message: Removes description of the non-existent (stateful) parameter and adds a note that numpy_function is always stateful
diff: @@ -603,6 +603,8 @@ def numpy_function(func, inp, Tout, name=None):
  through a numpy_function. If you require something that is differentiable,
  please consider using tf.py_function.
  + * The resulting function is assumed stateful and will never be optimized.
  +
  Args:
  func: A Python function, which accepts `numpy.ndarray` objects as arguments
  and returns a list of `numpy.ndarray` objects (or a single
  @@ -618,10 +620,6 @@ def numpy_function(func, inp, Tout, name=None):
  inp: A list of `tf.Tensor` objects.
  Tout: A list or tuple of tensorflow data types or a single tensorflow data
  type if there is only one, indicating what `func` returns.
  - stateful (bool): If True, the function should be considered stateful. If
  - a function is stateless, when given the same input it will return the same
  - output and have no observable side effects. Optimizations such as common
  - subexpression elimination are only performed on stateless operations.
  name: (Optional) A name for the operation.
  Returns:
  