code: def _prepare_study_with_cross_validation_scores() -> Study:
      study = create_study()
      for _ in range(3):
          trial = study.ask({"x": FloatDistribution(0, 1)})
          report_cross_validation_scores(trial, [1.0, 2.0])
          study.tell(trial, 0)
      return study
  
imports: from __future__ import annotations
  from io import BytesIO
  from typing import Any
  from typing import Callable
  import pytest
  from optuna.distributions import FloatDistribution
  from optuna.study import create_study
  from optuna.study import Study
  from optuna.terminator import BaseErrorEvaluator
  from optuna.terminator import BaseImprovementEvaluator
  from optuna.terminator import CrossValidationErrorEvaluator
  from optuna.terminator import RegretBoundEvaluator
  from optuna.terminator import report_cross_validation_scores
  from optuna.terminator import StaticErrorEvaluator
  from optuna.testing.objectives import fail_objective
  from optuna.testing.visualization import prepare_study_with_trials
  from optuna.trial import create_trial
  from optuna.trial import TrialState
  from optuna.visualization import plot_terminator_improvement
  from optuna.visualization._terminator_improvement import _get_improvement_info
  from optuna.visualization._terminator_improvement import _get_y_range
  from optuna.visualization._terminator_improvement import _ImprovementInfo
label_desc: Use image node_id 2 for calling a global function with example usage: _prepare_study_with_cross_validation_scores() and returns: study