Add comment about the DeviceWrapper class since TF 1.1

14_recurrent_neural_networks.ipynb

@@ -1390,23 +1390,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Alternatively, you can use the Tensorflow class DeviceWrapper - note you can define more than one layer per gpu"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "devices = [\"/gpu:0\", \"/gpu:1\", \"/gpu:2\"]  \n",
-    "cells = []\n",
-    "for dev in devices:\n",
-    "        cell = DeviceWrapper(rnn_cell.BasicRNNCell(num_units=n_neurons), dev)\n",
-    "        cells.append(cell)\n",
-    "\n",
-    "self.multiple_lstm_cells = tf.contrib.rnn.MultiRNNCell(cells, state_is_tuple=True)\n",
-    "outputs, states = tf.nn.dynamic_rnn(multi_layer_cell, X, dtype=tf.float32)"
+    "Alternatively, since TensorFlow 1.1, you can use the `tf.contrib.rnn.DeviceWrapper` class (alias `tf.nn.rnn_cell.DeviceWrapper` since TF 1.2)."
    ]
   },
   {
@@ -2722,21 +2706,21 @@
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
-    "version": 3.0
+    "version": 3
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.6.2"
   },
   "nav_menu": {},
   "toc": {
    "navigate_menu": true,
    "number_sections": true,
    "sideBar": true,
-   "threshold": 6.0,
+   "threshold": 6,
    "toc_cell": false,
    "toc_section_display": "block",
    "toc_window_display": false