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Functions112 in github.com/chu0802/SLA

⨍ Functions 112◇ Types & classes 22 ↳ Endpoints 1

↓ 9 callersFunction_float_parameter

src/randaugment.py:139

↓ 4 callersFunction_int_parameter

src/randaugment.py:143

↓ 4 callersFunctiondownload

(url, path, auto_mkdir=True)

data_preparation/data_preparation.py:12

↓ 4 callersMethodget_predictions

src/model.py:123

↓ 3 callersFunctionCutoutAbs

(img, v, **kwarg)

src/randaugment.py:47

↓ 3 callersFunctionPairEnum2D

Enumerate all pairs of feature in x with 2 dimensions.

src/cdac_loss.py:51

↓ 3 callersMethod__init__

(self, backbone="resnet34", **kwargs)

src/model.py:53

↓ 3 callersMethodinit

(self, model, t_loader)

src/model.py:30

↓ 3 callersMethodstep

↓ 3 callersMethodtrain

src/trainer.py:79

↓ 2 callersMethodbackward

(ctx, grad_output)

src/model.py:191

↓ 2 callersMethodbase_loss

src/model.py:126

↓ 2 callersFunctionevaluation

(loader, model)

src/evaluation.py:4

↓ 2 callersMethodforward

(self, x, reverse=False)

src/model.py:106

↓ 2 callersMethodfrom_args

src/util.py:108

↓ 2 callersMethodget_features

(self, x, reverse=False)

src/model.py:120

↓ 2 callersFunctionget_trainer

(base_class, label_trick=None)

src/trainer.py:172

↓ 2 callersMethodlogging

(self, step, info, unit="min")

src/trainer.py:46

↓ 1 callersFunctionPairEnum1D

Enumerate all pairs of feature in x with 1 dimension.

src/cdac_loss.py:41

↓ 1 callersMethod__init__

(self, loaders, args, **kwargs)

src/trainer.py:141

↓ 1 callersFunctionadvbce_unlabeled

Construct adversarial adpative clustering loss.

src/cdac_loss.py:7

↓ 1 callersFunctionarguments_parsing

↓ 1 callersFunctionarguments_parsing

data_preparation/data_preparation.py:85

↓ 1 callersMethodevaluate

src/trainer.py:56

↓ 1 callersMethodfeature_base_loss

src/model.py:129

↓ 1 callersFunctionfixmatch_augment_pool

src/randaugment.py:147

↓ 1 callersFunctionget_SLA_trainer

src/trainer.py:139

↓ 1 callersMethodget_features

(self, x, reverse=False)

src/model.py:74

↓ 1 callersFunctionget_generator

src/dataset.py:59

↓ 1 callersMethodget_list_file_name

src/dataset.py:152

↓ 1 callersMethodget_loader

src/dataset.py:161

↓ 1 callersMethodget_loader_name

src/dataset.py:147

↓ 1 callersMethodget_lr

src/util.py:101

↓ 1 callersMethodget_params

src/model.py:109

↓ 1 callersMethodget_predictions

src/model.py:80

↓ 1 callersMethodget_source_loss

(self, step, *data)

src/trainer.py:40

↓ 1 callersMethodget_target_loss

(self, step, *data)

src/trainer.py:43

↓ 1 callersFunctiongrad_reverse

src/model.py:196

↓ 1 callersFunctioninit_weights

src/model.py:11

↓ 1 callersFunctionload_yaml

↓ 1 callersFunctionmain

↓ 1 callersFunctionmy_augment_pool

src/randaugment.py:168

↓ 1 callersFunctionpairwise_target

Produce pairwise similarity label.

src/cdac_loss.py:16

↓ 1 callersFunctionpil_loader

src/dataset.py:47

↓ 1 callersMethodppc_update

src/trainer.py:155

↓ 1 callersFunctionprediction

(loader, model)

src/evaluation.py:18

↓ 1 callersFunctionprepare_text_list

data_preparation/data_preparation.py:55

↓ 1 callersMethodrefresh

↓ 1 callersFunctionset_seed

↓ 1 callersFunctionsigmoid_rampup

Exponential rampup from https://arxiv.org/abs/1610.02242

src/cdac_loss.py:59

↓ 1 callersMethodsla_loss

(self, f, y1, y2, alpha)

src/model.py:132

↓ 1 callersMethodtraining_step

(self, step, *data)

src/trainer.py:67

↓ 1 callersMethodtraining_step

(self, step, *data)

src/trainer.py:163

↓ 1 callersMethodunlabeled_training_step

(self, step, ux)

src/trainer.py:124

FunctionAutoContrast

src/randaugment.py:20

FunctionBrightness

(img, v, max_v, bias=0)

src/randaugment.py:24

(img, v, max_v, bias=0)

src/randaugment.py:29

FunctionContrast

(img, v, max_v, bias=0)

src/randaugment.py:34

(img, v, max_v, bias=0)

src/randaugment.py:39

FunctionEqualize

src/randaugment.py:63

FunctionIdentity

src/randaugment.py:67

src/randaugment.py:71

FunctionPosterize

(img, v, max_v, bias=0)

src/randaugment.py:75

(img, v, max_v, bias=0)

src/randaugment.py:80

FunctionSharpness

(img, v, max_v, bias=0)

src/randaugment.py:87

(img, v, max_v, bias=0)

src/randaugment.py:92

(img, v, max_v, bias=0)

src/randaugment.py:99

FunctionSolarize

(img, v, max_v, bias=0)

src/randaugment.py:106

FunctionSolarizeAdd

(img, v, max_v, bias=0, threshold=128)

src/randaugment.py:111

FunctionTranslateX

(img, v, max_v, bias=0)

src/randaugment.py:123

FunctionTranslateY

(img, v, max_v, bias=0)

src/randaugment.py:131

src/randaugment.py:199

src/randaugment.py:217

Method__getitem__

src/dataset.py:76

(self, root, list_file, transform, strong_transform=None)

src/dataset.py:66

(self, sampler)

src/dataset.py:89

( self, dataset, batch_size, worker_init_fn=None, generator=None,

src/dataset.py:99

(self, args, domain_type, mode, labeled=None, strong_transform=False)

src/dataset.py:132

(self, args, strong_transform=False)

src/dataset.py:198

src/randaugment.py:192

src/randaugment.py:210

(self, optimizer, num_iters, step=0, final_lr=None)

(self, loaders, args, backbone="resnet34")

src/trainer.py:18

(self, loaders, args, backbone="resnet34", unlabeled_method="mme")

src/trainer.py:120

src/model.py:24

(self, in_dim, hidden_dim=512, num_classes=65, temp=0.05)

src/model.py:64

( self, backbone="resnet34", hidden_dim=512, output_dim=65, temp=0.05,

src/model.py:85

src/dataset.py:92

src/dataset.py:123

src/dataset.py:223

src/dataset.py:73

src/dataset.py:127

src/dataset.py:240

Methodcdac_loss

(self, step, x, x1, x2)

src/model.py:152

Functiondecorator

Functiondownload_DomainNet

data_preparation/data_preparation.py:36

Functiondownload_OfficeHome

data_preparation/data_preparation.py:23

(self, x, T=1.0)

src/model.py:47

src/model.py:59

(self, x, reverse=False)

src/model.py:70

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