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flujo tensor:: operaciones:: SparseTensorDenseMatMul
#include <sparse_ops.h>
Multiplica SparseTensor (de rango 2) "A" por la matriz densa "B".
Resumen
No se realiza ninguna verificación de validez en los índices de A. Sin embargo, se recomienda el siguiente formato de entrada para un comportamiento óptimo:
if adjoint_a == false: A debe ordenarse en orden lexicográficamente creciente. Utilice SparseReorder si no está seguro. if adjoint_a == true: A debe ordenarse en orden creciente de dimensión 1 (es decir, orden de "columna mayor" en lugar de orden de "fila mayor").
Argumentos:
- alcance: un objeto de alcance
- a_indices: 2-D. Los
indices
de SparseTensor
, tamaño [nnz, 2]
Matrix. - valores_a: 1-D. Los
values
del SparseTensor
, tamaño [nnz]
Vector. - forma_a: 1-D. La
shape
del SparseTensor
, tamaño [2]
Vector. - b: 2-D. Una Matriz densa.
Atributos opcionales (ver Attrs
):
- adjoint_a: Utilice el adjunto de A en la matriz para multiplicar. Si A es complejo, esto es transposición (conj (A)). De lo contrario, es transpuesta (A).
- adjoint_b: Utilice el adjunto de B en la matriz para multiplicar. Si B es complejo, esto es transposición (conj (B)). De lo contrario, se transpone (B).
Devoluciones:
-
Output
: El tensor del producto.
Atributos públicos
Funciones públicas
nodo
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operador::tensorflow::Salida
operator::tensorflow::Output() const
Funciones estáticas públicas
AdjuntoA
Attrs AdjointA(
bool x
)
AdjuntoB
Attrs AdjointB(
bool x
)
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Última actualización: 2025-07-25 (UTC).
[null,null,["Última actualización: 2025-07-25 (UTC)."],[],[],null,["# tensorflow::ops::SparseTensorDenseMatMul Class Reference\n\ntensorflow::ops::SparseTensorDenseMatMul\n========================================\n\n`#include \u003csparse_ops.h\u003e`\n\n[Multiply](/versions/r1.15/api_docs/cc/class/tensorflow/ops/multiply#classtensorflow_1_1ops_1_1_multiply) SparseTensor (of rank 2) \"A\" by dense matrix \"B\".\n\nSummary\n-------\n\nNo validity checking is performed on the indices of A. However, the following input format is recommended for optimal behavior:\n\nif adjoint_a == false: A should be sorted in lexicographically increasing order. Use [SparseReorder](/versions/r1.15/api_docs/cc/class/tensorflow/ops/sparse-reorder#classtensorflow_1_1ops_1_1_sparse_reorder) if you're not sure. if adjoint_a == true: A should be sorted in order of increasing dimension 1 (i.e., \"column major\" order instead of \"row major\" order).\n\nArguments:\n\n- scope: A [Scope](/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- a_indices: 2-D. The `indices` of the `SparseTensor`, size `[nnz, 2]` Matrix.\n- a_values: 1-D. The `values` of the `SparseTensor`, size `[nnz]` Vector.\n- a_shape: 1-D. The `shape` of the `SparseTensor`, size `[2]` Vector.\n- b: 2-D. A dense Matrix.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/sparse-tensor-dense-mat-mul/attrs#structtensorflow_1_1ops_1_1_sparse_tensor_dense_mat_mul_1_1_attrs)):\n\n- adjoint_a: Use the adjoint of A in the matrix multiply. If A is complex, this is transpose(conj(A)). Otherwise it's transpose(A).\n- adjoint_b: Use the adjoint of B in the matrix multiply. If B is complex, this is transpose(conj(B)). Otherwise it's transpose(B).\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): The product tensor.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [SparseTensorDenseMatMul](#classtensorflow_1_1ops_1_1_sparse_tensor_dense_mat_mul_1adf1f689b8b8d0d72c059efbea5fb9cac)`(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)` a_indices, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` a_values, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` a_shape, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` b)` ||\n| [SparseTensorDenseMatMul](#classtensorflow_1_1ops_1_1_sparse_tensor_dense_mat_mul_1a3643c83b6940a54319e70b0bc094f948)`(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)` a_indices, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` a_values, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` a_shape, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` b, const `[SparseTensorDenseMatMul::Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/sparse-tensor-dense-mat-mul/attrs#structtensorflow_1_1ops_1_1_sparse_tensor_dense_mat_mul_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|---------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_sparse_tensor_dense_mat_mul_1a5213c7ac11f10109585773e8fe2cd041) | [Operation](/versions/r1.15/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [product](#classtensorflow_1_1ops_1_1_sparse_tensor_dense_mat_mul_1a8895f99af9af5585d8bd937b817bb0ae) | `::`[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_tensor_dense_mat_mul_1a3c65317b9c1886136c7de4e03ec51641)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_sparse_tensor_dense_mat_mul_1ac394c138be85d3c36ae20b40f867d72c)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_sparse_tensor_dense_mat_mul_1a888b8f4b59aea6d4ff0bdeeba2ad5338)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [AdjointA](#classtensorflow_1_1ops_1_1_sparse_tensor_dense_mat_mul_1a972ac5b3a5538d477e96e8d1d857ccca)`(bool x)` | [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/sparse-tensor-dense-mat-mul/attrs#structtensorflow_1_1ops_1_1_sparse_tensor_dense_mat_mul_1_1_attrs) |\n| [AdjointB](#classtensorflow_1_1ops_1_1_sparse_tensor_dense_mat_mul_1ac3e772adcb84c991bdd702ba2f6f7b98)`(bool x)` | [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/sparse-tensor-dense-mat-mul/attrs#structtensorflow_1_1ops_1_1_sparse_tensor_dense_mat_mul_1_1_attrs) |\n\n| ### Structs ||\n|----------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::SparseTensorDenseMatMul::Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/sparse-tensor-dense-mat-mul/attrs) | Optional attribute setters for [SparseTensorDenseMatMul](/versions/r1.15/api_docs/cc/class/tensorflow/ops/sparse-tensor-dense-mat-mul#classtensorflow_1_1ops_1_1_sparse_tensor_dense_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### SparseTensorDenseMatMul\n\n```gdscript\n SparseTensorDenseMatMul(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input a_indices,\n ::tensorflow::Input a_values,\n ::tensorflow::Input a_shape,\n ::tensorflow::Input b\n)\n``` \n\n### SparseTensorDenseMatMul\n\n```gdscript\n SparseTensorDenseMatMul(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input a_indices,\n ::tensorflow::Input a_values,\n ::tensorflow::Input a_shape,\n ::tensorflow::Input b,\n const SparseTensorDenseMatMul::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### AdjointA\n\n```text\nAttrs AdjointA(\n bool x\n)\n``` \n\n### AdjointB\n\n```text\nAttrs AdjointB(\n bool x\n)\n```"]]