code: def main(args):
      if use_auto_tune(args):
          dataset = get_dataset(args)
          tune_img_nums = 10
          auto_tune(args, dataset, tune_img_nums)
  
      predictor = DatasetPredictor(args)
      predictor.run_dataset()
  
      if use_auto_tune(args) and os.path.exists(
          args.auto_tuned_shape_file
      ):
          os.remove(args.auto_tuned_shape_file)
  
imports: import argparse
  import codecs
  import os
  import time
  import yaml
  import numpy
  import paddle
  import paddle.nn.functional
  from paddle.inference import create_predictor
  from paddle.inference import Config
  from paddleseg.deploy.infer import DeployConfig
  from paddleseg.cvlibs import manager
  from paddleseg.utils import logger, metrics, progbar
  from infer import auto_tune, use_auto_tune, Predictor
label_desc: Use image node_id 5 for calling a global function with example usage: main(args) without return types