code: def __init__(self):
      super().__init__()
      self.conv1 = torch.nn.Conv2d(1, 20, 5, 1)
      self.conv2 = torch.nn.Conv2d(20, 50, 5, 1)
      self.fc1 = torch.nn.Linear(4 * 4 * 50, 500)
      self.fc2 = torch.nn.Linear(500, 10)
      self.relu1 = torch.nn.ReLU6()
      self.relu2 = torch.nn.ReLU6()
      self.relu3 = torch.nn.ReLU6()
      self.max_pool1 = torch.nn.MaxPool2d(2, 2)
      self.max_pool2 = torch.nn.MaxPool2d(2, 2)
  
imports: import os
  import torch
  import torch.nn.functional
  from torchvision.models.vgg import vgg16
  from torchvision import datasets, transforms
  import unittest
  from unittest import TestCase, main
  from nni.compression.quantization import QATQuantizer
  from nni.compression.quantization_speedup import ModelSpeedupTensorRT
label_desc: Use image node_id 1 to create a new BackboneModel object from inherited base classes: torch.nn with example: obj = BackboneModel()