code: def main():
      parser = argparse.ArgumentParser(
          description="Script to convert mxnet params to chainer npz"
      )
      parser.add_argument(
          "mxnet_param_file",
          metavar="mxnet-param-file",
          help="Mxnet param file i.e. fcis_coco-0000.params",
      )
      parser.add_argument("--process", action="store_true")
      parser.add_argument(
          "--dataset", choices=("sbd", "coco"), type=str, default="sbd"
      )
      parser.add_argument("--out", "-o", type=str, default=None)
      args = parser.parse_args()
  
      if args.dataset == "sbd":
          model = FCISResNet101(n_fg_class=20, pretrained_model=None)
      elif args.dataset == "coco":
          model = FCISResNet101(
              n_fg_class=80,
              pretrained_model=None,
              anchor_scales=[4, 8, 16, 32],
              proposal_creator_params={
                  "nms_thresh": 0.7,
                  "n_train_pre_nms": 6000,
                  "n_train_post_nms": 300,
                  "n_test_pre_nms": 6000,
                  "n_test_post_nms": 300,
                  "force_cpu_nms": False,
                  "min_size": 2,
              },
          )
      params = mx.nd.load(args.mxnet_param_file)
      print("mxnet param is loaded: {}".format(args.mxnet_param_file))
      print("start conversion")
      if args.process:
          tests = [k for k in params.keys() if k.endswith("_test")]
          for test in tests:
              params[test.replace("_test", "")] = params.pop(test)
      model = convert(model, params)
      print("finish conversion")
      if args.out is None:
          out = "fcis_resnet101_{}_converted.npz".format(args.dataset)
      print("saving to {}".format(out))
      chainer.serializers.save_npz(out, model)
  
imports: import argparse
  import chainer
  import mxnet
  from chainercv.experimental.links import FCISResNet101
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types