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# tf.math.unsorted_segment_mean

Computes the mean along segments of a tensor.

Read the section on segmentation for an explanation of segments.

This operator is similar to the unsorted segment sum operator found here. Instead of computing the sum over segments, it computes the mean of all entries belonging to a segment such that:

$$output_i = 1/N_i \sum_{j...} data[j...]$$ 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.

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

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).

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.

[{ "type": "thumb-down", "id": "missingTheInformationINeed", "label":"Missing the information I need" },{ "type": "thumb-down", "id": "tooComplicatedTooManySteps", "label":"Too complicated / too many steps" },{ "type": "thumb-down", "id": "outOfDate", "label":"Out of date" },{ "type": "thumb-down", "id": "samplesCodeIssue", "label":"Samples / code issue" },{ "type": "thumb-down", "id": "otherDown", "label":"Other" }]
[{ "type": "thumb-up", "id": "easyToUnderstand", "label":"Easy to understand" },{ "type": "thumb-up", "id": "solvedMyProblem", "label":"Solved my problem" },{ "type": "thumb-up", "id": "otherUp", "label":"Other" }]