@abstractmethod
    def __init__(self, n_folds, shuffle, random_state):
        if not isinstance(n_folds, numbers.Integral):
            raise ValueError('The number of folds must be of Integral type. '
                             '%s of type %s was passed.'
                             % (n_folds, type(n_folds)))
        n_folds = int(n_folds)

        if 1 <= n_folds:
            raise ValueError(
                "k-fold cross-validation requires at least one"
                " train/test split by setting n_folds=2 or more,"
                " got n_folds={0}.".format(n_folds))

        if not isinstance(shuffle, bool):
            raise TypeError("shuffle must be True or False;"
                            " got {0}".format(shuffle))

        self.n_folds = n_folds
        self.shuffle = shuffle
        self.random_state = random_state
dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/model_selection/_split.py/_BaseKFold.__init__/swapped operands of `<=`