Tetap teratur dengan koleksi
Simpan dan kategorikan konten berdasarkan preferensi Anda.
aliran tensor:: operasi:: MatMul Terkuantisasi
#include <math_ops.h>
Lakukan perkalian matriks terkuantisasi a
dengan matriks b
.
Ringkasan
Inputnya harus berupa matriks dua dimensi dan dimensi dalam a
(setelah ditransposisi jika transpose_a
bukan nol) harus sesuai dengan dimensi luar b
(setelah ditransposisi jika transposed_b
bukan nol).
Argumen:
- ruang lingkup: Objek Lingkup
- a: Harus berupa tensor dua dimensi.
- b: Harus berupa tensor dua dimensi.
- min_a: Nilai float yang diwakili oleh
a
terkuantisasi terendah. - max_a: Nilai float yang diwakili oleh
a
terkuantisasi tertinggi. - min_b: Nilai float yang diwakili oleh nilai
b
terkuantisasi terendah. - max_b: Nilai float yang diwakili oleh nilai
b
terkuantisasi tertinggi.
Atribut opsional (lihat Attrs
):
- transpose_a: Jika benar,
a
dialihkan sebelum perkalian. - transpose_b: Jika benar,
b
dialihkan sebelum perkalian. - Taktivasi: Jenis output yang dihasilkan oleh fungsi aktivasi setelah operasi ini.
Pengembalian:
-
Output
keluar -
Output
min_out: Nilai float yang diwakili oleh nilai output terkuantisasi terendah. -
Output
max_out: Nilai float yang diwakili oleh nilai output terkuantisasi tertinggi.
Konstruktor dan Destruktor |
---|
QuantizedMatMul (const :: tensorflow::Scope & scope, :: tensorflow::Input a, :: tensorflow::Input b, :: tensorflow::Input min_a, :: tensorflow::Input max_a, :: tensorflow::Input min_b, :: tensorflow::Input max_b)
|
QuantizedMatMul (const :: tensorflow::Scope & scope, :: tensorflow::Input a, :: tensorflow::Input b, :: tensorflow::Input min_a, :: tensorflow::Input max_a, :: tensorflow::Input min_b, :: tensorflow::Input max_b, const QuantizedMatMul::Attrs & attrs) |
Atribut publik
Fungsi publik
Fungsi statis publik
Taktivasi
Attrs Tactivation(
DataType x
)
keluaran
Attrs Toutput(
DataType x
)
Mengubah urutanA
Attrs TransposeA(
bool x
)
TransposB
Attrs TransposeB(
bool x
)
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 2025-07-25 UTC.
[null,null,["Terakhir diperbarui pada 2025-07-25 UTC."],[],[],null,["# tensorflow::ops::QuantizedMatMul Class Reference\n\ntensorflow::ops::QuantizedMatMul\n================================\n\n`#include \u003cmath_ops.h\u003e`\n\nPerform a quantized matrix multiplication of `a` by the matrix `b`.\n\nSummary\n-------\n\nThe inputs must be two-dimensional matrices and the inner dimension of `a` (after being transposed if `transpose_a` is non-zero) must match the outer dimension of `b` (after being transposed if `transposed_b` is non-zero).\n\nArguments:\n\n- scope: A [Scope](/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- a: Must be a two-dimensional tensor.\n- b: Must be a two-dimensional tensor.\n- min_a: The float value that the lowest quantized `a` value represents.\n- max_a: The float value that the highest quantized `a` value represents.\n- min_b: The float value that the lowest quantized `b` value represents.\n- max_b: The float value that the highest quantized `b` value represents.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/quantized-mat-mul/attrs#structtensorflow_1_1ops_1_1_quantized_mat_mul_1_1_attrs)):\n\n- transpose_a: If true, `a` is transposed before multiplication.\n- transpose_b: If true, `b` is transposed before multiplication.\n- Tactivation: The type of output produced by activation function following this operation.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) out\n- [Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) min_out: The float value that the lowest quantized output value represents.\n- [Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) max_out: The float value that the highest quantized output value represents.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [QuantizedMatMul](#classtensorflow_1_1ops_1_1_quantized_mat_mul_1a0f09b0e35ddc6a6324c65db6ec69a731)`(const ::`[tensorflow::Scope](/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` a, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` b, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` min_a, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` max_a, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` min_b, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` max_b)` ||\n| [QuantizedMatMul](#classtensorflow_1_1ops_1_1_quantized_mat_mul_1a882f02d4d46fa0c4ddb44a2e201929dc)`(const ::`[tensorflow::Scope](/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` a, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` b, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` min_a, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` max_a, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` min_b, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` max_b, const `[QuantizedMatMul::Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/quantized-mat-mul/attrs#structtensorflow_1_1ops_1_1_quantized_mat_mul_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|-----------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|\n| [max_out](#classtensorflow_1_1ops_1_1_quantized_mat_mul_1ad70908bf74ce2c40aa1f778693c60d8f) | `::`[tensorflow::Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n| [min_out](#classtensorflow_1_1ops_1_1_quantized_mat_mul_1a8dfe353eb1695a006f27c2cd8210b728) | `::`[tensorflow::Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n| [operation](#classtensorflow_1_1ops_1_1_quantized_mat_mul_1ad9abd5818d18e9d7f03c3db5ef1464ff) | [Operation](/versions/r1.15/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [out](#classtensorflow_1_1ops_1_1_quantized_mat_mul_1a891101c5425593a778947c2a3019d4a3) | `::`[tensorflow::Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public static functions ||\n|---------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------|\n| [Tactivation](#classtensorflow_1_1ops_1_1_quantized_mat_mul_1adf046668cb84feff06bb62ac8dfe9cb9)`(DataType x)` | [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/quantized-mat-mul/attrs#structtensorflow_1_1ops_1_1_quantized_mat_mul_1_1_attrs) |\n| [Toutput](#classtensorflow_1_1ops_1_1_quantized_mat_mul_1ab91328f7f63e496fbf14e3f2a7ca46fe)`(DataType x)` | [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/quantized-mat-mul/attrs#structtensorflow_1_1ops_1_1_quantized_mat_mul_1_1_attrs) |\n| [TransposeA](#classtensorflow_1_1ops_1_1_quantized_mat_mul_1afbe2add319dc39e1db4dc583f556def9)`(bool x)` | [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/quantized-mat-mul/attrs#structtensorflow_1_1ops_1_1_quantized_mat_mul_1_1_attrs) |\n| [TransposeB](#classtensorflow_1_1ops_1_1_quantized_mat_mul_1a6525a94155917583356eb70dd02f1f72)`(bool x)` | [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/quantized-mat-mul/attrs#structtensorflow_1_1ops_1_1_quantized_mat_mul_1_1_attrs) |\n\n| ### Structs ||\n|----------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::QuantizedMatMul::Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/quantized-mat-mul/attrs) | Optional attribute setters for [QuantizedMatMul](/versions/r1.15/api_docs/cc/class/tensorflow/ops/quantized-mat-mul#classtensorflow_1_1ops_1_1_quantized_mat_mul). |\n\nPublic attributes\n-----------------\n\n### max_out\n\n```scdoc\n::tensorflow::Output max_out\n``` \n\n### min_out\n\n```scdoc\n::tensorflow::Output min_out\n``` \n\n### operation\n\n```text\nOperation operation\n``` \n\n### out\n\n```text\n::tensorflow::Output out\n``` \n\nPublic functions\n----------------\n\n### QuantizedMatMul\n\n```gdscript\n QuantizedMatMul(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input a,\n ::tensorflow::Input b,\n ::tensorflow::Input min_a,\n ::tensorflow::Input max_a,\n ::tensorflow::Input min_b,\n ::tensorflow::Input max_b\n)\n``` \n\n### QuantizedMatMul\n\n```gdscript\n QuantizedMatMul(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input a,\n ::tensorflow::Input b,\n ::tensorflow::Input min_a,\n ::tensorflow::Input max_a,\n ::tensorflow::Input min_b,\n ::tensorflow::Input max_b,\n const QuantizedMatMul::Attrs & attrs\n)\n``` \n\nPublic static functions\n-----------------------\n\n### Tactivation\n\n```text\nAttrs Tactivation(\n DataType x\n)\n``` \n\n### Toutput\n\n```text\nAttrs Toutput(\n DataType x\n)\n``` \n\n### TransposeA\n\n```text\nAttrs TransposeA(\n bool x\n)\n``` \n\n### TransposeB\n\n```text\nAttrs TransposeB(\n bool x\n)\n```"]]