Functions — github.com/THUYimingLi/BackdoorBox

Method__init__

(self, pattern, mask)

core/attacks/TUAP.py:189

Method__init__

(self, y_target)

core/attacks/TUAP.py:203

Method__init__

(self, benign_dataset, y_target, is_train_set,

core/attacks/TUAP.py:211

Method__init__

(self, benign_dataset, y_target, is_train_set,

core/attacks/TUAP.py:297

Method__init__

(self, benign_dataset, y_target, is_train_set,

core/attacks/TUAP.py:382

Method__init__

(self, train_dataset, test_dataset, model,

core/attacks/TUAP.py:749

Method__init__

(self, dataset_name, expected_values, variance)

core/attacks/ISSBA.py:33

Method__init__

(self, data, targets)

core/attacks/ISSBA.py:56

Method__init__

Wrap base convolution layer See official PyTorch documentation for parameter details https://pytorch.org/docs/stable/generated/torch.

core/attacks/ISSBA.py:109

Method__init__

(self, secret_size=20, height=32, width=32, in_channel=3)

core/attacks/ISSBA.py:170

Method__init__

(self, secret_size, height, width, in_channel)

core/attacks/ISSBA.py:249

Method__init__

(self, in_channel=3)

core/attacks/ISSBA.py:314

Method__init__

(self, secret_size=20, height=28, width=28, in_channel=1)

core/attacks/ISSBA.py:344

Method__init__

(self, secret_size, height, width, in_channel)

core/attacks/ISSBA.py:414

Method__init__

(self, in_channel=1)

core/attacks/ISSBA.py:477

Method__init__

(self, f, p=1)

core/attacks/ISSBA.py:514

Method__init__

(self, dataset_name)

core/attacks/ISSBA.py:532

Method__init__

(self)

core/attacks/WaNet.py:23

Method__init__

(self, identity_grid, noise_grid, noise=False, s=0.5, grid_rescale=1, noise_rescale=2)

core/attacks/WaNet.py:61

Method__init__

(self, identity_grid, noise_grid, noise=False, s=0.5, grid_rescale=1, noise_rescale=2)

core/attacks/WaNet.py:148

Method__init__

(self, identity_grid, noise_grid, noise=False, s=0.5, grid_rescale=1, noise_rescale=2)

core/attacks/WaNet.py:186

Method__init__

(self, y_target)

core/attacks/WaNet.py:210

Method__init__

(self, benign_dataset, y_target, poisoned_rate,

core/attacks/WaNet.py:218

Method__init__

(self, benign_dataset, y_target, poisoned_rate,

core/attacks/WaNet.py:296

Method__init__

(self, benign_dataset, y_target, poisoned_rate,

core/attacks/WaNet.py:368

Method__init__

(self, in_planes, planes, stride=1)

core/attacks/LIRA.py:29

Method__init__

(self)

core/attacks/LIRA.py:40

Method__init__

(self, y_target)

core/attacks/LIRA.py:99

Method__init__

(self, data_list, labels)

core/attacks/LIRA.py:113

Method__init__

(self)

core/attacks/LIRA.py:128

Method__init__

(self, out_channel)

core/attacks/LIRA.py:171

Method__init__

(self)

core/attacks/LIRA.py:225

Method__init__

(self, f, p=1)

core/attacks/LIRA.py:268

Method__init__

(self, dataset_name)

core/attacks/LIRA.py:286

Method__init__

(self, dataset_name, train_dataset, test_dataset,

core/attacks/LIRA.py:327

Method__init__

(self, y_target)

core/attacks/IAD.py:31

Method__init__

(self, data_list, labels)

core/attacks/IAD.py:45

Method__init__

(self, dataset_name, expected_values, variance)

core/attacks/IAD.py:66

Method__init__

(self, dataset_name, expected_values, variance)

core/attacks/IAD.py:90

Method__init__

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

core/attacks/IAD.py:109

Method__init__

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

core/attacks/IAD.py:125

Method__init__

(self, scale_factor=(2, 2), mode="nearest", p=0.0)

core/attacks/IAD.py:139

Method__init__

(self, dataset_name, out_channels=None)

core/attacks/IAD.py:158

Method__init__

(self, pattern, weight)

core/attacks/AdaptivePatch.py:44

Method__init__

(self, pattern, weight)

core/attacks/AdaptivePatch.py:130

Method__init__

(self, pattern, weight)

core/attacks/AdaptivePatch.py:169

Method__init__

(self, y_target)

core/attacks/AdaptivePatch.py:200

Method__init__

(self, benign_dataset, y_target, poisoned_rate,

core/attacks/AdaptivePatch.py:208

Method__init__

(self, benign_dataset, y_target, poisoned_rate,

core/attacks/AdaptivePatch.py:298

Method__init__

(self, benign_dataset, y_target, poisoned_rate,

core/attacks/AdaptivePatch.py:354

Method__init__

(self, train_dataset, test_dataset, model,

core/attacks/AdaptivePatch.py:445

Method__init__

Args: source and target size.

core/attacks/SleeperAgent.py:51

Method__init__

(self, train_dataset, test_dataset, model,

core/attacks/SleeperAgent.py:280

Method__init__

(self)

core/attacks/Blended.py:20

Method__init__

(self, pattern, weight)

core/attacks/Blended.py:43

Method__init__

(self, pattern, weight)

core/attacks/Blended.py:129

Method__init__

(self, pattern, weight)

core/attacks/Blended.py:168

Method__init__

(self, y_target)

core/attacks/Blended.py:199

Method__init__

(self, benign_dataset, y_target, poisoned_rate,

core/attacks/Blended.py:207

Method__init__

(self, benign_dataset, y_target, poisoned_rate,

core/attacks/Blended.py:267

Method__init__

(self, benign_dataset, y_target, poisoned_rate,

core/attacks/Blended.py:323

Method__init__

(self, in_channels, out_channels, mid_channels=None)

core/models/unet.py:11

Method__init__

(self, in_channels, out_channels)

core/models/unet.py:30

Method__init__

(self, in_channels, out_channels)

core/models/unet.py:70

Method__init__

(self, args, n_channels, n_classes, bilinear=True)

core/models/unet.py:79

Method__init__

(self, args, n_channels, n_classes, bilinear=True, first_channels=32)

core/models/unet.py:112

Method__init__

(self, args, n_channels, n_classes, bilinear=True)

core/models/unet.py:145

Method__init__

(self, args, n_channels, n_classes, bilinear=True)

core/models/unet.py:174

Method__init__

(self, in_planes, planes, fix_points, stride=1)

core/models/resnet_curve.py:18

Method__init__

(self, in_planes, planes, fix_points, stride=1)

core/models/resnet_curve.py:49

Method__init__

(self, features, num_classes=43, fix_points=None, initialize=False)

core/models/vgg_curve.py:16

Method__init__

(self)

core/models/baseline_MNIST_network.py:12

Method__init__

(self)

core/models/autoencoder.py:55

Method__init__

(self, features, num_classes=43)

core/models/vgg.py:9

Method__init__

(self, num_bends)

core/models/curves.py:34

Method__init__

(self, fix_points, parameter_names=())

core/models/curves.py:46

Method__init__

(self, in_features, out_features, fix_points, bias=True)

core/models/curves.py:71

Method__init__

(self, in_channels, out_channels, kernel_size, fix_points, stride=1, padding=0, dilation=1, g

core/models/curves.py:107

Method__init__

(self, num_features, fix_points, eps=1e-5, momentum=0.1, affine=True, track_running_stats=Tru

core/models/curves.py:164

Method__init__

(self, curve, base_model, num_bends, fix_start=True, fix_end=True)

core/models/curves.py:263

Method__init__

(self, in_planes, planes, stride=1)

core/models/resnet.py:15

Method__init__

(self, in_planes, planes, stride=1)

core/models/resnet.py:40

Method__init__

(self, in_planes, planes, stride=1)

tests/test_LIRA.py:272

Method__init__

(self)

tests/test_LIRA.py:283

Method__init__

(self, y_target)

tests/test_BAAT.py:70

Method__init__

(self, *data_roots)

tests/test_BAAT.py:140

Method__init__

(self, n_holes, length)

tests/test_NAD.py:40

Method__init__

(self, data_list, labels)

tests/test_ISSBA.py:44

Method__len__

(self)

core/defenses/ABL.py:97

Method__len__

(self)

core/attacks/ISSBA.py:60

Method__len__

(self)

core/attacks/LIRA.py:117

Method__len__

(self)

core/attacks/IAD.py:49

Method__len__

(self)

core/attacks/SleeperAgent.py:33

Method__len__

(self)

tests/test_ISSBA.py:48

Method__str__

(self)

core/utils/torchattacks/attack.py:170

Method_check_input_dim

(self, input)

core/models/curves.py:256

Method_generate_adv_dataset

(dataset, adv_model, adv_dataset_dir, adv_transform, eps, alpha, steps, y_target, poisoned_rate)

core/attacks/LabelConsistent.py:545

Method_get_attribute_identifier

(self, attribute_description: Dict[str, str])

core/attacks/BAAT.py:290

Method_get_label

r""" Function for changing the attack mode. Return input labels.

core/utils/torchattacks/attack.py:137

Method_get_least_likely_label

r""" Function for changing the attack mode. Return least likely labels.

core/utils/torchattacks/attack.py:144

Functions664 in github.com/THUYimingLi/BackdoorBox