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op {
graph_op_name: "SegmentMean"
in_arg {
name: "segment_ids"
description: <<END
A 1-D tensor whose rank is equal to the rank of `data`'s
first dimension. Values should be sorted and can be repeated.
END
}
out_arg {
name: "output"
description: <<END
Has same shape as data, except for dimension 0 which
has size `k`, the number of segments.
END
}
summary: "Computes the mean 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 = \frac{\sum_j data_j}{N}\\) where `mean` is
over `j` such that `segment_ids[j] == i` and `N` is the total number of
values summed.
If the mean is empty for a given segment ID `i`, `output[i] = 0`.
<div style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;">
<img style="width:100%" src="https://www.tensorflow.org/images/SegmentMean.png" alt>
</div>
END
}
|
