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tensoreflusso:: ops:: SparseSegmentMeanWithNumSegments
#include <math_ops.h>
Calcola la media lungo segmenti sparsi di un tensore.
Riepilogo
Come SparseSegmentMean
, ma consente ID mancanti in segment_ids
. Se manca un ID, il tensore output
in quella posizione verrà azzerato.
Leggi la sezione sulla segmentazione per una spiegazione dei segmenti.
Argomenti:
- scope: un oggetto Scope
- indici: un tensore 1-D. Ha lo stesso rango di
segment_ids
. - segment_ids: un tensore 1-D. I valori devono essere ordinati e possono essere ripetuti.
- num_segments: deve essere uguale al numero di ID di segmento distinti.
Resi:
-
Output
: ha la stessa forma dei dati, ad eccezione della dimensione 0 che ha dimensione num_segments
.
Attributi pubblici
Funzioni pubbliche
nodo
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operatore::tensorflow::Output
operator::tensorflow::Output() const
Salvo quando diversamente specificato, i contenuti di questa pagina sono concessi in base alla licenza Creative Commons Attribution 4.0, mentre gli esempi di codice sono concessi in base alla licenza Apache 2.0. Per ulteriori dettagli, consulta le norme del sito di Google Developers. Java è un marchio registrato di Oracle e/o delle sue consociate.
Ultimo aggiornamento 2025-07-25 UTC.
[null,null,["Ultimo aggiornamento 2025-07-25 UTC."],[],[],null,["# tensorflow::ops::SparseSegmentMeanWithNumSegments Class Reference\n\ntensorflow::ops::SparseSegmentMeanWithNumSegments\n=================================================\n\n`#include \u003cmath_ops.h\u003e`\n\nComputes the mean along sparse segments of a tensor.\n\nSummary\n-------\n\nLike [SparseSegmentMean](/versions/r1.15/api_docs/cc/class/tensorflow/ops/sparse-segment-mean#classtensorflow_1_1ops_1_1_sparse_segment_mean), but allows missing ids in `segment_ids`. If an id is misisng, the `output` tensor at that position will be zeroed.\n\nRead [the section on segmentation](https://tensorflow.org/api_docs/python/tf/math#Segmentation) for an explanation of segments.\n\nArguments:\n\n- scope: A [Scope](/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- indices: A 1-D tensor. Has same rank as `segment_ids`.\n- segment_ids: A 1-D tensor. Values should be sorted and can be repeated.\n- num_segments: Should equal the number of distinct segment IDs.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): Has same shape as data, except for dimension 0 which has size `num_segments`.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [SparseSegmentMeanWithNumSegments](#classtensorflow_1_1ops_1_1_sparse_segment_mean_with_num_segments_1acc14eb336c9bb422d63a332e5ff475aa)`(const ::`[tensorflow::Scope](/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` data, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` indices, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` segment_ids, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` num_segments)` ||\n\n| ### Public attributes ||\n|-------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_sparse_segment_mean_with_num_segments_1a1750008c63c66918b6adeac3d952ecef) | [Operation](/versions/r1.15/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output](#classtensorflow_1_1ops_1_1_sparse_segment_mean_with_num_segments_1a7a024ed618e930ac1bea2d738bd0f394) | `::`[tensorflow::Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public functions ||\n|-------------------------------------------------------------------------------------------------------------------------------------------------|------------------------|\n| [node](#classtensorflow_1_1ops_1_1_sparse_segment_mean_with_num_segments_1ab959360a1d82011d10097010d5274941)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_sparse_segment_mean_with_num_segments_1a0856c9bfce8692ac6cfaf403591e8d4e)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_sparse_segment_mean_with_num_segments_1a298a1bf3fbf9b34d2c306955c3090ff8)`() 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### SparseSegmentMeanWithNumSegments\n\n```gdscript\n SparseSegmentMeanWithNumSegments(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input data,\n ::tensorflow::Input indices,\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```"]]