A minor mistake in cross entropy loss (#357)

tf.reduce_mean(-tf.reduce_sum(y_true * tf.math.log(y_pred),1)) or else it simply finds the sum and the reduced mean remains the sum itself.

tensorflow_v2/notebooks/2_BasicModels/logistic_regression.ipynb

@@ -109,7 +109,7 @@
     "    # Clip prediction values to avoid log(0) error.\n",
     "    y_pred = tf.clip_by_value(y_pred, 1e-9, 1.)\n",
     "    # Compute cross-entropy.\n",
-    "    return tf.reduce_mean(-tf.reduce_sum(y_true * tf.math.log(y_pred)))\n",
+    "    return tf.reduce_mean(-tf.reduce_sum(y_true * tf.math.log(y_pred),1))\n",
     "\n",
     "# Accuracy metric.\n",
     "def accuracy(y_pred, y_true):\n",