def METHOD_NAME(self):
    with tempfile.TemporaryDirectory() as results_path:
        data = {
            "X": pd.DataFrame(
                np.array(
                    [[0, 0], [0, 1], [1, 0], [0, 1], [1, 0], [0, 1], [1, 0], [1, 1]]
                ),
                columns=["a", "b"],
            ),
            "y": pd.DataFrame(np.array([0, 0, 1, 0, 1, 0, 1, 1]), columns=["target"]),
        }
        X_path = os.path.join(results_path, "X.data")
        y_path = os.path.join(results_path, "y.data")
        dump_data(X_path, data["X"])
        dump_data(y_path, data["y"])
        params = {
            "shuffle": True,
            "stratify": False,
            "train_ratio": 0.5,
            "results_path": results_path,
            "X_path": X_path,
            "y_path": y_path,
            "repeats": 3,
        }
        vl = SplitValidator(params)
        self.assertEqual(1, vl.get_n_splits())
        self.assertEqual(3, vl.get_repeats())
        cnt = 0
        for repeat in range(vl.get_repeats()):
            for k_fold in range(vl.get_n_splits()):
                train, validation = vl.get_split(k_fold, repeat)
                X_train, y_train = train.get("X"), train.get("y")
                X_validation, y_validation = validation.get("X"), validation.get("y")
                self.assertEqual(X_train.shape[0], 4)
                self.assertEqual(y_train.shape[0], 4)
                self.assertEqual(X_validation.shape[0], 4)
                self.assertEqual(y_validation.shape[0], 4)
                cnt += 1
        self.assertEqual(cnt, 3)