docstr: If a bad optimization return a graph that
  is not functionally equal to the original graph;
  When config.verify_correctness=True, it will
  check the correctness of outputs and raise an error
docstr_tok: ["If","a","bad","optimization","return","a","graph","that","is","not","functionally","equal","to","the","original","graph",";","When","config.verify_correctness=True",",","it","will","check","the","correctness","of","outputs","and","raise","an","error"]
code: def test_incorrect_verify_true(self):
      """
      If a bad optimization return a graph that
      is not functionally equal to the original graph;
      When config.verify_correctness=True, it will
      check the correctness of outputs and raise an error
      """
      i1 = torch.randn(10)
      i2 = torch.randn(10)
  
      def incorrect_compile_fn(gm, example_inputs):
          return transform(gm).forward
  
      toy_example(i1, i2)
      try:
          opt_toy_example = torch._dynamo.optimize(
              incorrect_compile_fn
          )(toy_example)
          opt_toy_example(i1, i2)
      except RuntimeError:
          pass
      else:
          self.fail("expected failure")
  
imports: import operator
  import torch
  import torch._dynamo
  import torch._dynamo.config
  import torch._dynamo.test_case
  from torch._dynamo.testing import same
label_desc: Use image node_id 3 for calling the TestVerifyCorrectness obj's underlying member method code with example usage: obj.test_incorrect_verify_true() and returns: transform