code: def setUp(self):
      self.network = DBN()
      self.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", 0), ("I", 0)],
          evidence_card=[2, 2],
      )
      self.d_i_cpd = TabularCPD(
          ("D", 1),
          2,
          values=[[0.6, 0.3], [0.4, 0.7]],
          evidence=[("D", 0)],
          evidence_card=[2],
      )
      self.diff_cpd = TabularCPD(("D", 0), 2, values=[[0.6], [0.4]])
      self.intel_cpd = TabularCPD(("I", 0), 2, values=[[0.7], [0.3]])
      self.i_i_cpd = TabularCPD(
          ("I", 1),
          2,
          values=[[0.5, 0.4], [0.5, 0.6]],
          evidence=[("I", 0)],
          evidence_card=[2],
      )
      self.grade_1_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", 1), ("I", 1)],
          evidence_card=[2, 2],
      )
  
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 1 for calling the TestDynamicBayesianNetworkMethods obj's underlying member method code with example usage: obj.setUp() without return types