code: def test_check_model1(self):
      diff_cpd = TabularCPD(
          ("D", 0),
          3,
          values=[
              [0.3, 0.05, 0.7, 0.5],
              [0.4, 0.25, 0.1, 0.3],
              [0.3, 0.7, 0.2, 0.2],
          ],
          evidence=[("G", 0), ("I", 0)],
          evidence_card=[2, 2],
      )
      self.G.add_cpds(diff_cpd)
      self.assertRaises(ValueError, self.G.check_model)
      self.G.remove_cpds(diff_cpd)
  
      grade_cpd = TabularCPD(
          ("G", 0),
          2,
          values=[[0.6, 0.3], [0.4, 0.7]],
          evidence=[("D", 0)],
          evidence_card=[2],
      )
      self.G.add_cpds(grade_cpd)
      self.assertRaises(ValueError, self.G.check_model)
      self.G.remove_cpds(grade_cpd)
  
      diff_cpd = TabularCPD(
          ("D", 0),
          2,
          values=[[0.6, 0.3], [0.4, 0.7]],
          evidence=[("D", 1)],
          evidence_card=[2],
      )
      self.G.add_cpds(diff_cpd)
      self.assertRaises(ValueError, self.G.check_model)
      self.G.remove_cpds(diff_cpd)
  
      grade_cpd = TabularCPD(
          ("G", 0),
          3,
          values=[
              [0.3, 0.05, 0.8, 0.5],
              [0.4, 0.25, 0.1, 0.3],
              [0.3, 0.7, 0.1, 0.2],
          ],
          evidence=[("D", 1), ("I", 1)],
          evidence_card=[2, 2],
      )
      self.G.add_cpds(grade_cpd)
      self.assertRaises(ValueError, self.G.check_model)
      self.G.remove_cpds(grade_cpd)
  
      grade_cpd = TabularCPD(
          ("G", 1),
          3,
          values=[
              [0.3, 0.05, 0.8, 0.5],
              [0.4, 0.25, 0.1, 0.3],
              [0.3, 0.7, 0.1, 0.2],
          ],
          evidence=[("D", 0), ("I", 0)],
          evidence_card=[2, 2],
      )
      self.G.add_cpds(grade_cpd)
      self.assertRaises(ValueError, self.G.check_model)
      self.G.remove_cpds(grade_cpd)
  
      grade_cpd = TabularCPD(
          ("G", 0),
          2,
          values=[[0.6, 0.3], [0.4, 0.7]],
          evidence=[("D", 1)],
          evidence_card=[2],
      )
      self.G.add_cpds(grade_cpd)
      self.assertRaises(ValueError, self.G.check_model)
      self.G.remove_cpds(grade_cpd)
  
imports: import unittest
  import numpy
  import numpy.testing
  import pandas
  import pgmpy.tests.help_functions
  from pgmpy.factors.discrete import TabularCPD
  from pgmpy.inference import CausalInference, DBNInference, VariableElimination
  from pgmpy.models import BayesianNetwork
  from pgmpy.models import DynamicBayesianNetwork
label_desc: Use image node_id 3 for calling the TestDynamicBayesianNetworkMethods2 obj's underlying member method code with example usage: obj.test_check_model1() without return types