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flujo tensor:: operaciones:: LoteMatMulV2
#include <math_ops.h>
Multiplica porciones de dos tensores en lotes.
Resumen
Multiplica todos los sectores de Tensor
x
e y
(cada sector se puede ver como un elemento de un lote) y organiza los resultados individuales en un único tensor de salida del mismo tamaño de lote. Opcionalmente, cada uno de los sectores individuales se puede unir (adjuntar una matriz significa transponerla y conjugarla) antes de la multiplicación estableciendo el indicador adj_x
o adj_y
en True
, que por defecto son False
.
Los tensores de entrada x
son 2- y
o superiores con forma [..., r_x, c_x]
y [..., r_y, c_y]
.
El tensor de salida es 2-D o superior con forma [..., r_o, c_o]
, donde:
r_o = c_x if adj_x else r_x
c_o = r_y if adj_y else c_y
Se calcula como:
output[..., :, :] = matrix(x[..., :, :]) * matrix(y[..., :, :])
NOTA : BatchMatMulV2
admite la transmisión en dimensiones por lotes. Más sobre retransmisiones aquí .
Argumentos:
- alcance: un objeto de alcance
- x: 2-D o superior con forma
[..., r_x, c_x]
. - y: 2-D o superior con forma
[..., r_y, c_y]
.
Atributos opcionales (ver Attrs
):
- adj_x: si es
True
, une las porciones de x
. El valor predeterminado es False
. - adj_y: si es
True
, une los sectores de y
. El valor predeterminado es False
.
Devoluciones:
-
Output
: 3-D o superior con forma [..., r_o, c_o]
Funciones estáticas públicas |
---|
AdjX (bool x) | |
AdjY (bool x) | |
Atributos públicos
Funciones públicas
nodo
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operador::tensorflow::Salida
operator::tensorflow::Output() const
Funciones estáticas públicas
AdjX
Attrs AdjX(
bool x
)
AdjY
Attrs AdjY(
bool x
)
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Última actualización: 2025-07-26 (UTC).
[null,null,["Última actualización: 2025-07-26 (UTC)."],[],[],null,["# tensorflow::ops::BatchMatMulV2 Class Reference\n\ntensorflow::ops::BatchMatMulV2\n==============================\n\n`#include \u003cmath_ops.h\u003e`\n\nMultiplies slices of two tensors in batches.\n\nSummary\n-------\n\nMultiplies all slices of [Tensor](/versions/r1.15/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor)`x` and `y` (each slice can be viewed as an element of a batch), and arranges the individual results in a single output tensor of the same batch size. Each of the individual slices can optionally be adjointed (to adjoint a matrix means to transpose and conjugate it) before multiplication by setting the `adj_x` or `adj_y` flag to `True`, which are by default `False`.\n\nThe input tensors `x` and `y` are 2-D or higher with shape `[..., r_x, c_x]` and `[..., r_y, c_y]`.\n\nThe output tensor is 2-D or higher with shape `[..., r_o, c_o]`, where: \n\n```scdoc\nr_o = c_x if adj_x else r_x\nc_o = r_y if adj_y else c_y\n```\n\n\u003cbr /\u003e\n\nIt is computed as: \n\n```scdoc\noutput[..., :, :] = matrix(x[..., :, :]) * matrix(y[..., :, :])\n```\n\n\u003cbr /\u003e\n\n*NOTE* : [BatchMatMulV2](/versions/r1.15/api_docs/cc/class/tensorflow/ops/batch-mat-mul-v2#classtensorflow_1_1ops_1_1_batch_mat_mul_v2) supports broadcasting in the batch dimensions. More about broadcasting [here](http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html).\n\nArguments:\n\n- scope: A [Scope](/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- x: 2-D or higher with shape `[..., r_x, c_x]`.\n- y: 2-D or higher with shape `[..., r_y, c_y]`.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/batch-mat-mul-v2/attrs#structtensorflow_1_1ops_1_1_batch_mat_mul_v2_1_1_attrs)):\n\n- adj_x: If `True`, adjoint the slices of `x`. Defaults to `False`.\n- adj_y: If `True`, adjoint the slices of `y`. Defaults to `False`.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): 3-D or higher with shape `[..., r_o, c_o]`\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [BatchMatMulV2](#classtensorflow_1_1ops_1_1_batch_mat_mul_v2_1a72c2f4ad83e7c11063fadaf661ec6d54)`(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)` x, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` y)` ||\n| [BatchMatMulV2](#classtensorflow_1_1ops_1_1_batch_mat_mul_v2_1a6990e4599f21b54bb5f18572d215fcb1)`(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)` x, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` y, const `[BatchMatMulV2::Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/batch-mat-mul-v2/attrs#structtensorflow_1_1ops_1_1_batch_mat_mul_v2_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|----------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_batch_mat_mul_v2_1a6b83c78f1764f9f38262039680f75f48) | [Operation](/versions/r1.15/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output](#classtensorflow_1_1ops_1_1_batch_mat_mul_v2_1ac477c6e218d7285987ba896599db161e) | `::`[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_batch_mat_mul_v2_1a11c6e4f79b4fbd6ce36ecbc3c84c1e6e)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_batch_mat_mul_v2_1af48144aa8d3a20f660281a87abccb7b8)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_batch_mat_mul_v2_1a807920b129cb268198f13fa48d55d9b7)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|---------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------|\n| [AdjX](#classtensorflow_1_1ops_1_1_batch_mat_mul_v2_1a8f28eaff740f7852929cd5e69f82196d)`(bool x)` | [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/batch-mat-mul-v2/attrs#structtensorflow_1_1ops_1_1_batch_mat_mul_v2_1_1_attrs) |\n| [AdjY](#classtensorflow_1_1ops_1_1_batch_mat_mul_v2_1a76e0c3ea406e4d375518505611ff3358)`(bool x)` | [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/batch-mat-mul-v2/attrs#structtensorflow_1_1ops_1_1_batch_mat_mul_v2_1_1_attrs) |\n\n| ### Structs ||\n|-------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::BatchMatMulV2::Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/batch-mat-mul-v2/attrs) | Optional attribute setters for [BatchMatMulV2](/versions/r1.15/api_docs/cc/class/tensorflow/ops/batch-mat-mul-v2#classtensorflow_1_1ops_1_1_batch_mat_mul_v2). |\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### BatchMatMulV2\n\n```gdscript\n BatchMatMulV2(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input x,\n ::tensorflow::Input y\n)\n``` \n\n### BatchMatMulV2\n\n```gdscript\n BatchMatMulV2(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input x,\n ::tensorflow::Input y,\n const BatchMatMulV2::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### AdjX\n\n```text\nAttrs AdjX(\n bool x\n)\n``` \n\n### AdjY\n\n```text\nAttrs AdjY(\n bool x\n)\n```"]]