message: [XLA Docs] Clarify limitations of xla.compile and experimental_compile=True
diff: @@ -95,12 +95,19 @@ standard approach for
  of TF2 programs. You can enable compilation with XLA by setting the
  `experimental_compile` argument of `tf.function` to `True`.
  +Note: `experimental_compile` only works in
  +[eager](https://www.tensorflow.org/guide/eager) mode.
  +
  #### TF1: Use `xla.compile`
  If you are using TF1, you can use the `xla.compile` API for explicit compilation
  using XLA. See the [tutorial colab](./tutorials/xla_compile.ipynb) for usage
  examples.
  +Note: Gradient computation of graph in `xla.compile()` is prohibited because it
  +can cause performance degradation. To avoid this issue, move gradient
  +computation inside `xla.compile()`.
  +
  ### AOT (Ahead-of-time) compilation for CPU with `tfcompile`
  You can also use a standalone [`tfcompile`](./tfcompile) tool,
  