"source": [
"# Training computation: logits + cross-entropy loss.\n",
"logits = model(train_data_node, True)\n",
- "loss = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(\n",
+ "loss = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits_v2(\n",
" labels=train_labels_node, logits=logits))\n",
"\n",
"# L2 regularization for the fully connected parameters.\n",
"views": {}
},
"kernelspec": {
- "display_name": "Python [default]",
+ "display_name": "Python 3",
"language": "python",
"name": "python3"
},
}
},
"nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
}