def METHOD_NAME() -> None:
    study = optuna.multi_objective.create_study(["maximize", "minimize", "maximize"])
    def objective(trial: optuna.multi_objective.trial.MultiObjectiveTrial) -> List[float]:
        x = trial.suggest_uniform("x", 0, 10)
        assert set(trial.params.keys()) == {"x"}
        assert set(trial.distributions.keys()) == {"x"}
        assert isinstance(trial.distributions["x"], optuna.distributions.FloatDistribution)
        return [x, x, x]
    study.optimize(objective, n_trials=1)
    trial = study.trials[0]
    assert set(trial.params.keys()) == {"x"}
    assert set(trial.distributions.keys()) == {"x"}
    assert isinstance(trial.distributions["x"], optuna.distributions.FloatDistribution)