Refactor autoencoders for TF1.0

Signed-off-by: Norman Heckscher <[email protected]>
aymericdamien · Jan 14, 2017 · 6985952 · 6985952 · tgsmith61591 · Feb 20, 2017
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commit 6985952
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diff --git a/examples/3_NeuralNetworks/autoencoder.py b/examples/3_NeuralNetworks/autoencoder.py
@@ -17,7 +17,7 @@
 
 # Import MNIST data
 from tensorflow.examples.tutorials.mnist import input_data
-mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)
+mnist = input_data.read_data_sets("MNIST_data", one_hot=True)
 
 # Parameters
 learning_rate = 0.01
@@ -83,7 +83,7 @@ def decoder(x):
 optimizer = tf.train.RMSPropOptimizer(learning_rate).minimize(cost)
 
 # Initializing the variables
-init = tf.initialize_all_variables()
+init = tf.global_variables_initializer()
 
 # Launch the graph
 with tf.Session() as sess:

diff --git a/notebooks/3_NeuralNetworks/autoencoder.ipynb b/notebooks/3_NeuralNetworks/autoencoder.ipynb