code: def main(seed, config_file="configs/config_alstm.yaml"):
      # set random seed
      with open(config_file) as f:
          config = yaml.safe_load(f)
  
      # seed_suffix = "/seed1000" if "init" in config_file else f"/seed{seed}"
      seed_suffix = ""
      config["task"]["model"]["kwargs"].update(
          {
              "seed": seed,
              "logdir": config["task"]["model"]["kwargs"]["logdir"]
              + seed_suffix,
          }
      )
  
      # initialize workflow
      qlib.init(
          provider_uri=config["qlib_init"]["provider_uri"],
          region=config["qlib_init"]["region"],
      )
      dataset = init_instance_by_config(config["task"]["dataset"])
      model = init_instance_by_config(config["task"]["model"])
  
      # train model
      model.fit(dataset)
  
imports: import argparse
  import qlib
  import ruamel.yaml
  from qlib.utils import init_instance_by_config
label_desc: Use image node_id 1 for calling a global function with example usage: main(seed, config_file) without return types