Stay organized with collections
Save and categorize content based on your preferences.
tensorflow::ops::UnsortedSegmentProd
#include <math_ops.h>
Computes the product along segments of a tensor.
Summary
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 product of all entries belonging to a segment such that:
\(output_i = {j...} data[j...]\) where the product is over tuples j... such that segment_ids[j...] == i.
For example:
c = tf.constant([[1,2,3,4], [5,6,7,8], [4,3,2,1]])
tf.unsorted_segment_prod(c, tf.constant([0, 1, 0]), num_segments=2)
# ==> [[ 4, 6, 6, 4],
# [5, 6, 7, 8]]
If there is no entry for a given segment ID i, it outputs 1.
If the given segment ID i is negative, then the corresponding value is dropped, and will not be included in the result.
Arguments:
- scope: A Scope object
- segment_ids: A tensor whose shape is a prefix of
data.shape.
Returns:
Output: 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.
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.
Last updated 2020-04-20 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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2020-04-20 UTC."],[],[],null,["# tensorflow::ops::UnsortedSegmentProd Class Reference\n\ntensorflow::ops::UnsortedSegmentProd\n====================================\n\n`#include \u003cmath_ops.h\u003e`\n\nComputes the product along segments of a tensor.\n\nSummary\n-------\n\nRead [the section on segmentation](https://tensorflow.org/api_docs/python/tf/math#Segmentation) for an explanation of segments.\n\nThis 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 product of all entries belonging to a segment such that:\n\n\\\\(output_i = {j...} data\\[j...\\]\\\\) where the product is over tuples `j...` such that `segment_ids[j...] == i`.\n\nFor example:\n\n\n```gdscript\nc = tf.constant([[1,2,3,4], [5,6,7,8], [4,3,2,1]])\ntf.unsorted_segment_prod(c, tf.constant([0, 1, 0]), num_segments=2)\n# ==\u003e [[ 4, 6, 6, 4],\n# [5, 6, 7, 8]]\n```\n\n\u003cbr /\u003e\n\nIf there is no entry for a given segment ID `i`, it outputs 1.\n\nIf the given segment ID `i` is negative, then the corresponding value is dropped, and will not be included in the result.\n\nArguments:\n\n- scope: A [Scope](/versions/r2.0/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- segment_ids: A tensor whose shape is a prefix of `data.shape`.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): 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\n\n| ### Constructors and Destructors ||\n|---|---|\n| [UnsortedSegmentProd](#classtensorflow_1_1ops_1_1_unsorted_segment_prod_1a426fa7bf6679eaddb4357ecd2326ddfd)`(const ::`[tensorflow::Scope](/versions/r2.0/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` data, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` segment_ids, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` num_segments)` ||\n\n| ### Public attributes ||\n|---------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_unsorted_segment_prod_1a9f38a8974be98df327efd596fbfa4322) | [Operation](/versions/r2.0/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output](#classtensorflow_1_1ops_1_1_unsorted_segment_prod_1a3c1839365baeffc25fd511bcfdc9a12b) | `::`[tensorflow::Output](/versions/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public functions ||\n|---------------------------------------------------------------------------------------------------------------------------------|------------------------|\n| [node](#classtensorflow_1_1ops_1_1_unsorted_segment_prod_1a517e5b44536243635df5b97add2deb41)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_unsorted_segment_prod_1a0a2a984f6cbed916d58e6a8e9901380d)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_unsorted_segment_prod_1a561073eeb76d871584129b8b1c648d26)`() 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### UnsortedSegmentProd\n\n```gdscript\n UnsortedSegmentProd(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input data,\n ::tensorflow::Input segment_ids,\n ::tensorflow::Input num_segments\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```"]]
