code: def test_versioned_div_scalar_scalar(self):
      class MyModule(torch.nn.Module):
          def forward(self, a: float, b: int, c: float, d: int):
              result_0 = a / b
              result_1 = a / c
              result_2 = b / c
              result_3 = b / d
              return (result_0, result_1, result_2, result_3)
  
      try:
          v3_mobile_module = _load_for_lite_interpreter(
              pytorch_test_dir
              + "/cpp/jit/upgrader_models/test_versioned_div_scalar_scalar_v2.ptl"
          )
      except Exception as e:
          self.skipTest("Failed to load fixture!")
  
      current_mobile_module = self._save_load_mobile_module(MyModule)
  
      def _helper(m, fn):
          vals = (5.0, 3, 2.0, 7)
          m_result = m(*vals)
          fn_result = fn(*vals)
          for mr, hr in zip(m_result, fn_result):
              self.assertEqual(mr, hr)
  
      _helper(v3_mobile_module, current_mobile_module)
  
imports: from itertools import product
  import io
  import os
  import sys
  import hypothesis.strategies
  from hypothesis import example, settings, given
  from typing import Union
  import torch
  from torch.testing._internal.jit_utils import JitTestCase
  from torch.jit.mobile import _load_for_lite_interpreter
label_desc: Use image node_id 12 for calling the TestSaveLoadForOpVersion obj's underlying member method code with example usage: obj.test_versioned_div_scalar_scalar() and returns: result_0,  result_1,  result_2,  result_3