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#include <nn_ops.h> Calcula os gradientes de convolução em relação à entrada.
Resumo
Argumentos:
- escopo: um objeto Escopo
- input_sizes: um vetor inteiro que representa a forma de
input , onde input é um tensor 4-D [batch, height, width, channels] . - filtro: 4-D com forma
[filter_height, filter_width, in_channels, out_channels] . - out_backprop: 4-D com forma
[batch, out_height, out_width, out_channels] . Os gradientes representam a saída da convolução. - passos: O passo da janela deslizante para cada dimensão da entrada da convolução. Deve estar na mesma ordem que a dimensão especificada com formato.
- preenchimento: O tipo de algoritmo de preenchimento a ser usado.
Atributos opcionais (veja Attrs ):
- explicit_paddings: se
padding for "EXPLICIT" , a lista de valores de preenchimento explícitos. Para a i-ésima dimensão, a quantidade de preenchimento inserida antes e depois da dimensão é explicit_paddings[2 * i] e explicit_paddings[2 * i + 1] , respectivamente. Se padding não for "EXPLICIT" , explicit_paddings deverá estar vazio. - data_format: Especifique o formato dos dados de entrada e saída. Com o formato padrão "NHWC", os dados são armazenados na ordem de: [lote, in_height, in_width, in_channels]. Alternativamente, o formato pode ser "NCHW", a ordem de armazenamento de dados de: [lote, in_channels, in_height, in_width].
- dilatações: tensor 1-D de comprimento 4. O fator de dilatação para cada dimensão da
input . Se definido como k > 1, haverá k-1 células ignoradas entre cada elemento de filtro nessa dimensão. A ordem das dimensões é determinada pelo valor de data_format , veja detalhes acima. As dilatações nas dimensões do lote e profundidade devem ser 1.
Retorna:
-
Output : 4-D com forma [batch, in_height, in_width, in_channels] . Gradiente em relação à entrada da convolução.
Construtores e Destruidores |
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Conv2DBackpropInput (const :: tensorflow::Scope & scope, :: tensorflow::Input input_sizes, :: tensorflow::Input filter, :: tensorflow::Input out_backprop, const gtl::ArraySlice< int > & strides, StringPiece padding)
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Conv2DBackpropInput (const :: tensorflow::Scope & scope, :: tensorflow::Input input_sizes, :: tensorflow::Input filter, :: tensorflow::Input out_backprop, const gtl::ArraySlice< int > & strides, StringPiece padding, const Conv2DBackpropInput::Attrs & attrs)
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Atributos públicos
Funções públicas
Funções estáticas públicas
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Última atualização 2025-07-26 UTC.
[null,null,["Última atualização 2025-07-26 UTC."],[],[],null,["# tensorflow::ops::Conv2DBackpropInput Class Reference\n\ntensorflow::ops::Conv2DBackpropInput\n====================================\n\n`#include \u003cnn_ops.h\u003e`\n\nComputes the gradients of convolution with respect to the input.\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- input_sizes: An integer vector representing the shape of `input`, where `input` is a 4-D `[batch, height, width, channels]` tensor.\n- filter: 4-D with shape `[filter_height, filter_width, in_channels, out_channels]`.\n- out_backprop: 4-D with shape `[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. Must be in the same order as the dimension specified with format.\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/conv2-d-backprop-input/attrs#structtensorflow_1_1ops_1_1_conv2_d_backprop_input_1_1_attrs)):\n\n- explicit_paddings: If `padding` is `\"EXPLICIT\"`, the list of explicit padding amounts. For the ith dimension, the amount of padding inserted before and after the dimension is `explicit_paddings[2 * i]` and `explicit_paddings[2 * i + 1]`, respectively. If `padding` is not `\"EXPLICIT\"`, `explicit_paddings` must be empty.\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, in_height, in_width, in_channels\\]. Alternatively, the format could be \"NCHW\", the data storage order of: \\[batch, in_channels, in_height, in_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/r2.1/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): 4-D with shape `[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| [Conv2DBackpropInput](#classtensorflow_1_1ops_1_1_conv2_d_backprop_input_1aa5357992b64dbb43b51d35c084d442d8)`(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_sizes, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` filter, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` out_backprop, const gtl::ArraySlice\u003c int \u003e & strides, StringPiece padding)` ||\n| [Conv2DBackpropInput](#classtensorflow_1_1ops_1_1_conv2_d_backprop_input_1a01da97aaaf681a4f6f45d3bda57f0f82)`(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_sizes, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` filter, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` out_backprop, const gtl::ArraySlice\u003c int \u003e & strides, StringPiece padding, const `[Conv2DBackpropInput::Attrs](/versions/r2.1/api_docs/cc/struct/tensorflow/ops/conv2-d-backprop-input/attrs#structtensorflow_1_1ops_1_1_conv2_d_backprop_input_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|----------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_conv2_d_backprop_input_1aebb0f66b81bb602fa8600e2e32f621b2) | [Operation](/versions/r2.1/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output](#classtensorflow_1_1ops_1_1_conv2_d_backprop_input_1a53bf3bf2eb2af62764981f62c794fbe2) | `::`[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_conv2_d_backprop_input_1acf62af3e404315cfe9622e3d1295033b)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_conv2_d_backprop_input_1a94315c7d6148fb6451deb58f91955405)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_conv2_d_backprop_input_1a1bced60701935dddacef1af9398879df)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|-----------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------|\n| [DataFormat](#classtensorflow_1_1ops_1_1_conv2_d_backprop_input_1ac762988224740afda86e2a852ef11774)`(StringPiece x)` | [Attrs](/versions/r2.1/api_docs/cc/struct/tensorflow/ops/conv2-d-backprop-input/attrs#structtensorflow_1_1ops_1_1_conv2_d_backprop_input_1_1_attrs) |\n| [Dilations](#classtensorflow_1_1ops_1_1_conv2_d_backprop_input_1a01b3b905a6bba3d7c7e61238d45109e4)`(const gtl::ArraySlice\u003c int \u003e & x)` | [Attrs](/versions/r2.1/api_docs/cc/struct/tensorflow/ops/conv2-d-backprop-input/attrs#structtensorflow_1_1ops_1_1_conv2_d_backprop_input_1_1_attrs) |\n| [ExplicitPaddings](#classtensorflow_1_1ops_1_1_conv2_d_backprop_input_1a4f19fe8f8ae4c3b237038489ba58a721)`(const gtl::ArraySlice\u003c int \u003e & x)` | [Attrs](/versions/r2.1/api_docs/cc/struct/tensorflow/ops/conv2-d-backprop-input/attrs#structtensorflow_1_1ops_1_1_conv2_d_backprop_input_1_1_attrs) |\n| [UseCudnnOnGpu](#classtensorflow_1_1ops_1_1_conv2_d_backprop_input_1a6df425d872077ec66d9eb2e2b42f767b)`(bool x)` | [Attrs](/versions/r2.1/api_docs/cc/struct/tensorflow/ops/conv2-d-backprop-input/attrs#structtensorflow_1_1ops_1_1_conv2_d_backprop_input_1_1_attrs) |\n\n| ### Structs ||\n|------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::Conv2DBackpropInput::Attrs](/versions/r2.1/api_docs/cc/struct/tensorflow/ops/conv2-d-backprop-input/attrs) | Optional attribute setters for [Conv2DBackpropInput](/versions/r2.1/api_docs/cc/class/tensorflow/ops/conv2-d-backprop-input#classtensorflow_1_1ops_1_1_conv2_d_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### Conv2DBackpropInput\n\n```gdscript\n Conv2DBackpropInput(\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### Conv2DBackpropInput\n\n```gdscript\n Conv2DBackpropInput(\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 Conv2DBackpropInput::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``` \n\n### ExplicitPaddings\n\n```gdscript\nAttrs ExplicitPaddings(\n const gtl::ArraySlice\u003c int \u003e & x\n)\n``` \n\n### UseCudnnOnGpu\n\n```text\nAttrs UseCudnnOnGpu(\n bool x\n)\n```"]]
