code: def _vgg(arch, cfg, batch_norm, **kwargs):
      model = VGG(
          make_layers(cfgs[cfg], batch_norm=batch_norm), **kwargs
      )
      return model
  
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 2 for calling a global function with example usage: _vgg(arch, cfg, batch_norm) and returns: model