code: def _create_control_op(cls, init_model, pred_model, n, opset_version):
      control_inputs = []
      if "__control_inputs" in n.attrs:
          control_inputs.extend(n.attrs["__control_inputs"])
      node = cls._common_onnx_node_to_caffe2_op(
          init_model, pred_model, n, opset_version
      )
      node.control_input.extend(control_inputs)
      return Caffe2Ops([node], [], [])
  
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 7 for calling the Caffe2Backend obj's underlying member method code with example usage: obj._create_control_op(cls, init_model, pred_model, n, opset_version) and returns: Caffe2Ops