5.1.1.8.1.2. FedEval.strategy.FedOpt
5.1.1.8.1.2.1. Module Contents
5.1.1.8.1.2.1.1. Classes
the basic class of federated strategies. |
- class FedEval.strategy.FedOpt.FedOpt(*args, **kwags)
Bases:
FedEval.strategy.FedAvg.FedAvgthe basic class of federated strategies.
- retrieve_local_upload_info()
return the information aggregated from local model for uploading to the central server.
Called by the selected clients.
- Raises:
NotImplementedError – raised when called but not overriden.
- Returns:
the local model weights/params.
- Return type:
ModelWeights
- update_host_params(client_params, aggregate_weights)
update central server’s model params/weights with the aggregated params received from clients.
- Parameters:
client_params (Iterable[ModelWeights]) – the weights form different clients, ordered like [params1, params2, …]
aggregate_weights (Iterable[Union[float, int]]) – aggregate weights of different clients, usually set according to the clients’ training sample size. E.g., A, B, and C have 10, 20, and 30 images, then the aggregate_weights can be [1/6, 1/3, 1/2] or [10, 20, 30].
- Raises:
NotImplementedError – raised when called but not overriden.