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aliran tensor:: operasi:: QuantizeAndDequantizeV2:: Attr
#include <array_ops.h>
Penyetel atribut opsional untuk QuantizeAndDequantizeV2 .
Ringkasan
Fungsi publik |
---|
Axis (int64 x) | Jika ditentukan, sumbu ini diperlakukan sebagai sumbu saluran atau irisan, dan rentang kuantisasi terpisah digunakan untuk setiap saluran atau irisan di sepanjang sumbu ini. |
NarrowRange (bool x) | Jika Benar, maka nilai absolut dari nilai minimum yang terkuantisasi sama dengan nilai maksimum yang terkuantisasi, bukannya lebih besar 1. |
NumBits (int64 x) | Bitwidth kuantisasi. |
RangeGiven (bool x) | Apakah rentang tersebut diberikan atau harus ditentukan dari tensor input . |
RoundMode (StringPiece x) | Atribut 'round_mode' mengontrol algoritme pemutusan ikatan pembulatan mana yang digunakan saat membulatkan nilai float ke nilai terkuantisasinya. |
SignedInput (bool x) | Apakah kuantisasi ditandatangani atau tidak. |
Atribut publik
sumbu_
int64 tensorflow::ops::QuantizeAndDequantizeV2::Attrs::axis_ = -1
rentang_sempit_
bool tensorflow::ops::QuantizeAndDequantizeV2::Attrs::narrow_range_ = false
jumlah_bit_
int64 tensorflow::ops::QuantizeAndDequantizeV2::Attrs::num_bits_ = 8
rentang_diberikan_
bool tensorflow::ops::QuantizeAndDequantizeV2::Attrs::range_given_ = false
putaran_mode_
StringPiece tensorflow::ops::QuantizeAndDequantizeV2::Attrs::round_mode_ = "HALF_TO_EVEN"
bool tensorflow::ops::QuantizeAndDequantizeV2::Attrs::signed_input_ = true
Fungsi publik
Sumbu
TF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizeAndDequantizeV2::Attrs::Axis(
int64 x
)
Jika ditentukan, sumbu ini diperlakukan sebagai sumbu saluran atau irisan, dan rentang kuantisasi terpisah digunakan untuk setiap saluran atau irisan di sepanjang sumbu ini.
Defaultnya adalah -1
Rentang Sempit
TF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizeAndDequantizeV2::Attrs::NarrowRange(
bool x
)
Jika Benar, maka nilai absolut dari nilai minimum yang terkuantisasi sama dengan nilai maksimum yang terkuantisasi, bukannya lebih besar 1.
yaitu untuk kuantisasi 8 bit, nilai minimumnya adalah -127, bukan -128.
Defaultnya salah
NomorBits
TF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizeAndDequantizeV2::Attrs::NumBits(
int64 x
)
Bitwidth kuantisasi.
Defaultnya adalah 8
Rentang Diberikan
TF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizeAndDequantizeV2::Attrs::RangeGiven(
bool x
)
Apakah rentang tersebut diberikan atau harus ditentukan dari tensor input
.
Defaultnya salah
Mode Bulat
TF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizeAndDequantizeV2::Attrs::RoundMode(
StringPiece x
)
Atribut 'round_mode' mengontrol algoritme pemutusan ikatan pembulatan mana yang digunakan saat membulatkan nilai float ke nilai terkuantisasinya.
Mode pembulatan berikut saat ini didukung:
- HALF_TO_EVEN: ini adalah mode_bulat default.
- HALF_UP: bulat menuju positif. Dalam mode ini 7,5 putaran hingga 8 dan -7,5 putaran hingga -7.
Defaultnya adalah "HALF_TO_EVEN"
TF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizeAndDequantizeV2::Attrs::SignedInput(
bool x
)
Apakah kuantisasi ditandatangani atau tidak.
(sebenarnya parameter ini seharusnya disebut signed_output
)
Defaultnya adalah benar
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Terakhir diperbarui pada 2025-07-26 UTC.
[null,null,["Terakhir diperbarui pada 2025-07-26 UTC."],[],[],null,["# tensorflow::ops::QuantizeAndDequantizeV2::Attrs Struct Reference\n\ntensorflow::ops::QuantizeAndDequantizeV2::Attrs\n===============================================\n\n`#include \u003carray_ops.h\u003e`\n\nOptional attribute setters for [QuantizeAndDequantizeV2](/versions/r2.2/api_docs/cc/class/tensorflow/ops/quantize-and-dequantize-v2#classtensorflow_1_1ops_1_1_quantize_and_dequantize_v2).\n\nSummary\n-------\n\n| ### Public attributes ||\n|----------------------------------------------------------------------------------------------------------------------------------------|---------------|\n| [axis_](#structtensorflow_1_1ops_1_1_quantize_and_dequantize_v2_1_1_attrs_1a315bdca31eedd36ca93926e243fa1936)` = -1` | `int64` |\n| [narrow_range_](#structtensorflow_1_1ops_1_1_quantize_and_dequantize_v2_1_1_attrs_1adf347e0c1f8214c14d7694ae285cc9d0)` = false` | `bool` |\n| [num_bits_](#structtensorflow_1_1ops_1_1_quantize_and_dequantize_v2_1_1_attrs_1a11159f89f2414130b6a3ad313b27716c)` = 8` | `int64` |\n| [range_given_](#structtensorflow_1_1ops_1_1_quantize_and_dequantize_v2_1_1_attrs_1a865cf4c82b9089b872eb9b918531f2db)` = false` | `bool` |\n| [round_mode_](#structtensorflow_1_1ops_1_1_quantize_and_dequantize_v2_1_1_attrs_1a6dfc7a75f4a69171c6497bb1edfa0d05)` = \"HALF_TO_EVEN\"` | `StringPiece` |\n| [signed_input_](#structtensorflow_1_1ops_1_1_quantize_and_dequantize_v2_1_1_attrs_1a790cd895eec69aba604ac8e9cb7f8a9f)` = true` | `bool` |\n\n| ### Public functions ||\n|------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [Axis](#structtensorflow_1_1ops_1_1_quantize_and_dequantize_v2_1_1_attrs_1a763f00e13bdab9fb43c917bbc70cf634)`(int64 x)` | `TF_MUST_USE_RESULT `[Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/quantize-and-dequantize-v2/attrs#structtensorflow_1_1ops_1_1_quantize_and_dequantize_v2_1_1_attrs) If specified, this axis is treated as a channel or slice axis, and a separate quantization range is used for each channel or slice along this axis. |\n| [NarrowRange](#structtensorflow_1_1ops_1_1_quantize_and_dequantize_v2_1_1_attrs_1afaceca0792d45c8137aeb043c8cfda94)`(bool x)` | `TF_MUST_USE_RESULT `[Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/quantize-and-dequantize-v2/attrs#structtensorflow_1_1ops_1_1_quantize_and_dequantize_v2_1_1_attrs) If True, then the absolute value of the quantized minimum value is the same as the quantized maximum value, instead of 1 greater. |\n| [NumBits](#structtensorflow_1_1ops_1_1_quantize_and_dequantize_v2_1_1_attrs_1a76057cdbc84759b92af376d7af6e5542)`(int64 x)` | `TF_MUST_USE_RESULT `[Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/quantize-and-dequantize-v2/attrs#structtensorflow_1_1ops_1_1_quantize_and_dequantize_v2_1_1_attrs) The bitwidth of the quantization. |\n| [RangeGiven](#structtensorflow_1_1ops_1_1_quantize_and_dequantize_v2_1_1_attrs_1a6fa06a82baf6f5d343626b0ff362f28b)`(bool x)` | `TF_MUST_USE_RESULT `[Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/quantize-and-dequantize-v2/attrs#structtensorflow_1_1ops_1_1_quantize_and_dequantize_v2_1_1_attrs) Whether the range is given or should be determined from the `input` tensor. |\n| [RoundMode](#structtensorflow_1_1ops_1_1_quantize_and_dequantize_v2_1_1_attrs_1abbc6241855f1eb74e6c30f9bb38a9bea)`(StringPiece x)` | `TF_MUST_USE_RESULT `[Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/quantize-and-dequantize-v2/attrs#structtensorflow_1_1ops_1_1_quantize_and_dequantize_v2_1_1_attrs) The 'round_mode' attribute controls which rounding tie-breaking algorithm is used when rounding float values to their quantized equivalents. |\n| [SignedInput](#structtensorflow_1_1ops_1_1_quantize_and_dequantize_v2_1_1_attrs_1acc49af3428f348e5f27485c3d72e5598)`(bool x)` | `TF_MUST_USE_RESULT `[Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/quantize-and-dequantize-v2/attrs#structtensorflow_1_1ops_1_1_quantize_and_dequantize_v2_1_1_attrs) Whether the quantization is signed or unsigned. |\n\nPublic attributes\n-----------------\n\n### axis_\n\n```scdoc\nint64 tensorflow::ops::QuantizeAndDequantizeV2::Attrs::axis_ = -1\n``` \n\n### narrow_range_\n\n```scdoc\nbool tensorflow::ops::QuantizeAndDequantizeV2::Attrs::narrow_range_ = false\n``` \n\n### num_bits_\n\n```scdoc\nint64 tensorflow::ops::QuantizeAndDequantizeV2::Attrs::num_bits_ = 8\n``` \n\n### range_given_\n\n```scdoc\nbool tensorflow::ops::QuantizeAndDequantizeV2::Attrs::range_given_ = false\n``` \n\n### round_mode_\n\n```scdoc\nStringPiece tensorflow::ops::QuantizeAndDequantizeV2::Attrs::round_mode_ = \"HALF_TO_EVEN\"\n``` \n\n### signed_input_\n\n```scdoc\nbool tensorflow::ops::QuantizeAndDequantizeV2::Attrs::signed_input_ = true\n``` \n\nPublic functions\n----------------\n\n### Axis\n\n```scdoc\nTF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizeAndDequantizeV2::Attrs::Axis(\n int64 x\n)\n``` \nIf specified, this axis is treated as a channel or slice axis, and a separate quantization range is used for each channel or slice along this axis.\n\nDefaults to -1 \n\n### NarrowRange\n\n```scdoc\nTF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizeAndDequantizeV2::Attrs::NarrowRange(\n bool x\n)\n``` \nIf True, then the absolute value of the quantized minimum value is the same as the quantized maximum value, instead of 1 greater.\n\ni.e. for 8 bit quantization, the minimum value is -127 instead of -128.\n\nDefaults to false \n\n### NumBits\n\n```scdoc\nTF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizeAndDequantizeV2::Attrs::NumBits(\n int64 x\n)\n``` \nThe bitwidth of the quantization.\n\nDefaults to 8 \n\n### RangeGiven\n\n```scdoc\nTF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizeAndDequantizeV2::Attrs::RangeGiven(\n bool x\n)\n``` \nWhether the range is given or should be determined from the `input` tensor.\n\nDefaults to false \n\n### RoundMode\n\n```scdoc\nTF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizeAndDequantizeV2::Attrs::RoundMode(\n StringPiece x\n)\n``` \nThe 'round_mode' attribute controls which rounding tie-breaking algorithm is used when rounding float values to their quantized equivalents.\n\nThe following rounding modes are currently supported:\n\n\n- HALF_TO_EVEN: this is the default round_mode.\n- HALF_UP: round towards positive. In this mode 7.5 rounds up to 8 and -7.5 rounds up to -7.\n\n\u003cbr /\u003e\n\nDefaults to \"HALF_TO_EVEN\" \n\n### SignedInput\n\n```scdoc\nTF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizeAndDequantizeV2::Attrs::SignedInput(\n bool x\n)\n``` \nWhether the quantization is signed or unsigned.\n\n(actually this parameter should have been called **`signed_output`**)\n\nDefaults to true"]]