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#include <nn_ops.h> 입력값에 대한 형태학적 2차원 팽창의 기울기를 계산합니다.
요약
인수:
- 범위: 범위 개체
- 입력:
[batch, in_height, in_width, depth] 모양의 4D. - 필터:
[filter_height, filter_width, depth] 모양의 3D입니다. - out_backprop:
[batch, out_height, out_width, depth] 모양의 4D입니다. - strides: 길이 4의 1-D. 입력 텐서의 각 차원에 대한 슬라이딩 윈도우의 보폭입니다. 다음과 같아야 합니다:
[1, stride_height, stride_width, 1] . - 속도: 길이 4의 1-D. 심방 형태학적 확장에 대한 입력 보폭입니다. 다음과 같아야 합니다:
[1, rate_height, rate_width, 1] . - padding: 사용할 패딩 알고리즘 유형입니다.
보고:
-
Output : [batch, in_height, in_width, depth] 모양의 4D.
공개 속성
공공 기능
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최종 업데이트: 2025-07-26(UTC)
[null,null,["최종 업데이트: 2025-07-26(UTC)"],[],[],null,["# tensorflow::ops::Dilation2DBackpropInput Class Reference\n\ntensorflow::ops::Dilation2DBackpropInput\n========================================\n\n`#include \u003cnn_ops.h\u003e`\n\nComputes the gradient of morphological 2-D dilation with respect to the input.\n\nSummary\n-------\n\nArguments:\n\n- scope: A [Scope](/versions/r2.2/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- input: 4-D with shape `[batch, in_height, in_width, depth]`.\n- filter: 3-D with shape `[filter_height, filter_width, depth]`.\n- out_backprop: 4-D with shape `[batch, out_height, out_width, depth]`.\n- strides: 1-D of length 4. The stride of the sliding window for each dimension of the input tensor. Must be: `[1, stride_height, stride_width, 1]`.\n- rates: 1-D of length 4. The input stride for atrous morphological dilation. Must be: `[1, rate_height, rate_width, 1]`.\n- padding: The type of padding algorithm to use.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.2/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): 4-D with shape `[batch, in_height, in_width, depth]`.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [Dilation2DBackpropInput](#classtensorflow_1_1ops_1_1_dilation2_d_backprop_input_1a656665a13419870e177ca6b67a869f31)`(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)` input, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` filter, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` out_backprop, const gtl::ArraySlice\u003c int \u003e & strides, const gtl::ArraySlice\u003c int \u003e & rates, StringPiece padding)` ||\n\n| ### Public attributes ||\n|----------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [in_backprop](#classtensorflow_1_1ops_1_1_dilation2_d_backprop_input_1a40353e552051aa8801ef9f9ad4efc15c) | `::`[tensorflow::Output](/versions/r2.2/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n| [operation](#classtensorflow_1_1ops_1_1_dilation2_d_backprop_input_1a02412d298e84e41cd1bd2a21b9a064f4) | [Operation](/versions/r2.2/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n\n| ### Public functions ||\n|--------------------------------------------------------------------------------------------------------------------------------------|------------------------|\n| [node](#classtensorflow_1_1ops_1_1_dilation2_d_backprop_input_1ab58e7a7ffead7f2dd0dcc062204f47f8)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_dilation2_d_backprop_input_1a4ad020555d5b8ffc10bdf49956232358)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_dilation2_d_backprop_input_1a8029c3562d2413ed5a8b249933690e32)`() const ` | ` ` ` ` |\n\nPublic attributes\n-----------------\n\n### in_backprop\n\n```scdoc\n::tensorflow::Output in_backprop\n``` \n\n### operation\n\n```text\nOperation operation\n``` \n\nPublic functions\n----------------\n\n### Dilation2DBackpropInput\n\n```gdscript\n Dilation2DBackpropInput(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input input,\n ::tensorflow::Input filter,\n ::tensorflow::Input out_backprop,\n const gtl::ArraySlice\u003c int \u003e & strides,\n const gtl::ArraySlice\u003c int \u003e & rates,\n StringPiece padding\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```"]]
