Functions — github.com/G3H4N/GAN-Trained-Model-Detection-and-Attribution

hub / github.com/G3H4N/GAN-Trained-Model-Detection-and-Attribution / functions

Functions2,927 in github.com/G3H4N/GAN-Trained-Model-Detection-and-Attribution

⨍ Functions 2,927◇ Types & classes 307

↓ 3 callersFunctionsave_checkpoint

(obj, save_path, is_best=False, max_keep=None)

models/model_train_multi_real.py:142

↓ 3 callersFunctionsave_checkpoint

(obj, save_path, is_best=False, max_keep=None)

models/classifier_train_real_multiclass_byMstr.py:100

↓ 3 callersFunctionsave_checkpoint

(obj, save_path, is_best=False, max_keep=None)

models/CIFAR10_model_train_multi_MIA.py:141

↓ 3 callersFunctionsave_checkpoint

(obj, save_path, is_best=False, max_keep=None)

models/classifier_train_real_multiclass_byGANstr.py:100

↓ 3 callersFunctionsave_checkpoint

(obj, save_path, is_best=False, max_keep=None)

models/FMNIST_other_GANship_classifier_train.py:99

↓ 3 callersFunctionsave_checkpoint

(obj, save_path, is_best=False, max_keep=None)

models/CIFAR10_real_GANship_classifier_train.py:100

↓ 3 callersFunctionsave_checkpoint

(obj, save_path, is_best=False, max_keep=None)

models/classifier_train_real_multiclass.py:100

↓ 3 callersFunctionsave_checkpoint

(obj, save_path, is_best=False, max_keep=None)

models/Compare/SVHN_real_DUAL_classifier_train.py:112

↓ 3 callersFunctionsave_checkpoint

(obj, save_path, is_best=False, max_keep=None)

models/MIA_HALF/code/Attacker_train.py:103

↓ 3 callersMethodselect_indices_to_poison

(self, labels, poisoning_proportion=1.0, *, apply_to="all", confidence_ordering=None)

label-consistent-backdoor-code-main/poison_attack.py:84

↓ 3 callersFunctiontest

(net, i_index, t_index, test_loader)

models/SVHN_fake_GANship_Binary_classifier_train1.py:146

↓ 3 callersFunctiontest

(net, i_index, t_index, test_loader)

models/SVHN_real_GANship_classifier_train_labelonly.py:425

↓ 3 callersFunctiontest

(net, i_index, t_index, test_loader)

models/CelebA_real_GANship_classifier_train_sepVGG.py:239

↓ 3 callersFunctiontest

(net, i_index, t_index, test_loader)

models/FMNIST_real_GANship_classifier_train.py:394

↓ 3 callersFunctiontest

(net, i_index, t_index, test_loader)

models/SVHN_real_FakeORReal_classifier_train1.py:147

↓ 3 callersFunctiontest

(net, i_index, t_index, test_loader)

models/CIFAR10_backdoor_real_GANship_classifier_train.py.py:241

↓ 3 callersFunctiontest

(net, i_index, t_index, test_loader)

models/classifier_train_together_binaryclassify_multimage.py:518

↓ 3 callersFunctiontest

(net, i_index, t_index, test_loader)

models/CelebA_real_GANship_classifier_train.py:239

↓ 3 callersFunctiontest

(net, i_index, t_index, test_loader)

models/CIFAR10_real_GANship_classifier_train.py:264

↓ 3 callersFunctiontest_binary

(net, i_index, t_index, test_loader)

models/CelebA_real_FakeORReal_classifier_train.py:265

↓ 3 callersFunctiontest_binary

(net, i_index, t_index, test_loader)

models/FMNIST_real_FakeORReal_classifier_train.py:265

↓ 3 callersFunctiontest_binary

(net, i_index, t_index, test_loader)

models/CelebA_real_FakeORReal_classifier_train_sepVGG.py:265

↓ 3 callersFunctiontest_binary

(net, i_index, t_index, test_loader)

models/CelebA_fake_GANship_Binary_classifier_train.py:265

↓ 3 callersFunctiontest_binary

(net, i_index, t_index, test_loader)

models/CelebA_fake_GANship_Binary_classifier_train_sepVGG.py:265

↓ 3 callersFunctiontest_binary

(net, i_index, t_index, test_loader)

models/Compare/SVHN_real_DUAL_classifier_train.py:198

↓ 3 callersFunctiontest_binary

(net, i_index, t_index, test_loader)

models/MIA_HALF/code/Attacker_train.py:161

↓ 2 callersFunctionConcatDataset2Data

(Concated)

models/Compare/utils.py:90

↓ 2 callersFunctionDenormalize

(data)

models/CIFAR10_model_train_specified.py:172

↓ 2 callersFunctionDenormalize

(data)

models/SVHN_real_GANship_classifier_train.py:143

↓ 2 callersFunctionDenormalize

(data)

models/SVHN_other_GANship_classifier_train.py:130

↓ 2 callersFunctionDenormalize

(data)

models/classifier_train_multiclass_multiGAN.py:130

↓ 2 callersFunctionDenormalize

(data)

models/classifier_train_together_multiclass.py:180

↓ 2 callersFunctionDenormalize

(data)

models/Combine_Noise_GANStrctr_classifier_train.py:130

↓ 2 callersFunctionDenormalize

(data)

models/CelebA_other_GANship_classifier_train.py:129

↓ 2 callersFunctionDenormalize

(data)

models/CelebA_Noise_GANStrctr_classifier_train.py:130

↓ 2 callersFunctionDenormalize

(data)

models/SVHN_real_GANship_classifier_train_labelonly.py:136

↓ 2 callersFunctionDenormalize

(data)

models/SVHN_MNIST_GANStrctr_classifier_train.py:130

↓ 2 callersFunctionDenormalize

(data)

models/classifier_train_real_multi_GANStrctr_byMstr.py:130

↓ 2 callersFunctionDenormalize

(data)

models/classifier_train_real_multi_GANStrctr.py:130

↓ 2 callersFunctionDenormalize

(data)

models/Combine_real_GANStrctr_classifier_train.py:130

↓ 2 callersFunctionDenormalize

(data)

models/Combine_SVHN_real_GANStrctr_classifier_train_CelebA_only.py:130

↓ 2 callersFunctionDenormalize

(data)

models/SVHN_real_GANStrctr_classifier_train.py:142

↓ 2 callersFunctionDenormalize

(data)

models/FMNIST_SVHN_GANship_classifier_train.py:130

↓ 2 callersFunctionDenormalize

(data)

models/classifier_train_together.py:180

↓ 2 callersFunctionDenormalize

(data)

models/FMNIST_real_GANStrctr_classifier_train.py:130

↓ 2 callersFunctionDenormalize

(data)

models/FMNIST_MNIST_GANStrctr_classifier_train.py:130

↓ 2 callersFunctionDenormalize

(data)

models/FMNIST_real_GANship_classifier_train.py:130

↓ 2 callersFunctionDenormalize

(data)

models/CelebA_Noise_GANship_classifier_train.py:130

↓ 2 callersFunctionDenormalize

(data)

models/Noise_GANStrctr_classifier_train.py:130

↓ 2 callersFunctionDenormalize

(data)

models/CelebA_FFHQ_GANStrctr_classifier_train.py:130

↓ 2 callersFunctionDenormalize

(data)

models/Noise_GANship_classifier_train.py:130

↓ 2 callersFunctionDenormalize

(data)

models/SVHN_Noise_GANStrctr_classifier_train.py:130

↓ 2 callersFunctionDenormalize

(data)

models/FMNIST_Noise_GANship_classifier_train.py:130

↓ 2 callersFunctionDenormalize

(data)

models/Combine_CIFAR10_real_GANStrctr_classifier_train.py:130

↓ 2 callersFunctionDenormalize

(data)

models/SVHN_Noise_GANship_classifier_train.py:130

↓ 2 callersFunctionDenormalize

(data)

models/FMNIST_Noise_GANStrctr_classifier_train.py:130

↓ 2 callersFunctionDenormalize

(data)

models/CelebA_FFHQ_GANship_classifier_train.py:130

↓ 2 callersFunctionDenormalize

(data)

models/classifier_train_real_multiclass_byMstr.py:130

↓ 2 callersFunctionDenormalize

(data)

models/classifier_train_real_multiclass_byGANstr.py:130

↓ 2 callersFunctionDenormalize

(data)

models/FMNIST_other_GANship_classifier_train.py:129

↓ 2 callersFunctionDenormalize

(data)

models/classifier_train_real_multiclass.py:130

↓ 2 callersMethod__init__

(self, block, num_blocks, num_classes=10)

models/structures/senet.py:80

↓ 2 callersMethod__init__

(self, block, nblocks, growth_rate=12, reduction=0.5, num_classes=10)

models/structures/densenet.py:37

↓ 2 callersMethod__init__

(self, in_planes, out_planes, stride, groups)

models/structures/shufflenet.py:23

↓ 2 callersMethod__init__

(self, in_channels, se_channels)

models/structures/efficientnet.py:28

↓ 2 callersMethod__init__

(self, in_planes, planes, stride=1)

models/structures/preact_resnet.py:16

↓ 2 callersMethod__init__

(self, block, num_blocks, num_classes=8)

models/structures/resnet.py:74

↓ 2 callersMethod__init__

(self, in_planes, se_planes)

models/structures/regnet.py:15

↓ 2 callersMethod_downsample

(self, planes)

models/structures/pnasnet.py:95

↓ 2 callersFunction_interpolate

(a, b=None)

GANs/model.py:81

↓ 2 callersFunction_interpolate

(a, b=None)

models/GAN_structures.py:81

↓ 2 callersFunctionattacker_GANship_test

(attacker, information_name, targetGAN_list, All_GAN_list, model_addr='/data/gehan/PytorchProjects/GANInferenc

models/classifier_train_together_multiclass.py:289

↓ 2 callersFunctionattacker_GANship_test

(attacker, information_name, targetGAN_list, All_GAN_list, model_addr='/data/gehan/PytorchProjects/GANInferenc

models/classifier_train_together.py:289

↓ 2 callersMethodfmt

(self, second)

GANs/pylib/timer.py:56

↓ 2 callersFunctionformat_time

(seconds)

models/utils_NoUse.py:94

↓ 2 callersFunctionim2float

Transform images from [-1.0, 1.0] to [0.0, 1.0].

GANs/imlib/dtype.py:58

↓ 2 callersFunctionim2uint

Transform images from [-1.0, 1.0] to uint8.

GANs/imlib/dtype.py:53

↓ 2 callersFunctioninit_weights

(net, init_gain=0.02)

Attacks/model.py:278

↓ 2 callersFunctionloadData

(filename)

models/SVHN_real_GANship_trainsets_compare.py:117

↓ 2 callersFunctionloadData

(filename)

models/CelebA_real_GANStrctr_testsets.py:106

↓ 2 callersFunctionloadData

(filename)

models/CelebA_Noise_GANship_testsets.py:106

↓ 2 callersFunctionloadData

(filename)

models/FMNIST_real_GANship_testsets.py:107

↓ 2 callersFunctionloadData

(filename)

models/SVHN_fake_GANship_Binary_classifier_train1.py:77

↓ 2 callersFunctionloadData

(filename)

models/CIFAR10_real_GANStrctr_trainsets_CelebA.py:107

↓ 2 callersFunctionloadData

(filename)

models/posterio_GANship_trainsets_together_binaryclassify_multimge.py:106

↓ 2 callersFunctionloadData

(filename)

models/posterio_GANship_testsets_real_multiclass_byMstr.py:106

↓ 2 callersFunctionloadData

(filename)

models/CIFAR10_Noise_GANship_testsets.py:107

↓ 2 callersFunctionloadData

(filename)

models/SVHN_other_GANship_testsets.py:107

↓ 2 callersFunctionloadData

(filename)

models/CelebA_real_FakeORReal_classifier_train.py:65

↓ 2 callersFunctionloadData

(filename)

models/CelebA_Noise_GANship_trainsets.py:106

↓ 2 callersFunctionloadData

(filename)

models/FMNIST_Noise_GANStrctr_testsets.py:106

↓ 2 callersFunctionloadData

(filename)

models/SVHN_other_GANship_classifier_train.py:64

↓ 2 callersFunctionloadData

(filename)

models/classifier_train_multiclass_multiGAN.py:64

↓ 2 callersFunctionloadData

(filename)

models/FMNIST_real_FakeORReal_testsets.py:107

↓ 2 callersFunctionloadData

(filename)

models/FMNIST_MNIST_GANStrctr_testsets.py:107

↓ 2 callersFunctionloadData

(filename)

models/FMNIST_fake_GANship_Binary_trainsets.py:108

↓ 2 callersFunctionloadData

(filename)

models/SVHN_MNIST_GANStrctr_trainsets.py:107

↓ 2 callersFunctionloadData

(filename)

models/FMNIST_fake_GANship_Binary_testsets.py:108

↓ 2 callersFunctionloadData

(filename)

models/CIFAR10_real_GANship_trainsets_noVGG.py:107

↓ 2 callersFunctionloadData

(filename)

models/CelebA_Noise_GANStrctr_trainsets.py:106

← previous next →501–600 of 2,927, ranked by callers