o �J�hO �@svGdd�de�ZGdd�de�ZGdd�de�ZGdd�de�ZGdd �d e�ZGd d �d ee�ZGd d �d e�Z dS)c@�eZdZdZdS)� OptunaErrorz&Base class for Optuna specific errors.N��__name__� __module__� __qualname__�__doc__�rr�OC:\pinokio\api\whisper-webui.git\app\env\lib\site-packages\optuna\exceptions.pyrsrc@r)� TrialPruneda�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) Nrrrrr r s.r c@r)� CLIUsageErrorz^Exception for CLI. CLI raises this exception when it receives invalid configuration. Nrrrrr r 9�r c@r)�StorageInternalErrorzrException for storage operation. This error is raised when an operation failed in backend DB of storage. Nrrrrr r Br r c@r)�DuplicatedStudyErrorz�Exception for a duplicated study name. This error is raised when a specified study name already exists in the storage. Nrrrrr rKr rc@r)�UpdateFinishedTrialErrorzsException for updating a finished trial. This error is raised when attempting to update a finished trial. Nrrrrr rTr rc@r)�ExperimentalWarningz�Experimental 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. Nrrrrr r]srN) � Exceptionrr r r r� RuntimeErrorr�Warningrrrrr �<module>s2   
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