Merge pull request #1558 from rabinadk1:patch-1

PiperOrigin-RevId: 311608883

Author: copybara-github

site/en/tutorials/generative/adversarial_fgsm.ipynb

@@ -155,8 +155,8 @@
         "# Helper function to preprocess the image so that it can be inputted in MobileNetV2\n",
         "def preprocess(image):\n",
         "  image = tf.cast(image, tf.float32)\n",
-        "  image = image/255\n",
         "  image = tf.image.resize(image, (224, 224))\n",
+        "  image = tf.keras.applications.mobilenet_v2.preprocess_input(image)\n",
         "  image = image[None, ...]\n",
         "  return image\n",
         "\n",
@@ -215,7 +215,7 @@
       "outputs": [],
       "source": [
         "plt.figure()\n",
-        "plt.imshow(image[0])\n",
+        "plt.imshow(image[0]*0.5+0.5) # To change [-1, 1] to [0,1]\n",
         "_, image_class, class_confidence = get_imagenet_label(image_probs)\n",
         "plt.title('{} : {:.2f}% Confidence'.format(image_class, class_confidence*100))\n",
         "plt.show()"
@@ -285,7 +285,7 @@
         "label = tf.reshape(label, (1, image_probs.shape[-1]))\n",
         "\n",
         "perturbations = create_adversarial_pattern(image, label)\n",
-        "plt.imshow(perturbations[0])"
+        "plt.imshow(perturbations[0]*0.5+0.5); # To change [-1, 1] to [0,1]"
       ]
     },
     {
@@ -311,7 +311,7 @@
         "def display_images(image, description):\n",
         "  _, label, confidence = get_imagenet_label(pretrained_model.predict(image))\n",
         "  plt.figure()\n",
-        "  plt.imshow(image[0])\n",
+        "  plt.imshow(image[0]*0.5+0.5)\n",
         "  plt.title('{} \\n {} : {:.2f}% Confidence'.format(description,\n",
         "                                                   label, confidence*100))\n",
         "  plt.show()"
@@ -333,7 +333,7 @@
         "\n",
         "for i, eps in enumerate(epsilons):\n",
         "  adv_x = image + eps*perturbations\n",
-        "  adv_x = tf.clip_by_value(adv_x, 0, 1)\n",
+        "  adv_x = tf.clip_by_value(adv_x, -1, 1)\n",
         "  display_images(adv_x, descriptions[i])"
       ]
     },