Adding defun

PiperOrigin-RevId: 205901720

1 files changed, 22 insertions, 2 deletions

diff --git a/tensorflow/contrib/eager/python/examples/generative_examples/dcgan.ipynb b/tensorflow/contrib/eager/python/examples/generative_examples/dcgan.ipynb
index 54cc4dc5da..44ff43a111 100644
--- a/tensorflow/contrib/eager/python/examples/generative_examples/dcgan.ipynb
+++ b/tensorflow/contrib/eager/python/examples/generative_examples/dcgan.ipynb
@@ -29,7 +29,7 @@
       "source": [
         "This notebook demonstrates how to generate images of handwritten digits using [tf.keras](https://www.tensorflow.org/programmers_guide/keras) and [eager execution](https://www.tensorflow.org/programmers_guide/eager). To do so, we use Deep Convolutional Generative Adverserial Networks ([DCGAN](https://arxiv.org/pdf/1511.06434.pdf)).\n",
         "\n",
-        "This model takes about 40 seconds per epoch to train on a single Tesla K80 on Colab, as of July 2018.\n",
+        "This model takes about ~30 seconds per epoch (using tf.contrib.eager.defun to create graph functions) to train on a single Tesla K80 on Colab, as of July 2018.\n",
         "\n",
         "Below is the output generated after training the generator and discriminator models for 150 epochs.\n",
         "\n",
@@ -203,7 +203,7 @@
         "## Write the generator and discriminator models\n",
         "\n",
         "* **Generator** \n",
-        "  * It is responsible for **creating the convincing images good enough to fool the discriminator**.\n",
+        "  * It is responsible for **creating convincing images that are good enough to fool the discriminator**.\n",
         "  * It consists of Conv2DTranspose (Upsampling) layers. We start with a fully connected layer and upsample the image 2 times so as to reach the desired image size (mnist image size) which is (28, 28, 1). \n",
         "  * We use **leaky relu** activation except for the **last layer** which uses **tanh** activation.\n",
         "  \n",
@@ -315,6 +315,26 @@
       ]
     },
     {
+      "cell_type": "code",
+      "execution_count": 0,
+      "metadata": {
+        "colab": {
+          "autoexec": {
+            "startup": false,
+            "wait_interval": 0
+          }
+        },
+        "colab_type": "code",
+        "id": "k1HpMSLImuRi"
+      },
+      "outputs": [],
+      "source": [
+        "# Defun gives 10 secs/epoch performance boost\n",
+        "generator.call = tf.contrib.eager.defun(generator.call)\n",
+        "discriminator.call = tf.contrib.eager.defun(discriminator.call)"
+      ]
+    },
+    {
       "cell_type": "markdown",
       "metadata": {
         "colab_type": "text",