Feature/release preparation (#234)

* update getting started

* update some of basic concepts

* MultiAgent -> Multiagent

* update benchmark scripts

* more doc

* fix docs build issue

* update GPU recomendation

* make experiments write cleaner names for presets

* update directory names in getting started guide

* update basic concepts

* update benchmark performance docs page and fix some typos

all/agents/_multiagent.py

@@ -27,7 +27,7 @@ def act(self, multiagent_state):
         However, the agent must ultimately return an action.
 
         Args:
-            multiagent_state (all.core.MultiAgentState): The environment state at the current timestep.
+            multiagent_state (all.core.MultiagentState): The environment state at the current timestep.
 
         Returns:
             torch.Tensor: The action for the current agent to take at the current timestep.

all/core/__init__.py

@@ -1,3 +1,3 @@
-from .state import State, StateArray, MultiAgentState
+from .state import State, StateArray, MultiagentState
 
-__all__ = ['State', 'StateArray', 'MultiAgentState']
+__all__ = ['State', 'StateArray', 'MultiagentState']

all/core/state.py

@@ -388,10 +388,10 @@ def __len__(self):
         return self.shape[0]
 
 
-class MultiAgentState(State):
+class MultiagentState(State):
     def __init__(self, x, device='cpu', **kwargs):
         if 'agent' not in x:
-            raise Exception('MultiAgentState must contain an agent ID')
+            raise Exception('MultiagentState must contain an agent ID')
         super().__init__(x, device=device, **kwargs)
 
     @property
@@ -412,7 +412,7 @@ def from_zoo(cls, agent, state, device='cpu', dtype=np.float32):
             A State object.
         """
         if not isinstance(state, tuple):
-            return MultiAgentState({
+            return MultiagentState({
                 'agent': agent,
                 'observation': torch.from_numpy(
                     np.array(
@@ -438,7 +438,7 @@ def from_zoo(cls, agent, state, device='cpu', dtype=np.float32):
         info = info if info else {}
         for key in info:
             x[key] = info[key]
-        return MultiAgentState(x, device=device)
+        return MultiagentState(x, device=device)
 
     def to(self, device):
         if device == self.device:

all/environments/multiagent_atari.py

@@ -2,7 +2,7 @@
 import numpy as np
 import torch
 import gym
-from all.core import MultiAgentState
+from all.core import MultiagentState
 from ._multiagent_environment import MultiagentEnvironment
 from .multiagent_pettingzoo import MultiagentPettingZooEnv
 

all/environments/multiagent_pettingzoo.py

@@ -3,7 +3,7 @@
 import torch
 import cloudpickle
 import gym
-from all.core import MultiAgentState
+from all.core import MultiagentState
 from ._multiagent_environment import MultiagentEnvironment
 
 
@@ -80,7 +80,7 @@ def duplicate(self, n):
     def last(self):
         observation, reward, done, info = self._env.last()
         selected_obs_space = self._env.observation_spaces[self._env.agent_selection]
-        return MultiAgentState.from_zoo(self._env.agent_selection, (observation, reward, done, info), device=self._device, dtype=selected_obs_space.dtype)
+        return MultiagentState.from_zoo(self._env.agent_selection, (observation, reward, done, info), device=self._device, dtype=selected_obs_space.dtype)
 
     @property
     def name(self):

all/experiments/multiagent_env_experiment.py

@@ -34,7 +34,7 @@ def __init__(
             write_loss=True,
             writer="tensorboard"
     ):
-        self._name = name if name is not None else preset.__class__.__name__
+        self._name = name if name is not None else preset.name
         self._writer = self._make_writer(logdir, self._name, env.name, write_loss, writer)
         self._agent = preset.agent(writer=self._writer, train_steps=train_steps)
         self._env = env

all/experiments/multiagent_env_experiment_test.py

@@ -61,7 +61,7 @@ def setUp(self):
 
     def test_adds_default_name(self):
         experiment = MockExperiment(self.make_preset(), self.env, quiet=True, save_freq=float('inf'))
-        self.assertEqual(experiment._writer.label, "IndependentMultiagentPreset_space_invaders_v1")
+        self.assertEqual(experiment._writer.label, "independent_space_invaders_v1")
 
     def test_adds_custom_name(self):
         experiment = MockExperiment(self.make_preset(), self.env, name='custom', quiet=True, save_freq=float('inf'))

all/experiments/parallel_env_experiment.py

@@ -22,7 +22,7 @@ def __init__(
             write_loss=True,
             writer="tensorboard"
     ):
-        self._name = name if name is not None else preset.__class__.__name__
+        self._name = name if name is not None else preset.name
         super().__init__(self._make_writer(logdir, self._name, env.name, write_loss, writer), quiet)
         self._n_envs = preset.n_envs
         self._envs = env.duplicate(self._n_envs)

all/experiments/parallel_env_experiment_test.py

@@ -24,7 +24,7 @@ def setUp(self):
             env.seed(i)
 
     def test_adds_default_label(self):
-        self.assertEqual(self.experiment._writer.label, "A2CClassicControlPreset_CartPole-v0")
+        self.assertEqual(self.experiment._writer.label, "a2c_CartPole-v0")
 
     def test_adds_custom_label(self):
         env = GymEnvironment('CartPole-v0')

all/experiments/single_env_experiment.py

@@ -20,7 +20,7 @@ def __init__(
             write_loss=True,
             writer="tensorboard"
     ):
-        self._name = name if name is not None else preset.__class__.__name__
+        self._name = name if name is not None else preset.name
         super().__init__(self._make_writer(logdir, self._name, env.name, write_loss, writer), quiet)
         self._logdir = logdir
         self._preset = preset

all/experiments/single_env_experiment_test.py

@@ -60,7 +60,7 @@ def setUp(self):
 
     def test_adds_default_name(self):
         experiment = MockExperiment(self.make_preset(), self.env, quiet=True)
-        self.assertEqual(experiment._writer.label, "DQNClassicControlPreset_CartPole-v0")
+        self.assertEqual(experiment._writer.label, "dqn_CartPole-v0")
 
     def test_adds_custom_name(self):
         experiment = MockExperiment(self.make_preset(), self.env, name='dqn', quiet=True)

all/experiments/writer.py

@@ -23,15 +23,10 @@ class ExperimentWriter(SummaryWriter, Writer):
 
     def __init__(self, experiment, agent_name, env_name, loss=True, logdir='runs'):
         self.env_name = env_name
-        current_time = datetime.now().strftime('%Y-%m-%d %H:%M:%S %f')
-        os.makedirs(
-            os.path.join(
-                logdir, ("%s %s %s" % (agent_name, COMMIT_HASH, current_time)), env_name
-            )
-        )
-        self.log_dir = os.path.join(
-            logdir, ("%s %s %s" % (agent_name, COMMIT_HASH, current_time))
-        )
+        current_time = datetime.now().strftime('%Y-%m-%d_%H:%M:%S_%f')
+        dir_name = "%s_%s_%s" % (agent_name, COMMIT_HASH, current_time)
+        os.makedirs(os.path.join(logdir, dir_name, env_name))
+        self.log_dir = os.path.join(logdir, dir_name)
         self._experiment = experiment
         self._loss = loss
         super().__init__(log_dir=self.log_dir)

all/nn/__init__.py

@@ -6,6 +6,10 @@
 from all.core import State
 
 
+""""A Pytorch Module"""
+Module = nn.Module
+
+
 class RLNetwork(nn.Module):
     """
     Wraps a network such that States can be given as input.

benchmarks/atari40.py

@@ -4,14 +4,13 @@
 
 
 def main():
-    device = 'cuda'
     agents = [
-        atari.a2c(device=device),
-        atari.c51(device=device),
-        atari.dqn(device=device),
-        atari.ddqn(device=device),
-        atari.ppo(device=device),
-        atari.rainbow(device=device),
+        atari.a2c,
+        atari.c51,
+        atari.dqn,
+        atari.ddqn,
+        atari.ppo,
+        atari.rainbow,
     ]
     envs = [AtariEnvironment(env, device=device) for env in ['BeamRider', 'Breakout', 'Pong', 'Qbert', 'SpaceInvaders']]
     SlurmExperiment(agents, envs, 10e6, sbatch_args={

benchmarks/pybullet.py

@@ -11,9 +11,9 @@ def main():
     frames = int(1e7)
 
     agents = [
-        ddpg(device=device),
-        ppo(device=device),
-        sac(device=device)
+        ddpg,
+        ppo,
+        sac
     ]
 
     envs = [GymEnvironment(env, device) for env in [