optuna.study.MaxTrialsCallback

class optuna.study.MaxTrialsCallback(n_trials, states=(1,))[source]

Set a maximum number of trials before ending the study.

While the n_trials argument of optuna.study.Study.optimize() sets the number of trials that will be run, you may want to continue running until you have a certain number of successfully completed trials or stop the study when you have a certain number of trials that fail. This MaxTrialsCallback class allows you to set a maximum number of trials for a particular TrialState before stopping the study.

Example

import optuna
from optuna.study import MaxTrialsCallback
from optuna.trial import TrialState


def objective(trial):
    x = trial.suggest_float("x", -1, 1)
    return x**2


study = optuna.create_study()
study.optimize(
    objective,
    callbacks=[MaxTrialsCallback(10, states=(TrialState.COMPLETE,))],
)

Parameters:

n_trials (int) – The max number of trials. Must be set to an integer.
states (Container[TrialState] | None) – Tuple of the TrialState to be counted towards the max trials limit. Default value is (TrialState.COMPLETE,). If None, count all states.