tf.math.unsorted_segment_sqrt_n
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Computes the sum along segments of a tensor divided by the sqrt(N).
tf.math.unsorted_segment_sqrt_n(
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.
Additionally to computing the sum over segments, it divides the results by
sqrt(N).
\(output_i = 1/sqrt(N_i) \sum_{j...} data[j...]\) 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.
Note that this op only supports floating point and complex dtypes,
due to tf.sqrt only supporting these types.
If the given segment ID i is negative, the value is dropped and will not
be added to the sum of the segment.
Args |
|---|
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).
|
Returns |
|---|
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.
|
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Last updated 2020-10-01 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2020-10-01 UTC."],[],[],null,["# tf.math.unsorted_segment_sqrt_n\n\n|-----------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------|\n| [TensorFlow 1 version](/versions/r1.15/api_docs/python/tf/math/unsorted_segment_sqrt_n) | [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.0.0/tensorflow/python/ops/math_ops.py#L3573-L3619) |\n\nComputes the sum along segments of a tensor divided by the sqrt(N).\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.math.unsorted_segment_sqrt_n`](/api_docs/python/tf/math/unsorted_segment_sqrt_n), [`tf.compat.v1.unsorted_segment_sqrt_n`](/api_docs/python/tf/math/unsorted_segment_sqrt_n)\n\n\u003cbr /\u003e\n\n tf.math.unsorted_segment_sqrt_n(\n data, segment_ids, num_segments, name=None\n )\n\nRead [the section on\nsegmentation](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).\nAdditionally to computing the sum over segments, it divides the results by\nsqrt(N).\n\n\\\\(output_i = 1/sqrt(N_i) \\\\sum_{j...} data\\[j...\\]\\\\) where the sum is over\ntuples `j...` such that `segment_ids[j...] == i` with \\\\N_i\\\\ being the\nnumber of occurrences of id \\\\i\\\\.\n\nIf there is no entry for a given segment ID `i`, it outputs 0.\n\nNote that this op only supports floating point and complex dtypes,\ndue to tf.sqrt only supporting these types.\n\nIf the given segment ID `i` is negative, the value is dropped and will not\nbe added to the sum of the segment.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------------|-----------------------------------------------------------------|\n| `data` | A `Tensor` with floating point or complex dtype. |\n| `segment_ids` | An integer tensor whose shape is a prefix of `data.shape`. |\n| `num_segments` | An integer scalar `Tensor`. The number of distinct segment IDs. |\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 same shape as data, except for the first `segment_ids.rank` dimensions, which are replaced with a single dimension which has size `num_segments`. ||\n\n\u003cbr /\u003e"]]
TensorFlow 1 version
View source on GitHub