def METHOD_NAME(
    attrs: tuple[str, ...], multi_index: bool
) -> None:
    def f(trial: Trial) -> tuple[float, float]:
        x = trial.suggest_float("x", 1, 1)
        y = trial.suggest_float("y", 2, 2)
        return x + y, x**2 + y**2  # 3, 5
    # without set_metric_names()
    study = create_study(directions=["minimize", "maximize"])
    study.optimize(f, n_trials=1)
    df = study.trials_dataframe(attrs=attrs, multi_index=multi_index)
    if multi_index:
        assert df.get("values")[0][0] == 3
        assert df.get("values")[1][0] == 5
    else:
        assert df.values_0[0] == 3
        assert df.values_1[0] == 5
    # with set_metric_names()
    study.set_metric_names(["v0", "v1"])
    df = study.trials_dataframe(attrs=attrs, multi_index=multi_index)
    if multi_index:
        assert df.get("values")["v0"][0] == 3
        assert df.get("values")["v1"][0] == 5
    else:
        assert df.get("values_v0")[0] == 3
        assert df.get("values_v1")[0] == 5