Merge branch 'master' into her

.pfnci/lint.sh

@@ -3,9 +3,10 @@
 set -eux
 
 # Use latest black to apply https://github.com/psf/black/issues/1288
-pip3 install git+git://github.com/psf/black.git@88d12f88a97e5e4c8fd0d245df0a311e932fd1e1 flake8 mypy
+pip3 install git+git://github.com/psf/black.git@88d12f88a97e5e4c8fd0d245df0a311e932fd1e1 flake8 mypy isort
 
 black --diff --check pfrl tests examples
+isort --diff --check pfrl tests examples
 flake8 pfrl tests examples
 mypy pfrl
 # mypy does not search child directories unless there is __init__.py

examples/atari/reproduction/a3c/train_a3c.py

@@ -8,12 +8,10 @@
 from torch import nn
 
 import pfrl
+from pfrl import experiments, utils
 from pfrl.agents import a3c
-from pfrl import experiments
-from pfrl import utils
-from pfrl.policies import SoftmaxCategoricalHead
 from pfrl.optimizers import SharedRMSpropEpsInsideSqrt
-
+from pfrl.policies import SoftmaxCategoricalHead
 from pfrl.wrappers import atari_wrappers
 
 

examples/atari/reproduction/dqn/train_dqn.py

@@ -1,21 +1,17 @@
 import argparse
+import json
 import os
 
-import torch.nn as nn
 import numpy as np
+import torch.nn as nn
 
 import pfrl
-from pfrl.q_functions import DiscreteActionValueHead
-from pfrl import agents
-from pfrl import experiments
-from pfrl import explorers
+from pfrl import agents, experiments, explorers
 from pfrl import nn as pnn
-from pfrl import utils
-from pfrl import replay_buffers
-
-from pfrl.wrappers import atari_wrappers
+from pfrl import replay_buffers, utils
 from pfrl.initializers import init_chainer_default
-import json
+from pfrl.q_functions import DiscreteActionValueHead
+from pfrl.wrappers import atari_wrappers
 
 
 def main():

examples/atari/reproduction/iqn/train_iqn.py

@@ -7,10 +7,7 @@
 from torch import nn
 
 import pfrl
-from pfrl import experiments
-from pfrl import explorers
-from pfrl import utils
-from pfrl import replay_buffers
+from pfrl import experiments, explorers, replay_buffers, utils
 from pfrl.wrappers import atari_wrappers
 
 

examples/atari/reproduction/rainbow/train_rainbow.py

@@ -2,17 +2,14 @@
 import json
 import os
 
-import torch
 import numpy as np
+import torch
 
 import pfrl
-from pfrl import agents
-from pfrl import experiments
-from pfrl import explorers
+from pfrl import agents, experiments, explorers
 from pfrl import nn as pnn
-from pfrl import utils
+from pfrl import replay_buffers, utils
 from pfrl.q_functions import DistributionalDuelingDQN
-from pfrl import replay_buffers
 from pfrl.wrappers import atari_wrappers
 
 

examples/atari/train_a2c_ale.py

@@ -6,9 +6,8 @@
 from torch import nn
 
 import pfrl
+from pfrl import experiments, utils
 from pfrl.agents import a2c
-from pfrl import experiments
-from pfrl import utils
 from pfrl.policies import SoftmaxCategoricalHead
 from pfrl.wrappers import atari_wrappers
 

examples/atari/train_acer_ale.py

@@ -10,13 +10,11 @@
 from torch import nn
 
 import pfrl
+from pfrl import experiments, utils
 from pfrl.agents import acer
-from pfrl import experiments
-from pfrl import utils
-from pfrl.replay_buffers import EpisodicReplayBuffer
 from pfrl.policies import SoftmaxCategoricalHead
 from pfrl.q_functions import DiscreteActionValueHead
-
+from pfrl.replay_buffers import EpisodicReplayBuffer
 from pfrl.wrappers import atari_wrappers
 
 

examples/atari/train_categorical_dqn_ale.py

@@ -1,14 +1,10 @@
 import argparse
 
-import torch
 import numpy as np
+import torch
 
 import pfrl
-from pfrl import experiments
-from pfrl import explorers
-from pfrl import utils
-from pfrl import replay_buffers
-
+from pfrl import experiments, explorers, replay_buffers, utils
 from pfrl.wrappers import atari_wrappers
 
 

examples/atari/train_dqn_ale.py

@@ -1,21 +1,16 @@
 import argparse
 
+import numpy as np
 import torch
 import torch.nn as nn
-import numpy as np
 
 import pfrl
-from pfrl.q_functions import DiscreteActionValueHead
-from pfrl import agents
-from pfrl import experiments
-from pfrl import explorers
+from pfrl import agents, experiments, explorers
 from pfrl import nn as pnn
-from pfrl import utils
-from pfrl.q_functions import DuelingDQN
-from pfrl import replay_buffers
-
-from pfrl.wrappers import atari_wrappers
+from pfrl import replay_buffers, utils
 from pfrl.initializers import init_chainer_default
+from pfrl.q_functions import DiscreteActionValueHead, DuelingDQN
+from pfrl.wrappers import atari_wrappers
 
 
 class SingleSharedBias(nn.Module):

examples/atari/train_dqn_batch_ale.py

@@ -1,23 +1,18 @@
 import argparse
 import functools
 
+import numpy as np
 import torch
 import torch.nn as nn
 import torch.optim as optim
-import numpy as np
 
 import pfrl
-from pfrl import agents
-from pfrl import experiments
-from pfrl import explorers
+from pfrl import agents, experiments, explorers
 from pfrl import nn as pnn
-from pfrl import utils
-from pfrl.q_functions import DiscreteActionValueHead
-from pfrl.q_functions import DuelingDQN
-from pfrl import replay_buffers
-
-from pfrl.wrappers import atari_wrappers
+from pfrl import replay_buffers, utils
 from pfrl.initializers import init_chainer_default
+from pfrl.q_functions import DiscreteActionValueHead, DuelingDQN
+from pfrl.wrappers import atari_wrappers
 
 
 class SingleSharedBias(nn.Module):

examples/atari/train_drqn_ale.py

@@ -18,12 +18,8 @@
 from torch import nn
 
 import pfrl
-from pfrl import experiments
-from pfrl import explorers
-from pfrl import utils
-from pfrl import replay_buffers
+from pfrl import experiments, explorers, replay_buffers, utils
 from pfrl.q_functions import DiscreteActionValueHead
-
 from pfrl.wrappers import atari_wrappers
 
 

examples/atari/train_ppo_ale.py

@@ -15,11 +15,10 @@
 from torch import nn
 
 import pfrl
+from pfrl import experiments, utils
 from pfrl.agents import PPO
-from pfrl import experiments
-from pfrl import utils
-from pfrl.wrappers import atari_wrappers
 from pfrl.policies import SoftmaxCategoricalHead
+from pfrl.wrappers import atari_wrappers
 
 
 def main():

examples/atlas/train_soft_actor_critic_atlas.py

@@ -8,14 +8,11 @@
 import gym.wrappers
 import numpy as np
 import torch
-from torch import nn
-from torch import distributions
+from torch import distributions, nn
 
 import pfrl
-from pfrl import experiments
+from pfrl import experiments, replay_buffers, utils
 from pfrl.nn.lmbda import Lambda
-from pfrl import utils
-from pfrl import replay_buffers
 
 
 def make_env(args, seed, test):

examples/grasping/train_dqn_batch_grasping.py

@@ -9,11 +9,8 @@
 from torch import nn
 
 import pfrl
+from pfrl import experiments, explorers, replay_buffers, utils
 from pfrl.q_functions import DiscreteActionValueHead
-from pfrl import experiments
-from pfrl import explorers
-from pfrl import utils
-from pfrl import replay_buffers
 
 
 class CastAction(gym.ActionWrapper):
@@ -243,9 +240,9 @@ def main():
     max_episode_steps = 8
 
     def make_env(idx, test):
-        from pybullet_envs.bullet.kuka_diverse_object_gym_env import (
+        from pybullet_envs.bullet.kuka_diverse_object_gym_env import (  # NOQA
             KukaDiverseObjectEnv,
-        )  # NOQA
+        )
 
         # Use different random seeds for train and test envs
         process_seed = int(process_seeds[idx])

examples/gym/train_categorical_dqn_gym.py

@@ -10,15 +10,11 @@
 import argparse
 import sys
 
-import torch
 import gym
+import torch
 
 import pfrl
-from pfrl import experiments
-from pfrl import explorers
-from pfrl import utils
-from pfrl import q_functions
-from pfrl import replay_buffers
+from pfrl import experiments, explorers, q_functions, replay_buffers, utils
 
 
 def main():

examples/gym/train_dqn_gym.py

@@ -12,22 +12,19 @@
 """
 
 import argparse
-import sys
 import os
+import sys
 
-import torch.optim as optim
 import gym
-from gym import spaces
 import numpy as np
+import torch.optim as optim
+from gym import spaces
 
 import pfrl
-from pfrl.agents.dqn import DQN
-from pfrl import experiments
-from pfrl import explorers
+from pfrl import experiments, explorers
 from pfrl import nn as pnn
-from pfrl import utils
-from pfrl import q_functions
-from pfrl import replay_buffers
+from pfrl import q_functions, replay_buffers, utils
+from pfrl.agents.dqn import DQN
 
 
 def main():

examples/gym/train_reinforce_gym.py

@@ -17,10 +17,8 @@
 from torch import nn
 
 import pfrl
-from pfrl import experiments
-from pfrl import utils
-from pfrl.policies import SoftmaxCategoricalHead
-from pfrl.policies import GaussianHeadWithFixedCovariance
+from pfrl import experiments, utils
+from pfrl.policies import GaussianHeadWithFixedCovariance, SoftmaxCategoricalHead
 
 
 def main():

examples/mujoco/reproduction/ddpg/train_ddpg.py

@@ -15,13 +15,9 @@
 from torch import nn
 
 import pfrl
+from pfrl import experiments, explorers, replay_buffers, utils
 from pfrl.agents.ddpg import DDPG
-from pfrl import experiments
-from pfrl import explorers
-from pfrl import utils
-from pfrl import replay_buffers
-from pfrl.nn import ConcatObsAndAction
-from pfrl.nn import BoundByTanh
+from pfrl.nn import BoundByTanh, ConcatObsAndAction
 from pfrl.policies import DeterministicHead
 
 

examples/mujoco/reproduction/ppo/train_ppo.py

@@ -13,9 +13,8 @@
 from torch import nn
 
 import pfrl
+from pfrl import experiments, utils
 from pfrl.agents import PPO
-from pfrl import experiments
-from pfrl import utils
 
 
 def main():

examples/mujoco/reproduction/soft_actor_critic/train_soft_actor_critic.py

@@ -4,23 +4,20 @@
 as possible.
 """
 import argparse
-from distutils.version import LooseVersion
 import functools
 import logging
 import sys
+from distutils.version import LooseVersion
 
-import torch
-from torch import nn
-from torch import distributions
 import gym
 import gym.wrappers
 import numpy as np
+import torch
+from torch import distributions, nn
 
 import pfrl
-from pfrl import experiments
+from pfrl import experiments, replay_buffers, utils
 from pfrl.nn.lmbda import Lambda
-from pfrl import utils
-from pfrl import replay_buffers
 
 
 def main():

examples/mujoco/reproduction/td3/train_td3.py

@@ -15,10 +15,7 @@
 from torch import nn
 
 import pfrl
-from pfrl import experiments
-from pfrl import explorers
-from pfrl import utils
-from pfrl import replay_buffers
+from pfrl import experiments, explorers, replay_buffers, utils
 
 
 def main():