code: def setUp(self):
      super().setUp()
      self.opset_version = _constants.ONNX_DEFAULT_OPSET
  
      def incorrect_relu_symbolic_function(g, self):
          return g.op(
              "Add", self, g.op("Constant", value_t=torch.tensor(1.0))
          )
  
      torch.onnx.register_custom_op_symbolic(
          "aten::relu",
          incorrect_relu_symbolic_function,
          opset_version=self.opset_version,
      )
  
      class Model(torch.nn.Module):
          def __init__(self):
              super().__init__()
              self.layers = torch.nn.Sequential(
                  torch.nn.Linear(3, 4),
                  torch.nn.ReLU(),
                  torch.nn.Linear(4, 5),
                  torch.nn.ReLU(),
                  torch.nn.Linear(5, 6),
              )
  
          def forward(self, x):
              return self.layers(x)
  
      self.graph_info = verification.find_mismatch(
          Model(),
          (torch.randn(2, 3),),
          opset_version=self.opset_version,
          options=verification.VerificationOptions(
              backend=self.onnx_backend
          ),
      )
  
imports: import contextlib
  import io
  import tempfile
  import unittest
  import numpy
  import onnx
  import parameterized
  import pytorch_test_common
  import torch
  from packaging import version
  from torch.onnx import _constants, _experimental, verification
  from torch.testing._internal import common_utils
label_desc: Use image node_id 1 for calling the TestFindMismatch obj's underlying member method code with example usage: obj.setUp() and returns: g, self