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op {
graph_op_name: "UnsortedSegmentMin"
in_arg {
name: "segment_ids"
description: <<END
A 1-D tensor whose rank is equal to the rank of `data`'s
first dimension.
END
}
out_arg {
name: "output"
description: <<END
Has same shape as data, except for dimension 0 which
has size `num_segments`.
END
}
summary: "Computes the minimum 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.
This operator is similar to the unsorted segment sum operator found
[(here)](../../../api_docs/python/math_ops.md#UnsortedSegmentSum).
Instead of computing the sum over segments, it computes the minimum such that:
\\(output_i = \min_j data_j\\) where min is over `j` such
that `segment_ids[j] == i`.
If the minimum is empty for a given segment ID `i`, it outputs the largest
possible value for the specific numeric type,
`output[i] = numeric_limits<T>::max()`.
END
}
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