Zadbaj o dobrą organizację dzięki kolekcji
Zapisuj i kategoryzuj treści zgodnie ze swoimi preferencjami.
przepływ tensorowy:: ops:: Kwantowana instancjaNorm:: Atrybuty
#include <array_ops.h>
Opcjonalne moduły ustawiające atrybuty dla QuantizedInstanceNorm .
Streszczenie
Atrybuty publiczne
podane_y_max_
float tensorflow::ops::QuantizedInstanceNorm::Attrs::given_y_max_ = 0.0f
podane_y_min_
float tensorflow::ops::QuantizedInstanceNorm::Attrs::given_y_min_ = 0.0f
min_separacja_
float tensorflow::ops::QuantizedInstanceNorm::Attrs::min_separation_ = 0.001f
dany_zakres_wyjściowy_
bool tensorflow::ops::QuantizedInstanceNorm::Attrs::output_range_given_ = false
wariancja_epsilon_
float tensorflow::ops::QuantizedInstanceNorm::Attrs::variance_epsilon_ = 1e-05f
Funkcje publiczne
Biorąc pod uwagę YMaks
TF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizedInstanceNorm::Attrs::GivenYMax(
float x
)
Dane wyjściowe w y_max
, jeśli output_range_given
ma wartość True.
Wartość domyślna to 0
BiorącYMin
TF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizedInstanceNorm::Attrs::GivenYMin(
float x
)
Dane wyjściowe w y_min
, jeśli output_range_given
ma wartość True.
Wartość domyślna to 0
Min. separacja
TF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizedInstanceNorm::Attrs::MinSeparation(
float x
)
Minimalna wartość y_max - y_min
Wartość domyślna to 0,001
Podany zakres wyjściowy
TF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizedInstanceNorm::Attrs::OutputRangeGiven(
bool x
)
Jeśli True, given_y_min
i given_y_min
i given_y_max
są używane jako zakres wyjściowy.
W przeciwnym razie implementacja oblicza zakres wyjściowy.
Domyślnie jest to fałsz
WariancjaEpsilon
TF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizedInstanceNorm::Attrs::VarianceEpsilon(
float x
)
Mała liczba zmiennoprzecinkowa, aby uniknąć dzielenia przez 0.
Domyślnie jest to 1e-05
O ile nie stwierdzono inaczej, treść tej strony jest objęta licencją Creative Commons – uznanie autorstwa 4.0, a fragmenty kodu są dostępne na licencji Apache 2.0. Szczegółowe informacje na ten temat zawierają zasady dotyczące witryny Google Developers. Java jest zastrzeżonym znakiem towarowym firmy Oracle i jej podmiotów stowarzyszonych.
Ostatnia aktualizacja: 2025-07-25 UTC.
[null,null,["Ostatnia aktualizacja: 2025-07-25 UTC."],[],[],null,["# tensorflow::ops::QuantizedInstanceNorm::Attrs Struct Reference\n\ntensorflow::ops::QuantizedInstanceNorm::Attrs\n=============================================\n\n`#include \u003carray_ops.h\u003e`\n\nOptional attribute setters for [QuantizedInstanceNorm](/versions/r1.15/api_docs/cc/class/tensorflow/ops/quantized-instance-norm#classtensorflow_1_1ops_1_1_quantized_instance_norm).\n\nSummary\n-------\n\n| ### Public attributes ||\n|------------------------------------------------------------------------------------------------------------------------------------|---------|\n| [given_y_max_](#structtensorflow_1_1ops_1_1_quantized_instance_norm_1_1_attrs_1a143f0f1661df75a9345104b53d2a23a1)` = 0.0f` | `float` |\n| [given_y_min_](#structtensorflow_1_1ops_1_1_quantized_instance_norm_1_1_attrs_1a66a475c41d1d5351475d1b41f4c722b9)` = 0.0f` | `float` |\n| [min_separation_](#structtensorflow_1_1ops_1_1_quantized_instance_norm_1_1_attrs_1a02e61831bb492f7e82ab72cfdd164bcd)` = 0.001f` | `float` |\n| [output_range_given_](#structtensorflow_1_1ops_1_1_quantized_instance_norm_1_1_attrs_1a90012c405dc0d5545b200b2a7ca74651)` = false` | `bool` |\n| [variance_epsilon_](#structtensorflow_1_1ops_1_1_quantized_instance_norm_1_1_attrs_1a3eb30df9c538c1316ba64edd59220592)` = 1e-05f` | `float` |\n\n| ### Public functions ||\n|---------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [GivenYMax](#structtensorflow_1_1ops_1_1_quantized_instance_norm_1_1_attrs_1a553ab19eaa986e91efec9bcac303ae9b)`(float x)` | `TF_MUST_USE_RESULT `[Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/quantized-instance-norm/attrs#structtensorflow_1_1ops_1_1_quantized_instance_norm_1_1_attrs) [Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) in `y_max` if `output_range_given` is True. |\n| [GivenYMin](#structtensorflow_1_1ops_1_1_quantized_instance_norm_1_1_attrs_1a05f250f2de55e37648933a2b078bb1db)`(float x)` | `TF_MUST_USE_RESULT `[Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/quantized-instance-norm/attrs#structtensorflow_1_1ops_1_1_quantized_instance_norm_1_1_attrs) [Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) in `y_min` if `output_range_given` is True. |\n| [MinSeparation](#structtensorflow_1_1ops_1_1_quantized_instance_norm_1_1_attrs_1a990577e61d1a959e6b16f31deeef2ac3)`(float x)` | `TF_MUST_USE_RESULT `[Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/quantized-instance-norm/attrs#structtensorflow_1_1ops_1_1_quantized_instance_norm_1_1_attrs) [Minimum](/versions/r1.15/api_docs/cc/class/tensorflow/ops/minimum#classtensorflow_1_1ops_1_1_minimum) value of `y_max - y_min` |\n| [OutputRangeGiven](#structtensorflow_1_1ops_1_1_quantized_instance_norm_1_1_attrs_1a7715dcb9ec54a1cd7e45f9a30d1bd226)`(bool x)` | `TF_MUST_USE_RESULT `[Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/quantized-instance-norm/attrs#structtensorflow_1_1ops_1_1_quantized_instance_norm_1_1_attrs) If True, `given_y_min` and `given_y_min` and `given_y_max` are used as the output range. |\n| [VarianceEpsilon](#structtensorflow_1_1ops_1_1_quantized_instance_norm_1_1_attrs_1abee47b20aa34a84940f8449f1c4179b2)`(float x)` | `TF_MUST_USE_RESULT `[Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/quantized-instance-norm/attrs#structtensorflow_1_1ops_1_1_quantized_instance_norm_1_1_attrs) A small float number to avoid dividing by 0. |\n\nPublic attributes\n-----------------\n\n### given_y_max_\n\n```scdoc\nfloat tensorflow::ops::QuantizedInstanceNorm::Attrs::given_y_max_ = 0.0f\n``` \n\n### given_y_min_\n\n```scdoc\nfloat tensorflow::ops::QuantizedInstanceNorm::Attrs::given_y_min_ = 0.0f\n``` \n\n### min_separation_\n\n```scdoc\nfloat tensorflow::ops::QuantizedInstanceNorm::Attrs::min_separation_ = 0.001f\n``` \n\n### output_range_given_\n\n```scdoc\nbool tensorflow::ops::QuantizedInstanceNorm::Attrs::output_range_given_ = false\n``` \n\n### variance_epsilon_\n\n```gdscript\nfloat tensorflow::ops::QuantizedInstanceNorm::Attrs::variance_epsilon_ = 1e-05f\n``` \n\nPublic functions\n----------------\n\n### GivenYMax\n\n```scdoc\nTF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizedInstanceNorm::Attrs::GivenYMax(\n float x\n)\n``` \n[Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) in `y_max` if `output_range_given` is True.\n\nDefaults to 0 \n\n### GivenYMin\n\n```scdoc\nTF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizedInstanceNorm::Attrs::GivenYMin(\n float x\n)\n``` \n[Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) in `y_min` if `output_range_given` is True.\n\nDefaults to 0 \n\n### MinSeparation\n\n```scdoc\nTF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizedInstanceNorm::Attrs::MinSeparation(\n float x\n)\n``` \n[Minimum](/versions/r1.15/api_docs/cc/class/tensorflow/ops/minimum#classtensorflow_1_1ops_1_1_minimum) value of `y_max - y_min`\n\nDefaults to 0.001 \n\n### OutputRangeGiven\n\n```scdoc\nTF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizedInstanceNorm::Attrs::OutputRangeGiven(\n bool x\n)\n``` \nIf True, `given_y_min` and `given_y_min` and `given_y_max` are used as the output range.\n\nOtherwise, the implementation computes the output range.\n\nDefaults to false \n\n### VarianceEpsilon\n\n```scdoc\nTF_MUST_USE_RESULT Attrs tensorflow::ops::QuantizedInstanceNorm::Attrs::VarianceEpsilon(\n float x\n)\n``` \nA small float number to avoid dividing by 0.\n\nDefaults to 1e-05"]]