o
    /wÖiO
  ã                   @   sv   G d d„ de ƒZG dd„ deƒZG dd„ deƒZG dd„ deƒZG dd	„ d	eƒZG d
d„ deeƒZG dd„ deƒZ	dS )c                   @   ó   e Zd ZdZdS )ÚOptunaErrorz&Base class for Optuna specific errors.N©Ú__name__Ú
__module__Ú__qualname__Ú__doc__© r   r   úN/home/ubuntu/sommelier/.venv/lib/python3.10/site-packages/optuna/exceptions.pyr      s    r   c                   @   r   )ÚTrialPruneda¼  Exception for pruned trials.

    This error tells a trainer that the current :class:`~optuna.trial.Trial` was pruned. It is
    supposed to be raised after :func:`optuna.trial.Trial.should_prune` as shown in the following
    example.

    See also:
        :class:`optuna.TrialPruned` is an alias of :class:`optuna.exceptions.TrialPruned`.

    Example:

        .. testcode::

            import numpy as np
            from sklearn.datasets import load_iris
            from sklearn.linear_model import SGDClassifier
            from sklearn.model_selection import train_test_split

            import optuna

            X, y = load_iris(return_X_y=True)
            X_train, X_valid, y_train, y_valid = train_test_split(X, y)
            classes = np.unique(y)


            def objective(trial):
                alpha = trial.suggest_float("alpha", 0.0, 1.0)
                clf = SGDClassifier(alpha=alpha)
                n_train_iter = 100

                for step in range(n_train_iter):
                    clf.partial_fit(X_train, y_train, classes=classes)

                    intermediate_value = clf.score(X_valid, y_valid)
                    trial.report(intermediate_value, step)

                    if trial.should_prune():
                        raise optuna.TrialPruned()

                return clf.score(X_valid, y_valid)


            study = optuna.create_study(direction="maximize")
            study.optimize(objective, n_trials=20)
    Nr   r   r   r   r	   r
      s    .r
   c                   @   r   )ÚCLIUsageErrorz^Exception for CLI.

    CLI raises this exception when it receives invalid configuration.
    Nr   r   r   r   r	   r   9   ó    r   c                   @   r   )ÚStorageInternalErrorzrException for storage operation.

    This error is raised when an operation failed in backend DB of storage.
    Nr   r   r   r   r	   r   B   r   r   c                   @   r   )ÚDuplicatedStudyErrorz€Exception for a duplicated study name.

    This error is raised when a specified study name already exists in the storage.
    Nr   r   r   r   r	   r   K   r   r   c                   @   r   )ÚUpdateFinishedTrialErrorzsException for updating a finished trial.

    This error is raised when attempting to update a finished trial.
    Nr   r   r   r   r	   r   T   r   r   c                   @   r   )ÚExperimentalWarningzúExperimental Warning class.

    This implementation exists here because the policy of `FutureWarning` has been changed
    since Python 3.7 was released. See the details in
    https://docs.python.org/3/library/warnings.html#warning-categories.
    Nr   r   r   r   r	   r   ]   s    r   N)
Ú	Exceptionr   r
   r   r   r   ÚRuntimeErrorr   ÚWarningr   r   r   r   r	   Ú<module>   s    2				