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.

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.

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.