code: def test_contrib_op_with_loop(self):
      class M(torch.nn.Module):
          def __init__(self):
              super().__init__()
              self.gelu = torch.nn.GELU(approximate="none")
  
          def forward(self, x):
              res = []
              res2 = []
              for i in range(x.size(0)):
                  if len(res) > 0:
                      res2.append(res[0])
                  else:
                      res2.append(self.gelu(x[0]))
                  res.append(x[0])
              return torch.stack(res), torch.stack(res2)
  
      def symbolic_custom_gelu(g, input, approximate):
          return g.op("com.microsoft::Gelu", input).setType(
              input.type()
          )
  
      from torch.onnx import register_custom_op_symbolic
  
      register_custom_op_symbolic("::gelu", symbolic_custom_gelu, 1)
  
      x = torch.randn(3, 3, 4, requires_grad=True)
      model = torch.jit.script(M())
      onnx_test_common.run_model_test(self, model, input_args=(x,))
  
file_path: pytorch/test/onnx/test_custom_ops.py
imports: import onnx_test_common
  import pytorch_test_common
  import torch
  import torch.utils.cpp_extension
  from torch.onnx import symbolic_helper
  from torch.testing._internal import common_utils
label_desc: Use image node_id 1 for calling the TestExportAsContribOps obj's underlying member method code with example usage: obj.test_contrib_op_with_loop() and returns: g, torch,  torch