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Functions918 in github.com/HCPLab-SYSU/CD-FER-Benchmark

⨍ Functions 918◇ Types & classes 182
Method__init__
(self, numOfLayer, useIntraGCN=True, useInterGCN=True, useRandomMatrix=False, useAllOneMatrix=False, useCov=Fa
AGRA/ResNet.py:144
Method__init__
(self)
AGRA/ResNet.py:381
Method__init__
(self, imgs, labels, bboxs, landmarks, flag, transform=None, target_transform=None, loader=RGB_loader)
AGRA/Dataset.py:17
Method__init__
(self, inp, oup, stride, expand_ratio)
AGRA/MobileNet.py:18
Method__init__
(self, useIntraGCN=True, useInterGCN=True, useRandomMatrix=False, useAllOneMatrix=False, useCov=False, useClus
AGRA/MobileNet.py:46
Method__init__
(self, inverted_residual_setting=None, block=None)
AGRA/MobileNet.py:296
Method__init__
(self, num_features, momentum=0.1, track_running_stats=True)
SAFN/Model.py:42
Method__init__
(self, num_features, class_num=7, momentum=0.1, track_running_stats=True)
SAFN/Model.py:99
Method__init__
(self, in_features, out_features, bias=True)
SAFN/GraphConvolutionNetwork.py:26
Method__init__
(self, dim_in, dim_hid, dim_out, Link1=0.8, Link2=0.5, Link3=0.9, Link4=0.4, Link5=0.25,
SAFN/GraphConvolutionNetwork.py:164
Method__init__
(self)
SAFN/VGG.py:241
Method__init__
(self, input_dim_list=[], output_dim=1024)
SAFN/AdversarialNetwork.py:23
Method__init__
(self, num_classes=1000)
SAFN/AdversarialNetwork.py:69
Method__init__
(self, use_bottleneck=True, bottleneck_dim=256, new_cls=False, class_num=1000)
SAFN/AdversarialNetwork.py:120
Method__init__
(self, resnet_name, use_bottleneck=True, bottleneck_dim=256, new_cls=False, class_num=1000)
SAFN/AdversarialNetwork.py:176
Method__init__
(self, vgg_name, use_bottleneck=True, bottleneck_dim=256, new_cls=False, class_num=1000)
SAFN/AdversarialNetwork.py:235
Method__init__
(self)
SAFN/AdversarialNetwork.py:290
Method__init__
(self)
SAFN/AdversarialNetwork.py:328
Method__init__
(self, in_feature, hidden_size)
SAFN/AdversarialNetwork.py:364
Method__init__
(self)
SAFN/Utils.py:38
Method__init__
(self, in_channel, depth, stride)
SAFN/ResNet.py:50
Method__init__
(self, in_channel, depth, stride)
SAFN/ResNet.py:69
Method__init__
(self, numOfLayer, useIntraGCN=True, useInterGCN=True, useRandomMatrix=False, useAllOneMatrix=False, useCov=Fa
SAFN/ResNet.py:144
Method__init__
(self)
SAFN/ResNet.py:381
Method__init__
(self, imgs, labels, bboxs, landmarks, flag, transform=None, target_transform=None, loader=RGB_loader)
SAFN/Dataset.py:17
Method__init__
(self, inp, oup, stride, expand_ratio)
SAFN/MobileNet.py:18
Method__init__
(self, useIntraGCN=True, useInterGCN=True, useRandomMatrix=False, useAllOneMatrix=False, useCov=False, useClus
SAFN/MobileNet.py:46
Method__init__
(self, inverted_residual_setting=None, block=None)
SAFN/MobileNet.py:296
Method__init__
(self)
LPL/VGG.py:6
Method__init__
(self)
LPL/Utils.py:35
Method__init__
(self, in_channel, depth, stride)
LPL/ResNet.py:95
Method__init__
(self, in_channel, depth, stride)
LPL/ResNet.py:114
Method__init__
(self, numOfLayer)
LPL/ResNet.py:141
Method__init__
(self, imgs, labels, bboxs, landmarks, flag, transform=None, target_transform=None, loader=RGB_loader)
LPL/Dataset.py:17
Method__init__
(self, in_planes, out_planes, kernel_size=3, stride=1, groups=1)
LPL/MobileNet.py:6
Method__init__
(self, inp, oup, stride, expand_ratio)
LPL/MobileNet.py:15
Method__init__
(self)
SWD/VGG.py:6
Method__init__
(self)
SWD/Utils.py:35
Method__init__
(self, in_channel, depth, stride)
SWD/ResNet.py:95
Method__init__
(self, in_channel, depth, stride)
SWD/ResNet.py:114
Method__init__
(self, numOfLayer)
SWD/ResNet.py:141
Method__init__
(self, imgs, labels, bboxs, landmarks, flag, transform=None, target_transform=None, loader=RGB_loader)
SWD/Dataset.py:17
Method__init__
(self, in_planes, out_planes, kernel_size=3, stride=1, groups=1)
SWD/MobileNet.py:6
Method__init__
(self, inp, oup, stride, expand_ratio)
SWD/MobileNet.py:15
Method__init__
(self)
ICID/VGG.py:6
Method__init__
(self)
ICID/Utils.py:35
Method__init__
(self, in_channel, depth, stride)
ICID/ResNet.py:95
Method__init__
(self, in_channel, depth, stride)
ICID/ResNet.py:114
Method__init__
(self, numOfLayer)
ICID/ResNet.py:141
Method__init__
(self, imgs, labels, bboxs, landmarks, flag, transform=None, target_transform=None, loader=RGB_loader)
ICID/Dataset.py:17
Method__init__
(self, in_planes, out_planes, kernel_size=3, stride=1, groups=1)
ICID/MobileNet.py:6
Method__init__
(self, inp, oup, stride, expand_ratio)
ICID/MobileNet.py:15
Method__init__
(self)
DETN/VGG.py:6
Method__init__
(self)
DETN/Utils.py:35
Method__init__
(self, in_channel, depth, stride)
DETN/ResNet.py:47
Method__init__
(self, in_channel, depth, stride)
DETN/ResNet.py:66
Method__init__
(self, num_features, momentum=0.1, track_running_stats=True)
DETN/ResNet.py:141
Method__init__
(self, num_features, momentum=0.1, track_running_stats=True)
DETN/ResNet.py:175
Method__init__
(self, num_features, class_num=7, momentum=0.1, track_running_stats=True)
DETN/ResNet.py:232
Method__init__
(self, numOfLayer)
DETN/ResNet.py:295
Method__init__
(self, numOfLayer)
DETN/ResNet.py:420
Method__init__
(self, imgs, labels, bboxs, landmarks, flag, transform=None, target_transform=None, loader=RGB_loader)
DETN/Dataset.py:17
Method__init__
(self, in_planes, out_planes, kernel_size=3, stride=1, groups=1)
DETN/MobileNet.py:6
Method__init__
(self, inp, oup, stride, expand_ratio)
DETN/MobileNet.py:15
Method__init__
(self, num_features, momentum=0.1, track_running_stats=True)
CADA/Model.py:42
Method__init__
(self, num_features, class_num=7, momentum=0.1, track_running_stats=True)
CADA/Model.py:99
Method__init__
(self, in_features, out_features, bias=True)
CADA/GraphConvolutionNetwork.py:26
Method__init__
(self, dim_in, dim_hid, dim_out, Link1=0.8, Link2=0.5, Link3=0.9, Link4=0.4, Link5=0.25,
CADA/GraphConvolutionNetwork.py:164
Method__init__
(self)
CADA/VGG.py:241
Method__init__
(self, input_dim_list=[], output_dim=1024)
CADA/AdversarialNetwork.py:23
Method__init__
(self, num_classes=1000)
CADA/AdversarialNetwork.py:69
Method__init__
(self, use_bottleneck=True, bottleneck_dim=256, new_cls=False, class_num=1000)
CADA/AdversarialNetwork.py:120
Method__init__
(self, resnet_name, use_bottleneck=True, bottleneck_dim=256, new_cls=False, class_num=1000)
CADA/AdversarialNetwork.py:176
Method__init__
(self, vgg_name, use_bottleneck=True, bottleneck_dim=256, new_cls=False, class_num=1000)
CADA/AdversarialNetwork.py:235
Method__init__
(self)
CADA/AdversarialNetwork.py:290
Method__init__
(self)
CADA/AdversarialNetwork.py:328
Method__init__
(self, in_feature, hidden_size)
CADA/AdversarialNetwork.py:364
Method__init__
(self)
CADA/Utils.py:38
Method__init__
(self, in_channel, depth, stride)
CADA/ResNet.py:50
Method__init__
(self, in_channel, depth, stride)
CADA/ResNet.py:69
Method__init__
(self, numOfLayer, useIntraGCN=True, useInterGCN=True, useRandomMatrix=False, useAllOneMatrix=False, useCov=Fa
CADA/ResNet.py:144
Method__init__
(self)
CADA/ResNet.py:381
Method__init__
(self, imgs, labels, bboxs, landmarks, flag, transform=None, target_transform=None, loader=RGB_loader)
CADA/Dataset.py:17
Method__init__
(self, inp, oup, stride, expand_ratio)
CADA/MobileNet.py:18
Method__init__
(self, useIntraGCN=True, useInterGCN=True, useRandomMatrix=False, useAllOneMatrix=False, useCov=False, useClus
CADA/MobileNet.py:46
Method__init__
(self, inverted_residual_setting=None, block=None)
CADA/MobileNet.py:296
Method__init__
(self)
DFA/VGG.py:6
Method__init__
(self)
DFA/Utils.py:35
Method__init__
(self, in_channel, depth, stride)
DFA/ResNet.py:95
Method__init__
(self, in_channel, depth, stride)
DFA/ResNet.py:114
Method__init__
(self, numOfLayer)
DFA/ResNet.py:141
Method__init__
(self, imgs, labels, bboxs, landmarks, flag, transform=None, target_transform=None, loader=RGB_loader)
DFA/Dataset.py:17
Method__init__
(self, in_planes, out_planes, kernel_size=3, stride=1, groups=1)
DFA/MobileNet.py:6
Method__init__
(self, inp, oup, stride, expand_ratio)
DFA/MobileNet.py:15
Method__len__
(self)
ECAN/Dataset.py:100
Method__len__
(self)
FTDNN/Dataset.py:171
Method__len__
(self)
AGRA/Dataset.py:100
Method__len__
(self)
SAFN/Dataset.py:100
Method__len__
(self)
LPL/Dataset.py:100
Method__len__
(self)
SWD/Dataset.py:100
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