code: def main():
      parser = argparse.ArgumentParser()
  
      parser.add_argument(
          "model_name", choices=("resnet50", "resnet101", "resnet152")
      )
      parser.add_argument("caffemodel")
      parser.add_argument("output", nargs="?", default=None)
      args = parser.parse_args()
  
      caffemodel = CaffeFunction(args.caffemodel)
      if args.model_name == "resnet50":
          model = ResNet50(
              pretrained_model=None, n_class=1000, arch="he"
          )
          model(np.zeros((1, 3, 224, 224), dtype=np.float32))
          _transfer_resnet50(caffemodel, model)
      elif args.model_name == "resnet101":
          model = ResNet101(
              pretrained_model=None, n_class=1000, arch="he"
          )
          model(np.zeros((1, 3, 224, 224), dtype=np.float32))
          _transfer_resnet101(caffemodel, model)
      elif args.model_name == "resnet152":
          model = ResNet152(
              pretrained_model=None, n_class=1000, arch="he"
          )
          model(np.zeros((1, 3, 224, 224), dtype=np.float32))
          _transfer_resnet152(caffemodel, model)
  
      if args.output is None:
          output = "{}_imagenet_convert.npz".format(args.model_name)
      else:
          output = args.output
      chainer.serializers.save_npz(output, model)
  
file_path: chainercv/examples/resnet/caffe2npz.py
imports: import argparse
  import numpy
  import chainer
  from chainer.links.caffe.caffe_function import CaffeFunction
  from chainercv.links import ResNet101
  from chainercv.links import ResNet152
  from chainercv.links import ResNet50
label_desc: Use image node_id 8 for calling a global function with example usage: main() without return types