code: def get_model(name, task):
      n_class = _n_class[task]
      model = _model_class[name](
          n_class,
          min_input_size=(513, 513),
          scales=(1.0,),
          flip=False,
          extractor_kwargs={},
          aspp_kwargs={},
          decoder_kwargs={},
      )
      return model
  
file_path: chainercv/examples/deeplab/tf2npz.py
imports: import argparse
  import chainer
  from chainercv.datasets import ade20k_semantic_segmentation_label_names
  from chainercv.datasets import cityscapes_semantic_segmentation_label_names
  from chainercv.datasets import voc_semantic_segmentation_label_names
  from chainercv.links import DeepLabV3plusXception65
  import tensorflow
label_desc: Use image node_id 2 for calling a global function with example usage: get_model(name, task) and returns: model