code: def main(args):
      if args.seed is not None:
          paddle.seed(args.seed)
          np.random.seed(args.seed)
          random.seed(args.seed)
          logger.info("Set seed to {}".format(args.seed))
  
      env_info = get_sys_env()
      info = ["{}: {}".format(k, v) for k, v in env_info.items()]
      info = "\n".join(
          ["", format("Environment Information", "-^48s")]
          + info
          + ["-" * 48]
      )
      logger.info(info)
  
      place = (
          "gpu"
          if env_info["Paddle compiled with cuda"]
          and env_info["GPUs used"]
          else "cpu"
      )
  
      paddle.set_device(place)
  
      if not args.cfg:
          raise RuntimeError("No configuration file specified.")
  
      cfg = Config(
          args.cfg,
          learning_rate=args.learning_rate,
          iters=args.iters,
          batch_size=args.batch_size,
      )
  
      if cfg.dic["data"]["source"]["dataset"] == "synthia":
          train_dataset_src = SYNTHIADataset(
              split="train", **cfg.dic["data"]["source"]["kwargs"]
          )
          val_dataset_src = SYNTHIADataset(
              split="val", **cfg.dic["data"]["source"]["kwargs"]
          )
      elif cfg.dic["data"]["source"]["dataset"] == "gta5":
          train_dataset_src = GTA5Dataset(
              split="train", **cfg.dic["data"]["source"]["kwargs"]
          )
          val_dataset_src = GTA5Dataset(
              split="val", **cfg.dic["data"]["source"]["kwargs"]
          )
      else:
          raise NotImplementedError()
      if cfg.dic["data"]["target"]["dataset"] == "cityscapes":
          train_dataset_tgt = CityDataset(
              split="train", **cfg.dic["data"]["target"]["kwargs"]
          )
          val_dataset_tgt = CityDataset(
              split="val", **cfg.dic["data"]["target"]["kwargs"]
          )
      else:
          raise NotImplementedError()
  
      val_dataset_tgt = val_dataset_tgt if args.do_eval else None
      val_dataset_src = val_dataset_src if args.do_eval else None
  
      if train_dataset_src is None:
          raise RuntimeError(
              "The training dataset is not specified in the configuration file."
          )
      elif len(train_dataset_src) == 0:
          raise ValueError(
              "The length of train_dataset is 0. Please check if your dataset is valid"
          )
  
      msg = "\n---------------Config Information---------------\n"
      msg += str(cfg)
      msg += "------------------------------------------------"
      logger.info(msg)
  
      trainer = Trainer(model=cfg.model, cfg=cfg.dic)
      trainer.train(
          train_dataset_src,
          train_dataset_tgt,
          val_dataset_tgt=val_dataset_tgt,
          val_dataset_src=val_dataset_src,
          optimizer=cfg.optimizer,
          save_dir=args.save_dir,
          iters=cfg.iters,
          batch_size=cfg.batch_size,
          resume_model=args.resume_model,
          save_interval=args.save_interval,
          log_iters=args.log_iters,
          num_workers=args.num_workers,
          use_vdl=args.use_vdl,
          keep_checkpoint_max=args.keep_checkpoint_max,
          test_config=cfg.test_config,
      )
  
file_path: PaddleSeg/contrib/DomainAdaptation/train.py
imports: import random
  import argparse
  import numpy
  import paddle
  from paddleseg.utils import logger, get_sys_env
  import utils
  from cvlibs import Config
  from script.train import Trainer
  from datasets import CityDataset, GTA5Dataset, SYNTHIADataset
label_desc: Use image node_id 2 for calling a global function with example usage: main(args) without return types