update new tf types

kirstenlin · Jan 4, 2016 · ce5f4de · ce5f4de
1 parent c17a5a1
commit ce5f4de
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Showing 6 changed files with 6 additions and 6 deletions.
diff --git a/examples/3 - Neural Networks/alexnet.py b/examples/3 - Neural Networks/alexnet.py
@@ -107,7 +107,7 @@ def alex_net(_X, _weights, _biases, _dropout):
 
 # Evaluate model
 correct_pred = tf.equal(tf.argmax(pred,1), tf.argmax(y,1))
-accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.types.float32))
+accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))
 
 # Initializing the variables
 init = tf.initialize_all_variables()

diff --git a/examples/3 - Neural Networks/convolutional_network.py b/examples/3 - Neural Networks/convolutional_network.py
@@ -86,7 +86,7 @@ def conv_net(_X, _weights, _biases, _dropout):
 
 # Evaluate model
 correct_pred = tf.equal(tf.argmax(pred,1), tf.argmax(y,1))
-accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.types.float32))
+accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))
 
 # Initializing the variables
 init = tf.initialize_all_variables()

diff --git a/examples/3 - Neural Networks/recurrent_network.py b/examples/3 - Neural Networks/recurrent_network.py
@@ -77,7 +77,7 @@ def RNN(_X, _istate, _weights, _biases):
 
 # Evaluate model
 correct_pred = tf.equal(tf.argmax(pred,1), tf.argmax(y,1))
-accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.types.float32))
+accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))
 
 # Initializing the variables
 init = tf.initialize_all_variables()

diff --git a/notebooks/3 - Neural Networks/alexnet.ipynb b/notebooks/3 - Neural Networks/alexnet.ipynb
@@ -221,7 +221,7 @@
    "source": [
     "# Evaluate model\n",
     "correct_pred = tf.equal(tf.argmax(pred,1), tf.argmax(y,1))\n",
-    "accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.types.float32))"
+    "accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))"
    ]
   },
   {

diff --git a/notebooks/3 - Neural Networks/convolutional_network.ipynb b/notebooks/3 - Neural Networks/convolutional_network.ipynb
@@ -204,7 +204,7 @@
    "source": [
     "# Evaluate model\n",
     "correct_pred = tf.equal(tf.argmax(pred,1), tf.argmax(y,1))\n",
-    "accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.types.float32))"
+    "accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))"
    ]
   },
   {

diff --git a/notebooks/3 - Neural Networks/reccurent_network.ipynb b/notebooks/3 - Neural Networks/reccurent_network.ipynb
@@ -142,7 +142,7 @@
     "\n",
     "# Evaluate model\n",
     "correct_pred = tf.equal(tf.argmax(pred,1), tf.argmax(y,1))\n",
-    "accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.types.float32))"
+    "accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))"
    ]
   },
   {