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Functions93 in github.com/Albert0147/G-SFDA

⨍ Functions 93◇ Types & classes 15
↓ 7 callersFunctioncal_acc_sda
(loader, netF,netC,t=0)
Continual_SFDA/utils.py:44
↓ 5 callersFunctioncal_acc_sda
(loader, netF,netC,t=0)
utils.py:145
↓ 4 callersMethod__init__
(self, res_name)
network.py:32
↓ 3 callersFunctionEntropy
(input_)
utils.py:15
↓ 3 callersFunctioncal_acc
(loader, netF, netB, netC,t=0, flag=False)
train_src_visda.py:86
↓ 3 callersMethodforward
(self, inputs, targets)
utils.py:47
↓ 2 callersFunctioncal_acc
(loader, netF, netB, netC,t=0, flag=False)
train_tar_visda.py:103
↓ 2 callersFunctiondata_load
(args)
train_src_visda.py:58
↓ 2 callersFunctionimage_target
(resize_size=256, crop_size=224)
utils.py:187
↓ 2 callersFunctionimage_test
(resize_size=256, crop_size=224)
utils.py:212
↓ 2 callersFunctionimage_test
(resize_size=256, crop_size=224, alexnet=False)
train_src_visda.py:45
↓ 2 callersFunctionimage_test
(resize_size=256, crop_size=224, alexnet=False)
train_tar_visda.py:48
↓ 2 callersFunctionimage_train
(resize_size=256, crop_size=224)
utils.py:176
↓ 2 callersFunctionimage_train
(resize_size=256, crop_size=224, alexnet=False)
train_tar_visda.py:34
↓ 2 callersFunctionmake_dataset
(image_list, labels)
utils.py:223
↓ 2 callersFunctionmake_dataset
(image_list, labels)
data_list.py:13
↓ 2 callersFunctionoffice_load
(args)
utils.py:282
↓ 2 callersFunctionprint_args
(args)
Continual_SFDA/utils.py:78
↓ 2 callersFunctiontrain_target_near
(args,t,netF,oldC,dset_loader,mask_old=None)
Continual_SFDA/continual_sfda.py:229
↓ 1 callersFunctionEntropy
(input_)
loss.py:10
↓ 1 callersMethod__init__
(self, image_list, labels=None, transform=None,
utils.py:251
↓ 1 callersMethod__init__
(self, class_num, bottleneck_dim=256, type="linear")
Continual_SFDA/network.py:15
↓ 1 callersFunctiondata_load
(args)
train_tar_visda.py:61
↓ 1 callersMethodforward
(self, x)
network.py:46
↓ 1 callersMethodforward
(self, x)
Continual_SFDA/network.py:24
↓ 1 callersMethodforward
(self, inputs, targets)
Continual_SFDA/utils.py:29
↓ 1 callersFunctionimage_target
(resize_size=256, crop_size=224)
Continual_SFDA/utils.py:96
↓ 1 callersFunctionimage_test
(resize_size=256, crop_size=224)
Continual_SFDA/utils.py:107
↓ 1 callersFunctionimage_train
(resize_size=256, crop_size=224, alexnet=False)
train_src_visda.py:31
↓ 1 callersFunctionimage_train
(resize_size=256, crop_size=224)
Continual_SFDA/utils.py:85
↓ 1 callersFunctionlr_scheduler
(optimizer, iter_num, max_iter, gamma=10, power=0.75)
train_tar_oh.py:25
↓ 1 callersFunctionlr_scheduler
(optimizer, iter_num, max_iter, gamma=10, power=0.75)
train_src_visda.py:22
↓ 1 callersFunctionlr_scheduler
(optimizer, iter_num, max_iter, gamma=10, power=0.75)
train_tar_visda.py:24
↓ 1 callersFunctionlr_scheduler
(optimizer, iter_num, max_iter, gamma=10, power=0.75)
Continual_SFDA/continual_sfda.py:112
↓ 1 callersFunctionmake_dataset
(image_list, labels)
Continual_SFDA/utils.py:118
↓ 1 callersFunctionoffice_load_idx
(args)
train_tar_oh.py:73
↓ 1 callersFunctionoffice_load_idx
(args)
Continual_SFDA/continual_sfda.py:54
↓ 1 callersFunctionop_copy
(optimizer)
train_tar_oh.py:19
↓ 1 callersFunctionop_copy
(optimizer)
train_src_visda.py:17
↓ 1 callersFunctionop_copy
(optimizer)
train_tar_visda.py:18
↓ 1 callersFunctionop_copy
(optimizer)
Continual_SFDA/utils.py:72
↓ 1 callersFunctionprint_args
(args)
train_tar_oh.py:34
↓ 1 callersFunctionprint_args
(args)
train_src_oh.py:22
↓ 1 callersFunctionprint_args
(args)
train_src_visda.py:264
↓ 1 callersFunctionprint_args
(args)
train_tar_visda.py:311
↓ 1 callersFunctiontest_target
(args)
train_src_oh.py:124
↓ 1 callersFunctiontest_target
(args)
train_src_visda.py:235
↓ 1 callersFunctiontrain_source
(args)
train_src_oh.py:29
↓ 1 callersFunctiontrain_source
(args)
train_src_visda.py:120
↓ 1 callersFunctiontrain_source
(args,dset_loaders)
Continual_SFDA/continual_sfda.py:122
↓ 1 callersFunctiontrain_target
(args)
train_tar_visda.py:139
↓ 1 callersFunctiontrain_target_near
(args)
train_tar_oh.py:151
Method__getitem__
(self, index)
train_tar_oh.py:58
Method__getitem__
(self, index)
utils.py:267
Method__getitem__
(self, index)
data_list.py:50
Method__getitem__
(self, index)
data_list.py:78
Method__getitem__
(self, index)
Continual_SFDA/continual_sfda.py:39
Method__init__
(self, num_classes, epsilon=0.1, use_gpu=True, reduction=True)
loss.py:28
Method__init__
(self, feature_dim, bottleneck_dim=256, type="ori")
network.py:63
Method__init__
(self, feature_dim, bottleneck_dim=256, type="ori")
network.py:105
Method__init__
(self, class_num, bottleneck_dim=256, type="linear")
network.py:143
Method__init__
(self)
network.py:161
Method__init__
(self, image_list, labels=None, transform=None,
train_tar_oh.py:42
Method__init__
(self, num_classes, epsilon=0.1, use_gpu=True,
utils.py:35
Method__init__
(self, image_list, labels=None, transform=None, target_transform=None, mode='RGB')
data_list.py:36
Method__init__
(self, image_list, labels=None, transform=None, target_transform=None, mode='RGB')
data_list.py:64
Method__init__
(self)
Continual_SFDA/network.py:29
Method__init__
(self, num_classes, epsilon=0.1, use_gpu=True,
Continual_SFDA/utils.py:17
Method__init__
(self, image_list, labels=None, transform=None,
Continual_SFDA/continual_sfda.py:23
Method__len__
(self)
train_tar_oh.py:69
Method__len__
(self)
utils.py:278
Method__len__
(self)
data_list.py:60
Method__len__
(self)
data_list.py:88
Method__len__
(self)
Continual_SFDA/continual_sfda.py:50
Functioncal_acc
(loader, netF, netB, netC)
utils.py:62
Functioncal_acc_
(loader, netF, netC)
utils.py:88
Functioncal_acc_proto
(loader, netF, netC,proto)
utils.py:115
Functioncalc_coeff
(iter_num, high=1.0, low=0.0, alpha=10.0, max_iter=10000.0)
network.py:11
Functiondiscrepancy
(out1, out2)
utils.py:22
Methodforward
Args: inputs: prediction matrix (before softmax) with shape (batch_size, num_classes) targets: ground truth labels wi
loss.py:36
Methodforward
(self, x,t,s=100,all_mask=False)
network.py:73
Methodforward
(self, x, t, s=100, all_mask=False)
network.py:114
Methodforward
(self, x)
network.py:153
Methodforward
(self, x, t, s=100, all_out=False)
network.py:184
Methodforward
(self, x, t, s=100,all_out=False)
Continual_SFDA/network.py:52
Functionimage_shift
(resize_size=256, crop_size=224)
utils.py:198
Functioninit_weights
(m)
network.py:14
Functionl_loader
(path)
utils.py:244
Functionl_loader
(path)
data_list.py:30
Functionl_loader
(path)
Continual_SFDA/utils.py:139
Functionrgb_loader
(path)
utils.py:238
Functionrgb_loader
(path)
data_list.py:25
Functionrgb_loader
(path)
Continual_SFDA/utils.py:133