code: def __init__(
      self,
      n_class=None,
      pretrained_model=None,
      min_input_size=None,
      scales=None,
      flip=None,
      extractor_kwargs=None,
      aspp_kwargs=None,
      decoder_kwargs=None,
  ):
      param, path = utils.prepare_pretrained_model(
          {
              "n_class": n_class,
              "min_input_size": min_input_size,
              "scales": scales,
              "flip": flip,
              "extractor_kwargs": extractor_kwargs,
              "aspp_kwargs": aspp_kwargs,
              "decoder_kwargs": decoder_kwargs,
          },
          pretrained_model,
          self._models,
          default={
              "min_input_size": (513, 513),
              "scales": (1.0,),
              "flip": False,
              "extractor_kwargs": {},
              "aspp_kwargs": {},
              "decoder_kwargs": {},
          },
      )
  
      super(DeepLabV3plusXception65, self).__init__(
          Xception65(**param["extractor_kwargs"]),
          SeparableASPP(2048, 256, **param["aspp_kwargs"]),
          Decoder(
              256, param["n_class"], 48, 256, **param["decoder_kwargs"]
          ),
          min_input_size=param["min_input_size"],
          scales=param["scales"],
          flip=param["flip"],
      )
  
      if path:
          chainer.serializers.load_npz(path, self)
  
imports: from __future__ import division
  import chainer
  import chainer.functions
  import chainer.links
  from chainercv.links.connection import Conv2DBNActiv
  from chainercv.links.connection import SeparableConv2DBNActiv
  from chainercv.links.model.deeplab.aspp import SeparableASPP
  from chainercv.links.model.deeplab.xception import Xception65
  from chainercv.transforms import resize
  from chainercv import utils
  import numpy
label_desc: Use image node_id 1 to create a new DeepLabV3plusXception65 object from inherited base classes: DeepLabV3plus with example: obj = DeepLabV3plusXception65(n_class, pretrained_model, min_input_size, scales, flip, extractor_kwargs, aspp_kwargs, decoder_kwargs)