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#include <array_ops.h>
Extract
patches
from
input
and put them in the
"depth"
output dimension.
Summary
3D extension of
extract_image_patches
.
Args:
-
scope: A
Scope
object
-
input: 5-D
Tensor
with shape
[batch, in_planes, in_rows, in_cols, depth]
.
-
ksizes: The size of the sliding window for each dimension of
input
.
-
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]
.
-
padding: The type of padding algorithm to use.
The size-related attributes are specified as follows:
ksizes = [1, ksize_planes, ksize_rows, ksize_cols, 1]
strides = [1, stride_planes, strides_rows, strides_cols, 1]
Returns:
-
Output
: 5-D
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.
Public attributes
Public 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 2021-08-16 UTC.
[null,null,["Last updated 2021-08-16 UTC."],[],[],null,["# tensorflow::ops::ExtractVolumePatches Class Reference\n\ntensorflow::\nops::\nExtractVolumePatches\n=======================================\n\n`\n#include \u003carray_ops.h\u003e\n`\n\n\nExtract\n`\npatches\n`\nfrom\n`\ninput\n`\nand put them in the\n`\n\"depth\"\n`\noutput dimension.\n\nSummary\n-------\n\n\n3D extension of\n`\nextract_image_patches\n`\n.\n\n\nArgs:\n\n- scope: A [Scope](/versions/r2.6/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- input: 5-D [Tensor](/versions/r2.6/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor) with shape `\n [batch, in_planes, in_rows, in_cols, depth]\n ` .\n- ksizes: The size of the sliding window for each dimension of `\n input\n ` .\n- strides: 1-D of length 5. How far the centers of two consecutive patches are in `\n input\n ` . Must be: `\n [1, stride_planes, stride_rows, stride_cols, 1]\n ` .\n- padding: The type of padding algorithm to use.\n\n\u003cbr /\u003e\n\n\nThe size-related attributes are specified as follows:\n\n\n```scdoc\nksizes = [1, ksize_planes, ksize_rows, ksize_cols, 1]\nstrides = [1, stride_planes, strides_rows, strides_cols, 1]\n```\n\n\u003cbr /\u003e\n\n\nReturns:\n\n- `\n `[Output](/versions/r2.6/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output)`\n ` : 5-D [Tensor](/versions/r2.6/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor) with shape `\n [batch, out_planes, out_rows, out_cols, ksize_planes * ksize_rows * ksize_cols * depth]\n ` containing patches with size `\n ksize_planes x ksize_rows x ksize_cols x depth\n ` vectorized in the \"depth\" dimension. Note `\n out_planes\n ` , `\n out_rows\n ` and `\n out_cols\n ` 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/r2.6/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, :: `[tensorflow::Input](/versions/r2.6/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/r2.6/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation)` ` |\n| ` `[patches](#classtensorflow_1_1ops_1_1_extract_volume_patches_1a88a4e306f94549ed420d3e6770bf7bbc)` ` | ` :: `[tensorflow::Output](/versions/r2.6/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```"]]
