code: def test_params_and_distributions() -> 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,
      )
  
file_path: optuna/tests/multi_objective_tests/test_trial.py
imports: from __future__ import annotations
  import datetime
  from typing import List
  from typing import Tuple
  import pytest
  import optuna
  from optuna.multi_objective.trial import FrozenMultiObjectiveTrial
  from optuna.study._study_direction import StudyDirection
  from optuna.trial import TrialState
label_desc: Use image node_id 5 for calling a global function with example usage: test_params_and_distributions() and returns: list