Functions — github.com/VinAIResearch/Warping-based_Backdoor

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Functions227 in github.com/VinAIResearch/Warping-based_Backdoor_Attack-release

⨍ Functions 227◇ Types & classes 58

FunctionResNeXt29_4x64d

()

classifier_models/resnext.py:84

FunctionResNeXt29_8x64d

()

classifier_models/resnext.py:88

FunctionResNet101

()

classifier_models/resnet.py:117

FunctionResNet152

()

classifier_models/resnet.py:120

FunctionResNet34

()

classifier_models/resnet.py:111

FunctionResNet50

()

classifier_models/resnet.py:114

FunctionShuffleNetG3

()

classifier_models/shufflenet.py:93

Method__call__

(self, x)

utils/dataloader.py:16

Method__call__

(self, x)

networks/models.py:18

Method__call__

(self, x)

networks/models.py:32

Method__call__

(self, x)

networks/models.py:54

Method__call__

(self, x)

networks/models.py:75

Method__call__

(self, x)

defenses/STRIP/STRIP.py:27

Method__call__

(self, x)

defenses/STRIP/STRIP.py:41

Method__call__

(self, background, dataset, classifier)

defenses/STRIP/STRIP.py:112

Method__getitem__

(self, index)

utils/dataloader.py:115

Method__getitem__

(self, index)

utils/dataloader.py:135

Method__init__

(self, f, p=1)

utils/dataloader.py:24

Method__init__

(self, opt)

utils/dataloader.py:59

Method__init__

(self, opt, split, transforms)

utils/dataloader.py:123

Method__init__

(self, in_c, out_c, ker_size=(3, 3), stride=1, padding=1, batch_norm=True, relu=True)

networks/blocks.py:21

Method__init__

(self, ker_size=(2, 2), stride=2, dilation=(1, 1), ceil_mode=False, p=0.0)

networks/blocks.py:36

Method__init__

( self, in_c, out_c, kernel_size, stride, padding, scale_factor=(2, 2), mode="bilinear", batch_norm=Tr

networks/blocks.py:49

Method__init__

(self, opt, expected_values, variance)

networks/models.py:26

Method__init__

(self, opt)

networks/models.py:40

Method__init__

(self, opt)

networks/models.py:61

Method__init__

(self, in_planes, planes, stride=1)

networks/models.py:83

Method__init__

(self)

networks/models.py:94

Method__init__

(self, opt, init_mask, init_pattern)

defenses/neural_cleanse/detecting.py:20

Method__init__

(self, opt, expected_values, variance)

defenses/STRIP/STRIP.py:21

Method__init__

(self, opt, expected_values, variance)

defenses/STRIP/STRIP.py:35

Method__init__

(self, opt)

defenses/STRIP/STRIP.py:95

Method__init__

(self)

classifier_models/lenet.py:7

Method__init__

(self, num_blocks, cardinality, bottleneck_width, num_classes=10)

classifier_models/resnext.py:44

Method__init__

(self, in_planes, out_planes, kernel_size, stride)

classifier_models/pnasnet.py:13

Method__init__

(self, in_planes, out_planes, stride=1)

classifier_models/pnasnet.py:42

Method__init__

(self, cell_type, num_cells, num_planes)

classifier_models/pnasnet.py:74

Method__init__

(self, in_planes, planes, stride=1)

classifier_models/senet.py:11

Method__init__

(self, in_planes, planes, stride=1)

classifier_models/senet.py:45

Method__init__

(self, last_planes, in_planes, out_planes, dense_depth, stride, first_layer)

classifier_models/dpn.py:8

Method__init__

(self, in_planes, growth_rate)

classifier_models/densenet.py:10

Method__init__

(self, in_planes, out_planes)

classifier_models/densenet.py:25

Method__init__

(self, num_classes=10)

classifier_models/mobilenet.py:33

Method__init__

(self, groups=2)

classifier_models/shufflenetv2.py:11

Method__init__

(self, ratio)

classifier_models/shufflenetv2.py:23

Method__init__

(self, in_channels, split_ratio=0.5)

classifier_models/shufflenetv2.py:33

Method__init__

(self, net_size)

classifier_models/shufflenetv2.py:95

Method__init__

(self, vgg_name)

classifier_models/vgg.py:15

Method__init__

(self, groups)

classifier_models/shufflenet.py:11

Method__init__

(self, cfg)

classifier_models/shufflenet.py:54

Method__init__

(self, cfg, num_classes=10)

classifier_models/efficientnet.py:75

Method__init__

(self, num_classes=10)

classifier_models/mobilenetv2.py:53

Method__init__

(self, in_planes, planes, stride=1)

classifier_models/preact_resnet.py:47

Method__init__

(self, block, num_blocks, num_classes=10)

classifier_models/preact_resnet.py:72

Method__init__

(self, in_planes, planes, stride=1)

classifier_models/resnet.py:17

Method__init__

(self, in_planes, planes, stride=1)

classifier_models/resnet.py:46

Method__init__

(self)

classifier_models/googlenet.py:57

Method__len__

(self)

utils/dataloader.py:112

Method__len__

(self)

utils/dataloader.py:132

Functioncreate_bd

(netG, netM, inputs, targets, opt)

defenses/fine_pruning/fine-pruning-cifar10-gtsrb.py:27

Functioncreate_targets_bd

(targets, opt)

defenses/fine_pruning/fine-pruning-celeba.py:17

Methoddenormalize

(self, x)

defenses/STRIP/STRIP.py:107

utils/dataloader.py:29

Methodforward

(self, x)

utils/dataloader.py:68

Methodforward

(self, x)

networks/blocks.py:14

Methodforward

(self, x)

networks/blocks.py:29

Methodforward

(self, x)

networks/blocks.py:42

Methodforward

(self, x)

networks/blocks.py:60

Methodforward

(self, x)

networks/models.py:89

Methodforward

(self, x)

networks/models.py:106

Methodforward

(self, x)

defenses/neural_cleanse/detecting.py:30

Methodforward

(self, x)

classifier_models/lenet.py:15

Methodforward

(self, x)

classifier_models/resnext.py:34

Methodforward

(self, x)

classifier_models/resnext.py:68

Methodforward

(self, x)

classifier_models/pnasnet.py:20

Methodforward

(self, x)

classifier_models/pnasnet.py:33

Methodforward

(self, x)

classifier_models/pnasnet.py:57

Methodforward

(self, x)

classifier_models/pnasnet.py:102

Methodforward

(self, x)

classifier_models/senet.py:28

Methodforward

(self, x)

classifier_models/senet.py:59

Methodforward

(self, x)

classifier_models/senet.py:97

Methodforward

(self, x)

classifier_models/dpn.py:27

Methodforward

(self, x)

classifier_models/dpn.py:61

Methodforward

(self, x)

classifier_models/densenet.py:17

Methodforward

(self, x)

classifier_models/densenet.py:30

Methodforward

(self, x)

classifier_models/densenet.py:75

Methodforward

(self, x)

classifier_models/mobilenet.py:23

Methodforward

(self, x)

classifier_models/mobilenet.py:49

Methodforward

Channel shuffle: [N,C,H,W] -> [N,g,C/g,H,W] -> [N,C/g,g,H,w] -> [N,C,H,W]

classifier_models/shufflenetv2.py:15

Methodforward

(self, x)

classifier_models/shufflenetv2.py:27

Methodforward

(self, x)

classifier_models/shufflenetv2.py:47

Methodforward

(self, x)

classifier_models/shufflenetv2.py:80

Methodforward

(self, x)

classifier_models/shufflenetv2.py:117

Methodforward

(self, x)

classifier_models/vgg.py:20

Methodforward

Channel shuffle: [N,C,H,W] -> [N,g,C/g,H,W] -> [N,C/g,g,H,w] -> [N,C,H,W]

classifier_models/shufflenet.py:15

Methodforward

(self, x)

classifier_models/shufflenet.py:43

Methodforward

(self, x)

classifier_models/shufflenet.py:77

Methodforward

(self, x)

classifier_models/efficientnet.py:57

Methodforward

(self, x)

classifier_models/efficientnet.py:94

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