code: def test_terminator_cv_score_reporting(mock: MagicMock) -> None:
      scores = {
          "fit_time": np.array([2.01, 1.78, 3.22]),
          "score_time": np.array([0.33, 0.35, 0.48]),
          "test_score": np.array([0.04, 0.80, 0.70]),
      }
      mock.return_value = scores
  
      X, _ = make_blobs(n_samples=10)
      est = PCA()
      optuna_search = integration.OptunaSearchCV(
          est, {}, cv=3, error_score="raise", random_state=0
      )
      optuna_search.fit(X)
  
      for trial in optuna_search.study_.trials:
          assert (
              trial.system_attrs[_CROSS_VALIDATION_SCORES_KEY]
              == scores["test_score"]
          ).all()
  
imports: from __future__ import annotations
  from unittest.mock import MagicMock
  from unittest.mock import patch
  import warnings
  import numpy
  import pytest
  import scipy
  from sklearn.datasets import make_blobs
  from sklearn.datasets import make_regression
  from sklearn.decomposition import PCA
  from sklearn.exceptions import ConvergenceWarning
  from sklearn.exceptions import NotFittedError
  from sklearn.linear_model import LogisticRegression
  from sklearn.linear_model import SGDClassifier
  from sklearn.neighbors import KernelDensity
  from sklearn.tree import DecisionTreeRegressor
  from optuna import distributions
  from optuna import integration
  from optuna.samplers import BruteForceSampler
  from optuna.study import create_study
  from optuna.terminator.erroreval import _CROSS_VALIDATION_SCORES_KEY
label_desc: Use image node_id 21 for calling a global function with example usage: test_terminator_cv_score_reporting(mock) without return types