tf.sparse.segment_sqrt_n

Computes the sum along sparse segments of a tensor divided by the sqrt(N).

tf.sparse.segment_sqrt_n(
    data,
    indices,
    segment_ids,
    num_segments=None,
    name=None,
    sparse_gradient=False
)

Read the section on 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).
`sparse_gradient`	An optional `bool`. Defaults to `False`. If `True`, the gradient of this function will be sparse (`IndexedSlices`) instead of dense (`Tensor`). The sparse gradient will contain one non-zero row for each unique index in `indices`.

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`.

Args