code: def prepare(
      cls, model: ModelProto, device: str = "CPU", **kwargs: Any
  ) -> Optional[onnx.backend.base.BackendRep]:
      super().prepare(model, device, **kwargs)
  
      onnx.checker.check_model(model)
  
      # by default test strict shape inference
      kwargs = {"check_type": True, "strict_mode": True, **kwargs}
      model = onnx.shape_inference.infer_shapes(model, **kwargs)
  
      value_infos = {
          vi.name: vi
          for vi in itertools.chain(
              model.graph.value_info, model.graph.output
          )
      }
  
      if do_enforce_test_coverage_safelist(model):
          for node in model.graph.node:
              for i, output in enumerate(node.output):
                  if node.op_type == "Dropout" and i != 0:
                      continue
                  assert output in value_infos
                  tt = value_infos[output].type.tensor_type
                  assert tt.elem_type != TensorProto.UNDEFINED
                  for dim in tt.shape.dim:
                      assert dim.WhichOneof("value") == "dim_value"
  
      raise BackendIsNotSupposedToImplementIt(
          "This is the dummy backend test that doesn't verify the results but does run the checker"
      )
  
file_path: onnx/onnx/test/test_backend_test.py
imports: import itertools
  import os
  import platform
  import unittest
  from typing import Any, Optional, Sequence, Tuple
  import numpy
  import onnx.backend.base
  import onnx.backend.test
  import onnx.shape_inference
  import onnx.version_converter
  from onnx import ModelProto, NodeProto, TensorProto
  from onnx.backend.base import Device, DeviceType
  from onnx.backend.test.runner import BackendIsNotSupposedToImplementIt
label_desc: Use image node_id 1 for calling the DummyBackend obj's underlying member method code with example usage: obj.prepare(cls, model, device) without return types