optuna.integration.ChainerPruningExtension¶
- class optuna.integration.ChainerPruningExtension(trial: optuna.trial.Trial, observation_key: str, pruner_trigger: TriggerType)[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 – A
Trial
corresponding to the current evaluation of the objective function.observation_key – An evaluation metric for pruning, e.g.,
main/loss
andvalidation/main/accuracy
. Please refer to chainer.Reporter reference for further details.pruner_trigger –
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')
.
- __init__(trial: optuna.trial.Trial, observation_key: str, pruner_trigger: TriggerType) None [source]¶
Methods
__init__
(trial, observation_key, pruner_trigger)