code: def test_fit_model_creation(self):
      values = pd.DataFrame(
          np.random.randint(low=0, high=2, size=(1000, 5)),
          columns=["A", "B", "C", "D", "E"],
      )
  
      self.model1.fit(values, "A")
      self.assertCountEqual(
          self.model1.nodes(), ["A", "B", "C", "D", "E"]
      )
      self.assertCountEqual(
          self.model1.edges(),
          [("A", "B"), ("A", "C"), ("A", "D"), ("A", "E")],
      )
      self.assertEqual(self.model1.dependent, "A")
      self.assertSetEqual(self.model1.features, {"B", "C", "D", "E"})
  
      self.model2.fit(values)
      self.assertCountEqual(
          self.model1.nodes(), ["A", "B", "C", "D", "E"]
      )
      self.assertCountEqual(
          self.model1.edges(),
          [("A", "B"), ("A", "C"), ("A", "D"), ("A", "E")],
      )
      self.assertEqual(self.model2.dependent, "A")
      self.assertSetEqual(self.model2.features, {"B", "C", "D", "E"})
  
imports: import unittest
  import networkx
  import pandas
  import numpy
  from pgmpy.models import NaiveBayes
  from pgmpy.independencies import Independencies
label_desc: Use image node_id 2 for calling the TestNaiveBayesFit obj's underlying member method code with example usage: obj.test_fit_model_creation() without return types