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tensoreflusso:: ops:: SparseMatMul
#include <math_ops.h>
Moltiplicare la matrice "a" per la matrice "b".
Riepilogo
Gli input devono essere matrici bidimensionali e la dimensione interna di "a" deve corrispondere alla dimensione esterna di "b". Sia "a" che "b" devono essere Tensor
s e non SparseTensor
s. Questa operazione è ottimizzata per il caso in cui almeno uno tra "a" e "b" è sparso, nel senso che hanno una grande proporzione di valori zero. Il pareggio per l'utilizzo di questo rispetto a una matrice densa moltiplicata su una piattaforma era pari al 30% di valori zero nella matrice sparsa.
Il calcolo del gradiente di questa operazione trarrà vantaggio dalla scarsità nel gradiente di input solo quando tale gradiente proviene da un Relu .
Argomenti:
Resi:
-
Output
: il tensore del prodotto.
Attributi pubblici
Funzioni pubbliche
nodo
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operatore::tensorflow::Output
operator::tensorflow::Output() const
Funzioni pubbliche statiche
AISparse
Attrs AIsSparse(
bool x
)
BIsSparse
Attrs BIsSparse(
bool x
)
TrasporreA
Attrs TransposeA(
bool x
)
TrasporreB
Attrs TransposeB(
bool x
)
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 2025-07-27 UTC.
[null,null,["Ultimo aggiornamento 2025-07-27 UTC."],[],[],null,["# tensorflow::ops::SparseMatMul Class Reference\n\ntensorflow::ops::SparseMatMul\n=============================\n\n`#include \u003cmath_ops.h\u003e`\n\n[Multiply](/versions/r2.2/api_docs/cc/class/tensorflow/ops/multiply#classtensorflow_1_1ops_1_1_multiply) matrix \"a\" by matrix \"b\".\n\nSummary\n-------\n\nThe inputs must be two-dimensional matrices and the inner dimension of \"a\" must match the outer dimension of \"b\". Both \"a\" and \"b\" must be [Tensor](/versions/r2.2/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor)s not `SparseTensor`s. This op is optimized for the case where at least one of \"a\" or \"b\" is sparse, in the sense that they have a large proportion of zero values. The breakeven for using this versus a dense matrix multiply on one platform was 30% zero values in the sparse matrix.\n\nThe gradient computation of this operation will only take advantage of sparsity in the input gradient when that gradient comes from a [Relu](/versions/r2.2/api_docs/cc/class/tensorflow/ops/relu#classtensorflow_1_1ops_1_1_relu).\n\nArguments:\n\n- scope: A [Scope](/versions/r2.2/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.2/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): The product tensor.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [SparseMatMul](#classtensorflow_1_1ops_1_1_sparse_mat_mul_1a44ec3b9c8a4a6c27ec1e5defa921a8c2)`(const ::`[tensorflow::Scope](/versions/r2.2/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` a, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` b)` ||\n| [SparseMatMul](#classtensorflow_1_1ops_1_1_sparse_mat_mul_1a29e8ca18f70b1f18d2d5931606fa5108)`(const ::`[tensorflow::Scope](/versions/r2.2/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` a, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` b, const `[SparseMatMul::Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/sparse-mat-mul/attrs#structtensorflow_1_1ops_1_1_sparse_mat_mul_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|--------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_sparse_mat_mul_1af4bedc3c3ba71553d0c1e30513898430) | [Operation](/versions/r2.2/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [product](#classtensorflow_1_1ops_1_1_sparse_mat_mul_1a9b708969f18250faa3e40edad285ae45) | `::`[tensorflow::Output](/versions/r2.2/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public functions ||\n|--------------------------------------------------------------------------------------------------------------------------|------------------------|\n| [node](#classtensorflow_1_1ops_1_1_sparse_mat_mul_1ae461c34d275e4d996e21af14b8870531)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_sparse_mat_mul_1a7e6d0d764e73510a120ea967abaf9250)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_sparse_mat_mul_1a3fee7729e51d2b640d654a25a84f0185)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|-------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------|\n| [AIsSparse](#classtensorflow_1_1ops_1_1_sparse_mat_mul_1acaa26e8e9d1e5854dcfef57dcb4efd5b)`(bool x)` | [Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/sparse-mat-mul/attrs#structtensorflow_1_1ops_1_1_sparse_mat_mul_1_1_attrs) |\n| [BIsSparse](#classtensorflow_1_1ops_1_1_sparse_mat_mul_1aaf87a4805b8269233969a514bea852ef)`(bool x)` | [Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/sparse-mat-mul/attrs#structtensorflow_1_1ops_1_1_sparse_mat_mul_1_1_attrs) |\n| [TransposeA](#classtensorflow_1_1ops_1_1_sparse_mat_mul_1a41b864162f17688227aa34ee4d8021b2)`(bool x)` | [Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/sparse-mat-mul/attrs#structtensorflow_1_1ops_1_1_sparse_mat_mul_1_1_attrs) |\n| [TransposeB](#classtensorflow_1_1ops_1_1_sparse_mat_mul_1af58949ad4394aa0ba7869e65ba742487)`(bool x)` | [Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/sparse-mat-mul/attrs#structtensorflow_1_1ops_1_1_sparse_mat_mul_1_1_attrs) |\n\n| ### Structs ||\n|---------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::SparseMatMul::Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/sparse-mat-mul/attrs) | Optional attribute setters for [SparseMatMul](/versions/r2.2/api_docs/cc/class/tensorflow/ops/sparse-mat-mul#classtensorflow_1_1ops_1_1_sparse_mat_mul). |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### product\n\n```text\n::tensorflow::Output product\n``` \n\nPublic functions\n----------------\n\n### SparseMatMul\n\n```gdscript\n SparseMatMul(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input a,\n ::tensorflow::Input b\n)\n``` \n\n### SparseMatMul\n\n```gdscript\n SparseMatMul(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input a,\n ::tensorflow::Input b,\n const SparseMatMul::Attrs & attrs\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``` \n\nPublic static functions\n-----------------------\n\n### AIsSparse\n\n```text\nAttrs AIsSparse(\n bool x\n)\n``` \n\n### BIsSparse\n\n```text\nAttrs BIsSparse(\n bool x\n)\n``` \n\n### TransposeA\n\n```text\nAttrs TransposeA(\n bool x\n)\n``` \n\n### TransposeB\n\n```text\nAttrs TransposeB(\n bool x\n)\n```"]]