change: tf.initialize_all_variables() no long valid from 2017-03-02 if using tensorflow >= 0.12, use tf.global_variables_initializer() instead

Author: MorvanZhou

tensorflowTUT/tensorflow11_build_network.py

@@ -40,7 +40,9 @@ def add_layer(inputs, in_size, out_size, activation_function=None):
 train_step = tf.train.GradientDescentOptimizer(0.1).minimize(loss)
 
 # important step
-init = tf.initialize_all_variables()
+# tf.initialize_all_variables() no long valid from
+# 2017-03-02 if using tensorflow >= 0.12
+init = tf.global_variables_initializer()
 sess = tf.Session()
 sess.run(init)
 

tensorflowTUT/tensorflow12_plut_result.py

@@ -41,7 +41,9 @@ def add_layer(inputs, in_size, out_size, activation_function=None):
 train_step = tf.train.GradientDescentOptimizer(0.1).minimize(loss)
 
 # important step
-init = tf.initialize_all_variables()
+# tf.initialize_all_variables() no long valid from
+# 2017-03-02 if using tensorflow >= 0.12
+init = tf.global_variables_initializer()
 sess = tf.Session()
 sess.run(init)
 

tensorflowTUT/tensorflow7_variable.py

@@ -16,7 +16,9 @@
 new_value = tf.add(state, one)
 update = tf.assign(state, new_value)
 
-init = tf.initialize_all_variables()  # must have if define variable
+# tf.initialize_all_variables() no long valid from
+# 2017-03-02 if using tensorflow >= 0.12
+init = tf.global_variables_initializer()  # must have if define variable
 
 with tf.Session() as sess:
     sess.run(init)

tensorflowTUT/tf11_build_network/full_code.py

@@ -41,9 +41,10 @@ def add_layer(inputs, in_size, out_size, activation_function=None):
 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
-init = tf.initialize_all_variables()
 sess= tf.Session()
-sess.run(init)
+# tf.initialize_all_variables() no long valid from
+# 2017-03-02 if using tensorflow >= 0.12
+sess.run(tf.global_variables_initializer())
 
 for i in range(1000):
     # training

tensorflowTUT/tf12_plot_result/for_you_to_practice.py

@@ -41,9 +41,10 @@ def add_layer(inputs, in_size, out_size, activation_function=None):
 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
-init = tf.initialize_all_variables()
 sess= tf.Session()
-sess.run(init)
+# tf.initialize_all_variables() no long valid from
+# 2017-03-02 if using tensorflow >= 0.12
+sess.run(tf.global_variables_initializer())
 
 for i in range(1000):
     # training

tensorflowTUT/tf12_plot_result/full_code.py

@@ -41,9 +41,10 @@ def add_layer(inputs, in_size, out_size, activation_function=None):
 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
-init = tf.initialize_all_variables()
-sess= tf.Session()
-sess.run(init)
+sess = tf.Session()
+# tf.initialize_all_variables() no long valid from
+# 2017-03-02 if using tensorflow >= 0.12
+sess.run(tf.global_variables_initializer())
 
 # plot the real data
 fig = plt.figure()

tensorflowTUT/tf14_tensorboard/for_you_to_practice.py

@@ -38,8 +38,9 @@ def add_layer(inputs, in_size, out_size, activation_function=None):
 
 sess = tf.Session()
 
-# important step
-sess.run(tf.initialize_all_variables())
+# tf.initialize_all_variables() no long valid from
+# 2017-03-02 if using tensorflow >= 0.12
+sess.run(tf.global_variables_initializer())
 
 # direct to the local dir and run this in terminal:
 # $ tensorboard --logdir=logs

tensorflowTUT/tf14_tensorboard/full_code.py

@@ -46,8 +46,9 @@ def add_layer(inputs, in_size, out_size, activation_function=None):
 
 sess = tf.Session()
 writer = tf.train.SummaryWriter("logs/", sess.graph)
-# important step
-sess.run(tf.initialize_all_variables())
+# tf.initialize_all_variables() no long valid from
+# 2017-03-02 if using tensorflow >= 0.12
+sess.run(tf.global_variables_initializer())
 
 # direct to the local dir and run this in terminal:
 # $ tensorboard --logdir=logs

tensorflowTUT/tf15_tensorboard/for_you_to_practice.py

@@ -52,7 +52,8 @@ def add_layer(inputs, in_size, out_size, activation_function=None):
 sess = tf.Session()
 writer = tf.train.SummaryWriter("logs/", sess.graph)
 # important step
-sess.run(tf.initialize_all_variables())
-
+# tf.initialize_all_variables() no long valid from
+# 2017-03-02 if using tensorflow >= 0.12
+sess.run(tf.global_variables_initializer())
 # direct to the local dir and run this in terminal:
 # $ tensorboard --logdir=logs

tensorflowTUT/tf15_tensorboard/full_code.py

@@ -58,9 +58,9 @@ def add_layer(inputs, in_size, out_size, n_layer, activation_function=None):
 sess = tf.Session()
 merged = tf.merge_all_summaries()
 writer = tf.train.SummaryWriter("logs/", sess.graph)
-# important step
-sess.run(tf.initialize_all_variables())
-
+# tf.initialize_all_variables() no long valid from
+# 2017-03-02 if using tensorflow >= 0.12
+sess.run(tf.global_variables_initializer())
 for i in range(1000):
     sess.run(train_step, feed_dict={xs: x_data, ys: y_data})
     if i % 50 == 0:

tensorflowTUT/tf16_classification/for_you_to_practice.py

@@ -33,7 +33,9 @@ def add_layer(inputs, in_size, out_size, activation_function=None, ):
 
 sess = tf.Session()
 # important step
-sess.run(tf.initialize_all_variables())
+# tf.initialize_all_variables() no long valid from
+# 2017-03-02 if using tensorflow >= 0.12
+sess.run(tf.global_variables_initializer())
 
 for i in range(1000):
     pass

tensorflowTUT/tf16_classification/full_code.py

@@ -45,7 +45,9 @@ def compute_accuracy(v_xs, v_ys):
 
 sess = tf.Session()
 # important step
-sess.run(tf.initialize_all_variables())
+# tf.initialize_all_variables() no long valid from
+# 2017-03-02 if using tensorflow >= 0.12
+sess.run(tf.global_variables_initializer())
 
 for i in range(1000):
     batch_xs, batch_ys = mnist.train.next_batch(100)

tensorflowTUT/tf17_dropout/for_you_to_practice.py

@@ -52,7 +52,9 @@ def add_layer(inputs, in_size, out_size, layer_name, activation_function=None, )
 merged = tf.merge_all_summaries()
 # summary writer goes in here
 
-sess.run(tf.initialize_all_variables())
+# tf.initialize_all_variables() no long valid from
+# 2017-03-02 if using tensorflow >= 0.12
+sess.run(tf.global_variables_initializer())
 
 for i in range(500):
     sess.run(train_step, feed_dict={xs: X_train, ys: y_train})

tensorflowTUT/tf17_dropout/full_code.py

@@ -56,7 +56,9 @@ def add_layer(inputs, in_size, out_size, layer_name, activation_function=None, )
 train_writer = tf.train.SummaryWriter("logs/train", sess.graph)
 test_writer = tf.train.SummaryWriter("logs/test", sess.graph)
 
-sess.run(tf.initialize_all_variables())
+# tf.initialize_all_variables() no long valid from
+# 2017-03-02 if using tensorflow >= 0.12
+sess.run(tf.global_variables_initializer())
 
 for i in range(500):
     # here to determine the keeping probability

tensorflowTUT/tf18_CNN2/for_you_to_practice.py

@@ -49,7 +49,9 @@ def max_pool_2x2(x):
 
 sess = tf.Session()
 # important step
-sess.run(tf.initialize_all_variables())
+# tf.initialize_all_variables() no long valid from
+# 2017-03-02 if using tensorflow >= 0.12
+sess.run(tf.global_variables_initializer())
 
 for i in range(1000):
     batch_xs, batch_ys = mnist.train.next_batch(100)

tensorflowTUT/tf18_CNN2/full_code.py

@@ -58,7 +58,9 @@ def max_pool_2x2(x):
 
 sess = tf.Session()
 # important step
-sess.run(tf.initialize_all_variables())
+# tf.initialize_all_variables() no long valid from
+# 2017-03-02 if using tensorflow >= 0.12
+sess.run(tf.global_variables_initializer())
 
 for i in range(1000):
     batch_xs, batch_ys = mnist.train.next_batch(100)

tensorflowTUT/tf18_CNN3/for_you_to_practice.py

@@ -58,7 +58,9 @@ def max_pool_2x2(x):
 
 sess = tf.Session()
 # important step
-sess.run(tf.initialize_all_variables())
+# tf.initialize_all_variables() no long valid from
+# 2017-03-02 if using tensorflow >= 0.12
+sess.run(tf.global_variables_initializer())
 
 for i in range(1000):
     batch_xs, batch_ys = mnist.train.next_batch(100)

tensorflowTUT/tf18_CNN3/full_code.py

@@ -77,7 +77,9 @@ def max_pool_2x2(x):
 
 sess = tf.Session()
 # important step
-sess.run(tf.initialize_all_variables())
+# tf.initialize_all_variables() no long valid from
+# 2017-03-02 if using tensorflow >= 0.12
+sess.run(tf.global_variables_initializer())
 
 for i in range(1000):
     batch_xs, batch_ys = mnist.train.next_batch(100)

tensorflowTUT/tf19_saver.py

@@ -15,7 +15,9 @@
 ##W = tf.Variable([[1,2,3],[3,4,5]], dtype=tf.float32, name='weights')
 ##b = tf.Variable([[1,2,3]], dtype=tf.float32, name='biases')
 ##
-##init= tf.initialize_all_variables()
+## tf.initialize_all_variables() no long valid from
+## 2017-03-02 if using tensorflow >= 0.12
+##init = tf.global_variables_initializer()
 ##
 ##saver = tf.train.Saver()
 ##

tensorflowTUT/tf20_RNN2.2/for_practicing.py

@@ -101,7 +101,9 @@ def _bias_variable(self, shape, name='biases'):
     # relocate to the local dir and run this line to view it on Chrome (http://0.0.0.0:6006/):
     # $ tensorboard --logdir='logs'
 
-    sess.run(tf.initialize_all_variables())
+    # tf.initialize_all_variables() no long valid from
+    # 2017-03-02 if using tensorflow >= 0.12
+    sess.run(tf.global_variables_initializer())
     plt.ion()
     plt.show()
     for i in range(200):

tensorflowTUT/tf20_RNN2.2/full_code.py

@@ -117,7 +117,9 @@ def _bias_variable(self, shape, name='biases'):
     sess = tf.Session()
     merged = tf.merge_all_summaries()
     writer = tf.train.SummaryWriter("logs", sess.graph)
-    sess.run(tf.initialize_all_variables())
+    # tf.initialize_all_variables() no long valid from
+    # 2017-03-02 if using tensorflow >= 0.12
+    sess.run(tf.global_variables_initializer())
     # relocate to the local dir and run this line to view it on Chrome (http://0.0.0.0:6006/):
     # $ tensorboard --logdir='logs'
 

tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1480137911.Morvan

@@ -68,9 +68,10 @@ def RNN(X, weights, biases):
 correct_pred = tf.equal(tf.argmax(pred, 1), tf.argmax(y, 1))
 accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))
 
-init = tf.initialize_all_variables()
 with tf.Session() as sess:
-    sess.run(init)
+    # tf.initialize_all_variables() no long valid from
+    # 2017-03-02 if using tensorflow >= 0.12
+    sess.run(tf.global_variables_initializer())
     step = 0
     while step * batch_size < training_iters:
         batch_xs, batch_ys = mnist.train.next_batch(batch_size)

tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1480137928.Morvan

@@ -98,9 +98,10 @@ def RNN(X, weights, biases):
 correct_pred = tf.equal(tf.argmax(pred, 1), tf.argmax(y, 1))
 accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))
 
-init = tf.initialize_all_variables()
 with tf.Session() as sess:
-    sess.run(init)
+    # tf.initialize_all_variables() no long valid from
+    # 2017-03-02 if using tensorflow >= 0.12
+    sess.run(tf.global_variables_initializer())
     step = 0
     while step * batch_size < training_iters:
         batch_xs, batch_ys = mnist.train.next_batch(batch_size)

tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1480137982.Morvan

@@ -70,12 +70,11 @@ def decoder(x):
 cost = tf.reduce_mean(tf.pow(y_true - y_pred, 2))
 optimizer = tf.train.AdamOptimizer(learning_rate).minimize(cost)
 
-# Initializing the variables
-init = tf.initialize_all_variables()
-
 # Launch the graph
 with tf.Session() as sess:
-    sess.run(init)
+    # tf.initialize_all_variables() no long valid from
+    # 2017-03-02 if using tensorflow >= 0.12
+    sess.run(tf.global_variables_initializer())
     total_batch = int(mnist.train.num_examples/batch_size)
     # Training cycle
     for epoch in range(training_epochs):

tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1480139491.Morvan

@@ -147,12 +147,12 @@ def decoder(x):
 cost = tf.reduce_mean(tf.pow(y_true - y_pred, 2))
 optimizer = tf.train.AdamOptimizer(learning_rate).minimize(cost)
 
-# Initializing the variables
-init = tf.initialize_all_variables()
 
 # Launch the graph
 with tf.Session() as sess:
-    sess.run(init)
+    # tf.initialize_all_variables() no long valid from
+    # 2017-03-02 if using tensorflow >= 0.12
+    sess.run(tf.global_variables_initializer())
     total_batch = int(mnist.train.num_examples/batch_size)
     # Training cycle
     for epoch in range(training_epochs):

tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1480139516.Morvan

@@ -111,4 +111,6 @@ def _bias_variable(shape, name='biases'):
         train_rnn2 = RNN(train_config)
         scope.reuse_variables()
         test_rnn2 = RNN(test_config)
-        sess.run(tf.initialize_all_variables())
+        # tf.initialize_all_variables() no long valid from
+        # 2017-03-02 if using tensorflow >= 0.12
+        sess.run(tf.global_variables_initializer())

tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1480162641.Morvan

@@ -34,7 +34,9 @@
     var3_reuse = tf.get_variable(name='var3',)
 
 with tf.Session() as sess:
-    sess.run(tf.initialize_all_variables())
+    # tf.initialize_all_variables() no long valid from
+    # 2017-03-02 if using tensorflow >= 0.12
+    sess.run(tf.global_variables_initializer())
     print(var3.name)            # a_variable_scope/var3:0
     print(sess.run(var3))       # [ 3.]
     print(var4.name)            # a_variable_scope/var4:0

tensorflowTUT/tf20_RNN2/for_you_to_practice.py

@@ -28,7 +28,9 @@
 ### create tensorflow structure end ###
 
 sess = tf.Session()
-sess.run(init)          # Very important
+# tf.initialize_all_variables() no long valid from
+# 2017-03-02 if using tensorflow >= 0.12
+sess.run(tf.global_variables_initializer())
 
 for step in range(201):
     sess.run(train)