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#include <nn_ops.h>
Computes the gradients of convolution with respect to the input.
Summary
Args:
- scope: A Scope object
- input: 4-D with shape
[batch, in_height, in_width, in_channels]. Only shape of tensor is used.
- filter: 4-D with shape
[filter_height, filter_width, in_channels, out_channels].
- out_backprop: 4-D with shape
[batch, out_height, out_width, out_channels]. Gradients w.r.t. the output of the convolution.
- 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.
- padding: The type of padding algorithm to use.
Optional attributes (see Attrs):
- 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.
- 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].
- dilations: 1-D tensor of length 4. The dilation factor for each dimension of
input. If set to k > 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.
Returns:
Output: 4-D with shape [batch, in_height, in_width, in_channels]. Gradient w.r.t. the input of the convolution.
Constructors and Destructors
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Conv2DBackpropInputV2(const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input filter, ::tensorflow::Input out_backprop, const gtl::ArraySlice< int > & strides, StringPiece padding)
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Conv2DBackpropInputV2(const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input filter, ::tensorflow::Input out_backprop, const gtl::ArraySlice< int > & strides, StringPiece padding, const Conv2DBackpropInputV2::Attrs & attrs)
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Public attributes
Public functions
Public static functions
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.
Last updated 2023-10-06 UTC.
[null,null,["Last updated 2023-10-06 UTC."],[],[],null,["# tensorflow::ops::Conv2DBackpropInputV2 Class Reference\n\ntensorflow::ops::Conv2DBackpropInputV2\n======================================\n\n`#include \u003cnn_ops.h\u003e`\n\nComputes the gradients of convolution with respect to the input.\n\nSummary\n-------\n\nArgs:\n\n- scope: A [Scope](/versions/r2.14/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- input: 4-D with shape `[batch, in_height, in_width, in_channels]`. Only shape of tensor is used.\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/r2.14/api_docs/cc/struct/tensorflow/ops/conv2-d-backprop-input-v2/attrs#structtensorflow_1_1ops_1_1_conv2_d_backprop_input_v2_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/r2.14/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| [Conv2DBackpropInputV2](#classtensorflow_1_1ops_1_1_conv2_d_backprop_input_v2_1a7bace044045ebce4879b501ad04907e7)`(const ::`[tensorflow::Scope](/versions/r2.14/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` input, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` filter, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` out_backprop, const gtl::ArraySlice\u003c int \u003e & strides, StringPiece padding)` ||\n| [Conv2DBackpropInputV2](#classtensorflow_1_1ops_1_1_conv2_d_backprop_input_v2_1ab71fcee5df76bf8d4827790eef4a0abe)`(const ::`[tensorflow::Scope](/versions/r2.14/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` input, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` filter, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` out_backprop, const gtl::ArraySlice\u003c int \u003e & strides, StringPiece padding, const `[Conv2DBackpropInputV2::Attrs](/versions/r2.14/api_docs/cc/struct/tensorflow/ops/conv2-d-backprop-input-v2/attrs#structtensorflow_1_1ops_1_1_conv2_d_backprop_input_v2_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|-------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_conv2_d_backprop_input_v2_1a7520f614f8f64f74366298b75ea64b81) | [Operation](/versions/r2.14/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output](#classtensorflow_1_1ops_1_1_conv2_d_backprop_input_v2_1afe458062d295f1e06e0428d6b6497509) | `::`[tensorflow::Output](/versions/r2.14/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_v2_1af7cc64543ba4e5f5589372041795eefd)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_conv2_d_backprop_input_v2_1a6b292149b930da84c947b1341e3e9a21)`() const ` | |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_conv2_d_backprop_input_v2_1aeca7bcdb9c66e73fe91d74c74001b76f)`() const ` | |\n\n| ### Public static functions ||\n|--------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [DataFormat](#classtensorflow_1_1ops_1_1_conv2_d_backprop_input_v2_1aacb4d9b6af29eb8d2d25254101214760)`(StringPiece x)` | [Attrs](/versions/r2.14/api_docs/cc/struct/tensorflow/ops/conv2-d-backprop-input-v2/attrs#structtensorflow_1_1ops_1_1_conv2_d_backprop_input_v2_1_1_attrs) |\n| [Dilations](#classtensorflow_1_1ops_1_1_conv2_d_backprop_input_v2_1a09ea2713b984427062c383fba03048bb)`(const gtl::ArraySlice\u003c int \u003e & x)` | [Attrs](/versions/r2.14/api_docs/cc/struct/tensorflow/ops/conv2-d-backprop-input-v2/attrs#structtensorflow_1_1ops_1_1_conv2_d_backprop_input_v2_1_1_attrs) |\n| [ExplicitPaddings](#classtensorflow_1_1ops_1_1_conv2_d_backprop_input_v2_1a16635cc9f2868330acff6e4618e0f6a9)`(const gtl::ArraySlice\u003c int \u003e & x)` | [Attrs](/versions/r2.14/api_docs/cc/struct/tensorflow/ops/conv2-d-backprop-input-v2/attrs#structtensorflow_1_1ops_1_1_conv2_d_backprop_input_v2_1_1_attrs) |\n| [UseCudnnOnGpu](#classtensorflow_1_1ops_1_1_conv2_d_backprop_input_v2_1ab4668a249b61bcfa57a64143e34daf05)`(bool x)` | [Attrs](/versions/r2.14/api_docs/cc/struct/tensorflow/ops/conv2-d-backprop-input-v2/attrs#structtensorflow_1_1ops_1_1_conv2_d_backprop_input_v2_1_1_attrs) |\n\n| ### Structs ||\n|------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::Conv2DBackpropInputV2::Attrs](/versions/r2.14/api_docs/cc/struct/tensorflow/ops/conv2-d-backprop-input-v2/attrs) | Optional attribute setters for [Conv2DBackpropInputV2](/versions/r2.14/api_docs/cc/class/tensorflow/ops/conv2-d-backprop-input-v2#classtensorflow_1_1ops_1_1_conv2_d_backprop_input_v2). |\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### Conv2DBackpropInputV2\n\n```gdscript\n Conv2DBackpropInputV2(\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 StringPiece padding\n)\n``` \n\n### Conv2DBackpropInputV2\n\n```gdscript\n Conv2DBackpropInputV2(\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 StringPiece padding,\n const Conv2DBackpropInputV2::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```"]]
