collate from .meta import MAX_DELAY, MAX_ENTITY_NUM, NUM_ACTIONS, NUM_UNIT_TYPES, NUM_UPGRADES, NUM_CUMULATIVE_STAT_ACTIONS, \ - NUM_BEGINNING_ORDER_ACTIONS, NUM_UNIT_MIX_ABILITIES, NUM_QUEUE_ACTION, NUM_BUFFS, NUM_ADDON, MAX_SELECTED_UNITS_NUM + NUM_BEGINNING_ORDER_ACTIONS, NUM_UNIT_MIX_ABILITIES, NUM_QUEUE_ACTION, NUM_BUFFS, NUM_ADDON, \ + MAX_SELECTED_UNITS_NUM, DEFAULT_SPATIAL_SIZE -H, W = 152, 160 +H, W = DEFAULT_SPATIAL_SIZE def spatial_info(): diff --git a/dizoo/distar/envs/meta.py b/dizoo/distar/envs/meta.py index bb11787f79..7f6d137206 100644 --- a/dizoo/distar/envs/meta.py +++ b/dizoo/distar/envs/meta.py @@ -10,3 +10,7 @@ NUM_QUEUE_ACTION = 49 NUM_BUFFS = 50 NUM_ADDON = 9 +DEFAULT_SPATIAL_SIZE = [152, 160] +EFFECT_LENGTH = 100 +UPGRADE_LENGTH = 20 +BEGINNING_ORDER_LENGTH = 20 diff --git a/dizoo/distar/policy/distar_policy.py b/dizoo/distar/policy/distar_policy.py index e200ab2dca..90ec735670 100644 --- a/dizoo/distar/policy/distar_policy.py +++ b/dizoo/distar/policy/distar_policy.py @@ -12,13 +12,8 @@ from ding.utils import EasyTimer from ding.utils.data import default_collate, default_decollate from dizoo.distar.model import Model -from dizoo.distar.envs import NUM_UNIT_TYPES, ACTIONS, RACE_DICT, NUM_CUMULATIVE_STAT_ACTIONS, Stat +from dizoo.distar.envs import NUM_UNIT_TYPES, ACTIONS, NUM_CUMULATIVE_STAT_ACTIONS, Stat, parse_new_game, transform_obs from .utils import collate_fn_learn, kl_error, entropy_error -import os -import json -import random -from copy import deepcopy -from s2clientprotocol import sc2api_pb2 as sc_pb class DIStarPolicy(Policy): @@ -363,9 +358,7 @@ def _init_collect(self): self.z_idx = None self._reset_collect() - def _reset_collect(self, game_info, obs, map_name='KingsCove', env_id=0): - self.stat = Stat('zerg') # TODO - self.target_z_loop = 43200 # TODO + def _reset_collect(self, data: Dict, env_id=0): self.exceed_loop_flag = False self.hidden_state = None self.last_action_type = torch.tensor(0, dtype=torch.long) @@ -375,53 +368,15 @@ def _reset_collect(self, game_info, obs, map_name='KingsCove', env_id=0): self.last_targeted_unit_tag = None self.last_location = None # [x, y] self.enemy_unit_type_bool = torch.zeros(NUM_UNIT_TYPES, dtype=torch.uint8) - self.map_name = map_name - self.map_size = None # TODO - self.requested_races = { - info.player_id: info.race_requested - for info in game_info.player_info if info.type != sc_pb.Observer - } - # init Z - raw_ob = obs['raw_obs'] - location = [] - for i in raw_ob.observation.raw_data.units: - if i.unit_type == 59 or i.unit_type == 18 or i.unit_type == 86: - location.append([i.pos.x, i.pos.y]) - assert len(location) == 1, 'no fog of war, check game version!' - self.born_location = deepcopy(location[0]) - born_location = location[0] - born_location[0] = int(born_location[0]) - # TODO(zms): map_size from Features - born_location[1] = int(self.map_size.y - born_location[1]) - born_location_str = str(born_location[0] + born_location[1] * 160) - self.z_path = os.path.join(os.path.dirname(__file__), 'lib', self.z_path) - with open(self.z_path, 'r') as f: - self.z_data = json.load(f) - z_data = self.z_data - - z_type = None - idx = None - raw_ob = obs['raw_obs'] - # TODO(zms): requested_races from Features - race = RACE_DICT[self.requested_races[raw_ob.observation.player_common.player_id]] - opponent_id = 1 if raw_ob.observation.player_common.player_id == 2 else 2 - opponent_race = RACE_DICT[self.requested_races[opponent_id]] - if race == opponent_race: - mix_race = race - else: - mix_race = race + opponent_race - if self.z_idx is not None: - idx, z_type = random.choice(self.z_idx[self.map_name][mix_race][born_location_str]) - z = z_data[self.map_name][mix_race][born_location_str][idx] - else: - z = random.choice(z_data[self.map_name][mix_race][born_location_str]) + race, map_size, target_building_order, target_cumulative_stat, bo_location, target_z_loop = parse_new_game( + data, self.z_path, self.z_idx + ) + self.race = race + self.map_size = map_size + self.target_z_loop = target_z_loop + self.stat = Stat(self.race) - if len(z) == 5: - self.target_building_order, target_cumulative_stat, bo_location, self._target_z_loop, z_type = z - else: - self.target_building_order, target_cumulative_stat, bo_location, self._target_z_loop = z - # TODO(zms): other attributes like use_bo_reward self.target_building_order = torch.tensor(self.target_building_order, dtype=torch.long) self.target_bo_location = torch.tensor(bo_location, dtype=torch.long) self.target_cumulative_stat = torch.zeros(NUM_CUMULATIVE_STAT_ACTIONS, dtype=torch.float) @@ -446,7 +401,6 @@ def _forward_collect(self, data): return policy_output def _data_preprocess_collect(self, data, game_info): - transform_obs = None if self._cfg.use_value_feature: obs = transform_obs(data['raw_obs'], opponent_obs=data['opponent_obs']) else: From 37156d48529041ed9535bd2c96058ca7ae4cce6f Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Thu, 23 Jun 2022 14:07:08 +0800 Subject: [PATCH 148/229] drop get config --- ding/framework/middleware/functional/actor_data.py | 2 ++ ding/framework/middleware/league_actor.py | 14 ++++++++------ .../tests/test_league_actor_one_process.py | 8 ++++---- 3 files changed, 14 insertions(+), 10 deletions(-) diff --git a/ding/framework/middleware/functional/actor_data.py b/ding/framework/middleware/functional/actor_data.py index dc62b2081f..44ba0d7aea 100644 --- a/ding/framework/middleware/functional/actor_data.py +++ b/ding/framework/middleware/functional/actor_data.py @@ -1,6 +1,8 @@ from typing import Any, List from dataclasses import dataclass, field +#TODO(zms): simplify fields + @dataclass class ActorDataMeta: diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 43f8677873..0b8d95334a 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -26,7 +26,7 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.env_fn = env_fn self.env_num = env_fn().env_num self.policy_fn = policy_fn - self.n_rollout_samples = self.cfg.policy.collect.get("n_rollout_samples") or 0 + self.n_rollout_samples = self.cfg.policy.collect.n_rollout_samples self._collectors: Dict[str, BattleEpisodeCollector] = {} self.all_policies: Dict[str, "Policy.collect_function"] = {} task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), self._on_league_job) @@ -120,7 +120,7 @@ def __call__(self, ctx: "BattleContext"): main_player, ctx.current_policies = self._get_current_policies(job) - ctx.n_episode = self.cfg.policy.collect.get("n_episode") or 1 + ctx.n_episode = self.cfg.policy.collect.n_episode assert ctx.n_episode >= self.env_num, "Please make sure n_episode >= env_num" ctx.train_iter = main_player.total_agent_step @@ -130,9 +130,12 @@ def __call__(self, ctx: "BattleContext"): old_envstep = ctx.total_envstep_count time_begin = time.time() collector(ctx) + meta_data = ActorDataMeta( + player_total_env_step=ctx.total_envstep_count, actor_id=task.router.node_id, send_wall_time=time.time() + ) if not job.is_eval and len(ctx.episodes[0]) > 0: - actor_data = ActorData(env_step=ctx.total_envstep_count, train_data=ctx.episodes[0]) + actor_data = ActorData(meta=meta_data, train_data=ctx.episodes[0]) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=job.launch_player), actor_data) ctx.episodes = [] time_end = time.time() @@ -162,8 +165,7 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.env_fn = env_fn self.env_num = env_fn().env_num self.policy_fn = policy_fn - # TODO('self.unroll_len = self.cfg.policy.collect.unroll_len') - self.unroll_len = self.cfg.policy.collect.get("unroll_len") or 0 + self.unroll_len = self.cfg.policy.collect.unroll_len self._collectors: Dict[str, BattleEpisodeCollector] = {} self.all_policies: Dict[str, "Policy.collect_function"] = {} task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), self._on_league_job) @@ -260,7 +262,7 @@ def __call__(self, ctx: "BattleContext"): main_player, ctx.current_policies = self._get_current_policies(job) - ctx.n_episode = self.cfg.policy.collect.get("n_episode") or 1 + ctx.n_episode = self.cfg.policy.collect.n_episode assert ctx.n_episode >= self.env_num, "Please make sure n_episode >= env_num" ctx.train_iter = main_player.total_agent_step diff --git a/ding/framework/middleware/tests/test_league_actor_one_process.py b/ding/framework/middleware/tests/test_league_actor_one_process.py index 90ff5b3420..c91a683372 100644 --- a/ding/framework/middleware/tests/test_league_actor_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_one_process.py @@ -4,7 +4,7 @@ from ding.envs import BaseEnvManager from ding.framework.context import BattleContext from ding.framework.middleware.league_learner import LearnerModel -from ding.framework.middleware.tests.league_config import cfg +from dizoo.distar.config import distar_cfg from ding.framework.middleware import LeagueActor, StepLeagueActor from ding.framework.middleware.functional import ActorData from ding.league.player import PlayerMeta @@ -20,8 +20,8 @@ def prepare_test(): - global cfg - cfg = deepcopy(cfg) + global distar_cfg + cfg = deepcopy(distar_cfg) def env_fn(): env = BaseEnvManager( @@ -43,7 +43,7 @@ def test_league_actor(): cfg, env_fn, policy_fn = prepare_test() policy = policy_fn() with task.start(async_mode=True, ctx=BattleContext()): - league_actor = StepLeagueActor(cfg=cfg, env_fn=env_fn, policy_fn=policy_fn) + league_actor = LeagueActor(cfg=cfg, env_fn=env_fn, policy_fn=policy_fn) def test_actor(): job = Job( From c923c23a26bb3d5a9f1c2c0b0e28e30a78425adc Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Thu, 23 Jun 2022 16:38:31 +0800 Subject: [PATCH 149/229] drop useless remain_episode and ready_env_ids --- ding/framework/context.py | 4 +- .../middleware/functional/collector.py | 9 ++- ding/framework/middleware/league_actor.py | 1 - .../middleware/tests/mock_for_test.py | 56 ++++++++----------- .../test_league_actor_distar_one_process.py | 8 +-- 5 files changed, 34 insertions(+), 44 deletions(-) diff --git a/ding/framework/context.py b/ding/framework/context.py index 9bce71fbcd..97e178a5bd 100644 --- a/ding/framework/context.py +++ b/ding/framework/context.py @@ -92,8 +92,6 @@ def __init__(self, *args, **kwargs) -> None: self.train_iter = 0 self.collect_kwargs = {} self.current_policies = [] - self.ready_env_id = set() - self.remain_episode = 0 #job paras self.player_id_list = [] @@ -111,4 +109,4 @@ def __init__(self, *args, **kwargs) -> None: self.trajectories_list = [] self.train_data = None - self.keep('env_step', 'env_episode', 'train_iter', 'last_eval_iter') + self.keep('train_iter') diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 3f677f626e..af309fe18a 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -114,7 +114,6 @@ def _cut_trajectory_from_episode(self, episode: list): if num_tail_transitions > 0: trajectory = episode[-self._unroll_len:] if len(trajectory) < self._unroll_len: - # TODO(zms): 少于 64 直接删 initial_elements = [] for _ in range(self._unroll_len - len(trajectory)): initial_elements.append(trajectory[0]) @@ -135,7 +134,7 @@ def clear_newest_episode(self, env_id: int) -> None: self._done_episode[env_id].pop() return len_newest_episode - def append(self, env_id: int, transition: Any) -> None: + def append(self, env_id: int, transition: Any) -> bool: # If previous episode is done, we create a new episode if len(self._done_episode[env_id]) == 0 or self._done_episode[env_id][-1] is True: self._transitions[env_id].append([]) @@ -143,6 +142,12 @@ def append(self, env_id: int, transition: Any) -> None: self._transitions[env_id][-1].append(transition) if transition.done: self._done_episode[env_id][-1] = True + if len(self._transitions[env_id][-1]) < self._unroll_len: + newest_episode = self._transitions[env_id].pop() + newest_episode.clear() + self._done_episode[env_id].pop() + return False + return True def clear(self): for item in self._transitions: diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 0b8d95334a..9dffe22587 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -267,7 +267,6 @@ def __call__(self, ctx: "BattleContext"): ctx.train_iter = main_player.total_agent_step ctx.episode_info = [[] for _ in range(self.agent_num)] - ctx.remain_episode = ctx.n_episode while True: time_begin = time.time() diff --git a/ding/framework/middleware/tests/mock_for_test.py b/ding/framework/middleware/tests/mock_for_test.py index eb508ea8e8..fe2ae656c5 100644 --- a/ding/framework/middleware/tests/mock_for_test.py +++ b/ding/framework/middleware/tests/mock_for_test.py @@ -1,6 +1,7 @@ from typing import TYPE_CHECKING, Union, Any, List, Callable, Dict, Optional from collections import namedtuple import random +from numpy import append import torch import treetensor.numpy as tnp from easydict import EasyDict @@ -10,6 +11,7 @@ from ding.league.player import PlayerMeta from ding.league.v2 import BaseLeague, Job from ding.framework.storage import FileStorage +from ding.policy import PPOPolicy from dizoo.distar.envs.distar_env import DIStarEnv from dizoo.distar.policy.distar_policy import DIStarPolicy from ding.envs import BaseEnvManager @@ -186,6 +188,15 @@ def _forward_collect(self, data: Dict[int, Any]) -> Dict[int, Any]: return DIStarEnv.random_action(data) +class DIStarMockPPOPolicy(PPOPolicy): + + def _forward_learn(self, data: Dict[str, Any]) -> Dict[str, Any]: + pass + + def _forward_collect(self, data: Dict[int, Any]) -> Dict[int, Any]: + return DIStarEnv.random_action(data) + + class DIstarCollectMode: def __init__(self) -> None: @@ -237,29 +248,14 @@ def _battle_inferencer(ctx: "BattleContext"): # Get current env obs. obs = env.ready_obs - # { - # env_id: { - # policy_id:{ - # 'raw_obs': - # 'opponent_obs': - # 'action_result': - # } - # } - # } - - # the role of remain_episode is to mask necessary rollouts, avoid processing unnecessary data - # 如果每个 actor 只有一个 env, 下面这部分代码可以全部去掉 - new_available_env_id = set(obs.keys()).difference(ctx.ready_env_id) - ctx.ready_env_id = ctx.ready_env_id.union(set(list(new_available_env_id)[:ctx.remain_episode])) - ctx.remain_episode -= min(len(new_available_env_id), ctx.remain_episode) - obs = {env_id: obs[env_id] for env_id in ctx.ready_env_id} + assert isinstance(obs, dict) ctx.obs = obs # Policy forward. inference_output = {} actions = {} - for env_id in ctx.ready_env_id: + for env_id in ctx.obs.keys(): observations = obs[env_id] inference_output[env_id] = {} actions[env_id] = {} @@ -268,15 +264,6 @@ def _battle_inferencer(ctx: "BattleContext"): output = ctx.current_policies[policy_id].forward(policy_obs) inference_output[env_id][policy_id] = output actions[env_id][policy_id] = output['action'] - # aciton[env_id][policy_id] = { - # 'func_id': func_id, - # 'skip_steps': random.randint(0, MAX_DELAY - 1), - # # 'skip_steps': 8, - # 'queued': random.randint(0, 1), - # 'unit_tags': unit_tags, - # 'target_unit_tag': target_unit_tag, - # 'location': (random.randint(0, SPATIAL_SIZE[0] - 1), random.randint(0, SPATIAL_SIZE[1] - 1)) - # } ctx.inference_output = inference_output ctx.actions = actions @@ -287,10 +274,10 @@ def battle_rolloutor_for_distar(cfg: EasyDict, env: BaseEnvManager, transitions_ def _battle_rolloutor(ctx: "BattleContext"): timesteps = env.step(ctx.actions) - # ctx.total_envstep_count += len(timesteps) ctx.env_step += len(timesteps) + # for env_id, timestep in timesteps.items(): # TODO(zms): make sure a standard # 这里 timestep 是 一个 env_num 长的 list，但是每次step真的会返回所有 env 的 timestep 吗？（需要确认）是就用 dict，否就用 list @@ -301,22 +288,23 @@ def _battle_rolloutor(ctx: "BattleContext"): # ctx.total_envstep_count -= transitions_list[0].length(env_id) # ctx.env_step -= transitions_list[0].length(env_id) - # TODO(zms): 如果要有available_env_id 的话，这里也要更新 - for transitions in transitions_list: - transitions.clear_newest_episode(env_id) + for policy_id, _ in enumerate(ctx.current_policies): + transitions_list[policy_id].clear_newest_episode(env_id) + ctx.current_policies[policy_id].reset([env_id]) continue + append_succeed = True for policy_id, _ in enumerate(ctx.current_policies): transition = ctx.current_policies[policy_id].process_transition(timestep) transition = EasyDict(transition) transition.collect_train_iter = ttorch.as_tensor([ctx.train_iter]) - transitions_list[policy_id].append(env_id, transition) + append_succeed = transitions_list[policy_id].append(env_id, transition) if timestep.done: ctx.current_policies[policy_id].reset([env_id]) - ctx.episode_info[policy_id].append(timestep.info[policy_id]) + if append_succeed: + ctx.episode_info[policy_id].append(timestep.info[policy_id]) - if timestep.done: - ctx.ready_env_id.remove(env_id) + if timestep.done and append_succeed: ctx.env_episode += 1 return _battle_rolloutor diff --git a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py index d44e2e01a8..dc53bfc49a 100644 --- a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py @@ -4,7 +4,7 @@ from ding.envs import BaseEnvManager, EnvSupervisor from ding.framework.context import BattleContext from ding.framework.middleware.league_learner import LearnerModel -from ding.framework.middleware.tests.league_config import cfg +from dizoo.distar.config import distar_cfg from ding.framework.middleware import StepLeagueActor from ding.framework.middleware.functional import ActorData from ding.league.player import PlayerMeta @@ -20,10 +20,10 @@ from distar.ctools.utils import read_config from ding.model import VAC -from ding.framework.middleware.tests import DIStarMockPolicy, DIStarMockPolicyCollect, \ +from ding.framework.middleware.tests import DIStarMockPPOPolicy, DIStarMockPolicyCollect, \ battle_inferencer_for_distar, battle_rolloutor_for_distar -cfg = deepcopy(cfg) +cfg = deepcopy(distar_cfg) env_cfg = read_config('./test_distar_config.yaml') @@ -46,7 +46,7 @@ def get_env_supervisor(cls): @classmethod def policy_fn(cls): model = VAC(**cfg.policy.model) - policy = DIStarMockPolicy(cfg.policy, model=model) + policy = DIStarMockPPOPolicy(cfg.policy, model=model) return policy @classmethod From 5db2b52836b2c6271367d66f78fc6fe28114e5a5 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Thu, 23 Jun 2022 17:14:26 +0800 Subject: [PATCH 150/229] feature(zms): remove the episodes shorter than unroll_len --- .../middleware/functional/collector.py | 20 ++++++++++--------- .../middleware/tests/mock_for_test.py | 17 ++++++++++------ 2 files changed, 22 insertions(+), 15 deletions(-) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index af309fe18a..81632b309a 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -8,6 +8,7 @@ import torch from ding.utils import dicts_to_lists from ding.torch_utils import to_tensor, to_ndarray +from ding.framework import task # if TYPE_CHECKING: from ding.framework import OnlineRLContext, BattleContext @@ -15,6 +16,8 @@ from ding.framework.middleware.functional.actor_data import ActorEnvTrajectories from dizoo.distar.envs.fake_data import rl_step_data +import logging + class TransitionList: @@ -126,12 +129,10 @@ def _cut_trajectory_from_episode(self, episode: list): def clear_newest_episode(self, env_id: int) -> None: # Use it when env.step raise some error - len_newest_episode = 0 - if self._done_episode[env_id][-1] is False: - newest_episode = self._transitions[env_id].pop() - len_newest_episode = len(newest_episode) - newest_episode.clear() - self._done_episode[env_id].pop() + newest_episode = self._transitions[env_id].pop() + len_newest_episode = len(newest_episode) + newest_episode.clear() + self._done_episode[env_id].pop() return len_newest_episode def append(self, env_id: int, transition: Any) -> bool: @@ -143,9 +144,10 @@ def append(self, env_id: int, transition: Any) -> bool: if transition.done: self._done_episode[env_id][-1] = True if len(self._transitions[env_id][-1]) < self._unroll_len: - newest_episode = self._transitions[env_id].pop() - newest_episode.clear() - self._done_episode[env_id].pop() + logging.warning( + 'The length of the newest finished episode in node {}, env {}, is {}, which is shorter than unroll_len: {}, and need to be dropped' + .format(task.router.node_id, env_id, len(self._transitions[env_id][-1]), self._unroll_len) + ) return False return True diff --git a/ding/framework/middleware/tests/mock_for_test.py b/ding/framework/middleware/tests/mock_for_test.py index fe2ae656c5..e176ef7080 100644 --- a/ding/framework/middleware/tests/mock_for_test.py +++ b/ding/framework/middleware/tests/mock_for_test.py @@ -1,7 +1,6 @@ from typing import TYPE_CHECKING, Union, Any, List, Callable, Dict, Optional from collections import namedtuple import random -from numpy import append import torch import treetensor.numpy as tnp from easydict import EasyDict @@ -280,7 +279,7 @@ def _battle_rolloutor(ctx: "BattleContext"): # for env_id, timestep in timesteps.items(): # TODO(zms): make sure a standard - # 这里 timestep 是 一个 env_num 长的 list，但是每次step真的会返回所有 env 的 timestep 吗？（需要确认）是就用 dict，否就用 list + # If for each step, the env manager can't get the obs of all envs, we need to use dict here. for env_id, timestep in enumerate(timesteps): if timestep.info.get('abnormal'): # TODO(zms): cannot get exact env_step of a episode because for each observation, @@ -288,6 +287,7 @@ def _battle_rolloutor(ctx: "BattleContext"): # ctx.total_envstep_count -= transitions_list[0].length(env_id) # ctx.env_step -= transitions_list[0].length(env_id) + # 1st case when env step has bug and need to reset. for policy_id, _ in enumerate(ctx.current_policies): transitions_list[policy_id].clear_newest_episode(env_id) ctx.current_policies[policy_id].reset([env_id]) @@ -298,13 +298,18 @@ def _battle_rolloutor(ctx: "BattleContext"): transition = ctx.current_policies[policy_id].process_transition(timestep) transition = EasyDict(transition) transition.collect_train_iter = ttorch.as_tensor([ctx.train_iter]) - append_succeed = transitions_list[policy_id].append(env_id, transition) + + # 2nd case when the number of transitions in one of all the episodes is shorter than unroll_len + append_succeed = append_succeed and transitions_list[policy_id].append(env_id, transition) if timestep.done: ctx.current_policies[policy_id].reset([env_id]) - if append_succeed: - ctx.episode_info[policy_id].append(timestep.info[policy_id]) + ctx.episode_info[policy_id].append(timestep.info[policy_id]) - if timestep.done and append_succeed: + if not append_succeed: + for policy_id, _ in enumerate(ctx.current_policies): + transitions_list[policy_id].clear_newest_episode(env_id) + ctx.episode_info[policy_id].pop() + elif timestep.done: ctx.env_episode += 1 return _battle_rolloutor From 63ac2df3fba4ce923fa3cbb3cc832d76fd685bf9 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Thu, 23 Jun 2022 17:47:38 +0800 Subject: [PATCH 151/229] get game_info, map_name, map_size inside DIStarEnv.reset() --- dizoo/distar/envs/distar_env.py | 13 +++++++++++-- 1 file changed, 11 insertions(+), 2 deletions(-) diff --git a/dizoo/distar/envs/distar_env.py b/dizoo/distar/envs/distar_env.py index cf78177401..03a3023fd3 100644 --- a/dizoo/distar/envs/distar_env.py +++ b/dizoo/distar/envs/distar_env.py @@ -1,8 +1,10 @@ -from distar.envs.env import SC2Env - from ding.envs import BaseEnv, BaseEnvTimestep + +from distar.envs.env import SC2Env +from distar.envs.map_info import get_map_size from distar.agent.default.lib.features import MAX_DELAY, SPATIAL_SIZE, MAX_SELECTED_UNITS_NUM from distar.pysc2.lib.action_dict import ACTIONS_STAT + import torch import random @@ -14,6 +16,13 @@ def __init__(self, cfg): def reset(self): observations, game_info, map_name = super(DIStarEnv, self).reset() + map_size = get_map_size(map_name) + + for policy_id, policy_obs in observations.items(): + policy_obs['game_info'] = game_info[policy_id] + policy_obs['map_name'] = map_name + policy_obs['map_size'] = map_size + return observations def close(self): From c1cc5afdf7d5405d90db52fedd4992847c4c012d Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Thu, 23 Jun 2022 18:28:05 +0800 Subject: [PATCH 152/229] final_eval_reward --- dizoo/distar/envs/distar_env.py | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/dizoo/distar/envs/distar_env.py b/dizoo/distar/envs/distar_env.py index 03a3023fd3..ed6445bc2b 100644 --- a/dizoo/distar/envs/distar_env.py +++ b/dizoo/distar/envs/distar_env.py @@ -1,3 +1,4 @@ +from ding import policy from ding.envs import BaseEnv, BaseEnvTimestep from distar.envs.env import SC2Env @@ -33,12 +34,14 @@ def step(self, actions): # Here in DI-star, the return is ({'raw_obs': self._obs[agent_idx], 'opponent_obs': opponent_obs, 'action_result': self._action_result[agent_idx]}, reward, episode_complete) next_observations, reward, done = super(DIStarEnv, self).step(actions) # next_observations 和 observations 格式一样 - # reward 是 list [policy reward 1, policy reard 2] + # reward 是 list [policy reward 1, policy reward 2] # done 是 一个 bool 值 # TODO(zms): final_eval_reward 这局赢没赢 info = {} for policy_id in range(self._num_agents): - info[policy_id] = {'result': None} + info[policy_id] = {} + if done: + info[policy_id]['final_eval_reward'] = reward[policy_id] timestep = BaseEnvTimestep(obs=next_observations, reward=reward, done=done, info=info) return timestep From 6aefbe2ccba1067af63f5491e1e1bb1eb52d0673 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Thu, 23 Jun 2022 18:46:23 +0800 Subject: [PATCH 153/229] change a bit --- ding/framework/middleware/collector.py | 6 +++--- dizoo/distar/envs/distar_env.py | 1 - 2 files changed, 3 insertions(+), 4 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 4012ef698a..00c9c91575 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -43,14 +43,14 @@ def __del__(self) -> None: self.env.close() def _update_policies(self, player_id_list) -> None: - # TODO(zms): update train_iter + # TODO(zms): update train_iter, update train_iter and player_id inside policy is a good idea for player_id in player_id_list: if self.model_dict.get(player_id) is None: continue else: learner_model = self.model_dict.get(player_id) policy = self.all_policies.get(player_id) - assert policy, "for player{}, policy should have been initialized already" + assert policy, "for player {}, policy should have been initialized already".format(player_id) # update policy model policy.load_state_dict(learner_model.state_dict) self.model_dict[player_id] = None @@ -121,7 +121,7 @@ def __del__(self) -> None: self.env.close() def _update_policies(self, player_id_list) -> None: - # TODO: 60 秒 没有更新 就阻塞，更新才返回 + # TODO(zms): 60 秒 没有更新 就阻塞，更新才返回 for player_id in player_id_list: if self.model_dict.get(player_id) is None: continue diff --git a/dizoo/distar/envs/distar_env.py b/dizoo/distar/envs/distar_env.py index ed6445bc2b..27e3f9cb12 100644 --- a/dizoo/distar/envs/distar_env.py +++ b/dizoo/distar/envs/distar_env.py @@ -36,7 +36,6 @@ def step(self, actions): # next_observations 和 observations 格式一样 # reward 是 list [policy reward 1, policy reward 2] # done 是 一个 bool 值 - # TODO(zms): final_eval_reward 这局赢没赢 info = {} for policy_id in range(self._num_agents): info[policy_id] = {} From b0a1051196a06657430f06110674f382e5c1d6cc Mon Sep 17 00:00:00 2001 From: lixuelin Date: Thu, 23 Jun 2022 19:25:17 +0800 Subject: [PATCH 154/229] add logging --- ding/framework/context.py | 2 +- .../middleware/functional/data_processor.py | 4 +- ding/framework/middleware/league_actor.py | 59 +++-- .../middleware/league_coordinator.py | 24 +- ding/framework/middleware/league_learner.py | 220 +++++++++--------- ...0326-f2a0-11ec-8459-4649caa90281.SC2Replay | Bin 0 -> 37685 bytes ...c7a4-f2a1-11ec-9ca0-4649caa90281.SC2Replay | Bin 0 -> 31275 bytes ...19a2-f2a5-11ec-aa3e-4649caa90281.SC2Replay | Bin 0 -> 27882 bytes ...0152-f2a6-11ec-91ba-4649caa90281.SC2Replay | Bin 0 -> 30063 bytes ...3286-f2a7-11ec-8470-4649caa90281.SC2Replay | Bin 0 -> 28645 bytes 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100644 ding/framework/middleware/tests/2022-06-23-13/KingsCove_agent1_vs_agent2_[0, 0]_2022-06-23-05-27-46_36d4ff90-f2b5-11ec-86b3-4649caa90281.SC2Replay create mode 100644 ding/framework/middleware/tests/2022-06-23-13/KingsCove_agent1_vs_agent2_[0, 0]_2022-06-23-05-32-50_ebe3669c-f2b5-11ec-86b3-4649caa90281.SC2Replay create mode 100644 ding/framework/middleware/tests/2022-06-23-19/KingsCove_agent1_vs_agent2_[0, 0]_2022-06-23-11-24-59_1e3586ee-f2e7-11ec-99fe-4649caa90281.SC2Replay create mode 100644 ding/utils/sparse_logging.py create mode 100644 ding/utils/tests/test_sparse_logging.py diff --git a/ding/framework/context.py b/ding/framework/context.py index 9bce71fbcd..bf2b54f970 100644 --- a/ding/framework/context.py +++ b/ding/framework/context.py @@ -111,4 +111,4 @@ def __init__(self, *args, **kwargs) -> None: self.trajectories_list = [] self.train_data = None - self.keep('env_step', 'env_episode', 'train_iter', 'last_eval_iter') + self.keep('train_iter') diff --git a/ding/framework/middleware/functional/data_processor.py b/ding/framework/middleware/functional/data_processor.py index bc1700049b..88185839fb 100644 --- a/ding/framework/middleware/functional/data_processor.py +++ b/ding/framework/middleware/functional/data_processor.py @@ -6,6 +6,7 @@ from ding.data import Buffer, Dataset, DataLoader, offline_data_save_type from ding.data.buffer.middleware import PriorityExperienceReplay from ding.framework import task +from ding.utils.sparse_logging import log_every_sec if TYPE_CHECKING: from ding.framework import Context, OnlineRLContext, OfflineRLContext @@ -113,7 +114,8 @@ def _fetch(ctx: "OnlineRLContext"): assert buffered_data is not None except (ValueError, AssertionError): # You can modify data collect config to avoid this warning, e.g. increasing n_sample, n_episode. - logging.warning( + log_every_sec( + logging.warning, 10, "Replay buffer's data is not enough to support training, so skip this training for waiting more data." ) ctx.train_data = None diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 43f8677873..724b2fe26d 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -1,5 +1,5 @@ from ding.framework import task, EventEnum -import logging +from ditk import logging from typing import TYPE_CHECKING, Dict, Callable from ding.league import player @@ -13,6 +13,8 @@ from easydict import EasyDict import time +from ding.utils.sparse_logging import log_every_sec + if TYPE_CHECKING: from ding.league.v2.base_league import Job from ding.framework import BattleContext @@ -42,7 +44,7 @@ def _on_learner_model(self, learner_model: "LearnerModel"): """ If get newest learner model, put it inside model_queue. """ - print("Actor {} receive model from learner \n".format(task.router.node_id), flush=True) + log_every_sec(logging.INFO, 5, "[Actor {}] receive model from learner \n".format(task.router.node_id)) with self.model_dict_lock: self.model_dict[learner_model.player_id] = learner_model @@ -86,7 +88,7 @@ def _get_job(self): try: job = self.job_queue.get(timeout=10) except queue.Empty: - logging.warning("For actor_{}, no Job get from coordinator".format(task.router.node_id)) + logging.warning("[Actor {}] no Job got from coordinator".format(task.router.node_id)) return job @@ -97,7 +99,7 @@ def _get_current_policies(self, job): current_policies.append(self._get_policy(player)) if player.player_id == job.launch_player: main_player = player - assert main_player, "can not find active player, on actor: {}".format(task.router.node_id) + assert main_player, "[Actor {}] cannot find active player.".format(task.router.node_id) if current_policies is not None: assert len(current_policies) > 1, "battle collector needs more than 1 policies" @@ -121,7 +123,9 @@ def __call__(self, ctx: "BattleContext"): main_player, ctx.current_policies = self._get_current_policies(job) ctx.n_episode = self.cfg.policy.collect.get("n_episode") or 1 - assert ctx.n_episode >= self.env_num, "Please make sure n_episode >= env_num" + assert ctx.n_episode >= self.env_num, "[Actor {}] Please make sure n_episode >= env_num".format( + task.router.node_id + ) ctx.train_iter = main_player.total_agent_step ctx.episode_info = [[] for _ in range(self.agent_num)] @@ -141,8 +145,9 @@ def __call__(self, ctx: "BattleContext"): job.launch_player] != 0 else 0 envstep_passed = ctx.total_envstep_count - old_envstep real_time_speed = envstep_passed / (time_end - time_begin) - print( - 'in actor {}, total_env_step:{}, current job env_step: {}, total_collect_speed: {} env_step/s, real-time collect speed: {} env_step/s' + log_every_sec( + logging.INFO, 5, + '[Actor {}] total_env_step:{}, current job env_step: {}, total_collect_speed: {} env_step/s, real-time collect speed: {} env_step/s' .format( task.router.node_id, ctx.total_envstep_count, ctx.env_step, total_collect_speed, real_time_speed ) @@ -182,7 +187,9 @@ def _on_learner_model(self, learner_model: "LearnerModel"): """ If get newest learner model, put it inside model_queue. """ - print('Actor {} recieved model {} \n'.format(task.router.node_id, learner_model.player_id), flush=True) + log_every_sec( + logging.INFO, 5, '[Actor {}] recieved model {}'.format(task.router.node_id, learner_model.player_id) + ) with self.model_dict_lock: self.model_dict[learner_model.player_id] = learner_model @@ -225,7 +232,7 @@ def _get_job(self): try: job = self.job_queue.get(timeout=10) except queue.Empty: - logging.warning("For actor {}, no Job get from coordinator".format(task.router.node_id)) + logging.warning("[Actor {}] no Job got from coordinator.".format(task.router.node_id)) return job @@ -236,14 +243,16 @@ def _get_current_policies(self, job): current_policies.append(self._get_policy(player)) if player.player_id == job.launch_player: main_player = player - assert main_player, "can not find active player, on actor: {}".format(task.router.node_id) + assert main_player, "[Actor {}] can not find active player.".format(task.router.node_id) if current_policies is not None: - assert len(current_policies) > 1, "battle collector needs more than 1 policies" + assert len(current_policies) > 1, "[Actor {}] battle collector needs more than 1 policies".format( + task.router.node_id + ) for p in current_policies: p.reset() else: - raise RuntimeError('current_policies should not be None') + raise RuntimeError('[Actor {}] current_policies should not be None'.format(task.router.node_id)) return main_player, current_policies @@ -252,7 +261,9 @@ def __call__(self, ctx: "BattleContext"): job = self._get_job() if job is None: return - print('For actor {}, a job {} begin \n'.format(task.router.node_id, job.launch_player), flush=True) + log_every_sec( + logging.INFO, 5, '[Actor {}] job of player {} begins.'.format(task.router.node_id, job.launch_player) + ) ctx.player_id_list = [player.player_id for player in job.players] self.agent_num = len(job.players) @@ -261,7 +272,9 @@ def __call__(self, ctx: "BattleContext"): main_player, ctx.current_policies = self._get_current_policies(job) ctx.n_episode = self.cfg.policy.collect.get("n_episode") or 1 - assert ctx.n_episode >= self.env_num, "Please make sure n_episode >= env_num" + assert ctx.n_episode >= self.env_num, "[Actor {}] Please make sure n_episode >= env_num".format( + task.router.node_id + ) ctx.train_iter = main_player.total_agent_step ctx.episode_info = [[] for _ in range(self.agent_num)] @@ -272,19 +285,20 @@ def __call__(self, ctx: "BattleContext"): old_envstep = ctx.total_envstep_count collector(ctx) - # print(ctx.trajectories_list) # ctx.trajectories_list[0] for policy_id 0 # ctx.trajectories_list[0][0] for first env if len(ctx.trajectories_list[0]) > 0: for traj in ctx.trajectories_list[0][0].trajectories: assert len(traj) == self.unroll_len + 1 if ctx.job_finish is True: - print('we finish the job !') + logging.info('[Actor {}] finish current job !'.format(task.router.node_id)) assert len(ctx.trajectories_list[0][0].trajectories) > 0 # TODO(zms): 判断是不是main_player if not job.is_eval and len(ctx.trajectories_list[0]) > 0: trajectories = ctx.trajectories_list[0] - print('actor {}, {} envs send traj '.format(task.router.node_id, len(trajectories)), flush=True) + log_every_sec( + logging.INFO, 5, '[Actor {}] send {} trajectories.'.format(task.router.node_id, len(trajectories)) + ) meta_data = ActorDataMeta( player_total_env_step=ctx.total_envstep_count, actor_id=task.router.node_id, @@ -292,7 +306,7 @@ def __call__(self, ctx: "BattleContext"): ) actor_data = ActorData(meta=meta_data, train_data=trajectories) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=job.launch_player), actor_data) - print('Actor {} send data\n'.format(task.router.node_id), flush=True) + log_every_sec(logging.INFO, 5, '[Actor {}] send data\n'.format(task.router.node_id)) ctx.trajectories_list = [] time_end = time.time() @@ -301,16 +315,17 @@ def __call__(self, ctx: "BattleContext"): job.launch_player] != 0 else 0 envstep_passed = ctx.total_envstep_count - old_envstep real_time_speed = envstep_passed / (time_end - time_begin) - print( - 'in actor {}, total_env_step: {}, current job env_step: {}, total_collect_speed: {} env_step/s, real-time collect speed: {} env_step/s' + log_every_sec( + logging.INFO, 5, + '[Actor {}] total_env_step: {}, current job env_step: {}, total_collect_speed: {} env_step/s, real-time collect speed: {} env_step/s' .format( task.router.node_id, ctx.total_envstep_count, ctx.env_step, total_collect_speed, real_time_speed ) ) if ctx.job_finish is True: - job.result = None + job.result = [['wins']] task.emit(EventEnum.ACTOR_FINISH_JOB, job) ctx.episode_info = [[] for _ in range(self.agent_num)] - print('Actor {} job finish, send job\n'.format(task.router.node_id), flush=True) + logging.info('[Actor {}] job finish, send job\n'.format(task.router.node_id)) break diff --git a/ding/framework/middleware/league_coordinator.py b/ding/framework/middleware/league_coordinator.py index 80f5d7a9c1..9c269f434a 100644 --- a/ding/framework/middleware/league_coordinator.py +++ b/ding/framework/middleware/league_coordinator.py @@ -4,7 +4,9 @@ from dataclasses import dataclass from typing import TYPE_CHECKING from ding.framework import task, EventEnum -import logging +from ditk import logging + +from ding.utils.sparse_logging import log_every_sec if TYPE_CHECKING: from easydict import EasyDict @@ -21,13 +23,14 @@ def __init__(self, cfg: "EasyDict", league: "BaseLeague") -> None: self._lock = Lock() self._total_send_jobs = 0 self._eval_frequency = 10 + self._running_jobs = dict() task.on(EventEnum.ACTOR_GREETING, self._on_actor_greeting) task.on(EventEnum.LEARNER_SEND_META, self._on_learner_meta) task.on(EventEnum.ACTOR_FINISH_JOB, self._on_actor_job) def _on_actor_greeting(self, actor_id): - print('coordinator recieve actor {} greeting\n'.format(actor_id), flush=True) + logging.info("[Coordinator {}] recieve actor {} greeting".format(task.router.node_id, actor_id)) with self._lock: player_num = len(self.league.active_players_ids) player_id = self.league.active_players_ids[self._total_send_jobs % player_num] @@ -37,21 +40,28 @@ def _on_actor_greeting(self, actor_id): if job.job_no > 0 and job.job_no % self._eval_frequency == 0: job.is_eval = True job.actor_id = actor_id - print('coordinator emit job (main_player: {}) to actor {}\n'.format(job.launch_player, actor_id), flush=True) + self._running_jobs["actor_{}".format(actor_id)] = job task.emit(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=actor_id), job) def _on_learner_meta(self, player_meta: "PlayerMeta"): - print('coordinator recieve learner meta for player{}\n'.format(player_meta.player_id), flush=True) + log_every_sec( + logging.INFO, 5, + '[Coordinator {}] recieve learner meta from player {}'.format(task.router.node_id, player_meta.player_id) + ) self.league.update_active_player(player_meta) self.league.create_historical_player(player_meta) def _on_actor_job(self, job: "Job"): - print('coordinator recieve actor finished job, palyer {}\n'.format(job.launch_player), flush=True) - print("on_actor_job {}\n".format(job.launch_player)) # right + logging.info( + "[Coordinator {}] recieve actor finished job, player {}".format(task.router.node_id, job.launch_player) + ) self.league.update_payoff(job) def __del__(self): - print('task finished, coordinator {} closed'.format(task.router.node_id), flush=True) + logging.info("[Coordinator {}] all tasks finished, coordinator closed".format(task.router.node_id)) def __call__(self, ctx: "Context") -> None: sleep(1) + log_every_sec( + logging.INFO, 30, "[Coordinator {}] running jobs {}".format(task.router.node_id, self._running_jobs) + ) diff --git a/ding/framework/middleware/league_learner.py b/ding/framework/middleware/league_learner.py index d0be9a1c91..5b97be1b96 100644 --- a/ding/framework/middleware/league_learner.py +++ b/ding/framework/middleware/league_learner.py @@ -1,3 +1,4 @@ +from ditk import logging import os from dataclasses import dataclass from collections import deque @@ -10,6 +11,7 @@ from ding.framework.middleware import OffPolicyLearner, CkptSaver, data_pusher from ding.framework.storage import Storage, FileStorage from ding.league.player import PlayerMeta +from ding.utils.sparse_logging import log_every_sec from ding.worker.learner.base_learner import BaseLearner if TYPE_CHECKING: @@ -38,23 +40,28 @@ def __init__(self, cfg: dict, policy: "Policy", player: "ActivePlayer") -> None: task.on(EventEnum.ACTOR_SEND_DATA.format(player=self.player_id), self._push_data) def _push_data(self, data: "ActorData"): - print("learner {} receive data from actor! \n".format(task.router.node_id), flush=True) + log_every_sec( + logging.INFO, 5, + "[Learner {}] receive data of player {} from actor! \n".format(task.router.node_id, self.player_id) + ) for env_trajectories in data.train_data: for traj in env_trajectories.trajectories: self._cache.append(traj) - # self._cache.append(data.train_data) + # if isinstance(data.train_data, list): + # self._cache.extend(data.train_data) + # else: + # self._cache.append(data.train_data) def __call__(self, ctx: "Context"): - # print("push data into the ctx") + log_every_sec(logging.INFO, 5, "[Learner {}] pour data into the ctx".format(task.router.node_id)) ctx.trajectories = list(self._cache) self._cache.clear() - sleep(1) + sleep(0.1) yield - # print("Learner: save model, ctx.train_iter:", ctx.train_iter) + log_every_sec(logging.INFO, 5, "[Learner {}] ctx.train_iter {}".format(task.router.node_id, ctx.train_iter)) self.player.total_agent_step = ctx.train_iter if self.player.is_trained_enough(): - print('trained enough!') - print('----------------------------------------------------------------------------------') + logging.info('{1} [Learner {0}] trained enough! {1} \n\n'.format(task.router.node_id, "-" * 40)) storage = FileStorage( path=os.path.join(self.prefix, "{}_{}_ckpt.pth".format(self.player_id, ctx.train_iter)) ) @@ -70,103 +77,102 @@ def __call__(self, ctx: "Context"): task.emit(EventEnum.LEARNER_SEND_MODEL, learner_model) -class OffPolicyLeagueLearner: - - def __init__(self, cfg: dict, policy_fn: Callable, player: "ActivePlayer") -> None: - self._buffer = DequeBuffer(size=10000) - self._policy = policy_fn().learn_mode - self.player_id = player.player_id - task.on(EventEnum.ACTOR_SEND_DATA.format(player=self.player_id), self._push_data) - self._learner = OffPolicyLearner(cfg, self._policy, self._buffer) - # self._ckpt_handler = CkptSaver(cfg, self._policy, train_freq=100) - - def _push_data(self, data: "ActorData"): - print("push data into the buffer!") - self._buffer.push(data.train_data) - - def __call__(self, ctx: "Context"): - print("num of objects in buffer:", self._buffer.count()) - self._learner(ctx) - checkpoint = None - - sleep(2) - print('learner send player meta\n', flush=True) - task.emit( - EventEnum.LEARNER_SEND_META, - PlayerMeta(player_id=self.player_id, checkpoint=checkpoint, total_agent_step=0) - ) - - learner_model = LearnerModel( - player_id=self.player_id, - state_dict=self._policy.state_dict(), - train_iter=ctx.train_iter # self._policy.state_dict() - ) - print('learner send model\n', flush=True) - task.emit(EventEnum.LEARNER_SEND_MODEL, learner_model) - - -class LeagueLearner: - - def __init__(self, cfg: dict, policy_fn: Callable, player: "ActivePlayer") -> None: - self.cfg = cfg - self.policy_fn = policy_fn - self.player = player - self.player_id = player.player_id - self.checkpoint_prefix = cfg.policy.other.league.path_policy - self._learner = self._get_learner() - self._lock = Lock() - task.on(EventEnum.ACTOR_SEND_DATA.format(player=self.player_id), self._on_actor_send_data) - self._step = 0 - - def _on_actor_send_data(self, actor_data: "ActorData"): - print("learner {} receive data from actor! \n".format(task.router.node_id), flush=True) - with self._lock: - cfg = self.cfg - for _ in range(cfg.policy.learn.update_per_collect): - pass - # print("train model") - # print(actor_data.train_data) - # self._learner.train(actor_data.train_data, actor_data.env_step) - - self.player.total_agent_step = self._learner.train_iter - # print("save checkpoint") - checkpoint = self._save_checkpoint() if self.player.is_trained_enough() else None - - print('learner {} send player meta {}\n'.format(task.router.node_id, self.player_id), flush=True) - task.emit( - EventEnum.LEARNER_SEND_META, - PlayerMeta(player_id=self.player_id, checkpoint=checkpoint, total_agent_step=self._learner.train_iter) - ) - - # print("pack model") - learner_model = LearnerModel( - player_id=self.player_id, state_dict=self._learner.policy.state_dict(), train_iter=self._learner.train_iter - ) - print('learner {} send model\n'.format(task.router.node_id), flush=True) - task.emit(EventEnum.LEARNER_SEND_MODEL, learner_model) - - def _get_learner(self) -> BaseLearner: - policy = self.policy_fn().learn_mode - learner = BaseLearner( - self.cfg.policy.learn.learner, - policy, - exp_name=self.cfg.exp_name, - instance_name=self.player_id + '_learner' - ) - return learner - - def _save_checkpoint(self) -> Optional[Storage]: - if not os.path.exists(self.checkpoint_prefix): - os.makedirs(self.checkpoint_prefix) - storage = FileStorage( - path=os.path. - join(self.checkpoint_prefix, "{}_{}_ckpt.pth".format(self.player_id, self._learner.train_iter)) - ) - storage.save(self._learner.policy.state_dict()) - return storage - - def __del__(self): - print('task finished, learner {} closed\n'.format(task.router.node_id), flush=True) - - def __call__(self, _: "Context") -> None: - sleep(1) +# class OffPolicyLeagueLearner: + +# def __init__(self, cfg: dict, policy_fn: Callable, player: "ActivePlayer") -> None: +# self._buffer = DequeBuffer(size=10000) +# self._policy = policy_fn().learn_mode +# self.player_id = player.player_id +# task.on(EventEnum.ACTOR_SEND_DATA.format(player=self.player_id), self._push_data) +# self._learner = OffPolicyLearner(cfg, self._policy, self._buffer) +# # self._ckpt_handler = CkptSaver(cfg, self._policy, train_freq=100) + +# def _push_data(self, data: "ActorData"): +# print("push data into the buffer!") +# self._buffer.push(data.train_data) + +# def __call__(self, ctx: "Context"): +# print("num of objects in buffer:", self._buffer.count()) +# self._learner(ctx) +# checkpoint = None + +# sleep(2) +# print('learner send player meta\n', flush=True) +# task.emit( +# EventEnum.LEARNER_SEND_META, +# PlayerMeta(player_id=self.player_id, checkpoint=checkpoint, total_agent_step=0) +# ) + +# learner_model = LearnerModel( +# player_id=self.player_id, +# state_dict=self._policy.state_dict(), +# train_iter=ctx.train_iter # self._policy.state_dict() +# ) +# print('learner send model\n', flush=True) +# task.emit(EventEnum.LEARNER_SEND_MODEL, learner_model) + +# class LeagueLearner: + +# def __init__(self, cfg: dict, policy_fn: Callable, player: "ActivePlayer") -> None: +# self.cfg = cfg +# self.policy_fn = policy_fn +# self.player = player +# self.player_id = player.player_id +# self.checkpoint_prefix = cfg.policy.other.league.path_policy +# self._learner = self._get_learner() +# self._lock = Lock() +# task.on(EventEnum.ACTOR_SEND_DATA.format(player=self.player_id), self._on_actor_send_data) +# self._step = 0 + +# def _on_actor_send_data(self, actor_data: "ActorData"): +# logging.info("learner {} receive data from actor! \n".format(task.router.node_id), flush=True) +# with self._lock: +# cfg = self.cfg +# for _ in range(cfg.policy.learn.update_per_collect): +# pass +# # print("train model") +# # print(actor_data.train_data) +# # self._learner.train(actor_data.train_data, actor_data.env_step) + +# self.player.total_agent_step = self._learner.train_iter +# # print("save checkpoint") +# checkpoint = self._save_checkpoint() if self.player.is_trained_enough() else None + +# print('learner {} send player meta {}\n'.format(task.router.node_id, self.player_id), flush=True) +# task.emit( +# EventEnum.LEARNER_SEND_META, +# PlayerMeta(player_id=self.player_id, checkpoint=checkpoint, total_agent_step=self._learner.train_iter) +# ) + +# # print("pack model") +# learner_model = LearnerModel( +# player_id=self.player_id, state_dict=self._learner.policy.state_dict(), train_iter=self._learner.train_iter +# ) +# print('learner {} send model\n'.format(task.router.node_id), flush=True) +# task.emit(EventEnum.LEARNER_SEND_MODEL, learner_model) + +# def _get_learner(self) -> BaseLearner: +# policy = self.policy_fn().learn_mode +# learner = BaseLearner( +# self.cfg.policy.learn.learner, +# policy, +# exp_name=self.cfg.exp_name, +# instance_name=self.player_id + '_learner' +# ) +# return learner + +# def _save_checkpoint(self) -> Optional[Storage]: +# if not os.path.exists(self.checkpoint_prefix): +# os.makedirs(self.checkpoint_prefix) +# storage = FileStorage( +# path=os.path. +# join(self.checkpoint_prefix, "{}_{}_ckpt.pth".format(self.player_id, self._learner.train_iter)) +# ) +# storage.save(self._learner.policy.state_dict()) +# return storage + +# def __del__(self): +# print('task finished, learner {} closed\n'.format(task.router.node_id), flush=True) + +# def __call__(self, _: "Context") -> None: +# sleep(1) diff --git a/ding/framework/middleware/tests/2022-06-23-10/KingsCove_agent1_vs_agent2_[0, 0]_2022-06-23-02-57-22_345d0326-f2a0-11ec-8459-4649caa90281.SC2Replay b/ding/framework/middleware/tests/2022-06-23-10/KingsCove_agent1_vs_agent2_[0, 0]_2022-06-23-02-57-22_345d0326-f2a0-11ec-8459-4649caa90281.SC2Replay new file mode 100644 index 0000000000000000000000000000000000000000..c8ef8006f963155f70cf13d85b89709ebaa53c81 GIT binary patch literal 37685 zcmeFXWl)^Y)-O7^%b>#`8DMaS!3n_`WN>$PmjHnzgS$)c;O?#o1ShxzcMGl|5Fsc3 z_dUC6pHrvKy`S!vyH`EctF^kH-&(!as_sT;Xi@`E0RR9x0O0+XVUPe&IkkN(y=1*C z?R+3gN)Rtw4;RY-YCb+x4153%Dk=^(Iu02o4gecxE*}T?p9CET9TR6F4Idj51s4Mq z6&2EvW9nZ1`Cgveixl{=$E6AXpI(Ij)%16Y|AmM#|Ci!_3jaaiKM4GPhyX%E6Fl>G zKEXr)01bcv5RChqPXGWQf9r_q*G 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zzT2`rou8O#pXnbFmr@w96HUE&6!aMPEnGS=UiN8#Q_|IaIuo>m9VT{h12y_!j^thwYDJh;i92Qc` z!-WhSG6Y8&++b1D`}BSi$?wGb-08_rt>@?5ekdQ~#y9)*R53}!N8Mu$lYSF+G Dict[str, Any]: - print("Call forward_learn:") + print("Call forward_learn:", flush=True) return super()._forward_learn(data) def _forward_collect(self, data: Dict[int, Any]) -> Dict[int, Any]: diff --git a/ding/framework/middleware/tests/test_league_learner.py b/ding/framework/middleware/tests/test_league_learner.py index 5e80e251f7..2a8bee0d30 100644 --- a/ding/framework/middleware/tests/test_league_learner.py +++ b/ding/framework/middleware/tests/test_league_learner.py @@ -1,9 +1,10 @@ from copy import deepcopy from dataclasses import dataclass from time import sleep -import torch +import time import pytest import logging +from typing import Any from ding.data import DequeBuffer from ding.envs import BaseEnvManager @@ -11,18 +12,14 @@ from ding.framework import EventEnum from ding.framework.task import task, Parallel from ding.framework.middleware import data_pusher, OffPolicyLearner, LeagueLearnerCommunicator -from ding.framework.middleware.functional.actor_data import ActorData, ActorDataMeta, ActorEnvTrajectories -from dizoo.distar.config import distar_cfg +from ding.framework.middleware.functional.actor_data import * from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy from ding.league.v2 import BaseLeague +from ding.utils import run_every_s from dizoo.distar.config import distar_cfg -from dizoo.distar.envs import get_fake_rl_trajectory, fake_rl_data_batch_with_last +from dizoo.distar.envs import fake_rl_data_batch_with_last from dizoo.distar.envs.distar_env import DIStarEnv from distar.ctools.utils import read_config -import time -from typing import Any - -logging.getLogger().setLevel(logging.INFO) def prepare_test(): @@ -46,8 +43,8 @@ def policy_fn(): def coordinator_mocker(): - task.on(EventEnum.LEARNER_SEND_META, lambda x: print("test:", x)) - task.on(EventEnum.LEARNER_SEND_MODEL, lambda x: print("test: send model success")) + task.on(EventEnum.LEARNER_SEND_META, lambda x: run_every_s("test:", x)) + task.on(EventEnum.LEARNER_SEND_MODEL, lambda x: run_every_s("test: send model success")) def _coordinator_mocker(ctx): sleep(10) @@ -66,13 +63,11 @@ def actor_mocker(league): def _actor_mocker(ctx): n_players = len(league.active_players_ids) player = league.active_players[(task.router.node_id + 2) % n_players] - print("Actor: actor player:", player.player_id) + run_every_s(5, "Actor: actor player:", player.player_id) for _ in range(24): meta = ActorDataMeta(player_total_env_step=0, actor_id=0, send_wall_time=time.time()) data = fake_rl_data_batch_with_last() actor_data = ActorData(meta=meta, train_data=[ActorEnvTrajectories(env_id=0, trajectories=[data])]) - - # data = fake_rl_data_batch_with_last() # actor_data = TestActorData(env_step=0, train_data=data) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=player.player_id), actor_data) sleep(9) @@ -81,9 +76,11 @@ def _actor_mocker(ctx): def _main(): - logging.disable(logging.WARNING) + logging.getLogger().setLevel(logging.DEBUG) cfg, env_fn, policy_fn = prepare_test() league = BaseLeague(cfg.policy.other.league) + n_players = len(league.active_players_ids) + print("League: n_players: ", n_players) with task.start(async_mode=True, ctx=BattleContext()): if task.router.node_id == 0: @@ -93,8 +90,6 @@ def _main(): else: cfg.policy.collect.unroll_len = 1 buffer_ = DequeBuffer(size=cfg.policy.other.replay_buffer.replay_buffer_size) - n_players = len(league.active_players_ids) - print("League: n_players: ", n_players) player = league.active_players[task.router.node_id % n_players] policy = policy_fn() task.use(LeagueLearnerCommunicator(cfg, policy.learn_mode, player)) diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index e02906358a..a5e488f9ec 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -66,8 +66,7 @@ def collect_policy_fn(cls): def main(): - logging.disable(logging.WARNING) - # cfg, env_fn, policy_fn, collect_policy_fn = prepare_test() + logging.getLogger().setLevel(logging.INFO) league = BaseLeague(cfg.policy.other.league) N_PLAYERS = len(league.active_players_ids) print("League: n_players =", N_PLAYERS) @@ -97,8 +96,8 @@ def main(): @pytest.mark.unittest def test_league_pipeline(): - Parallel.runner(n_parallel_workers=4, protocol="tcp", topology="mesh")(main) + Parallel.runner(n_parallel_workers=3, protocol="tcp", topology="mesh")(main) if __name__ == "__main__": - Parallel.runner(n_parallel_workers=4, protocol="tcp", topology="mesh")(main) + Parallel.runner(n_parallel_workers=3, protocol="tcp", topology="mesh")(main) diff --git a/ding/utils/__init__.py b/ding/utils/__init__.py index b4229c4982..b0d8508cb6 100644 --- a/ding/utils/__init__.py +++ b/ding/utils/__init__.py @@ -29,6 +29,7 @@ from .type_helper import SequenceType from .render_helper import render, fps from .fast_copy import fastcopy +from .sparse_logging import log_every_n, log_every_sec if ding.enable_linklink: from .linklink_dist_helper import get_rank, get_world_size, dist_mode, dist_init, dist_finalize, \ diff --git a/ding/utils/data/collate_fn.py b/ding/utils/data/collate_fn.py index a6c61f8d1b..dd41637016 100644 --- a/ding/utils/data/collate_fn.py +++ b/ding/utils/data/collate_fn.py @@ -7,6 +7,7 @@ from torch._six import string_classes import collections.abc as container_abcs from ding.compatibility import torch_ge_131 +from easydict import EasyDict int_classes = int np_str_obj_array_pattern = re.compile(r'[SaUO]') @@ -62,6 +63,13 @@ def default_collate( """ elem = batch[0] + # if isinstance(elem, dict): + # for key, val in elem.items(): + # if isinstance(val, torch.Tensor): + # print("{}: {}".format(key, print(val.size()))) + # elif isinstance(val, EasyDict): + # print("{}: {}".format(key, val.keys())) + elem_type = type(elem) if isinstance(batch, ttorch.Tensor): return batch.json() @@ -75,6 +83,9 @@ def default_collate( out = elem.new(storage) if elem.shape == (1, ) and cat_1dim: # reshape (B, 1) -> (B) + # print("debug:", batch) + # print("debug:", len(batch)) + # print("debug:", len(batch[0])) return torch.cat(batch, dim, out=out) # return torch.stack(batch, 0, out=out) else: diff --git a/ding/utils/log_helper.py b/ding/utils/log_helper.py index 9ba7e0cddf..904b0f88e7 100644 --- a/ding/utils/log_helper.py +++ b/ding/utils/log_helper.py @@ -1,7 +1,7 @@ import json from ditk import logging import os -from typing import Optional, Tuple, Union, Dict, Any +from typing import Callable, Optional, Tuple, Union, Dict, Any import ditk.logging import numpy as np diff --git a/ding/utils/sparse_logging.py b/ding/utils/sparse_logging.py new file mode 100644 index 0000000000..cd7fb20c9a --- /dev/null +++ b/ding/utils/sparse_logging.py @@ -0,0 +1,70 @@ +from ditk import logging +import itertools +import timeit + +_log_counter_per_token = {} +_log_timer_per_token = {} + + +def _get_next_log_count_per_token(token): + """Wrapper for _log_counter_per_token. Thread-safe. + Args: + token: The token for which to look up the count. + Returns: + The number of times this function has been called with + *token* as an argument (starting at 0). + """ + # Can't use a defaultdict because defaultdict isn't atomic, whereas + # setdefault is. + return next(_log_counter_per_token.setdefault(token, itertools.count())) + + +def _seconds_have_elapsed(token, num_seconds): + """Tests if 'num_seconds' have passed since 'token' was requested. + Not strictly thread-safe - may log with the wrong frequency if called + concurrently from multiple threads. Accuracy depends on resolution of + 'timeit.default_timer()'. + Always returns True on the first call for a given 'token'. + Args: + token: The token for which to look up the count. + num_seconds: The number of seconds to test for. + Returns: + Whether it has been >= 'num_seconds' since 'token' was last requested. + """ + now = timeit.default_timer() + then = _log_timer_per_token.get(token, None) + if then is None or (now - then) >= num_seconds: + _log_timer_per_token[token] = now + return True + else: + return False + + +def log_every_n(level, n, msg, *args): + """Logs 'msg % args' at level 'level' once per 'n' times. + Logs the 1st call, (N+1)st call, (2N+1)st call, etc. + Not threadsafe. + Args: + level: int, the absl logging level at which to log. + msg: str, the message to be logged. + n: int, the number of times this should be called before it is logged. + *args: The args to be substituted into the msg. + """ + count = _get_next_log_count_per_token(logging.getLogger().findCaller()) + if count % n == 0: + logging.log(level, msg, *args) + + +def log_every_sec(level, n_seconds, msg, *args): + """Logs 'msg % args' at level 'level' iff 'n_seconds' elapsed since last call. + Logs the first call, logs subsequent calls if 'n' seconds have elapsed since + the last logging call from the same call site (file + line). Not thread-safe. + Args: + level: int, the absl logging level at which to log. + msg: str, the message to be logged. + n_seconds: float or int, seconds which should elapse before logging again. + *args: The args to be substituted into the msg. + """ + should_log = _seconds_have_elapsed(logging.getLogger().findCaller(), n_seconds) + if should_log: + logging.log(level, msg, *args) diff --git a/ding/utils/tests/test_sparse_logging.py b/ding/utils/tests/test_sparse_logging.py new file mode 100644 index 0000000000..83294ccaa9 --- /dev/null +++ b/ding/utils/tests/test_sparse_logging.py @@ -0,0 +1,13 @@ +import pytest +import logging +import time +from ding.utils import log_every_n, log_every_sec + +if __name__ == "__main__": + logging.getLogger().setLevel(logging.INFO) + for i in range(30): + log_every_n(logging.INFO, 5, "abc_{}".format(i)) + + for i in range(30): + time.sleep(0.1) + log_every_sec(logging.INFO, 1, "abc_{}".format(i)) diff --git a/dizoo/distar/config/distar_config.py b/dizoo/distar/config/distar_config.py index 0b532f2da3..c462d3d671 100644 --- a/dizoo/distar/config/distar_config.py +++ b/dizoo/distar/config/distar_config.py @@ -48,7 +48,7 @@ }, 'multi_gpu': False, 'epoch_per_collect': 10, - 'batch_size': 16, + 'batch_size': 3, 'learning_rate': 1e-05, 'value_weight': 0.5, 'entropy_weight': 0.0, @@ -105,7 +105,7 @@ 'player_category': ['default'], 'path_policy': 'league_demo/ckpt', 'active_players': { - 'main_player': 2 + 'main_player': 1 }, 'main_player': { 'one_phase_step': 10, # 20 From 4ef8ea8adf2d75d4daf71897836459d2a11b3468 Mon Sep 17 00:00:00 2001 From: lixuelin Date: Thu, 23 Jun 2022 19:26:11 +0800 Subject: [PATCH 155/229] rm exp files --- ...5d0326-f2a0-11ec-8459-4649caa90281.SC2Replay | Bin 37685 -> 0 bytes ...5cc7a4-f2a1-11ec-9ca0-4649caa90281.SC2Replay | Bin 31275 -> 0 bytes ...9f19a2-f2a5-11ec-aa3e-4649caa90281.SC2Replay | Bin 27882 -> 0 bytes ...df0152-f2a6-11ec-91ba-4649caa90281.SC2Replay | Bin 30063 -> 0 bytes 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zzT2`rou8O#pXnbFmr@w96HUE&6!aMPEnGS=UiN8#Q_|IaIuo>m9VT{h12y_!j^thwYDJh;i92Qc` z!-WhSG6Y8&++b1D`}BSi$?wGb-08_rt>@?5ekdQ~#y9)*R53}!N8Mu$lYSF+G Date: Thu, 23 Jun 2022 19:31:47 +0800 Subject: [PATCH 156/229] add info["result"] --- dizoo/distar/envs/distar_env.py | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/dizoo/distar/envs/distar_env.py b/dizoo/distar/envs/distar_env.py index 27e3f9cb12..74d7785706 100644 --- a/dizoo/distar/envs/distar_env.py +++ b/dizoo/distar/envs/distar_env.py @@ -41,6 +41,11 @@ def step(self, actions): info[policy_id] = {} if done: info[policy_id]['final_eval_reward'] = reward[policy_id] + info[policy_id]['result'] = 'draws' + if reward[policy_id] == 1: + info[policy_id]['result'] = 'wins' + elif reward[policy_id] == -1: + info[policy_id]['result'] = 'losses' timestep = BaseEnvTimestep(obs=next_observations, reward=reward, done=done, info=info) return timestep From c7e0b4c8dd875f9d692de8e24b82afa720677607 Mon Sep 17 00:00:00 2001 From: lixuelin Date: Thu, 23 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<744762298@qq.com> Date: Fri, 24 Jun 2022 11:28:30 +0800 Subject: [PATCH 159/229] add comment --- ding/framework/middleware/functional/collector.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 81632b309a..e3915c19a2 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -65,7 +65,7 @@ def __init__(self, env_num: int, unroll_len: int) -> None: self._unroll_len = unroll_len # TODO(zms): last transition + 1 - def get_env_trajectories(self, env_id: int, only_finished: bool = False): + def get_env_trajectories(self, env_id: int, only_finished: bool = False) -> List[List]: trajectories = [] if len(self._transitions[env_id]) == 0: # if we have no episode for this env, we return an empty list @@ -92,7 +92,7 @@ def get_env_trajectories(self, env_id: int, only_finished: bool = False): return trajectories - def to_trajectories(self, only_finished: bool = False): + def to_trajectories(self, only_finished: bool = False) -> List[ActorEnvTrajectories]: all_env_data = [] for env_id in range(self.env_num): trajectories = self.get_env_trajectories(env_id, only_finished=only_finished) @@ -100,7 +100,7 @@ def to_trajectories(self, only_finished: bool = False): all_env_data.append(ActorEnvTrajectories(env_id=env_id, trajectories=trajectories)) return all_env_data - def _cut_trajectory_from_episode(self, episode: list): + def _cut_trajectory_from_episode(self, episode: list) -> List[List]: # first we cut complete trajectories (list of transitions whose length equal to unroll_len) # then we gather the transitions in the tail of episode, and fill up the trajectory with the tail transitions in Trajectory(t-1) # If we don't have Trajectory(t-1), i.e. the length of the whole episode is smaller than unroll_len, we fill up the trajectory @@ -151,7 +151,7 @@ def append(self, env_id: int, transition: Any) -> bool: return False return True - def clear(self): + def clear(self) -> None: for item in self._transitions: item.clear() for item in self._done_episode: From 02b9d0b1b54bc41860331548fbd2292d56133b29 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Fri, 24 Jun 2022 14:15:25 +0800 Subject: [PATCH 160/229] add result info in job.info --- ding/framework/middleware/league_actor.py | 2 +- .../middleware/tests/test_league_actor_distar_one_process.py | 1 + 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 14b20440bf..0762e95552 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -328,7 +328,7 @@ def __call__(self, ctx: "BattleContext"): ) if ctx.job_finish is True: - job.result = [['wins']] + job.result = [e['result'] for e in ctx.episode_info[0]] task.emit(EventEnum.ACTOR_FINISH_JOB, job) ctx.episode_info = [[] for _ in range(self.agent_num)] logging.info('[Actor {}] job finish, send job\n'.format(task.router.node_id)) diff --git a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py index dc53bfc49a..bf2b4a2296 100644 --- a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py @@ -84,6 +84,7 @@ def on_actor_greeting(actor_id): def on_actor_job(job_: Job): assert job_.launch_player == job.launch_player + print(job) testcases["on_actor_job"] = True def on_actor_data(actor_data): From b72cb783ec8799eda72ffce5f6155910b6be3cd4 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Fri, 24 Jun 2022 14:37:51 +0800 Subject: [PATCH 161/229] comment Episode Actor and Episode Collector --- ding/framework/middleware/__init__.py | 4 +- ding/framework/middleware/collector.py | 154 ++++++------ ding/framework/middleware/league_actor.py | 284 +++++++++++----------- 3 files changed, 221 insertions(+), 221 deletions(-) diff --git a/ding/framework/middleware/__init__.py b/ding/framework/middleware/__init__.py index 62001ea92e..f2a68c64bf 100644 --- a/ding/framework/middleware/__init__.py +++ b/ding/framework/middleware/__init__.py @@ -1,7 +1,7 @@ from .functional import * -from .collector import StepCollector, EpisodeCollector, BattleEpisodeCollector, BattleStepCollector +from .collector import StepCollector, EpisodeCollector, BattleStepCollector from .learner import OffPolicyLearner, HERLearner from .ckpt_handler import CkptSaver -from .league_actor import LeagueActor, StepLeagueActor +from .league_actor import StepLeagueActor from .league_coordinator import LeagueCoordinator from .league_learner import * diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 00c9c91575..925cad194f 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -9,83 +9,6 @@ from ding.framework import OnlineRLContext, BattleContext -class BattleEpisodeCollector: - - def __init__( - self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int, model_dict: Dict, all_policies: Dict, - agent_num: int - ): - self.cfg = cfg - self.end_flag = False - # self._reset(env) - self.env = env - self.env_num = self.env.env_num - - self.total_envstep_count = 0 - self.n_rollout_samples = n_rollout_samples - self.model_dict = model_dict - self.all_policies = all_policies - self.agent_num = agent_num - - self._battle_inferencer = task.wrap(battle_inferencer(self.cfg, self.env)) - self._transitions_list = [TransitionList(self.env.env_num) for _ in range(self.agent_num)] - self._battle_rolloutor = task.wrap(battle_rolloutor(self.cfg, self.env, self._transitions_list)) - - def __del__(self) -> None: - """ - Overview: - Execute the close command and close the collector. __del__ is automatically called to \ - destroy the collector instance when the collector finishes its work - """ - if self.end_flag: - return - self.end_flag = True - self.env.close() - - def _update_policies(self, player_id_list) -> None: - # TODO(zms): update train_iter, update train_iter and player_id inside policy is a good idea - for player_id in player_id_list: - if self.model_dict.get(player_id) is None: - continue - else: - learner_model = self.model_dict.get(player_id) - policy = self.all_policies.get(player_id) - assert policy, "for player {}, policy should have been initialized already".format(player_id) - # update policy model - policy.load_state_dict(learner_model.state_dict) - self.model_dict[player_id] = None - - def __call__(self, ctx: "BattleContext") -> None: - """ - Input of ctx: - - n_episode (:obj:`int`): the number of collecting data episode - - train_iter (:obj:`int`): the number of training iteration - - collect_kwargs (:obj:`dict`): the keyword args for policy forward - Output of ctx: - - ctx.train_data (:obj:`Tuple[List, List]`): A tuple with training sample(data) and episode info, \ - the former is a list containing collected episodes if not get_train_sample, \ - otherwise, return train_samples split by unroll_len. - """ - ctx.total_envstep_count = self.total_envstep_count - old = ctx.env_episode - while True: - self._update_policies(ctx.player_id_list) - self._battle_inferencer(ctx) - self._battle_rolloutor(ctx) - - self.total_envstep_count = ctx.total_envstep_count - - if (self.n_rollout_samples > 0 - and ctx.env_episode - old >= self.n_rollout_samples) or ctx.env_episode >= ctx.n_episode: - for transitions in self._transitions_list: - ctx.episodes.append(transitions.to_episodes()) - transitions.clear() - if ctx.env_episode >= ctx.n_episode: - self.env.close() - ctx.job_finish = True - break - - class BattleStepCollector: def __init__( @@ -167,6 +90,83 @@ def __call__(self, ctx: "BattleContext") -> None: break +# class BattleEpisodeCollector: + +# def __init__( +# self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int, model_dict: Dict, all_policies: Dict, +# agent_num: int +# ): +# self.cfg = cfg +# self.end_flag = False +# # self._reset(env) +# self.env = env +# self.env_num = self.env.env_num + +# self.total_envstep_count = 0 +# self.n_rollout_samples = n_rollout_samples +# self.model_dict = model_dict +# self.all_policies = all_policies +# self.agent_num = agent_num + +# self._battle_inferencer = task.wrap(battle_inferencer(self.cfg, self.env)) +# self._transitions_list = [TransitionList(self.env.env_num) for _ in range(self.agent_num)] +# self._battle_rolloutor = task.wrap(battle_rolloutor(self.cfg, self.env, self._transitions_list)) + +# def __del__(self) -> None: +# """ +# Overview: +# Execute the close command and close the collector. __del__ is automatically called to \ +# destroy the collector instance when the collector finishes its work +# """ +# if self.end_flag: +# return +# self.end_flag = True +# self.env.close() + +# def _update_policies(self, player_id_list) -> None: +# # TODO(zms): update train_iter, update train_iter and player_id inside policy is a good idea +# for player_id in player_id_list: +# if self.model_dict.get(player_id) is None: +# continue +# else: +# learner_model = self.model_dict.get(player_id) +# policy = self.all_policies.get(player_id) +# assert policy, "for player {}, policy should have been initialized already".format(player_id) +# # update policy model +# policy.load_state_dict(learner_model.state_dict) +# self.model_dict[player_id] = None + +# def __call__(self, ctx: "BattleContext") -> None: +# """ +# Input of ctx: +# - n_episode (:obj:`int`): the number of collecting data episode +# - train_iter (:obj:`int`): the number of training iteration +# - collect_kwargs (:obj:`dict`): the keyword args for policy forward +# Output of ctx: +# - ctx.train_data (:obj:`Tuple[List, List]`): A tuple with training sample(data) and episode info, \ +# the former is a list containing collected episodes if not get_train_sample, \ +# otherwise, return train_samples split by unroll_len. +# """ +# ctx.total_envstep_count = self.total_envstep_count +# old = ctx.env_episode +# while True: +# self._update_policies(ctx.player_id_list) +# self._battle_inferencer(ctx) +# self._battle_rolloutor(ctx) + +# self.total_envstep_count = ctx.total_envstep_count + +# if (self.n_rollout_samples > 0 +# and ctx.env_episode - old >= self.n_rollout_samples) or ctx.env_episode >= ctx.n_episode: +# for transitions in self._transitions_list: +# ctx.episodes.append(transitions.to_episodes()) +# transitions.clear() +# if ctx.env_episode >= ctx.n_episode: +# self.env.close() +# ctx.job_finish = True +# break + + class StepCollector: """ Overview: diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 0762e95552..4123c11e2a 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -21,148 +21,6 @@ from ding.framework.middleware.league_learner import LearnerModel -class LeagueActor: - - def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): - self.cfg = cfg - self.env_fn = env_fn - self.env_num = env_fn().env_num - self.policy_fn = policy_fn - self.n_rollout_samples = self.cfg.policy.collect.n_rollout_samples - self._collectors: Dict[str, BattleEpisodeCollector] = {} - self.all_policies: Dict[str, "Policy.collect_function"] = {} - task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), self._on_league_job) - task.on(EventEnum.LEARNER_SEND_MODEL, self._on_learner_model) - self.job_queue = queue.Queue() - self.model_dict = {} - self.model_dict_lock = Lock() - - self.agent_num = 2 - self.collect_time = {} - - def _on_learner_model(self, learner_model: "LearnerModel"): - """ - If get newest learner model, put it inside model_queue. - """ - log_every_sec(logging.INFO, 5, "[Actor {}] receive model from learner \n".format(task.router.node_id)) - with self.model_dict_lock: - self.model_dict[learner_model.player_id] = learner_model - - def _on_league_job(self, job: "Job"): - """ - Deal with job distributed by coordinator, put it inside job_queue. - """ - self.job_queue.put(job) - - def _get_collector(self, player_id: str): - if self._collectors.get(player_id): - return self._collectors.get(player_id) - cfg = self.cfg - env = self.env_fn() - collector = task.wrap( - BattleEpisodeCollector( - cfg.policy.collect.collector, env, self.n_rollout_samples, self.model_dict, self.all_policies, - self.agent_num - ) - ) - self._collectors[player_id] = collector - self.collect_time[player_id] = 0 - return collector - - def _get_policy(self, player: "PlayerMeta") -> "Policy.collect_function": - player_id = player.player_id - if self.all_policies.get(player_id): - return self.all_policies.get(player_id) - policy: "Policy.collect_function" = self.policy_fn().collect_mode - self.all_policies[player_id] = policy - if "historical" in player.player_id: - policy.load_state_dict(player.checkpoint.load()) - - return policy - - def _get_job(self): - if self.job_queue.empty(): - task.emit(EventEnum.ACTOR_GREETING, task.router.node_id) - job = None - - try: - job = self.job_queue.get(timeout=10) - except queue.Empty: - logging.warning("[Actor {}] no Job got from coordinator".format(task.router.node_id)) - - return job - - def _get_current_policies(self, job): - current_policies = [] - main_player: "PlayerMeta" = None - for player in job.players: - current_policies.append(self._get_policy(player)) - if player.player_id == job.launch_player: - main_player = player - assert main_player, "[Actor {}] cannot find active player.".format(task.router.node_id) - - if current_policies is not None: - assert len(current_policies) > 1, "battle collector needs more than 1 policies" - for p in current_policies: - p.reset() - else: - raise RuntimeError('current_policies should not be None') - - return main_player, current_policies - - def __call__(self, ctx: "BattleContext"): - - job = self._get_job() - if job is None: - return - - ctx.player_id_list = [player.player_id for player in job.players] - self.agent_num = len(job.players) - collector = self._get_collector(job.launch_player) - - main_player, ctx.current_policies = self._get_current_policies(job) - - ctx.n_episode = self.cfg.policy.collect.n_episode - assert ctx.n_episode >= self.env_num, "[Actor {}] Please make sure n_episode >= env_num".format( - task.router.node_id - ) - - ctx.train_iter = main_player.total_agent_step - ctx.episode_info = [[] for _ in range(self.agent_num)] - ctx.remain_episode = ctx.n_episode - while True: - old_envstep = ctx.total_envstep_count - time_begin = time.time() - collector(ctx) - meta_data = ActorDataMeta( - player_total_env_step=ctx.total_envstep_count, actor_id=task.router.node_id, send_wall_time=time.time() - ) - - if not job.is_eval and len(ctx.episodes[0]) > 0: - actor_data = ActorData(meta=meta_data, train_data=ctx.episodes[0]) - task.emit(EventEnum.ACTOR_SEND_DATA.format(player=job.launch_player), actor_data) - ctx.episodes = [] - time_end = time.time() - self.collect_time[job.launch_player] += time_end - time_begin - total_collect_speed = ctx.total_envstep_count / self.collect_time[job.launch_player] if self.collect_time[ - job.launch_player] != 0 else 0 - envstep_passed = ctx.total_envstep_count - old_envstep - real_time_speed = envstep_passed / (time_end - time_begin) - log_every_sec( - logging.INFO, 5, - '[Actor {}] total_env_step:{}, current job env_step: {}, total_collect_speed: {} env_step/s, real-time collect speed: {} env_step/s' - .format( - task.router.node_id, ctx.total_envstep_count, ctx.env_step, total_collect_speed, real_time_speed - ) - ) - - if ctx.job_finish is True: - job.result = [e['result'] for e in ctx.episode_info[0]] - task.emit(EventEnum.ACTOR_FINISH_JOB, job) - ctx.episode_info = [[] for _ in range(self.agent_num)] - break - - class StepLeagueActor: def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): @@ -333,3 +191,145 @@ def __call__(self, ctx: "BattleContext"): ctx.episode_info = [[] for _ in range(self.agent_num)] logging.info('[Actor {}] job finish, send job\n'.format(task.router.node_id)) break + + +# class LeagueActor: + +# def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): +# self.cfg = cfg +# self.env_fn = env_fn +# self.env_num = env_fn().env_num +# self.policy_fn = policy_fn +# self.n_rollout_samples = self.cfg.policy.collect.n_rollout_samples +# self._collectors: Dict[str, BattleEpisodeCollector] = {} +# self.all_policies: Dict[str, "Policy.collect_function"] = {} +# task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), self._on_league_job) +# task.on(EventEnum.LEARNER_SEND_MODEL, self._on_learner_model) +# self.job_queue = queue.Queue() +# self.model_dict = {} +# self.model_dict_lock = Lock() + +# self.agent_num = 2 +# self.collect_time = {} + +# def _on_learner_model(self, learner_model: "LearnerModel"): +# """ +# If get newest learner model, put it inside model_queue. +# """ +# log_every_sec(logging.INFO, 5, "[Actor {}] receive model from learner \n".format(task.router.node_id)) +# with self.model_dict_lock: +# self.model_dict[learner_model.player_id] = learner_model + +# def _on_league_job(self, job: "Job"): +# """ +# Deal with job distributed by coordinator, put it inside job_queue. +# """ +# self.job_queue.put(job) + +# def _get_collector(self, player_id: str): +# if self._collectors.get(player_id): +# return self._collectors.get(player_id) +# cfg = self.cfg +# env = self.env_fn() +# collector = task.wrap( +# BattleEpisodeCollector( +# cfg.policy.collect.collector, env, self.n_rollout_samples, self.model_dict, self.all_policies, +# self.agent_num +# ) +# ) +# self._collectors[player_id] = collector +# self.collect_time[player_id] = 0 +# return collector + +# def _get_policy(self, player: "PlayerMeta") -> "Policy.collect_function": +# player_id = player.player_id +# if self.all_policies.get(player_id): +# return self.all_policies.get(player_id) +# policy: "Policy.collect_function" = self.policy_fn().collect_mode +# self.all_policies[player_id] = policy +# if "historical" in player.player_id: +# policy.load_state_dict(player.checkpoint.load()) + +# return policy + +# def _get_job(self): +# if self.job_queue.empty(): +# task.emit(EventEnum.ACTOR_GREETING, task.router.node_id) +# job = None + +# try: +# job = self.job_queue.get(timeout=10) +# except queue.Empty: +# logging.warning("[Actor {}] no Job got from coordinator".format(task.router.node_id)) + +# return job + +# def _get_current_policies(self, job): +# current_policies = [] +# main_player: "PlayerMeta" = None +# for player in job.players: +# current_policies.append(self._get_policy(player)) +# if player.player_id == job.launch_player: +# main_player = player +# assert main_player, "[Actor {}] cannot find active player.".format(task.router.node_id) + +# if current_policies is not None: +# assert len(current_policies) > 1, "battle collector needs more than 1 policies" +# for p in current_policies: +# p.reset() +# else: +# raise RuntimeError('current_policies should not be None') + +# return main_player, current_policies + +# def __call__(self, ctx: "BattleContext"): + +# job = self._get_job() +# if job is None: +# return + +# ctx.player_id_list = [player.player_id for player in job.players] +# self.agent_num = len(job.players) +# collector = self._get_collector(job.launch_player) + +# main_player, ctx.current_policies = self._get_current_policies(job) + +# ctx.n_episode = self.cfg.policy.collect.n_episode +# assert ctx.n_episode >= self.env_num, "[Actor {}] Please make sure n_episode >= env_num".format( +# task.router.node_id +# ) + +# ctx.train_iter = main_player.total_agent_step +# ctx.episode_info = [[] for _ in range(self.agent_num)] +# ctx.remain_episode = ctx.n_episode +# while True: +# old_envstep = ctx.total_envstep_count +# time_begin = time.time() +# collector(ctx) +# meta_data = ActorDataMeta( +# player_total_env_step=ctx.total_envstep_count, actor_id=task.router.node_id, send_wall_time=time.time() +# ) + +# if not job.is_eval and len(ctx.episodes[0]) > 0: +# actor_data = ActorData(meta=meta_data, train_data=ctx.episodes[0]) +# task.emit(EventEnum.ACTOR_SEND_DATA.format(player=job.launch_player), actor_data) +# ctx.episodes = [] +# time_end = time.time() +# self.collect_time[job.launch_player] += time_end - time_begin +# total_collect_speed = ctx.total_envstep_count / self.collect_time[job.launch_player] if self.collect_time[ +# job.launch_player] != 0 else 0 +# envstep_passed = ctx.total_envstep_count - old_envstep +# real_time_speed = envstep_passed / (time_end - time_begin) +# log_every_sec( +# logging.INFO, 5, +# '[Actor {}] total_env_step:{}, current job env_step: {}, total_collect_speed: {} env_step/s, real-time collect speed: {} env_step/s' +# .format( +# task.router.node_id, ctx.total_envstep_count, ctx.env_step, total_collect_speed, real_time_speed +# ) +# ) + +# if ctx.job_finish is True: +# job.result = [e['result'] for e in ctx.episode_info[0]] +# task.emit(EventEnum.ACTOR_FINISH_JOB, job) +# ctx.episode_info = [[] for _ in range(self.agent_num)] +# break From e12a82e84505c5b9849981ee6c869200b3cbd642 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Fri, 24 Jun 2022 14:54:43 +0800 Subject: [PATCH 162/229] move battle_inferencer_for_distar, battle_rolloutor_for_distar to functional.collector.py --- ding/example/distar.py | 3 +- .../middleware/functional/__init__.py | 3 +- .../middleware/functional/collector.py | 77 ++++++++++++++++++ ding/framework/middleware/league_actor.py | 4 +- ...9367-f38a-11ec-8e04-00ffb15e39af.SC2Replay | Bin 0 -> 27884 bytes .../middleware/tests/mock_for_test.py | 77 ------------------ .../test_league_actor_distar_one_process.py | 4 +- .../middleware/tests/test_league_pipeline.py | 5 +- .../tests/test_league_pipeline_one_process.py | 6 +- 9 files changed, 90 insertions(+), 89 deletions(-) create mode 100644 ding/framework/middleware/tests/2022-06-24-14/KingsCove_agent1_vs_agent2_[0, 0]_2022-06-24-06-51-44_1c3a9367-f38a-11ec-8e04-00ffb15e39af.SC2Replay diff --git a/ding/example/distar.py b/ding/example/distar.py index de51043fbc..28a87906eb 100644 --- a/ding/example/distar.py +++ b/ding/example/distar.py @@ -6,7 +6,8 @@ from ding.envs import BaseEnvManager from ding.framework.context import BattleContext from ding.framework.middleware import StepLeagueActor, LeagueCoordinator, LeagueLearnerCommunicator, data_pusher, OffPolicyLearner -from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, DIStarMockPolicyCollect, battle_inferencer_for_distar, battle_rolloutor_for_distar +from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, DIStarMockPolicyCollect +from ding.framework.middleware.functional.collector import battle_inferencer_for_distar, battle_rolloutor_for_distar from ding.framework.task import task, Parallel from ding.league.v2 import BaseLeague from dizoo.distar.config import distar_cfg diff --git a/ding/framework/middleware/functional/__init__.py b/ding/framework/middleware/functional/__init__.py index 01d87b71ca..dde50535b2 100644 --- a/ding/framework/middleware/functional/__init__.py +++ b/ding/framework/middleware/functional/__init__.py @@ -1,7 +1,8 @@ from .trainer import trainer, multistep_trainer from .data_processor import offpolicy_data_fetcher, data_pusher, offline_data_fetcher, offline_data_saver, \ sqil_data_pusher -from .collector import inferencer, rolloutor, TransitionList, BattleTransitionList, battle_inferencer, battle_rolloutor +from .collector import inferencer, rolloutor, TransitionList, BattleTransitionList, \ + battle_inferencer, battle_rolloutor, battle_inferencer_for_distar, battle_rolloutor_for_distar from .evaluator import interaction_evaluator from .termination_checker import termination_checker from .pace_controller import pace_controller diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index e3915c19a2..83b2757514 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -305,3 +305,80 @@ def _battle_rolloutor(ctx: "BattleContext"): ctx.env_episode += 1 return _battle_rolloutor + + +def battle_inferencer_for_distar(cfg: EasyDict, env: BaseEnvManager): + + def _battle_inferencer(ctx: "BattleContext"): + + if env.closed: + env.launch() + + # Get current env obs. + obs = env.ready_obs + assert isinstance(obs, dict) + + ctx.obs = obs + + # Policy forward. + inference_output = {} + actions = {} + for env_id in ctx.obs.keys(): + observations = obs[env_id] + inference_output[env_id] = {} + actions[env_id] = {} + for policy_id, policy_obs in observations.items(): + # policy.forward + output = ctx.current_policies[policy_id].forward(policy_obs) + inference_output[env_id][policy_id] = output + actions[env_id][policy_id] = output['action'] + ctx.inference_output = inference_output + ctx.actions = actions + + return _battle_inferencer + + +def battle_rolloutor_for_distar(cfg: EasyDict, env: BaseEnvManager, transitions_list: List): + + def _battle_rolloutor(ctx: "BattleContext"): + timesteps = env.step(ctx.actions) + + ctx.total_envstep_count += len(timesteps) + ctx.env_step += len(timesteps) + + # for env_id, timestep in timesteps.items(): + # TODO(zms): make sure a standard + # If for each step, the env manager can't get the obs of all envs, we need to use dict here. + for env_id, timestep in enumerate(timesteps): + if timestep.info.get('abnormal'): + # TODO(zms): cannot get exact env_step of a episode because for each observation, + # in most cases only one of two policies has a obs. + # ctx.total_envstep_count -= transitions_list[0].length(env_id) + # ctx.env_step -= transitions_list[0].length(env_id) + + # 1st case when env step has bug and need to reset. + for policy_id, _ in enumerate(ctx.current_policies): + transitions_list[policy_id].clear_newest_episode(env_id) + ctx.current_policies[policy_id].reset([env_id]) + continue + + append_succeed = True + for policy_id, _ in enumerate(ctx.current_policies): + transition = ctx.current_policies[policy_id].process_transition(timestep) + transition = EasyDict(transition) + transition.collect_train_iter = ttorch.as_tensor([ctx.train_iter]) + + # 2nd case when the number of transitions in one of all the episodes is shorter than unroll_len + append_succeed = append_succeed and transitions_list[policy_id].append(env_id, transition) + if timestep.done: + ctx.current_policies[policy_id].reset([env_id]) + ctx.episode_info[policy_id].append(timestep.info[policy_id]) + + if not append_succeed: + for policy_id, _ in enumerate(ctx.current_policies): + transitions_list[policy_id].clear_newest_episode(env_id) + ctx.episode_info[policy_id].pop() + elif timestep.done: + ctx.env_episode += 1 + + return _battle_rolloutor \ No newline at end of file diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 4123c11e2a..eba1bc1735 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -5,7 +5,7 @@ from ding.league import player from ding.policy import Policy -from ding.framework.middleware import BattleEpisodeCollector, BattleStepCollector +from ding.framework.middleware import BattleStepCollector from ding.framework.middleware.functional import ActorData, ActorDataMeta from ding.league.player import PlayerMeta from threading import Lock @@ -29,7 +29,7 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.env_num = env_fn().env_num self.policy_fn = policy_fn self.unroll_len = self.cfg.policy.collect.unroll_len - self._collectors: Dict[str, BattleEpisodeCollector] = {} + self._collectors: Dict[str, BattleStepCollector] = {} self.all_policies: Dict[str, "Policy.collect_function"] = {} task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), self._on_league_job) task.on(EventEnum.LEARNER_SEND_MODEL, self._on_learner_model) diff --git a/ding/framework/middleware/tests/2022-06-24-14/KingsCove_agent1_vs_agent2_[0, 0]_2022-06-24-06-51-44_1c3a9367-f38a-11ec-8e04-00ffb15e39af.SC2Replay b/ding/framework/middleware/tests/2022-06-24-14/KingsCove_agent1_vs_agent2_[0, 0]_2022-06-24-06-51-44_1c3a9367-f38a-11ec-8e04-00ffb15e39af.SC2Replay new file mode 100644 index 0000000000000000000000000000000000000000..a63bf2bc9d39e8cf8e741a2faa7010c934de0949 GIT binary patch literal 27884 zcmeFYRd8I(vMAVMY%ybtnOiK`EoNqBxy8(~x0q!yGcz+;%*?jPVrG^l+t2&#d)}OP zBPM3P=4WnwR90res>saBtXh$&q^d>=fCT^m@Bo0@AAo=ZfMwNiH*=M6HM4dH$;p9S zt(@)6d`P*tU=h#(D6p_7$nYq5h$sMLl!aUr)W0iu6nI3GuSH16h%l%Ku&}V8_ADc( 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zx_P*y5*zCkTw=1fpwbTZ(^r}aT(cqLV5c{ML@Rp-VI{a%b` zjxQ2*FAI*)J)kTCt?;Pc|8zb)(-2u-DqQJ~cPH5)eo5B$PnQ>=JH2R#^FvfE`%{E| zna~Bd1n)d>oPJ`LW%i_ru&xgRXA4M94zE&fwI$u}3;q8B^zKjb literal 0 HcmV?d00001 diff --git a/ding/framework/middleware/tests/mock_for_test.py b/ding/framework/middleware/tests/mock_for_test.py index 290a5da04d..e39b625ef5 100644 --- a/ding/framework/middleware/tests/mock_for_test.py +++ b/ding/framework/middleware/tests/mock_for_test.py @@ -236,80 +236,3 @@ class DIStarMockPolicyCollect: def __init__(self): self.collect_mode = DIstarCollectMode() - - -def battle_inferencer_for_distar(cfg: EasyDict, env: BaseEnvManager): - - def _battle_inferencer(ctx: "BattleContext"): - - if env.closed: - env.launch() - - # Get current env obs. - obs = env.ready_obs - assert isinstance(obs, dict) - - ctx.obs = obs - - # Policy forward. - inference_output = {} - actions = {} - for env_id in ctx.obs.keys(): - observations = obs[env_id] - inference_output[env_id] = {} - actions[env_id] = {} - for policy_id, policy_obs in observations.items(): - # policy.forward - output = ctx.current_policies[policy_id].forward(policy_obs) - inference_output[env_id][policy_id] = output - actions[env_id][policy_id] = output['action'] - ctx.inference_output = inference_output - ctx.actions = actions - - return _battle_inferencer - - -def battle_rolloutor_for_distar(cfg: EasyDict, env: BaseEnvManager, transitions_list: List): - - def _battle_rolloutor(ctx: "BattleContext"): - timesteps = env.step(ctx.actions) - - ctx.total_envstep_count += len(timesteps) - ctx.env_step += len(timesteps) - - # for env_id, timestep in timesteps.items(): - # TODO(zms): make sure a standard - # If for each step, the env manager can't get the obs of all envs, we need to use dict here. - for env_id, timestep in enumerate(timesteps): - if timestep.info.get('abnormal'): - # TODO(zms): cannot get exact env_step of a episode because for each observation, - # in most cases only one of two policies has a obs. - # ctx.total_envstep_count -= transitions_list[0].length(env_id) - # ctx.env_step -= transitions_list[0].length(env_id) - - # 1st case when env step has bug and need to reset. - for policy_id, _ in enumerate(ctx.current_policies): - transitions_list[policy_id].clear_newest_episode(env_id) - ctx.current_policies[policy_id].reset([env_id]) - continue - - append_succeed = True - for policy_id, _ in enumerate(ctx.current_policies): - transition = ctx.current_policies[policy_id].process_transition(timestep) - transition = EasyDict(transition) - transition.collect_train_iter = ttorch.as_tensor([ctx.train_iter]) - - # 2nd case when the number of transitions in one of all the episodes is shorter than unroll_len - append_succeed = append_succeed and transitions_list[policy_id].append(env_id, transition) - if timestep.done: - ctx.current_policies[policy_id].reset([env_id]) - ctx.episode_info[policy_id].append(timestep.info[policy_id]) - - if not append_succeed: - for policy_id, _ in enumerate(ctx.current_policies): - transitions_list[policy_id].clear_newest_episode(env_id) - ctx.episode_info[policy_id].pop() - elif timestep.done: - ctx.env_episode += 1 - - return _battle_rolloutor diff --git a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py index bf2b4a2296..f9378af09a 100644 --- a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py @@ -20,8 +20,8 @@ from distar.ctools.utils import read_config from ding.model import VAC -from ding.framework.middleware.tests import DIStarMockPPOPolicy, DIStarMockPolicyCollect, \ - battle_inferencer_for_distar, battle_rolloutor_for_distar +from ding.framework.middleware.tests import DIStarMockPPOPolicy, DIStarMockPolicyCollect +from ding.framework.middleware.functional.collector import battle_inferencer_for_distar, battle_rolloutor_for_distar cfg = deepcopy(distar_cfg) env_cfg = read_config('./test_distar_config.yaml') diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index a5e488f9ec..4047f9b6bc 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -7,13 +7,12 @@ from ding.framework.supervisor import ChildType from ding.framework.context import BattleContext from ding.framework.middleware import StepLeagueActor, LeagueCoordinator, LeagueLearnerCommunicator, data_pusher, OffPolicyLearner -from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, DIStarMockPolicyCollect, battle_inferencer_for_distar, battle_rolloutor_for_distar +from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, DIStarMockPolicyCollect +from ding.framework.middleware.functional.collector import battle_inferencer_for_distar, battle_rolloutor_for_distar from ding.framework.task import task, Parallel from ding.league.v2 import BaseLeague from dizoo.distar.config import distar_cfg from dizoo.distar.envs.distar_env import DIStarEnv -from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, DIStarMockPolicyCollect, \ - battle_inferencer_for_distar, battle_rolloutor_for_distar from unittest.mock import patch env_cfg = dict( diff --git a/ding/framework/middleware/tests/test_league_pipeline_one_process.py b/ding/framework/middleware/tests/test_league_pipeline_one_process.py index 825a86b2cb..919562d4cf 100644 --- a/ding/framework/middleware/tests/test_league_pipeline_one_process.py +++ b/ding/framework/middleware/tests/test_league_pipeline_one_process.py @@ -2,15 +2,15 @@ import pytest from ding.envs import BaseEnvManager, EnvSupervisor from ding.framework.context import BattleContext -from ding.framework.middleware import StepLeagueActor, LeagueCoordinator, LeagueLearner +from ding.framework.middleware import StepLeagueActor, LeagueCoordinator from ding.framework.supervisor import ChildType from ding.model import VAC from ding.framework.task import task from ding.framework.middleware.tests import cfg, MockLeague, MockLogger from dizoo.distar.envs.distar_env import DIStarEnv -from ding.framework.middleware.tests import DIStarMockPolicy, DIStarMockPolicyCollect, \ - battle_inferencer_for_distar, battle_rolloutor_for_distar +from ding.framework.middleware.tests import DIStarMockPolicy, DIStarMockPolicyCollect +from ding.framework.middleware.functional.collector import battle_inferencer_for_distar, battle_rolloutor_for_distar from distar.ctools.utils import read_config from unittest.mock import patch import os From cb976289418878748da597ddc0a74ef0dbafa3b8 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Fri, 24 Jun 2022 14:55:19 +0800 Subject: [PATCH 163/229] remove rep --- ...3a9367-f38a-11ec-8e04-00ffb15e39af.SC2Replay | Bin 27884 -> 0 bytes 1 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19aae0945da88d959b08cfbb77531bec69367c89 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Fri, 24 Jun 2022 17:35:47 +0800 Subject: [PATCH 164/229] change to fix bug on k8s --- ding/framework/middleware/functional/collector.py | 5 ++--- ding/framework/middleware/league_learner.py | 2 ++ 2 files changed, 4 insertions(+), 3 deletions(-) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 83b2757514..85022eb34a 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -1,7 +1,6 @@ from typing import TYPE_CHECKING, Optional, Callable, List, Tuple, Any from easydict import EasyDict from functools import reduce -from more_itertools import only import treetensor.torch as ttorch from ding.envs import BaseEnvManager from ding.policy import Policy @@ -16,7 +15,7 @@ from ding.framework.middleware.functional.actor_data import ActorEnvTrajectories from dizoo.distar.envs.fake_data import rl_step_data -import logging +from ditk import logging class TransitionList: @@ -381,4 +380,4 @@ def _battle_rolloutor(ctx: "BattleContext"): elif timestep.done: ctx.env_episode += 1 - return _battle_rolloutor \ No newline at end of file + return _battle_rolloutor diff --git a/ding/framework/middleware/league_learner.py b/ding/framework/middleware/league_learner.py index 5b97be1b96..8dea75305d 100644 --- a/ding/framework/middleware/league_learner.py +++ b/ding/framework/middleware/league_learner.py @@ -37,6 +37,8 @@ def __init__(self, cfg: dict, policy: "Policy", player: "ActivePlayer") -> None: self.player_id = player.player_id self.policy = policy self.prefix = '{}/ckpt'.format(cfg.exp_name) + if not os.path.exists(self.prefix): + os.makedirs(self.prefix) task.on(EventEnum.ACTOR_SEND_DATA.format(player=self.player_id), self._push_data) def _push_data(self, data: "ActorData"): From e9aad7eeda804a046f714121d87a5ebde0733fe0 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Mon, 27 Jun 2022 10:21:20 +0800 Subject: [PATCH 165/229] change a bit data_processor.py --- ding/framework/middleware/functional/data_processor.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ding/framework/middleware/functional/data_processor.py b/ding/framework/middleware/functional/data_processor.py index 88185839fb..b136885017 100644 --- a/ding/framework/middleware/functional/data_processor.py +++ b/ding/framework/middleware/functional/data_processor.py @@ -115,7 +115,7 @@ def _fetch(ctx: "OnlineRLContext"): except (ValueError, AssertionError): # You can modify data collect config to avoid this warning, e.g. increasing n_sample, n_episode. log_every_sec( - logging.warning, 10, + logging.WARNING, 10, "Replay buffer's data is not enough to support training, so skip this training for waiting more data." ) ctx.train_data = None From 98effdcc676e27134a4e02b7d52724420730d615 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Mon, 27 Jun 2022 15:56:44 +0800 Subject: [PATCH 166/229] make old tests could run --- ding/framework/middleware/functional/collector.py | 12 ++++++------ .../tests/test_league_actor_one_process.py | 4 ++-- 2 files changed, 8 insertions(+), 8 deletions(-) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 85022eb34a..6a7dca28fe 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -256,10 +256,10 @@ def _battle_inferencer(ctx: "BattleContext"): # Get current env obs. obs = env.ready_obs # the role of remain_episode is to mask necessary rollouts, avoid processing unnecessary data - new_available_env_id = set(obs.keys()).difference(ctx.ready_env_id) - ctx.ready_env_id = ctx.ready_env_id.union(set(list(new_available_env_id)[:ctx.remain_episode])) - ctx.remain_episode -= min(len(new_available_env_id), ctx.remain_episode) - obs = {env_id: obs[env_id] for env_id in ctx.ready_env_id} + # new_available_env_id = set(obs.keys()).difference(ctx.ready_env_id) + # ctx.ready_env_id = ctx.ready_env_id.union(set(list(new_available_env_id)[:ctx.remain_episode])) + # ctx.remain_episode -= min(len(new_available_env_id), ctx.remain_episode) + # obs = {env_id: obs[env_id] for env_id in ctx.ready_env_id} # Policy forward. if cfg.transform_obs: @@ -270,7 +270,7 @@ def _battle_inferencer(ctx: "BattleContext"): ctx.inference_output = inference_output # Interact with env. actions = {} - for env_id in ctx.ready_env_id: + for env_id in range(env.env_num): actions[env_id] = [] for output in inference_output: actions[env_id].append(output[env_id]['action']) @@ -300,7 +300,7 @@ def _battle_rolloutor(ctx: "BattleContext"): ctx.episode_info[policy_id].append(timestep.info[policy_id]) if timestep.done: - ctx.ready_env_id.remove(env_id) + # ctx.ready_env_id.remove(env_id) ctx.env_episode += 1 return _battle_rolloutor diff --git a/ding/framework/middleware/tests/test_league_actor_one_process.py b/ding/framework/middleware/tests/test_league_actor_one_process.py index c91a683372..f1afb1d1fe 100644 --- a/ding/framework/middleware/tests/test_league_actor_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_one_process.py @@ -5,7 +5,7 @@ from ding.framework.context import BattleContext from ding.framework.middleware.league_learner import LearnerModel from dizoo.distar.config import distar_cfg -from ding.framework.middleware import LeagueActor, StepLeagueActor +from ding.framework.middleware import StepLeagueActor from ding.framework.middleware.functional import ActorData from ding.league.player import PlayerMeta from ding.framework.storage import FileStorage @@ -43,7 +43,7 @@ def test_league_actor(): cfg, env_fn, policy_fn = prepare_test() policy = policy_fn() with task.start(async_mode=True, ctx=BattleContext()): - league_actor = LeagueActor(cfg=cfg, env_fn=env_fn, policy_fn=policy_fn) + league_actor = StepLeagueActor(cfg=cfg, env_fn=env_fn, policy_fn=policy_fn) def test_actor(): job = Job( From 2d712784e9d00aa4f588a8dfb5087205ac836a48 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Mon, 27 Jun 2022 16:39:34 +0800 Subject: [PATCH 167/229] feature(zms): check for 60s if get new model or not --- ding/framework/middleware/collector.py | 38 +++++++++++++++++-- ding/framework/middleware/league_actor.py | 20 +++++----- .../tests/test_league_actor_one_process.py | 3 +- 3 files changed, 45 insertions(+), 16 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 925cad194f..fa44bbf834 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -1,18 +1,26 @@ from easydict import EasyDict +from typing import Dict, TYPE_CHECKING +import time +from ditk import logging + from ding.policy import get_random_policy from ding.envs import BaseEnvManager +from ding.utils import log_every_sec from ding.framework import task -from .functional import inferencer, rolloutor, TransitionList, BattleTransitionList, battle_inferencer, battle_rolloutor -from typing import Dict, TYPE_CHECKING +from .functional import inferencer, rolloutor, TransitionList, BattleTransitionList, \ + battle_inferencer, battle_rolloutor if TYPE_CHECKING: from ding.framework import OnlineRLContext, BattleContext +WAIT_MODEL_TIME = 60 + class BattleStepCollector: def __init__( - self, cfg: EasyDict, env: BaseEnvManager, unroll_len: int, model_dict: Dict, all_policies: Dict, agent_num: int + self, cfg: EasyDict, env: BaseEnvManager, unroll_len: int, model_dict: Dict, model_time_dict: Dict, + all_policies: Dict, agent_num: int ): self.cfg = cfg self.end_flag = False @@ -23,6 +31,7 @@ def __init__( self.total_envstep_count = 0 self.unroll_len = unroll_len self.model_dict = model_dict + self.model_time_dict = model_time_dict self.all_policies = all_policies self.agent_num = agent_num @@ -44,7 +53,28 @@ def __del__(self) -> None: self.env.close() def _update_policies(self, player_id_list) -> None: - # TODO(zms): 60 秒 没有更新 就阻塞，更新才返回 + for player_id in player_id_list: + # for this player, actor didn't recieve any new model, use initial model instead. + if self.model_time_dict.get(player_id) is None: + self.model_time_dict[player_id] = time.time() + + while True: + time_now = time.time() + time_list = [time_now - self.model_time_dict[player_id] for player_id in player_id_list] + if any(x >= WAIT_MODEL_TIME for x in time_list): + for player_id in player_id_list: + if time_now - self.model_time_dict[player_id] >= WAIT_MODEL_TIME: + #TODO: log_every_sec can only print the first model that not updated + log_every_sec( + logging.WARNING, 5, + 'In actor {}, model for {} is not updated for {} senconds, and need new model'.format( + task.router.node_id, player_id, time_now - self.model_time_dict[player_id] + ) + ) + time.sleep(1) + else: + break + for player_id in player_id_list: if self.model_dict.get(player_id) is None: continue diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index eba1bc1735..e282005332 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -1,18 +1,15 @@ -from ding.framework import task, EventEnum -from ditk import logging - from typing import TYPE_CHECKING, Dict, Callable -from ding.league import player - -from ding.policy import Policy -from ding.framework.middleware import BattleStepCollector -from ding.framework.middleware.functional import ActorData, ActorDataMeta -from ding.league.player import PlayerMeta from threading import Lock import queue from easydict import EasyDict import time +from ditk import logging +from ding.policy import Policy +from ding.framework import task, EventEnum +from ding.framework.middleware import BattleStepCollector +from ding.framework.middleware.functional import ActorData, ActorDataMeta +from ding.league.player import PlayerMeta from ding.utils.sparse_logging import log_every_sec if TYPE_CHECKING: @@ -36,6 +33,7 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.job_queue = queue.Queue() self.model_dict = {} self.model_dict_lock = Lock() + self.model_time_dict = {} self.agent_num = 2 @@ -52,6 +50,7 @@ def _on_learner_model(self, learner_model: "LearnerModel"): ) with self.model_dict_lock: self.model_dict[learner_model.player_id] = learner_model + self.model_time_dict[learner_model.player_id] = time.time() def _on_league_job(self, job: "Job"): """ @@ -66,7 +65,8 @@ def _get_collector(self, player_id: str): env = self.env_fn() collector = task.wrap( BattleStepCollector( - cfg.policy.collect.collector, env, self.unroll_len, self.model_dict, self.all_policies, self.agent_num + cfg.policy.collect.collector, env, self.unroll_len, self.model_dict, self.model_time_dict, + self.all_policies, self.agent_num ) ) self._collectors[player_id] = collector diff --git a/ding/framework/middleware/tests/test_league_actor_one_process.py b/ding/framework/middleware/tests/test_league_actor_one_process.py index f1afb1d1fe..cce7fb97f3 100644 --- a/ding/framework/middleware/tests/test_league_actor_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_one_process.py @@ -82,7 +82,7 @@ def on_actor_data(actor_data): def _test_actor(ctx): sleep(0.3) task.emit(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), job) - sleep(0.3) + sleep(5) task.emit( EventEnum.LEARNER_SEND_MODEL, @@ -90,7 +90,6 @@ def _test_actor(ctx): player_id='main_player_default_0', state_dict=policy.learn_mode.state_dict(), train_iter=0 ) ) - sleep(5) try: print(testcases) assert all(testcases.values()) From 61883a7f7e610d344fa2196076b3c889bd1e4c7c Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Mon, 27 Jun 2022 17:05:31 +0800 Subject: [PATCH 168/229] change commit to run in k8s --- dizoo/distar/config/distar_config.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/dizoo/distar/config/distar_config.py b/dizoo/distar/config/distar_config.py index c462d3d671..60412fdf07 100644 --- a/dizoo/distar/config/distar_config.py +++ b/dizoo/distar/config/distar_config.py @@ -95,7 +95,7 @@ 'other': { 'replay_buffer': { 'type': 'naive', - 'replay_buffer_size': 10000, + 'replay_buffer_size': 20, 'deepcopy': False, 'enable_track_used_data': False, 'periodic_thruput_seconds': 60, @@ -105,7 +105,7 @@ 'player_category': ['default'], 'path_policy': 'league_demo/ckpt', 'active_players': { - 'main_player': 1 + 'main_player': 2 }, 'main_player': { 'one_phase_step': 10, # 20 From 05cc0f0962b501c5e1bba699f5d7b26d15fdea30 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Mon, 27 Jun 2022 18:33:31 +0800 Subject: [PATCH 169/229] fix(zms): fix the bug that when job begin, there is a infinite loop --- ding/framework/middleware/collector.py | 4 ++++ ding/framework/middleware/functional/collector.py | 8 -------- 2 files changed, 4 insertions(+), 8 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index fa44bbf834..ef56e89683 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -101,6 +101,8 @@ def __call__(self, ctx: "BattleContext") -> None: old = ctx.env_step while True: + if self.env.closed: + self.env.launch() self._update_policies(ctx.player_id_list) self._battle_inferencer(ctx) self._battle_rolloutor(ctx) @@ -180,6 +182,8 @@ def __call__(self, ctx: "BattleContext") -> None: # ctx.total_envstep_count = self.total_envstep_count # old = ctx.env_episode # while True: +# if self.env.closed: +# self.env.launch() # self._update_policies(ctx.player_id_list) # self._battle_inferencer(ctx) # self._battle_rolloutor(ctx) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 6a7dca28fe..b1ccd3ff8e 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -249,10 +249,6 @@ def _rollout(ctx: "OnlineRLContext"): def battle_inferencer(cfg: EasyDict, env: BaseEnvManager): def _battle_inferencer(ctx: "BattleContext"): - - if env.closed: - env.launch() - # Get current env obs. obs = env.ready_obs # the role of remain_episode is to mask necessary rollouts, avoid processing unnecessary data @@ -309,10 +305,6 @@ def _battle_rolloutor(ctx: "BattleContext"): def battle_inferencer_for_distar(cfg: EasyDict, env: BaseEnvManager): def _battle_inferencer(ctx: "BattleContext"): - - if env.closed: - env.launch() - # Get current env obs. obs = env.ready_obs assert isinstance(obs, dict) From d6ef348c621288a6851e1a87b8201000b1c4246c Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 28 Jun 2022 10:56:24 +0800 Subject: [PATCH 170/229] update train iter --- ding/framework/middleware/collector.py | 24 ++++++++++++------- .../middleware/functional/__init__.py | 2 +- .../middleware/functional/actor_data.py | 7 ++++++ .../middleware/functional/collector.py | 15 ++++++++---- ding/framework/middleware/league_actor.py | 10 ++++---- 5 files changed, 39 insertions(+), 19 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index ef56e89683..5c1ba1f6ed 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -7,6 +7,7 @@ from ding.envs import BaseEnvManager from ding.utils import log_every_sec from ding.framework import task +from ding.framework.middleware.functional import ModelInfo from .functional import inferencer, rolloutor, TransitionList, BattleTransitionList, \ battle_inferencer, battle_rolloutor @@ -19,7 +20,7 @@ class BattleStepCollector: def __init__( - self, cfg: EasyDict, env: BaseEnvManager, unroll_len: int, model_dict: Dict, model_time_dict: Dict, + self, cfg: EasyDict, env: BaseEnvManager, unroll_len: int, model_dict: Dict, model_info_dict: Dict, all_policies: Dict, agent_num: int ): self.cfg = cfg @@ -31,7 +32,7 @@ def __init__( self.total_envstep_count = 0 self.unroll_len = unroll_len self.model_dict = model_dict - self.model_time_dict = model_time_dict + self.model_info_dict = model_info_dict self.all_policies = all_policies self.agent_num = agent_num @@ -39,7 +40,9 @@ def __init__( self._transitions_list = [ BattleTransitionList(self.env.env_num, self.unroll_len) for _ in range(self.agent_num) ] - self._battle_rolloutor = task.wrap(battle_rolloutor(self.cfg, self.env, self._transitions_list)) + self._battle_rolloutor = task.wrap( + battle_rolloutor(self.cfg, self.env, self._transitions_list, self.model_info_dict) + ) def __del__(self) -> None: """ @@ -55,20 +58,22 @@ def __del__(self) -> None: def _update_policies(self, player_id_list) -> None: for player_id in player_id_list: # for this player, actor didn't recieve any new model, use initial model instead. - if self.model_time_dict.get(player_id) is None: - self.model_time_dict[player_id] = time.time() + if self.model_info_dict.get(player_id) is None: + self.model_info_dict[player_id] = ModelInfo( + get_model_time=time.time(), update_model_time=None, train_iter=0 + ) while True: time_now = time.time() - time_list = [time_now - self.model_time_dict[player_id] for player_id in player_id_list] + time_list = [time_now - self.model_info_dict[player_id].get_model_time for player_id in player_id_list] if any(x >= WAIT_MODEL_TIME for x in time_list): - for player_id in player_id_list: - if time_now - self.model_time_dict[player_id] >= WAIT_MODEL_TIME: + for index, player_id in enumerate(player_id_list): + if time_list[index] >= WAIT_MODEL_TIME: #TODO: log_every_sec can only print the first model that not updated log_every_sec( logging.WARNING, 5, 'In actor {}, model for {} is not updated for {} senconds, and need new model'.format( - task.router.node_id, player_id, time_now - self.model_time_dict[player_id] + task.router.node_id, player_id, time_list[index] ) ) time.sleep(1) @@ -84,6 +89,7 @@ def _update_policies(self, player_id_list) -> None: assert policy, "for player{}, policy should have been initialized already" # update policy model policy.load_state_dict(learner_model.state_dict) + self.model_info_dict[player_id].update_model_time = time.time() self.model_dict[player_id] = None def __call__(self, ctx: "BattleContext") -> None: diff --git a/ding/framework/middleware/functional/__init__.py b/ding/framework/middleware/functional/__init__.py index dde50535b2..e22066bc76 100644 --- a/ding/framework/middleware/functional/__init__.py +++ b/ding/framework/middleware/functional/__init__.py @@ -11,4 +11,4 @@ from .explorer import eps_greedy_handler, eps_greedy_masker from .advantage_estimator import gae_estimator from .enhancer import reward_estimator, her_data_enhancer, nstep_reward_enhancer -from .actor_data import ActorData, ActorDataMeta, ActorEnvTrajectories +from .actor_data import ActorData, ActorDataMeta, ActorEnvTrajectories, ModelInfo diff --git a/ding/framework/middleware/functional/actor_data.py b/ding/framework/middleware/functional/actor_data.py index 44ba0d7aea..342a5884f3 100644 --- a/ding/framework/middleware/functional/actor_data.py +++ b/ding/framework/middleware/functional/actor_data.py @@ -21,3 +21,10 @@ class ActorEnvTrajectories: class ActorData: meta: ActorDataMeta train_data: List[ActorEnvTrajectories] = field(default_factory=[]) + + +@dataclass +class ModelInfo: + get_model_time: float + update_model_time: float + train_iter: int diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index b1ccd3ff8e..a8c3030caf 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -1,7 +1,8 @@ -from typing import TYPE_CHECKING, Optional, Callable, List, Tuple, Any +from typing import TYPE_CHECKING, Optional, Callable, List, Tuple, Any, Dict from easydict import EasyDict from functools import reduce import treetensor.torch as ttorch +from ding import policy from ding.envs import BaseEnvManager from ding.policy import Policy import torch @@ -275,7 +276,7 @@ def _battle_inferencer(ctx: "BattleContext"): return _battle_inferencer -def battle_rolloutor(cfg: EasyDict, env: BaseEnvManager, transitions_list: List): +def battle_rolloutor(cfg: EasyDict, env: BaseEnvManager, transitions_list: List, model_info_dict: Dict): def _battle_rolloutor(ctx: "BattleContext"): timesteps = env.step(ctx.actions) @@ -289,7 +290,9 @@ def _battle_rolloutor(ctx: "BattleContext"): ctx.obs[policy_id][env_id], ctx.inference_output[policy_id][env_id], policy_timestep ) transition = ttorch.as_tensor(transition) - transition.collect_train_iter = ttorch.as_tensor([ctx.train_iter]) + transition.collect_train_iter = ttorch.as_tensor( + [model_info_dict[ctx.player_id_list[policy_id]].train_iter] + ) transitions_list[policy_id].append(env_id, transition) if timestep.done: ctx.current_policies[policy_id].reset([env_id]) @@ -329,7 +332,7 @@ def _battle_inferencer(ctx: "BattleContext"): return _battle_inferencer -def battle_rolloutor_for_distar(cfg: EasyDict, env: BaseEnvManager, transitions_list: List): +def battle_rolloutor_for_distar(cfg: EasyDict, env: BaseEnvManager, transitions_list: List, model_info_dict: Dict): def _battle_rolloutor(ctx: "BattleContext"): timesteps = env.step(ctx.actions) @@ -357,7 +360,9 @@ def _battle_rolloutor(ctx: "BattleContext"): for policy_id, _ in enumerate(ctx.current_policies): transition = ctx.current_policies[policy_id].process_transition(timestep) transition = EasyDict(transition) - transition.collect_train_iter = ttorch.as_tensor([ctx.train_iter]) + transition.collect_train_iter = ttorch.as_tensor( + [model_info_dict[ctx.player_id_list[policy_id]].train_iter] + ) # 2nd case when the number of transitions in one of all the episodes is shorter than unroll_len append_succeed = append_succeed and transitions_list[policy_id].append(env_id, transition) diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index e282005332..1859a5ce97 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -8,7 +8,7 @@ from ding.policy import Policy from ding.framework import task, EventEnum from ding.framework.middleware import BattleStepCollector -from ding.framework.middleware.functional import ActorData, ActorDataMeta +from ding.framework.middleware.functional import ActorData, ActorDataMeta, ModelInfo from ding.league.player import PlayerMeta from ding.utils.sparse_logging import log_every_sec @@ -33,7 +33,7 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.job_queue = queue.Queue() self.model_dict = {} self.model_dict_lock = Lock() - self.model_time_dict = {} + self.model_info_dict = {} self.agent_num = 2 @@ -50,7 +50,9 @@ def _on_learner_model(self, learner_model: "LearnerModel"): ) with self.model_dict_lock: self.model_dict[learner_model.player_id] = learner_model - self.model_time_dict[learner_model.player_id] = time.time() + self.model_info_dict[learner_model.player_id] = ModelInfo( + get_model_time=time.time(), update_model_time=None, train_iter=learner_model.train_iter + ) def _on_league_job(self, job: "Job"): """ @@ -65,7 +67,7 @@ def _get_collector(self, player_id: str): env = self.env_fn() collector = task.wrap( BattleStepCollector( - cfg.policy.collect.collector, env, self.unroll_len, self.model_dict, self.model_time_dict, + cfg.policy.collect.collector, env, self.unroll_len, self.model_dict, self.model_info_dict, self.all_policies, self.agent_num ) ) From 0cb987f03db2876e19797fb1ba147d6ea490a521 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 28 Jun 2022 14:40:35 +0800 Subject: [PATCH 171/229] change logic of update train_iter --- ding/framework/context.py | 1 - ding/framework/middleware/collector.py | 15 +++++++++------ ding/framework/middleware/functional/__init__.py | 2 +- .../framework/middleware/functional/actor_data.py | 8 ++++---- ding/framework/middleware/functional/collector.py | 4 ++-- ding/framework/middleware/league_actor.py | 14 ++++++++------ 6 files changed, 24 insertions(+), 20 deletions(-) diff --git a/ding/framework/context.py b/ding/framework/context.py index 97e178a5bd..873cd37a91 100644 --- a/ding/framework/context.py +++ b/ding/framework/context.py @@ -89,7 +89,6 @@ def __init__(self, *args, **kwargs) -> None: self.env_episode = 0 self.env_step = 0 self.total_envstep_count = 0 - self.train_iter = 0 self.collect_kwargs = {} self.current_policies = [] diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 5c1ba1f6ed..3ddddd0821 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -2,12 +2,14 @@ from typing import Dict, TYPE_CHECKING import time from ditk import logging +from more_itertools import last +from ding.league import player from ding.policy import get_random_policy from ding.envs import BaseEnvManager from ding.utils import log_every_sec from ding.framework import task -from ding.framework.middleware.functional import ModelInfo +from ding.framework.middleware.functional import PlayerModelInfo from .functional import inferencer, rolloutor, TransitionList, BattleTransitionList, \ battle_inferencer, battle_rolloutor @@ -57,15 +59,15 @@ def __del__(self) -> None: def _update_policies(self, player_id_list) -> None: for player_id in player_id_list: - # for this player, actor didn't recieve any new model, use initial model instead. + # for this player, in the beginning of actor's lifetime, actor didn't recieve any new model, use initial model instead. if self.model_info_dict.get(player_id) is None: - self.model_info_dict[player_id] = ModelInfo( - get_model_time=time.time(), update_model_time=None, train_iter=0 + self.model_info_dict[player_id] = PlayerModelInfo( + get_new_model_time=time.time(), update_new_model_time=None ) while True: time_now = time.time() - time_list = [time_now - self.model_info_dict[player_id].get_model_time for player_id in player_id_list] + time_list = [time_now - self.model_info_dict[player_id].get_new_model_time for player_id in player_id_list] if any(x >= WAIT_MODEL_TIME for x in time_list): for index, player_id in enumerate(player_id_list): if time_list[index] >= WAIT_MODEL_TIME: @@ -89,7 +91,8 @@ def _update_policies(self, player_id_list) -> None: assert policy, "for player{}, policy should have been initialized already" # update policy model policy.load_state_dict(learner_model.state_dict) - self.model_info_dict[player_id].update_model_time = time.time() + self.model_info_dict[player_id].update_new_model_time = time.time() + self.model_info_dict[player_id].update_train_iter = learner_model.train_iter self.model_dict[player_id] = None def __call__(self, ctx: "BattleContext") -> None: diff --git a/ding/framework/middleware/functional/__init__.py b/ding/framework/middleware/functional/__init__.py index e22066bc76..a15af5a844 100644 --- a/ding/framework/middleware/functional/__init__.py +++ b/ding/framework/middleware/functional/__init__.py @@ -11,4 +11,4 @@ from .explorer import eps_greedy_handler, eps_greedy_masker from .advantage_estimator import gae_estimator from .enhancer import reward_estimator, her_data_enhancer, nstep_reward_enhancer -from .actor_data import ActorData, ActorDataMeta, ActorEnvTrajectories, ModelInfo +from .actor_data import ActorData, ActorDataMeta, ActorEnvTrajectories, PlayerModelInfo diff --git a/ding/framework/middleware/functional/actor_data.py b/ding/framework/middleware/functional/actor_data.py index 342a5884f3..f86cd12325 100644 --- a/ding/framework/middleware/functional/actor_data.py +++ b/ding/framework/middleware/functional/actor_data.py @@ -24,7 +24,7 @@ class ActorData: @dataclass -class ModelInfo: - get_model_time: float - update_model_time: float - train_iter: int +class PlayerModelInfo: + get_new_model_time: float + update_new_model_time: float + update_train_iter: int = 0 diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index a8c3030caf..6cd2e4de86 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -291,7 +291,7 @@ def _battle_rolloutor(ctx: "BattleContext"): ) transition = ttorch.as_tensor(transition) transition.collect_train_iter = ttorch.as_tensor( - [model_info_dict[ctx.player_id_list[policy_id]].train_iter] + [model_info_dict[ctx.player_id_list[policy_id]].update_train_iter] ) transitions_list[policy_id].append(env_id, transition) if timestep.done: @@ -361,7 +361,7 @@ def _battle_rolloutor(ctx: "BattleContext"): transition = ctx.current_policies[policy_id].process_transition(timestep) transition = EasyDict(transition) transition.collect_train_iter = ttorch.as_tensor( - [model_info_dict[ctx.player_id_list[policy_id]].train_iter] + [model_info_dict[ctx.player_id_list[policy_id]].update_train_iter] ) # 2nd case when the number of transitions in one of all the episodes is shorter than unroll_len diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 1859a5ce97..4700ab1a19 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -8,7 +8,7 @@ from ding.policy import Policy from ding.framework import task, EventEnum from ding.framework.middleware import BattleStepCollector -from ding.framework.middleware.functional import ActorData, ActorDataMeta, ModelInfo +from ding.framework.middleware.functional import ActorData, ActorDataMeta, PlayerModelInfo from ding.league.player import PlayerMeta from ding.utils.sparse_logging import log_every_sec @@ -50,9 +50,13 @@ def _on_learner_model(self, learner_model: "LearnerModel"): ) with self.model_dict_lock: self.model_dict[learner_model.player_id] = learner_model - self.model_info_dict[learner_model.player_id] = ModelInfo( - get_model_time=time.time(), update_model_time=None, train_iter=learner_model.train_iter - ) + if self.model_info_dict.get(learner_model.player_id): + self.model_info_dict[learner_model.player_id].get_new_model_time = time.time() + self.model_info_dict[learner_model.player_id].update_new_model_time = None + else: + self.model_info_dict[learner_model.player_id] = PlayerModelInfo( + get_new_model_time=time.time(), update_new_model_time=None + ) def _on_league_job(self, job: "Job"): """ @@ -141,7 +145,6 @@ def __call__(self, ctx: "BattleContext"): ctx.n_episode = self.cfg.policy.collect.n_episode assert ctx.n_episode >= self.env_num, "Please make sure n_episode >= env_num" - ctx.train_iter = main_player.total_agent_step ctx.episode_info = [[] for _ in range(self.agent_num)] while True: @@ -301,7 +304,6 @@ def __call__(self, ctx: "BattleContext"): # task.router.node_id # ) -# ctx.train_iter = main_player.total_agent_step # ctx.episode_info = [[] for _ in range(self.agent_num)] # ctx.remain_episode = ctx.n_episode # while True: From 7012966481daad474b23f384ceced70db84fa7e8 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 28 Jun 2022 15:32:53 +0800 Subject: [PATCH 172/229] add check of main player --- ding/framework/middleware/collector.py | 1 - ding/framework/middleware/league_actor.py | 42 +++++++++++------------ 2 files changed, 21 insertions(+), 22 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 3ddddd0821..a902299948 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -165,7 +165,6 @@ def __call__(self, ctx: "BattleContext") -> None: # self.env.close() # def _update_policies(self, player_id_list) -> None: -# # TODO(zms): update train_iter, update train_iter and player_id inside policy is a good idea # for player_id in player_id_list: # if self.model_dict.get(player_id) is None: # continue diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 4700ab1a19..e8dbbf58b2 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -132,6 +132,7 @@ def __call__(self, ctx: "BattleContext"): ) ctx.player_id_list = [player.player_id for player in job.players] + main_player_idx = [idx for idx, player in enumerate(job.players) if player.player_id == job.launch_player] self.agent_num = len(job.players) collector = self._get_collector(job.launch_player) @@ -152,28 +153,24 @@ def __call__(self, ctx: "BattleContext"): old_envstep = ctx.total_envstep_count collector(ctx) - # ctx.trajectories_list[0] for policy_id 0 - # ctx.trajectories_list[0][0] for first env - if len(ctx.trajectories_list[0]) > 0: - for traj in ctx.trajectories_list[0][0].trajectories: - assert len(traj) == self.unroll_len + 1 if ctx.job_finish is True: logging.info('[Actor {}] finish current job !'.format(task.router.node_id)) - assert len(ctx.trajectories_list[0][0].trajectories) > 0 - # TODO(zms): 判断是不是main_player - if not job.is_eval and len(ctx.trajectories_list[0]) > 0: - trajectories = ctx.trajectories_list[0] - log_every_sec( - logging.INFO, 5, '[Actor {}] send {} trajectories.'.format(task.router.node_id, len(trajectories)) - ) - meta_data = ActorDataMeta( - player_total_env_step=ctx.total_envstep_count, - actor_id=task.router.node_id, - send_wall_time=time.time() - ) - actor_data = ActorData(meta=meta_data, train_data=trajectories) - task.emit(EventEnum.ACTOR_SEND_DATA.format(player=job.launch_player), actor_data) - log_every_sec(logging.INFO, 5, '[Actor {}] send data\n'.format(task.router.node_id)) + + for idx in main_player_idx: + if not job.is_eval and len(ctx.trajectories_list[idx]) > 0: + trajectories = ctx.trajectories_list[idx] + log_every_sec( + logging.INFO, 5, + '[Actor {}] send {} trajectories.'.format(task.router.node_id, len(trajectories)) + ) + meta_data = ActorDataMeta( + player_total_env_step=ctx.total_envstep_count, + actor_id=task.router.node_id, + send_wall_time=time.time() + ) + actor_data = ActorData(meta=meta_data, train_data=trajectories) + task.emit(EventEnum.ACTOR_SEND_DATA.format(player=job.launch_player), actor_data) + log_every_sec(logging.INFO, 5, '[Actor {}] send data\n'.format(task.router.node_id)) ctx.trajectories_list = [] time_end = time.time() @@ -191,7 +188,10 @@ def __call__(self, ctx: "BattleContext"): ) if ctx.job_finish is True: - job.result = [e['result'] for e in ctx.episode_info[0]] + job.result = [] + for idx in main_player_idx: + for e in ctx.episode_info[idx]: + job.result.append(e['result']) task.emit(EventEnum.ACTOR_FINISH_JOB, job) ctx.episode_info = [[] for _ in range(self.agent_num)] logging.info('[Actor {}] job finish, send job\n'.format(task.router.node_id)) From 7912613defb325d91713adb6e6c5f293cf6a4abb Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 28 Jun 2022 16:40:35 +0800 Subject: [PATCH 173/229] fix bug --- ding/framework/middleware/collector.py | 2 -- 1 file changed, 2 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index a902299948..d78f9c85e8 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -2,8 +2,6 @@ from typing import Dict, TYPE_CHECKING import time from ditk import logging -from more_itertools import last -from ding.league import player from ding.policy import get_random_policy from ding.envs import BaseEnvManager From 2b51afcc0be6c9ac3c995ccf903858ba74ad4599 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 28 Jun 2022 17:07:47 +0800 Subject: [PATCH 174/229] fix bug --- ding/framework/context.py | 1 + 1 file changed, 1 insertion(+) diff --git a/ding/framework/context.py b/ding/framework/context.py index 873cd37a91..97e178a5bd 100644 --- a/ding/framework/context.py +++ b/ding/framework/context.py @@ -89,6 +89,7 @@ def __init__(self, *args, **kwargs) -> None: self.env_episode = 0 self.env_step = 0 self.total_envstep_count = 0 + self.train_iter = 0 self.collect_kwargs = {} self.current_policies = [] From c912e4bc4833c3b7abf98dc78e92dc44d56d71d2 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 28 Jun 2022 18:17:57 +0800 Subject: [PATCH 175/229] change structure of map_size from list to point --- dizoo/distar/envs/distar_env.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/dizoo/distar/envs/distar_env.py b/dizoo/distar/envs/distar_env.py index 74d7785706..f6a6f191ea 100644 --- a/dizoo/distar/envs/distar_env.py +++ b/dizoo/distar/envs/distar_env.py @@ -17,10 +17,10 @@ def __init__(self, cfg): def reset(self): observations, game_info, map_name = super(DIStarEnv, self).reset() - map_size = get_map_size(map_name) for policy_id, policy_obs in observations.items(): policy_obs['game_info'] = game_info[policy_id] + map_size = game_info[policy_id].start_raw.map_size policy_obs['map_name'] = map_name policy_obs['map_size'] = map_size From 83d93d0f2f3ba39b35fe1cb23d6de3881750b12a Mon Sep 17 00:00:00 2001 From: niuyazhe Date: Tue, 28 Jun 2022 18:33:49 +0800 Subject: [PATCH 176/229] test(nyz): add naive distar policy collect test --- dizoo/distar/envs/__init__.py | 2 +- dizoo/distar/envs/distar_env.py | 25 +- dizoo/distar/envs/fake_data.py | 486 ++++++++++++++++++ .../distar/{policy => envs}/z_files/12D.json | 0 .../{policy => envs}/z_files/1758k.json | 0 .../distar/{policy => envs}/z_files/3map.json | 0 .../z_files/7map_filter_spine.json | 0 .../z_files/NewRepugnancy.json | 0 .../{policy => envs}/z_files/filter.json | 0 .../{policy => envs}/z_files/lurker.json | 0 .../{policy => envs}/z_files/mutalisk.json | 0 .../{policy => envs}/z_files/nydus.json | 0 .../{policy => envs}/z_files/perfect_z.json | 0 .../{policy => envs}/z_files/stairs.json | 0 .../{policy => envs}/z_files/worker_rush.json | 0 dizoo/distar/policy/distar_policy.py | 36 +- dizoo/distar/policy/test_distar_policy.py | 11 +- 17 files changed, 530 insertions(+), 30 deletions(-) rename dizoo/distar/{policy => envs}/z_files/12D.json (100%) rename dizoo/distar/{policy => envs}/z_files/1758k.json (100%) rename dizoo/distar/{policy => envs}/z_files/3map.json (100%) rename dizoo/distar/{policy => envs}/z_files/7map_filter_spine.json (100%) rename dizoo/distar/{policy => envs}/z_files/NewRepugnancy.json (100%) rename dizoo/distar/{policy => envs}/z_files/filter.json (100%) rename dizoo/distar/{policy => envs}/z_files/lurker.json (100%) rename dizoo/distar/{policy => envs}/z_files/mutalisk.json (100%) rename dizoo/distar/{policy => envs}/z_files/nydus.json (100%) rename dizoo/distar/{policy => envs}/z_files/perfect_z.json (100%) rename dizoo/distar/{policy => envs}/z_files/stairs.json (100%) rename dizoo/distar/{policy => envs}/z_files/worker_rush.json (100%) diff --git a/dizoo/distar/envs/__init__.py b/dizoo/distar/envs/__init__.py index 5837c285ba..5fec4947d1 100644 --- a/dizoo/distar/envs/__init__.py +++ b/dizoo/distar/envs/__init__.py @@ -2,4 +2,4 @@ from .meta import * from .static_data import RACE_DICT, BEGIN_ACTIONS, ACTION_RACE_MASK, SELECTED_UNITS_MASK, ACTIONS from .stat import Stat -from .fake_data import get_fake_rl_trajectory, fake_rl_data_batch_with_last +from .fake_data import get_fake_rl_trajectory, get_fake_env_reset_data, get_fake_env_step_data diff --git a/dizoo/distar/envs/distar_env.py b/dizoo/distar/envs/distar_env.py index c61f3c8454..9201b33c83 100644 --- a/dizoo/distar/envs/distar_env.py +++ b/dizoo/distar/envs/distar_env.py @@ -2,7 +2,7 @@ from copy import deepcopy from collections import defaultdict from s2clientprotocol import sc2api_pb2 as sc_pb -from pysc2.lib import named_array, colors +from pysc2.lib import named_array, colors, point from pysc2.lib.features import Effects, ScoreCategories, FeatureType, Feature from torch import int8, uint8, int16, int32, float32, float16, int64 @@ -168,13 +168,15 @@ def __repr__(self): def parse_new_game(data, z_path: str, z_idx: Optional[None] = List): # init Z - z_path = osp.join(osp.dirname(__file__), '../envs', z_path) + z_path = osp.join(osp.dirname(__file__), "z_files", z_path) with open(z_path, 'r') as f: z_data = json.load(f) raw_ob = data['raw_obs'] game_info = data['game_info'] map_size = data['map_size'] + if isinstance(map_size, list): + map_size = point.Point(map_size[0], map_size[1]) map_name = data['map_name'] requested_races = { info.player_id: info.race_requested @@ -210,7 +212,7 @@ def parse_new_game(data, z_path: str, z_idx: Optional[None] = List): target_building_order, target_cumulative_stat, bo_location, target_z_loop, z_type = z else: target_building_order, target_cumulative_stat, bo_location, target_z_loop = z - return race, map_size, target_building_order, target_cumulative_stat, bo_location, target_z_loop + return race, requested_races, map_size, target_building_order, target_cumulative_stat, bo_location, target_z_loop class FeatureUnit(enum.IntEnum): @@ -258,7 +260,7 @@ class FeatureUnit(enum.IntEnum): class MinimapFeatures(collections.namedtuple( "MinimapFeatures", - ["height_map", "visibility_map", "creep", "player_relative", "alerts", "pathable", "buildable"])): + ["height_map", "visibility_map", "creep", "player_relative", "alerts", "pathable", "buildable"])): """The set of minimap feature layers.""" __slots__ = () @@ -359,10 +361,10 @@ def compute_battle_score(obs): return battle_score -def transform_obs(self, obs, padding_spatial=False, opponent_obs=None): +def transform_obs(obs, map_size, requested_races, padding_spatial=False, opponent_obs=None): spatial_info = defaultdict(list) scalar_info = {} - entity_info = dict() + entity_info = {} game_info = {} raw = obs.observation.raw_data @@ -380,7 +382,7 @@ def transform_obs(self, obs, padding_spatial=False, opponent_obs=None): if name in ['LiberatorDefenderZone', 'LurkerSpines'] and e.owner == 1: continue for p in e.pos: - location = int(p.x) + int(self.map_size.y - p.y) * DEFAULT_SPATIAL_SIZE[1] + location = int(p.x) + int(map_size.y - p.y) * DEFAULT_SPATIAL_SIZE[1] spatial_info['effect_' + name].append(location) for k, _ in SPATIAL_INFO: if 'effect' in k: @@ -538,7 +540,7 @@ def get_addon_type(tag): elif k == 'vespene_contents': entity_info[k] = torch.as_tensor(raw_entity_info[:, 'vespene_contents'], dtype=dtype) / 2500 elif k == 'y': - entity_info[k] = torch.as_tensor(self.map_size.y - raw_entity_info[:, 'y'], dtype=dtype) + entity_info[k] = torch.as_tensor(map_size.y - raw_entity_info[:, 'y'], dtype=dtype) else: entity_info[k] = torch.as_tensor(raw_entity_info[:, k], dtype=dtype) @@ -554,8 +556,8 @@ def get_addon_type(tag): ) scalar_info['agent_statistics'] = torch.log(scalar_info['agent_statistics'] + 1) - scalar_info["home_race"] = torch.tensor(self._requested_races[player.player_id], dtype=torch.uint8) - for player_id, race in self._requested_races.items(): + scalar_info["home_race"] = torch.tensor(requested_races[player.player_id], dtype=torch.uint8) + for player_id, race in requested_races.items(): if player_id != player.player_id: scalar_info["away_race"] = torch.tensor(race, dtype=torch.uint8) @@ -586,7 +588,6 @@ def get_addon_type(tag): ) # game info - game_info['map_name'] = self._map_name game_info['action_result'] = [o.result for o in obs.action_errors] game_info['game_loop'] = obs.observation.game_loop game_info['tags'] = tags @@ -628,7 +629,7 @@ def get_addon_type(tag): unit_x = torch.cat([enemy_x, entity_info['x'][entity_info['alliance'] == 1]], dim=0) enemy_y = torch.as_tensor(enemy_y, dtype=float32) - enemy_y = torch.as_tensor(self.map_size.y - enemy_y, dtype=uint8) + enemy_y = torch.as_tensor(map_size.y - enemy_y, dtype=uint8) unit_y = torch.cat([enemy_y, entity_info['y'][entity_info['alliance'] == 1]], dim=0) total_unit_count = len(unit_y) unit_alliance += [0] * (total_unit_count - len(unit_alliance)) diff --git a/dizoo/distar/envs/fake_data.py b/dizoo/distar/envs/fake_data.py index 569ce70031..91fddc463d 100644 --- a/dizoo/distar/envs/fake_data.py +++ b/dizoo/distar/envs/fake_data.py @@ -1,6 +1,15 @@ from typing import Sequence +import math +import six +import numpy as np import torch +from pysc2.lib import features, actions, point, units +from pysc2.maps.melee import Melee +from s2clientprotocol import raw_pb2 +from s2clientprotocol import sc2api_pb2 as sc_pb +from s2clientprotocol import score_pb2, common_pb2 + from ding.utils.data import default_collate from .meta import MAX_DELAY, MAX_ENTITY_NUM, NUM_ACTIONS, NUM_UNIT_TYPES, NUM_UPGRADES, NUM_CUMULATIVE_STAT_ACTIONS, \ NUM_BEGINNING_ORDER_ACTIONS, NUM_UNIT_MIX_ABILITIES, NUM_QUEUE_ACTION, NUM_BUFFS, NUM_ADDON, \ @@ -183,3 +192,480 @@ def fake_rl_data_batch_with_last(unroll_len=4): def get_fake_rl_trajectory(batch_size=3, unroll_len=4): data_batch = [fake_rl_data_batch_with_last(unroll_len) for _ in range(batch_size)] return data_batch + + +class Unit(object): + """Class to hold unit data for the builder.""" + + def __init__( + self, + unit_type, # see lib/units.py + player_relative, # features.PlayerRelative, + health, + shields=0, + energy=0, + transport_slots_taken=0, + build_progress=1.0 + ): + + self.unit_type = unit_type + self.player_relative = player_relative + self.health = health + self.shields = shields + self.energy = energy + self.transport_slots_taken = transport_slots_taken + self.build_progress = build_progress + + def fill(self, unit_proto): + """Fill a proto unit data object from this Unit.""" + unit_proto.unit_type = self.unit_type + unit_proto.player_relative = self.player_relative + unit_proto.health = self.health + unit_proto.shields = self.shields + unit_proto.energy = self.energy + unit_proto.transport_slots_taken = self.transport_slots_taken + unit_proto.build_progress = self.build_progress + + def as_array(self): + """Return the unit represented as a numpy array.""" + return np.array( + [ + self.unit_type, self.player_relative, self.health, self.shields, self.energy, + self.transport_slots_taken, + int(self.build_progress * 100) + ], + dtype=np.int32 + ) + + def as_dict(self): + return vars(self) + + +class FeatureUnit(object): + """Class to hold feature unit data for the builder.""" + + def __init__( + self, + unit_type, # see lib/units + alliance, # features.PlayerRelative, + owner, # 1-15, 16=neutral + pos, # common_pb2.Point, + radius, + health, + health_max, + is_on_screen, + shield=0, + shield_max=0, + energy=0, + energy_max=0, + cargo_space_taken=0, + cargo_space_max=0, + build_progress=1.0, + facing=0.0, + display_type=raw_pb2.Visible, # raw_pb.DisplayType + cloak=raw_pb2.NotCloaked, # raw_pb.CloakState + is_selected=False, + is_blip=False, + is_powered=True, + mineral_contents=0, + vespene_contents=0, + assigned_harvesters=0, + ideal_harvesters=0, + weapon_cooldown=0.0, + orders=None, + is_flying=False, + is_burrowed=False, + is_hallucination=False, + is_active=False, + attack_upgrade_level=0, + armor_upgrade_level=0, + shield_upgrade_level=0, + ): + + self.unit_type = unit_type + self.alliance = alliance + self.owner = owner + self.pos = pos + self.radius = radius + self.health = health + self.health_max = health_max + self.is_on_screen = is_on_screen + self.shield = shield + self.shield_max = shield_max + self.energy = energy + self.energy_max = energy_max + self.cargo_space_taken = cargo_space_taken + self.cargo_space_max = cargo_space_max + self.build_progress = build_progress + self.facing = facing + self.display_type = display_type + self.cloak = cloak + self.is_selected = is_selected + self.is_blip = is_blip + self.is_powered = is_powered + self.mineral_contents = mineral_contents + self.vespene_contents = vespene_contents + self.assigned_harvesters = assigned_harvesters + self.ideal_harvesters = ideal_harvesters + self.weapon_cooldown = weapon_cooldown + self.is_flying = is_flying + self.is_burrowed = is_burrowed + self.is_hallucination = is_hallucination + self.is_active = is_active + self.attack_upgrade_level = attack_upgrade_level + self.armor_upgrade_level = armor_upgrade_level + self.shield_upgrade_level = shield_upgrade_level + if orders is not None: + self.orders = orders + + def as_dict(self): + return vars(self) + + +class FeatureResource(object): + """Class to hold feature unit data for the builder.""" + + def __init__( + self, + unit_type, # see lib/units + alliance, # features.PlayerRelative, + owner, # 1-15, 16=neutral + pos, # common_pb2.Point, + radius, + is_on_screen, + build_progress=1.0, + facing=0.0, + display_type=raw_pb2.Visible, # raw_pb.DisplayType + cloak=raw_pb2.NotCloaked, # raw_pb.CloakState + is_blip=False, + is_powered=True, + ): + + self.unit_type = unit_type + self.alliance = alliance + self.owner = owner + self.pos = pos + self.radius = radius + self.is_on_screen = is_on_screen + self.build_progress = build_progress + self.facing = facing + self.display_type = display_type + self.cloak = cloak + self.is_blip = is_blip + self.is_powered = is_powered + + def as_dict(self): + return vars(self) + + +class Builder(object): + """For test code - build a dummy ResponseObservation proto.""" + + def __init__(self, obs_spec): + self._game_loop = 1 + self._player_common = sc_pb.PlayerCommon( + player_id=1, + minerals=20, + vespene=50, + food_cap=36, + food_used=21, + food_army=6, + food_workers=15, + idle_worker_count=2, + army_count=6, + warp_gate_count=0, + ) + + self._score = 300 + self._score_type = Melee + self._score_details = score_pb2.ScoreDetails( + idle_production_time=0, + idle_worker_time=0, + total_value_units=190, + total_value_structures=230, + killed_value_units=0, + killed_value_structures=0, + collected_minerals=2130, + collected_vespene=560, + collection_rate_minerals=50, + collection_rate_vespene=20, + spent_minerals=2000, + spent_vespene=500, + food_used=score_pb2.CategoryScoreDetails( + none=0.0, army=0.0, economy=self._player_common.food_used, technology=0.0, upgrade=0.0 + ), + killed_minerals=score_pb2.CategoryScoreDetails( + none=0.0, army=0.0, economy=0.0, technology=0.0, upgrade=0.0 + ), + killed_vespene=score_pb2.CategoryScoreDetails(none=0.0, army=0.0, economy=0.0, technology=0.0, upgrade=0.0), + lost_minerals=score_pb2.CategoryScoreDetails(none=0.0, army=0.0, economy=0.0, technology=0.0, upgrade=0.0), + lost_vespene=score_pb2.CategoryScoreDetails(none=0.0, army=0.0, economy=0.0, technology=0.0, upgrade=0.0), + friendly_fire_minerals=score_pb2.CategoryScoreDetails( + none=0.0, army=0.0, economy=0.0, technology=0.0, upgrade=0.0 + ), + friendly_fire_vespene=score_pb2.CategoryScoreDetails( + none=0.0, army=0.0, economy=0.0, technology=0.0, upgrade=0.0 + ), + used_minerals=score_pb2.CategoryScoreDetails(none=0.0, army=0.0, economy=0.0, technology=0.0, upgrade=0.0), + used_vespene=score_pb2.CategoryScoreDetails(none=0.0, army=0.0, economy=0.0, technology=0.0, upgrade=0.0), + total_used_minerals=score_pb2.CategoryScoreDetails( + none=0.0, army=0.0, economy=0.0, technology=0.0, upgrade=0.0 + ), + total_used_vespene=score_pb2.CategoryScoreDetails( + none=0.0, army=0.0, economy=0.0, technology=0.0, upgrade=0.0 + ), + total_damage_dealt=score_pb2.VitalScoreDetails(life=0.0, shields=0.0, energy=0.0), + total_damage_taken=score_pb2.VitalScoreDetails(life=0.0, shields=0.0, energy=0.0), + total_healed=score_pb2.VitalScoreDetails(life=0.0, shields=0.0, energy=0.0), + ) + + self._obs_spec = obs_spec + self._single_select = None + self._multi_select = None + self._build_queue = None + self._production = None + self._feature_units = None + + def game_loop(self, game_loop): + self._game_loop = game_loop + return self + + # pylint:disable=unused-argument + def player_common( + self, + player_id=None, + minerals=None, + vespene=None, + food_cap=None, + food_used=None, + food_army=None, + food_workers=None, + idle_worker_count=None, + army_count=None, + warp_gate_count=None, + larva_count=None + ): + """Update some or all of the fields in the PlayerCommon data.""" + + args = dict(locals()) + for key, value in six.iteritems(args): + if value is not None and key != 'self': + setattr(self._player_common, key, value) + return self + + def score(self, score): + self._score = score + return self + + def score_details( + self, + idle_production_time=None, + idle_worker_time=None, + total_value_units=None, + total_value_structures=None, + killed_value_units=None, + killed_value_structures=None, + collected_minerals=None, + collected_vespene=None, + collection_rate_minerals=None, + collection_rate_vespene=None, + spent_minerals=None, + spent_vespene=None + ): + """Update some or all of the fields in the ScoreDetails data.""" + + args = dict(locals()) + for key, value in six.iteritems(args): + if value is not None and key != 'self': + setattr(self._score_details, key, value) + return self + + # pylint:enable=unused-argument + + def score_by_category(self, entry_name, none, army, economy, technology, upgrade): + + field = getattr(self._score_details, entry_name) + field.CopyFrom( + score_pb2.CategoryScoreDetails( + none=none, army=army, economy=economy, technology=technology, upgrade=upgrade + ) + ) + + def score_by_vital(self, entry_name, life, shields, energy): + field = getattr(self._score_details, entry_name) + field.CopyFrom(score_pb2.VitalScoreDetails(life=life, shields=shields, energy=energy)) + + def single_select(self, unit): + self._single_select = unit + return self + + def multi_select(self, units): + self._multi_select = units + return self + + def build_queue(self, build_queue, production=None): + self._build_queue = build_queue + self._production = production + return self + + def feature_units(self, feature_units): + self._feature_units = feature_units + return self + + def build(self): + """Builds and returns a proto ResponseObservation.""" + response_observation = sc_pb.ResponseObservation() + obs = response_observation.observation + + obs.game_loop = self._game_loop + obs.player_common.CopyFrom(self._player_common) + + obs.score.score_type = 2 + obs.score.score = self._score + obs.score.score_details.CopyFrom(self._score_details) + + def fill(image_data, size, bits): + image_data.bits_per_pixel = bits + image_data.size.y = size[0] + image_data.size.x = size[1] + image_data.data = b'\0' * int(math.ceil(size[0] * size[1] * bits / 8)) + + if 'feature_screen' in self._obs_spec: + for feature in features.SCREEN_FEATURES: + fill(getattr(obs.feature_layer_data.renders, feature.name), self._obs_spec['feature_screen'][1:], 8) + + if 'feature_minimap' in self._obs_spec: + for feature in features.MINIMAP_FEATURES: + fill( + getattr(obs.feature_layer_data.minimap_renders, feature.name), + self._obs_spec['feature_minimap'][1:], 8 + ) + + # if 'rgb_screen' in self._obs_spec: + # fill(obs.render_data.map, self._obs_spec['rgb_screen'][:2], 24) + + # if 'rgb_minimap' in self._obs_spec: + # fill(obs.render_data.minimap, self._obs_spec['rgb_minimap'][:2], 24) + + if self._single_select: + self._single_select.fill(obs.ui_data.single.unit) + + if self._multi_select: + for unit in self._multi_select: + obs.ui_data.multi.units.add(**unit.as_dict()) + + if self._build_queue: + for unit in self._build_queue: + obs.ui_data.production.build_queue.add(**unit.as_dict()) + + if self._production: + for item in self._production: + obs.ui_data.production.production_queue.add(**item) + + if self._feature_units: + for tag, feature_unit in enumerate(self._feature_units, 1): + args = dict(tag=tag) + args.update(feature_unit.as_dict()) + obs.raw_data.units.add(**args) + + return response_observation + + +def fake_raw_obs(): + _features = features.Features( + features.AgentInterfaceFormat( + feature_dimensions=features.Dimensions(screen=(1, 1), minimap=(W, H)), + rgb_dimensions=features.Dimensions(screen=(128, 124), minimap=(1, 1)), + action_space=actions.ActionSpace.RAW, + use_raw_units=True + ), + map_size=point.Point(256, 256) + ) + obs_spec = _features.observation_spec() + builder = Builder(obs_spec).game_loop(0) + feature_units = [ + FeatureResource( + units.Neutral.MineralField, + features.PlayerRelative.NEUTRAL, + owner=16, + pos=common_pb2.Point(x=10, y=10, z=0), + facing=0.0, + radius=1.125, + build_progress=1.0, + cloak=raw_pb2.CloakedUnknown, + is_on_screen=True, + is_blip=False, + is_powered=False, + ), + FeatureResource( + units.Neutral.MineralField, + features.PlayerRelative.NEUTRAL, + owner=16, + pos=common_pb2.Point(x=120, y=10, z=0), + facing=0.0, + radius=1.125, + build_progress=1.0, + cloak=raw_pb2.CloakedUnknown, + is_on_screen=False, + is_blip=False, + is_powered=False, + ), + FeatureResource( + units.Neutral.MineralField, + features.PlayerRelative.NEUTRAL, + owner=16, + pos=common_pb2.Point(x=10, y=120, z=0), + facing=0.0, + radius=1.125, + build_progress=1.0, + cloak=raw_pb2.CloakedUnknown, + is_on_screen=False, + is_blip=False, + is_powered=False, + ), + FeatureResource( + units.Neutral.MineralField, + features.PlayerRelative.NEUTRAL, + owner=16, + pos=common_pb2.Point(x=120, y=120, z=0), + facing=0.0, + radius=1.125, + build_progress=1.0, + cloak=raw_pb2.CloakedUnknown, + is_on_screen=False, + is_blip=False, + is_powered=False, + ), + FeatureUnit( + units.Zerg.Drone, + features.PlayerRelative.SELF, + owner=1, + display_type=raw_pb2.Visible, + pos=common_pb2.Point(x=10, y=11, z=0), + radius=0.375, + facing=3, + cloak=raw_pb2.NotCloaked, + is_selected=False, + is_on_screen=True, + is_blip=False, + health_max=40, + health=40, + is_flying=False, + is_burrowed=False + ), + ] + + builder.feature_units(feature_units) + return builder.build() + + +def get_fake_env_step_data(): + return {'raw_obs': fake_raw_obs(), 'opponent_obs': None, 'action_result': [0]} + + +def get_fake_env_reset_data(): + import os + import pickle + with open(os.path.join(os.path.dirname(__file__), 'fake_reset.pkl'), 'rb') as f: + data = pickle.load(f) + return data diff --git a/dizoo/distar/policy/z_files/12D.json b/dizoo/distar/envs/z_files/12D.json similarity index 100% rename from dizoo/distar/policy/z_files/12D.json rename to dizoo/distar/envs/z_files/12D.json diff --git a/dizoo/distar/policy/z_files/1758k.json b/dizoo/distar/envs/z_files/1758k.json similarity index 100% rename from dizoo/distar/policy/z_files/1758k.json rename to dizoo/distar/envs/z_files/1758k.json diff --git a/dizoo/distar/policy/z_files/3map.json b/dizoo/distar/envs/z_files/3map.json similarity index 100% rename from dizoo/distar/policy/z_files/3map.json rename to dizoo/distar/envs/z_files/3map.json diff --git a/dizoo/distar/policy/z_files/7map_filter_spine.json b/dizoo/distar/envs/z_files/7map_filter_spine.json similarity index 100% rename from dizoo/distar/policy/z_files/7map_filter_spine.json rename to dizoo/distar/envs/z_files/7map_filter_spine.json diff --git a/dizoo/distar/policy/z_files/NewRepugnancy.json b/dizoo/distar/envs/z_files/NewRepugnancy.json similarity index 100% rename from dizoo/distar/policy/z_files/NewRepugnancy.json rename to dizoo/distar/envs/z_files/NewRepugnancy.json diff --git a/dizoo/distar/policy/z_files/filter.json b/dizoo/distar/envs/z_files/filter.json similarity index 100% rename from dizoo/distar/policy/z_files/filter.json rename to dizoo/distar/envs/z_files/filter.json diff --git a/dizoo/distar/policy/z_files/lurker.json b/dizoo/distar/envs/z_files/lurker.json similarity index 100% rename from dizoo/distar/policy/z_files/lurker.json rename to dizoo/distar/envs/z_files/lurker.json diff --git a/dizoo/distar/policy/z_files/mutalisk.json b/dizoo/distar/envs/z_files/mutalisk.json similarity index 100% rename from dizoo/distar/policy/z_files/mutalisk.json rename to dizoo/distar/envs/z_files/mutalisk.json diff --git a/dizoo/distar/policy/z_files/nydus.json b/dizoo/distar/envs/z_files/nydus.json similarity index 100% rename from dizoo/distar/policy/z_files/nydus.json rename to dizoo/distar/envs/z_files/nydus.json diff --git a/dizoo/distar/policy/z_files/perfect_z.json b/dizoo/distar/envs/z_files/perfect_z.json similarity index 100% rename from dizoo/distar/policy/z_files/perfect_z.json rename to dizoo/distar/envs/z_files/perfect_z.json diff --git a/dizoo/distar/policy/z_files/stairs.json b/dizoo/distar/envs/z_files/stairs.json similarity index 100% rename from dizoo/distar/policy/z_files/stairs.json rename to dizoo/distar/envs/z_files/stairs.json diff --git a/dizoo/distar/policy/z_files/worker_rush.json b/dizoo/distar/envs/z_files/worker_rush.json similarity index 100% rename from dizoo/distar/policy/z_files/worker_rush.json rename to dizoo/distar/envs/z_files/worker_rush.json diff --git a/dizoo/distar/policy/distar_policy.py b/dizoo/distar/policy/distar_policy.py index 90ec735670..059e0ef467 100644 --- a/dizoo/distar/policy/distar_policy.py +++ b/dizoo/distar/policy/distar_policy.py @@ -356,11 +356,12 @@ def _init_collect(self): self.z_path = self._cfg.z_path # TODO(zms): in _setup_agents, load state_dict to set up z_idx self.z_idx = None - self._reset_collect() - def _reset_collect(self, data: Dict, env_id=0): + def _reset_collect(self, data: Dict): self.exceed_loop_flag = False - self.hidden_state = None + hidden_size = 384 # TODO(nyz) set from cfg + num_layers = 3 + self.hidden_state = [(torch.zeros(hidden_size), torch.zeros(hidden_size)) for _ in range(num_layers)] self.last_action_type = torch.tensor(0, dtype=torch.long) self.last_delay = torch.tensor(0, dtype=torch.long) self.last_queued = torch.tensor(0, dtype=torch.long) @@ -369,15 +370,16 @@ def _reset_collect(self, data: Dict, env_id=0): self.last_location = None # [x, y] self.enemy_unit_type_bool = torch.zeros(NUM_UNIT_TYPES, dtype=torch.uint8) - race, map_size, target_building_order, target_cumulative_stat, bo_location, target_z_loop = parse_new_game( + race, requested_race, map_size, target_building_order, target_cumulative_stat, bo_location, target_z_loop = parse_new_game( data, self.z_path, self.z_idx ) - self.race = race + self.race = race # home_race + self.requested_race = requested_race self.map_size = map_size self.target_z_loop = target_z_loop self.stat = Stat(self.race) - self.target_building_order = torch.tensor(self.target_building_order, dtype=torch.long) + self.target_building_order = torch.tensor(target_building_order, dtype=torch.long) self.target_bo_location = torch.tensor(bo_location, dtype=torch.long) self.target_cumulative_stat = torch.zeros(NUM_CUMULATIVE_STAT_ACTIONS, dtype=torch.float) self.target_cumulative_stat.scatter_( @@ -385,8 +387,7 @@ def _reset_collect(self, data: Dict, env_id=0): ) def _forward_collect(self, data): - game_info = data.pop('game_info') - obs = self._data_preprocess_collect(data, game_info) + obs, game_info = self._data_preprocess_collect(data) obs = default_collate([obs]) if self._cfg.cuda: obs = to_device(obs, self._device) @@ -400,15 +401,16 @@ def _forward_collect(self, data): policy_output = self._data_postprocess_collect(policy_output, game_info) return policy_output - def _data_preprocess_collect(self, data, game_info): + def _data_preprocess_collect(self, data): if self._cfg.use_value_feature: - obs = transform_obs(data['raw_obs'], opponent_obs=data['opponent_obs']) + obs = transform_obs(data['raw_obs'], self.map_size, self.requested_race, opponent_obs=data['opponent_obs']) else: raise NotImplementedError + game_info = obs.pop('game_info') game_step = game_info['game_loop'] - if self._cfg.zero_z_exceed_loop and game_step > self._target_z_loop: - self._exceed_loop_flag = True + if self._cfg.zero_z_exceed_loop and game_step > self.target_z_loop: + self.exceed_loop_flag = True last_selected_units = torch.zeros(obs['entity_num'], dtype=torch.int8) last_targeted_unit = torch.zeros(obs['entity_num'], dtype=torch.int8) @@ -431,16 +433,18 @@ def _data_preprocess_collect(self, data, game_info): obs['scalar_info']['enemy_unit_type_bool'] = ( self.enemy_unit_type_bool | obs['scalar_info']['enemy_unit_type_bool'] ).to(torch.uint8) - obs['scalar_info']['beginning_order'] = self.target_building_order * (~self.exceed_loop_flag) - obs['scalar_info']['bo_location'] = self.target_bo_location * (~self.exceed_loop_flag) if self.exceed_loop_flag: obs['scalar_info']['cumulative_stat'] = self.target_cumulative_stat * 0 + self._cfg.zero_z_value + obs['scalar_info']['beginning_order'] = self.target_building_order * 0 + obs['scalar_info']['bo_location'] = self.target_bo_location * 0 else: obs['scalar_info']['cumulative_stat'] = self.target_cumulative_stat + obs['scalar_info']['beginning_order'] = self.target_building_order + obs['scalar_info']['bo_location'] = self.target_bo_location # update stat self.stat.update(self.last_action_type, data['action_result'][0], obs, game_step) - return obs + return obs, game_info def _data_postprocess_collect(self, data, game_info): self.hidden_state = data['hidden_state'] @@ -456,7 +460,7 @@ def _data_postprocess_collect(self, data, game_info): raw_action = {} raw_action['func_id'] = action_attr['func_id'] raw_action['skip_steps'] = self.last_delay.item() - raw_action['queued'] = self.queued.item() + raw_action['queued'] = self.last_queued.item() unit_tags = [] for i in range(data['selected_units_num'] - 1): # remove end flag diff --git a/dizoo/distar/policy/test_distar_policy.py b/dizoo/distar/policy/test_distar_policy.py index c2d9c08272..77d2473a0d 100644 --- a/dizoo/distar/policy/test_distar_policy.py +++ b/dizoo/distar/policy/test_distar_policy.py @@ -1,7 +1,7 @@ import pytest from dizoo.distar.policy import DIStarPolicy -from dizoo.distar.envs import get_fake_rl_trajectory +from dizoo.distar.envs import get_fake_rl_trajectory, get_fake_env_reset_data, get_fake_env_step_data @pytest.mark.envtest @@ -13,3 +13,12 @@ def test_forward_learn(self): data = get_fake_rl_trajectory(batch_size=3) output = policy.forward(data) print(output) + + def test_forward_collect(self): + policy = DIStarPolicy(DIStarPolicy.default_config(), enable_field=['collect']) + policy = policy.collect_mode + data = get_fake_env_reset_data() + policy.reset(data) + data = get_fake_env_step_data() + output = policy.forward(data) + print(output) From 7b5b233d7dcd1406bbe98e2531c93ad83fbc6347 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 29 Jun 2022 11:03:01 +0800 Subject: [PATCH 177/229] to run in k8s --- ding/framework/middleware/league_learner.py | 2 +- .../middleware/tests/test_league_pipeline.py | 18 +++++++++++------- 2 files changed, 12 insertions(+), 8 deletions(-) diff --git a/ding/framework/middleware/league_learner.py b/ding/framework/middleware/league_learner.py index 8dea75305d..413ee62980 100644 --- a/ding/framework/middleware/league_learner.py +++ b/ding/framework/middleware/league_learner.py @@ -32,7 +32,7 @@ class LeagueLearnerCommunicator: def __init__(self, cfg: dict, policy: "Policy", player: "ActivePlayer") -> None: self.cfg = cfg - self._cache = deque(maxlen=1000) + self._cache = deque(maxlen=50) self.player = player self.player_id = player.player_id self.policy = policy diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index 4047f9b6bc..1e77e0fb41 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -45,13 +45,17 @@ def get_env_fn(cls): @classmethod def get_env_supervisor(cls): - env = EnvSupervisor( - type_=ChildType.THREAD, - env_fn=[cls.get_env_fn for _ in range(cfg.env.collector_env_num)], - **cfg.env.manager - ) - env.seed(cfg.seed) - return env + for _ in range(10): + try: + env = EnvSupervisor( + type_=ChildType.THREAD, + env_fn=[cls.get_env_fn for _ in range(cfg.env.collector_env_num)], + **cfg.env.manager + ) + env.seed(cfg.seed) + return env + except: + continue @classmethod def policy_fn(cls): From 0b985d25516f5543ef449380a23bcb876ae305c0 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 29 Jun 2022 11:07:22 +0800 Subject: [PATCH 178/229] change num workers --- ding/framework/middleware/tests/test_league_pipeline.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index 1e77e0fb41..5b98010b94 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -99,8 +99,8 @@ def main(): @pytest.mark.unittest def test_league_pipeline(): - Parallel.runner(n_parallel_workers=3, protocol="tcp", topology="mesh")(main) + Parallel.runner(n_parallel_workers=7, protocol="tcp", topology="mesh")(main) if __name__ == "__main__": - Parallel.runner(n_parallel_workers=3, protocol="tcp", topology="mesh")(main) + Parallel.runner(n_parallel_workers=7, protocol="tcp", topology="mesh")(main) From 57d3a431290d27c46c9a4ca242e1149ae09203e7 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 29 Jun 2022 23:44:36 +0800 Subject: [PATCH 179/229] to run real policy forward_collect --- ding/framework/middleware/collector.py | 5 ++- .../middleware/functional/collector.py | 38 ++++++++++--------- ding/framework/middleware/league_actor.py | 4 +- .../middleware/tests/mock_for_test.py | 3 +- .../test_league_actor_distar_one_process.py | 35 ++++++++--------- dizoo/distar/policy/distar_policy.py | 17 +++++---- 6 files changed, 56 insertions(+), 46 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index d78f9c85e8..07c5f57471 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -14,7 +14,7 @@ if TYPE_CHECKING: from ding.framework import OnlineRLContext, BattleContext -WAIT_MODEL_TIME = 60 +WAIT_MODEL_TIME = 6000 class BattleStepCollector: @@ -110,6 +110,9 @@ def __call__(self, ctx: "BattleContext") -> None: while True: if self.env.closed: self.env.launch() + # TODO(zms): only runnable when 1 actor has exactly one env, need to write more general + for policy_id, policy in enumerate(ctx.current_policies): + policy.reset(self.env.ready_obs[0][policy_id]) self._update_policies(ctx.player_id_list) self._battle_inferencer(ctx) self._battle_rolloutor(ctx) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 6cd2e4de86..b3c4dd1d50 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -2,7 +2,6 @@ from easydict import EasyDict from functools import reduce import treetensor.torch as ttorch -from ding import policy from ding.envs import BaseEnvManager from ding.policy import Policy import torch @@ -129,11 +128,14 @@ def _cut_trajectory_from_episode(self, episode: list) -> List[List]: def clear_newest_episode(self, env_id: int) -> None: # Use it when env.step raise some error - newest_episode = self._transitions[env_id].pop() - len_newest_episode = len(newest_episode) - newest_episode.clear() - self._done_episode[env_id].pop() - return len_newest_episode + if len(self._transitions[env_id]) > 0: + newest_episode = self._transitions[env_id].pop() + len_newest_episode = len(newest_episode) + newest_episode.clear() + self._done_episode[env_id].pop() + return len_newest_episode + else: + return 0 def append(self, env_id: int, transition: Any) -> bool: # If previous episode is done, we create a new episode @@ -283,10 +285,10 @@ def _battle_rolloutor(ctx: "BattleContext"): ctx.total_envstep_count += len(timesteps) ctx.env_step += len(timesteps) for env_id, timestep in timesteps.items(): - for policy_id, _ in enumerate(ctx.current_policies): + for policy_id, policy in enumerate(ctx.current_policies): policy_timestep_data = [d[policy_id] if not isinstance(d, bool) else d for d in timestep] policy_timestep = type(timestep)(*policy_timestep_data) - transition = ctx.current_policies[policy_id].process_transition( + transition = policy.process_transition( ctx.obs[policy_id][env_id], ctx.inference_output[policy_id][env_id], policy_timestep ) transition = ttorch.as_tensor(transition) @@ -295,7 +297,7 @@ def _battle_rolloutor(ctx: "BattleContext"): ) transitions_list[policy_id].append(env_id, transition) if timestep.done: - ctx.current_policies[policy_id].reset([env_id]) + policy.reset([env_id]) ctx.episode_info[policy_id].append(timestep.info[policy_id]) if timestep.done: @@ -351,26 +353,28 @@ def _battle_rolloutor(ctx: "BattleContext"): # ctx.env_step -= transitions_list[0].length(env_id) # 1st case when env step has bug and need to reset. - for policy_id, _ in enumerate(ctx.current_policies): + + # TODO(zms): if it is first step of the episode, do not delete the last episode in the TransitionList + for policy_id, policy in enumerate(ctx.current_policies): transitions_list[policy_id].clear_newest_episode(env_id) - ctx.current_policies[policy_id].reset([env_id]) + policy.reset(env.ready_obs[0][policy_id]) continue - append_succeed = True - for policy_id, _ in enumerate(ctx.current_policies): - transition = ctx.current_policies[policy_id].process_transition(timestep) + episode_long_enough = True + for policy_id, policy in enumerate(ctx.current_policies): + transition = policy.process_transition(timestep) transition = EasyDict(transition) transition.collect_train_iter = ttorch.as_tensor( [model_info_dict[ctx.player_id_list[policy_id]].update_train_iter] ) # 2nd case when the number of transitions in one of all the episodes is shorter than unroll_len - append_succeed = append_succeed and transitions_list[policy_id].append(env_id, transition) + episode_long_enough = episode_long_enough and transitions_list[policy_id].append(env_id, transition) if timestep.done: - ctx.current_policies[policy_id].reset([env_id]) + policy.reset(env.ready_obs[0][policy_id]) ctx.episode_info[policy_id].append(timestep.info[policy_id]) - if not append_succeed: + if not episode_long_enough: for policy_id, _ in enumerate(ctx.current_policies): transitions_list[policy_id].clear_newest_episode(env_id) ctx.episode_info[policy_id].pop() diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index e8dbbf58b2..cbefa81518 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -115,8 +115,6 @@ def _get_current_policies(self, job): assert len(current_policies) > 1, "[Actor {}] battle collector needs more than 1 policies".format( task.router.node_id ) - for p in current_policies: - p.reset() else: raise RuntimeError('[Actor {}] current_policies should not be None'.format(task.router.node_id)) @@ -130,7 +128,7 @@ def __call__(self, ctx: "BattleContext"): log_every_sec( logging.INFO, 5, '[Actor {}] job of player {} begins.'.format(task.router.node_id, job.launch_player) ) - + # TODO(zms): when get job, update the policies to the checkpoint in job ctx.player_id_list = [player.player_id for player in job.players] main_player_idx = [idx for idx, player in enumerate(job.players) if player.player_id == job.launch_player] self.agent_num = len(job.players) diff --git a/ding/framework/middleware/tests/mock_for_test.py b/ding/framework/middleware/tests/mock_for_test.py index e39b625ef5..7b75dda960 100644 --- a/ding/framework/middleware/tests/mock_for_test.py +++ b/ding/framework/middleware/tests/mock_for_test.py @@ -184,7 +184,8 @@ def _forward_learn(self, data: Dict[str, Any]) -> Dict[str, Any]: return super()._forward_learn(data) def _forward_collect(self, data: Dict[int, Any]) -> Dict[int, Any]: - return DIStarEnv.random_action(data) + print("Call forward_collect:", flush=True) + return super()._forward_collect(data) class DIStarMockPPOPolicy(PPOPolicy): diff --git a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py index f9378af09a..d362f45510 100644 --- a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py @@ -20,7 +20,7 @@ from distar.ctools.utils import read_config from ding.model import VAC -from ding.framework.middleware.tests import DIStarMockPPOPolicy, DIStarMockPolicyCollect +from ding.framework.middleware.tests import DIStarMockPPOPolicy, DIStarMockPolicyCollect, DIStarMockPolicy from ding.framework.middleware.functional.collector import battle_inferencer_for_distar, battle_rolloutor_for_distar cfg = deepcopy(distar_cfg) @@ -35,31 +35,34 @@ def get_env_fn(cls): @classmethod def get_env_supervisor(cls): - env = EnvSupervisor( - type_=ChildType.THREAD, - env_fn=[cls.get_env_fn for _ in range(cfg.env.collector_env_num)], - **cfg.env.manager - ) - env.seed(cfg.seed) - return env + for _ in range(10): + try: + env = EnvSupervisor( + type_=ChildType.THREAD, + env_fn=[cls.get_env_fn for _ in range(cfg.env.collector_env_num)], + **cfg.env.manager + ) + env.seed(cfg.seed) + return env + except: + continue @classmethod - def policy_fn(cls): - model = VAC(**cfg.policy.model) - policy = DIStarMockPPOPolicy(cfg.policy, model=model) + def learn_policy_fn(cls): + policy = DIStarMockPolicy(DIStarMockPolicy.default_config(), enable_field=['learn']) return policy @classmethod def collect_policy_fn(cls): - policy = DIStarMockPolicyCollect() + # policy = DIStarMockPolicyCollect() + policy = DIStarMockPolicy(DIStarMockPolicy.default_config(), enable_field=['collect']) return policy @pytest.mark.unittest def test_league_actor(): with task.start(async_mode=True, ctx=BattleContext()): - policy = PrepareTest.policy_fn() - + policy = PrepareTest.learn_policy_fn().learn_mode def test_actor(): job = Job( launch_player='main_player_default_0', @@ -103,9 +106,7 @@ def _test_actor(ctx): task.emit( EventEnum.LEARNER_SEND_MODEL, - LearnerModel( - player_id='main_player_default_0', state_dict=policy.learn_mode.state_dict(), train_iter=0 - ) + LearnerModel(player_id='main_player_default_0', state_dict=policy.state_dict(), train_iter=0) ) # sleep(100) # try: diff --git a/dizoo/distar/policy/distar_policy.py b/dizoo/distar/policy/distar_policy.py index 059e0ef467..afc571f3e3 100644 --- a/dizoo/distar/policy/distar_policy.py +++ b/dizoo/distar/policy/distar_policy.py @@ -12,7 +12,7 @@ from ding.utils import EasyTimer from ding.utils.data import default_collate, default_decollate from dizoo.distar.model import Model -from dizoo.distar.envs import NUM_UNIT_TYPES, ACTIONS, NUM_CUMULATIVE_STAT_ACTIONS, Stat, parse_new_game, transform_obs +from dizoo.distar.envs import NUM_UNIT_TYPES, ACTIONS, NUM_CUMULATIVE_STAT_ACTIONS, DEFAULT_SPATIAL_SIZE, Stat, parse_new_game, transform_obs from .utils import collate_fn_learn, kl_error, entropy_error @@ -351,8 +351,11 @@ def _load_state_dict_learn(self, _state_dict: Dict) -> None: self._learn_model.load_state_dict(_state_dict['model']) self.optimizer.load_state_dict(_state_dict['optimizer']) + def _load_state_dict_collect(self, _state_dict: Dict) -> None: + self._collect_model.load_state_dict(_state_dict['model'], strict=False) + def _init_collect(self): - self.collect_model = model_wrap(self._model, 'base') + self._collect_model = model_wrap(self._model, 'base') self.z_path = self._cfg.z_path # TODO(zms): in _setup_agents, load state_dict to set up z_idx self.z_idx = None @@ -393,7 +396,7 @@ def _forward_collect(self, data): obs = to_device(obs, self._device) with torch.no_grad(): - policy_output = self.collect_model.compute_logp_action(**obs) + policy_output = self._collect_model.compute_logp_action(**obs) if self._cfg.cuda: policy_output = to_device(policy_output, self._device) @@ -403,7 +406,7 @@ def _forward_collect(self, data): def _data_preprocess_collect(self, data): if self._cfg.use_value_feature: - obs = transform_obs(data['raw_obs'], self.map_size, self.requested_race, opponent_obs=data['opponent_obs']) + obs = transform_obs(data['raw_obs'], self.map_size, self.requested_race, padding_spatial=True, opponent_obs=data['opponent_obs']) else: raise NotImplementedError @@ -481,13 +484,13 @@ def _data_postprocess_collect(self, data, game_info): else: self.last_targeted_unit_tag = None - x = data['action_info']['target_location'].item() % self.map_size.x - y = data['action_info']['target_location'].item() // self.map_size.x + x = data['action_info']['target_location'].item() % DEFAULT_SPATIAL_SIZE[1] + y = data['action_info']['target_location'].item() // DEFAULT_SPATIAL_SIZE[1] inverse_y = max(self.map_size.y - y, 0) raw_action['location'] = (x, inverse_y) self.last_location = data['action_info']['target_location'] - data['action'] = raw_action + data['action'] = [raw_action] return data From 584fd822189aa2b0d9f6b0e031887e206b83ebb1 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Thu, 30 Jun 2022 10:53:24 +0800 Subject: [PATCH 180/229] print exception --- .../middleware/tests/test_league_actor_distar_one_process.py | 3 ++- ding/framework/middleware/tests/test_league_pipeline.py | 3 ++- 2 files changed, 4 insertions(+), 2 deletions(-) diff --git a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py index d362f45510..c63b53d35b 100644 --- a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py @@ -44,7 +44,8 @@ def get_env_supervisor(cls): ) env.seed(cfg.seed) return env - except: + except Exception as e: + print(e) continue @classmethod diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index 5b98010b94..be63e30e66 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -54,7 +54,8 @@ def get_env_supervisor(cls): ) env.seed(cfg.seed) return env - except: + except Exception as e: + print(e) continue @classmethod From df21a9a804af8e998afd2e8bfefd11e1d3e7a84e Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Thu, 30 Jun 2022 13:45:34 +0800 Subject: [PATCH 181/229] reformat test --- .../test_league_actor_distar_one_process.py | 49 +++++++++++++------ 1 file changed, 33 insertions(+), 16 deletions(-) diff --git a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py index c63b53d35b..4a950e268f 100644 --- a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py @@ -1,30 +1,46 @@ from time import sleep import pytest from copy import deepcopy -from ding.envs import BaseEnvManager, EnvSupervisor -from ding.framework.context import BattleContext -from ding.framework.middleware.league_learner import LearnerModel -from dizoo.distar.config import distar_cfg -from ding.framework.middleware import StepLeagueActor -from ding.framework.middleware.functional import ActorData -from ding.league.player import PlayerMeta -from ding.framework.storage import FileStorage +from unittest.mock import patch +from easydict import EasyDict -from ding.framework.task import task -from ding.league.v2.base_league import Job +from dizoo.distar.config import distar_cfg from dizoo.distar.envs.distar_env import DIStarEnv -from unittest.mock import patch -from ding.framework.supervisor import ChildType +from ding.envs import EnvSupervisor +from ding.league.player import PlayerMeta +from ding.league.v2.base_league import Job from ding.framework import EventEnum -from distar.ctools.utils import read_config -from ding.model import VAC +from ding.framework.storage import FileStorage +from ding.framework.task import task +from ding.framework.context import BattleContext -from ding.framework.middleware.tests import DIStarMockPPOPolicy, DIStarMockPolicyCollect, DIStarMockPolicy +from ding.framework.supervisor import ChildType +from ding.framework.middleware import StepLeagueActor +from ding.framework.middleware.functional import ActorData +from ding.framework.middleware.tests import DIStarMockPolicy from ding.framework.middleware.functional.collector import battle_inferencer_for_distar, battle_rolloutor_for_distar +env_cfg = dict( + actor=dict(job_type='train', ), + env=dict( + map_name='KingsCove', + player_ids=['agent1', 'agent2'], + races=['zerg', 'zerg'], + map_size_resolutions=[True, True], # if True, ignore minimap_resolutions + minimap_resolutions=[[160, 152], [160, 152]], + realtime=False, + replay_dir='.', + random_seed='none', + game_steps_per_episode=100000, + update_bot_obs=False, + save_replay_episodes=1, + update_both_obs=False, + version='4.10.0', + ), +) +env_cfg = EasyDict(env_cfg) cfg = deepcopy(distar_cfg) -env_cfg = read_config('./test_distar_config.yaml') class PrepareTest(): @@ -64,6 +80,7 @@ def collect_policy_fn(cls): def test_league_actor(): with task.start(async_mode=True, ctx=BattleContext()): policy = PrepareTest.learn_policy_fn().learn_mode + def test_actor(): job = Job( launch_player='main_player_default_0', From 72803ef9f5c7da1b450b5ba7cf05d54479f989e3 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Thu, 30 Jun 2022 13:58:24 +0800 Subject: [PATCH 182/229] fix bug --- .../middleware/tests/test_league_actor_distar_one_process.py | 1 + 1 file changed, 1 insertion(+) diff --git a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py index 4a950e268f..b77e427297 100644 --- a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py +++ b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py @@ -19,6 +19,7 @@ from ding.framework.middleware import StepLeagueActor from ding.framework.middleware.functional import ActorData from ding.framework.middleware.tests import DIStarMockPolicy +from ding.framework.middleware.league_learner import LearnerModel from ding.framework.middleware.functional.collector import battle_inferencer_for_distar, battle_rolloutor_for_distar env_cfg = dict( From e8e7551b66085edda9562785eba81bb5ab41311b Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 6 Jul 2022 14:09:56 +0800 Subject: [PATCH 183/229] tools to do serialization and test if two objects same --- ding/utils/tensor_dict_to_shm.py | 154 +++++++++++++++++++++++++++++++ 1 file changed, 154 insertions(+) create mode 100644 ding/utils/tensor_dict_to_shm.py diff --git a/ding/utils/tensor_dict_to_shm.py b/ding/utils/tensor_dict_to_shm.py new file mode 100644 index 0000000000..e1b377ac36 --- /dev/null +++ b/ding/utils/tensor_dict_to_shm.py @@ -0,0 +1,154 @@ +import torch +import torch.multiprocessing as mp +from array import array +import numpy as np + + +def shm_encode_with_schema(data, maxlen=1024 * 1024 * 64): + idx = 0 + encoding = np.zeros(shape=(maxlen, ), dtype=np.float32) + + def _helper(data): + nonlocal idx + if isinstance(data, torch.Tensor): + if data.size(): + tmp = data.flatten() + encoding[idx:idx + len(tmp)] = tmp + idx += len(tmp) + else: + encoding[idx] = data.item() + idx += 1 + return data.size() + elif isinstance(data, dict): + schema = {} + for key, chunk in data.items(): + schema[key] = _helper(chunk) + return schema + elif isinstance(data, (list, tuple)): + schema = [] + for chunk in data: + schema.append(_helper(chunk)) + if isinstance(data, tuple): + schema = tuple(schema) + return schema + else: + raise ValueError("not supported dtype! {}".format(type(data))) + + schema = _helper(data) + return encoding[:idx], schema + + +def shm_decode(encoding, schema): + + def _shm_decode_helper(encoding, schema, start): + if isinstance(schema, torch.Size): + storage = 1 + for d in schema: + storage *= d + # if isinstance(encoding[start], int): + # decoding = torch.LongTensor(encoding[start: start + storage]).view(schema) + # else: + # decoding = torch.FloatTensor(encoding[start: start + storage]).view(schema) + decoding = torch.Tensor(encoding[start:start + storage]).view(schema) + start += storage + return decoding, start + elif isinstance(schema, dict): + decoding = {} + for key, chunk in schema.items(): + decoding[key], start = _shm_decode_helper(encoding, chunk, start) + return decoding, start + elif isinstance(schema, (list, tuple)): + decoding = [] + for chunk in schema: + chunk, start = _shm_decode_helper(encoding, chunk, start) + decoding.append(chunk) + if isinstance(schema, tuple): + decoding = tuple(decoding) + return decoding, start + else: + raise ValueError("not supported schema! {}".format(schema)) + + decoding, start = _shm_decode_helper(encoding, schema, 0) + assert len(encoding) == start, "Encoding length and schema do not match!" + return decoding + + +def equal(data1, data2, check_dict_order=True, strict_dtype=False, parent_key=None): + if type(data1) != type(data2): + print(parent_key) + # print("data1: {} {}".format(parent_key, data1)) + # print("data2: {} {}".format(parent_key, data2)) + return False + if isinstance(data1, torch.Tensor): + if not strict_dtype: + data1 = data1.float() + data2 = data2.float() + if data1.dtype != data2.dtype: + print("data type does not match! data1({}), data2({})".format(data1.dtype, data2.dtype)) + # print("data1: {} {}".format(parent_key, data1)) + # print("data2: {} {}".format(parent_key, data2)) + return False + if data1.equal(data2): + return True + else: + print("value not match") + # print("parent key of data1: {}".format(parent_key)) + print("data1: {} {}".format(parent_key, data1)) + print("data2: {} {}".format(parent_key, data2)) + return False + elif isinstance(data1, dict): + key_set1 = data1.keys() + key_set2 = data2.keys() + if check_dict_order and key_set1 != key_set2: + print("key sequence not match!") + # print("data1: {}".format(data1)) + # print("data2: {}".format(data2)) + return False + elif set(key_set1) != set(key_set2): + print("key set not match!") + # print("data1: {}".format(data1)) + # print("data2: {}".format(data2)) + return False + for key in key_set1: + if equal(data1[key], data2[key], check_dict_order, strict_dtype, key): + print("passed:", key) + else: + print("!!!!!!! not match:", key) + return False + return True + elif isinstance(data1, (tuple, list)): + if len(data1) != len(data2): + print("list length does not match!") + # print("data1: {}".format(data1)) + # print("data2: {}".format(data2)) + return False + return all([equal(data1[i], data2[i], check_dict_order, strict_dtype, parent_key) for i in range(len(data1))]) + else: + raise ValueError("not supported dtype! {}".format(data1)) + + +def equal_v0(data1, data2, check_dict_order=True, strict_dtype=False): + if type(data1) != type(data2): + return False + if isinstance(data1, torch.Tensor): + if not strict_dtype: + data1 = data1.float() + data2 = data2.float() + if data1.dtype != data2.dtype: + print("data type does not match! data1({}), data2({})".format(data1.dtype, data2.dtype)) + return False + return data1.equal(data2) + elif isinstance(data1, dict): + key_set1 = data1.keys() + key_set2 = data2.keys() + if check_dict_order and key_set1 != key_set2: + return False + elif set(key_set1) != set(key_set2): + return False + return all([equal(data1[key], data2[key], check_dict_order, strict_dtype) for key in key_set1]) + elif isinstance(data1, (tuple, list)): + if len(data1) != len(data2): + return False + return all([equal(data1[i], data2[i], check_dict_order, strict_dtype) for i in range(len(data1))]) + else: + raise ValueError("not supported dtype! {}".format(data1)) \ No newline at end of file From 2da40100329247fabb85899fff9a809f1975691c Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 6 Jul 2022 14:23:38 +0800 Subject: [PATCH 184/229] changes in the model to correctly make actions using pretrained model --- ding/torch_utils/network/activation.py | 3 +- ding/torch_utils/network/transformer.py | 26 +++++++++++++---- dizoo/distar/model/head/action_type_head.py | 29 ++++++++++++++++++- .../model/obs_encoder/entity_encoder.py | 1 + 4 files changed, 51 insertions(+), 8 deletions(-) diff --git a/ding/torch_utils/network/activation.py b/ding/torch_utils/network/activation.py index 56afa03ce3..8fe27c1108 100644 --- a/ding/torch_utils/network/activation.py +++ b/ding/torch_utils/network/activation.py @@ -85,7 +85,8 @@ def build_activation(activation: str, inplace: bool = None) -> nn.Module: if inplace is not None: assert activation == 'relu', 'inplace argument is not compatible with {}'.format(activation) else: - inplace = False + # TODO(nyz): influence dizoo/gfootball/model/iql/iql_network.py, and tests of this function + inplace = True act_func = {'relu': nn.ReLU(inplace=inplace), 'glu': GLU, 'prelu': nn.PReLU(), 'swish': Swish()} if activation in act_func.keys(): return act_func[activation] diff --git a/ding/torch_utils/network/transformer.py b/ding/torch_utils/network/transformer.py index e707134a3f..49e0a67a2f 100644 --- a/ding/torch_utils/network/transformer.py +++ b/ding/torch_utils/network/transformer.py @@ -89,7 +89,7 @@ class TransformerLayer(nn.Module): def __init__( self, input_dim: int, head_dim: int, hidden_dim: int, output_dim: int, head_num: int, mlp_num: int, - dropout: nn.Module, activation: nn.Module + dropout: nn.Module, activation: nn.Module, ln_type ) -> None: r""" Overview: @@ -117,6 +117,7 @@ def __init__( layers.append(self.dropout) self.mlp = nn.Sequential(*layers) self.layernorm2 = build_normalization('LN')(output_dim) + self.ln_type = ln_type def forward(self, inputs: Tuple[torch.Tensor, torch.Tensor]) -> Tuple[torch.Tensor, torch.Tensor]: """ @@ -128,10 +129,22 @@ def forward(self, inputs: Tuple[torch.Tensor, torch.Tensor]) -> Tuple[torch.Tens - output (:obj:`Tuple[torch.Tensor, torch.Tensor]`): predict value and mask """ x, mask = inputs - a = self.dropout(self.attention(x, mask)) - x = self.layernorm1(x + a) - m = self.dropout(self.mlp(x)) - x = self.layernorm2(x + m) + if self.ln_type == "pre": + a = self.attention(self.layernorm1(x), mask) + if self.dropout: + a = self.dropout(a) + x = x + a + m = self.mlp(self.layernorm2(x)) + if self.dropout: + m = self.dropout(m) + x = x + m + elif self.ln_type == "post": + a = self.dropout(self.attention(x, mask)) + x = self.layernorm1(x + a) + m = self.dropout(self.mlp(x)) + x = self.layernorm2(x + m) + else: + raise NotImplementedError(self.ln_type) return (x, mask) @@ -156,6 +169,7 @@ def __init__( layer_num: int = 3, dropout_ratio: float = 0., activation: nn.Module = nn.ReLU(), + ln_type = 'pre' ): r""" Overview: @@ -179,7 +193,7 @@ def __init__( self.dropout = nn.Dropout(dropout_ratio) for i in range(layer_num): layers.append( - TransformerLayer(dims[i], head_dim, hidden_dim, dims[i + 1], head_num, mlp_num, self.dropout, self.act) + TransformerLayer(dims[i], head_dim, hidden_dim, dims[i + 1], head_num, mlp_num, self.dropout, self.act, ln_type) ) self.main = nn.Sequential(*layers) diff --git a/dizoo/distar/model/head/action_type_head.py b/dizoo/distar/model/head/action_type_head.py index d16c2cdd3b..ddcda01b80 100644 --- a/dizoo/distar/model/head/action_type_head.py +++ b/dizoo/distar/model/head/action_type_head.py @@ -9,10 +9,37 @@ import torch import torch.nn as nn import torch.nn.functional as F -from ding.torch_utils import ResFCBlock, fc_block, build_activation +from ding.torch_utils import ResFCBlock, fc_block, conv2d_block from dizoo.distar.envs import ACTION_RACE_MASK +class GLU(nn.Module): + def __init__(self, input_dim, output_dim, context_dim, input_type='fc'): + super(GLU, self).__init__() + assert (input_type in ['fc', 'conv2d']) + if input_type == 'fc': + self.layer1 = fc_block(context_dim, input_dim) + self.layer2 = fc_block(input_dim, output_dim) + elif input_type == 'conv2d': + self.layer1 = conv2d_block(context_dim, input_dim, 1, 1, 0) + self.layer2 = conv2d_block(input_dim, output_dim, 1, 1, 0) + + def forward(self, x, context): + gate = self.layer1(context) + gate = torch.sigmoid(gate) + x = gate * x + x = self.layer2(x) + return x + + +def build_activation(activation): + act_func = {'relu': nn.ReLU(inplace=True), 'glu': GLU, 'prelu': nn.PReLU(init=0.0)} + if activation in act_func.keys(): + return act_func[activation] + else: + raise KeyError("invalid key for activation: {}".format(activation)) + + class ActionTypeHead(nn.Module): __constants__ = ['mask_action'] diff --git a/dizoo/distar/model/obs_encoder/entity_encoder.py b/dizoo/distar/model/obs_encoder/entity_encoder.py index 93ffb7fe29..a94de40037 100644 --- a/dizoo/distar/model/obs_encoder/entity_encoder.py +++ b/dizoo/distar/model/obs_encoder/entity_encoder.py @@ -48,6 +48,7 @@ def __init__(self, cfg): layer_num=self.cfg.layer_num, dropout_ratio=self.cfg.dropout_ratio, activation=self.act, + ln_type=self.cfg.ln_type ) self.entity_fc = fc_block(self.cfg.output_dim, self.cfg.output_dim, activation=self.act) self.embed_fc = fc_block(self.cfg.output_dim, self.cfg.output_dim, activation=self.act) From a0efe1cc4aa829f87ab07d9b482c38ef2c3a4937 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 6 Jul 2022 14:26:02 +0800 Subject: [PATCH 185/229] changes to run the test using pretrained model --- ding/framework/middleware/collector.py | 2 +- ding/framework/middleware/league_actor.py | 15 ++++++++++++--- 2 files changed, 13 insertions(+), 4 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 07c5f57471..166bad50be 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -14,7 +14,7 @@ if TYPE_CHECKING: from ding.framework import OnlineRLContext, BattleContext -WAIT_MODEL_TIME = 6000 +WAIT_MODEL_TIME = 600000 class BattleStepCollector: diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index cbefa81518..01289bf6d4 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -4,6 +4,7 @@ from easydict import EasyDict import time from ditk import logging +import torch from ding.policy import Policy from ding.framework import task, EventEnum @@ -112,9 +113,11 @@ def _get_current_policies(self, job): assert main_player, "[Actor {}] can not find active player.".format(task.router.node_id) if current_policies is not None: - assert len(current_policies) > 1, "[Actor {}] battle collector needs more than 1 policies".format( - task.router.node_id - ) + #TODO(zms): make it more general, should we have the restriction of 1 policies + # assert len(current_policies) > 1, "[Actor {}] battle collector needs more than 1 policies".format( + # task.router.node_id + # ) + pass else: raise RuntimeError('[Actor {}] current_policies should not be None'.format(task.router.node_id)) @@ -136,6 +139,12 @@ def __call__(self, ctx: "BattleContext"): main_player, ctx.current_policies = self._get_current_policies(job) + #TODO(zms): only for test pretrained model + rl_model = torch.load('./rl_model.pth') + for policy in ctx.current_policies: + policy.load_state_dict(rl_model) + print('load state_dict okay') + ctx.n_episode = self.cfg.policy.collect.n_episode assert ctx.n_episode >= self.env_num, "[Actor {}] Please make sure n_episode >= env_num".format( task.router.node_id From a3c9e3942d63253407b6b17b4b950a8da0378d46 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 6 Jul 2022 14:29:52 +0800 Subject: [PATCH 186/229] tests to test the performance againist bot using pretrained mdoel --- dizoo/distar/policy/test_distar_policy.py | 15 +- ...test_league_actor_with_pretrained_model.py | 178 ++++++++++++++++++ 2 files changed, 191 insertions(+), 2 deletions(-) create mode 100644 dizoo/distar/tests/test_league_actor_with_pretrained_model.py diff --git a/dizoo/distar/policy/test_distar_policy.py b/dizoo/distar/policy/test_distar_policy.py index 77d2473a0d..76ff7ea9aa 100644 --- a/dizoo/distar/policy/test_distar_policy.py +++ b/dizoo/distar/policy/test_distar_policy.py @@ -3,6 +3,9 @@ from dizoo.distar.policy import DIStarPolicy from dizoo.distar.envs import get_fake_rl_trajectory, get_fake_env_reset_data, get_fake_env_step_data +import torch +from ding.utils import set_pkg_seed + @pytest.mark.envtest class TestDIStarPolicy: @@ -17,8 +20,16 @@ def test_forward_learn(self): def test_forward_collect(self): policy = DIStarPolicy(DIStarPolicy.default_config(), enable_field=['collect']) policy = policy.collect_mode + + rl_model = torch.load('./rl_model.pth') + policy.load_state_dict(rl_model) + data = get_fake_env_reset_data() policy.reset(data) - data = get_fake_env_step_data() output = policy.forward(data) - print(output) + +if __name__ == '__main__': + set_pkg_seed(0, use_cuda=False) + torch.set_printoptions(profile="full") + test = TestDIStarPolicy() + test.test_forward_collect() \ No newline at end of file diff --git a/dizoo/distar/tests/test_league_actor_with_pretrained_model.py b/dizoo/distar/tests/test_league_actor_with_pretrained_model.py new file mode 100644 index 0000000000..dfac92d6ac --- /dev/null +++ b/dizoo/distar/tests/test_league_actor_with_pretrained_model.py @@ -0,0 +1,178 @@ +from time import sleep +import pytest +from copy import deepcopy +from unittest.mock import patch +from easydict import EasyDict + +from dizoo.distar.config import distar_cfg +from dizoo.distar.envs.distar_env import DIStarEnv + +from ding.envs import EnvSupervisor +from ding.league.player import PlayerMeta +from ding.league.v2.base_league import Job +from ding.framework import EventEnum +from ding.framework.storage import FileStorage +from ding.framework.task import task +from ding.framework.context import BattleContext + +from ding.framework.supervisor import ChildType +from ding.framework.middleware import StepLeagueActor +from ding.framework.middleware.functional import ActorData +from ding.framework.middleware.tests import DIStarMockPolicy +from ding.framework.middleware.league_learner import LearnerModel +from ding.framework.middleware.functional.collector import battle_inferencer_for_distar + + +def battle_rolloutor_for_distar(cfg, env, transitions_list, model_info_dict): + + def _battle_rolloutor(ctx: "BattleContext"): + timesteps = env.step(ctx.actions) + + ctx.total_envstep_count += len(timesteps) + ctx.env_step += len(timesteps) + + for env_id, timestep in enumerate(timesteps): + if timestep.info.get('abnormal'): + for policy_id, policy in enumerate(ctx.current_policies): + policy.reset(env.ready_obs[0][policy_id]) + continue + + for policy_id, policy in enumerate(ctx.current_policies): + if timestep.done: + policy.reset(env.ready_obs[0][policy_id]) + ctx.episode_info[policy_id].append(timestep.info[policy_id]) + + if timestep.done: + ctx.env_episode += 1 + + return _battle_rolloutor + + +env_cfg = dict( + actor=dict(job_type='train', ), + env=dict( + map_name='KingsCove', + player_ids=['agent1', 'bot10'], + races=['zerg', 'zerg'], + map_size_resolutions=[True, True], # if True, ignore minimap_resolutions + minimap_resolutions=[[160, 152], [160, 152]], + realtime=False, + replay_dir='.', + random_seed='none', + game_steps_per_episode=100000, + update_bot_obs=False, + save_replay_episodes=1, + update_both_obs=False, + version='4.10.0', + ), +) +env_cfg = EasyDict(env_cfg) +cfg = deepcopy(distar_cfg) + + +class PrepareTest(): + + @classmethod + def get_env_fn(cls): + return DIStarEnv(env_cfg) + + @classmethod + def get_env_supervisor(cls): + for _ in range(10): + try: + env = EnvSupervisor( + type_=ChildType.THREAD, + env_fn=[cls.get_env_fn for _ in range(cfg.env.collector_env_num)], + **cfg.env.manager + ) + env.seed(cfg.seed) + return env + except Exception as e: + print(e) + continue + + @classmethod + def learn_policy_fn(cls): + policy = DIStarMockPolicy(DIStarMockPolicy.default_config(), enable_field=['learn']) + return policy + + @classmethod + def collect_policy_fn(cls): + # policy = DIStarMockPolicyCollect() + policy = DIStarMockPolicy(DIStarMockPolicy.default_config(), enable_field=['collect']) + return policy + + +total_games = 0 +win_games = 0 +draw_games = 0 +loss_games = 0 + + +@pytest.mark.unittest +def test_league_actor(): + with task.start(async_mode=True, ctx=BattleContext()): + policy = PrepareTest.learn_policy_fn().learn_mode + + def test_actor(): + job = Job( + launch_player='main_player_default_0', + players=[ + PlayerMeta( + player_id='main_player_default_0', checkpoint=FileStorage(path=None), total_agent_step=0 + ) + ] + ) + + def on_actor_job(job_: Job): + assert job_.launch_player == job.launch_player + print(job) + global total_games + global win_games + global draw_games + global loss_games + + for r in job_.result: + total_games += 1 + if r == 'wins': + win_games += 1 + elif r == 'draws': + draw_games += 1 + elif r == 'losses': + loss_games += 1 + else: + raise NotImplementedError + + print( + 'total games {}, win games {}, draw_games {}, loss_games {}'.format( + total_games, win_games, draw_games, loss_games + ) + ) + + def on_actor_data(actor_data): + print('got actor_data') + assert isinstance(actor_data, ActorData) + + task.on(EventEnum.ACTOR_FINISH_JOB, on_actor_job) + task.on(EventEnum.ACTOR_SEND_DATA.format(player=job.launch_player), on_actor_data) + + def _test_actor(ctx): + sleep(0.3) + for _ in range(20): + task.emit(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), job) + sleep(0.3) + + return _test_actor + + with patch("ding.framework.middleware.collector.battle_inferencer", battle_inferencer_for_distar): + with patch("ding.framework.middleware.collector.battle_rolloutor", battle_rolloutor_for_distar): + league_actor = StepLeagueActor( + cfg=cfg, env_fn=PrepareTest.get_env_supervisor, policy_fn=PrepareTest.collect_policy_fn + ) + task.use(test_actor()) + task.use(league_actor) + task.run() + + +if __name__ == '__main__': + test_league_actor() From 43f86a1a3c7d6dc040f65ad9dafd1e7b9df3f3fe Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 6 Jul 2022 14:52:26 +0800 Subject: [PATCH 187/229] changes in the policy(agent) to correctly make actions using pretrained model --- dizoo/distar/envs/distar_env.py | 4 +- .../model/actor_critic_default_config.yaml | 1 + dizoo/distar/policy/distar_policy.py | 60 +++++++++++++++---- 3 files changed, 51 insertions(+), 14 deletions(-) diff --git a/dizoo/distar/envs/distar_env.py b/dizoo/distar/envs/distar_env.py index 6800c0a5e8..a7138c9db1 100644 --- a/dizoo/distar/envs/distar_env.py +++ b/dizoo/distar/envs/distar_env.py @@ -225,7 +225,7 @@ def parse_new_game(data, z_path: str, z_idx: Optional[None] = List): target_building_order, target_cumulative_stat, bo_location, target_z_loop, z_type = z else: target_building_order, target_cumulative_stat, bo_location, target_z_loop = z - return race, requested_races, map_size, target_building_order, target_cumulative_stat, bo_location, target_z_loop + return race, requested_races, map_size, target_building_order, target_cumulative_stat, bo_location, target_z_loop, z_type class FeatureUnit(enum.IntEnum): @@ -599,7 +599,7 @@ def get_addon_type(tag): index=enemy_unit_types.long(), src=torch.ones_like(enemy_unit_types, dtype=torch.uint8) ) - + # game info game_info['action_result'] = [o.result for o in obs.action_errors] game_info['game_loop'] = obs.observation.game_loop diff --git a/dizoo/distar/model/actor_critic_default_config.yaml b/dizoo/distar/model/actor_critic_default_config.yaml index 05edf693e4..7ddc366f7b 100644 --- a/dizoo/distar/model/actor_critic_default_config.yaml +++ b/dizoo/distar/model/actor_critic_default_config.yaml @@ -401,6 +401,7 @@ model: activation: 'relu' norm_type: 'LN' ln_type: 'normal' + # TODO(zms): use_mask when common_type is play, i.e. evaluate. e.g. play against bot. use_mask: False race: 'zerg' temperature: 1.0 diff --git a/dizoo/distar/policy/distar_policy.py b/dizoo/distar/policy/distar_policy.py index afc571f3e3..088ad73ba4 100644 --- a/dizoo/distar/policy/distar_policy.py +++ b/dizoo/distar/policy/distar_policy.py @@ -3,6 +3,7 @@ import os.path as osp import torch from torch.optim import Adam +import random from ding.model import model_wrap from ding.policy import Policy @@ -104,11 +105,12 @@ class DIStarPolicy(Policy): ), grad_clip=dict(threshold=1.0, ), # collect - use_value_feature=True, # whether to use value feature, this must be False when play against bot + use_value_feature=True, # TODO(zms): whether to use value feature, this must be False when play against bot zero_z_exceed_loop=True, # set Z to 0 if game passes the game loop in Z zero_z_value=1, extra_units=True, # selcet extra units if selected units exceed 64 - z_path='7map_filter_spine.json' + z_path='7map_filter_spine.json', + use_upia_model=True ) def _create_model( @@ -157,6 +159,8 @@ def _forward_learn(self, inputs: Dict): if self._cfg.cuda: inputs = to_device(inputs, self._device) + self._learn_model.train() + # ============= # model forward # ============= @@ -352,11 +356,30 @@ def _load_state_dict_learn(self, _state_dict: Dict) -> None: self.optimizer.load_state_dict(_state_dict['optimizer']) def _load_state_dict_collect(self, _state_dict: Dict) -> None: - self._collect_model.load_state_dict(_state_dict['model'], strict=False) + #TODO(zms): need to load state_dict after collect, which is very dirty and need to rewrite + + if 'map_name' in _state_dict: + # map_names.append(_state_dict['map_name']) + self.fake_reward_prob = _state_dict['fake_reward_prob'] + # agent._z_path = state_dict['z_path'] + self.z_idx = _state_dict['z_idx'] + _state_dict = {k: v for k, v in _state_dict['model'].items() if 'value_networks' not in k} + + if self.use_upia_model: + for key in list(_state_dict.keys()): + new = key + if "transformer" in key: + new = key.replace('layers', 'main').replace('mlp.1', 'mlp.2') + elif "location_head" in key: + new = key.replace('GateWeightG', 'gate').replace('UpdateSP','update_sp') + _state_dict[new] = _state_dict.pop(key) + + self._collect_model.load_state_dict(_state_dict, strict=False) def _init_collect(self): self._collect_model = model_wrap(self._model, 'base') self.z_path = self._cfg.z_path + self.use_upia_model = self._cfg.use_upia_model # TODO(zms): in _setup_agents, load state_dict to set up z_idx self.z_idx = None @@ -373,9 +396,21 @@ def _reset_collect(self, data: Dict): self.last_location = None # [x, y] self.enemy_unit_type_bool = torch.zeros(NUM_UNIT_TYPES, dtype=torch.uint8) - race, requested_race, map_size, target_building_order, target_cumulative_stat, bo_location, target_z_loop = parse_new_game( + race, requested_race, map_size, target_building_order, target_cumulative_stat, bo_location, target_z_loop, z_type = parse_new_game( data, self.z_path, self.z_idx ) + self.use_cum_reward = True + self.use_bo_reward = True + if z_type is not None: + if z_type == 2 or z_type == 3: + self.use_cum_reward = False + if z_type == 1 or z_type == 3: + self.use_bo_reward = False + if random.random() > self.fake_reward_prob: + self.use_cum_reward = False + if random.random() > self.fake_reward_prob: + self.use_bo_reward = False + self.race = race # home_race self.requested_race = requested_race self.map_size = map_size @@ -395,6 +430,7 @@ def _forward_collect(self, data): if self._cfg.cuda: obs = to_device(obs, self._device) + self._collect_model.eval() with torch.no_grad(): policy_output = self._collect_model.compute_logp_action(**obs) @@ -408,7 +444,7 @@ def _data_preprocess_collect(self, data): if self._cfg.use_value_feature: obs = transform_obs(data['raw_obs'], self.map_size, self.requested_race, padding_spatial=True, opponent_obs=data['opponent_obs']) else: - raise NotImplementedError + obs = transform_obs(data['raw_obs'], self.map_size, self.requested_race, padding_spatial=True) game_info = obs.pop('game_info') game_step = game_info['game_loop'] @@ -436,14 +472,14 @@ def _data_preprocess_collect(self, data): obs['scalar_info']['enemy_unit_type_bool'] = ( self.enemy_unit_type_bool | obs['scalar_info']['enemy_unit_type_bool'] ).to(torch.uint8) - if self.exceed_loop_flag: - obs['scalar_info']['cumulative_stat'] = self.target_cumulative_stat * 0 + self._cfg.zero_z_value - obs['scalar_info']['beginning_order'] = self.target_building_order * 0 - obs['scalar_info']['bo_location'] = self.target_bo_location * 0 - else: + + obs['scalar_info']['beginning_order'] = self.target_building_order * (self.use_bo_reward & (not self.exceed_loop_flag)) + obs['scalar_info']['bo_location'] = self.target_bo_location * (self.use_bo_reward & (not self.exceed_loop_flag)) + + if self.use_cum_reward and not self.exceed_loop_flag: obs['scalar_info']['cumulative_stat'] = self.target_cumulative_stat - obs['scalar_info']['beginning_order'] = self.target_building_order - obs['scalar_info']['bo_location'] = self.target_bo_location + else: + obs['scalar_info']['cumulative_stat'] = self.target_cumulative_stat * 0 + self._cfg.zero_z_value # update stat self.stat.update(self.last_action_type, data['action_result'][0], obs, game_step) From a99c8bb289b1da980b951549eea466cbc39318c9 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 6 Jul 2022 16:27:35 +0800 Subject: [PATCH 188/229] move GLU and build_activation in action_type_head.py to ding/torch_utils/network/activation.py, rename them to GLU2 and build_activation2 --- ding/torch_utils/network/__init__.py | 2 +- ding/torch_utils/network/activation.py | 28 ++++++++++++++++ dizoo/distar/model/head/action_type_head.py | 37 +++------------------ 3 files changed, 34 insertions(+), 33 deletions(-) diff --git a/ding/torch_utils/network/__init__.py b/ding/torch_utils/network/__init__.py index 56926e7180..23bad434b5 100644 --- a/ding/torch_utils/network/__init__.py +++ b/ding/torch_utils/network/__init__.py @@ -1,4 +1,4 @@ -from .activation import build_activation, Swish +from .activation import build_activation, Swish, build_activation2 from .res_block import ResBlock, ResFCBlock, GatedConvResBlock from .nn_module import fc_block, conv2d_block, one_hot, deconv2d_block, BilinearUpsample, NearestUpsample, \ binary_encode, NoiseLinearLayer, noise_block, MLP, Flatten, normed_linear, normed_conv2d, AttentionPool diff --git a/ding/torch_utils/network/activation.py b/ding/torch_utils/network/activation.py index 8fe27c1108..167395d3aa 100644 --- a/ding/torch_utils/network/activation.py +++ b/ding/torch_utils/network/activation.py @@ -1,6 +1,7 @@ import torch import torch.nn as nn import torch.nn.functional as F +from ding.torch_utils.network.nn_module import fc_block, conv2d_block class GLU(nn.Module): @@ -92,3 +93,30 @@ def build_activation(activation: str, inplace: bool = None) -> nn.Module: return act_func[activation] else: raise KeyError("invalid key for activation: {}".format(activation)) + + +class GLU2(nn.Module): + def __init__(self, input_dim, output_dim, context_dim, input_type='fc'): + super(GLU2, self).__init__() + assert (input_type in ['fc', 'conv2d']) + if input_type == 'fc': + self.layer1 = fc_block(context_dim, input_dim) + self.layer2 = fc_block(input_dim, output_dim) + elif input_type == 'conv2d': + self.layer1 = conv2d_block(context_dim, input_dim, 1, 1, 0) + self.layer2 = conv2d_block(input_dim, output_dim, 1, 1, 0) + + def forward(self, x, context): + gate = self.layer1(context) + gate = torch.sigmoid(gate) + x = gate * x + x = self.layer2(x) + return x + + +def build_activation2(activation): + act_func = {'relu': nn.ReLU(inplace=True), 'glu': GLU2, 'prelu': nn.PReLU(init=0.0)} + if activation in act_func.keys(): + return act_func[activation] + else: + raise KeyError("invalid key for activation: {}".format(activation)) diff --git a/dizoo/distar/model/head/action_type_head.py b/dizoo/distar/model/head/action_type_head.py index ddcda01b80..ad91ce06e8 100644 --- a/dizoo/distar/model/head/action_type_head.py +++ b/dizoo/distar/model/head/action_type_head.py @@ -9,48 +9,21 @@ import torch import torch.nn as nn import torch.nn.functional as F -from ding.torch_utils import ResFCBlock, fc_block, conv2d_block +from ding.torch_utils import ResFCBlock, fc_block, build_activation2 from dizoo.distar.envs import ACTION_RACE_MASK -class GLU(nn.Module): - def __init__(self, input_dim, output_dim, context_dim, input_type='fc'): - super(GLU, self).__init__() - assert (input_type in ['fc', 'conv2d']) - if input_type == 'fc': - self.layer1 = fc_block(context_dim, input_dim) - self.layer2 = fc_block(input_dim, output_dim) - elif input_type == 'conv2d': - self.layer1 = conv2d_block(context_dim, input_dim, 1, 1, 0) - self.layer2 = conv2d_block(input_dim, output_dim, 1, 1, 0) - - def forward(self, x, context): - gate = self.layer1(context) - gate = torch.sigmoid(gate) - x = gate * x - x = self.layer2(x) - return x - - -def build_activation(activation): - act_func = {'relu': nn.ReLU(inplace=True), 'glu': GLU, 'prelu': nn.PReLU(init=0.0)} - if activation in act_func.keys(): - return act_func[activation] - else: - raise KeyError("invalid key for activation: {}".format(activation)) - - class ActionTypeHead(nn.Module): __constants__ = ['mask_action'] def __init__(self, cfg): super(ActionTypeHead, self).__init__() self.cfg = cfg - self.act = build_activation(self.cfg.activation) # use relu as default + self.act = build_activation2(self.cfg.activation) # use relu as default self.project = fc_block(self.cfg.input_dim, self.cfg.res_dim, activation=self.act, norm_type=None) blocks = [ResFCBlock(self.cfg.res_dim, self.act, self.cfg.norm_type) for _ in range(self.cfg.res_num)] self.res = nn.Sequential(*blocks) - self.action_fc = build_activation('glu')(self.cfg.res_dim, self.cfg.action_num, self.cfg.context_dim) + self.action_fc = build_activation2('glu')(self.cfg.res_dim, self.cfg.action_num, self.cfg.context_dim) self.action_map_fc1 = fc_block( self.cfg.action_num, self.cfg.action_map_dim, activation=self.act, norm_type=None @@ -58,8 +31,8 @@ def __init__(self, cfg): self.action_map_fc2 = fc_block( self.cfg.action_map_dim, self.cfg.action_map_dim, activation=None, norm_type=None ) - self.glu1 = build_activation('glu')(self.cfg.action_map_dim, self.cfg.gate_dim, self.cfg.context_dim) - self.glu2 = build_activation('glu')(self.cfg.input_dim, self.cfg.gate_dim, self.cfg.context_dim) + self.glu1 = build_activation2('glu')(self.cfg.action_map_dim, self.cfg.gate_dim, self.cfg.context_dim) + self.glu2 = build_activation2('glu')(self.cfg.input_dim, self.cfg.gate_dim, self.cfg.context_dim) self.action_num = self.cfg.action_num self.use_mask = self.cfg.use_mask self.race = self.cfg.race From a11e14628fb6eb26e79ea9c412e1898669602d4a Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Mon, 11 Jul 2022 01:04:13 +0800 Subject: [PATCH 189/229] change default value of build_activation to False --- ding/torch_utils/network/activation.py | 4 ++-- dizoo/distar/model/head/action_arg_head.py | 20 +++++++++---------- .../model/obs_encoder/entity_encoder.py | 2 +- .../model/obs_encoder/scalar_encoder.py | 4 ++-- .../model/obs_encoder/spatial_encoder.py | 2 +- .../distar/model/obs_encoder/value_encoder.py | 2 +- dizoo/distar/model/value.py | 2 +- dizoo/distar/policy/test_distar_policy.py | 3 ++- 8 files changed, 20 insertions(+), 19 deletions(-) diff --git a/ding/torch_utils/network/activation.py b/ding/torch_utils/network/activation.py index 167395d3aa..c1a9110758 100644 --- a/ding/torch_utils/network/activation.py +++ b/ding/torch_utils/network/activation.py @@ -86,8 +86,7 @@ def build_activation(activation: str, inplace: bool = None) -> nn.Module: if inplace is not None: assert activation == 'relu', 'inplace argument is not compatible with {}'.format(activation) else: - # TODO(nyz): influence dizoo/gfootball/model/iql/iql_network.py, and tests of this function - inplace = True + inplace = False act_func = {'relu': nn.ReLU(inplace=inplace), 'glu': GLU, 'prelu': nn.PReLU(), 'swish': Swish()} if activation in act_func.keys(): return act_func[activation] @@ -96,6 +95,7 @@ def build_activation(activation: str, inplace: bool = None) -> nn.Module: class GLU2(nn.Module): + def __init__(self, input_dim, output_dim, context_dim, input_type='fc'): super(GLU2, self).__init__() assert (input_type in ['fc', 'conv2d']) diff --git a/dizoo/distar/model/head/action_arg_head.py b/dizoo/distar/model/head/action_arg_head.py index 1c7e7b61fc..f9df39b9ba 100644 --- a/dizoo/distar/model/head/action_arg_head.py +++ b/dizoo/distar/model/head/action_arg_head.py @@ -26,7 +26,7 @@ class DelayHead(nn.Module): def __init__(self, cfg): super(DelayHead, self).__init__() self.cfg = cfg - self.act = build_activation(self.cfg.activation) + self.act = build_activation(self.cfg.activation, inplace=True) self.fc1 = fc_block(self.cfg.input_dim, self.cfg.decode_dim, activation=self.act, norm_type=None) self.fc2 = fc_block(self.cfg.decode_dim, self.cfg.decode_dim, activation=self.act, norm_type=None) self.fc3 = fc_block(self.cfg.decode_dim, self.cfg.delay_dim, activation=None, norm_type=None) # regression @@ -55,7 +55,7 @@ class QueuedHead(nn.Module): def __init__(self, cfg): super(QueuedHead, self).__init__() self.cfg = cfg - self.act = build_activation(self.cfg.activation) + self.act = build_activation(self.cfg.activation, inplace=True) # to get queued logits self.fc1 = fc_block(self.cfg.input_dim, self.cfg.decode_dim, activation=self.act, norm_type=None) self.fc2 = fc_block(self.cfg.decode_dim, self.cfg.decode_dim, activation=self.act, norm_type=None) @@ -88,7 +88,7 @@ class SelectedUnitsHead(nn.Module): def __init__(self, cfg): super(SelectedUnitsHead, self).__init__() self.cfg = cfg - self.act = build_activation(self.cfg.activation) + self.act = build_activation(self.cfg.activation, inplace=True) self.key_fc = fc_block(self.cfg.entity_embedding_dim, self.cfg.key_dim, activation=None, norm_type=None) self.query_fc1 = fc_block(self.cfg.input_dim, self.cfg.func_dim, activation=self.act) self.query_fc2 = fc_block(self.cfg.func_dim, self.cfg.key_dim, activation=None) @@ -300,7 +300,7 @@ class TargetUnitHead(nn.Module): def __init__(self, cfg): super(TargetUnitHead, self).__init__() self.cfg = cfg - self.act = build_activation(self.cfg.activation) + self.act = build_activation(self.cfg.activation, inplace=True) self.key_fc = fc_block(self.cfg.entity_embedding_dim, self.cfg.key_dim, activation=None, norm_type=None) self.query_fc1 = fc_block(self.cfg.input_dim, self.cfg.key_dim, activation=self.act, norm_type=None) self.query_fc2 = fc_block(self.cfg.key_dim, self.cfg.key_dim, activation=None, norm_type=None) @@ -329,7 +329,7 @@ class LocationHead(nn.Module): def __init__(self, cfg): super(LocationHead, self).__init__() self.cfg = cfg - self.act = build_activation(self.cfg.activation) + self.act = build_activation(self.cfg.activation, inplace=True) self.reshape_channel = self.cfg.reshape_channel self.conv1 = conv2d_block( @@ -338,7 +338,7 @@ def __init__(self, cfg): 1, 1, 0, - activation=build_activation(self.cfg.activation), + activation=build_activation(self.cfg.activation, inplace=True), norm_type=None ) self.res = nn.ModuleList() @@ -348,7 +348,7 @@ def __init__(self, cfg): self.project_embed = fc_block( self.cfg.input_dim, self.cfg.spatial_y // 8 * self.cfg.spatial_x // 8 * 4, - activation=build_activation(self.cfg.activation) + activation=build_activation(self.cfg.activation, inplace=True) ) self.res = nn.ModuleList() @@ -361,12 +361,12 @@ def __init__(self, cfg): 3, 1, 1, - activation=build_activation(self.cfg.activation), + activation=build_activation(self.cfg.activation, inplace=True), norm_type=None ) ) else: - self.res.append(ResBlock(self.dim, build_activation(self.cfg.activation), norm_type=None)) + self.res.append(ResBlock(self.dim, build_activation(self.cfg.activation, inplace=True), norm_type=None)) self.upsample = nn.ModuleList() # upsample list dims = [self.res_dim] + self.cfg.upsample_dims @@ -375,7 +375,7 @@ def __init__(self, cfg): if i == len(self.cfg.upsample_dims) - 1: activation = None else: - activation = build_activation(self.cfg.activation) + activation = build_activation(self.cfg.activation, inplace=True) if self.cfg.upsample_type == 'deconv': self.upsample.append( deconv2d_block(dims[i], dims[i + 1], 4, 2, 1, activation=activation, norm_type=None) diff --git a/dizoo/distar/model/obs_encoder/entity_encoder.py b/dizoo/distar/model/obs_encoder/entity_encoder.py index a94de40037..a47f34fd3a 100644 --- a/dizoo/distar/model/obs_encoder/entity_encoder.py +++ b/dizoo/distar/model/obs_encoder/entity_encoder.py @@ -37,7 +37,7 @@ def __init__(self, cfg): self.encode_modules[k] = torch.nn.Embedding.from_pretrained( get_binary_embed_mat(item['num_embeddings']), freeze=True, padding_idx=None ) - self.act = build_activation(self.cfg.activation) + self.act = build_activation(self.cfg.activation, inplace=True) self.transformer = Transformer( input_dim=self.cfg.input_dim, head_dim=self.cfg.head_dim, diff --git a/dizoo/distar/model/obs_encoder/scalar_encoder.py b/dizoo/distar/model/obs_encoder/scalar_encoder.py index 3bad5cb933..14e02086bc 100644 --- a/dizoo/distar/model/obs_encoder/scalar_encoder.py +++ b/dizoo/distar/model/obs_encoder/scalar_encoder.py @@ -22,7 +22,7 @@ def __init__(self, cfg): self.cfg = cfg self.output_dim = self.cfg.output_dim self.input_dim = self.cfg.action_one_hot_dim + 20 + self.cfg.binary_dim * 2 - self.act = build_activation(self.cfg.activation) + self.act = build_activation(self.cfg.activation, inplace=True) self.transformer = Transformer( input_dim=self.input_dim, head_dim=self.cfg.head_dim, @@ -65,7 +65,7 @@ class ScalarEncoder(nn.Module): def __init__(self, cfg): super(ScalarEncoder, self).__init__() self.cfg = cfg - self.act = build_activation(self.cfg.activation) + self.act = build_activation(self.cfg.activation, inplace=True) self.keys = [] self.scalar_context_keys = [] self.baseline_feature_keys = [] diff --git a/dizoo/distar/model/obs_encoder/spatial_encoder.py b/dizoo/distar/model/obs_encoder/spatial_encoder.py index 95549eef07..8bfda6fcfe 100644 --- a/dizoo/distar/model/obs_encoder/spatial_encoder.py +++ b/dizoo/distar/model/obs_encoder/spatial_encoder.py @@ -12,7 +12,7 @@ class SpatialEncoder(nn.Module): def __init__(self, cfg): super(SpatialEncoder, self).__init__() self.cfg = cfg - self.act = build_activation(self.cfg.activation) + self.act = build_activation(self.cfg.activation, inplace=True) if self.cfg.norm_type == 'none': self.norm = None else: diff --git a/dizoo/distar/model/obs_encoder/value_encoder.py b/dizoo/distar/model/obs_encoder/value_encoder.py index a8183c3233..fa49ae0362 100644 --- a/dizoo/distar/model/obs_encoder/value_encoder.py +++ b/dizoo/distar/model/obs_encoder/value_encoder.py @@ -14,7 +14,7 @@ def __init__(self, cfg): super(ValueEncoder, self).__init__() self.whole_cfg = cfg self.cfg = cfg.model.value.encoder - self.act = build_activation('relu') + self.act = build_activation('relu', inplace=True) self.encode_modules = nn.ModuleDict() for k, item in self.cfg.modules.items(): if item['arc'] == 'fc': diff --git a/dizoo/distar/model/value.py b/dizoo/distar/model/value.py index 501b8ebbc8..b3e76e5f9d 100644 --- a/dizoo/distar/model/value.py +++ b/dizoo/distar/model/value.py @@ -15,7 +15,7 @@ class ValueBaseline(nn.Module): def __init__(self, cfg): super(ValueBaseline, self).__init__() - self.act = build_activation(cfg.activation) + self.act = build_activation(cfg.activation, inplace=True) if cfg.use_value_feature: input_dim = cfg.input_dim + 1056 else: diff --git a/dizoo/distar/policy/test_distar_policy.py b/dizoo/distar/policy/test_distar_policy.py index 76ff7ea9aa..40a786d352 100644 --- a/dizoo/distar/policy/test_distar_policy.py +++ b/dizoo/distar/policy/test_distar_policy.py @@ -23,11 +23,12 @@ def test_forward_collect(self): rl_model = torch.load('./rl_model.pth') policy.load_state_dict(rl_model) - + data = get_fake_env_reset_data() policy.reset(data) output = policy.forward(data) + if __name__ == '__main__': set_pkg_seed(0, use_cuda=False) torch.set_printoptions(profile="full") From ca651b54c0bec1801d94336e3b7956932a3fe7bd Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Mon, 11 Jul 2022 02:08:19 +0800 Subject: [PATCH 190/229] add util to change ia's model --- dizoo/distar/policy/distar_policy.py | 28 ++++++++++------------- dizoo/distar/policy/test_distar_policy.py | 1 + dizoo/distar/state_dict_utils.py | 19 +++++++++++++++ 3 files changed, 32 insertions(+), 16 deletions(-) create mode 100644 dizoo/distar/state_dict_utils.py diff --git a/dizoo/distar/policy/distar_policy.py b/dizoo/distar/policy/distar_policy.py index 088ad73ba4..4aa3414848 100644 --- a/dizoo/distar/policy/distar_policy.py +++ b/dizoo/distar/policy/distar_policy.py @@ -110,7 +110,6 @@ class DIStarPolicy(Policy): zero_z_value=1, extra_units=True, # selcet extra units if selected units exceed 64 z_path='7map_filter_spine.json', - use_upia_model=True ) def _create_model( @@ -357,7 +356,7 @@ def _load_state_dict_learn(self, _state_dict: Dict) -> None: def _load_state_dict_collect(self, _state_dict: Dict) -> None: #TODO(zms): need to load state_dict after collect, which is very dirty and need to rewrite - + if 'map_name' in _state_dict: # map_names.append(_state_dict['map_name']) self.fake_reward_prob = _state_dict['fake_reward_prob'] @@ -365,21 +364,11 @@ def _load_state_dict_collect(self, _state_dict: Dict) -> None: self.z_idx = _state_dict['z_idx'] _state_dict = {k: v for k, v in _state_dict['model'].items() if 'value_networks' not in k} - if self.use_upia_model: - for key in list(_state_dict.keys()): - new = key - if "transformer" in key: - new = key.replace('layers', 'main').replace('mlp.1', 'mlp.2') - elif "location_head" in key: - new = key.replace('GateWeightG', 'gate').replace('UpdateSP','update_sp') - _state_dict[new] = _state_dict.pop(key) - self._collect_model.load_state_dict(_state_dict, strict=False) def _init_collect(self): self._collect_model = model_wrap(self._model, 'base') self.z_path = self._cfg.z_path - self.use_upia_model = self._cfg.use_upia_model # TODO(zms): in _setup_agents, load state_dict to set up z_idx self.z_idx = None @@ -410,7 +399,7 @@ def _reset_collect(self, data: Dict): self.use_cum_reward = False if random.random() > self.fake_reward_prob: self.use_bo_reward = False - + self.race = race # home_race self.requested_race = requested_race self.map_size = map_size @@ -442,7 +431,13 @@ def _forward_collect(self, data): def _data_preprocess_collect(self, data): if self._cfg.use_value_feature: - obs = transform_obs(data['raw_obs'], self.map_size, self.requested_race, padding_spatial=True, opponent_obs=data['opponent_obs']) + obs = transform_obs( + data['raw_obs'], + self.map_size, + self.requested_race, + padding_spatial=True, + opponent_obs=data['opponent_obs'] + ) else: obs = transform_obs(data['raw_obs'], self.map_size, self.requested_race, padding_spatial=True) @@ -473,9 +468,10 @@ def _data_preprocess_collect(self, data): self.enemy_unit_type_bool | obs['scalar_info']['enemy_unit_type_bool'] ).to(torch.uint8) - obs['scalar_info']['beginning_order'] = self.target_building_order * (self.use_bo_reward & (not self.exceed_loop_flag)) + obs['scalar_info']['beginning_order' + ] = self.target_building_order * (self.use_bo_reward & (not self.exceed_loop_flag)) obs['scalar_info']['bo_location'] = self.target_bo_location * (self.use_bo_reward & (not self.exceed_loop_flag)) - + if self.use_cum_reward and not self.exceed_loop_flag: obs['scalar_info']['cumulative_stat'] = self.target_cumulative_stat else: diff --git a/dizoo/distar/policy/test_distar_policy.py b/dizoo/distar/policy/test_distar_policy.py index 40a786d352..6eedf13f2a 100644 --- a/dizoo/distar/policy/test_distar_policy.py +++ b/dizoo/distar/policy/test_distar_policy.py @@ -27,6 +27,7 @@ def test_forward_collect(self): data = get_fake_env_reset_data() policy.reset(data) output = policy.forward(data) + print(output) if __name__ == '__main__': diff --git a/dizoo/distar/state_dict_utils.py b/dizoo/distar/state_dict_utils.py new file mode 100644 index 0000000000..9c94b39f5a --- /dev/null +++ b/dizoo/distar/state_dict_utils.py @@ -0,0 +1,19 @@ +import torch + + +def adjust_ia_state_dict(model_path): + state_dict = torch.load(model_path) + for key in list(state_dict['model'].keys()): + new = key + if "transformer" in key: + new = key.replace('layers', 'main').replace('mlp.1', 'mlp.2') + elif "location_head" in key: + new = key.replace('GateWeightG', 'gate').replace('UpdateSP', 'update_sp') + state_dict['model'][new] = state_dict['model'].pop(key) + + torch.save(state_dict, model_path) + + +if __name__ == '__main__': + model_path = './tests/rl_model.pth' + adjust_ia_state_dict(model_path) From 8dd3b393ed738c7527773d049ec1b32b0d10f5ee Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Mon, 11 Jul 2022 16:04:55 +0800 Subject: [PATCH 191/229] add update_fake_reward; change behaviour to behavior --- ding/torch_utils/__init__.py | 2 +- ding/torch_utils/metric.py | 10 ++ dizoo/distar/envs/__init__.py | 4 +- dizoo/distar/envs/distar_env.py | 6 +- dizoo/distar/policy/distar_policy.py | 202 ++++++++++++++++++++++++--- 5 files changed, 199 insertions(+), 25 deletions(-) diff --git a/ding/torch_utils/__init__.py b/ding/torch_utils/__init__.py index b78d0f08b2..69f0891dd0 100644 --- a/ding/torch_utils/__init__.py +++ b/ding/torch_utils/__init__.py @@ -2,7 +2,7 @@ from .data_helper import to_device, to_tensor, to_ndarray, to_list, to_dtype, same_shape, tensor_to_list, \ build_log_buffer, CudaFetcher, get_tensor_data, unsqueeze, get_null_data, detach_grad, flatten from .distribution import CategoricalPd, CategoricalPdPytorch -from .metric import levenshtein_distance, hamming_distance +from .metric import l2_distance, levenshtein_distance, hamming_distance from .network import * from .loss import * from .optimizer_helper import Adam, RMSprop, calculate_grad_norm, calculate_grad_norm_without_bias_two_norm diff --git a/ding/torch_utils/metric.py b/ding/torch_utils/metric.py index 7fc2edf230..827bee4634 100644 --- a/ding/torch_utils/metric.py +++ b/ding/torch_utils/metric.py @@ -2,6 +2,16 @@ from typing import Optional, Callable +def l2_distance(a, b, min=0, max=0.8, threshold=5, spatial_x=160): + x0 = a % spatial_x + y0 = a // spatial_x + x1 = b % spatial_x + y1 = b // spatial_x + l2 = torch.sqrt((torch.square(x1 - x0) + torch.square(y1 - y0)).float()) + cost = (l2 / threshold).clamp_(min=min, max=max) + return cost + + def levenshtein_distance( pred: torch.LongTensor, target: torch.LongTensor, diff --git a/dizoo/distar/envs/__init__.py b/dizoo/distar/envs/__init__.py index 5fec4947d1..d1eb59ed5a 100644 --- a/dizoo/distar/envs/__init__.py +++ b/dizoo/distar/envs/__init__.py @@ -1,5 +1,5 @@ -from .distar_env import DIStarEnv, parse_new_game, transform_obs +from .distar_env import DIStarEnv, parse_new_game, transform_obs, compute_battle_score from .meta import * -from .static_data import RACE_DICT, BEGIN_ACTIONS, ACTION_RACE_MASK, SELECTED_UNITS_MASK, ACTIONS +from .static_data import RACE_DICT, BEGIN_ACTIONS, ACTION_RACE_MASK, SELECTED_UNITS_MASK, ACTIONS, BEGINNING_ORDER_ACTIONS, UNIT_TO_CUM, UPGRADE_TO_CUM, UNIT_ABILITY_TO_ACTION, QUEUE_ACTIONS, CUMULATIVE_STAT_ACTIONS from .stat import Stat from .fake_data import get_fake_rl_trajectory, get_fake_env_reset_data, get_fake_env_step_data diff --git a/dizoo/distar/envs/distar_env.py b/dizoo/distar/envs/distar_env.py index a7138c9db1..a4aeaca3df 100644 --- a/dizoo/distar/envs/distar_env.py +++ b/dizoo/distar/envs/distar_env.py @@ -200,7 +200,7 @@ def parse_new_game(data, z_path: str, z_idx: Optional[None] = List): if i.unit_type == 59 or i.unit_type == 18 or i.unit_type == 86: location.append([i.pos.x, i.pos.y]) assert len(location) == 1, 'no fog of war, check game version!' - born_location = deepcopy(location[0]) + _born_location = deepcopy(location[0]) born_location = location[0] born_location[0] = int(born_location[0]) born_location[1] = int(map_size.y - born_location[1]) @@ -225,7 +225,7 @@ def parse_new_game(data, z_path: str, z_idx: Optional[None] = List): target_building_order, target_cumulative_stat, bo_location, target_z_loop, z_type = z else: target_building_order, target_cumulative_stat, bo_location, target_z_loop = z - return race, requested_races, map_size, target_building_order, target_cumulative_stat, bo_location, target_z_loop, z_type + return race, requested_races, map_size, target_building_order, target_cumulative_stat, bo_location, target_z_loop, z_type, _born_location class FeatureUnit(enum.IntEnum): @@ -599,7 +599,7 @@ def get_addon_type(tag): index=enemy_unit_types.long(), src=torch.ones_like(enemy_unit_types, dtype=torch.uint8) ) - + # game info game_info['action_result'] = [o.result for o in obs.action_errors] game_info['game_loop'] = obs.observation.game_loop diff --git a/dizoo/distar/policy/distar_policy.py b/dizoo/distar/policy/distar_policy.py index 4aa3414848..5b7d10925a 100644 --- a/dizoo/distar/policy/distar_policy.py +++ b/dizoo/distar/policy/distar_policy.py @@ -1,19 +1,22 @@ +from logging.config import DEFAULT_LOGGING_CONFIG_PORT from typing import Dict, Optional, List from easydict import EasyDict import os.path as osp import torch from torch.optim import Adam import random +from functools import partial from ding.model import model_wrap from ding.policy import Policy -from ding.torch_utils import to_device +from ding.torch_utils import to_device, levenshtein_distance, l2_distance, hamming_distance from ding.rl_utils import td_lambda_data, td_lambda_error, vtrace_data_with_rho, vtrace_error_with_rho, \ upgo_data, upgo_error from ding.utils import EasyTimer from ding.utils.data import default_collate, default_decollate from dizoo.distar.model import Model -from dizoo.distar.envs import NUM_UNIT_TYPES, ACTIONS, NUM_CUMULATIVE_STAT_ACTIONS, DEFAULT_SPATIAL_SIZE, Stat, parse_new_game, transform_obs +from dizoo.distar.envs import NUM_UNIT_TYPES, ACTIONS, NUM_CUMULATIVE_STAT_ACTIONS, DEFAULT_SPATIAL_SIZE, BEGINNING_ORDER_LENGTH, BEGINNING_ORDER_ACTIONS, UNIT_TO_CUM, UPGRADE_TO_CUM, UNIT_ABILITY_TO_ACTION, QUEUE_ACTIONS, CUMULATIVE_STAT_ACTIONS,\ + Stat, parse_new_game, transform_obs, compute_battle_score from .utils import collate_fn_learn, kl_error, entropy_error @@ -107,9 +110,12 @@ class DIStarPolicy(Policy): # collect use_value_feature=True, # TODO(zms): whether to use value feature, this must be False when play against bot zero_z_exceed_loop=True, # set Z to 0 if game passes the game loop in Z - zero_z_value=1, + fake_reward_prob=0.0, # probablity which set Z to 0 + zero_z_value=1, # value used for 0Z extra_units=True, # selcet extra units if selected units exceed 64 + clip_bo=False, # clip the length of teacher's building order to agent's length z_path='7map_filter_spine.json', + realtime=False, #TODO(zms): set from env, need to use only one cfg define policy and env ) def _create_model( @@ -174,7 +180,7 @@ def _forward_learn(self, inputs: Dict): # =========== target_policy_logits_dict = model_output['target_logit'] # shape (T,B) baseline_values_dict = model_output['value'] # shape (T+1,B) - behaviour_action_log_probs_dict = model_output['action_log_prob'] # shape (T,B) + behavior_action_log_probs_dict = model_output['action_log_prob'] # shape (T,B) teacher_policy_logits_dict = model_output['teacher_logit'] # shape (T,B) masks_dict = model_output['mask'] # shape (T,B) actions_dict = model_output['action'] # shape (T,B) @@ -192,7 +198,7 @@ def _forward_learn(self, inputs: Dict): clipped_rhos_dict = {} # ============================================================ - # get distribution info for behaviour policy and target policy + # get distribution info for behavior policy and target policy # ============================================================ for head_type in self.head_types: # take info from correspondent input dict @@ -203,10 +209,10 @@ def _forward_learn(self, inputs: Dict): target_policy_probs = pi_target.probs target_policy_log_probs = pi_target.logits target_action_log_probs = pi_target.log_prob(actions) - behaviour_action_log_probs = behaviour_action_log_probs_dict[head_type] + behavior_action_log_probs = behavior_action_log_probs_dict[head_type] with torch.no_grad(): - log_rhos = target_action_log_probs - behaviour_action_log_probs + log_rhos = target_action_log_probs - behavior_action_log_probs if head_type == 'selected_units': log_rhos *= masks_dict['selected_units_mask'] log_rhos = log_rhos.sum(dim=-1) @@ -369,8 +375,14 @@ def _load_state_dict_collect(self, _state_dict: Dict) -> None: def _init_collect(self): self._collect_model = model_wrap(self._model, 'base') self.z_path = self._cfg.z_path - # TODO(zms): in _setup_agents, load state_dict to set up z_idx self.z_idx = None + self.bo_norm = 20 #TODO(nyz): set from cfg + self.cum_norm = 30 #TODO(nyz): set from cfg + self.battle_norm = 30 #TODO(nyz): set from cfg + self.fake_reward_prob = self._cfg.fake_reward_prob + self.clip_bo = self._cfg.clip_bo + self.cum_type = 'action' # observation or action + self.realtime = self._cfg.realtime def _reset_collect(self, data: Dict): self.exceed_loop_flag = False @@ -384,10 +396,18 @@ def _reset_collect(self, data: Dict): self.last_targeted_unit_tag = None self.last_location = None # [x, y] self.enemy_unit_type_bool = torch.zeros(NUM_UNIT_TYPES, dtype=torch.uint8) - - race, requested_race, map_size, target_building_order, target_cumulative_stat, bo_location, target_z_loop, z_type = parse_new_game( + self._observation = None # TODO(zms): need to move to input and output of function + self._output = None # TODO(zms): need to move to input and output of function + self.game_step = 0 # step * 10 is game duration time + self.behavior_building_order = [] # idx in BEGINNING_ORDER_ACTIONS + self.behavior_bo_location = [] + self.bo_zergling_count = 0 + self.behavior_cumulative_stat = [0] * NUM_CUMULATIVE_STAT_ACTIONS + + race, requested_race, map_size, target_building_order, target_cumulative_stat, bo_location, target_z_loop, z_type, _born_location = parse_new_game( data, self.z_path, self.z_idx ) + self.born_location = _born_location self.use_cum_reward = True self.use_bo_reward = True if z_type is not None: @@ -400,6 +420,9 @@ def _reset_collect(self, data: Dict): if random.random() > self.fake_reward_prob: self.use_bo_reward = False + self.bo_norm = len(self.target_building_order) + self.cum_norm = len(target_cumulative_stat) + self.race = race # home_race self.requested_race = requested_race self.map_size = map_size @@ -412,6 +435,18 @@ def _reset_collect(self, data: Dict): self.target_cumulative_stat.scatter_( index=torch.tensor(target_cumulative_stat, dtype=torch.long), dim=0, value=1. ) + if not self.realtime: + if not self.clip_bo: + self.old_bo_reward = -levenshtein_distance( + torch.as_tensor(self.behavior_building_order, dtype=torch.long), self.target_building_order + ) / self.bo_norm + else: + self.old_bo_reward = torch.tensor(0.) + self.old_cum_reward = -hamming_distance( + torch.as_tensor(self.behavior_cumulative_stat, dtype=torch.float), self.target_cumulative_stat + ) / self.cum_norm + self.total_bo_reward = torch.zeros(size=(), dtype=torch.float) + self.total_cum_reward = torch.zeros(size=(), dtype=torch.float) def _forward_collect(self, data): obs, game_info = self._data_preprocess_collect(data) @@ -442,8 +477,10 @@ def _data_preprocess_collect(self, data): obs = transform_obs(data['raw_obs'], self.map_size, self.requested_race, padding_spatial=True) game_info = obs.pop('game_info') - game_step = game_info['game_loop'] - if self._cfg.zero_z_exceed_loop and game_step > self.target_z_loop: + self.battle_score = game_info['battle_score'] + self.opponent_battle_score = game_info['opponent_battle_score'] + self.game_step = game_info['game_loop'] + if self._cfg.zero_z_exceed_loop and self.game_step > self.target_z_loop: self.exceed_loop_flag = True last_selected_units = torch.zeros(obs['entity_num'], dtype=torch.int8) @@ -477,16 +514,20 @@ def _data_preprocess_collect(self, data): else: obs['scalar_info']['cumulative_stat'] = self.target_cumulative_stat * 0 + self._cfg.zero_z_value + self._observation = obs + # update stat - self.stat.update(self.last_action_type, data['action_result'][0], obs, game_step) + self.stat.update(self.last_action_type, data['action_result'][0], obs, self.game_step) return obs, game_info def _data_postprocess_collect(self, data, game_info): self.hidden_state = data['hidden_state'] - + self.last_queued = data['action_info']['queued'] self.last_action_type = data['action_info']['action_type'] self.last_delay = data['action_info']['delay'] - self.last_queued = data['action_info']['queued'] + self.last_location = data['action_info']['target_location'] + self._output = data + action_type = self.last_action_type.item() action_attr = ACTIONS[action_type] @@ -520,20 +561,143 @@ def _data_postprocess_collect(self, data, game_info): y = data['action_info']['target_location'].item() // DEFAULT_SPATIAL_SIZE[1] inverse_y = max(self.map_size.y - y, 0) raw_action['location'] = (x, inverse_y) - self.last_location = data['action_info']['target_location'] data['action'] = [raw_action] return data - def _process_transition(self, obs, policy_output, timestep): + def _process_transition(self, next_obs, reward, done): + action_result = False if next_obs is None else ('Success' in next_obs['action_result']) + + behavior_z = self.get_behavior_z() + bo_reward, cum_reward, battle_reward = self.update_fake_reward(next_obs) + + def get_behavior_z(self): + bo = self.behavior_building_order + [0] * (BEGINNING_ORDER_LENGTH - len(self.behavior_building_order)) + bo_location = self.behavior_bo_location + [0] * (BEGINNING_ORDER_LENGTH - len(self.behavior_bo_location)) return { - 'obs': obs, - 'action': policy_output['action_info'], + 'beginning_order': torch.as_tensor(bo, dtype=torch.long), + 'bo_location': torch.as_tensor(bo_location, dtype=torch.long), + 'cumulative_stat': torch.as_tensor(self.behavior_cumulative_stat, dtype=torch.bool).long() } + def update_fake_reward(self, next_obs): + bo_reward, cum_reward, battle_reward = self._update_fake_reward( + self.last_action_type, self.last_location, next_obs + ) + return bo_reward, cum_reward, battle_reward + + def _update_fake_reward(self, action_type, location, next_obs): + bo_reward = torch.zeros(size=(), dtype=torch.float) + cum_reward = torch.zeros(size=(), dtype=torch.float) + + battle_score = compute_battle_score(next_obs['raw_obs']) + opponent_battle_score = compute_battle_score(next_obs['opponent_obs']) + battle_reward = battle_score - self.battle_score - (opponent_battle_score - self.opponent_battle_score) + battle_reward = torch.tensor(battle_reward, dtype=torch.float) / self.battle_norm + + if self.exceed_loop_flag: + return bo_reward, cum_reward, battle_reward + + if action_type in BEGINNING_ORDER_ACTIONS and next_obs['action_result'][0] == 1: + if action_type == 322: + self.bo_zergling_count += 1 + if self.bo_zergling_count > 8: + return bo_reward, cum_reward, battle_reward + order_index = BEGINNING_ORDER_ACTIONS.index(action_type) + if order_index == 39 and 39 not in self.target_building_order: # ignore spinecrawler + return bo_reward, cum_reward, battle_reward + if len(self.behavior_building_order) < len(self.target_building_order): + # only consider bo_reward if behaviour size < target size + self.behavior_building_order.append(order_index) + if ACTIONS[action_type]['target_location']: + self.behavior_bo_location.append(location.item()) + else: + self.behavior_bo_location.append(0) + if self.use_bo_reward: + if self.clip_bo: + tz = self.target_building_order[:len(self.behavior_building_order)] + tz_lo = self.target_bo_location[:len(self.behavior_building_order)] + else: + tz = self.target_building_order + tz_lo = self.target_bo_location + new_bo_dist = -levenshtein_distance( #TODO(nyz): merge levenshtein_distance of DI-star and DI-engine to the same + torch.as_tensor(self.behavior_building_order, dtype=torch.int), + torch.as_tensor(tz, dtype=torch.int), + torch.as_tensor(self.behavior_bo_location, dtype=torch.int), + torch.as_tensor(tz_lo, dtype=torch.int), + partial(l2_distance, spatial_x=DEFAULT_SPATIAL_SIZE[1]) + ) / self.bo_norm + bo_reward = new_bo_dist - self.old_bo_reward + self.old_bo_reward = new_bo_dist + + if self.cum_type == 'observation': + cum_flag = True + for u in next_obs['raw_obs'].observation.raw_data.units: + if u.alliance == 1 and u.unit_type in [59, 18, 86]: # ignore first base + if u.pos.x == self.born_location[0] and u.pos.y == self.born_location[1]: + continue + if u.alliance == 1 and u.build_progress == 1 and UNIT_TO_CUM[u.unit_type] != -1: + self.behavior_cumulative_stat[UNIT_TO_CUM[u.unit_type]] = 1 + for u in next_obs['raw_obs'].observation.raw_data.player.upgrade_ids: + if UPGRADE_TO_CUM[u] != -1: + self.behavior_cumulative_stat[UPGRADE_TO_CUM[u]] = 1 + from distar.pysc2.lib.upgrades import Upgrades + for up in Upgrades: + if up.value == u: + name = up.name + break + elif self.cum_type == 'action': + action_name = ACTIONS[action_type]['name'] + action_info = self._output['action_info'] + cum_flag = False + if action_name == 'Cancel_quick' or action_name == 'Cancel_Last_quick': + unit_index = action_info['selected_units'][0].item() + order_len = self._observation['entity_info']['order_length'][unit_index] + if order_len == 0: + action_index = 0 + elif order_len == 1: + action_index = UNIT_ABILITY_TO_ACTION[self._observation['entity_info']['order_id_0'] + [unit_index].item()] + elif order_len > 1: + order_str = 'order_id_{}'.format(order_len - 1) + action_index = QUEUE_ACTIONS[self._observation['entity_info'][order_str][unit_index].item() - 1] + if action_index in CUMULATIVE_STAT_ACTIONS: + cum_flag = True + cum_index = CUMULATIVE_STAT_ACTIONS.index(action_index) + self.behavior_cumulative_stat[cum_index] = max(0, self.behavior_cumulative_stat[cum_index] - 1) + + if action_type in CUMULATIVE_STAT_ACTIONS: + cum_flag = True + cum_index = CUMULATIVE_STAT_ACTIONS.index(action_type) + self.behavior_cumulative_stat[cum_index] += 1 + else: + raise NotImplementedError + + if self.use_cum_reward and cum_flag and (self.cum_type == 'observation' or next_obs['action_result'][0] == 1): + new_cum_reward = -hamming_distance( + torch.as_tensor(self.behavior_cumulative_stat, dtype=torch.bool), + torch.as_tensor(self.target_cumulative_stat, dtype=torch.bool) + ) / self.cum_norm + cum_reward = (new_cum_reward - self.old_cum_reward) * self._get_time_factor(self.game_step) + self.old_cum_reward = new_cum_reward + self.total_bo_reward += bo_reward + self.total_cum_reward += cum_reward + return bo_reward, cum_reward, battle_reward + def _get_train_sample(self): pass + @staticmethod + def _get_time_factor(game_step): + if game_step < 1 * 10000: + return 1.0 + elif game_step < 2 * 10000: + return 0.5 + elif game_step < 3 * 10000: + return 0.25 + else: + return 0 + _init_eval = _init_collect _forward_eval = _forward_collect From b2cfa91ba1eeefd86f97484faeeea0709596609a Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Mon, 11 Jul 2022 19:00:13 +0800 Subject: [PATCH 192/229] add processss_transition --- dizoo/distar/policy/distar_policy.py | 121 +++++++++++++++++++++++++-- 1 file changed, 114 insertions(+), 7 deletions(-) diff --git a/dizoo/distar/policy/distar_policy.py b/dizoo/distar/policy/distar_policy.py index 5b7d10925a..d1144df0f2 100644 --- a/dizoo/distar/policy/distar_policy.py +++ b/dizoo/distar/policy/distar_policy.py @@ -6,6 +6,7 @@ from torch.optim import Adam import random from functools import partial +from copy import deepcopy from ding.model import model_wrap from ding.policy import Policy @@ -24,7 +25,8 @@ class DIStarPolicy(Policy): config = dict( type='distar', on_policy=False, - cuda=True, + learn_cuda=True, + collect_cuda=False, learning_rate=1e-5, model=dict(), # learn @@ -154,14 +156,14 @@ def _init_learn(self): eps=1e-5, ) # utils - self.timer = EasyTimer(cuda=self._cfg.cuda) + self.timer = EasyTimer(cuda=self._cfg.learn_cuda) def _forward_learn(self, inputs: Dict): # =========== # pre-process # =========== inputs = collate_fn_learn(inputs) - if self._cfg.cuda: + if self._cfg.learn_cuda: inputs = to_device(inputs, self._device) self._learn_model.train() @@ -374,6 +376,7 @@ def _load_state_dict_collect(self, _state_dict: Dict) -> None: def _init_collect(self): self._collect_model = model_wrap(self._model, 'base') + self.only_cum_action_kl = False self.z_path = self._cfg.z_path self.z_idx = None self.bo_norm = 20 #TODO(nyz): set from cfg @@ -383,9 +386,12 @@ def _init_collect(self): self.clip_bo = self._cfg.clip_bo self.cum_type = 'action' # observation or action self.realtime = self._cfg.realtime + self.teacher_model = Model(self._cfg.model + ).eval() # TODO(zms): load teacher_model's state_dict when init policy. def _reset_collect(self, data: Dict): self.exceed_loop_flag = False + self.map_name = data['map_name'] hidden_size = 384 # TODO(nyz) set from cfg num_layers = 3 self.hidden_state = [(torch.zeros(hidden_size), torch.zeros(hidden_size)) for _ in range(num_layers)] @@ -398,12 +404,16 @@ def _reset_collect(self, data: Dict): self.enemy_unit_type_bool = torch.zeros(NUM_UNIT_TYPES, dtype=torch.uint8) self._observation = None # TODO(zms): need to move to input and output of function self._output = None # TODO(zms): need to move to input and output of function + self.model_last_iter = 0 self.game_step = 0 # step * 10 is game duration time self.behavior_building_order = [] # idx in BEGINNING_ORDER_ACTIONS self.behavior_bo_location = [] self.bo_zergling_count = 0 self.behavior_cumulative_stat = [0] * NUM_CUMULATIVE_STAT_ACTIONS + self.hidden_state_backup = [(torch.zeros(hidden_size), torch.zeros(hidden_size)) for _ in range(num_layers)] + self.teacher_hidden_state = [(torch.zeros(hidden_size), torch.zeros(hidden_size)) for _ in range(num_layers)] + race, requested_race, map_size, target_building_order, target_cumulative_stat, bo_location, target_z_loop, z_type, _born_location = parse_new_game( data, self.z_path, self.z_idx ) @@ -451,14 +461,14 @@ def _reset_collect(self, data: Dict): def _forward_collect(self, data): obs, game_info = self._data_preprocess_collect(data) obs = default_collate([obs]) - if self._cfg.cuda: + if self._cfg.collect_cuda: obs = to_device(obs, self._device) self._collect_model.eval() with torch.no_grad(): policy_output = self._collect_model.compute_logp_action(**obs) - if self._cfg.cuda: + if self._cfg.collect_cuda: policy_output = to_device(policy_output, self._device) policy_output = default_decollate(policy_output)[0] policy_output = self._data_postprocess_collect(policy_output, game_info) @@ -567,10 +577,81 @@ def _data_postprocess_collect(self, data, game_info): return data def _process_transition(self, next_obs, reward, done): - action_result = False if next_obs is None else ('Success' in next_obs['action_result']) - behavior_z = self.get_behavior_z() bo_reward, cum_reward, battle_reward = self.update_fake_reward(next_obs) + agent_obs = self._observation + teacher_obs = { + 'spatial_info': agent_obs['spatial_info'], + 'entity_info': agent_obs['entity_info'], + 'scalar_info': agent_obs['scalar_info'], + 'entity_num': agent_obs['entity_num'], + 'hidden_state': self.teacher_hidden_state, + 'selected_units_num': self._output['selected_units_num'], + 'action_info': self._output['action_info'] + } + if self._cfg.collect_cuda: + teacher_obs = to_device(teacher_obs, 'cuda:0') + + teacher_model_input = default_collate([teacher_obs]) + teacher_output = self.teacher_model.compute_teacher_logit(**teacher_model_input) + teacher_output = self.decollate_output(teacher_output) + self.teacher_hidden_state = teacher_output['hidden_state'] + + # gather step data + action_info = deepcopy(self._output['action_info']) + mask = dict() + mask['actions_mask'] = deepcopy( + { + k: val + for k, val in ACTIONS[action_info['action_type'].item()].items() + if k not in ['name', 'goal', 'func_id', 'general_ability_id', 'game_id'] + } + ) + if self.only_cum_action_kl: + mask['cum_action_mask'] = torch.tensor(0.0, dtype=torch.float) + else: + mask['cum_action_mask'] = torch.tensor(1.0, dtype=torch.float) + if self.use_bo_reward: + mask['build_order_mask'] = torch.tensor(1.0, dtype=torch.float) + else: + mask['build_order_mask'] = torch.tensor(0.0, dtype=torch.float) + if self.use_cum_reward: + mask['built_unit_mask'] = torch.tensor(1.0, dtype=torch.float) + mask['cum_action_mask'] = torch.tensor(1.0, dtype=torch.float) + else: + mask['built_unit_mask'] = torch.tensor(0.0, dtype=torch.float) + selected_units_num = self._output['selected_units_num'] + for k, v in mask['actions_mask'].items(): + mask['actions_mask'][k] = torch.tensor(v, dtype=torch.long) + step_data = { + 'map_name': self.map_name, + 'spatial_info': agent_obs['spatial_info'], + 'model_last_iter': torch.tensor(self.model_last_iter, dtype=torch.float), + # 'spatial_info_ref': spatial_info_ref, + 'entity_info': agent_obs['entity_info'], + 'scalar_info': agent_obs['scalar_info'], + 'entity_num': agent_obs['entity_num'], + 'selected_units_num': selected_units_num, + 'hidden_state': self.hidden_state_backup, + 'action_info': action_info, + 'behaviour_logp': self._output['action_logp'], + 'teacher_logit': teacher_output['logit'], + # 'successive_logit': deepcopy(teacher_output['logit']), + 'reward': { + 'winloss': torch.tensor(reward, dtype=torch.float), + 'build_order': bo_reward, + 'built_unit': cum_reward, + # 'upgrade': torch.randint(-1, 1, size=(), dtype=torch.float), + 'battle': battle_reward, + }, + 'step': torch.tensor(self.game_step, dtype=torch.float), + 'mask': mask, + } + ##TODO: add value feature + if self._cfg.use_value_feature: + step_data['value_feature'] = agent_obs['value_feature'] + step_data['value_feature'].update(behavior_z) + self.hidden_state_backup = self.hidden_state def get_behavior_z(self): bo = self.behavior_building_order + [0] * (BEGINNING_ORDER_LENGTH - len(self.behavior_building_order)) @@ -685,6 +766,32 @@ def _update_fake_reward(self, action_type, location, next_obs): self.total_cum_reward += cum_reward return bo_reward, cum_reward, battle_reward + def decollate_output(self, output, k=None, batch_idx=None): + if isinstance(output, torch.Tensor): + if batch_idx is None: + return output.squeeze(dim=0) + else: + return output[batch_idx].clone().cpu() + elif k == 'hidden_state': + if batch_idx is None: + return [(output[l][0].squeeze(dim=0), output[l][1].squeeze(dim=0)) for l in range(len(output))] + else: + return [ + (output[l][0][batch_idx].clone().cpu(), output[l][1][batch_idx].clone().cpu()) + for l in range(len(output)) + ] + elif isinstance(output, dict): + data = {k: self.decollate_output(v, k, batch_idx) for k, v in output.items()} + if batch_idx is not None and k is None: + entity_num = data['entity_num'] + selected_units_num = data['selected_units_num'] + data['logit']['selected_units'] = data['logit']['selected_units'][:selected_units_num, :entity_num + 1] + data['logit']['target_unit'] = data['logit']['target_unit'][:entity_num] + if 'action_info' in data.keys(): + data['action_info']['selected_units'] = data['action_info']['selected_units'][:selected_units_num] + data['action_logp']['selected_units'] = data['action_logp']['selected_units'][:selected_units_num] + return data + def _get_train_sample(self): pass From 25a8a54004e716e6f56469ebc041c733b0b81fde Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 12 Jul 2022 12:05:59 +0800 Subject: [PATCH 193/229] load state_dict of teacher model and other debugs --- ding/torch_utils/__init__.py | 2 +- ding/torch_utils/metric.py | 29 ++++++++++++++++++++++++++++ dizoo/distar/policy/distar_policy.py | 27 +++++++++++++++----------- 3 files changed, 46 insertions(+), 12 deletions(-) diff --git a/ding/torch_utils/__init__.py b/ding/torch_utils/__init__.py index 69f0891dd0..9a0dfc5734 100644 --- a/ding/torch_utils/__init__.py +++ b/ding/torch_utils/__init__.py @@ -2,7 +2,7 @@ from .data_helper import to_device, to_tensor, to_ndarray, to_list, to_dtype, same_shape, tensor_to_list, \ build_log_buffer, CudaFetcher, get_tensor_data, unsqueeze, get_null_data, detach_grad, flatten from .distribution import CategoricalPd, CategoricalPdPytorch -from .metric import l2_distance, levenshtein_distance, hamming_distance +from .metric import l2_distance, levenshtein_distance, hamming_distance, hamming_distance2 from .network import * from .loss import * from .optimizer_helper import Adam, RMSprop, calculate_grad_norm, calculate_grad_norm_without_bias_two_norm diff --git a/ding/torch_utils/metric.py b/ding/torch_utils/metric.py index 827bee4634..da213aadb7 100644 --- a/ding/torch_utils/metric.py +++ b/ding/torch_utils/metric.py @@ -85,3 +85,32 @@ def hamming_distance(pred: torch.LongTensor, target: torch.LongTensor, weight=1. assert (pred.device == target.device) assert (pred.shape == target.shape) return pred.ne(target).sum(dim=1).float().mul_(weight) + + +def hamming_distance2(behaviour, target): + r''' + Overview: + Hamming Distance + + Arguments: + Note: + behaviour, target are also boolean vector(0 or 1) + + - behaviour (:obj:`torch.LongTensor`): behaviour input, shape[B, N], while B is the batch size + - target (:obj:`torch.LongTensor`): target input, shape[B, N], while B is the batch size + + Returns: + - distance(:obj:`torch.LongTensor`): distance(scalar), the shape[1] + + Shapes: + - behaviour & target (:obj:`torch.LongTensor`): shape :math:`(B, N)`, \ + while B is the batch size and N is the dimension + + Test: + torch_utils/network/tests/test_metric.py + ''' + assert (isinstance(behaviour, torch.Tensor) and isinstance(target, torch.Tensor)) + assert behaviour.dtype == target.dtype, f'bahaviour_dtype: {behaviour.dtype}, target_dtype: {target.dtype}' + assert (behaviour.device == target.device) + assert (behaviour.shape == target.shape) + return behaviour.ne(target).sum(dim=-1).float() diff --git a/dizoo/distar/policy/distar_policy.py b/dizoo/distar/policy/distar_policy.py index d1144df0f2..9470ab360e 100644 --- a/dizoo/distar/policy/distar_policy.py +++ b/dizoo/distar/policy/distar_policy.py @@ -7,10 +7,11 @@ import random from functools import partial from copy import deepcopy +import os.path as osp from ding.model import model_wrap from ding.policy import Policy -from ding.torch_utils import to_device, levenshtein_distance, l2_distance, hamming_distance +from ding.torch_utils import to_device, levenshtein_distance, l2_distance, hamming_distance2 as hamming_distance from ding.rl_utils import td_lambda_data, td_lambda_error, vtrace_data_with_rho, vtrace_error_with_rho, \ upgo_data, upgo_error from ding.utils import EasyTimer @@ -25,8 +26,7 @@ class DIStarPolicy(Policy): config = dict( type='distar', on_policy=False, - learn_cuda=True, - collect_cuda=False, + cuda=True, learning_rate=1e-5, model=dict(), # learn @@ -118,6 +118,7 @@ class DIStarPolicy(Policy): clip_bo=False, # clip the length of teacher's building order to agent's length z_path='7map_filter_spine.json', realtime=False, #TODO(zms): set from env, need to use only one cfg define policy and env + teacher_model_path='sl_model.pth', ) def _create_model( @@ -156,14 +157,14 @@ def _init_learn(self): eps=1e-5, ) # utils - self.timer = EasyTimer(cuda=self._cfg.learn_cuda) + self.timer = EasyTimer(cuda=self._cfg.cuda) def _forward_learn(self, inputs: Dict): # =========== # pre-process # =========== inputs = collate_fn_learn(inputs) - if self._cfg.learn_cuda: + if self._cfg.cuda: inputs = to_device(inputs, self._device) self._learn_model.train() @@ -386,8 +387,12 @@ def _init_collect(self): self.clip_bo = self._cfg.clip_bo self.cum_type = 'action' # observation or action self.realtime = self._cfg.realtime - self.teacher_model = Model(self._cfg.model - ).eval() # TODO(zms): load teacher_model's state_dict when init policy. + self.teacher_model = Model(self._cfg.model).eval() + teacher_model_path = osp.join(osp.dirname(__file__), self._cfg.teacher_model_path) + t_state_dict = torch.load(teacher_model_path, map_location='cpu') + teacher_state_dict = {k: v for k, v in t_state_dict['model'].items() if 'value_networks' not in k} + self.teacher_model.load_state_dict(teacher_state_dict) + # TODO(zms): load teacher_model's state_dict when init policy. def _reset_collect(self, data: Dict): self.exceed_loop_flag = False @@ -430,7 +435,7 @@ def _reset_collect(self, data: Dict): if random.random() > self.fake_reward_prob: self.use_bo_reward = False - self.bo_norm = len(self.target_building_order) + self.bo_norm = len(target_building_order) self.cum_norm = len(target_cumulative_stat) self.race = race # home_race @@ -461,14 +466,14 @@ def _reset_collect(self, data: Dict): def _forward_collect(self, data): obs, game_info = self._data_preprocess_collect(data) obs = default_collate([obs]) - if self._cfg.collect_cuda: + if self._cfg.cuda: obs = to_device(obs, self._device) self._collect_model.eval() with torch.no_grad(): policy_output = self._collect_model.compute_logp_action(**obs) - if self._cfg.collect_cuda: + if self._cfg.cuda: policy_output = to_device(policy_output, self._device) policy_output = default_decollate(policy_output)[0] policy_output = self._data_postprocess_collect(policy_output, game_info) @@ -589,7 +594,7 @@ def _process_transition(self, next_obs, reward, done): 'selected_units_num': self._output['selected_units_num'], 'action_info': self._output['action_info'] } - if self._cfg.collect_cuda: + if self._cfg.cuda: teacher_obs = to_device(teacher_obs, 'cuda:0') teacher_model_input = default_collate([teacher_obs]) From 6c75891176a57b5b22397343ad3e6a6e6455fbb7 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 12 Jul 2022 12:13:31 +0800 Subject: [PATCH 194/229] not delete last episode when before append, the first step of newest episode has error --- ding/framework/middleware/functional/collector.py | 14 ++++++++++---- 1 file changed, 10 insertions(+), 4 deletions(-) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index b3c4dd1d50..7f8eff0ac0 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -126,8 +126,14 @@ def _cut_trajectory_from_episode(self, episode: list) -> List[List]: return return_episode # list of trajectories - def clear_newest_episode(self, env_id: int) -> None: - # Use it when env.step raise some error + def clear_newest_episode(self, env_id: int, before_append=False) -> None: + # Call this method when env.step raise some error + + # If call this method before append, and the last episode of this env is done, + # it means that the env had some error at the first step of the newest episode, + # and we should not delete the last episode because it is a normal episode. + if before_append == True and len(self._done_episode[env_id]) > 0 and self._done_episode[env_id][-1] == True: + return 0 if len(self._transitions[env_id]) > 0: newest_episode = self._transitions[env_id].pop() len_newest_episode = len(newest_episode) @@ -354,9 +360,9 @@ def _battle_rolloutor(ctx: "BattleContext"): # 1st case when env step has bug and need to reset. - # TODO(zms): if it is first step of the episode, do not delete the last episode in the TransitionList + # TODO(zms): if it is first step of the episode, do not delete the last episode in the TransitionList for policy_id, policy in enumerate(ctx.current_policies): - transitions_list[policy_id].clear_newest_episode(env_id) + transitions_list[policy_id].clear_newest_episode(env_id, before_append=True) policy.reset(env.ready_obs[0][policy_id]) continue From 1f2bc17e5cc30db0122a43bfcc505d23db004bc2 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 12 Jul 2022 16:20:31 +0800 Subject: [PATCH 195/229] insert process transition into rolloutor, fix bug; move self._observation, self._output to make code more clear --- .../middleware/functional/collector.py | 23 ++++--- dizoo/distar/policy/distar_policy.py | 63 +++++++++++-------- ...test_league_actor_with_pretrained_model.py | 4 +- 3 files changed, 56 insertions(+), 34 deletions(-) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 7f8eff0ac0..0e632ed55e 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -3,6 +3,7 @@ from functools import reduce import treetensor.torch as ttorch from ding.envs import BaseEnvManager +from ding.envs.env.base_env import BaseEnvTimestep from ding.policy import Policy import torch from ding.utils import dicts_to_lists @@ -368,14 +369,22 @@ def _battle_rolloutor(ctx: "BattleContext"): episode_long_enough = True for policy_id, policy in enumerate(ctx.current_policies): - transition = policy.process_transition(timestep) - transition = EasyDict(transition) - transition.collect_train_iter = ttorch.as_tensor( - [model_info_dict[ctx.player_id_list[policy_id]].update_train_iter] - ) + if timestep.obs.get(policy_id): + policy_timestep = BaseEnvTimestep( + obs=timestep.obs.get(policy_id), + reward=timestep.reward[policy_id], + done=timestep.done, + info=timestep.info[policy_id] + ) + transition = policy.process_transition(obs=None, model_output=None, timestep=policy_timestep) + transition = EasyDict(transition) + transition.collect_train_iter = ttorch.as_tensor( + [model_info_dict[ctx.player_id_list[policy_id]].update_train_iter] + ) + + # 2nd case when the number of transitions in one of all the episodes is shorter than unroll_len + episode_long_enough = episode_long_enough and transitions_list[policy_id].append(env_id, transition) - # 2nd case when the number of transitions in one of all the episodes is shorter than unroll_len - episode_long_enough = episode_long_enough and transitions_list[policy_id].append(env_id, transition) if timestep.done: policy.reset(env.ready_obs[0][policy_id]) ctx.episode_info[policy_id].append(timestep.info[policy_id]) diff --git a/dizoo/distar/policy/distar_policy.py b/dizoo/distar/policy/distar_policy.py index 9470ab360e..3c396825e5 100644 --- a/dizoo/distar/policy/distar_policy.py +++ b/dizoo/distar/policy/distar_policy.py @@ -8,6 +8,7 @@ from functools import partial from copy import deepcopy import os.path as osp +from typing import Any from ding.model import model_wrap from ding.policy import Policy @@ -16,6 +17,7 @@ upgo_data, upgo_error from ding.utils import EasyTimer from ding.utils.data import default_collate, default_decollate +from ding.envs.env.base_env import BaseEnvTimestep from dizoo.distar.model import Model from dizoo.distar.envs import NUM_UNIT_TYPES, ACTIONS, NUM_CUMULATIVE_STAT_ACTIONS, DEFAULT_SPATIAL_SIZE, BEGINNING_ORDER_LENGTH, BEGINNING_ORDER_ACTIONS, UNIT_TO_CUM, UPGRADE_TO_CUM, UNIT_ABILITY_TO_ACTION, QUEUE_ACTIONS, CUMULATIVE_STAT_ACTIONS,\ Stat, parse_new_game, transform_obs, compute_battle_score @@ -110,7 +112,7 @@ class DIStarPolicy(Policy): ), grad_clip=dict(threshold=1.0, ), # collect - use_value_feature=True, # TODO(zms): whether to use value feature, this must be False when play against bot + use_value_feature=False, # TODO(zms): whether to use value feature, this must be False when play against bot zero_z_exceed_loop=True, # set Z to 0 if game passes the game loop in Z fake_reward_prob=0.0, # probablity which set Z to 0 zero_z_value=1, # value used for 0Z @@ -387,9 +389,11 @@ def _init_collect(self): self.clip_bo = self._cfg.clip_bo self.cum_type = 'action' # observation or action self.realtime = self._cfg.realtime - self.teacher_model = Model(self._cfg.model).eval() + self.teacher_model = model_wrap(Model(self._cfg.model), 'base') + if self._cfg.cuda: + self.teacher_model = self.teacher_model.cuda() teacher_model_path = osp.join(osp.dirname(__file__), self._cfg.teacher_model_path) - t_state_dict = torch.load(teacher_model_path, map_location='cpu') + t_state_dict = torch.load(teacher_model_path) teacher_state_dict = {k: v for k, v in t_state_dict['model'].items() if 'value_networks' not in k} self.teacher_model.load_state_dict(teacher_state_dict) # TODO(zms): load teacher_model's state_dict when init policy. @@ -407,8 +411,10 @@ def _reset_collect(self, data: Dict): self.last_targeted_unit_tag = None self.last_location = None # [x, y] self.enemy_unit_type_bool = torch.zeros(NUM_UNIT_TYPES, dtype=torch.uint8) - self._observation = None # TODO(zms): need to move to input and output of function - self._output = None # TODO(zms): need to move to input and output of function + # TODO(zms): need to move obs and policy_output inside rolloutor, but for each step, + # it is possible that only one policy in the two has observation and output, so for now just leave it here. + self.obs = None + self.policy_output = None self.model_last_iter = 0 self.game_step = 0 # step * 10 is game duration time self.behavior_building_order = [] # idx in BEGINNING_ORDER_ACTIONS @@ -465,6 +471,7 @@ def _reset_collect(self, data: Dict): def _forward_collect(self, data): obs, game_info = self._data_preprocess_collect(data) + self.obs = obs obs = default_collate([obs]) if self._cfg.cuda: obs = to_device(obs, self._device) @@ -476,8 +483,8 @@ def _forward_collect(self, data): if self._cfg.cuda: policy_output = to_device(policy_output, self._device) policy_output = default_decollate(policy_output)[0] - policy_output = self._data_postprocess_collect(policy_output, game_info) - return policy_output + self.policy_output = self._data_postprocess_collect(policy_output, game_info) + return self.policy_output def _data_preprocess_collect(self, data): if self._cfg.use_value_feature: @@ -529,8 +536,6 @@ def _data_preprocess_collect(self, data): else: obs['scalar_info']['cumulative_stat'] = self.target_cumulative_stat * 0 + self._cfg.zero_z_value - self._observation = obs - # update stat self.stat.update(self.last_action_type, data['action_result'][0], obs, self.game_step) return obs, game_info @@ -541,7 +546,6 @@ def _data_postprocess_collect(self, data, game_info): self.last_action_type = data['action_info']['action_type'] self.last_delay = data['action_info']['delay'] self.last_location = data['action_info']['target_location'] - self._output = data action_type = self.last_action_type.item() action_attr = ACTIONS[action_type] @@ -581,29 +585,39 @@ def _data_postprocess_collect(self, data, game_info): return data - def _process_transition(self, next_obs, reward, done): + def _process_transition(self, obs: Any, model_output: dict, timestep: BaseEnvTimestep): + next_obs = timestep.obs + reward = timestep.reward + done = timestep.done behavior_z = self.get_behavior_z() bo_reward, cum_reward, battle_reward = self.update_fake_reward(next_obs) - agent_obs = self._observation + agent_obs = self.obs teacher_obs = { 'spatial_info': agent_obs['spatial_info'], 'entity_info': agent_obs['entity_info'], 'scalar_info': agent_obs['scalar_info'], 'entity_num': agent_obs['entity_num'], 'hidden_state': self.teacher_hidden_state, - 'selected_units_num': self._output['selected_units_num'], - 'action_info': self._output['action_info'] + 'selected_units_num': self.policy_output['selected_units_num'], + 'action_info': self.policy_output['action_info'] } - if self._cfg.cuda: - teacher_obs = to_device(teacher_obs, 'cuda:0') teacher_model_input = default_collate([teacher_obs]) - teacher_output = self.teacher_model.compute_teacher_logit(**teacher_model_input) + + if self._cfg.cuda: + teacher_model_input = to_device(teacher_model_input, self._device) + + self.teacher_model.eval() + with torch.no_grad(): + teacher_output = self.teacher_model.compute_teacher_logit(**teacher_model_input) + + if self._cfg.cuda: + teacher_output = to_device(teacher_output, self._device) teacher_output = self.decollate_output(teacher_output) self.teacher_hidden_state = teacher_output['hidden_state'] # gather step data - action_info = deepcopy(self._output['action_info']) + action_info = deepcopy(self.policy_output['action_info']) mask = dict() mask['actions_mask'] = deepcopy( { @@ -625,7 +639,7 @@ def _process_transition(self, next_obs, reward, done): mask['cum_action_mask'] = torch.tensor(1.0, dtype=torch.float) else: mask['built_unit_mask'] = torch.tensor(0.0, dtype=torch.float) - selected_units_num = self._output['selected_units_num'] + selected_units_num = self.policy_output['selected_units_num'] for k, v in mask['actions_mask'].items(): mask['actions_mask'][k] = torch.tensor(v, dtype=torch.long) step_data = { @@ -639,7 +653,7 @@ def _process_transition(self, next_obs, reward, done): 'selected_units_num': selected_units_num, 'hidden_state': self.hidden_state_backup, 'action_info': action_info, - 'behaviour_logp': self._output['action_logp'], + 'behaviour_logp': self.policy_output['action_logp'], 'teacher_logit': teacher_output['logit'], # 'successive_logit': deepcopy(teacher_output['logit']), 'reward': { @@ -735,19 +749,18 @@ def _update_fake_reward(self, action_type, location, next_obs): break elif self.cum_type == 'action': action_name = ACTIONS[action_type]['name'] - action_info = self._output['action_info'] + action_info = self.policy_output['action_info'] cum_flag = False if action_name == 'Cancel_quick' or action_name == 'Cancel_Last_quick': unit_index = action_info['selected_units'][0].item() - order_len = self._observation['entity_info']['order_length'][unit_index] + order_len = self.obs['entity_info']['order_length'][unit_index] if order_len == 0: action_index = 0 elif order_len == 1: - action_index = UNIT_ABILITY_TO_ACTION[self._observation['entity_info']['order_id_0'] - [unit_index].item()] + action_index = UNIT_ABILITY_TO_ACTION[self.obs['entity_info']['order_id_0'][unit_index].item()] elif order_len > 1: order_str = 'order_id_{}'.format(order_len - 1) - action_index = QUEUE_ACTIONS[self._observation['entity_info'][order_str][unit_index].item() - 1] + action_index = QUEUE_ACTIONS[self.obs['entity_info'][order_str][unit_index].item() - 1] if action_index in CUMULATIVE_STAT_ACTIONS: cum_flag = True cum_index = CUMULATIVE_STAT_ACTIONS.index(action_index) diff --git a/dizoo/distar/tests/test_league_actor_with_pretrained_model.py b/dizoo/distar/tests/test_league_actor_with_pretrained_model.py index dfac92d6ac..f84d8bf0ad 100644 --- a/dizoo/distar/tests/test_league_actor_with_pretrained_model.py +++ b/dizoo/distar/tests/test_league_actor_with_pretrained_model.py @@ -20,10 +20,10 @@ from ding.framework.middleware.functional import ActorData from ding.framework.middleware.tests import DIStarMockPolicy from ding.framework.middleware.league_learner import LearnerModel -from ding.framework.middleware.functional.collector import battle_inferencer_for_distar +from ding.framework.middleware.functional.collector import battle_inferencer_for_distar, battle_rolloutor_for_distar -def battle_rolloutor_for_distar(cfg, env, transitions_list, model_info_dict): +def battle_rolloutor_for_distar2(cfg, env, transitions_list, model_info_dict): def _battle_rolloutor(ctx: "BattleContext"): timesteps = env.step(ctx.actions) From 8dfa961d19c0abdc97793ee6abea8fbb632a742f Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 12 Jul 2022 16:59:26 +0800 Subject: [PATCH 196/229] fix bug of calling hamming_distance --- ding/torch_utils/__init__.py | 2 +- ding/torch_utils/metric.py | 29 ---------------------------- dizoo/distar/policy/distar_policy.py | 13 +++++++------ 3 files changed, 8 insertions(+), 36 deletions(-) diff --git a/ding/torch_utils/__init__.py b/ding/torch_utils/__init__.py index 9a0dfc5734..69f0891dd0 100644 --- a/ding/torch_utils/__init__.py +++ b/ding/torch_utils/__init__.py @@ -2,7 +2,7 @@ from .data_helper import to_device, to_tensor, to_ndarray, to_list, to_dtype, same_shape, tensor_to_list, \ build_log_buffer, CudaFetcher, get_tensor_data, unsqueeze, get_null_data, detach_grad, flatten from .distribution import CategoricalPd, CategoricalPdPytorch -from .metric import l2_distance, levenshtein_distance, hamming_distance, hamming_distance2 +from .metric import l2_distance, levenshtein_distance, hamming_distance from .network import * from .loss import * from .optimizer_helper import Adam, RMSprop, calculate_grad_norm, calculate_grad_norm_without_bias_two_norm diff --git a/ding/torch_utils/metric.py b/ding/torch_utils/metric.py index da213aadb7..827bee4634 100644 --- a/ding/torch_utils/metric.py +++ b/ding/torch_utils/metric.py @@ -85,32 +85,3 @@ def hamming_distance(pred: torch.LongTensor, target: torch.LongTensor, weight=1. assert (pred.device == target.device) assert (pred.shape == target.shape) return pred.ne(target).sum(dim=1).float().mul_(weight) - - -def hamming_distance2(behaviour, target): - r''' - Overview: - Hamming Distance - - Arguments: - Note: - behaviour, target are also boolean vector(0 or 1) - - - behaviour (:obj:`torch.LongTensor`): behaviour input, shape[B, N], while B is the batch size - - target (:obj:`torch.LongTensor`): target input, shape[B, N], while B is the batch size - - Returns: - - distance(:obj:`torch.LongTensor`): distance(scalar), the shape[1] - - Shapes: - - behaviour & target (:obj:`torch.LongTensor`): shape :math:`(B, N)`, \ - while B is the batch size and N is the dimension - - Test: - torch_utils/network/tests/test_metric.py - ''' - assert (isinstance(behaviour, torch.Tensor) and isinstance(target, torch.Tensor)) - assert behaviour.dtype == target.dtype, f'bahaviour_dtype: {behaviour.dtype}, target_dtype: {target.dtype}' - assert (behaviour.device == target.device) - assert (behaviour.shape == target.shape) - return behaviour.ne(target).sum(dim=-1).float() diff --git a/dizoo/distar/policy/distar_policy.py b/dizoo/distar/policy/distar_policy.py index 3c396825e5..6e20b642f1 100644 --- a/dizoo/distar/policy/distar_policy.py +++ b/dizoo/distar/policy/distar_policy.py @@ -12,7 +12,7 @@ from ding.model import model_wrap from ding.policy import Policy -from ding.torch_utils import to_device, levenshtein_distance, l2_distance, hamming_distance2 as hamming_distance +from ding.torch_utils import to_device, levenshtein_distance, l2_distance, hamming_distance from ding.rl_utils import td_lambda_data, td_lambda_error, vtrace_data_with_rho, vtrace_error_with_rho, \ upgo_data, upgo_error from ding.utils import EasyTimer @@ -464,8 +464,9 @@ def _reset_collect(self, data: Dict): else: self.old_bo_reward = torch.tensor(0.) self.old_cum_reward = -hamming_distance( - torch.as_tensor(self.behavior_cumulative_stat, dtype=torch.float), self.target_cumulative_stat - ) / self.cum_norm + torch.unsqueeze(torch.as_tensor(self.behavior_cumulative_stat, dtype=torch.long), dim=0), + torch.unsqueeze(torch.as_tensor(self.target_cumulative_stat, dtype=torch.long), dim=0) + )[0] / self.cum_norm self.total_bo_reward = torch.zeros(size=(), dtype=torch.float) self.total_cum_reward = torch.zeros(size=(), dtype=torch.float) @@ -775,9 +776,9 @@ def _update_fake_reward(self, action_type, location, next_obs): if self.use_cum_reward and cum_flag and (self.cum_type == 'observation' or next_obs['action_result'][0] == 1): new_cum_reward = -hamming_distance( - torch.as_tensor(self.behavior_cumulative_stat, dtype=torch.bool), - torch.as_tensor(self.target_cumulative_stat, dtype=torch.bool) - ) / self.cum_norm + torch.unsqueeze(torch.as_tensor(self.behavior_cumulative_stat, dtype=torch.long), dim=0), + torch.unsqueeze(torch.as_tensor(self.target_cumulative_stat, dtype=torch.long), dim=0) + )[0] / self.cum_norm cum_reward = (new_cum_reward - self.old_cum_reward) * self._get_time_factor(self.game_step) self.old_cum_reward = new_cum_reward self.total_bo_reward += bo_reward From 4a01f3d8ced2b2f8851920fbadb3403a62f565ca Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 12 Jul 2022 18:26:33 +0800 Subject: [PATCH 197/229] fix bug when calling levenshtein_distance --- dizoo/distar/policy/distar_policy.py | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) diff --git a/dizoo/distar/policy/distar_policy.py b/dizoo/distar/policy/distar_policy.py index 6e20b642f1..d7218a253d 100644 --- a/dizoo/distar/policy/distar_policy.py +++ b/dizoo/distar/policy/distar_policy.py @@ -460,7 +460,7 @@ def _reset_collect(self, data: Dict): if not self.clip_bo: self.old_bo_reward = -levenshtein_distance( torch.as_tensor(self.behavior_building_order, dtype=torch.long), self.target_building_order - ) / self.bo_norm + )[0] / self.bo_norm else: self.old_bo_reward = torch.tensor(0.) self.old_cum_reward = -hamming_distance( @@ -666,12 +666,14 @@ def _process_transition(self, obs: Any, model_output: dict, timestep: BaseEnvTim }, 'step': torch.tensor(self.game_step, dtype=torch.float), 'mask': mask, + 'done': done } ##TODO: add value feature if self._cfg.use_value_feature: step_data['value_feature'] = agent_obs['value_feature'] step_data['value_feature'].update(behavior_z) self.hidden_state_backup = self.hidden_state + return step_data def get_behavior_z(self): bo = self.behavior_building_order + [0] * (BEGINNING_ORDER_LENGTH - len(self.behavior_building_order)) @@ -722,13 +724,13 @@ def _update_fake_reward(self, action_type, location, next_obs): else: tz = self.target_building_order tz_lo = self.target_bo_location - new_bo_dist = -levenshtein_distance( #TODO(nyz): merge levenshtein_distance of DI-star and DI-engine to the same - torch.as_tensor(self.behavior_building_order, dtype=torch.int), - torch.as_tensor(tz, dtype=torch.int), + new_bo_dist = -levenshtein_distance( + torch.as_tensor(self.behavior_building_order, dtype=torch.long), + torch.as_tensor(tz, dtype=torch.long), torch.as_tensor(self.behavior_bo_location, dtype=torch.int), torch.as_tensor(tz_lo, dtype=torch.int), partial(l2_distance, spatial_x=DEFAULT_SPATIAL_SIZE[1]) - ) / self.bo_norm + )[0] / self.bo_norm bo_reward = new_bo_dist - self.old_bo_reward self.old_bo_reward = new_bo_dist From b06d6d8f07fad396d45ad8b91390e77c5125ff05 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Wed, 13 Jul 2022 21:25:58 +0800 Subject: [PATCH 198/229] fix bug of dimension selected_units --- dizoo/distar/policy/distar_policy.py | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/dizoo/distar/policy/distar_policy.py b/dizoo/distar/policy/distar_policy.py index d7218a253d..b9126d91af 100644 --- a/dizoo/distar/policy/distar_policy.py +++ b/dizoo/distar/policy/distar_policy.py @@ -604,6 +604,11 @@ def _process_transition(self, obs: Any, model_output: dict, timestep: BaseEnvTim } teacher_model_input = default_collate([teacher_obs]) + if teacher_model_input['action_info'].get('selected_units') is not None and teacher_model_input['action_info'][ + 'selected_units'].shape == torch.Size([1]): + teacher_model_input['action_info']['selected_units'] = torch.unsqueeze( + teacher_model_input['action_info']['selected_units'], dim=0 + ) if self._cfg.cuda: teacher_model_input = to_device(teacher_model_input, self._device) From 0aedb778543df2375e9fafb89a8b7021d1e332ef Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Thu, 14 Jul 2022 19:36:08 +0800 Subject: [PATCH 199/229] changes to run the whole pipeline from sl_model --- .../framework/middleware/functional/collector.py | 4 ++-- ding/framework/middleware/league_actor.py | 6 ------ .../middleware/tests/test_league_pipeline.py | 2 +- dizoo/distar/policy/distar_policy.py | 16 ++++++++++++++-- 4 files changed, 17 insertions(+), 11 deletions(-) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 0e632ed55e..67166847d2 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -111,7 +111,7 @@ def _cut_trajectory_from_episode(self, episode: list) -> List[List]: for i in range(num_complele_trajectory): trajectory = episode[i * self._unroll_len:(i + 1) * self._unroll_len] # TODO(zms): 测试专用，之后去掉 - trajectory.append(rl_step_data(last=True)) + # trajectory.append(rl_step_data(last=True)) return_episode.append(trajectory) if num_tail_transitions > 0: @@ -122,7 +122,7 @@ def _cut_trajectory_from_episode(self, episode: list) -> List[List]: initial_elements.append(trajectory[0]) trajectory = initial_elements + trajectory # TODO(zms): 测试专用，之后去掉 - trajectory.append(rl_step_data(last=True)) + # trajectory.append(rl_step_data(last=True)) return_episode.append(trajectory) return return_episode # list of trajectories diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 01289bf6d4..1df7e53cce 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -139,12 +139,6 @@ def __call__(self, ctx: "BattleContext"): main_player, ctx.current_policies = self._get_current_policies(job) - #TODO(zms): only for test pretrained model - rl_model = torch.load('./rl_model.pth') - for policy in ctx.current_policies: - policy.load_state_dict(rl_model) - print('load state_dict okay') - ctx.n_episode = self.cfg.policy.collect.n_episode assert ctx.n_episode >= self.env_num, "[Actor {}] Please make sure n_episode >= env_num".format( task.router.node_id diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index be63e30e66..212f5e63b1 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -65,7 +65,7 @@ def policy_fn(cls): @classmethod def collect_policy_fn(cls): - policy = DIStarMockPolicyCollect() + policy = DIStarMockPolicy(DIStarMockPolicy.default_config(), enable_field=['collect']) return policy diff --git a/dizoo/distar/policy/distar_policy.py b/dizoo/distar/policy/distar_policy.py index b9126d91af..e5913d800e 100644 --- a/dizoo/distar/policy/distar_policy.py +++ b/dizoo/distar/policy/distar_policy.py @@ -120,6 +120,7 @@ class DIStarPolicy(Policy): clip_bo=False, # clip the length of teacher's building order to agent's length z_path='7map_filter_spine.json', realtime=False, #TODO(zms): set from env, need to use only one cfg define policy and env + model_path='sl_model.pth', teacher_model_path='sl_model.pth', ) @@ -141,6 +142,11 @@ def _create_model( def _init_learn(self): self._learn_model = model_wrap(self._model, 'base') + # TODO(zms): maybe initialize state_dict inside learner + learn_model_path = osp.join(osp.dirname(__file__), self._cfg.model_path) + learn_state_dict = torch.load(learn_model_path) + self._load_state_dict_learn(learn_state_dict) + self.head_types = ['action_type', 'delay', 'queued', 'target_unit', 'selected_units', 'target_location'] # policy parameters self.gammas = self._cfg.gammas @@ -362,8 +368,9 @@ def _state_dict(self) -> Dict: } def _load_state_dict_learn(self, _state_dict: Dict) -> None: - self._learn_model.load_state_dict(_state_dict['model']) - self.optimizer.load_state_dict(_state_dict['optimizer']) + self._learn_model.load_state_dict(_state_dict['model'], strict=False) + if 'optimizer' in _state_dict: + self.optimizer.load_state_dict(_state_dict['optimizer']) def _load_state_dict_collect(self, _state_dict: Dict) -> None: #TODO(zms): need to load state_dict after collect, which is very dirty and need to rewrite @@ -379,6 +386,11 @@ def _load_state_dict_collect(self, _state_dict: Dict) -> None: def _init_collect(self): self._collect_model = model_wrap(self._model, 'base') + # TODO(zms): maybe initialize state_dict inside actor + collect_model_path = osp.join(osp.dirname(__file__), self._cfg.model_path) + collect_state_dict = torch.load(collect_model_path) + self._load_state_dict_collect(collect_state_dict) + self.only_cum_action_kl = False self.z_path = self._cfg.z_path self.z_idx = None From 1dfda4235fe6af922452f2bad974c0443fc511fd Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 19 Jul 2022 13:45:07 +0800 Subject: [PATCH 200/229] changes to run the winrate test --- dizoo/distar/policy/distar_policy.py | 2 +- .../test_league_actor_with_pretrained_model.py | 16 +++++++++------- 2 files changed, 10 insertions(+), 8 deletions(-) diff --git a/dizoo/distar/policy/distar_policy.py b/dizoo/distar/policy/distar_policy.py index e5913d800e..9142c3cf59 100644 --- a/dizoo/distar/policy/distar_policy.py +++ b/dizoo/distar/policy/distar_policy.py @@ -28,7 +28,7 @@ class DIStarPolicy(Policy): config = dict( type='distar', on_policy=False, - cuda=True, + cuda=False, learning_rate=1e-5, model=dict(), # learn diff --git a/dizoo/distar/tests/test_league_actor_with_pretrained_model.py b/dizoo/distar/tests/test_league_actor_with_pretrained_model.py index f84d8bf0ad..cd1775bb08 100644 --- a/dizoo/distar/tests/test_league_actor_with_pretrained_model.py +++ b/dizoo/distar/tests/test_league_actor_with_pretrained_model.py @@ -6,6 +6,7 @@ from dizoo.distar.config import distar_cfg from dizoo.distar.envs.distar_env import DIStarEnv +from dizoo.distar.policy.distar_policy import DIStarPolicy from ding.envs import EnvSupervisor from ding.league.player import PlayerMeta @@ -18,7 +19,6 @@ from ding.framework.supervisor import ChildType from ding.framework.middleware import StepLeagueActor from ding.framework.middleware.functional import ActorData -from ding.framework.middleware.tests import DIStarMockPolicy from ding.framework.middleware.league_learner import LearnerModel from ding.framework.middleware.functional.collector import battle_inferencer_for_distar, battle_rolloutor_for_distar @@ -51,8 +51,8 @@ def _battle_rolloutor(ctx: "BattleContext"): env_cfg = dict( actor=dict(job_type='train', ), env=dict( - map_name='KingsCove', - player_ids=['agent1', 'bot10'], + map_name='random', + player_ids=['agent1', 'bot7'], races=['zerg', 'zerg'], map_size_resolutions=[True, True], # if True, ignore minimap_resolutions minimap_resolutions=[[160, 152], [160, 152]], @@ -93,13 +93,13 @@ def get_env_supervisor(cls): @classmethod def learn_policy_fn(cls): - policy = DIStarMockPolicy(DIStarMockPolicy.default_config(), enable_field=['learn']) + policy = DIStarPolicy(DIStarPolicy.default_config(), enable_field=['learn']) return policy @classmethod def collect_policy_fn(cls): # policy = DIStarMockPolicyCollect() - policy = DIStarMockPolicy(DIStarMockPolicy.default_config(), enable_field=['collect']) + policy = DIStarPolicy(DIStarPolicy.default_config(), enable_field=['collect']) return policy @@ -112,7 +112,6 @@ def collect_policy_fn(cls): @pytest.mark.unittest def test_league_actor(): with task.start(async_mode=True, ctx=BattleContext()): - policy = PrepareTest.learn_policy_fn().learn_mode def test_actor(): job = Job( @@ -148,6 +147,9 @@ def on_actor_job(job_: Job): total_games, win_games, draw_games, loss_games ) ) + if total_games >= 100: + task.finish = True + exit(0) def on_actor_data(actor_data): print('got actor_data') @@ -175,4 +177,4 @@ def _test_actor(ctx): if __name__ == '__main__': - test_league_actor() + test_league_actor() \ No newline at end of file From 3d194367b55b995b807bc35f27db45f4f52c7f0c Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Tue, 19 Jul 2022 13:59:05 +0800 Subject: [PATCH 201/229] changes to make whole pipeline running bug freely --- .../middleware/functional/collector.py | 14 ++- .../middleware/tests/mock_for_test.py | 2 +- .../middleware/tests/test_league_pipeline.py | 5 +- .../tests/test_league_pipeline_fake_data.py | 108 ++++++++++++++++++ dizoo/distar/policy/distar_policy.py | 13 ++- 5 files changed, 132 insertions(+), 10 deletions(-) create mode 100644 ding/framework/middleware/tests/test_league_pipeline_fake_data.py diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 67166847d2..334f244ccc 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -15,6 +15,7 @@ from collections import deque from ding.framework.middleware.functional.actor_data import ActorEnvTrajectories from dizoo.distar.envs.fake_data import rl_step_data +from copy import deepcopy from ditk import logging @@ -111,7 +112,10 @@ def _cut_trajectory_from_episode(self, episode: list) -> List[List]: for i in range(num_complele_trajectory): trajectory = episode[i * self._unroll_len:(i + 1) * self._unroll_len] # TODO(zms): 测试专用，之后去掉 - # trajectory.append(rl_step_data(last=True)) + last_step = deepcopy(trajectory[-1]) + for k in ['mask', 'action_info', 'teacher_logit', 'behaviour_logp', 'selected_units_num', 'reward', 'step']: + last_step.pop(k) + trajectory.append(last_step) return_episode.append(trajectory) if num_tail_transitions > 0: @@ -122,7 +126,10 @@ def _cut_trajectory_from_episode(self, episode: list) -> List[List]: initial_elements.append(trajectory[0]) trajectory = initial_elements + trajectory # TODO(zms): 测试专用，之后去掉 - # trajectory.append(rl_step_data(last=True)) + last_step = deepcopy(trajectory[-1]) + for k in ['mask', 'action_info', 'teacher_logit', 'behaviour_logp', 'selected_units_num', 'reward', 'step']: + last_step.pop(k) + trajectory.append(last_step) return_episode.append(trajectory) return return_episode # list of trajectories @@ -385,7 +392,8 @@ def _battle_rolloutor(ctx: "BattleContext"): # 2nd case when the number of transitions in one of all the episodes is shorter than unroll_len episode_long_enough = episode_long_enough and transitions_list[policy_id].append(env_id, transition) - if timestep.done: + if timestep.done: + for policy_id, policy in enumerate(ctx.current_policies): policy.reset(env.ready_obs[0][policy_id]) ctx.episode_info[policy_id].append(timestep.info[policy_id]) diff --git a/ding/framework/middleware/tests/mock_for_test.py b/ding/framework/middleware/tests/mock_for_test.py index 7b75dda960..b4b7769ef2 100644 --- a/ding/framework/middleware/tests/mock_for_test.py +++ b/ding/framework/middleware/tests/mock_for_test.py @@ -226,7 +226,7 @@ def forward(self, policy_obs: Dict[int, Any]) -> Dict[int, Any]: return return_data - def process_transition(self, timestep) -> dict: + def process_transition(self, obs, model_output, timestep) -> dict: step_data = rl_step_data() step_data['done'] = timestep.done return step_data diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index 212f5e63b1..2a8da3d101 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -14,6 +14,7 @@ from dizoo.distar.config import distar_cfg from dizoo.distar.envs.distar_env import DIStarEnv from unittest.mock import patch +from dizoo.distar.policy.distar_policy import DIStarPolicy env_cfg = dict( actor=dict(job_type='train', ), @@ -60,12 +61,12 @@ def get_env_supervisor(cls): @classmethod def policy_fn(cls): - policy = DIStarMockPolicy(DIStarMockPolicy.default_config(), enable_field=['learn']) + policy = DIStarPolicy(DIStarPolicy.default_config(), enable_field=['learn']) return policy @classmethod def collect_policy_fn(cls): - policy = DIStarMockPolicy(DIStarMockPolicy.default_config(), enable_field=['collect']) + policy = DIStarPolicy(DIStarPolicy.default_config(), enable_field=['collect']) return policy diff --git a/ding/framework/middleware/tests/test_league_pipeline_fake_data.py b/ding/framework/middleware/tests/test_league_pipeline_fake_data.py new file mode 100644 index 0000000000..2684a9f2fe --- /dev/null +++ b/ding/framework/middleware/tests/test_league_pipeline_fake_data.py @@ -0,0 +1,108 @@ +import logging +import pytest +from easydict import EasyDict +from copy import deepcopy +from ding.data import DequeBuffer +from ding.envs import BaseEnvManager, EnvSupervisor +from ding.framework.supervisor import ChildType +from ding.framework.context import BattleContext +from ding.framework.middleware import StepLeagueActor, LeagueCoordinator, LeagueLearnerCommunicator, data_pusher, OffPolicyLearner +from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, DIStarMockPolicyCollect +from ding.framework.middleware.functional.collector import battle_inferencer_for_distar, battle_rolloutor_for_distar +from ding.framework.task import task, Parallel +from ding.league.v2 import BaseLeague +from dizoo.distar.config import distar_cfg +from dizoo.distar.envs.distar_env import DIStarEnv +from unittest.mock import patch +from dizoo.distar.policy.distar_policy import DIStarPolicy + +env_cfg = dict( + actor=dict(job_type='train', ), + env=dict( + map_name='KingsCove', + player_ids=['agent1', 'agent2'], + races=['zerg', 'zerg'], + map_size_resolutions=[True, True], # if True, ignore minimap_resolutions + minimap_resolutions=[[160, 152], [160, 152]], + realtime=False, + replay_dir='.', + random_seed='none', + game_steps_per_episode=100000, + update_bot_obs=False, + save_replay_episodes=1, + update_both_obs=False, + version='4.10.0', + ), +) +env_cfg = EasyDict(env_cfg) +cfg = deepcopy(distar_cfg) + + +class PrepareTest(): + + @classmethod + def get_env_fn(cls): + return DIStarEnv(env_cfg) + + @classmethod + def get_env_supervisor(cls): + for _ in range(10): + try: + env = EnvSupervisor( + type_=ChildType.THREAD, + env_fn=[cls.get_env_fn for _ in range(cfg.env.collector_env_num)], + **cfg.env.manager + ) + env.seed(cfg.seed) + return env + except Exception as e: + print(e) + continue + + @classmethod + def policy_fn(cls): + policy = DIStarPolicy(DIStarPolicy.default_config(), enable_field=['learn']) + return policy + + @classmethod + def collect_policy_fn(cls): + policy = DIStarMockPolicyCollect() + return policy + + +def main(): + logging.getLogger().setLevel(logging.INFO) + league = BaseLeague(cfg.policy.other.league) + N_PLAYERS = len(league.active_players_ids) + print("League: n_players =", N_PLAYERS) + + with task.start(async_mode=True, ctx=BattleContext()),\ + patch("ding.framework.middleware.collector.battle_inferencer", battle_inferencer_for_distar),\ + patch("ding.framework.middleware.collector.battle_rolloutor", battle_rolloutor_for_distar): + print("node id:", task.router.node_id) + if task.router.node_id == 0: + task.use(LeagueCoordinator(cfg, league)) + elif task.router.node_id <= N_PLAYERS: + cfg.policy.collect.unroll_len = 1 + buffer_ = DequeBuffer(size=cfg.policy.other.replay_buffer.replay_buffer_size) + player = league.active_players[task.router.node_id % N_PLAYERS] + + buffer_ = DequeBuffer(size=cfg.policy.other.replay_buffer.replay_buffer_size) + policy = PrepareTest.policy_fn() + + task.use(LeagueLearnerCommunicator(cfg, policy.learn_mode, player)) + task.use(data_pusher(cfg, buffer_)) + task.use(OffPolicyLearner(cfg, policy.learn_mode, buffer_)) + else: + task.use(StepLeagueActor(cfg, PrepareTest.get_env_supervisor, PrepareTest.collect_policy_fn)) + + task.run() + + +@pytest.mark.unittest +def test_league_pipeline(): + Parallel.runner(n_parallel_workers=5, protocol="tcp", topology="mesh")(main) + + +if __name__ == "__main__": + Parallel.runner(n_parallel_workers=5, protocol="tcp", topology="mesh")(main) diff --git a/dizoo/distar/policy/distar_policy.py b/dizoo/distar/policy/distar_policy.py index e5913d800e..09ccd3d6ae 100644 --- a/dizoo/distar/policy/distar_policy.py +++ b/dizoo/distar/policy/distar_policy.py @@ -28,7 +28,7 @@ class DIStarPolicy(Policy): config = dict( type='distar', on_policy=False, - cuda=True, + cuda=False, learning_rate=1e-5, model=dict(), # learn @@ -555,9 +555,12 @@ def _data_preprocess_collect(self, data): def _data_postprocess_collect(self, data, game_info): self.hidden_state = data['hidden_state'] - self.last_queued = data['action_info']['queued'] - self.last_action_type = data['action_info']['action_type'] - self.last_delay = data['action_info']['delay'] + assert data['action_info']['queued'].shape == torch.Size([1]), data['action_info']['queued'] + self.last_queued = data['action_info']['queued'][0] + assert data['action_info']['action_type'].shape == torch.Size([1]), data['action_info']['action_type'] + self.last_action_type = data['action_info']['action_type'][0] + assert data['action_info']['action_type'].shape == torch.Size([1]), data['action_info']['delay'] + self.last_delay = data['action_info']['delay'][0] self.last_location = data['action_info']['target_location'] action_type = self.last_action_type.item() @@ -678,6 +681,8 @@ def _process_transition(self, obs: Any, model_output: dict, timestep: BaseEnvTim 'winloss': torch.tensor(reward, dtype=torch.float), 'build_order': bo_reward, 'built_unit': cum_reward, + 'effect': torch.randint(-1, 1, size=(), dtype=torch.float), + 'upgrade': torch.randint(-1, 1, size=(), dtype=torch.float), # 'upgrade': torch.randint(-1, 1, size=(), dtype=torch.float), 'battle': battle_reward, }, From 206b293d3bb5af372f97c74e9f410471d301f797 Mon Sep 17 00:00:00 2001 From: zhumengshen <744762298@qq.com> Date: Tue, 23 Aug 2022 18:40:22 +0800 Subject: [PATCH 202/229] feature(zms):updates for distar --- ding/framework/middleware/collector.py | 42 +++++--- .../middleware/functional/trainer.py | 6 +- ding/framework/middleware/league_actor.py | 102 +++++++++++++----- .../middleware/league_coordinator.py | 21 +++- ding/framework/middleware/league_learner.py | 12 +-- .../middleware/tests/test_league_learner.py | 4 +- .../middleware/tests/test_league_pipeline.py | 46 +++++--- .../tests/test_league_pipeline_fake_data.py | 10 +- ding/framework/parallel.py | 27 ++++- ding/league/algorithm.py | 2 +- ding/league/starcraft_player.py | 11 ++ ding/league/v2/base_league.py | 3 + ding/torch_utils/network/__init__.py | 2 +- .../torch_utils/network/scatter_connection.py | 26 +++++ dizoo/distar/config/distar_config.py | 19 ++-- dizoo/distar/envs/__init__.py | 2 +- dizoo/distar/envs/fake_data.py | 10 +- .../model/actor_critic_default_config.yaml | 6 +- .../distar/model/obs_encoder/value_encoder.py | 10 +- dizoo/distar/policy/distar_policy.py | 91 ++++++++++++---- dizoo/distar/policy/test_distar_policy.py | 4 +- dizoo/distar/policy/utils.py | 2 +- 22 files changed, 335 insertions(+), 123 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 166bad50be..02ed30d403 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -14,14 +14,14 @@ if TYPE_CHECKING: from ding.framework import OnlineRLContext, BattleContext -WAIT_MODEL_TIME = 600000 +WAIT_MODEL_TIME = float('inf') class BattleStepCollector: def __init__( self, cfg: EasyDict, env: BaseEnvManager, unroll_len: int, model_dict: Dict, model_info_dict: Dict, - all_policies: Dict, agent_num: int + player_policy_collect_dict: Dict, agent_num: int ): self.cfg = cfg self.end_flag = False @@ -33,7 +33,7 @@ def __init__( self.unroll_len = unroll_len self.model_dict = model_dict self.model_info_dict = model_info_dict - self.all_policies = all_policies + self.player_policy_collect_dict = player_policy_collect_dict self.agent_num = agent_num self._battle_inferencer = task.wrap(battle_inferencer(self.cfg, self.env)) @@ -55,19 +55,23 @@ def __del__(self) -> None: self.end_flag = True self.env.close() - def _update_policies(self, player_id_list) -> None: - for player_id in player_id_list: + def _update_policies(self, player_id_set) -> None: + for player_id in player_id_set: # for this player, in the beginning of actor's lifetime, actor didn't recieve any new model, use initial model instead. if self.model_info_dict.get(player_id) is None: self.model_info_dict[player_id] = PlayerModelInfo( get_new_model_time=time.time(), update_new_model_time=None ) + update_player_id_set = set() + for player_id in player_id_set: + if 'historical' not in player_id: + update_player_id_set.add(player_id) while True: time_now = time.time() - time_list = [time_now - self.model_info_dict[player_id].get_new_model_time for player_id in player_id_list] + time_list = [time_now - self.model_info_dict[player_id].get_new_model_time for player_id in update_player_id_set] if any(x >= WAIT_MODEL_TIME for x in time_list): - for index, player_id in enumerate(player_id_list): + for index, player_id in enumerate(update_player_id_set): if time_list[index] >= WAIT_MODEL_TIME: #TODO: log_every_sec can only print the first model that not updated log_every_sec( @@ -80,12 +84,12 @@ def _update_policies(self, player_id_list) -> None: else: break - for player_id in player_id_list: + for player_id in update_player_id_set: if self.model_dict.get(player_id) is None: continue else: learner_model = self.model_dict.get(player_id) - policy = self.all_policies.get(player_id) + policy = self.player_policy_collect_dict.get(player_id) assert policy, "for player{}, policy should have been initialized already" # update policy model policy.load_state_dict(learner_model.state_dict) @@ -113,9 +117,17 @@ def __call__(self, ctx: "BattleContext") -> None: # TODO(zms): only runnable when 1 actor has exactly one env, need to write more general for policy_id, policy in enumerate(ctx.current_policies): policy.reset(self.env.ready_obs[0][policy_id]) - self._update_policies(ctx.player_id_list) - self._battle_inferencer(ctx) - self._battle_rolloutor(ctx) + self._update_policies(set(ctx.player_id_list)) + try: + self._battle_inferencer(ctx) + self._battle_rolloutor(ctx) + except Exception as e: + # TODO(zms): need to handle the exception cleaner + logging.error("[Actor {}] got an exception: {} when collect data".format(task.router.node_id, e)) + self.env.close() + for env_id in range(self.env_num): + for policy_id, policy in enumerate(ctx.current_policies): + self._transitions_list[policy_id].clear_newest_episode(env_id, before_append=True) self.total_envstep_count = ctx.total_envstep_count @@ -135,7 +147,7 @@ def __call__(self, ctx: "BattleContext") -> None: # class BattleEpisodeCollector: # def __init__( -# self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int, model_dict: Dict, all_policies: Dict, +# self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int, model_dict: Dict, player_policy_collect_dict: Dict, # agent_num: int # ): # self.cfg = cfg @@ -147,7 +159,7 @@ def __call__(self, ctx: "BattleContext") -> None: # self.total_envstep_count = 0 # self.n_rollout_samples = n_rollout_samples # self.model_dict = model_dict -# self.all_policies = all_policies +# self.player_policy_collect_dict = player_policy_collect_dict # self.agent_num = agent_num # self._battle_inferencer = task.wrap(battle_inferencer(self.cfg, self.env)) @@ -171,7 +183,7 @@ def __call__(self, ctx: "BattleContext") -> None: # continue # else: # learner_model = self.model_dict.get(player_id) -# policy = self.all_policies.get(player_id) +# policy = self.player_policy_collect_dict.get(player_id) # assert policy, "for player {}, policy should have been initialized already".format(player_id) # # update policy model # policy.load_state_dict(learner_model.state_dict) diff --git a/ding/framework/middleware/functional/trainer.py b/ding/framework/middleware/functional/trainer.py index 5c7f99467b..27be583dd1 100644 --- a/ding/framework/middleware/functional/trainer.py +++ b/ding/framework/middleware/functional/trainer.py @@ -5,9 +5,7 @@ from ding.policy import Policy from ding.framework import task -if TYPE_CHECKING: - from ding.framework import OnlineRLContext, OfflineRLContext - +from ding.framework import OnlineRLContext, OfflineRLContext, BattleContext def trainer(cfg: EasyDict, policy: Policy) -> Callable: """ @@ -18,7 +16,7 @@ def trainer(cfg: EasyDict, policy: Policy) -> Callable: - policy (:obj:`Policy`): The policy to be trained in step-by-step mode. """ - def _train(ctx: Union["OnlineRLContext", "OfflineRLContext"]): + def _train(ctx: Union["OnlineRLContext", "OfflineRLContext", "BattleContext"]): """ Input of ctx: - train_data (:obj:`Dict`): The data used to update the network. It will train only if \ diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 1df7e53cce..02a202c709 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -5,6 +5,7 @@ import time from ditk import logging import torch +import gc from ding.policy import Policy from ding.framework import task, EventEnum @@ -28,14 +29,21 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.policy_fn = policy_fn self.unroll_len = self.cfg.policy.collect.unroll_len self._collectors: Dict[str, BattleStepCollector] = {} - self.all_policies: Dict[str, "Policy.collect_function"] = {} + self.player_policy_dict: Dict[str, "Policy"] = {} + self.player_policy_collect_dict: Dict[str, "Policy.collect_function"] = {} + task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), self._on_league_job) task.on(EventEnum.LEARNER_SEND_MODEL, self._on_learner_model) + self.job_queue = queue.Queue() self.model_dict = {} self.model_dict_lock = Lock() self.model_info_dict = {} + self.traj_num = 0 + self.total_time = 0 + self.total_episode_num = 0 + self.agent_num = 2 self.collect_time = {} @@ -73,23 +81,43 @@ def _get_collector(self, player_id: str): collector = task.wrap( BattleStepCollector( cfg.policy.collect.collector, env, self.unroll_len, self.model_dict, self.model_info_dict, - self.all_policies, self.agent_num + self.player_policy_collect_dict, self.agent_num ) ) self._collectors[player_id] = collector self.collect_time[player_id] = 0 return collector - def _get_policy(self, player: "PlayerMeta") -> "Policy.collect_function": + def _get_policy(self, player: "PlayerMeta", duplicate: bool = False) -> "Policy.collect_function": player_id = player.player_id - if self.all_policies.get(player_id): - return self.all_policies.get(player_id) - policy: "Policy.collect_function" = self.policy_fn().collect_mode - self.all_policies[player_id] = policy - if "historical" in player.player_id: - policy.load_state_dict(player.checkpoint.load()) - return policy + if self.player_policy_collect_dict.get(player_id): + player_policy_collect_mode = self.player_policy_collect_dict.get(player_id) + if duplicate is False: + return player_policy_collect_mode + else: + player_policy = self.player_policy_dict.get(player_id) + duplicate_policy: "Policy.collect_function" = self.policy_fn() + del duplicate_policy._collect_model + del duplicate_policy.teacher_model + duplicate_policy._collect_model = player_policy._collect_model + duplicate_policy.teacher_model = player_policy.teacher_model + return duplicate_policy.collect_mode + else: + policy: "Policy.collect_function" = self.policy_fn() + self.player_policy_dict[player_id] = policy + + policy_collect_mode = policy.collect_mode + self.player_policy_collect_dict[player_id] = policy_collect_mode + if "historical" in player.player_id: + print( + '[Actor {}] recieved historical player {}, checkpoint.path is {}'.format( + task.router.node_id, player.player_id, player.checkpoint.path + ) + ) + policy_collect_mode.load_state_dict(player.checkpoint.load()) + + return policy_collect_mode def _get_job(self): if self.job_queue.empty(): @@ -106,8 +134,13 @@ def _get_job(self): def _get_current_policies(self, job): current_policies = [] main_player: "PlayerMeta" = None + player_set = set() for player in job.players: - current_policies.append(self._get_policy(player)) + if player.player_id not in player_set: + current_policies.append(self._get_policy(player, duplicate=False)) + player_set.add(player.player_id) + else: + current_policies.append(self._get_policy(player, duplicate=True)) if player.player_id == job.launch_player: main_player = player assert main_player, "[Actor {}] can not find active player.".format(task.router.node_id) @@ -128,6 +161,7 @@ def __call__(self, ctx: "BattleContext"): job = self._get_job() if job is None: return + print('[Actor {}] recieve job {}'.format(task.router.node_id, job)) log_every_sec( logging.INFO, 5, '[Actor {}] job of player {} begins.'.format(task.router.node_id, job.launch_player) ) @@ -160,10 +194,7 @@ def __call__(self, ctx: "BattleContext"): for idx in main_player_idx: if not job.is_eval and len(ctx.trajectories_list[idx]) > 0: trajectories = ctx.trajectories_list[idx] - log_every_sec( - logging.INFO, 5, - '[Actor {}] send {} trajectories.'.format(task.router.node_id, len(trajectories)) - ) + self.traj_num += len(trajectories) meta_data = ActorDataMeta( player_total_env_step=ctx.total_envstep_count, actor_id=task.router.node_id, @@ -171,22 +202,26 @@ def __call__(self, ctx: "BattleContext"): ) actor_data = ActorData(meta=meta_data, train_data=trajectories) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=job.launch_player), actor_data) - log_every_sec(logging.INFO, 5, '[Actor {}] send data\n'.format(task.router.node_id)) ctx.trajectories_list = [] + time_end = time.time() + self.total_time += time_end - time_begin + log_every_sec( + logging.INFO, 5, + '[Actor {}] sent {} trajectories till now, total trajectory send speed is {} traj/s'.format( + task.router.node_id, + self.traj_num, + self.traj_num / self.total_time, + ) + ) + self.collect_time[job.launch_player] += time_end - time_begin total_collect_speed = ctx.total_envstep_count / self.collect_time[job.launch_player] if self.collect_time[ job.launch_player] != 0 else 0 envstep_passed = ctx.total_envstep_count - old_envstep real_time_speed = envstep_passed / (time_end - time_begin) - log_every_sec( - logging.INFO, 5, - '[Actor {}] total_env_step: {}, current job env_step: {}, total_collect_speed: {} env_step/s, real-time collect speed: {} env_step/s' - .format( - task.router.node_id, ctx.total_envstep_count, ctx.env_step, total_collect_speed, real_time_speed - ) - ) + gc.collect() if ctx.job_finish is True: job.result = [] @@ -197,6 +232,17 @@ def __call__(self, ctx: "BattleContext"): ctx.episode_info = [[] for _ in range(self.agent_num)] logging.info('[Actor {}] job finish, send job\n'.format(task.router.node_id)) break + self.total_episode_num += ctx.env_episode + logging.info( + '[Actor {}] finish {} episodes till now, speed is {} episode/s'.format( + task.router.node_id, self.total_episode_num, self.total_episode_num / self.total_time + ) + ) + logging.info( + '[Actor {}] sent {} trajectories till now, the episode trajectory speed is {} traj/episode'.format( + task.router.node_id, self.traj_num, self.traj_num / self.total_episode_num + ) + ) # class LeagueActor: @@ -208,7 +254,7 @@ def __call__(self, ctx: "BattleContext"): # self.policy_fn = policy_fn # self.n_rollout_samples = self.cfg.policy.collect.n_rollout_samples # self._collectors: Dict[str, BattleEpisodeCollector] = {} -# self.all_policies: Dict[str, "Policy.collect_function"] = {} +# self.player_policy_collect_dict: Dict[str, "Policy.collect_function"] = {} # task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), self._on_league_job) # task.on(EventEnum.LEARNER_SEND_MODEL, self._on_learner_model) # self.job_queue = queue.Queue() @@ -239,7 +285,7 @@ def __call__(self, ctx: "BattleContext"): # env = self.env_fn() # collector = task.wrap( # BattleEpisodeCollector( -# cfg.policy.collect.collector, env, self.n_rollout_samples, self.model_dict, self.all_policies, +# cfg.policy.collect.collector, env, self.n_rollout_samples, self.model_dict, self.player_policy_collect_dict, # self.agent_num # ) # ) @@ -249,10 +295,10 @@ def __call__(self, ctx: "BattleContext"): # def _get_policy(self, player: "PlayerMeta") -> "Policy.collect_function": # player_id = player.player_id -# if self.all_policies.get(player_id): -# return self.all_policies.get(player_id) +# if self.player_policy_collect_dict.get(player_id): +# return self.player_policy_collect_dict.get(player_id) # policy: "Policy.collect_function" = self.policy_fn().collect_mode -# self.all_policies[player_id] = policy +# self.player_policy_collect_dict[player_id] = policy # if "historical" in player.player_id: # policy.load_state_dict(player.checkpoint.load()) diff --git a/ding/framework/middleware/league_coordinator.py b/ding/framework/middleware/league_coordinator.py index 9c269f434a..0cd1b7b69c 100644 --- a/ding/framework/middleware/league_coordinator.py +++ b/ding/framework/middleware/league_coordinator.py @@ -1,5 +1,5 @@ from collections import defaultdict -from time import sleep +from time import sleep, time from threading import Lock from dataclasses import dataclass from typing import TYPE_CHECKING @@ -22,8 +22,11 @@ def __init__(self, cfg: "EasyDict", league: "BaseLeague") -> None: self.league = league self._lock = Lock() self._total_send_jobs = 0 + self._total_recv_jobs = 0 self._eval_frequency = 10 self._running_jobs = dict() + self._last_collect_time = None + self._total_collect_time = None task.on(EventEnum.ACTOR_GREETING, self._on_actor_greeting) task.on(EventEnum.LEARNER_SEND_META, self._on_learner_meta) @@ -31,6 +34,10 @@ def __init__(self, cfg: "EasyDict", league: "BaseLeague") -> None: def _on_actor_greeting(self, actor_id): logging.info("[Coordinator {}] recieve actor {} greeting".format(task.router.node_id, actor_id)) + if self._last_collect_time is None: + self._last_collect_time = time() + if self._total_collect_time is None: + self._total_collect_time = 0 with self._lock: player_num = len(self.league.active_players_ids) player_id = self.league.active_players_ids[self._total_send_jobs % player_num] @@ -52,8 +59,16 @@ def _on_learner_meta(self, player_meta: "PlayerMeta"): self.league.create_historical_player(player_meta) def _on_actor_job(self, job: "Job"): + self._total_recv_jobs += 1 + old_time = self._last_collect_time + self._last_collect_time = time() + self._total_collect_time += self._last_collect_time - old_time logging.info( - "[Coordinator {}] recieve actor finished job, player {}".format(task.router.node_id, job.launch_player) + "[Coordinator {}] recieve actor finished job, player {}, recieve {} jobs in total, collect job speed is {} s/job" + .format( + task.router.node_id, job.launch_player, self._total_recv_jobs, + self._total_collect_time / self._total_recv_jobs + ) ) self.league.update_payoff(job) @@ -63,5 +78,5 @@ def __del__(self): def __call__(self, ctx: "Context") -> None: sleep(1) log_every_sec( - logging.INFO, 30, "[Coordinator {}] running jobs {}".format(task.router.node_id, self._running_jobs) + logging.INFO, 600, "[Coordinator {}] running jobs {}".format(task.router.node_id, self._running_jobs) ) diff --git a/ding/framework/middleware/league_learner.py b/ding/framework/middleware/league_learner.py index 413ee62980..409e68647d 100644 --- a/ding/framework/middleware/league_learner.py +++ b/ding/framework/middleware/league_learner.py @@ -16,7 +16,7 @@ if TYPE_CHECKING: from ding.policy import Policy - from ding.framework import Context + from ding.framework import Context, BattleContext from ding.framework.middleware.league_actor import ActorData from ding.league import ActivePlayer @@ -32,7 +32,7 @@ class LeagueLearnerCommunicator: def __init__(self, cfg: dict, policy: "Policy", player: "ActivePlayer") -> None: self.cfg = cfg - self._cache = deque(maxlen=50) + self._cache = deque(maxlen=20) self.player = player self.player_id = player.player_id self.policy = policy @@ -54,13 +54,13 @@ def _push_data(self, data: "ActorData"): # else: # self._cache.append(data.train_data) - def __call__(self, ctx: "Context"): - log_every_sec(logging.INFO, 5, "[Learner {}] pour data into the ctx".format(task.router.node_id)) + def __call__(self, ctx: "BattleContext"): + # log_every_sec(logging.INFO, 5, "[Learner {}] pour data into the ctx".format(task.router.node_id)) ctx.trajectories = list(self._cache) self._cache.clear() - sleep(0.1) + sleep(0.0001) yield - log_every_sec(logging.INFO, 5, "[Learner {}] ctx.train_iter {}".format(task.router.node_id, ctx.train_iter)) + log_every_sec(logging.INFO, 20, "[Learner {}] ctx.train_iter {}".format(task.router.node_id, ctx.train_iter)) self.player.total_agent_step = ctx.train_iter if self.player.is_trained_enough(): logging.info('{1} [Learner {0}] trained enough! {1} \n\n'.format(task.router.node_id, "-" * 40)) diff --git a/ding/framework/middleware/tests/test_league_learner.py b/ding/framework/middleware/tests/test_league_learner.py index 1d79847dac..0410201715 100644 --- a/ding/framework/middleware/tests/test_league_learner.py +++ b/ding/framework/middleware/tests/test_league_learner.py @@ -17,7 +17,7 @@ from ding.league.v2 import BaseLeague from ding.utils import log_every_sec from dizoo.distar.config import distar_cfg -from dizoo.distar.envs import fake_rl_data_batch_with_last +from dizoo.distar.envs import fake_rl_traj_with_last from dizoo.distar.envs.distar_env import DIStarEnv from distar.ctools.utils import read_config @@ -66,7 +66,7 @@ def _actor_mocker(ctx): log_every_sec(logging.INFO, 5, "Actor: actor player: {}".format(player.player_id)) for _ in range(24): meta = ActorDataMeta(player_total_env_step=0, actor_id=0, send_wall_time=time.time()) - data = fake_rl_data_batch_with_last() + data = fake_rl_traj_with_last() actor_data = ActorData(meta=meta, train_data=[ActorEnvTrajectories(env_id=0, trajectories=[data])]) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=player.player_id), actor_data) sleep(9) diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py index 2a8da3d101..63ce241237 100644 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ b/ding/framework/middleware/tests/test_league_pipeline.py @@ -15,6 +15,7 @@ from dizoo.distar.envs.distar_env import DIStarEnv from unittest.mock import patch from dizoo.distar.policy.distar_policy import DIStarPolicy +from ding.data.buffer.middleware import use_time_check env_cfg = dict( actor=dict(job_type='train', ), @@ -70,32 +71,49 @@ def collect_policy_fn(cls): return policy +def coordinator(): + coordinator_league = BaseLeague(cfg.policy.other.league) + task.use(LeagueCoordinator(cfg, coordinator_league)) + + +def learner(): + league = BaseLeague(cfg.policy.other.league) + N_PLAYERS = len(league.active_players_ids) + + cfg.policy.collect.unroll_len = 1 + player = league.active_players[task.router.node_id % N_PLAYERS] + del league + + buffer_ = DequeBuffer(size=cfg.policy.other.replay_buffer.replay_buffer_size) + buffer_.use(use_time_check(buffer_, max_use=cfg.policy.other.replay_buffer.max_use)) + policy = PrepareTest.policy_fn() + + task.use(LeagueLearnerCommunicator(cfg, policy.learn_mode, player)) + task.use(data_pusher(cfg, buffer_)) + task.use(OffPolicyLearner(cfg, policy.learn_mode, buffer_)) + + +def actor(): + task.use(StepLeagueActor(cfg, PrepareTest.get_env_supervisor, PrepareTest.collect_policy_fn)) + + def main(): logging.getLogger().setLevel(logging.INFO) league = BaseLeague(cfg.policy.other.league) N_PLAYERS = len(league.active_players_ids) + del league print("League: n_players =", N_PLAYERS) - with task.start(async_mode=True, ctx=BattleContext()),\ + with task.start(async_mode=False, ctx=BattleContext()),\ patch("ding.framework.middleware.collector.battle_inferencer", battle_inferencer_for_distar),\ patch("ding.framework.middleware.collector.battle_rolloutor", battle_rolloutor_for_distar): print("node id:", task.router.node_id) if task.router.node_id == 0: - task.use(LeagueCoordinator(cfg, league)) + coordinator() elif task.router.node_id <= N_PLAYERS: - cfg.policy.collect.unroll_len = 1 - buffer_ = DequeBuffer(size=cfg.policy.other.replay_buffer.replay_buffer_size) - player = league.active_players[task.router.node_id % N_PLAYERS] - - buffer_ = DequeBuffer(size=cfg.policy.other.replay_buffer.replay_buffer_size) - policy = PrepareTest.policy_fn() - - task.use(LeagueLearnerCommunicator(cfg, policy.learn_mode, player)) - task.use(data_pusher(cfg, buffer_)) - task.use(OffPolicyLearner(cfg, policy.learn_mode, buffer_)) + learner() else: - task.use(StepLeagueActor(cfg, PrepareTest.get_env_supervisor, PrepareTest.collect_policy_fn)) - + actor() task.run() diff --git a/ding/framework/middleware/tests/test_league_pipeline_fake_data.py b/ding/framework/middleware/tests/test_league_pipeline_fake_data.py index 2684a9f2fe..a9eabe4d02 100644 --- a/ding/framework/middleware/tests/test_league_pipeline_fake_data.py +++ b/ding/framework/middleware/tests/test_league_pipeline_fake_data.py @@ -15,6 +15,7 @@ from dizoo.distar.envs.distar_env import DIStarEnv from unittest.mock import patch from dizoo.distar.policy.distar_policy import DIStarPolicy +from ding.data.buffer.middleware import use_time_check env_cfg = dict( actor=dict(job_type='train', ), @@ -81,13 +82,14 @@ def main(): patch("ding.framework.middleware.collector.battle_rolloutor", battle_rolloutor_for_distar): print("node id:", task.router.node_id) if task.router.node_id == 0: - task.use(LeagueCoordinator(cfg, league)) + coordinator_league = BaseLeague(cfg.policy.other.league) + task.use(LeagueCoordinator(cfg, coordinator_league)) elif task.router.node_id <= N_PLAYERS: cfg.policy.collect.unroll_len = 1 - buffer_ = DequeBuffer(size=cfg.policy.other.replay_buffer.replay_buffer_size) player = league.active_players[task.router.node_id % N_PLAYERS] buffer_ = DequeBuffer(size=cfg.policy.other.replay_buffer.replay_buffer_size) + buffer_.use(use_time_check(buffer_, max_use=cfg.policy.other.replay_buffer.max_use)) policy = PrepareTest.policy_fn() task.use(LeagueLearnerCommunicator(cfg, policy.learn_mode, player)) @@ -101,8 +103,8 @@ def main(): @pytest.mark.unittest def test_league_pipeline(): - Parallel.runner(n_parallel_workers=5, protocol="tcp", topology="mesh")(main) + Parallel.runner(n_parallel_workers=7, protocol="tcp", topology="mesh")(main) if __name__ == "__main__": - Parallel.runner(n_parallel_workers=5, protocol="tcp", topology="mesh")(main) + Parallel.runner(n_parallel_workers=7, protocol="tcp", topology="mesh")(main) diff --git a/ding/framework/parallel.py b/ding/framework/parallel.py index 469ae7e77f..6c5d2e80b6 100644 --- a/ding/framework/parallel.py +++ b/ding/framework/parallel.py @@ -5,6 +5,7 @@ import traceback from mpire.pool import WorkerPool import pickle +import io from ditk import logging import tempfile import socket @@ -15,11 +16,35 @@ from ding.utils.design_helper import SingletonMetaclass from ding.framework.message_queue import * from ding.utils.registry_factory import MQ_REGISTRY +import torch # Avoid ipc address conflict, random should always use random seed random = random.Random() +class CpuUnpickler(pickle.Unpickler): + + def find_class(self, module, name): + if module == 'torch.storage' and name == '_load_from_bytes': + return lambda b: torch.load(io.BytesIO(b), map_location='cpu') + else: + return super().find_class(module, name) + + +def cpu_loads(x): + bs = io.BytesIO(x) + unpickler = CpuUnpickler(bs) + return unpickler.load() + + +def my_pickle_loads(msg): + if not torch.cuda.is_available(): + payload = cpu_loads(msg) + else: + payload = pickle.loads(msg) + return payload + + class Parallel(metaclass=SingletonMetaclass): def __init__(self) -> None: @@ -337,7 +362,7 @@ def _handle_message(self, topic: str, msg: bytes) -> None: logging.debug("Event {} was not listened in parallel {}".format(event, self.node_id)) return try: - payload = pickle.loads(msg) + payload = my_pickle_loads(msg) except Exception as e: logging.error("Error when unpacking message on node {}, msg: {}".format(self.node_id, e)) return diff --git a/ding/league/algorithm.py b/ding/league/algorithm.py index 09cb23b352..b7de39970a 100644 --- a/ding/league/algorithm.py +++ b/ding/league/algorithm.py @@ -22,7 +22,7 @@ def pfsp(win_rates: np.ndarray, weighting: str) -> np.ndarray: raise KeyError("invalid weighting arg: {} in pfsp".format(weighting)) assert isinstance(win_rates, np.ndarray) - assert win_rates.shape[0] >= 1, win_rates.shape + assert win_rates.shape[0] >= 1, "win rate is {}".format(win_rates) # all zero win rates case, return uniform selection prob if win_rates.sum() < 1e-8: return np.full_like(win_rates, 1.0 / len(win_rates)) diff --git a/ding/league/starcraft_player.py b/ding/league/starcraft_player.py index 81d53e73bd..900fed6149 100644 --- a/ding/league/starcraft_player.py +++ b/ding/league/starcraft_player.py @@ -54,6 +54,17 @@ def _sp_branch(self): p = pfsp(win_rates, weighting='variance') return self._get_opponent(historical, p) + def _sl_branch(self): + """ + Overview: + Select one opponent, whose ckpt is sl_model.pth + """ + historical = self._get_players( + lambda p: isinstance(p, HistoricalPlayer) and p.player_id == 'main_player_default_0_pretrain_historical' + ) + main_opponent = self._get_opponent(historical) + return main_opponent + def _verification_branch(self): """ Overview: diff --git a/ding/league/v2/base_league.py b/ding/league/v2/base_league.py index 260f34d951..f5ca20eaa6 100644 --- a/ding/league/v2/base_league.py +++ b/ding/league/v2/base_league.py @@ -9,6 +9,7 @@ from ding.league.metric import LeagueMetricEnv from ding.framework.storage import Storage from typing import TYPE_CHECKING +from ditk import logging if TYPE_CHECKING: from ding.league import Player, PlayerMeta @@ -195,6 +196,8 @@ def update_payoff(self, job: Job) -> None: "result": job.result } self.payoff.update(job_info) + + logging.info("show the current payoff {}".format(self.payoff._data)) # Update player rating home_id, away_id = job_info['player_id'] home_player, away_player = self.get_player_by_id(home_id), self.get_player_by_id(away_id) diff --git a/ding/torch_utils/network/__init__.py b/ding/torch_utils/network/__init__.py index 23bad434b5..3d5a285f2b 100644 --- a/ding/torch_utils/network/__init__.py +++ b/ding/torch_utils/network/__init__.py @@ -6,7 +6,7 @@ from .rnn import get_lstm, sequence_mask from .soft_argmax import SoftArgmax from .transformer import Transformer -from .scatter_connection import ScatterConnection +from .scatter_connection import ScatterConnection, scatter_connection_v2 from .resnet import resnet18, ResNet from .gumbel_softmax import GumbelSoftmax from .gtrxl import GTrXL, GRUGatingUnit diff --git a/ding/torch_utils/network/scatter_connection.py b/ding/torch_utils/network/scatter_connection.py index 5b2f3b4ee5..58c40204aa 100644 --- a/ding/torch_utils/network/scatter_connection.py +++ b/ding/torch_utils/network/scatter_connection.py @@ -93,3 +93,29 @@ def forward(self, x: torch.Tensor, spatial_size: Tuple[int, int], location: torc output = output.reshape(N, B, H, W) output = output.permute(1, 0, 2, 3).contiguous() return output + + +def scatter_connection_v2(shape, project_embeddings, entity_location, scatter_dim, scatter_type='add'): + B, H, W = shape + device = entity_location.device + entity_num = entity_location.shape[1] + index = entity_location.view(-1, 2).long() + bias = torch.arange(B).unsqueeze(1).repeat(1, entity_num).view(-1).to(device) + bias *= H * W + index[:, 0].clamp_(0, W - 1) + index[:, 1].clamp_(0, H - 1) + index = index[:, 1] * W + index[:, 0] # entity_location: (x, y), spatial_info: (y, x) + index += bias + index = index.repeat(scatter_dim, 1) + # flat scatter map and project embeddings + scatter_map = torch.zeros(scatter_dim, B * H * W, device=device) + project_embeddings = project_embeddings.view(-1, scatter_dim).permute(1, 0) + if scatter_type == 'cover': + scatter_map.scatter_(dim=1, index=index, src=project_embeddings) + elif scatter_type == 'add': + scatter_map.scatter_add_(dim=1, index=index, src=project_embeddings) + else: + raise NotImplementedError + scatter_map = scatter_map.reshape(scatter_dim, B, H, W) + scatter_map = scatter_map.permute(1, 0, 2, 3) + return scatter_map diff --git a/dizoo/distar/config/distar_config.py b/dizoo/distar/config/distar_config.py index 60412fdf07..c209c8dd2c 100644 --- a/dizoo/distar/config/distar_config.py +++ b/dizoo/distar/config/distar_config.py @@ -48,7 +48,7 @@ }, 'multi_gpu': False, 'epoch_per_collect': 10, - 'batch_size': 3, + 'batch_size': 4, 'learning_rate': 1e-05, 'value_weight': 0.5, 'entropy_weight': 0.0, @@ -80,9 +80,7 @@ 'discount_factor': 1.0, 'gae_lambda': 1.0, 'n_episode': 1, - 'n_rollout_samples': 64, - 'n_sample': 64, - 'unroll_len': 4 + 'unroll_len': 16 }, 'eval': { 'evaluator': { @@ -95,7 +93,8 @@ 'other': { 'replay_buffer': { 'type': 'naive', - 'replay_buffer_size': 20, + 'replay_buffer_size': 6, + 'max_use': 2, 'deepcopy': False, 'enable_track_used_data': False, 'periodic_thruput_seconds': 60, @@ -105,13 +104,14 @@ 'player_category': ['default'], 'path_policy': 'league_demo/ckpt', 'active_players': { - 'main_player': 2 + 'main_player': 1 }, 'main_player': { 'one_phase_step': 10, # 20 'branch_probs': { 'pfsp': 0.0, - 'sp': 1.0 + 'sp': 0.0, + 'sl': 1.0 }, 'strong_win_rate': 0.7 }, @@ -132,7 +132,10 @@ 'mutate_prob': 0.5 }, 'use_pretrain': False, - 'use_pretrain_init_historical': False, + 'use_pretrain_init_historical': True, + 'pretrain_checkpoint_path': { + 'default': 'sl_model.pth', + }, 'payoff': { 'type': 'battle', 'decay': 0.99, diff --git a/dizoo/distar/envs/__init__.py b/dizoo/distar/envs/__init__.py index d1eb59ed5a..2db9af3a2a 100644 --- a/dizoo/distar/envs/__init__.py +++ b/dizoo/distar/envs/__init__.py @@ -2,4 +2,4 @@ from .meta import * from .static_data import RACE_DICT, BEGIN_ACTIONS, ACTION_RACE_MASK, SELECTED_UNITS_MASK, ACTIONS, BEGINNING_ORDER_ACTIONS, UNIT_TO_CUM, UPGRADE_TO_CUM, UNIT_ABILITY_TO_ACTION, QUEUE_ACTIONS, CUMULATIVE_STAT_ACTIONS from .stat import Stat -from .fake_data import get_fake_rl_trajectory, get_fake_env_reset_data, get_fake_env_step_data +from .fake_data import get_fake_rl_batch, get_fake_env_reset_data, get_fake_env_step_data diff --git a/dizoo/distar/envs/fake_data.py b/dizoo/distar/envs/fake_data.py index 91fddc463d..436d5fb1ab 100644 --- a/dizoo/distar/envs/fake_data.py +++ b/dizoo/distar/envs/fake_data.py @@ -112,11 +112,13 @@ def get_mask(action): selected_units_logits_mask = torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.long) target_units_logits_mask = torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.long) target_units_logits_mask[action['target_unit']] = 1 + cum_action_mask= torch.tensor(1.0,dtype=torch.float) return { 'actions_mask': mask, 'selected_units_logits_mask': selected_units_logits_mask, 'target_units_logits_mask': target_units_logits_mask, + 'cum_action_mask': cum_action_mask } @@ -156,7 +158,7 @@ def rl_step_data(last=False): 'spatial_info': spatial_info(), 'entity_info': entity_info(), 'scalar_info': scalar_info(), - 'entity_num': torch.randint(5, 100, size=(1, ), dtype=torch.long), + 'entity_num': torch.randint(5, 100, size=(), dtype=torch.long), 'selected_units_num': torch.randint(0, MAX_SELECTED_UNITS_NUM, size=(), dtype=torch.long), 'entity_location': torch.randint(0, H, size=(512, 2), dtype=torch.long), 'hidden_state': [(torch.zeros(size=(384, )), torch.zeros(size=(384, ))) for _ in range(3)], @@ -180,7 +182,7 @@ def rl_step_data(last=False): return data -def fake_rl_data_batch_with_last(unroll_len=4): +def fake_rl_traj_with_last(unroll_len=4): list_step_data = [] for i in range(unroll_len): step_data = rl_step_data() @@ -189,8 +191,8 @@ def fake_rl_data_batch_with_last(unroll_len=4): return list_step_data -def get_fake_rl_trajectory(batch_size=3, unroll_len=4): - data_batch = [fake_rl_data_batch_with_last(unroll_len) for _ in range(batch_size)] +def get_fake_rl_batch(batch_size=3, unroll_len=4): + data_batch = [fake_rl_traj_with_last(unroll_len) for _ in range(batch_size)] return data_batch diff --git a/dizoo/distar/model/actor_critic_default_config.yaml b/dizoo/distar/model/actor_critic_default_config.yaml index 7ddc366f7b..629154d8ea 100644 --- a/dizoo/distar/model/actor_critic_default_config.yaml +++ b/dizoo/distar/model/actor_critic_default_config.yaml @@ -20,7 +20,9 @@ model: enable_baselines: ['winloss', 'build_order', 'built_unit', 'effect', 'upgrade', 'battle'] # ===== Value ===== value: - use_value_feature: False + use_value_feature: True + spatial_x: *SPATIAL_X + spatial_y: *SPATIAL_Y encoder: modules: enemy_unit_counts_bow: @@ -54,6 +56,8 @@ model: head_dim: 8 output_dim: 64 activation: 'relu' + spatial_x: *SPATIAL_X + spatial_y: *SPATIAL_Y cumulative_stat: arc: fc input_dim: *NUM_CUMULATIVE_STAT_ACTIONS diff --git a/dizoo/distar/model/obs_encoder/value_encoder.py b/dizoo/distar/model/obs_encoder/value_encoder.py index fa49ae0362..ef87a03766 100644 --- a/dizoo/distar/model/obs_encoder/value_encoder.py +++ b/dizoo/distar/model/obs_encoder/value_encoder.py @@ -2,7 +2,7 @@ import torch.nn as nn import torch.nn.functional as F from ding.torch_utils import fc_block, build_activation, conv2d_block, ResBlock, same_shape, sequence_mask, \ - Transformer, scatter_connection + Transformer, scatter_connection_v2 from dizoo.distar.envs import BEGIN_ACTIONS from .spatial_encoder import SpatialEncoder from .scalar_encoder import BeginningBuildOrderEncoder @@ -13,7 +13,7 @@ class ValueEncoder(nn.Module): def __init__(self, cfg): super(ValueEncoder, self).__init__() self.whole_cfg = cfg - self.cfg = cfg.model.value.encoder + self.cfg = cfg.encoder self.act = build_activation('relu', inplace=True) self.encode_modules = nn.ModuleDict() for k, item in self.cfg.modules.items(): @@ -25,7 +25,7 @@ def __init__(self, cfg): ) bo_cfg = self.cfg.modules.beginning_order - self.encode_modules['beginning_order'] = BeginningBuildOrderEncoder(self.whole_cfg, bo_cfg) + self.encode_modules['beginning_order'] = BeginningBuildOrderEncoder(bo_cfg) self.scatter_project = fc_block( self.cfg.scatter.scatter_input_dim, self.cfg.scatter.scatter_dim, activation=self.act ) @@ -47,7 +47,7 @@ def __init__(self, cfg): for i in range(self.resblock_num): self.res.append(ResBlock(dim, self.act, norm_type=None)) self.spatial_fc = fc_block( - dim * self.cfg.spatial_y // 8 * self.cfg.spatial_x // 8, + dim * self.whole_cfg.spatial_y // 8 * self.whole_cfg.spatial_x // 8, self.cfg.spatial.spatial_fc_dim, activation=self.act ) @@ -71,7 +71,7 @@ def forward(self, x): project_embedding = project_embedding * unit_mask.unsqueeze(dim=2) entity_location = torch.cat([x['unit_x'].unsqueeze(dim=-1), x['unit_y'].unsqueeze(dim=-1)], dim=-1) b, c, h, w = x['own_units_spatial'].shape - scatter_map = scatter_connection( + scatter_map = scatter_connection_v2( (b, h, w), project_embedding, entity_location, self.scatter_dim, self.scatter_type ) spatial_x = torch.cat([scatter_map, x['own_units_spatial'].float(), x['enemy_units_spatial'].float()], dim=1) diff --git a/dizoo/distar/policy/distar_policy.py b/dizoo/distar/policy/distar_policy.py index 09ccd3d6ae..57809ff5cc 100644 --- a/dizoo/distar/policy/distar_policy.py +++ b/dizoo/distar/policy/distar_policy.py @@ -9,7 +9,12 @@ from copy import deepcopy import os.path as osp from typing import Any +from ditk import logging +import pickle +import os +import time +from ding.framework import task from ding.model import model_wrap from ding.policy import Policy from ding.torch_utils import to_device, levenshtein_distance, l2_distance, hamming_distance @@ -28,7 +33,7 @@ class DIStarPolicy(Policy): config = dict( type='distar', on_policy=False, - cuda=False, + cuda=True, learning_rate=1e-5, model=dict(), # learn @@ -112,7 +117,7 @@ class DIStarPolicy(Policy): ), grad_clip=dict(threshold=1.0, ), # collect - use_value_feature=False, # TODO(zms): whether to use value feature, this must be False when play against bot + use_value_feature=True, # TODO(zms): whether to use value feature, this must be False when play against bot zero_z_exceed_loop=True, # set Z to 0 if game passes the game loop in Z fake_reward_prob=0.0, # probablity which set Z to 0 zero_z_value=1, # value used for 0Z @@ -122,6 +127,7 @@ class DIStarPolicy(Policy): realtime=False, #TODO(zms): set from env, need to use only one cfg define policy and env model_path='sl_model.pth', teacher_model_path='sl_model.pth', + value_pretrain_iters=4000, ) def _create_model( @@ -144,7 +150,9 @@ def _init_learn(self): self._learn_model = model_wrap(self._model, 'base') # TODO(zms): maybe initialize state_dict inside learner learn_model_path = osp.join(osp.dirname(__file__), self._cfg.model_path) - learn_state_dict = torch.load(learn_model_path) + + learn_state_dict = torch.load(learn_model_path, map_location=self._device) + self._load_state_dict_learn(learn_state_dict) self.head_types = ['action_type', 'delay', 'queued', 'target_unit', 'selected_units', 'target_location'] @@ -156,6 +164,8 @@ def _init_learn(self): self.upgo_head_weights = self._cfg.upgo_head_weights self.entropy_head_weights = self._cfg.entropy_head_weights self.kl_head_weights = self._cfg.kl_head_weights + self._only_update_value = False + self._remain_value_pretrain_iters = self._cfg.value_pretrain_iters # optimizer self.optimizer = Adam( @@ -165,15 +175,27 @@ def _init_learn(self): eps=1e-5, ) # utils - self.timer = EasyTimer(cuda=self._cfg.cuda) + self.timer = EasyTimer(cuda=self._cuda) + + def _step_value_pretrain(self): + if self._remain_value_pretrain_iters > 0: + self._only_update_value = True + self._remain_value_pretrain_iters -= 1 + self._learn_model._model._model.only_update_baseline = True + + elif self._remain_value_pretrain_iters == 0: + self._only_update_value = False + self._remain_value_pretrain_iters -= 1 + self._learn_model._model._model.only_update_baseline = False def _forward_learn(self, inputs: Dict): # =========== # pre-process # =========== - inputs = collate_fn_learn(inputs) - if self._cfg.cuda: + self._step_value_pretrain() + if self._cuda: inputs = to_device(inputs, self._device) + inputs = collate_fn_learn(inputs) self._learn_model.train() @@ -336,15 +358,19 @@ def _forward_learn(self, inputs: Dict): # ====== # update # ====== - total_loss = ( - total_vtrace_loss + total_upgo_loss + total_critic_loss + total_entropy_loss + total_kl_loss + - action_type_kl_loss - ) + + if self._only_update_value: + total_loss = total_critic_loss + else: + total_loss = ( + total_vtrace_loss + total_upgo_loss + total_critic_loss + total_entropy_loss + total_kl_loss + + action_type_kl_loss + ) with self.timer: self.optimizer.zero_grad() total_loss.backward() if self._cfg.learn.multi_gpu: - self.sync_gradients() + self.sync_gradients(self._learn_model) gradient = torch.nn.utils.clip_grad_norm_(self._learn_model.parameters(), self._cfg.grad_clip.threshold, 2) self.optimizer.step() @@ -371,10 +397,12 @@ def _load_state_dict_learn(self, _state_dict: Dict) -> None: self._learn_model.load_state_dict(_state_dict['model'], strict=False) if 'optimizer' in _state_dict: self.optimizer.load_state_dict(_state_dict['optimizer']) + del _state_dict def _load_state_dict_collect(self, _state_dict: Dict) -> None: #TODO(zms): need to load state_dict after collect, which is very dirty and need to rewrite - + if not self._cuda: + _state_dict = to_device(_state_dict, self._device) if 'map_name' in _state_dict: # map_names.append(_state_dict['map_name']) self.fake_reward_prob = _state_dict['fake_reward_prob'] @@ -383,13 +411,17 @@ def _load_state_dict_collect(self, _state_dict: Dict) -> None: _state_dict = {k: v for k, v in _state_dict['model'].items() if 'value_networks' not in k} self._collect_model.load_state_dict(_state_dict, strict=False) + del _state_dict def _init_collect(self): self._collect_model = model_wrap(self._model, 'base') # TODO(zms): maybe initialize state_dict inside actor collect_model_path = osp.join(osp.dirname(__file__), self._cfg.model_path) - collect_state_dict = torch.load(collect_model_path) + + collect_state_dict = torch.load(collect_model_path, self._device) + self._load_state_dict_collect(collect_state_dict) + del collect_state_dict self.only_cum_action_kl = False self.z_path = self._cfg.z_path @@ -402,13 +434,17 @@ def _init_collect(self): self.cum_type = 'action' # observation or action self.realtime = self._cfg.realtime self.teacher_model = model_wrap(Model(self._cfg.model), 'base') - if self._cfg.cuda: + if self._cuda: self.teacher_model = self.teacher_model.cuda() teacher_model_path = osp.join(osp.dirname(__file__), self._cfg.teacher_model_path) - t_state_dict = torch.load(teacher_model_path) + print("self._cuda is ", self._cuda) + + t_state_dict = torch.load(teacher_model_path, self._device) + teacher_state_dict = {k: v for k, v in t_state_dict['model'].items() if 'value_networks' not in k} self.teacher_model.load_state_dict(teacher_state_dict) # TODO(zms): load teacher_model's state_dict when init policy. + del t_state_dict def _reset_collect(self, data: Dict): self.exceed_loop_flag = False @@ -486,14 +522,25 @@ def _forward_collect(self, data): obs, game_info = self._data_preprocess_collect(data) self.obs = obs obs = default_collate([obs]) - if self._cfg.cuda: + if self._cuda: obs = to_device(obs, self._device) self._collect_model.eval() - with torch.no_grad(): - policy_output = self._collect_model.compute_logp_action(**obs) - - if self._cfg.cuda: + try: + with torch.no_grad(): + policy_output = self._collect_model.compute_logp_action(**obs) + except Exception as e: + logging.error("[Actor {}] got an exception: {} in the collect model".format(task.router.node_id, e)) + bug_time = str(int(time.time())) + file_name = 'bug_obs_' + bug_time + '.pkl' + with open(os.path.join(os.path.dirname(__file__), file_name), 'wb+') as f: + pickle.dump(self.obs, f) + model_path_name = 'bug_model_' + bug_time + '.pth' + model_path = os.path.join(os.path.dirname(__file__), model_path_name) + torch.save(self._collect_model.state_dict(), model_path) + raise e + + if self._cuda: policy_output = to_device(policy_output, self._device) policy_output = default_decollate(policy_output)[0] self.policy_output = self._data_postprocess_collect(policy_output, game_info) @@ -625,14 +672,14 @@ def _process_transition(self, obs: Any, model_output: dict, timestep: BaseEnvTim teacher_model_input['action_info']['selected_units'], dim=0 ) - if self._cfg.cuda: + if self._cuda: teacher_model_input = to_device(teacher_model_input, self._device) self.teacher_model.eval() with torch.no_grad(): teacher_output = self.teacher_model.compute_teacher_logit(**teacher_model_input) - if self._cfg.cuda: + if self._cuda: teacher_output = to_device(teacher_output, self._device) teacher_output = self.decollate_output(teacher_output) self.teacher_hidden_state = teacher_output['hidden_state'] diff --git a/dizoo/distar/policy/test_distar_policy.py b/dizoo/distar/policy/test_distar_policy.py index 6eedf13f2a..aee5e423c9 100644 --- a/dizoo/distar/policy/test_distar_policy.py +++ b/dizoo/distar/policy/test_distar_policy.py @@ -1,7 +1,7 @@ import pytest from dizoo.distar.policy import DIStarPolicy -from dizoo.distar.envs import get_fake_rl_trajectory, get_fake_env_reset_data, get_fake_env_step_data +from dizoo.distar.envs import get_fake_rl_batch, get_fake_env_reset_data, get_fake_env_step_data import torch from ding.utils import set_pkg_seed @@ -13,7 +13,7 @@ class TestDIStarPolicy: def test_forward_learn(self): policy = DIStarPolicy(DIStarPolicy.default_config(), enable_field=['learn']) policy = policy.learn_mode - data = get_fake_rl_trajectory(batch_size=3) + data = get_fake_rl_batch(batch_size=3) output = policy.forward(data) print(output) diff --git a/dizoo/distar/policy/utils.py b/dizoo/distar/policy/utils.py index 393fd6e2c5..0b72f15304 100644 --- a/dizoo/distar/policy/utils.py +++ b/dizoo/distar/policy/utils.py @@ -137,7 +137,7 @@ def kl_error( kl = kl * mask['actions_mask'][head_type] if head_type == 'action_type': flag = game_steps < action_type_kl_steps - action_type_kl = kl * flag + action_type_kl = kl * flag * mask['cum_action_mask'] action_type_kl_loss = action_type_kl.mean() kl_loss_dict['kl/extra_at'] = action_type_kl_loss.item() kl_loss = kl.mean() From ea11bc12f845e559381bb2c25f4eebeabb83303f Mon Sep 17 00:00:00 2001 From: zhumengshen <744762298@qq.com> Date: Wed, 24 Aug 2022 10:38:24 +0800 Subject: [PATCH 203/229] change comments and delete useless code --- ding/envs/env_manager/env_supervisor.py | 6 +- ding/example/distar.py | 88 ------------------------- ding/framework/__init__.py | 2 +- 3 files changed, 4 insertions(+), 92 deletions(-) delete mode 100644 ding/example/distar.py diff --git a/ding/envs/env_manager/env_supervisor.py b/ding/envs/env_manager/env_supervisor.py index 919e7e6ca2..a12a20ed0d 100644 --- a/ding/envs/env_manager/env_supervisor.py +++ b/ding/envs/env_manager/env_supervisor.py @@ -79,7 +79,9 @@ def __init__( - retry_waiting_time (:obj:`Optional[float]`): Wait time on each retry. - shared_memory (:obj:`bool`): Use shared memory in multiprocessing. - copy_on_get (:obj:`bool`): Use copy on get in multiprocessing. - - return_original_data (:obj:`bool`): Return original observation or processed observation. + - return_original_data (:obj:`bool`): Return original observation, + so that the attribute self._ready_obs is not a tnp.array but only the original observation, + and the property self.ready_obs is a dict in which the key is the env_id. """ if kwargs: logging.warning("Unknown parameters on env supervisor: {}".format(kwargs)) @@ -258,7 +260,6 @@ def ready_obs(self) -> tnp.array: >>> timesteps = env_manager.step(action) """ active_env = [i for i, s in self._env_states.items() if s == EnvState.RUN] - # TODO(zms): change it here or in env? if self._return_original_data: return {i: self._ready_obs[i] for i in active_env} active_env.sort() @@ -415,7 +416,6 @@ def _recv_step_callback( remain_payloads[p.req_id] = p # make the type and content of key as similar as identifier, # in order to call them as attribute (e.g. timestep.xxx), such as ``TimeLimit.truncated`` in cartpole info - # TODO(zms): change it here or in DI-star env? if not self._return_original_data: info = make_key_as_identifier(info) payload.data = tnp.array( diff --git a/ding/example/distar.py b/ding/example/distar.py deleted file mode 100644 index 28a87906eb..0000000000 --- a/ding/example/distar.py +++ /dev/null @@ -1,88 +0,0 @@ -import logging -import pytest -from easydict import EasyDict -from copy import deepcopy -from ding.data import DequeBuffer -from ding.envs import BaseEnvManager -from ding.framework.context import BattleContext -from ding.framework.middleware import StepLeagueActor, LeagueCoordinator, LeagueLearnerCommunicator, data_pusher, OffPolicyLearner -from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, DIStarMockPolicyCollect -from ding.framework.middleware.functional.collector import battle_inferencer_for_distar, battle_rolloutor_for_distar -from ding.framework.task import task, Parallel -from ding.league.v2 import BaseLeague -from dizoo.distar.config import distar_cfg -from dizoo.distar.envs.distar_env import DIStarEnv -from unittest.mock import patch - -env_cfg = dict( - actor=dict(job_type='train', ), - env=dict( - map_name='KingsCove', - player_ids=['agent1', 'agent2'], - races=['zerg', 'zerg'], - map_size_resolutions=[True, True], # if True, ignore minimap_resolutions - minimap_resolutions=[[160, 152], [160, 152]], - realtime=False, - replay_dir='.', - random_seed='none', - game_steps_per_episode=100000, - update_bot_obs=False, - save_replay_episodes=1, - update_both_obs=False, - version='4.10.0', - ), -) - - -def prepare_test(): - global distar_cfg, env_cfg - env_cfg = EasyDict(env_cfg) - cfg = deepcopy(distar_cfg) - - def env_fn(): - # subprocess env manager - env = BaseEnvManager( - env_fn=[lambda: DIStarEnv(env_cfg) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager - ) - env.seed(cfg.seed) - return env - - def policy_fn(): - policy = DIStarMockPolicy(DIStarMockPolicy.default_config(), enable_field=['learn']) - return policy - - def collect_policy_fn(): - policy = DIStarMockPolicyCollect() - return policy - - return cfg, env_fn, policy_fn, collect_policy_fn - - -def main(): - logging.getLogger().setLevel(logging.INFO) - cfg, env_fn, policy_fn, collect_policy_fn = prepare_test() - league = BaseLeague(cfg.policy.other.league) - N_PLAYERS = len(league.active_players_ids) - print("League: n_players =", N_PLAYERS) - - with task.start(async_mode=True, ctx=BattleContext()),\ - patch("ding.framework.middleware.collector.battle_inferencer", battle_inferencer_for_distar),\ - patch("ding.framework.middleware.collector.battle_rolloutor", battle_rolloutor_for_distar): - print("node id:", task.router.node_id) - if task.router.node_id == 0: - task.use(LeagueCoordinator(cfg, league)) - elif task.router.node_id <= N_PLAYERS: - buffer_ = DequeBuffer(size=cfg.policy.other.replay_buffer.replay_buffer_size) - player = league.active_players[task.router.node_id % N_PLAYERS] - policy = policy_fn() - task.use(LeagueLearnerCommunicator(cfg, policy.learn_mode, player)) - task.use(data_pusher(cfg, buffer_)) - task.use(OffPolicyLearner(cfg, policy.learn_mode, buffer_)) - else: - task.use(StepLeagueActor(cfg, env_fn, collect_policy_fn)) - - task.run() - - -if __name__ == "__main__": - Parallel.runner(n_parallel_workers=4, protocol="tcp", topology="mesh")(main) diff --git a/ding/framework/__init__.py b/ding/framework/__init__.py index 82119909b5..11b247d512 100644 --- a/ding/framework/__init__.py +++ b/ding/framework/__init__.py @@ -3,4 +3,4 @@ from .parallel import Parallel from .event_loop import EventLoop from .event_enum import EventEnum -from .supervisor import Supervisor \ No newline at end of file +from .supervisor import Supervisor From 2e60364a3155185632cce1d1349cbcc72ae0f0d6 Mon Sep 17 00:00:00 2001 From: zhumengshen Date: Wed, 24 Aug 2022 06:56:24 +0000 Subject: [PATCH 204/229] move out the distar files into DI-star --- dizoo/distar/__init__.py | 0 dizoo/distar/config/__init__.py | 1 - dizoo/distar/config/distar_config.py | 168 -- dizoo/distar/envs/__init__.py | 5 - dizoo/distar/envs/distar_env.py | 702 ----- dizoo/distar/envs/fake_data.py | 673 ----- dizoo/distar/envs/meta.py | 16 - dizoo/distar/envs/stat.py | 789 ----- dizoo/distar/envs/static_data.py | 2599 ----------------- .../distar/envs/tests/test_distar_config.yaml | 16 - .../distar/envs/tests/test_distar_env_data.py | 64 - .../envs/tests/test_distar_env_time_space.py | 87 - .../tests/test_distar_env_with_manager.py | 91 - dizoo/distar/envs/z_files/12D.json | 1 - dizoo/distar/envs/z_files/1758k.json | 1 - dizoo/distar/envs/z_files/3map.json | 1 - .../envs/z_files/7map_filter_spine.json | 1 - dizoo/distar/envs/z_files/NewRepugnancy.json | 1 - dizoo/distar/envs/z_files/filter.json | 1 - dizoo/distar/envs/z_files/lurker.json | 1 - dizoo/distar/envs/z_files/mutalisk.json | 1 - dizoo/distar/envs/z_files/nydus.json | 1 - dizoo/distar/envs/z_files/perfect_z.json | 1 - dizoo/distar/envs/z_files/stairs.json | 1 - dizoo/distar/envs/z_files/worker_rush.json | 1 - dizoo/distar/model/__init__.py | 1 - .../model/actor_critic_default_config.yaml | 463 --- dizoo/distar/model/encoder.py | 40 - dizoo/distar/model/head/__init__.py | 2 - dizoo/distar/model/head/action_arg_head.py | 415 --- dizoo/distar/model/head/action_type_head.py | 63 - dizoo/distar/model/model.py | 191 -- dizoo/distar/model/obs_encoder/__init__.py | 4 - .../model/obs_encoder/entity_encoder.py | 101 - .../model/obs_encoder/scalar_encoder.py | 143 - .../model/obs_encoder/spatial_encoder.py | 96 - .../distar/model/obs_encoder/value_encoder.py | 84 - dizoo/distar/model/policy.py | 78 - dizoo/distar/model/tests/test_encoder.py | 31 - dizoo/distar/model/tests/test_head.py | 119 - dizoo/distar/model/tests/test_value.py | 23 - dizoo/distar/model/value.py | 38 - dizoo/distar/policy/__init__.py | 1 - dizoo/distar/policy/distar_policy.py | 900 ------ dizoo/distar/policy/test_distar_policy.py | 37 - dizoo/distar/policy/utils.py | 146 - dizoo/distar/state_dict_utils.py | 19 - ...test_league_actor_with_pretrained_model.py | 180 -- 48 files changed, 8398 deletions(-) delete mode 100644 dizoo/distar/__init__.py delete mode 100644 dizoo/distar/config/__init__.py delete mode 100644 dizoo/distar/config/distar_config.py delete mode 100644 dizoo/distar/envs/__init__.py delete mode 100644 dizoo/distar/envs/distar_env.py delete mode 100644 dizoo/distar/envs/fake_data.py delete mode 100644 dizoo/distar/envs/meta.py delete mode 100644 dizoo/distar/envs/stat.py delete mode 100644 dizoo/distar/envs/static_data.py delete mode 100644 dizoo/distar/envs/tests/test_distar_config.yaml delete mode 100644 dizoo/distar/envs/tests/test_distar_env_data.py delete mode 100644 dizoo/distar/envs/tests/test_distar_env_time_space.py delete mode 100644 dizoo/distar/envs/tests/test_distar_env_with_manager.py delete mode 100644 dizoo/distar/envs/z_files/12D.json delete mode 100644 dizoo/distar/envs/z_files/1758k.json delete mode 100644 dizoo/distar/envs/z_files/3map.json delete mode 100644 dizoo/distar/envs/z_files/7map_filter_spine.json delete mode 100644 dizoo/distar/envs/z_files/NewRepugnancy.json delete mode 100644 dizoo/distar/envs/z_files/filter.json delete mode 100644 dizoo/distar/envs/z_files/lurker.json delete mode 100644 dizoo/distar/envs/z_files/mutalisk.json delete mode 100644 dizoo/distar/envs/z_files/nydus.json delete mode 100644 dizoo/distar/envs/z_files/perfect_z.json delete mode 100644 dizoo/distar/envs/z_files/stairs.json delete mode 100644 dizoo/distar/envs/z_files/worker_rush.json delete mode 100644 dizoo/distar/model/__init__.py delete mode 100644 dizoo/distar/model/actor_critic_default_config.yaml delete mode 100644 dizoo/distar/model/encoder.py delete mode 100644 dizoo/distar/model/head/__init__.py delete mode 100644 dizoo/distar/model/head/action_arg_head.py delete mode 100644 dizoo/distar/model/head/action_type_head.py delete mode 100644 dizoo/distar/model/model.py delete mode 100644 dizoo/distar/model/obs_encoder/__init__.py delete mode 100644 dizoo/distar/model/obs_encoder/entity_encoder.py delete mode 100644 dizoo/distar/model/obs_encoder/scalar_encoder.py delete mode 100644 dizoo/distar/model/obs_encoder/spatial_encoder.py delete mode 100644 dizoo/distar/model/obs_encoder/value_encoder.py delete mode 100644 dizoo/distar/model/policy.py delete mode 100644 dizoo/distar/model/tests/test_encoder.py delete mode 100644 dizoo/distar/model/tests/test_head.py delete mode 100644 dizoo/distar/model/tests/test_value.py delete mode 100644 dizoo/distar/model/value.py delete mode 100644 dizoo/distar/policy/__init__.py delete mode 100644 dizoo/distar/policy/distar_policy.py delete mode 100644 dizoo/distar/policy/test_distar_policy.py delete mode 100644 dizoo/distar/policy/utils.py delete mode 100644 dizoo/distar/state_dict_utils.py delete mode 100644 dizoo/distar/tests/test_league_actor_with_pretrained_model.py diff --git a/dizoo/distar/__init__.py b/dizoo/distar/__init__.py deleted file mode 100644 index e69de29bb2..0000000000 diff --git a/dizoo/distar/config/__init__.py b/dizoo/distar/config/__init__.py deleted file mode 100644 index a05f2cbff3..0000000000 --- a/dizoo/distar/config/__init__.py +++ /dev/null @@ -1 +0,0 @@ -from .distar_config import distar_cfg \ No newline at end of file diff --git a/dizoo/distar/config/distar_config.py b/dizoo/distar/config/distar_config.py deleted file mode 100644 index c209c8dd2c..0000000000 --- a/dizoo/distar/config/distar_config.py +++ /dev/null @@ -1,168 +0,0 @@ -from easydict import EasyDict - -distar_cfg = EasyDict( - { - 'env': { - 'manager': { - 'episode_num': 100000, - 'max_retry': 1000, - 'retry_type': 'renew', - 'auto_reset': True, - 'step_timeout': None, - 'reset_timeout': None, - 'retry_waiting_time': 0.1, - 'cfg_type': 'BaseEnvManagerDict', - 'shared_memory': False, - 'return_original_data': True - }, - 'collector_env_num': 1, - 'evaluator_env_num': 1, - 'n_evaluator_episode': 100, - 'env_type': 'prisoner_dilemma', - 'stop_value': [-10.1, -5.05] - }, - 'policy': { - 'model': { - 'obs_shape': 2, - 'action_shape': 2, - 'action_space': 'discrete', - 'encoder_hidden_size_list': [32, 32], - 'critic_head_hidden_size': 32, - 'actor_head_hidden_size': 32, - 'share_encoder': False - }, - 'learn': { - 'learner': { - 'train_iterations': 1000000000, - 'dataloader': { - 'num_workers': 0 - }, - 'log_policy': False, - 'hook': { - 'load_ckpt_before_run': '', - 'log_show_after_iter': 100, - 'save_ckpt_after_iter': 10000, - 'save_ckpt_after_run': True - }, - 'cfg_type': 'BaseLearnerDict' - }, - 'multi_gpu': False, - 'epoch_per_collect': 10, - 'batch_size': 4, - 'learning_rate': 1e-05, - 'value_weight': 0.5, - 'entropy_weight': 0.0, - 'clip_ratio': 0.2, - 'adv_norm': True, - 'value_norm': True, - 'ppo_param_init': True, - 'grad_clip_type': 'clip_norm', - 'grad_clip_value': 0.5, - 'ignore_done': False, - 'update_per_collect': 3, - 'scheduler': { - 'schedule_flag': False, - 'schedule_mode': 'reduce', - 'factor': 0.005, - 'change_range': [0, 1], - 'threshold': 0.5, - 'patience': 50 - } - }, - 'collect': { - 'collector': { - 'deepcopy_obs': False, - 'transform_obs': False, - 'collect_print_freq': 100, - 'get_train_sample': True, - 'cfg_type': 'BattleEpisodeSerialCollectorDict' - }, - 'discount_factor': 1.0, - 'gae_lambda': 1.0, - 'n_episode': 1, - 'unroll_len': 16 - }, - 'eval': { - 'evaluator': { - 'eval_freq': 50, - 'cfg_type': 'BattleInteractionSerialEvaluatorDict', - 'stop_value': [-10.1, -5.05], - 'n_episode': 100 - } - }, - 'other': { - 'replay_buffer': { - 'type': 'naive', - 'replay_buffer_size': 6, - 'max_use': 2, - 'deepcopy': False, - 'enable_track_used_data': False, - 'periodic_thruput_seconds': 60, - 'cfg_type': 'NaiveReplayBufferDict' - }, - 'league': { - 'player_category': ['default'], - 'path_policy': 'league_demo/ckpt', - 'active_players': { - 'main_player': 1 - }, - 'main_player': { - 'one_phase_step': 10, # 20 - 'branch_probs': { - 'pfsp': 0.0, - 'sp': 0.0, - 'sl': 1.0 - }, - 'strong_win_rate': 0.7 - }, - 'main_exploiter': { - 'one_phase_step': 200, - 'branch_probs': { - 'main_players': 1.0 - }, - 'strong_win_rate': 0.7, - 'min_valid_win_rate': 0.3 - }, - 'league_exploiter': { - 'one_phase_step': 200, - 'branch_probs': { - 'pfsp': 1.0 - }, - 'strong_win_rate': 0.7, - 'mutate_prob': 0.5 - }, - 'use_pretrain': False, - 'use_pretrain_init_historical': True, - 'pretrain_checkpoint_path': { - 'default': 'sl_model.pth', - }, - 'payoff': { - 'type': 'battle', - 'decay': 0.99, - 'min_win_rate_games': 8 - }, - 'metric': { - 'mu': 0, - 'sigma': 8.333333333333334, - 'beta': 4.166666666666667, - 'tau': 0.0, - 'draw_probability': 0.02 - } - } - }, - 'type': 'ppo', - 'cuda': False, - 'on_policy': True, - 'priority': False, - 'priority_IS_weight': False, - 'recompute_adv': True, - 'action_space': 'discrete', - 'nstep_return': False, - 'multi_agent': False, - 'transition_with_policy_data': True, - 'cfg_type': 'PPOPolicyDict' - }, - 'exp_name': 'league_demo', - 'seed': 0 - } -) diff --git a/dizoo/distar/envs/__init__.py b/dizoo/distar/envs/__init__.py deleted file mode 100644 index 2db9af3a2a..0000000000 --- a/dizoo/distar/envs/__init__.py +++ /dev/null @@ -1,5 +0,0 @@ -from .distar_env import DIStarEnv, parse_new_game, transform_obs, compute_battle_score -from .meta import * -from .static_data import RACE_DICT, BEGIN_ACTIONS, ACTION_RACE_MASK, SELECTED_UNITS_MASK, ACTIONS, BEGINNING_ORDER_ACTIONS, UNIT_TO_CUM, UPGRADE_TO_CUM, UNIT_ABILITY_TO_ACTION, QUEUE_ACTIONS, CUMULATIVE_STAT_ACTIONS -from .stat import Stat -from .fake_data import get_fake_rl_batch, get_fake_env_reset_data, get_fake_env_step_data diff --git a/dizoo/distar/envs/distar_env.py b/dizoo/distar/envs/distar_env.py deleted file mode 100644 index a4aeaca3df..0000000000 --- a/dizoo/distar/envs/distar_env.py +++ /dev/null @@ -1,702 +0,0 @@ -from typing import Optional, List -from copy import deepcopy -from collections import defaultdict -from s2clientprotocol import sc2api_pb2 as sc_pb -from pysc2.lib import named_array, colors, point -from pysc2.lib.features import Effects, ScoreCategories, FeatureType, Feature -from torch import int8, uint8, int16, int32, float32, float16, int64 - -import six -import collections -import enum -import json -import random -import numpy as np -import torch -import os.path as osp - -from ding.envs import BaseEnv, BaseEnvTimestep -try: - from distar.envs.env import SC2Env -except ImportError: - - class SC2Env: - pass -from .meta import MAX_DELAY, MAX_SELECTED_UNITS_NUM, DEFAULT_SPATIAL_SIZE, MAX_ENTITY_NUM, NUM_UPGRADES, NUM_ACTIONS, \ - NUM_UNIT_TYPES, NUM_UNIT_MIX_ABILITIES, EFFECT_LENGTH, UPGRADE_LENGTH, BEGINNING_ORDER_LENGTH -from .static_data import ACTIONS_STAT, RACE_DICT, UNIT_TYPES_REORDER_ARRAY, UPGRADES_REORDER_ARRAY, \ - CUMULATIVE_STAT_ACTIONS, UNIT_ABILITY_REORDER, ABILITY_TO_QUEUE_ACTION, BUFFS_REORDER_ARRAY, \ - ADDON_REORDER_ARRAY - - -class DIStarEnv(SC2Env, BaseEnv): - - def __init__(self, cfg): - super(DIStarEnv, self).__init__(cfg) - - def reset(self): - observations, game_info, map_name = super(DIStarEnv, self).reset() - - for policy_id, policy_obs in observations.items(): - policy_obs['game_info'] = game_info[policy_id] - map_size = game_info[policy_id].start_raw.map_size - policy_obs['map_name'] = map_name - policy_obs['map_size'] = map_size - - return observations - - def close(self): - super(DIStarEnv, self).close() - - def step(self, actions): - # In DI-engine, the return of BaseEnv.step is ('obs', 'reward', 'done', 'info') - # Here in DI-star, the return is ({'raw_obs': self._obs[agent_idx], 'opponent_obs': opponent_obs, - # 'action_result': self._action_result[agent_idx]}, reward, episode_complete) - next_observations, reward, done = super(DIStarEnv, self).step(actions) - # next_observations 和 observations 格式一样 - # reward 是 list [policy reward 1, policy reward 2] - # done 是 一个 bool 值 - info = {} - for policy_id in range(self._num_agents): - info[policy_id] = {} - if done: - info[policy_id]['final_eval_reward'] = reward[policy_id] - info[policy_id]['result'] = 'draws' - if reward[policy_id] == 1: - info[policy_id]['result'] = 'wins' - elif reward[policy_id] == -1: - info[policy_id]['result'] = 'losses' - timestep = BaseEnvTimestep(obs=next_observations, reward=reward, done=done, info=info) - return timestep - - def seed(self, seed, dynamic_seed=False): - self._random_seed = seed - - @property - def game_info(self): - return self._game_info - - @property - def map_name(self): - return self._map_name - - @property - def observation_space(self): - #TODO - pass - - @property - def action_space(self): - #TODO - pass - - @classmethod - def random_action(cls, obs): - raw = obs['raw_obs'].observation.raw_data - - all_unit_types = set() - self_unit_types = set() - - for u in raw.units: - # Here we select the units except “buildings that are in building progress” for simplification - if u.build_progress == 1: - all_unit_types.add(u.unit_type) - if u.alliance == 1: - self_unit_types.add(u.unit_type) - - avail_actions = [ - { - 0: { - 'exist_selected_types': [], - 'exist_target_types': [] - } - }, { - 168: { - 'exist_selected_types': [], - 'exist_target_types': [] - } - } - ] # no_op and raw_move_camera don't have seleted_units - - for action_id, action in ACTIONS_STAT.items(): - exist_selected_types = list(self_unit_types.intersection(set(action['selected_type']))) - exist_target_types = list(all_unit_types.intersection(set(action['target_type']))) - - # if an action should have target, but we don't have valid target in this observation, - # then discard this action - if len(action['target_type']) != 0 and len(exist_target_types) == 0: - continue - - if len(exist_selected_types) > 0: - avail_actions.append( - { - action_id: { - 'exist_selected_types': exist_selected_types, - 'exist_target_types': exist_target_types - } - } - ) - - current_action = random.choice(avail_actions) - func_id, exist_types = current_action.popitem() - - if func_id not in [0, 168]: - correspond_selected_units = [ - u.tag for u in raw.units if u.unit_type in exist_types['exist_selected_types'] and u.build_progress == 1 - ] - correspond_targets = [ - u.tag for u in raw.units if u.unit_type in exist_types['exist_target_types'] and u.build_progress == 1 - ] - - num_selected_unit = random.randint(0, min(MAX_SELECTED_UNITS_NUM, len(correspond_selected_units))) - - unit_tags = random.sample(correspond_selected_units, num_selected_unit) - target_unit_tag = random.choice(correspond_targets) if len(correspond_targets) > 0 else None - - else: - unit_tags = [] - target_unit_tag = None - - data = { - 'func_id': func_id, - 'skip_steps': random.randint(0, MAX_DELAY - 1), - # 'skip_steps': 8, - 'queued': random.randint(0, 1), - 'unit_tags': unit_tags, - 'target_unit_tag': target_unit_tag, - 'location': ( - random.randint(0, DEFAULT_SPATIAL_SIZE[0] - 1), random.randint(0, DEFAULT_SPATIAL_SIZE[1] - 1) - ) - } - return [data] - - @property - def reward_space(self): - #TODO - pass - - def __repr__(self): - return "DI-engine DI-star Env" - - -def parse_new_game(data, z_path: str, z_idx: Optional[None] = List): - # init Z - z_path = osp.join(osp.dirname(__file__), "z_files", z_path) - with open(z_path, 'r') as f: - z_data = json.load(f) - - raw_ob = data['raw_obs'] - game_info = data['game_info'] - map_size = data['map_size'] - if isinstance(map_size, list): - map_size = point.Point(map_size[0], map_size[1]) - map_name = data['map_name'] - requested_races = { - info.player_id: info.race_requested - for info in game_info.player_info if info.type != sc_pb.Observer - } - location = [] - for i in raw_ob.observation.raw_data.units: - if i.unit_type == 59 or i.unit_type == 18 or i.unit_type == 86: - location.append([i.pos.x, i.pos.y]) - assert len(location) == 1, 'no fog of war, check game version!' - _born_location = deepcopy(location[0]) - born_location = location[0] - born_location[0] = int(born_location[0]) - born_location[1] = int(map_size.y - born_location[1]) - born_location_str = str(born_location[0] + born_location[1] * 160) - - z_type = None - idx = None - race = RACE_DICT[requested_races[raw_ob.observation.player_common.player_id]] - opponent_id = 1 if raw_ob.observation.player_common.player_id == 2 else 2 - opponent_race = RACE_DICT[requested_races[opponent_id]] - if race == opponent_race: - mix_race = race - else: - mix_race = race + opponent_race - if z_idx is not None: - idx, z_type = random.choice(z_idx[map_name][mix_race][born_location_str]) - z = z_data[map_name][mix_race][born_location_str][idx] - else: - z = random.choice(z_data[map_name][mix_race][born_location_str]) - - if len(z) == 5: - target_building_order, target_cumulative_stat, bo_location, target_z_loop, z_type = z - else: - target_building_order, target_cumulative_stat, bo_location, target_z_loop = z - return race, requested_races, map_size, target_building_order, target_cumulative_stat, bo_location, target_z_loop, z_type, _born_location - - -class FeatureUnit(enum.IntEnum): - """Indices for the `feature_unit` observations.""" - unit_type = 0 - alliance = 1 - cargo_space_taken = 2 - build_progress = 3 - health_max = 4 - shield_max = 5 - energy_max = 6 - display_type = 7 - owner = 8 - x = 9 - y = 10 - cloak = 11 - is_blip = 12 - is_powered = 13 - mineral_contents = 14 - vespene_contents = 15 - cargo_space_max = 16 - assigned_harvesters = 17 - weapon_cooldown = 18 - order_length = 19 # If zero, the unit is idle. - order_id_0 = 20 - order_id_1 = 21 - # tag = 22 # Unique identifier for a unit (only populated for raw units). - is_hallucination = 22 - buff_id_0 = 23 - buff_id_1 = 24 - addon_unit_type = 25 - is_active = 26 - order_progress_0 = 27 - order_progress_1 = 28 - order_id_2 = 29 - order_id_3 = 30 - is_in_cargo = 31 - attack_upgrade_level = 32 - armor_upgrade_level = 33 - shield_upgrade_level = 34 - health = 35 - shield = 36 - energy = 37 - - -class MinimapFeatures(collections.namedtuple( - "MinimapFeatures", - ["height_map", "visibility_map", "creep", "player_relative", "alerts", "pathable", "buildable"])): - """The set of minimap feature layers.""" - __slots__ = () - - def __new__(cls, **kwargs): - feats = {} - for name, (scale, type_, palette) in six.iteritems(kwargs): - feats[name] = Feature( - index=MinimapFeatures._fields.index(name), - name=name, - layer_set="minimap_renders", - full_name="minimap " + name, - scale=scale, - type=type_, - palette=palette(scale) if callable(palette) else palette, - clip=False - ) - return super(MinimapFeatures, cls).__new__(cls, **feats) # pytype: disable=missing-parameter - - -MINIMAP_FEATURES = MinimapFeatures( - height_map=(256, FeatureType.SCALAR, colors.height_map), - visibility_map=(4, FeatureType.CATEGORICAL, colors.VISIBILITY_PALETTE), - creep=(2, FeatureType.CATEGORICAL, colors.CREEP_PALETTE), - player_relative=(5, FeatureType.CATEGORICAL, colors.PLAYER_RELATIVE_PALETTE), - alerts=(2, FeatureType.CATEGORICAL, colors.winter), - pathable=(2, FeatureType.CATEGORICAL, colors.winter), - buildable=(2, FeatureType.CATEGORICAL, colors.winter), -) - -SPATIAL_INFO = [ - ('height_map', uint8), ('visibility_map', uint8), ('creep', uint8), ('player_relative', uint8), ('alerts', uint8), - ('pathable', uint8), ('buildable', uint8), ('effect_PsiStorm', int16), ('effect_NukeDot', int16), - ('effect_LiberatorDefenderZone', int16), ('effect_BlindingCloud', int16), ('effect_CorrosiveBile', int16), - ('effect_LurkerSpines', int16) -] - -# (name, dtype, size) -SCALAR_INFO = [ - ('home_race', uint8, ()), ('away_race', uint8, ()), ('upgrades', int16, (NUM_UPGRADES, )), ('time', float32, ()), - ('unit_counts_bow', uint8, (NUM_UNIT_TYPES, )), ('agent_statistics', float32, (10, )), - ('cumulative_stat', uint8, (len(CUMULATIVE_STAT_ACTIONS), )), - ('beginning_order', int16, (BEGINNING_ORDER_LENGTH, )), ('last_queued', int16, ()), ('last_delay', int16, ()), - ('last_action_type', int16, ()), ('bo_location', int16, (BEGINNING_ORDER_LENGTH, )), - ('unit_order_type', uint8, (NUM_UNIT_MIX_ABILITIES, )), ('unit_type_bool', uint8, (NUM_UNIT_TYPES, )), - ('enemy_unit_type_bool', uint8, (NUM_UNIT_TYPES, )) -] - -ENTITY_INFO = [ - ('unit_type', int16), ('alliance', uint8), ('cargo_space_taken', uint8), ('build_progress', float16), - ('health_ratio', float16), ('shield_ratio', float16), ('energy_ratio', float16), ('display_type', uint8), - ('x', uint8), ('y', uint8), ('cloak', uint8), ('is_blip', uint8), ('is_powered', uint8), - ('mineral_contents', float16), ('vespene_contents', float16), ('cargo_space_max', uint8), - ('assigned_harvesters', uint8), ('weapon_cooldown', uint8), ('order_length', uint8), ('order_id_0', int16), - ('order_id_1', int16), ('is_hallucination', uint8), ('buff_id_0', uint8), ('buff_id_1', uint8), - ('addon_unit_type', uint8), ('is_active', uint8), ('order_progress_0', float16), ('order_progress_1', float16), - ('order_id_2', int16), ('order_id_3', int16), ('is_in_cargo', uint8), ('attack_upgrade_level', uint8), - ('armor_upgrade_level', uint8), ('shield_upgrade_level', uint8), ('last_selected_units', int8), - ('last_targeted_unit', int8) -] - -ACTION_INFO = { - 'action_type': torch.tensor(0, dtype=torch.long), - 'delay': torch.tensor(0, dtype=torch.long), - 'queued': torch.tensor(0, dtype=torch.long), - 'selected_units': torch.zeros((MAX_SELECTED_UNITS_NUM, ), dtype=torch.long), - 'target_unit': torch.tensor(0, dtype=torch.long), - 'target_location': torch.tensor(0, dtype=torch.long) -} - -ACTION_LOGP = { - 'action_type': torch.tensor(0, dtype=torch.float), - 'delay': torch.tensor(0, dtype=torch.float), - 'queued': torch.tensor(0, dtype=torch.float), - 'selected_units': torch.zeros((MAX_SELECTED_UNITS_NUM, ), dtype=torch.float), - 'target_unit': torch.tensor(0, dtype=torch.float), - 'target_location': torch.tensor(0, dtype=torch.float) -} - -ACTION_LOGIT = { - 'action_type': torch.zeros(NUM_ACTIONS, dtype=torch.float), - 'delay': torch.zeros(MAX_DELAY + 1, dtype=torch.float), - 'queued': torch.zeros(2, dtype=torch.float), - 'selected_units': torch.zeros((MAX_SELECTED_UNITS_NUM, MAX_ENTITY_NUM + 1), dtype=torch.float), - 'target_unit': torch.zeros(MAX_ENTITY_NUM, dtype=torch.float), - 'target_location': torch.zeros(DEFAULT_SPATIAL_SIZE[0] * DEFAULT_SPATIAL_SIZE[1], dtype=torch.float) -} - - -def compute_battle_score(obs): - if obs is None: - return 0. - score_details = obs.observation.score.score_details - killed_mineral, killed_vespene = 0., 0. - for s in ScoreCategories: - killed_mineral += getattr(score_details.killed_minerals, s.name) - killed_vespene += getattr(score_details.killed_vespene, s.name) - battle_score = killed_mineral + 1.5 * killed_vespene - return battle_score - - -def transform_obs(obs, map_size, requested_races, padding_spatial=False, opponent_obs=None): - spatial_info = defaultdict(list) - scalar_info = {} - entity_info = {} - game_info = {} - - raw = obs.observation.raw_data - # spatial info - for f in MINIMAP_FEATURES: - d = f.unpack(obs.observation).copy() - d = torch.from_numpy(d) - padding_y = DEFAULT_SPATIAL_SIZE[0] - d.shape[0] - padding_x = DEFAULT_SPATIAL_SIZE[1] - d.shape[1] - if (padding_y != 0 or padding_x != 0) and padding_spatial: - d = torch.nn.functional.pad(d, (0, padding_x, 0, padding_y), 'constant', 0) - spatial_info[f.name] = d - for e in raw.effects: - name = Effects(e.effect_id).name - if name in ['LiberatorDefenderZone', 'LurkerSpines'] and e.owner == 1: - continue - for p in e.pos: - location = int(p.x) + int(map_size.y - p.y) * DEFAULT_SPATIAL_SIZE[1] - spatial_info['effect_' + name].append(location) - for k, _ in SPATIAL_INFO: - if 'effect' in k: - padding_num = EFFECT_LENGTH - len(spatial_info[k]) - if padding_num > 0: - spatial_info[k] += [0] * padding_num - else: - spatial_info[k] = spatial_info[k][:EFFECT_LENGTH] - spatial_info[k] = torch.as_tensor(spatial_info[k], dtype=int16) - - # entity info - tag_types = {} # Only populate the cache if it's needed. - - def get_addon_type(tag): - if not tag_types: - for u in raw.units: - tag_types[u.tag] = u.unit_type - return tag_types.get(tag, 0) - - tags = [] - units = [] - for u in raw.units: - tags.append(u.tag) - units.append( - [ - u.unit_type, - u.alliance, # Self = 1, Ally = 2, Neutral = 3, Enemy = 4 - u.cargo_space_taken, - u.build_progress, - u.health_max, - u.shield_max, - u.energy_max, - u.display_type, # Visible = 1, Snapshot = 2, Hidden = 3 - u.owner, # 1-15, 16 = neutral - u.pos.x, - u.pos.y, - u.cloak, # Cloaked = 1, CloakedDetected = 2, NotCloaked = 3 - u.is_blip, - u.is_powered, - u.mineral_contents, - u.vespene_contents, - # Not populated for enemies or neutral - u.cargo_space_max, - u.assigned_harvesters, - u.weapon_cooldown, - len(u.orders), - u.orders[0].ability_id if len(u.orders) > 0 else 0, - u.orders[1].ability_id if len(u.orders) > 1 else 0, - u.is_hallucination, - u.buff_ids[0] if len(u.buff_ids) >= 1 else 0, - u.buff_ids[1] if len(u.buff_ids) >= 2 else 0, - get_addon_type(u.add_on_tag) if u.add_on_tag else 0, - u.is_active, - u.orders[0].progress if len(u.orders) >= 1 else 0, - u.orders[1].progress if len(u.orders) >= 2 else 0, - u.orders[2].ability_id if len(u.orders) > 2 else 0, - u.orders[3].ability_id if len(u.orders) > 3 else 0, - 0, - u.attack_upgrade_level, - u.armor_upgrade_level, - u.shield_upgrade_level, - u.health, - u.shield, - u.energy, - ] - ) - for v in u.passengers: - tags.append(v.tag) - units.append( - [ - v.unit_type, - u.alliance, # Self = 1, Ally = 2, Neutral = 3, Enemy = 4 - 0, - 0, - v.health_max, - v.shield_max, - v.energy_max, - 0, # Visible = 1, Snapshot = 2, Hidden = 3 - u.owner, # 1-15, 16 = neutral - u.pos.x, - u.pos.y, - 0, # Cloaked = 1, CloakedDetected = 2, NotCloaked = 3 - 0, - 0, - 0, - 0, - # Not populated for enemies or neutral - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 1, - 0, - 0, - 0, - v.health, - v.shield, - v.energy, - ] - ) - units = units[:MAX_ENTITY_NUM] - tags = tags[:MAX_ENTITY_NUM] - raw_entity_info = named_array.NamedNumpyArray(units, [None, FeatureUnit], dtype=np.float32) - - for k, dtype in ENTITY_INFO: - if 'last' in k: - pass - elif k == 'unit_type': - entity_info[k] = UNIT_TYPES_REORDER_ARRAY[raw_entity_info[:, 'unit_type']].short() - elif 'order_id' in k: - order_idx = int(k.split('_')[-1]) - if order_idx == 0: - entity_info[k] = UNIT_ABILITY_REORDER[raw_entity_info[:, k]].short() - invalid_actions = entity_info[k] == -1 - if invalid_actions.any(): - print('[ERROR] invalid unit ability', raw_entity_info[invalid_actions, k]) - else: - entity_info[k] = ABILITY_TO_QUEUE_ACTION[raw_entity_info[:, k]].short() - invalid_actions = entity_info[k] == -1 - if invalid_actions.any(): - print('[ERROR] invalid queue ability', raw_entity_info[invalid_actions, k]) - elif 'buff_id' in k: - entity_info[k] = BUFFS_REORDER_ARRAY[raw_entity_info[:, k]].short() - elif k == 'addon_unit_type': - entity_info[k] = ADDON_REORDER_ARRAY[raw_entity_info[:, k]].short() - elif k == 'cargo_space_taken': - entity_info[k] = torch.as_tensor(raw_entity_info[:, 'cargo_space_taken'], dtype=dtype).clamp_(min=0, max=8) - elif k == 'cargo_space_max': - entity_info[k] = torch.as_tensor(raw_entity_info[:, 'cargo_space_max'], dtype=dtype).clamp_(min=0, max=8) - elif k == 'health_ratio': - entity_info[k] = torch.as_tensor( - raw_entity_info[:, 'health'], dtype=dtype - ) / (torch.as_tensor(raw_entity_info[:, 'health_max'], dtype=dtype) + 1e-6) - elif k == 'shield_ratio': - entity_info[k] = torch.as_tensor( - raw_entity_info[:, 'shield'], dtype=dtype - ) / (torch.as_tensor(raw_entity_info[:, 'shield_max'], dtype=dtype) + 1e-6) - elif k == 'energy_ratio': - entity_info[k] = torch.as_tensor( - raw_entity_info[:, 'energy'], dtype=dtype - ) / (torch.as_tensor(raw_entity_info[:, 'energy_max'], dtype=dtype) + 1e-6) - elif k == 'mineral_contents': - entity_info[k] = torch.as_tensor(raw_entity_info[:, 'mineral_contents'], dtype=dtype) / 1800 - elif k == 'vespene_contents': - entity_info[k] = torch.as_tensor(raw_entity_info[:, 'vespene_contents'], dtype=dtype) / 2500 - elif k == 'y': - entity_info[k] = torch.as_tensor(map_size.y - raw_entity_info[:, 'y'], dtype=dtype) - else: - entity_info[k] = torch.as_tensor(raw_entity_info[:, k], dtype=dtype) - - # scalar info - scalar_info['time'] = torch.tensor(obs.observation.game_loop, dtype=torch.float) - player = obs.observation.player_common - scalar_info['agent_statistics'] = torch.tensor( - [ - player.minerals, player.vespene, player.food_used, player.food_cap, player.food_army, player.food_workers, - player.idle_worker_count, player.army_count, player.warp_gate_count, player.larva_count - ], - dtype=torch.float - ) - scalar_info['agent_statistics'] = torch.log(scalar_info['agent_statistics'] + 1) - - scalar_info["home_race"] = torch.tensor(requested_races[player.player_id], dtype=torch.uint8) - for player_id, race in requested_races.items(): - if player_id != player.player_id: - scalar_info["away_race"] = torch.tensor(race, dtype=torch.uint8) - - upgrades = torch.zeros(NUM_UPGRADES, dtype=torch.uint8) - raw_upgrades = UPGRADES_REORDER_ARRAY[raw.player.upgrade_ids[:UPGRADE_LENGTH]] - upgrades.scatter_(dim=0, index=raw_upgrades, value=1.) - scalar_info["upgrades"] = upgrades - - unit_counts_bow = torch.zeros(NUM_UNIT_TYPES, dtype=torch.uint8) - scalar_info['unit_type_bool'] = torch.zeros(NUM_UNIT_TYPES, dtype=uint8) - own_unit_types = entity_info['unit_type'][entity_info['alliance'] == 1] - scalar_info['unit_counts_bow'] = torch.scatter_add( - unit_counts_bow, dim=0, index=own_unit_types.long(), src=torch.ones_like(own_unit_types, dtype=torch.uint8) - ) - scalar_info['unit_type_bool'] = (scalar_info['unit_counts_bow'] > 0).to(uint8) - - scalar_info['unit_order_type'] = torch.zeros(NUM_UNIT_MIX_ABILITIES, dtype=uint8) - own_unit_orders = entity_info['order_id_0'][entity_info['alliance'] == 1] - scalar_info['unit_order_type'].scatter_(0, own_unit_orders.long(), torch.ones_like(own_unit_orders, dtype=uint8)) - - enemy_unit_types = entity_info['unit_type'][entity_info['alliance'] == 4] - enemy_unit_type_bool = torch.zeros(NUM_UNIT_TYPES, dtype=torch.uint8) - scalar_info['enemy_unit_type_bool'] = torch.scatter( - enemy_unit_type_bool, - dim=0, - index=enemy_unit_types.long(), - src=torch.ones_like(enemy_unit_types, dtype=torch.uint8) - ) - - # game info - game_info['action_result'] = [o.result for o in obs.action_errors] - game_info['game_loop'] = obs.observation.game_loop - game_info['tags'] = tags - game_info['battle_score'] = compute_battle_score(obs) - game_info['opponent_battle_score'] = 0. - ret = { - 'spatial_info': spatial_info, - 'scalar_info': scalar_info, - 'entity_num': torch.tensor(len(entity_info['unit_type']), dtype=torch.long), - 'entity_info': entity_info, - 'game_info': game_info, - } - - # value feature - if opponent_obs: - raw = opponent_obs.observation.raw_data - enemy_unit_counts_bow = torch.zeros(NUM_UNIT_TYPES, dtype=torch.uint8) - enemy_x = [] - enemy_y = [] - enemy_unit_type = [] - unit_alliance = [] - for u in raw.units: - if u.alliance == 1: - enemy_x.append(u.pos.x) - enemy_y.append(u.pos.y) - enemy_unit_type.append(u.unit_type) - unit_alliance.append(1) - enemy_unit_type = UNIT_TYPES_REORDER_ARRAY[enemy_unit_type].short() - enemy_unit_counts_bow = torch.scatter_add( - enemy_unit_counts_bow, - dim=0, - index=enemy_unit_type.long(), - src=torch.ones_like(enemy_unit_type, dtype=torch.uint8) - ) - enemy_unit_type_bool = (enemy_unit_counts_bow > 0).to(uint8) - - unit_type = torch.cat([enemy_unit_type, own_unit_types], dim=0) - enemy_x = torch.as_tensor(enemy_x, dtype=uint8) - unit_x = torch.cat([enemy_x, entity_info['x'][entity_info['alliance'] == 1]], dim=0) - - enemy_y = torch.as_tensor(enemy_y, dtype=float32) - enemy_y = torch.as_tensor(map_size.y - enemy_y, dtype=uint8) - unit_y = torch.cat([enemy_y, entity_info['y'][entity_info['alliance'] == 1]], dim=0) - total_unit_count = len(unit_y) - unit_alliance += [0] * (total_unit_count - len(unit_alliance)) - unit_alliance = torch.as_tensor(unit_alliance, dtype=torch.bool) - - padding_num = MAX_ENTITY_NUM - total_unit_count - if padding_num > 0: - unit_x = torch.nn.functional.pad(unit_x, (0, padding_num), 'constant', 0) - unit_y = torch.nn.functional.pad(unit_y, (0, padding_num), 'constant', 0) - unit_type = torch.nn.functional.pad(unit_type, (0, padding_num), 'constant', 0) - unit_alliance = torch.nn.functional.pad(unit_alliance, (0, padding_num), 'constant', 0) - else: - unit_x = unit_x[:MAX_ENTITY_NUM] - unit_y = unit_y[:MAX_ENTITY_NUM] - unit_type = unit_type[:MAX_ENTITY_NUM] - unit_alliance = unit_alliance[:MAX_ENTITY_NUM] - - total_unit_count = torch.tensor(total_unit_count, dtype=torch.long) - - player = opponent_obs.observation.player_common - enemy_agent_statistics = torch.tensor( - [ - player.minerals, player.vespene, player.food_used, player.food_cap, player.food_army, - player.food_workers, player.idle_worker_count, player.army_count, player.warp_gate_count, - player.larva_count - ], - dtype=torch.float - ) - enemy_agent_statistics = torch.log(enemy_agent_statistics + 1) - enemy_raw_upgrades = UPGRADES_REORDER_ARRAY[raw.player.upgrade_ids[:UPGRADE_LENGTH]] - enemy_upgrades = torch.zeros(NUM_UPGRADES, dtype=torch.uint8) - enemy_upgrades.scatter_(dim=0, index=enemy_raw_upgrades, value=1.) - - d = MINIMAP_FEATURES.player_relative.unpack(opponent_obs.observation).copy() - d = torch.from_numpy(d) - padding_y = DEFAULT_SPATIAL_SIZE[0] - d.shape[0] - padding_x = DEFAULT_SPATIAL_SIZE[1] - d.shape[1] - if (padding_y != 0 or padding_x != 0) and padding_spatial: - d = torch.nn.functional.pad(d, (0, padding_x, 0, padding_y), 'constant', 0) - enemy_units_spatial = d == 1 - own_units_spatial = ret['spatial_info']['player_relative'] == 1 - value_feature = { - 'unit_type': unit_type, - 'enemy_unit_counts_bow': enemy_unit_counts_bow, - 'enemy_unit_type_bool': enemy_unit_type_bool, - 'unit_x': unit_x, - 'unit_y': unit_y, - 'unit_alliance': unit_alliance, - 'total_unit_count': total_unit_count, - 'enemy_agent_statistics': enemy_agent_statistics, - 'enemy_upgrades': enemy_upgrades, - 'own_units_spatial': own_units_spatial.unsqueeze(dim=0), - 'enemy_units_spatial': enemy_units_spatial.unsqueeze(dim=0) - } - ret['value_feature'] = value_feature - game_info['opponent_battle_score'] = compute_battle_score(opponent_obs) - return ret diff --git a/dizoo/distar/envs/fake_data.py b/dizoo/distar/envs/fake_data.py deleted file mode 100644 index 436d5fb1ab..0000000000 --- a/dizoo/distar/envs/fake_data.py +++ /dev/null @@ -1,673 +0,0 @@ -from typing import Sequence -import math -import six -import numpy as np -import torch - -from pysc2.lib import features, actions, point, units -from pysc2.maps.melee import Melee -from s2clientprotocol import raw_pb2 -from s2clientprotocol import sc2api_pb2 as sc_pb -from s2clientprotocol import score_pb2, common_pb2 - -from ding.utils.data import default_collate -from .meta import MAX_DELAY, MAX_ENTITY_NUM, NUM_ACTIONS, NUM_UNIT_TYPES, NUM_UPGRADES, NUM_CUMULATIVE_STAT_ACTIONS, \ - NUM_BEGINNING_ORDER_ACTIONS, NUM_UNIT_MIX_ABILITIES, NUM_QUEUE_ACTION, NUM_BUFFS, NUM_ADDON, \ - MAX_SELECTED_UNITS_NUM, DEFAULT_SPATIAL_SIZE - -H, W = DEFAULT_SPATIAL_SIZE - - -def spatial_info(): - return { - 'height_map': torch.rand(H, W), - 'visibility_map': torch.randint(0, 4, size=(H, W), dtype=torch.float), - 'creep': torch.randint(0, 2, size=(H, W), dtype=torch.float), - 'player_relative': torch.randint(0, 5, size=(H, W), dtype=torch.float), - 'alerts': torch.randint(0, 2, size=(H, W), dtype=torch.float), - 'pathable': torch.randint(0, 2, size=(H, W), dtype=torch.float), - 'buildable': torch.randint(0, 2, size=(H, W), dtype=torch.float), - 'effect_PsiStorm': torch.randint(0, min(H, W), size=(2, ), dtype=torch.float), - 'effect_NukeDot': torch.randint(0, min(H, W), size=(2, ), dtype=torch.float), - 'effect_LiberatorDefenderZone': torch.randint(0, min(H, W), size=(2, ), dtype=torch.float), - 'effect_BlindingCloud': torch.randint(0, min(H, W), size=(2, ), dtype=torch.float), - 'effect_CorrosiveBile': torch.randint(0, min(H, W), size=(2, ), dtype=torch.float), - 'effect_LurkerSpines': torch.randint(0, min(H, W), size=(2, ), dtype=torch.float), - } - - -def entity_info(): - data = { - 'unit_type': torch.randint(0, NUM_UNIT_TYPES, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'alliance': torch.randint(0, 5, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'cargo_space_taken': torch.randint(0, 9, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'build_progress': torch.rand(MAX_ENTITY_NUM), - 'health_ratio': torch.rand(MAX_ENTITY_NUM), - 'shield_ratio': torch.rand(MAX_ENTITY_NUM), - 'energy_ratio': torch.rand(MAX_ENTITY_NUM), - 'display_type': torch.randint(0, 5, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'x': torch.randint(0, 11, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'y': torch.randint(0, 11, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'cloak': torch.randint(0, 5, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'is_blip': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'is_powered': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'mineral_contents': torch.rand(MAX_ENTITY_NUM), - 'vespene_contents': torch.rand(MAX_ENTITY_NUM), - 'cargo_space_max': torch.randint(0, 9, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'assigned_harvesters': torch.randint(0, 24, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'weapon_cooldown': torch.randint(0, 32, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'order_length': torch.randint(0, 9, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'order_id_0': torch.randint(0, NUM_ACTIONS, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'order_id_1': torch.randint(0, NUM_QUEUE_ACTION, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'is_hallucination': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'buff_id_0': torch.randint(0, NUM_BUFFS, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'buff_id_1': torch.randint(0, NUM_BUFFS, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'addon_unit_type': torch.randint(0, NUM_ADDON, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'is_active': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'order_progress_0': torch.rand(MAX_ENTITY_NUM), - 'order_progress_1': torch.rand(MAX_ENTITY_NUM), - 'order_id_2': torch.randint(0, NUM_QUEUE_ACTION, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'order_id_3': torch.randint(0, NUM_QUEUE_ACTION, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'is_in_cargo': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'attack_upgrade_level': torch.randint(0, 4, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'armor_upgrade_level': torch.randint(0, 4, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'shield_upgrade_level': torch.randint(0, 4, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'last_selected_units': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - 'last_targeted_unit': torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.float), - } - return data - - -def scalar_info(): - data = { - 'home_race': torch.randint(0, 4, size=(), dtype=torch.float), - 'away_race': torch.randint(0, 4, size=(), dtype=torch.float), - 'agent_statistics': torch.rand(10), - 'time': torch.randint(0, 100, size=(), dtype=torch.float), - 'unit_counts_bow': torch.randint(0, 10, size=(NUM_UNIT_TYPES, ), dtype=torch.float), - 'beginning_build_order': torch.randint(0, 20, size=(20, ), dtype=torch.float), - 'cumulative_stat': torch.randint(0, 2, size=(NUM_CUMULATIVE_STAT_ACTIONS, ), dtype=torch.float), - 'last_delay': torch.randint(0, MAX_DELAY, size=(), dtype=torch.float), - 'last_queued': torch.randint(0, 2, size=(), dtype=torch.float), - 'last_action_type': torch.randint(0, NUM_ACTIONS, size=(), dtype=torch.float), - 'upgrades': torch.randint(0, 2, size=(NUM_UPGRADES, ), dtype=torch.float), - 'beginning_order': torch.randint(0, NUM_BEGINNING_ORDER_ACTIONS, size=(20, ), dtype=torch.float), - 'bo_location': torch.randint(0, 100 * 100, size=(20, ), dtype=torch.float), - 'unit_type_bool': torch.randint(0, 2, size=(NUM_UNIT_TYPES, ), dtype=torch.float), - 'enemy_unit_type_bool': torch.randint(0, 2, size=(NUM_UNIT_TYPES, ), dtype=torch.float), - 'unit_order_type': torch.randint(0, 2, size=(NUM_UNIT_MIX_ABILITIES, ), dtype=torch.float) - } - return data - - -def get_mask(action): - mask = { - 'action_type': torch.ones(1, dtype=torch.long).squeeze(), - 'delay': torch.ones(1, dtype=torch.long).squeeze(), - 'queued': torch.ones(1, dtype=torch.long).squeeze(), - 'selected_units': torch.randint(0, 2, size=(), dtype=torch.long), - 'target_unit': torch.randint(0, 2, size=(), dtype=torch.long), - 'target_location': torch.randint(0, 2, size=(), dtype=torch.long) - } - selected_units_logits_mask = torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.long) - target_units_logits_mask = torch.randint(0, 2, size=(MAX_ENTITY_NUM, ), dtype=torch.long) - target_units_logits_mask[action['target_unit']] = 1 - cum_action_mask= torch.tensor(1.0,dtype=torch.float) - - return { - 'actions_mask': mask, - 'selected_units_logits_mask': selected_units_logits_mask, - 'target_units_logits_mask': target_units_logits_mask, - 'cum_action_mask': cum_action_mask - } - - -def action_info(): - data = { - 'action_type': torch.randint(0, NUM_ACTIONS, size=(), dtype=torch.long), - 'delay': torch.randint(0, MAX_DELAY, size=(), dtype=torch.long), - 'queued': torch.randint(0, 2, size=(), dtype=torch.long), - 'selected_units': torch.randint(0, 5, size=(MAX_SELECTED_UNITS_NUM, ), dtype=torch.long), - 'target_unit': torch.randint(0, MAX_ENTITY_NUM, size=(), dtype=torch.long), - 'target_location': torch.randint(0, H, size=(), dtype=torch.long) - } - mask = get_mask(data) - return data, mask - - -def action_logits(logp=False, action=None): - data = { - 'action_type': torch.rand(size=(NUM_ACTIONS, )) - 0.5, - 'delay': torch.rand(size=(MAX_DELAY, )) - 0.5, - 'queued': torch.rand(size=(2, )) - 0.5, - 'selected_units': torch.rand(size=(MAX_SELECTED_UNITS_NUM, MAX_ENTITY_NUM + 1)) - 0.5, - 'target_unit': torch.rand(size=(MAX_ENTITY_NUM, )) - 0.5, - 'target_location': torch.rand(size=(H * W, )) - 0.5 - } - if logp: - for k in data: - dist = torch.distributions.Categorical(logits=data[k]) - data[k] = dist.log_prob(action[k]) - return data - - -def rl_step_data(last=False): - action, mask = action_info() - teacher_action_logits = action_logits() - data = { - 'spatial_info': spatial_info(), - 'entity_info': entity_info(), - 'scalar_info': scalar_info(), - 'entity_num': torch.randint(5, 100, size=(), dtype=torch.long), - 'selected_units_num': torch.randint(0, MAX_SELECTED_UNITS_NUM, size=(), dtype=torch.long), - 'entity_location': torch.randint(0, H, size=(512, 2), dtype=torch.long), - 'hidden_state': [(torch.zeros(size=(384, )), torch.zeros(size=(384, ))) for _ in range(3)], - 'action_info': action, - 'behaviour_logp': action_logits(logp=True, action=action), - 'teacher_logit': action_logits(logp=False), - 'reward': { - 'winloss': torch.randint(-1, 1, size=(), dtype=torch.float), - 'build_order': torch.randint(-1, 1, size=(), dtype=torch.float), - 'built_unit': torch.randint(-1, 1, size=(), dtype=torch.float), - 'effect': torch.randint(-1, 1, size=(), dtype=torch.float), - 'upgrade': torch.randint(-1, 1, size=(), dtype=torch.float), - 'battle': torch.randint(-1, 1, size=(), dtype=torch.float), - }, - 'step': torch.randint(100, 1000, size=(), dtype=torch.long), - 'mask': mask, - } - if last: - for k in ['mask', 'action_info', 'teacher_logit', 'behaviour_logp', 'selected_units_num', 'reward', 'step']: - data.pop(k) - return data - - -def fake_rl_traj_with_last(unroll_len=4): - list_step_data = [] - for i in range(unroll_len): - step_data = rl_step_data() - list_step_data.append(step_data) - list_step_data.append(rl_step_data(last=True)) # last step - return list_step_data - - -def get_fake_rl_batch(batch_size=3, unroll_len=4): - data_batch = [fake_rl_traj_with_last(unroll_len) for _ in range(batch_size)] - return data_batch - - -class Unit(object): - """Class to hold unit data for the builder.""" - - def __init__( - self, - unit_type, # see lib/units.py - player_relative, # features.PlayerRelative, - health, - shields=0, - energy=0, - transport_slots_taken=0, - build_progress=1.0 - ): - - self.unit_type = unit_type - self.player_relative = player_relative - self.health = health - self.shields = shields - self.energy = energy - self.transport_slots_taken = transport_slots_taken - self.build_progress = build_progress - - def fill(self, unit_proto): - """Fill a proto unit data object from this Unit.""" - unit_proto.unit_type = self.unit_type - unit_proto.player_relative = self.player_relative - unit_proto.health = self.health - unit_proto.shields = self.shields - unit_proto.energy = self.energy - unit_proto.transport_slots_taken = self.transport_slots_taken - unit_proto.build_progress = self.build_progress - - def as_array(self): - """Return the unit represented as a numpy array.""" - return np.array( - [ - self.unit_type, self.player_relative, self.health, self.shields, self.energy, - self.transport_slots_taken, - int(self.build_progress * 100) - ], - dtype=np.int32 - ) - - def as_dict(self): - return vars(self) - - -class FeatureUnit(object): - """Class to hold feature unit data for the builder.""" - - def __init__( - self, - unit_type, # see lib/units - alliance, # features.PlayerRelative, - owner, # 1-15, 16=neutral - pos, # common_pb2.Point, - radius, - health, - health_max, - is_on_screen, - shield=0, - shield_max=0, - energy=0, - energy_max=0, - cargo_space_taken=0, - cargo_space_max=0, - build_progress=1.0, - facing=0.0, - display_type=raw_pb2.Visible, # raw_pb.DisplayType - cloak=raw_pb2.NotCloaked, # raw_pb.CloakState - is_selected=False, - is_blip=False, - is_powered=True, - mineral_contents=0, - vespene_contents=0, - assigned_harvesters=0, - ideal_harvesters=0, - weapon_cooldown=0.0, - orders=None, - is_flying=False, - is_burrowed=False, - is_hallucination=False, - is_active=False, - attack_upgrade_level=0, - armor_upgrade_level=0, - shield_upgrade_level=0, - ): - - self.unit_type = unit_type - self.alliance = alliance - self.owner = owner - self.pos = pos - self.radius = radius - self.health = health - self.health_max = health_max - self.is_on_screen = is_on_screen - self.shield = shield - self.shield_max = shield_max - self.energy = energy - self.energy_max = energy_max - self.cargo_space_taken = cargo_space_taken - self.cargo_space_max = cargo_space_max - self.build_progress = build_progress - self.facing = facing - self.display_type = display_type - self.cloak = cloak - self.is_selected = is_selected - self.is_blip = is_blip - self.is_powered = is_powered - self.mineral_contents = mineral_contents - self.vespene_contents = vespene_contents - self.assigned_harvesters = assigned_harvesters - self.ideal_harvesters = ideal_harvesters - self.weapon_cooldown = weapon_cooldown - self.is_flying = is_flying - self.is_burrowed = is_burrowed - self.is_hallucination = is_hallucination - self.is_active = is_active - self.attack_upgrade_level = attack_upgrade_level - self.armor_upgrade_level = armor_upgrade_level - self.shield_upgrade_level = shield_upgrade_level - if orders is not None: - self.orders = orders - - def as_dict(self): - return vars(self) - - -class FeatureResource(object): - """Class to hold feature unit data for the builder.""" - - def __init__( - self, - unit_type, # see lib/units - alliance, # features.PlayerRelative, - owner, # 1-15, 16=neutral - pos, # common_pb2.Point, - radius, - is_on_screen, - build_progress=1.0, - facing=0.0, - display_type=raw_pb2.Visible, # raw_pb.DisplayType - cloak=raw_pb2.NotCloaked, # raw_pb.CloakState - is_blip=False, - is_powered=True, - ): - - self.unit_type = unit_type - self.alliance = alliance - self.owner = owner - self.pos = pos - self.radius = radius - self.is_on_screen = is_on_screen - self.build_progress = build_progress - self.facing = facing - self.display_type = display_type - self.cloak = cloak - self.is_blip = is_blip - self.is_powered = is_powered - - def as_dict(self): - return vars(self) - - -class Builder(object): - """For test code - build a dummy ResponseObservation proto.""" - - def __init__(self, obs_spec): - self._game_loop = 1 - self._player_common = sc_pb.PlayerCommon( - player_id=1, - minerals=20, - vespene=50, - food_cap=36, - food_used=21, - food_army=6, - food_workers=15, - idle_worker_count=2, - army_count=6, - warp_gate_count=0, - ) - - self._score = 300 - self._score_type = Melee - self._score_details = score_pb2.ScoreDetails( - idle_production_time=0, - idle_worker_time=0, - total_value_units=190, - total_value_structures=230, - killed_value_units=0, - killed_value_structures=0, - collected_minerals=2130, - collected_vespene=560, - collection_rate_minerals=50, - collection_rate_vespene=20, - spent_minerals=2000, - spent_vespene=500, - food_used=score_pb2.CategoryScoreDetails( - none=0.0, army=0.0, economy=self._player_common.food_used, technology=0.0, upgrade=0.0 - ), - killed_minerals=score_pb2.CategoryScoreDetails( - none=0.0, army=0.0, economy=0.0, technology=0.0, upgrade=0.0 - ), - killed_vespene=score_pb2.CategoryScoreDetails(none=0.0, army=0.0, economy=0.0, technology=0.0, upgrade=0.0), - lost_minerals=score_pb2.CategoryScoreDetails(none=0.0, army=0.0, economy=0.0, technology=0.0, upgrade=0.0), - lost_vespene=score_pb2.CategoryScoreDetails(none=0.0, army=0.0, economy=0.0, technology=0.0, upgrade=0.0), - friendly_fire_minerals=score_pb2.CategoryScoreDetails( - none=0.0, army=0.0, economy=0.0, technology=0.0, upgrade=0.0 - ), - friendly_fire_vespene=score_pb2.CategoryScoreDetails( - none=0.0, army=0.0, economy=0.0, technology=0.0, upgrade=0.0 - ), - used_minerals=score_pb2.CategoryScoreDetails(none=0.0, army=0.0, economy=0.0, technology=0.0, upgrade=0.0), - used_vespene=score_pb2.CategoryScoreDetails(none=0.0, army=0.0, economy=0.0, technology=0.0, upgrade=0.0), - total_used_minerals=score_pb2.CategoryScoreDetails( - none=0.0, army=0.0, economy=0.0, technology=0.0, upgrade=0.0 - ), - total_used_vespene=score_pb2.CategoryScoreDetails( - none=0.0, army=0.0, economy=0.0, technology=0.0, upgrade=0.0 - ), - total_damage_dealt=score_pb2.VitalScoreDetails(life=0.0, shields=0.0, energy=0.0), - total_damage_taken=score_pb2.VitalScoreDetails(life=0.0, shields=0.0, energy=0.0), - total_healed=score_pb2.VitalScoreDetails(life=0.0, shields=0.0, energy=0.0), - ) - - self._obs_spec = obs_spec - self._single_select = None - self._multi_select = None - self._build_queue = None - self._production = None - self._feature_units = None - - def game_loop(self, game_loop): - self._game_loop = game_loop - return self - - # pylint:disable=unused-argument - def player_common( - self, - player_id=None, - minerals=None, - vespene=None, - food_cap=None, - food_used=None, - food_army=None, - food_workers=None, - idle_worker_count=None, - army_count=None, - warp_gate_count=None, - larva_count=None - ): - """Update some or all of the fields in the PlayerCommon data.""" - - args = dict(locals()) - for key, value in six.iteritems(args): - if value is not None and key != 'self': - setattr(self._player_common, key, value) - return self - - def score(self, score): - self._score = score - return self - - def score_details( - self, - idle_production_time=None, - idle_worker_time=None, - total_value_units=None, - total_value_structures=None, - killed_value_units=None, - killed_value_structures=None, - collected_minerals=None, - collected_vespene=None, - collection_rate_minerals=None, - collection_rate_vespene=None, - spent_minerals=None, - spent_vespene=None - ): - """Update some or all of the fields in the ScoreDetails data.""" - - args = dict(locals()) - for key, value in six.iteritems(args): - if value is not None and key != 'self': - setattr(self._score_details, key, value) - return self - - # pylint:enable=unused-argument - - def score_by_category(self, entry_name, none, army, economy, technology, upgrade): - - field = getattr(self._score_details, entry_name) - field.CopyFrom( - score_pb2.CategoryScoreDetails( - none=none, army=army, economy=economy, technology=technology, upgrade=upgrade - ) - ) - - def score_by_vital(self, entry_name, life, shields, energy): - field = getattr(self._score_details, entry_name) - field.CopyFrom(score_pb2.VitalScoreDetails(life=life, shields=shields, energy=energy)) - - def single_select(self, unit): - self._single_select = unit - return self - - def multi_select(self, units): - self._multi_select = units - return self - - def build_queue(self, build_queue, production=None): - self._build_queue = build_queue - self._production = production - return self - - def feature_units(self, feature_units): - self._feature_units = feature_units - return self - - def build(self): - """Builds and returns a proto ResponseObservation.""" - response_observation = sc_pb.ResponseObservation() - obs = response_observation.observation - - obs.game_loop = self._game_loop - obs.player_common.CopyFrom(self._player_common) - - obs.score.score_type = 2 - obs.score.score = self._score - obs.score.score_details.CopyFrom(self._score_details) - - def fill(image_data, size, bits): - image_data.bits_per_pixel = bits - image_data.size.y = size[0] - image_data.size.x = size[1] - image_data.data = b'\0' * int(math.ceil(size[0] * size[1] * bits / 8)) - - if 'feature_screen' in self._obs_spec: - for feature in features.SCREEN_FEATURES: - fill(getattr(obs.feature_layer_data.renders, feature.name), self._obs_spec['feature_screen'][1:], 8) - - if 'feature_minimap' in self._obs_spec: - for feature in features.MINIMAP_FEATURES: - fill( - getattr(obs.feature_layer_data.minimap_renders, feature.name), - self._obs_spec['feature_minimap'][1:], 8 - ) - - # if 'rgb_screen' in self._obs_spec: - # fill(obs.render_data.map, self._obs_spec['rgb_screen'][:2], 24) - - # if 'rgb_minimap' in self._obs_spec: - # fill(obs.render_data.minimap, self._obs_spec['rgb_minimap'][:2], 24) - - if self._single_select: - self._single_select.fill(obs.ui_data.single.unit) - - if self._multi_select: - for unit in self._multi_select: - obs.ui_data.multi.units.add(**unit.as_dict()) - - if self._build_queue: - for unit in self._build_queue: - obs.ui_data.production.build_queue.add(**unit.as_dict()) - - if self._production: - for item in self._production: - obs.ui_data.production.production_queue.add(**item) - - if self._feature_units: - for tag, feature_unit in enumerate(self._feature_units, 1): - args = dict(tag=tag) - args.update(feature_unit.as_dict()) - obs.raw_data.units.add(**args) - - return response_observation - - -def fake_raw_obs(): - _features = features.Features( - features.AgentInterfaceFormat( - feature_dimensions=features.Dimensions(screen=(1, 1), minimap=(W, H)), - rgb_dimensions=features.Dimensions(screen=(128, 124), minimap=(1, 1)), - action_space=actions.ActionSpace.RAW, - use_raw_units=True - ), - map_size=point.Point(256, 256) - ) - obs_spec = _features.observation_spec() - builder = Builder(obs_spec).game_loop(0) - feature_units = [ - FeatureResource( - units.Neutral.MineralField, - features.PlayerRelative.NEUTRAL, - owner=16, - pos=common_pb2.Point(x=10, y=10, z=0), - facing=0.0, - radius=1.125, - build_progress=1.0, - cloak=raw_pb2.CloakedUnknown, - is_on_screen=True, - is_blip=False, - is_powered=False, - ), - FeatureResource( - units.Neutral.MineralField, - features.PlayerRelative.NEUTRAL, - owner=16, - pos=common_pb2.Point(x=120, y=10, z=0), - facing=0.0, - radius=1.125, - build_progress=1.0, - cloak=raw_pb2.CloakedUnknown, - is_on_screen=False, - is_blip=False, - is_powered=False, - ), - FeatureResource( - units.Neutral.MineralField, - features.PlayerRelative.NEUTRAL, - owner=16, - pos=common_pb2.Point(x=10, y=120, z=0), - facing=0.0, - radius=1.125, - build_progress=1.0, - cloak=raw_pb2.CloakedUnknown, - is_on_screen=False, - is_blip=False, - is_powered=False, - ), - FeatureResource( - units.Neutral.MineralField, - features.PlayerRelative.NEUTRAL, - owner=16, - pos=common_pb2.Point(x=120, y=120, z=0), - facing=0.0, - radius=1.125, - build_progress=1.0, - cloak=raw_pb2.CloakedUnknown, - is_on_screen=False, - is_blip=False, - is_powered=False, - ), - FeatureUnit( - units.Zerg.Drone, - features.PlayerRelative.SELF, - owner=1, - display_type=raw_pb2.Visible, - pos=common_pb2.Point(x=10, y=11, z=0), - radius=0.375, - facing=3, - cloak=raw_pb2.NotCloaked, - is_selected=False, - is_on_screen=True, - is_blip=False, - health_max=40, - health=40, - is_flying=False, - is_burrowed=False - ), - ] - - builder.feature_units(feature_units) - return builder.build() - - -def get_fake_env_step_data(): - return {'raw_obs': fake_raw_obs(), 'opponent_obs': None, 'action_result': [0]} - - -def get_fake_env_reset_data(): - import os - import pickle - with open(os.path.join(os.path.dirname(__file__), 'fake_reset.pkl'), 'rb') as f: - data = pickle.load(f) - return data diff --git a/dizoo/distar/envs/meta.py b/dizoo/distar/envs/meta.py deleted file mode 100644 index 7f6d137206..0000000000 --- a/dizoo/distar/envs/meta.py +++ /dev/null @@ -1,16 +0,0 @@ -MAX_DELAY = 128 -MAX_ENTITY_NUM = 512 -MAX_SELECTED_UNITS_NUM = 64 -NUM_UNIT_TYPES = 260 -NUM_ACTIONS = 327 -NUM_UPGRADES = 90 -NUM_CUMULATIVE_STAT_ACTIONS = 167 -NUM_BEGINNING_ORDER_ACTIONS = 174 -NUM_UNIT_MIX_ABILITIES = 269 -NUM_QUEUE_ACTION = 49 -NUM_BUFFS = 50 -NUM_ADDON = 9 -DEFAULT_SPATIAL_SIZE = [152, 160] -EFFECT_LENGTH = 100 -UPGRADE_LENGTH = 20 -BEGINNING_ORDER_LENGTH = 20 diff --git a/dizoo/distar/envs/stat.py b/dizoo/distar/envs/stat.py deleted file mode 100644 index cebc3a028c..0000000000 --- a/dizoo/distar/envs/stat.py +++ /dev/null @@ -1,789 +0,0 @@ -from collections import defaultdict -import torch -from .static_data import ACTIONS - - -class Stat(object): - - def __init__(self, race_id): - self._unit_num = defaultdict(int) - self._unit_num['max_unit_num'] = 0 - self._race_id = race_id - for k, v in unit_dict[race_id].items(): - self._unit_num[v] = 0 - self._action_success_count = defaultdict(int) - - def update(self, last_action_type, action_result, observation, game_step): - if action_result < 1: - return - if action_result == 1: - self.count_unit_num(last_action_type) - entity_info, entity_num = observation['entity_info'], observation['entity_num'] - try: - if (entity_info['alliance'][:entity_num] == 1).sum() > 10: - self.success_rate_calc(last_action_type, action_result) - except Exception as e: - print('ERROR_ stat.py', e, entity_info['alliance'], entity_num) - - def success_rate_calc(self, last_action_type, action_result): - action_name = ACTIONS[last_action_type]['name'] - error_msg = action_result_dict[action_result] - self._action_success_count['rate/{}/{}'.format(action_name, error_msg)] += 1 - self._action_success_count['rate/{}/{}'.format(action_name, 'count')] += 1 - - def get_stat_data(self): - data = {} - for k, v in self._unit_num.items(): - if k != 'max_unit_num': - data['units/' + k] = v / self._unit_num['max_unit_num'] - for k, v in self._action_success_count.items(): - action_type = k.split('rate/')[1].split('/')[0] - if 'count' in k: - data[k] = v - else: - data[k] = v / (self._action_success_count['rate/{}/{}'.format(action_type, 'count')] + 1e-6) - return data - - def count_unit_num(self, last_action_type): - unit_name = self.get_build_unit_name(last_action_type, self._race_id) - if not unit_name: - return - self._unit_num[unit_name] += 1 - self._unit_num['max_unit_num'] = max(self._unit_num[unit_name], self._unit_num['max_unit_num']) - - @staticmethod - def get_build_unit_name(action_type, race_id): - action_type = ACTIONS[action_type]['func_id'] - unit_name = unit_dict[race_id].get(action_type, False) - return unit_name - - def set_race_id(self, race_id: int): - self._race_id = race_id - - @property - def unit_num(self): - return self._unit_num - - -unit_dict = { - 'zerg': { - 383: 'BroodLord', - 391: 'Lurker', - 395: 'OverlordTransport', - 396: 'Overseer', - 400: 'Ravager', - 498: 'Baneling', - 501: 'Corruptor', - 503: 'Drone', - 507: 'Hydralisk', - 508: 'Infestor', - 514: 'Mutalisk', - 515: 'Overlord', - 516: 'Queen', - 519: 'Roach', - 522: 'SwarmHost', - 524: 'Ultralisk', - 526: 'Viper', - 528: 'Zergling' - }, - 'terran': { - 499: 'Banshee', - 500: 'Battlecruiser', - 502: 'Cyclone', - 504: 'Ghost', - 505: 'Hellbat', - 506: 'Hellion', - 509: 'Liberator', - 510: 'Marauder', - 511: 'Marine', - 512: 'Medivac', - 517: 'Raven', - 518: 'Reaper', - 520: 'SCV', - 521: 'SiegeTank', - 523: 'Thor', - 525: 'VikingFighter', - 527: 'WidowMine' - }, - 'protoss': { - 86: 'Archon', - 393: 'Mothership', - 54: 'Adept', - 56: 'Carrier', - 62: 'Colossus', - 52: 'DarkTemplar', - 166: 'Disruptor', - 51: 'HighTemplar', - 63: 'Immortal', - 513: 'MothershipCore', - 21: 'Mothership', - 61: 'Observer', - 58: 'Oracle', - 55: 'Phoenix', - 64: 'Probe', - 53: 'Sentry', - 50: 'Stalker', - 59: 'Tempest', - 57: 'VoidRay', - 76: 'Adept', - 74: 'DarkTemplar', - 73: 'HighTemplar', - 60: 'WarpPrism', - 75: 'Sentry', - 72: 'Stalker', - 71: 'Zealot', - 49: 'Zealot' - } -} - -cum_dict = [ - { - 'race': ['zerg', 'terran', 'protoss'], - 'name': 'no_op' - }, { - 'race': ['terran'], - 'name': 'Armory' - }, { - 'race': ['protoss'], - 'name': 'Assimilator' - }, { - 'race': ['zerg'], - 'name': 'BanelingNest' - }, { - 'race': ['terran'], - 'name': 'Barracks' - }, { - 'race': ['terran'], - 'name': 'CommandCenter' - }, { - 'race': ['protoss'], - 'name': 'CyberneticsCore' - }, { - 'race': ['protoss'], - 'name': 'DarkShrine' - }, { - 'race': ['terran'], - 'name': 'EngineeringBay' - }, { - 'race': ['zerg'], - 'name': 'EvolutionChamber' - }, { - 'race': ['zerg'], - 'name': 'Extractor' - }, { - 'race': ['terran'], - 'name': 'Factory' - }, { - 'race': ['protoss'], - 'name': 'FleetBeacon' - }, { - 'race': ['protoss'], - 'name': 'Forge' - }, { - 'race': ['terran'], - 'name': 'FusionCore' - }, { - 'race': ['protoss'], - 'name': 'Gateway' - }, { - 'race': ['terran'], - 'name': 'GhostAcademy' - }, { - 'race': ['zerg'], - 'name': 'Hatchery' - }, { - 'race': ['zerg'], - 'name': 'HydraliskDen' - }, { - 'race': ['zerg'], - 'name': 'InfestationPit' - }, { - 'race': ['protoss'], - 'name': 'Interceptors' - }, { - 'race': ['protoss'], - 'name': 'Interceptors' - }, { - 'race': ['zerg'], - 'name': 'LurkerDen' - }, { - 'race': ['protoss'], - 'name': 'Nexus' - }, { - 'race': ['terran'], - 'name': 'Nuke' - }, { - 'race': ['zerg'], - 'name': 'NydusNetwork' - }, { - 'race': ['zerg'], - 'name': 'NydusWorm' - }, { - 'race': ['terran'], - 'name': 'Reactor' - }, { - 'race': ['terran'], - 'name': 'Reactor' - }, { - 'race': ['terran'], - 'name': 'Refinery' - }, { - 'race': ['zerg'], - 'name': 'RoachWarren' - }, { - 'race': ['protoss'], - 'name': 'RoboticsBay' - }, { - 'race': ['protoss'], - 'name': 'RoboticsFacility' - }, { - 'race': ['terran'], - 'name': 'SensorTower' - }, { - 'race': ['zerg'], - 'name': 'SpawningPool' - }, { - 'race': ['zerg'], - 'name': 'Spire' - }, { - 'race': ['protoss'], - 'name': 'Stargate' - }, { - 'race': ['terran'], - 'name': 'Starport' - }, { - 'race': ['protoss'], - 'name': 'StasisTrap' - }, { - 'race': ['terran'], - 'name': 'TechLab' - }, { - 'race': ['terran'], - 'name': 'TechLab' - }, { - 'race': ['protoss'], - 'name': 'TemplarArchive' - }, { - 'race': ['protoss'], - 'name': 'TwilightCouncil' - }, { - 'race': ['zerg'], - 'name': 'UltraliskCavern' - }, { - 'race': ['protoss'], - 'name': 'Archon' - }, { - 'race': ['zerg'], - 'name': 'BroodLord' - }, { - 'race': ['zerg'], - 'name': 'GreaterSpire' - }, { - 'race': ['zerg'], - 'name': 'Hive' - }, { - 'race': ['zerg'], - 'name': 'Lair' - }, { - 'race': ['zerg'], - 'name': 'LurkerDen' - }, { - 'race': ['zerg'], - 'name': 'Lurker' - }, { - 'race': ['protoss'], - 'name': 'Mothership' - }, { - 'race': ['terran'], - 'name': 'OrbitalCommand' - }, { - 'race': ['zerg'], - 'name': 'OverlordTransport' - }, { - 'race': ['terran'], - 'name': 'PlanetaryFortress' - }, { - 'race': ['zerg'], - 'name': 'Ravager' - }, { - 'race': ['zerg'], - 'name': 'Research_AdaptiveTalons' - }, { - 'race': ['protoss'], - 'name': 'Research_AdeptResonatingGlaives' - }, { - 'race': ['terran'], - 'name': 'Research_AdvancedBallistics' - }, { - 'race': ['zerg'], - 'name': 'Research_AnabolicSynthesis' - }, { - 'race': ['terran'], - 'name': 'Research_BansheeCloakingField' - }, { - 'race': ['terran'], - 'name': 'Research_BansheeHyperflightRotors' - }, { - 'race': ['terran'], - 'name': 'Research_BattlecruiserWeaponRefit' - }, { - 'race': ['protoss'], - 'name': 'Research_Blink' - }, { - 'race': ['zerg'], - 'name': 'Research_Burrow' - }, { - 'race': ['zerg'], - 'name': 'Research_CentrifugalHooks' - }, { - 'race': ['protoss'], - 'name': 'Research_Charge' - }, { - 'race': ['zerg'], - 'name': 'Research_ChitinousPlating' - }, { - 'race': ['terran'], - 'name': 'Research_CombatShield' - }, { - 'race': ['terran'], - 'name': 'Research_ConcussiveShells' - }, { - 'race': ['terran'], - 'name': 'Research_CycloneLockOnDamage' - }, { - 'race': ['terran'], - 'name': 'Research_CycloneRapidFireLaunchers' - }, { - 'race': ['terran'], - 'name': 'Research_DrillingClaws' - }, { - 'race': ['terran'], - 'name': 'Research_EnhancedShockwaves' - }, { - 'race': ['protoss'], - 'name': 'Research_ExtendedThermalLance' - }, { - 'race': ['zerg'], - 'name': 'Research_GlialRegeneration' - }, { - 'race': ['protoss'], - 'name': 'Research_GraviticBooster' - }, { - 'race': ['protoss'], - 'name': 'Research_GraviticDrive' - }, { - 'race': ['zerg'], - 'name': 'Research_GroovedSpines' - }, { - 'race': ['terran'], - 'name': 'Research_HighCapacityFuelTanks' - }, { - 'race': ['terran'], - 'name': 'Research_HiSecAutoTracking' - }, { - 'race': ['terran'], - 'name': 'Research_InfernalPreigniter' - }, { - 'race': ['protoss'], - 'name': 'Research_InterceptorGravitonCatapult' - }, { - 'race': ['zerg'], - 'name': 'Research_MuscularAugments' - }, { - 'race': ['terran'], - 'name': 'Research_NeosteelFrame' - }, { - 'race': ['zerg'], - 'name': 'Research_NeuralParasite' - }, { - 'race': ['zerg'], - 'name': 'Research_PathogenGlands' - }, { - 'race': ['terran'], - 'name': 'Research_PersonalCloaking' - }, { - 'race': ['protoss'], - 'name': 'Research_PhoenixAnionPulseCrystals' - }, { - 'race': ['zerg'], - 'name': 'Research_PneumatizedCarapace' - }, { - 'race': ['protoss'], - 'name': 'Research_ProtossAirArmor' - }, { - 'race': ['protoss'], - 'name': 'Research_ProtossAirWeapons' - }, { - 'race': ['protoss'], - 'name': 'Research_ProtossGroundArmor' - }, { - 'race': ['protoss'], - 'name': 'Research_ProtossGroundWeapons' - }, { - 'race': ['protoss'], - 'name': 'Research_ProtossShields' - }, { - 'race': ['protoss'], - 'name': 'Research_PsiStorm' - }, { - 'race': ['terran'], - 'name': 'Research_RavenCorvidReactor' - }, { - 'race': ['terran'], - 'name': 'Research_RavenRecalibratedExplosives' - }, { - 'race': ['protoss'], - 'name': 'Research_ShadowStrike' - }, { - 'race': ['terran'], - 'name': 'Research_SmartServos' - }, { - 'race': ['terran'], - 'name': 'Research_Stimpack' - }, { - 'race': ['terran'], - 'name': 'Research_TerranInfantryArmor' - }, { - 'race': ['terran'], - 'name': 'Research_TerranInfantryWeapons' - }, { - 'race': ['terran'], - 'name': 'Research_TerranShipWeapons' - }, { - 'race': ['terran'], - 'name': 'Research_TerranStructureArmorUpgrade' - }, { - 'race': ['terran'], - 'name': 'Research_TerranVehicleAndShipPlating' - }, { - 'race': ['terran'], - 'name': 'Research_TerranVehicleWeapons' - }, { - 'race': ['zerg'], - 'name': 'Research_TunnelingClaws' - }, { - 'race': ['protoss'], - 'name': 'Research_WarpGate' - }, { - 'race': ['zerg'], - 'name': 'Research_ZergFlyerArmor' - }, { - 'race': ['zerg'], - 'name': 'Research_ZergFlyerAttack' - }, { - 'race': ['zerg'], - 'name': 'Research_ZergGroundArmor' - }, { - 'race': ['zerg'], - 'name': 'Research_ZerglingAdrenalGlands' - }, { - 'race': ['zerg'], - 'name': 'Research_ZerglingMetabolicBoost' - }, { - 'race': ['zerg'], - 'name': 'Research_ZergMeleeWeapons' - }, { - 'race': ['zerg'], - 'name': 'Research_ZergMissileWeapons' - }, { - 'race': ['protoss'], - 'name': 'Adept' - }, { - 'race': ['zerg'], - 'name': 'Baneling' - }, { - 'race': ['terran'], - 'name': 'Banshee' - }, { - 'race': ['terran'], - 'name': 'Battlecruiser' - }, { - 'race': ['protoss'], - 'name': 'Carrier' - }, { - 'race': ['protoss'], - 'name': 'Colossus' - }, { - 'race': ['zerg'], - 'name': 'Corruptor' - }, { - 'race': ['terran'], - 'name': 'Cyclone' - }, { - 'race': ['protoss'], - 'name': 'DarkTemplar' - }, { - 'race': ['protoss'], - 'name': 'Disruptor' - }, { - 'race': ['terran'], - 'name': 'Ghost' - }, { - 'race': ['terran'], - 'name': 'Hellbat' - }, { - 'race': ['terran'], - 'name': 'Hellion' - }, { - 'race': ['protoss'], - 'name': 'HighTemplar' - }, { - 'race': ['zerg'], - 'name': 'Hydralisk' - }, { - 'race': ['protoss'], - 'name': 'Immortal' - }, { - 'race': ['zerg'], - 'name': 'Infestor' - }, { - 'race': ['terran'], - 'name': 'Liberator' - }, { - 'race': ['terran'], - 'name': 'Marauder' - }, { - 'race': ['terran'], - 'name': 'Marine' - }, { - 'race': ['terran'], - 'name': 'Medivac' - }, { - 'race': ['protoss'], - 'name': 'MothershipCore' - }, { - 'race': ['protoss'], - 'name': 'Mothership' - }, { - 'race': ['zerg'], - 'name': 'Mutalisk' - }, { - 'race': ['protoss'], - 'name': 'Observer' - }, { - 'race': ['protoss'], - 'name': 'Oracle' - }, { - 'race': ['protoss'], - 'name': 'Phoenix' - }, { - 'race': ['zerg'], - 'name': 'Queen' - }, { - 'race': ['terran'], - 'name': 'Raven' - }, { - 'race': ['terran'], - 'name': 'Reaper' - }, { - 'race': ['zerg'], - 'name': 'Roach' - }, { - 'race': ['protoss'], - 'name': 'Sentry' - }, { - 'race': ['terran'], - 'name': 'SiegeTank' - }, { - 'race': ['protoss'], - 'name': 'Stalker' - }, { - 'race': ['zerg'], - 'name': 'SwarmHost' - }, { - 'race': ['protoss'], - 'name': 'Tempest' - }, { - 'race': ['terran'], - 'name': 'Thor' - }, { - 'race': ['zerg'], - 'name': 'Ultralisk' - }, { - 'race': ['terran'], - 'name': 'VikingFighter' - }, { - 'race': ['zerg'], - 'name': 'Viper' - }, { - 'race': ['protoss'], - 'name': 'VoidRay' - }, { - 'race': ['protoss'], - 'name': 'Adept' - }, { - 'race': ['protoss'], - 'name': 'DarkTemplar' - }, { - 'race': ['protoss'], - 'name': 'HighTemplar' - }, { - 'race': ['protoss'], - 'name': 'WarpPrism' - }, { - 'race': ['protoss'], - 'name': 'Sentry' - }, { - 'race': ['protoss'], - 'name': 'Stalker' - }, { - 'race': ['protoss'], - 'name': 'Zealot' - }, { - 'race': ['terran'], - 'name': 'WidowMine' - }, { - 'race': ['protoss'], - 'name': 'Zealot' - }, { - 'race': ['zerg'], - 'name': 'Zergling' - } -] - -action_result_dict = [ - '', 'Success', 'ERROR_NotSupported', 'ERROR_Error', 'ERROR_CantQueueThatOrder', 'ERROR_Retry', 'ERROR_Cooldown', - 'ERROR_QueueIsFull', 'ERROR_RallyQueueIsFull', 'ERROR_NotEnoughMinerals', 'ERROR_NotEnoughVespene', - 'ERROR_NotEnoughTerrazine', 'ERROR_NotEnoughCustom', 'ERROR_NotEnoughFood', 'ERROR_FoodUsageImpossible', - 'ERROR_NotEnoughLife', 'ERROR_NotEnoughShields', 'ERROR_NotEnoughEnergy', 'ERROR_LifeSuppressed', - 'ERROR_ShieldsSuppressed', 'ERROR_EnergySuppressed', 'ERROR_NotEnoughCharges', 'ERROR_CantAddMoreCharges', - 'ERROR_TooMuchMinerals', 'ERROR_TooMuchVespene', 'ERROR_TooMuchTerrazine', 'ERROR_TooMuchCustom', - 'ERROR_TooMuchFood', 'ERROR_TooMuchLife', 'ERROR_TooMuchShields', 'ERROR_TooMuchEnergy', - 'ERROR_MustTargetUnitWithLife', 'ERROR_MustTargetUnitWithShields', 'ERROR_MustTargetUnitWithEnergy', - 'ERROR_CantTrade', 'ERROR_CantSpend', 'ERROR_CantTargetThatUnit', 'ERROR_CouldntAllocateUnit', 'ERROR_UnitCantMove', - 'ERROR_TransportIsHoldingPosition', 'ERROR_BuildTechRequirementsNotMet', 'ERROR_CantFindPlacementLocation', - 'ERROR_CantBuildOnThat', 'ERROR_CantBuildTooCloseToDropOff', 'ERROR_CantBuildLocationInvalid', - 'ERROR_CantSeeBuildLocation', 'ERROR_CantBuildTooCloseToCreepSource', 'ERROR_CantBuildTooCloseToResources', - 'ERROR_CantBuildTooFarFromWater', 'ERROR_CantBuildTooFarFromCreepSource', - 'ERROR_CantBuildTooFarFromBuildPowerSource', 'ERROR_CantBuildOnDenseTerrain', - 'ERROR_CantTrainTooFarFromTrainPowerSource', 'ERROR_CantLandLocationInvalid', 'ERROR_CantSeeLandLocation', - 'ERROR_CantLandTooCloseToCreepSource', 'ERROR_CantLandTooCloseToResources', 'ERROR_CantLandTooFarFromWater', - 'ERROR_CantLandTooFarFromCreepSource', 'ERROR_CantLandTooFarFromBuildPowerSource', - 'ERROR_CantLandTooFarFromTrainPowerSource', 'ERROR_CantLandOnDenseTerrain', 'ERROR_AddOnTooFarFromBuilding', - 'ERROR_MustBuildRefineryFirst', 'ERROR_BuildingIsUnderConstruction', 'ERROR_CantFindDropOff', - 'ERROR_CantLoadOtherPlayersUnits', 'ERROR_NotEnoughRoomToLoadUnit', 'ERROR_CantUnloadUnitsThere', - 'ERROR_CantWarpInUnitsThere', 'ERROR_CantLoadImmobileUnits', 'ERROR_CantRechargeImmobileUnits', - 'ERROR_CantRechargeUnderConstructionUnits', 'ERROR_CantLoadThatUnit', 'ERROR_NoCargoToUnload', - 'ERROR_LoadAllNoTargetsFound', 'ERROR_NotWhileOccupied', 'ERROR_CantAttackWithoutAmmo', 'ERROR_CantHoldAnyMoreAmmo', - 'ERROR_TechRequirementsNotMet', 'ERROR_MustLockdownUnitFirst', 'ERROR_MustTargetUnit', 'ERROR_MustTargetInventory', - 'ERROR_MustTargetVisibleUnit', 'ERROR_MustTargetVisibleLocation', 'ERROR_MustTargetWalkableLocation', - 'ERROR_MustTargetPawnableUnit', 'ERROR_YouCantControlThatUnit', 'ERROR_YouCantIssueCommandsToThatUnit', - 'ERROR_MustTargetResources', 'ERROR_RequiresHealTarget', 'ERROR_RequiresRepairTarget', 'ERROR_NoItemsToDrop', - 'ERROR_CantHoldAnyMoreItems', 'ERROR_CantHoldThat', 'ERROR_TargetHasNoInventory', 'ERROR_CantDropThisItem', - 'ERROR_CantMoveThisItem', 'ERROR_CantPawnThisUnit', 'ERROR_MustTargetCaster', 'ERROR_CantTargetCaster', - 'ERROR_MustTargetOuter', 'ERROR_CantTargetOuter', 'ERROR_MustTargetYourOwnUnits', 'ERROR_CantTargetYourOwnUnits', - 'ERROR_MustTargetFriendlyUnits', 'ERROR_CantTargetFriendlyUnits', 'ERROR_MustTargetNeutralUnits', - 'ERROR_CantTargetNeutralUnits', 'ERROR_MustTargetEnemyUnits', 'ERROR_CantTargetEnemyUnits', - 'ERROR_MustTargetAirUnits', 'ERROR_CantTargetAirUnits', 'ERROR_MustTargetGroundUnits', - 'ERROR_CantTargetGroundUnits', 'ERROR_MustTargetStructures', 'ERROR_CantTargetStructures', - 'ERROR_MustTargetLightUnits', 'ERROR_CantTargetLightUnits', 'ERROR_MustTargetArmoredUnits', - 'ERROR_CantTargetArmoredUnits', 'ERROR_MustTargetBiologicalUnits', 'ERROR_CantTargetBiologicalUnits', - 'ERROR_MustTargetHeroicUnits', 'ERROR_CantTargetHeroicUnits', 'ERROR_MustTargetRoboticUnits', - 'ERROR_CantTargetRoboticUnits', 'ERROR_MustTargetMechanicalUnits', 'ERROR_CantTargetMechanicalUnits', - 'ERROR_MustTargetPsionicUnits', 'ERROR_CantTargetPsionicUnits', 'ERROR_MustTargetMassiveUnits', - 'ERROR_CantTargetMassiveUnits', 'ERROR_MustTargetMissile', 'ERROR_CantTargetMissile', 'ERROR_MustTargetWorkerUnits', - 'ERROR_CantTargetWorkerUnits', 'ERROR_MustTargetEnergyCapableUnits', 'ERROR_CantTargetEnergyCapableUnits', - 'ERROR_MustTargetShieldCapableUnits', 'ERROR_CantTargetShieldCapableUnits', 'ERROR_MustTargetFlyers', - 'ERROR_CantTargetFlyers', 'ERROR_MustTargetBuriedUnits', 'ERROR_CantTargetBuriedUnits', - 'ERROR_MustTargetCloakedUnits', 'ERROR_CantTargetCloakedUnits', 'ERROR_MustTargetUnitsInAStasisField', - 'ERROR_CantTargetUnitsInAStasisField', 'ERROR_MustTargetUnderConstructionUnits', - 'ERROR_CantTargetUnderConstructionUnits', 'ERROR_MustTargetDeadUnits', 'ERROR_CantTargetDeadUnits', - 'ERROR_MustTargetRevivableUnits', 'ERROR_CantTargetRevivableUnits', 'ERROR_MustTargetHiddenUnits', - 'ERROR_CantTargetHiddenUnits', 'ERROR_CantRechargeOtherPlayersUnits', 'ERROR_MustTargetHallucinations', - 'ERROR_CantTargetHallucinations', 'ERROR_MustTargetInvulnerableUnits', 'ERROR_CantTargetInvulnerableUnits', - 'ERROR_MustTargetDetectedUnits', 'ERROR_CantTargetDetectedUnits', 'ERROR_CantTargetUnitWithEnergy', - 'ERROR_CantTargetUnitWithShields', 'ERROR_MustTargetUncommandableUnits', 'ERROR_CantTargetUncommandableUnits', - 'ERROR_MustTargetPreventDefeatUnits', 'ERROR_CantTargetPreventDefeatUnits', 'ERROR_MustTargetPreventRevealUnits', - 'ERROR_CantTargetPreventRevealUnits', 'ERROR_MustTargetPassiveUnits', 'ERROR_CantTargetPassiveUnits', - 'ERROR_MustTargetStunnedUnits', 'ERROR_CantTargetStunnedUnits', 'ERROR_MustTargetSummonedUnits', - 'ERROR_CantTargetSummonedUnits', 'ERROR_MustTargetUser1', 'ERROR_CantTargetUser1', - 'ERROR_MustTargetUnstoppableUnits', 'ERROR_CantTargetUnstoppableUnits', 'ERROR_MustTargetResistantUnits', - 'ERROR_CantTargetResistantUnits', 'ERROR_MustTargetDazedUnits', 'ERROR_CantTargetDazedUnits', 'ERROR_CantLockdown', - 'ERROR_CantMindControl', 'ERROR_MustTargetDestructibles', 'ERROR_CantTargetDestructibles', 'ERROR_MustTargetItems', - 'ERROR_CantTargetItems', 'ERROR_NoCalldownAvailable', 'ERROR_WaypointListFull', 'ERROR_MustTargetRace', - 'ERROR_CantTargetRace', 'ERROR_MustTargetSimilarUnits', 'ERROR_CantTargetSimilarUnits', - 'ERROR_CantFindEnoughTargets', 'ERROR_AlreadySpawningLarva', 'ERROR_CantTargetExhaustedResources', - 'ERROR_CantUseMinimap', 'ERROR_CantUseInfoPanel', 'ERROR_OrderQueueIsFull', 'ERROR_CantHarvestThatResource', - 'ERROR_HarvestersNotRequired', 'ERROR_AlreadyTargeted', 'ERROR_CantAttackWeaponsDisabled', - 'ERROR_CouldntReachTarget', 'ERROR_TargetIsOutOfRange', 'ERROR_TargetIsTooClose', 'ERROR_TargetIsOutOfArc', - 'ERROR_CantFindTeleportLocation', 'ERROR_InvalidItemClass', 'ERROR_CantFindCancelOrder' -] -NUM_ACTION_RESULT = 214 - -ACTION_RACE_MASK = { - 'zerg': torch.tensor( - [ - False, False, True, True, True, True, False, False, True, True, True, True, False, False, False, False, - True, False, False, False, True, False, False, False, True, True, False, False, False, False, False, False, - True, True, True, False, False, True, False, False, False, True, True, False, False, False, False, False, - True, False, False, False, False, True, True, True, True, False, False, False, False, False, False, False, - False, True, True, True, True, True, True, True, False, False, False, True, False, False, False, False, - True, False, False, False, False, False, True, True, False, False, True, False, False, True, True, False, - False, False, False, False, False, False, True, True, False, False, False, False, False, True, False, False, - True, False, False, True, False, False, False, False, False, False, False, False, False, True, True, True, - True, False, False, False, False, True, True, False, False, False, False, False, False, False, False, False, - False, False, False, False, False, False, False, False, False, False, True, True, True, False, False, False, - True, False, True, False, True, False, False, True, True, False, False, True, True, False, False, False, - True, True, True, True, False, True, True, False, False, False, False, False, False, False, True, False, - False, False, False, False, False, True, True, True, True, True, True, True, True, True, False, False, True, - False, False, False, False, True, True, False, True, False, False, False, False, False, False, False, True, - False, False, True, False, False, False, False, True, False, True, True, False, False, True, False, False, - False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, - True, False, True, True, True, True, True, True, True, True, True, True, False, True, False, False, False, - False, True, False, False, False, True, False, False, False, False, True, False, True, False, False, False, - False, False, False, True, False, False, True, False, False, True, False, False, True, False, False, False, - False, True, False, False, True, False, True, False, False, False, False, False, False, False, False, False, - False, True, True, True, True, True - ] - ), - 'terran': torch.tensor( - [ - False, False, True, True, False, False, True, True, False, False, True, True, False, False, True, False, - False, True, True, True, False, False, False, True, False, False, True, False, False, True, False, True, - False, False, False, False, False, False, True, False, True, False, False, False, False, True, True, True, - False, False, False, True, False, False, False, False, False, False, True, False, True, True, True, False, - False, False, True, True, True, True, True, False, False, True, True, False, False, False, True, True, - False, False, False, False, False, False, False, False, True, True, False, False, False, False, False, True, - False, False, True, True, False, False, False, False, True, True, True, True, True, False, False, True, - False, True, False, False, False, False, True, True, True, False, False, True, True, False, False, False, - True, True, True, True, False, False, False, False, True, True, True, True, False, False, False, False, - False, False, False, False, False, False, False, False, False, True, True, True, True, True, True, True, - True, False, False, False, False, True, True, False, False, True, True, False, False, False, False, True, - False, False, False, False, True, False, False, True, True, True, False, True, True, True, False, True, - True, False, False, False, False, True, True, True, True, True, True, True, True, False, False, True, False, - True, True, True, False, False, False, False, False, True, True, True, True, True, True, False, False, - False, False, False, True, True, True, False, False, True, False, False, True, False, False, False, False, - False, False, False, False, True, True, False, True, True, True, True, True, True, True, True, False, False, - False, False, False, False, False, False, False, True, True, True, False, False, True, True, False, False, - False, True, False, False, False, True, True, True, False, False, False, False, True, True, True, True, - False, False, False, False, False, False, False, False, False, True, True, False, True, False, True, False, - False, False, True, False, True, False, False, False, False, False, False, False, False, False, True, False, - False, True, True, True, True - ] - ), - 'protoss': torch.tensor( - [ - False, False, True, True, False, False, False, False, False, False, False, False, True, True, False, True, - False, False, False, False, False, True, True, False, False, False, False, True, True, False, True, False, - False, False, False, True, True, False, False, True, False, False, False, True, True, False, False, False, - False, True, True, False, True, False, False, False, False, True, False, True, False, False, False, True, - True, False, False, False, False, True, True, False, True, False, False, False, True, True, False, False, - False, True, True, True, True, True, False, False, False, False, False, True, True, False, False, False, - True, True, False, False, True, True, False, False, False, False, False, False, False, False, True, False, - False, False, True, False, True, True, False, False, False, True, True, False, False, False, False, False, - True, False, False, False, True, False, False, True, False, False, False, False, True, True, True, True, - True, True, True, True, True, True, True, True, True, False, True, True, True, False, False, False, True, - True, False, True, False, False, False, False, False, False, False, False, False, True, True, False, False, - False, False, False, False, False, False, False, False, False, True, False, False, False, False, False, - False, True, True, True, True, True, True, True, True, True, True, True, True, False, True, False, False, - False, False, False, True, False, False, True, False, False, False, False, False, False, False, True, False, - True, True, False, False, False, False, True, False, False, False, False, False, True, False, True, True, - True, True, True, True, False, False, True, False, False, False, False, False, False, False, False, False, - True, False, False, False, False, False, False, False, True, True, True, True, False, False, False, True, - True, False, False, True, True, False, False, False, False, True, False, True, False, False, False, False, - False, True, True, False, True, True, False, True, True, False, False, False, False, False, True, False, - True, False, True, False, False, False, False, True, True, True, True, True, True, True, True, False, True, - False, True, True, False, True - ] - ) -} diff --git a/dizoo/distar/envs/static_data.py b/dizoo/distar/envs/static_data.py deleted file mode 100644 index 824497efae..0000000000 --- a/dizoo/distar/envs/static_data.py +++ /dev/null @@ -1,2599 +0,0 @@ -import six -import torch -import numpy as np -from collections import defaultdict - -RACE_DICT = { - 1: 'terran', - 2: 'zerg', - 3: 'protoss', - 4: 'random', -} - -ACTION_INFO_MASK = \ - { - 0: {'name': 'no_op', 'func_type': 'raw_no_op', 'ability_id': None, 'general_id': None, 'goal': 'other', 'special_goal': None, 'queued': False, 'selected_units': False, 'target_unit': False, 'target_location': False}, - 168: {'name': 'raw_move_camera', 'func_type': 'raw_move_camera', 'ability_id': None, 'general_id': None, 'goal': 'other', 'special_goal': None, 'queued': False, 'selected_units': False, 'target_unit': False, 'target_location': True}, - 2: {'name': 'Attack_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3674, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BATTLECRUISER', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MEDIVAC', 'TERRAN_MISSILETURRET', 'TERRAN_MULE', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_RAVEN', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'TERRAN_WIDOWMINE', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CHANGELING', 'ZERG_CHANGELINGMARINE', 'ZERG_CHANGELINGMARINESHIELD', 'ZERG_CHANGELINGZEALOT', 'ZERG_CHANGELINGZERGLING', 'ZERG_CHANGELINGZERGLINGWINGS', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTOR', 'ZERG_INFESTORBURROWED', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMP', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_OVERLORD', 'ZERG_OVERLORDTRANSPORT', 'ZERG_OVERSEER', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_ROACHBURROWED', 'ZERG_SPINECRAWLER', 'ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLER', 'ZERG_SPORECRAWLERUPROOTED', 'ZERG_SWARMHOSTMP', 'ZERG_ULTRALISK', 'ZERG_VIPER', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ADEPTPHASESHIFT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 57, 24, 692, 50, 53, 484, 689, 734, 51, 48, 54, 23, 268, 130, 56, 49, 45, 33, 32, 52, 691, 34, 35, 498, 9, 289, 114, 12, 15, 14, 13, 17, 16, 112, 104, 107, 111, 127, 7, 489, 693, 502, 503, 108, 106, 893, 129, 126, 688, 110, 118, 98, 139, 99, 140, 494, 109, 499, 105, 311, 801, 141, 79, 4, 76, 694, 733, 75, 83, 85, 10, 488, 82, 495, 78, 66, 84, 894, 77, 74, 496, 80, 81, 73]}, - 3: {'name': 'Attack_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3674, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BATTLECRUISER', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MEDIVAC', 'TERRAN_MISSILETURRET', 'TERRAN_MULE', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_RAVEN', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'TERRAN_WIDOWMINE', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CHANGELING', 'ZERG_CHANGELINGMARINE', 'ZERG_CHANGELINGMARINESHIELD', 'ZERG_CHANGELINGZEALOT', 'ZERG_CHANGELINGZERGLING', 'ZERG_CHANGELINGZERGLINGWINGS', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTOR', 'ZERG_INFESTORBURROWED', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMP', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_OVERLORD', 'ZERG_OVERLORDTRANSPORT', 'ZERG_OVERSEER', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_ROACHBURROWED', 'ZERG_SPINECRAWLER', 'ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLER', 'ZERG_SPORECRAWLERUPROOTED', 'ZERG_SWARMHOSTMP', 'ZERG_ULTRALISK', 'ZERG_VIPER', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ADEPTPHASESHIFT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 57, 24, 692, 50, 53, 484, 689, 734, 51, 48, 54, 23, 268, 130, 56, 49, 45, 33, 32, 52, 691, 34, 35, 498, 9, 289, 114, 12, 15, 14, 13, 17, 16, 112, 104, 107, 111, 127, 7, 489, 693, 502, 503, 108, 106, 893, 129, 126, 688, 110, 118, 98, 139, 99, 140, 494, 109, 499, 105, 311, 801, 141, 79, 4, 76, 694, 733, 75, 83, 85, 10, 488, 82, 495, 78, 66, 84, 894, 77, 74, 496, 80, 81, 73]}, - 4: {'name': 'Attack_Attack_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 23, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MISSILETURRET', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_SPINECRAWLER', 'ZERG_SPORECRAWLER', 'ZERG_ULTRALISK', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 24, 692, 50, 53, 484, 689, 734, 51, 48, 23, 130, 49, 45, 33, 32, 52, 691, 34, 35, 9, 289, 114, 112, 104, 107, 7, 489, 693, 503, 108, 126, 688, 110, 98, 99, 109, 105, 311, 141, 79, 4, 76, 83, 85, 10, 488, 78, 66, 84, 894, 77, 74, 496, 80, 73]}, - 6: {'name': 'Attack_AttackBuilding_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2048, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MISSILETURRET', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_SPINECRAWLER', 'ZERG_SPORECRAWLER', 'ZERG_ULTRALISK', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 24, 692, 50, 53, 484, 689, 734, 51, 48, 23, 130, 49, 45, 33, 32, 52, 691, 34, 35, 9, 289, 114, 112, 104, 107, 7, 489, 693, 503, 108, 126, 688, 110, 98, 99, 109, 105, 311, 141, 79, 4, 76, 83, 85, 10, 488, 78, 66, 84, 894, 77, 74, 496, 80, 73]}, - 5: {'name': 'Attack_Attack_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 23, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MISSILETURRET', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_SPINECRAWLER', 'ZERG_SPORECRAWLER', 'ZERG_ULTRALISK', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 24, 692, 50, 53, 484, 689, 734, 51, 48, 23, 130, 49, 45, 33, 32, 52, 691, 34, 35, 9, 289, 114, 112, 104, 107, 7, 489, 693, 503, 108, 126, 688, 110, 98, 99, 109, 105, 311, 141, 79, 4, 76, 83, 85, 10, 488, 78, 66, 84, 894, 77, 74, 496, 80, 73]}, - 7: {'name': 'Attack_AttackBuilding_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2048, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MISSILETURRET', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_SPINECRAWLER', 'ZERG_SPORECRAWLER', 'ZERG_ULTRALISK', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 24, 692, 50, 53, 484, 689, 734, 51, 48, 23, 130, 49, 45, 33, 32, 52, 691, 34, 35, 9, 289, 114, 112, 104, 107, 7, 489, 693, 503, 108, 126, 688, 110, 98, 99, 109, 105, 311, 141, 79, 4, 76, 83, 85, 10, 488, 78, 66, 84, 894, 77, 74, 496, 80, 73]}, - 539: {'name': 'Attack_Battlecruiser_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3771, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_BATTLECRUISER'], 'avail_unit_type_id': [57]}, - 540: {'name': 'Attack_Battlecruiser_unit', 'func_type': 'raw_cmd_unit', 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'ZERG_HYDRALISK', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_SPINECRAWLER', 'ZERG_SPORECRAWLER', 'ZERG_ULTRALISK', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_PHOENIX', 'PROTOSS_PHOTONCANNON', 'PROTOSS_PROBE', 'PROTOSS_PYLONOVERCHARGED', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [31, 55, 24, 692, 50, 53, 484, 689, 734, 51, 48, 23, 130, 49, 45, 33, 32, 52, 691, 34, 35, 9, 289, 114, 112, 104, 107, 7, 489, 693, 503, 108, 126, 688, 110, 98, 99, 109, 105, 311, 141, 79, 4, 76, 83, 85, 10, 488, 78, 66, 84, 894, 77, 74, 496, 80, 73]}, - 9: {'name': 'Attack_Redirect_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 1682, 'general_id': 3674, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_AUTOTURRET', 'TERRAN_BANSHEE', 'TERRAN_BUNKER', 'TERRAN_CYCLONE', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_LIBERATORAG', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MISSILETURRET', 'TERRAN_PLANETARYFORTRESS', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_SIEGETANKSIEGED', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMPBURROWED', 'ZERG_MUTALISK', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_SPINECRAWLER', 'ZERG_SPORECRAWLER', 'ZERG_ULTRALISK', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 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'target_location': False, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, - 172: {'name': 'Behavior_CloakOn_quick', 'func_type': 'raw_cmd', 'ability_id': 3676, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_BANSHEE', 'TERRAN_GHOST'], 'avail_unit_type_id': [55, 50]}, - 173: {'name': 'Behavior_CloakOn_Banshee_quick', 'func_type': 'raw_cmd', 'ability_id': 392, 'general_id': 3676, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_BANSHEE'], 'avail_unit_type_id': [55]}, - 174: {'name': 'Behavior_CloakOn_Ghost_quick', 'func_type': 'raw_cmd', 'ability_id': 382, 'general_id': 3676, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, - 175: {'name': 'Behavior_GenerateCreepOff_quick', 'func_type': 'raw_cmd', 'ability_id': 1693, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_OVERLORD', 'ZERG_OVERLORDTRANSPORT'], 'avail_unit_type_id': [106, 893]}, - 176: {'name': 'Behavior_GenerateCreepOn_quick', 'func_type': 'raw_cmd', 'ability_id': 1692, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_OVERLORD', 'ZERG_OVERLORDTRANSPORT'], 'avail_unit_type_id': [106, 893]}, - 178: {'name': 'Behavior_HoldFireOff_Ghost_quick', 'func_type': 'raw_cmd', 'ability_id': 38, 'general_id': 3689, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, - 179: {'name': 'Behavior_HoldFireOff_Lurker_quick', 'func_type': 'raw_cmd', 'ability_id': 2552, 'general_id': 3689, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_LURKERMP'], 'avail_unit_type_id': [502]}, - 177: {'name': 'Behavior_HoldFireOff_quick', 'func_type': 'raw_cmd', 'ability_id': 3689, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_GHOST', 'ZERG_LURKERMPBURROWED'], 'avail_unit_type_id': [50, 503]}, - 181: {'name': 'Behavior_HoldFireOn_Ghost_quick', 'func_type': 'raw_cmd', 'ability_id': 36, 'general_id': 3688, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, - 182: {'name': 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'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_DRONE'], 'avail_unit_type_id': [104]}, - 185: {'name': 'Build_Barracks_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 321, 'general_id': 0, 'goal': 'build', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_SCV'], 'avail_unit_type_id': [45]}, - 186: {'name': 'Build_Bunker_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 324, 'general_id': 0, 'goal': 'build', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_SCV'], 'avail_unit_type_id': [45]}, - 187: {'name': 'Build_CommandCenter_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 318, 'general_id': 0, 'goal': 'build', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_SCV'], 'avail_unit_type_id': [45]}, - 188: {'name': 'Build_CreepTumor_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3691, 'general_id': 0, 'goal': 'build', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_CREEPTUMORBURROWED', 'ZERG_QUEEN'], 'avail_unit_type_id': [137, 126]}, - 189: {'name': 'Build_CreepTumor_Queen_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1694, 'general_id': 3691, 'goal': 'build', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_QUEEN'], 'avail_unit_type_id': [126]}, - 190: {'name': 'Build_CreepTumor_Tumor_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1733, 'general_id': 3691, 'goal': 'build', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_CREEPTUMORBURROWED'], 'avail_unit_type_id': [137]}, - 47: {'name': 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[690]}, - 262: {'name': 'BurrowUp_Roach_autocast', 'func_type': 'raw_autocast', 'ability_id': 1388, 'general_id': 3662, 'goal': 'other', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_ROACHBURROWED'], 'avail_unit_type_id': [118]}, - 261: {'name': 'BurrowUp_Roach_quick', 'func_type': 'raw_cmd', 'ability_id': 1388, 'general_id': 3662, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_ROACHBURROWED'], 'avail_unit_type_id': [118]}, - 263: {'name': 'BurrowUp_SwarmHost_quick', 'func_type': 'raw_cmd', 'ability_id': 2016, 'general_id': 3662, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_SWARMHOSTBURROWEDMP'], 'avail_unit_type_id': [493]}, - 265: {'name': 'BurrowUp_Ultralisk_autocast', 'func_type': 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{'name': 'Cancel_MorphBroodlord_quick', 'func_type': 'raw_cmd', 'ability_id': 1373, 'general_id': 3659, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_BROODLORDCOCOON'], 'avail_unit_type_id': [113]}, - 275: {'name': 'Cancel_MorphGreaterSpire_quick', 'func_type': 'raw_cmd', 'ability_id': 1221, 'general_id': 3659, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_SPIRE'], 'avail_unit_type_id': [92]}, - 276: {'name': 'Cancel_MorphHive_quick', 'func_type': 'raw_cmd', 'ability_id': 1219, 'general_id': 3659, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_LAIR'], 'avail_unit_type_id': [100]}, - 277: {'name': 'Cancel_MorphLair_quick', 'func_type': 'raw_cmd', 'ability_id': 1217, 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'func_type': 'raw_cmd', 'ability_id': 306, 'general_id': 3671, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': [], 'avail_unit_type_id': []}, - 289: {'name': 'Cancel_QueueAddOn_quick', 'func_type': 'raw_cmd', 'ability_id': 312, 'general_id': 3671, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_BARRACKS', 'TERRAN_FACTORY', 'TERRAN_STARPORT'], 'avail_unit_type_id': [21, 27, 28]}, - 132: {'name': 'Cancel_QueueCancelToSelection_quick', 'func_type': 'raw_cmd', 'ability_id': 308, 'general_id': 3671, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': [], 'avail_unit_type_id': []}, - 134: {'name': 'Cancel_QueuePassiveCancelToSelection_quick', 'func_type': 'raw_cmd', 'ability_id': 1833, 'general_id': 3671, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': [], 'avail_unit_type_id': []}, - 133: {'name': 'Cancel_QueuePassive_quick', 'func_type': 'raw_cmd', 'ability_id': 1831, 'general_id': 3671, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': [], 'avail_unit_type_id': []}, - 290: {'name': 'Cancel_SpineCrawlerRoot_quick', 'func_type': 'raw_cmd', 'ability_id': 1730, 'general_id': 3659, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_SPINECRAWLERUPROOTED'], 'avail_unit_type_id': [139]}, - 291: {'name': 'Cancel_SporeCrawlerRoot_quick', 'func_type': 'raw_cmd', 'ability_id': 1732, 'general_id': 3659, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_SPORECRAWLERUPROOTED'], 'avail_unit_type_id': [140]}, - 292: {'name': 'Cancel_StarportAddOn_quick', 'func_type': 'raw_cmd', 'ability_id': 517, 'general_id': 3659, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_STARPORTREACTOR', 'TERRAN_STARPORTTECHLAB'], 'avail_unit_type_id': [42, 41]}, - 127: {'name': 'Cancel_StasisTrap_quick', 'func_type': 'raw_cmd', 'ability_id': 2535, 'general_id': 3659, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_ORACLE'], 'avail_unit_type_id': [495]}, - 128: {'name': 'Cancel_VoidRayPrismaticAlignment_quick', 'func_type': 'raw_cmd', 'ability_id': 3707, 'general_id': 3659, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_VOIDRAY'], 'avail_unit_type_id': [80]}, - 293: {'name': 'Effect_Abduct_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2067, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_VIPER'], 'avail_unit_type_id': [499]}, - 96: {'name': 'Effect_AdeptPhaseShift_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2544, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_ADEPT'], 'avail_unit_type_id': [311]}, - 294: {'name': 'Effect_AntiArmorMissile_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3753, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_RAVEN'], 'avail_unit_type_id': [56]}, - 295: {'name': 'Effect_AutoTurret_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1764, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_RAVEN'], 'avail_unit_type_id': [56]}, - 296: {'name': 'Effect_BlindingCloud_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2063, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_VIPER'], 'avail_unit_type_id': [499]}, - 111: {'name': 'Effect_Blink_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3687, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_DARKTEMPLAR', 'PROTOSS_STALKER'], 'avail_unit_type_id': [76, 74]}, - 135: {'name': 'Effect_Blink_Stalker_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1442, 'general_id': 3687, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_STALKER'], 'avail_unit_type_id': [74]}, - 112: {'name': 'Effect_Blink_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3687, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_DARKTEMPLAR', 'PROTOSS_STALKER'], 'avail_unit_type_id': [76, 74]}, - 297: {'name': 'Effect_CalldownMULE_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 171, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_ORBITALCOMMAND'], 'avail_unit_type_id': [132]}, - 298: {'name': 'Effect_CalldownMULE_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 171, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_ORBITALCOMMAND'], 'avail_unit_type_id': [132]}, - 299: {'name': 'Effect_CausticSpray_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2324, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_CORRUPTOR'], 'avail_unit_type_id': [112]}, - 302: {'name': 'Effect_Charge_autocast', 'func_type': 'raw_autocast', 'ability_id': 1819, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_ZEALOT'], 'avail_unit_type_id': [73]}, - 300: {'name': 'Effect_Charge_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1819, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_ZEALOT'], 'avail_unit_type_id': [73]}, - 301: {'name': 'Effect_Charge_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 1819, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_ZEALOT'], 'avail_unit_type_id': [73]}, - 122: {'name': 'Effect_ChronoBoostEnergyCost_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3755, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_NEXUS'], 'avail_unit_type_id': [59]}, - 33: {'name': 'Effect_ChronoBoost_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 261, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_NEXUS'], 'avail_unit_type_id': [59]}, - 303: {'name': 'Effect_Contaminate_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 1825, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_OVERSEER'], 'avail_unit_type_id': [129]}, - 304: {'name': 'Effect_CorrosiveBile_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2338, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_RAVAGER'], 'avail_unit_type_id': [688]}, - 305: {'name': 'Effect_EMP_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1628, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, - 306: {'name': 'Effect_EMP_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 1628, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, - 307: {'name': 'Effect_Explode_quick', 'func_type': 'raw_cmd', 'ability_id': 42, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_BANELING', 'ZERG_BANELINGBURROWED'], 'avail_unit_type_id': [9, 115]}, - 157: {'name': 'Effect_Feedback_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 140, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_HIGHTEMPLAR'], 'avail_unit_type_id': [75]}, - 79: {'name': 'Effect_ForceField_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1526, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 308: {'name': 'Effect_FungalGrowth_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 74, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_INFESTOR', 'ZERG_INFESTORBURROWED'], 'avail_unit_type_id': [111, 127]}, - 309: {'name': 'Effect_FungalGrowth_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 74, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_INFESTOR', 'ZERG_INFESTORBURROWED'], 'avail_unit_type_id': [111, 127]}, - 310: {'name': 'Effect_GhostSnipe_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2714, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, - 32: {'name': 'Effect_GravitonBeam_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 173, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_PHOENIX'], 'avail_unit_type_id': [78]}, - 20: {'name': 'Effect_GuardianShield_quick', 'func_type': 'raw_cmd', 'ability_id': 76, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 312: {'name': 'Effect_Heal_autocast', 'func_type': 'raw_autocast', 'ability_id': 386, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_MEDIVAC'], 'avail_unit_type_id': [54]}, - 311: {'name': 'Effect_Heal_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 386, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_MEDIVAC'], 'avail_unit_type_id': [54]}, - 313: {'name': 'Effect_ImmortalBarrier_autocast', 'func_type': 'raw_autocast', 'ability_id': 2328, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_IMMORTAL'], 'avail_unit_type_id': [83]}, - 91: {'name': 'Effect_ImmortalBarrier_quick', 'func_type': 'raw_cmd', 'ability_id': 2328, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_IMMORTAL'], 'avail_unit_type_id': [83]}, - 314: {'name': 'Effect_InfestedTerrans_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 247, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_INFESTOR', 'ZERG_INFESTORBURROWED'], 'avail_unit_type_id': [111, 127]}, - 315: {'name': 'Effect_InjectLarva_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 251, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_QUEEN'], 'avail_unit_type_id': [126]}, - 316: {'name': 'Effect_InterferenceMatrix_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3747, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_RAVEN'], 'avail_unit_type_id': [56]}, - 317: {'name': 'Effect_KD8Charge_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2588, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_REAPER'], 'avail_unit_type_id': [49]}, - 538: {'name': 'Effect_KD8Charge_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2588, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_REAPER'], 'avail_unit_type_id': [49]}, - 318: {'name': 'Effect_LockOn_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2350, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_CYCLONE'], 'avail_unit_type_id': [692]}, - 541: {'name': 'Effect_LockOn_autocast', 'func_type': 'raw_autocast', 'ability_id': 2350, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_CYCLONE'], 'avail_unit_type_id': [692]}, - 319: {'name': 'Effect_LocustSwoop_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2387, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_LOCUSTMPFLYING'], 'avail_unit_type_id': [693]}, - 110: {'name': 'Effect_MassRecall_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3686, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE'], 'avail_unit_type_id': [10, 488]}, - 136: {'name': 'Effect_MassRecall_Mothership_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2368, 'general_id': 3686, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_MOTHERSHIP'], 'avail_unit_type_id': [10]}, - 162: {'name': 'Effect_MassRecall_Nexus_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3757, 'general_id': 3686, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_NEXUS'], 'avail_unit_type_id': [59]}, - 137: {'name': 'Effect_MassRecall_StrategicRecall_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 142, 'general_id': 3686, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_MOTHERSHIP'], 'avail_unit_type_id': [10]}, - 320: {'name': 'Effect_MedivacIgniteAfterburners_quick', 'func_type': 'raw_cmd', 'ability_id': 2116, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_MEDIVAC'], 'avail_unit_type_id': [54]}, - 321: {'name': 'Effect_NeuralParasite_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 249, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_INFESTOR', 'ZERG_INFESTORBURROWED'], 'avail_unit_type_id': [111, 127]}, - 322: {'name': 'Effect_NukeCalldown_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1622, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_GHOST'], 'avail_unit_type_id': [50]}, - 90: {'name': 'Effect_OracleRevelation_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2146, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_ORACLE'], 'avail_unit_type_id': [495]}, - 323: {'name': 'Effect_ParasiticBomb_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2542, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_VIPER'], 'avail_unit_type_id': [499]}, - 65: {'name': 'Effect_PsiStorm_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 1036, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_HIGHTEMPLAR'], 'avail_unit_type_id': [75]}, - 167: {'name': 'Effect_PurificationNova_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2346, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_DISRUPTOR'], 'avail_unit_type_id': [694]}, - 324: {'name': 'Effect_Repair_autocast', 'func_type': 'raw_autocast', 'ability_id': 3685, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_MULE', 'TERRAN_SCV', 'TERRAN_REPAIRDRONE'], 'avail_unit_type_id': [268, 45, 1913]}, - 108: {'name': 'Effect_Repair_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3685, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_MULE', 'TERRAN_SCV', 'TERRAN_REPAIRDRONE'], 'avail_unit_type_id': [268, 45, 1913]}, - 109: {'name': 'Effect_Repair_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3685, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_MULE', 'TERRAN_SCV', 'TERRAN_REPAIRDRONE'], 'avail_unit_type_id': [268, 45, 1913]}, - 326: {'name': 'Effect_Repair_Mule_autocast', 'func_type': 'raw_autocast', 'ability_id': 78, 'general_id': 3685, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_MULE'], 'avail_unit_type_id': [268]}, - 325: {'name': 'Effect_Repair_Mule_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 78, 'general_id': 3685, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_MULE'], 'avail_unit_type_id': [268]}, - 328: {'name': 'Effect_Repair_RepairDrone_autocast', 'func_type': 'raw_autocast', 'ability_id': 3751, 'general_id': 3685, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_REPAIRDRONE'], 'avail_unit_type_id': [1913]}, - 327: {'name': 'Effect_Repair_RepairDrone_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3751, 'general_id': 3685, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_REPAIRDRONE'], 'avail_unit_type_id': [1913]}, - 330: {'name': 'Effect_Repair_SCV_autocast', 'func_type': 'raw_autocast', 'ability_id': 316, 'general_id': 3685, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_SCV'], 'avail_unit_type_id': [45]}, - 329: {'name': 'Effect_Repair_SCV_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 316, 'general_id': 3685, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_SCV'], 'avail_unit_type_id': [45]}, - 331: {'name': 'Effect_Restore_autocast', 'func_type': 'raw_autocast', 'ability_id': 3765, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SHIELDBATTERY'], 'avail_unit_type_id': [1910]}, - 161: {'name': 'Effect_Restore_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3765, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['PROTOSS_SHIELDBATTERY'], 'avail_unit_type_id': [1910]}, - 332: {'name': 'Effect_Salvage_quick', 'func_type': 'raw_cmd', 'ability_id': 32, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_BUNKER'], 'avail_unit_type_id': [24]}, - 333: {'name': 'Effect_Scan_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 399, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_ORBITALCOMMAND'], 'avail_unit_type_id': [132]}, - 113: {'name': 'Effect_ShadowStride_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2700, 'general_id': 3687, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_DARKTEMPLAR'], 'avail_unit_type_id': [76]}, - 334: {'name': 'Effect_SpawnChangeling_quick', 'func_type': 'raw_cmd', 'ability_id': 181, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_OVERSEER'], 'avail_unit_type_id': [129]}, - 335: {'name': 'Effect_SpawnLocusts_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2704, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_SWARMHOSTBURROWEDMP', 'ZERG_SWARMHOSTMP'], 'avail_unit_type_id': [493, 494]}, - 336: {'name': 'Effect_SpawnLocusts_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2704, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_SWARMHOSTBURROWEDMP', 'ZERG_SWARMHOSTMP'], 'avail_unit_type_id': [493, 494]}, - 337: {'name': 'Effect_Spray_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3684, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_SCV', 'ZERG_DRONE', 'PROTOSS_PROBE'], 'avail_unit_type_id': [45, 104, 84]}, - 338: {'name': 'Effect_Spray_Protoss_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 30, 'general_id': 3684, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_PROBE'], 'avail_unit_type_id': [84]}, - 339: {'name': 'Effect_Spray_Terran_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 26, 'general_id': 3684, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_SCV'], 'avail_unit_type_id': [45]}, - 340: {'name': 'Effect_Spray_Zerg_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 28, 'general_id': 3684, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_DRONE'], 'avail_unit_type_id': [104]}, - 341: {'name': 'Effect_Stim_quick', 'func_type': 'raw_cmd', 'ability_id': 3675, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_BUNKER', 'TERRAN_MARAUDER', 'TERRAN_MARINE'], 'avail_unit_type_id': [24, 51, 48]}, - 342: {'name': 'Effect_Stim_Marauder_quick', 'func_type': 'raw_cmd', 'ability_id': 253, 'general_id': 3675, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_MARAUDER'], 'avail_unit_type_id': [51]}, - 343: {'name': 'Effect_Stim_Marauder_Redirect_quick', 'func_type': 'raw_cmd', 'ability_id': 1684, 'general_id': 3675, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_MARAUDER'], 'avail_unit_type_id': [51]}, - 344: {'name': 'Effect_Stim_Marine_quick', 'func_type': 'raw_cmd', 'ability_id': 380, 'general_id': 3675, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_MARINE'], 'avail_unit_type_id': [48]}, - 345: {'name': 'Effect_Stim_Marine_Redirect_quick', 'func_type': 'raw_cmd', 'ability_id': 1683, 'general_id': 3675, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_MARINE'], 'avail_unit_type_id': [48]}, - 346: {'name': 'Effect_SupplyDrop_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 255, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_ORBITALCOMMAND'], 'avail_unit_type_id': [132]}, - 347: {'name': 'Effect_TacticalJump_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2358, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_BATTLECRUISER'], 'avail_unit_type_id': [57]}, - 348: {'name': 'Effect_TimeWarp_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2244, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE'], 'avail_unit_type_id': [10, 488]}, - 349: {'name': 'Effect_Transfusion_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 1664, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_QUEEN'], 'avail_unit_type_id': [126]}, - 350: {'name': 'Effect_ViperConsume_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2073, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_VIPER'], 'avail_unit_type_id': [499]}, - 94: {'name': 'Effect_VoidRayPrismaticAlignment_quick', 'func_type': 'raw_cmd', 'ability_id': 2393, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_VOIDRAY'], 'avail_unit_type_id': [80]}, - 353: {'name': 'Effect_WidowMineAttack_autocast', 'func_type': 'raw_autocast', 'ability_id': 2099, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': False, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_WIDOWMINEBURROWED'], 'avail_unit_type_id': [500]}, - 351: {'name': 'Effect_WidowMineAttack_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 2099, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_WIDOWMINEBURROWED'], 'avail_unit_type_id': [500]}, - 352: {'name': 'Effect_WidowMineAttack_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 2099, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_WIDOWMINEBURROWED'], 'avail_unit_type_id': [500]}, - 537: {'name': 'Effect_YamatoGun_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 401, 'general_id': 0, 'goal': 'effect', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_BATTLECRUISER'], 'avail_unit_type_id': [57]}, - 93: {'name': 'Hallucination_Adept_quick', 'func_type': 'raw_cmd', 'ability_id': 2391, 'general_id': 0, 'goal': 'effect', 'special_goal': 'hallucination', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 22: {'name': 'Hallucination_Archon_quick', 'func_type': 'raw_cmd', 'ability_id': 146, 'general_id': 0, 'goal': 'effect', 'special_goal': 'hallucination', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 23: {'name': 'Hallucination_Colossus_quick', 'func_type': 'raw_cmd', 'ability_id': 148, 'general_id': 0, 'goal': 'effect', 'special_goal': 'hallucination', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 92: {'name': 'Hallucination_Disruptor_quick', 'func_type': 'raw_cmd', 'ability_id': 2389, 'general_id': 0, 'goal': 'effect', 'special_goal': 'hallucination', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 24: {'name': 'Hallucination_HighTemplar_quick', 'func_type': 'raw_cmd', 'ability_id': 150, 'general_id': 0, 'goal': 'effect', 'special_goal': 'hallucination', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 25: {'name': 'Hallucination_Immortal_quick', 'func_type': 'raw_cmd', 'ability_id': 152, 'general_id': 0, 'goal': 'effect', 'special_goal': 'hallucination', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 89: {'name': 'Hallucination_Oracle_quick', 'func_type': 'raw_cmd', 'ability_id': 2114, 'general_id': 0, 'goal': 'effect', 'special_goal': 'hallucination', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 26: {'name': 'Hallucination_Phoenix_quick', 'func_type': 'raw_cmd', 'ability_id': 154, 'general_id': 0, 'goal': 'effect', 'special_goal': 'hallucination', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 27: {'name': 'Hallucination_Probe_quick', 'func_type': 'raw_cmd', 'ability_id': 156, 'general_id': 0, 'goal': 'effect', 'special_goal': 'hallucination', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 28: {'name': 'Hallucination_Stalker_quick', 'func_type': 'raw_cmd', 'ability_id': 158, 'general_id': 0, 'goal': 'effect', 'special_goal': 'hallucination', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 29: {'name': 'Hallucination_VoidRay_quick', 'func_type': 'raw_cmd', 'ability_id': 160, 'general_id': 0, 'goal': 'effect', 'special_goal': 'hallucination', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['PROTOSS_SENTRY'], 'avail_unit_type_id': [77]}, - 30: {'name': 'Hallucination_WarpPrism_quick', 'func_type': 'raw_cmd', 'ability_id': 162, 'general_id': 0, 'goal': 'effect', 'special_goal': 'hallucination', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': 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399: {'name': 'Morph_PlanetaryFortress_quick', 'func_type': 'raw_cmd', 'ability_id': 1450, 'general_id': 0, 'goal': 'build', 'special_goal': 'morph', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['TERRAN_COMMANDCENTER'], 'avail_unit_type_id': [18]}, - 400: {'name': 'Morph_Ravager_quick', 'func_type': 'raw_cmd', 'ability_id': 2330, 'general_id': 0, 'goal': 'unit', 'special_goal': 'morph', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': False, 'avail_unit_type': ['ZERG_ROACH'], 'avail_unit_type_id': [110]}, - 401: {'name': 'Morph_Root_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3680, 'general_id': 0, 'goal': 'other', 'special_goal': 'morph', 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLERUPROOTED'], 'avail_unit_type_id': [139, 140]}, - 402: {'name': 'Morph_SiegeMode_quick', 'func_type': 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'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PROBE', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [55, 46, 36, 692, 43, 50, 53, 484, 689, 51, 48, 54, 268, 134, 56, 49, 45, 33, 44, 52, 691, 34, 35, 498, 9, 289, 114, 113, 12, 15, 14, 13, 17, 16, 112, 104, 107, 150, 111, 127, 7, 489, 693, 502, 108, 106, 128, 893, 129, 126, 688, 110, 118, 139, 140, 494, 892, 109, 499, 105, 311, 801, 141, 79, 4, 76, 694, 733, 75, 83, 85, 10, 488, 82, 495, 78, 84, 77, 74, 496, 80, 81, 73]}, - 15: {'name': 'Patrol_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3795, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_BANSHEE', 'TERRAN_BARRACKSFLYING', 'TERRAN_BATTLECRUISER', 'TERRAN_COMMANDCENTERFLYING', 'TERRAN_CYCLONE', 'TERRAN_FACTORYFLYING', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MEDIVAC', 'TERRAN_MULE', 'TERRAN_ORBITALCOMMANDFLYING', 'TERRAN_RAVEN', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_STARPORTFLYING', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'TERRAN_WIDOWMINE', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_BROODLORDCOCOON', 'ZERG_CHANGELING', 'ZERG_CHANGELINGMARINE', 'ZERG_CHANGELINGMARINESHIELD', 'ZERG_CHANGELINGZEALOT', 'ZERG_CHANGELINGZERGLING', 'ZERG_CHANGELINGZERGLINGWINGS', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTEDTERRANSEGG', 'ZERG_INFESTOR', 'ZERG_INFESTORBURROWED', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMP', 'ZERG_MUTALISK', 'ZERG_OVERLORD', 'ZERG_OVERLORDCOCOON', 'ZERG_OVERLORDTRANSPORT', 'ZERG_OVERSEER', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_ROACHBURROWED', 'ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLERUPROOTED', 'ZERG_SWARMHOSTMP', 'ZERG_TRANSPORTOVERLORDCOCOON', 'ZERG_ULTRALISK', 'ZERG_VIPER', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ADEPTPHASESHIFT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PROBE', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [55, 46, 57, 36, 692, 43, 50, 53, 484, 689, 51, 48, 54, 268, 134, 56, 49, 45, 33, 44, 52, 691, 34, 35, 498, 9, 289, 114, 113, 12, 15, 14, 13, 17, 16, 112, 104, 107, 150, 111, 127, 7, 489, 693, 502, 108, 106, 128, 893, 129, 126, 688, 110, 118, 139, 140, 494, 892, 109, 499, 105, 311, 801, 141, 79, 4, 76, 694, 733, 75, 83, 85, 10, 488, 82, 495, 78, 84, 77, 74, 496, 80, 81, 73]}, - 16: {'name': 'Patrol_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3795, 'general_id': 0, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_BANSHEE', 'TERRAN_BARRACKSFLYING', 'TERRAN_BATTLECRUISER', 'TERRAN_COMMANDCENTERFLYING', 'TERRAN_CYCLONE', 'TERRAN_FACTORYFLYING', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MEDIVAC', 'TERRAN_MULE', 'TERRAN_ORBITALCOMMANDFLYING', 'TERRAN_RAVEN', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_STARPORTFLYING', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'TERRAN_WIDOWMINE', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_BROODLORDCOCOON', 'ZERG_CHANGELING', 'ZERG_CHANGELINGMARINE', 'ZERG_CHANGELINGMARINESHIELD', 'ZERG_CHANGELINGZEALOT', 'ZERG_CHANGELINGZERGLING', 'ZERG_CHANGELINGZERGLINGWINGS', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTEDTERRANSEGG', 'ZERG_INFESTOR', 'ZERG_INFESTORBURROWED', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMP', 'ZERG_MUTALISK', 'ZERG_OVERLORD', 'ZERG_OVERLORDCOCOON', 'ZERG_OVERLORDTRANSPORT', 'ZERG_OVERSEER', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_ROACHBURROWED', 'ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLERUPROOTED', 'ZERG_SWARMHOSTMP', 'ZERG_TRANSPORTOVERLORDCOCOON', 'ZERG_ULTRALISK', 'ZERG_VIPER', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ADEPTPHASESHIFT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PROBE', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [55, 46, 57, 36, 692, 43, 50, 53, 484, 689, 51, 48, 54, 268, 134, 56, 49, 45, 33, 44, 52, 691, 34, 35, 498, 9, 289, 114, 113, 12, 15, 14, 13, 17, 16, 112, 104, 107, 150, 111, 127, 7, 489, 693, 502, 108, 106, 128, 893, 129, 126, 688, 110, 118, 139, 140, 494, 892, 109, 499, 105, 311, 801, 141, 79, 4, 76, 694, 733, 75, 83, 85, 10, 488, 82, 495, 78, 84, 77, 74, 496, 80, 81, 73]}, - 549: {'name': 'Patrol_Battlecruiser_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 3777, 'general_id': 3795, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_BATTLECRUISER'], 'avail_unit_type_id': [57]}, - 550: {'name': 'Patrol_Battlecruiser_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 3777, 'general_id': 3795, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_BATTLECRUISER'], 'avail_unit_type_id': [57]}, - 551: {'name': 'Patrol_Patrol_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 17, 'general_id': 3795, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_BANSHEE', 'TERRAN_BARRACKSFLYING', 'TERRAN_COMMANDCENTERFLYING', 'TERRAN_CYCLONE', 'TERRAN_FACTORYFLYING', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MEDIVAC', 'TERRAN_MULE', 'TERRAN_ORBITALCOMMANDFLYING', 'TERRAN_RAVEN', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_STARPORTFLYING', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'TERRAN_WIDOWMINE', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_BROODLORDCOCOON', 'ZERG_CHANGELING', 'ZERG_CHANGELINGMARINE', 'ZERG_CHANGELINGMARINESHIELD', 'ZERG_CHANGELINGZEALOT', 'ZERG_CHANGELINGZERGLING', 'ZERG_CHANGELINGZERGLINGWINGS', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTEDTERRANSEGG', 'ZERG_INFESTOR', 'ZERG_INFESTORBURROWED', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMP', 'ZERG_MUTALISK', 'ZERG_OVERLORD', 'ZERG_OVERLORDCOCOON', 'ZERG_OVERLORDTRANSPORT', 'ZERG_OVERSEER', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_ROACHBURROWED', 'ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLERUPROOTED', 'ZERG_SWARMHOSTMP', 'ZERG_TRANSPORTOVERLORDCOCOON', 'ZERG_ULTRALISK', 'ZERG_VIPER', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ADEPTPHASESHIFT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PROBE', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [55, 46, 36, 692, 43, 50, 53, 484, 689, 51, 48, 54, 268, 134, 56, 49, 45, 33, 44, 52, 691, 34, 35, 498, 9, 289, 114, 113, 12, 15, 14, 13, 17, 16, 112, 104, 107, 150, 111, 127, 7, 489, 693, 502, 108, 106, 128, 893, 129, 126, 688, 110, 118, 139, 140, 494, 892, 109, 499, 105, 311, 801, 141, 79, 4, 76, 694, 733, 75, 83, 85, 10, 488, 82, 495, 78, 84, 77, 74, 496, 80, 81, 73]}, - 552: {'name': 'Patrol_Patrol_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 17, 'general_id': 3795, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_BANSHEE', 'TERRAN_BARRACKSFLYING', 'TERRAN_COMMANDCENTERFLYING', 'TERRAN_CYCLONE', 'TERRAN_FACTORYFLYING', 'TERRAN_GHOST', 'TERRAN_HELLION', 'TERRAN_HELLIONTANK', 'TERRAN_LIBERATOR', 'TERRAN_MARAUDER', 'TERRAN_MARINE', 'TERRAN_MEDIVAC', 'TERRAN_MULE', 'TERRAN_ORBITALCOMMANDFLYING', 'TERRAN_RAVEN', 'TERRAN_REAPER', 'TERRAN_SCV', 'TERRAN_SIEGETANK', 'TERRAN_STARPORTFLYING', 'TERRAN_THOR', 'TERRAN_THORAP', 'TERRAN_VIKINGASSAULT', 'TERRAN_VIKINGFIGHTER', 'TERRAN_WIDOWMINE', 'ZERG_BANELING', 'ZERG_BROODLING', 'ZERG_BROODLORD', 'ZERG_BROODLORDCOCOON', 'ZERG_CHANGELING', 'ZERG_CHANGELINGMARINE', 'ZERG_CHANGELINGMARINESHIELD', 'ZERG_CHANGELINGZEALOT', 'ZERG_CHANGELINGZERGLING', 'ZERG_CHANGELINGZERGLINGWINGS', 'ZERG_CORRUPTOR', 'ZERG_DRONE', 'ZERG_HYDRALISK', 'ZERG_INFESTEDTERRANSEGG', 'ZERG_INFESTOR', 'ZERG_INFESTORBURROWED', 'ZERG_INFESTORTERRAN', 'ZERG_LOCUSTMP', 'ZERG_LOCUSTMPFLYING', 'ZERG_LURKERMP', 'ZERG_MUTALISK', 'ZERG_OVERLORD', 'ZERG_OVERLORDCOCOON', 'ZERG_OVERLORDTRANSPORT', 'ZERG_OVERSEER', 'ZERG_QUEEN', 'ZERG_RAVAGER', 'ZERG_ROACH', 'ZERG_ROACHBURROWED', 'ZERG_SPINECRAWLERUPROOTED', 'ZERG_SPORECRAWLERUPROOTED', 'ZERG_SWARMHOSTMP', 'ZERG_TRANSPORTOVERLORDCOCOON', 'ZERG_ULTRALISK', 'ZERG_VIPER', 'ZERG_ZERGLING', 'PROTOSS_ADEPT', 'PROTOSS_ADEPTPHASESHIFT', 'PROTOSS_ARCHON', 'PROTOSS_CARRIER', 'PROTOSS_COLOSSUS', 'PROTOSS_DARKTEMPLAR', 'PROTOSS_DISRUPTOR', 'PROTOSS_DISRUPTORPHASED', 'PROTOSS_HIGHTEMPLAR', 'PROTOSS_IMMORTAL', 'PROTOSS_INTERCEPTOR', 'PROTOSS_MOTHERSHIP', 'PROTOSS_MOTHERSHIPCORE', 'PROTOSS_OBSERVER', 'PROTOSS_ORACLE', 'PROTOSS_PHOENIX', 'PROTOSS_PROBE', 'PROTOSS_SENTRY', 'PROTOSS_STALKER', 'PROTOSS_TEMPEST', 'PROTOSS_VOIDRAY', 'PROTOSS_WARPPRISM', 'PROTOSS_ZEALOT'], 'avail_unit_type_id': [55, 46, 36, 692, 43, 50, 53, 484, 689, 51, 48, 54, 268, 134, 56, 49, 45, 33, 44, 52, 691, 34, 35, 498, 9, 289, 114, 113, 12, 15, 14, 13, 17, 16, 112, 104, 107, 150, 111, 127, 7, 489, 693, 502, 108, 106, 128, 893, 129, 126, 688, 110, 118, 139, 140, 494, 892, 109, 499, 105, 311, 801, 141, 79, 4, 76, 694, 733, 75, 83, 85, 10, 488, 82, 495, 78, 84, 77, 74, 496, 80, 81, 73]}, - 415: {'name': 'Rally_Building_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 195, 'general_id': 3673, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_BARRACKS', 'TERRAN_BUNKER', 'TERRAN_FACTORY', 'TERRAN_STARPORT', 'ZERG_NYDUSCANAL', 'ZERG_NYDUSNETWORK', 'ZERG_RAVAGERCOCOON', 'PROTOSS_GATEWAY', 'PROTOSS_ROBOTICSFACILITY', 'PROTOSS_STARGATE'], 'avail_unit_type_id': [21, 24, 27, 28, 142, 95, 687, 62, 71, 67]}, - 416: {'name': 'Rally_Building_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 195, 'general_id': 3673, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_BARRACKS', 'TERRAN_BUNKER', 'TERRAN_FACTORY', 'TERRAN_STARPORT', 'ZERG_NYDUSCANAL', 'ZERG_NYDUSNETWORK', 'ZERG_RAVAGERCOCOON', 'PROTOSS_GATEWAY', 'PROTOSS_ROBOTICSFACILITY', 'PROTOSS_STARGATE'], 'avail_unit_type_id': [21, 24, 27, 28, 142, 95, 687, 62, 71, 67]}, - 417: {'name': 'Rally_CommandCenter_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 203, 'general_id': 3690, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['TERRAN_COMMANDCENTER', 'TERRAN_ORBITALCOMMAND', 'TERRAN_PLANETARYFORTRESS'], 'avail_unit_type_id': [18, 132, 130]}, - 418: {'name': 'Rally_CommandCenter_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 203, 'general_id': 3690, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['TERRAN_COMMANDCENTER', 'TERRAN_ORBITALCOMMAND', 'TERRAN_PLANETARYFORTRESS'], 'avail_unit_type_id': [18, 132, 130]}, - 419: {'name': 'Rally_Hatchery_Units_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 211, 'general_id': 3673, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_HATCHERY', 'ZERG_HIVE', 'ZERG_LAIR'], 'avail_unit_type_id': [86, 101, 100]}, - 420: {'name': 'Rally_Hatchery_Units_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 211, 'general_id': 3673, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': True, 'target_location': False, 'avail_unit_type': ['ZERG_HATCHERY', 'ZERG_HIVE', 'ZERG_LAIR'], 'avail_unit_type_id': [86, 101, 100]}, - 421: {'name': 'Rally_Hatchery_Workers_pt', 'func_type': 'raw_cmd_pt', 'ability_id': 212, 'general_id': 3690, 'goal': 'other', 'special_goal': None, 'queued': True, 'selected_units': True, 'target_unit': False, 'target_location': True, 'avail_unit_type': ['ZERG_HATCHERY', 'ZERG_HIVE', 'ZERG_LAIR'], 'avail_unit_type_id': [86, 101, 100]}, - 422: {'name': 'Rally_Hatchery_Workers_unit', 'func_type': 'raw_cmd_unit', 'ability_id': 212, 'general_id': 3690, 'goal': 'other', 'special_goal': None, 'queued': 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'Phoenix', 'PhotonCannon', 'Probe', 'PylonOvercharged', 'RoboticsFacility', 'Sentry', 'ShieldBattery', 'Stalker', 'Stargate', 'Tempest', 'VoidRay', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'Factory', 'FactoryFlying', 'Ghost', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reaper', 'RepairDrone', 'SCV', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': []}, - 2: {'action_name': 'Attack_pt', 'selected_type': [311, 801, 1955, 79, 4, 76, 694, 733, 75, 83, 10, 488, 82, 1911, 495, 78, 66, 84, 894, 77, 1910, 74, 496, 80, 81, 136, 73, 31, 55, 57, 24, 692, 50, 144, 53, 484, 689, 734, 268, 51, 48, 54, 23, 130, 11, 56, 49, 1913, 45, 33, 32, 52, 691, 34, 35, 498, 500, 9, 115, 8, 114, 113, 289, 12, 15, 14, 13, 17, 16, 103, 112, 104, 116, 107, 117, 94, 7, 120, 150, 111, 127, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 98, 139, 99, 140, 494, 493, 109, 131, 499, 105, 119], 'target_type': [], 'selected_type_name': ['Adept', 'AdeptPhaseShift', 'AssimilatorRich', 'Carrier', 'Colossus', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'HighTemplar', 'Immortal', 'Mothership', 'MothershipCore', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'PylonOvercharged', 'Sentry', 'ShieldBattery', 'Stalker', 'Tempest', 'VoidRay', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'AutoTurret', 'Banshee', 'Battlecruiser', 'Bunker', 'Cyclone', 'Ghost', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reaper', 'RepairDrone', 'SCV', 'SiegeTank', 'SiegeTankSieged', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': []}, - 3: {'action_name': 'Attack_unit', 'selected_type': [311, 801, 1955, 79, 4, 76, 694, 733, 75, 83, 10, 488, 82, 1911, 495, 78, 66, 84, 894, 77, 1910, 74, 496, 80, 81, 136, 73, 31, 55, 57, 24, 692, 50, 144, 53, 484, 689, 734, 268, 51, 48, 54, 23, 130, 11, 56, 49, 1913, 45, 33, 32, 52, 691, 34, 35, 498, 500, 9, 115, 8, 114, 113, 289, 12, 15, 14, 13, 17, 16, 103, 112, 104, 116, 107, 117, 94, 7, 120, 150, 111, 127, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 98, 139, 99, 140, 494, 493, 109, 131, 499, 105, 119], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Adept', 'AdeptPhaseShift', 'AssimilatorRich', 'Carrier', 'Colossus', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'HighTemplar', 'Immortal', 'Mothership', 'MothershipCore', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'PylonOvercharged', 'Sentry', 'ShieldBattery', 'Stalker', 'Tempest', 'VoidRay', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'AutoTurret', 'Banshee', 'Battlecruiser', 'Bunker', 'Cyclone', 'Ghost', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reaper', 'RepairDrone', 'SCV', 'SiegeTank', 'SiegeTankSieged', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 12: {'action_name': 'Smart_unit', 'selected_type': [311, 801, 1955, 79, 4, 76, 694, 733, 62, 75, 83, 10, 488, 59, 82, 1911, 495, 78, 66, 84, 894, 71, 77, 1910, 74, 67, 496, 80, 81, 136, 73, 31, 55, 21, 46, 57, 24, 18, 36, 692, 27, 43, 50, 144, 53, 484, 689, 734, 268, 51, 48, 54, 23, 132, 134, 130, 11, 56, 49, 1913, 45, 33, 32, 28, 44, 52, 691, 34, 35, 498, 500, 9, 115, 8, 114, 113, 289, 12, 15, 14, 13, 17, 16, 103, 112, 104, 116, 86, 101, 107, 117, 94, 7, 120, 150, 111, 127, 100, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 98, 139, 99, 140, 494, 493, 109, 131, 499, 105, 119], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Adept', 'AdeptPhaseShift', 'AssimilatorRich', 'Carrier', 'Colossus', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'Gateway', 'HighTemplar', 'Immortal', 'Mothership', 'MothershipCore', 'Nexus', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'PylonOvercharged', 'RoboticsFacility', 'Sentry', 'ShieldBattery', 'Stalker', 'Stargate', 'Tempest', 'VoidRay', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'Factory', 'FactoryFlying', 'Ghost', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reaper', 'RepairDrone', 'SCV', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 13: {'action_name': 'Move_pt', 'selected_type': [311, 801, 1955, 79, 4, 76, 694, 733, 75, 83, 10, 488, 82, 1911, 495, 78, 84, 894, 77, 1910, 74, 496, 80, 81, 136, 73, 31, 55, 46, 57, 36, 692, 43, 50, 144, 53, 484, 689, 734, 268, 51, 48, 54, 23, 134, 11, 56, 49, 1913, 45, 33, 32, 44, 52, 691, 34, 35, 498, 500, 9, 115, 8, 114, 113, 289, 12, 15, 14, 13, 17, 16, 103, 112, 104, 116, 107, 117, 94, 7, 120, 150, 111, 127, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 98, 139, 99, 140, 494, 493, 109, 131, 499, 105, 119], 'target_type': [], 'selected_type_name': ['Adept', 'AdeptPhaseShift', 'AssimilatorRich', 'Carrier', 'Colossus', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'HighTemplar', 'Immortal', 'Mothership', 'MothershipCore', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'Probe', 'PylonOvercharged', 'Sentry', 'ShieldBattery', 'Stalker', 'Tempest', 'VoidRay', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'AutoTurret', 'Banshee', 'BarracksFlying', 'Battlecruiser', 'CommandCenterFlying', 'Cyclone', 'FactoryFlying', 'Ghost', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'OrbitalCommandFlying', 'PointDefenseDrone', 'Raven', 'Reaper', 'RepairDrone', 'SCV', 'SiegeTank', 'SiegeTankSieged', 'StarportFlying', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': []}, - 14: {'action_name': 'Move_unit', 'selected_type': [311, 801, 1955, 79, 4, 76, 694, 733, 75, 83, 10, 488, 82, 1911, 495, 78, 84, 894, 77, 1910, 74, 496, 80, 81, 136, 73, 31, 55, 46, 57, 36, 692, 43, 50, 144, 53, 484, 689, 734, 268, 51, 48, 54, 23, 134, 11, 56, 49, 1913, 45, 33, 32, 44, 52, 691, 34, 35, 498, 500, 9, 115, 8, 114, 113, 289, 12, 15, 14, 13, 17, 16, 103, 112, 104, 116, 107, 117, 94, 7, 120, 150, 111, 127, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 98, 139, 99, 140, 494, 493, 109, 131, 499, 105, 119], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Adept', 'AdeptPhaseShift', 'AssimilatorRich', 'Carrier', 'Colossus', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'HighTemplar', 'Immortal', 'Mothership', 'MothershipCore', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'Probe', 'PylonOvercharged', 'Sentry', 'ShieldBattery', 'Stalker', 'Tempest', 'VoidRay', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'AutoTurret', 'Banshee', 'BarracksFlying', 'Battlecruiser', 'CommandCenterFlying', 'Cyclone', 'FactoryFlying', 'Ghost', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'OrbitalCommandFlying', 'PointDefenseDrone', 'Raven', 'Reaper', 'RepairDrone', 'SCV', 'SiegeTank', 'SiegeTankSieged', 'StarportFlying', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 15: {'action_name': 'Patrol_pt', 'selected_type': [311, 801, 1955, 79, 4, 76, 694, 733, 75, 83, 10, 488, 82, 1911, 495, 78, 84, 894, 77, 1910, 74, 496, 80, 81, 136, 73, 31, 55, 46, 57, 36, 692, 43, 50, 144, 53, 484, 689, 734, 268, 51, 48, 54, 23, 134, 11, 56, 49, 1913, 45, 33, 32, 44, 52, 691, 34, 35, 498, 500, 9, 115, 8, 114, 113, 289, 12, 15, 14, 13, 17, 16, 103, 112, 104, 116, 107, 117, 94, 7, 120, 150, 111, 127, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 98, 139, 99, 140, 494, 493, 109, 131, 499, 105, 119], 'target_type': [], 'selected_type_name': ['Adept', 'AdeptPhaseShift', 'AssimilatorRich', 'Carrier', 'Colossus', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'HighTemplar', 'Immortal', 'Mothership', 'MothershipCore', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'Probe', 'PylonOvercharged', 'Sentry', 'ShieldBattery', 'Stalker', 'Tempest', 'VoidRay', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'AutoTurret', 'Banshee', 'BarracksFlying', 'Battlecruiser', 'CommandCenterFlying', 'Cyclone', 'FactoryFlying', 'Ghost', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'OrbitalCommandFlying', 'PointDefenseDrone', 'Raven', 'Reaper', 'RepairDrone', 'SCV', 'SiegeTank', 'SiegeTankSieged', 'StarportFlying', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': []}, - 16: {'action_name': 'Patrol_unit', 'selected_type': [311, 801, 1955, 79, 4, 76, 694, 733, 75, 83, 10, 488, 82, 1911, 495, 78, 84, 894, 77, 1910, 74, 496, 80, 81, 136, 73, 31, 55, 46, 57, 36, 692, 43, 50, 144, 53, 484, 689, 734, 268, 51, 48, 54, 23, 134, 11, 56, 49, 1913, 45, 33, 32, 44, 52, 691, 34, 35, 498, 500, 9, 115, 8, 114, 113, 289, 12, 15, 14, 13, 17, 16, 103, 112, 104, 116, 107, 117, 94, 7, 120, 150, 111, 127, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 98, 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'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 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'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'Drone', 'DroneBurrowed', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpineCrawler', 'SpineCrawlerUprooted', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': []}, - 19: {'action_name': 'Research_PhoenixAnionPulseCrystals_quick', 'selected_type': [64], 'target_type': [], 'selected_type_name': 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'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 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'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BanelingNest', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'BroodlingEscort', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'CreepTumor', 'CreepTumorBurrowed', 'CreepTumorQueen', 'Drone', 'DroneBurrowed', 'EvolutionChamber', 'Extractor', 'ExtractorRich', 'GreaterSpire', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'HydraliskDen', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Larva', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpawningPool', 'SpineCrawler', 'SpineCrawlerUprooted', 'Spire', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'UltraliskCavern', 'Viper', 'Zergling', 'ZerglingBurrowed']}, - 105: {'action_name': 'UnloadAllAt_pt', 'selected_type': [81, 136, 24, 18, 54, 142, 95, 893, 36, 130], 'target_type': [], 'selected_type_name': ['WarpPrism', 'WarpPrismPhasing', 'Bunker', 'CommandCenter', 'Medivac', 'NydusCanal', 'NydusNetwork', 'OverlordTransport', 'CommandCenterFlying', 'PlanetaryFortress'], 'target_type_name': []}, - 106: {'action_name': 'Rally_Units_pt', 'selected_type': [311, 801, 141, 61, 1955, 79, 4, 72, 69, 76, 694, 733, 64, 135, 63, 62, 75, 83, 85, 10, 488, 59, 82, 1911, 495, 78, 66, 84, 60, 894, 70, 71, 77, 1910, 74, 67, 732, 496, 68, 65, 80, 133, 81, 136, 73, 29, 31, 55, 21, 46, 38, 37, 57, 24, 18, 36, 692, 22, 27, 43, 40, 39, 30, 50, 26, 144, 145, 53, 484, 830, 689, 734, 268, 51, 48, 54, 23, 58, 132, 134, 130, 11, 56, 6, 49, 20, 1960, 1913, 45, 25, 33, 32, 28, 44, 42, 41, 19, 47, 5, 52, 691, 34, 35, 498, 500, 9, 115, 8, 96, 114, 113, 289, 143, 12, 15, 14, 13, 17, 16, 103, 112, 87, 137, 138, 104, 116, 90, 88, 1956, 102, 86, 101, 107, 117, 91, 94, 7, 120, 150, 111, 127, 100, 151, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 89, 98, 139, 92, 99, 140, 494, 493, 109, 131, 93, 499, 105, 119], 'target_type': [], 'selected_type_name': ['Adept', 'AdeptPhaseShift', 'Archon', 'Assimilator', 'AssimilatorRich', 'Carrier', 'Colossus', 'CyberneticsCore', 'DarkShrine', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'FleetBeacon', 'ForceField', 'Forge', 'Gateway', 'HighTemplar', 'Immortal', 'Interceptor', 'Mothership', 'MothershipCore', 'Nexus', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'Pylon', 'PylonOvercharged', 'RoboticsBay', 'RoboticsFacility', 'Sentry', 'ShieldBattery', 'Stalker', 'Stargate', 'StasisTrap', 'Tempest', 'TemplarArchive', 'TwilightCouncil', 'VoidRay', 'WarpGate', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'Armory', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'BarracksReactor', 'BarracksTechLab', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'EngineeringBay', 'Factory', 'FactoryFlying', 'FactoryReactor', 'FactoryTechLab', 'FusionCore', 'Ghost', 'GhostAcademy', 'GhostAlternate', 'GhostNova', 'Hellion', 'Hellbat', 'KD8Charge', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'Nuke', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reactor', 'Reaper', 'Refinery', 'RefineryRich', 'RepairDrone', 'SCV', 'SensorTower', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'StarportReactor', 'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BanelingNest', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'BroodlingEscort', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'CreepTumor', 'CreepTumorBurrowed', 'CreepTumorQueen', 'Drone', 'DroneBurrowed', 'EvolutionChamber', 'Extractor', 'ExtractorRich', 'GreaterSpire', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'HydraliskDen', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Larva', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpawningPool', 'SpineCrawler', 'SpineCrawlerUprooted', 'Spire', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'UltraliskCavern', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': []}, - 107: {'action_name': 'Rally_Units_unit', 'selected_type': [311, 801, 141, 61, 1955, 79, 4, 72, 69, 76, 694, 733, 64, 135, 63, 62, 75, 83, 85, 10, 488, 59, 82, 1911, 495, 78, 66, 84, 60, 894, 70, 71, 77, 1910, 74, 67, 732, 496, 68, 65, 80, 133, 81, 136, 73, 29, 31, 55, 21, 46, 38, 37, 57, 24, 18, 36, 692, 22, 27, 43, 40, 39, 30, 50, 26, 144, 145, 53, 484, 830, 689, 734, 268, 51, 48, 54, 23, 58, 132, 134, 130, 11, 56, 6, 49, 20, 1960, 1913, 45, 25, 33, 32, 28, 44, 42, 41, 19, 47, 5, 52, 691, 34, 35, 498, 500, 9, 115, 8, 96, 114, 113, 289, 143, 12, 15, 14, 13, 17, 16, 103, 112, 87, 137, 138, 104, 116, 90, 88, 1956, 102, 86, 101, 107, 117, 91, 94, 7, 120, 150, 111, 127, 100, 151, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 89, 98, 139, 92, 99, 140, 494, 493, 109, 131, 93, 499, 105, 119], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Adept', 'AdeptPhaseShift', 'Archon', 'Assimilator', 'AssimilatorRich', 'Carrier', 'Colossus', 'CyberneticsCore', 'DarkShrine', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'FleetBeacon', 'ForceField', 'Forge', 'Gateway', 'HighTemplar', 'Immortal', 'Interceptor', 'Mothership', 'MothershipCore', 'Nexus', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'Pylon', 'PylonOvercharged', 'RoboticsBay', 'RoboticsFacility', 'Sentry', 'ShieldBattery', 'Stalker', 'Stargate', 'StasisTrap', 'Tempest', 'TemplarArchive', 'TwilightCouncil', 'VoidRay', 'WarpGate', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'Armory', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'BarracksReactor', 'BarracksTechLab', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'EngineeringBay', 'Factory', 'FactoryFlying', 'FactoryReactor', 'FactoryTechLab', 'FusionCore', 'Ghost', 'GhostAcademy', 'GhostAlternate', 'GhostNova', 'Hellion', 'Hellbat', 'KD8Charge', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'Nuke', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reactor', 'Reaper', 'Refinery', 'RefineryRich', 'RepairDrone', 'SCV', 'SensorTower', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'StarportReactor', 'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BanelingNest', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'BroodlingEscort', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'CreepTumor', 'CreepTumorBurrowed', 'CreepTumorQueen', 'Drone', 'DroneBurrowed', 'EvolutionChamber', 'Extractor', 'ExtractorRich', 'GreaterSpire', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'HydraliskDen', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Larva', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpawningPool', 'SpineCrawler', 'SpineCrawlerUprooted', 'Spire', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'UltraliskCavern', 'Viper', 'Zergling', 'ZerglingBurrowed'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 109: {'action_name': 'Effect_Repair_unit', 'selected_type': [268, 45], 'target_type': [29, 31, 55, 21, 46, 38, 37, 57, 24, 18, 36, 692, 22, 27, 43, 40, 39, 30, 26, 144, 53, 484, 689, 734, 268, 54, 23, 132, 134, 130, 11, 56, 6, 49, 20, 1960, 1913, 45, 25, 33, 32, 28, 44, 42, 41, 19, 47, 5, 52, 691, 34, 35, 498, 500], 'selected_type_name': ['MULE', 'SCV'], 'target_type_name': ['Armory', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'BarracksReactor', 'BarracksTechLab', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'EngineeringBay', 'Factory', 'FactoryFlying', 'FactoryReactor', 'FactoryTechLab', 'FusionCore', 'GhostAcademy', 'GhostAlternate', 'Hellion', 'Hellbat', 'Liberator', 'LiberatorAG', 'MULE', 'Medivac', 'MissileTurret', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reactor', 'Reaper', 'Refinery', 'RefineryRich', 'RepairDrone', 'SCV', 'SensorTower', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'StarportReactor', 'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed']}, - 110: {'action_name': 'Effect_MassRecall_pt', 'selected_type': [10, 59], 'target_type': [], 'selected_type_name': ['Mothership', 'Nexus'], 'target_type_name': []}, - 111: {'action_name': 'Effect_Blink_pt', 'selected_type': [74, 76], 'target_type': [], 'selected_type_name': ['Stalker', 'DarkTemplar'], 'target_type_name': []}, - 114: {'action_name': 'Rally_Workers_pt', 'selected_type': [59, 18, 132, 130, 86, 100, 101], 'target_type': [], 'selected_type_name': ['Nexus', 'CommandCenter', 'OrbitalCommand', 'PlanetaryFortress', 'Hatchery', 'Lair', 'Hive'], 'target_type_name': []}, - 115: {'action_name': 'Rally_Workers_unit', 'selected_type': [59, 18, 132, 130, 86, 100, 101], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 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'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 116: {'action_name': 'Research_ProtossAirArmor_quick', 'selected_type': [72], 'target_type': [], 'selected_type_name': ['CyberneticsCore'], 'target_type_name': []}, - 117: {'action_name': 'Research_ProtossAirWeapons_quick', 'selected_type': [72], 'target_type': [], 'selected_type_name': ['CyberneticsCore'], 'target_type_name': []}, - 118: {'action_name': 'Research_ProtossGroundArmor_quick', 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'Nuke', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reactor', 'Reaper', 'Refinery', 'RefineryRich', 'RepairDrone', 'SCV', 'SensorTower', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'StarportReactor', 'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BanelingNest', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'BroodlingEscort', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'CreepTumor', 'CreepTumorBurrowed', 'CreepTumorQueen', 'Drone', 'DroneBurrowed', 'EvolutionChamber', 'Extractor', 'ExtractorRich', 'GreaterSpire', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'HydraliskDen', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 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'target_type_name': ['WarpPrism', 'WarpPrismPhasing', 'Bunker', 'CommandCenter', 'Medivac', 'NydusCanal', 'NydusNetwork', 'OverlordTransport', 'CommandCenterFlying', 'PlanetaryFortress']}, - 166: {'action_name': 'Train_Disruptor_quick', 'selected_type': [71], 'target_type': [], 'selected_type_name': ['RoboticsFacility'], 'target_type_name': []}, - 167: {'action_name': 'Effect_PurificationNova_pt', 'selected_type': [694], 'target_type': [], 'selected_type_name': ['Disruptor'], 'target_type_name': []}, - 168: {'action_name': 'raw_move_camera', 'selected_type': [], 'target_type': [], 'selected_type_name': [], 'target_type_name': []}, - 169: {'action_name': 'Behavior_CloakOff_quick', 'selected_type': [144, 50, 55], 'target_type': [], 'selected_type_name': ['GhostAlternate', 'Ghost', 'Banshee'], 'target_type_name': []}, - 172: {'action_name': 'Behavior_CloakOn_quick', 'selected_type': [144, 145, 50, 55], 'target_type': [], 'selected_type_name': ['GhostAlternate', 'GhostNova', 'Ghost', 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27, 28], 'target_type': [], 'selected_type_name': ['FactoryFlying', 'StarportFlying', 'BarracksFlying', 'Barracks', 'Factory', 'Starport'], 'target_type_name': []}, - 207: {'action_name': 'Build_Reactor_pt', 'selected_type': [43, 44, 46, 21, 27, 28], 'target_type': [], 'selected_type_name': ['FactoryFlying', 'StarportFlying', 'BarracksFlying', 'Barracks', 'Factory', 'Starport'], 'target_type_name': []}, - 214: {'action_name': 'Build_Refinery_pt', 'selected_type': [45], 'target_type': [344, 342, 343, 880, 881], 'selected_type_name': ['SCV'], 'target_type_name': ['RichVespeneGeyser', 'VespeneGeyser', 'SpacePlatformGeyser', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser']}, - 215: {'action_name': 'Build_RoachWarren_pt', 'selected_type': [104], 'target_type': [], 'selected_type_name': ['Drone'], 'target_type_name': []}, - 216: {'action_name': 'Build_SensorTower_pt', 'selected_type': [45], 'target_type': [], 'selected_type_name': ['SCV'], 'target_type_name': []}, - 217: {'action_name': 'Build_SpawningPool_pt', 'selected_type': [104], 'target_type': [], 'selected_type_name': ['Drone'], 'target_type_name': []}, - 218: {'action_name': 'Build_SpineCrawler_pt', 'selected_type': [104], 'target_type': [], 'selected_type_name': ['Drone'], 'target_type_name': []}, - 219: {'action_name': 'Build_Spire_pt', 'selected_type': [104], 'target_type': [], 'selected_type_name': ['Drone'], 'target_type_name': []}, - 220: {'action_name': 'Build_SporeCrawler_pt', 'selected_type': [104], 'target_type': [], 'selected_type_name': ['Drone'], 'target_type_name': []}, - 221: {'action_name': 'Build_Starport_pt', 'selected_type': [45], 'target_type': [], 'selected_type_name': ['SCV'], 'target_type_name': []}, - 222: {'action_name': 'Build_SupplyDepot_pt', 'selected_type': [45], 'target_type': [], 'selected_type_name': ['SCV'], 'target_type_name': []}, - 223: {'action_name': 'Build_TechLab_quick', 'selected_type': [43, 44, 46, 21, 27, 28], 'target_type': [], 'selected_type_name': ['FactoryFlying', 'StarportFlying', 'BarracksFlying', 'Barracks', 'Factory', 'Starport'], 'target_type_name': []}, - 224: {'action_name': 'Build_TechLab_pt', 'selected_type': [43, 44, 46, 21, 27, 28], 'target_type': [], 'selected_type_name': ['FactoryFlying', 'StarportFlying', 'BarracksFlying', 'Barracks', 'Factory', 'Starport'], 'target_type_name': []}, - 231: {'action_name': 'Build_UltraliskCavern_pt', 'selected_type': [104], 'target_type': [], 'selected_type_name': ['Drone'], 'target_type_name': []}, - 232: {'action_name': 'BurrowDown_quick', 'selected_type': [7, 104, 105, 9, 107, 109, 110, 494, 111, 688, 498, 502, 503, 126], 'target_type': [], 'selected_type_name': ['InfestedTerran', 'Drone', 'Zergling', 'Baneling', 'Hydralisk', 'Ultralisk', 'Roach', 'SwarmHost', 'Infestor', 'Ravager', 'WidowMine', 'Lurker', 'LurkerBurrowed', 'Queen'], 'target_type_name': []}, - 246: {'action_name': 'BurrowUp_quick', 'selected_type': [131, 503, 493, 690, 115, 500, 116, 118, 119, 117, 125, 127, 120], 'target_type': [], 'selected_type_name': ['UltraliskBurrowed', 'LurkerBurrowed', 'SwarmHostBurrowed', 'RavagerBurrowed', 'BanelingBurrowed', 'WidowMineBurrowed', 'DroneBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'HydraliskBurrowed', 'QueenBurrowed', 'InfestorBurrowed', 'InfestedTerranBurrowed'], 'target_type_name': []}, - 293: {'action_name': 'Effect_Abduct_unit', 'selected_type': [499], 'target_type': [311, 801, 141, 61, 1955, 79, 4, 72, 69, 76, 694, 733, 64, 135, 63, 62, 75, 83, 85, 10, 488, 59, 82, 1911, 495, 78, 66, 84, 60, 894, 70, 71, 77, 1910, 74, 67, 732, 496, 68, 65, 80, 133, 81, 136, 73, 29, 31, 55, 21, 46, 38, 37, 57, 24, 18, 36, 692, 22, 27, 43, 40, 39, 30, 50, 26, 144, 145, 53, 484, 830, 689, 734, 268, 51, 48, 54, 23, 58, 132, 134, 130, 11, 56, 6, 49, 20, 1960, 1913, 45, 25, 33, 32, 28, 44, 42, 41, 19, 47, 5, 52, 691, 34, 35, 498, 500, 9, 115, 8, 96, 114, 113, 289, 143, 12, 15, 14, 13, 17, 16, 103, 112, 87, 137, 138, 104, 116, 90, 88, 1956, 102, 86, 101, 107, 117, 91, 94, 7, 120, 150, 111, 127, 100, 151, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 89, 98, 139, 92, 99, 140, 494, 493, 109, 131, 93, 499, 105, 119], 'selected_type_name': ['Viper'], 'target_type_name': ['Adept', 'AdeptPhaseShift', 'Archon', 'Assimilator', 'AssimilatorRich', 'Carrier', 'Colossus', 'CyberneticsCore', 'DarkShrine', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'FleetBeacon', 'ForceField', 'Forge', 'Gateway', 'HighTemplar', 'Immortal', 'Interceptor', 'Mothership', 'MothershipCore', 'Nexus', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'Pylon', 'PylonOvercharged', 'RoboticsBay', 'RoboticsFacility', 'Sentry', 'ShieldBattery', 'Stalker', 'Stargate', 'StasisTrap', 'Tempest', 'TemplarArchive', 'TwilightCouncil', 'VoidRay', 'WarpGate', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'Armory', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'BarracksReactor', 'BarracksTechLab', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'EngineeringBay', 'Factory', 'FactoryFlying', 'FactoryReactor', 'FactoryTechLab', 'FusionCore', 'Ghost', 'GhostAcademy', 'GhostAlternate', 'GhostNova', 'Hellion', 'Hellbat', 'KD8Charge', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'Nuke', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reactor', 'Reaper', 'Refinery', 'RefineryRich', 'RepairDrone', 'SCV', 'SensorTower', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'StarportReactor', 'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BanelingNest', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'BroodlingEscort', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'CreepTumor', 'CreepTumorBurrowed', 'CreepTumorQueen', 'Drone', 'DroneBurrowed', 'EvolutionChamber', 'Extractor', 'ExtractorRich', 'GreaterSpire', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'HydraliskDen', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Larva', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpawningPool', 'SpineCrawler', 'SpineCrawlerUprooted', 'Spire', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'UltraliskCavern', 'Viper', 'Zergling', 'ZerglingBurrowed']}, - 294: {'action_name': 'Effect_AntiArmorMissile_unit', 'selected_type': [56], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Raven'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 295: {'action_name': 'Effect_AutoTurret_pt', 'selected_type': [56], 'target_type': [], 'selected_type_name': ['Raven'], 'target_type_name': []}, - 296: {'action_name': 'Effect_BlindingCloud_pt', 'selected_type': [499], 'target_type': [], 'selected_type_name': ['Viper'], 'target_type_name': []}, - 297: {'action_name': 'Effect_CalldownMULE_pt', 'selected_type': [132], 'target_type': [], 'selected_type_name': ['OrbitalCommand'], 'target_type_name': []}, - 298: {'action_name': 'Effect_CalldownMULE_unit', 'selected_type': [132], 'target_type': [665, 666, 483, 341, 146, 147, 884, 885, 796, 797, 1961], 'selected_type_name': ['OrbitalCommand'], 'target_type_name': ['LabMineralField', 'LabMineralField750', 'MineralField750', 'MineralField', 'RichMineralField', 'RichMineralField750', 'PurifierMineralField', 'PurifierMineralField750', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'MineralField450']}, - 299: {'action_name': 'Effect_CausticSpray_unit', 'selected_type': [112], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Corruptor'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 301: {'action_name': 'Effect_Charge_unit', 'selected_type': [73], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Zealot'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 303: {'action_name': 'Effect_Contaminate_unit', 'selected_type': [1912, 129], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['OverseerOversightMode', 'Overseer'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 304: {'action_name': 'Effect_CorrosiveBile_pt', 'selected_type': [688], 'target_type': [], 'selected_type_name': ['Ravager'], 'target_type_name': []}, - 305: {'action_name': 'Effect_EMP_pt', 'selected_type': [144, 50], 'target_type': [], 'selected_type_name': ['GhostAlternate', 'Ghost'], 'target_type_name': []}, - 307: {'action_name': 'Effect_Explode_quick', 'selected_type': [9, 115], 'target_type': [], 'selected_type_name': ['Baneling', 'BanelingBurrowed'], 'target_type_name': []}, - 308: {'action_name': 'Effect_FungalGrowth_pt', 'selected_type': [111], 'target_type': [], 'selected_type_name': ['Infestor'], 'target_type_name': []}, - 310: {'action_name': 'Effect_GhostSnipe_unit', 'selected_type': [144, 145, 50], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['GhostAlternate', 'GhostNova', 'Ghost'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 311: {'action_name': 'Effect_Heal_unit', 'selected_type': [54], 'target_type': [48, 51, 49], 'selected_type_name': ['Medivac'], 'target_type_name': ['Marine', 'Marauder', 'Reaper']}, - 314: {'action_name': 'Effect_InfestedTerrans_pt', 'selected_type': [111, 127], 'target_type': [], 'selected_type_name': ['Infestor', 'InfestorBurrowed'], 'target_type_name': []}, - 315: {'action_name': 'Effect_InjectLarva_unit', 'selected_type': [126], 'target_type': [100, 101, 86], 'selected_type_name': ['Queen'], 'target_type_name': ['Lair', 'Hive', 'Hatchery']}, - 316: {'action_name': 'Effect_InterferenceMatrix_unit', 'selected_type': [56], 'target_type': [311, 801, 141, 61, 1955, 79, 4, 72, 69, 76, 694, 733, 64, 135, 63, 62, 75, 83, 85, 10, 488, 59, 82, 1911, 495, 78, 66, 84, 60, 894, 70, 71, 77, 1910, 74, 67, 732, 496, 68, 65, 80, 133, 81, 136, 73, 29, 31, 55, 21, 46, 38, 37, 57, 24, 18, 36, 692, 22, 27, 43, 40, 39, 30, 50, 26, 144, 145, 53, 484, 830, 689, 734, 268, 51, 48, 54, 23, 58, 132, 134, 130, 11, 56, 6, 49, 20, 1960, 1913, 45, 25, 33, 32, 28, 44, 42, 41, 19, 47, 5, 52, 691, 34, 35, 498, 500, 9, 115, 8, 96, 114, 113, 289, 143, 12, 15, 14, 13, 17, 16, 103, 112, 87, 137, 138, 104, 116, 90, 88, 1956, 102, 86, 101, 107, 117, 91, 94, 7, 120, 150, 111, 127, 100, 151, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 89, 98, 139, 92, 99, 140, 494, 493, 109, 131, 93, 499, 105, 119], 'selected_type_name': ['Raven'], 'target_type_name': ['Adept', 'AdeptPhaseShift', 'Archon', 'Assimilator', 'AssimilatorRich', 'Carrier', 'Colossus', 'CyberneticsCore', 'DarkShrine', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'FleetBeacon', 'ForceField', 'Forge', 'Gateway', 'HighTemplar', 'Immortal', 'Interceptor', 'Mothership', 'MothershipCore', 'Nexus', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'Pylon', 'PylonOvercharged', 'RoboticsBay', 'RoboticsFacility', 'Sentry', 'ShieldBattery', 'Stalker', 'Stargate', 'StasisTrap', 'Tempest', 'TemplarArchive', 'TwilightCouncil', 'VoidRay', 'WarpGate', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'Armory', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'BarracksReactor', 'BarracksTechLab', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'EngineeringBay', 'Factory', 'FactoryFlying', 'FactoryReactor', 'FactoryTechLab', 'FusionCore', 'Ghost', 'GhostAcademy', 'GhostAlternate', 'GhostNova', 'Hellion', 'Hellbat', 'KD8Charge', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'Nuke', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reactor', 'Reaper', 'Refinery', 'RefineryRich', 'RepairDrone', 'SCV', 'SensorTower', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'StarportReactor', 'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BanelingNest', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'BroodlingEscort', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'CreepTumor', 'CreepTumorBurrowed', 'CreepTumorQueen', 'Drone', 'DroneBurrowed', 'EvolutionChamber', 'Extractor', 'ExtractorRich', 'GreaterSpire', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'HydraliskDen', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Larva', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpawningPool', 'SpineCrawler', 'SpineCrawlerUprooted', 'Spire', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'UltraliskCavern', 'Viper', 'Zergling', 'ZerglingBurrowed']}, - 317: {'action_name': 'Effect_KD8Charge_pt', 'selected_type': [49], 'target_type': [], 'selected_type_name': ['Reaper'], 'target_type_name': []}, - 318: {'action_name': 'Effect_LockOn_unit', 'selected_type': [692], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Cyclone'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 319: {'action_name': 'Effect_LocustSwoop_pt', 'selected_type': [693], 'target_type': [], 'selected_type_name': ['LocustFlying'], 'target_type_name': []}, - 320: {'action_name': 'Effect_MedivacIgniteAfterburners_quick', 'selected_type': [54], 'target_type': [], 'selected_type_name': ['Medivac'], 'target_type_name': []}, - 321: {'action_name': 'Effect_NeuralParasite_unit', 'selected_type': [111, 127], 'target_type': [311, 801, 141, 61, 1955, 79, 4, 72, 69, 76, 694, 733, 64, 135, 63, 62, 75, 83, 85, 10, 488, 59, 82, 1911, 495, 78, 66, 84, 60, 894, 70, 71, 77, 1910, 74, 67, 732, 496, 68, 65, 80, 133, 81, 136, 73, 29, 31, 55, 21, 46, 38, 37, 57, 24, 18, 36, 692, 22, 27, 43, 40, 39, 30, 50, 26, 144, 145, 53, 484, 830, 689, 734, 268, 51, 48, 54, 23, 58, 132, 134, 130, 11, 56, 6, 49, 20, 1960, 1913, 45, 25, 33, 32, 28, 44, 42, 41, 19, 47, 5, 52, 691, 34, 35, 498, 500, 9, 115, 8, 96, 114, 113, 289, 143, 12, 15, 14, 13, 17, 16, 103, 112, 87, 137, 138, 104, 116, 90, 88, 1956, 102, 86, 101, 107, 117, 91, 94, 7, 120, 150, 111, 127, 100, 151, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 89, 98, 139, 92, 99, 140, 494, 493, 109, 131, 93, 499, 105, 119], 'selected_type_name': ['Infestor', 'InfestorBurrowed'], 'target_type_name': ['Adept', 'AdeptPhaseShift', 'Archon', 'Assimilator', 'AssimilatorRich', 'Carrier', 'Colossus', 'CyberneticsCore', 'DarkShrine', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'FleetBeacon', 'ForceField', 'Forge', 'Gateway', 'HighTemplar', 'Immortal', 'Interceptor', 'Mothership', 'MothershipCore', 'Nexus', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'Pylon', 'PylonOvercharged', 'RoboticsBay', 'RoboticsFacility', 'Sentry', 'ShieldBattery', 'Stalker', 'Stargate', 'StasisTrap', 'Tempest', 'TemplarArchive', 'TwilightCouncil', 'VoidRay', 'WarpGate', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'Armory', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'BarracksReactor', 'BarracksTechLab', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'EngineeringBay', 'Factory', 'FactoryFlying', 'FactoryReactor', 'FactoryTechLab', 'FusionCore', 'Ghost', 'GhostAcademy', 'GhostAlternate', 'GhostNova', 'Hellion', 'Hellbat', 'KD8Charge', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'Nuke', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reactor', 'Reaper', 'Refinery', 'RefineryRich', 'RepairDrone', 'SCV', 'SensorTower', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'StarportReactor', 'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BanelingNest', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'BroodlingEscort', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'CreepTumor', 'CreepTumorBurrowed', 'CreepTumorQueen', 'Drone', 'DroneBurrowed', 'EvolutionChamber', 'Extractor', 'ExtractorRich', 'GreaterSpire', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'HydraliskDen', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Larva', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpawningPool', 'SpineCrawler', 'SpineCrawlerUprooted', 'Spire', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'UltraliskCavern', 'Viper', 'Zergling', 'ZerglingBurrowed']}, - 322: {'action_name': 'Effect_NukeCalldown_pt', 'selected_type': [144, 145, 50], 'target_type': [], 'selected_type_name': ['GhostAlternate', 'GhostNova', 'Ghost'], 'target_type_name': []}, - 323: {'action_name': 'Effect_ParasiticBomb_unit', 'selected_type': [499], 'target_type': [311, 801, 141, 61, 1955, 79, 4, 72, 69, 76, 694, 733, 64, 135, 63, 62, 75, 83, 85, 10, 488, 59, 82, 1911, 495, 78, 66, 84, 60, 894, 70, 71, 77, 1910, 74, 67, 732, 496, 68, 65, 80, 133, 81, 136, 73, 29, 31, 55, 21, 46, 38, 37, 57, 24, 18, 36, 692, 22, 27, 43, 40, 39, 30, 50, 26, 144, 145, 53, 484, 830, 689, 734, 268, 51, 48, 54, 23, 58, 132, 134, 130, 11, 56, 6, 49, 20, 1960, 1913, 45, 25, 33, 32, 28, 44, 42, 41, 19, 47, 5, 52, 691, 34, 35, 498, 500, 9, 115, 8, 96, 114, 113, 289, 143, 12, 15, 14, 13, 17, 16, 103, 112, 87, 137, 138, 104, 116, 90, 88, 1956, 102, 86, 101, 107, 117, 91, 94, 7, 120, 150, 111, 127, 100, 151, 489, 693, 502, 503, 504, 501, 108, 142, 95, 106, 893, 892, 129, 128, 1912, 824, 126, 125, 688, 690, 687, 110, 118, 97, 89, 98, 139, 92, 99, 140, 494, 493, 109, 131, 93, 499, 105, 119], 'selected_type_name': ['Viper'], 'target_type_name': ['Adept', 'AdeptPhaseShift', 'Archon', 'Assimilator', 'AssimilatorRich', 'Carrier', 'Colossus', 'CyberneticsCore', 'DarkShrine', 'DarkTemplar', 'Disruptor', 'DisruptorPhased', 'FleetBeacon', 'ForceField', 'Forge', 'Gateway', 'HighTemplar', 'Immortal', 'Interceptor', 'Mothership', 'MothershipCore', 'Nexus', 'Observer', 'ObserverSurveillanceMode', 'Oracle', 'Phoenix', 'PhotonCannon', 'Probe', 'Pylon', 'PylonOvercharged', 'RoboticsBay', 'RoboticsFacility', 'Sentry', 'ShieldBattery', 'Stalker', 'Stargate', 'StasisTrap', 'Tempest', 'TemplarArchive', 'TwilightCouncil', 'VoidRay', 'WarpGate', 'WarpPrism', 'WarpPrismPhasing', 'Zealot', 'Armory', 'AutoTurret', 'Banshee', 'Barracks', 'BarracksFlying', 'BarracksReactor', 'BarracksTechLab', 'Battlecruiser', 'Bunker', 'CommandCenter', 'CommandCenterFlying', 'Cyclone', 'EngineeringBay', 'Factory', 'FactoryFlying', 'FactoryReactor', 'FactoryTechLab', 'FusionCore', 'Ghost', 'GhostAcademy', 'GhostAlternate', 'GhostNova', 'Hellion', 'Hellbat', 'KD8Charge', 'Liberator', 'LiberatorAG', 'MULE', 'Marauder', 'Marine', 'Medivac', 'MissileTurret', 'Nuke', 'OrbitalCommand', 'OrbitalCommandFlying', 'PlanetaryFortress', 'PointDefenseDrone', 'Raven', 'Reactor', 'Reaper', 'Refinery', 'RefineryRich', 'RepairDrone', 'SCV', 'SensorTower', 'SiegeTank', 'SiegeTankSieged', 'Starport', 'StarportFlying', 'StarportReactor', 'StarportTechLab', 'SupplyDepot', 'SupplyDepotLowered', 'TechLab', 'Thor', 'ThorHighImpactMode', 'VikingAssault', 'VikingFighter', 'WidowMine', 'WidowMineBurrowed', 'Baneling', 'BanelingBurrowed', 'BanelingCocoon', 'BanelingNest', 'BroodLord', 'BroodLordCocoon', 'Broodling', 'BroodlingEscort', 'Changeling', 'ChangelingMarine', 'ChangelingMarineShield', 'ChangelingZealot', 'ChangelingZergling', 'ChangelingZerglingWings', 'Cocoon', 'Corruptor', 'CreepTumor', 'CreepTumorBurrowed', 'CreepTumorQueen', 'Drone', 'DroneBurrowed', 'EvolutionChamber', 'Extractor', 'ExtractorRich', 'GreaterSpire', 'Hatchery', 'Hive', 'Hydralisk', 'HydraliskBurrowed', 'HydraliskDen', 'InfestationPit', 'InfestedTerran', 'InfestedTerranBurrowed', 'InfestedTerranCocoon', 'Infestor', 'InfestorBurrowed', 'Lair', 'Larva', 'Locust', 'LocustFlying', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'LurkerCocoon', 'Mutalisk', 'NydusCanal', 'NydusNetwork', 'Overlord', 'OverlordTransport', 'OverlordTransportCocoon', 'Overseer', 'OverseerCocoon', 'OverseerOversightMode', 'ParasiticBombDummy', 'Queen', 'QueenBurrowed', 'Ravager', 'RavagerBurrowed', 'RavagerCocoon', 'Roach', 'RoachBurrowed', 'RoachWarren', 'SpawningPool', 'SpineCrawler', 'SpineCrawlerUprooted', 'Spire', 'SporeCrawler', 'SporeCrawlerUprooted', 'SwarmHost', 'SwarmHostBurrowed', 'Ultralisk', 'UltraliskBurrowed', 'UltraliskCavern', 'Viper', 'Zergling', 'ZerglingBurrowed']}, - 332: {'action_name': 'Effect_Salvage_quick', 'selected_type': [24], 'target_type': [], 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'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 538: {'action_name': 'Effect_KD8Charge_unit', 'selected_type': [49], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 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'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 553: {'action_name': 'Research_AnabolicSynthesis_quick', 'selected_type': [93], 'target_type': [], 'selected_type_name': ['UltraliskCavern'], 'target_type_name': []}, - 554: {'action_name': 'Research_CycloneLockOnDamage_quick', 'selected_type': [39], 'target_type': [], 'selected_type_name': ['FactoryTechLab'], 'target_type_name': []}, - 556: {'action_name': 'UnloadUnit_quick', 'selected_type': [81, 136, 24, 18, 54, 142, 95, 893, 36, 130], 'target_type': [], 'selected_type_name': ['WarpPrism', 'WarpPrismPhasing', 'Bunker', 'CommandCenter', 'Medivac', 'NydusCanal', 'NydusNetwork', 'OverlordTransport', 'CommandCenterFlying', 'PlanetaryFortress'], 'target_type_name': []}, - 24: {'action_name': 'Hallucination_HighTemplar_quick', 'selected_type': [77], 'target_type': [], 'selected_type_name': ['Sentry'], 'target_type_name': []}, - 93: {'action_name': 'Hallucination_Adept_quick', 'selected_type': [77], 'target_type': [], 'selected_type_name': ['Sentry'], 'target_type_name': []}, - 200: {'action_name': 'Build_Interceptors_autocast', 'selected_type': [79], 'target_type': [], 'selected_type_name': ['Carrier'], 'target_type_name': []}, - 247: {'action_name': 'BurrowUp_autocast', 'selected_type': [115, 117, 119], 'target_type': [], 'selected_type_name': ['BanelingBurrowed', 'HydraliskBurrowed', 'ZerglingBurrowed'], 'target_type_name': []}, - 302: {'action_name': 'Effect_Charge_autocast', 'selected_type': [73], 'target_type': [], 'selected_type_name': ['Zealot'], 'target_type_name': []}, - 312: {'action_name': 'Effect_Heal_autocast', 'selected_type': [54], 'target_type': [], 'selected_type_name': ['Medivac'], 'target_type_name': []}, - 324: {'action_name': 'Effect_Repair_autocast', 'selected_type': [268, 45], 'target_type': [], 'selected_type_name': ['MULE', 'SCV'], 'target_type_name': []}, - 331: {'action_name': 'Effect_Restore_autocast', 'selected_type': [1910], 'target_type': [], 'selected_type_name': ['ShieldBattery'], 'target_type_name': []}, - 541: {'action_name': 'Effect_LockOn_autocast', 'selected_type': [692], 'target_type': [], 'selected_type_name': ['Cyclone'], 'target_type_name': []}, - 544: {'action_name': 'Morph_WarpGate_autocast', 'selected_type': [62], 'target_type': [], 'selected_type_name': ['Gateway'], 'target_type_name': []}, - 112: {'action_name': 'Effect_Blink_unit', 'selected_type': [74, 76], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Stalker', 'DarkTemplar'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 300: {'action_name': 'Effect_Charge_pt', 'selected_type': [73], 'target_type': [], 'selected_type_name': ['Zealot'], 'target_type_name': []}, - 33: {'action_name': 'Effect_ChronoBoost_unit', 'selected_type': [59], 'target_type': [64, 65, 67, 68, 69, 70, 71, 72, 133, 59, 62, 63], 'selected_type_name': ['Nexus'], 'target_type_name': ['FleetBeacon', 'TwilightCouncil', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'WarpGate', 'Nexus', 'Gateway', 'Forge']}, - 306: {'action_name': 'Effect_EMP_unit', 'selected_type': [144, 145, 50], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['GhostAlternate', 'GhostNova', 'Ghost'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 309: {'action_name': 'Effect_FungalGrowth_unit', 'selected_type': [111], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['Infestor'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 313: {'action_name': 'Effect_ImmortalBarrier_autocast', 'selected_type': [83], 'target_type': [], 'selected_type_name': ['Immortal'], 'target_type_name': []}, - 91: {'action_name': 'Effect_ImmortalBarrier_quick', 'selected_type': [83], 'target_type': [], 'selected_type_name': ['Immortal'], 'target_type_name': []}, - 108: {'action_name': 'Effect_Repair_pt', 'selected_type': [268, 45], 'target_type': [], 'selected_type_name': ['MULE', 'SCV'], 'target_type_name': []}, - 336: {'action_name': 'Effect_SpawnLocusts_unit', 'selected_type': [493, 494], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['SwarmHostBurrowed', 'SwarmHost'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 353: {'action_name': 'Effect_WidowMineAttack_autocast', 'selected_type': [498, 500], 'target_type': [], 'selected_type_name': ['WidowMine', 'WidowMineBurrowed'], 'target_type_name': []}, - 351: {'action_name': 'Effect_WidowMineAttack_pt', 'selected_type': [498, 500], 'target_type': [], 'selected_type_name': ['WidowMine', 'WidowMineBurrowed'], 'target_type_name': []}, - 352: {'action_name': 'Effect_WidowMineAttack_unit', 'selected_type': [498, 500], 'target_type': [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 268, 289, 311, 321, 322, 324, 330, 335, 336, 341, 342, 343, 344, 350, 364, 365, 371, 372, 373, 376, 377, 472, 473, 474, 475, 483, 484, 485, 486, 487, 488, 489, 490, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 517, 518, 559, 560, 561, 562, 563, 564, 588, 589, 590, 591, 608, 609, 610, 612, 628, 629, 630, 638, 639, 640, 641, 642, 643, 648, 649, 651, 661, 662, 663, 664, 665, 666, 687, 688, 689, 690, 691, 692, 693, 694, 732, 733, 734, 796, 797, 801, 824, 830, 877, 880, 881, 884, 885, 886, 887, 892, 893, 894, 1904, 1908, 1910, 1911, 1912, 1913, 1955, 1956, 1957, 1958, 1960, 1961], 'selected_type_name': ['WidowMine', 'WidowMineBurrowed'], 'target_type_name': ['Colossus', 'TechLab', 'Reactor', 'InfestedTerran', 'BanelingCocoon', 'Baneling', 'Mothership', 'PointDefenseDrone', 'Changeling', 'ChangelingZealot', 'ChangelingMarineShield', 'ChangelingMarine', 'ChangelingZerglingWings', 'ChangelingZergling', 'CommandCenter', 'SupplyDepot', 'Refinery', 'Barracks', 'EngineeringBay', 'MissileTurret', 'Bunker', 'SensorTower', 'GhostAcademy', 'Factory', 'Starport', 'Armory', 'FusionCore', 'AutoTurret', 'SiegeTankSieged', 'SiegeTank', 'VikingAssault', 'VikingFighter', 'CommandCenterFlying', 'BarracksTechLab', 'BarracksReactor', 'FactoryTechLab', 'FactoryReactor', 'StarportTechLab', 'StarportReactor', 'FactoryFlying', 'StarportFlying', 'SCV', 'BarracksFlying', 'SupplyDepotLowered', 'Marine', 'Reaper', 'Ghost', 'Marauder', 'Thor', 'Hellion', 'Medivac', 'Banshee', 'Raven', 'Battlecruiser', 'Nuke', 'Nexus', 'Pylon', 'Assimilator', 'Gateway', 'Forge', 'FleetBeacon', 'TwilightCouncil', 'PhotonCannon', 'Stargate', 'TemplarArchive', 'DarkShrine', 'RoboticsBay', 'RoboticsFacility', 'CyberneticsCore', 'Zealot', 'Stalker', 'HighTemplar', 'DarkTemplar', 'Sentry', 'Phoenix', 'Carrier', 'VoidRay', 'WarpPrism', 'Observer', 'Immortal', 'Probe', 'Interceptor', 'Hatchery', 'CreepTumor', 'Extractor', 'SpawningPool', 'EvolutionChamber', 'HydraliskDen', 'Spire', 'UltraliskCavern', 'InfestationPit', 'NydusNetwork', 'BanelingNest', 'RoachWarren', 'SpineCrawler', 'SporeCrawler', 'Lair', 'Hive', 'GreaterSpire', 'Cocoon', 'Drone', 'Zergling', 'Overlord', 'Hydralisk', 'Mutalisk', 'Ultralisk', 'Roach', 'Infestor', 'Corruptor', 'BroodLordCocoon', 'BroodLord', 'BanelingBurrowed', 'DroneBurrowed', 'HydraliskBurrowed', 'RoachBurrowed', 'ZerglingBurrowed', 'InfestedTerranBurrowed', 'QueenBurrowed', 'Queen', 'InfestorBurrowed', 'OverseerCocoon', 'Overseer', 'PlanetaryFortress', 'UltraliskBurrowed', 'OrbitalCommand', 'WarpGate', 'OrbitalCommandFlying', 'ForceField', 'WarpPrismPhasing', 'CreepTumorBurrowed', 'CreepTumorQueen', 'SpineCrawlerUprooted', 'SporeCrawlerUprooted', 'Archon', 'NydusCanal', 'BroodlingEscort', 'GhostAlternate', 'GhostNova', 'RichMineralField', 'RichMineralField750', 'XelNagaTower', 'InfestedTerranCocoon', 'Larva', 'MULE', 'Broodling', 'Adept', 'Lyote', 'CarrionBird', 'KarakFemale', 'UtilityBot', 'Scantipede', 'Dog', 'MineralField', 'VespeneGeyser', 'SpacePlatformGeyser', 'RichVespeneGeyser', 'DestructibleBillboardTall', 'DestructibleDebris4x4', 'DestructibleDebris6x6', 'DestructibleRock6x6', 'DestructibleRampDiagonalHugeULBR', 'DestructibleRampDiagonalHugeBLUR', 'DestructibleDebrisRampDiagonalHugeULBR', 'DestructibleDebrisRampDiagonalHugeBLUR', 'UnbuildableRocksDestructible', 'UnbuildableBricksDestructible', 'UnbuildablePlatesDestructible', 'Debris2x2NonConjoined', 'MineralField750', 'Hellbat', 'CollapsibleTerranTowerDebris', 'DebrisRampLeft', 'DebrisRampRight', 'MothershipCore', 'Locust', 'CollapsibleRockTowerDebris', 'SwarmHostBurrowed', 'SwarmHost', 'Oracle', 'Tempest', 'WidowMine', 'Viper', 'WidowMineBurrowed', 'LurkerCocoon', 'Lurker', 'LurkerBurrowed', 'LurkerDen', 'CollapsibleRockTowerDebrisRampRight', 'CollapsibleRockTowerDebrisRampLeft', 'CollapsibleTerranTowerPushUnitRampLeft', 'CollapsibleTerranTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnit', 'CollapsibleTerranTowerPushUnit', 'CollapsibleRockTowerPushUnitRampRight', 'CollapsibleRockTowerPushUnitRampLeft', 'CollapsibleRockTowerDiagonal', 'CollapsibleTerranTowerDiagonal', 'CollapsibleTerranTowerRampLeft', 'CollapsibleTerranTowerRampRight', 'ProtossVespeneGeyser', 'CollapsibleRockTower', 'CollapsibleTerranTower', 'CleaningBot', 'DestructibleCityDebris4x4', 'DestructibleCityDebris6x6', 'DestructibleCityDebrisHugeDiagonalBLUR', 'DestructibleRockEx14x4', 'DestructibleRockEx16x6', 'DestructibleRockEx1DiagonalHugeULBR', 'DestructibleRockEx1DiagonalHugeBLUR', 'DestructibleRockEx1VerticalHuge', 'DestructibleRockEx1HorizontalHuge', 'DestructibleIce4x4', 'DestructibleIce6x6', 'DestructibleIceDiagonalHugeBLUR', 'LabBot', 'Crabeetle', 'CollapsibleRockTowerRampRight', 'CollapsibleRockTowerRampLeft', 'LabMineralField', 'LabMineralField750', 'RavagerCocoon', 'Ravager', 'Liberator', 'RavagerBurrowed', 'ThorHighImpactMode', 'Cyclone', 'LocustFlying', 'Disruptor', 'StasisTrap', 'DisruptorPhased', 'LiberatorAG', 'PurifierRichMineralField', 'PurifierRichMineralField750', 'AdeptPhaseShift', 'ParasiticBombDummy', 'KD8Charge', 'ReptileCrate', 'PurifierVespeneGeyser', 'ShakurasVespeneGeyser', 'PurifierMineralField', 'PurifierMineralField750', 'BattleStationMineralField', 'BattleStationMineralField750', 'OverlordTransportCocoon', 'OverlordTransport', 'PylonOvercharged', 'XelNagaDestructibleBlocker8NE', 'XelNagaDestructibleBlocker8SW', 'ShieldBattery', 'ObserverSurveillanceMode', 'OverseerOversightMode', 'RepairDrone', 'AssimilatorRich', 'ExtractorRich', 'InhibitorZoneSmall', 'InhibitorZoneMedium', 'RefineryRich', 'MineralField450']}, - 392: {'action_name': 'Morph_LurkerDen_quick', 'selected_type': [91], 'target_type': [], 'selected_type_name': ['HydraliskDen'], 'target_type_name': []}, - 393: {'action_name': 'Morph_Mothership_quick', 'selected_type': [488], 'target_type': [], 'selected_type_name': ['MothershipCore'], 'target_type_name': []}, - 435: {'action_name': 'Research_CycloneRapidFireLaunchers_quick', 'selected_type': [39], 'target_type': [], 'selected_type_name': ['FactoryTechLab'], 'target_type_name': []}, - 563: {'action_name': 'Research_EnhancedShockwaves_quick', 'selected_type': [26], 'target_type': [], 'selected_type_name': ['GhostAcademy'], 'target_type_name': []}, - 18: {'action_name': 'Research_InterceptorGravitonCatapult_quick', 'selected_type': [64], 'target_type': [], 'selected_type_name': ['FleetBeacon'], 'target_type_name': []}, - 443: {'action_name': 'Research_NeosteelFrame_quick', 'selected_type': [22], 'target_type': [], 'selected_type_name': ['EngineeringBay'], 'target_type_name': []}, - 449: {'action_name': 'Research_RavenRecalibratedExplosives_quick', 'selected_type': [41], 'target_type': [], 'selected_type_name': ['StarportTechLab'], 'target_type_name': []}, - 513: {'action_name': 'Train_MothershipCore_quick', 'selected_type': [59], 'target_type': [], 'selected_type_name': ['Nexus'], 'target_type_name': []}, -} - -def get_general(general_id): - return {k: v for k, v in ACTION_INFO_MASK.items() if v['ability_id'] == general_id} - - -def merge_judge(target_general_action, val): - ret = [] - for k, v in target_general_action.items(): - if v['target_unit'] != val['target_unit']: - continue - if v['target_location'] != val['target_location']: - continue - if v['func_type'] != val['func_type']: - continue - ret.append(k) - try: - assert(len(ret) == 1) - except AssertionError: - print(target_general_action) - print(val) - print(ret) - return ret[0] - - -GENERAL_ACTION_INFO_MASK = {} -ACT_TO_GENERAL_ACT = {} -ACT_TO_GENERAL_ACT_ARRAY = np.full(max(ACTION_INFO_MASK.keys()) + 1, -1, dtype=np.int) -for k, v in ACTION_INFO_MASK.items(): - general_id = v['general_id'] - if general_id is None or general_id == 0: - GENERAL_ACTION_INFO_MASK[k] = v - ACT_TO_GENERAL_ACT[k] = k - ACT_TO_GENERAL_ACT_ARRAY[k] = k - else: - target_general_action = get_general(general_id) - action_id = merge_judge(target_general_action, v) - ACT_TO_GENERAL_ACT[k] = action_id - ACT_TO_GENERAL_ACT_ARRAY[k] = action_id - - -ACTION_RACE_MASK = { -'zerg': torch.tensor([False, False, True, True, True, True, False, False, True, True, - True, True, False, False, False, False, True, False, False, False, - True, False, False, False, True, True, False, False, False, False, - False, False, True, True, True, False, False, True, False, False, - False, True, True, False, False, False, False, False, True, False, - False, False, False, True, True, True, True, False, False, False, - False, False, False, False, False, True, True, True, True, True, - True, True, False, False, False, True, False, False, False, False, - True, False, False, False, False, False, True, True, False, False, - True, False, False, True, True, False, False, False, False, False, - False, False, True, True, False, False, False, False, False, True, - False, False, True, False, False, True, False, False, False, False, - False, False, False, False, False, True, True, True, True, False, - False, False, False, True, True, False, False, False, False, False, - False, False, False, False, False, False, False, False, False, False, - False, False, False, False, True, True, True, False, False, False, - True, False, True, False, True, False, False, True, True, False, - False, True, True, False, False, False, True, True, True, True, - False, True, True, False, False, False, False, False, False, False, - True, False, False, False, False, False, False, True, True, True, - True, True, True, True, True, True, False, False, True, False, - False, False, False, True, True, False, True, False, False, False, - False, False, False, False, True, False, False, True, False, False, - False, False, True, False, True, True, False, False, True, False, - False, False, False, False, False, False, False, False, False, False, - False, False, False, False, False, False, True, False, True, True, - True, True, True, True, True, True, True, True, False, True, - False, False, False, False, True, False, False, False, True, False, - False, False, False, True, False, True, False, False, False, False, - False, False, True, False, False, True, False, False, True, False, - False, True, False, False, False, False, True, False, False, True, - False, True, False, False, False, False, False, False, False, False, - False, False, True, True, True, True, True]), -'terran': torch.tensor([False, False, True, True, False, False, True, True, False, False, - True, True, False, False, True, False, False, True, True, True, - False, False, False, True, False, False, True, False, False, True, - False, True, False, False, False, False, False, False, True, False, - True, False, False, False, False, True, True, True, False, False, - False, True, False, False, False, False, False, False, True, False, - True, True, True, False, False, False, True, True, True, True, - True, False, False, True, True, False, False, False, True, True, - False, False, False, False, False, False, False, False, True, True, - False, False, False, False, False, True, False, False, True, True, - False, False, False, False, True, True, True, True, True, False, - False, True, False, True, False, False, False, False, True, True, - True, False, False, True, True, False, False, False, True, True, - True, True, False, False, False, False, True, True, True, True, - False, False, False, False, False, False, False, False, False, False, - False, False, False, True, True, True, True, True, True, True, - True, False, False, False, False, True, True, False, False, True, - True, False, False, False, False, True, False, False, False, False, - True, False, False, True, True, True, False, True, True, True, - False, True, True, False, False, False, False, True, True, True, - True, True, True, True, True, False, False, True, False, True, - True, True, False, False, False, False, False, True, True, True, - True, True, True, False, False, False, False, False, True, True, - True, False, False, True, False, False, True, False, False, False, - False, False, False, False, False, True, True, False, True, True, - True, True, True, True, True, True, False, False, False, False, - False, False, False, False, False, True, True, True, False, False, - True, True, False, False, False, True, False, False, False, True, - True, True, False, False, False, False, True, True, True, True, - False, False, False, False, False, False, False, False, False, True, - True, False, True, False, True, False, False, False, True, False, - True, False, False, False, False, False, False, False, False, False, - True, False, False, True, True, True, True]), -'protoss': torch.tensor([False, False, True, True, False, False, False, False, False, False, - False, False, True, True, False, True, False, False, False, False, - False, True, True, False, False, False, False, True, True, False, - True, False, False, False, False, True, True, False, False, True, - False, False, False, True, True, False, False, False, False, True, - True, False, True, False, False, False, False, True, False, True, - False, False, False, True, True, False, False, False, False, True, - True, False, True, False, False, False, True, True, False, False, - False, True, True, True, True, True, False, False, False, False, - False, True, True, False, False, False, True, True, False, False, - True, True, False, False, False, False, False, False, False, False, - True, False, False, False, True, False, True, True, False, False, - False, True, True, False, False, False, False, False, True, False, - False, False, True, False, False, True, False, False, False, False, - True, True, True, True, True, True, True, True, True, True, - True, True, True, False, True, True, True, False, False, False, - True, True, False, True, False, False, False, False, False, False, - False, False, False, True, True, False, False, False, False, False, - False, False, False, False, False, False, True, False, False, False, - False, False, False, True, True, True, True, True, True, True, - True, True, True, True, True, False, True, False, False, False, - False, False, True, False, False, True, False, False, False, False, - False, False, False, True, False, True, True, False, False, False, - False, True, False, False, False, False, False, True, False, True, - True, True, True, True, True, False, False, True, False, False, - False, False, False, False, False, False, False, True, False, False, - False, False, False, False, False, True, True, True, True, False, - False, False, True, True, False, False, True, True, False, False, - False, False, True, False, True, False, False, False, False, False, - True, True, False, True, True, False, True, True, False, False, - False, False, False, True, False, True, False, True, False, False, - False, False, True, True, True, True, True, True, True, True, - False, True, False, True, True, False, True])} - - -class StaticData(object): - """Expose static data in a more useful form than the raw protos.""" - - def __init__(self, data): - """Takes data from RequestData.""" - self._units = {u.unit_id: u.name for u in data.units} - self._unit_stats = {u.unit_id: u for u in data.units} - self._upgrades = {a.upgrade_id: a for a in data.upgrades} - self._abilities = {a.ability_id: a for a in data.abilities} - self._general_abilities = {a.remaps_to_ability_id for a in data.abilities if a.remaps_to_ability_id} - - for a in six.itervalues(self._abilities): - a.hotkey = a.hotkey.lower() - - @property - def abilities(self): - return self._abilities - - @property - def upgrades(self): - return self._upgrades - - @property - def units(self): - return self._units - - @property - def unit_stats(self): - return self._unit_stats - - @property - def general_abilities(self): - return self._general_abilities - - -def get_reorder_lookup_array(input): - num = max(input) - # use -1 as marker for invalid entry - array = torch.full((num + 1, ), -1, dtype=torch.long) - for index, item in enumerate(input): - array[item] = index - return array - - -# List of used/available abilities found by parsing replays. -ABILITIES = [ - 0, # invalid - 1, - 4, - 6, - 7, - 16, - 17, - 18, - 19, - 23, - 26, - 28, - 30, - 32, - 36, - 38, - 42, - 44, - 46, - 74, - 76, - 78, - 80, - 110, - 140, - 142, - 144, - 146, - 148, - 150, - 152, - 154, - 156, - 158, - 160, - 162, - 164, - 166, - 167, - 169, - 171, - 173, - 174, - 181, - 195, - 199, - 203, - 207, - 211, - 212, - 216, - 217, - 247, - 249, - 250, - 251, - 253, - 255, - 261, - 263, - 265, - 295, - 296, - 298, - 299, - 304, - 305, - 306, - 307, - 308, - 309, - 312, - 313, - 314, - 315, - 316, - 318, - 319, - 320, - 321, - 322, - 323, - 324, - 326, - 327, - 328, - 329, - 331, - 333, - 348, - 380, - 382, - 383, - 386, - 388, - 390, - 392, - 393, - 394, - 396, - 397, - 399, - 401, - 403, - 405, - 407, - 408, - 410, - 413, - 415, - 416, - 417, - 419, - 421, - 422, - 451, - 452, - 454, - 455, - 484, - 485, - 487, - 488, - 517, - 518, - 520, - 522, - 524, - 554, - 556, - 558, - 560, - 561, - 562, - 563, - 591, - 594, - 595, - 596, - 597, - 614, - 620, - 621, - 622, - 623, - 624, - 626, - 650, - 651, - 652, - 653, - 654, - 655, - 656, - 657, - 658, - 710, - 730, - 731, - 732, - 761, - 764, - 766, - 768, - 769, - 790, - 793, - 799, - 803, - 804, - 805, - 820, - 822, - 855, - 856, - 857, - 861, - 862, - 863, - 864, - 865, - 866, - 880, - 881, - 882, - 883, - 884, - 885, - 886, - 887, - 889, - 890, - 891, - 892, - 893, - 894, - 895, - 911, - 913, - 914, - 916, - 917, - 919, - 920, - 921, - 922, - 946, - 948, - 950, - 954, - 955, - 976, - 977, - 978, - 979, - 994, - 1006, - 1036, - 1038, - 1039, - 1042, - 1062, - 1063, - 1064, - 1065, - 1066, - 1067, - 1068, - 1069, - 1070, - 1093, - 1094, - 1097, - 1126, - 1152, - 1154, - 1155, - 1156, - 1157, - 1158, - 1159, - 1160, - 1161, - 1162, - 1163, - 1165, - 1166, - 1167, - 1183, - 1184, - 1186, - 1187, - 1188, - 1189, - 1190, - 1191, - 1192, - 1193, - 1194, - 1216, - 1217, - 1218, - 1219, - 1220, - 1221, - 1223, - 1225, - 1252, - 1253, - 1282, - 1283, - 1312, - 1313, - 1314, - 1315, - 1316, - 1317, - 1342, - 1343, - 1344, - 1345, - 1346, - 1348, - 1351, - 1352, - 1353, - 1354, - 1356, - 1372, - 1373, - 1374, - 1376, - 1378, - 1380, - 1382, - 1384, - 1386, - 1388, - 1390, - 1392, - 1394, - 1396, - 1406, - 1408, - 1409, - 1413, - 1414, - 1416, - 1417, - 1418, - 1419, - 1433, - 1435, - 1437, - 1438, - 1440, - 1442, - 1444, - 1446, - 1448, - 1449, - 1450, - 1451, - 1454, - 1455, - 1482, - 1512, - 1514, - 1516, - 1517, - 1518, - 1520, - 1522, - 1524, - 1526, - 1528, - 1530, - 1532, - 1562, - 1563, - 1564, - 1565, - 1566, - 1567, - 1568, - 1592, - 1593, - 1594, - 1622, - 1623, - 1628, - 1632, - 1664, - 1682, - 1683, - 1684, - 1691, - 1692, - 1693, - 1694, - 1725, - 1727, - 1729, - 1730, - 1731, - 1732, - 1733, - 1763, - 1764, - 1766, - 1768, - 1819, - 1825, - 1831, - 1832, - 1833, - 1834, - 1847, - 1848, - 1853, - 1974, - 1978, - 1998, - 2014, - 2016, - 2048, - 2057, - 2063, - 2067, - 2073, - 2081, - 2082, - 2095, - 2097, - 2099, - 2108, - 2110, - 2112, - 2113, - 2114, - 2116, - 2146, - 2162, - 2244, - 2324, - 2328, - 2330, - 2331, - 2332, - 2333, - 2338, - 2340, - 2342, - 2346, - 2350, - 2354, - 2358, - 2362, - 2364, - 2365, - 2368, - 2370, - 2371, - 2373, - 2375, - 2376, - 2387, - 2389, - 2391, - 2393, - 2505, - 2535, - 2542, - 2544, - 2550, - 2552, - 2558, - 2560, - 2588, - 2594, - 2596, - 2700, - 2704, - 2708, - 2709, - 2714, - 2720, - 3707, - 3709, - 3739, - 3741, - 3743, - 3745, - 3747, - 3749, - 3751, - 3753, - 3755, - 3757, - 3765, - 3771, - 3776, - 3777, - 3778, - 3783, -] - -# 356, 503, 547, 360, 515, 193, 10, 197, 528, 495, 516, 184, 491, 190, 483, # TODO -# 498, 192, 215, 189, 437, 519, 514, 219, 198, 507, 204, 400, 349, 492, 431, -# 543, 201, 387, 442, 479, 551, 489, 425, 218, 447, 238, 220, 501, 391, 445, -# 438, 526, 350, 256, 494, 493, - -NUM_ABILITIES = len(ABILITIES) - -ABILITIES_REORDER = {item: idx for idx, item in enumerate(ABILITIES)} - -ABILITIES_REORDER_ARRAY = get_reorder_lookup_array(ABILITIES) - -# List of known unit types. It is generated by parsing replays and from: -# https://github.com/Blizzard/s2client-api/blob/master/include/sc2api/sc2_typeenums.h -UNIT_TYPES = [ - 0, - 4, - 5, - 6, - 7, - 8, - 9, - 10, - 11, - 12, - 13, - 14, - 15, - 16, - 17, - 18, - 19, - 20, - 21, - 22, - 23, - 24, - 25, - 26, - 27, - 28, - 29, - 30, - 31, - 32, - 33, - 34, - 35, - 36, - 37, - 38, - 39, - 40, - 41, - 42, - 43, - 44, - 45, - 46, - 47, - 48, - 49, - 50, - 51, - 52, - 53, - 54, - 55, - 56, - 57, - 58, - 59, - 60, - 61, - 62, - 63, - 64, - 65, - 66, - 67, - 68, - 69, - 70, - 71, - 72, - 73, - 74, - 75, - 76, - 77, - 78, - 79, - 80, - 81, - 82, - 83, - 84, - 85, - 86, - 87, - 88, - 89, - 90, - 91, - 92, - 93, - 94, - 95, - 96, - 97, - 98, - 99, - 100, - 101, - 102, - 103, - 104, - 105, - 106, - 107, - 108, - 109, - 110, - 111, - 112, - 113, - 114, - 115, - 116, - 117, - 118, - 119, - 120, - 125, - 126, - 127, - 128, - 129, - 130, - 131, - 132, - 133, - 134, - 135, - 136, - 137, - 138, - 139, - 140, - 141, - 142, - 143, - 144, - 145, - 146, - 147, - 149, - 150, - 151, - 268, - 289, - 311, - 321, - 322, - 324, - 330, - 335, - 336, - 341, - 342, - 343, - 344, - 350, - 364, - 365, - 371, - 372, - 373, - 376, - 377, - 472, - 473, - 474, - 475, - 483, - 484, - 485, - 486, - 487, - 488, - 489, - 490, - 493, - 494, - 495, - 496, - 498, - 499, - 500, - 501, - 502, - 503, - 504, - 517, - 518, - 559, - 560, - 561, - 562, - 563, - 564, - 588, - 589, - 590, - 591, - 608, - 609, - 610, - 612, - 628, - 629, - 630, - 638, - 639, - 640, - 641, - 642, - 643, - 648, - 649, - 651, - 661, - 662, - 663, - 664, - 665, - 666, - 687, - 688, - 689, - 690, - 691, - 692, - 693, - 694, - 732, - 733, - 734, - 796, - 797, - 801, - 824, - 830, - 877, - 880, - 881, - 884, - 885, - 886, - 887, - 892, - 893, - 894, - 1904, - 1908, - 1910, - 1911, - 1912, - 1913, - 1955, - 1956, - 1957, - 1958, - 1960, - 1961, -] - -UNIT_TYPES_REORDER = {item: idx for idx, item in enumerate(UNIT_TYPES)} - -NUM_UNIT_TYPES = len(UNIT_TYPES) - -UNIT_TYPES_REORDER_ARRAY = get_reorder_lookup_array(UNIT_TYPES) - -# List of used buffs found by parsing replays. -BUFFS = [ - 0, # TODO - 5, - 6, - 7, - 8, - 11, - 12, - 13, - 16, - 17, - 18, - 22, - 24, - 25, - 27, - 28, - 29, - 30, - 33, - 36, - 38, - 49, - 59, - 83, - 89, - 99, - 102, - 116, - 121, - 122, - 129, - 132, - 133, - 134, - 136, - 137, - 145, - 271, - 272, - 273, - 274, - 275, - 277, - 279, - 280, - 281, - 288, - 289, - 20, - 97, -] - -NUM_BUFFS = len(BUFFS) - -BUFFS_REORDER = {item: idx for idx, item in enumerate(BUFFS)} - -BUFFS_REORDER_ARRAY = get_reorder_lookup_array(BUFFS) - -# List of used upgrades found by parsing replays. -UPGRADES = [ - 0, - 1, - 2, - 3, - 4, - 5, - 6, - 7, - 8, - 9, - 10, - 11, - 12, - 13, - 15, - 16, - 17, - 19, - 20, - 22, - 25, - 30, - 31, - 32, - 36, - 37, - 38, - 39, - 40, - 41, - 42, - 43, - 44, - 45, - 46, - 47, - 48, - 49, - 50, - 52, - 53, - 54, - 55, - 56, - 57, - 58, - 59, - 60, - 61, - 62, - 64, - 65, - 66, - 68, - 69, - 70, - 71, - 72, - 73, - 74, - 75, - 76, - 78, - 79, - 80, - 81, - 82, - 83, - 84, - 86, - 87, - 88, - 99, - 101, - 116, - 117, - 118, - 122, - 130, - 134, - 135, - 136, - 139, - 140, - 141, - 144, - 289, - 291, - 293, - 296, -] - -NUM_UPGRADES = len(UPGRADES) - -UPGRADES_REORDER = {item: idx for idx, item in enumerate(UPGRADES)} - -UPGRADES_REORDER_ARRAY = get_reorder_lookup_array(UPGRADES) - -UPGRADES_REORDER_INV = {v: k for k, v in UPGRADES_REORDER.items()} - -UPGRADES_REORDER_INV_ARRAY = UPGRADES - -ADDON = [0, 5, 6, 37, 38, 39, 40, 41, 42] - -NUM_ADDON = len(ADDON) - -ADDON_REORDER = {item: idx for idx, item in enumerate(ADDON)} - -ADDON_REORDER_ARRAY = get_reorder_lookup_array(ADDON) - -ACTIONS = list(GENERAL_ACTION_INFO_MASK.keys()) - -NUM_ACTIONS = len(ACTIONS) - -NUM_ACTIONS_RAW = len(list(ACTION_INFO_MASK.keys())) - -# this is for the translation from distar.ctools.pysc2 ability id to distar.ctools.pysc2 raw ability id -# _FUNCTIONS: -# https://github.com/deepmind/ctools.pysc2/blob/5ca04dbf6dd0b852966418379e2d95d9ad3393f8/ctools.pysc2/lib/actions.py#L583 -# _RAW_FUNCTIONS: -# https://github.com/deepmind/ctools.pysc2/blob/5ca04dbf6dd0b852966418379e2d95d9ad3393f8/ctools.pysc2/lib/actions.py#L1186 -# ACTIONS_REORDER[ctools.pysc2_ability_id] = distar.ctools.pysc2_raw_ability_id -ACTIONS_REORDER = {item: idx for idx, item in enumerate(ACTIONS)} - -ACTIONS_REORDER_ARRAY = get_reorder_lookup_array(ACTIONS) - -ACTIONS_REORDER_INV = {v: k for k, v in ACTIONS_REORDER.items()} - -ACTIONS_REORDER_INV_ARRAY = ACTIONS - -# Begin actions: actions (raw ability ids) included in the beginning_build_order -target_list = ['unit', 'build', 'research'] -BEGIN_ACTIONS = [k for k, v in GENERAL_ACTION_INFO_MASK.items() if v['goal'] in target_list] -OLD_BEGIN_ACTIONS = [k for k, v in GENERAL_ACTION_INFO_MASK.items() if v['goal'] in target_list + ['effect']] - -removed_actions = [35, 64, 520, 222, 515, 503] -for i in removed_actions: - BEGIN_ACTIONS.remove(i) -NUM_BEGIN_ACTIONS = len(BEGIN_ACTIONS) - -OLD_BEGIN_ACTIONS_REORDER = {item: idx for idx, item in enumerate(OLD_BEGIN_ACTIONS)} - -OLD_BEGIN_ACTIONS_REORDER_INV = {v: k for k, v in OLD_BEGIN_ACTIONS_REORDER.items()} - -BUILD_ORDER_REWARD_ACTIONS = BEGIN_ACTIONS - -BEGIN_ACTIONS_REORDER_ARRAY = get_reorder_lookup_array(BEGIN_ACTIONS) - -UNIT_BUILD_ACTIONS = [k for k, v in GENERAL_ACTION_INFO_MASK.items() if v['goal'] in ['unit', 'build']] - -NUM_UNIT_BUILD_ACTIONS = len(UNIT_BUILD_ACTIONS) - -UNIT_BUILD_ACTIONS_REORDER = {item: idx for idx, item in enumerate(UNIT_BUILD_ACTIONS)} - -UNIT_BUILD_ACTIONS_REORDER_ARRAY = get_reorder_lookup_array(UNIT_BUILD_ACTIONS) - -EFFECT_ACTIONS = [k for k, v in GENERAL_ACTION_INFO_MASK.items() if v['goal'] in ['effect']] - -NUM_EFFECT_ACTIONS = len(EFFECT_ACTIONS) - -EFFECT_ACTIONS_REORDER = {item: idx for idx, item in enumerate(EFFECT_ACTIONS)} - -EFFECT_ACTIONS_REORDER_ARRAY = get_reorder_lookup_array(EFFECT_ACTIONS) - -RESEARCH_ACTIONS = [k for k, v in GENERAL_ACTION_INFO_MASK.items() if v['goal'] in ['research']] - -NUM_RESEARCH_ACTIONS = len(RESEARCH_ACTIONS) - -RESEARCH_ACTIONS_REORDER = {item: idx for idx, item in enumerate(RESEARCH_ACTIONS)} - -RESEARCH_ACTIONS_REORDER_ARRAY = get_reorder_lookup_array(RESEARCH_ACTIONS) - -ORDER_ACTIONS = [ - 425, 85, 426, 553, 427, 428, 429, 84, 430, 431, 83, 432, 433, 434, 554, 435, 436, 563, 69, 437, 67, 68, 438, 440, - 439, 441, 18, 442, 443, 444, 445, 446, 19, 447, 116, 117, 118, 119, 120, 70, 448, 449, 97, 450, 451, 452, 456, 460, - 464, 465, 469, 473, 82, 474, 478, 482, 494, 495, 486, 490, 54, 499, 500, 56, 62, 501, 502, 52, 166, 504, 505, 506, - 51, 63, 509, 510, 511, 512, 513, 21, 61, 58, 55, 64, 516, 517, 518, 520, 53, 521, 50, 59, 523, 525, 57, 76, 74, 73, - 60, 75, 72, 71, 527, 49 -] - -NUM_ORDER_ACTIONS = len(ORDER_ACTIONS) + 1 -ORDER_ACTIONS_REORDER_ARRAY = torch.zeros(max(GENERAL_ACTION_INFO_MASK.keys()) + 1, dtype=torch.long) -for idx, v in enumerate(ORDER_ACTIONS): - ORDER_ACTIONS_REORDER_ARRAY[v] = idx + 1 - - -def ger_reorder_tag(val, template): - low = 0 - high = len(template) - while low < high: - mid = (low + high) // 2 - mid_val = template[mid] - if val == mid_val: - return mid - elif val > mid_val: - low = mid + 1 - else: - high = mid - raise ValueError("unknow found val: {}".format(val)) - - -SELECTED_UNITS_MASK = torch.zeros(NUM_ACTIONS, NUM_UNIT_TYPES) -TARGET_UNITS_MASK = torch.zeros(NUM_ACTIONS, NUM_UNIT_TYPES) -for i in range(NUM_ACTIONS): - a = ACTIONS_REORDER_INV[i] - type_set = set(ACTIONS_STAT[a]['selected_type']) - reorder_type_list = [UNIT_TYPES_REORDER[i] for i in type_set] - SELECTED_UNITS_MASK[i, reorder_type_list] = 1 - type_set = set(ACTIONS_STAT[a]['target_type']) - reorder_type_list = [UNIT_TYPES_REORDER[i] for i in type_set] - TARGET_UNITS_MASK[i, reorder_type_list] = 1 - -UNIT_SPECIFIC_ABILITIES = [ - 4, 6, 7, 9, 2063, 16, 17, 18, 19, 2067, 23, 2073, 26, 28, 30, 2081, 36, 38, 40, 42, 46, 2095, 2097, 2099, 2108, - 2110, 2116, 74, 76, 78, 80, 2146, 110, 140, 142, 146, 148, 152, 154, 166, 167, 173, 181, 2244, 216, 217, 247, 249, - 251, 253, 263, 265, 2324, 2330, 2332, 2338, 2340, 2342, 295, 296, 2346, 298, 299, 2350, 2358, 2362, 316, 2364, 318, - 319, 320, 321, 322, 323, 324, 2370, 326, 2375, 2376, 327, 328, 329, 331, 333, 2383, 2385, 2387, 2393, 380, 382, 383, - 386, 388, 390, 392, 393, 394, 396, 397, 401, 403, 405, 407, 412, 413, 416, 417, 419, 421, 422, 452, 454, 455, 2505, - 485, 487, 488, 2536, 2542, 2544, 2554, 2556, 2558, 2560, 518, 520, 522, 524, 2588, 2594, 2596, 554, 556, 558, 560, - 561, 562, 563, 591, 594, 595, 596, 597, 614, 620, 621, 622, 623, 624, 626, 650, 651, 652, 653, 654, 2700, 656, 657, - 2706, 658, 2708, 2704, 2714, 2720, 710, 730, 731, 732, 761, 764, 766, 769, 790, 793, 799, 804, 805, 820, 855, 856, - 857, 861, 862, 863, 864, 865, 866, 880, 881, 882, 883, 884, 885, 886, 887, 889, 890, 891, 892, 893, 894, 895, 911, - 913, 914, 916, 917, 919, 920, 921, 922, 946, 948, 950, 954, 955, 976, 977, 978, 979, 994, 1006, 1036, 1042, 1062, - 1063, 1064, 1065, 1066, 1067, 1068, 1069, 1070, 1093, 1094, 1097, 1126, 1152, 1154, 1155, 1156, 1157, 1158, 1159, - 1160, 1161, 1162, 1163, 1165, 1166, 1167, 1183, 1184, 1186, 1187, 1188, 1189, 1190, 1191, 1192, 1193, 1194, 1216, - 1218, 1220, 1223, 1225, 1252, 1253, 1282, 1283, 1312, 1313, 1314, 1315, 1316, 1317, 1342, 1343, 1344, 1345, 1346, - 1348, 1351, 1352, 1353, 1354, 1356, 1372, 1374, 1376, 1378, 1380, 1382, 1384, 1386, 1388, 1390, 1392, 1394, 1396, - 1406, 1408, 1409, 1433, 1435, 1437, 1438, 1440, 1442, 1444, 1446, 1448, 1450, 1454, 1455, 1482, 1512, 1514, 1516, - 1518, 1520, 1522, 1524, 1526, 1528, 1530, 1532, 1562, 1563, 1564, 1565, 1566, 1567, 1568, 1592, 1593, 1594, 1622, - 1628, 1632, 3707, 3709, 1662, 1664, 3739, 1692, 1693, 1694, 3741, 3743, 3745, 3747, 3753, 3765, 3771, 1725, 1727, - 3776, 1729, 3778, 1731, 3777, 1733, 3783, 1764, 1767, 1768, 1819, 1825, 1978, 1998, 2014, 2016 -] - -# correspond to UNIT_SPECIFIC_ABILITIES -UNIT_GENERAL_ABILITIES = [ - 3665, 3665, 3665, 3665, 0, 3794, 3795, 3793, 3674, 0, 3674, 0, 3684, 3684, 3684, 0, 3688, 3689, 0, 0, 0, 3661, 3662, - 0, 3661, 3662, 0, 0, 0, 3685, 0, 0, 0, 0, 3686, 0, 0, 0, 0, 3666, 3667, 0, 0, 0, 0, 0, 0, 0, 0, 3675, 0, 0, 0, 0, 0, - 0, 3661, 3662, 3666, 3667, 0, 3666, 3667, 0, 0, 0, 3685, 0, 0, 0, 0, 0, 0, 0, 0, 3668, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, - 0, 0, 3675, 3676, 3677, 0, 0, 0, 3676, 3677, 3668, 3669, 3796, 0, 0, 0, 3668, 3668, 3664, 3663, 3679, 3678, 3682, - 3683, 3679, 3682, 3683, 0, 3679, 3682, 3683, 0, 0, 0, 0, 0, 0, 0, 3679, 3678, 3678, 0, 0, 3659, 3659, 3678, 0, 0, 0, - 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3698, 3698, 3698, 3687, 3697, 3697, 0, 3697, 0, 0, 0, 0, 0, 0, 0, - 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3701, 3701, 3701, 3699, 3699, 3699, 3700, 3700, 3700, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, - 0, 0, 0, 0, 0, 3668, 3669, 3796, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3695, 3695, 3695, 3694, - 3694, 3694, 3696, 3696, 3696, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3666, 3667, 3705, 3705, 3705, - 3704, 3704, 3704, 3706, 3706, 3706, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3703, 3703, 3703, 3702, 3702, 3702, 0, 0, 0, 0, 0, 0, - 0, 0, 0, 0, 0, 0, 3661, 3662, 3661, 3662, 3661, 3662, 3661, 3662, 3661, 3662, 3661, 3662, 3668, 3669, 3796, 3661, - 3662, 3668, 3664, 3796, 3687, 3661, 3662, 0, 0, 0, 0, 0, 3661, 3662, 0, 0, 0, 3679, 3678, 0, 0, 0, 0, 3693, 3693, - 3693, 3692, 3692, 3692, 0, 0, 0, 0, 0, 0, 0, 3659, 0, 3661, 0, 0, 0, 0, 3691, 0, 0, 0, 0, 0, 0, 3674, 3681, 3681, - 3794, 3680, 3793, 3680, 3795, 3691, 3665, 0, 0, 0, 0, 0, 0, 0, 3661, 3662 -] - -# UNIT_MIX_ABILITIES = [] -# for idx in range(len(UNIT_SPECIFIC_ABILITIES)): -# if UNIT_GENERAL_ABILITIES[idx] == 0: -# UNIT_MIX_ABILITIES.append(UNIT_SPECIFIC_ABILITIES[idx]) -# else: -# UNIT_MIX_ABILITIES.append(UNIT_GENERAL_ABILITIES[idx]) -# UNIT_MIX_ABILITIES = [0] + list(set(UNIT_MIX_ABILITIES)) # use 0 as no op - -UNIT_MIX_ABILITIES = [ - 0, 2560, 524, 1036, 2063, 1042, 2067, 1530, 2073, 1344, 2588, 1532, 1568, 2081, 1126, 40, 42, 556, 46, 558, 560, - 561, 562, 2099, 563, 1345, 1592, 1593, 1594, 2116, 1093, 1094, 1097, 74, 3659, 76, 3661, 3662, 3663, 3664, 80, 3665, - 3666, 3667, 3669, 3668, 591, 594, 595, 3674, 3675, 3676, 3677, 3678, 3679, 1628, 1632, 2146, 3682, 3684, 3685, 3686, - 3683, 3688, 3689, 614, 3687, 620, 621, 110, 622, 623, 624, 626, 3698, 3697, 3701, 3699, 3700, 3695, 3696, 3705, - 3704, 3706, 3703, 3702, 1348, 1152, 3709, 1154, 1155, 1156, 1157, 1158, 1159, 1160, 1161, 650, 651, 140, 1162, 1163, - 1165, 2704, 1166, 146, 2706, 148, 2708, 1167, 3693, 152, 3692, 154, 2714, 3694, 1354, 3739, 1692, 2720, 1693, 3741, - 3743, 3745, 3747, 3753, 173, 181, 1664, 3765, 3691, 1216, 1218, 2244, 1220, 710, 1223, 1225, 3793, 3794, 3795, 3796, - 216, 217, 730, 731, 732, 1252, 1253, 1764, 1767, 1768, 247, 249, 761, 251, 764, 766, 769, 1282, 1283, 263, 265, - 2324, 790, 793, 2330, 1819, 2332, 799, 1825, 2338, 804, 805, 2346, 2350, 820, 2358, 2362, 2364, 318, 319, 320, 321, - 322, 323, 324, 1342, 326, 2375, 2376, 327, 328, 331, 329, 333, 1351, 2383, 1352, 2385, 1353, 2387, 1356, 2393, 1372, - 880, 881, 882, 883, 884, 885, 886, 887, 1346, 889, 890, 891, 892, 893, 894, 895, 386, 388, 390, 401, 403, 916, 405, - 917, 919, 920, 921, 922, 1448, 3680, 1450, 1454, 1455, 946, 948, 950, 596, 954, 955, 597, 1978, 3681, 2505, 1482, - 1998, 976, 977, 978, 979, 1622, 994, 2536, 1516, 2542, 1006, 2544, 1518, 1520, 1526, 1528, 2554, 1343, 2556, 2558 -] -ACTIONS = [ - {'func_id': 0, 'general_ability_id': None, 'goal': 'other', 'name': 'no_op', 'queued': False, 'selected_units': False, 'target_location': False, 'target_unit': False} , - {'func_id': 168, 'general_ability_id': None, 'goal': 'other', 'name': 'raw_move_camera', 'queued': False, 'selected_units': False, 'target_location': True, 'target_unit': False} , - {'func_id': 2, 'general_ability_id': 3674, 'goal': 'other', 'name': 'Attack_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False} , - {'func_id': 3, 'general_ability_id': 3674, 'goal': 'other', 'name': 'Attack_unit', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': True} , - {'func_id': 88, 'general_ability_id': 2082, 'goal': 'other', 'name': 'Behavior_BuildingAttackOff_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , - {'func_id': 87, 'general_ability_id': 2081, 'goal': 'other', 'name': 'Behavior_BuildingAttackOn_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , - {'func_id': 169, 'general_ability_id': 3677, 'goal': 'other', 'name': 'Behavior_CloakOff_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , - {'func_id': 172, 'general_ability_id': 3676, 'goal': 'other', 'name': 'Behavior_CloakOn_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , - {'func_id': 175, 'general_ability_id': 1693, 'goal': 'other', 'name': 'Behavior_GenerateCreepOff_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , - {'func_id': 176, 'general_ability_id': 1692, 'goal': 'other', 'name': 'Behavior_GenerateCreepOn_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , - {'func_id': 177, 'general_ability_id': 3689, 'goal': 'other', 'name': 'Behavior_HoldFireOff_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , - {'func_id': 180, 'general_ability_id': 3688, 'goal': 'other', 'name': 'Behavior_HoldFireOn_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , - {'func_id': 158, 'general_ability_id': 2376, 'goal': 'other', 'name': 'Behavior_PulsarBeamOff_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , - {'func_id': 159, 'general_ability_id': 2375, 'goal': 'other', 'name': 'Behavior_PulsarBeamOn_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , - {'func_id': 183, 'general_ability_id': 331, 'goal': 'build', 'name': 'Build_Armory_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 29} , - {'func_id': 36, 'general_ability_id': 882, 'goal': 'build', 'name': 'Build_Assimilator_unit', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': True, 'game_id': 61} , - {'func_id': 184, 'general_ability_id': 1162, 'goal': 'build', 'name': 'Build_BanelingNest_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 96} , - {'func_id': 185, 'general_ability_id': 321, 'goal': 'build', 'name': 'Build_Barracks_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 21} , - {'func_id': 186, 'general_ability_id': 324, 'goal': 'build', 'name': 'Build_Bunker_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 24} , - {'func_id': 187, 'general_ability_id': 318, 'goal': 'build', 'name': 'Build_CommandCenter_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 18} , - {'func_id': 188, 'general_ability_id': 3691, 'goal': 'build', 'name': 'Build_CreepTumor_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 87} , - {'func_id': 47, 'general_ability_id': 894, 'goal': 'build', 'name': 'Build_CyberneticsCore_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 72} , - {'func_id': 44, 'general_ability_id': 891, 'goal': 'build', 'name': 'Build_DarkShrine_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 69} , - {'func_id': 191, 'general_ability_id': 322, 'goal': 'build', 'name': 'Build_EngineeringBay_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 22} , - {'func_id': 192, 'general_ability_id': 1156, 'goal': 'build', 'name': 'Build_EvolutionChamber_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 90} , - {'func_id': 193, 'general_ability_id': 1154, 'goal': 'build', 'name': 'Build_Extractor_unit', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': True, 'game_id': 88} , - {'func_id': 194, 'general_ability_id': 328, 'goal': 'build', 'name': 'Build_Factory_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 27} , - {'func_id': 39, 'general_ability_id': 885, 'goal': 'build', 'name': 'Build_FleetBeacon_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 64} , - {'func_id': 38, 'general_ability_id': 884, 'goal': 'build', 'name': 'Build_Forge_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 63} , - {'func_id': 195, 'general_ability_id': 333, 'goal': 'build', 'name': 'Build_FusionCore_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 30} , - {'func_id': 37, 'general_ability_id': 883, 'goal': 'build', 'name': 'Build_Gateway_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 62} , - {'func_id': 196, 'general_ability_id': 327, 'goal': 'build', 'name': 'Build_GhostAcademy_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 26} , - {'func_id': 197, 'general_ability_id': 1152, 'goal': 'build', 'name': 'Build_Hatchery_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 86} , - {'func_id': 198, 'general_ability_id': 1157, 'goal': 'build', 'name': 'Build_HydraliskDen_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 91} , - {'func_id': 199, 'general_ability_id': 1160, 'goal': 'build', 'name': 'Build_InfestationPit_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 94} , - {'func_id': 200, 'general_ability_id': 1042, 'goal': 'build', 'name': 'Build_Interceptors_autocast', 'queued': False, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 85} , - {'func_id': 66, 'general_ability_id': 1042, 'goal': 'build', 'name': 'Build_Interceptors_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 85} , - {'func_id': 201, 'general_ability_id': 1163, 'goal': 'build', 'name': 'Build_LurkerDen_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 504} , - {'func_id': 202, 'general_ability_id': 323, 'goal': 'build', 'name': 'Build_MissileTurret_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 23} , - {'func_id': 34, 'general_ability_id': 880, 'goal': 'build', 'name': 'Build_Nexus_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 59} , - {'func_id': 203, 'general_ability_id': 710, 'goal': 'build', 'name': 'Build_Nuke_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 58} , - {'func_id': 204, 'general_ability_id': 1161, 'goal': 'build', 'name': 'Build_NydusNetwork_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 95} , - {'func_id': 205, 'general_ability_id': 1768, 'goal': 'build', 'name': 'Build_NydusWorm_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 142} , - {'func_id': 41, 'general_ability_id': 887, 'goal': 'build', 'name': 'Build_PhotonCannon_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 66} , - {'func_id': 35, 'general_ability_id': 881, 'goal': 'build', 'name': 'Build_Pylon_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 60} , - {'func_id': 207, 'general_ability_id': 3683, 'goal': 'build', 'name': 'Build_Reactor_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 6} , - {'func_id': 206, 'general_ability_id': 3683, 'goal': 'build', 'name': 'Build_Reactor_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 6} , - {'func_id': 214, 'general_ability_id': 320, 'goal': 'build', 'name': 'Build_Refinery_pt', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': True, 'game_id': 20} , - {'func_id': 215, 'general_ability_id': 1165, 'goal': 'build', 'name': 'Build_RoachWarren_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 97} , - {'func_id': 45, 'general_ability_id': 892, 'goal': 'build', 'name': 'Build_RoboticsBay_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 70} , - {'func_id': 46, 'general_ability_id': 893, 'goal': 'build', 'name': 'Build_RoboticsFacility_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 71} , - {'func_id': 216, 'general_ability_id': 326, 'goal': 'build', 'name': 'Build_SensorTower_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 25} , - {'func_id': 48, 'general_ability_id': 895, 'goal': 'build', 'name': 'Build_ShieldBattery_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 1910} , - {'func_id': 217, 'general_ability_id': 1155, 'goal': 'build', 'name': 'Build_SpawningPool_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 89} , - {'func_id': 218, 'general_ability_id': 1166, 'goal': 'build', 'name': 'Build_SpineCrawler_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 98} , - {'func_id': 219, 'general_ability_id': 1158, 'goal': 'build', 'name': 'Build_Spire_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 92} , - {'func_id': 220, 'general_ability_id': 1167, 'goal': 'build', 'name': 'Build_SporeCrawler_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 99} , - {'func_id': 42, 'general_ability_id': 889, 'goal': 'build', 'name': 'Build_Stargate_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 67} , - {'func_id': 221, 'general_ability_id': 329, 'goal': 'build', 'name': 'Build_Starport_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 28} , - {'func_id': 95, 'general_ability_id': 2505, 'goal': 'build', 'name': 'Build_StasisTrap_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 732} , - {'func_id': 222, 'general_ability_id': 319, 'goal': 'build', 'name': 'Build_SupplyDepot_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 19} , - {'func_id': 224, 'general_ability_id': 3682, 'goal': 'build', 'name': 'Build_TechLab_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 5} , - {'func_id': 223, 'general_ability_id': 3682, 'goal': 'build', 'name': 'Build_TechLab_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 5} , - {'func_id': 43, 'general_ability_id': 890, 'goal': 'build', 'name': 'Build_TemplarArchive_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 68} , - {'func_id': 40, 'general_ability_id': 886, 'goal': 'build', 'name': 'Build_TwilightCouncil_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 65} , - {'func_id': 231, 'general_ability_id': 1159, 'goal': 'build', 'name': 'Build_UltraliskCavern_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 93} , - {'func_id': 232, 'general_ability_id': 3661, 'goal': 'effect', 'name': 'BurrowDown_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , - {'func_id': 247, 'general_ability_id': 3662, 'goal': 'other', 'name': 'BurrowUp_autocast', 'queued': False, 'selected_units': True, 'target_location': False, 'target_unit': False} , - {'func_id': 246, 'general_ability_id': 3662, 'goal': 'other', 'name': 'BurrowUp_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , - {'func_id': 98, 'general_ability_id': 3659, 'goal': 'other', 'name': 'Cancel_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , - {'func_id': 129, 'general_ability_id': 3671, 'goal': 'other', 'name': 'Cancel_Last_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , - {'func_id': 293, 'general_ability_id': 2067, 'goal': 'effect', 'name': 'Effect_Abduct_unit', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': True} , - {'func_id': 96, 'general_ability_id': 2544, 'goal': 'effect', 'name': 'Effect_AdeptPhaseShift_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False} , - {'func_id': 294, 'general_ability_id': 3753, 'goal': 'effect', 'name': 'Effect_AntiArmorMissile_unit', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': True} , - {'func_id': 295, 'general_ability_id': 1764, 'goal': 'effect', 'name': 'Effect_AutoTurret_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False} , - {'func_id': 296, 'general_ability_id': 2063, 'goal': 'effect', 'name': 'Effect_BlindingCloud_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False} , - {'func_id': 111, 'general_ability_id': 3687, 'goal': 'effect', 'name': 'Effect_Blink_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False} , - {'func_id': 112, 'general_ability_id': 3687, 'goal': 'effect', 'name': 'Effect_Blink_unit', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': True} , - {'func_id': 297, 'general_ability_id': 171, 'goal': 'effect', 'name': 'Effect_CalldownMULE_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False} , - {'func_id': 298, 'general_ability_id': 171, 'goal': 'effect', 'name': 'Effect_CalldownMULE_unit', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': True} , - {'func_id': 299, 'general_ability_id': 2324, 'goal': 'effect', 'name': 'Effect_CausticSpray_unit', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': True} , - {'func_id': 302, 'general_ability_id': 1819, 'goal': 'effect', 'name': 'Effect_Charge_autocast', 'queued': False, 'selected_units': True, 'target_location': False, 'target_unit': False} , - {'func_id': 300, 'general_ability_id': 1819, 'goal': 'effect', 'name': 'Effect_Charge_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False} , - {'func_id': 301, 'general_ability_id': 1819, 'goal': 'effect', 'name': 'Effect_Charge_unit', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': True} , - {'func_id': 122, 'general_ability_id': 3755, 'goal': 'effect', 'name': 'Effect_ChronoBoostEnergyCost_unit', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': True} , - {'func_id': 33, 'general_ability_id': 261, 'goal': 'effect', 'name': 'Effect_ChronoBoost_unit', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': True} , - {'func_id': 303, 'general_ability_id': 1825, 'goal': 'effect', 'name': 'Effect_Contaminate_unit', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': True} , - {'func_id': 304, 'general_ability_id': 2338, 'goal': 'effect', 'name': 'Effect_CorrosiveBile_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False} , - {'func_id': 305, 'general_ability_id': 1628, 'goal': 'effect', 'name': 'Effect_EMP_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False} , - {'func_id': 306, 'general_ability_id': 1628, 'goal': 'effect', 'name': 'Effect_EMP_unit', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': True} , - {'func_id': 307, 'general_ability_id': 42, 'goal': 'effect', 'name': 'Effect_Explode_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , - {'func_id': 157, 'general_ability_id': 140, 'goal': 'effect', 'name': 'Effect_Feedback_unit', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': True} , - {'func_id': 79, 'general_ability_id': 1526, 'goal': 'effect', 'name': 'Effect_ForceField_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False} , - {'func_id': 308, 'general_ability_id': 74, 'goal': 'effect', 'name': 'Effect_FungalGrowth_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False} , - {'func_id': 309, 'general_ability_id': 74, 'goal': 'effect', 'name': 'Effect_FungalGrowth_unit', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': True} , - {'func_id': 310, 'general_ability_id': 2714, 'goal': 'effect', 'name': 'Effect_GhostSnipe_unit', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': True} , - {'func_id': 32, 'general_ability_id': 173, 'goal': 'effect', 'name': 'Effect_GravitonBeam_unit', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': True} , - {'func_id': 20, 'general_ability_id': 76, 'goal': 'effect', 'name': 'Effect_GuardianShield_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , - {'func_id': 312, 'general_ability_id': 386, 'goal': 'effect', 'name': 'Effect_Heal_autocast', 'queued': False, 'selected_units': True, 'target_location': False, 'target_unit': False} , - {'func_id': 311, 'general_ability_id': 386, 'goal': 'effect', 'name': 'Effect_Heal_unit', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': True} , - {'func_id': 313, 'general_ability_id': 2328, 'goal': 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'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 35} , - {'func_id': 526, 'general_ability_id': 1354, 'goal': 'unit', 'name': 'Train_Viper_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 499} , - {'func_id': 57, 'general_ability_id': 950, 'goal': 'unit', 'name': 'Train_VoidRay_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 80} , - {'func_id': 76, 'general_ability_id': 1419, 'goal': 'unit', 'name': 'TrainWarp_Adept_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 311} , - {'func_id': 74, 'general_ability_id': 1417, 'goal': 'unit', 'name': 'TrainWarp_DarkTemplar_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 76} , - {'func_id': 73, 'general_ability_id': 1416, 'goal': 'unit', 'name': 'TrainWarp_HighTemplar_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 75} , - {'func_id': 60, 'general_ability_id': 976, 'goal': 'unit', 'name': 'Train_WarpPrism_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 81} , - {'func_id': 75, 'general_ability_id': 1418, 'goal': 'unit', 'name': 'TrainWarp_Sentry_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 77} , - {'func_id': 72, 'general_ability_id': 1414, 'goal': 'unit', 'name': 'TrainWarp_Stalker_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 74} , - {'func_id': 71, 'general_ability_id': 1413, 'goal': 'unit', 'name': 'TrainWarp_Zealot_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False, 'game_id': 73} , - {'func_id': 527, 'general_ability_id': 614, 'goal': 'unit', 'name': 'Train_WidowMine_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 498} , - {'func_id': 49, 'general_ability_id': 916, 'goal': 'unit', 'name': 'Train_Zealot_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 73} , - {'func_id': 528, 'general_ability_id': 1343, 'goal': 'unit', 'name': 'Train_Zergling_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False, 'game_id': 105} , - {'func_id': 105, 'general_ability_id': 3669, 'goal': 'other', 'name': 'UnloadAllAt_pt', 'queued': True, 'selected_units': True, 'target_location': True, 'target_unit': False} , - {'func_id': 164, 'general_ability_id': 3669, 'goal': 'other', 'name': 'UnloadAllAt_unit', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': True} , - {'func_id': 100, 'general_ability_id': 3664, 'goal': 'other', 'name': 'UnloadAll_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , - {'func_id': 556, 'general_ability_id': 3796, 'goal': 'other', 'name': 'UnloadUnit_quick', 'queued': True, 'selected_units': True, 'target_location': False, 'target_unit': False} , -] - - -NUM_UNIT_MIX_ABILITIES = len(UNIT_MIX_ABILITIES) #269 - -UNIT_ABILITY_REORDER = torch.full((max(UNIT_MIX_ABILITIES) + 1, ), fill_value=-1, dtype=torch.long) -for idx in range(len(UNIT_SPECIFIC_ABILITIES)): - if UNIT_GENERAL_ABILITIES[idx] == 0: - UNIT_ABILITY_REORDER[UNIT_SPECIFIC_ABILITIES[idx]] = UNIT_MIX_ABILITIES.index(UNIT_SPECIFIC_ABILITIES[idx]) - else: - UNIT_ABILITY_REORDER[UNIT_SPECIFIC_ABILITIES[idx]] = UNIT_MIX_ABILITIES.index(UNIT_GENERAL_ABILITIES[idx]) -UNIT_ABILITY_REORDER[0] = 0 # use 0 as no op - -FUNC_ID_TO_ACTION_TYPE_DICT = {a['func_id']: idx for idx, a in enumerate(ACTIONS)} -ABILITY_TO_GABILITY = {} -for idx in range(len(UNIT_SPECIFIC_ABILITIES)): - if UNIT_GENERAL_ABILITIES[idx] == 0: - ABILITY_TO_GABILITY[UNIT_SPECIFIC_ABILITIES[idx]] = UNIT_SPECIFIC_ABILITIES[idx] - else: - ABILITY_TO_GABILITY[UNIT_SPECIFIC_ABILITIES[idx]] = UNIT_GENERAL_ABILITIES[idx] - -GABILITY_TO_QUEUE_ACTION = {} -QUEUE_ACTIONS = [] -count = 1 # use 0 as no op -for idx, f in enumerate(ACTIONS): - if 'Train_' in f['name'] or 'Research' in f['name']: - GABILITY_TO_QUEUE_ACTION[f['general_ability_id']] = count - QUEUE_ACTIONS.append(idx) - count += 1 - else: - GABILITY_TO_QUEUE_ACTION[f['general_ability_id']] = 0 - -ABILITY_TO_QUEUE_ACTION = torch.full((max(ABILITY_TO_GABILITY.keys()) + 1, ), fill_value=-1, dtype=torch.long) -ABILITY_TO_QUEUE_ACTION[0] = 0 # use 0 as no op -for a_id, g_id in ABILITY_TO_GABILITY.items(): - if g_id in GABILITY_TO_QUEUE_ACTION.keys(): - ABILITY_TO_QUEUE_ACTION[a_id] = GABILITY_TO_QUEUE_ACTION[g_id] - else: - ABILITY_TO_QUEUE_ACTION[a_id] = 0 - -EXCLUDE_ACTIONS = [ - 'Build_Pylon_pt', 'Train_Overlord_quick', 'Build_SupplyDepot_pt', # supply action - 'Train_Drone_quick', 'Train_SCV_quick', 'Train_Probe_quick', # worker action - 'Build_CreepTumor_pt', '' -] - -BO_EXCLUDE_ACTIONS = [ -] - -CUM_EXCLUDE_ACTIONS = [ - 'Build_SpineCrawler_pt', 'Build_SporeCrawler_pt', 'Build_PhotonCannon_pt', 'Build_ShieldBattery_pt', - 'Build_Bunker_pt', 'Morph_Overseer_quick', 'Build_MissileTurret_pt' -] - -BEGINNING_ORDER_ACTIONS = [0] -CUMULATIVE_STAT_ACTIONS = [0] -for idx, f in enumerate(ACTIONS): - if f['goal'] in ['unit', 'build', 'research'] and f['name'] not in EXCLUDE_ACTIONS and f['name'] not in CUM_EXCLUDE_ACTIONS: - CUMULATIVE_STAT_ACTIONS.append(idx) - if f['goal'] in ['unit', 'build', 'research'] and f['name'] not in EXCLUDE_ACTIONS: - BEGINNING_ORDER_ACTIONS.append(idx) - -NUM_ACTIONS = len(ACTIONS) -NUM_QUEUE_ACTIONS = len(QUEUE_ACTIONS) -NUM_BEGINNING_ORDER_ACTIONS = len(BEGINNING_ORDER_ACTIONS) -NUM_CUMULATIVE_STAT_ACTIONS = len(CUMULATIVE_STAT_ACTIONS) - -SELECTED_UNITS_MASK = torch.zeros(len(ACTIONS), dtype=torch.bool) -for idx, a in enumerate(ACTIONS): - if a['selected_units']: - SELECTED_UNITS_MASK[idx] = 1 - -UNIT_BUILD_ACTIONS = [a['func_id'] for a in ACTIONS if a['goal'] == 'build'] -UNIT_TRAIN_ACTIONS = [a['func_id'] for a in ACTIONS if a['goal'] == 'unit'] - -GENERAL_ABILITY_IDS = [] -for idx, a in enumerate(ACTIONS): - GENERAL_ABILITY_IDS.append(a['general_ability_id']) -UNIT_ABILITY_TO_ACTION = {} -for idx, a in enumerate(UNIT_MIX_ABILITIES): - if a in GENERAL_ABILITY_IDS: - UNIT_ABILITY_TO_ACTION[idx] = GENERAL_ABILITY_IDS.index(a) - -UNIT_TO_CUM = defaultdict(lambda: -1) -UPGRADE_TO_CUM = defaultdict(lambda: -1) -for idx, a in enumerate(ACTIONS): - if 'game_id' in a and a['goal'] in ['unit', 'build'] and idx in CUMULATIVE_STAT_ACTIONS: - UNIT_TO_CUM[a['game_id']] = CUMULATIVE_STAT_ACTIONS.index(idx) - elif 'game_id' in a and a['goal'] in ['research'] and idx in CUMULATIVE_STAT_ACTIONS: - UPGRADE_TO_CUM[a['game_id']] = CUMULATIVE_STAT_ACTIONS.index(idx) diff --git a/dizoo/distar/envs/tests/test_distar_config.yaml b/dizoo/distar/envs/tests/test_distar_config.yaml deleted file mode 100644 index 18247e5a54..0000000000 --- a/dizoo/distar/envs/tests/test_distar_config.yaml +++ /dev/null @@ -1,16 +0,0 @@ -actor: - job_type: 'train' # ['train', 'eval', 'train_test', 'eval_test'] -env: - map_name: 'KingsCove' - player_ids: ['agent1', 'agent2'] - races: ['zerg', 'zerg'] - map_size_resolutions: [True, True] # if True, ignore minimap_resolutions - minimap_resolutions: [[160, 152], [160, 152]] - realtime: False - replay_dir: '.' - random_seed: 'none' - game_steps_per_episode: 100000 - update_bot_obs: False - save_replay_episodes: 1 - update_both_obs: False - version: '4.10.0' \ No newline at end of file diff --git a/dizoo/distar/envs/tests/test_distar_env_data.py b/dizoo/distar/envs/tests/test_distar_env_data.py deleted file mode 100644 index 05c09d4002..0000000000 --- a/dizoo/distar/envs/tests/test_distar_env_data.py +++ /dev/null @@ -1,64 +0,0 @@ -import os -import shutil - -from distar.ctools.utils import read_config -import torch - -from dizoo.distar.envs import DIStarEnv -import traceback - -from dizoo.distar.envs import DIStarEnv -import traceback - -class TestDIstarEnv: - def __init__(self): - - cfg = read_config('./test_distar_config.yaml') - self._whole_cfg = cfg - - def _inference_loop(self, job={}): - - torch.set_num_threads(1) - - self._env = DIStarEnv(self._whole_cfg) - - with torch.no_grad(): - for _ in range(5): - try: - observations = self._env.reset() - - for iter in range(1000): # one episode loop - # agent step - actions = {} - for player_index, player_obs in observations.items(): - actions[player_index] = DIStarEnv.random_action(player_obs) - # env step - timestep = self._env.step(actions) - if not timestep.done: - observations = timestep.obs - else: - break - - except Exception as e: - print('[EPISODE LOOP ERROR]', e, flush=True) - print(''.join(traceback.format_tb(e.__traceback__)), flush=True) - self._env.close() - self._env.close() - -if __name__ == '__main__': - - ## main - if os.path.exists(r'C:\Program Files (x86)\StarCraft II'): - sc2path = r'C:\Program Files (x86)\StarCraft II' - elif os.path.exists('/Applications/StarCraft II'): - sc2path = '/Applications/StarCraft II' - else: - assert 'SC2PATH' in os.environ.keys(), 'please add StarCraft2 installation path to your environment variables!' - sc2path = os.environ['SC2PATH'] - assert os.path.exists(sc2path), 'SC2PATH: {} does not exist!'.format(sc2path) - if not os.path.exists(os.path.join(sc2path, 'Maps/Ladder2019Season2')): - shutil.copytree(os.path.join(os.path.dirname(__file__), '../envs/maps/Ladder2019Season2'), os.path.join(sc2path, 'Maps/Ladder2019Season2')) - - ## actor_run - actor = TestDIstarEnv() - actor._inference_loop() \ No newline at end of file diff --git a/dizoo/distar/envs/tests/test_distar_env_time_space.py b/dizoo/distar/envs/tests/test_distar_env_time_space.py deleted file mode 100644 index 9252c88597..0000000000 --- a/dizoo/distar/envs/tests/test_distar_env_time_space.py +++ /dev/null @@ -1,87 +0,0 @@ -import os -import shutil - -from distar.ctools.utils import read_config -import torch -import time -import sys - -from dizoo.distar.envs import DIStarEnv -import traceback - -class TestDIstarEnv: - def __init__(self): - - cfg = read_config('./test_distar_config.yaml') - self._whole_cfg = cfg - self._total_iters = 0 - self._total_time = 0 - self._total_space = 0 - - def _inference_loop(self, job={}): - - torch.set_num_threads(1) - - self._env = DIStarEnv(self._whole_cfg) - - with torch.no_grad(): - for _ in range(5): - try: - observations = self._env.reset() - - for iter in range(1000): # one episode loop - # agent step - actions = {} - for player_index, player_obs in observations.items(): - actions[player_index] = DIStarEnv.random_action(player_obs) - # env step - before_step_time = time.time() - timestep = self._env.step(actions) - after_step_time = time.time() - - self._total_time += after_step_time - before_step_time - self._total_iters += 1 - self._total_space += sys.getsizeof((actions,observations,timestep.obs,timestep.reward,timestep.done)) - print('observations: ', sys.getsizeof(observations), ' Byte') - print('actions: ', sys.getsizeof(actions), ' Byte') - print('reward: ', sys.getsizeof(timestep.reward), ' Byte') - print('done: ', sys.getsizeof(timestep.done), ' Byte') - print('total: ', sys.getsizeof((actions,observations,timestep.obs,timestep.reward,timestep.done)),' Byte') - print(type(observations)) # dict - print(type(timestep.reward)) # list - print(type(timestep.done)) # bool - print(type(actions)) # dict - - - if not timestep.done: - observations = timestep.obs - else: - break - - except Exception as e: - print('[EPISODE LOOP ERROR]', e, flush=True) - print(''.join(traceback.format_tb(e.__traceback__)), flush=True) - self._env.close() - self._env.close() - - print('total iters:', self._total_iters) - print('average step time:', self._total_time/self._total_iters) - print('average step data space:', self._total_space/self._total_iters) - -if __name__ == '__main__': - - ## main - if os.path.exists(r'C:\Program Files (x86)\StarCraft II'): - sc2path = r'C:\Program Files (x86)\StarCraft II' - elif os.path.exists('/Applications/StarCraft II'): - sc2path = '/Applications/StarCraft II' - else: - assert 'SC2PATH' in os.environ.keys(), 'please add StarCraft2 installation path to your environment variables!' - sc2path = os.environ['SC2PATH'] - assert os.path.exists(sc2path), 'SC2PATH: {} does not exist!'.format(sc2path) - if not os.path.exists(os.path.join(sc2path, 'Maps/Ladder2019Season2')): - shutil.copytree(os.path.join(os.path.dirname(__file__), '../envs/maps/Ladder2019Season2'), os.path.join(sc2path, 'Maps/Ladder2019Season2')) - - ## actor_run - actor = TestDIstarEnv() - actor._inference_loop() \ No newline at end of file diff --git a/dizoo/distar/envs/tests/test_distar_env_with_manager.py b/dizoo/distar/envs/tests/test_distar_env_with_manager.py deleted file mode 100644 index 6741db2eda..0000000000 --- a/dizoo/distar/envs/tests/test_distar_env_with_manager.py +++ /dev/null @@ -1,91 +0,0 @@ -import os -import shutil - -from distar.ctools.utils import read_config -import torch -from ding.envs import BaseEnvManager -from dizoo.distar.envs import DIStarEnv -import traceback - -from easydict import EasyDict -env_cfg = EasyDict( - { - 'env': { - 'manager': { - 'episode_num': 100000, - 'max_retry': 1, - 'retry_type': 'reset', - 'auto_reset': True, - 'step_timeout': None, - 'reset_timeout': None, - 'retry_waiting_time': 0.1, - 'cfg_type': 'BaseEnvManagerDict', - 'shared_memory': False - } - } - } -) - -ENV_NUMBER = 2 - - -class TestDIstarEnv: - - def __init__(self): - - cfg = read_config('./test_distar_config.yaml') - self._whole_cfg = cfg - - def _inference_loop(self, job={}): - - torch.set_num_threads(1) - - # self._env = DIStarEnv(self._whole_cfg) - self._env = BaseEnvManager( - env_fn=[lambda: DIStarEnv(self._whole_cfg) for _ in range(ENV_NUMBER)], cfg=env_cfg.env.manager - ) - self._env.seed(1) - - with torch.no_grad(): - for episode in range(2): - self._env.launch() - try: - for env_step in range(1000): - obs = self._env.ready_obs - # print(obs) - obs = {env_id: obs[env_id] for env_id in range(ENV_NUMBER)} - actions = {} - for env_id in range(ENV_NUMBER): - observations = obs[env_id] - actions[env_id] = {} - for player_index, player_obs in observations.items(): - actions[env_id][player_index] = DIStarEnv.random_action(player_obs) - timesteps = self._env.step(actions) - print(actions) - - except Exception as e: - print('[EPISODE LOOP ERROR]', e, flush=True) - print(''.join(traceback.format_tb(e.__traceback__)), flush=True) - self._env.close() - - self._env.close() - - -if __name__ == '__main__': - if os.path.exists(r'C:\Program Files (x86)\StarCraft II'): - sc2path = r'C:\Program Files (x86)\StarCraft II' - elif os.path.exists('/Applications/StarCraft II'): - sc2path = '/Applications/StarCraft II' - else: - assert 'SC2PATH' in os.environ.keys(), 'please add StarCraft2 installation path to your environment variables!' - sc2path = os.environ['SC2PATH'] - assert os.path.exists(sc2path), 'SC2PATH: {} does not exist!'.format(sc2path) - if not os.path.exists(os.path.join(sc2path, 'Maps/Ladder2019Season2')): - shutil.copytree( - os.path.join(os.path.dirname(__file__), '../envs/maps/Ladder2019Season2'), - os.path.join(sc2path, 'Maps/Ladder2019Season2') - ) - - # actor_run - actor = TestDIstarEnv() - actor._inference_loop() \ No newline at end of file diff --git a/dizoo/distar/envs/z_files/12D.json b/dizoo/distar/envs/z_files/12D.json deleted file mode 100644 index c1af4fc25f..0000000000 --- a/dizoo/distar/envs/z_files/12D.json +++ /dev/null @@ -1 +0,0 @@ -{"NewRepugnancy": {"zerg": {"16176": [[[38, 173, 173, 173, 173, 173, 173, 173, 39, 39, 173, 39, 0, 0, 0, 0, 0, 0, 0, 0], [34, 166], [15692, 0, 0, 0, 0, 0, 0, 0, 4934, 4934, 0, 4772, 0, 0, 0, 0, 0, 0, 0, 0], 3718], [[38, 173, 173, 173, 173, 173, 173, 39, 173, 39, 39, 39, 173, 0, 0, 0, 0, 0, 0, 0], [34, 166], [15692, 0, 0, 0, 0, 0, 0, 2844, 0, 2844, 4451, 4773, 0, 0, 0, 0, 0, 0, 0, 0], 4037], [[18, 11, 38, 150, 150, 173, 173, 173, 120, 173, 3, 150, 124, 124, 124, 124, 124, 173, 173, 173], [3, 10, 17, 34, 113, 117, 143, 166], [12496, 0, 16980, 0, 0, 0, 0, 0, 0, 0, 16501, 0, 0, 0, 0, 0, 0, 0, 0, 0], 4835], [[18, 38, 11, 173, 173, 150, 173, 173, 173, 173, 173, 173, 0, 0, 0, 0, 0, 0, 0, 0], [10, 17, 34, 143, 166], [12496, 17612, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 3585], [[18, 11, 38, 173, 173, 150, 150, 173, 173, 120, 173, 0, 0, 0, 0, 0, 0, 0, 0, 0], [10, 17, 34, 113, 143, 166], [12496, 0, 15692, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 4273], [[38, 11, 173, 173, 173, 3, 173, 173, 173, 173, 150, 124, 124, 173, 124, 0, 0, 0, 0, 0], [3, 10, 34, 117, 143, 166], [15692, 0, 0, 0, 0, 16166, 0, 0, 0, 0, 0, 0, 0, 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index 3b4d86ebbc..0000000000 --- a/dizoo/distar/model/__init__.py +++ /dev/null @@ -1 +0,0 @@ -from .model import Model diff --git a/dizoo/distar/model/actor_critic_default_config.yaml b/dizoo/distar/model/actor_critic_default_config.yaml deleted file mode 100644 index 629154d8ea..0000000000 --- a/dizoo/distar/model/actor_critic_default_config.yaml +++ /dev/null @@ -1,463 +0,0 @@ -var1: &NUM_ADDON 9 -var2: &NUM_BUFFS 50 -var3: &NUM_UNIT_TYPES 260 -var4: &NUM_UPGRADES 90 -var5: &NUM_ACTIONS 327 -var6: &NUM_QUEUE_ACTIONS 49 -var7: &NUM_BEGINNING_ORDER_ACTIONS 174 -var8: &NUM_CUMULATIVE_STAT_ACTIONS 167 -var9: &SPATIAL_X 160 -var10: &SPATIAL_Y 152 -var11: &NUM_UNIT_MIX_ABILITIES 269 - - -model: - # ===== Tuning ===== - freeze_targets: [] - state_dict_mask: [] - use_value_network: False - only_update_baseline: False - enable_baselines: ['winloss', 'build_order', 'built_unit', 'effect', 'upgrade', 'battle'] - # ===== Value ===== - value: - use_value_feature: True - spatial_x: *SPATIAL_X - spatial_y: *SPATIAL_Y - encoder: - modules: - enemy_unit_counts_bow: - arc: fc - input_dim: *NUM_UNIT_TYPES - output_dim: 64 - enemy_unit_type_bool: - arc: fc - input_dim: *NUM_UNIT_TYPES - output_dim: 64 - enemy_agent_statistics: - arc: fc - input_dim: 10 - output_dim: 64 - enemy_upgrades: - arc: fc - input_dim: *NUM_UPGRADES - output_dim: 32 - unit_alliance: - arc: one_hot - num_embeddings: 2 - embedding_dim: 16 - unit_type: - arc: one_hot - num_embeddings: *NUM_UNIT_TYPES - embedding_dim: 48 - beginning_order: - arc: transformer - action_one_hot_dim: *NUM_BEGINNING_ORDER_ACTIONS - binary_dim: 10 - head_dim: 8 - output_dim: 64 - activation: 'relu' - spatial_x: *SPATIAL_X - spatial_y: *SPATIAL_Y - cumulative_stat: - arc: fc - input_dim: *NUM_CUMULATIVE_STAT_ACTIONS - output_dim: 128 - scatter: - scatter_input_dim: 64 - scatter_dim: 8 - scatter_type: add - spatial: - input_dim: 10 # 8 + 2 - project_dim: 16 - down_channels: [16, 32, 32] - resblock_num: 4 - spatial_fc_dim: 128 - - winloss: - name: winloss - cum_stat_keys: ['unit_build', 'research'] - param: - name: 'winloss' - input_dim: 384 #1920 - activation: 'relu' - norm_type: 'LN' - res_dim: 256 - res_num: 16 - atan: True - build_order: - name: build_order - cum_stat_keys: ['unit_build', 'effect', 'research'] - param: - name: 'build_order' - input_dim: 384 #2016 - activation: 'relu' - norm_type: 'LN' - res_dim: 256 - res_num: 16 - atan: False - built_unit: - name: built_unit - cum_stat_keys: ['unit_build'] - param: - name: 'built_unit' - input_dim: 384 #1824 - activation: 'relu' - norm_type: 'LN' - res_dim: 256 - res_num: 16 - atan: False - effect: - name: effect - cum_stat_keys: ['effect'] - param: - name: 'effect' - input_dim: 384 #1824 - activation: 'relu' - norm_type: 'LN' - res_dim: 256 - res_num: 16 - atan: False - upgrade: - name: upgrade - cum_stat_keys: ['research'] - param: - name: 'upgrade' - input_dim: 384 #1824 - activation: 'relu' - norm_type: 'LN' - res_dim: 256 - res_num: 16 - atan: False - battle: - name: battle - cum_stat_keys: ['unit_build', 'effect', 'research'] - param: - name: 'battle' - input_dim: 384 #2016 - activation: 'relu' - norm_type: 'LN' - res_dim: 256 - res_num: 16 - atan: False - # ===== Encoder ===== - encoder: - obs_encoder: - encoder_names: [scalar_encoder, spatial_encoder, entity_encoder] - scalar_encoder: - module: - agent_statistics: - arc: fc - input_dim: 10 - output_dim: 64 - baseline_feature: True - home_race: - arc: one_hot - num_embeddings: 5 - embedding_dim: 32 - scalar_context: True - away_race: - arc: one_hot - num_embeddings: 5 - embedding_dim: 32 - scalar_context: True - upgrades: - arc: fc - input_dim: *NUM_UPGRADES - output_dim: 128 - baseline_feature: True - time: - arc: identity - output_dim: 32 - unit_counts_bow: - arc: fc - input_dim: *NUM_UNIT_TYPES - output_dim: 128 - baseline_feature: True - last_delay: - arc: one_hot - num_embeddings: 128 - embedding_dim: 64 - last_queued: - arc: one_hot - num_embeddings: 2 - embedding_dim: 32 - last_action_type: - arc: one_hot - num_embeddings: *NUM_ACTIONS - embedding_dim: 128 - cumulative_stat: - arc: fc - input_dim: *NUM_CUMULATIVE_STAT_ACTIONS - output_dim: 128 - scalar_context: True - baseline_feature: True - beginning_order: - arc: transformer - action_one_hot_dim: *NUM_BEGINNING_ORDER_ACTIONS - spatial_x: *SPATIAL_X - binary_dim: 10 - head_dim: 8 - output_dim: 64 - scalar_context: True - activation: 'relu' - baseline_feature: True - unit_type_bool: - arc: fc - input_dim: *NUM_UNIT_TYPES - output_dim: 64 - scalar_context: True - enemy_unit_type_bool: - arc: fc - input_dim: *NUM_UNIT_TYPES - output_dim: 64 - scalar_context: True - unit_order_type: - arc: fc - input_dim: *NUM_UNIT_MIX_ABILITIES - output_dim: 64 - scalar_context: True - activation: 'relu' - output_dim: 1024 - spatial_encoder: - module: - height_map: - arc: other - visibility_map: - arc: one_hot - num_embeddings: 4 - creep: - arc: one_hot - num_embeddings: 2 - player_relative: - arc: one_hot - num_embeddings: 5 - alerts: - arc: one_hot - num_embeddings: 2 - pathable: - arc: one_hot - num_embeddings: 2 - buildable: - arc: one_hot - num_embeddings: 2 - effect_PsiStorm: - arc: scatter - effect_NukeDot: - arc: scatter - effect_LiberatorDefenderZone: - arc: scatter - effect_BlindingCloud: - arc: scatter - effect_CorrosiveBile: - arc: scatter - effect_LurkerSpines: - arc: scatter - input_dim: 56 - resblock_num: 4 - fc_dim: 256 - project_dim: 32 - downsample_type: 'maxpool' - down_channels: [64, 128, 128] - activation: 'relu' - norm_type: 'none' - head_type: 'fc' - spatial_x: *SPATIAL_X - spatial_y: *SPATIAL_Y - entity_encoder: - module: - unit_type: - arc: one_hot - num_embeddings: *NUM_UNIT_TYPES - alliance: - arc: one_hot - num_embeddings: 5 - cargo_space_taken: - arc: one_hot - num_embeddings: 9 - build_progress: - arc: unsqueeze - health_ratio: - arc: unsqueeze - shield_ratio: - arc: unsqueeze - energy_ratio: - arc: unsqueeze - display_type: - arc: one_hot - num_embeddings: 5 - x: - arc: binary - num_embeddings: 11 - y: - arc: binary - num_embeddings: 11 - cloak: - arc: one_hot - num_embeddings: 5 - is_blip: - arc: one_hot - num_embeddings: 2 - is_powered: - arc: one_hot - num_embeddings: 2 - mineral_contents: - arc: unsqueeze - vespene_contents: - arc: unsqueeze - cargo_space_max: - arc: one_hot - num_embeddings: 9 - assigned_harvesters: - arc: one_hot - num_embeddings: 24 - weapon_cooldown: - arc: one_hot - num_embeddings: 32 - order_length: - arc: one_hot - num_embeddings: 9 - order_id_0: - arc: one_hot - num_embeddings: *NUM_ACTIONS - order_id_1: - arc: one_hot - num_embeddings: *NUM_QUEUE_ACTIONS - is_hallucination: - arc: one_hot - num_embeddings: 2 - buff_id_0: - arc: one_hot - num_embeddings: *NUM_BUFFS - buff_id_1: - arc: one_hot - num_embeddings: *NUM_BUFFS - addon_unit_type: - arc: one_hot - num_embeddings: *NUM_ADDON - is_active: - arc: one_hot - num_embeddings: 2 - order_progress_0: - arc: unsqueeze - order_progress_1: - arc: unsqueeze - order_id_2: - arc: one_hot - num_embeddings: *NUM_QUEUE_ACTIONS - order_id_3: - arc: one_hot - num_embeddings: *NUM_QUEUE_ACTIONS - is_in_cargo: - arc: one_hot - num_embeddings: 2 - attack_upgrade_level: - arc: one_hot - num_embeddings: 4 - armor_upgrade_level: - arc: one_hot - num_embeddings: 4 - shield_upgrade_level: - arc: one_hot - num_embeddings: 4 - last_selected_units: - arc: one_hot - num_embeddings: 2 - last_targeted_unit: - arc: one_hot - num_embeddings: 2 - input_dim: 997 # cat all entity info - head_dim: 128 - hidden_dim: 1024 - output_dim: 256 - head_num: 2 - mlp_num: 2 - layer_num: 3 - dropout_ratio: 0 - activation: 'relu' - ln_type: 'post' - entity_reduce_type: 'selected_units_num' # ['constant', 'entity_num', 'selected_units_num'] - scatter: - input_dim: 256 # entity_encoder.output_dim - output_dim: 32 - scatter_type: 'add' - core_lstm: - lstm_type: 'normal' - input_size: 1536 # spatial_encoder.fc_dim + entity_encoder.output_dim + scalar_encoder.output_dim - hidden_size: 384 - num_layers: 3 - dropout: 0.0 - score_cumulative: - input_dim: 13 - output_dim: 64 - activation: 'relu' - # ===== Policy ===== - policy: - head: - head_names: [action_type_head, delay_head, queued_head, selected_units_head, target_unit_head, location_head] - action_type_head: - input_dim: 384 # core.hidden_size - res_dim: 256 - res_num: 2 - action_num: *NUM_ACTIONS - action_map_dim: 256 # scalar context - gate_dim: 1024 - context_dim: 448 - activation: 'relu' - norm_type: 'LN' - ln_type: 'normal' - # TODO(zms): use_mask when common_type is play, i.e. evaluate. e.g. play against bot. - use_mask: False - race: 'zerg' - temperature: 1.0 - delay_head: - input_dim: 1024 # action_type_head.gate_dim - decode_dim: 256 - delay_dim: 128 - delay_map_dim: 256 - activation: 'relu' - queued_head: - input_dim: 1024 # action_type_head.gate_dim - decode_dim: 256 - queued_dim: 2 - queued_map_dim: 256 - activation: 'relu' - temperature: 1.0 - selected_units_head: - lstm_type: 'pytorch' - lstm_norm_type: 'none' - lstm_dropout: 0. - input_dim: 1024 # action_type_head.gate_dim - entity_embedding_dim: 256 # entity_encoder.output_dim - key_dim: 32 - unit_type_dim: 259 - func_dim: 256 - hidden_dim: 32 - num_layers: 1 - max_entity_num: 64 - activation: 'relu' - extra_units: True # select extra units if selected units exceed max_entity_num=64 - entity_reduce_type: 'selected_units_num' - temperature: 1.0 - target_unit_head: - input_dim: 1024 # action_type_head.gate_dim - entity_embedding_dim: 256 # entity_encoder.output_dim - key_dim: 32 - unit_type_dim: 259 - func_dim: 256 - activation: 'relu' - embedding_norm: True - temperature: 1.0 - location_head: - input_dim: 1024 - project_dim: 1024 - upsample_type: 'bilinear' - upsample_dims: [64, 32, 1] # len(upsample_dims)-len(down_channels)+1 = ratio - res_dim: 128 - res_num: 4 - gate: True - reshape_channel: 4 # entity_encoder.gate_dim / reshape_size - map_skip_dim: 128 # spatial_encoder.down_channels[-1] - activation: 'relu' - spatial_x: *SPATIAL_X - spatial_y: *SPATIAL_Y - temperature: 1.0 diff --git a/dizoo/distar/model/encoder.py b/dizoo/distar/model/encoder.py deleted file mode 100644 index bd341f70f5..0000000000 --- a/dizoo/distar/model/encoder.py +++ /dev/null @@ -1,40 +0,0 @@ -import collections - -import torch -import torch.nn as nn -from typing import Dict -from torch import Tensor - -from ding.torch_utils import fc_block, ScatterConnection - -from .obs_encoder import ScalarEncoder, SpatialEncoder, EntityEncoder - - -class Encoder(nn.Module): - - def __init__(self, cfg): - super(Encoder, self).__init__() - self.cfg = cfg.encoder - self.encoder = nn.ModuleDict() - self.scalar_encoder = ScalarEncoder(self.cfg.obs_encoder.scalar_encoder) - self.spatial_encoder = SpatialEncoder(self.cfg.obs_encoder.spatial_encoder) - self.entity_encoder = EntityEncoder(self.cfg.obs_encoder.entity_encoder) - self.scatter_project = fc_block(self.cfg.scatter.input_dim, self.cfg.scatter.output_dim, activation=nn.ReLU()) - self.scatter_dim = self.cfg.scatter.output_dim - self.scatter_connection = ScatterConnection(self.cfg.scatter.scatter_type) - - def forward( - self, spatial_info: Dict[str, Tensor], entity_info: Dict[str, Tensor], scalar_info: Dict[str, Tensor], - entity_num: Tensor - ): - embedded_scalar, scalar_context, baseline_feature = self.scalar_encoder(scalar_info) - entity_embeddings, embedded_entity, entity_mask = self.entity_encoder(entity_info, entity_num) - entity_location = torch.cat([entity_info['y'].unsqueeze(dim=-1), entity_info['x'].unsqueeze(dim=-1)], dim=-1) - shape = spatial_info['height_map'].shape[-2:] - project_embeddings = self.scatter_project(entity_embeddings) - project_embeddings = project_embeddings * entity_mask.unsqueeze(dim=2) - - scatter_map = self.scatter_connection(project_embeddings, shape, entity_location) - embedded_spatial, map_skip = self.spatial_encoder(spatial_info, scatter_map) - lstm_input = torch.cat([embedded_scalar, embedded_entity, embedded_spatial], dim=-1) - return lstm_input, scalar_context, baseline_feature, entity_embeddings, map_skip diff --git a/dizoo/distar/model/head/__init__.py b/dizoo/distar/model/head/__init__.py deleted file mode 100644 index 94e44e0486..0000000000 --- a/dizoo/distar/model/head/__init__.py +++ /dev/null @@ -1,2 +0,0 @@ -from .action_arg_head import DelayHead, SelectedUnitsHead, TargetUnitHead, LocationHead, QueuedHead -from .action_type_head import ActionTypeHead diff --git a/dizoo/distar/model/head/action_arg_head.py b/dizoo/distar/model/head/action_arg_head.py deleted file mode 100644 index f9df39b9ba..0000000000 --- a/dizoo/distar/model/head/action_arg_head.py +++ /dev/null @@ -1,415 +0,0 @@ -''' -Copyright 2020 Sensetime X-lab. All Rights Reserved - -Main Function: - 1. Implementation for action_type_head, including basic processes. - 2. Implementation for delay_head, including basic processes. - 3. Implementation for queue_type_head, including basic processes. - 4. Implementation for selected_units_type_head, including basic processes. - 5. Implementation for target_unit_head, including basic processes. - 6. Implementation for location_head, including basic processes. -''' -from typing import Optional, List -from torch import Tensor -import math - -import torch -import torch.nn as nn -import torch.nn.functional as F -from ding.torch_utils import fc_block, conv2d_block, deconv2d_block, build_activation, ResBlock, NearestUpsample, \ - BilinearUpsample, sequence_mask, GatedConvResBlock, AttentionPool, script_lstm -from dizoo.distar.envs import MAX_ENTITY_NUM, MAX_SELECTED_UNITS_NUM - - -class DelayHead(nn.Module): - - def __init__(self, cfg): - super(DelayHead, self).__init__() - self.cfg = cfg - self.act = build_activation(self.cfg.activation, inplace=True) - self.fc1 = fc_block(self.cfg.input_dim, self.cfg.decode_dim, activation=self.act, norm_type=None) - self.fc2 = fc_block(self.cfg.decode_dim, self.cfg.decode_dim, activation=self.act, norm_type=None) - self.fc3 = fc_block(self.cfg.decode_dim, self.cfg.delay_dim, activation=None, norm_type=None) # regression - self.embed_fc1 = fc_block(self.cfg.delay_dim, self.cfg.delay_map_dim, activation=self.act, norm_type=None) - self.embed_fc2 = fc_block(self.cfg.delay_map_dim, self.cfg.input_dim, activation=None, norm_type=None) - - self.delay_dim = self.cfg.delay_dim - - def forward(self, embedding, delay: Optional[torch.Tensor] = None): - x = self.fc1(embedding) - x = self.fc2(x) - x = self.fc3(x) - if delay is None: - p = F.softmax(x, dim=1) - delay = torch.multinomial(p, 1)[:, 0] - - delay_encode = torch.nn.functional.one_hot(delay.long(), self.delay_dim).float() - embedding_delay = self.embed_fc1(delay_encode) - embedding_delay = self.embed_fc2(embedding_delay) # get autoregressive_embedding - - return x, delay, embedding + embedding_delay - - -class QueuedHead(nn.Module): - - def __init__(self, cfg): - super(QueuedHead, self).__init__() - self.cfg = cfg - self.act = build_activation(self.cfg.activation, inplace=True) - # to get queued logits - self.fc1 = fc_block(self.cfg.input_dim, self.cfg.decode_dim, activation=self.act, norm_type=None) - self.fc2 = fc_block(self.cfg.decode_dim, self.cfg.decode_dim, activation=self.act, norm_type=None) - self.fc3 = fc_block(self.cfg.decode_dim, self.cfg.queued_dim, activation=None, norm_type=None) - - # to get autoregressive_embedding - self.embed_fc1 = fc_block(self.cfg.queued_dim, self.cfg.queued_map_dim, activation=self.act, norm_type=None) - self.embed_fc2 = fc_block(self.cfg.queued_map_dim, self.cfg.input_dim, activation=None, norm_type=None) - - self.queued_dim = self.cfg.queued_dim - - def forward(self, embedding, queued=None): - x = self.fc1(embedding) - x = self.fc2(x) - x = self.fc3(x) - x.div_(self.cfg.temperature) - if queued is None: - p = F.softmax(x, dim=1) - queued = torch.multinomial(p, 1)[:, 0] - - queued_one_hot = torch.nn.functional.one_hot(queued.long(), self.queued_dim).float() - embedding_queued = self.embed_fc1(queued_one_hot) - embedding_queued = self.embed_fc2(embedding_queued) # get autoregressive_embedding - - return x, queued, embedding + embedding_queued - - -class SelectedUnitsHead(nn.Module): - - def __init__(self, cfg): - super(SelectedUnitsHead, self).__init__() - self.cfg = cfg - self.act = build_activation(self.cfg.activation, inplace=True) - self.key_fc = fc_block(self.cfg.entity_embedding_dim, self.cfg.key_dim, activation=None, norm_type=None) - self.query_fc1 = fc_block(self.cfg.input_dim, self.cfg.func_dim, activation=self.act) - self.query_fc2 = fc_block(self.cfg.func_dim, self.cfg.key_dim, activation=None) - self.embed_fc1 = fc_block(self.cfg.key_dim, self.cfg.func_dim, activation=self.act, norm_type=None) - self.embed_fc2 = fc_block(self.cfg.func_dim, self.cfg.input_dim, activation=None, norm_type=None) - - self.max_select_num = MAX_SELECTED_UNITS_NUM - self.max_entity_num = MAX_ENTITY_NUM - self.key_dim = self.cfg.key_dim - - self.num_layers = self.cfg.num_layers - - self.lstm = script_lstm(self.cfg.key_dim, self.cfg.hidden_dim, self.cfg.num_layers, LN=True) - self.end_embedding = torch.nn.Parameter(torch.FloatTensor(1, self.key_dim)) - stdv = 1. / math.sqrt(self.end_embedding.size(1)) - self.end_embedding.data.uniform_(-stdv, stdv) - if self.cfg.entity_reduce_type == 'attention_pool': - self.attention_pool = AttentionPool(key_dim=self.cfg.key_dim, head_num=2, output_dim=self.cfg.input_dim) - elif self.cfg.entity_reduce_type == 'attention_pool_add_num': - self.attention_pool = AttentionPool( - key_dim=self.cfg.key_dim, head_num=2, output_dim=self.cfg.input_dim, max_num=MAX_SELECTED_UNITS_NUM + 1 - ) - self.extra_units = self.cfg.extra_units # select extra units if selected units exceed max_entity_num=64 - - def _get_key_mask(self, entity_embedding, entity_num): - bs = entity_embedding.shape[0] - padding_end = torch.zeros(1, self.end_embedding.shape[1]).repeat(bs, 1, - 1).to(entity_embedding.device) # b, 1, c - key = self.key_fc(entity_embedding) # b, n, c - key = torch.cat([key, padding_end], dim=1) - end_embeddings = torch.ones(key.shape, dtype=key.dtype, device=key.device) * self.end_embedding.squeeze(dim=0) - flag = torch.ones(key.shape[:2], dtype=torch.bool, device=key.device).unsqueeze(dim=2) - flag[torch.arange(bs), entity_num] = 0 - end_embeddings = end_embeddings * ~flag - key = key * flag - key = key + end_embeddings - reduce_type = self.cfg.entity_reduce_type - if reduce_type == 'entity_num': - key_reduce = torch.div(key, entity_num.reshape(-1, 1, 1)) - key_embeddings = self.embed_fc(key_reduce) - elif reduce_type == 'constant': - key_reduce = torch.div(key, 512) - key_embeddings = self.embed_fc(key_reduce) - elif reduce_type == 'selected_units_num' or 'attention' in reduce_type: - key_embeddings = key - else: - raise NotImplementedError - - new_entity_num = entity_num + 1 # add end entity - mask = sequence_mask(new_entity_num, max_len=entity_embedding.shape[1] + 1) - return key, mask, key_embeddings - - def _get_pred_with_logit(self, logit): - logit.div_(self.cfg.temperature) - p = F.softmax(logit, dim=-1) - units = torch.multinomial(p, 1)[:, 0] - return units - - def _query( - self, - key: Tensor, - entity_num: Tensor, - autoregressive_embedding: Tensor, - logits_mask: Tensor, - key_embeddings: Tensor, - selected_units_num: Optional[Tensor] = None, - selected_units: Optional[Tensor] = None, - su_mask: Tensor = None - ): - ae = autoregressive_embedding - bs = ae.shape[0] - end_flag = torch.zeros(bs, dtype=torch.bool).to(ae.device) - results_list, logits_list = [], [] - state = [ - (torch.zeros(ae.shape[0], 32, device=ae.device), torch.zeros(ae.shape[0], 32, device=ae.device)) - for _ in range(self.num_layers) - ] - logits_mask[torch.arange(bs), entity_num] = torch.tensor([0], dtype=torch.bool, device=ae.device) - - result: Optional[Tensor] = None - results: Optional[Tensor] = None - if selected_units is not None and selected_units_num is not None: # train - bs = selected_units.shape[0] - seq_len = selected_units_num.max() - queries = [] - selected_mask = sequence_mask(selected_units_num) # b, s - logits_mask = logits_mask.repeat(max(seq_len, 1), 1, 1) # b, n -> s, b, n - logits_mask[0, torch.arange(bs), entity_num] = 0 # end flag is not available at first selection - selected_units_one_hot = torch.zeros(*key_embeddings.shape[:2], device=ae.device).unsqueeze(dim=2) - for i in range(max(seq_len, 1)): - if i > 0: - logits_mask[i] = logits_mask[i - 1] - if i == 1: # enable end flag - logits_mask[i, torch.arange(bs), entity_num] = 1 - logits_mask[i, torch.arange(bs), selected_units[:, i - 1]] = 0 # mask selected units - lstm_input = self.query_fc2(self.query_fc1(ae)).unsqueeze(0) - lstm_output, state = self.lstm(lstm_input, state) - queries.append(lstm_output) - reduce_type = self.cfg.entity_reduce_type - if reduce_type == 'selected_units_num' or 'attention' in reduce_type: - new_selected_units_one_hot = selected_units_one_hot.clone() # inplace operation can not backward - end_flag[selected_units[:, i] == entity_num] = 1 - new_selected_units_one_hot[torch.arange(bs)[~end_flag], selected_units[:, i][~end_flag], :] = 1 - if reduce_type == 'selected_units_num': - selected_units_emebedding = (key_embeddings * new_selected_units_one_hot).sum(dim=1) - S = selected_units_num - selected_units_emebedding[S != 0] = \ - selected_units_emebedding[S != 0] / new_selected_units_one_hot.sum(dim=1)[S != 0] - selected_units_emebedding = self.embed_fc2(self.embed_fc1(selected_units_emebedding)) - ae = autoregressive_embedding + selected_units_emebedding - elif reduce_type == 'attention_pool': - ae = autoregressive_embedding + self.attention_pool( - key_embeddings, mask=new_selected_units_one_hot - ) - elif reduce_type == 'attention_pool_add_num': - ae = autoregressive_embedding + self.attention_pool( - key_embeddings, - num=new_selected_units_one_hot.sum(dim=1).squeeze(dim=1), - mask=new_selected_units_one_hot, - ) - selected_units_one_hot = new_selected_units_one_hot.clone() - else: - ae = ae + key_embeddings[torch.arange(bs), - selected_units[:, i]] * (i + 1 < selected_units_num).unsqueeze(1) - - queries = torch.cat(queries, dim=0).unsqueeze(dim=2) # s, b, 1, -1 - key = key.unsqueeze(dim=0) # 1, b, n, -1 - query_result = queries * key - logits = query_result.sum(dim=3) # s, b, n - logits = logits.masked_fill(~logits_mask, -1e9) - logits = logits.permute(1, 0, 2).contiguous() - results = selected_units - extra_units = None - else: - selected_units_num = torch.ones(bs, dtype=torch.long, device=ae.device) * self.max_select_num - end_flag[~su_mask] = 1 - selected_units_num[~su_mask] = 0 - selected_units_one_hot = torch.zeros(*key_embeddings.shape[:2], device=ae.device).unsqueeze(dim=2) - for i in range(self.max_select_num): - if i > 0: - if i == 1: # end flag can be selected at second selection - logits_mask[torch.arange(bs), - entity_num] = torch.tensor([1], dtype=torch.bool, device=ae.device) - if result is not None: - logits_mask[torch.arange(bs), result.detach()] = torch.tensor( - [0], dtype=torch.bool, device=ae.device - ) # mask selected units - lstm_input = self.query_fc2(self.query_fc1(ae)).unsqueeze(0) - lstm_output, state = self.lstm(lstm_input, state) - queries = lstm_output.permute(1, 0, 2) # b, 1, c - query_result = queries * key - step_logits = query_result.sum(dim=2) # b, n - step_logits = step_logits.masked_fill(~logits_mask, -1e9) - step_logits = step_logits.div(1) - result = self._get_pred_with_logit(step_logits) - selected_units_num[(result == entity_num) * ~(end_flag)] = torch.tensor(i + 1).to(result.device) - end_flag[result == entity_num] = torch.tensor([1], dtype=torch.bool, device=ae.device) - results_list.append(result) - logits_list.append(step_logits) - reduce_type = self.cfg.entity_reduce_type - if reduce_type == 'selected_units_num' or 'attention' in reduce_type: - selected_units_one_hot[torch.arange(bs)[~end_flag], result[~end_flag], :] = 1 - if reduce_type == 'selected_units_num': - selected_units_emebedding = (key_embeddings * selected_units_one_hot).sum(dim=1) - slected_num = selected_units_one_hot.sum(dim=1).squeeze(dim=1) - selected_units_emebedding[slected_num != 0] = selected_units_emebedding[ - slected_num != 0] / slected_num[slected_num != 0].unsqueeze(dim=1) - selected_units_emebedding = self.embed_fc2(self.embed_fc1(selected_units_emebedding)) - ae = autoregressive_embedding + selected_units_emebedding - elif reduce_type == 'attention_pool': - ae = autoregressive_embedding + self.attention_pool(key_embeddings, mask=selected_units_one_hot) - elif reduce_type == 'attention_pool_add_num': - ae = autoregressive_embedding + self.attention_pool( - key_embeddings, - num=selected_units_one_hot.sum(dim=1).squeeze(dim=1), - mask=selected_units_one_hot, - ) - else: - ae = ae + key_embeddings[torch.arange(bs), result] * ~end_flag.unsqueeze(dim=1) - if end_flag.all(): - break - if self.extra_units: - end_flag_logit = step_logits[torch.arange(bs), entity_num] - extra_units = ((step_logits > end_flag_logit.unsqueeze(dim=1)) * ~end_flag.unsqueeze(dim=1)).float() - results = torch.stack(results_list, dim=0) - results = results.transpose(1, 0).contiguous() - logits = torch.stack(logits_list, dim=0) - logits = logits.transpose(1, 0).contiguous() - return logits, results, ae, selected_units_num, extra_units - - def forward( - self, - embedding, - entity_embedding, - entity_num, - selected_units_num: Optional[Tensor] = None, - selected_units: Optional[Tensor] = None, - su_mask: Optional[Tensor] = None - ): - key, mask, key_embeddings = self._get_key_mask(entity_embedding, entity_num) - logits, units, embedding, selected_units_num, extra_units = self._query( - key, entity_num, embedding, mask, key_embeddings, selected_units_num, selected_units, su_mask - ) - return logits, units, embedding, selected_units_num, extra_units - - -class TargetUnitHead(nn.Module): - - def __init__(self, cfg): - super(TargetUnitHead, self).__init__() - self.cfg = cfg - self.act = build_activation(self.cfg.activation, inplace=True) - self.key_fc = fc_block(self.cfg.entity_embedding_dim, self.cfg.key_dim, activation=None, norm_type=None) - self.query_fc1 = fc_block(self.cfg.input_dim, self.cfg.key_dim, activation=self.act, norm_type=None) - self.query_fc2 = fc_block(self.cfg.key_dim, self.cfg.key_dim, activation=None, norm_type=None) - self.key_dim = self.cfg.key_dim - self.max_entity_num = MAX_ENTITY_NUM - - def forward(self, embedding, entity_embedding, entity_num, target_unit: Optional[torch.Tensor] = None): - key = self.key_fc(entity_embedding) - mask = sequence_mask(entity_num, max_len=entity_embedding.shape[1]) - - query = self.query_fc2(self.query_fc1(embedding)) - - logits = query.unsqueeze(1) * key - logits = logits.sum(dim=2) # b, n, -1 - logits.masked_fill_(~mask, value=-1e9) - - logits.div_(self.cfg.temperature) - if target_unit is None: - p = F.softmax(logits, dim=1) - target_unit = torch.multinomial(p, 1)[:, 0] - return logits, target_unit - - -class LocationHead(nn.Module): - - def __init__(self, cfg): - super(LocationHead, self).__init__() - self.cfg = cfg - self.act = build_activation(self.cfg.activation, inplace=True) - self.reshape_channel = self.cfg.reshape_channel - - self.conv1 = conv2d_block( - self.cfg.map_skip_dim + self.cfg.reshape_channel, - self.cfg.res_dim, - 1, - 1, - 0, - activation=build_activation(self.cfg.activation, inplace=True), - norm_type=None - ) - self.res = nn.ModuleList() - self.res_act = nn.ModuleList() - self.res_dim = self.cfg.res_dim - self.use_gate = self.cfg.gate - self.project_embed = fc_block( - self.cfg.input_dim, - self.cfg.spatial_y // 8 * self.cfg.spatial_x // 8 * 4, - activation=build_activation(self.cfg.activation, inplace=True) - ) - - self.res = nn.ModuleList() - for i in range(self.cfg.res_num): - if self.use_gate: - self.res.append( - GatedConvResBlock( - self.res_dim, - self.res_dim, - 3, - 1, - 1, - activation=build_activation(self.cfg.activation, inplace=True), - norm_type=None - ) - ) - else: - self.res.append(ResBlock(self.dim, build_activation(self.cfg.activation, inplace=True), norm_type=None)) - - self.upsample = nn.ModuleList() # upsample list - dims = [self.res_dim] + self.cfg.upsample_dims - assert (self.cfg.upsample_type in ['deconv', 'nearest', 'bilinear']) - for i in range(len(self.cfg.upsample_dims)): - if i == len(self.cfg.upsample_dims) - 1: - activation = None - else: - activation = build_activation(self.cfg.activation, inplace=True) - if self.cfg.upsample_type == 'deconv': - self.upsample.append( - deconv2d_block(dims[i], dims[i + 1], 4, 2, 1, activation=activation, norm_type=None) - ) - else: - self.upsample.append(conv2d_block(dims[i], dims[i + 1], 3, 1, 1, activation=activation, norm_type=None)) - - def forward(self, embedding, map_skip: List[Tensor], location=None): - projected_embedding = self.project_embed(embedding) - reshape_embedding = projected_embedding.reshape( - projected_embedding.shape[0], self.reshape_channel, self.cfg.spatial_y // 8, self.cfg.spatial_x // 8 - ) - cat_feature = torch.cat([reshape_embedding, map_skip[-1]], dim=1) - - x1 = self.act(cat_feature) - x = self.conv1(x1) - - # reverse cat_feature instead of reversing resblock - for i in range(self.cfg.res_num): - x = x + map_skip[len(map_skip) - i - 1] - if self.use_gate: - x = self.res[i](x, x) - else: - x = self.res[i](x) - for i, layer in enumerate(self.upsample): - if self.cfg.upsample_type == 'nearest': - x = F.interpolate(x, scale_factor=2., mode='nearest') - elif self.cfg.upsample_type == 'bilinear': - x = F.interpolate(x, scale_factor=2., mode='bilinear') - x = layer(x) - - logits_flatten = x.view(x.shape[0], -1) - logits_flatten.div_(self.cfg.temperature) - p = F.softmax(logits_flatten, dim=1) - if location is None: - location = torch.multinomial(p, 1)[:, 0] - return logits_flatten, location diff --git a/dizoo/distar/model/head/action_type_head.py b/dizoo/distar/model/head/action_type_head.py deleted file mode 100644 index ad91ce06e8..0000000000 --- a/dizoo/distar/model/head/action_type_head.py +++ /dev/null @@ -1,63 +0,0 @@ -''' -Copyright 2020 Sensetime X-lab. All Rights Reserved - -Main Function: - 1. Implementation for action_type_head, including basic processes. -''' -from typing import Optional, List, Tuple -from torch import Tensor -import torch -import torch.nn as nn -import torch.nn.functional as F -from ding.torch_utils import ResFCBlock, fc_block, build_activation2 -from dizoo.distar.envs import ACTION_RACE_MASK - - -class ActionTypeHead(nn.Module): - __constants__ = ['mask_action'] - - def __init__(self, cfg): - super(ActionTypeHead, self).__init__() - self.cfg = cfg - self.act = build_activation2(self.cfg.activation) # use relu as default - self.project = fc_block(self.cfg.input_dim, self.cfg.res_dim, activation=self.act, norm_type=None) - blocks = [ResFCBlock(self.cfg.res_dim, self.act, self.cfg.norm_type) for _ in range(self.cfg.res_num)] - self.res = nn.Sequential(*blocks) - self.action_fc = build_activation2('glu')(self.cfg.res_dim, self.cfg.action_num, self.cfg.context_dim) - - self.action_map_fc1 = fc_block( - self.cfg.action_num, self.cfg.action_map_dim, activation=self.act, norm_type=None - ) - self.action_map_fc2 = fc_block( - self.cfg.action_map_dim, self.cfg.action_map_dim, activation=None, norm_type=None - ) - self.glu1 = build_activation2('glu')(self.cfg.action_map_dim, self.cfg.gate_dim, self.cfg.context_dim) - self.glu2 = build_activation2('glu')(self.cfg.input_dim, self.cfg.gate_dim, self.cfg.context_dim) - self.action_num = self.cfg.action_num - self.use_mask = self.cfg.use_mask - self.race = self.cfg.race - - def forward(self, - lstm_output, - scalar_context, - action_type: Optional[torch.Tensor] = None) -> Tuple[Tensor, Tensor, Tensor]: - x = self.project(lstm_output) - x = self.res(x) - x = self.action_fc(x, scalar_context) - x.div_(self.cfg.temperature) - if self.use_mask: - mask = ACTION_RACE_MASK[self.race].to(x.device) - x = x.masked_fill(~mask.unsqueeze(dim=0), -1e9) - if action_type is None: - p = F.softmax(x, dim=1) - action_type = torch.multinomial(p, 1)[:, 0] - - # one-hot version of action_type - action_one_hot = torch.nn.functional.one_hot(action_type.long(), self.action_num).float() - embedding1 = self.action_map_fc1(action_one_hot) - embedding1 = self.action_map_fc2(embedding1) - embedding1 = self.glu1(embedding1, scalar_context) - embedding2 = self.glu2(lstm_output, scalar_context) - embedding = embedding1 + embedding2 - - return x, action_type, embedding diff --git a/dizoo/distar/model/model.py b/dizoo/distar/model/model.py deleted file mode 100644 index 0e0a874483..0000000000 --- a/dizoo/distar/model/model.py +++ /dev/null @@ -1,191 +0,0 @@ -from collections import OrderedDict -from typing import Dict, Tuple, List -from torch import Tensor - -import os.path as osp -import torch -import torch.nn as nn - -from ding.utils import read_yaml_config, deep_merge_dicts -from ding.torch_utils import detach_grad, script_lstm -from dizoo.distar.envs import MAX_SELECTED_UNITS_NUM -from .encoder import Encoder -from .obs_encoder.value_encoder import ValueEncoder -from .policy import Policy -from .value import ValueBaseline - -alphastar_model_default_config = read_yaml_config(osp.join(osp.dirname(__file__), "actor_critic_default_config.yaml")) - - -class Model(nn.Module): - - def __init__(self, cfg, use_value_network=False): - super(Model, self).__init__() - self.cfg = deep_merge_dicts(alphastar_model_default_config, cfg).model - self.encoder = Encoder(self.cfg) - self.policy = Policy(self.cfg) - self.use_value_network = use_value_network - if self.use_value_network: - self.use_value_feature = self.cfg.value.use_value_feature - if self.use_value_feature: - self.value_encoder = ValueEncoder(self.cfg.value) - self.value_networks = nn.ModuleDict() - for k, v in self.cfg.value.items(): - if k in self.cfg.enable_baselines: - # creating a ValueBaseline network for each baseline, to be used in _critic_forward - value_cfg = v.param - value_cfg['use_value_feature'] = self.use_value_feature - self.value_networks[v.name] = ValueBaseline(value_cfg) - # name of needed cumulative stat items - self.only_update_baseline = self.cfg.only_update_baseline - self.core_lstm = script_lstm( - self.cfg.encoder.core_lstm.input_size, - self.cfg.encoder.core_lstm.hidden_size, - self.cfg.encoder.core_lstm.num_layers, - LN=True - ) - - def forward( - self, - spatial_info: Tensor, - entity_info: Dict[str, Tensor], - scalar_info: Dict[str, Tensor], - entity_num: Tensor, - hidden_state: List[Tuple[Tensor, Tensor]], - ): - lstm_input, scalar_context, baseline_feature, entity_embeddings, map_skip = \ - self.encoder(spatial_info, entity_info, scalar_info, entity_num) - lstm_output, out_state = self.core_lstm(lstm_input.unsqueeze(dim=0), hidden_state) - action_info, selected_units_num, logit, extra_units = self.policy( - lstm_output.squeeze(dim=0), entity_embeddings, map_skip, scalar_context, entity_num - ) - return action_info, selected_units_num, out_state - - def compute_logp_action( - self, spatial_info: Tensor, entity_info: Dict[str, Tensor], scalar_info: Dict[str, Tensor], entity_num: Tensor, - hidden_state: List[Tuple[Tensor, Tensor]], **kwargs - ): - lstm_input, scalar_context, baseline_feature, entity_embeddings, map_skip = \ - self.encoder(spatial_info, entity_info, scalar_info, entity_num) - lstm_output, out_state = self.core_lstm(lstm_input.unsqueeze(dim=0), hidden_state) - action_info, selected_units_num, logit, extra_units = self.policy( - lstm_output.squeeze(dim=0), entity_embeddings, map_skip, scalar_context, entity_num - ) - log_action_probs = {} - for k, action in action_info.items(): - dist = torch.distributions.Categorical(logits=logit[k]) - action_log_probs = dist.log_prob(action) - log_action_probs[k] = action_log_probs - return { - 'action_info': action_info, - 'action_logp': log_action_probs, - 'selected_units_num': selected_units_num, - 'entity_num': entity_num, - 'hidden_state': out_state, - 'logit': logit, - 'extra_units': extra_units - } - - def compute_teacher_logit( - self, spatial_info: Tensor, entity_info: Dict[str, Tensor], scalar_info: Dict[str, Tensor], entity_num: Tensor, - hidden_state: List[Tuple[Tensor, Tensor]], selected_units_num, action_info: Dict[str, Tensor], **kwargs - ): - lstm_input, scalar_context, baseline_feature, entity_embeddings, map_skip = \ - self.encoder(spatial_info, entity_info, scalar_info, entity_num) - lstm_output, out_state = self.core_lstm(lstm_input.unsqueeze(dim=0), hidden_state) - action_info, selected_units_num, logit = self.policy.train_forward( - lstm_output.squeeze(dim=0), entity_embeddings, map_skip, scalar_context, entity_num, action_info, - selected_units_num - ) - return { - 'logit': logit, - 'hidden_state': out_state, - 'entity_num': entity_num, - 'selected_units_num': selected_units_num - } - - def rl_learn_forward( - self, spatial_info, entity_info, scalar_info, entity_num, hidden_state, action_info, selected_units_num, - behaviour_logp, teacher_logit, mask, reward, step, batch_size, unroll_len, **kwargs - ): - assert self.use_value_network - flat_action_info = {} - for k, val in action_info.items(): - flat_action_info[k] = torch.flatten(val, start_dim=0, end_dim=1) - flat_selected_units_num = torch.flatten(selected_units_num, start_dim=0, end_dim=1) - - lstm_input, scalar_context, baseline_feature, entity_embeddings, map_skip = \ - self.encoder(spatial_info, entity_info, scalar_info, entity_num) - hidden_size = hidden_state[0][0].shape[-1] - - hidden_state = [ - [hidden_state[i][j].view(-1, batch_size, hidden_size)[0, :, :] for j in range(len(hidden_state[i]))] - for i in range(len(hidden_state)) - ] - lstm_output, out_state = self.core_lstm(lstm_input.view(-1, batch_size, lstm_input.shape[-1]), hidden_state) - lstm_output = lstm_output.view(-1, lstm_output.shape[-1]) - - policy_lstm_input = lstm_output.squeeze(dim=0)[:-batch_size] - policy_entity_embeddings = entity_embeddings[:-batch_size] - policy_map_skip = [map[:-batch_size] for map in map_skip] - policy_scalar_context = scalar_context[:-batch_size] - policy_entity_num = entity_num[:-batch_size] - _, _, logits = self.policy.train_forward( - policy_lstm_input, policy_entity_embeddings, policy_map_skip, policy_scalar_context, policy_entity_num, - flat_action_info, flat_selected_units_num - ) - - # logits['selected_units'] = logits['selected_units'].mean(dim=1) - critic_input = lstm_output.squeeze(0) - # add state info - if self.only_update_baseline: - critic_input = detach_grad(critic_input) - baseline_feature = detach_grad(baseline_feature) - if self.use_value_feature: - value_feature = kwargs['value_feature'] - value_feature = self.value_encoder(value_feature) - critic_input = torch.cat([critic_input, value_feature, baseline_feature], dim=1) - baseline_values = {} - for k, v in self.value_networks.items(): - baseline_values[k] = v(critic_input) - for k, val in logits.items(): - logits[k] = val.view(unroll_len, batch_size, *val.shape[1:]) - for k, val in baseline_values.items(): - baseline_values[k] = val.view(unroll_len + 1, batch_size) - outputs = {} - outputs['unroll_len'] = unroll_len - outputs['batch_size'] = batch_size - outputs['selected_units_num'] = selected_units_num - logits['selected_units'] = torch.nn.functional.pad( - logits['selected_units'], ( - 0, - 0, - 0, - MAX_SELECTED_UNITS_NUM - logits['selected_units'].shape[2], - ), 'constant', -1e9 - ) - outputs['target_logit'] = logits - outputs['value'] = baseline_values - outputs['action_log_prob'] = behaviour_logp - outputs['teacher_logit'] = teacher_logit - outputs['mask'] = mask - outputs['action'] = action_info - outputs['reward'] = reward - outputs['step'] = step - - return outputs - - def sl_learn_forward( - self, spatial_info, entity_info, scalar_info, entity_num, selected_units_num, traj_lens, hidden_state, - action_info, **kwargs - ): - batch_size = len(traj_lens) - lstm_input, scalar_context, baseline_feature, entity_embeddings, map_skip = \ - self.encoder(spatial_info, entity_info, scalar_info, entity_num) - lstm_input = lstm_input.view(-1, lstm_input.shape[0] // batch_size, lstm_input.shape[-1]).permute(1, 0, 2) - lstm_output, out_state = self.core_lstm(lstm_input, hidden_state) - lstm_output = lstm_output.permute(1, 0, 2).contiguous().view(-1, lstm_output.shape[-1]) - action_info, selected_units_num, logits = self.policy.train_forward( - lstm_output, entity_embeddings, map_skip, scalar_context, entity_num, action_info, selected_units_num - ) - return logits, action_info, out_state diff --git a/dizoo/distar/model/obs_encoder/__init__.py b/dizoo/distar/model/obs_encoder/__init__.py deleted file mode 100644 index 6a6dc1103e..0000000000 --- a/dizoo/distar/model/obs_encoder/__init__.py +++ /dev/null @@ -1,4 +0,0 @@ -from .scalar_encoder import ScalarEncoder -from .spatial_encoder import SpatialEncoder -from .entity_encoder import EntityEncoder -from .value_encoder import ValueEncoder diff --git a/dizoo/distar/model/obs_encoder/entity_encoder.py b/dizoo/distar/model/obs_encoder/entity_encoder.py deleted file mode 100644 index a47f34fd3a..0000000000 --- a/dizoo/distar/model/obs_encoder/entity_encoder.py +++ /dev/null @@ -1,101 +0,0 @@ -import torch -import torch.nn as nn -from typing import Dict -from torch import Tensor - -from ding.torch_utils import fc_block, build_activation, sequence_mask, Transformer -from dizoo.distar.envs import MAX_ENTITY_NUM - - -def get_binary_embed_mat(bit_num): - location_embedding = [] - for n in range(2 ** bit_num): - s = '0' * (bit_num - len(bin(n)[2:])) + bin(n)[2:] - location_embedding.append(list(int(i) for i in s)) - return torch.tensor(location_embedding).float() - - -class EntityEncoder(nn.Module): - r''' - B=batch size EN=any number of entities ID=input_dim OS=output_size=256 - (B*EN*ID) (EN'*OS) (EN'*OS) (EN'*OS) (B*EN*OS) - x -> combine -> Transformer -> act -> entity_fc -> split -> entity_embeddings - batch | (B*EN*OS) (B*OS) (B*OS) - \-> split -> mean -> embed_fc -> embedded_entity - ''' - - def __init__(self, cfg): - super(EntityEncoder, self).__init__() - self.encode_modules = nn.ModuleDict() - self.cfg = cfg - for k, item in self.cfg.module.items(): - if item['arc'] == 'one_hot': - self.encode_modules[k] = nn.Embedding.from_pretrained( - torch.eye(item['num_embeddings']), freeze=True, padding_idx=None - ) - if item['arc'] == 'binary': - self.encode_modules[k] = torch.nn.Embedding.from_pretrained( - get_binary_embed_mat(item['num_embeddings']), freeze=True, padding_idx=None - ) - self.act = build_activation(self.cfg.activation, inplace=True) - self.transformer = Transformer( - input_dim=self.cfg.input_dim, - head_dim=self.cfg.head_dim, - hidden_dim=self.cfg.hidden_dim, - output_dim=self.cfg.output_dim, - head_num=self.cfg.head_num, - mlp_num=self.cfg.mlp_num, - layer_num=self.cfg.layer_num, - dropout_ratio=self.cfg.dropout_ratio, - activation=self.act, - ln_type=self.cfg.ln_type - ) - self.entity_fc = fc_block(self.cfg.output_dim, self.cfg.output_dim, activation=self.act) - self.embed_fc = fc_block(self.cfg.output_dim, self.cfg.output_dim, activation=self.act) - if self.cfg.entity_reduce_type == 'attention_pool': - from ding.torch_utils import AttentionPool - self.attention_pool = AttentionPool(key_dim=self.cfg.output_dim, head_num=2, output_dim=self.cfg.output_dim) - elif self.cfg.entity_reduce_type == 'attention_pool_add_num': - from ding.torch_utils import AttentionPool - self.attention_pool = AttentionPool( - key_dim=self.cfg.output_dim, head_num=2, output_dim=self.cfg.output_dim, max_num=MAX_ENTITY_NUM + 1 - ) - - def forward(self, x: Dict[str, Tensor], entity_num): - entity_embedding = [] - for k, item in self.cfg.module.items(): - assert k in x.keys(), '{} not in {}'.format(k, x.keys()) - if item['arc'] == 'one_hot': - # check data - over_cross_data = x[k] >= item['num_embeddings'] - # if over_cross_data.any(): - # print(k, x[k][over_cross_data]) - lower_cross_data = x[k] < 0 - if lower_cross_data.any(): - print(k, x[k][lower_cross_data]) - raise RuntimeError - clipped_data = x[k].long().clamp_(max=item['num_embeddings'] - 1) - entity_embedding.append(self.encode_modules[k](clipped_data)) - elif item['arc'] == 'binary': - entity_embedding.append(self.encode_modules[k](x[k].long())) - elif item['arc'] == 'unsqueeze': - entity_embedding.append(x[k].float().unsqueeze(dim=-1)) - x = torch.cat(entity_embedding, dim=-1) - mask = sequence_mask(entity_num, max_len=x.shape[1]) - x = self.transformer(x, mask=mask) - entity_embeddings = self.entity_fc(self.act(x)) - - if self.cfg.entity_reduce_type in ['entity_num', 'selected_units_num']: - x_mask = x * mask.unsqueeze(dim=2) - embedded_entity = x_mask.sum(dim=1) / entity_num.unsqueeze(dim=-1) - elif self.cfg.entity_reduce_type == 'constant': - x_mask = x * mask.unsqueeze(dim=2) - embedded_entity = x_mask.sum(dim=1) / 512 - elif self.cfg.entity_reduce_type == 'attention_pool': - embedded_entity = self.attention_pool(x, mask=mask.unsqueeze(dim=2)) - elif self.cfg.entity_reduce_type == 'attention_pool_add_num': - embedded_entity = self.attention_pool(x, num=entity_num, mask=mask.unsqueeze(dim=2)) - else: - raise NotImplementedError - embedded_entity = self.embed_fc(embedded_entity) - return entity_embeddings, embedded_entity, mask diff --git a/dizoo/distar/model/obs_encoder/scalar_encoder.py b/dizoo/distar/model/obs_encoder/scalar_encoder.py deleted file mode 100644 index 14e02086bc..0000000000 --- a/dizoo/distar/model/obs_encoder/scalar_encoder.py +++ /dev/null @@ -1,143 +0,0 @@ -from typing import Dict -from torch import Tensor -import torch -import torch.nn as nn -import torch.nn.functional as F -from ding.torch_utils import fc_block, build_activation, Transformer -from .entity_encoder import get_binary_embed_mat - - -def compute_denominator(x: torch.Tensor, dim: int) -> torch.Tensor: - x = x // 2 * 2 - x = torch.div(x, dim) - x = torch.pow(10000., x) - x = torch.div(1., x) - return x - - -class BeginningBuildOrderEncoder(nn.Module): - - def __init__(self, cfg): - super(BeginningBuildOrderEncoder, self).__init__() - self.cfg = cfg - self.output_dim = self.cfg.output_dim - self.input_dim = self.cfg.action_one_hot_dim + 20 + self.cfg.binary_dim * 2 - self.act = build_activation(self.cfg.activation, inplace=True) - self.transformer = Transformer( - input_dim=self.input_dim, - head_dim=self.cfg.head_dim, - hidden_dim=self.cfg.output_dim * 2, - output_dim=self.cfg.output_dim - ) - self.embedd_fc = fc_block(self.cfg.output_dim, self.output_dim, activation=self.act) - self.action_one_hot = nn.Embedding.from_pretrained( - torch.eye(self.cfg.action_one_hot_dim), freeze=True, padding_idx=None - ) - self.order_one_hot = nn.Embedding.from_pretrained(torch.eye(20), freeze=True, padding_idx=None) - self.location_binary = nn.Embedding.from_pretrained( - get_binary_embed_mat(self.cfg.binary_dim), freeze=True, padding_idx=None - ) - - def _add_seq_info(self, x): - indices_one_hot = torch.zeros(size=(x.shape[1], x.shape[1]), device=x.device) - indices = torch.arange(x.shape[1], device=x.device).unsqueeze(dim=1) - indices_one_hot = indices_one_hot.scatter_(dim=-1, index=indices, value=1.) - indices_one_hot = indices_one_hot.unsqueeze(0).repeat(x.shape[0], 1, 1) # expand to batch dim - return torch.cat([x, indices_one_hot], dim=2) - - def forward(self, x, bo_location): - x = self.action_one_hot(x.long()) - x = self._add_seq_info(x) - location_x = bo_location % self.cfg.spatial_x - location_y = bo_location // self.cfg.spatial_x - location_x = self.location_binary(location_x.long()) - location_y = self.location_binary(location_y.long()) - x = torch.cat([x, location_x, location_y], dim=2) - assert len(x.shape) == 3 - x = self.transformer(x) - x = x.mean(dim=1) - x = self.embedd_fc(x) - return x - - -class ScalarEncoder(nn.Module): - - def __init__(self, cfg): - super(ScalarEncoder, self).__init__() - self.cfg = cfg - self.act = build_activation(self.cfg.activation, inplace=True) - self.keys = [] - self.scalar_context_keys = [] - self.baseline_feature_keys = [] - self.one_hot_keys = [] - - self.encode_modules = nn.ModuleDict() - - for k, item in self.cfg.module.items(): - if k == 'time': - continue - if item['arc'] == 'one_hot': - encoder = nn.Embedding(num_embeddings=item['num_embeddings'], embedding_dim=item['embedding_dim']) - torch.nn.init.xavier_uniform_(encoder.weight) - self.encode_modules[k] = encoder - self.one_hot_keys.append(k) - elif item['arc'] == 'fc': - encoder = fc_block(item['input_dim'], item['output_dim'], activation=self.act) - self.encode_modules[k] = encoder - if 'scalar_context' in item.keys() and item['scalar_context']: - self.scalar_context_keys.append(k) - if 'baseline_feature' in item.keys() and item['baseline_feature']: - self.baseline_feature_keys.append(k) - - self.position_array = torch.nn.Parameter( - compute_denominator( - torch.arange(0, self.cfg.module.time.output_dim, dtype=torch.float), self.cfg.module.time.output_dim - ), - requires_grad=False - ) - self.time_embedding_dim = self.cfg.module.time.output_dim - bo_cfg = self.cfg.module.beginning_order - self.encode_modules['beginning_order'] = BeginningBuildOrderEncoder(bo_cfg) - - def time_encoder(self, x: Tensor): - v = torch.zeros(size=(x.shape[0], self.time_embedding_dim), dtype=torch.float, device=x.device) - assert len(x.shape) == 1 - x = x.unsqueeze(dim=1) - v[:, 0::2] = torch.sin(x * self.position_array[0::2]) # even - v[:, 1::2] = torch.cos(x * self.position_array[1::2]) # odd - return v - - def forward(self, x: Dict[str, Tensor]): - embedded_scalar = [] - scalar_context = [] - baseline_feature = [] - - for key, item in self.cfg.module.items(): - assert key in x.keys(), key - if key == 'time': - continue - elif item['arc'] == 'one_hot': - # check data - over_cross_data = x[key] >= item['num_embeddings'] - if over_cross_data.any(): - print(key, x[key][over_cross_data]) - - x[key] = x[key].clamp_(max=item['num_embeddings'] - 1) - embedding = self.encode_modules[key](x[key].long()) - embedding = self.act(embedding) - elif key == 'beginning_order': - embedding = self.encode_modules[key](x[key].float(), x['bo_location'].long()) - else: - embedding = self.encode_modules[key](x[key].float()) - embedded_scalar.append(embedding) - if key in self.scalar_context_keys: - scalar_context.append(embedding) - if key in self.baseline_feature_keys: - baseline_feature.append(embedding) - time_embedding = self.time_encoder(x['time']) - embedded_scalar.append(time_embedding) - embedded_scalar = torch.cat(embedded_scalar, dim=1) - scalar_context = torch.cat(scalar_context, dim=1) - baseline_feature = torch.cat(baseline_feature, dim=1) - - return embedded_scalar, scalar_context, baseline_feature diff --git a/dizoo/distar/model/obs_encoder/spatial_encoder.py b/dizoo/distar/model/obs_encoder/spatial_encoder.py deleted file mode 100644 index 8bfda6fcfe..0000000000 --- a/dizoo/distar/model/obs_encoder/spatial_encoder.py +++ /dev/null @@ -1,96 +0,0 @@ -import math -from collections.abc import Sequence -import torch -import torch.nn as nn -import torch.nn.functional as F -from ding.torch_utils import conv2d_block, fc_block, build_activation, ResBlock, same_shape - - -class SpatialEncoder(nn.Module): - __constants__ = ['head_type'] - - def __init__(self, cfg): - super(SpatialEncoder, self).__init__() - self.cfg = cfg - self.act = build_activation(self.cfg.activation, inplace=True) - if self.cfg.norm_type == 'none': - self.norm = None - else: - self.norm = self.cfg.norm_type - self.project = conv2d_block( - self.cfg.input_dim, self.cfg.project_dim, 1, 1, 0, activation=self.act, norm_type=self.norm - ) - dims = [self.cfg.project_dim] + self.cfg.down_channels - self.down_channels = self.cfg.down_channels - self.encode_modules = nn.ModuleDict() - self.downsample = nn.ModuleList() - for k, item in self.cfg.module.items(): - if item['arc'] == 'one_hot': - self.encode_modules[k] = nn.Embedding.from_pretrained( - torch.eye(item['num_embeddings']), freeze=True, padding_idx=None - ) - for i in range(len(self.down_channels)): - if self.cfg.downsample_type == 'conv2d': - self.downsample.append( - conv2d_block(dims[i], dims[i + 1], 4, 2, 1, activation=self.act, norm_type=self.norm) - ) - elif self.cfg.downsample_type in ['avgpool', 'maxpool']: - self.downsample.append( - conv2d_block(dims[i], dims[i + 1], 3, 1, 1, activation=self.act, norm_type=self.norm) - ) - else: - raise KeyError("invalid downsample module type :{}".format(type(self.cfg.downsample_type))) - self.res = nn.ModuleList() - self.head_type = self.cfg.get('head_type', 'pool') - dim = dims[-1] - self.resblock_num = self.cfg.resblock_num - for i in range(self.cfg.resblock_num): - self.res.append(ResBlock(dim, self.act, norm_type=self.norm)) - if self.head_type == 'fc': - self.fc = fc_block( - dim * self.cfg.spatial_y // 8 * self.cfg.spatial_x // 8, self.cfg.fc_dim, activation=self.act - ) - else: - self.gap = nn.AdaptiveAvgPool2d((1, 1)) - self.fc = fc_block(dim, self.cfg.fc_dim, activation=self.act) - - def forward(self, x, scatter_map): - embeddings = [] - for k, item in self.cfg.module.items(): - if item['arc'] == 'one_hot': - embedding = self.encode_modules[k](x[k].long()) - embedding = embedding.permute(0, 3, 1, 2) - embeddings.append(embedding) - elif item['arc'] == 'other': - assert k == 'height_map' - embeddings.append(x[k].unsqueeze(dim=1).float() / 256) - elif item['arc'] == 'scatter': - bs, shape_x, shape_y = x[k].shape[0], self.cfg.spatial_x, self.cfg.spatial_y - embedding = torch.zeros(bs * shape_y * shape_x, device=x[k].device) - bias = torch.arange(bs, device=x[k].device).unsqueeze(dim=1) * shape_y * shape_x - x[k] = x[k] + bias - x[k] = x[k].view(-1) - embedding[x[k].long()] = 1. - embedding = embedding.view(bs, 1, shape_y, shape_x) - embeddings.append(embedding) - embeddings.append(scatter_map) - x = torch.cat(embeddings, dim=1) - x = self.project(x) - map_skip = [] - for i in range(len(self.downsample)): - map_skip.append(x) - if self.cfg.downsample_type == 'avgpool': - x = torch.nn.functional.avg_pool2d(x, 2, 2) - elif self.cfg.downsample_type == 'maxpool': - x = torch.nn.functional.max_pool2d(x, 2, 2) - x = self.downsample[i](x) - for block in self.res: - map_skip.append(x) - x = block(x) - if isinstance(x, torch.Tensor): - if self.head_type != 'fc': - x = self.gap(x) - - x = x.view(x.shape[0], -1) - x = self.fc(x) - return x, map_skip diff --git a/dizoo/distar/model/obs_encoder/value_encoder.py b/dizoo/distar/model/obs_encoder/value_encoder.py deleted file mode 100644 index ef87a03766..0000000000 --- a/dizoo/distar/model/obs_encoder/value_encoder.py +++ /dev/null @@ -1,84 +0,0 @@ -import torch -import torch.nn as nn -import torch.nn.functional as F -from ding.torch_utils import fc_block, build_activation, conv2d_block, ResBlock, same_shape, sequence_mask, \ - Transformer, scatter_connection_v2 -from dizoo.distar.envs import BEGIN_ACTIONS -from .spatial_encoder import SpatialEncoder -from .scalar_encoder import BeginningBuildOrderEncoder - - -class ValueEncoder(nn.Module): - - def __init__(self, cfg): - super(ValueEncoder, self).__init__() - self.whole_cfg = cfg - self.cfg = cfg.encoder - self.act = build_activation('relu', inplace=True) - self.encode_modules = nn.ModuleDict() - for k, item in self.cfg.modules.items(): - if item['arc'] == 'fc': - self.encode_modules[k] = fc_block(item['input_dim'], item['output_dim'], activation=self.act) - elif item['arc'] == 'one_hot': - self.encode_modules[k] = nn.Embedding( - num_embeddings=item['num_embeddings'], embedding_dim=item['embedding_dim'] - ) - - bo_cfg = self.cfg.modules.beginning_order - self.encode_modules['beginning_order'] = BeginningBuildOrderEncoder(bo_cfg) - self.scatter_project = fc_block( - self.cfg.scatter.scatter_input_dim, self.cfg.scatter.scatter_dim, activation=self.act - ) - self.scatter_type = self.cfg.scatter.scatter_type - self.scatter_dim = self.cfg.scatter.scatter_dim - - self.project = conv2d_block( - self.cfg.spatial.input_dim, self.cfg.spatial.project_dim, 1, 1, 0, activation=self.act - ) - down_layers = [] - dims = [self.cfg.spatial.project_dim] + self.cfg.spatial.down_channels - for i in range(len(self.cfg.spatial.down_channels)): - down_layers.append(nn.MaxPool2d(2, 2)) - down_layers.append(conv2d_block(dims[i], dims[i + 1], 3, 1, 1, activation=self.act)) - self.downsample = nn.Sequential(*down_layers) - dim = dims[-1] - self.resblock_num = self.cfg.spatial.resblock_num - self.res = nn.ModuleList() - for i in range(self.resblock_num): - self.res.append(ResBlock(dim, self.act, norm_type=None)) - self.spatial_fc = fc_block( - dim * self.whole_cfg.spatial_y // 8 * self.whole_cfg.spatial_x // 8, - self.cfg.spatial.spatial_fc_dim, - activation=self.act - ) - - def forward(self, x): - spatial_embedding = [] - fc_embedding = [] - for k, item in self.cfg.modules.items(): - if item['arc'] == 'fc': - embedding = self.encode_modules[k](x[k].float()) - fc_embedding.append(embedding) - if item['arc'] == 'one_hot': - embedding = self.encode_modules[k](x[k].long()) - spatial_embedding.append(embedding) - - bo_embedding = self.encode_modules['beginning_order'](x['beginning_order'].float(), x['bo_location'].long()) - fc_embedding = torch.cat(fc_embedding, dim=-1) - spatial_embedding = torch.cat(spatial_embedding, dim=-1) - project_embedding = self.scatter_project(spatial_embedding) - unit_mask = sequence_mask(x['total_unit_count'], max_len=project_embedding.shape[1]) - project_embedding = project_embedding * unit_mask.unsqueeze(dim=2) - entity_location = torch.cat([x['unit_x'].unsqueeze(dim=-1), x['unit_y'].unsqueeze(dim=-1)], dim=-1) - b, c, h, w = x['own_units_spatial'].shape - scatter_map = scatter_connection_v2( - (b, h, w), project_embedding, entity_location, self.scatter_dim, self.scatter_type - ) - spatial_x = torch.cat([scatter_map, x['own_units_spatial'].float(), x['enemy_units_spatial'].float()], dim=1) - spatial_x = self.project(spatial_x) - spatial_x = self.downsample(spatial_x) - for i in range(self.resblock_num): - spatial_x = self.res[i](spatial_x) - spatial_x = self.spatial_fc(spatial_x.view(spatial_x.shape[0], -1)) - x = torch.cat([fc_embedding, spatial_x, bo_embedding], dim=-1) - return x diff --git a/dizoo/distar/model/policy.py b/dizoo/distar/model/policy.py deleted file mode 100644 index 45b7d24604..0000000000 --- a/dizoo/distar/model/policy.py +++ /dev/null @@ -1,78 +0,0 @@ -from typing import List, Dict, Optional -from torch import Tensor -import torch -import torch.nn as nn - -from dizoo.distar.envs import SELECTED_UNITS_MASK -from .head import DelayHead, QueuedHead, SelectedUnitsHead, TargetUnitHead, LocationHead, ActionTypeHead - - -class Policy(nn.Module): - - def __init__(self, cfg): - super(Policy, self).__init__() - self.cfg = cfg.policy - self.action_type_head = ActionTypeHead(self.cfg.head.action_type_head) - self.delay_head = DelayHead(self.cfg.head.delay_head) - self.queued_head = QueuedHead(self.cfg.head.queued_head) - self.selected_units_head = SelectedUnitsHead(self.cfg.head.selected_units_head) - self.target_unit_head = TargetUnitHead(self.cfg.head.target_unit_head) - self.location_head = LocationHead(self.cfg.head.location_head) - - def forward( - self, lstm_output: Tensor, entity_embeddings: Tensor, map_skip: List[Tensor], scalar_context: Tensor, - entity_num: Tensor - ): - action = torch.jit.annotate(Dict[str, Tensor], {}) - logit = torch.jit.annotate(Dict[str, Tensor], {}) - - # action type - logit['action_type'], action['action_type'], embeddings = self.action_type_head(lstm_output, scalar_context) - - #action arg delay - logit['delay'], action['delay'], embeddings = self.delay_head(embeddings) - - logit['queued'], action['queued'], embeddings = self.queued_head(embeddings) - - # selected_units_head cannot be compiled to onnx due to indice - su_mask = SELECTED_UNITS_MASK[action['action_type']] - logit['selected_units'], action['selected_units' - ], embeddings, selected_units_num, extra_units = self.selected_units_head( - embeddings, entity_embeddings, entity_num, None, None, su_mask - ) - - logit['target_unit'], action['target_unit'] = self.target_unit_head(embeddings, entity_embeddings, entity_num) - - logit['target_location'], action['target_location'] = self.location_head(embeddings, map_skip) - - return action, selected_units_num, logit, extra_units - - def train_forward( - self, lstm_output, entity_embeddings, map_skip: List[Tensor], scalar_context, entity_num, action_info, - selected_units_num - ): - action = torch.jit.annotate(Dict[str, Tensor], {}) - logit = torch.jit.annotate(Dict[str, Tensor], {}) - - # action type - logit['action_type'], action['action_type'], embeddings = self.action_type_head( - lstm_output, scalar_context, action_info['action_type'] - ) - - # action arg delay - logit['delay'], action['delay'], embeddings = self.delay_head(embeddings, action_info['delay']) - - logit['queued'], action['queued'], embeddings = self.queued_head(embeddings, action_info['queued']) - - logit['selected_units'], action['selected_units'], embeddings, selected_units_num, _ = self.selected_units_head( - embeddings, entity_embeddings, entity_num, selected_units_num, action_info['selected_units'] - ) - - logit['target_unit'], action['target_unit'] = self.target_unit_head( - embeddings, entity_embeddings, entity_num, action_info['target_unit'] - ) - - logit['target_location'], action['target_location'] = self.location_head( - embeddings, map_skip, action_info['target_location'] - ) - return action, selected_units_num, logit diff --git a/dizoo/distar/model/tests/test_encoder.py b/dizoo/distar/model/tests/test_encoder.py deleted file mode 100644 index 1e64a0701b..0000000000 --- a/dizoo/distar/model/tests/test_encoder.py +++ /dev/null @@ -1,31 +0,0 @@ -from easydict import EasyDict -import pytest -import torch -from ding.utils import read_yaml_config -from ding.utils.data import default_collate -from dizoo.distar.model.encoder import Encoder -from dizoo.distar.envs.fake_data import scalar_info, entity_info, spatial_info - - -@pytest.mark.envtest -def test_encoder(): - B, M = 4, 512 - cfg = read_yaml_config('../actor_critic_default_config.yaml') - cfg = EasyDict(cfg) - encoder = Encoder(cfg) - print(encoder) - - spatial_info_data = default_collate([spatial_info() for _ in range(B)]) - entity_info_data = default_collate([entity_info() for _ in range(B)]) - scalar_info_data = default_collate([scalar_info() for _ in range(B)]) - entity_num = torch.randint(M // 2, M, size=(B, )) - entity_num[-1] = M - - lstm_input, scalar_context, baseline_feature, entity_embeddings, map_skip = encoder( - spatial_info_data, entity_info_data, scalar_info_data, entity_num - ) - assert lstm_input.shape == (B, 1536) - assert scalar_context.shape == (B, 448) - assert baseline_feature.shape == (B, 512) - assert entity_embeddings.shape == (B, 512, 256) - assert isinstance(map_skip, list) and len(map_skip) == 7 diff --git a/dizoo/distar/model/tests/test_head.py b/dizoo/distar/model/tests/test_head.py deleted file mode 100644 index 4408f39df5..0000000000 --- a/dizoo/distar/model/tests/test_head.py +++ /dev/null @@ -1,119 +0,0 @@ -import pytest -import torch -from easydict import EasyDict -from ding.utils import read_yaml_config -from dizoo.distar.model.head import ActionTypeHead, DelayHead, SelectedUnitsHead, TargetUnitHead, LocationHead, \ - QueuedHead -B, ENTITY = 4, 128 -total_config = EasyDict(read_yaml_config('../actor_critic_default_config.yaml')) - - -@pytest.mark.envtest -class TestHead(): - - def test_action_type_head(self): - cfg = total_config.model.policy.head.action_type_head - head = ActionTypeHead(cfg) - lstm_output = torch.randn(B, cfg.input_dim) - scalar_context = torch.randn(B, cfg.context_dim) - - logit, action_type, embedding = head(lstm_output, scalar_context) - assert logit.shape == (B, 327) - assert action_type.shape == (B, ) - assert embedding.shape == (B, cfg.gate_dim) - - logit, output_action_type, embedding = head(lstm_output, scalar_context, action_type) - assert logit.shape == (B, 327) - assert embedding.shape == (B, cfg.gate_dim) - assert output_action_type.eq(action_type).all() - - def test_delay_head(self): - cfg = total_config.model.policy.head.delay_head - head = DelayHead(cfg) - inputs = torch.randn(B, cfg.input_dim) - - logit, delay, embedding = head(inputs) - assert logit.shape == (B, cfg.delay_dim) - assert delay.shape == (B, ) - assert embedding.shape == (B, cfg.input_dim) - - logit, output_delay, embedding = head(inputs, delay) - assert logit.shape == (B, cfg.delay_dim) - assert embedding.shape == (B, cfg.input_dim) - assert output_delay.eq(delay).all() - - def test_queued_head(self): - cfg = total_config.model.policy.head.queued_head - head = QueuedHead(cfg) - inputs = torch.randn(B, cfg.input_dim) - - logit, queued, embedding = head(inputs) - assert logit.shape == (B, cfg.queued_dim) - assert queued.shape == (B, ) - assert embedding.shape == (B, cfg.input_dim) - - logit, output_queued, embedding = head(inputs, queued) - assert logit.shape == (B, cfg.queued_dim) - assert embedding.shape == (B, cfg.input_dim) - assert output_queued.eq(queued).all() - - def test_target_unit_head(self): - cfg = total_config.model.policy.head.target_unit_head - head = TargetUnitHead(cfg) - inputs = torch.randn(B, cfg.input_dim) - entity_embedding = torch.rand(B, ENTITY, cfg.entity_embedding_dim) - entity_num = torch.randint(ENTITY // 2, ENTITY, size=(B, )) - entity_num[-1] = ENTITY - - logit, target_unit = head(inputs, entity_embedding, entity_num) - assert logit.shape == (B, ENTITY) - assert target_unit.shape == (B, ) - - logit, output_target_unit = head(inputs, entity_embedding, entity_num, target_unit) - assert logit.shape == (B, ENTITY) - assert output_target_unit.eq(target_unit).all() - - def test_location_head(self): - cfg = total_config.model.policy.head.location_head - head = LocationHead(cfg) - inputs = torch.randn(B, cfg.input_dim) - Y, X = cfg.spatial_y, cfg.spatial_x - map_skip = [torch.randn(B, cfg.res_dim, Y // 8, X // 8) for _ in range(cfg.res_num)] - - logit, location = head(inputs, map_skip) - assert logit.shape == (B, Y * X) - assert location.shape == (B, ) - - logit, output_location = head(inputs, map_skip, location) - assert logit.shape == (B, Y * X) - assert output_location.eq(location).all() - - def test_selected_units_head(self): - cfg = total_config.model.policy.head.selected_units_head - head = SelectedUnitsHead(cfg) - inputs = torch.randn(B, cfg.input_dim) - entity_embedding = torch.rand(B, ENTITY, cfg.entity_embedding_dim) - entity_num = torch.randint(ENTITY // 2, ENTITY, size=(B, )) - entity_num[-1] = ENTITY - su_mask = torch.randint(0, 2, size=(B, )).bool() - su_mask[-1] = 1 - - logit, selected_units, embedding, selected_units_num, extra_units = head( - inputs, entity_embedding, entity_num, su_mask=su_mask - ) - N = selected_units_num.max() - assert embedding.shape == (B, cfg.input_dim) - assert logit.shape == (B, N, ENTITY + 1) - assert selected_units.shape == (B, N) - assert selected_units_num.shape == (B, ) - assert extra_units.shape == (B, ENTITY + 1) - - selected_units_num = selected_units_num.clamp(0, 64) - logit, output_selected_units, embedding, selected_units_num, extra_units = head( - inputs, entity_embedding, entity_num, selected_units_num, selected_units, su_mask - ) - N = selected_units_num.max() - assert embedding.shape == (B, cfg.input_dim) - assert logit.shape == (B, N, ENTITY + 1) - assert extra_units is None - assert output_selected_units.eq(selected_units).all() diff --git a/dizoo/distar/model/tests/test_value.py b/dizoo/distar/model/tests/test_value.py deleted file mode 100644 index fcaa0bbaf7..0000000000 --- a/dizoo/distar/model/tests/test_value.py +++ /dev/null @@ -1,23 +0,0 @@ -import pytest -import torch -from dizoo.distar.model.value import ValueBaseline - - -@pytest.mark.envtest -def test_value_baseline(): - - class CFG: - - def __init__(self): - self.activation = 'relu' - self.norm_type = 'LN' - self.input_dim = 1024 - self.res_dim = 256 - self.res_num = 16 - self.use_value_feature = False - self.atan = True - - model = ValueBaseline(CFG()) - inputs = torch.randn(4, 1024) - output = model(inputs) - assert (output.shape == (4, )) diff --git a/dizoo/distar/model/value.py b/dizoo/distar/model/value.py deleted file mode 100644 index b3e76e5f9d..0000000000 --- a/dizoo/distar/model/value.py +++ /dev/null @@ -1,38 +0,0 @@ -import torch -import torch.nn as nn -import torch.nn.functional as F -import numpy as np -from ding.torch_utils import fc_block, build_activation, ResFCBlock - - -class ValueBaseline(nn.Module): - ''' - Network to be applied on each baseline input, parameters for the current baseline are defined in the cfg - - input_dim res_dim res_dim 1 - x -> fc (norm & act) -> ResFCBlock*res_num -> fc (no norm no act) -> atan act -> value - ''' - - def __init__(self, cfg): - super(ValueBaseline, self).__init__() - self.act = build_activation(cfg.activation, inplace=True) - if cfg.use_value_feature: - input_dim = cfg.input_dim + 1056 - else: - input_dim = cfg.input_dim - self.project = fc_block(input_dim, cfg.res_dim, activation=self.act, norm_type=None) - blocks = [ResFCBlock(cfg.res_dim, self.act, cfg.norm_type) for _ in range(cfg.res_num)] - self.res = nn.Sequential(*blocks) - self.value_fc = fc_block(cfg.res_dim, 1, activation=None, norm_type=None, init_gain=0.1) - self.atan = cfg.atan - self.PI = np.pi - - def forward(self, x): - x = self.project(x) - x = self.res(x) - x = self.value_fc(x) - - x = x.squeeze(1) - if self.atan: - x = (2.0 / self.PI) * torch.atan((self.PI / 2.0) * x) - return x diff --git a/dizoo/distar/policy/__init__.py b/dizoo/distar/policy/__init__.py deleted file mode 100644 index 061c38a426..0000000000 --- a/dizoo/distar/policy/__init__.py +++ /dev/null @@ -1 +0,0 @@ -from .distar_policy import DIStarPolicy diff --git a/dizoo/distar/policy/distar_policy.py b/dizoo/distar/policy/distar_policy.py deleted file mode 100644 index 57809ff5cc..0000000000 --- a/dizoo/distar/policy/distar_policy.py +++ /dev/null @@ -1,900 +0,0 @@ -from logging.config import DEFAULT_LOGGING_CONFIG_PORT -from typing import Dict, Optional, List -from easydict import EasyDict -import os.path as osp -import torch -from torch.optim import Adam -import random -from functools import partial -from copy import deepcopy -import os.path as osp -from typing import Any -from ditk import logging -import pickle -import os -import time - -from ding.framework import task -from ding.model import model_wrap -from ding.policy import Policy -from ding.torch_utils import to_device, levenshtein_distance, l2_distance, hamming_distance -from ding.rl_utils import td_lambda_data, td_lambda_error, vtrace_data_with_rho, vtrace_error_with_rho, \ - upgo_data, upgo_error -from ding.utils import EasyTimer -from ding.utils.data import default_collate, default_decollate -from ding.envs.env.base_env import BaseEnvTimestep -from dizoo.distar.model import Model -from dizoo.distar.envs import NUM_UNIT_TYPES, ACTIONS, NUM_CUMULATIVE_STAT_ACTIONS, DEFAULT_SPATIAL_SIZE, BEGINNING_ORDER_LENGTH, BEGINNING_ORDER_ACTIONS, UNIT_TO_CUM, UPGRADE_TO_CUM, UNIT_ABILITY_TO_ACTION, QUEUE_ACTIONS, CUMULATIVE_STAT_ACTIONS,\ - Stat, parse_new_game, transform_obs, compute_battle_score -from .utils import collate_fn_learn, kl_error, entropy_error - - -class DIStarPolicy(Policy): - config = dict( - type='distar', - on_policy=False, - cuda=True, - learning_rate=1e-5, - model=dict(), - # learn - learn=dict(multi_gpu=False, ), - loss_weights=dict( - baseline=dict( - winloss=10.0, - build_order=0.0, - built_unit=0.0, - effect=0.0, - upgrade=0.0, - battle=0.0, - ), - vtrace=dict( - winloss=1.0, - build_order=0.0, - built_unit=0.0, - effect=0.0, - upgrade=0.0, - battle=0.0, - ), - upgo=dict(winloss=1.0, ), - kl=0.02, - action_type_kl=0.1, - entropy=0.0001, - ), - vtrace_head_weights=dict( - action_type=1.0, - delay=1.0, - queued=1.0, - select_unit_num_logits=1.0, - selected_units=0.01, - target_unit=1.0, - target_location=1.0, - ), - upgo_head_weights=dict( - action_type=1.0, - delay=1.0, - queued=1.0, - select_unit_num_logits=1.0, - selected_units=0.01, - target_unit=1.0, - target_location=1.0, - ), - entropy_head_weights=dict( - action_type=1.0, - delay=1.0, - queued=1.0, - select_unit_num_logits=1.0, - selected_units=0.01, - target_unit=1.0, - target_location=1.0, - ), - kl_head_weights=dict( - action_type=1.0, - delay=1.0, - queued=1.0, - select_unit_num_logits=1.0, - selected_units=0.01, - target_unit=1.0, - target_location=1.0, - ), - kl=dict(action_type_kl_steps=2400, ), - gammas=dict( - baseline=dict( - winloss=1.0, - build_order=1.0, - built_unit=1.0, - effect=1.0, - upgrade=1.0, - battle=0.997, - ), - pg=dict( - winloss=1.0, - build_order=1.0, - built_unit=1.0, - effect=1.0, - upgrade=1.0, - battle=0.997, - ), - ), - grad_clip=dict(threshold=1.0, ), - # collect - use_value_feature=True, # TODO(zms): whether to use value feature, this must be False when play against bot - zero_z_exceed_loop=True, # set Z to 0 if game passes the game loop in Z - fake_reward_prob=0.0, # probablity which set Z to 0 - zero_z_value=1, # value used for 0Z - extra_units=True, # selcet extra units if selected units exceed 64 - clip_bo=False, # clip the length of teacher's building order to agent's length - z_path='7map_filter_spine.json', - realtime=False, #TODO(zms): set from env, need to use only one cfg define policy and env - model_path='sl_model.pth', - teacher_model_path='sl_model.pth', - value_pretrain_iters=4000, - ) - - def _create_model( - self, - cfg: EasyDict, - model: Optional[torch.nn.Module] = None, - enable_field: Optional[List[str]] = None - ) -> torch.nn.Module: - assert model is None, "not implemented user-defined model" - assert len(enable_field) == 1, "only support distributed enable policy" - field = enable_field[0] - if field == 'learn': - return Model(self._cfg.model, use_value_network=True) - elif field == 'collect': # disable value network - return Model(self._cfg.model) - else: - raise KeyError("invalid policy mode: {}".format(field)) - - def _init_learn(self): - self._learn_model = model_wrap(self._model, 'base') - # TODO(zms): maybe initialize state_dict inside learner - learn_model_path = osp.join(osp.dirname(__file__), self._cfg.model_path) - - learn_state_dict = torch.load(learn_model_path, map_location=self._device) - - self._load_state_dict_learn(learn_state_dict) - - self.head_types = ['action_type', 'delay', 'queued', 'target_unit', 'selected_units', 'target_location'] - # policy parameters - self.gammas = self._cfg.gammas - self.loss_weights = self._cfg.loss_weights - self.action_type_kl_steps = self._cfg.kl.action_type_kl_steps - self.vtrace_head_weights = self._cfg.vtrace_head_weights - self.upgo_head_weights = self._cfg.upgo_head_weights - self.entropy_head_weights = self._cfg.entropy_head_weights - self.kl_head_weights = self._cfg.kl_head_weights - self._only_update_value = False - self._remain_value_pretrain_iters = self._cfg.value_pretrain_iters - - # optimizer - self.optimizer = Adam( - self._learn_model.parameters(), - lr=self._cfg.learning_rate, - betas=(0, 0.99), - eps=1e-5, - ) - # utils - self.timer = EasyTimer(cuda=self._cuda) - - def _step_value_pretrain(self): - if self._remain_value_pretrain_iters > 0: - self._only_update_value = True - self._remain_value_pretrain_iters -= 1 - self._learn_model._model._model.only_update_baseline = True - - elif self._remain_value_pretrain_iters == 0: - self._only_update_value = False - self._remain_value_pretrain_iters -= 1 - self._learn_model._model._model.only_update_baseline = False - - def _forward_learn(self, inputs: Dict): - # =========== - # pre-process - # =========== - self._step_value_pretrain() - if self._cuda: - inputs = to_device(inputs, self._device) - inputs = collate_fn_learn(inputs) - - self._learn_model.train() - - # ============= - # model forward - # ============= - # create loss show dict - loss_info_dict = {} - with self.timer: - model_output = self._learn_model.rl_learn_forward(**inputs) - loss_info_dict['model_forward_time'] = self.timer.value - - # =========== - # preparation - # =========== - target_policy_logits_dict = model_output['target_logit'] # shape (T,B) - baseline_values_dict = model_output['value'] # shape (T+1,B) - behavior_action_log_probs_dict = model_output['action_log_prob'] # shape (T,B) - teacher_policy_logits_dict = model_output['teacher_logit'] # shape (T,B) - masks_dict = model_output['mask'] # shape (T,B) - actions_dict = model_output['action'] # shape (T,B) - rewards_dict = model_output['reward'] # shape (T,B) - game_steps = model_output['step'] # shape (T,B) target_action_log_prob - - flag = rewards_dict['winloss'][-1] == 0 - for filed in baseline_values_dict.keys(): - baseline_values_dict[filed][-1] *= flag - - # create preparation info dict - target_policy_probs_dict = {} - target_policy_log_probs_dict = {} - target_action_log_probs_dict = {} - clipped_rhos_dict = {} - - # ============================================================ - # get distribution info for behavior policy and target policy - # ============================================================ - for head_type in self.head_types: - # take info from correspondent input dict - target_policy_logits = target_policy_logits_dict[head_type] - actions = actions_dict[head_type] - # compute target log_probs, probs(for entropy,kl), target_action_log_probs, log_rhos(for pg_loss, upgo_loss) - pi_target = torch.distributions.Categorical(logits=target_policy_logits) - target_policy_probs = pi_target.probs - target_policy_log_probs = pi_target.logits - target_action_log_probs = pi_target.log_prob(actions) - behavior_action_log_probs = behavior_action_log_probs_dict[head_type] - - with torch.no_grad(): - log_rhos = target_action_log_probs - behavior_action_log_probs - if head_type == 'selected_units': - log_rhos *= masks_dict['selected_units_mask'] - log_rhos = log_rhos.sum(dim=-1) - rhos = torch.exp(log_rhos) - clipped_rhos = rhos.clamp_(max=1) - # save preparation results to correspondent dict - target_policy_probs_dict[head_type] = target_policy_probs - target_policy_log_probs_dict[head_type] = target_policy_log_probs - if head_type == 'selected_units': - target_action_log_probs.masked_fill_(~masks_dict['selected_units_mask'], 0) - target_action_log_probs = target_action_log_probs.sum(-1) - target_action_log_probs_dict[head_type] = target_action_log_probs - # log_rhos_dict[head_type] = log_rhos - clipped_rhos_dict[head_type] = clipped_rhos - - # ==================== - # vtrace loss - # ==================== - total_vtrace_loss = 0. - vtrace_loss_dict = {} - - for field, baseline in baseline_values_dict.items(): - baseline_value = baseline_values_dict[field] - reward = rewards_dict[field] - for head_type in self.head_types: - weight = self.vtrace_head_weights[head_type] - if head_type not in ['action_type', 'delay']: - weight = weight * masks_dict['actions_mask'][head_type] - # if field in ['build_order', 'built_unit', 'effect']: - # weight = weight * masks_dict[field + '_mask'] - - data_item = vtrace_data_with_rho( - target_action_log_probs_dict[head_type], clipped_rhos_dict[head_type], baseline_value, reward, - weight - ) - vtrace_loss_item = vtrace_error_with_rho(data_item, gamma=1.0, lambda_=1.0) - - vtrace_loss_dict['vtrace/' + field + '/' + head_type] = vtrace_loss_item.item() - total_vtrace_loss += self.loss_weights.vtrace[field] * self.vtrace_head_weights[head_type - ] * vtrace_loss_item - - loss_info_dict.update(vtrace_loss_dict) - - # =========== - # upgo loss - # =========== - upgo_loss_dict = {} - total_upgo_loss = 0. - for head_type in self.head_types: - weight = self.upgo_head_weights[head_type] - if head_type not in ['action_type', 'delay']: - weight = weight * masks_dict['actions_mask'][head_type] - - data_item = upgo_data( - target_action_log_probs_dict[head_type], clipped_rhos_dict[head_type], baseline_values_dict['winloss'], - rewards_dict['winloss'], weight - ) - upgo_loss_item = upgo_error(data_item) - - total_upgo_loss += upgo_loss_item - upgo_loss_dict['upgo/' + head_type] = upgo_loss_item.item() - total_upgo_loss *= self.loss_weights.upgo.winloss - loss_info_dict.update(upgo_loss_dict) - - # =========== - # critic loss - # =========== - total_critic_loss = 0. - # field is from ['winloss', 'build_order', 'built_unit', 'effect', 'upgrade', 'battle'] - for field, baseline in baseline_values_dict.items(): - reward = rewards_dict[field] - # Notice: in general, we need to include done when we consider discount factor, but in our implementation - # of alphastar, traj_data(with size equal to unroll-len) sent from actor comes from the same episode. - # If the game is draw, we don't consider it is actually done - # if field in ['build_order', 'built_unit', 'effect']: - # weight = masks_dict[[field + '_mask']] - # else: - # weight = None - weight = None - - field_data = td_lambda_data(baseline, reward, weight) - critic_loss = td_lambda_error(field_data, gamma=self.gammas.baseline[field]) - - total_critic_loss += self.loss_weights.baseline[field] * critic_loss - loss_info_dict['td/' + field] = critic_loss.item() - loss_info_dict['reward/' + field] = reward.float().mean().item() - loss_info_dict['value/' + field] = baseline.mean().item() - loss_info_dict['reward/battle'] = rewards_dict['battle'].float().mean().item() - - # ============ - # entropy loss - # ============ - total_entropy_loss, entropy_dict = \ - entropy_error(target_policy_probs_dict, target_policy_log_probs_dict, masks_dict, - head_weights_dict=self.entropy_head_weights) - - total_entropy_loss *= self.loss_weights.entropy - loss_info_dict.update(entropy_dict) - - # ======= - # kl loss - # ======= - total_kl_loss, action_type_kl_loss, kl_loss_dict = \ - kl_error(target_policy_log_probs_dict, teacher_policy_logits_dict, masks_dict, game_steps, - action_type_kl_steps=self.action_type_kl_steps, head_weights_dict=self.kl_head_weights) - total_kl_loss *= self.loss_weights.kl - action_type_kl_loss *= self.loss_weights.action_type_kl - loss_info_dict.update(kl_loss_dict) - - # ====== - # update - # ====== - - if self._only_update_value: - total_loss = total_critic_loss - else: - total_loss = ( - total_vtrace_loss + total_upgo_loss + total_critic_loss + total_entropy_loss + total_kl_loss + - action_type_kl_loss - ) - with self.timer: - self.optimizer.zero_grad() - total_loss.backward() - if self._cfg.learn.multi_gpu: - self.sync_gradients(self._learn_model) - gradient = torch.nn.utils.clip_grad_norm_(self._learn_model.parameters(), self._cfg.grad_clip.threshold, 2) - self.optimizer.step() - - loss_info_dict['backward_time'] = self.timer.value - loss_info_dict['total_loss'] = total_loss - loss_info_dict['gradient'] = gradient - return loss_info_dict - - def _monitor_var_learn(self): - ret = ['total_loss', 'kl/extra_at', 'gradient', 'backward_time', 'model_forward_time'] - for k1 in ['winloss', 'build_order', 'built_unit', 'effect', 'upgrade', 'battle', 'upgo', 'kl', 'entropy']: - for k2 in ['reward', 'value', 'td', 'action_type', 'delay', 'queued', 'selected_units', 'target_unit', - 'target_location']: - ret.append(k1 + '/' + k2) - return ret - - def _state_dict(self) -> Dict: - return { - 'model': self._learn_model.state_dict(), - 'optimizer': self.optimizer.state_dict(), - } - - def _load_state_dict_learn(self, _state_dict: Dict) -> None: - self._learn_model.load_state_dict(_state_dict['model'], strict=False) - if 'optimizer' in _state_dict: - self.optimizer.load_state_dict(_state_dict['optimizer']) - del _state_dict - - def _load_state_dict_collect(self, _state_dict: Dict) -> None: - #TODO(zms): need to load state_dict after collect, which is very dirty and need to rewrite - if not self._cuda: - _state_dict = to_device(_state_dict, self._device) - if 'map_name' in _state_dict: - # map_names.append(_state_dict['map_name']) - self.fake_reward_prob = _state_dict['fake_reward_prob'] - # agent._z_path = state_dict['z_path'] - self.z_idx = _state_dict['z_idx'] - _state_dict = {k: v for k, v in _state_dict['model'].items() if 'value_networks' not in k} - - self._collect_model.load_state_dict(_state_dict, strict=False) - del _state_dict - - def _init_collect(self): - self._collect_model = model_wrap(self._model, 'base') - # TODO(zms): maybe initialize state_dict inside actor - collect_model_path = osp.join(osp.dirname(__file__), self._cfg.model_path) - - collect_state_dict = torch.load(collect_model_path, self._device) - - self._load_state_dict_collect(collect_state_dict) - del collect_state_dict - - self.only_cum_action_kl = False - self.z_path = self._cfg.z_path - self.z_idx = None - self.bo_norm = 20 #TODO(nyz): set from cfg - self.cum_norm = 30 #TODO(nyz): set from cfg - self.battle_norm = 30 #TODO(nyz): set from cfg - self.fake_reward_prob = self._cfg.fake_reward_prob - self.clip_bo = self._cfg.clip_bo - self.cum_type = 'action' # observation or action - self.realtime = self._cfg.realtime - self.teacher_model = model_wrap(Model(self._cfg.model), 'base') - if self._cuda: - self.teacher_model = self.teacher_model.cuda() - teacher_model_path = osp.join(osp.dirname(__file__), self._cfg.teacher_model_path) - print("self._cuda is ", self._cuda) - - t_state_dict = torch.load(teacher_model_path, self._device) - - teacher_state_dict = {k: v for k, v in t_state_dict['model'].items() if 'value_networks' not in k} - self.teacher_model.load_state_dict(teacher_state_dict) - # TODO(zms): load teacher_model's state_dict when init policy. - del t_state_dict - - def _reset_collect(self, data: Dict): - self.exceed_loop_flag = False - self.map_name = data['map_name'] - hidden_size = 384 # TODO(nyz) set from cfg - num_layers = 3 - self.hidden_state = [(torch.zeros(hidden_size), torch.zeros(hidden_size)) for _ in range(num_layers)] - self.last_action_type = torch.tensor(0, dtype=torch.long) - self.last_delay = torch.tensor(0, dtype=torch.long) - self.last_queued = torch.tensor(0, dtype=torch.long) - self.last_selected_unit_tags = None - self.last_targeted_unit_tag = None - self.last_location = None # [x, y] - self.enemy_unit_type_bool = torch.zeros(NUM_UNIT_TYPES, dtype=torch.uint8) - # TODO(zms): need to move obs and policy_output inside rolloutor, but for each step, - # it is possible that only one policy in the two has observation and output, so for now just leave it here. - self.obs = None - self.policy_output = None - self.model_last_iter = 0 - self.game_step = 0 # step * 10 is game duration time - self.behavior_building_order = [] # idx in BEGINNING_ORDER_ACTIONS - self.behavior_bo_location = [] - self.bo_zergling_count = 0 - self.behavior_cumulative_stat = [0] * NUM_CUMULATIVE_STAT_ACTIONS - - self.hidden_state_backup = [(torch.zeros(hidden_size), torch.zeros(hidden_size)) for _ in range(num_layers)] - self.teacher_hidden_state = [(torch.zeros(hidden_size), torch.zeros(hidden_size)) for _ in range(num_layers)] - - race, requested_race, map_size, target_building_order, target_cumulative_stat, bo_location, target_z_loop, z_type, _born_location = parse_new_game( - data, self.z_path, self.z_idx - ) - self.born_location = _born_location - self.use_cum_reward = True - self.use_bo_reward = True - if z_type is not None: - if z_type == 2 or z_type == 3: - self.use_cum_reward = False - if z_type == 1 or z_type == 3: - self.use_bo_reward = False - if random.random() > self.fake_reward_prob: - self.use_cum_reward = False - if random.random() > self.fake_reward_prob: - self.use_bo_reward = False - - self.bo_norm = len(target_building_order) - self.cum_norm = len(target_cumulative_stat) - - self.race = race # home_race - self.requested_race = requested_race - self.map_size = map_size - self.target_z_loop = target_z_loop - self.stat = Stat(self.race) - - self.target_building_order = torch.tensor(target_building_order, dtype=torch.long) - self.target_bo_location = torch.tensor(bo_location, dtype=torch.long) - self.target_cumulative_stat = torch.zeros(NUM_CUMULATIVE_STAT_ACTIONS, dtype=torch.float) - self.target_cumulative_stat.scatter_( - index=torch.tensor(target_cumulative_stat, dtype=torch.long), dim=0, value=1. - ) - if not self.realtime: - if not self.clip_bo: - self.old_bo_reward = -levenshtein_distance( - torch.as_tensor(self.behavior_building_order, dtype=torch.long), self.target_building_order - )[0] / self.bo_norm - else: - self.old_bo_reward = torch.tensor(0.) - self.old_cum_reward = -hamming_distance( - torch.unsqueeze(torch.as_tensor(self.behavior_cumulative_stat, dtype=torch.long), dim=0), - torch.unsqueeze(torch.as_tensor(self.target_cumulative_stat, dtype=torch.long), dim=0) - )[0] / self.cum_norm - self.total_bo_reward = torch.zeros(size=(), dtype=torch.float) - self.total_cum_reward = torch.zeros(size=(), dtype=torch.float) - - def _forward_collect(self, data): - obs, game_info = self._data_preprocess_collect(data) - self.obs = obs - obs = default_collate([obs]) - if self._cuda: - obs = to_device(obs, self._device) - - self._collect_model.eval() - try: - with torch.no_grad(): - policy_output = self._collect_model.compute_logp_action(**obs) - except Exception as e: - logging.error("[Actor {}] got an exception: {} in the collect model".format(task.router.node_id, e)) - bug_time = str(int(time.time())) - file_name = 'bug_obs_' + bug_time + '.pkl' - with open(os.path.join(os.path.dirname(__file__), file_name), 'wb+') as f: - pickle.dump(self.obs, f) - model_path_name = 'bug_model_' + bug_time + '.pth' - model_path = os.path.join(os.path.dirname(__file__), model_path_name) - torch.save(self._collect_model.state_dict(), model_path) - raise e - - if self._cuda: - policy_output = to_device(policy_output, self._device) - policy_output = default_decollate(policy_output)[0] - self.policy_output = self._data_postprocess_collect(policy_output, game_info) - return self.policy_output - - def _data_preprocess_collect(self, data): - if self._cfg.use_value_feature: - obs = transform_obs( - data['raw_obs'], - self.map_size, - self.requested_race, - padding_spatial=True, - opponent_obs=data['opponent_obs'] - ) - else: - obs = transform_obs(data['raw_obs'], self.map_size, self.requested_race, padding_spatial=True) - - game_info = obs.pop('game_info') - self.battle_score = game_info['battle_score'] - self.opponent_battle_score = game_info['opponent_battle_score'] - self.game_step = game_info['game_loop'] - if self._cfg.zero_z_exceed_loop and self.game_step > self.target_z_loop: - self.exceed_loop_flag = True - - last_selected_units = torch.zeros(obs['entity_num'], dtype=torch.int8) - last_targeted_unit = torch.zeros(obs['entity_num'], dtype=torch.int8) - tags = game_info['tags'] - if self.last_selected_unit_tags is not None: - for t in self.last_selected_unit_tags: - if t in tags: - last_selected_units[tags.index(t)] = 1 - if self.last_targeted_unit_tag is None: - if self.last_targeted_unit_tag in tags: - last_targeted_unit[tags.index(self.last_targeted_unit_tag)] = 1 - obs['entity_info']['last_selected_units'] = last_selected_units - obs['entity_info']['last_targeted_unit'] = last_targeted_unit - - obs['hidden_state'] = self.hidden_state - - obs['scalar_info']['last_action_type'] = self.last_action_type - obs['scalar_info']['last_delay'] = self.last_delay - obs['scalar_info']['last_queued'] = self.last_queued - obs['scalar_info']['enemy_unit_type_bool'] = ( - self.enemy_unit_type_bool | obs['scalar_info']['enemy_unit_type_bool'] - ).to(torch.uint8) - - obs['scalar_info']['beginning_order' - ] = self.target_building_order * (self.use_bo_reward & (not self.exceed_loop_flag)) - obs['scalar_info']['bo_location'] = self.target_bo_location * (self.use_bo_reward & (not self.exceed_loop_flag)) - - if self.use_cum_reward and not self.exceed_loop_flag: - obs['scalar_info']['cumulative_stat'] = self.target_cumulative_stat - else: - obs['scalar_info']['cumulative_stat'] = self.target_cumulative_stat * 0 + self._cfg.zero_z_value - - # update stat - self.stat.update(self.last_action_type, data['action_result'][0], obs, self.game_step) - return obs, game_info - - def _data_postprocess_collect(self, data, game_info): - self.hidden_state = data['hidden_state'] - assert data['action_info']['queued'].shape == torch.Size([1]), data['action_info']['queued'] - self.last_queued = data['action_info']['queued'][0] - assert data['action_info']['action_type'].shape == torch.Size([1]), data['action_info']['action_type'] - self.last_action_type = data['action_info']['action_type'][0] - assert data['action_info']['action_type'].shape == torch.Size([1]), data['action_info']['delay'] - self.last_delay = data['action_info']['delay'][0] - self.last_location = data['action_info']['target_location'] - - action_type = self.last_action_type.item() - action_attr = ACTIONS[action_type] - - # transform into env format action - tags = game_info['tags'] - raw_action = {} - raw_action['func_id'] = action_attr['func_id'] - raw_action['skip_steps'] = self.last_delay.item() - raw_action['queued'] = self.last_queued.item() - - unit_tags = [] - for i in range(data['selected_units_num'] - 1): # remove end flag - unit_tags.append(tags[data['action_info']['selected_units'][i].item()]) - if self._cfg.extra_units: - extra_units = torch.nonzero(data['extra_units']).squeeze(dim=1).tolist() - for unit_index in extra_units: - unit_tags.append(tags[unit_index]) - raw_action['unit_tags'] = unit_tags - if action_attr['selected_units']: - self.last_selected_unit_tags = unit_tags - else: - self.last_selected_unit_tags = None - - raw_action['target_unit_tag'] = tags[data['action_info']['target_unit'].item()] - if action_attr['target_unit']: - self.last_targeted_unit_tag = raw_action['target_unit_tag'] - else: - self.last_targeted_unit_tag = None - - x = data['action_info']['target_location'].item() % DEFAULT_SPATIAL_SIZE[1] - y = data['action_info']['target_location'].item() // DEFAULT_SPATIAL_SIZE[1] - inverse_y = max(self.map_size.y - y, 0) - raw_action['location'] = (x, inverse_y) - - data['action'] = [raw_action] - - return data - - def _process_transition(self, obs: Any, model_output: dict, timestep: BaseEnvTimestep): - next_obs = timestep.obs - reward = timestep.reward - done = timestep.done - behavior_z = self.get_behavior_z() - bo_reward, cum_reward, battle_reward = self.update_fake_reward(next_obs) - agent_obs = self.obs - teacher_obs = { - 'spatial_info': agent_obs['spatial_info'], - 'entity_info': agent_obs['entity_info'], - 'scalar_info': agent_obs['scalar_info'], - 'entity_num': agent_obs['entity_num'], - 'hidden_state': self.teacher_hidden_state, - 'selected_units_num': self.policy_output['selected_units_num'], - 'action_info': self.policy_output['action_info'] - } - - teacher_model_input = default_collate([teacher_obs]) - if teacher_model_input['action_info'].get('selected_units') is not None and teacher_model_input['action_info'][ - 'selected_units'].shape == torch.Size([1]): - teacher_model_input['action_info']['selected_units'] = torch.unsqueeze( - teacher_model_input['action_info']['selected_units'], dim=0 - ) - - if self._cuda: - teacher_model_input = to_device(teacher_model_input, self._device) - - self.teacher_model.eval() - with torch.no_grad(): - teacher_output = self.teacher_model.compute_teacher_logit(**teacher_model_input) - - if self._cuda: - teacher_output = to_device(teacher_output, self._device) - teacher_output = self.decollate_output(teacher_output) - self.teacher_hidden_state = teacher_output['hidden_state'] - - # gather step data - action_info = deepcopy(self.policy_output['action_info']) - mask = dict() - mask['actions_mask'] = deepcopy( - { - k: val - for k, val in ACTIONS[action_info['action_type'].item()].items() - if k not in ['name', 'goal', 'func_id', 'general_ability_id', 'game_id'] - } - ) - if self.only_cum_action_kl: - mask['cum_action_mask'] = torch.tensor(0.0, dtype=torch.float) - else: - mask['cum_action_mask'] = torch.tensor(1.0, dtype=torch.float) - if self.use_bo_reward: - mask['build_order_mask'] = torch.tensor(1.0, dtype=torch.float) - else: - mask['build_order_mask'] = torch.tensor(0.0, dtype=torch.float) - if self.use_cum_reward: - mask['built_unit_mask'] = torch.tensor(1.0, dtype=torch.float) - mask['cum_action_mask'] = torch.tensor(1.0, dtype=torch.float) - else: - mask['built_unit_mask'] = torch.tensor(0.0, dtype=torch.float) - selected_units_num = self.policy_output['selected_units_num'] - for k, v in mask['actions_mask'].items(): - mask['actions_mask'][k] = torch.tensor(v, dtype=torch.long) - step_data = { - 'map_name': self.map_name, - 'spatial_info': agent_obs['spatial_info'], - 'model_last_iter': torch.tensor(self.model_last_iter, dtype=torch.float), - # 'spatial_info_ref': spatial_info_ref, - 'entity_info': agent_obs['entity_info'], - 'scalar_info': agent_obs['scalar_info'], - 'entity_num': agent_obs['entity_num'], - 'selected_units_num': selected_units_num, - 'hidden_state': self.hidden_state_backup, - 'action_info': action_info, - 'behaviour_logp': self.policy_output['action_logp'], - 'teacher_logit': teacher_output['logit'], - # 'successive_logit': deepcopy(teacher_output['logit']), - 'reward': { - 'winloss': torch.tensor(reward, dtype=torch.float), - 'build_order': bo_reward, - 'built_unit': cum_reward, - 'effect': torch.randint(-1, 1, size=(), dtype=torch.float), - 'upgrade': torch.randint(-1, 1, size=(), dtype=torch.float), - # 'upgrade': torch.randint(-1, 1, size=(), dtype=torch.float), - 'battle': battle_reward, - }, - 'step': torch.tensor(self.game_step, dtype=torch.float), - 'mask': mask, - 'done': done - } - ##TODO: add value feature - if self._cfg.use_value_feature: - step_data['value_feature'] = agent_obs['value_feature'] - step_data['value_feature'].update(behavior_z) - self.hidden_state_backup = self.hidden_state - return step_data - - def get_behavior_z(self): - bo = self.behavior_building_order + [0] * (BEGINNING_ORDER_LENGTH - len(self.behavior_building_order)) - bo_location = self.behavior_bo_location + [0] * (BEGINNING_ORDER_LENGTH - len(self.behavior_bo_location)) - return { - 'beginning_order': torch.as_tensor(bo, dtype=torch.long), - 'bo_location': torch.as_tensor(bo_location, dtype=torch.long), - 'cumulative_stat': torch.as_tensor(self.behavior_cumulative_stat, dtype=torch.bool).long() - } - - def update_fake_reward(self, next_obs): - bo_reward, cum_reward, battle_reward = self._update_fake_reward( - self.last_action_type, self.last_location, next_obs - ) - return bo_reward, cum_reward, battle_reward - - def _update_fake_reward(self, action_type, location, next_obs): - bo_reward = torch.zeros(size=(), dtype=torch.float) - cum_reward = torch.zeros(size=(), dtype=torch.float) - - battle_score = compute_battle_score(next_obs['raw_obs']) - opponent_battle_score = compute_battle_score(next_obs['opponent_obs']) - battle_reward = battle_score - self.battle_score - (opponent_battle_score - self.opponent_battle_score) - battle_reward = torch.tensor(battle_reward, dtype=torch.float) / self.battle_norm - - if self.exceed_loop_flag: - return bo_reward, cum_reward, battle_reward - - if action_type in BEGINNING_ORDER_ACTIONS and next_obs['action_result'][0] == 1: - if action_type == 322: - self.bo_zergling_count += 1 - if self.bo_zergling_count > 8: - return bo_reward, cum_reward, battle_reward - order_index = BEGINNING_ORDER_ACTIONS.index(action_type) - if order_index == 39 and 39 not in self.target_building_order: # ignore spinecrawler - return bo_reward, cum_reward, battle_reward - if len(self.behavior_building_order) < len(self.target_building_order): - # only consider bo_reward if behaviour size < target size - self.behavior_building_order.append(order_index) - if ACTIONS[action_type]['target_location']: - self.behavior_bo_location.append(location.item()) - else: - self.behavior_bo_location.append(0) - if self.use_bo_reward: - if self.clip_bo: - tz = self.target_building_order[:len(self.behavior_building_order)] - tz_lo = self.target_bo_location[:len(self.behavior_building_order)] - else: - tz = self.target_building_order - tz_lo = self.target_bo_location - new_bo_dist = -levenshtein_distance( - torch.as_tensor(self.behavior_building_order, dtype=torch.long), - torch.as_tensor(tz, dtype=torch.long), - torch.as_tensor(self.behavior_bo_location, dtype=torch.int), - torch.as_tensor(tz_lo, dtype=torch.int), - partial(l2_distance, spatial_x=DEFAULT_SPATIAL_SIZE[1]) - )[0] / self.bo_norm - bo_reward = new_bo_dist - self.old_bo_reward - self.old_bo_reward = new_bo_dist - - if self.cum_type == 'observation': - cum_flag = True - for u in next_obs['raw_obs'].observation.raw_data.units: - if u.alliance == 1 and u.unit_type in [59, 18, 86]: # ignore first base - if u.pos.x == self.born_location[0] and u.pos.y == self.born_location[1]: - continue - if u.alliance == 1 and u.build_progress == 1 and UNIT_TO_CUM[u.unit_type] != -1: - self.behavior_cumulative_stat[UNIT_TO_CUM[u.unit_type]] = 1 - for u in next_obs['raw_obs'].observation.raw_data.player.upgrade_ids: - if UPGRADE_TO_CUM[u] != -1: - self.behavior_cumulative_stat[UPGRADE_TO_CUM[u]] = 1 - from distar.pysc2.lib.upgrades import Upgrades - for up in Upgrades: - if up.value == u: - name = up.name - break - elif self.cum_type == 'action': - action_name = ACTIONS[action_type]['name'] - action_info = self.policy_output['action_info'] - cum_flag = False - if action_name == 'Cancel_quick' or action_name == 'Cancel_Last_quick': - unit_index = action_info['selected_units'][0].item() - order_len = self.obs['entity_info']['order_length'][unit_index] - if order_len == 0: - action_index = 0 - elif order_len == 1: - action_index = UNIT_ABILITY_TO_ACTION[self.obs['entity_info']['order_id_0'][unit_index].item()] - elif order_len > 1: - order_str = 'order_id_{}'.format(order_len - 1) - action_index = QUEUE_ACTIONS[self.obs['entity_info'][order_str][unit_index].item() - 1] - if action_index in CUMULATIVE_STAT_ACTIONS: - cum_flag = True - cum_index = CUMULATIVE_STAT_ACTIONS.index(action_index) - self.behavior_cumulative_stat[cum_index] = max(0, self.behavior_cumulative_stat[cum_index] - 1) - - if action_type in CUMULATIVE_STAT_ACTIONS: - cum_flag = True - cum_index = CUMULATIVE_STAT_ACTIONS.index(action_type) - self.behavior_cumulative_stat[cum_index] += 1 - else: - raise NotImplementedError - - if self.use_cum_reward and cum_flag and (self.cum_type == 'observation' or next_obs['action_result'][0] == 1): - new_cum_reward = -hamming_distance( - torch.unsqueeze(torch.as_tensor(self.behavior_cumulative_stat, dtype=torch.long), dim=0), - torch.unsqueeze(torch.as_tensor(self.target_cumulative_stat, dtype=torch.long), dim=0) - )[0] / self.cum_norm - cum_reward = (new_cum_reward - self.old_cum_reward) * self._get_time_factor(self.game_step) - self.old_cum_reward = new_cum_reward - self.total_bo_reward += bo_reward - self.total_cum_reward += cum_reward - return bo_reward, cum_reward, battle_reward - - def decollate_output(self, output, k=None, batch_idx=None): - if isinstance(output, torch.Tensor): - if batch_idx is None: - return output.squeeze(dim=0) - else: - return output[batch_idx].clone().cpu() - elif k == 'hidden_state': - if batch_idx is None: - return [(output[l][0].squeeze(dim=0), output[l][1].squeeze(dim=0)) for l in range(len(output))] - else: - return [ - (output[l][0][batch_idx].clone().cpu(), output[l][1][batch_idx].clone().cpu()) - for l in range(len(output)) - ] - elif isinstance(output, dict): - data = {k: self.decollate_output(v, k, batch_idx) for k, v in output.items()} - if batch_idx is not None and k is None: - entity_num = data['entity_num'] - selected_units_num = data['selected_units_num'] - data['logit']['selected_units'] = data['logit']['selected_units'][:selected_units_num, :entity_num + 1] - data['logit']['target_unit'] = data['logit']['target_unit'][:entity_num] - if 'action_info' in data.keys(): - data['action_info']['selected_units'] = data['action_info']['selected_units'][:selected_units_num] - data['action_logp']['selected_units'] = data['action_logp']['selected_units'][:selected_units_num] - return data - - def _get_train_sample(self): - pass - - @staticmethod - def _get_time_factor(game_step): - if game_step < 1 * 10000: - return 1.0 - elif game_step < 2 * 10000: - return 0.5 - elif game_step < 3 * 10000: - return 0.25 - else: - return 0 - - _init_eval = _init_collect - _forward_eval = _forward_collect diff --git a/dizoo/distar/policy/test_distar_policy.py b/dizoo/distar/policy/test_distar_policy.py deleted file mode 100644 index aee5e423c9..0000000000 --- a/dizoo/distar/policy/test_distar_policy.py +++ /dev/null @@ -1,37 +0,0 @@ -import pytest - -from dizoo.distar.policy import DIStarPolicy -from dizoo.distar.envs import get_fake_rl_batch, get_fake_env_reset_data, get_fake_env_step_data - -import torch -from ding.utils import set_pkg_seed - - -@pytest.mark.envtest -class TestDIStarPolicy: - - def test_forward_learn(self): - policy = DIStarPolicy(DIStarPolicy.default_config(), enable_field=['learn']) - policy = policy.learn_mode - data = get_fake_rl_batch(batch_size=3) - output = policy.forward(data) - print(output) - - def test_forward_collect(self): - policy = DIStarPolicy(DIStarPolicy.default_config(), enable_field=['collect']) - policy = policy.collect_mode - - rl_model = torch.load('./rl_model.pth') - policy.load_state_dict(rl_model) - - data = get_fake_env_reset_data() - policy.reset(data) - output = policy.forward(data) - print(output) - - -if __name__ == '__main__': - set_pkg_seed(0, use_cuda=False) - torch.set_printoptions(profile="full") - test = TestDIStarPolicy() - test.test_forward_collect() \ No newline at end of file diff --git a/dizoo/distar/policy/utils.py b/dizoo/distar/policy/utils.py deleted file mode 100644 index 0b72f15304..0000000000 --- a/dizoo/distar/policy/utils.py +++ /dev/null @@ -1,146 +0,0 @@ -import torch -import torch.nn.functional as F -from ding.torch_utils import flatten, sequence_mask -from ding.utils.data import default_collate -from dizoo.distar.envs import MAX_SELECTED_UNITS_NUM - -MASK_INF = -1e9 -EPS = 1e-9 - - -def padding_entity_info(traj_data, max_entity_num): - # traj_data.pop('map_name', None) - entity_padding_num = max_entity_num - len(traj_data['entity_info']['x']) - if 'entity_embeddings' in traj_data.keys(): - traj_data['entity_embeddings'] = torch.nn.functional.pad( - traj_data['entity_embeddings'], (0, 0, 0, entity_padding_num), 'constant', 0 - ) - - for k in traj_data['entity_info'].keys(): - traj_data['entity_info'][k] = torch.nn.functional.pad( - traj_data['entity_info'][k], (0, entity_padding_num), 'constant', 0 - ) - if 'action_info' in traj_data: - su_padding_num = MAX_SELECTED_UNITS_NUM - traj_data['teacher_logit']['selected_units'].shape[0] - - traj_data['mask']['selected_units_mask'] = sequence_mask( - traj_data['selected_units_num'].unsqueeze(dim=0), max_len=MAX_SELECTED_UNITS_NUM - ).squeeze(dim=0) - traj_data['action_info']['selected_units'] = torch.nn.functional.pad( - traj_data['action_info']['selected_units'], - (0, MAX_SELECTED_UNITS_NUM - traj_data['action_info']['selected_units'].shape[-1]), 'constant', 0 - ) - - traj_data['behaviour_logp']['selected_units'] = torch.nn.functional.pad( - traj_data['behaviour_logp']['selected_units'], ( - 0, - su_padding_num, - ), 'constant', MASK_INF - ) - - traj_data['teacher_logit']['selected_units'] = torch.nn.functional.pad( - traj_data['teacher_logit']['selected_units'], ( - 0, - entity_padding_num, - 0, - su_padding_num, - ), 'constant', MASK_INF - ) - traj_data['teacher_logit']['target_unit'] = torch.nn.functional.pad( - traj_data['teacher_logit']['target_unit'], (0, entity_padding_num), 'constant', MASK_INF - ) - - traj_data['mask']['selected_units_logits_mask'] = sequence_mask( - traj_data['entity_num'].unsqueeze(dim=0) + 1, max_len=max_entity_num + 1 - ).squeeze(dim=0) - traj_data['mask']['target_units_logits_mask'] = sequence_mask( - traj_data['entity_num'].unsqueeze(dim=0), max_len=max_entity_num - ).squeeze(dim=0) - - return traj_data - - -def collate_fn_learn(traj_batch): - # data list of list, with shape batch_size, unroll_len - # find max_entity_num in data_batch - max_entity_num = max( - [len(traj_data['entity_info']['x']) for traj_data_list in traj_batch for traj_data in traj_data_list] - ) - - # padding entity_info in observation, target_unit, selected_units, mask - traj_batch = [ - [padding_entity_info(traj_data, max_entity_num) for traj_data in traj_data_list] - for traj_data_list in traj_batch - ] - - data = [default_collate(traj_data_list, allow_key_mismatch=True) for traj_data_list in traj_batch] - - batch_size = len(data) - unroll_len = len(data[0]['step']) - data = default_collate(data, dim=1) - - new_data = {} - for k, val in data.items(): - if k in ['spatial_info', 'entity_info', 'scalar_info', 'entity_num', 'entity_location', 'hidden_state', - 'value_feature']: - new_data[k] = flatten(val) - else: - new_data[k] = val - new_data['aux_type'] = batch_size - new_data['batch_size'] = batch_size - new_data['unroll_len'] = unroll_len - return new_data - - -def entropy_error(target_policy_probs_dict, target_policy_log_probs_dict, mask, head_weights_dict): - total_entropy_loss = 0. - entropy_dict = {} - for head_type in ['action_type', 'queued', 'delay', 'selected_units', 'target_unit', 'target_location']: - ent = -target_policy_probs_dict[head_type] * target_policy_log_probs_dict[head_type] - if head_type == 'selected_units': - ent = ent.sum(dim=-1) / ( - EPS + torch.log(mask['selected_units_logits_mask'].float().sum(dim=-1) + 1).unsqueeze(-1) - ) # normalize - ent = (ent * mask['selected_units_mask']).sum(-1) - ent = ent.div(mask['selected_units_mask'].sum(-1) + EPS) - elif head_type == 'target_unit': - # normalize by unit - ent = ent.sum(dim=-1) / (EPS + torch.log(mask['target_units_logits_mask'].float().sum(dim=-1) + 1)) - else: - ent = ent.sum(dim=-1) / torch.log(torch.FloatTensor([ent.shape[-1]]).to(ent.device)) - if head_type not in ['action_type', 'delay']: - ent = ent * mask['actions_mask'][head_type] - entropy = ent.mean() - entropy_dict['entropy/' + head_type] = entropy.item() - total_entropy_loss += (-entropy * head_weights_dict[head_type]) - return total_entropy_loss, entropy_dict - - -def kl_error( - target_policy_log_probs_dict, teacher_policy_logits_dict, mask, game_steps, action_type_kl_steps, head_weights_dict -): - total_kl_loss = 0. - kl_loss_dict = {} - - for head_type in ['action_type', 'queued', 'delay', 'selected_units', 'target_unit', 'target_location']: - target_policy_log_probs = target_policy_log_probs_dict[head_type] - teacher_policy_logits = teacher_policy_logits_dict[head_type] - - teacher_policy_log_probs = F.log_softmax(teacher_policy_logits, dim=-1) - teacher_policy_probs = torch.exp(teacher_policy_log_probs) - kl = teacher_policy_probs * (teacher_policy_log_probs - target_policy_log_probs) - - kl = kl.sum(dim=-1) - if head_type == 'selected_units': - kl = (kl * mask['selected_units_mask']).sum(-1) - if head_type not in ['action_type', 'delay']: - kl = kl * mask['actions_mask'][head_type] - if head_type == 'action_type': - flag = game_steps < action_type_kl_steps - action_type_kl = kl * flag * mask['cum_action_mask'] - action_type_kl_loss = action_type_kl.mean() - kl_loss_dict['kl/extra_at'] = action_type_kl_loss.item() - kl_loss = kl.mean() - total_kl_loss += (kl_loss * head_weights_dict[head_type]) - kl_loss_dict['kl/' + head_type] = kl_loss.item() - return total_kl_loss, action_type_kl_loss, kl_loss_dict diff --git a/dizoo/distar/state_dict_utils.py b/dizoo/distar/state_dict_utils.py deleted file mode 100644 index 9c94b39f5a..0000000000 --- a/dizoo/distar/state_dict_utils.py +++ /dev/null @@ -1,19 +0,0 @@ -import torch - - -def adjust_ia_state_dict(model_path): - state_dict = torch.load(model_path) - for key in list(state_dict['model'].keys()): - new = key - if "transformer" in key: - new = key.replace('layers', 'main').replace('mlp.1', 'mlp.2') - elif "location_head" in key: - new = key.replace('GateWeightG', 'gate').replace('UpdateSP', 'update_sp') - state_dict['model'][new] = state_dict['model'].pop(key) - - torch.save(state_dict, model_path) - - -if __name__ == '__main__': - model_path = './tests/rl_model.pth' - adjust_ia_state_dict(model_path) diff --git a/dizoo/distar/tests/test_league_actor_with_pretrained_model.py b/dizoo/distar/tests/test_league_actor_with_pretrained_model.py deleted file mode 100644 index cd1775bb08..0000000000 --- a/dizoo/distar/tests/test_league_actor_with_pretrained_model.py +++ /dev/null @@ -1,180 +0,0 @@ -from time import sleep -import pytest -from copy import deepcopy -from unittest.mock import patch -from easydict import EasyDict - -from dizoo.distar.config import distar_cfg -from dizoo.distar.envs.distar_env import DIStarEnv -from dizoo.distar.policy.distar_policy import DIStarPolicy - -from ding.envs import EnvSupervisor -from ding.league.player import PlayerMeta -from ding.league.v2.base_league import Job -from ding.framework import EventEnum -from ding.framework.storage import FileStorage -from ding.framework.task import task -from ding.framework.context import BattleContext - -from ding.framework.supervisor import ChildType -from ding.framework.middleware import StepLeagueActor -from ding.framework.middleware.functional import ActorData -from ding.framework.middleware.league_learner import LearnerModel -from ding.framework.middleware.functional.collector import battle_inferencer_for_distar, battle_rolloutor_for_distar - - -def battle_rolloutor_for_distar2(cfg, env, transitions_list, model_info_dict): - - def _battle_rolloutor(ctx: "BattleContext"): - timesteps = env.step(ctx.actions) - - ctx.total_envstep_count += len(timesteps) - ctx.env_step += len(timesteps) - - for env_id, timestep in enumerate(timesteps): - if timestep.info.get('abnormal'): - for policy_id, policy in enumerate(ctx.current_policies): - policy.reset(env.ready_obs[0][policy_id]) - continue - - for policy_id, policy in enumerate(ctx.current_policies): - if timestep.done: - policy.reset(env.ready_obs[0][policy_id]) - ctx.episode_info[policy_id].append(timestep.info[policy_id]) - - if timestep.done: - ctx.env_episode += 1 - - return _battle_rolloutor - - -env_cfg = dict( - actor=dict(job_type='train', ), - env=dict( - map_name='random', - player_ids=['agent1', 'bot7'], - races=['zerg', 'zerg'], - map_size_resolutions=[True, True], # if True, ignore minimap_resolutions - minimap_resolutions=[[160, 152], [160, 152]], - realtime=False, - replay_dir='.', - random_seed='none', - game_steps_per_episode=100000, - update_bot_obs=False, - save_replay_episodes=1, - update_both_obs=False, - version='4.10.0', - ), -) -env_cfg = EasyDict(env_cfg) -cfg = deepcopy(distar_cfg) - - -class PrepareTest(): - - @classmethod - def get_env_fn(cls): - return DIStarEnv(env_cfg) - - @classmethod - def get_env_supervisor(cls): - for _ in range(10): - try: - env = EnvSupervisor( - type_=ChildType.THREAD, - env_fn=[cls.get_env_fn for _ in range(cfg.env.collector_env_num)], - **cfg.env.manager - ) - env.seed(cfg.seed) - return env - except Exception as e: - print(e) - continue - - @classmethod - def learn_policy_fn(cls): - policy = DIStarPolicy(DIStarPolicy.default_config(), enable_field=['learn']) - return policy - - @classmethod - def collect_policy_fn(cls): - # policy = DIStarMockPolicyCollect() - policy = DIStarPolicy(DIStarPolicy.default_config(), enable_field=['collect']) - return policy - - -total_games = 0 -win_games = 0 -draw_games = 0 -loss_games = 0 - - -@pytest.mark.unittest -def test_league_actor(): - with task.start(async_mode=True, ctx=BattleContext()): - - def test_actor(): - job = Job( - launch_player='main_player_default_0', - players=[ - PlayerMeta( - player_id='main_player_default_0', checkpoint=FileStorage(path=None), total_agent_step=0 - ) - ] - ) - - def on_actor_job(job_: Job): - assert job_.launch_player == job.launch_player - print(job) - global total_games - global win_games - global draw_games - global loss_games - - for r in job_.result: - total_games += 1 - if r == 'wins': - win_games += 1 - elif r == 'draws': - draw_games += 1 - elif r == 'losses': - loss_games += 1 - else: - raise NotImplementedError - - print( - 'total games {}, win games {}, draw_games {}, loss_games {}'.format( - total_games, win_games, draw_games, loss_games - ) - ) - if total_games >= 100: - task.finish = True - exit(0) - - def on_actor_data(actor_data): - print('got actor_data') - assert isinstance(actor_data, ActorData) - - task.on(EventEnum.ACTOR_FINISH_JOB, on_actor_job) - task.on(EventEnum.ACTOR_SEND_DATA.format(player=job.launch_player), on_actor_data) - - def _test_actor(ctx): - sleep(0.3) - for _ in range(20): - task.emit(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), job) - sleep(0.3) - - return _test_actor - - with patch("ding.framework.middleware.collector.battle_inferencer", battle_inferencer_for_distar): - with patch("ding.framework.middleware.collector.battle_rolloutor", battle_rolloutor_for_distar): - league_actor = StepLeagueActor( - cfg=cfg, env_fn=PrepareTest.get_env_supervisor, policy_fn=PrepareTest.collect_policy_fn - ) - task.use(test_actor()) - task.use(league_actor) - task.run() - - -if __name__ == '__main__': - test_league_actor() \ No newline at end of file From 2dc4ab5785bc4359f7265885a25a33a82ef18680 Mon Sep 17 00:00:00 2001 From: zhumengshen Date: Wed, 24 Aug 2022 07:27:44 +0000 Subject: [PATCH 205/229] move out tensor_dict_to_shm --- ding/utils/tensor_dict_to_shm.py | 154 ------------------------------- 1 file changed, 154 deletions(-) delete mode 100644 ding/utils/tensor_dict_to_shm.py diff --git a/ding/utils/tensor_dict_to_shm.py b/ding/utils/tensor_dict_to_shm.py deleted file mode 100644 index e1b377ac36..0000000000 --- a/ding/utils/tensor_dict_to_shm.py +++ /dev/null @@ -1,154 +0,0 @@ -import torch -import torch.multiprocessing as mp -from array import array -import numpy as np - - -def shm_encode_with_schema(data, maxlen=1024 * 1024 * 64): - idx = 0 - encoding = np.zeros(shape=(maxlen, ), dtype=np.float32) - - def _helper(data): - nonlocal idx - if isinstance(data, torch.Tensor): - if data.size(): - tmp = data.flatten() - encoding[idx:idx + len(tmp)] = tmp - idx += len(tmp) - else: - encoding[idx] = data.item() - idx += 1 - return data.size() - elif isinstance(data, dict): - schema = {} - for key, chunk in data.items(): - schema[key] = _helper(chunk) - return schema - elif isinstance(data, (list, tuple)): - schema = [] - for chunk in data: - schema.append(_helper(chunk)) - if isinstance(data, tuple): - schema = tuple(schema) - return schema - else: - raise ValueError("not supported dtype! {}".format(type(data))) - - schema = _helper(data) - return encoding[:idx], schema - - -def shm_decode(encoding, schema): - - def _shm_decode_helper(encoding, schema, start): - if isinstance(schema, torch.Size): - storage = 1 - for d in schema: - storage *= d - # if isinstance(encoding[start], int): - # decoding = torch.LongTensor(encoding[start: start + storage]).view(schema) - # else: - # decoding = torch.FloatTensor(encoding[start: start + storage]).view(schema) - decoding = torch.Tensor(encoding[start:start + storage]).view(schema) - start += storage - return decoding, start - elif isinstance(schema, dict): - decoding = {} - for key, chunk in schema.items(): - decoding[key], start = _shm_decode_helper(encoding, chunk, start) - return decoding, start - elif isinstance(schema, (list, tuple)): - decoding = [] - for chunk in schema: - chunk, start = _shm_decode_helper(encoding, chunk, start) - decoding.append(chunk) - if isinstance(schema, tuple): - decoding = tuple(decoding) - return decoding, start - else: - raise ValueError("not supported schema! {}".format(schema)) - - decoding, start = _shm_decode_helper(encoding, schema, 0) - assert len(encoding) == start, "Encoding length and schema do not match!" - return decoding - - -def equal(data1, data2, check_dict_order=True, strict_dtype=False, parent_key=None): - if type(data1) != type(data2): - print(parent_key) - # print("data1: {} {}".format(parent_key, data1)) - # print("data2: {} {}".format(parent_key, data2)) - return False - if isinstance(data1, torch.Tensor): - if not strict_dtype: - data1 = data1.float() - data2 = data2.float() - if data1.dtype != data2.dtype: - print("data type does not match! data1({}), data2({})".format(data1.dtype, data2.dtype)) - # print("data1: {} {}".format(parent_key, data1)) - # print("data2: {} {}".format(parent_key, data2)) - return False - if data1.equal(data2): - return True - else: - print("value not match") - # print("parent key of data1: {}".format(parent_key)) - print("data1: {} {}".format(parent_key, data1)) - print("data2: {} {}".format(parent_key, data2)) - return False - elif isinstance(data1, dict): - key_set1 = data1.keys() - key_set2 = data2.keys() - if check_dict_order and key_set1 != key_set2: - print("key sequence not match!") - # print("data1: {}".format(data1)) - # print("data2: {}".format(data2)) - return False - elif set(key_set1) != set(key_set2): - print("key set not match!") - # print("data1: {}".format(data1)) - # print("data2: {}".format(data2)) - return False - for key in key_set1: - if equal(data1[key], data2[key], check_dict_order, strict_dtype, key): - print("passed:", key) - else: - print("!!!!!!! not match:", key) - return False - return True - elif isinstance(data1, (tuple, list)): - if len(data1) != len(data2): - print("list length does not match!") - # print("data1: {}".format(data1)) - # print("data2: {}".format(data2)) - return False - return all([equal(data1[i], data2[i], check_dict_order, strict_dtype, parent_key) for i in range(len(data1))]) - else: - raise ValueError("not supported dtype! {}".format(data1)) - - -def equal_v0(data1, data2, check_dict_order=True, strict_dtype=False): - if type(data1) != type(data2): - return False - if isinstance(data1, torch.Tensor): - if not strict_dtype: - data1 = data1.float() - data2 = data2.float() - if data1.dtype != data2.dtype: - print("data type does not match! data1({}), data2({})".format(data1.dtype, data2.dtype)) - return False - return data1.equal(data2) - elif isinstance(data1, dict): - key_set1 = data1.keys() - key_set2 = data2.keys() - if check_dict_order and key_set1 != key_set2: - return False - elif set(key_set1) != set(key_set2): - return False - return all([equal(data1[key], data2[key], check_dict_order, strict_dtype) for key in key_set1]) - elif isinstance(data1, (tuple, list)): - if len(data1) != len(data2): - return False - return all([equal(data1[i], data2[i], check_dict_order, strict_dtype) for i in range(len(data1))]) - else: - raise ValueError("not supported dtype! {}".format(data1)) \ No newline at end of file From 2c0e527cb28160abeac422a767753dc85a1a8033 Mon Sep 17 00:00:00 2001 From: zhumengshen Date: Wed, 24 Aug 2022 07:41:09 +0000 Subject: [PATCH 206/229] add comment of CpuUnpickler --- ding/framework/parallel.py | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/ding/framework/parallel.py b/ding/framework/parallel.py index 28a2fe523d..20a3c750ca 100644 --- a/ding/framework/parallel.py +++ b/ding/framework/parallel.py @@ -38,6 +38,11 @@ def cpu_loads(x): def my_pickle_loads(msg): + """ + Overview: + This method allows you to recieve gpu tensors from gpu bug freely, if you are in an only-cpu node. + refrence: https://github.com/pytorch/pytorch/issues/16797 + """ if not torch.cuda.is_available(): payload = cpu_loads(msg) else: From 7a3bc0bd7c16d99369b740545f74c8fe2f2b28ba Mon Sep 17 00:00:00 2001 From: zhumengshen Date: Wed, 24 Aug 2022 11:01:15 +0000 Subject: [PATCH 207/229] move out distar_test_pipelines --- .../middleware/tests/mock_for_test.py | 6 +- .../middleware/tests/test_distar_config.yaml | 16 -- .../test_league_actor_distar_one_process.py | 150 ------------------ .../tests/test_league_actor_one_process.py | 107 ------------- .../middleware/tests/test_league_learner.py | 106 ------------- .../middleware/tests/test_league_pipeline.py | 126 --------------- .../tests/test_league_pipeline_fake_data.py | 110 ------------- .../tests/test_league_pipeline_one_process.py | 80 ---------- 8 files changed, 3 insertions(+), 698 deletions(-) delete mode 100644 ding/framework/middleware/tests/test_distar_config.yaml delete mode 100644 ding/framework/middleware/tests/test_league_actor_distar_one_process.py delete mode 100644 ding/framework/middleware/tests/test_league_actor_one_process.py delete mode 100644 ding/framework/middleware/tests/test_league_learner.py delete mode 100644 ding/framework/middleware/tests/test_league_pipeline.py delete mode 100644 ding/framework/middleware/tests/test_league_pipeline_fake_data.py delete mode 100644 ding/framework/middleware/tests/test_league_pipeline_one_process.py diff --git a/ding/framework/middleware/tests/mock_for_test.py b/ding/framework/middleware/tests/mock_for_test.py index b4b7769ef2..07d46b1330 100644 --- a/ding/framework/middleware/tests/mock_for_test.py +++ b/ding/framework/middleware/tests/mock_for_test.py @@ -11,12 +11,12 @@ from ding.league.v2 import BaseLeague, Job from ding.framework.storage import FileStorage from ding.policy import PPOPolicy -from dizoo.distar.envs.distar_env import DIStarEnv -from dizoo.distar.policy.distar_policy import DIStarPolicy +from distar.diengine.dizoo.envs.distar_env import DIStarEnv +from distar.diengine.dizoo.policy.distar_policy import DIStarPolicy from ding.envs import BaseEnvManager import treetensor.torch as ttorch from ding.envs import BaseEnvTimestep -from dizoo.distar.envs.fake_data import rl_step_data +from distar.diengine.dizoo.envs.fake_data import rl_step_data if TYPE_CHECKING: from ding.framework import BattleContext diff --git a/ding/framework/middleware/tests/test_distar_config.yaml b/ding/framework/middleware/tests/test_distar_config.yaml deleted file mode 100644 index 18247e5a54..0000000000 --- a/ding/framework/middleware/tests/test_distar_config.yaml +++ /dev/null @@ -1,16 +0,0 @@ -actor: - job_type: 'train' # ['train', 'eval', 'train_test', 'eval_test'] -env: - map_name: 'KingsCove' - player_ids: ['agent1', 'agent2'] - races: ['zerg', 'zerg'] - map_size_resolutions: [True, True] # if True, ignore minimap_resolutions - minimap_resolutions: [[160, 152], [160, 152]] - realtime: False - replay_dir: '.' - random_seed: 'none' - game_steps_per_episode: 100000 - update_bot_obs: False - save_replay_episodes: 1 - update_both_obs: False - version: '4.10.0' \ No newline at end of file diff --git a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py b/ding/framework/middleware/tests/test_league_actor_distar_one_process.py deleted file mode 100644 index b77e427297..0000000000 --- a/ding/framework/middleware/tests/test_league_actor_distar_one_process.py +++ /dev/null @@ -1,150 +0,0 @@ -from time import sleep -import pytest -from copy import deepcopy -from unittest.mock import patch -from easydict import EasyDict - -from dizoo.distar.config import distar_cfg -from dizoo.distar.envs.distar_env import DIStarEnv - -from ding.envs import EnvSupervisor -from ding.league.player import PlayerMeta -from ding.league.v2.base_league import Job -from ding.framework import EventEnum -from ding.framework.storage import FileStorage -from ding.framework.task import task -from ding.framework.context import BattleContext - -from ding.framework.supervisor import ChildType -from ding.framework.middleware import StepLeagueActor -from ding.framework.middleware.functional import ActorData -from ding.framework.middleware.tests import DIStarMockPolicy -from ding.framework.middleware.league_learner import LearnerModel -from ding.framework.middleware.functional.collector import battle_inferencer_for_distar, battle_rolloutor_for_distar - -env_cfg = dict( - actor=dict(job_type='train', ), - env=dict( - map_name='KingsCove', - player_ids=['agent1', 'agent2'], - races=['zerg', 'zerg'], - map_size_resolutions=[True, True], # if True, ignore minimap_resolutions - minimap_resolutions=[[160, 152], [160, 152]], - realtime=False, - replay_dir='.', - random_seed='none', - game_steps_per_episode=100000, - update_bot_obs=False, - save_replay_episodes=1, - update_both_obs=False, - version='4.10.0', - ), -) -env_cfg = EasyDict(env_cfg) -cfg = deepcopy(distar_cfg) - - -class PrepareTest(): - - @classmethod - def get_env_fn(cls): - return DIStarEnv(env_cfg) - - @classmethod - def get_env_supervisor(cls): - for _ in range(10): - try: - env = EnvSupervisor( - type_=ChildType.THREAD, - env_fn=[cls.get_env_fn for _ in range(cfg.env.collector_env_num)], - **cfg.env.manager - ) - env.seed(cfg.seed) - return env - except Exception as e: - print(e) - continue - - @classmethod - def learn_policy_fn(cls): - policy = DIStarMockPolicy(DIStarMockPolicy.default_config(), enable_field=['learn']) - return policy - - @classmethod - def collect_policy_fn(cls): - # policy = DIStarMockPolicyCollect() - policy = DIStarMockPolicy(DIStarMockPolicy.default_config(), enable_field=['collect']) - return policy - - -@pytest.mark.unittest -def test_league_actor(): - with task.start(async_mode=True, ctx=BattleContext()): - policy = PrepareTest.learn_policy_fn().learn_mode - - def test_actor(): - job = Job( - launch_player='main_player_default_0', - players=[ - PlayerMeta( - player_id='main_player_default_0', checkpoint=FileStorage(path=None), total_agent_step=0 - ), - PlayerMeta( - player_id='main_player_default_1', checkpoint=FileStorage(path=None), total_agent_step=0 - ) - ] - ) - testcases = { - "on_actor_greeting": False, - "on_actor_job": False, - "on_actor_data": False, - } - - def on_actor_greeting(actor_id): - assert actor_id == task.router.node_id - testcases["on_actor_greeting"] = True - - def on_actor_job(job_: Job): - assert job_.launch_player == job.launch_player - print(job) - testcases["on_actor_job"] = True - - def on_actor_data(actor_data): - print('got actor_data') - assert isinstance(actor_data, ActorData) - testcases["on_actor_data"] = True - - task.on(EventEnum.ACTOR_GREETING, on_actor_greeting) - task.on(EventEnum.ACTOR_FINISH_JOB, on_actor_job) - task.on(EventEnum.ACTOR_SEND_DATA.format(player=job.launch_player), on_actor_data) - - def _test_actor(ctx): - sleep(0.3) - task.emit(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), job) - sleep(0.3) - - task.emit( - EventEnum.LEARNER_SEND_MODEL, - LearnerModel(player_id='main_player_default_0', state_dict=policy.state_dict(), train_iter=0) - ) - # sleep(100) - # try: - # print(testcases) - # assert all(testcases.values()) - # finally: - # task.finish = True - - return _test_actor - - with patch("ding.framework.middleware.collector.battle_inferencer", battle_inferencer_for_distar): - with patch("ding.framework.middleware.collector.battle_rolloutor", battle_rolloutor_for_distar): - league_actor = StepLeagueActor( - cfg=cfg, env_fn=PrepareTest.get_env_supervisor, policy_fn=PrepareTest.collect_policy_fn - ) - task.use(test_actor()) - task.use(league_actor) - task.run() - - -if __name__ == '__main__': - test_league_actor() diff --git a/ding/framework/middleware/tests/test_league_actor_one_process.py b/ding/framework/middleware/tests/test_league_actor_one_process.py deleted file mode 100644 index cce7fb97f3..0000000000 --- a/ding/framework/middleware/tests/test_league_actor_one_process.py +++ /dev/null @@ -1,107 +0,0 @@ -from time import sleep -import pytest -from copy import deepcopy -from ding.envs import BaseEnvManager -from ding.framework.context import BattleContext -from ding.framework.middleware.league_learner import LearnerModel -from dizoo.distar.config import distar_cfg -from ding.framework.middleware import StepLeagueActor -from ding.framework.middleware.functional import ActorData -from ding.league.player import PlayerMeta -from ding.framework.storage import FileStorage - -from ding.framework.task import task -from ding.league.v2.base_league import Job -from ding.model import VAC -from ding.policy.ppo import PPOPolicy -from dizoo.league_demo.game_env import GameEnv - -from ding.framework import EventEnum - - -def prepare_test(): - global distar_cfg - cfg = deepcopy(distar_cfg) - - def env_fn(): - env = BaseEnvManager( - env_fn=[lambda: GameEnv(cfg.env.env_type) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager - ) - env.seed(cfg.seed) - return env - - def policy_fn(): - model = VAC(**cfg.policy.model) - policy = PPOPolicy(cfg.policy, model=model) - return policy - - return cfg, env_fn, policy_fn - - -@pytest.mark.unittest -def test_league_actor(): - cfg, env_fn, policy_fn = prepare_test() - policy = policy_fn() - with task.start(async_mode=True, ctx=BattleContext()): - league_actor = StepLeagueActor(cfg=cfg, env_fn=env_fn, policy_fn=policy_fn) - - def test_actor(): - job = Job( - launch_player='main_player_default_0', - players=[ - PlayerMeta( - player_id='main_player_default_0', checkpoint=FileStorage(path=None), total_agent_step=0 - ), - PlayerMeta( - player_id='main_player_default_1', checkpoint=FileStorage(path=None), total_agent_step=0 - ) - ] - ) - testcases = { - "on_actor_greeting": False, - "on_actor_job": False, - "on_actor_data": False, - } - - def on_actor_greeting(actor_id): - assert actor_id == task.router.node_id - testcases["on_actor_greeting"] = True - - def on_actor_job(job_: Job): - assert job_.launch_player == job.launch_player - testcases["on_actor_job"] = True - - def on_actor_data(actor_data): - assert isinstance(actor_data, ActorData) - testcases["on_actor_data"] = True - - task.on(EventEnum.ACTOR_GREETING, on_actor_greeting) - task.on(EventEnum.ACTOR_FINISH_JOB, on_actor_job) - task.on(EventEnum.ACTOR_SEND_DATA.format(player=job.launch_player), on_actor_data) - - def _test_actor(ctx): - sleep(0.3) - task.emit(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), job) - sleep(5) - - task.emit( - EventEnum.LEARNER_SEND_MODEL, - LearnerModel( - player_id='main_player_default_0', state_dict=policy.learn_mode.state_dict(), train_iter=0 - ) - ) - try: - print(testcases) - assert all(testcases.values()) - finally: - task.finish = True - - return _test_actor - - task.use(test_actor()) - task.use(league_actor) - task.run() - - -if __name__ == '__main__': - test_league_actor() diff --git a/ding/framework/middleware/tests/test_league_learner.py b/ding/framework/middleware/tests/test_league_learner.py deleted file mode 100644 index 0410201715..0000000000 --- a/ding/framework/middleware/tests/test_league_learner.py +++ /dev/null @@ -1,106 +0,0 @@ -from copy import deepcopy -from dataclasses import dataclass -from time import sleep -import time -import pytest -import logging -from typing import Any - -from ding.data import DequeBuffer -from ding.envs import BaseEnvManager -from ding.framework.context import BattleContext -from ding.framework import EventEnum -from ding.framework.task import task, Parallel -from ding.framework.middleware import data_pusher, OffPolicyLearner, LeagueLearnerCommunicator -from ding.framework.middleware.functional.actor_data import * -from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy -from ding.league.v2 import BaseLeague -from ding.utils import log_every_sec -from dizoo.distar.config import distar_cfg -from dizoo.distar.envs import fake_rl_traj_with_last -from dizoo.distar.envs.distar_env import DIStarEnv -from distar.ctools.utils import read_config - - -def prepare_test(): - global distar_cfg - cfg = deepcopy(distar_cfg) - env_cfg = read_config('./test_distar_config.yaml') - - def env_fn(): - # subprocess env manager - env = BaseEnvManager( - env_fn=[lambda: DIStarEnv(env_cfg) for _ in range(cfg.env.collector_env_num)], cfg=cfg.env.manager - ) - env.seed(cfg.seed) - return env - - def policy_fn(): - policy = DIStarMockPolicy(DIStarMockPolicy.default_config(), enable_field=['learn']) - return policy - - return cfg, env_fn, policy_fn - - -def coordinator_mocker(): - task.on(EventEnum.LEARNER_SEND_META, lambda x: logging.info("test: {}".format(x))) - task.on(EventEnum.LEARNER_SEND_MODEL, lambda x: logging.info("test: send model success")) - - def _coordinator_mocker(ctx): - sleep(10) - - return _coordinator_mocker - - -@dataclass -class TestActorData: - env_step: int - train_data: Any - - -def actor_mocker(league): - - def _actor_mocker(ctx): - n_players = len(league.active_players_ids) - player = league.active_players[(task.router.node_id + 2) % n_players] - log_every_sec(logging.INFO, 5, "Actor: actor player: {}".format(player.player_id)) - for _ in range(24): - meta = ActorDataMeta(player_total_env_step=0, actor_id=0, send_wall_time=time.time()) - data = fake_rl_traj_with_last() - actor_data = ActorData(meta=meta, train_data=[ActorEnvTrajectories(env_id=0, trajectories=[data])]) - task.emit(EventEnum.ACTOR_SEND_DATA.format(player=player.player_id), actor_data) - sleep(9) - - return _actor_mocker - - -def _main(): - logging.getLogger().setLevel(logging.INFO) - cfg, env_fn, policy_fn = prepare_test() - league = BaseLeague(cfg.policy.other.league) - n_players = len(league.active_players_ids) - print("League: n_players: ", n_players) - - with task.start(async_mode=True, ctx=BattleContext()): - if task.router.node_id == 0: - task.use(coordinator_mocker()) - elif task.router.node_id <= 1: - task.use(actor_mocker(league)) - else: - cfg.policy.collect.unroll_len = 1 - buffer_ = DequeBuffer(size=cfg.policy.other.replay_buffer.replay_buffer_size) - player = league.active_players[task.router.node_id % n_players] - policy = policy_fn() - task.use(LeagueLearnerCommunicator(cfg, policy.learn_mode, player)) - task.use(data_pusher(cfg, buffer_)) - task.use(OffPolicyLearner(cfg, policy.learn_mode, buffer_)) - task.run(max_step=30) - - -@pytest.mark.unittest -def test_league_learner(): - Parallel.runner(n_parallel_workers=4, protocol="tcp", topology="mesh")(_main) - - -if __name__ == '__main__': - Parallel.runner(n_parallel_workers=4, protocol="tcp", topology="mesh")(_main) diff --git a/ding/framework/middleware/tests/test_league_pipeline.py b/ding/framework/middleware/tests/test_league_pipeline.py deleted file mode 100644 index 63ce241237..0000000000 --- a/ding/framework/middleware/tests/test_league_pipeline.py +++ /dev/null @@ -1,126 +0,0 @@ -import logging -import pytest -from easydict import EasyDict -from copy import deepcopy -from ding.data import DequeBuffer -from ding.envs import BaseEnvManager, EnvSupervisor -from ding.framework.supervisor import ChildType -from ding.framework.context import BattleContext -from ding.framework.middleware import StepLeagueActor, LeagueCoordinator, LeagueLearnerCommunicator, data_pusher, OffPolicyLearner -from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, DIStarMockPolicyCollect -from ding.framework.middleware.functional.collector import battle_inferencer_for_distar, battle_rolloutor_for_distar -from ding.framework.task import task, Parallel -from ding.league.v2 import BaseLeague -from dizoo.distar.config import distar_cfg -from dizoo.distar.envs.distar_env import DIStarEnv -from unittest.mock import patch -from dizoo.distar.policy.distar_policy import DIStarPolicy -from ding.data.buffer.middleware import use_time_check - -env_cfg = dict( - actor=dict(job_type='train', ), - env=dict( - map_name='KingsCove', - player_ids=['agent1', 'agent2'], - races=['zerg', 'zerg'], - map_size_resolutions=[True, True], # if True, ignore minimap_resolutions - minimap_resolutions=[[160, 152], [160, 152]], - realtime=False, - replay_dir='.', - random_seed='none', - game_steps_per_episode=100000, - update_bot_obs=False, - save_replay_episodes=1, - update_both_obs=False, - version='4.10.0', - ), -) -env_cfg = EasyDict(env_cfg) -cfg = deepcopy(distar_cfg) - - -class PrepareTest(): - - @classmethod - def get_env_fn(cls): - return DIStarEnv(env_cfg) - - @classmethod - def get_env_supervisor(cls): - for _ in range(10): - try: - env = EnvSupervisor( - type_=ChildType.THREAD, - env_fn=[cls.get_env_fn for _ in range(cfg.env.collector_env_num)], - **cfg.env.manager - ) - env.seed(cfg.seed) - return env - except Exception as e: - print(e) - continue - - @classmethod - def policy_fn(cls): - policy = DIStarPolicy(DIStarPolicy.default_config(), enable_field=['learn']) - return policy - - @classmethod - def collect_policy_fn(cls): - policy = DIStarPolicy(DIStarPolicy.default_config(), enable_field=['collect']) - return policy - - -def coordinator(): - coordinator_league = BaseLeague(cfg.policy.other.league) - task.use(LeagueCoordinator(cfg, coordinator_league)) - - -def learner(): - league = BaseLeague(cfg.policy.other.league) - N_PLAYERS = len(league.active_players_ids) - - cfg.policy.collect.unroll_len = 1 - player = league.active_players[task.router.node_id % N_PLAYERS] - del league - - buffer_ = DequeBuffer(size=cfg.policy.other.replay_buffer.replay_buffer_size) - buffer_.use(use_time_check(buffer_, max_use=cfg.policy.other.replay_buffer.max_use)) - policy = PrepareTest.policy_fn() - - task.use(LeagueLearnerCommunicator(cfg, policy.learn_mode, player)) - task.use(data_pusher(cfg, buffer_)) - task.use(OffPolicyLearner(cfg, policy.learn_mode, buffer_)) - - -def actor(): - task.use(StepLeagueActor(cfg, PrepareTest.get_env_supervisor, PrepareTest.collect_policy_fn)) - - -def main(): - logging.getLogger().setLevel(logging.INFO) - league = BaseLeague(cfg.policy.other.league) - N_PLAYERS = len(league.active_players_ids) - del league - print("League: n_players =", N_PLAYERS) - - with task.start(async_mode=False, ctx=BattleContext()),\ - patch("ding.framework.middleware.collector.battle_inferencer", battle_inferencer_for_distar),\ - patch("ding.framework.middleware.collector.battle_rolloutor", battle_rolloutor_for_distar): - print("node id:", task.router.node_id) - if task.router.node_id == 0: - coordinator() - elif task.router.node_id <= N_PLAYERS: - learner() - else: - actor() - task.run() - - -@pytest.mark.unittest -def test_league_pipeline(): - Parallel.runner(n_parallel_workers=7, protocol="tcp", topology="mesh")(main) - - -if __name__ == "__main__": - Parallel.runner(n_parallel_workers=7, protocol="tcp", topology="mesh")(main) diff --git a/ding/framework/middleware/tests/test_league_pipeline_fake_data.py b/ding/framework/middleware/tests/test_league_pipeline_fake_data.py deleted file mode 100644 index a9eabe4d02..0000000000 --- a/ding/framework/middleware/tests/test_league_pipeline_fake_data.py +++ /dev/null @@ -1,110 +0,0 @@ -import logging -import pytest -from easydict import EasyDict -from copy import deepcopy -from ding.data import DequeBuffer -from ding.envs import BaseEnvManager, EnvSupervisor -from ding.framework.supervisor import ChildType -from ding.framework.context import BattleContext -from ding.framework.middleware import StepLeagueActor, LeagueCoordinator, LeagueLearnerCommunicator, data_pusher, OffPolicyLearner -from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy, DIStarMockPolicyCollect -from ding.framework.middleware.functional.collector import battle_inferencer_for_distar, battle_rolloutor_for_distar -from ding.framework.task import task, Parallel -from ding.league.v2 import BaseLeague -from dizoo.distar.config import distar_cfg -from dizoo.distar.envs.distar_env import DIStarEnv -from unittest.mock import patch -from dizoo.distar.policy.distar_policy import DIStarPolicy -from ding.data.buffer.middleware import use_time_check - -env_cfg = dict( - actor=dict(job_type='train', ), - env=dict( - map_name='KingsCove', - player_ids=['agent1', 'agent2'], - races=['zerg', 'zerg'], - map_size_resolutions=[True, True], # if True, ignore minimap_resolutions - minimap_resolutions=[[160, 152], [160, 152]], - realtime=False, - replay_dir='.', - random_seed='none', - game_steps_per_episode=100000, - update_bot_obs=False, - save_replay_episodes=1, - update_both_obs=False, - version='4.10.0', - ), -) -env_cfg = EasyDict(env_cfg) -cfg = deepcopy(distar_cfg) - - -class PrepareTest(): - - @classmethod - def get_env_fn(cls): - return DIStarEnv(env_cfg) - - @classmethod - def get_env_supervisor(cls): - for _ in range(10): - try: - env = EnvSupervisor( - type_=ChildType.THREAD, - env_fn=[cls.get_env_fn for _ in range(cfg.env.collector_env_num)], - **cfg.env.manager - ) - env.seed(cfg.seed) - return env - except Exception as e: - print(e) - continue - - @classmethod - def policy_fn(cls): - policy = DIStarPolicy(DIStarPolicy.default_config(), enable_field=['learn']) - return policy - - @classmethod - def collect_policy_fn(cls): - policy = DIStarMockPolicyCollect() - return policy - - -def main(): - logging.getLogger().setLevel(logging.INFO) - league = BaseLeague(cfg.policy.other.league) - N_PLAYERS = len(league.active_players_ids) - print("League: n_players =", N_PLAYERS) - - with task.start(async_mode=True, ctx=BattleContext()),\ - patch("ding.framework.middleware.collector.battle_inferencer", battle_inferencer_for_distar),\ - patch("ding.framework.middleware.collector.battle_rolloutor", battle_rolloutor_for_distar): - print("node id:", task.router.node_id) - if task.router.node_id == 0: - coordinator_league = BaseLeague(cfg.policy.other.league) - task.use(LeagueCoordinator(cfg, coordinator_league)) - elif task.router.node_id <= N_PLAYERS: - cfg.policy.collect.unroll_len = 1 - player = league.active_players[task.router.node_id % N_PLAYERS] - - buffer_ = DequeBuffer(size=cfg.policy.other.replay_buffer.replay_buffer_size) - buffer_.use(use_time_check(buffer_, max_use=cfg.policy.other.replay_buffer.max_use)) - policy = PrepareTest.policy_fn() - - task.use(LeagueLearnerCommunicator(cfg, policy.learn_mode, player)) - task.use(data_pusher(cfg, buffer_)) - task.use(OffPolicyLearner(cfg, policy.learn_mode, buffer_)) - else: - task.use(StepLeagueActor(cfg, PrepareTest.get_env_supervisor, PrepareTest.collect_policy_fn)) - - task.run() - - -@pytest.mark.unittest -def test_league_pipeline(): - Parallel.runner(n_parallel_workers=7, protocol="tcp", topology="mesh")(main) - - -if __name__ == "__main__": - Parallel.runner(n_parallel_workers=7, protocol="tcp", topology="mesh")(main) diff --git a/ding/framework/middleware/tests/test_league_pipeline_one_process.py b/ding/framework/middleware/tests/test_league_pipeline_one_process.py deleted file mode 100644 index 919562d4cf..0000000000 --- a/ding/framework/middleware/tests/test_league_pipeline_one_process.py +++ /dev/null @@ -1,80 +0,0 @@ -from copy import deepcopy -import pytest -from ding.envs import BaseEnvManager, EnvSupervisor -from ding.framework.context import BattleContext -from ding.framework.middleware import StepLeagueActor, LeagueCoordinator -from ding.framework.supervisor import ChildType - -from ding.model import VAC -from ding.framework.task import task -from ding.framework.middleware.tests import cfg, MockLeague, MockLogger -from dizoo.distar.envs.distar_env import DIStarEnv -from ding.framework.middleware.tests import DIStarMockPolicy, DIStarMockPolicyCollect -from ding.framework.middleware.functional.collector import battle_inferencer_for_distar, battle_rolloutor_for_distar -from distar.ctools.utils import read_config -from unittest.mock import patch -import os - -cfg = deepcopy(cfg) -env_cfg = read_config('./test_distar_config.yaml') - - -class PrepareTest(): - - @classmethod - def get_env_fn(cls): - return DIStarEnv(env_cfg) - - @classmethod - def get_env_supervisor(cls): - env = EnvSupervisor( - type_=ChildType.THREAD, - env_fn=[cls.get_env_fn for _ in range(cfg.env.collector_env_num)], - **cfg.env.manager - ) - env.seed(cfg.seed) - return env - - @classmethod - def policy_fn(cls): - model = VAC(**cfg.policy.model) - policy = DIStarMockPolicy(cfg.policy, model=model) - return policy - - @classmethod - def collect_policy_fn(cls): - policy = DIStarMockPolicyCollect() - return policy - - -def _main(): - league = MockLeague(cfg.policy.other.league) - n_players = len(league.active_players_ids) - print(n_players) - - with task.start(async_mode=True, ctx=BattleContext()): - with patch("ding.framework.middleware.collector.battle_inferencer", battle_inferencer_for_distar): - with patch("ding.framework.middleware.collector.battle_rolloutor", battle_rolloutor_for_distar): - player_0 = league.active_players[0] - learner_0 = LeagueLearner(cfg, PrepareTest.policy_fn, player_0) - learner_0._learner._tb_logger = MockLogger() - - player_1 = league.active_players[1] - learner_1 = LeagueLearner(cfg, PrepareTest.policy_fn, player_1) - learner_1._learner._tb_logger = MockLogger() - - task.use(LeagueCoordinator(league)) - task.use(StepLeagueActor(cfg, PrepareTest.get_env_supervisor, PrepareTest.collect_policy_fn)) - task.use(learner_0) - task.use(learner_1) - - task.run(max_step=300) - - -@pytest.mark.unittest -def test_league_actor(): - _main() - - -if __name__ == '__main__': - _main() From 3f21d3cb910a67b999b73f600748cfbfa5d26c77 Mon Sep 17 00:00:00 2001 From: zhumengshen Date: Wed, 24 Aug 2022 11:02:03 +0000 Subject: [PATCH 208/229] change import of collector.py --- ding/framework/middleware/functional/collector.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index 532348f419..da13c4a7af 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -2,7 +2,7 @@ from easydict import EasyDict from functools import reduce import treetensor.torch as ttorch -from ding.envs import BaseEnvManager +from ding.envs.env_manager.base_env_manager import BaseEnvManager from ding.envs.env.base_env import BaseEnvTimestep from ding.policy import Policy import torch @@ -14,7 +14,6 @@ from ding.framework import OnlineRLContext, BattleContext from collections import deque from ding.framework.middleware.functional.actor_data import ActorEnvTrajectories -from dizoo.distar.envs.fake_data import rl_step_data from copy import deepcopy from ditk import logging From 37b6bc7f5fc79ae0dc8236ebbc7052887006858c Mon Sep 17 00:00:00 2001 From: zhumengshen Date: Wed, 24 Aug 2022 18:32:19 +0000 Subject: [PATCH 209/229] drop out useless mocks --- .../middleware/tests/mock_for_test.py | 72 ------------------- 1 file changed, 72 deletions(-) diff --git a/ding/framework/middleware/tests/mock_for_test.py b/ding/framework/middleware/tests/mock_for_test.py index 07d46b1330..03c0827d60 100644 --- a/ding/framework/middleware/tests/mock_for_test.py +++ b/ding/framework/middleware/tests/mock_for_test.py @@ -10,16 +10,6 @@ from ding.league.player import PlayerMeta from ding.league.v2 import BaseLeague, Job from ding.framework.storage import FileStorage -from ding.policy import PPOPolicy -from distar.diengine.dizoo.envs.distar_env import DIStarEnv -from distar.diengine.dizoo.policy.distar_policy import DIStarPolicy -from ding.envs import BaseEnvManager -import treetensor.torch as ttorch -from ding.envs import BaseEnvTimestep -from distar.diengine.dizoo.envs.fake_data import rl_step_data - -if TYPE_CHECKING: - from ding.framework import BattleContext obs_dim = [2, 2] action_space = 1 @@ -175,65 +165,3 @@ def close(*args): def flush(*args): pass - - -class DIStarMockPolicy(DIStarPolicy): - - def _forward_learn(self, data: Dict[str, Any]) -> Dict[str, Any]: - print("Call forward_learn:", flush=True) - return super()._forward_learn(data) - - def _forward_collect(self, data: Dict[int, Any]) -> Dict[int, Any]: - print("Call forward_collect:", flush=True) - return super()._forward_collect(data) - - -class DIStarMockPPOPolicy(PPOPolicy): - - def _forward_learn(self, data: Dict[str, Any]) -> Dict[str, Any]: - pass - - def _forward_collect(self, data: Dict[int, Any]) -> Dict[int, Any]: - return DIStarEnv.random_action(data) - - -class DIstarCollectMode: - - def __init__(self) -> None: - self._cfg = EasyDict(dict(collect=dict(n_episode=1))) - self._race = 'zerg' - - def load_state_dict(self, state_dict): - return - - def get_attribute(self, name: str) -> Any: - if hasattr(self, '_get_' + name): - return getattr(self, '_get_' + name)() - elif hasattr(self, '_' + name): - return getattr(self, '_' + name) - else: - raise NotImplementedError - - def reset(self, data_id: Optional[List[int]] = None) -> None: - pass - - def forward(self, policy_obs: Dict[int, Any]) -> Dict[int, Any]: - # print("Call forward_collect:") - return_data = {} - return_data['action'] = DIStarEnv.random_action(policy_obs) - return_data['logit'] = [1] - return_data['value'] = [0] - - return return_data - - def process_transition(self, obs, model_output, timestep) -> dict: - step_data = rl_step_data() - step_data['done'] = timestep.done - return step_data - - -class DIStarMockPolicyCollect: - - def __init__(self): - - self.collect_mode = DIstarCollectMode() From de8b6eba55150ddc909b4e0f7baf799188b2b6d9 Mon Sep 17 00:00:00 2001 From: zhumengshen Date: Thu, 25 Aug 2022 06:58:37 +0000 Subject: [PATCH 210/229] make test of coordinator pass --- ding/framework/middleware/functional/trainer.py | 3 ++- ding/framework/middleware/league_coordinator.py | 5 +++++ .../middleware/tests/test_league_coordinator.py | 15 ++++++--------- 3 files changed, 13 insertions(+), 10 deletions(-) diff --git a/ding/framework/middleware/functional/trainer.py b/ding/framework/middleware/functional/trainer.py index 27be583dd1..a54c9c0a83 100644 --- a/ding/framework/middleware/functional/trainer.py +++ b/ding/framework/middleware/functional/trainer.py @@ -5,7 +5,8 @@ from ding.policy import Policy from ding.framework import task -from ding.framework import OnlineRLContext, OfflineRLContext, BattleContext +if TYPE_CHECKING: + from ding.framework import OnlineRLContext, OfflineRLContext, BattleContext def trainer(cfg: EasyDict, policy: Policy) -> Callable: """ diff --git a/ding/framework/middleware/league_coordinator.py b/ding/framework/middleware/league_coordinator.py index 0cd1b7b69c..95b5ada20b 100644 --- a/ding/framework/middleware/league_coordinator.py +++ b/ding/framework/middleware/league_coordinator.py @@ -59,6 +59,11 @@ def _on_learner_meta(self, player_meta: "PlayerMeta"): self.league.create_historical_player(player_meta) def _on_actor_job(self, job: "Job"): + if self._last_collect_time is None: + self._last_collect_time = time() + if self._total_collect_time is None: + self._total_collect_time = 0 + self._total_recv_jobs += 1 old_time = self._last_collect_time self._last_collect_time = time() diff --git a/ding/framework/middleware/tests/test_league_coordinator.py b/ding/framework/middleware/tests/test_league_coordinator.py index 8a95ca1278..8abe2599df 100644 --- a/ding/framework/middleware/tests/test_league_coordinator.py +++ b/ding/framework/middleware/tests/test_league_coordinator.py @@ -2,10 +2,10 @@ import time from unittest.mock import patch from ding.framework import task, Parallel -from ding.framework.context import OnlineRLContext from ding.framework.middleware import LeagueCoordinator -from ding.league.v2 import BaseLeague, Job +from ding.league.v2 import Job from ding.framework import EventEnum +from ding.league.player import PlayerMeta class MockLeague: @@ -36,7 +36,7 @@ def _main(): if task.router.node_id == 0: with patch("ding.league.BaseLeague", MockLeague): league = MockLeague() - coordinator = LeagueCoordinator(league) + coordinator = LeagueCoordinator(None, league) time.sleep(3) assert league.update_payoff_cnt == 3 assert league.update_active_player_cnt == 3 @@ -55,8 +55,9 @@ def _main(): assert task.router.node_id == res[-1].actor_id elif task.router.node_id == 2: # test LEARNER_SEND_META - for _ in range(3): - task.emit(EventEnum.LEARNER_SEND_META, {"meta": task.router.node_id}) + for i in range(3): + player_meta = PlayerMeta(player_id="test_player_{}".format(i), checkpoint=None) + task.emit(EventEnum.LEARNER_SEND_META, player_meta) time.sleep(3) elif task.router.node_id == 3: # test ACTOR_FINISH_JOB @@ -71,7 +72,3 @@ def _main(): @pytest.mark.unittest def test_coordinator(): Parallel.runner(n_parallel_workers=4, protocol="tcp", topology="star")(_main) - - -if __name__ == "__main__": - Parallel.runner(n_parallel_workers=4, protocol="tcp", topology="star")(_main) From e63d710ff6ddde2957617c969c55293239f5a2be Mon Sep 17 00:00:00 2001 From: zhumengshen Date: Thu, 25 Aug 2022 21:02:22 +0000 Subject: [PATCH 211/229] feature(zms): add test_league_learner_communicator.py --- ding/framework/middleware/league_learner.py | 111 +----------- .../middleware/tests/mock_for_test.py | 165 ++++++++++++++++++ .../middleware/tests/test_league_actor.py | 2 +- .../tests/test_league_learner_communicator.py | 135 ++++++++++++++ 4 files changed, 304 insertions(+), 109 deletions(-) create mode 100644 ding/framework/middleware/tests/test_league_learner_communicator.py diff --git a/ding/framework/middleware/league_learner.py b/ding/framework/middleware/league_learner.py index 409e68647d..c9c5cb7654 100644 --- a/ding/framework/middleware/league_learner.py +++ b/ding/framework/middleware/league_learner.py @@ -2,21 +2,17 @@ import os from dataclasses import dataclass from collections import deque -from threading import Lock from time import sleep -from typing import TYPE_CHECKING, Callable, Optional -from ding.data.buffer.deque_buffer import DequeBuffer +from typing import TYPE_CHECKING from ding.framework import task, EventEnum -from ding.framework.middleware import OffPolicyLearner, CkptSaver, data_pusher -from ding.framework.storage import Storage, FileStorage +from ding.framework.storage import FileStorage from ding.league.player import PlayerMeta from ding.utils.sparse_logging import log_every_sec -from ding.worker.learner.base_learner import BaseLearner if TYPE_CHECKING: from ding.policy import Policy - from ding.framework import Context, BattleContext + from ding.framework import BattleContext from ding.framework.middleware.league_actor import ActorData from ding.league import ActivePlayer @@ -77,104 +73,3 @@ def __call__(self, ctx: "BattleContext"): player_id=self.player_id, state_dict=self.policy.state_dict(), train_iter=ctx.train_iter ) task.emit(EventEnum.LEARNER_SEND_MODEL, learner_model) - - -# class OffPolicyLeagueLearner: - -# def __init__(self, cfg: dict, policy_fn: Callable, player: "ActivePlayer") -> None: -# self._buffer = DequeBuffer(size=10000) -# self._policy = policy_fn().learn_mode -# self.player_id = player.player_id -# task.on(EventEnum.ACTOR_SEND_DATA.format(player=self.player_id), self._push_data) -# self._learner = OffPolicyLearner(cfg, self._policy, self._buffer) -# # self._ckpt_handler = CkptSaver(cfg, self._policy, train_freq=100) - -# def _push_data(self, data: "ActorData"): -# print("push data into the buffer!") -# self._buffer.push(data.train_data) - -# def __call__(self, ctx: "Context"): -# print("num of objects in buffer:", self._buffer.count()) -# self._learner(ctx) -# checkpoint = None - -# sleep(2) -# print('learner send player meta\n', flush=True) -# task.emit( -# EventEnum.LEARNER_SEND_META, -# PlayerMeta(player_id=self.player_id, checkpoint=checkpoint, total_agent_step=0) -# ) - -# learner_model = LearnerModel( -# player_id=self.player_id, -# state_dict=self._policy.state_dict(), -# train_iter=ctx.train_iter # self._policy.state_dict() -# ) -# print('learner send model\n', flush=True) -# task.emit(EventEnum.LEARNER_SEND_MODEL, learner_model) - -# class LeagueLearner: - -# def __init__(self, cfg: dict, policy_fn: Callable, player: "ActivePlayer") -> None: -# self.cfg = cfg -# self.policy_fn = policy_fn -# self.player = player -# self.player_id = player.player_id -# self.checkpoint_prefix = cfg.policy.other.league.path_policy -# self._learner = self._get_learner() -# self._lock = Lock() -# task.on(EventEnum.ACTOR_SEND_DATA.format(player=self.player_id), self._on_actor_send_data) -# self._step = 0 - -# def _on_actor_send_data(self, actor_data: "ActorData"): -# logging.info("learner {} receive data from actor! \n".format(task.router.node_id), flush=True) -# with self._lock: -# cfg = self.cfg -# for _ in range(cfg.policy.learn.update_per_collect): -# pass -# # print("train model") -# # print(actor_data.train_data) -# # self._learner.train(actor_data.train_data, actor_data.env_step) - -# self.player.total_agent_step = self._learner.train_iter -# # print("save checkpoint") -# checkpoint = self._save_checkpoint() if self.player.is_trained_enough() else None - -# print('learner {} send player meta {}\n'.format(task.router.node_id, self.player_id), flush=True) -# task.emit( -# EventEnum.LEARNER_SEND_META, -# PlayerMeta(player_id=self.player_id, checkpoint=checkpoint, total_agent_step=self._learner.train_iter) -# ) - -# # print("pack model") -# learner_model = LearnerModel( -# player_id=self.player_id, state_dict=self._learner.policy.state_dict(), train_iter=self._learner.train_iter -# ) -# print('learner {} send model\n'.format(task.router.node_id), flush=True) -# task.emit(EventEnum.LEARNER_SEND_MODEL, learner_model) - -# def _get_learner(self) -> BaseLearner: -# policy = self.policy_fn().learn_mode -# learner = BaseLearner( -# self.cfg.policy.learn.learner, -# policy, -# exp_name=self.cfg.exp_name, -# instance_name=self.player_id + '_learner' -# ) -# return learner - -# def _save_checkpoint(self) -> Optional[Storage]: -# if not os.path.exists(self.checkpoint_prefix): -# os.makedirs(self.checkpoint_prefix) -# storage = FileStorage( -# path=os.path. -# join(self.checkpoint_prefix, "{}_{}_ckpt.pth".format(self.player_id, self._learner.train_iter)) -# ) -# storage.save(self._learner.policy.state_dict()) -# return storage - -# def __del__(self): -# print('task finished, learner {} closed\n'.format(task.router.node_id), flush=True) - -# def __call__(self, _: "Context") -> None: -# sleep(1) diff --git a/ding/framework/middleware/tests/mock_for_test.py b/ding/framework/middleware/tests/mock_for_test.py index 03c0827d60..cfb937bf09 100644 --- a/ding/framework/middleware/tests/mock_for_test.py +++ b/ding/framework/middleware/tests/mock_for_test.py @@ -165,3 +165,168 @@ def close(*args): def flush(*args): pass + + +league_cfg = EasyDict( + { + 'env': { + 'manager': { + 'episode_num': 100000, + 'max_retry': 1000, + 'retry_type': 'renew', + 'auto_reset': True, + 'step_timeout': None, + 'reset_timeout': None, + 'retry_waiting_time': 0.1, + 'cfg_type': 'BaseEnvManagerDict', + 'shared_memory': False, + 'return_original_data': True + }, + 'collector_env_num': 1, + 'evaluator_env_num': 1, + 'n_evaluator_episode': 100, + 'env_type': 'prisoner_dilemma', + 'stop_value': [-10.1, -5.05] + }, + 'policy': { + 'model': { + 'obs_shape': 2, + 'action_shape': 2, + 'action_space': 'discrete', + 'encoder_hidden_size_list': [32, 32], + 'critic_head_hidden_size': 32, + 'actor_head_hidden_size': 32, + 'share_encoder': False + }, + 'learn': { + 'learner': { + 'train_iterations': 1000000000, + 'dataloader': { + 'num_workers': 0 + }, + 'log_policy': False, + 'hook': { + 'load_ckpt_before_run': '', + 'log_show_after_iter': 100, + 'save_ckpt_after_iter': 10000, + 'save_ckpt_after_run': True + }, + 'cfg_type': 'BaseLearnerDict' + }, + 'multi_gpu': False, + 'epoch_per_collect': 10, + 'batch_size': 16, + 'learning_rate': 1e-05, + 'value_weight': 0.5, + 'entropy_weight': 0.0, + 'clip_ratio': 0.2, + 'adv_norm': True, + 'value_norm': True, + 'ppo_param_init': True, + 'grad_clip_type': 'clip_norm', + 'grad_clip_value': 0.5, + 'ignore_done': False, + 'update_per_collect': 3, + 'scheduler': { + 'schedule_flag': False, + 'schedule_mode': 'reduce', + 'factor': 0.005, + 'change_range': [0, 1], + 'threshold': 0.5, + 'patience': 50 + } + }, + 'collect': { + 'collector': { + 'deepcopy_obs': False, + 'transform_obs': False, + 'collect_print_freq': 100, + 'get_train_sample': True, + 'cfg_type': 'BattleEpisodeSerialCollectorDict' + }, + 'discount_factor': 1.0, + 'gae_lambda': 1.0, + 'n_episode': 1, + 'n_rollout_samples': 64, + 'n_sample': 64, + 'unroll_len': 1 + }, + 'eval': { + 'evaluator': { + 'eval_freq': 50, + 'cfg_type': 'BattleInteractionSerialEvaluatorDict', + 'stop_value': [-10.1, -5.05], + 'n_episode': 100 + } + }, + 'other': { + 'replay_buffer': { + 'type': 'naive', + 'replay_buffer_size': 10000, + 'deepcopy': False, + 'enable_track_used_data': False, + 'periodic_thruput_seconds': 60, + 'cfg_type': 'NaiveReplayBufferDict' + }, + 'league': { + 'player_category': ['default'], + 'path_policy': 'league_demo/ckpt', + 'active_players': { + 'main_player': 2 + }, + 'main_player': { + 'one_phase_step': 10, # 20 + 'branch_probs': { + 'pfsp': 0.0, + 'sp': 1.0 + }, + 'strong_win_rate': 0.7 + }, + 'main_exploiter': { + 'one_phase_step': 200, + 'branch_probs': { + 'main_players': 1.0 + }, + 'strong_win_rate': 0.7, + 'min_valid_win_rate': 0.3 + }, + 'league_exploiter': { + 'one_phase_step': 200, + 'branch_probs': { + 'pfsp': 1.0 + }, + 'strong_win_rate': 0.7, + 'mutate_prob': 0.5 + }, + 'use_pretrain': False, + 'use_pretrain_init_historical': False, + 'payoff': { + 'type': 'battle', + 'decay': 0.99, + 'min_win_rate_games': 8 + }, + 'metric': { + 'mu': 0, + 'sigma': 8.333333333333334, + 'beta': 4.166666666666667, + 'tau': 0.0, + 'draw_probability': 0.02 + } + } + }, + 'type': 'ppo', + 'cuda': False, + 'on_policy': True, + 'priority': False, + 'priority_IS_weight': False, + 'recompute_adv': True, + 'action_space': 'discrete', + 'nstep_return': False, + 'multi_agent': False, + 'transition_with_policy_data': True, + 'cfg_type': 'PPOPolicyDict' + }, + 'exp_name': 'league_demo', + 'seed': 0 + } +) diff --git a/ding/framework/middleware/tests/test_league_actor.py b/ding/framework/middleware/tests/test_league_actor.py index 6d5416a554..c1c9823707 100644 --- a/ding/framework/middleware/tests/test_league_actor.py +++ b/ding/framework/middleware/tests/test_league_actor.py @@ -4,7 +4,7 @@ from ding.envs import BaseEnvManager from ding.framework.context import BattleContext from ding.framework.middleware.league_learner import LearnerModel -from ding.framework.middleware.tests.league_config import cfg +from ding.framework.middleware.tests.mock_for_test import league_cfg from ding.framework.middleware import LeagueActor, StepLeagueActor from ding.framework.middleware.functional import ActorData from ding.league.player import PlayerMeta diff --git a/ding/framework/middleware/tests/test_league_learner_communicator.py b/ding/framework/middleware/tests/test_league_learner_communicator.py new file mode 100644 index 0000000000..d2c4f5cfa4 --- /dev/null +++ b/ding/framework/middleware/tests/test_league_learner_communicator.py @@ -0,0 +1,135 @@ +from copy import deepcopy +from dataclasses import dataclass +from time import sleep +import time +import pytest +import logging +from typing import Any +from unittest.mock import patch +from typing import Callable, Optional + +from ding.framework.context import BattleContext +from ding.framework import EventEnum +from ding.framework.task import task, Parallel +from ding.framework.middleware import LeagueLearnerCommunicator, LearnerModel +from ding.framework.middleware.functional.actor_data import * +from ding.framework.middleware.tests.mock_for_test import league_cfg + +from ding.model import VAC +from ding.policy.ppo import PPOPolicy + +PLAYER_ID = "test_player" + +def prepare_test(): + global league_cfg + cfg = deepcopy(league_cfg) + + def policy_fn(): + model = VAC(**cfg.policy.model) + policy = PPOPolicy(cfg.policy, model=model) + return policy + + return cfg, policy_fn + + +@dataclass +class TestActorData: + env_step: int + train_data: Any + + +class MockFileStorage: + + def __init__(self, path: str) -> None: + self.path = path + + def save(self, data: Any) -> bool: + assert isinstance(data, dict) + + +class MockPlayer: + + def __init__(self) -> None: + self.player_id = PLAYER_ID + self.total_agent_step = 0 + + def is_trained_enough(self) -> bool: + return True + + +def coordinator_mocker(): + + test_cases = { + "on_learner_meta": False + } + + def on_learner_meta(player_meta): + assert player_meta.player_id == PLAYER_ID + test_cases["on_learner_meta"] = True + + + task.on(EventEnum.LEARNER_SEND_META.format(player=PLAYER_ID), on_learner_meta) + + def _coordinator_mocker(ctx): + sleep(0.8) + assert all(test_cases.values()) + + return _coordinator_mocker + + +def actor_mocker(): + + test_cases = { + "on_learner_model": False + } + + def on_learner_model(learner_model): + assert isinstance(learner_model, LearnerModel) + assert learner_model.player_id == PLAYER_ID + test_cases["on_learner_model"] = True + + task.on(EventEnum.LEARNER_SEND_MODEL.format(player=PLAYER_ID), on_learner_model) + + def _actor_mocker(ctx): + sleep(0.2) + player = MockPlayer() + for _ in range(10): + meta = ActorDataMeta(player_total_env_step=0, actor_id=0, send_wall_time=time.time()) + data = [] + actor_data = ActorData(meta=meta, train_data=[ActorEnvTrajectories(env_id=0, trajectories=[data])]) + task.emit(EventEnum.ACTOR_SEND_DATA.format(player=player.player_id), actor_data) + + sleep(0.8) + assert all(test_cases.values()) + + return _actor_mocker + + +def _main(): + logging.getLogger().setLevel(logging.INFO) + cfg, policy_fn = prepare_test() + + with task.start(async_mode=False, ctx=BattleContext()): + if task.router.node_id == 0: + task.use(coordinator_mocker()) + elif task.router.node_id <= 1: + task.use(actor_mocker()) + else: + player = MockPlayer() + policy = policy_fn() + with patch("ding.framework.storage.FileStorage", MockFileStorage): + learner_communicator = LeagueLearnerCommunicator(cfg, policy.learn_mode, player) + sleep(0.5) + assert len(learner_communicator._cache) == 10 + task.use(learner_communicator) + sleep(0.1) + task.run(max_step=1) + + +@pytest.mark.unittest +def test_league_learner(): + Parallel.runner(n_parallel_workers=3, protocol="tcp", topology="mesh")(_main) + + +if __name__ == '__main__': + Parallel.runner(n_parallel_workers=3, protocol="tcp", topology="mesh")(_main) From 30e6249002bca333def4f9018efc901a99f0b44d Mon Sep 17 00:00:00 2001 From: zhumengshen Date: Thu, 25 Aug 2022 21:08:13 +0000 Subject: [PATCH 212/229] change a bit --- ding/framework/middleware/__init__.py | 2 +- .../{league_learner.py => league_learner_communicator.py} | 5 ----- .../middleware/tests/test_league_learner_communicator.py | 4 ---- 3 files changed, 1 insertion(+), 10 deletions(-) rename ding/framework/middleware/{league_learner.py => league_learner_communicator.py} (88%) diff --git a/ding/framework/middleware/__init__.py b/ding/framework/middleware/__init__.py index f2a68c64bf..12484568c6 100644 --- a/ding/framework/middleware/__init__.py +++ b/ding/framework/middleware/__init__.py @@ -4,4 +4,4 @@ from .ckpt_handler import CkptSaver from .league_actor import StepLeagueActor from .league_coordinator import LeagueCoordinator -from .league_learner import * +from .league_learner_communicator import LeagueLearnerCommunicator, LearnerModel diff --git a/ding/framework/middleware/league_learner.py b/ding/framework/middleware/league_learner_communicator.py similarity index 88% rename from ding/framework/middleware/league_learner.py rename to ding/framework/middleware/league_learner_communicator.py index c9c5cb7654..1e437bfd74 100644 --- a/ding/framework/middleware/league_learner.py +++ b/ding/framework/middleware/league_learner_communicator.py @@ -45,13 +45,8 @@ def _push_data(self, data: "ActorData"): for env_trajectories in data.train_data: for traj in env_trajectories.trajectories: self._cache.append(traj) - # if isinstance(data.train_data, list): - # self._cache.extend(data.train_data) - # else: - # self._cache.append(data.train_data) def __call__(self, ctx: "BattleContext"): - # log_every_sec(logging.INFO, 5, "[Learner {}] pour data into the ctx".format(task.router.node_id)) ctx.trajectories = list(self._cache) self._cache.clear() sleep(0.0001) diff --git a/ding/framework/middleware/tests/test_league_learner_communicator.py b/ding/framework/middleware/tests/test_league_learner_communicator.py index d2c4f5cfa4..6399ad09a4 100644 --- a/ding/framework/middleware/tests/test_league_learner_communicator.py +++ b/ding/framework/middleware/tests/test_league_learner_communicator.py @@ -129,7 +129,3 @@ def _main(): @pytest.mark.unittest def test_league_learner(): Parallel.runner(n_parallel_workers=3, protocol="tcp", topology="mesh")(_main) - - -if __name__ == '__main__': - Parallel.runner(n_parallel_workers=3, protocol="tcp", topology="mesh")(_main) From 9dc8770a9af2df92b6bd149cc3d6a11e266cbd38 Mon Sep 17 00:00:00 2001 From: zhumengshen Date: Thu, 25 Aug 2022 21:09:43 +0000 Subject: [PATCH 213/229] change file name --- ding/framework/middleware/league_actor.py | 2 +- ding/framework/middleware/tests/test_league_actor.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 02a202c709..cc080ddf1d 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -17,7 +17,7 @@ if TYPE_CHECKING: from ding.league.v2.base_league import Job from ding.framework import BattleContext - from ding.framework.middleware.league_learner import LearnerModel + from ding.framework.middleware.league_learner_communicator import LearnerModel class StepLeagueActor: diff --git a/ding/framework/middleware/tests/test_league_actor.py b/ding/framework/middleware/tests/test_league_actor.py index c1c9823707..71d4b53425 100644 --- a/ding/framework/middleware/tests/test_league_actor.py +++ b/ding/framework/middleware/tests/test_league_actor.py @@ -3,7 +3,7 @@ from copy import deepcopy from ding.envs import BaseEnvManager from ding.framework.context import BattleContext -from ding.framework.middleware.league_learner import LearnerModel +from ding.framework.middleware.league_learner_communicator import LearnerModel from ding.framework.middleware.tests.mock_for_test import league_cfg from ding.framework.middleware import LeagueActor, StepLeagueActor from ding.framework.middleware.functional import ActorData From 117ae79cdc79b335b919ee3e7ca98b2bc0c8bfe4 Mon Sep 17 00:00:00 2001 From: zhumengshen Date: Thu, 25 Aug 2022 21:58:02 +0000 Subject: [PATCH 214/229] update test_handle_step_exception.py --- .../tests/test_handle_step_exception.py | 31 +++++++++++++------ 1 file changed, 21 insertions(+), 10 deletions(-) diff --git a/ding/framework/middleware/tests/test_handle_step_exception.py b/ding/framework/middleware/tests/test_handle_step_exception.py index 0ebbd460fc..7466e27b9b 100644 --- a/ding/framework/middleware/tests/test_handle_step_exception.py +++ b/ding/framework/middleware/tests/test_handle_step_exception.py @@ -1,37 +1,48 @@ from ding.framework.context import BattleContext -from ding.framework.middleware.functional.collector import TransitionList -from ding.framework.middleware.tests import battle_rolloutor_for_distar +from ding.framework.middleware.functional.collector import BattleTransitionList +from ding.framework.middleware.functional import battle_rolloutor_for_distar import pytest from unittest.mock import Mock from ding.envs import BaseEnvTimestep from easydict import EasyDict -class MockEnvManager(Mock): +class MockEnvManager: + + def __init__(self) -> None: + self.ready_obs = [[[]]] def step(self, actions): timesteps = {} for env_id in actions.keys(): - timesteps[env_id] = BaseEnvTimestep(obs=[1], reward=[1, 1], done=False, info={'step_error': True}) + timesteps[env_id] = BaseEnvTimestep(obs=[1], reward=[1, 1], done=False, info={'abnormal': True}) return timesteps +class MockPolicy: + + def __init__(self) -> None: + pass + + def reset(self, data): + pass + + @pytest.mark.unittest def test_handle_step_exception(): ctx = BattleContext() ctx.total_envstep_count = 10 ctx.env_step = 20 - transitions_list = [TransitionList(env_num=2)] + transitions_list = [BattleTransitionList(env_num=2, unroll_len=5)] + ctx.current_policies = [MockPolicy()] for _ in range(5): transitions_list[0].append(env_id=0, transition=BaseEnvTimestep(obs=[1], reward=[1, 1], done=False, info={})) transitions_list[0].append(env_id=1, transition=BaseEnvTimestep(obs=[1], reward=[1, 1], done=False, info={})) ctx.actions = {0: {}} ctx.obs = {0: {0: {}}} - rolloutor = battle_rolloutor_for_distar(cfg=EasyDict(), env=MockEnvManager(), transitions_list=transitions_list) + rolloutor = battle_rolloutor_for_distar(cfg=EasyDict(), env=MockEnvManager(), transitions_list=transitions_list, model_info_dict=None) rolloutor(ctx) - assert ctx.total_envstep_count == 5 - assert ctx.env_step == 15 - assert transitions_list[0].length(0) == 0 - assert transitions_list[0].length(1) == 5 + assert len(transitions_list[0]._transitions[0]) == 0 + assert len(transitions_list[0]._transitions[1]) == 1 From f66248dee1d6ecb3d927c89830adf4f077e57ffa Mon Sep 17 00:00:00 2001 From: zhumengshen Date: Thu, 25 Aug 2022 22:22:20 +0000 Subject: [PATCH 215/229] update test of BattleTransitionList, and add last_step_fn in BattleTransitionList, make battle_rolloutor_for_distar run in dict and list cases --- .../middleware/tests/test_collector.py | 19 +++++++------------ 1 file changed, 7 insertions(+), 12 deletions(-) diff --git a/ding/framework/middleware/tests/test_collector.py b/ding/framework/middleware/tests/test_collector.py index 6d231afa09..81cd1db608 100644 --- a/ding/framework/middleware/tests/test_collector.py +++ b/ding/framework/middleware/tests/test_collector.py @@ -89,8 +89,7 @@ def test_episode_collector(): assert len(ctx.episodes) == 16 -@pytest.mark.unittest -def test_battle_transition_list(): +def test_battle_transition(): env_num = 2 unroll_len = 32 transition_list = BattleTransitionList(env_num, unroll_len) @@ -182,17 +181,13 @@ def test_battle_transition_list(): assert transition.obs == i i += 1 - # print(env_0_result) - # print(env_1_result) - # print(transition_list._transitions[0]) - # print(transition_list._transitions[1]) - - transition_list_2.clear_newest_episode(env_id=0) - transition_list_2.clear_newest_episode(env_id=1) - + transition_list_2.clear_newest_episode(env_id=0, before_append=True) + transition_list_2.clear_newest_episode(env_id=1, before_append=True) assert len(transition_list_2._transitions[0]) == 2 assert len(transition_list_2._transitions[1]) == 1 -if __name__ == '__main__': - test_battle_transition_list() \ No newline at end of file +@pytest.mark.unittest +def test_battle_transition_list(): + with task.start(): + test_battle_transition() From 8cf4a820a1402dbfc1f6af1920037f946e8ce367 Mon Sep 17 00:00:00 2001 From: zhumengshen Date: Fri, 26 Aug 2022 06:31:50 +0000 Subject: [PATCH 216/229] uupdate tests; actor, collector, functional collector --- ding/framework/middleware/collector.py | 320 +++++++----------- .../middleware/functional/__init__.py | 2 +- .../middleware/functional/collector.py | 126 ++----- ding/framework/middleware/league_actor.py | 186 +--------- .../tests/test_handle_step_exception.py | 4 +- .../middleware/tests/test_league_actor.py | 12 +- .../tests/test_league_coordinator.py | 3 + .../tests/test_league_learner_communicator.py | 2 +- 8 files changed, 165 insertions(+), 490 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 02ed30d403..b2f1494cca 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -14,6 +14,110 @@ if TYPE_CHECKING: from ding.framework import OnlineRLContext, BattleContext + +class StepCollector: + """ + Overview: + The class of the collector running by steps, including model inference and transition \ + process. Use the `__call__` method to execute the whole collection process. + """ + + def __init__(self, cfg: EasyDict, policy, env: BaseEnvManager, random_collect_size: int = 0) -> None: + """ + Arguments: + - cfg (:obj:`EasyDict`): Config. + - policy (:obj:`Policy`): The policy to be collected. + - env (:obj:`BaseEnvManager`): The env for the collection, the BaseEnvManager object or \ + its derivatives are supported. + - random_collect_size (:obj:`int`): The count of samples that will be collected randomly, \ + typically used in initial runs. + """ + self.cfg = cfg + self.env = env + self.policy = policy + self.random_collect_size = random_collect_size + self._transitions = TransitionList(self.env.env_num) + self._inferencer = task.wrap(inferencer(cfg, policy, env)) + self._rolloutor = task.wrap(rolloutor(cfg, policy, env, self._transitions)) + + def __call__(self, ctx: "OnlineRLContext") -> None: + """ + Overview: + An encapsulation of inference and rollout middleware. Stop when completing \ + the target number of steps. + Input of ctx: + - env_step (:obj:`int`): The env steps which will increase during collection. + """ + old = ctx.env_step + if self.random_collect_size > 0 and old < self.random_collect_size: + target_size = self.random_collect_size - old + random_policy = get_random_policy(self.cfg, self.policy, self.env) + current_inferencer = task.wrap(inferencer(self.cfg, random_policy, self.env)) + else: + # compatible with old config, a train sample = unroll_len step + target_size = self.cfg.policy.collect.n_sample * self.cfg.policy.collect.unroll_len + current_inferencer = self._inferencer + + while True: + current_inferencer(ctx) + self._rolloutor(ctx) + if ctx.env_step - old >= target_size: + ctx.trajectories, ctx.trajectory_end_idx = self._transitions.to_trajectories() + self._transitions.clear() + break + + +class EpisodeCollector: + """ + Overview: + The class of the collector running by episodes, including model inference and transition \ + process. Use the `__call__` method to execute the whole collection process. + """ + + def __init__(self, cfg: EasyDict, policy, env: BaseEnvManager, random_collect_size: int = 0) -> None: + """ + Arguments: + - cfg (:obj:`EasyDict`): Config. + - policy (:obj:`Policy`): The policy to be collected. + - env (:obj:`BaseEnvManager`): The env for the collection, the BaseEnvManager object or \ + its derivatives are supported. + - random_collect_size (:obj:`int`): The count of samples that will be collected randomly, \ + typically used in initial runs. + """ + self.cfg = cfg + self.env = env + self.policy = policy + self.random_collect_size = random_collect_size + self._transitions = TransitionList(self.env.env_num) + self._inferencer = task.wrap(inferencer(cfg, policy, env)) + self._rolloutor = task.wrap(rolloutor(cfg, policy, env, self._transitions)) + + def __call__(self, ctx: "OnlineRLContext") -> None: + """ + Overview: + An encapsulation of inference and rollout middleware. Stop when completing the \ + target number of episodes. + Input of ctx: + - env_episode (:obj:`int`): The env env_episode which will increase during collection. + """ + old = ctx.env_episode + if self.random_collect_size > 0 and old < self.random_collect_size: + target_size = self.random_collect_size - old + random_policy = get_random_policy(self.cfg, self.policy, self.env) + current_inferencer = task.wrap(inferencer(self.cfg, random_policy, self.env)) + else: + target_size = self.cfg.policy.collect.n_episode + current_inferencer = self._inferencer + + while True: + current_inferencer(ctx) + self._rolloutor(ctx) + if ctx.env_episode - old >= target_size: + ctx.episodes = self._transitions.to_episodes() + self._transitions.clear() + break + + WAIT_MODEL_TIME = float('inf') @@ -57,7 +161,8 @@ def __del__(self) -> None: def _update_policies(self, player_id_set) -> None: for player_id in player_id_set: - # for this player, in the beginning of actor's lifetime, actor didn't recieve any new model, use initial model instead. + # for this player, if in the beginning of actor's lifetime, + # actor didn't recieve any new model, use initial model instead. if self.model_info_dict.get(player_id) is None: self.model_info_dict[player_id] = PlayerModelInfo( get_new_model_time=time.time(), update_new_model_time=None @@ -73,7 +178,6 @@ def _update_policies(self, player_id_set) -> None: if any(x >= WAIT_MODEL_TIME for x in time_list): for index, player_id in enumerate(update_player_id_set): if time_list[index] >= WAIT_MODEL_TIME: - #TODO: log_every_sec can only print the first model that not updated log_every_sec( logging.WARNING, 5, 'In actor {}, model for {} is not updated for {} senconds, and need new model'.format( @@ -98,36 +202,19 @@ def _update_policies(self, player_id_set) -> None: self.model_dict[player_id] = None def __call__(self, ctx: "BattleContext") -> None: - """ - Input of ctx: - - n_episode (:obj:`int`): the number of collecting data episode - - train_iter (:obj:`int`): the number of training iteration - - collect_kwargs (:obj:`dict`): the keyword args for policy forward - Output of ctx: - - ctx.train_data (:obj:`Tuple[List, List]`): A tuple with training sample(data) and episode info, \ - the former is a list containing collected episodes if not get_train_sample, \ - otherwise, return train_samples split by unroll_len. - """ + ctx.total_envstep_count = self.total_envstep_count old = ctx.env_step while True: if self.env.closed: self.env.launch() - # TODO(zms): only runnable when 1 actor has exactly one env, need to write more general - for policy_id, policy in enumerate(ctx.current_policies): - policy.reset(self.env.ready_obs[0][policy_id]) - self._update_policies(set(ctx.player_id_list)) - try: - self._battle_inferencer(ctx) - self._battle_rolloutor(ctx) - except Exception as e: - # TODO(zms): need to handle the exception cleaner - logging.error("[Actor {}] got an exception: {} when collect data".format(task.router.node_id, e)) - self.env.close() for env_id in range(self.env_num): - for policy_id, policy in enumerate(ctx.current_policies): - self._transitions_list[policy_id].clear_newest_episode(env_id, before_append=True) + for policy in ctx.current_policies: + policy.reset([env_id]) + self._update_policies(set(ctx.player_id_list)) + self._battle_inferencer(ctx) + self._battle_rolloutor(ctx) self.total_envstep_count = ctx.total_envstep_count @@ -144,185 +231,4 @@ def __call__(self, ctx: "BattleContext") -> None: break -# class BattleEpisodeCollector: - -# def __init__( -# self, cfg: EasyDict, env: BaseEnvManager, n_rollout_samples: int, model_dict: Dict, player_policy_collect_dict: Dict, -# agent_num: int -# ): -# self.cfg = cfg -# self.end_flag = False -# # self._reset(env) -# self.env = env -# self.env_num = self.env.env_num - -# self.total_envstep_count = 0 -# self.n_rollout_samples = n_rollout_samples -# self.model_dict = model_dict -# self.player_policy_collect_dict = player_policy_collect_dict -# self.agent_num = agent_num - -# self._battle_inferencer = task.wrap(battle_inferencer(self.cfg, self.env)) -# self._transitions_list = [TransitionList(self.env.env_num) for _ in range(self.agent_num)] -# self._battle_rolloutor = task.wrap(battle_rolloutor(self.cfg, self.env, self._transitions_list)) - -# def __del__(self) -> None: -# """ -# Overview: -# Execute the close command and close the collector. __del__ is automatically called to \ -# destroy the collector instance when the collector finishes its work -# """ -# if self.end_flag: -# return -# self.end_flag = True -# self.env.close() - -# def _update_policies(self, player_id_list) -> None: -# for player_id in player_id_list: -# if self.model_dict.get(player_id) is None: -# continue -# else: -# learner_model = self.model_dict.get(player_id) -# policy = self.player_policy_collect_dict.get(player_id) -# assert policy, "for player {}, policy should have been initialized already".format(player_id) -# # update policy model -# policy.load_state_dict(learner_model.state_dict) -# self.model_dict[player_id] = None - -# def __call__(self, ctx: "BattleContext") -> None: -# """ -# Input of ctx: -# - n_episode (:obj:`int`): the number of collecting data episode -# - train_iter (:obj:`int`): the number of training iteration -# - collect_kwargs (:obj:`dict`): the keyword args for policy forward -# Output of ctx: -# - ctx.train_data (:obj:`Tuple[List, List]`): A tuple with training sample(data) and episode info, \ -# the former is a list containing collected episodes if not get_train_sample, \ -# otherwise, return train_samples split by unroll_len. -# """ -# ctx.total_envstep_count = self.total_envstep_count -# old = ctx.env_episode -# while True: -# if self.env.closed: -# self.env.launch() -# self._update_policies(ctx.player_id_list) -# self._battle_inferencer(ctx) -# self._battle_rolloutor(ctx) - -# self.total_envstep_count = ctx.total_envstep_count - -# if (self.n_rollout_samples > 0 -# and ctx.env_episode - old >= self.n_rollout_samples) or ctx.env_episode >= ctx.n_episode: -# for transitions in self._transitions_list: -# ctx.episodes.append(transitions.to_episodes()) -# transitions.clear() -# if ctx.env_episode >= ctx.n_episode: -# self.env.close() -# ctx.job_finish = True -# break - - -class StepCollector: - """ - Overview: - The class of the collector running by steps, including model inference and transition \ - process. Use the `__call__` method to execute the whole collection process. - """ - - def __init__(self, cfg: EasyDict, policy, env: BaseEnvManager, random_collect_size: int = 0) -> None: - """ - Arguments: - - cfg (:obj:`EasyDict`): Config. - - policy (:obj:`Policy`): The policy to be collected. - - env (:obj:`BaseEnvManager`): The env for the collection, the BaseEnvManager object or \ - its derivatives are supported. - - random_collect_size (:obj:`int`): The count of samples that will be collected randomly, \ - typically used in initial runs. - """ - self.cfg = cfg - self.env = env - self.policy = policy - self.random_collect_size = random_collect_size - self._transitions = TransitionList(self.env.env_num) - self._inferencer = task.wrap(inferencer(cfg, policy, env)) - self._rolloutor = task.wrap(rolloutor(cfg, policy, env, self._transitions)) - - def __call__(self, ctx: "OnlineRLContext") -> None: - """ - Overview: - An encapsulation of inference and rollout middleware. Stop when completing \ - the target number of steps. - Input of ctx: - - env_step (:obj:`int`): The env steps which will increase during collection. - """ - old = ctx.env_step - if self.random_collect_size > 0 and old < self.random_collect_size: - target_size = self.random_collect_size - old - random_policy = get_random_policy(self.cfg, self.policy, self.env) - current_inferencer = task.wrap(inferencer(self.cfg, random_policy, self.env)) - else: - # compatible with old config, a train sample = unroll_len step - target_size = self.cfg.policy.collect.n_sample * self.cfg.policy.collect.unroll_len - current_inferencer = self._inferencer - - while True: - current_inferencer(ctx) - self._rolloutor(ctx) - if ctx.env_step - old >= target_size: - ctx.trajectories, ctx.trajectory_end_idx = self._transitions.to_trajectories() - self._transitions.clear() - break - - -class EpisodeCollector: - """ - Overview: - The class of the collector running by episodes, including model inference and transition \ - process. Use the `__call__` method to execute the whole collection process. - """ - - def __init__(self, cfg: EasyDict, policy, env: BaseEnvManager, random_collect_size: int = 0) -> None: - """ - Arguments: - - cfg (:obj:`EasyDict`): Config. - - policy (:obj:`Policy`): The policy to be collected. - - env (:obj:`BaseEnvManager`): The env for the collection, the BaseEnvManager object or \ - its derivatives are supported. - - random_collect_size (:obj:`int`): The count of samples that will be collected randomly, \ - typically used in initial runs. - """ - self.cfg = cfg - self.env = env - self.policy = policy - self.random_collect_size = random_collect_size - self._transitions = TransitionList(self.env.env_num) - self._inferencer = task.wrap(inferencer(cfg, policy, env)) - self._rolloutor = task.wrap(rolloutor(cfg, policy, env, self._transitions)) - - def __call__(self, ctx: "OnlineRLContext") -> None: - """ - Overview: - An encapsulation of inference and rollout middleware. Stop when completing the \ - target number of episodes. - Input of ctx: - - env_episode (:obj:`int`): The env env_episode which will increase during collection. - """ - old = ctx.env_episode - if self.random_collect_size > 0 and old < self.random_collect_size: - target_size = self.random_collect_size - old - random_policy = get_random_policy(self.cfg, self.policy, self.env) - current_inferencer = task.wrap(inferencer(self.cfg, random_policy, self.env)) - else: - target_size = self.cfg.policy.collect.n_episode - current_inferencer = self._inferencer - - while True: - current_inferencer(ctx) - self._rolloutor(ctx) - if ctx.env_episode - old >= target_size: - ctx.episodes = self._transitions.to_episodes() - self._transitions.clear() - break - - -# TODO battle collector +# TODO BattleEpisodeCollector diff --git a/ding/framework/middleware/functional/__init__.py b/ding/framework/middleware/functional/__init__.py index c67dec4777..d3e124d2c3 100644 --- a/ding/framework/middleware/functional/__init__.py +++ b/ding/framework/middleware/functional/__init__.py @@ -2,7 +2,7 @@ from .data_processor import offpolicy_data_fetcher, data_pusher, offline_data_fetcher, offline_data_saver, \ sqil_data_pusher from .collector import inferencer, rolloutor, TransitionList, BattleTransitionList, \ - battle_inferencer, battle_rolloutor, battle_inferencer_for_distar, battle_rolloutor_for_distar + battle_inferencer, battle_rolloutor from .evaluator import interaction_evaluator from .termination_checker import termination_checker from .ctx_helper import final_ctx_saver diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index da13c4a7af..aa9570e2ce 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -56,13 +56,14 @@ def clear(self): class BattleTransitionList: - def __init__(self, env_num: int, unroll_len: int) -> None: + def __init__(self, env_num: int, unroll_len: int, last_step_fn: Callable = None) -> None: # for each env, we have a deque to buffer episodes, # and a deque to tell each episode is finished or not self.env_num = env_num self._transitions = [deque() for _ in range(env_num)] self._done_episode = [deque() for _ in range(env_num)] self._unroll_len = unroll_len + self._last_step_fn = last_step_fn # TODO(zms): last transition + 1 def get_env_trajectories(self, env_id: int, only_finished: bool = False) -> List[List]: @@ -110,11 +111,10 @@ def _cut_trajectory_from_episode(self, episode: list) -> List[List]: num_complele_trajectory, num_tail_transitions = divmod(len(episode), self._unroll_len) for i in range(num_complele_trajectory): trajectory = episode[i * self._unroll_len:(i + 1) * self._unroll_len] - # TODO(zms): 测试专用，之后去掉 - last_step = deepcopy(trajectory[-1]) - for k in ['mask', 'action_info', 'teacher_logit', 'behaviour_logp', 'selected_units_num', 'reward', 'step']: - last_step.pop(k) - trajectory.append(last_step) + if self._last_step_fn: + last_step = deepcopy(trajectory[-1]) + last_step = self._last_step_fn(last_step) + trajectory.append(last_step) return_episode.append(trajectory) if num_tail_transitions > 0: @@ -124,11 +124,10 @@ def _cut_trajectory_from_episode(self, episode: list) -> List[List]: for _ in range(self._unroll_len - len(trajectory)): initial_elements.append(trajectory[0]) trajectory = initial_elements + trajectory - # TODO(zms): 测试专用，之后去掉 - last_step = deepcopy(trajectory[-1]) - for k in ['mask', 'action_info', 'teacher_logit', 'behaviour_logp', 'selected_units_num', 'reward', 'step']: - last_step.pop(k) - trajectory.append(last_step) + if self._last_step_fn: + last_step = deepcopy(trajectory[-1]) + last_step = self._last_step_fn(last_step) + trajectory.append(last_step) return_episode.append(trajectory) return return_episode # list of trajectories @@ -267,11 +266,6 @@ def battle_inferencer(cfg: EasyDict, env: BaseEnvManager): def _battle_inferencer(ctx: "BattleContext"): # Get current env obs. obs = env.ready_obs - # the role of remain_episode is to mask necessary rollouts, avoid processing unnecessary data - # new_available_env_id = set(obs.keys()).difference(ctx.ready_env_id) - # ctx.ready_env_id = ctx.ready_env_id.union(set(list(new_available_env_id)[:ctx.remain_episode])) - # ctx.remain_episode -= min(len(new_available_env_id), ctx.remain_episode) - # obs = {env_id: obs[env_id] for env_id in ctx.ready_env_id} # Policy forward. if cfg.transform_obs: @@ -297,7 +291,21 @@ def _battle_rolloutor(ctx: "BattleContext"): timesteps = env.step(ctx.actions) ctx.total_envstep_count += len(timesteps) ctx.env_step += len(timesteps) + + if isinstance(timesteps, list): + new_time_steps = {} + for env_id, timestep in enumerate(timesteps): + new_time_steps[env_id] = timestep + timesteps = new_time_steps + for env_id, timestep in timesteps.items(): + if isinstance(timestep.info, dict) and timestep.info.get('abnormal'): + for policy_id, policy in enumerate(ctx.current_policies): + transitions_list[policy_id].clear_newest_episode(env_id, before_append=True) + policy.reset([env_id]) + continue + + episode_long_enough = True for policy_id, policy in enumerate(ctx.current_policies): policy_timestep_data = [d[policy_id] if not isinstance(d, bool) else d for d in timestep] policy_timestep = type(timestep)(*policy_timestep_data) @@ -308,92 +316,12 @@ def _battle_rolloutor(ctx: "BattleContext"): transition.collect_train_iter = ttorch.as_tensor( [model_info_dict[ctx.player_id_list[policy_id]].update_train_iter] ) - transitions_list[policy_id].append(env_id, transition) - if timestep.done: - policy.reset([env_id]) - ctx.episode_info[policy_id].append(timestep.info[policy_id]) - - if timestep.done: - # ctx.ready_env_id.remove(env_id) - ctx.env_episode += 1 - - return _battle_rolloutor - - -def battle_inferencer_for_distar(cfg: EasyDict, env: BaseEnvManager): - - def _battle_inferencer(ctx: "BattleContext"): - # Get current env obs. - obs = env.ready_obs - assert isinstance(obs, dict) - - ctx.obs = obs - - # Policy forward. - inference_output = {} - actions = {} - for env_id in ctx.obs.keys(): - observations = obs[env_id] - inference_output[env_id] = {} - actions[env_id] = {} - for policy_id, policy_obs in observations.items(): - # policy.forward - output = ctx.current_policies[policy_id].forward(policy_obs) - inference_output[env_id][policy_id] = output - actions[env_id][policy_id] = output['action'] - ctx.inference_output = inference_output - ctx.actions = actions - - return _battle_inferencer - - -def battle_rolloutor_for_distar(cfg: EasyDict, env: BaseEnvManager, transitions_list: List, model_info_dict: Dict): - - def _battle_rolloutor(ctx: "BattleContext"): - timesteps = env.step(ctx.actions) - - ctx.total_envstep_count += len(timesteps) - ctx.env_step += len(timesteps) - - # for env_id, timestep in timesteps.items(): - # TODO(zms): make sure a standard - # If for each step, the env manager can't get the obs of all envs, we need to use dict here. - for env_id, timestep in enumerate(timesteps): - if timestep.info.get('abnormal'): - # TODO(zms): cannot get exact env_step of a episode because for each observation, - # in most cases only one of two policies has a obs. - # ctx.total_envstep_count -= transitions_list[0].length(env_id) - # ctx.env_step -= transitions_list[0].length(env_id) - - # 1st case when env step has bug and need to reset. - - # TODO(zms): if it is first step of the episode, do not delete the last episode in the TransitionList - for policy_id, policy in enumerate(ctx.current_policies): - transitions_list[policy_id].clear_newest_episode(env_id, before_append=True) - policy.reset(env.ready_obs[0][policy_id]) - continue - - episode_long_enough = True - for policy_id, policy in enumerate(ctx.current_policies): - if timestep.obs.get(policy_id): - policy_timestep = BaseEnvTimestep( - obs=timestep.obs.get(policy_id), - reward=timestep.reward[policy_id], - done=timestep.done, - info=timestep.info[policy_id] - ) - transition = policy.process_transition(obs=None, model_output=None, timestep=policy_timestep) - transition = EasyDict(transition) - transition.collect_train_iter = ttorch.as_tensor( - [model_info_dict[ctx.player_id_list[policy_id]].update_train_iter] - ) - - # 2nd case when the number of transitions in one of all the episodes is shorter than unroll_len - episode_long_enough = episode_long_enough and transitions_list[policy_id].append(env_id, transition) + + episode_long_enough = episode_long_enough and transitions_list[policy_id].append(env_id, transition) if timestep.done: for policy_id, policy in enumerate(ctx.current_policies): - policy.reset(env.ready_obs[0][policy_id]) + policy.reset([env_id]) ctx.episode_info[policy_id].append(timestep.info[policy_id]) if not episode_long_enough: diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index cc080ddf1d..f582ed9a03 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -39,17 +39,12 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.model_dict = {} self.model_dict_lock = Lock() self.model_info_dict = {} + self.agent_num = 2 self.traj_num = 0 self.total_time = 0 self.total_episode_num = 0 - self.agent_num = 2 - - self.collect_time = {} - - # self._gae_estimator = gae_estimator(cfg, policy_fn().collect_mode) - def _on_learner_model(self, learner_model: "LearnerModel"): """ If get newest learner model, put it inside model_queue. @@ -85,7 +80,6 @@ def _get_collector(self, player_id: str): ) ) self._collectors[player_id] = collector - self.collect_time[player_id] = 0 return collector def _get_policy(self, player: "PlayerMeta", duplicate: bool = False) -> "Policy.collect_function": @@ -99,9 +93,10 @@ def _get_policy(self, player: "PlayerMeta", duplicate: bool = False) -> "Policy. player_policy = self.player_policy_dict.get(player_id) duplicate_policy: "Policy.collect_function" = self.policy_fn() del duplicate_policy._collect_model - del duplicate_policy.teacher_model duplicate_policy._collect_model = player_policy._collect_model - duplicate_policy.teacher_model = player_policy.teacher_model + if getattr(player_policy, 'teacher_model') and getattr(duplicate_policy, 'teacher_model'): + del duplicate_policy.teacher_model + duplicate_policy.teacher_model = player_policy.teacher_model return duplicate_policy.collect_mode else: policy: "Policy.collect_function" = self.policy_fn() @@ -109,12 +104,9 @@ def _get_policy(self, player: "PlayerMeta", duplicate: bool = False) -> "Policy. policy_collect_mode = policy.collect_mode self.player_policy_collect_dict[player_id] = policy_collect_mode + # TODO(zms): not only historical players, but also other players should + # update the policies to the checkpoint in job if "historical" in player.player_id: - print( - '[Actor {}] recieved historical player {}, checkpoint.path is {}'.format( - task.router.node_id, player.player_id, player.checkpoint.path - ) - ) policy_collect_mode.load_state_dict(player.checkpoint.load()) return policy_collect_mode @@ -143,16 +135,10 @@ def _get_current_policies(self, job): current_policies.append(self._get_policy(player, duplicate=True)) if player.player_id == job.launch_player: main_player = player - assert main_player, "[Actor {}] can not find active player.".format(task.router.node_id) - - if current_policies is not None: - #TODO(zms): make it more general, should we have the restriction of 1 policies - # assert len(current_policies) > 1, "[Actor {}] battle collector needs more than 1 policies".format( - # task.router.node_id - # ) - pass - else: - raise RuntimeError('[Actor {}] current_policies should not be None'.format(task.router.node_id)) + assert main_player, "[Actor {}] cannot find active player.".format(task.router.node_id) + assert current_policies, "[Actor {}] current_policies should not be None".format( + task.router.node_id + ) return main_player, current_policies @@ -165,13 +151,13 @@ def __call__(self, ctx: "BattleContext"): log_every_sec( logging.INFO, 5, '[Actor {}] job of player {} begins.'.format(task.router.node_id, job.launch_player) ) - # TODO(zms): when get job, update the policies to the checkpoint in job + ctx.player_id_list = [player.player_id for player in job.players] main_player_idx = [idx for idx, player in enumerate(job.players) if player.player_id == job.launch_player] self.agent_num = len(job.players) collector = self._get_collector(job.launch_player) - main_player, ctx.current_policies = self._get_current_policies(job) + _, ctx.current_policies = self._get_current_policies(job) ctx.n_episode = self.cfg.policy.collect.n_episode assert ctx.n_episode >= self.env_num, "[Actor {}] Please make sure n_episode >= env_num".format( @@ -185,7 +171,6 @@ def __call__(self, ctx: "BattleContext"): while True: time_begin = time.time() - old_envstep = ctx.total_envstep_count collector(ctx) if ctx.job_finish is True: @@ -216,11 +201,6 @@ def __call__(self, ctx: "BattleContext"): ) ) - self.collect_time[job.launch_player] += time_end - time_begin - total_collect_speed = ctx.total_envstep_count / self.collect_time[job.launch_player] if self.collect_time[ - job.launch_player] != 0 else 0 - envstep_passed = ctx.total_envstep_count - old_envstep - real_time_speed = envstep_passed / (time_end - time_begin) gc.collect() if ctx.job_finish is True: @@ -232,6 +212,7 @@ def __call__(self, ctx: "BattleContext"): ctx.episode_info = [[] for _ in range(self.agent_num)] logging.info('[Actor {}] job finish, send job\n'.format(task.router.node_id)) break + self.total_episode_num += ctx.env_episode logging.info( '[Actor {}] finish {} episodes till now, speed is {} episode/s'.format( @@ -244,143 +225,4 @@ def __call__(self, ctx: "BattleContext"): ) ) - -# class LeagueActor: - -# def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): -# self.cfg = cfg -# self.env_fn = env_fn -# self.env_num = env_fn().env_num -# self.policy_fn = policy_fn -# self.n_rollout_samples = self.cfg.policy.collect.n_rollout_samples -# self._collectors: Dict[str, BattleEpisodeCollector] = {} -# self.player_policy_collect_dict: Dict[str, "Policy.collect_function"] = {} -# task.on(EventEnum.COORDINATOR_DISPATCH_ACTOR_JOB.format(actor_id=task.router.node_id), self._on_league_job) -# task.on(EventEnum.LEARNER_SEND_MODEL, self._on_learner_model) -# self.job_queue = queue.Queue() -# self.model_dict = {} -# self.model_dict_lock = Lock() - -# self.agent_num = 2 -# self.collect_time = {} - -# def _on_learner_model(self, learner_model: "LearnerModel"): -# """ -# If get newest learner model, put it inside model_queue. -# """ -# log_every_sec(logging.INFO, 5, "[Actor {}] receive model from learner \n".format(task.router.node_id)) -# with self.model_dict_lock: -# self.model_dict[learner_model.player_id] = learner_model - -# def _on_league_job(self, job: "Job"): -# """ -# Deal with job distributed by coordinator, put it inside job_queue. -# """ -# self.job_queue.put(job) - -# def _get_collector(self, player_id: str): -# if self._collectors.get(player_id): -# return self._collectors.get(player_id) -# cfg = self.cfg -# env = self.env_fn() -# collector = task.wrap( -# BattleEpisodeCollector( -# cfg.policy.collect.collector, env, self.n_rollout_samples, self.model_dict, self.player_policy_collect_dict, -# self.agent_num -# ) -# ) -# self._collectors[player_id] = collector -# self.collect_time[player_id] = 0 -# return collector - -# def _get_policy(self, player: "PlayerMeta") -> "Policy.collect_function": -# player_id = player.player_id -# if self.player_policy_collect_dict.get(player_id): -# return self.player_policy_collect_dict.get(player_id) -# policy: "Policy.collect_function" = self.policy_fn().collect_mode -# self.player_policy_collect_dict[player_id] = policy -# if "historical" in player.player_id: -# policy.load_state_dict(player.checkpoint.load()) - -# return policy - -# def _get_job(self): -# if self.job_queue.empty(): -# task.emit(EventEnum.ACTOR_GREETING, task.router.node_id) -# job = None - -# try: -# job = self.job_queue.get(timeout=10) -# except queue.Empty: -# logging.warning("[Actor {}] no Job got from coordinator".format(task.router.node_id)) - -# return job - -# def _get_current_policies(self, job): -# current_policies = [] -# main_player: "PlayerMeta" = None -# for player in job.players: -# current_policies.append(self._get_policy(player)) -# if player.player_id == job.launch_player: -# main_player = player -# assert main_player, "[Actor {}] cannot find active player.".format(task.router.node_id) - -# if current_policies is not None: -# assert len(current_policies) > 1, "battle collector needs more than 1 policies" -# for p in current_policies: -# p.reset() -# else: -# raise RuntimeError('current_policies should not be None') - -# return main_player, current_policies - -# def __call__(self, ctx: "BattleContext"): - -# job = self._get_job() -# if job is None: -# return - -# ctx.player_id_list = [player.player_id for player in job.players] -# self.agent_num = len(job.players) -# collector = self._get_collector(job.launch_player) - -# main_player, ctx.current_policies = self._get_current_policies(job) - -# ctx.n_episode = self.cfg.policy.collect.n_episode -# assert ctx.n_episode >= self.env_num, "[Actor {}] Please make sure n_episode >= env_num".format( -# task.router.node_id -# ) - -# ctx.episode_info = [[] for _ in range(self.agent_num)] -# ctx.remain_episode = ctx.n_episode -# while True: -# old_envstep = ctx.total_envstep_count -# time_begin = time.time() -# collector(ctx) -# meta_data = ActorDataMeta( -# player_total_env_step=ctx.total_envstep_count, actor_id=task.router.node_id, send_wall_time=time.time() -# ) - -# if not job.is_eval and len(ctx.episodes[0]) > 0: -# actor_data = ActorData(meta=meta_data, train_data=ctx.episodes[0]) -# task.emit(EventEnum.ACTOR_SEND_DATA.format(player=job.launch_player), actor_data) -# ctx.episodes = [] -# time_end = time.time() -# self.collect_time[job.launch_player] += time_end - time_begin -# total_collect_speed = ctx.total_envstep_count / self.collect_time[job.launch_player] if self.collect_time[ -# job.launch_player] != 0 else 0 -# envstep_passed = ctx.total_envstep_count - old_envstep -# real_time_speed = envstep_passed / (time_end - time_begin) -# log_every_sec( -# logging.INFO, 5, -# '[Actor {}] total_env_step:{}, current job env_step: {}, total_collect_speed: {} env_step/s, real-time collect speed: {} env_step/s' -# .format( -# task.router.node_id, ctx.total_envstep_count, ctx.env_step, total_collect_speed, real_time_speed -# ) -# ) - -# if ctx.job_finish is True: -# job.result = [e['result'] for e in ctx.episode_info[0]] -# task.emit(EventEnum.ACTOR_FINISH_JOB, job) -# ctx.episode_info = [[] for _ in range(self.agent_num)] -# break +#TODO: EpisodeLeagueActor \ No newline at end of file diff --git a/ding/framework/middleware/tests/test_handle_step_exception.py b/ding/framework/middleware/tests/test_handle_step_exception.py index 7466e27b9b..3cf3bc12d6 100644 --- a/ding/framework/middleware/tests/test_handle_step_exception.py +++ b/ding/framework/middleware/tests/test_handle_step_exception.py @@ -1,6 +1,6 @@ from ding.framework.context import BattleContext from ding.framework.middleware.functional.collector import BattleTransitionList -from ding.framework.middleware.functional import battle_rolloutor_for_distar +from ding.framework.middleware.functional import battle_rolloutor import pytest from unittest.mock import Mock from ding.envs import BaseEnvTimestep @@ -41,7 +41,7 @@ def test_handle_step_exception(): ctx.actions = {0: {}} ctx.obs = {0: {0: {}}} - rolloutor = battle_rolloutor_for_distar(cfg=EasyDict(), env=MockEnvManager(), transitions_list=transitions_list, model_info_dict=None) + rolloutor = battle_rolloutor(cfg=EasyDict(), env=MockEnvManager(), transitions_list=transitions_list, model_info_dict=None) rolloutor(ctx) assert len(transitions_list[0]._transitions[0]) == 0 diff --git a/ding/framework/middleware/tests/test_league_actor.py b/ding/framework/middleware/tests/test_league_actor.py index 71d4b53425..3cd005530c 100644 --- a/ding/framework/middleware/tests/test_league_actor.py +++ b/ding/framework/middleware/tests/test_league_actor.py @@ -5,7 +5,7 @@ from ding.framework.context import BattleContext from ding.framework.middleware.league_learner_communicator import LearnerModel from ding.framework.middleware.tests.mock_for_test import league_cfg -from ding.framework.middleware import LeagueActor, StepLeagueActor +from ding.framework.middleware import StepLeagueActor from ding.framework.middleware.functional import ActorData from ding.league.player import PlayerMeta from ding.framework.storage import FileStorage @@ -20,8 +20,8 @@ def prepare_test(): - global cfg - cfg = deepcopy(cfg) + global league_cfg + cfg = deepcopy(league_cfg) def env_fn(): env = BaseEnvManager( @@ -51,7 +51,7 @@ def _main(): ACTOR_ID = 0 with task.start(async_mode=True, ctx=BattleContext()): - league_actor = LeagueActor(cfg, env_fn, policy_fn) + league_actor = StepLeagueActor(cfg, env_fn, policy_fn) def test_actor(): testcases = { @@ -106,7 +106,3 @@ def _test_actor(ctx): @pytest.mark.unittest def test_league_actor(): Parallel.runner(n_parallel_workers=2, protocol="tcp", topology="mesh")(_main) - - -if __name__ == '__main__': - Parallel.runner(n_parallel_workers=2, protocol="tcp", topology="mesh")(_main) diff --git a/ding/framework/middleware/tests/test_league_coordinator.py b/ding/framework/middleware/tests/test_league_coordinator.py index 8abe2599df..429ebde796 100644 --- a/ding/framework/middleware/tests/test_league_coordinator.py +++ b/ding/framework/middleware/tests/test_league_coordinator.py @@ -72,3 +72,6 @@ def _main(): @pytest.mark.unittest def test_coordinator(): Parallel.runner(n_parallel_workers=4, protocol="tcp", topology="star")(_main) + +if __name__ == "__main__": + test_coordinator() diff --git a/ding/framework/middleware/tests/test_league_learner_communicator.py b/ding/framework/middleware/tests/test_league_learner_communicator.py index 6399ad09a4..f41dcb55c0 100644 --- a/ding/framework/middleware/tests/test_league_learner_communicator.py +++ b/ding/framework/middleware/tests/test_league_learner_communicator.py @@ -127,5 +127,5 @@ def _main(): @pytest.mark.unittest -def test_league_learner(): +def test_league_learner_communicator(): Parallel.runner(n_parallel_workers=3, protocol="tcp", topology="mesh")(_main) From 9af816867445e24b48503d35419e189036bb3143 Mon Sep 17 00:00:00 2001 From: zhumengshen Date: Fri, 26 Aug 2022 07:26:51 +0000 Subject: [PATCH 217/229] remove one todo --- ding/framework/middleware/functional/collector.py | 1 - 1 file changed, 1 deletion(-) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index aa9570e2ce..d19f6b1d83 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -64,7 +64,6 @@ def __init__(self, env_num: int, unroll_len: int, last_step_fn: Callable = None) self._done_episode = [deque() for _ in range(env_num)] self._unroll_len = unroll_len self._last_step_fn = last_step_fn - # TODO(zms): last transition + 1 def get_env_trajectories(self, env_id: int, only_finished: bool = False) -> List[List]: trajectories = [] From 6221024640eb1bf48ea2525d3c22ac49a25ded33 Mon Sep 17 00:00:00 2001 From: zhumengshen Date: Fri, 26 Aug 2022 07:46:54 +0000 Subject: [PATCH 218/229] reformat --- ding/framework/middleware/collector.py | 6 ++++-- .../framework/middleware/functional/collector.py | 4 ++-- ding/framework/middleware/functional/trainer.py | 1 + ding/framework/middleware/league_actor.py | 11 +++++------ ding/framework/middleware/league_coordinator.py | 2 +- .../tests/test_handle_step_exception.py | 4 +++- .../middleware/tests/test_league_coordinator.py | 1 + .../tests/test_league_learner_communicator.py | 16 ++++++---------- ding/torch_utils/network/transformer.py | 6 ++++-- 9 files changed, 27 insertions(+), 24 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index b2f1494cca..50cf496b9d 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -161,7 +161,7 @@ def __del__(self) -> None: def _update_policies(self, player_id_set) -> None: for player_id in player_id_set: - # for this player, if in the beginning of actor's lifetime, + # for this player, if in the beginning of actor's lifetime, # actor didn't recieve any new model, use initial model instead. if self.model_info_dict.get(player_id) is None: self.model_info_dict[player_id] = PlayerModelInfo( @@ -174,7 +174,9 @@ def _update_policies(self, player_id_set) -> None: update_player_id_set.add(player_id) while True: time_now = time.time() - time_list = [time_now - self.model_info_dict[player_id].get_new_model_time for player_id in update_player_id_set] + time_list = [ + time_now - self.model_info_dict[player_id].get_new_model_time for player_id in update_player_id_set + ] if any(x >= WAIT_MODEL_TIME for x in time_list): for index, player_id in enumerate(update_player_id_set): if time_list[index] >= WAIT_MODEL_TIME: diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index d19f6b1d83..dfa8e58018 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -303,7 +303,7 @@ def _battle_rolloutor(ctx: "BattleContext"): transitions_list[policy_id].clear_newest_episode(env_id, before_append=True) policy.reset([env_id]) continue - + episode_long_enough = True for policy_id, policy in enumerate(ctx.current_policies): policy_timestep_data = [d[policy_id] if not isinstance(d, bool) else d for d in timestep] @@ -315,7 +315,7 @@ def _battle_rolloutor(ctx: "BattleContext"): transition.collect_train_iter = ttorch.as_tensor( [model_info_dict[ctx.player_id_list[policy_id]].update_train_iter] ) - + episode_long_enough = episode_long_enough and transitions_list[policy_id].append(env_id, transition) if timestep.done: diff --git a/ding/framework/middleware/functional/trainer.py b/ding/framework/middleware/functional/trainer.py index a54c9c0a83..2965a6dcaf 100644 --- a/ding/framework/middleware/functional/trainer.py +++ b/ding/framework/middleware/functional/trainer.py @@ -8,6 +8,7 @@ if TYPE_CHECKING: from ding.framework import OnlineRLContext, OfflineRLContext, BattleContext + def trainer(cfg: EasyDict, policy: Policy) -> Callable: """ Overview: diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index f582ed9a03..61afb03583 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -136,9 +136,7 @@ def _get_current_policies(self, job): if player.player_id == job.launch_player: main_player = player assert main_player, "[Actor {}] cannot find active player.".format(task.router.node_id) - assert current_policies, "[Actor {}] current_policies should not be None".format( - task.router.node_id - ) + assert current_policies, "[Actor {}] current_policies should not be None".format(task.router.node_id) return main_player, current_policies @@ -151,7 +149,7 @@ def __call__(self, ctx: "BattleContext"): log_every_sec( logging.INFO, 5, '[Actor {}] job of player {} begins.'.format(task.router.node_id, job.launch_player) ) - + ctx.player_id_list = [player.player_id for player in job.players] main_player_idx = [idx for idx, player in enumerate(job.players) if player.player_id == job.launch_player] self.agent_num = len(job.players) @@ -212,7 +210,7 @@ def __call__(self, ctx: "BattleContext"): ctx.episode_info = [[] for _ in range(self.agent_num)] logging.info('[Actor {}] job finish, send job\n'.format(task.router.node_id)) break - + self.total_episode_num += ctx.env_episode logging.info( '[Actor {}] finish {} episodes till now, speed is {} episode/s'.format( @@ -225,4 +223,5 @@ def __call__(self, ctx: "BattleContext"): ) ) -#TODO: EpisodeLeagueActor \ No newline at end of file + +#TODO: EpisodeLeagueActor diff --git a/ding/framework/middleware/league_coordinator.py b/ding/framework/middleware/league_coordinator.py index 95b5ada20b..d4a9f1e4d1 100644 --- a/ding/framework/middleware/league_coordinator.py +++ b/ding/framework/middleware/league_coordinator.py @@ -63,7 +63,7 @@ def _on_actor_job(self, job: "Job"): self._last_collect_time = time() if self._total_collect_time is None: self._total_collect_time = 0 - + self._total_recv_jobs += 1 old_time = self._last_collect_time self._last_collect_time = time() diff --git a/ding/framework/middleware/tests/test_handle_step_exception.py b/ding/framework/middleware/tests/test_handle_step_exception.py index 3cf3bc12d6..240f280be4 100644 --- a/ding/framework/middleware/tests/test_handle_step_exception.py +++ b/ding/framework/middleware/tests/test_handle_step_exception.py @@ -41,7 +41,9 @@ def test_handle_step_exception(): ctx.actions = {0: {}} ctx.obs = {0: {0: {}}} - rolloutor = battle_rolloutor(cfg=EasyDict(), env=MockEnvManager(), transitions_list=transitions_list, model_info_dict=None) + rolloutor = battle_rolloutor( + cfg=EasyDict(), env=MockEnvManager(), transitions_list=transitions_list, model_info_dict=None + ) rolloutor(ctx) assert len(transitions_list[0]._transitions[0]) == 0 diff --git a/ding/framework/middleware/tests/test_league_coordinator.py b/ding/framework/middleware/tests/test_league_coordinator.py index 429ebde796..ceb34770ad 100644 --- a/ding/framework/middleware/tests/test_league_coordinator.py +++ b/ding/framework/middleware/tests/test_league_coordinator.py @@ -73,5 +73,6 @@ def _main(): def test_coordinator(): Parallel.runner(n_parallel_workers=4, protocol="tcp", topology="star")(_main) + if __name__ == "__main__": test_coordinator() diff --git a/ding/framework/middleware/tests/test_league_learner_communicator.py b/ding/framework/middleware/tests/test_league_learner_communicator.py index f41dcb55c0..56b5b07d28 100644 --- a/ding/framework/middleware/tests/test_league_learner_communicator.py +++ b/ding/framework/middleware/tests/test_league_learner_communicator.py @@ -20,6 +20,7 @@ PLAYER_ID = "test_player" + def prepare_test(): global league_cfg cfg = deepcopy(league_cfg) @@ -42,7 +43,7 @@ class MockFileStorage: def __init__(self, path: str) -> None: self.path = path - + def save(self, data: Any) -> bool: assert isinstance(data, dict) @@ -59,15 +60,12 @@ def is_trained_enough(self) -> bool: def coordinator_mocker(): - test_cases = { - "on_learner_meta": False - } + test_cases = {"on_learner_meta": False} def on_learner_meta(player_meta): assert player_meta.player_id == PLAYER_ID test_cases["on_learner_meta"] = True - task.on(EventEnum.LEARNER_SEND_META.format(player=PLAYER_ID), on_learner_meta) def _coordinator_mocker(ctx): @@ -79,15 +77,13 @@ def _coordinator_mocker(ctx): def actor_mocker(): - test_cases = { - "on_learner_model": False - } + test_cases = {"on_learner_model": False} def on_learner_model(learner_model): assert isinstance(learner_model, LearnerModel) assert learner_model.player_id == PLAYER_ID test_cases["on_learner_model"] = True - + task.on(EventEnum.LEARNER_SEND_MODEL.format(player=PLAYER_ID), on_learner_model) def _actor_mocker(ctx): @@ -98,7 +94,7 @@ def _actor_mocker(ctx): data = [] actor_data = ActorData(meta=meta, train_data=[ActorEnvTrajectories(env_id=0, trajectories=[data])]) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=player.player_id), actor_data) - + sleep(0.8) assert all(test_cases.values()) diff --git a/ding/torch_utils/network/transformer.py b/ding/torch_utils/network/transformer.py index 49e0a67a2f..f7f31653c9 100644 --- a/ding/torch_utils/network/transformer.py +++ b/ding/torch_utils/network/transformer.py @@ -169,7 +169,7 @@ def __init__( layer_num: int = 3, dropout_ratio: float = 0., activation: nn.Module = nn.ReLU(), - ln_type = 'pre' + ln_type='pre' ): r""" Overview: @@ -193,7 +193,9 @@ def __init__( self.dropout = nn.Dropout(dropout_ratio) for i in range(layer_num): layers.append( - TransformerLayer(dims[i], head_dim, hidden_dim, dims[i + 1], head_num, mlp_num, self.dropout, self.act, ln_type) + TransformerLayer( + dims[i], head_dim, hidden_dim, dims[i + 1], head_num, mlp_num, self.dropout, self.act, ln_type + ) ) self.main = nn.Sequential(*layers) From 16281d9068d05aeb68e5e6b8bfcff56d19eddb05 Mon Sep 17 00:00:00 2001 From: zhumengshen Date: Fri, 26 Aug 2022 08:19:42 +0000 Subject: [PATCH 219/229] reformat --- ding/framework/middleware/functional/collector.py | 12 +++++++----- ding/framework/middleware/league_coordinator.py | 3 ++- ding/framework/middleware/tests/test_collector.py | 1 - .../tests/test_league_learner_communicator.py | 2 +- ding/league/player.py | 2 +- ding/rl_utils/__init__.py | 1 - ding/torch_utils/network/nn_module.py | 1 - 7 files changed, 11 insertions(+), 11 deletions(-) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index dfa8e58018..d4918a2f6f 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -102,9 +102,10 @@ def to_trajectories(self, only_finished: bool = False) -> List[ActorEnvTrajector def _cut_trajectory_from_episode(self, episode: list) -> List[List]: # first we cut complete trajectories (list of transitions whose length equal to unroll_len) - # then we gather the transitions in the tail of episode, and fill up the trajectory with the tail transitions in Trajectory(t-1) - # If we don't have Trajectory(t-1), i.e. the length of the whole episode is smaller than unroll_len, we fill up the trajectory - # with the first element of episode. + # then we gather the transitions in the tail of episode, + # and fill up the trajectory with the tail transitions in Trajectory(t-1) + # If we don't have Trajectory(t-1), i.e. the length of the whole episode is smaller than unroll_len, + # we fill up the trajectory with the first element of episode. return_episode = [] i = 0 num_complele_trajectory, num_tail_transitions = divmod(len(episode), self._unroll_len) @@ -137,7 +138,7 @@ def clear_newest_episode(self, env_id: int, before_append=False) -> None: # If call this method before append, and the last episode of this env is done, # it means that the env had some error at the first step of the newest episode, # and we should not delete the last episode because it is a normal episode. - if before_append == True and len(self._done_episode[env_id]) > 0 and self._done_episode[env_id][-1] == True: + if before_append is True and len(self._done_episode[env_id]) > 0 and self._done_episode[env_id][-1] == True: return 0 if len(self._transitions[env_id]) > 0: newest_episode = self._transitions[env_id].pop() @@ -158,7 +159,8 @@ def append(self, env_id: int, transition: Any) -> bool: self._done_episode[env_id][-1] = True if len(self._transitions[env_id][-1]) < self._unroll_len: logging.warning( - 'The length of the newest finished episode in node {}, env {}, is {}, which is shorter than unroll_len: {}, and need to be dropped' + 'The length of the newest finished episode in node {}, env {}, is {}, '\ + 'which is shorter than unroll_len: {}, and need to be dropped' .format(task.router.node_id, env_id, len(self._transitions[env_id][-1]), self._unroll_len) ) return False diff --git a/ding/framework/middleware/league_coordinator.py b/ding/framework/middleware/league_coordinator.py index d4a9f1e4d1..206aff2a01 100644 --- a/ding/framework/middleware/league_coordinator.py +++ b/ding/framework/middleware/league_coordinator.py @@ -69,7 +69,8 @@ def _on_actor_job(self, job: "Job"): self._last_collect_time = time() self._total_collect_time += self._last_collect_time - old_time logging.info( - "[Coordinator {}] recieve actor finished job, player {}, recieve {} jobs in total, collect job speed is {} s/job" + "[Coordinator {}] recieve finished job of player {}, "\ + "recieve {} jobs in total, collect job speed is {} s/job" .format( task.router.node_id, job.launch_player, self._total_recv_jobs, self._total_collect_time / self._total_recv_jobs diff --git a/ding/framework/middleware/tests/test_collector.py b/ding/framework/middleware/tests/test_collector.py index 81cd1db608..bfb1eaf9e0 100644 --- a/ding/framework/middleware/tests/test_collector.py +++ b/ding/framework/middleware/tests/test_collector.py @@ -8,7 +8,6 @@ from ding.framework.middleware.tests import MockPolicy, MockEnv, CONFIG from ding.framework.middleware import BattleTransitionList from easydict import EasyDict -import copy @pytest.mark.unittest diff --git a/ding/framework/middleware/tests/test_league_learner_communicator.py b/ding/framework/middleware/tests/test_league_learner_communicator.py index 56b5b07d28..7769f91cc3 100644 --- a/ding/framework/middleware/tests/test_league_learner_communicator.py +++ b/ding/framework/middleware/tests/test_league_learner_communicator.py @@ -12,7 +12,7 @@ from ding.framework import EventEnum from ding.framework.task import task, Parallel from ding.framework.middleware import LeagueLearnerCommunicator, LearnerModel -from ding.framework.middleware.functional.actor_data import * +from ding.framework.middleware.functional.actor_data import ActorData, ActorDataMeta, ActorEnvTrajectories from ding.framework.middleware.tests.mock_for_test import league_cfg from ding.model import VAC diff --git a/ding/league/player.py b/ding/league/player.py index 61b1916a9a..7e2e031be2 100644 --- a/ding/league/player.py +++ b/ding/league/player.py @@ -369,4 +369,4 @@ def create_player(cfg: EasyDict, player_type: str, *args, **kwargs) -> Player: player_mapping's values """ import_module(cfg.get('import_names', [])) - return PLAYER_REGISTRY.build(player_type, *args, **kwargs) \ No newline at end of file + return PLAYER_REGISTRY.build(player_type, *args, **kwargs) diff --git a/ding/rl_utils/__init__.py b/ding/rl_utils/__init__.py index f0eb990a52..673ce2da19 100644 --- a/ding/rl_utils/__init__.py +++ b/ding/rl_utils/__init__.py @@ -12,7 +12,6 @@ fqf_nstep_td_data, fqf_nstep_td_error, fqf_calculate_fraction_loss, evaluate_quantile_at_action, \ q_nstep_sql_td_error, dqfd_nstep_td_error, dqfd_nstep_td_data, q_v_1step_td_error, q_v_1step_td_data,\ dqfd_nstep_td_error_with_rescale, discount_cumsum -from .vtrace import vtrace_loss, compute_importance_weights from .upgo import upgo_data, upgo_error from .adder import get_gae, get_gae_with_default_last_value, get_nstep_return_data, get_train_sample from .value_rescale import value_transform, value_inv_transform diff --git a/ding/torch_utils/network/nn_module.py b/ding/torch_utils/network/nn_module.py index 833262a697..719607d3ed 100644 --- a/ding/torch_utils/network/nn_module.py +++ b/ding/torch_utils/network/nn_module.py @@ -4,7 +4,6 @@ import torch.nn as nn import torch.nn.functional as F from torch.nn.init import xavier_normal_, kaiming_normal_, orthogonal_ -from typing import Union, Tuple, List, Callable from ding.compatibility import torch_ge_131 from .normalization import build_normalization From fb83c8e4ec5716c9ae80c35d926e72d4707bd026 Mon Sep 17 00:00:00 2001 From: zhumengshen Date: Fri, 26 Aug 2022 08:37:51 +0000 Subject: [PATCH 220/229] fix bug --- ding/framework/middleware/league_coordinator.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ding/framework/middleware/league_coordinator.py b/ding/framework/middleware/league_coordinator.py index 206aff2a01..209de2f267 100644 --- a/ding/framework/middleware/league_coordinator.py +++ b/ding/framework/middleware/league_coordinator.py @@ -69,7 +69,7 @@ def _on_actor_job(self, job: "Job"): self._last_collect_time = time() self._total_collect_time += self._last_collect_time - old_time logging.info( - "[Coordinator {}] recieve finished job of player {}, "\ + "[Coordinator {}] recieve finished job of player {}, "\ "recieve {} jobs in total, collect job speed is {} s/job" .format( task.router.node_id, job.launch_player, self._total_recv_jobs, From bc7b47785bf801d21cafa80b8121057772c10d79 Mon Sep 17 00:00:00 2001 From: zhumengshen Date: Fri, 26 Aug 2022 09:27:11 +0000 Subject: [PATCH 221/229] reformat; add last_step_fn in entry of LeagueActor and BattleStepCollector --- ding/framework/middleware/collector.py | 15 +++++++++++---- ding/framework/middleware/functional/collector.py | 4 ++-- ding/framework/middleware/league_actor.py | 5 +++-- 3 files changed, 16 insertions(+), 8 deletions(-) diff --git a/ding/framework/middleware/collector.py b/ding/framework/middleware/collector.py index 50cf496b9d..8d16000bef 100644 --- a/ding/framework/middleware/collector.py +++ b/ding/framework/middleware/collector.py @@ -1,5 +1,5 @@ from easydict import EasyDict -from typing import Dict, TYPE_CHECKING +from typing import Dict, TYPE_CHECKING, Callable import time from ditk import logging @@ -124,8 +124,15 @@ def __call__(self, ctx: "OnlineRLContext") -> None: class BattleStepCollector: def __init__( - self, cfg: EasyDict, env: BaseEnvManager, unroll_len: int, model_dict: Dict, model_info_dict: Dict, - player_policy_collect_dict: Dict, agent_num: int + self, + cfg: EasyDict, + env: BaseEnvManager, + unroll_len: int, + model_dict: Dict, + model_info_dict: Dict, + player_policy_collect_dict: Dict, + agent_num: int, + last_step_fn: Callable = None ): self.cfg = cfg self.end_flag = False @@ -142,7 +149,7 @@ def __init__( self._battle_inferencer = task.wrap(battle_inferencer(self.cfg, self.env)) self._transitions_list = [ - BattleTransitionList(self.env.env_num, self.unroll_len) for _ in range(self.agent_num) + BattleTransitionList(self.env.env_num, self.unroll_len, last_step_fn) for _ in range(self.agent_num) ] self._battle_rolloutor = task.wrap( battle_rolloutor(self.cfg, self.env, self._transitions_list, self.model_info_dict) diff --git a/ding/framework/middleware/functional/collector.py b/ding/framework/middleware/functional/collector.py index d4918a2f6f..ab59b3c02b 100644 --- a/ding/framework/middleware/functional/collector.py +++ b/ding/framework/middleware/functional/collector.py @@ -102,9 +102,9 @@ def to_trajectories(self, only_finished: bool = False) -> List[ActorEnvTrajector def _cut_trajectory_from_episode(self, episode: list) -> List[List]: # first we cut complete trajectories (list of transitions whose length equal to unroll_len) - # then we gather the transitions in the tail of episode, + # then we gather the transitions in the tail of episode, # and fill up the trajectory with the tail transitions in Trajectory(t-1) - # If we don't have Trajectory(t-1), i.e. the length of the whole episode is smaller than unroll_len, + # If we don't have Trajectory(t-1), i.e. the length of the whole episode is smaller than unroll_len, # we fill up the trajectory with the first element of episode. return_episode = [] i = 0 diff --git a/ding/framework/middleware/league_actor.py b/ding/framework/middleware/league_actor.py index 61afb03583..84b0832157 100644 --- a/ding/framework/middleware/league_actor.py +++ b/ding/framework/middleware/league_actor.py @@ -22,7 +22,7 @@ class StepLeagueActor: - def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): + def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable, last_step_fn: Callable = None): self.cfg = cfg self.env_fn = env_fn self.env_num = env_fn().env_num @@ -40,6 +40,7 @@ def __init__(self, cfg: EasyDict, env_fn: Callable, policy_fn: Callable): self.model_dict_lock = Lock() self.model_info_dict = {} self.agent_num = 2 + self.last_step_fn = last_step_fn self.traj_num = 0 self.total_time = 0 @@ -76,7 +77,7 @@ def _get_collector(self, player_id: str): collector = task.wrap( BattleStepCollector( cfg.policy.collect.collector, env, self.unroll_len, self.model_dict, self.model_info_dict, - self.player_policy_collect_dict, self.agent_num + self.player_policy_collect_dict, self.agent_num, self.last_step_fn ) ) self._collectors[player_id] = collector From 7fc8354b263bc4592f233f329418a2b2d0be69c7 Mon Sep 17 00:00:00 2001 From: zhumengshen Date: Fri, 26 Aug 2022 09:44:25 +0000 Subject: [PATCH 222/229] update tests --- ding/framework/middleware/tests/test_league_coordinator.py | 6 +----- .../middleware/tests/test_league_learner_communicator.py | 3 +-- 2 files changed, 2 insertions(+), 7 deletions(-) diff --git a/ding/framework/middleware/tests/test_league_coordinator.py b/ding/framework/middleware/tests/test_league_coordinator.py index ceb34770ad..fee2713850 100644 --- a/ding/framework/middleware/tests/test_league_coordinator.py +++ b/ding/framework/middleware/tests/test_league_coordinator.py @@ -51,7 +51,7 @@ def _main(): ) for _ in range(3): task.emit(EventEnum.ACTOR_GREETING, task.router.node_id) - time.sleep(3) + time.sleep(5) assert task.router.node_id == res[-1].actor_id elif task.router.node_id == 2: # test LEARNER_SEND_META @@ -72,7 +72,3 @@ def _main(): @pytest.mark.unittest def test_coordinator(): Parallel.runner(n_parallel_workers=4, protocol="tcp", topology="star")(_main) - - -if __name__ == "__main__": - test_coordinator() diff --git a/ding/framework/middleware/tests/test_league_learner_communicator.py b/ding/framework/middleware/tests/test_league_learner_communicator.py index 7769f91cc3..7207eb3c14 100644 --- a/ding/framework/middleware/tests/test_league_learner_communicator.py +++ b/ding/framework/middleware/tests/test_league_learner_communicator.py @@ -116,10 +116,9 @@ def _main(): with patch("ding.framework.storage.FileStorage", MockFileStorage): learner_communicator = LeagueLearnerCommunicator(cfg, policy.learn_mode, player) sleep(0.5) - assert len(learner_communicator._cache) == 10 task.use(learner_communicator) sleep(0.1) - task.run(max_step=1) + task.run(max_step=5) @pytest.mark.unittest From 3e0121395b92491360bb912a9ac3724645281985 Mon Sep 17 00:00:00 2001 From: zhumengshen Date: Fri, 2 Sep 2022 08:42:32 +0000 Subject: [PATCH 223/229] delete useless files --- ding/rl_utils/steve.py | 74 ------------------------------------- ding/rl_utils/test_steve.py | 42 --------------------- 2 files changed, 116 deletions(-) delete mode 100644 ding/rl_utils/steve.py delete mode 100644 ding/rl_utils/test_steve.py diff --git a/ding/rl_utils/steve.py b/ding/rl_utils/steve.py deleted file mode 100644 index 23077bda63..0000000000 --- a/ding/rl_utils/steve.py +++ /dev/null @@ -1,74 +0,0 @@ -from typing import List, Callable -import torch - - -def steve_target( - obs, reward, done, q_fn, rew_fn, policy_fn, transition_fn, done_fn, rollout_step, discount_factor, ensemble_num -) -> torch.Tensor: - """ - Shapes: - - obs (:obj:`torch.Tensor`): :math:`(B, N1)`, where N1 is obs shape - - reward (:obj:`torch.Tensor`): :math:`(B, )` - - done (:obj:`torch.Tensor`): :math:`(B, )` - - return_ (:obj:`torch.Tensor`): :math:`(B, )` - """ - # tile first data - ensemble_q_num, ensemble_r_num, ensemble_d_num = ensemble_num - obs = obs.unsqueeze(1).repeat(1, ensemble_q_num, 1) - reward = reward.unsqueeze(1).repeat(1, ensemble_r_num) - done = done.unsqueeze(1).repeat(1, ensemble_d_num) - - with torch.no_grad(): - device = reward.device - # real data - action = policy_fn(obs) - q_value = q_fn(obs, action) - q_list, r_list, d_list = [q_value], [reward], [done] - # imagination data - for i in range(rollout_step): - next_obs = transition_fn(obs, action) - reward = rew_fn(obs, action, next_obs) - done = done_fn(obs, action, next_obs) - obs = next_obs - action = policy_fn(obs) - q_value = q_fn(obs, action) - - q_list.append(q_value) - r_list.append(reward) - d_list.append(done) - - q_value = torch.stack(q_list, dim=1) # B, H, M - reward = torch.stack(r_list, dim=1) # B, H, N - done = torch.stack(d_list, dim=1) # B, H, L - - H = rollout_step + 1 - - time_factor = torch.full((1, H), discount_factor).to(device) ** torch.arange(float(H)) - upper_tri = torch.triu(torch.randn(H, H)).to(device) - reward_coeff = (upper_tri * time_factor).unsqueeze(0).unsqueeze(-1).unsqueeze(-1) # 1, H, H, 1, 1 - value_coeff = (time_factor ** discount_factor).unsqueeze(-1).unsqueeze(-1) # 1, H, 1, 1 - - # (B, 1, L) cat (B, H-1, L) - reward_done = torch.cat([torch.ones_like(done[:, 0]).unsqueeze(1), torch.cumprod(done[:, :-1], dim=1)], dim=1) - reward_done = reward_done.unsqueeze(1).unsqueeze(-2) - value_done = done.unsqueeze(-2) - - # (B, 1, H, N, 1) x (1, H, H, 1, 1) x (B, 1, H, 1, L) - reward = reward.unsqueeze(1).unsqueeze(-1) * reward_coeff * reward_done - # (B, H, N, L) - cum_reward = torch.sum(reward, dim=2) # sum in the second H - # (B, H, M, 1) x (1, H, 1, 1) x (B, H, 1, L) = B, H, M, L - q_value = q_value.unsqueeze(-1) * value_coeff * value_done - # (B, H, 1, N, L) + (B, H, M, 1, L) = B, H, M, N, L - target = cum_reward.unsqueeze(-3) + q_value.unsqueeze(-2) - - target = target.view(target.shape[0], H, -1) # B, H, MxNxL - target_mean = target.mean(-1) - target_var = target.var(-1) - target_confidence = 1. / (target_var + 1e-8) # B, H - target_confidence = torch.clamp(target_confidence, 0, 100) # for some special case - # norm - target_confidence /= target_confidence.sum(dim=1, keepdim=True) - - return_ = (target_mean * target_confidence).sum(dim=1) - return return_ diff --git a/ding/rl_utils/test_steve.py b/ding/rl_utils/test_steve.py deleted file mode 100644 index acfa74f7d0..0000000000 --- a/ding/rl_utils/test_steve.py +++ /dev/null @@ -1,42 +0,0 @@ -import pytest -import torch -from .steve import steve_target - - -@pytest.mark.unittest -def test_steve_target(): - B = 2 - M, N, L = 3, 4, 5 - obs_tplus1 = torch.randn(B, 16) - reward_t = torch.randn(B, ) - done_t = torch.randint(0, 2, size=(B, )).float() - - def q_fn(obs, action): - return torch.randn(obs.shape[0], M) - - def rew_fn(obs, action, next_obs): - return torch.randn(obs.shape[0], N) - - def policy_fn(obs): - return torch.randn(obs.shape[0], ) - - def transition_fn(obs, action): - return torch.randn(obs.shape[0], L, obs.shape[1]) - - def done_fn(obs, action, next_obs): - return torch.randint(0, 2, size=(obs.shape[0], L)).float() - - return_ = steve_target( - obs_tplus1, - reward_t, - done_t, - q_fn, - rew_fn, - policy_fn, - transition_fn, - done_fn, - rollout_step=6, - discount_factor=0.99, - ensemble_num=(M, N, L) - ) - assert return_.shape == (B, ) From 0a8be2e5815806be08aa407f4541bb6881244cd5 Mon Sep 17 00:00:00 2001 From: zhumengshen <744762298@qq.com> Date: Thu, 22 Sep 2022 07:49:49 +0000 Subject: [PATCH 224/229] add unittest of flatten and detach_grad --- ding/torch_utils/tests/test_data_helper.py | 36 +++++++++++++++++++++- 1 file changed, 35 insertions(+), 1 deletion(-) diff --git a/ding/torch_utils/tests/test_data_helper.py b/ding/torch_utils/tests/test_data_helper.py index 218ce59ba7..11ba45184c 100644 --- a/ding/torch_utils/tests/test_data_helper.py +++ b/ding/torch_utils/tests/test_data_helper.py @@ -6,7 +6,7 @@ from torch.utils.data import DataLoader from ding.torch_utils import CudaFetcher, to_device, to_dtype, to_tensor, to_ndarray, to_list, \ - tensor_to_list, same_shape, build_log_buffer, get_tensor_data + tensor_to_list, same_shape, build_log_buffer, get_tensor_data, detach_grad, flatten from ding.utils import EasyTimer @@ -217,3 +217,37 @@ def test_to_device_cpu(setup_data_dict): other = EasyTimer() with pytest.raises(TypeError): to_device(other) + + +@pytest.mark.unittest +def test_detach_grad(): + tensor_list = [torch.tensor(1., requires_grad=True) for _ in range(4)] + tensor_dict = {'a': torch.tensor(1., requires_grad=True), 'b': torch.tensor(2., requires_grad=True)} + assert all(t.requires_grad is True for t in tensor_list) + assert all(t.requires_grad is True for _, t in tensor_dict.items()) + tensor_list = detach_grad(tensor_list) + tensor_dict = detach_grad(tensor_dict) + assert all(t.requires_grad is False for t in tensor_list) + assert all(t.requires_grad is False for _, t in tensor_dict.items()) + + with pytest.raises(TypeError): + detach_grad(1) + + +@pytest.mark.unittest +def test_flatten(): + + def test_tensor(): + return torch.tensor([[[1, 2], [3, 4]], [[5, 6], [7, 8]]]) + + tensor_list = [test_tensor() for _ in range(4)] + tensor_dict = {'a': test_tensor(), 'b': test_tensor()} + assert all(t.shape == torch.Size([2, 2, 2]) for t in tensor_list) + assert all(t.shape == torch.Size([2, 2, 2]) for _, t in tensor_dict.items()) + tensor_list = flatten(tensor_list) + tensor_dict = flatten(tensor_dict) + assert all(t.shape == torch.Size([4, 2]) for t in tensor_list) + assert all(t.shape == torch.Size([4, 2]) for t in tensor_list) + + with pytest.raises(TypeError): + flatten(1) From b3d39f9247645d023764bfffdaf7f8cf3742eb8b Mon Sep 17 00:00:00 2001 From: zhumengshen <744762298@qq.com> Date: Thu, 22 Sep 2022 11:09:13 +0000 Subject: [PATCH 225/229] add comments about the difference between GLU2 and GLU --- ding/torch_utils/network/activation.py | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/ding/torch_utils/network/activation.py b/ding/torch_utils/network/activation.py index c1a9110758..b6a6517e25 100644 --- a/ding/torch_utils/network/activation.py +++ b/ding/torch_utils/network/activation.py @@ -95,6 +95,12 @@ def build_activation(activation: str, inplace: bool = None) -> nn.Module: class GLU2(nn.Module): + r""" + Overview: + Gating Linear Unit different from GLU defined above, + Which uses fc_block instead of nn.Linear if input_type is 'fc', + and uses conv2d_block instead of nn.Conv2d if input_type is 'conv2d' + """ def __init__(self, input_dim, output_dim, context_dim, input_type='fc'): super(GLU2, self).__init__() From 4f09857375ada4094d13bb5178354a92023e6551 Mon Sep 17 00:00:00 2001 From: zhumengshen <744762298@qq.com> Date: Fri, 23 Sep 2022 03:26:06 +0000 Subject: [PATCH 226/229] add unittest of parameter "dim" in default_collate; remove dim from cat because it is useless --- ding/utils/data/collate_fn.py | 3 +-- ding/utils/data/tests/test_collate_fn.py | 10 ++++++++++ 2 files changed, 11 insertions(+), 2 deletions(-) diff --git a/ding/utils/data/collate_fn.py b/ding/utils/data/collate_fn.py index 27262d7a5c..7f27b38491 100644 --- a/ding/utils/data/collate_fn.py +++ b/ding/utils/data/collate_fn.py @@ -84,8 +84,7 @@ def default_collate( out = elem.new(storage) if elem.shape == (1, ) and cat_1dim: # reshape (B, 1) -> (B) - return torch.cat(batch, dim, out=out) - # return torch.stack(batch, 0, out=out) + return torch.cat(batch, 0, out=out) else: return torch.stack(batch, dim, out=out) elif isinstance(elem, ttorch.Tensor): diff --git a/ding/utils/data/tests/test_collate_fn.py b/ding/utils/data/tests/test_collate_fn.py index 83611377c1..f4a1246813 100644 --- a/ding/utils/data/tests/test_collate_fn.py +++ b/ding/utils/data/tests/test_collate_fn.py @@ -104,6 +104,16 @@ def test_basic(self): data = default_collate(data) assert isinstance(data, dict) assert len(data['collate_ignore_data']) == 4 + + def test_dim_attirbute(self): + def test_tensor(): + return torch.tensor([[[1, 2], [3, 4]], [[5, 6], [7, 8]]]) + test_batch_tensor = [test_tensor() for _ in range(4)] + assert test_batch_tensor[0].shape == torch.Size([2,2,2]) + assert default_collate(test_batch_tensor,dim=0).shape == torch.Size([4,2,2,2]) + assert default_collate(test_batch_tensor,dim=1).shape == torch.Size([2,4,2,2]) + assert default_collate(test_batch_tensor,dim=2).shape == torch.Size([2,2,4,2]) + assert default_collate(test_batch_tensor,dim=3).shape == torch.Size([2,2,2,4]) @pytest.mark.unittest From 54ea00e6c8c66cc8e45547217e0076f5b5062874 Mon Sep 17 00:00:00 2001 From: zhumengshen <744762298@qq.com> Date: Fri, 23 Sep 2022 03:26:47 +0000 Subject: [PATCH 227/229] reformat --- ding/utils/data/tests/test_collate_fn.py | 14 ++++++++------ 1 file changed, 8 insertions(+), 6 deletions(-) diff --git a/ding/utils/data/tests/test_collate_fn.py b/ding/utils/data/tests/test_collate_fn.py index f4a1246813..97b4b96bd6 100644 --- a/ding/utils/data/tests/test_collate_fn.py +++ b/ding/utils/data/tests/test_collate_fn.py @@ -104,16 +104,18 @@ def test_basic(self): data = default_collate(data) assert isinstance(data, dict) assert len(data['collate_ignore_data']) == 4 - + def test_dim_attirbute(self): + def test_tensor(): return torch.tensor([[[1, 2], [3, 4]], [[5, 6], [7, 8]]]) + test_batch_tensor = [test_tensor() for _ in range(4)] - assert test_batch_tensor[0].shape == torch.Size([2,2,2]) - assert default_collate(test_batch_tensor,dim=0).shape == torch.Size([4,2,2,2]) - assert default_collate(test_batch_tensor,dim=1).shape == torch.Size([2,4,2,2]) - assert default_collate(test_batch_tensor,dim=2).shape == torch.Size([2,2,4,2]) - assert default_collate(test_batch_tensor,dim=3).shape == torch.Size([2,2,2,4]) + assert test_batch_tensor[0].shape == torch.Size([2, 2, 2]) + assert default_collate(test_batch_tensor, dim=0).shape == torch.Size([4, 2, 2, 2]) + assert default_collate(test_batch_tensor, dim=1).shape == torch.Size([2, 4, 2, 2]) + assert default_collate(test_batch_tensor, dim=2).shape == torch.Size([2, 2, 4, 2]) + assert default_collate(test_batch_tensor, dim=3).shape == torch.Size([2, 2, 2, 4]) @pytest.mark.unittest From ef64a7e5ce61f10af1b864c1db6f8c44bdc5513e Mon Sep 17 00:00:00 2001 From: zhumengshen <744762298@qq.com> Date: Fri, 23 Sep 2022 03:29:46 +0000 Subject: [PATCH 228/229] usee pytest of test_sparse_logging --- ding/utils/tests/test_sparse_logging.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/ding/utils/tests/test_sparse_logging.py b/ding/utils/tests/test_sparse_logging.py index 83294ccaa9..47b7085157 100644 --- a/ding/utils/tests/test_sparse_logging.py +++ b/ding/utils/tests/test_sparse_logging.py @@ -3,7 +3,9 @@ import time from ding.utils import log_every_n, log_every_sec -if __name__ == "__main__": + +@pytest.mark.unittest +def test_sparse_logging(): logging.getLogger().setLevel(logging.INFO) for i in range(30): log_every_n(logging.INFO, 5, "abc_{}".format(i)) From 543f1ecbd385f511236845038846ab87ddab4975 Mon Sep 17 00:00:00 2001 From: zhumengshen <744762298@qq.com> Date: Fri, 23 Sep 2022 07:33:52 +0000 Subject: [PATCH 229/229] change format of comment of sparse_logging --- ding/utils/sparse_logging.py | 68 ++++++++++++++++++++---------------- 1 file changed, 38 insertions(+), 30 deletions(-) diff --git a/ding/utils/sparse_logging.py b/ding/utils/sparse_logging.py index cd7fb20c9a..d54f77d7c5 100644 --- a/ding/utils/sparse_logging.py +++ b/ding/utils/sparse_logging.py @@ -7,12 +7,14 @@ def _get_next_log_count_per_token(token): - """Wrapper for _log_counter_per_token. Thread-safe. - Args: - token: The token for which to look up the count. + """ + Overview: + Wrapper for _log_counter_per_token. Thread-safe. + Arguments: + - token: The token for which to look up the count. Returns: - The number of times this function has been called with - *token* as an argument (starting at 0). + - ret: The number of times this function has been called + with *token* as an argument (starting at 0). """ # Can't use a defaultdict because defaultdict isn't atomic, whereas # setdefault is. @@ -20,16 +22,18 @@ def _get_next_log_count_per_token(token): def _seconds_have_elapsed(token, num_seconds): - """Tests if 'num_seconds' have passed since 'token' was requested. - Not strictly thread-safe - may log with the wrong frequency if called - concurrently from multiple threads. Accuracy depends on resolution of - 'timeit.default_timer()'. - Always returns True on the first call for a given 'token'. - Args: - token: The token for which to look up the count. - num_seconds: The number of seconds to test for. + """ + Overview: + Tests if 'num_seconds' have passed since 'token' was requested. + Not strictly thread-safe - may log with the wrong frequency if called + concurrently from multiple threads. Accuracy depends on resolution of + 'timeit.default_timer()'. + Always returns True on the first call for a given 'token'. + Arguments: + - token: The token for which to look up the count. + - num_seconds: The number of seconds to test for. Returns: - Whether it has been >= 'num_seconds' since 'token' was last requested. + - ret: Whether it has been >= 'num_seconds' since 'token' was last requested. """ now = timeit.default_timer() then = _log_timer_per_token.get(token, None) @@ -41,14 +45,16 @@ def _seconds_have_elapsed(token, num_seconds): def log_every_n(level, n, msg, *args): - """Logs 'msg % args' at level 'level' once per 'n' times. - Logs the 1st call, (N+1)st call, (2N+1)st call, etc. - Not threadsafe. - Args: - level: int, the absl logging level at which to log. - msg: str, the message to be logged. - n: int, the number of times this should be called before it is logged. - *args: The args to be substituted into the msg. + """ + Overview: + Logs 'msg % args' at level 'level' once per 'n' times. + Logs the 1st call, (N+1)st call, (2N+1)st call, etc. + Not threadsafe. + Arguments: + - level (:obj:`int`): the absl logging level at which to log. + - msg (:obj:`str`): the message to be logged. + - n (:obj:`int`): the number of times this should be called before it is logged. + - *args: The args to be substituted into the msg. """ count = _get_next_log_count_per_token(logging.getLogger().findCaller()) if count % n == 0: @@ -56,14 +62,16 @@ def log_every_n(level, n, msg, *args): def log_every_sec(level, n_seconds, msg, *args): - """Logs 'msg % args' at level 'level' iff 'n_seconds' elapsed since last call. - Logs the first call, logs subsequent calls if 'n' seconds have elapsed since - the last logging call from the same call site (file + line). Not thread-safe. - Args: - level: int, the absl logging level at which to log. - msg: str, the message to be logged. - n_seconds: float or int, seconds which should elapse before logging again. - *args: The args to be substituted into the msg. + """ + Overview: + Logs 'msg % args' at level 'level' iff 'n_seconds' elapsed since last call. + Logs the first call, logs subsequent calls if 'n' seconds have elapsed since + the last logging call from the same call site (file + line). Not thread-safe. + Arguments: + - level (:obj:`int`): the absl logging level at which to log. + - msg (:obj:`str`): the message to be logged. + - n_seconds (:obj:`Union[int, float]`): seconds which should elapse before logging again. + - *args: The args to be substituted into the msg. """ should_log = _seconds_have_elapsed(logging.getLogger().findCaller(), n_seconds) if should_log:

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b/ding/framework/middleware/tests/test_league_learner.py index 2a8bee0d30..1d79847dac 100644 --- a/ding/framework/middleware/tests/test_league_learner.py +++ b/ding/framework/middleware/tests/test_league_learner.py @@ -15,7 +15,7 @@ from ding.framework.middleware.functional.actor_data import * from ding.framework.middleware.tests.mock_for_test import DIStarMockPolicy from ding.league.v2 import BaseLeague -from ding.utils import run_every_s +from ding.utils import log_every_sec from dizoo.distar.config import distar_cfg from dizoo.distar.envs import fake_rl_data_batch_with_last from dizoo.distar.envs.distar_env import DIStarEnv @@ -43,8 +43,8 @@ def policy_fn(): def coordinator_mocker(): - task.on(EventEnum.LEARNER_SEND_META, lambda x: run_every_s("test:", x)) - task.on(EventEnum.LEARNER_SEND_MODEL, lambda x: run_every_s("test: send model success")) + task.on(EventEnum.LEARNER_SEND_META, lambda x: logging.info("test: {}".format(x))) + task.on(EventEnum.LEARNER_SEND_MODEL, lambda x: logging.info("test: send model success")) def _coordinator_mocker(ctx): sleep(10) @@ -63,12 +63,11 @@ def actor_mocker(league): def _actor_mocker(ctx): n_players = len(league.active_players_ids) player = league.active_players[(task.router.node_id + 2) % n_players] - run_every_s(5, "Actor: actor player:", player.player_id) + log_every_sec(logging.INFO, 5, "Actor: actor player: {}".format(player.player_id)) for _ in range(24): meta = ActorDataMeta(player_total_env_step=0, actor_id=0, send_wall_time=time.time()) data = fake_rl_data_batch_with_last() actor_data = ActorData(meta=meta, train_data=[ActorEnvTrajectories(env_id=0, trajectories=[data])]) - # actor_data = TestActorData(env_step=0, train_data=data) task.emit(EventEnum.ACTOR_SEND_DATA.format(player=player.player_id), actor_data) sleep(9) @@ -76,7 +75,7 @@ def _actor_mocker(ctx): def _main(): - logging.getLogger().setLevel(logging.DEBUG) + logging.getLogger().setLevel(logging.INFO) cfg, env_fn, policy_fn = prepare_test() league = BaseLeague(cfg.policy.other.league) n_players = len(league.active_players_ids) diff --git a/ding/utils/data/collate_fn.py b/ding/utils/data/collate_fn.py index dd41637016..a6c61f8d1b 100644 --- a/ding/utils/data/collate_fn.py +++ b/ding/utils/data/collate_fn.py @@ -7,7 +7,6 @@ from torch._six import string_classes import collections.abc as container_abcs from ding.compatibility import torch_ge_131 -from easydict import EasyDict int_classes = int np_str_obj_array_pattern = re.compile(r'[SaUO]') @@ -63,13 +62,6 @@ def default_collate( """ elem = batch[0] - # if isinstance(elem, dict): - # for key, val in elem.items(): - # if isinstance(val, torch.Tensor): - # print("{}: {}".format(key, print(val.size()))) - # elif isinstance(val, EasyDict): - # print("{}: {}".format(key, val.keys())) - elem_type = type(elem) if isinstance(batch, ttorch.Tensor): return batch.json() @@ -83,9 +75,6 @@ def default_collate( out = elem.new(storage) if elem.shape == (1, ) and cat_1dim: # reshape (B, 1) -> (B) - # print("debug:", batch) - # print("debug:", len(batch)) - # print("debug:", len(batch[0])) return torch.cat(batch, dim, out=out) # return torch.stack(batch, 0, out=out) else: diff --git a/ding/utils/log_helper.py b/ding/utils/log_helper.py index 904b0f88e7..9ba7e0cddf 100644 --- a/ding/utils/log_helper.py +++ b/ding/utils/log_helper.py @@ -1,7 +1,7 @@ import json from ditk import logging import os -from typing import Callable, Optional, Tuple, Union, Dict, Any +from typing import Optional, Tuple, Union, Dict, Any import ditk.logging import numpy as np From 723cbcc4b450e22494ce0e61f4eb3419ada99494 Mon Sep 17 00:00:00 2001 From: hiha3456 <744762298@qq.com> Date: Thu, 23 Jun 2022 19:45:42 +0800 Subject: [PATCH 158/229] remove rep --- ...81c120-f2e7-11ec-99fe-4649caa90281.SC2Replay | Bin 28538 -> 0 bytes 1 file changed, 0 insertions(+), 0 deletions(-) delete mode 100644 ding/framework/middleware/tests/2022-06-23-19/KingsCove_agent1_vs_agent2_[0, 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