edit tf init

Author: MorvanZhou

tensorflowTUT/tensorflow11_build_network.py

@@ -42,7 +42,10 @@ 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
-init = tf.global_variables_initializer()
+if int((tf.__version__).split('.')[1]) < 12:
+    init = tf.initialize_all_variables()
+else:
+    init = tf.global_variables_initializer()
 sess = tf.Session()
 sess.run(init)
 

tensorflowTUT/tensorflow12_plut_result.py

@@ -43,7 +43,10 @@ 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
-init = tf.global_variables_initializer()
+if int((tf.__version__).split('.')[1]) < 12:
+    init = tf.initialize_all_variables()
+else:
+    init = tf.global_variables_initializer()
 sess = tf.Session()
 sess.run(init)
 

tensorflowTUT/tensorflow7_variable.py

@@ -18,7 +18,10 @@
 
 # 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
+if int((tf.__version__).split('.')[1]) < 12:
+    init = tf.initialize_all_variables()
+else:
+    init = tf.global_variables_initializer()
 
 with tf.Session() as sess:
     sess.run(init)

tensorflowTUT/tf11_build_network/full_code.py

@@ -44,7 +44,11 @@ def add_layer(inputs, in_size, out_size, activation_function=None):
 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())
+if int((tf.__version__).split('.')[1]) < 12:
+    init = tf.initialize_all_variables()
+else:
+    init = tf.global_variables_initializer()
+sess.run(init)
 
 for i in range(1000):
     # training

tensorflowTUT/tf12_plot_result/for_you_to_practice.py

@@ -44,7 +44,11 @@ def add_layer(inputs, in_size, out_size, activation_function=None):
 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())
+if int((tf.__version__).split('.')[1]) < 12:
+    init = tf.initialize_all_variables()
+else:
+    init = tf.global_variables_initializer()
+sess.run(init)
 
 for i in range(1000):
     # training

tensorflowTUT/tf12_plot_result/full_code.py

@@ -44,7 +44,11 @@ def add_layer(inputs, in_size, out_size, activation_function=None):
 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())
+if int((tf.__version__).split('.')[1]) < 12:
+    init = tf.initialize_all_variables()
+else:
+    init = tf.global_variables_initializer()
+sess.run(init)
 
 # plot the real data
 fig = plt.figure()

tensorflowTUT/tf14_tensorboard/for_you_to_practice.py

@@ -40,7 +40,11 @@ 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
-sess.run(tf.global_variables_initializer())
+if int((tf.__version__).split('.')[1]) < 12:
+    init = tf.initialize_all_variables()
+else:
+    init = tf.global_variables_initializer()
+sess.run(init)
 
 # direct to the local dir and run this in terminal:
 # $ tensorboard --logdir=logs

tensorflowTUT/tf14_tensorboard/full_code.py

@@ -51,7 +51,11 @@ 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
-sess.run(tf.global_variables_initializer())
+if int((tf.__version__).split('.')[1]) < 12:
+    init = tf.initialize_all_variables()
+else:
+    init = tf.global_variables_initializer()
+sess.run(init)
 
 # direct to the local dir and run this in terminal:
 # $ tensorboard --logdir=logs

tensorflowTUT/tf15_tensorboard/for_you_to_practice.py

@@ -54,6 +54,10 @@ 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
-sess.run(tf.global_variables_initializer())
+if int((tf.__version__).split('.')[1]) < 12:
+    init = tf.initialize_all_variables()
+else:
+    init = tf.global_variables_initializer()
+sess.run(init)
 # direct to the local dir and run this in terminal:
 # $ tensorboard --logdir=logs

tensorflowTUT/tf15_tensorboard/full_code.py

@@ -63,7 +63,11 @@ def add_layer(inputs, in_size, out_size, n_layer, activation_function=None):
 
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12
-sess.run(tf.global_variables_initializer())
+if int((tf.__version__).split('.')[1]) < 12:
+    init = tf.initialize_all_variables()
+else:
+    init = tf.global_variables_initializer()
+sess.run(init)
 
 for i in range(1000):
     sess.run(train_step, feed_dict={xs: x_data, ys: y_data})

tensorflowTUT/tf16_classification/for_you_to_practice.py

@@ -35,7 +35,11 @@ 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
-sess.run(tf.global_variables_initializer())
+if int((tf.__version__).split('.')[1]) < 12:
+    init = tf.initialize_all_variables()
+else:
+    init = tf.global_variables_initializer()
+sess.run(init)
 
 for i in range(1000):
     pass

tensorflowTUT/tf16_classification/full_code.py

@@ -47,7 +47,11 @@ 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
-sess.run(tf.global_variables_initializer())
+if int((tf.__version__).split('.')[1]) < 12:
+    init = tf.initialize_all_variables()
+else:
+    init = tf.global_variables_initializer()
+sess.run(init)
 
 for i in range(1000):
     batch_xs, batch_ys = mnist.train.next_batch(100)

tensorflowTUT/tf17_dropout/for_you_to_practice.py

@@ -54,7 +54,11 @@ 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
-sess.run(tf.global_variables_initializer())
+if int((tf.__version__).split('.')[1]) < 12:
+    init = tf.initialize_all_variables()
+else:
+    init = tf.global_variables_initializer()
+sess.run(init)
 
 for i in range(500):
     sess.run(train_step, feed_dict={xs: X_train, ys: y_train})

tensorflowTUT/tf17_dropout/full_code.py

@@ -58,7 +58,11 @@ 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
-sess.run(tf.global_variables_initializer())
+if int((tf.__version__).split('.')[1]) < 12:
+    init = tf.initialize_all_variables()
+else:
+    init = tf.global_variables_initializer()
+sess.run(init)
 
 for i in range(500):
     # here to determine the keeping probability

tensorflowTUT/tf18_CNN2/for_you_to_practice.py

@@ -51,7 +51,11 @@ def max_pool_2x2(x):
 # important step
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12
-sess.run(tf.global_variables_initializer())
+if int((tf.__version__).split('.')[1]) < 12:
+    init = tf.initialize_all_variables()
+else:
+    init = tf.global_variables_initializer()
+sess.run(init)
 
 for i in range(1000):
     batch_xs, batch_ys = mnist.train.next_batch(100)

tensorflowTUT/tf18_CNN2/full_code.py

@@ -60,7 +60,11 @@ def max_pool_2x2(x):
 # important step
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12
-sess.run(tf.global_variables_initializer())
+if int((tf.__version__).split('.')[1]) < 12:
+    init = tf.initialize_all_variables()
+else:
+    init = tf.global_variables_initializer()
+sess.run(init)
 
 for i in range(1000):
     batch_xs, batch_ys = mnist.train.next_batch(100)

tensorflowTUT/tf18_CNN3/for_you_to_practice.py

@@ -60,7 +60,11 @@ def max_pool_2x2(x):
 # important step
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12
-sess.run(tf.global_variables_initializer())
+if int((tf.__version__).split('.')[1]) < 12:
+    init = tf.initialize_all_variables()
+else:
+    init = tf.global_variables_initializer()
+sess.run(init)
 
 for i in range(1000):
     batch_xs, batch_ys = mnist.train.next_batch(100)

tensorflowTUT/tf18_CNN3/full_code.py

@@ -79,7 +79,11 @@ def max_pool_2x2(x):
 # important step
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12
-sess.run(tf.global_variables_initializer())
+if int((tf.__version__).split('.')[1]) < 12:
+    init = tf.initialize_all_variables()
+else:
+    init = tf.global_variables_initializer()
+sess.run(init)
 
 for i in range(1000):
     batch_xs, batch_ys = mnist.train.next_batch(100)

tensorflowTUT/tf19_saver.py

@@ -10,22 +10,25 @@
 import tensorflow as tf
 import numpy as np
 
-## Save to file
+# Save to file
 # remember to define the same dtype and shape when restore
-##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')
-##
-## 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()
-##
-##with tf.Session() as sess:
-##    sess.run(init)
-##    save_path = saver.save(sess, "my_net/save_net.ckpt")
-##    print("Save to path: ", save_path)
-##
+# 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')
+
+# tf.initialize_all_variables() no long valid from
+# 2017-03-02 if using tensorflow >= 0.12
+# if int((tf.__version__).split('.')[1]) < 12:
+#     init = tf.initialize_all_variables()
+# else:
+#     init = tf.global_variables_initializer()
+#
+# saver = tf.train.Saver()
+#
+# with tf.Session() as sess:
+#    sess.run(init)
+#    save_path = saver.save(sess, "my_net/save_net.ckpt")
+#    print("Save to path: ", save_path)
+
 
 ################################################
 # restore variables

tensorflowTUT/tf20_RNN2.2/for_practicing.py

@@ -103,7 +103,11 @@ def _bias_variable(self, shape, name='biases'):
 
     # tf.initialize_all_variables() no long valid from
     # 2017-03-02 if using tensorflow >= 0.12
-    sess.run(tf.global_variables_initializer())
+    if int((tf.__version__).split('.')[1]) < 12:
+        init = tf.initialize_all_variables()
+    else:
+        init = tf.global_variables_initializer()
+    sess.run(init)
     plt.ion()
     plt.show()
     for i in range(200):

tensorflowTUT/tf20_RNN2.2/full_code.py

@@ -119,7 +119,11 @@ 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
-    sess.run(tf.global_variables_initializer())
+    if int((tf.__version__).split('.')[1]) < 12:
+        init = tf.initialize_all_variables()
+    else:
+        init = tf.global_variables_initializer()
+    sess.run(init)
     # 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/for_you_to_practice.py

@@ -71,7 +71,11 @@ 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
-    sess.run(tf.global_variables_initializer())
+    if int((tf.__version__).split('.')[1]) < 12:
+        init = tf.initialize_all_variables()
+    else:
+        init = tf.global_variables_initializer()
+    sess.run(init)
     step = 0
     while step * batch_size < training_iters:
         batch_xs, batch_ys = mnist.train.next_batch(batch_size)

tensorflowTUT/tf20_RNN2/full_code.py

@@ -101,7 +101,11 @@ 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
-    sess.run(tf.global_variables_initializer())
+    if int((tf.__version__).split('.')[1]) < 12:
+        init = tf.initialize_all_variables()
+    else:
+        init = tf.global_variables_initializer()
+    sess.run(init)
     step = 0
     while step * batch_size < training_iters:
         batch_xs, batch_ys = mnist.train.next_batch(batch_size)

tensorflowTUT/tf21_autoencoder/for_practicing.py

@@ -74,7 +74,11 @@ def decoder(x):
 with tf.Session() as sess:
     # tf.initialize_all_variables() no long valid from
     # 2017-03-02 if using tensorflow >= 0.12
-    sess.run(tf.global_variables_initializer())
+    if int((tf.__version__).split('.')[1]) < 12:
+        init = tf.initialize_all_variables()
+    else:
+        init = tf.global_variables_initializer()
+    sess.run(init)
     total_batch = int(mnist.train.num_examples/batch_size)
     # Training cycle
     for epoch in range(training_epochs):

tensorflowTUT/tf21_autoencoder/full_code.py

@@ -152,7 +152,11 @@ def decoder(x):
 with tf.Session() as sess:
     # tf.initialize_all_variables() no long valid from
     # 2017-03-02 if using tensorflow >= 0.12
-    sess.run(tf.global_variables_initializer())
+    if int((tf.__version__).split('.')[1]) < 12:
+        init = tf.initialize_all_variables()
+    else:
+        init = tf.global_variables_initializer()
+    sess.run(init)
     total_batch = int(mnist.train.num_examples/batch_size)
     # Training cycle
     for epoch in range(training_epochs):

tensorflowTUT/tf22_scope/tf22_RNN_scope.py

@@ -113,4 +113,8 @@ 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
-        sess.run(tf.global_variables_initializer())
+        if int((tf.__version__).split('.')[1]) < 12:
+            init = tf.initialize_all_variables()
+        else:
+            init = tf.global_variables_initializer()
+        sess.run(init)

tensorflowTUT/tf22_scope/tf22_scope.py

@@ -36,7 +36,11 @@
 with tf.Session() as sess:
     # tf.initialize_all_variables() no long valid from
     # 2017-03-02 if using tensorflow >= 0.12
-    sess.run(tf.global_variables_initializer())
+    if int((tf.__version__).split('.')[1]) < 12:
+        init = tf.initialize_all_variables()
+    else:
+        init = tf.global_variables_initializer()
+    sess.run(init)
     print(var3.name)            # a_variable_scope/var3:0
     print(sess.run(var3))       # [ 3.]
     print(var4.name)            # a_variable_scope/var4:0

tensorflowTUT/tf23_BN/tf23_BN.py

@@ -154,7 +154,11 @@ def mean_var_with_update():
 train_op_norm, cost_norm, layers_inputs_norm = built_net(xs, ys, norm=True) # with BN
 
 sess = tf.Session()
-sess.run(tf.global_variables_initializer())
+if int((tf.__version__).split('.')[1]) < 12:
+    init = tf.initialize_all_variables()
+else:
+    init = tf.global_variables_initializer()
+sess.run(init)
 
 # record cost
 cost_his = []

tensorflowTUT/tf5_example2/full_code.py

@@ -30,7 +30,11 @@
 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())
+if int((tf.__version__).split('.')[1]) < 12:
+    init = tf.initialize_all_variables()
+else:
+    init = tf.global_variables_initializer()
+sess.run(init)
 
 for step in range(201):
     sess.run(train)