# tf.math.unsorted_segment_sqrt_n

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

### Aliases:

• tf.compat.v1.math.unsorted_segment_sqrt_n
• tf.compat.v1.unsorted_segment_sqrt_n
• tf.compat.v2.math.unsorted_segment_sqrt_n
tf.math.unsorted_segment_sqrt_n(
data,
segment_ids,
num_segments,
name=None
)


Read the section on segmentation for an explanation of segments.

This operator is similar to the unsorted segment sum operator found here. Additionally to computing the sum over segments, it divides the results by sqrt(N).

$$outputi = 1/sqrt(N_i) \sum{j...} data[j...]$$ where the sum is over tuples j... such that segment_ids[j...] == i with \N_i\ being the number of occurrences of id \i\.

If there is no entry for a given segment ID i, it outputs 0.

Note that this op only supports floating point and complex dtypes, due to tf.sqrt only supporting these types.

If the given segment ID i is negative, the value is dropped and will not be added to the sum of the segment.

#### Args:

• data: A Tensor with floating point or complex dtype.
• segment_ids: An integer tensor whose shape is a prefix of data.shape.
• num_segments: An integer scalar Tensor. The number of distinct segment IDs.
• name: A name for the operation (optional).

#### Returns:

A Tensor. Has same shape as data, except for the first segment_ids.rank dimensions, which are replaced with a single dimension which has size num_segments.