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fluxo tensor:: ops:: BatchToSpace
#include <array_ops.h> BatchToSpace para tensores 4-D do tipo T.
Resumo
Esta é uma versão legada do BatchToSpaceND mais geral.
Reorganiza (permuta) os dados do lote em blocos de dados espaciais, seguido de corte. Esta é a transformação reversa do SpaceToBatch. Mais especificamente, esta operação gera uma cópia do tensor de entrada onde os valores da dimensão batch são movidos em blocos espaciais para as dimensões height e width , seguido pelo corte ao longo das dimensões height e width .
Argumentos:
- escopo: um objeto Escopo
- entrada: tensor 4-D com forma
[batch*block_size*block_size, height_pad/block_size, width_pad/block_size, depth] . Observe que o tamanho do lote do tensor de entrada deve ser divisível por block_size * block_size . - culturas: tensor 2-D de inteiros não negativos com forma
[2, 2] . Ele especifica quantos elementos cortar do resultado intermediário nas dimensões espaciais da seguinte forma: crops = [[crop_top, crop_bottom], [crop_left, crop_right]]
Retorna:
-
Output : 4-D com forma [batch, height, width, depth] , onde: height = height_pad - crop_top - crop_bottom
width = width_pad - crop_left - crop_right
O atributo block_size deve ser maior que um. Indica o tamanho do bloco.
Alguns exemplos:
(1) Para a seguinte entrada de formato [4, 1, 1, 1] e block_size de 2:
[[[[1]]], [[[2]]], [[[3]]], [[[4]]]]
O tensor de saída tem forma [1, 2, 2, 1] e valor:
x = [[[[1], [2]], [[3], [4]]]]
(2) Para a seguinte entrada de formato [4, 1, 1, 3] e block_size de 2:
[[[[1, 2, 3]]], [[[4, 5, 6]]], [[[7, 8, 9]]], [[[10, 11, 12]]]]
O tensor de saída tem forma [1, 2, 2, 3] e valor:
x = [[[[1, 2, 3], [4, 5, 6]],
[[7, 8, 9], [10, 11, 12]]]] (3) Para a seguinte entrada de formato [4, 2, 2, 1] e block_size de 2:
x = [[[[1], [3]], [[9], [11]]],
[[[2], [4]], [[10], [12]]],
[[[5], [7]], [[13], [15]]],
[[[6], [8]], [[14], [16]]]] O tensor de saída tem formato [1, 4, 4, 1] e valor:
x = [[[[1], [2], [3], [4]],
[[5], [6], [7], [8]],
[[9], [10], [11], [12]],
[[13], [14], [15], [16]]]] (4) Para a seguinte entrada de formato [8, 1, 2, 1] e block_size de 2:
x = [[[[1], [3]]], [[[9], [11]]], [[[2], [4]]], [[[10], [12]]],
[[[5], [7]]], [[[13], [15]]], [[[6], [8]]], [[[14], [16]]]] O tensor de saída tem forma [2, 2, 4, 1] e valor:
x = [[[[1], [3]], [[5], [7]]],
[[[2], [4]], [[10], [12]]],
[[[5], [7]], [[13], [15]]],
[[[6], [8]], [[14], [16]]]] Atributos públicos
Funções públicas
nó
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operador::tensorflow::Saída
operator::tensorflow::Output() const
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Última atualização 2025-07-26 UTC.
[null,null,["Última atualização 2025-07-26 UTC."],[],[],null,["# tensorflow::ops::BatchToSpace Class Reference\n\ntensorflow::ops::BatchToSpace\n=============================\n\n`#include \u003carray_ops.h\u003e`\n\n[BatchToSpace](/versions/r2.1/api_docs/cc/class/tensorflow/ops/batch-to-space#classtensorflow_1_1ops_1_1_batch_to_space) for 4-D tensors of type T.\n\nSummary\n-------\n\nThis is a legacy version of the more general [BatchToSpaceND](/versions/r2.1/api_docs/cc/class/tensorflow/ops/batch-to-space-n-d#classtensorflow_1_1ops_1_1_batch_to_space_n_d).\n\nRearranges (permutes) data from batch into blocks of spatial data, followed by cropping. This is the reverse transformation of SpaceToBatch. More specifically, this op outputs a copy of the input tensor where values from the `batch` dimension are moved in spatial blocks to the `height` and `width` dimensions, followed by cropping along the `height` and `width` dimensions.\n\nArguments:\n\n- scope: A [Scope](/versions/r2.1/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- input: 4-D tensor with shape `[batch*block_size*block_size, height_pad/block_size, width_pad/block_size, depth]`. Note that the batch size of the input tensor must be divisible by `block_size * block_size`.\n- crops: 2-D tensor of non-negative integers with shape `[2, 2]`. It specifies how many elements to crop from the intermediate result across the spatial dimensions as follows: \n\n ```scdoc\n crops = [[crop_top, crop_bottom], [crop_left, crop_right]]\n ```\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.1/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): 4-D with shape `[batch, height, width, depth]`, where: \n\n ```scdoc\n height = height_pad - crop_top - crop_bottom\n width = width_pad - crop_left - crop_right\n ```\n\n\u003cbr /\u003e\n\nThe attr `block_size` must be greater than one. It indicates the block size.\n\nSome examples:\n\n(1) For the following input of shape `[4, 1, 1, 1]` and block_size of 2:\n\n\n```text\n[[[[1]]], [[[2]]], [[[3]]], [[[4]]]]\n```\n\n\u003cbr /\u003e\n\nThe output tensor has shape `[1, 2, 2, 1]` and value:\n\n\n```text\nx = [[[[1], [2]], [[3], [4]]]]\n```\n\n\u003cbr /\u003e\n\n(2) For the following input of shape `[4, 1, 1, 3]` and block_size of 2:\n\n\n```text\n[[[[1, 2, 3]]], [[[4, 5, 6]]], [[[7, 8, 9]]], [[[10, 11, 12]]]]\n```\n\n\u003cbr /\u003e\n\nThe output tensor has shape `[1, 2, 2, 3]` and value:\n\n\n```text\nx = [[[[1, 2, 3], [4, 5, 6]],\n [[7, 8, 9], [10, 11, 12]]]]\n```\n\n\u003cbr /\u003e\n\n(3) For the following input of shape `[4, 2, 2, 1]` and block_size of 2:\n\n\n```text\nx = [[[[1], [3]], [[9], [11]]],\n [[[2], [4]], [[10], [12]]],\n [[[5], [7]], [[13], [15]]],\n [[[6], [8]], [[14], [16]]]]\n```\n\n\u003cbr /\u003e\n\nThe output tensor has shape `[1, 4, 4, 1]` and value:\n\n\n```text\nx = [[[[1], [2], [3], [4]],\n [[5], [6], [7], [8]],\n [[9], [10], [11], [12]],\n [[13], [14], [15], [16]]]]\n```\n\n\u003cbr /\u003e\n\n(4) For the following input of shape `[8, 1, 2, 1]` and block_size of 2:\n\n\n```text\nx = [[[[1], [3]]], [[[9], [11]]], [[[2], [4]]], [[[10], [12]]],\n [[[5], [7]]], [[[13], [15]]], [[[6], [8]]], [[[14], [16]]]]\n```\n\n\u003cbr /\u003e\n\nThe output tensor has shape `[2, 2, 4, 1]` and value:\n\n\n```text\nx = [[[[1], [3]], [[5], [7]]],\n [[[2], [4]], [[10], [12]]],\n [[[5], [7]], [[13], [15]]],\n [[[6], [8]], [[14], [16]]]]\n```\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [BatchToSpace](#classtensorflow_1_1ops_1_1_batch_to_space_1a813bf5c031d4af21a394ba903c8dd8e7)`(const ::`[tensorflow::Scope](/versions/r2.1/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` input, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` crops, int64 block_size)` ||\n\n| ### Public attributes ||\n|--------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_batch_to_space_1a4f9b292d9339c4c44142a6dcec013410) | [Operation](/versions/r2.1/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output](#classtensorflow_1_1ops_1_1_batch_to_space_1aacc62122ef498fc3a9ee89afdbcc6b74) | `::`[tensorflow::Output](/versions/r2.1/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public functions ||\n|--------------------------------------------------------------------------------------------------------------------------|------------------------|\n| [node](#classtensorflow_1_1ops_1_1_batch_to_space_1a54c1c787b320c2f52099bc7bc02a85ed)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_batch_to_space_1a23f9170b61d8e17feb37f1615a383de2)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_batch_to_space_1a6e84c3b9b55d05ad30e6bcf376278c1d)`() 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### BatchToSpace\n\n```gdscript\n BatchToSpace(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input input,\n ::tensorflow::Input crops,\n int64 block_size\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```"]]
