code: def onnx_graph_to_caffe2_net(
      cls, model, device="CPU", opset_version=_known_opset_version
  ):
      return cls._onnx_model_to_caffe2_net(
          model,
          device=device,
          opset_version=opset_version,
          include_initializers=True,
      )
  
imports: import collections
  import sys
  import zipfile
  import itertools
  import onnx.backend
  from caffe2.python import core, workspace, rnn_cell, gru_cell
  from caffe2.python.model_helper import ModelHelper
  from caffe2.proto import caffe2_pb2
  import caffe2.python.utils
  import numpy
  import onnx
  from onnx import TensorProto
  import onnx.numpy_helper
  import onnx.defs
  import onnx.shape_inference
  import onnx.utils
  from onnx.backend.base import Backend, Device, DeviceType, namedtupledict
  from caffe2.python.onnx.workspace import Workspace
  from caffe2.python.onnx.backend_rep import Caffe2Rep
  import caffe2.python._import_c_extension
  import warnings
label_desc: Use image node_id 24 for calling the Caffe2Backend obj's underlying member method code with example usage: obj.onnx_graph_to_caffe2_net(cls, model, device, opset_version) and returns: cls