code: def test_roc_auc_score_multiclass_labels_error(
      setup, msg, y_true, labels, multi_class
  ):
      y_scores = np.array(
          [
              [0.1, 0.8, 0.1],
              [0.3, 0.4, 0.3],
              [0.35, 0.5, 0.15],
              [0, 0.2, 0.8],
          ]
      )
  
      with pytest.raises(ValueError, match=msg):
          roc_auc_score(
              y_true, y_scores, labels=labels, multi_class=multi_class
          )
  
imports: import re
  import warnings
  import numpy
  import pandas
  import pytest
  from sklearn.metrics import roc_curve, auc, accuracy_score
  from sklearn.metrics.tests.test_ranking import make_prediction, _auc
  from sklearn.exceptions import UndefinedMetricWarning
  from sklearn.utils import check_random_state
  from sklearn.utils._testing import assert_almost_equal, assert_array_almost_equal
  from ....None import dataframe
  from ....None import tensor
  from ...utils.extmath import softmax
  from ..None import roc_curve, auc, accuracy_score, roc_auc_score
label_desc: Use image node_id 17 for calling a global function with example usage: test_roc_auc_score_multiclass_labels_error(setup, msg, y_true, labels, multi_class) without return types