format

Author: quantumiracle

examples/basic_tutorials/tutorial_cifar10_cnn_static.py

@@ -1,13 +1,15 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 
+import multiprocessing
 import time
+
 import numpy as np
-import multiprocessing
 import tensorflow as tf
 
 import tensorlayer as tl
-from tensorlayer.layers import (BatchNorm, Conv2d, Dense, Flatten, Input, LocalResponseNorm, MaxPool2d)
+from tensorlayer.layers import (BatchNorm, Conv2d, Dense, Flatten, Input,
+                                LocalResponseNorm, MaxPool2d)
 from tensorlayer.models import Model
 
 # enable debug logging

examples/basic_tutorials/tutorial_mnist_mlp_dynamic.py

@@ -1,4 +1,5 @@
 import time
+
 import numpy as np
 import tensorflow as tf
 

examples/basic_tutorials/tutorial_mnist_mlp_dynamic_2.py

@@ -1,4 +1,5 @@
 import time
+
 import numpy as np
 import tensorflow as tf
 

examples/basic_tutorials/tutorial_mnist_mlp_static.py

@@ -1,5 +1,6 @@
 import pprint
 import time
+
 import numpy as np
 import tensorflow as tf
 

examples/basic_tutorials/tutorial_mnist_mlp_static_2.py

@@ -1,4 +1,5 @@
 import time
+
 import numpy as np
 import tensorflow as tf
 

examples/deprecated_tutorials/tutorial_imagenet_inceptionV3_distributed.py

@@ -21,7 +21,8 @@
 import numpy as np
 import tensorflow as tf
 from tensorflow.contrib import slim
-from tensorflow.contrib.slim.python.slim.nets.inception_v3 import (inception_v3, inception_v3_arg_scope)
+from tensorflow.contrib.slim.python.slim.nets.inception_v3 import (inception_v3,
+                                                                   inception_v3_arg_scope)
 from tensorflow.python.framework.errors_impl import OutOfRangeError
 from tensorflow.python.training import session_run_hook
 from tensorflow.python.training.basic_session_run_hooks import StopAtStepHook

examples/distributed_training/tutorial_cifar10_distributed_trainer.py

@@ -18,7 +18,8 @@
 import tensorflow as tf
 
 import tensorlayer as tl
-from tensorlayer.layers import (BatchNormLayer, Conv2d, DenseLayer, FlattenLayer, InputLayer, MaxPool2d)
+from tensorlayer.layers import (BatchNormLayer, Conv2d, DenseLayer,
+                                FlattenLayer, InputLayer, MaxPool2d)
 
 tf.logging.set_verbosity(tf.logging.DEBUG)
 tl.logging.set_verbosity(tl.logging.DEBUG)

examples/pretrained_cnn/tutorial_models_resnet50.py

@@ -8,8 +8,8 @@
 import time
 
 import numpy as np
-
 import tensorflow as tf
+
 import tensorlayer as tl
 from tensorlayer.models.imagenet_classes import class_names
 

examples/reinforcement_learning/tutorial_A3C.py

@@ -46,16 +46,16 @@
 
 import argparse
 import multiprocessing
+import os
 import threading
 import time
-import os
-import matplotlib.pyplot as plt
 
 import gym
+import matplotlib.pyplot as plt
 import numpy as np
 import tensorflow as tf
-import tensorflow_probability as tfp
 
+import tensorflow_probability as tfp
 import tensorlayer as tl
 
 tfd = tfp.distributions

examples/reinforcement_learning/tutorial_AC.py

@@ -46,11 +46,11 @@
 
 """
 import argparse
-import time
-import matplotlib.pyplot as plt
 import os
+import time
 
 import gym
+import matplotlib.pyplot as plt
 import numpy as np
 import tensorflow as tf
 

examples/reinforcement_learning/tutorial_C51.py

@@ -26,12 +26,12 @@
 import random
 import time
 
+import gym
+import matplotlib.pyplot as plt
 import numpy as np
 import tensorflow as tf
-import matplotlib.pyplot as plt
 
 import tensorlayer as tl
-import gym
 
 parser = argparse.ArgumentParser()
 parser.add_argument('--train', dest='train', action='store_true', default=True)
@@ -338,4 +338,4 @@ def _train_func(self, b_o, b_index, b_m):
                 'Testing  | Episode: {}  | Episode Reward: {:.4f}  | Running Time: {:.4f}'.format(
                     nepisode, episode_reward, time.time() - t0
                 )
-            )
+            )

examples/reinforcement_learning/tutorial_DDPG.py

@@ -29,8 +29,8 @@
 
 import argparse
 import os
-import time
 import threading
+import time
 
 import gym
 import matplotlib.pyplot as plt

examples/reinforcement_learning/tutorial_DPPO.py

@@ -37,8 +37,8 @@
 import matplotlib.pyplot as plt
 import numpy as np
 import tensorflow as tf
-import tensorflow_probability as tfp
 
+import tensorflow_probability as tfp
 import tensorlayer as tl
 
 parser = argparse.ArgumentParser(description='Train or test neural net motor controller.')

examples/reinforcement_learning/tutorial_DQN.py

@@ -35,13 +35,13 @@
 python tutorial_DQN.py --train/test
 """
 import argparse
+import os
 import time
 
-import os
 import gym
+import matplotlib.pyplot as plt
 import numpy as np
 import tensorflow as tf
-import matplotlib.pyplot as plt
 
 import tensorlayer as tl
 

examples/reinforcement_learning/tutorial_DQN_variants.py

@@ -39,12 +39,12 @@
 import random
 import time
 
+import gym
+import matplotlib.pyplot as plt
 import numpy as np
 import tensorflow as tf
-import matplotlib.pyplot as plt
 
 import tensorlayer as tl
-import gym
 
 parser = argparse.ArgumentParser()
 parser.add_argument('--train', dest='train', action='store_true', default=True)
@@ -428,4 +428,4 @@ def load(self, path):
                 'Testing  | Episode: {}  | Episode Reward: {:.4f}  | Running Time: {:.4f}'.format(
                     nepisode, episode_reward, time.time() - t0
                 )
-            )
+            )

examples/reinforcement_learning/tutorial_PG.py

@@ -34,6 +34,7 @@
 import matplotlib.pyplot as plt
 import numpy as np
 import tensorflow as tf
+
 import tensorlayer as tl
 
 parser = argparse.ArgumentParser(description='Train or test neural net motor controller.')
@@ -223,4 +224,3 @@ def load(self):
                 'Testing  | Episode: {}/{}  | Episode Reward: {:.0f}  | Running Time: {:.4f}'.format(
                     episode + 1, TEST_EPISODES, episode_reward,
                     time.time() - t0))
-

examples/reinforcement_learning/tutorial_PPO.py

@@ -30,8 +30,8 @@
 import matplotlib.pyplot as plt
 import numpy as np
 import tensorflow as tf
-import tensorflow_probability as tfp
 
+import tensorflow_probability as tfp
 import tensorlayer as tl
 
 parser = argparse.ArgumentParser(description='Train or test neural net motor controller.')

examples/reinforcement_learning/tutorial_Qlearning.py

@@ -9,12 +9,13 @@
 tensorlayer==2.0.0
 """
 
+import argparse
 import os
-import gym
 import time
-import argparse
-import numpy as np
+
+import gym
 import matplotlib.pyplot as plt
+import numpy as np
 
 parser = argparse.ArgumentParser()
 parser.add_argument('--train', dest='train', action='store_true', default=True)
@@ -107,4 +108,4 @@
             'Testing  | Episode: {}/{}  | Episode Reward: {:.4f}  | Running Time: {:.4f}'.format(
                 i + 1, num_episodes, rAll, time.time() - t0
             )
-        )
+        )

examples/reinforcement_learning/tutorial_SAC.py

@@ -28,16 +28,16 @@
 """
 
 import argparse
+import os
 import random
 import time
-import os
 
 import gym
 import matplotlib.pyplot as plt
 import numpy as np
 import tensorflow as tf
-import tensorflow_probability as tfp
 
+import tensorflow_probability as tfp
 import tensorlayer as tl
 from tensorlayer.layers import Dense
 from tensorlayer.models import Model
@@ -447,4 +447,3 @@ def load_weights(self):  # load trained weights
                 'Testing  | Episode: {}/{}  | Episode Reward: {:.4f}  | Running Time: {:.4f}'.format(
                     episode + 1, TEST_EPISODES, episode_reward,
                     time.time() - t0))
-

examples/reinforcement_learning/tutorial_TD3.py

@@ -41,16 +41,16 @@
 """
 
 import argparse
+import os
 import random
 import time
-import os
 
 import gym
 import matplotlib.pyplot as plt
 import numpy as np
 import tensorflow as tf
-import tensorflow_probability as tfp
 
+import tensorflow_probability as tfp
 import tensorlayer as tl
 from tensorlayer.layers import Dense
 from tensorlayer.models import Model
@@ -430,4 +430,3 @@ def load(self):  # load trained weights
                 'Testing  | Episode: {}/{}  | Episode Reward: {:.4f}  | Running Time: {:.4f}'.format(
                     episode + 1, TEST_EPISODES, episode_reward,
                     time.time() - t0))
-

examples/reinforcement_learning/tutorial_TRPO.py

@@ -39,6 +39,7 @@
 import numpy as np
 import scipy.signal
 import tensorflow as tf
+
 import tensorflow_probability as tfp
 import tensorlayer as tl
 

examples/reinforcement_learning/tutorial_atari_pong.py

@@ -21,10 +21,10 @@
 """
 import time
 
-import numpy as np
-
 import gym
+import numpy as np
 import tensorflow as tf
+
 import tensorlayer as tl
 
 tl.logging.set_verbosity(tl.logging.DEBUG)

examples/reinforcement_learning/tutorial_prioritized_replay.py

@@ -28,11 +28,11 @@
 import random
 import time
 
+import gym
+import matplotlib.pyplot as plt
 import numpy as np
 import tensorflow as tf
-import matplotlib.pyplot as plt
 
-import gym
 import tensorlayer as tl
 
 parser = argparse.ArgumentParser()
@@ -523,4 +523,4 @@ def _tderror_func(self, b_o, b_a, b_r, b_o_, b_d):
                 'Testing  | Episode: {}  | Episode Reward: {:.4f}  | Running Time: {:.4f}'.format(
                     nepisode, episode_reward, time.time() - t0
                 )
-            )
+            )

examples/text_generation/tutorial_generate_text.py

@@ -26,10 +26,10 @@
 import re
 import time
 
+import nltk
 import numpy as np
 import tensorflow as tf
 
-import nltk
 import tensorlayer as tl
 from tensorlayer.layers import *
 from tensorlayer.models import Model

tensorlayer/db.py

@@ -640,7 +640,7 @@ def run_top_task(self, task_name=None, sort=None, **kwargs):
         logging.info("[Database] Start Task: key: {} sort: {} push time: {}".format(task_name, sort, _datetime))
         _script = _script.decode('utf-8')
         with tf.Graph().as_default():  #  # as graph: # clear all TF graphs
-            exec(_script, globals())
+            exec (_script, globals())
 
         # set status to finished
         _ = self.db.Task.find_one_and_update({'_id': _id}, {'$set': {'status': 'finished'}})

tensorlayer/files/dataset_loaders/celebA_dataset.py

@@ -5,7 +5,8 @@
 import zipfile
 
 from tensorlayer import logging
-from tensorlayer.files.utils import (download_file_from_google_drive, exists_or_mkdir, load_file_list)
+from tensorlayer.files.utils import (download_file_from_google_drive,
+                                     exists_or_mkdir, load_file_list)
 
 __all__ = ['load_celebA_dataset']
 

tensorlayer/files/dataset_loaders/cyclegan_dataset.py

@@ -6,7 +6,8 @@
 import numpy as np
 
 from tensorlayer import logging, visualize
-from tensorlayer.files.utils import (del_file, folder_exists, load_file_list, maybe_download_and_extract)
+from tensorlayer.files.utils import (del_file, folder_exists, load_file_list,
+                                     maybe_download_and_extract)
 
 __all__ = ['load_cyclegan_dataset']
 

tensorlayer/files/dataset_loaders/flickr_1M_dataset.py

@@ -4,9 +4,9 @@
 import os
 
 from tensorlayer import logging, visualize
-from tensorlayer.files.utils import (
-    del_file, folder_exists, load_file_list, load_folder_list, maybe_download_and_extract, read_file
-)
+from tensorlayer.files.utils import (del_file, folder_exists, load_file_list,
+                                     load_folder_list,
+                                     maybe_download_and_extract, read_file)
 
 __all__ = ['load_flickr1M_dataset']
 

tensorlayer/files/dataset_loaders/flickr_25k_dataset.py

@@ -4,9 +4,9 @@
 import os
 
 from tensorlayer import logging, visualize
-from tensorlayer.files.utils import (
-    del_file, folder_exists, load_file_list, maybe_download_and_extract, natural_keys, read_file
-)
+from tensorlayer.files.utils import (del_file, folder_exists, load_file_list,
+                                     maybe_download_and_extract, natural_keys,
+                                     read_file)
 
 __all__ = ['load_flickr25k_dataset']