__init__.py 文件源码

def __call__(self, X, y, net):
        if self.eval_size is not None:
            if net.regression or not self.stratify:
                # test_size = self.eval_size
                # kf = ShuffleSplit(
                #     y.shape[0], test_size=test_size,
                #     random_state=self.random_state
                # )
                # train_indices, valid_indices = next(iter(kf))
                # valid_indices = shuffle(valid_indices)
                test_size = 1 - self.eval_size
                kf = ShuffleSplit(
                    y.shape[0], test_size=test_size,
                    random_state=self.random_state
                )
                valid_indices, train_indices = next(iter(kf))
            else:
                n_folds = int(round(1 / self.eval_size))
                kf = StratifiedKFold(y, n_folds=n_folds, random_state=self.random_state)
                train_indices, valid_indices = next(iter(kf))

            X_train, y_train = X[train_indices], y[train_indices]
            X_valid, y_valid = X[valid_indices], y[valid_indices]
        else:
            X_train, y_train = X, y
            X_valid, y_valid = X[len(X):], y[len(y):]

        return X_train, X_valid, y_train, y_valid