Koleksiyonlar ile düzeninizi koruyun
İçeriği tercihlerinize göre kaydedin ve kategorilere ayırın.
tensor akışı:: işlem:: MaxPool3DGradGrad
#include <nn_ops.h> Maksimum havuzlama fonksiyonunun ikinci dereceden gradyanlarını hesaplar.
Özet
Argümanlar:
- kapsam: Bir Kapsam nesnesi
- orig_input: Orijinal giriş tensörü.
- orig_output: Orijinal çıkış tensörü.
- 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: uzunluğun 1 boyutlu tensörü 5.
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, derinlemesine, yükseklik, yükseklik, genişlik, kanallar içi]. Alternatif olarak format "NCDHW" olabilir ve veri depolama sırası şu şekildedir: [toplu iş, kanal içi, derinlik, yükseklik, genişlik].
İade:
-
Output : max_pool girilen degradelerin gradyanları.
Yapıcılar ve Yıkıcılar |
|---|
MaxPool3DGradGrad (const :: tensorflow::Scope & scope, :: tensorflow::Input orig_input, :: tensorflow::Input orig_output, :: tensorflow::Input grad, const gtl::ArraySlice< int > & ksize, const gtl::ArraySlice< int > & strides, StringPiece padding)
|
MaxPool3DGradGrad (const :: tensorflow::Scope & scope, :: tensorflow::Input orig_input, :: tensorflow::Input orig_output, :: tensorflow::Input grad, const gtl::ArraySlice< int > & ksize, const gtl::ArraySlice< int > & strides, StringPiece padding, const MaxPool3DGradGrad::Attrs & attrs)
|
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
)
Aksi belirtilmediği sürece bu sayfanın içeriği Creative Commons Atıf 4.0 Lisansı altında ve kod örnekleri Apache 2.0 Lisansı altında lisanslanmıştır. Ayrıntılı bilgi için Google Developers Site Politikaları'na göz atın. Java, Oracle ve/veya satış ortaklarının tescilli ticari markasıdır.
Son güncelleme tarihi: 2025-07-26 UTC.
[null,null,["Son güncelleme tarihi: 2025-07-26 UTC."],[],[],null,["# tensorflow::ops::MaxPool3DGradGrad Class Reference\n\ntensorflow::ops::MaxPool3DGradGrad\n==================================\n\n`#include \u003cnn_ops.h\u003e`\n\nComputes second-order gradients of the maxpooling function.\n\nSummary\n-------\n\nArguments:\n\n- scope: A [Scope](/versions/r2.0/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- orig_input: The original input tensor.\n- orig_output: The original output tensor.\n- grad: [Output](/versions/r2.0/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/r2.0/api_docs/cc/struct/tensorflow/ops/max-pool3-d-grad-grad/attrs#structtensorflow_1_1ops_1_1_max_pool3_d_grad_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/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): Gradients of gradients w.r.t. the input to `max_pool`.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [MaxPool3DGradGrad](#classtensorflow_1_1ops_1_1_max_pool3_d_grad_grad_1a321b0af89e0d474f1c47e1b56a901da5)`(const ::`[tensorflow::Scope](/versions/r2.0/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` orig_input, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` orig_output, ::`[tensorflow::Input](/versions/r2.0/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| [MaxPool3DGradGrad](#classtensorflow_1_1ops_1_1_max_pool3_d_grad_grad_1a1ab771fc14377bbd003cf6a0eb96c2ad)`(const ::`[tensorflow::Scope](/versions/r2.0/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` orig_input, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` orig_output, ::`[tensorflow::Input](/versions/r2.0/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 `[MaxPool3DGradGrad::Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/max-pool3-d-grad-grad/attrs#structtensorflow_1_1ops_1_1_max_pool3_d_grad_grad_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|---------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_max_pool3_d_grad_grad_1a3df083c1b8bff3fe07b796c995dbc1f5) | [Operation](/versions/r2.0/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output](#classtensorflow_1_1ops_1_1_max_pool3_d_grad_grad_1aa69fe26b83a309417a0103b09488eafa) | `::`[tensorflow::Output](/versions/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public functions ||\n|---------------------------------------------------------------------------------------------------------------------------------|------------------------|\n| [node](#classtensorflow_1_1ops_1_1_max_pool3_d_grad_grad_1ac2acbdab5dde8105877b14badb46ccc7)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_max_pool3_d_grad_grad_1ae8e6a0a8acc839a71d2353beb944e2fa)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_max_pool3_d_grad_grad_1a574f83f847b22b01963e9649f6fe60f5)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|---------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------|\n| [DataFormat](#classtensorflow_1_1ops_1_1_max_pool3_d_grad_grad_1a6edaa5d5fd12c37d7a45ad75ea3719ea)`(StringPiece x)` | [Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/max-pool3-d-grad-grad/attrs#structtensorflow_1_1ops_1_1_max_pool3_d_grad_grad_1_1_attrs) |\n\n| ### Structs ||\n|---------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::MaxPool3DGradGrad::Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/max-pool3-d-grad-grad/attrs) | Optional attribute setters for [MaxPool3DGradGrad](/versions/r2.0/api_docs/cc/class/tensorflow/ops/max-pool3-d-grad-grad#classtensorflow_1_1ops_1_1_max_pool3_d_grad_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### MaxPool3DGradGrad\n\n```gdscript\n MaxPool3DGradGrad(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input orig_input,\n ::tensorflow::Input orig_output,\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### MaxPool3DGradGrad\n\n```gdscript\n MaxPool3DGradGrad(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input orig_input,\n ::tensorflow::Input orig_output,\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 MaxPool3DGradGrad::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```"]]
