message: Added license for the test image
diff: "\n",
  "![alt text](https://tensorflow.org/images/surf.jpg) \n",
  "\n",
  - "NOTE: This image was originally hosted at [https://commons.wikimedia.org/wiki/Surfing#/media/File:Surfing_in_Hawaii.jpg](https://commons.wikimedia.org/wiki/Surfing#/media/File:Surfing_in_Hawaii.jpg)\n",
  + "[Image Source](https://commons.wikimedia.org/wiki/Surfing#/media/File:Surfing_in_Hawaii.jpg), License: Public Domain\n",
  "\n",
  "Our goal is generate a caption, such as \"a surfer riding on a wave\". Here, we'll use an attention based model. This enables us to see which parts of the image the model focuses on as it generates a caption.\n",
  "\n",
  "\n",
  "The code requires TensorFlow version >=1.9. If you're running this in [Colab]()\n",
  "\n",
  - "In this example, we're training on a relatively small amount of data as an example. On a single P100 GPU, this example will take about ~2 hours to train. We train on the first 30,000 captions (corresponding to about ~20,000 images depending on shuffling, as there are multiple captions per image in the dataset)"
  + "In this example, we're training on a relatively small amount of data as an example. On a single P100 GPU, this example will take about ~2 hours to train. We train on the first 30,000 captions (corresponding to about ~20,000 images depending on shuffling, as there are multiple captions per image in the dataset)\n"
  ]
  },
  {
  "# NOTE: Be sure to set num_parallel_calls to the number of CPU cores you have\n",
  "# https://www.tensorflow.org/api_docs/python/tf/py_func\n",
  "dataset = dataset.map(lambda item1, item2: tf.py_func(\n",
  - " map_func, [item1, item2], [tf.float32, tf.int32]), num_parallel_calls=16)\n",
  + " map_func, [item1, item2], [tf.float32, tf.int32]), num_parallel_calls=8)\n",
  "\n",
  "# shuffling and batching\n",
  "dataset = dataset.shuffle(BUFFER_SIZE)\n",
  