code: def test_gnb_partial_fit():
      clf = GaussianNB().fit(X, y)
      clf_pf = GaussianNB().partial_fit(X, y, np.unique(y))
      assert_array_almost_equal(clf.theta_, clf_pf.theta_)
      assert_array_almost_equal(clf.var_, clf_pf.var_)
      assert_array_almost_equal(clf.class_prior_, clf_pf.class_prior_)
  
      clf_pf2 = GaussianNB().partial_fit(
          X[0::2, :], y[0::2], np.unique(y)
      )
      clf_pf2.partial_fit(X[1::2], y[1::2])
      assert_array_almost_equal(clf.theta_, clf_pf2.theta_)
      assert_array_almost_equal(clf.var_, clf_pf2.var_)
      assert_array_almost_equal(clf.class_prior_, clf_pf2.class_prior_)
  
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 13 for calling a global function with example usage: test_gnb_partial_fit() without return types