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aliran tensor:: operasi:: Konv3D
#include <nn_ops.h> Menghitung konvolusi 3-D dengan input 5-D dan tensor filter .
Ringkasan
Dalam pemrosesan sinyal, korelasi silang adalah ukuran kemiripan dua bentuk gelombang sebagai fungsi jeda waktu yang diterapkan pada salah satunya. Ini juga dikenal sebagai perkalian titik geser atau perkalian dalam geser.
Conv3D kami menerapkan bentuk korelasi silang.
Argumen:
- ruang lingkup: Objek Lingkup
- masukan: Bentuk
[batch, in_depth, in_height, in_width, in_channels] . - filter: Bentuk
[filter_depth, filter_height, filter_width, in_channels, out_channels] . in_channels harus cocok antara input dan filter . - langkah: tensor 1-D dengan panjang 5. Langkah jendela geser untuk setiap dimensi
input . Harus memiliki strides[0] = strides[4] = 1 . - padding: Jenis algoritma padding yang akan digunakan.
Atribut opsional (lihat Attrs ):
- data_format: Format data dari data masukan dan keluaran. Dengan format default "NDHWC", data disimpan dalam urutan: [batch, in_ depth, in_height, in_width, in_channels]. Alternatifnya, formatnya bisa "NCDHW", urutan penyimpanan datanya adalah: [batch, in_channels, in_ depth, in_height, in_width].
- dilatasi: tensor 1-D dengan panjang 5. Faktor dilatasi untuk setiap dimensi
input . Jika diatur ke k > 1, akan ada k-1 sel yang dilewati di antara setiap elemen filter pada dimensi tersebut. Urutan dimensi ditentukan oleh nilai data_format , lihat di atas untuk detailnya. Pelebaran dalam dimensi batch dan kedalaman harus 1.
Pengembalian:
Atribut publik
Fungsi publik
simpul
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operator::tensorflow::Keluaran
operator::tensorflow::Output() const
Fungsi statis publik
Attrs DataFormat(
StringPiece x
)
Pelebaran
Attrs Dilations(
const gtl::ArraySlice< int > & x
)
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Terakhir diperbarui pada 2025-07-26 UTC.
[null,null,["Terakhir diperbarui pada 2025-07-26 UTC."],[],[],null,["# tensorflow::ops::Conv3D Class Reference\n\ntensorflow::ops::Conv3D\n=======================\n\n`#include \u003cnn_ops.h\u003e`\n\nComputes a 3-D convolution given 5-D `input` and `filter` tensors.\n\nSummary\n-------\n\nIn signal processing, cross-correlation is a measure of similarity of two waveforms as a function of a time-lag applied to one of them. This is also known as a sliding dot product or sliding inner-product.\n\nOur [Conv3D](/versions/r2.1/api_docs/cc/class/tensorflow/ops/conv3-d#classtensorflow_1_1ops_1_1_conv3_d) implements a form of cross-correlation.\n\nArguments:\n\n- scope: A [Scope](/versions/r2.1/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- input: Shape `[batch, in_depth, in_height, in_width, in_channels]`.\n- filter: Shape `[filter_depth, filter_height, filter_width, in_channels, out_channels]`. `in_channels` must match between `input` and `filter`.\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/conv3-d/attrs#structtensorflow_1_1ops_1_1_conv3_d_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- dilations: 1-D tensor of length 5. 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/r2.1/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): The output tensor.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [Conv3D](#classtensorflow_1_1ops_1_1_conv3_d_1aef63039997c4f9586d2b8627e3cf5c5a)`(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)` input, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` filter, const gtl::ArraySlice\u003c int \u003e & strides, StringPiece padding)` ||\n| [Conv3D](#classtensorflow_1_1ops_1_1_conv3_d_1abb396c1cb8bf48f57ad11862ac7406ad)`(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)` input, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` filter, const gtl::ArraySlice\u003c int \u003e & strides, StringPiece padding, const `[Conv3D::Attrs](/versions/r2.1/api_docs/cc/struct/tensorflow/ops/conv3-d/attrs#structtensorflow_1_1ops_1_1_conv3_d_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|-------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_conv3_d_1a34a87b1c84b82ab0a1dec637ee277ced) | [Operation](/versions/r2.1/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output](#classtensorflow_1_1ops_1_1_conv3_d_1a426b9a63272f1905184fdfd1b78ba33a) | `::`[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_conv3_d_1a33ab1a0f2fa69089a8f835175d1dc732)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_conv3_d_1a418b91ef5b6437901248965d572533e5)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_conv3_d_1abebfb46d5b9c472aebb4f25ad6d2eeb6)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|-------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------|\n| [DataFormat](#classtensorflow_1_1ops_1_1_conv3_d_1a148ca9c798353ee9073c60f57e45a41f)`(StringPiece x)` | [Attrs](/versions/r2.1/api_docs/cc/struct/tensorflow/ops/conv3-d/attrs#structtensorflow_1_1ops_1_1_conv3_d_1_1_attrs) |\n| [Dilations](#classtensorflow_1_1ops_1_1_conv3_d_1a90d138624ebc69f365e225d25ece6e2a)`(const gtl::ArraySlice\u003c int \u003e & x)` | [Attrs](/versions/r2.1/api_docs/cc/struct/tensorflow/ops/conv3-d/attrs#structtensorflow_1_1ops_1_1_conv3_d_1_1_attrs) |\n\n| ### Structs ||\n|--------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::Conv3D::Attrs](/versions/r2.1/api_docs/cc/struct/tensorflow/ops/conv3-d/attrs) | Optional attribute setters for [Conv3D](/versions/r2.1/api_docs/cc/class/tensorflow/ops/conv3-d#classtensorflow_1_1ops_1_1_conv3_d). |\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### Conv3D\n\n```gdscript\n Conv3D(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input input,\n ::tensorflow::Input filter,\n const gtl::ArraySlice\u003c int \u003e & strides,\n StringPiece padding\n)\n``` \n\n### Conv3D\n\n```gdscript\n Conv3D(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input input,\n ::tensorflow::Input filter,\n const gtl::ArraySlice\u003c int \u003e & strides,\n StringPiece padding,\n const Conv3D::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```"]]
