parameters: (data,
                               indices,
                               segment_ids,
                               num_segments=None,
                               name=None)
return_statement: return sparse_segment_sqrt_n(
        data, indices, segment_ids, name=name, num_segments=num_segments)
docstring: r"""Computes the sum along sparse segments of a tensor divided by the sqrt(N).
  
    Read [the section on
    segmentation](https://www.tensorflow.org/versions/r2.0/api_docs/python/tf/math#about_segmentation)
    for an explanation of segments.
  
    Like `tf.sparse.segment_mean`, but instead of dividing by the size of the
    segment, `N`, divide by `sqrt(N)` instead.
  
    Args:
      data: A `Tensor` with data that will be assembled in the output.
      indices: A 1-D `Tensor` with indices into `data`. Has same rank as
        `segment_ids`.
      segment_ids: A 1-D `Tensor` with indices into the output `Tensor`. Values
        should be sorted and can be repeated.
      num_segments: An optional int32 scalar. Indicates the size of the output
        `Tensor`.
      name: A name for the operation (optional).
  
    Returns:
      A `tensor` of the shape as data, except for dimension 0 which
      has size `k`, the number of segments specified via `num_segments` or
      inferred for the last element in `segments_ids`.
docstring_summary: r"""Computes the sum along sparse segments of a tensor divided by the sqrt(N).
docstring_tokens: r Computes the sum along sparse segments of a tensor divided by the sqrt ( N ) .
function: def sparse_segment_sqrt_n_v2(data,
                               indices,
                               segment_ids,
                               num_segments=None,
                               name=None):
    r"""Computes the sum along sparse segments of a tensor divided by the sqrt(N).
  
    Read [the section on
    segmentation](https://www.tensorflow.org/versions/r2.0/api_docs/python/tf/math#about_segmentation)
    for an explanation of segments.
  
    Like `tf.sparse.segment_mean`, but instead of dividing by the size of the
    segment, `N`, divide by `sqrt(N)` instead.
  
    Args:
      data: A `Tensor` with data that will be assembled in the output.
      indices: A 1-D `Tensor` with indices into `data`. Has same rank as
        `segment_ids`.
      segment_ids: A 1-D `Tensor` with indices into the output `Tensor`. Values
        should be sorted and can be repeated.
      num_segments: An optional int32 scalar. Indicates the size of the output
        `Tensor`.
      name: A name for the operation (optional).
  
    Returns:
      A `tensor` of the shape as data, except for dimension 0 which
      has size `k`, the number of segments specified via `num_segments` or
      inferred for the last element in `segments_ids`.
    """
    return sparse_segment_sqrt_n(
        data, indices, segment_ids, name=name, num_segments=num_segments)
function_tokens: def sparse_segment_sqrt_n_v2 ( data , indices , segment_ids , num_segments = None , name = None ) : return sparse_segment_sqrt_n ( data , indices , segment_ids , name = name , num_segments = num_segments )