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Functions330 in github.com/WenkeHuang/FCCL

⨍ Functions 330◇ Types & classes 66
↓ 15 callersFunctiondata_path
()
fccl+/utils/conf.py:9
↓ 15 callersMethodtrain
(self, mode=True)
fccl/Idea/_base.py:12
↓ 14 callersFunctionget_dataloader
(dataset, datadir, train_bs, test_bs, dataidxs=None, noise_level=0,num_workers=4)
fccl/Dataset/utils_dataset.py:97
↓ 12 callersFunctionmkdirs
(dirpath)
fccl/Idea/utils_idea.py:27
↓ 10 callersFunctioncreate_if_not_exists
(path: str)
fccl+/utils/util.py:8
↓ 7 callersFunctionadd_management_args
(parser: ArgumentParser)
fccl+/utils/args.py:37
↓ 6 callersFunctionadd_experiment_args
Adds the arguments used by all the models. :param parser: the parser instance
fccl+/utils/args.py:7
↓ 6 callersMethodaggregate_nets
(self, freq=None)
fccl+/models/utils/federated_model.py:50
↓ 6 callersMethodget_imagedata_info
(self, data)
fccl+/datasets/market1501.py:37
↓ 6 callersFunctioninit_nets
(n_parties,nets_name_list)
fccl/Network/utils_network.py:5
↓ 6 callersFunctionswish
(x)
fccl+/backbone/efficientnet.py:6
↓ 5 callersFunctionargs_parser
()
fccl/Idea/params.py:3
↓ 4 callersMethod_make_layer
(self, block, planes, num_blocks, stride)
fccl/Network/resnet.py:85
↓ 4 callersMethod_make_layer
Instantiates a ResNet layer. :param block: ResNet basic block :param planes: channels across the network :param num_b
fccl+/backbone/ResNet.py:101
↓ 4 callersFunctionevaluate_network
(network,dataloader,logger)
fccl/Idea/utils_idea.py:86
↓ 4 callersMethodfeatures
(self, x: torch.Tensor)
fccl+/backbone/ResNet.py:118
↓ 4 callersFunctioninit_logs
(log_level=logging.INFO,log_path = Project_Path+'Logs/',sub_name=None)
fccl/Dataset/utils_dataset.py:18
↓ 4 callersFunctionrandom_loaders
(train_dataset: datasets, setting: PublicDataset)
fccl+/datasets/utils/public_dataset.py:70
↓ 4 callersFunctionresnet12
Instantiates a ResNet18 network. :param nclasses: number of output classes :param nf: number of filters :return: ResNet network
fccl+/backbone/ResNet.py:155
↓ 4 callersFunctionswish
(x)
fccl/Network/efficientnet.py:6
↓ 3 callersMethod_make_layer
(self, out_planes, num_blocks, groups)
fccl/Network/shufflenet.py:86
↓ 3 callersMethod_make_layer
(self, out_planes, num_blocks, groups)
fccl+/backbone/shufflenet.py:86
↓ 3 callersMethod_process_dir
(self, dir_path, relabel=False)
fccl+/datasets/market1501.py:143
↓ 3 callersFunctionconv3x3
Instantiates a 3x3 convolutional layer with no bias. :param in_planes: number of input channels :param out_planes: number of output chann
fccl+/backbone/ResNet.py:8
↓ 3 callersMethodcopy_nets2_prevnets
(self)
fccl+/models/utils/federated_model.py:117
↓ 3 callersFunctionevaluate_network
(net,dataloader)
fccl/Network/train_network.py:63
↓ 3 callersFunctionget_all_models
()
fccl+/models/__init__.py:9
↓ 3 callersMethodget_data_loaders
(self, selected_domain_list=[])
fccl+/datasets/digits.py:95
↓ 3 callersFunctionpartition_office_domain_skew_loaders
(train_datasets: list, test_datasets: list, setting: FederatedDataset
fccl+/datasets/utils/federated_dataset.py:183
↓ 2 callersFunctionEfficientNetB0
(num_classes=10)
fccl/Network/efficientnet.py:148
↓ 2 callersFunctionResNet10
(num_classes=10)
fccl/Network/resnet.py:104
↓ 2 callersFunctionResNet12
(num_classes=10)
fccl/Network/resnet.py:108
↓ 2 callersFunctionShuffleNetG2
()
fccl/Network/shufflenet.py:103
↓ 2 callersMethod__init__
(self, in_planes, out_planes, stride, groups)
fccl/Network/shufflenet.py:22
↓ 2 callersMethod__init__
(self, in_channels, se_channels)
fccl/Network/efficientnet.py:22
↓ 2 callersMethod__init__
(self, block, num_blocks, num_classes=10)
fccl/Network/resnet.py:72
↓ 2 callersMethod__init__
(self, in_planes, out_planes, stride, groups)
fccl+/backbone/shufflenet.py:22
↓ 2 callersMethod__init__
(self, in_channels, se_channels)
fccl+/backbone/efficientnet.py:22
↓ 2 callersMethod_evaluate_net
(self,index,net, test_dl)
fccl+/models/fccl.py:184
↓ 2 callersMethod_write_all_acc
(self,all_path,all_acc_list)
fccl+/utils/logger.py:124
↓ 2 callersMethod_write_mean_acc
(self,mean_path,mean_acc_list)
fccl+/utils/logger.py:98
↓ 2 callersMethodcol_update
(self, communication_idx,publoader)
fccl+/models/fccl.py:57
↓ 2 callersFunctionevaluate_network_generalization
(network,dataloader_list,particiapnt_index,logger)
fccl/Idea/utils_idea.py:113
↓ 2 callersFunctiongenerate_public_data_idxs
(dataset,datadir,size,epoch=None)
fccl/Dataset/utils_dataset.py:77
↓ 2 callersFunctionget_all_models
()
fccl+/datasets/__init__.py:9
↓ 2 callersMethodget_backbone
(parti_num, names_list)
fccl+/datasets/digits.py:145
↓ 2 callersMethodget_normalization_transform
()
fccl+/datasets/digits.py:158
↓ 2 callersMethodload_pretrained_nets
(self)
fccl+/models/utils/federated_model.py:108
↓ 2 callersMethodloc_update
(self, priloader_list)
fccl+/models/moon.py:37
↓ 2 callersFunctionpretrain_network
(epoch,net,data_loader,loss_function,optimizer_name,learning_rate)
fccl/Network/train_network.py:34
↓ 2 callersFunctiontsne_network
(net,dataloader,model_name,classes)
fccl/Network/train_network.py:78
↓ 1 callersMethodConstruct_Participant_Dataset
(self)
fccl/Dataset/init_dataset.py:22
↓ 1 callersMethodConstruct_Participant_Dataset
(self)
fccl/Dataset/init_dataset.py:55
↓ 1 callersMethodConstruct_Participant_Dataset
(self)
fccl/Dataset/init_dataset.py:88
↓ 1 callersMethodConstruct_Participant_Dataset
(self)
fccl/Dataset/init_dataset.py:122
↓ 1 callersMethodConstruct_Participant_Dataset
(self)
fccl/Dataset/init_dataset.py:155
↓ 1 callersMethodConstruct_Participant_Dataset
(self)
fccl/Dataset/init_dataset.py:188
↓ 1 callersMethodConstruct_Participant_Dataset
(self)
fccl+/datasets/fashion_mnist.py:23
↓ 1 callersMethod__build_truncated_dataset__
(self)
fccl+/datasets/digits.py:26
↓ 1 callersMethod__init__
(self, student)
fccl/Idea/_base.py:44
↓ 1 callersMethod__init__
(self, in_planes, out_planes, expansion, stride)
fccl/Network/mobilnet_v2.py:12
↓ 1 callersMethod__init__
(self, in_planes, n1x1, n3x3red, n3x3, n5x5red, n5x5, pool_planes)
fccl/Network/googlenet.py:8
↓ 1 callersMethod__init__
(self, in_planes, out_planes, expansion, stride)
fccl+/backbone/mobilnet_v2.py:12
↓ 1 callersMethod__init__
Instantiates the layers of the network. :param block: the basic ResNet block :param num_blocks: the number of blocks per laye
fccl+/backbone/ResNet.py:64
↓ 1 callersMethod__init__
(self, in_planes, n1x1, n3x3red, n3x3, n5x5red, n5x5, pool_planes)
fccl+/backbone/googlenet.py:8
↓ 1 callersMethod__init__
(self, root: str, train: bool=True, transform: transforms=None, target_transform: transforms=N
fccl+/datasets/tinyimagenet.py:15
↓ 1 callersMethod_calculate_isd_sim
(self, features)
fccl+/models/fcclplus.py:120
↓ 1 callersMethod_check_before_run
Check if all files are available before going deeper
fccl+/datasets/market1501.py:132
↓ 1 callersMethod_draw_heatmap
(self,data,model_name,communication_idx,net_idx)
fccl+/models/fccl.py:211
↓ 1 callersMethod_make_layers
(self, in_planes)
fccl/Network/mobilnet_v2.py:59
↓ 1 callersMethod_make_layers
(self, in_channels)
fccl/Network/efficientnet.py:115
↓ 1 callersMethod_make_layers
(self, in_planes)
fccl+/backbone/mobilnet_v2.py:65
↓ 1 callersMethod_make_layers
(self, in_channels)
fccl+/backbone/efficientnet.py:120
↓ 1 callersMethod_model_folder_path
(self)
fccl+/utils/logger.py:18
↓ 1 callersMethod_off_diagonal
(self,x)
fccl+/models/fccl.py:206
↓ 1 callersMethod_off_diagonal
(self, x)
fccl+/models/fcclplus.py:180
↓ 1 callersMethod_pretrain_intra_nets
(self)
fccl+/models/fccl.py:143
↓ 1 callersMethod_pretrain_net
(self,index,net,train_loader,epoch,test_loader)
fccl+/models/fccl.py:161
↓ 1 callersMethod_train_net
(self, index, net, train_loader)
fccl+/models/fedavg.py:39
↓ 1 callersMethod_train_net
(self, index, net, prev_net, train_loader)
fccl+/models/moon.py:45
↓ 1 callersMethod_train_net
(self, index, net, train_loader)
fccl+/models/feddf.py:78
↓ 1 callersMethod_train_net
(self,index,net,inter_net,intra_net,train_loader)
fccl+/models/fccl.py:115
↓ 1 callersMethod_train_net
(self,index,net,train_loader)
fccl+/models/fedprox.py:39
↓ 1 callersMethod_train_net
(self, index, net, inter_net, train_loader)
fccl+/models/fcclplus.py:142
↓ 1 callersMethod_write_args
(self)
fccl+/utils/logger.py:50
↓ 1 callersFunctionadapt_single
(image,net)
fccl/Idea/utils_idea.py:41
↓ 1 callersFunctionbase_path
Returns the base bath where to log accuracies and tensorboard data.
fccl+/utils/conf.py:13
↓ 1 callersFunctioncheckpoint_path
Returns the base bath where to log accuracies and tensorboard data.
fccl+/utils/conf.py:19
↓ 1 callersFunctiondrop_connect
(x, drop_ratio)
fccl/Network/efficientnet.py:10
↓ 1 callersFunctiondrop_connect
(x, drop_ratio)
fccl+/backbone/efficientnet.py:10
↓ 1 callersFunctionevaluate
(model: FederatedModel, test_dl: DataLoader, setting: str, name: str)
fccl+/utils/training.py:16
↓ 1 callersMethodfeatures
(self, x)
fccl+/backbone/googlenet.py:105
↓ 1 callersMethodforward_test
(self, image)
fccl/Idea/_base.py:34
↓ 1 callersMethodforward_test
(self, image)
fccl/Idea/_base.py:61
↓ 1 callersMethodforward_train
(self, **kwargs)
fccl/Idea/_base.py:30
↓ 1 callersMethodforward_train
(self, image, target, **kwargs)
fccl/Idea/_base.py:51
↓ 1 callersFunctionget_all_models
()
fccl+/datasets/utils/__init__.py:9
↓ 1 callersFunctionget_device
(device_id)
fccl+/utils/conf.py:5
↓ 1 callersFunctionget_model
(nets_list,args, transform)
fccl+/models/__init__.py:19
↓ 1 callersMethodget_normalization_transform
()
fccl+/datasets/office31.py:115
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