History#

class History[소스]#

기반 클래스: object

메트릭 콜렉션을 훈련 및 평가하기 위한 History class.

메소드

`add_loss_centralized`(server_round, loss)	Add one loss entry (from centralized evaluation).
`add_loss_distributed`(server_round, loss)	Add one loss entry (from distributed evaluation).
`add_metrics_centralized`(server_round, metrics)	Add metrics entries (from centralized evaluation).
`add_metrics_distributed`(server_round, metrics)	Add metrics entries (from distributed evaluation).
`add_metrics_distributed_fit`(server_round, ...)	Add metrics entries (from distributed fit).

add_loss_centralized(server_round: int, loss: float) → None[소스]#: Add one loss entry (from centralized evaluation).

add_loss_distributed(server_round: int, loss: float) → None[소스]#: Add one loss entry (from distributed evaluation).

add_metrics_centralized(server_round: int, metrics: dict[str, Union[bool, bytes, float, int, str]]) → None[소스]#: Add metrics entries (from centralized evaluation).

add_metrics_distributed(server_round: int, metrics: dict[str, Union[bool, bytes, float, int, str]]) → None[소스]#: Add metrics entries (from distributed evaluation).

add_metrics_distributed_fit(server_round: int, metrics: dict[str, Union[bool, bytes, float, int, str]]) → None[소스]#: Add metrics entries (from distributed fit).