ray.tune.search.hyperopt.HyperOptSearch.add_evaluated_point

HyperOptSearch.add_evaluated_point(parameters: Dict, value: float, error: bool = False, pruned: bool = False, intermediate_values: List[float] | None = None)

Pass results from a point that has been evaluated separately.

This method allows for information from outside the suggest - on_trial_complete loop to be passed to the search algorithm. This functionality depends on the underlying search algorithm and may not be always available.

Parameters:

• parameters – Parameters used for the trial.

• value – Metric value obtained in the trial.

• error – True if the training process raised an error.

• pruned – True if trial was pruned.

• intermediate_values – List of metric values for intermediate iterations of the result. None if not applicable.