code: def _check_plot_args(
      study: Study | Sequence[Study],
      target: Callable[[FrozenTrial], float] | None,
      target_name: str,
  ) -> None:
      studies: Sequence[Study]
      if isinstance(study, Study):
          studies = [study]
      else:
          studies = study
  
      if target is None and any(
          study._is_multi_objective() for study in studies
      ):
          raise ValueError(
              "If the `study` is being used for multi-objective optimization, "
              "please specify the `target`."
          )
  
      if target is not None and target_name == "Objective Value":
          warnings.warn(
              "`target` is specified, but `target_name` is the default value, 'Objective Value'."
          )
  
imports: from __future__ import annotations
  import json
  from typing import Any
  from typing import Callable
  from typing import cast
  from typing import Sequence
  import warnings
  import numpy
  import optuna
  from optuna.distributions import CategoricalDistribution
  from optuna.distributions import FloatDistribution
  from optuna.distributions import IntDistribution
  from optuna.study import Study
  from optuna.study._study_direction import StudyDirection
  from optuna.trial import FrozenTrial
  from optuna.visualization import _plotly_imports
label_desc: Use image node_id 2 for calling a global function with example usage: _check_plot_args(study, target, target_name) without return types