code: def test_net_conversion_and_append_net(self):
      other = model_helper.ModelHelper()
      fc1 = brew.fc(
          other, "data", "other_fc1", dim_in=3 * 227 * 227, dim_out=10
      )
      fc2 = brew.fc(other, fc1, "other_fc2", dim_in=10, dim_out=10)
      brew.fc(other, fc2, "other_fc3", dim_in=10, dim_out=10)
  
      def add_input_ops(model):
          model.net.UniformFill([], ["data"], shape=[4, 227, 227, 3])
          model.net.UniformFill([], ["label"], shape=[4])
  
      def add_model_ops(model, loss_scale):
          model.NHWC2NCHW("data", "data_nchw")
          model.Conv(
              "data_nchw",
              "conv1",
              3,
              64,
              weight_init=("MSRAFill", {}),
              kernel=7,
              stride=2,
              pad=3,
              no_bias=0,
          )
          model.SpatialBN(
              "conv1",
              "conv1_spatbn_relu",
              64,
              epsilon=1e-3,
              is_test=False,
          )
          model.Relu("conv1_spatbn_relu", "conv1_spatbn_relu")
          model.MaxPool(
              "conv1_spatbn_relu", "pool1", kernel=3, stride=2
          )
          model.FC("pool1", "fc", dim_in=(64 * 56 * 56), dim_out=10)
  
          # Append the net and param_init_net of the other model
          appendnet = data_parallel_model.ConvertNetForDevice(other.net)
          model.net.AppendNet(appendnet)
  
          model.param_init_net.AppendNet(
              data_parallel_model.ConvertNetForDevice(
                  other.param_init_net
              )
          )
  
          model.Sigmoid("fc", "fc_sigm")
          model.Softmax("fc_sigm", "softmax")
          loss = model.AveragedLoss("softmax", "loss")
          return [loss]
  
      def add_optimizer(model):
          optimizer.build_sgd(model, 0.1, policy="fixed", momentum=0.9)
  
      model = cnn.CNNModelHelper(
          order="NCHW",
          name="test",
      )
      data_parallel_model.Parallelize_CPU(
          model,
          input_builder_fun=add_input_ops,
          forward_pass_builder_fun=add_model_ops,
          optimizer_builder_fun=add_optimizer,
          devices=range(4),
      )
  
      # Just create and run net and confirm no exception is thrown
      workspace.RunNetOnce(model.param_init_net)
      workspace.CreateNet(model.net)
      workspace.RunNet(model.net)
  
imports: from multiprocessing import Process, Queue
  import numpy
  import os
  import shutil
  import tempfile
  import unittest
  import time
  from unittest.mock import Mock
  from hypothesis import assume, given, settings
  import hypothesis.strategies
  from caffe2.proto import caffe2_pb2
  from caffe2.python import brew, core, cnn, data_parallel_model, dyndep, model_helper, optimizer, rnn_cell, workspace
  from caffe2.python.test_util import TestCase
label_desc: Use image node_id 5 for calling the DataParallelModelTest obj's underlying member method code with example usage: obj.test_net_conversion_and_append_net() and returns: list