code: def prepare(
      cls,
      model,  # type: ModelProto
      device="CPU",  # type: Text
      minimum_ios_deployment_target="13",  # type: str
      **kwargs,  # type: Any
  ):
      # type: (...) -> CoreMLRep
      super(CoreMLBackendND, cls).prepare(model, device, **kwargs)
      if DEBUG:
          with open("/tmp/node_model.onnx", "wb") as f:
              s = model.SerializeToString()
              f.write(s)
      coreml_model = convert(
          model,
          minimum_ios_deployment_target=minimum_ios_deployment_target,
      )
      if DEBUG:
          coreml_model.save("/tmp/node_model.mlmodel")
      onnx_outputs_info = _get_onnx_outputs_info(model)
      return CoreMLRep(
          coreml_model,
          onnx_outputs_info,
          device == "CPU",
          minimum_ios_deployment_target=minimum_ios_deployment_target,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  from typing import Any, Text, Dict, Tuple
  from onnx import ModelProto
  from onnx.backend.base import Backend
  from six import string_types
  from ._backend_rep import CoreMLRep
  from ._converter import convert
  import onnx
  from ._graph import _input_from_onnx_input, EdgeInfo
label_desc: Use image node_id 1 for calling the CoreMLBackendND obj's underlying member method code with example usage: obj.prepare(cls, model, device, minimum_ios_deployment_target) and returns: CoreMLRep