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텐서플로우:: 작전:: AvgPool3DGrad
#include <nn_ops.h>
평균 풀링 함수의 기울기를 계산합니다.
요약
인수:
- 범위: 범위 개체
- orig_input_shape: 원래 입력 크기입니다.
- grad:
[batch, depth, rows, cols, channels]
모양의 출력 역전파. - ksize: 길이가 5인 1차원 텐서. 입력 텐서의 각 차원에 대한 창 크기입니다.
ksize[0] = ksize[4] = 1
이어야 합니다. - strides: 길이가 5인 1차원 텐서.
input
의 각 차원에 대한 슬라이딩 윈도우의 보폭입니다. strides[0] = strides[4] = 1
이어야 합니다. - padding: 사용할 패딩 알고리즘 유형입니다.
선택적 속성( Attrs
참조):
- data_format: 입력 및 출력 데이터의 데이터 형식입니다. 기본 형식 "NDHWC"를 사용하면 데이터가 [batch, in_length, in_height, in_width, in_channels] 순서로 저장됩니다. 또는 형식이 "NCDHW"일 수 있으며 데이터 저장 순서는 [batch, in_channels, in_length, in_height, in_width]입니다.
보고:
생성자와 소멸자 |
---|
AvgPool3DGrad (const :: tensorflow::Scope & scope, :: tensorflow::Input orig_input_shape, :: tensorflow::Input grad, const gtl::ArraySlice< int > & ksize, const gtl::ArraySlice< int > & strides, StringPiece padding)
|
AvgPool3DGrad (const :: tensorflow::Scope & scope, :: tensorflow::Input orig_input_shape, :: tensorflow::Input grad, const gtl::ArraySlice< int > & ksize, const gtl::ArraySlice< int > & strides, StringPiece padding, const AvgPool3DGrad::Attrs & attrs) |
공개 속성
공공 기능
마디
::tensorflow::Node * node() const
operator::tensorflow::Input() const
연산자::텐서플로우::출력
operator::tensorflow::Output() const
공개 정적 함수
Attrs DataFormat(
StringPiece x
)
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최종 업데이트: 2025-07-26(UTC)
[null,null,["최종 업데이트: 2025-07-26(UTC)"],[],[],null,["# tensorflow::ops::AvgPool3DGrad Class Reference\n\ntensorflow::ops::AvgPool3DGrad\n==============================\n\n`#include \u003cnn_ops.h\u003e`\n\nComputes gradients of average pooling function.\n\nSummary\n-------\n\nArguments:\n\n- scope: A [Scope](/versions/r2.1/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- orig_input_shape: The original input dimensions.\n- grad: [Output](/versions/r2.1/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) backprop of shape `[batch, depth, rows, cols, channels]`.\n- ksize: 1-D tensor of length 5. The size of the window for each dimension of the input tensor. Must have `ksize[0] = ksize[4] = 1`.\n- strides: 1-D tensor of length 5. The stride of the sliding window for each dimension of `input`. Must have `strides[0] = strides[4] = 1`.\n- padding: The type of padding algorithm to use.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r2.1/api_docs/cc/struct/tensorflow/ops/avg-pool3-d-grad/attrs#structtensorflow_1_1ops_1_1_avg_pool3_d_grad_1_1_attrs)):\n\n- data_format: The data format of the input and output data. With the default format \"NDHWC\", the data is stored in the order of: \\[batch, in_depth, in_height, in_width, in_channels\\]. Alternatively, the format could be \"NCDHW\", the data storage order is: \\[batch, in_channels, in_depth, in_height, in_width\\].\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.1/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): The backprop for input.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [AvgPool3DGrad](#classtensorflow_1_1ops_1_1_avg_pool3_d_grad_1ac294eebcd4d868dfa68e6a5f7d4c5ea9)`(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)` orig_input_shape, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` grad, const gtl::ArraySlice\u003c int \u003e & ksize, const gtl::ArraySlice\u003c int \u003e & strides, StringPiece padding)` ||\n| [AvgPool3DGrad](#classtensorflow_1_1ops_1_1_avg_pool3_d_grad_1a8362b0628d56d49ee76c24faaed842f9)`(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)` orig_input_shape, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` grad, const gtl::ArraySlice\u003c int \u003e & ksize, const gtl::ArraySlice\u003c int \u003e & strides, StringPiece padding, const `[AvgPool3DGrad::Attrs](/versions/r2.1/api_docs/cc/struct/tensorflow/ops/avg-pool3-d-grad/attrs#structtensorflow_1_1ops_1_1_avg_pool3_d_grad_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|----------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_avg_pool3_d_grad_1ac7d2ea5c42f4949a936e71f6debf81be) | [Operation](/versions/r2.1/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output](#classtensorflow_1_1ops_1_1_avg_pool3_d_grad_1a9709fb2d31ca099ef81e317ecef40df8) | `::`[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_avg_pool3_d_grad_1a30c25a58bfaad694e981cf0bbf407254)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_avg_pool3_d_grad_1a4738d18b18c18a46d9f6d9c262df86a2)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_avg_pool3_d_grad_1ac991ec111bedce628daadef30690cd18)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|----------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------|\n| [DataFormat](#classtensorflow_1_1ops_1_1_avg_pool3_d_grad_1aa9e0fbc35b1b72dd2e277ff5db79ca99)`(StringPiece x)` | [Attrs](/versions/r2.1/api_docs/cc/struct/tensorflow/ops/avg-pool3-d-grad/attrs#structtensorflow_1_1ops_1_1_avg_pool3_d_grad_1_1_attrs) |\n\n| ### Structs ||\n|------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::AvgPool3DGrad::Attrs](/versions/r2.1/api_docs/cc/struct/tensorflow/ops/avg-pool3-d-grad/attrs) | Optional attribute setters for [AvgPool3DGrad](/versions/r2.1/api_docs/cc/class/tensorflow/ops/avg-pool3-d-grad#classtensorflow_1_1ops_1_1_avg_pool3_d_grad). |\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### AvgPool3DGrad\n\n```gdscript\n AvgPool3DGrad(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input orig_input_shape,\n ::tensorflow::Input grad,\n const gtl::ArraySlice\u003c int \u003e & ksize,\n const gtl::ArraySlice\u003c int \u003e & strides,\n StringPiece padding\n)\n``` \n\n### AvgPool3DGrad\n\n```gdscript\n AvgPool3DGrad(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input orig_input_shape,\n ::tensorflow::Input grad,\n const gtl::ArraySlice\u003c int \u003e & ksize,\n const gtl::ArraySlice\u003c int \u003e & strides,\n StringPiece padding,\n const AvgPool3DGrad::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### DataFormat\n\n```text\nAttrs DataFormat(\n StringPiece x\n)\n```"]]