code: def get_xcetption(
      pretrained=False, ctx=cpu(), root="~/.mxnet/models", **kwargs
  ):
      r"""Xception model from
  
      Parameters
      ----------
      pretrained : bool or str
          Boolean value controls whether to load the default pretrained weights for model.
          String value represents the hashtag for a certain version of pretrained weights.
      ctx : Context, default CPU
          The context in which to load the pretrained weights.
      root : str, default $MXNET_HOME/models
          Location for keeping the model parameters.
      norm_layer : object
          Normalization layer used (default: :class:`mxnet.gluon.nn.BatchNorm`)
          Can be :class:`mxnet.gluon.nn.BatchNorm` or :class:`mxnet.gluon.contrib.nn.SyncBatchNorm`.
      norm_kwargs : dict
          Additional `norm_layer` arguments, for example `num_devices=4`
          for :class:`mxnet.gluon.contrib.nn.SyncBatchNorm`.
      """
      net = Xception65(**kwargs)
      if pretrained:
          from .model_store import get_model_file
  
          net.load_parameters(
              get_model_file("xception", tag=pretrained, root=root),
              ctx=ctx,
          )
          from ..data import ImageNet1kAttr
  
          attrib = ImageNet1kAttr()
          net.synset = attrib.synset
          net.classes = attrib.classes
          net.classes_long = attrib.classes_long
      return net
  
imports: from mxnet.context import cpu
  import mxnet.gluon.nn
label_desc: Use image node_id 1 for calling a global function with example usage: get_xcetption(pretrained, ctx, root) and returns: net