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tensoreflusso:: ops:: BatchMatMul
#include <math_ops.h>
Moltiplica le fette di due tensori in batch.
Riepilogo
Moltiplica tutte le sezioni del Tensor
x
(ogni sezione può essere visualizzata come un elemento di un batch y
e dispone i singoli risultati in un singolo tensore di output della stessa dimensione del batch. Ciascuna delle singole fette può facoltativamente essere unita (aggiungere una matrice significa trasponerla e coniugarla) prima della moltiplicazione impostando il flag adj_x
o adj_y
su True
, che sono per impostazione predefinita False
.
I tensori di input x
y
2-D o superiori con forma [..., r_x, c_x]
e [..., r_y, c_y]
.
Il tensore di output è 2-D o superiore con forma [..., r_o, c_o]
, dove:
r_o = c_x if adj_x else r_x
c_o = r_y if adj_y else c_y
Viene calcolato come:
output[..., :, :] = matrix(x[..., :, :]) * matrix(y[..., :, :])
Argomenti:
- scope: un oggetto Scope
- x: 2-D o superiore con forma
[..., r_x, c_x]
. - y: 2-D o superiore con forma
[..., r_y, c_y]
.
Attributi facoltativi (vedi Attrs
):
- adj_x: Se
True
, aggiunge le fette di x
. Il valore predefinito è False
. - adj_y: Se
True
, aggiunge le fette di y
. Il valore predefinito è False
.
Resi:
-
Output
: 3-D o superiore con forma [..., r_o, c_o]
Funzioni pubbliche statiche |
---|
AdjX (bool x) | |
AdjY (bool x) | |
Attributi pubblici
Funzioni pubbliche
nodo
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operatore::tensorflow::Output
operator::tensorflow::Output() const
Funzioni pubbliche statiche
AdjX
Attrs AdjX(
bool x
)
AdjY
Attrs AdjY(
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 2025-07-26 UTC.
[null,null,["Ultimo aggiornamento 2025-07-26 UTC."],[],[],null,["# tensorflow::ops::BatchMatMul Class Reference\n\ntensorflow::ops::BatchMatMul\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/r2.2/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\nArguments:\n\n- scope: A [Scope](/versions/r2.2/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/r2.2/api_docs/cc/struct/tensorflow/ops/batch-mat-mul/attrs#structtensorflow_1_1ops_1_1_batch_mat_mul_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/r2.2/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| [BatchMatMul](#classtensorflow_1_1ops_1_1_batch_mat_mul_1a951cabca8c8dbcf8b746969d80f2b480)`(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)` x, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` y)` ||\n| [BatchMatMul](#classtensorflow_1_1ops_1_1_batch_mat_mul_1aec4aecf952592bd193eca45a9900ebe1)`(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)` x, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` y, const `[BatchMatMul::Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/batch-mat-mul/attrs#structtensorflow_1_1ops_1_1_batch_mat_mul_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|-------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_batch_mat_mul_1a255c486fdefe3708a3355e3f85e8daf2) | [Operation](/versions/r2.2/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output](#classtensorflow_1_1ops_1_1_batch_mat_mul_1ad3a290bbf8589298ccf6cd5bf0018a53) | `::`[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_batch_mat_mul_1af21f279f44b701fb277af586e5f0dd69)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_batch_mat_mul_1aa6685ef6076abe41dc6d4f97156d77cb)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_batch_mat_mul_1a7d6d385af7d73a390e36ccc7e6989345)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------|\n| [AdjX](#classtensorflow_1_1ops_1_1_batch_mat_mul_1a47c8466020881eced6720f2f415053dd)`(bool x)` | [Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/batch-mat-mul/attrs#structtensorflow_1_1ops_1_1_batch_mat_mul_1_1_attrs) |\n| [AdjY](#classtensorflow_1_1ops_1_1_batch_mat_mul_1a3f939eb8aea098cdf431a3b626274e6b)`(bool x)` | [Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/batch-mat-mul/attrs#structtensorflow_1_1ops_1_1_batch_mat_mul_1_1_attrs) |\n\n| ### Structs ||\n|-------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::BatchMatMul::Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/batch-mat-mul/attrs) | Optional attribute setters for [BatchMatMul](/versions/r2.2/api_docs/cc/class/tensorflow/ops/batch-mat-mul#classtensorflow_1_1ops_1_1_batch_mat_mul). |\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### BatchMatMul\n\n```gdscript\n BatchMatMul(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input x,\n ::tensorflow::Input y\n)\n``` \n\n### BatchMatMul\n\n```gdscript\n BatchMatMul(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input x,\n ::tensorflow::Input y,\n const BatchMatMul::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```"]]