code: def test_aten_unsupported(self):
      class Erf(torch.autograd.Function):
          @staticmethod
          def forward(ctx, x):
              erf_out = torch.special.erf(x)
              ctx.save_for_backward(erf_out)
              return erf_out
  
          @staticmethod
          def backward(ctx, grad_output):
              result = ctx.saved_tensors
              return torch.special.erfinv(result), None
  
      class Caller(torch.nn.Module):
          def forward(self, input):
              return Erf.apply(input)
  
      model = Caller()
      input = torch.ones(1, 5)
  
      # Test ONNX_FALLTHROUGH_MODE
      graph, _, _ = _model_to_graph(
          model,
          (input,),
          operator_export_type=OperatorExportTypes.ONNX_FALLTHROUGH,
      )
      iter = graph.nodes()
      self.assertEqual(next(iter).kind(), "prim::PythonOp")
  
      # Test ATEN_FALLBACK_MODE
      graph, _, _ = _model_to_graph(
          model,
          (input,),
          operator_export_type=OperatorExportTypes.ONNX_ATEN_FALLBACK,
      )
      iter = graph.nodes()
      self.assertEqual(next(iter).kind(), "aten::ATen")
  
file_path: pytorch/test/onnx/test_autograd_funs.py
imports: import pytorch_test_common
  import torch
  from onnx_test_common import run_model_test
  from torch.onnx import OperatorExportTypes
  from torch.onnx._globals import GLOBALS
  from torch.onnx.utils import _model_to_graph
  from torch.testing._internal import common_utils
label_desc: Use image node_id 5 for calling the TestAutogradFuns obj's underlying member method code with example usage: obj.test_aten_unsupported() and returns: erf_out, torch,  None, Erf