code: def __init__(self, features, with_pool=True):
      super(VGG, self).__init__()
      self.features = features
      self.with_pool = with_pool
  
      if with_pool:
          self.avgpool = nn.AdaptiveAvgPool2D((7, 7))
  
imports: import os
  from typing import Union
  import numpy
  import paddle
  import paddle.nn
  import paddlehub.vision.transforms
  from paddlehub.module.module import moduleinfo
  from paddlehub.module.cv_module import ImageClassifierModule
  import paddle
  from paddle import nn
label_desc: Use image node_id 1 to create a new VGG object from inherited base classes: nn with example: obj = VGG(features, with_pool)