tf.raw_ops.UnsortedSegmentMin
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Computes the minimum along segments of a tensor.
tf.raw_ops.UnsortedSegmentMin(
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).
Instead of computing the sum over segments, it computes the minimum such that:
\(output_i = \min_{j...} data_[j...]\) where min is over tuples 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().
For example:
c = tf.constant([[1,2,3,4], [5,6,7,8], [4,3,2,1]])
tf.unsorted_segment_min(c, tf.constant([0, 1, 0]), num_segments=2)
# ==> [[ 1, 2, 2, 1],
# [5, 6, 7, 8]]
If the given segment ID i is negative, then the corresponding value is
dropped, and will not be included in the result.
Args |
|---|
data
|
A Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, int64, bfloat16, uint16, half, uint32, uint64.
|
segment_ids
|
A Tensor. Must be one of the following types: int32, int64.
A tensor whose shape is a prefix of data.shape.
|
num_segments
|
A Tensor. Must be one of the following types: int32, int64.
|
name
|
A name for the operation (optional).
|
Returns |
|---|
A Tensor. Has the same type as data.
|
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Last updated 2021-05-14 UTC.
[null,null,["Last updated 2021-05-14 UTC."],[],[],null,["# tf.raw_ops.UnsortedSegmentMin\n\nComputes the minimum along segments of a tensor.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.raw_ops.UnsortedSegmentMin`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/UnsortedSegmentMin)\n\n\u003cbr /\u003e\n\n tf.raw_ops.UnsortedSegmentMin(\n data, segment_ids, num_segments, name=None\n )\n\nRead\n[the section on segmentation](https://tensorflow.org/api_docs/python/tf/math#Segmentation)\nfor an explanation of segments.\n\nThis operator is similar to the unsorted segment sum operator found\n[(here)](../../../api_docs/python/math_ops#UnsortedSegmentSum).\nInstead of computing the sum over segments, it computes the minimum such that:\n\n\\\\(output_i = \\\\min_{j...} data_\\[j...\\]\\\\) where min is over tuples `j...` such\nthat `segment_ids[j...] == i`.\n\nIf the minimum is empty for a given segment ID `i`, it outputs the largest\npossible value for the specific numeric type,\n`output[i] = numeric_limits\u003cT\u003e::max()`.\n\n#### For example:\n\n c = tf.constant([[1,2,3,4], [5,6,7,8], [4,3,2,1]])\n tf.unsorted_segment_min(c, tf.constant([0, 1, 0]), num_segments=2)\n # ==\u003e [[ 1, 2, 2, 1],\n # [5, 6, 7, 8]]\n\nIf the given segment ID `i` is negative, then the corresponding value is\ndropped, and will not be included in the result.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `data` | A `Tensor`. Must be one of the following types: `float32`, `float64`, `int32`, `uint8`, `int16`, `int8`, `int64`, `bfloat16`, `uint16`, `half`, `uint32`, `uint64`. |\n| `segment_ids` | A `Tensor`. Must be one of the following types: `int32`, `int64`. A tensor whose shape is a prefix of `data.shape`. |\n| `num_segments` | A `Tensor`. Must be one of the following types: `int32`, `int64`. |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `Tensor`. Has the same type as `data`. ||\n\n\u003cbr /\u003e"]]
