code: def test_get_pareto_front_info_invalid_target_values(
      include_dominated_trials: bool,
      constraints_func: Callable[[FrozenTrial], Sequence[float]] | None,
  ) -> None:
      study = optuna.create_study(directions=["minimize", "minimize"])
      study.optimize(lambda _: [0, 0], n_trials=3)
      with pytest.raises(ValueError):
          _get_pareto_front_info(
              study=study,
              targets=lambda t: t.values[0],
              include_dominated_trials=include_dominated_trials,
              constraints_func=constraints_func,
          )
  
imports: from __future__ import annotations
  from io import BytesIO
  from typing import Any
  from typing import Callable
  from typing import Sequence
  import warnings
  import pytest
  import optuna
  from optuna import create_study
  from optuna import create_trial
  from optuna.distributions import FloatDistribution
  from optuna.study.study import Study
  from optuna.trial import FrozenTrial
  from optuna.visualization import plot_pareto_front
  import optuna.visualization._pareto_front
  from optuna.visualization._pareto_front import _get_pareto_front_info
  from optuna.visualization._pareto_front import _ParetoFrontInfo
  from optuna.visualization._plotly_imports import go
  from optuna.visualization._utils import COLOR_SCALE
  from optuna.visualization.matplotlib._matplotlib_imports import plt
  import optuna.visualization.matplotlib._pareto_front
label_desc: Use image node_id 10 for calling a global function with example usage: test_get_pareto_front_info_invalid_target_values(include_dominated_trials, constraints_func) without return types