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op {
graph_op_name: "UnsortedSegmentSum"
in_arg {
name: "segment_ids"
description: <<END
A tensor whose shape is a prefix of `data.shape`.
END
}
out_arg {
name: "output"
description: <<END
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`.
END
}
summary: "Computes the sum along segments of a tensor."
description: <<END
Read
[the section on segmentation](https://tensorflow.org/api_guides/python/math_ops#Segmentation)
for an explanation of segments.
Computes a tensor such that
\\(output[i] = \sum_{j...} data[j...]\\) where the sum is over tuples `j...` such
that `segment_ids[j...] == i`. Unlike `SegmentSum`, `segment_ids`
need not be sorted and need not cover all values in the full
range of valid values.
If the sum is empty for a given segment ID `i`, `output[i] = 0`.
If the given segment ID `i` is negative, the value is dropped and will not be
added to the sum of the segment.
`num_segments` should equal the number of distinct segment IDs.
<div style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;">
<img style="width:100%" src="https://www.tensorflow.org/images/UnsortedSegmentSum.png" alt>
</div>
END
}
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