class_docstr: DeepLabWV3Plus
  
  Parameters
  ----------
  nclass : int
      Number of categories for the training dataset.
  backbone : string
      Pre-trained dilated backbone network type (default:'wideresnet').
  norm_layer : object
      Normalization layer used in backbone network (default: :class:`mxnet.gluon.nn.BatchNorm`;
      for Synchronized Cross-GPU BachNormalization).
  aux : bool
      Auxiliary loss.
  
  Reference:
  
      Chen, Liang-Chieh, et al. "Encoder-Decoder with Atrous Separable Convolution for Semantic
      Image Segmentation.", https://arxiv.org/abs/1802.02611, ECCV 2018
class_docstr_tok: ["DeepLabWV3Plus","Parameters","--","--","--","--","--","nclass",":","int","Number","of","categories","for","the","training","dataset",".","backbone",":","string","Pre-trained","dilated","backbone","network","type","(","default",":","'wideresnet","'",")",".","norm_layer",":","object","Normalization","layer","used","in","backbone","network","(","default",":",":","class",":","`","mxnet.gluon.nn.BatchNorm","`",";","for","Synchronized","Cross-GPU","BachNormalization",")",".","aux",":","bool","Auxiliary","loss",".","Reference",":","Chen",",","Liang-Chieh",",","et","al",".","``","Encoder-Decoder","with","Atrous","Separable","Convolution","for","Semantic","Image","Segmentation",".","``",",","https",":","\/\/arxiv.org\/abs\/1802.02611",",","ECCV","2018"]
code: def demo(self, x):
      return self.predict(x)
  
imports: from mxnet.gluon import nn
  from mxnet.context import cpu
  from mxnet.gluon.nn import HybridBlock
  from .wideresnet import wider_resnet38_a2
label_desc: Use image node_id 3 for calling the DeepLabWV3Plus obj's underlying member method code with example usage: obj.demo(x) and returns: self