code: def main(cfg) -> None:
      logging.info(
          "\n\n************** Experiment configuration ***********"
      )
      logging.info(f"\n{OmegaConf.to_yaml(cfg)}")
  
      trainer = MegatronTrainerBuilder(cfg).create_trainer()
      exp_manager(trainer, cfg.exp_manager)
  
      # hydra interpolation does not work here as the interpolation key is lost when PTL saves hparams
      with open_dict(cfg):
          cfg.model.finetune = True
          cfg.model.precision = cfg.trainer.precision
  
      model = MegatronVitClassificationModel.restore_from(
          restore_path=cfg.model.restore_from_path,
          trainer=trainer,
          override_config_path=cfg.model,
          save_restore_connector=NLPSaveRestoreConnector(),
          strict=False,
      )
  
      trainer.fit(model)
  
imports: from omegaconf.omegaconf import OmegaConf, open_dict
  from nemo.collections.nlp.parts.megatron_trainer_builder import MegatronTrainerBuilder
  from nemo.collections.nlp.parts.nlp_overrides import NLPSaveRestoreConnector
  from nemo.collections.vision.models.megatron_vit_classification_models import MegatronVitClassificationModel
  from nemo.core.config import hydra_runner
  from nemo.utils import logging
  from nemo.utils.exp_manager import exp_manager
label_desc: Use image node_id 1 for calling a global function with example usage: main(cfg) without return types