Functions — github.com/KarhouTam/FL-bench

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Functions580 in github.com/KarhouTam/FL-bench

⨍ Functions 580◇ Types & classes 144

↓ 1 callersMethodtrain_and_test_discriminator

src/server/adcol.py:101

↓ 1 callersMethodtrain_discriminator

src/server/adcol.py:117

↓ 1 callersMethodtrain_generator

(self, client_packages: dict[int, dict[str, Any]])

src/server/fedgen.py:77

↓ 1 callersMethodtrain_one_round

The function of indicating specific things FL method need to do (at server side) in each communication round.

src/server/fedavg.py:494

↓ 1 callersMethodupdate_alpha

src/client/apfl.py:74

↓ 1 callersMethodupdate_data_sample_weights

src/client/fedem.py:41

↓ 1 callersMethodupdate_learner_weights

src/client/fedem.py:69

↓ 1 callersMethodupdate_neural_collapse

(self, client_packages: dict[int, dict[str, Any]])

src/server/flute.py:35

↓ 1 callersMethodupdate_privacy_stats

Update global privacy statistics from client reports with cumulative tracking. Args: client_id: The ID of the client reporting pr

src/utils/dp_manager.py:133

↓ 1 callersMethodupdate_weight_matrix

src/server/pfedsim.py:135

↓ 1 callersMethodvalidate_privacy_budget

Check if privacy budget is still available.

src/utils/dp_manager.py:186

↓ 1 callersFunctionwasserstein

(m1, v1, m2, v2, mode="nosquare")

src/server/fedap.py:201

↓ 1 callersFunctionwrite_json

data/celeba/preprocess/metadata_to_json.py:87

src/utils/metrics.py:78

Method__getitem__

data/utils/datasets.py:48

Method__getitem__

data/utils/datasets.py:625

Method__getitem__

src/client/fedem.py:115

Method__getitem__

src/server/ccvr.py:109

Method__getitem__

src/server/adcol.py:42

( self, data: torch.Tensor, targets: torch.Tensor, classes: List[int],

data/utils/datasets.py:20

( self, root, args=None, test_data_transform=None, test_target_tr

data/utils/datasets.py:70

(self, root, *args, **kwargs)

data/utils/datasets.py:103

( self, root, args=None, test_data_transform=None, test_target_tr

data/utils/datasets.py:124

( self, root, args=None, test_data_transform=None, test_target_tr

data/utils/datasets.py:157

( self, root, args=None, test_data_transform=None, test_target_tr

data/utils/datasets.py:181

( self, root, args=None, test_data_transform=None, test_target_tr

data/utils/datasets.py:236

( self, root, args=None, test_data_transform=None, test_target_tr

data/utils/datasets.py:266

( self, root, args=None, test_data_transform=None, test_target_tr

data/utils/datasets.py:294

( self, root, args, test_data_transform=None, test_target_transfo

data/utils/datasets.py:322

( self, root, args=None, test_data_transform=None, test_target_tr

data/utils/datasets.py:361

( self, root, args, test_data_transform=None, test_target_transfo

data/utils/datasets.py:389

( self, root, args=None, test_data_transform=None, test_target_tr

data/utils/datasets.py:460

( self, root, args=None, test_data_transform=None, test_target_tr

data/utils/datasets.py:523

( self, root, args=None, test_data_transform=None, test_target_tr

data/utils/datasets.py:580

(self, VAE_cls, VAE_optimizer_cls, **commons)

src/client/fedfed.py:13

(self, **commons)

src/client/metafed.py:14

(self, generator: torch.nn.Module, **commons)

src/client/fedgen.py:13

(self, **commons)

src/client/feddyn.py:10

(self, dataset)

src/client/fedem.py:112

(self, learners: List[DecoupledModel], learners_weights: torch.Tensor)

src/client/fedem.py:124

(self, **commons)

src/client/scaffold.py:10

(self, **commons)

src/client/fedproto.py:11

(self, hypernetwork: torch.nn.Module, **commons)

src/client/fedrod.py:25

( self, model: DecoupledModel, optimizer_cls: type[torch.optim.Optimizer], lr_

src/client/fedavg.py:16

(self, **commons)

src/client/fedrep.py:5

(self, **commons)

src/client/floco.py:11

(self, **kwargs)

src/client/fedfomo.py:12

(self, **commons)

src/client/moon.py:11

(self, **commons)

src/client/knnper.py:12

(self, **commons)

src/client/ditto.py:9

(self, **commons)

src/client/perfedavg.py:11

(self, **commons)

src/client/fedmd.py:9

(self, **commons)

src/client/fedadmm.py:10

(self, **commons)

src/client/dpfedavg.py:17

(self, **commons)

src/client/fedbn.py:5

(self, **commons)

src/client/fedap.py:9

(self, **commons)

src/client/fedbabu.py:5

(self, **commons)

src/client/fedas.py:13

(self, params, lr=0.01, lamda=0.1, mu=0.001)

src/client/pfedme.py:74

(self, **commons)

src/client/ccvr.py:9

(self, **commons)

src/client/fediir.py:11

(self, **commons)

src/client/fedsr.py:8

(self, **commons)

src/client/lgfedavg.py:7

(self, **commons)

src/client/fedprox.py:5

(self, **commons)

src/client/elastic.py:12

(self, **commons)

src/client/fedpac.py:13

(self, **commons)

src/client/pfedfda.py:15

(self, **commons)

src/client/flute.py:9

( self, local_model: DecoupledModel, global_model: DecoupledModel, alpha: float )

src/client/apfl.py:98

src/client/pefll.py:93

(self, backbone: nn.Module, args: Namespace)

src/client/pefll.py:138

(self, **commons)

src/client/fedlc.py:10

(self, discriminator: torch.nn.Module, client_num: int, **commons)

src/client/adcol.py:11

(self, **commons)

src/client/fedala.py:14

(self, **commons)

src/client/fedah.py:11

(self, **commons)

src/client/fedper.py:5

src/utils/models.py:15

(self, dataset: str, pretrained)

src/utils/models.py:151

(self, dataset: str, pretrained)

src/utils/models.py:188

(self, dataset: str, pretrained)

src/utils/models.py:228

(self, dataset, pretrained)

src/utils/models.py:258

(self, version, dataset, pretrained)

src/utils/models.py:279

(self, version, dataset, pretrained)

src/utils/models.py:311

(self, version, dataset, pretrained)

src/utils/models.py:345

(self, version, dataset, pretrained)

src/utils/models.py:370

(self, version, dataset, pretrained)

src/utils/models.py:401

(self, version, dataset, pretrained)

src/utils/models.py:428

(self, dataset)

src/utils/models.py:477

(self, loss=None, predicts=None, targets=None)

src/utils/metrics.py:18

This class is for solving the incompatibility between the progress bar and log function in library `rich`. Args: stdout (

src/utils/logger.py:9

src/utils/dp_manager.py:24

( self, server, client_cls, mode: str, num_workers: int, init_args: dict )

src/utils/trainer.py:11

(self, args: DictConfig)

src/server/fedfed.py:50

(self, in_channels, out_channels=None)

src/server/fedfed.py:180

(self, args: DictConfig)

src/server/metafed.py:29

(self, args: DictConfig)

src/server/pfedsim.py:21

(self, args: DictConfig)

src/server/fedgen.py:43

src/server/fedgen.py:208

(self, args: DictConfig)

src/server/cfl.py:26

(self, args: DictConfig)

src/server/feddyn.py:27

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