Use frozen_outputs instead of dnn_outputs

ageron · ageron · commit 9a3a2e9de575 · 2019-03-06T20:14:59.000+08:00
diff --git a/11_deep_learning.ipynb b/11_deep_learning.ipynb
@@ -25550,7 +25550,7 @@
     "dnn_outputs = dnn(X, name=\"DNN_A\")\n",
     "frozen_outputs = tf.stop_gradient(dnn_outputs)\n",
     "\n",
-    "logits = tf.layers.dense(dnn_outputs, n_outputs, kernel_initializer=he_init)\n",
+    "logits = tf.layers.dense(frozen_outputs, n_outputs, kernel_initializer=he_init)\n",
     "Y_proba = tf.nn.softmax(logits)\n",
     "\n",
     "xentropy = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=y, logits=logits)\n",
