update new tf types

examples/3 - Neural Networks/alexnet.py

@@ -107,7 +107,7 @@ optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate).minimize(cost)
 
 # 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()

examples/3 - Neural Networks/convolutional_network.py

@@ -86,7 +86,7 @@ optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate).minimize(cost)
 
 # 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()

examples/3 - Neural Networks/recurrent_network.py

@@ -77,7 +77,7 @@ optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate).minimize(cost) #
 
 # 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()

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))"
    ]
   },
   {

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))"
    ]
   },
   {

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))"
    ]
   },
   {