code: def test_str(self):
      self.expected_string = """network unknown {
  }
  variable bowel-problem {
      type discrete [ 2 ] { 0, 1 };
      property position = (335, 99) ;
      property weight = None ;
  }
  variable dog-out {
      type discrete [ 2 ] { 0, 1 };
      property position = (300, 195) ;
      property weight = None ;
  }
  variable family-out {
      type discrete [ 2 ] { 0, 1 };
      property position = (257, 99) ;
      property weight = None ;
  }
  variable hear-bark {
      type discrete [ 2 ] { 0, 1 };
      property position = (296, 268) ;
      property weight = None ;
  }
  variable kid {
      type discrete [ 2 ] { 0, 1 };
      property position = (100, 165) ;
      property weight = None ;
  }
  variable light-on {
      type discrete [ 2 ] { 0, 1 };
      property position = (218, 195) ;
      property weight = None ;
  }
  probability ( bowel-problem ) {
      table 0.01, 0.99 ;
  }
  probability ( dog-out | bowel-problem, family-out ) {
      ( 0, 0 ) 0.99, 0.01;
      ( 0, 1 ) 0.9, 0.1;
      ( 1, 0 ) 0.97, 0.03;
      ( 1, 1 ) 0.3, 0.7;
  
  }
  probability ( family-out ) {
      table 0.15, 0.85 ;
  }
  probability ( hear-bark | dog-out ) {
      ( 0 ) 0.7, 0.3;
      ( 1 ) 0.01, 0.99;
  
  }
  probability ( kid ) {
      table 0.3, 0.7 ;
  }
  probability ( light-on | family-out ) {
      ( 0 ) 0.6, 0.4;
      ( 1 ) 0.95, 0.05;
  
  }
  """
      self.maxDiff = None
      self.assertEqual(self.writer.__str__(), self.expected_string)
  
imports: import os
  import unittest
  import networkx
  import numpy
  import numpy.testing
  from pgmpy import config
  from pgmpy.factors.discrete import TabularCPD
  from pgmpy.models import BayesianNetwork
  from pgmpy.readwrite import BIFReader, BIFWriter
label_desc: Use image node_id 2 for calling the TestBIFWriterTorch obj's underlying member method code with example usage: obj.test_str() without return types