update new tf types

aymericdamien · aymericdamien · commit ce5f4deb31e8 · 2016-01-04T16:10:56.000+08:00
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))"
    ]
   },
   {

Original file line number	Diff line number	Diff line change
`@@ -221,7 +221,7 @@`
`221`	`221`	`"source": [`
`222`	`222`	`"# Evaluate model\n",`
`223`	`223`	`"correct_pred = tf.equal(tf.argmax(pred,1), tf.argmax(y,1))\n",`
`224`		`- "accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.types.float32))"`
	`224`	`+ "accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))"`
`225`	`225`	`]`
`226`	`226`	`},`
`227`	`227`	`{`
Original file line number	Diff line number	Diff line change
`@@ -204,7 +204,7 @@`
`204`	`204`	`"source": [`
`205`	`205`	`"# Evaluate model\n",`
`206`	`206`	`"correct_pred = tf.equal(tf.argmax(pred,1), tf.argmax(y,1))\n",`
`207`		`- "accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.types.float32))"`
	`207`	`+ "accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))"`
`208`	`208`	`]`
`209`	`209`	`},`
`210`	`210`	`{`
Original file line number	Diff line number	Diff line change
`@@ -142,7 +142,7 @@`
`142`	`142`	`"\n",`
`143`	`143`	`"# Evaluate model\n",`
`144`	`144`	`"correct_pred = tf.equal(tf.argmax(pred,1), tf.argmax(y,1))\n",`
`145`		`- "accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.types.float32))"`
	`145`	`+ "accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))"`
`146`	`146`	`]`
`147`	`147`	`},`
`148`	`148`	`{`