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tensor akışı:: işlem:: OrtPool3DGrad
#include <nn_ops.h> Ortalama havuzlama fonksiyonunun gradyanlarını hesaplar.
Özet
Argümanlar:
- kapsam: Bir Kapsam nesnesi
- orig_input_shape: Orijinal giriş boyutları.
- grad: Şeklin çıktı arka desteği
[batch, depth, rows, cols, channels] . - ksize: 5 uzunluğundaki 1 boyutlu tensör. Giriş tensörünün her boyutu için pencerenin boyutu.
ksize[0] = ksize[4] = 1 olmalıdır. - adımlar: 5 uzunluğundaki 1 boyutlu tensör.
input her boyutu için kayan pencerenin adımı. strides[0] = strides[4] = 1 olmalıdır. - padding: Kullanılacak dolgu algoritmasının türü.
İsteğe bağlı özellikler (bkz. Attrs ):
- data_format: Giriş ve çıkış verilerinin veri formatı. Varsayılan "NDHWC" biçimiyle veriler şu sırayla saklanır: [toplu iş, derinlik_içi, yükseklik_içi, genişlik_içi, kanallar_içi]. Alternatif olarak format "NCDHW" olabilir ve veri depolama sırası şu şekildedir: [toplu iş, kanal içi, derinlik, derinlik, yükseklik, genişlik].
İade:
-
Output : Giriş için arka destek.
Yapıcılar ve Yıkıcılar |
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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)
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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)
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Genel özellikler
Kamu işlevleri
düğüm
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operatör::tensorflow::Çıktı
operator::tensorflow::Output() const
Genel statik işlevler
Attrs DataFormat(
StringPiece x
)
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Son güncelleme tarihi: 2025-07-26 UTC.
[null,null,["Son güncelleme tarihi: 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```"]]
