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tensorflow::
ops::
SparseSegmentSum
#include <math_ops.h>
Computes the sum along sparse segments of a tensor.
Summary
Read
the section on segmentation
for an explanation of segments.
Like
SegmentSum
, but
segment_ids
can have rank less than
data
's first dimension, selecting a subset of dimension 0, specified by
indices
.
For example:
c = tf.constant([[1,2,3,4], [-1,-2,-3,-4], [5,6,7,8]])
# Select two rows, one segment.
tf.sparse_segment_sum(c, tf.constant([0, 1]), tf.constant([0, 0]))
# => [[0 0 0 0]]
# Select two rows, two segment.
tf.sparse_segment_sum(c, tf.constant([0, 1]), tf.constant([0, 1]))
# => [[ 1 2 3 4]
# [-1 -2 -3 -4]]
# Select all rows, two segments.
tf.sparse_segment_sum(c, tf.constant([0, 1, 2]), tf.constant([0, 0, 1]))
# => [[0 0 0 0]
# [5 6 7 8]]
# Which is equivalent to:
tf.segment_sum(c, tf.constant([0, 0, 1]))
Args:
-
scope: A
Scope
object
-
indices: A 1-D tensor. Has same rank as
segment_ids
.
-
segment_ids: A 1-D tensor. Values should be sorted and can be repeated.
Returns:
-
Output
: Has same shape as data, except for dimension 0 which has size
k
, the number of segments.
Public attributes
Public functions
node
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.
Last updated 2021-08-16 UTC.
[null,null,["Last updated 2021-08-16 UTC."],[],[],null,["# tensorflow::ops::SparseSegmentSum Class Reference\n\ntensorflow::\nops::\nSparseSegmentSum\n===================================\n\n`\n#include \u003cmath_ops.h\u003e\n`\n\n\nComputes the sum along sparse segments of a tensor.\n\nSummary\n-------\n\n\nRead\n[the section on segmentation](https://tensorflow.org/api_docs/python/tf/math#Segmentation)\nfor an explanation of segments.\n\n\nLike\n`\n`[SegmentSum](/versions/r2.6/api_docs/cc/class/tensorflow/ops/segment-sum#classtensorflow_1_1ops_1_1_segment_sum)`\n`\n, but\n`\nsegment_ids\n`\ncan have rank less than\n`\ndata\n`\n's first dimension, selecting a subset of dimension 0, specified by\n`\nindices\n`\n.\n\n\nFor example:\n\n\n```gdscript\nc = tf.constant([[1,2,3,4], [-1,-2,-3,-4], [5,6,7,8]])\n```\n\n\u003cbr /\u003e\n\n\n```gdscript\n# Select two rows, one segment.\ntf.sparse_segment_sum(c, tf.constant([0, 1]), tf.constant([0, 0]))\n# =\u003e [[0 0 0 0]]\n```\n\n\u003cbr /\u003e\n\n\n```gdscript\n# Select two rows, two segment.\ntf.sparse_segment_sum(c, tf.constant([0, 1]), tf.constant([0, 1]))\n# =\u003e [[ 1 2 3 4]\n# [-1 -2 -3 -4]]\n```\n\n\u003cbr /\u003e\n\n\n```gdscript\n# Select all rows, two segments.\ntf.sparse_segment_sum(c, tf.constant([0, 1, 2]), tf.constant([0, 0, 1]))\n# =\u003e [[0 0 0 0]\n# [5 6 7 8]]\n```\n\n\u003cbr /\u003e\n\n\n```gdscript\n# Which is equivalent to:\ntf.segment_sum(c, tf.constant([0, 0, 1]))\n```\n\n\u003cbr /\u003e\n\n\nArgs:\n\n- scope: A [Scope](/versions/r2.6/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- indices: A 1-D tensor. Has same rank as `\n segment_ids\n ` .\n- segment_ids: A 1-D tensor. Values should be sorted and can be repeated.\n\n\u003cbr /\u003e\n\n\nReturns:\n\n- `\n `[Output](/versions/r2.6/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output)`\n ` : Has same shape as data, except for dimension 0 which has size `\n k\n ` , the number of segments.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| ` `[SparseSegmentSum](#classtensorflow_1_1ops_1_1_sparse_segment_sum_1a02259862f31344aafc95082e08aa9aab)` (const :: `[tensorflow::Scope](/versions/r2.6/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, :: `[tensorflow::Input](/versions/r2.6/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` data, :: `[tensorflow::Input](/versions/r2.6/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` indices, :: `[tensorflow::Input](/versions/r2.6/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` segment_ids) ` ||\n\n| ### Public attributes ||\n|------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------|\n| ` `[operation](#classtensorflow_1_1ops_1_1_sparse_segment_sum_1ad649884f20027c1aad55e81c08e7957b)` ` | ` `[Operation](/versions/r2.6/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation)` ` |\n| ` `[output](#classtensorflow_1_1ops_1_1_sparse_segment_sum_1a40540c212fd500b0d52073ad1fc9d0c8)` ` | ` :: `[tensorflow::Output](/versions/r2.6/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output)` ` |\n\n| ### Public functions ||\n|----------------------------------------------------------------------------------------------------------------------------------|--------------------------|\n| ` `[node](#classtensorflow_1_1ops_1_1_sparse_segment_sum_1a51e3e189f4da0718eca9673f4245f2b2)` () const ` | ` ::tensorflow::Node * ` |\n| ` `[operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_sparse_segment_sum_1a61710c54c59674e886a27a1025c266ba)` () const ` | ` ` |\n| ` `[operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_sparse_segment_sum_1ad6961f104657b05da798100d4ac7f68b)` () const ` | ` ` |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### output\n\n```text\n::tensorflow::Output output\n``` \n\nPublic functions\n----------------\n\n### SparseSegmentSum\n\n```gdscript\n SparseSegmentSum(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input data,\n ::tensorflow::Input indices,\n ::tensorflow::Input segment_ids\n)\n``` \n\n### node\n\n```gdscript\n::tensorflow::Node * node() const \n``` \n\n### operator::tensorflow::Input\n\n```gdscript\n operator::tensorflow::Input() const \n``` \n\n### operator::tensorflow::Output\n\n```gdscript\n operator::tensorflow::Output() const \n```"]]
