code: def test_suggest() -> None:
      study = optuna.multi_objective.create_study(
          ["maximize", "maximize"]
      )
  
      def objective(
          trial: optuna.multi_objective.trial.MultiObjectiveTrial,
      ) -> Tuple[float, float]:
          p0 = trial.suggest_float("p0", -10, 10)
          p1 = trial.suggest_float("p1", 3, 5)
          p2 = trial.suggest_float("p2", 0.00001, 0.1, log=True)
          p3 = trial.suggest_float("p3", 100, 200, step=5)
          p4 = trial.suggest_int("p4", -20, -15)
          p5 = trial.suggest_categorical("p5", [7, 1, 100])
          p6 = trial.suggest_float("p6", -10, 10, step=1.0)
          p7 = trial.suggest_int("p7", 1, 7, log=True)
          return (
              p0 + p1 + p2,
              p3 + p4 + p5 + p6 + p7,
          )
  
      study.optimize(objective, n_trials=10)
  
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 1 for calling a global function with example usage: test_suggest() and returns: unknown,  unknown