code: def setUp(self):
      self.model = DBN()
      self.model.add_edges_from(
          [
              (("Z", 0), ("X", 0)),
              (("X", 0), ("Y", 0)),
              (("Z", 0), ("Z", 1)),
          ]
      )
      z_start_cpd = TabularCPD(("Z", 0), 2, [[0.5], [0.5]])
      x_i_cpd = TabularCPD(
          ("X", 0),
          2,
          [[0.6, 0.9], [0.4, 0.1]],
          evidence=[("Z", 0)],
          evidence_card=[2],
      )
      y_i_cpd = TabularCPD(
          ("Y", 0),
          2,
          [[0.2, 0.3], [0.8, 0.7]],
          evidence=[("X", 0)],
          evidence_card=[2],
      )
      z_trans_cpd = TabularCPD(
          ("Z", 1),
          2,
          [[0.4, 0.7], [0.6, 0.3]],
          evidence=[("Z", 0)],
          evidence_card=[2],
      )
      self.model.add_cpds(z_start_cpd, z_trans_cpd, x_i_cpd, y_i_cpd)
      self.model.initialize_initial_state()
      self.infer = ApproxInference(self.model)
  
imports: import unittest
  from pgmpy import config
  from pgmpy.factors.discrete import DiscreteFactor, TabularCPD
  from pgmpy.inference import ApproxInference, VariableElimination
  from pgmpy.models import DynamicBayesianNetwork
  from pgmpy.utils import get_example_model
label_desc: Use image node_id 1 for calling the TestApproxInferenceDBN obj's underlying member method code with example usage: obj.setUp() without return types