code: def test_gnb_wrong_nb_priors():
      """Test whether an error is raised if the number of prior is different
      from the number of class"""
      clf = GaussianNB(priors=np.array([0.25, 0.25, 0.25, 0.25]))
  
      msg = "Number of priors must match number of classes"
      with pytest.raises(ValueError, match=msg):
          clf.fit(X, y)
  
imports: import re
  import warnings
  import numpy
  import pytest
  from scipy.special import logsumexp
  from sklearn.datasets import load_digits, load_iris
  from sklearn.model_selection import cross_val_score, train_test_split
  from sklearn.naive_bayes import BernoulliNB, CategoricalNB, ComplementNB, GaussianNB, MultinomialNB
  from sklearn.utils._testing import assert_allclose, assert_almost_equal, assert_array_almost_equal, assert_array_equal
  from sklearn.utils.fixes import CSR_CONTAINERS
label_desc: Use image node_id 9 for calling a global function with example usage: test_gnb_wrong_nb_priors() without return types