code: def test_get_model(self):
      model = self.reader_string.get_model()
      node_expected = {
          "c": {
              "STATES": ["Present", "Absent"],
              "DESCRIPTION": "(c) Brain Tumor",
              "YPOS": "11935",
              "XPOS": "15250",
              "TYPE": "discrete",
          },
          "a": {
              "STATES": ["Present", "Absent"],
              "DESCRIPTION": "(a) Metastatic Cancer",
              "YPOS": "10465",
              "XPOS": "13495",
              "TYPE": "discrete",
          },
          "b": {
              "STATES": ["Present", "Absent"],
              "DESCRIPTION": "(b) Serum Calcium Increase",
              "YPOS": "11965",
              "XPOS": "11290",
              "TYPE": "discrete",
          },
          "e": {
              "STATES": ["Present", "Absent"],
              "DESCRIPTION": "(e) Papilledema",
              "YPOS": "13240",
              "XPOS": "17305",
              "TYPE": "discrete",
          },
          "f": {
              "STATES": ["Present", "Absent"],
              "DESCRIPTION": "(f) Asthma",
              "YPOS": "10489",
              "XPOS": "13440",
              "TYPE": "discrete",
          },
          "d": {
              "STATES": ["Present", "Absent"],
              "DESCRIPTION": "(d) Coma",
              "YPOS": "12985",
              "XPOS": "13960",
              "TYPE": "discrete",
          },
      }
      cpds_expected = {
          "b": np.array([[0.8, 0.2], [0.2, 0.8]]),
          "e": np.array([[0.8, 0.6], [0.2, 0.4]]),
          "f": np.array([[0.3], [0.7]]),
          "c": np.array([[0.2, 0.05], [0.8, 0.95]]),
          "a": np.array([[0.2], [0.8]]),
          "d": np.array([[0.8, 0.9, 0.7, 0.05], [0.2, 0.1, 0.3, 0.95]]),
      }
      for cpd in model.get_cpds():
          np_test.assert_array_equal(
              cpd.get_values(), cpds_expected[cpd.variable]
          )
      self.assertListEqual(
          sorted(model.edges()),
          sorted(
              [
                  ("b", "d"),
                  ("a", "b"),
                  ("a", "c"),
                  ("c", "d"),
                  ("c", "e"),
              ]
          ),
      )
      self.assertDictEqual(dict(model.nodes), node_expected)
  
imports: import io
  import sys
  import unittest
  import xml.etree.ElementTree
  import networkx
  import numpy
  import numpy.testing
  from pgmpy.factors.discrete import TabularCPD
  from pgmpy.models import BayesianNetwork
  from pgmpy.readwrite import XMLBeliefNetwork
label_desc: Use image node_id 9 for calling the TestXBNReaderTorch obj's underlying member method code with example usage: obj.test_get_model() without return types