class_docstr: VGG Atrous multi layer feature extractor which produces multiple output
  feature maps.
  
  Parameters
  ----------
  layers : list of int
      Number of layer for vgg base network.
  filters : list of int
      Number of convolution filters for each layer.
  extras : list of list
      Extra layers configurations.
  batch_norm : bool
      If `True`, will use BatchNorm layers.
class_docstr_tok: ["VGG","Atrous","multi","layer","feature","extractor","which","produces","multiple","output","feature","maps",".","Parameters","--","--","--","--","--","layers",":","list","of","int","Number","of","layer","for","vgg","base","network",".","filters",":","list","of","int","Number","of","convolution","filters","for","each","layer",".","extras",":","list","of","list","Extra","layers","configurations",".","batch_norm",":","bool","If","`","True","`",",","will","use","BatchNorm","layers","."]
code: def hybrid_forward(self, F, x, init_scale):
      x = F.broadcast_mul(x, init_scale)
      assert len(self.stages) == 6
      outputs = []
      for stage in self.stages[:3]:
          x = stage(x)
          x = F.Pooling(
              x,
              pool_type="max",
              kernel=(2, 2),
              stride=(2, 2),
              pooling_convention="full",
          )
      x = self.stages[3](x)
      norm = self.norm4(x)
      outputs.append(norm)
      x = F.Pooling(
          x,
          pool_type="max",
          kernel=(2, 2),
          stride=(2, 2),
          pooling_convention="full",
      )
      x = self.stages[4](x)
      x = F.Pooling(
          x,
          pool_type="max",
          kernel=(3, 3),
          stride=(1, 1),
          pad=(1, 1),
          pooling_convention="full",
      )
      x = self.stages[5](x)
      outputs.append(x)
      for extra in self.extras:
          x = extra(x)
          outputs.append(x)
      return outputs
  
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 VGGAtrousExtractor obj's underlying member method code with example usage: obj.hybrid_forward(F, x, init_scale) and returns: outputs