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Functions728 in github.com/BeierZhu/xERM

⨍ Functions 728◇ Types & classes 145
Method__init__
(self, data, test_mode=False)
xERM.PC.public/data/ClassAwareSampler.py:26
Method__init__
(self, data_source, num_samples_cls=1,)
xERM.PC.public/data/ClassAwareSampler.py:67
Method__init__
(self, num_classes=1000, feat_dim=2048, use_route=False, *args)
xERM.PC.public/models/DotProductClassifier.py:22
Method__init__
(self, lambd)
xERM.PC.public/models/ResNet32Feature.py:19
Method__init__
(self, block, num_blocks)
xERM.PC.public/models/ResNet32Feature.py:76
Method__init__
(self, num_classes=1000, feat_dim=2048, use_effect=False, num_head=2, apply_gate=False, *args)
xERM.PC.public/models/TauNormClassifier.py:24
Method__init__
(self, inplanes, planes, stride=1, downsample=None)
xERM.PC.public/models/ResNextFeature.py:22
Method__init__
(self, inplanes, planes, stride=1, downsample=None, groups=1, base_width=64, is_last=False, l
xERM.PC.public/models/ResNextFeature.py:53
Method__init__
(self, num_classes=1000, feat_dim=2048, use_effect=True, num_head=2, tau=16.0, alpha=3.0, gamma=0.03125, *args
xERM.PC.public/models/CausalNormClassifier.py:9
Method__init__
(self, inplanes, planes, stride=1, downsample=None)
xERM.PC.public/models/ResNetFeature.py:28
Method__init__
(self, inplanes, planes, stride=1, downsample=None)
xERM.PC.public/models/ResNetFeature.py:59
Method__init__
(self, num_classes, img_max=None, prior=None, prior_txt=None)
xERM.PC.public/loss/PriorCELoss.py:15
Method__init__
(self, gamma=0, alpha=None, size_average=True)
xERM.PC.public/loss/FocalLoss.py:6
Method__init__
(self, num_classes=10, img_max=None, prior=None, prior_txt=None, remine_lambda=0.1)
xERM.PC.public/loss/LADELoss.py:15
Method__init__
(self, gamma=2)
xERM.PC.public/loss/xERMLoss.py:6
Method__init__
(self, config, data, test=False)
xERM.TDE.public/run_networks.py:20
Method__init__
( self, optimizer, milestones, gamma=0.1, warmup_factor=1.0 / 3,
xERM.TDE.public/utils.py:360
Method__init__
(self, logdir)
xERM.TDE.public/logger.py:15
Method__init__
(self, data, test_mode=False)
xERM.TDE.public/data/ClassPrioritySampler.py:16
Method__init__
fixed_weights: weights that wont be updated by self.update()
xERM.TDE.public/data/ClassPrioritySampler.py:37
Method__init__
xERM.TDE.public/data/ClassPrioritySampler.py:264
Method__init__
(self, root, txt, transform=None, template=None, top_k=None)
xERM.TDE.public/data/dataloader.py:69
Method__init__
fixed_weights: weights that wont be updated by self.update()
xERM.TDE.public/data/MixedPrioritizedSampler.py:15
Method__init__
xERM.TDE.public/data/MixedPrioritizedSampler.py:194
Method__init__
(self, phase, imbalance_ratio, root = '/gruntdata5/kaihua/datasets', imb_type='exp')
xERM.TDE.public/data/ImbalanceCIFAR.py:18
Method__init__
(self, data, test_mode=False)
xERM.TDE.public/data/ClassAwareSampler.py:26
Method__init__
(self, data_source, num_samples_cls=1,)
xERM.TDE.public/data/ClassAwareSampler.py:67
Method__init__
(self, num_classes=1000, feat_dim=2048, *args)
xERM.TDE.public/models/DotProductClassifier.py:22
Method__init__
(self, num_classes=10, feat_dim=128, tau=16, gamma=0.03125)
xERM.TDE.public/models/BaselineCosineClassifier.py:9
Method__init__
(self, lambd)
xERM.TDE.public/models/ResNet32Feature.py:19
Method__init__
(self, block, num_blocks)
xERM.TDE.public/models/ResNet32Feature.py:76
Method__init__
(self, num_classes=1000, feat_dim=2048, use_effect=True, num_head=2, tau=16.0, alpha=3.0, gamma=0.03125, *args
xERM.TDE.public/models/CausalNormClassifierFixWeight.py:9
Method__init__
(self, num_classes=1000, feat_dim=2048, use_effect=False, num_head=2, apply_gate=False, *args)
xERM.TDE.public/models/TauNormClassifier.py:24
Method__init__
(self, inplanes, planes, stride=1, downsample=None)
xERM.TDE.public/models/ResNextFeature.py:22
Method__init__
(self, inplanes, planes, stride=1, downsample=None, groups=1, base_width=64, is_last=False, l
xERM.TDE.public/models/ResNextFeature.py:53
Method__init__
(self, num_classes=1000, feat_dim=2048, use_effect=True, num_head=2, tau=16.0, alpha=3.0, gamma=0.03125, *args
xERM.TDE.public/models/CausalNormClassifierTrain.py:9
Method__init__
(self, lambd)
xERM.TDE.public/models/ResNet32FeatureCausal.py:21
Method__init__
(self, block, num_blocks)
xERM.TDE.public/models/ResNet32FeatureCausal.py:77
Method__init__
(self, num_classes=1000, feat_dim=2048, use_effect=True, num_head=2, tau=16.0, alpha=3.0, gamma=0.03125, *args
xERM.TDE.public/models/CausalNormClassifier.py:9
Method__init__
(self, inplanes, planes, stride=1, downsample=None)
xERM.TDE.public/models/ResNetFeature.py:28
Method__init__
(self, inplanes, planes, stride=1, downsample=None)
xERM.TDE.public/models/ResNetFeature.py:59
Method__init__
(self, gamma=0, alpha=None, size_average=True)
xERM.TDE.public/loss/FocalLoss.py:6
Method__init__
(self, gamma)
xERM.TDE.public/loss/xERM_loss.py:6
Method__iter__
(self)
xERM.RIDE.public/data_loader/imagenet_lt_data_loaders.py:20
Method__iter__
(self)
xERM.RIDE.public/data_loader/cifar_data_loaders.py:70
Method__iter__
(self)
xERM.RIDE.public/data_loader/inaturalist_data_loaders.py:20
Method__iter__
(self)
xERM.PC.public/data/ClassPrioritySampler.py:22
Method__iter__
(self)
xERM.PC.public/data/ClassPrioritySampler.py:437
Method__iter__
(self)
xERM.PC.public/data/MixedPrioritizedSampler.py:314
Method__iter__
(self)
xERM.PC.public/data/ClassAwareSampler.py:32
Method__iter__
(self)
xERM.PC.public/data/ClassAwareSampler.py:77
Method__iter__
(self)
xERM.TDE.public/data/ClassPrioritySampler.py:22
Method__iter__
(self)
xERM.TDE.public/data/ClassPrioritySampler.py:437
Method__iter__
(self)
xERM.TDE.public/data/MixedPrioritizedSampler.py:314
Method__iter__
(self)
xERM.TDE.public/data/ClassAwareSampler.py:32
Method__iter__
(self)
xERM.TDE.public/data/ClassAwareSampler.py:77
Method__len__
(self)
xERM.RIDE.public/data_loader/imagenet_lt_data_loaders.py:54
Method__len__
(self)
xERM.RIDE.public/data_loader/inaturalist_data_loaders.py:54
Method__len__
(self)
xERM.PC.public/data/ClassPrioritySampler.py:138
Method__len__
(self)
xERM.PC.public/data/ClassPrioritySampler.py:443
Method__len__
(self)
xERM.PC.public/data/dataloader.py:111
Method__len__
(self)
xERM.PC.public/data/MixedPrioritizedSampler.py:94
Method__len__
(self)
xERM.PC.public/data/MixedPrioritizedSampler.py:320
Method__len__
(self)
xERM.PC.public/data/ImbalanceCIFAR.py:113
Method__len__
(self)
xERM.PC.public/data/ClassAwareSampler.py:81
Method__len__
(self)
xERM.TDE.public/data/ClassPrioritySampler.py:138
Method__len__
(self)
xERM.TDE.public/data/ClassPrioritySampler.py:443
Method__len__
(self)
xERM.TDE.public/data/dataloader.py:102
Method__len__
(self)
xERM.TDE.public/data/MixedPrioritizedSampler.py:94
Method__len__
(self)
xERM.TDE.public/data/MixedPrioritizedSampler.py:320
Method__len__
(self)
xERM.TDE.public/data/ImbalanceCIFAR.py:102
Method__len__
(self)
xERM.TDE.public/data/ClassAwareSampler.py:81
Method__next__
(self)
xERM.PC.public/data/ClassPrioritySampler.py:25
Method__next__
(self)
xERM.PC.public/data/ClassAwareSampler.py:35
Method__next__
(self)
xERM.TDE.public/data/ClassPrioritySampler.py:25
Method__next__
(self)
xERM.TDE.public/data/ClassAwareSampler.py:35
Method_get_class_dict
(self)
xERM.PC.public/data/ImbalanceCIFAR.py:51
Method_get_class_dict
(self)
xERM.TDE.public/data/ImbalanceCIFAR.py:43
Method_hook_before_epoch
(self, epoch)
xERM.RIDE.public/model/loss.py:29
Method_hook_before_epoch
(self, epoch)
xERM.RIDE.public/model/loss.py:188
Method_hook_before_epoch
(self, epoch)
xERM.RIDE.public/model/loss.py:278
Method_hook_before_epoch
(self, epoch)
xERM.RIDE.public/model/loss.py:411
Method_hook_before_epoch
(self, epoch)
xERM.RIDE.public/model/loss.py:533
Method_hook_before_epoch
(self, epoch)
xERM.RIDE.public/model/loss.py:645
Method_hook_before_epoch
(self, epoch)
xERM.RIDE.public/model/loss.py:744
Method_hook_before_epoch
(self, epoch)
xERM.RIDE.public/model/loss.py:772
Method_hook_before_iter
(self)
xERM.RIDE.public/model/model.py:41
Method_hook_before_iter
(self)
xERM.RIDE.public/model/ldam_drw_resnets/ea_resnet_cifar.py:170
Method_hook_before_iter
(self)
xERM.RIDE.public/model/ldam_drw_resnets/resnet_cifar.py:139
Method_hook_before_iter
(self)
xERM.RIDE.public/model/ldam_drw_resnets/ride_resnet_cifar.py:154
Method_hook_before_iter
(self)
xERM.RIDE.public/model/fb_resnets/EAResNeXt.py:194
Method_hook_before_iter
(self)
xERM.RIDE.public/model/fb_resnets/RIDEResNeXt.py:166
Method_hook_before_iter
(self)
xERM.RIDE.public/model/fb_resnets/ResNet.py:192
Method_hook_before_iter
(self)
xERM.RIDE.public/model/fb_resnets/RIDEResNet.py:171
Method_hook_before_iter
(self)
xERM.RIDE.public/model/fb_resnets/EAResNet.py:192
Method_hook_before_iter
(self)
xERM.RIDE.public/model/fb_resnets/ResNeXt.py:142
Method_train_epoch
Training logic for an epoch :param epoch: Integer, current training epoch. :return: A log that contains average loss and met
xERM.RIDE.public/trainer/trainer.py:85
Function_weights_init
(m)
xERM.RIDE.public/model/ldam_drw_resnets/ea_resnet_cifar.py:33
Function_weights_init
(m)
xERM.RIDE.public/model/ldam_drw_resnets/resnet_cifar.py:33
Function_weights_init
(m)
xERM.RIDE.public/model/ldam_drw_resnets/ride_resnet_cifar.py:35
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