[[["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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2021-05-14 UTC."],[],[],null,["# tensorflow::ops::SegmentMean Class Reference\n\ntensorflow::\nops::\nSegmentMean\n==============================\n\n`\n#include \u003cmath_ops.h\u003e\n`\n\n\nComputes the mean along 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\nComputes a tensor such that \\\\(output_i = { data_j}{N}\\\\) where\n`\nmean\n`\nis over\n`\nj\n`\nsuch that\n`\nsegment_ids[j] == i\n`\nand\n`\nN\n`\nis the total number of values summed.\n\n\nIf the mean is empty for a given segment ID\n`\ni\n`\n,\n`\noutput[i] = 0\n`\n.\n\n\n\u003cbr /\u003e\n\n\nFor example:\n\n\n```gdscript\nc = tf.constant([[1.0,2,3,4], [4, 3, 2, 1], [5,6,7,8]])\ntf.segment_mean(c, tf.constant([0, 0, 1]))\n# ==\u003e [[2.5, 2.5, 2.5, 2.5],\n# [5, 6, 7, 8]]\n```\n\n\u003cbr /\u003e\n\n\nArgs:\n\n- scope: A [Scope](/versions/r2.5/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- segment_ids: A 1-D tensor whose size is equal to the size of `\n data\n ` 's first dimension. Values should be sorted and can be repeated.\n\n\u003cbr /\u003e\n\n\nReturns:\n\n- `\n `[Output](/versions/r2.5/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| ` `[SegmentMean](#classtensorflow_1_1ops_1_1_segment_mean_1a9fc798114162e49ca1a2e3be55c67c4e)` (const :: `[tensorflow::Scope](/versions/r2.5/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, :: `[tensorflow::Input](/versions/r2.5/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` data, :: `[tensorflow::Input](/versions/r2.5/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` segment_ids) ` ||\n\n| ### Public attributes ||\n|------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------|\n| ` `[operation](#classtensorflow_1_1ops_1_1_segment_mean_1ab33c7bc6ed3ae2192796a60aa4e2603d)` ` | ` `[Operation](/versions/r2.5/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation)` ` |\n| ` `[output](#classtensorflow_1_1ops_1_1_segment_mean_1a64036d8ee48b0555a734f063c8b5e21e)` ` | ` :: `[tensorflow::Output](/versions/r2.5/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output)` ` |\n\n| ### Public functions ||\n|----------------------------------------------------------------------------------------------------------------------------|--------------------------|\n| ` `[node](#classtensorflow_1_1ops_1_1_segment_mean_1a9a1dd3986731336496132e50f5882bfd)` () const ` | ` ::tensorflow::Node * ` |\n| ` `[operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_segment_mean_1a4555ae396508ae3dd5a91c67b3f7d8f4)` () const ` | ` ` |\n| ` `[operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_segment_mean_1a5a63b16dc3408efa63a3d07570c08783)` () 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### SegmentMean\n\n```gdscript\n SegmentMean(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input data,\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```"]]
