Small fixes in ch7

Author: fchollet

chapter07_working-with-keras.ipynb

@@ -567,7 +567,7 @@
    },
    "outputs": [],
    "source": [
-    "keras.utils.plot_model(model, \"updated_ticket_classifier.png\", show_shapes=True)"
+    "keras.utils.plot_model(new_model, \"updated_ticket_classifier.png\", show_shapes=True)"
    ]
   },
   {
@@ -846,8 +846,7 @@
     "\n",
     "    def __init__(self, name=\"rmse\", **kwargs):\n",
     "        super().__init__(name=name, **kwargs)\n",
-    "        self.mse_sum = self.add_weight(\n",
-    "            name=\"mse_sum\", initializer=\"zeros\")\n",
+    "        self.mse_sum = self.add_weight(name=\"mse_sum\", initializer=\"zeros\")\n",
     "        self.total_samples = self.add_weight(\n",
     "            name=\"total_samples\", initializer=\"zeros\", dtype=\"int32\")\n",
     "\n",
@@ -925,7 +924,7 @@
     "        patience=1,\n",
     "    ),\n",
     "    keras.callbacks.ModelCheckpoint(\n",
-    "        filepath=\"my_checkpoint_path\",\n",
+    "        filepath=\"checkpoint_path.keras\",\n",
     "        monitor=\"val_loss\",\n",
     "        save_best_only=True,\n",
     "    )\n",
@@ -948,7 +947,7 @@
    },
    "outputs": [],
    "source": [
-    "model = keras.models.load_model(\"my_checkpoint_path\")"
+    "model = keras.models.load_model(\"checkpoint_path.keras\")"
    ]
   },
   {
@@ -1024,6 +1023,40 @@
     "### Monitoring and visualization with TensorBoard"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 0,
+   "metadata": {
+    "colab_type": "code"
+   },
+   "outputs": [],
+   "source": [
+    "model = get_mnist_model()\n",
+    "model.compile(optimizer=\"rmsprop\",\n",
+    "              loss=\"sparse_categorical_crossentropy\",\n",
+    "              metrics=[\"accuracy\"])\n",
+    "\n",
+    "tensorboard = keras.callbacks.TensorBoard(\n",
+    "    log_dir=\"/full_path_to_your_log_dir\",\n",
+    ")\n",
+    "model.fit(train_images, train_labels,\n",
+    "          epochs=10,\n",
+    "          validation_data=(val_images, val_labels),\n",
+    "          callbacks=[tensorboard])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 0,
+   "metadata": {
+    "colab_type": "code"
+   },
+   "outputs": [],
+   "source": [
+    "%load_ext tensorboard\n",
+    "%tensorboard --logdir /full_path_to_your_log_dir"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {