qfedavg#

Module Contents#

qFedAvgServerHandler

qFedAvg server handler.

qFedAvgClientTrainer

Federated client with modified upload package and local SGD solver.
class qFedAvgServerHandler(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

qFedAvg server handler.

global_update(buffer)#
class qFedAvgClientTrainer(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 modified upload package and local SGD solver.

Return a tensor list for uploading to server.

This attribute will be called by client manager. Customize it for new algorithms.

setup_optim(epochs, batch_size, lr, q)#

Set up local optimization configuration.

Parameters:

  • epochs (int) – Local epochs.

  • batch_size (int) – Local batch size.

  • lr (float) – Learning rate.

train(model_parameters, train_loader) → None#

Client trains its local model on local dataset. :param model_parameters: Serialized model parameters. :type model_parameters: torch.Tensor