code: def test_gnb_prior(global_random_seed):
      # Test whether class priors are properly set.
      clf = GaussianNB().fit(X, y)
      assert_array_almost_equal(
          np.array([3, 3]) / 6.0, clf.class_prior_, 8
      )
      X1, y1 = get_random_normal_x_binary_y(global_random_seed)
      clf = GaussianNB().fit(X1, y1)
      # Check that the class priors sum to 1
      assert_array_almost_equal(clf.class_prior_.sum(), 1)
  
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 4 for calling a global function with example usage: test_gnb_prior(global_random_seed) without return types