flake8 fix

.github/workflows/pytest.yml

@@ -30,10 +30,7 @@ jobs:
     - name: Lint with flake8
       run: |
         pip install flake8
-        # stop the build if there are Python syntax errors or undefined names
-        flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
-        # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
-        flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
+        ./flake_check.sh
     - name: Test with pytest
       run: |
         pip install pytest

flake_check.sh

@@ -0,0 +1,3 @@
+#!/bin/sh
+flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics                 
+flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics

setup.py

@@ -40,12 +40,12 @@ setup(
                                     'examples', 'examples.*',
                                     'docs', 'docs.*']),
     install_requires=[
-        'numpy', 
-        'torch', 
-        'tensorboard', 
-        'tqdm', 
-        # 'ray', 
-        'gym', 
+        'numpy',
+        'torch',
+        'tensorboard',
+        'tqdm',
+        # 'ray',
+        'gym',
         'cloudpickle'
     ],
-)
+)

tianshou/data/buffer.py

@@ -20,7 +20,7 @@ class ReplayBuffer(object):
                 self.__dict__[name] = np.zeros([self._maxsize, *inst.shape])
             elif isinstance(inst, dict):
                 self.__dict__[name] = np.array([{} for _ in range(self._maxsize)])
-            else: # assume `inst` is a number
+            else:  # assume `inst` is a number
                 self.__dict__[name] = np.zeros([self._maxsize])
         self.__dict__[name][self._index] = inst
 
@@ -46,15 +46,21 @@ class ReplayBuffer(object):
 
     def sample(self, batch_size):
         indice = self.sample_index(batch_size)
-        return Batch(obs=self.obs[indice], act=self.act[indice], rew=self.rew[indice], 
-            done=self.done[indice], obs_next=self.obs_next[indice], info=self.info[indice])
+        return Batch(
+            obs=self.obs[indice],
+            act=self.act[indice],
+            rew=self.rew[indice],
+            done=self.done[indice],
+            obs_next=self.obs_next[indice],
+            info=self.info[indice]
+        )
 
 
 class PrioritizedReplayBuffer(ReplayBuffer):
     """docstring for PrioritizedReplayBuffer"""
     def __init__(self, size):
         super().__init__(size)
-    
+
     def add(self, obs, act, rew, done, obs_next, info={}, weight=None):
         raise NotImplementedError
 

tianshou/env/wrapper.py

@@ -1,6 +1,10 @@
 import numpy as np
 from collections import deque
 from multiprocessing import Process, Pipe
+try:
+    import ray
+except ImportError:
+    pass
 
 from tianshou.utils import CloudpickleWrapper
 
@@ -11,10 +15,10 @@ class EnvWrapper(object):
 
     def step(self, action):
         return self.env.step(action)
-    
+
     def reset(self):
         self.env.reset()
-    
+
     def seed(self, seed=None):
         if hasattr(self.env, 'seed'):
             self.env.seed(seed)
@@ -55,7 +59,7 @@ class VectorEnv(object):
         super().__init__()
         self.envs = [_() for _ in env_fns]
         self._reset_after_done = kwargs.get('reset_after_done', False)
-        
+
     def __len__(self):
         return len(self.envs)
 
@@ -89,12 +93,15 @@ class VectorEnv(object):
 class SubprocVectorEnv(object):
     """docstring for SubProcVectorEnv"""
     def __init__(self, env_fns, **kwargs):
+
         super().__init__()
         self.env_num = len(env_fns)
         self.closed = False
         self.parent_remote, self.child_remote = zip(*[Pipe() for _ in range(self.env_num)])
-        self.processes = [Process(target=worker, args=(parent, child, CloudpickleWrapper(env_fn), kwargs), daemon=True)
-            for (parent, child, env_fn) in zip(self.parent_remote, self.child_remote, env_fns)]
+        self.processes = [
+            Process(target=self.worker, args=(parent, child, CloudpickleWrapper(env_fn), kwargs), daemon=True)
+            for (parent, child, env_fn) in zip(self.parent_remote, self.child_remote, env_fns)
+        ]
         for p in self.processes:
             p.start()
         for c in self.child_remote:
@@ -102,27 +109,27 @@ class SubprocVectorEnv(object):
 
     def __len__(self):
         return self.env_num
-        
-    def worker(parent, p, env_fn_wrapper, **kwargs):
+
+    def worker(self, parent, p, env_fn_wrapper, **kwargs):
         reset_after_done = kwargs.get('reset_after_done', True)
         parent.close()
         env = env_fn_wrapper.data()
         while True:
             cmd, data = p.recv()
-            if cmd is 'step':
+            if cmd == 'step':
                 obs, rew, done, info = env.step(data)
                 if reset_after_done and done:
                     # s_ is useless when episode finishes
                     obs = env.reset()
                 p.send([obs, rew, done, info])
-            elif cmd is 'reset':
+            elif cmd == 'reset':
                 p.send(env.reset())
-            elif cmd is 'close':
+            elif cmd == 'close':
                 p.close()
                 break
-            elif cmd is 'render':
+            elif cmd == 'render':
                 p.send(env.render())
-            elif cmd is 'seed':
+            elif cmd == 'seed':
                 p.send(env.seed(data))
             else:
                 raise NotImplementedError
@@ -163,7 +170,6 @@ class SubprocVectorEnv(object):
             p.join()
 
 
-
 class RayVectorEnv(object):
     """docstring for RayVectorEnv"""
     def __init__(self, env_fns, **kwargs):

tianshou/utils/cloudpicklewrapper.py

@@ -4,7 +4,9 @@ import cloudpickle
 class CloudpickleWrapper(object):
     def __init__(self, data):
         self.data = data
+
     def __getstate__(self):
         return cloudpickle.dumps(self.data)
+
     def __setstate__(self, data):
         self.data = cloudpickle.loads(data)