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Functions728 in github.com/BeierZhu/xERM

⨍ Functions 728◇ Types & classes 145
↓ 90 callersMethodsize
(self)
xERM.PC.public/data/ClassPrioritySampler.py:131
↓ 45 callersMethodto
(self, device)
xERM.RIDE.public/model/loss.py:83
↓ 31 callersMethodsize
(self)
xERM.TDE.public/data/ClassPrioritySampler.py:131
↓ 26 callersMethodmax
(self)
xERM.PC.public/data/ClassPrioritySampler.py:199
↓ 24 callersMethodeval
(self, phase='val', save_feat=False)
xERM.PC.public/run_networks.py:979
↓ 24 callersMethodupdate
(self, val, n=1)
xERM.RIDE.public/utils/util.py:122
↓ 21 callersMethodupdate
(self, val, n=1)
xERM.PC.public/utils.py:383
↓ 20 callersMethodupdate
(self, val, n=1)
xERM.TDE.public/utils.py:39
↓ 14 callersMethodmax
(self)
xERM.TDE.public/data/ClassPrioritySampler.py:199
↓ 13 callersMethod__init__
(self, num_classes, backbone_class=None)
xERM.RIDE.public/model/model.py:18
↓ 13 callersFunctionprint_write
(print_str, log_file)
xERM.PC.public/utils.py:55
↓ 13 callersFunctionprint_write
(print_str, log_file)
xERM.TDE.public/utils.py:75
↓ 12 callersMethodinit_obj
Finds a function handle with the name given as 'type' in config, and returns the instance initialized with corresponding arguments gi
xERM.RIDE.public/parse_config.py:88
↓ 10 callersMethod__init__
(self, T)
xERM.RIDE.public/model/loss.py:126
↓ 9 callersFunctionprint_w
(print_str, log_file)
xERM.PC.public/utils.py:29
↓ 9 callersFunctionshot_acc
(preds, labels, train_data, many_shot_thr=100, low_shot_thr=20, acc_per_cls=False)
xERM.PC.public/utils.py:82
↓ 9 callersFunctionshot_acc
(preds, labels, train_data, many_shot_thr=100, low_shot_thr=20, acc_per_cls=False)
xERM.TDE.public/utils.py:109
↓ 8 callersMethodeval
(self, phase='val', save_feat=False)
xERM.TDE.public/run_networks.py:848
↓ 8 callersFunctioninit_weights
Initialize weights
xERM.PC.public/utils.py:62
↓ 8 callersFunctionload_state_dict
(model, state_dict, no_ignore=False)
xERM.RIDE.public/utils/util.py:41
↓ 8 callersMethodpointer_to_treeidx
(self, pointer)
xERM.PC.public/data/ClassPrioritySampler.py:141
↓ 8 callersMethodpointer_to_treeidx
(self, pointer)
xERM.TDE.public/data/ClassPrioritySampler.py:141
↓ 8 callersFunctionprint_w
(print_str, log_file)
xERM.TDE.public/utils.py:82
↓ 7 callersFunctioninit_weights
Initialize weights
xERM.TDE.public/utils.py:89
↓ 6 callersMethod_hook_before_epoch
(self, epoch)
xERM.RIDE.public/model/loss.py:93
↓ 6 callersFunctionsource_import
This function imports python module directly from source code using importlib
xERM.PC.public/utils.py:36
↓ 6 callersFunctionsource_import
This function imports python module directly from source code using importlib
xERM.TDE.public/utils.py:56
↓ 5 callersMethod_make_layer
(self, block, planes, blocks, stride=1)
xERM.RIDE.public/model/fb_resnets/RIDEResNet.py:183
↓ 5 callersMethod_make_layer
(self, block, planes, blocks, stride=1)
xERM.RIDE.public/model/fb_resnets/EAResNet.py:204
↓ 5 callersMethodpointer_to_treeidx
(self, pointer)
xERM.PC.public/data/MixedPrioritizedSampler.py:97
↓ 5 callersMethodpointer_to_treeidx
(self, pointer)
xERM.TDE.public/data/MixedPrioritizedSampler.py:97
↓ 5 callersMethodupdate
(self, pointer, priority)
xERM.TDE.public/data/ClassPrioritySampler.py:145
↓ 4 callersMethod_make_layer
(self, block, planes, blocks, stride=1, is_last=False)
xERM.RIDE.public/model/fb_resnets/EAResNeXt.py:206
↓ 4 callersMethod_make_layer
(self, block, planes, blocks, stride=1, is_last=False)
xERM.RIDE.public/model/fb_resnets/RIDEResNeXt.py:178
↓ 4 callersMethod_make_layer
(self, block, planes, blocks, stride=1)
xERM.RIDE.public/model/fb_resnets/ResNet.py:204
↓ 4 callersMethod_make_layer
(self, block, planes, blocks, stride=1, is_last=False)
xERM.RIDE.public/model/fb_resnets/ResNeXt.py:154
↓ 4 callersMethod_make_layer
(self, block, planes, blocks, stride=1, is_last=False, last_relu=True)
xERM.PC.public/models/ResNextFeature.py:136
↓ 4 callersMethod_make_layer
(self, block, planes, blocks, stride=1)
xERM.PC.public/models/ResNetFeature.py:129
↓ 4 callersMethod_make_layer
(self, block, planes, blocks, stride=1, is_last=False, last_relu=True)
xERM.TDE.public/models/ResNextFeature.py:136
↓ 4 callersMethod_make_layer
(self, block, planes, blocks, stride=1)
xERM.TDE.public/models/ResNetFeature.py:129
↓ 4 callersMethodbatch_forward
This is a general single batch running function.
xERM.PC.public/run_networks.py:208
↓ 4 callersMethodload_model
(self, exp_dir=None)
xERM.PC.public/run_networks.py:1111
↓ 4 callersMethodload_model
(self, model_dir=None)
xERM.TDE.public/run_networks.py:958
↓ 4 callersFunctionparallel
(key)
xERM.RIDE.public/t-normalization.py:31
↓ 4 callersMethodresult
(self)
xERM.RIDE.public/utils/util.py:104
↓ 4 callersFunctionshot_acc
(preds, labels, train_data, many_shot_thr=100, low_shot_thr=20, acc_per_cls=False)
xERM.RIDE.public/utils/util.py:131
↓ 4 callersFunctiontorch2numpy
(x)
xERM.PC.public/utils.py:157
↓ 4 callersFunctiontorch2numpy
(x)
xERM.TDE.public/utils.py:216
↓ 4 callersMethodupdate
(self, pointer, priority)
xERM.PC.public/data/ClassPrioritySampler.py:145
↓ 3 callersMethod__init__
(self, buckets, retain_epoch_size=False)
xERM.RIDE.public/data_loader/cifar_data_loaders.py:61
↓ 3 callersMethod__init__
(self, block, num_blocks, num_experts, num_classes=10, reduce_dimension=False, layer2_output_dim=None, layer3_
xERM.RIDE.public/model/ldam_drw_resnets/ea_resnet_cifar.py:97
↓ 3 callersMethod__init__
(self, block, num_blocks, num_classes=10, reduce_dimension=False, layer2_output_dim=None, layer3_output_dim=No
xERM.RIDE.public/model/ldam_drw_resnets/resnet_cifar.py:97
↓ 3 callersMethod__init__
(self, block, num_blocks, num_experts, num_classes=10, reduce_dimension=False, layer2_output_dim=None, layer3_
xERM.RIDE.public/model/ldam_drw_resnets/ride_resnet_cifar.py:99
↓ 3 callersMethod__init__
(self, block, layers, num_experts, groups=1, width_per_group=64, dropout=None, num_classes=1000, use_norm=Fals
xERM.RIDE.public/model/fb_resnets/EAResNeXt.py:111
↓ 3 callersMethod__init__
(self, block, layers, num_experts, groups=1, width_per_group=64, dropout=None, num_classes=1000, use_norm=Fals
xERM.RIDE.public/model/fb_resnets/RIDEResNeXt.py:106
↓ 3 callersMethod__init__
(self, block, layers, dropout=None, num_classes=1000, use_norm=False, reduce_dimension=False, layer3_output_di
xERM.RIDE.public/model/fb_resnets/ResNet.py:112
↓ 3 callersMethod__init__
(self, block, layers, num_experts, dropout=None, num_classes=1000, use_norm=False, reduce_dimension=False, lay
xERM.RIDE.public/model/fb_resnets/RIDEResNet.py:110
↓ 3 callersMethod__init__
(self, block, layers, num_experts, dropout=None, num_classes=1000, use_norm=False, reduce_dimension=False, lay
xERM.RIDE.public/model/fb_resnets/EAResNet.py:108
↓ 3 callersMethod_make_layer
(self, block, planes, num_blocks, stride)
xERM.RIDE.public/model/ldam_drw_resnets/ea_resnet_cifar.py:160
↓ 3 callersMethod_make_layer
(self, block, planes, num_blocks, stride)
xERM.RIDE.public/model/ldam_drw_resnets/resnet_cifar.py:130
↓ 3 callersMethod_make_layer
(self, block, planes, num_blocks, stride)
xERM.RIDE.public/model/ldam_drw_resnets/ride_resnet_cifar.py:144
↓ 3 callersMethod_make_layer
(self, block, planes, num_blocks, stride, add_flag=True)
xERM.PC.public/models/ResNet32Feature.py:109
↓ 3 callersMethod_make_layer
(self, block, planes, num_blocks, stride, add_flag=True)
xERM.TDE.public/models/ResNet32Feature.py:109
↓ 3 callersMethod_make_layer
(self, block, planes, num_blocks, stride, add_flag=True)
xERM.TDE.public/models/ResNet32FeatureCausal.py:111
↓ 3 callersMethod_separate_part
(self, x, ind)
xERM.RIDE.public/model/ldam_drw_resnets/ea_resnet_cifar.py:182
↓ 3 callersMethod_separate_part
(self, x, ind)
xERM.RIDE.public/model/fb_resnets/EAResNeXt.py:226
↓ 3 callersMethod_separate_part
(self, x, ind)
xERM.RIDE.public/model/fb_resnets/EAResNet.py:221
↓ 3 callersMethodbatch_forward
This is a general single batch running function.
xERM.TDE.public/run_networks.py:184
↓ 3 callersMethodget_img_num_per_cls
(self, cls_num, imb_type, imb_factor, reverse=False)
xERM.PC.public/data/ImbalanceCIFAR.py:61
↓ 3 callersMethodget_logger
(self, name, verbosity=2)
xERM.RIDE.public/parse_config.py:123
↓ 3 callersFunctionmic_acc_cal
(preds, labels)
xERM.PC.public/utils.py:133
↓ 3 callersFunctionmic_acc_cal
(preds, labels)
xERM.TDE.public/utils.py:192
↓ 3 callersMethodmulti_head_call
(self, func, x, weight=None)
xERM.PC.public/models/CausalNormClassifier.py:54
↓ 3 callersMethodmulti_head_call
(self, func, x, weight=None)
xERM.TDE.public/models/CausalNormClassifierFixWeight.py:54
↓ 3 callersMethodmulti_head_call
(self, func, x, weight=None)
xERM.TDE.public/models/CausalNormClassifierTrain.py:55
↓ 3 callersMethodmulti_head_call
(self, func, x, weight=None)
xERM.TDE.public/models/CausalNormClassifier.py:55
↓ 3 callersFunctionread_json
(fname)
xERM.RIDE.public/utils/util.py:67
↓ 3 callersFunctionrename_parallel_state_dict
(state_dict)
xERM.RIDE.public/utils/util.py:29
↓ 3 callersMethodreset
(self)
xERM.RIDE.public/utils/util.py:114
↓ 3 callersFunctionshot_precision
(preds, labels, train_data, many_shot_thr=100, low_shot_thr=20, acc_per_cls=False)
xERM.PC.public/utils.py:392
↓ 3 callersMethodstore_logits
(self, phase)
xERM.PC.public/run_networks.py:948
↓ 3 callersMethodupdate_whole
Update the whole tree based on per-example sampling weights
xERM.PC.public/data/ClassPrioritySampler.py:90
↓ 3 callersMethodupdate_whole
Update the whole tree based on per-example sampling weights
xERM.TDE.public/data/ClassPrioritySampler.py:90
↓ 3 callersMethodxERM_eval
(self, phase='test')
xERM.PC.public/run_networks.py:535
↓ 2 callersMethod__init__
(self, block, layers, groups=1, width_per_group=64, dropout=None, num_classes=1000, reduce_dimension=False, la
xERM.RIDE.public/model/fb_resnets/ResNeXt.py:94
↓ 2 callersMethod__init__
(self, in_planes, planes, stride=1, option="A")
xERM.PC.public/models/ResNet32Feature.py:30
↓ 2 callersMethod__init__
(self, block, layers, groups=1, width_per_group=64, use_fc=False, dropout=None, use_glore=Fal
xERM.PC.public/models/ResNextFeature.py:97
↓ 2 callersMethod__init__
(self, block, layers, use_fc=False, dropout=None)
xERM.PC.public/models/ResNetFeature.py:96
↓ 2 callersMethod__init__
(self, in_planes, planes, stride=1, option="A")
xERM.TDE.public/models/ResNet32Feature.py:30
↓ 2 callersMethod__init__
(self, block, layers, groups=1, width_per_group=64, use_fc=False, dropout=None, use_glore=Fal
xERM.TDE.public/models/ResNextFeature.py:97
↓ 2 callersMethod__init__
(self, in_planes, planes, stride=1, option="A")
xERM.TDE.public/models/ResNet32FeatureCausal.py:31
↓ 2 callersMethod__init__
(self, block, layers, use_fc=False, dropout=None)
xERM.TDE.public/models/ResNetFeature.py:96
↓ 2 callersMethod_hook_before_iter
(self)
xERM.RIDE.public/model/model.py:23
↓ 2 callersMethod_save_checkpoint
Saving checkpoints :param epoch: current epoch number :param log: logging information of the epoch :param save_best:
xERM.RIDE.public/base/base_trainer.py:133
↓ 2 callersMethodbroadcast
(self, per_cls_info)
xERM.PC.public/data/ClassPrioritySampler.py:385
↓ 2 callersMethodbroadcast
(self, per_cls_info)
xERM.TDE.public/data/ClassPrioritySampler.py:385
↓ 2 callersFunctioncalculate_prior
(num_classes, img_max=None, prior=None, prior_txt=None, reverse=False, return_num=False)
xERM.PC.public/utils.py:345
↓ 2 callersFunctionconv3x3
3x3 convolution with padding
xERM.RIDE.public/model/fb_resnets/EAResNeXt.py:21
↓ 2 callersFunctionconv3x3
3x3 convolution with padding
xERM.RIDE.public/model/fb_resnets/RIDEResNeXt.py:16
↓ 2 callersFunctionconv3x3
3x3 convolution with padding
xERM.RIDE.public/model/fb_resnets/ResNet.py:24
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