Server#

class Server(*, client_manager: ClientManager, strategy: Strategy | None = None)[source]#

Bases: object

Flower server.

Methods

`client_manager`()	Return ClientManager.
`disconnect_all_clients`(timeout)	Send shutdown signal to all clients.
`evaluate_round`(server_round, timeout)	Validate current global model on a number of clients.
`fit`(num_rounds, timeout)	Run federated averaging for a number of rounds.
`fit_round`(server_round, timeout)	Perform a single round of federated averaging.
`set_max_workers`(max_workers)	Set the max_workers used by ThreadPoolExecutor.
`set_strategy`(strategy)	Replace server strategy.

client_manager() → ClientManager[source]#: Return ClientManager.

disconnect_all_clients(timeout: float | None) → None[source]#: Send shutdown signal to all clients.

evaluate_round(server_round: int, timeout: float | None) → Tuple[float | None, Dict[str, bool | bytes | float | int | str], Tuple[List[Tuple[ClientProxy, EvaluateRes]], List[Tuple[ClientProxy, EvaluateRes] | BaseException]]] | None[source]#: Validate current global model on a number of clients.

fit(num_rounds: int, timeout: float | None) → Tuple[History, float][source]#: Run federated averaging for a number of rounds.

fit_round(server_round: int, timeout: float | None) → Tuple[Parameters | None, Dict[str, bool | bytes | float | int | str], Tuple[List[Tuple[ClientProxy, FitRes]], List[Tuple[ClientProxy, FitRes] | BaseException]]] | None[source]#: Perform a single round of federated averaging.

set_max_workers(max_workers: int | None) → None[source]#: Set the max_workers used by ThreadPoolExecutor.

set_strategy(strategy: Strategy) → None[source]#: Replace server strategy.