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#include <array_ops.h> patches input çıkarın ve bunları "derinlik" çıktı boyutuna yerleştirin.
Özet
extract_image_patches 3 boyutlu uzantısı.
Argümanlar:
- kapsam: Bir Kapsam nesnesi
- giriş: şekilli 5-D Tensör
[batch, in_planes, in_rows, in_cols, depth] . - ksizes:
input her boyutu için kayan pencerenin boyutu. - adımlar: 1 boyutlu uzunluk 5. Ardışık iki parçanın merkezlerinin
input ne kadar uzakta olduğu. Şunlar olmalıdır: [1, stride_planes, stride_rows, stride_cols, 1] . - padding: Kullanılacak dolgu algoritmasının türü.
Boyutla ilgili nitelikleri şu şekilde belirtiyoruz:
ksizes = [1, ksize_planes, ksize_rows, ksize_cols, 1]
strides = [1, stride_planes, strides_rows, strides_cols, 1] İade:
-
Output : "Derinlik" boyutunda vektörleştirilmiş ksize_planes x ksize_rows x ksize_cols x depth yamalar içeren [batch, out_planes, out_rows, out_cols, ksize_planes * ksize_rows * ksize_cols * depth] şeklindeki 5-D Tensör . out_planes , out_rows ve out_cols çıktı yamalarının boyutlarıdır.
Genel özellikler
Kamu işlevleri
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Son güncelleme tarihi: 2025-07-26 UTC.
[null,null,["Son güncelleme tarihi: 2025-07-26 UTC."],[],[],null,["# tensorflow::ops::ExtractVolumePatches Class Reference\n\ntensorflow::ops::ExtractVolumePatches\n=====================================\n\n`#include \u003carray_ops.h\u003e`\n\nExtract `patches` from `input` and put them in the \"depth\" output dimension.\n\nSummary\n-------\n\n3D extension of `extract_image_patches`.\n\nArguments:\n\n- scope: A [Scope](/versions/r2.0/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- input: 5-D [Tensor](/versions/r2.0/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor) with shape `[batch, in_planes, in_rows, in_cols, depth]`.\n- ksizes: The size of the sliding window for each dimension of `input`.\n- strides: 1-D of length 5. How far the centers of two consecutive patches are in `input`. Must be: `[1, stride_planes, stride_rows, stride_cols, 1]`.\n- padding: The type of padding algorithm to use.\n\n\u003cbr /\u003e\n\nWe specify the size-related attributes as:\n\n\n```scdoc\n ksizes = [1, ksize_planes, ksize_rows, ksize_cols, 1]\n strides = [1, stride_planes, strides_rows, strides_cols, 1]\n```\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): 5-D [Tensor](/versions/r2.0/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor) with shape `[batch, out_planes, out_rows, out_cols, ksize_planes * ksize_rows * ksize_cols * depth]` containing patches with size `ksize_planes x ksize_rows x ksize_cols x depth` vectorized in the \"depth\" dimension. Note `out_planes`, `out_rows` and `out_cols` are the dimensions of the output patches.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [ExtractVolumePatches](#classtensorflow_1_1ops_1_1_extract_volume_patches_1a752dba9a13577efb227d68e11e73e4e7)`(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)` input, const gtl::ArraySlice\u003c int \u003e & ksizes, const gtl::ArraySlice\u003c int \u003e & strides, StringPiece padding)` ||\n\n| ### Public attributes ||\n|----------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_extract_volume_patches_1ab7a74fc2dc2e90c7c44399f5673a6664) | [Operation](/versions/r2.0/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [patches](#classtensorflow_1_1ops_1_1_extract_volume_patches_1a88a4e306f94549ed420d3e6770bf7bbc) | `::`[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_extract_volume_patches_1ad156203fcbe558f0a53b6c0b7f34c016)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_extract_volume_patches_1ad316cf0f924cac92315f835a66c577f8)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_extract_volume_patches_1a6ff00c0c8df929a77bf90a0258d87a88)`() const ` | ` ` ` ` |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### patches\n\n```text\n::tensorflow::Output patches\n``` \n\nPublic functions\n----------------\n\n### ExtractVolumePatches\n\n```gdscript\n ExtractVolumePatches(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input input,\n const gtl::ArraySlice\u003c int \u003e & ksizes,\n const gtl::ArraySlice\u003c int \u003e & strides,\n StringPiece padding\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```"]]
