message: Improve docs for broadcast_static_shape and broadcast_dynamic_shape
diff: @@ -165,7 +165,18 @@ setdiff1d.__doc__ = gen_array_ops.list_diff.__doc__
  @tf_export("broadcast_dynamic_shape")
  def broadcast_dynamic_shape(shape_x, shape_y):
  - """Returns the broadcasted dynamic shape between `shape_x` and `shape_y`.
  + """Computes the shape of a broadcast given symbolic shapes.
  +
  + When shape_x and shape_y are Tensors representing shapes (i.e. the result of
  + calling tf.shape on another Tensor) this computes a Tensor which is the shape
  + of the result of a broadcasting op applied in tensors of shapes shape_x and
  + shape_y.
  +
  + For example, if shape_x is [1, 2, 3] and shape_y is [5, 1, 3], the result is a
  + Tensor whose value is [5, 2, 3].
  +
  + This is useful when validating the result of a broadcasting operation when the
  + tensors do not have statically known shapes.
  Args:
  shape_x: A rank 1 integer `Tensor`, representing the shape of x.
  @@ -179,7 +190,17 @@ def broadcast_dynamic_shape(shape_x, shape_y):
  @tf_export("broadcast_static_shape")
  def broadcast_static_shape(shape_x, shape_y):
  - """Returns the broadcasted static shape between `shape_x` and `shape_y`.
  + """Computes the shape of a broadcast given known shapes.
  +
  + When shape_x and shape_y are fully known TensorShapes this computes a
  + TensorShape which is the shape of the result of a broadcasting op applied in
  + tensors of shapes shape_x and shape_y.
  +
  + For example, if shape_x is [1, 2, 3] and shape_y is [5, 1, 3], the result is a
  + TensorShape whose value is [5, 2, 3].
  +
  + This is useful when validating the result of a broadcasting operation when the
  + tensors have statically known shapes.
  Args:
  shape_x: A `TensorShape`
  