Tetap teratur dengan koleksi
Simpan dan kategorikan konten berdasarkan preferensi Anda.
aliran tensor:: operasi:: Konjugasi Transpose
#include <array_ops.h> Kocok dimensi x menurut permutasi dan konjugasikan hasilnya.
Ringkasan
Outputnya y memiliki peringkat yang sama dengan x . Bentuk x dan y memenuhi: y.shape[i] == x.shape[perm[i]] for i in [0, 1, ..., rank(x) - 1] y[i,j,k,...,s,t,u] == conj(x[perm[i], perm[j], perm[k],...,perm[s], perm[t], perm[u]])
Argumen:
Pengembalian:
Atribut publik
Fungsi publik
simpul
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operator::tensorflow::Keluaran
operator::tensorflow::Output() const
Kecuali dinyatakan lain, konten di halaman ini dilisensikan berdasarkan Lisensi Creative Commons Attribution 4.0, sedangkan contoh kode dilisensikan berdasarkan Lisensi Apache 2.0. Untuk mengetahui informasi selengkapnya, lihat Kebijakan Situs Google Developers. Java adalah merek dagang terdaftar dari Oracle dan/atau afiliasinya.
Terakhir diperbarui pada 2025-07-26 UTC.
[null,null,["Terakhir diperbarui pada 2025-07-26 UTC."],[],[],null,["# tensorflow::ops::ConjugateTranspose Class Reference\n\ntensorflow::ops::ConjugateTranspose\n===================================\n\n`#include \u003carray_ops.h\u003e`\n\nShuffle dimensions of x according to a permutation and conjugate the result.\n\nSummary\n-------\n\nThe output `y` has the same rank as `x`. The shapes of `x` and `y` satisfy: `y.shape[i] == x.shape[perm[i]] for i in [0, 1, ..., rank(x) - 1]``y[i,j,k,...,s,t,u] == conj(x[perm[i], perm[j], perm[k],...,perm[s], perm[t], perm[u]])`\n\nArguments:\n\n- scope: A [Scope](/versions/r2.3/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): The y tensor.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [ConjugateTranspose](#classtensorflow_1_1ops_1_1_conjugate_transpose_1a4a5368d3cec175ad261612c95e8da6d3)`(const ::`[tensorflow::Scope](/versions/r2.3/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` x, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` perm)` ||\n\n| ### Public attributes ||\n|-------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_conjugate_transpose_1aa4e3004e201a961572c3999a46990f0b) | [Operation](/versions/r2.3/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [y](#classtensorflow_1_1ops_1_1_conjugate_transpose_1a804efbc2f1fec9fee64ccac9402bbbdd) | `::`[tensorflow::Output](/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public functions ||\n|-------------------------------------------------------------------------------------------------------------------------------|------------------------|\n| [node](#classtensorflow_1_1ops_1_1_conjugate_transpose_1a3829d54bcdcdc65f244e364383c52a12)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_conjugate_transpose_1af0205b3679ff8def147607935343b1c1)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_conjugate_transpose_1aec6563c894874b88ae5b51e91f251ef5)`() const ` | ` ` ` ` |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### y\n\n```text\n::tensorflow::Output y\n``` \n\nPublic functions\n----------------\n\n### ConjugateTranspose\n\n```gdscript\n ConjugateTranspose(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input x,\n ::tensorflow::Input perm\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```"]]
