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내 환경설정을 기준으로 콘텐츠를 저장하고 분류하세요.
#include <nn_ops.h>
입력에 대한 깊이별 컨벌루션의 기울기를 계산합니다.
요약
인수:
- 범위: 범위 개체
- input_sizes:
data_format
기반으로 input
의 모양을 나타내는 정수 벡터입니다. 예를 들어 data_format
이 'NHWC'인 경우 input
4차원 [batch, height, width, channels]
텐서입니다. - 필터:
[filter_height, filter_width, in_channels, depthwise_multiplier]
모양의 4차원입니다. - out_backprop:
data_format
기반으로 한 모양의 4D입니다. 예를 들어 data_format
'NHWC'이면 out_backprop 모양은 [batch, out_height, out_width, out_channels]
입니다. 그라데이션은 컨볼루션의 출력을 나타냅니다. - strides: 컨볼루션 입력의 각 차원에 대한 슬라이딩 윈도우의 보폭입니다.
- padding: 사용할 패딩 알고리즘 유형입니다.
선택적 속성( Attrs
참조):
- data_format: 입력 및 출력 데이터의 데이터 형식을 지정합니다. 기본 형식인 "NHWC"를 사용하면 데이터가 [배치, 높이, 너비, 채널] 순서로 저장됩니다. 또는 형식은 [배치, 채널, 높이, 너비]의 데이터 저장 순서인 "NCHW"일 수 있습니다.
- 팽창: 길이가 4인 1차원 텐서.
input
의 각 차원에 대한 팽창 인자입니다. k > 1로 설정되면 해당 차원의 각 필터 요소 사이에 k-1개의 건너뛴 셀이 있게 됩니다. 차원 순서는 data_format
값에 따라 결정됩니다. 자세한 내용은 위를 참조하세요. 배치 차원과 깊이 차원의 팽창은 1이어야 합니다.
보고:
-
Output
: data_format
에 따른 모양의 4D. 예를 들어 data_format
'NHWC'인 경우 출력 모양은 [batch, in_height, in_width, in_channels]
입니다. 컨볼루션의 입력에 대한 그라데이션입니다.
생성자와 소멸자 |
---|
DepthwiseConv2dNativeBackpropInput (const :: tensorflow::Scope & scope, :: tensorflow::Input input_sizes, :: tensorflow::Input filter, :: tensorflow::Input out_backprop, const gtl::ArraySlice< int > & strides, StringPiece padding)
|
DepthwiseConv2dNativeBackpropInput (const :: tensorflow::Scope & scope, :: tensorflow::Input input_sizes, :: tensorflow::Input filter, :: tensorflow::Input out_backprop, const gtl::ArraySlice< int > & strides, StringPiece padding, const DepthwiseConv2dNativeBackpropInput::Attrs & attrs) |
공개 속성
공공 기능
공개 정적 함수
달리 명시되지 않는 한 이 페이지의 콘텐츠에는 Creative Commons Attribution 4.0 라이선스에 따라 라이선스가 부여되며, 코드 샘플에는 Apache 2.0 라이선스에 따라 라이선스가 부여됩니다. 자세한 내용은 Google Developers 사이트 정책을 참조하세요. 자바는 Oracle 및/또는 Oracle 계열사의 등록 상표입니다.
최종 업데이트: 2025-07-27(UTC)
[null,null,["최종 업데이트: 2025-07-27(UTC)"],[],[],null,["# tensorflow::ops::DepthwiseConv2dNativeBackpropInput Class Reference\n\ntensorflow::ops::DepthwiseConv2dNativeBackpropInput\n===================================================\n\n`#include \u003cnn_ops.h\u003e`\n\nComputes the gradients of depthwise convolution 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_sizes: An integer vector representing the shape of `input`, based on `data_format`. For example, if `data_format` is 'NHWC' then `input` is a 4-D `[batch, height, width, channels]` tensor.\n- filter: 4-D with shape `[filter_height, filter_width, in_channels, depthwise_multiplier]`.\n- out_backprop: 4-D with shape based on `data_format`. For example, if `data_format` is 'NHWC' then out_backprop shape is `[batch, out_height, out_width, out_channels]`. Gradients w.r.t. the output of the convolution.\n- strides: The stride of the sliding window for each dimension of the input of the convolution.\n- padding: The type of padding algorithm to use.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/depthwise-conv2d-native-backprop-input/attrs#structtensorflow_1_1ops_1_1_depthwise_conv2d_native_backprop_input_1_1_attrs)):\n\n- data_format: Specify the data format of the input and output data. With the default format \"NHWC\", the data is stored in the order of: \\[batch, height, width, channels\\]. Alternatively, the format could be \"NCHW\", the data storage order of: \\[batch, channels, height, width\\].\n- dilations: 1-D tensor of length 4. The dilation factor for each dimension of `input`. If set to k \\\u003e 1, there will be k-1 skipped cells between each filter element on that dimension. The dimension order is determined by the value of `data_format`, see above for details. Dilations in the batch and depth dimensions must be 1.\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 according to `data_format`. For example, if `data_format` is 'NHWC', output shape is `[batch, in_height, in_width, in_channels]`. Gradient w.r.t. the input of the convolution.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [DepthwiseConv2dNativeBackpropInput](#classtensorflow_1_1ops_1_1_depthwise_conv2d_native_backprop_input_1a44860b426baf7a003c44728e835f9d05)`(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_sizes, ::`[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, StringPiece padding)` ||\n| [DepthwiseConv2dNativeBackpropInput](#classtensorflow_1_1ops_1_1_depthwise_conv2d_native_backprop_input_1a014c3bb2ee403a82ec24f10992c7b580)`(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_sizes, ::`[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, StringPiece padding, const `[DepthwiseConv2dNativeBackpropInput::Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/depthwise-conv2d-native-backprop-input/attrs#structtensorflow_1_1ops_1_1_depthwise_conv2d_native_backprop_input_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|--------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_depthwise_conv2d_native_backprop_input_1a66a4628fc7014482be2512ecff5a7f06) | [Operation](/versions/r2.2/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output](#classtensorflow_1_1ops_1_1_depthwise_conv2d_native_backprop_input_1a024ccdda3b9ee57913c71eb5dae1929c) | `::`[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_depthwise_conv2d_native_backprop_input_1a6e062166cae2aa251281f02dcec6154c)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_depthwise_conv2d_native_backprop_input_1a4d40006ebcb3defcaf1f2e6e469516d9)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_depthwise_conv2d_native_backprop_input_1af4f0b912eeeefe1eecf1c33eb20dd4b4)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|--------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [DataFormat](#classtensorflow_1_1ops_1_1_depthwise_conv2d_native_backprop_input_1a3120c51e47ec70855e85f50c57743e34)`(StringPiece x)` | [Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/depthwise-conv2d-native-backprop-input/attrs#structtensorflow_1_1ops_1_1_depthwise_conv2d_native_backprop_input_1_1_attrs) |\n| [Dilations](#classtensorflow_1_1ops_1_1_depthwise_conv2d_native_backprop_input_1a94c81fcd8b2ef27c98cec5ec75a8819b)`(const gtl::ArraySlice\u003c int \u003e & x)` | [Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/depthwise-conv2d-native-backprop-input/attrs#structtensorflow_1_1ops_1_1_depthwise_conv2d_native_backprop_input_1_1_attrs) |\n\n| ### Structs ||\n|-------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::DepthwiseConv2dNativeBackpropInput::Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/depthwise-conv2d-native-backprop-input/attrs) | Optional attribute setters for [DepthwiseConv2dNativeBackpropInput](/versions/r2.2/api_docs/cc/class/tensorflow/ops/depthwise-conv2d-native-backprop-input#classtensorflow_1_1ops_1_1_depthwise_conv2d_native_backprop_input). |\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### DepthwiseConv2dNativeBackpropInput\n\n```gdscript\n DepthwiseConv2dNativeBackpropInput(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input input_sizes,\n ::tensorflow::Input filter,\n ::tensorflow::Input out_backprop,\n const gtl::ArraySlice\u003c int \u003e & strides,\n StringPiece padding\n)\n``` \n\n### DepthwiseConv2dNativeBackpropInput\n\n```gdscript\n DepthwiseConv2dNativeBackpropInput(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input input_sizes,\n ::tensorflow::Input filter,\n ::tensorflow::Input out_backprop,\n const gtl::ArraySlice\u003c int \u003e & strides,\n StringPiece padding,\n const DepthwiseConv2dNativeBackpropInput::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``` \n\n### Dilations\n\n```gdscript\nAttrs Dilations(\n const gtl::ArraySlice\u003c int \u003e & x\n)\n```"]]