message: Update functional_op docstrings to explain the second argument of `fn`.
diff: @@ -56,8 +56,9 @@ def foldl(fn,
  of elements from first to last. The elements are made of the tensors
  unpacked from `elems` on dimension 0. The callable fn takes two tensors as
  arguments. The first argument is the accumulated value computed from the
  - preceding invocation of fn. If `initializer` is None, `elems` must contain
  - at least one element, and its first element is used as the initializer.
  + preceding invocation of fn, and the second is the value at the current
  + position of `elems`. If `initializer` is None, `elems` must contain at least
  + one element, and its first element is used as the initializer.
  Suppose that `elems` is unpacked into `values`, a list of tensors. The shape
  of the result tensor is fn(initializer, values[0]).shape`.
  @@ -172,8 +173,9 @@ def foldr(fn,
  of elements from last to first. The elements are made of the tensors
  unpacked from `elems`. The callable fn takes two tensors as arguments.
  The first argument is the accumulated value computed from the preceding
  - invocation of fn. If `initializer` is None, `elems` must contain at least
  - one element, and its first element is used as the initializer.
  + invocation of fn, and the second is the value at the current position of
  + `elems`. If `initializer` is None, `elems` must contain at least one element,
  + and its first element is used as the initializer.
  Suppose that `elems` is unpacked into `values`, a list of tensors. The shape
  of the result tensor is `fn(initializer, values[0]).shape`.
  @@ -291,8 +293,9 @@ def scan(fn,
  sequence of elements from first to last. The elements are made of the tensors
  unpacked from `elems` on dimension 0. The callable fn takes two tensors as
  arguments. The first argument is the accumulated value computed from the
  - preceding invocation of fn. If `initializer` is None, `elems` must contain
  - at least one element, and its first element is used as the initializer.
  + preceding invocation of fn, and the second is the value at the current
  + position of `elems`. If `initializer` is None, `elems` must contain at least
  + one element, and its first element is used as the initializer.
  Suppose that `elems` is unpacked into `values`, a list of tensors. The shape
  of the result tensor is `[len(values)] + fn(initializer, values[0]).shape`.
  