message: Reword the docstring of experimental_compile.
diff: @@ -269,14 +269,19 @@ class Function(object):
  conversion options when autograph is set to True.
  experimental_relax_shapes: When true, argument shapes may be relaxed to
  avoid unecessary retracing.
  - experimental_compile: If false, the function is interpreted by the
  - standard TensorFlow executor, which dispatches op kernels one by one as
  - they become executable. If True, the function is compiled by XLA. XLA
  - would fuse all the ops and emit more efficient code to run for some
  - devices (e.g. TPU, XLA_GPU) and some use cases (e.g. dense tensor
  - computation). It requires that the whole function is compilable by XLA.
  - If None (default), compile the function with XLA when running on TPU and
  - use the standard TensorFlow executor when running on other devices.
  + experimental_compile: If false, execute the function in a regular way. The
  + function is optimized by some graph rewrite passes (some ops might be
  + clustered into a single op) and interpreted by the standard TensorFlow
  + executor, which dispatches op kernels one by one as they become
  + executable. Set it to false when directly running a multi-device
  + function on TPUs (e.g. two TPU cores, one TPU core and its
  + host CPU). If True, the function is compiled directly by XLA. XLA would
  + fuse all the ops and emit more efficient code to run for some devices
  + (e.g. TPU, XLA_GPU) and some use cases (e.g. dense tensor computation).
  + It requires that the whole function is compilable by XLA. If None
  + (default), compile the function with XLA when running on TPU and go
  + through the regular function execution path when running on other
  + devices.
  Raises:
  ValueError: if `input_signature` is not None and the `python_function`'s
  @@ -1004,17 +1009,22 @@ def function(func=None,
  autograph=True.
  experimental_relax_shapes: When true, argument shapes may be relaxed to
  avoid unecessary retracing.
  - experimental_compile: If false, the function is interpreted by the standard
  - TensorFlow executor, which dispatches op kernels one by one as they become
  - executable. If True, the function is compiled by XLA
  - (https://www.tensorflow.org/xla). XLA would fuse all the ops and emit more
  - efficient code to run for some devices (e.g. TPU, XLA_GPU) and some use
  - cases (e.g. dense tensor computation). It requires that the whole function
  - is compilable by XLA (e.g. static tensor shape, a subset of operations,
  - no string, compile-time constant input, etc). If None (default),
  - compile the function with XLA when running on TPU and use the standard
  - TensorFlow executor when running on other devices. Note: TensorArrays on
  - TPU don't work with standard TensorFlow executor.
  + experimental_compile: If false, execute the function in a regular way. The
  + function is optimized by some graph rewrite passes (some ops might be
  + clustered into a single op) and interpreted by the standard TensorFlow
  + executor, which dispatches op kernels one by one as they become
  + executable. Set it to false when directly running a multi-device function
  + on TPUs (e.g. two TPU cores, one TPU core and its host CPU). If True, the
  + function is compiled directly by XLA (https://www.tensorflow.org/xla).
  + XLA would fuse all the ops and emit more efficient code to run for some
  + devices (e.g. TPU, XLA_GPU) and some use cases (e.g. dense tensor
  + computation). It requires that the whole function is compilable by XLA
  + (e.g. static tensor shape, a subset of operations, no string, compile-time
  + constant input, etc). If None (default), compile the function with XLA
  + when running on TPU and go through the regular function execution path
  + when running on other devices. Note: TensorArrays on TPU don't work with
  + standard TensorFlow executor.
  +
  Returns:
  If `func` is not None, returns a callable that will execute the compiled
  function (and return zero or more `tf.Tensor` objects).
  