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Change to tf.dtype

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This commit is contained in:
Anish Shah 2016-01-04 20:36:24 +05:30
parent 9eb19b66db
commit 3a5c12bd85
3 changed files with 24 additions and 24 deletions
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18
deep-learning/tensor-flow-examples/notebooks/3_neural_networks/alexnet.ipynb
View File

@ -86,9 +86,9 @@
"outputs": [],
"source": [
"# tf Graph input\n",
"x = tf.placeholder(tf.types.float32, [None, n_input])\n",
"y = tf.placeholder(tf.types.float32, [None, n_classes])\n",
"keep_prob = tf.placeholder(tf.types.float32) # dropout (keep probability)"
"x = tf.placeholder(tf.float32, [None, n_input])\n",
"y = tf.placeholder(tf.float32, [None, n_classes])\n",
"keep_prob = tf.placeholder(tf.float32) # dropout (keep probability)"
]
},
{
@ -218,7 +218,7 @@
"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))"
]
},
{
@ -323,21 +323,21 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"display_name": "Python 2",
"language": "python",
"name": "python3"
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.4.3"
"pygments_lexer": "ipython2",
"version": "2.7.5+"
}
},
"nbformat": 4,

18
deep-learning/tensor-flow-examples/notebooks/3_neural_networks/convolutional_network.ipynb
View File

@ -86,9 +86,9 @@
"outputs": [],
"source": [
"# tf Graph input\n",
"x = tf.placeholder(tf.types.float32, [None, n_input])\n",
"y = tf.placeholder(tf.types.float32, [None, n_classes])\n",
"keep_prob = tf.placeholder(tf.types.float32) #dropout (keep probability)"
"x = tf.placeholder(tf.float32, [None, n_input])\n",
"y = tf.placeholder(tf.float32, [None, n_classes])\n",
"keep_prob = tf.placeholder(tf.float32) #dropout (keep probability)"
]
},
{
@ -201,7 +201,7 @@
"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))"
]
},
{
@ -299,21 +299,21 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"display_name": "Python 2",
"language": "python",
"name": "python3"
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.4.3"
"pygments_lexer": "ipython2",
"version": "2.7.5+"
}
},
"nbformat": 4,

12
deep-learning/tensor-flow-examples/notebooks/3_neural_networks/recurrent_network.ipynb
View File

@ -137,7 +137,7 @@
"\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))"
]
},
{
@ -272,21 +272,21 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"display_name": "Python 2",
"language": "python",
"name": "python3"
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.4.3"
"pygments_lexer": "ipython2",
"version": "2.7.5+"
}
},
"nbformat": 4,