code: def parse_args():
      parser = argparse.ArgumentParser(description="Model pruning")
      # params of pruning
      parser.add_argument(
          "--config",
          dest="cfg",
          help="The config file.",
          type=str,
          default=None,
      )
      parser.add_argument(
          "--batch_size",
          dest="batch_size",
          help="Mini batch size of one gpu or cpu",
          type=int,
          default=None,
      )
      parser.add_argument(
          "--learning_rate",
          dest="learning_rate",
          help="Learning rate",
          type=float,
          default=None,
      )
      parser.add_argument(
          "--pruning_ratio",
          dest="pruning_ratio",
          help="The ratio of model pruning.",
          type=float,
          default=None,
          required=True,
      )
      parser.add_argument(
          "--retraining_iters",
          dest="retraining_iters",
          help="Number of iterations of retraining.",
          type=int,
          default=None,
          required=True,
      )
      parser.add_argument(
          "--save_dir",
          dest="save_dir",
          help="The directory for saving the model snapshot",
          type=str,
          default="./output",
      )
      parser.add_argument(
          "--model_path",
          dest="model_path",
          help="The path of model for evaluation",
          type=str,
          default=None,
      )
      parser.add_argument(
          "--num_workers",
          dest="num_workers",
          help="Num workers for data loader",
          type=int,
          default=0,
      )
      parser.add_argument(
          "--opts",
          help="Update the key-value pairs of all options.",
          nargs="+",
      )
  
      return parser.parse_args()
  
file_path: PaddleSeg/deploy/slim/prune/prune.py
imports: import argparse
  import os
  import shutil
  from functools import partial
  import yaml
  import paddle
  from paddleslim.dygraph import L1NormFilterPruner
  from paddleslim.analysis import dygraph_flops
  from paddleseg.cvlibs import Config, SegBuilder
  from paddleseg.core.val import evaluate
  from paddleseg.core.train import train
  from paddleseg.utils import logger, utils
label_desc: Use image node_id 1 for calling a global function with example usage: parse_args() and returns: parser