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tensorflow::
ops::
SegmentMean
#include <math_ops.h>
Computes the mean along segments of a tensor.
Summary
Read
the section on segmentation
for an explanation of segments.
Computes a tensor such that \(output_i = { data_j}{N}\) where
mean
is over
j
such that
segment_ids[j] == i
and
N
is the total number of values summed.
If the mean is empty for a given segment ID
i
,
output[i] = 0
.
For example:
c = tf.constant([[1.0,2,3,4], [4, 3, 2, 1], [5,6,7,8]])
tf.segment_mean(c, tf.constant([0, 0, 1]))
# ==> [[2.5, 2.5, 2.5, 2.5],
# [5, 6, 7, 8]]
Args:
-
scope: A
Scope
object
-
segment_ids: A 1-D tensor whose size is equal to the size of
data
's first dimension. 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 2021-05-14 UTC.
[null,null,["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```"]]
