code: def _make_fake_loop_op(self, body_nodes, input_types, output_types):
      ten = helper.make_tensor(
          "trip_count_value", TensorProto.INT64, (1,), [10]
      )
      true = helper.make_tensor(
          "condition", TensorProto.BOOL, (1,), [True]
      )
      # lcd is a dummy loop-carried dependency that only exists because
      # right now the schema checker is broken and assumes a variadic
      # input needs at least one value.
      graph_inputs = [
          helper.make_tensor_value_info("i", TensorProto.INT64, (1,)),
          helper.make_tensor_value_info("cond", TensorProto.BOOL, (1,)),
      ]
      for type, shape, name in input_types:
          graph_inputs.append(
              helper.make_tensor_value_info("_" + name, type, shape)
          )
      graph_outputs = [
          helper.make_tensor_value_info("cond", TensorProto.BOOL, (1,))
      ]
      for type, shape, name in output_types:
          graph_outputs.append(
              helper.make_tensor_value_info("_" + name, type, shape)
          )
      body_graph = helper.make_graph(
          body_nodes, "body_graph", graph_inputs, graph_outputs
      )
      loop_inputs = ["trip_count", "condition"]
      loop_inputs.extend([name for _, _, name in input_types])
      loop_outputs = [name for _, _, name in output_types]
      retval_nodes = [
          helper.make_node("Constant", [], ["trip_count"], value=ten),
          helper.make_node("Constant", [], ["condition"], value=true),
          helper.make_node(
              "Loop", loop_inputs, loop_outputs, body=body_graph
          ),
      ]
      return retval_nodes
  
imports: import json
  import tempfile
  import textwrap
  import traceback
  import unittest
  import zipfile
  from caffe2.proto import caffe2_pb2
  from caffe2.python import brew, core
  from caffe2.python.model_helper import ModelHelper
  from click.testing import CliRunner
  import numpy
  from onnx import helper, ModelProto, TensorProto
  from caffe2.python.onnx.helper import c2_native_run_net
  from caffe2.python.onnx.bin.conversion import caffe2_to_onnx, onnx_to_caffe2
  import caffe2.python.onnx.backend
  from caffe2.python.onnx.tests.test_utils import TestCase
label_desc: Use image node_id 8 for calling the TestConversion obj's underlying member method code with example usage: obj._make_fake_loop_op(body_nodes, input_types, output_types) and returns: retval_nodes