code: def test_roc_auc_score_multiclass_error(setup, msg, kwargs):
      # Test that roc_auc_score function returns an error when trying
      # to compute multiclass AUC for parameters where an output
      # is not defined.
      rng = check_random_state(404)
      y_score = rng.rand(20, 3)
      y_prob = softmax(y_score)
      y_true = rng.randint(0, 3, size=20)
      with pytest.raises(ValueError, match=msg):
          roc_auc_score(y_true, y_prob, **kwargs)
  
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 18 for calling a global function with example usage: test_roc_auc_score_multiclass_error(setup, msg, kwargs) without return types