optuna_integration.ChainerPruningExtension

class optuna_integration.ChainerPruningExtension(trial, observation_key, pruner_trigger)[source]

Chainer extension to prune unpromising trials.

See the example if you want to add a pruning extension which observes validation accuracy of a Chainer Trainer.

Parameters:

trial (optuna.trial.Trial) – A Trial corresponding to the current evaluation of the objective function.
observation_key (str) – An evaluation metric for pruning, e.g., main/loss and validation/main/accuracy. Please refer to chainer.Reporter reference for further details.
pruner_trigger (tuple[int, str] | 'IntervalTrigger' | 'ManualScheduleTrigger') –
A trigger to execute pruning. pruner_trigger is an instance of IntervalTrigger or ManualScheduleTrigger. IntervalTrigger can be specified by a tuple of the interval length and its unit like (1, 'epoch').

Warning

Deprecated in v3.5.0. This feature will be removed in the future. The removal of this feature is currently scheduled for v5.0.0, but this schedule is subject to change. See https://github.com/optuna/optuna/releases/tag/v3.5.0.