message: Added see also references
  Added see also references for `tf.split`, `tf.unstack`, `tf.size`,`tf.shape`, `tf.repeat`, `tf.concat`, `tf.tile`, `tf.stack`.
diff: @@ -535,6 +535,8 @@ def shape_v2(input, out_type=dtypes.int32, name=None):
  # pylint: disable=redefined-builtin
  """Returns the shape of a tensor.
  + See also `tf.size`.
  +
  This operation returns a 1-D integer tensor representing the shape of `input`.
  This represents the minimal set of known information at definition time.
  @@ -653,6 +655,8 @@ def size_v2(input, out_type=dtypes.int32, name=None):
  # pylint: disable=redefined-builtin
  """Returns the size of a tensor.
  + See also `tf.shape`.
  +
  Returns a 0-D `Tensor` representing the number of elements in `input`
  of type `out_type`. Defaults to tf.int32.
  @@ -1279,6 +1283,8 @@ def parallel_stack(values, name="parallel_stack"):
  def stack(values, axis=0, name="stack"):
  """Stacks a list of rank-`R` tensors into one rank-`(R+1)` tensor.
  + See also `tf.concat`, `tf.tile`, `tf.repeat`.
  +
  Packs the list of tensors in `values` into a tensor with rank one higher than
  each tensor in `values`, by packing them along the `axis` dimension.
  Given a list of length `N` of tensors of shape `(A, B, C)`;
  @@ -1510,6 +1516,8 @@ def unstack(value, num=None, axis=0, name="unstack"):
  def concat(values, axis, name="concat"):
  """Concatenates tensors along one dimension.
  + See also `tf.tile`, `tf.stack`, `tf.repeat`.
  +
  Concatenates the list of tensors `values` along dimension `axis`. If
  `values[i].shape = [D0, D1, ... Daxis(i), ...Dn]`, the concatenated
  result has shape
  @@ -1881,6 +1889,8 @@ unique_with_counts.__doc__ = gen_array_ops.unique_with_counts.__doc__
  def split(value, num_or_size_splits, axis=0, num=None, name="split"):
  """Splits a tensor `value` into a list of sub tensors.
  + See also `tf.unstack`.
  +
  If `num_or_size_splits` is an integer, then `value` is split along the
  dimension `axis` into `num_split` smaller tensors. This requires that
  `value.shape[axis]` is divisible by `num_split`.
  @@ -5571,6 +5581,8 @@ def _with_nonzero_rank(data):
  def repeat(input, repeats, axis=None, name=None): # pylint: disable=redefined-builtin
  """Repeat elements of `input`.
  + See also `tf.concat`, `tf.stack`, `tf.tile`.
  +
  Args:
  input: An `N`-dimensional Tensor.
  repeats: An 1-D `int` Tensor. The number of repetitions for each element.
  