code: def setUp(self):
      config.set_backend("torch")
  
      self.model1 = get_example_model("cancer")
      self.data1 = self.model1.simulate(int(1e4), seed=42)
  
      self.model2 = BayesianNetwork(
          self.model1.edges(), latents={"Smoker"}
      )
      self.model2.add_cpds(*self.model1.cpds)
      self.data2 = self.model2.simulate(int(1e4), seed=42)
  
file_path: pgmpy/pgmpy/tests/test_estimators/test_EM.py
imports: import unittest
  import numpy
  import pandas
  from joblib.externals.loky import get_reusable_executor
  from pgmpy import config
  from pgmpy.estimators import ExpectationMaximization
  from pgmpy.models import BayesianNetwork
  from pgmpy.sampling import BayesianModelSampling
  from pgmpy.utils import get_example_model
label_desc: Use image node_id 1 for calling the TestEMTorch obj's underlying member method code with example usage: obj.setUp() without return types