code: def test_discretenb_prior(DiscreteNaiveBayes, global_random_seed):
      # Test whether class priors are properly set.
      X2, y2 = get_random_integer_x_three_classes_y(global_random_seed)
      clf = DiscreteNaiveBayes().fit(X2, y2)
      assert_array_almost_equal(
          np.log(np.array([2, 2, 2]) / 6.0), clf.class_log_prior_, 8
      )
  
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 15 for calling a global function with example usage: test_discretenb_prior(DiscreteNaiveBayes, global_random_seed) without return types