edited

Author: MorvanZhou

tensorflowTUT/tensorflow11_build_network.py

@@ -34,7 +34,7 @@ def add_layer(inputs, in_size, out_size, activation_function=None):
 # add output layer
 prediction = add_layer(l1, 10, 1, activation_function=None)
 
-# the error between prediciton and real data
+# the error between prediction and real data
 loss = tf.reduce_mean(tf.reduce_sum(tf.square(ys - prediction),
                      reduction_indices=[1]))
 train_step = tf.train.GradientDescentOptimizer(0.1).minimize(loss)

tensorflowTUT/tensorflow12_plut_result.py

@@ -43,7 +43,7 @@ def add_layer(inputs, in_size, out_size, activation_function=None):
 # important step
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12
-if int((tf.__version__).split('.')[1]) < 12:
+if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
     init = tf.initialize_all_variables()
 else:
     init = tf.global_variables_initializer()

tensorflowTUT/tensorflow7_variable.py

@@ -18,7 +18,7 @@
 
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12
-if int((tf.__version__).split('.')[1]) < 12:
+if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
     init = tf.initialize_all_variables()
 else:
     init = tf.global_variables_initializer()

tensorflowTUT/tf11_build_network/for_you_to_practice.py

@@ -30,7 +30,7 @@ def add_layer(inputs, in_size, out_size, activation_function=None):
 # add output layer
 
 
-# the error between prediciton and real data
+# the error between prediction and real data
 
 # important step
 

tensorflowTUT/tf11_build_network/full_code.py

@@ -37,14 +37,14 @@ def add_layer(inputs, in_size, out_size, activation_function=None):
 # add output layer
 prediction = add_layer(l1, 10, 1, activation_function=None)
 
-# the error between prediciton and real data
+# the error between prediction and real data
 loss = tf.reduce_mean(tf.reduce_sum(tf.square(ys-prediction), reduction_indices=[1]))
 train_step = tf.train.GradientDescentOptimizer(0.1).minimize(loss)
 # important step
 sess = tf.Session()
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12
-if int((tf.__version__).split('.')[1]) < 12:
+if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
     init = tf.initialize_all_variables()
 else:
     init = tf.global_variables_initializer()

tensorflowTUT/tf12_plot_result/for_you_to_practice.py

@@ -37,14 +37,14 @@ def add_layer(inputs, in_size, out_size, activation_function=None):
 # add output layer
 prediction = add_layer(l1, 10, 1, activation_function=None)
 
-# the error between prediciton and real data
+# the error between prediction and real data
 loss = tf.reduce_mean(tf.reduce_sum(tf.square(ys-prediction), reduction_indices=[1]))
 train_step = tf.train.GradientDescentOptimizer(0.1).minimize(loss)
 # important step
 sess= tf.Session()
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12
-if int((tf.__version__).split('.')[1]) < 12:
+if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
     init = tf.initialize_all_variables()
 else:
     init = tf.global_variables_initializer()

tensorflowTUT/tf12_plot_result/full_code.py

@@ -37,14 +37,14 @@ def add_layer(inputs, in_size, out_size, activation_function=None):
 # add output layer
 prediction = add_layer(l1, 10, 1, activation_function=None)
 
-# the error between prediciton and real data
+# the error between prediction and real data
 loss = tf.reduce_mean(tf.reduce_sum(tf.square(ys-prediction), reduction_indices=[1]))
 train_step = tf.train.GradientDescentOptimizer(0.1).minimize(loss)
 # important step
 sess = tf.Session()
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12
-if int((tf.__version__).split('.')[1]) < 12:
+if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
     init = tf.initialize_all_variables()
 else:
     init = tf.global_variables_initializer()

tensorflowTUT/tf14_tensorboard/for_you_to_practice.py

@@ -40,7 +40,7 @@ def add_layer(inputs, in_size, out_size, activation_function=None):
 
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12
-if int((tf.__version__).split('.')[1]) < 12:
+if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
     init = tf.initialize_all_variables()
 else:
     init = tf.global_variables_initializer()

tensorflowTUT/tf14_tensorboard/full_code.py

@@ -47,14 +47,14 @@ def add_layer(inputs, in_size, out_size, activation_function=None):
 sess = tf.Session()
 
 # tf.train.SummaryWriter soon be deprecated, use following
-if int((tf.__version__).split('.')[1]) < 12:  # tensorflow version < 0.12
+if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:  # tensorflow version < 0.12
     writer = tf.train.SummaryWriter('logs/', sess.graph)
 else: # tensorflow version >= 0.12
     writer = tf.summary.FileWriter("logs/", sess.graph)
 
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12
-if int((tf.__version__).split('.')[1]) < 12:
+if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
     init = tf.initialize_all_variables()
 else:
     init = tf.global_variables_initializer()

tensorflowTUT/tf15_tensorboard/for_you_to_practice.py

@@ -54,7 +54,7 @@ def add_layer(inputs, in_size, out_size, activation_function=None):
 # important step
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12
-if int((tf.__version__).split('.')[1]) < 12:
+if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
     init = tf.initialize_all_variables()
 else:
     init = tf.global_variables_initializer()

tensorflowTUT/tf15_tensorboard/full_code.py

@@ -16,7 +16,7 @@ def add_layer(inputs, in_size, out_size, n_layer, activation_function=None):
     layer_name = 'layer%s' % n_layer
 
     # for tensorflow version < 0.12
-    if int((tf.__version__).split('.')[1]) < 12:
+    if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
         with tf.name_scope(layer_name):
             with tf.name_scope('weights'):
                 Weights = tf.Variable(tf.random_normal([in_size, out_size]), name='W')
@@ -68,7 +68,7 @@ def add_layer(inputs, in_size, out_size, n_layer, activation_function=None):
 with tf.name_scope('loss'):
     loss = tf.reduce_mean(tf.reduce_sum(tf.square(ys - prediction),
                                         reduction_indices=[1]))
-    if int((tf.__version__).split('.')[1]) < 12:    # tensorflow version < 0.12
+    if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:    # tensorflow version < 0.12
         tf.scalar_summary('loss', loss)
     else:   # tensorflow version >= 0.12
         tf.summary.scalar('loss', loss)
@@ -77,20 +77,20 @@ def add_layer(inputs, in_size, out_size, n_layer, activation_function=None):
     train_step = tf.train.GradientDescentOptimizer(0.1).minimize(loss)
 
 sess = tf.Session()
-if int((tf.__version__).split('.')[1]) < 12:  # tensorflow version < 0.12
+if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:  # tensorflow version < 0.12
     merged = tf.merge_all_summaries()
 else:   # tensorflow version >= 0.12
     merged = tf.summary.merge_all()
 
 # tf.train.SummaryWriter soon be deprecated, use following
-if int((tf.__version__).split('.')[1]) < 12:  # tensorflow version < 0.12
+if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:  # tensorflow version < 0.12
     writer = tf.train.SummaryWriter('logs/', sess.graph)
 else: # tensorflow version >= 0.12
     writer = tf.summary.FileWriter("logs/", sess.graph)
 
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12
-if int((tf.__version__).split('.')[1]) < 12:
+if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
     init = tf.initialize_all_variables()
 else:
     init = tf.global_variables_initializer()

tensorflowTUT/tf16_classification/for_you_to_practice.py

@@ -35,7 +35,7 @@ def add_layer(inputs, in_size, out_size, activation_function=None, ):
 # important step
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12
-if int((tf.__version__).split('.')[1]) < 12:
+if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
     init = tf.initialize_all_variables()
 else:
     init = tf.global_variables_initializer()

tensorflowTUT/tf16_classification/full_code.py

@@ -47,7 +47,7 @@ def compute_accuracy(v_xs, v_ys):
 # important step
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12
-if int((tf.__version__).split('.')[1]) < 12:
+if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
     init = tf.initialize_all_variables()
 else:
     init = tf.global_variables_initializer()

tensorflowTUT/tf17_dropout/for_you_to_practice.py

@@ -54,7 +54,7 @@ def add_layer(inputs, in_size, out_size, layer_name, activation_function=None, )
 
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12
-if int((tf.__version__).split('.')[1]) < 12:
+if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
     init = tf.initialize_all_variables()
 else:
     init = tf.global_variables_initializer()

tensorflowTUT/tf17_dropout/full_code.py

@@ -58,7 +58,7 @@ def add_layer(inputs, in_size, out_size, layer_name, activation_function=None, )
 
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12
-if int((tf.__version__).split('.')[1]) < 12:
+if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
     init = tf.initialize_all_variables()
 else:
     init = tf.global_variables_initializer()

tensorflowTUT/tf18_CNN2/for_you_to_practice.py

@@ -51,7 +51,7 @@ def max_pool_2x2(x):
 # important step
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12
-if int((tf.__version__).split('.')[1]) < 12:
+if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
     init = tf.initialize_all_variables()
 else:
     init = tf.global_variables_initializer()

tensorflowTUT/tf18_CNN2/full_code.py

@@ -60,7 +60,7 @@ def max_pool_2x2(x):
 # important step
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12
-if int((tf.__version__).split('.')[1]) < 12:
+if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
     init = tf.initialize_all_variables()
 else:
     init = tf.global_variables_initializer()

tensorflowTUT/tf18_CNN3/for_you_to_practice.py

@@ -60,7 +60,7 @@ def max_pool_2x2(x):
 # important step
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12
-if int((tf.__version__).split('.')[1]) < 12:
+if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
     init = tf.initialize_all_variables()
 else:
     init = tf.global_variables_initializer()

tensorflowTUT/tf18_CNN3/full_code.py

@@ -79,7 +79,7 @@ def max_pool_2x2(x):
 # important step
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12
-if int((tf.__version__).split('.')[1]) < 12:
+if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
     init = tf.initialize_all_variables()
 else:
     init = tf.global_variables_initializer()

tensorflowTUT/tf19_saver.py

@@ -17,7 +17,7 @@
 
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12
-# if int((tf.__version__).split('.')[1]) < 12:
+# if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
 #     init = tf.initialize_all_variables()
 # else:
 #     init = tf.global_variables_initializer()

tensorflowTUT/tf20_RNN2.2/for_practicing.py

@@ -103,7 +103,7 @@ def _bias_variable(self, shape, name='biases'):
 
     # tf.initialize_all_variables() no long valid from
     # 2017-03-02 if using tensorflow >= 0.12
-    if int((tf.__version__).split('.')[1]) < 12:
+    if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
         init = tf.initialize_all_variables()
     else:
         init = tf.global_variables_initializer()

tensorflowTUT/tf20_RNN2.2/full_code.py

@@ -119,7 +119,7 @@ def _bias_variable(self, shape, name='biases'):
     writer = tf.train.SummaryWriter("logs", sess.graph)
     # tf.initialize_all_variables() no long valid from
     # 2017-03-02 if using tensorflow >= 0.12
-    if int((tf.__version__).split('.')[1]) < 12:
+    if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
         init = tf.initialize_all_variables()
     else:
         init = tf.global_variables_initializer()

tensorflowTUT/tf20_RNN2/for_you_to_practice.py

@@ -71,7 +71,7 @@ def RNN(X, weights, biases):
 with tf.Session() as sess:
     # tf.initialize_all_variables() no long valid from
     # 2017-03-02 if using tensorflow >= 0.12
-    if int((tf.__version__).split('.')[1]) < 12:
+    if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
         init = tf.initialize_all_variables()
     else:
         init = tf.global_variables_initializer()

tensorflowTUT/tf20_RNN2/full_code.py

@@ -101,7 +101,7 @@ def RNN(X, weights, biases):
 with tf.Session() as sess:
     # tf.initialize_all_variables() no long valid from
     # 2017-03-02 if using tensorflow >= 0.12
-    if int((tf.__version__).split('.')[1]) < 12:
+    if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
         init = tf.initialize_all_variables()
     else:
         init = tf.global_variables_initializer()

tensorflowTUT/tf21_autoencoder/for_practicing.py

@@ -74,7 +74,7 @@ def decoder(x):
 with tf.Session() as sess:
     # tf.initialize_all_variables() no long valid from
     # 2017-03-02 if using tensorflow >= 0.12
-    if int((tf.__version__).split('.')[1]) < 12:
+    if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
         init = tf.initialize_all_variables()
     else:
         init = tf.global_variables_initializer()

tensorflowTUT/tf21_autoencoder/full_code.py

@@ -152,7 +152,7 @@ def decoder(x):
 with tf.Session() as sess:
     # tf.initialize_all_variables() no long valid from
     # 2017-03-02 if using tensorflow >= 0.12
-    if int((tf.__version__).split('.')[1]) < 12:
+    if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
         init = tf.initialize_all_variables()
     else:
         init = tf.global_variables_initializer()

tensorflowTUT/tf22_scope/tf22_RNN_scope.py

@@ -113,7 +113,7 @@ def _bias_variable(shape, name='biases'):
         test_rnn2 = RNN(test_config)
         # tf.initialize_all_variables() no long valid from
         # 2017-03-02 if using tensorflow >= 0.12
-        if int((tf.__version__).split('.')[1]) < 12:
+        if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
             init = tf.initialize_all_variables()
         else:
             init = tf.global_variables_initializer()

tensorflowTUT/tf22_scope/tf22_scope.py

@@ -36,7 +36,7 @@
 with tf.Session() as sess:
     # tf.initialize_all_variables() no long valid from
     # 2017-03-02 if using tensorflow >= 0.12
-    if int((tf.__version__).split('.')[1]) < 12:
+    if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
         init = tf.initialize_all_variables()
     else:
         init = tf.global_variables_initializer()

tensorflowTUT/tf23_BN/tf23_BN.py

@@ -154,7 +154,7 @@ def mean_var_with_update():
 train_op_norm, cost_norm, layers_inputs_norm = built_net(xs, ys, norm=True) # with BN
 
 sess = tf.Session()
-if int((tf.__version__).split('.')[1]) < 12:
+if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
     init = tf.initialize_all_variables()
 else:
     init = tf.global_variables_initializer()

tensorflowTUT/tf5_example2/full_code.py

@@ -30,7 +30,7 @@
 sess = tf.Session()
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12
-if int((tf.__version__).split('.')[1]) < 12:
+if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
     init = tf.initialize_all_variables()
 else:
     init = tf.global_variables_initializer()