code: def test_target_is_none_and_study_is_multi_obj() -> None:
      study = create_study(directions=["minimize", "minimize"])
      with pytest.raises(ValueError):
          _get_optimization_history_info_list(
              study,
              target=None,
              target_name="Objective Value",
              error_bar=False,
          )
  
imports: from __future__ import annotations
  from io import BytesIO
  import math
  from typing import Sequence
  import numpy
  import pytest
  from optuna import samplers
  from optuna import TrialPruned
  from optuna.study import create_study
  from optuna.testing.objectives import fail_objective
  from optuna.testing.objectives import pruned_objective
  from optuna.trial import FrozenTrial
  from optuna.trial import Trial
  from optuna.visualization._optimization_history import _get_optimization_history_info_list
  from optuna.visualization._optimization_history import _get_optimization_history_plot
  from optuna.visualization._optimization_history import _OptimizationHistoryInfo
  from optuna.visualization._optimization_history import _ValuesInfo
  from optuna.visualization._optimization_history import _ValueState
label_desc: Use image node_id 1 for calling a global function with example usage: test_target_is_none_and_study_is_multi_obj() without return types