Sets Sampling Strategy

class rizemind.strategies.contribution.sampling.sets_sampling_strat.SetsSamplingStrategy

Bases: ABC

Abstract strategy for sampling trainer sets during federated learning rounds.

This abstract base class defines the interface for strategies that create sets of trainers to evaluate during contribution assessment.

abstractmethod get_set(round_id: int, id: str) → TrainerSet

Returns a specific trainer set by ID for the specified round.

Parameters:

• round_id – The round identifier to retrieve the set from.

• id – The unique identifier of the trainer set to retrieve.

abstractmethod get_sets(round_id: int) → list[TrainerSet]

Returns all trainer sets for the specified round.

Parameters:

round_id – The round identifier to retrieve sets for.

abstractmethod get_trainer_mapping(round_id: int) → ParticipantMapping

Returns the participant mapping for the specified round.

Parameters:

round_id – The round identifier to retrieve the mapping for.

abstractmethod sample_trainer_sets(server_round: int, results: list[tuple[ClientProxy, FitRes]]) → list[TrainerSet]

Samples and generates trainer sets for the given round.

Parameters:

• server_round – The current server round number.

• results – A list of tuples containing client proxies and their

• round. (corresponding fit results from the training)

Returns:

A list of TrainerSet objects representing the sampled combinations of trainers for this round.