code: def parse_args():
      parser = argparse.ArgumentParser(description="Model evaluation")
  
      # params of evaluate
      parser.add_argument(
          "--config",
          dest="cfg",
          help="The config file.",
          default=None,
          type=str,
      )
  
      parser.add_argument(
          "--model_path",
          dest="model_path",
          help="The path of model for evaluation",
          type=str,
          default="saved_model/vnet_lung_coronavirus_128_128_128_15k/best_model/model.pdparams",
      )
  
      parser.add_argument(
          "--predict_next_stage",
          action="store_true",
          default=False,
          help="whether predict stage 2 training data.",
      )
  
      parser.add_argument(
          "--val_save_folder",
          dest="val_save_folder",
          help="The path to val data predicted result",
          type=str,
          default="val_save_folder",
      )
  
      parser.add_argument(
          "--precision",
          default="fp32",
          type=str,
          choices=["fp32", "fp16"],
          help="Use AMP (Auto mixed precision) if precision='fp16'. If precision='fp32', the training is normal.",
      )
  
      parser.add_argument(
          "--do_mirroring",
          dest="do_mirroring",
          type=bool,
          default=True,
          help="Whether use mirroring when inference.",
      )
  
      parser.add_argument(
          "--use_sliding_window",
          dest="use_sliding_window",
          type=bool,
          default=True,
          help="Whether use sliding window when inference.",
      )
  
      parser.add_argument(
          "--step_size",
          dest="step_size",
          type=float,
          default=0.5,
          help="step size when predict.",
      )
  
      parser.add_argument(
          "--use_gaussian",
          dest="use_gaussian",
          type=bool,
          default=True,
          help="Whether use gaussian.",
      )
  
      parser.add_argument(
          "--verbose",
          dest="verbose",
          type=bool,
          default=True,
          help="Whether print log.",
      )
  
      return parser.parse_args()
  
file_path: PaddleSeg/contrib/MedicalSeg/nnunet/single_fold_eval.py
imports: import argparse
  import os
  import shutil
  import paddle
  import numpy
  import pickle
  import sys
  from medicalseg.cvlibs import Config
  from medicalseg.utils import get_sys_env, logger, config_check, utils
  from nnunet.utils import DynamicPredictor, save_segmentation_nifti_from_softmax, aggregate_scores, determine_postprocessing, resample_and_save, predict_next_stage
label_desc: Use image node_id 3 for calling a global function with example usage: parse_args() and returns: parser