class_docstr: VGG Atrous multi layer base network. You must inherit from it to define
  how the features are computed.
  
  Parameters
  ----------
  layers : list of int
      Number of layer for vgg base network.
  filters : list of int
      Number of convolution filters for each layer.
  batch_norm : bool, default is False
      If `True`, will use BatchNorm layers.
class_docstr_tok: ["VGG","Atrous","multi","layer","base","network",".","You","must","inherit","from","it","to","define","how","the","features","are","computed",".","Parameters","--","--","--","--","--","layers",":","list","of","int","Number","of","layer","for","vgg","base","network",".","filters",":","list","of","int","Number","of","convolution","filters","for","each","layer",".","batch_norm",":","bool",",","default","is","False","If","`","True","`",",","will","use","BatchNorm","layers","."]
code: def hybrid_forward(self, F, x, init_scale):
      raise NotImplementedError
  
imports: from __future__ import division
  import os
  import mxnet
  from mxnet import gluon
  from mxnet.gluon import nn
  from mxnet.initializer import Xavier
label_desc: Use image node_id 2 for calling the VGGAtrousBase obj's underlying member method code with example usage: obj.hybrid_forward(F, x, init_scale) without return types