code: def main(cfg: DictConfig):
      """
      Train a diffusion model.
  
      Args:
          cfg: Configuration for training.
      """
      model, diffusion, dataloader = setup(cfg, train=True)
      trainer = hydra.utils.instantiate(
          cfg.trainer,
          model=model,
          diffusion=diffusion,
          data=dataloader,
          schedule_sampler={"diffusion": diffusion},
      )
  
      if cfg.trainer.get("resume_checkpoint"):
          logger.log(
              f"resume training from checkpoint {cfg.trainer.resume_checkpoint}..."
          )
      else:
          logger.log("start training...")
      trainer.run_loop()
  
imports: import hydra
  from bits_back_diffusion.script_util import setup
  from improved_diffusion import logger
  from omegaconf import DictConfig
label_desc: Use image node_id 1 for calling a global function with example usage: main(cfg) without return types