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Functions180 in github.com/Albert0147/AaD_SFDA

⨍ Functions 180◇ Types & classes 22
↓ 1 callersFunctiontest_target_srconly
(args)
oda/image_multisource.py:107
↓ 1 callersFunctiontrain_source
(args)
src_pretrain.py:135
↓ 1 callersFunctiontrain_source
(args)
office-home/train_src.py:40
↓ 1 callersFunctiontrain_source
(args)
office-home/office31_src.py:27
↓ 1 callersFunctiontrain_source
(args)
oda/image_source.py:185
↓ 1 callersFunctiontrain_target
(args)
tar_adaptation.py:214
↓ 1 callersFunctiontrain_target
(args)
oda/image_pretrained.py:98
↓ 1 callersFunctiontrain_target
(args)
oda/image_multitarget.py:117
↓ 1 callersFunctiontrain_target
(args)
oda/image_target_oda.py:145
↓ 1 callersFunctiontrain_target
(args)
oda/image_target.py:124
↓ 1 callersFunctiontrain_target
(args)
oda/tar_open.py:146
↓ 1 callersFunctiontrain_target_decay
(args)
office-home/train_tar.py:166
↓ 1 callersFunctiontrain_target_near1
(args)
office-home/office31_tar.py:223
FunctionCDAN
(input_list, ad_net, entropy=None, coeff=None, random_layer=None)
oda/loss.py:21
FunctionDANN
(features, ad_net)
oda/loss.py:47
FunctionEntropy
(input_)
tar_adaptation.py:18
FunctionEntropy
(input_)
office-home/train_tar.py:22
FunctionEntropy
(input_)
oda/loss.py:9
Method__getitem__
(self, index)
data_list.py:50
Method__getitem__
(self, index)
data_list.py:78
Method__getitem__
(self, index)
office-home/office31_tar.py:59
Method__getitem__
(self, index)
office-home/utils.py:221
Method__getitem__
(self, index)
office-home/train_tar.py:67
Method__getitem__
(self, index)
oda/data_list.py:63
Method__getitem__
(self, index)
oda/data_list.py:100
Method__init__
(self, num_classes, epsilon=0.1, use_gpu=True, reduction=True)
loss.py:20
Method__init__
(self, feature_dim, bottleneck_dim=256, type="ori")
network.py:62
Method__init__
(self, class_num, bottleneck_dim=256, type="linear")
network.py:82
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, class_num, bottleneck_dim=256, type="linear")
office-home/network.py:34
Method__init__
( self, image_list, labels=None, transform=None, target_transform=None, mode="RGB" )
office-home/office31_tar.py:46
Method__init__
(self, num_classes, epsilon=0.1, use_gpu=True, size_average=True)
office-home/utils.py:17
Method__init__
(self, num_classes, epsilon=0.1, use_gpu=True, size_average=True)
office-home/utils.py:47
Method__init__
( self, image_list, labels=None, transform=None, target_transform=None, mode="RGB" )
office-home/train_tar.py:54
Method__init__
(self, num_classes, epsilon=0.1, use_gpu=True, reduction=True)
oda/loss.py:64
Method__init__
(self, vgg_name)
oda/network.py:29
Method__init__
(self, res_name)
oda/network.py:48
Method__init__
(self, feature_dim, bottleneck_dim=256, type="ori")
oda/network.py:76
Method__init__
(self, class_num, bottleneck_dim=256, type="linear")
oda/network.py:92
Method__init__
(self, class_num, input_dim, bottleneck_dim=256)
oda/network.py:107
Method__init__
(self, image_list, labels=None, transform=None,
oda/data_list.py:42
Method__init__
(self, image_list, labels=None, transform=None,
oda/data_list.py:79
Method__len__
(self)
data_list.py:60
Method__len__
(self)
data_list.py:88
Method__len__
(self)
office-home/office31_tar.py:70
Method__len__
(self)
office-home/utils.py:232
Method__len__
(self)
office-home/train_tar.py:78
Method__len__
(self)
oda/data_list.py:73
Method__len__
(self)
oda/data_list.py:110
Functioncalc_coeff
(iter_num, high=1.0, low=0.0, alpha=10.0, max_iter=10000.0)
network.py:11
Functioncalc_coeff
(iter_num, high=1.0, low=0.0, alpha=10.0, max_iter=10000.0)
oda/network.py:11
Methodforward
Args: inputs: prediction matrix (before softmax) with shape (batch_size, num_classes) targets: ground truth labels wi
loss.py:28
Methodforward
(self, x)
network.py:46
Methodforward
(self, x)
network.py:71
Methodforward
(self, x)
network.py:92
Methodforward
(self, x)
office-home/network.py:43
Methodforward
(self, inputs, targets)
office-home/utils.py:55
Methodforward
(self, x)
oda/network.py:38
Methodforward
(self, x)
oda/network.py:62
Methodforward
(self, x)
oda/network.py:85
Methodforward
(self, x)
oda/network.py:102
Methodforward
(self, x)
oda/network.py:115
Methodforward
(self, x)
oda/network.py:136
Functionfun1
(grad)
oda/loss.py:17
Functionhyper_decay
(x, beta=-2, alpha=1)
tar_adaptation.py:209
Functionhyper_decay
(x, beta=-5, alpha=1)
office-home/train_tar.py:161
Functionimage_shift
(resize_size=256, crop_size=224)
office-home/utils.py:136
Functionimage_train
(resize_size=256, crop_size=224, alexnet=False)
oda/image_multisource.py:17
Functioninit_weights
(m)
network.py:14
Functioninit_weights
(m)
office-home/network.py:15
Functioninit_weights
(m)
oda/network.py:14
Functionl_loader
(path)
data_list.py:30
Functionl_loader
(path)
office-home/utils.py:201
Functionl_loader
(path)
oda/data_list.py:34
Functionlr_scheduler
(optimizer, iter_num, max_iter, gamma=10, power=0.75)
office-home/office31_tar.py:35
Functionrgb_loader
(path)
data_list.py:25
Functionrgb_loader
(path)
office-home/utils.py:195
Functionrgb_loader
(path)
oda/data_list.py:28
Functiontest_and_nd
(step, dataset_test, name, G, C)
snd.py:22
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