Callback¶

class Callback(BaseClassWrapper):
    """Wrapper for Optuna callback classes invoked during optimization.

    Parameters
    ----------
    callback : type
        Optuna callback class to instantiate. The class must implement
        ``__call__(study, trial)`` to be invoked at the end of each trial.

    **params : dict
        Parameters to pass to the callback constructor.

    See Also
    --------
    sklearn_optuna.search.OptunaSearchCV : The main search class that uses callbacks.
    sklearn_optuna.optuna.Sampler : Wrapper for Optuna samplers.

    Examples
    --------
    >>> from optuna.study import MaxTrialsCallback
    >>> callback = Callback(callback=MaxTrialsCallback, n_trials=100)

    """

    _estimator_name = "callback"
    _estimator_base_class = object

    def __init__(self, callback: type, **params: dict[str, object]) -> None:
        if not isinstance(callback, type):
            raise TypeError(f"callback must be a class, got {type(callback)}")
        BaseClassWrapper.__init__(self, callback=callback, **params)

    def __call__(self, study: optuna.study.Study, trial: optuna.trial.FrozenTrial) -> None:
        """Invoke the callback by instantiating it and calling it.

        Parameters
        ----------
        study : optuna.study.Study
            The study object.

        trial : optuna.trial.FrozenTrial
            The completed trial.

        """
        return self.instance_(study, trial)