Organízate con las colecciones
Guarda y clasifica el contenido según tus preferencias.
flujo tensor:: operaciones:: Lote al espacio
#include <array_ops.h>
BatchToSpace para tensores 4-D de tipo T.
Resumen
Esta es una versión heredada del BatchToSpaceND más general.
Reorganiza (permuta) datos del lote en bloques de datos espaciales, seguido de recorte. Esta es la transformación inversa de SpaceToBatch. Más específicamente, esta operación genera una copia del tensor de entrada donde los valores de la dimensión batch
se mueven en bloques espaciales a las dimensiones height
y width
, seguido de un recorte a lo largo de las dimensiones height
y width
.
Argumentos:
- alcance: un objeto de alcance
- entrada: tensor 4-D con forma
[batch*block_size*block_size, height_pad/block_size, width_pad/block_size, depth]
. Tenga en cuenta que el tamaño del lote del tensor de entrada debe ser divisible por block_size * block_size
. - cultivos: tensor 2-D de números enteros no negativos con forma
[2, 2]
. Especifica cuántos elementos recortar del resultado intermedio en las dimensiones espaciales de la siguiente manera: crops = [[crop_top, crop_bottom], [crop_left, crop_right]]
Devoluciones:
-
Output
: 4-D con forma [batch, height, width, depth]
, donde: height = height_pad - crop_top - crop_bottom
width = width_pad - crop_left - crop_right
El atributo block_size
debe ser mayor que uno. Indica el tamaño del bloque.
Algunos ejemplos:
(1) Para la siguiente entrada de forma [4, 1, 1, 1]
y tamaño_bloque de 2:
[[[[1]]], [[[2]]], [[[3]]], [[[4]]]]
El tensor de salida tiene forma [1, 2, 2, 1]
y valor:
x = [[[[1], [2]], [[3], [4]]]]
(2) Para la siguiente entrada de forma [4, 1, 1, 3]
y tamaño_bloque de 2:
[[[[1, 2, 3]]], [[[4, 5, 6]]], [[[7, 8, 9]]], [[[10, 11, 12]]]]
El tensor de salida tiene forma [1, 2, 2, 3]
y valor:
x = [[[[1, 2, 3], [4, 5, 6]],
[[7, 8, 9], [10, 11, 12]]]]
(3) Para la siguiente entrada de forma [4, 2, 2, 1]
y tamaño_bloque de 2:
x = [[[[1], [3]], [[9], [11]]],
[[[2], [4]], [[10], [12]]],
[[[5], [7]], [[13], [15]]],
[[[6], [8]], [[14], [16]]]]
El tensor de salida tiene forma [1, 4, 4, 1]
y valor:
x = [[[[1], [2], [3], [4]],
[[5], [6], [7], [8]],
[[9], [10], [11], [12]],
[[13], [14], [15], [16]]]]
(4) Para la siguiente entrada de forma [8, 1, 2, 1]
y tamaño_bloque de 2:
x = [[[[1], [3]]], [[[9], [11]]], [[[2], [4]]], [[[10], [12]]],
[[[5], [7]]], [[[13], [15]]], [[[6], [8]]], [[[14], [16]]]]
El tensor de salida tiene forma [2, 2, 4, 1]
y valor:
x = [[[[1], [3]], [[5], [7]]],
[[[2], [4]], [[10], [12]]],
[[[5], [7]], [[13], [15]]],
[[[6], [8]], [[14], [16]]]]
Atributos públicos
Funciones públicas
nodo
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operador::tensorflow::Salida
operator::tensorflow::Output() const
A menos que se indique lo contrario, el contenido de esta página está sujeto a la licencia Reconocimiento 4.0 de Creative Commons y las muestras de código están sujetas a la licencia Apache 2.0. Para obtener más información, consulta las políticas del sitio web de Google Developers. Java es una marca registrada de Oracle o sus afiliados.
Última actualización: 2025-07-26 (UTC).
[null,null,["Última actualización: 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```"]]