code: def test_example_inputs(self):
      def fn(a, bc, d):
          b, c = bc
          return a / d - b / c
  
      def compiler_fn(graph, example_inputs):
          nonlocal r1
          r1 = graph(*example_inputs)[0]
          return graph.forward
  
      a = torch.empty(2).fill_(1)
      b = torch.empty(2).fill_(2)
      c = torch.empty(2).fill_(3)
      d = 4
      r1 = None
      r2 = fn(a, (b, c), d)
      opt_fn = torch._dynamo.optimize_assert(compiler_fn)(fn)
      r3 = opt_fn(a, (b, c), d)
  
      self.assertIsNotNone(r1)
      self.assertEqual(r1.size(), r2.size())
      self.assertEqual(r1.stride(), r2.stride())
      self.assertEqual(r1.dtype, r2.dtype)
  
      self.assertEqual(r1.size(), r3.size())
      self.assertEqual(r1.stride(), r3.stride())
      self.assertEqual(r1.dtype, r3.dtype)
  
imports: import functools
  import unittest
  import torch
  import torch._dynamo
  import torch._dynamo.test_case
  from torch._dynamo.backends.debugging import ExplainWithBackend
  from torch._dynamo.backends.onnxrt import has_onnxruntime
  from torch._dynamo.backends.tvm import has_tvm
  from torch._dynamo.testing import same
  from torch.testing._internal.inductor_utils import HAS_CUDA
label_desc: Use image node_id 1 for calling the TestOptimizations obj's underlying member method code with example usage: obj.test_example_inputs() and returns: unknown, graph