fedavg#

Module Contents#

FedAvgServerHandler

FedAvg server handler.

FedAvgClientTrainer

Federated client with local SGD solver.

FedAvgSerialClientTrainer

Federated client with local SGD solver.
class FedAvgServerHandler(model: torch.nn.Module, global_round: int, num_clients: int = 0, sample_ratio: float = 1, cuda: bool = False, device: str = None, sampler: fedlab.contrib.client_sampler.base_sampler.FedSampler = None, logger: fedlab.utils.Logger = None)#

Bases: fedlab.contrib.algorithm.basic_server.SyncServerHandler

FedAvg server handler.

global_update(buffer)#
class FedAvgClientTrainer(model: torch.nn.Module, cuda: bool = False, device: str = None, logger: fedlab.utils.Logger = None)#

Bases: fedlab.contrib.algorithm.basic_client.SGDClientTrainer

Federated client with local SGD solver.

global_update(buffer)#
class FedAvgSerialClientTrainer(model, num_clients, cuda=False, device=None, logger=None, personal=False)#

Bases: fedlab.contrib.algorithm.basic_client.SGDSerialClientTrainer

Federated client with local SGD solver.

train(model_parameters, train_loader)#

Single round of local training for one client.

Note

Overwrite this method to customize the PyTorch training pipeline.

Parameters: