message: [XLA] Update jit_compile tutorial to mention experimental_get_compiler_ir
diff: "accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))\n",
  "print(\"Prediction accuracy after training: %s\" % accuracy)"
  ]
  + },
  + {
  + "cell_type": "markdown",
  + "metadata": {
  + "id": "PXoOjJnuZRaV"
  + },
  + "source": [
  + "Behind the scenes, the XLA compiler has compiled the entire TF function to HLO, which has enabled fusion optimizations. Using the introspection facilities, we can see the HLO code (other interesting possible values for \"stage\" are `optimized_hlo` for HLO after optimizations and `optimized_hlo_dot` for a Graphviz graph):"
  + ]
  + },
  + {
  + "cell_type": "code",
  + "execution_count": null,
  + "metadata": {
  + "id": "_a8GsNLVaLSQ"
  + },
  + "outputs": [],
  + "source": [
  + "print(train_mnist.experimental_get_compiler_ir(images, labels)(stage='hlo'))"
  + ]
  }
  ],
  "metadata": {
  "colab": {
  "collapsed_sections": [],
  + "last_runtime": {
  + "build_target": "//learning/deepmind/public/tools/ml_python:ml_notebook",
  + "kind": "private"
  + },
  "name": "Use XLA with tf.function",
  + "private_outputs": true,
  "provenance": [],
  "toc_visible": true
  },
  