Fix unused code (#358)

* remove unused code

* static method

* remove as vs

* remove reimport

Author: zsdonghao

example/tutorial_cifar10_tfrecord.py

@@ -45,7 +45,7 @@
 # import numpy as np
 import tensorflow as tf
 import tensorlayer as tl
-from PIL import Image
+# from PIL import Image
 from tensorlayer.layers import *
 
 model_file_name = "model_cifar10_tfrecord.ckpt"

example/tutorial_frozenlake_dqn.py

@@ -27,8 +27,7 @@
 """
 
 import time
-
-import matplotlib.pyplot as plt
+import gym
 import numpy as np
 import tensorflow as tf
 import tensorlayer as tl

example/tutorial_ptb_lstm_state_is_tuple.py

@@ -106,7 +106,6 @@
 import numpy as np
 import tensorflow as tf
 import tensorlayer as tl
-from tensorlayer.layers import set_keep
 
 flags = tf.flags
 flags.DEFINE_string("model", "small", "A type of model. Possible options are: small, medium, large.")

example/tutorial_vgg16.py

@@ -50,11 +50,9 @@
 
 def conv_layers(net_in):
     with tf.name_scope('preprocess'):
-        """
-        Notice that we include a preprocessing layer that takes the RGB image
-        with pixels values in the range of 0-255 and subtracts the mean image
-        values (calculated over the entire ImageNet training set).
-        """
+        # Notice that we include a preprocessing layer that takes the RGB image
+        # with pixels values in the range of 0-255 and subtracts the mean image
+        # values (calculated over the entire ImageNet training set).
         mean = tf.constant([123.68, 116.779, 103.939], dtype=tf.float32, shape=[1, 1, 1, 3], name='img_mean')
         net_in.outputs = net_in.outputs - mean
 

tensorlayer/db.py

@@ -205,7 +205,8 @@ def del_params(self, args=None):
 
         print("[TensorDB] Delete params SUCCESS: {}".format(args))
 
-    def _print_dict(self, args):
+    @staticmethod
+    def _print_dict(args):
         # return " / ".join(str(key) + ": "+ str(value) for key, value in args.items())
 
         string = ''

tensorlayer/files.py

@@ -1456,7 +1456,7 @@ def load_ckpt(sess=None, mode_name='model.ckpt', save_dir='checkpoint', var_list
         logging.info("[*] load ckpt fail ...")
 
 
-def save_any_to_npy(save_dict={}, name='file.npy'):
+def save_any_to_npy(save_dict=None, name='file.npy'):
     """Save variables to `.npy` file.
 
     Parameters
@@ -1503,8 +1503,7 @@ def load_npy_to_any(path='', name='file.npy'):
         try:
             return npy
         except Exception:
-            logging.info("[!] Fail to load %s" % file_path)
-            exit()
+            raise Exception("[!] Fail to load %s" % file_path)
 
 
 def file_exists(filepath):

tensorlayer/layers/convolution.py

@@ -374,7 +374,7 @@ def __init__(
             act = tf.identity
         logging.info("Conv3dLayer %s: shape:%s strides:%s pad:%s act:%s" % (self.name, str(shape), str(strides), padding, act.__name__))
 
-        with tf.variable_scope(name) as vs:
+        with tf.variable_scope(name):
             # W = tf.Variable(W_init(shape=shape, **W_init_args), name='W_conv')
             # b = tf.Variable(b_init(shape=[shape[-1]], **b_init_args), name='b_conv')
             W = tf.get_variable(name='W_conv3d', shape=shape, initializer=W_init, dtype=D_TYPE, **W_init_args)

tensorlayer/layers/core.py

@@ -878,7 +878,7 @@ def __init__(
         n_in = int(self.inputs.get_shape()[-1])
         self.n_units = n_units
         logging.info("DenseLayer  %s: %d %s" % (self.name, self.n_units, act.__name__))
-        with tf.variable_scope(name) as vs:
+        with tf.variable_scope(name):
             W = tf.get_variable(name='W', shape=(n_in, n_units), initializer=W_init, dtype=D_TYPE, **W_init_args)
             if b_init is not None:
                 try:

tensorlayer/layers/normalization.py

@@ -138,7 +138,7 @@ def __init__(
                 update_moving_variance = moving_averages.assign_moving_average(
                     moving_variance, variance, decay, zero_debias=False)  # if zero_debias=True, has bias
                 # logging.info("TF12 moving")
-            except Exception as e:  # TF11
+            except Exception:  # TF11
                 update_moving_mean = moving_averages.assign_moving_average(moving_mean, mean, decay)
                 update_moving_variance = moving_averages.assign_moving_average(moving_variance, variance, decay)
                 # logging.info("TF11 moving")

tensorlayer/nlp.py

@@ -652,7 +652,7 @@ def build_words_dataset(words=None, vocabulary_size=50000, printable=True, unk_k
     """
     if words is None:
         raise Exception("words : list of str or byte")
-    import collections
+
     count = [[unk_key, -1]]
     count.extend(collections.Counter(words).most_common(vocabulary_size - 1))
     dictionary = dict()