code: def __init__(self):
      super().__init__()
      self.conv1 = nn.Conv2d(1, 20, 5, 1)
      self.conv2 = nn.Conv2d(20, 50, 5, 1)
      self.bn1 = nn.BatchNorm2d(self.conv1.out_channels)
      self.bn2 = nn.BatchNorm2d(self.conv2.out_channels)
      self.fc1 = nn.Linear(4 * 4 * 50, 500)
      self.fc2 = nn.Linear(500, 10)
  
imports: import sys
  import os
  import math
  import uuid
  import shutil
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from tensorboard.compat.proto.graph_pb2 import GraphDef
  from google.protobuf import text_format
  import unittest
  from unittest import TestCase, main
  from nni.common.graph_utils import build_module_graph, build_graph, TorchModuleGraph, TUPLE_UNPACK_KIND
label_desc: Use image node_id 1 to create a new BackboneModel2 object from inherited base classes: torch.nn with example: obj = BackboneModel2()