code: def main(cfg) -> None:
      logging.info(
          "\n\n************** Experiment configuration ***********"
      )
      logging.info(f"\n{OmegaConf.to_yaml(cfg)}")
  
      assert (
          cfg.trainer.devices * cfg.trainer.num_nodes
      ) * cfg.model.micro_batch_size == cfg.model.global_batch_size, (
          "Gradient accumulation is not supported in CLIP yet."
      )
  
      trainer = MegatronTrainerBuilder(cfg).create_trainer()
      exp_manager(trainer, cfg.exp_manager)
  
      model = MegatronCLIPModel(cfg.model, trainer)
  
      trainer.fit(model)
  
imports: from omegaconf.omegaconf import OmegaConf
  from nemo.collections.multimodal.models.vision_language_foundation.clip.megatron_clip_models import MegatronCLIPModel
  from nemo.collections.nlp.parts.megatron_trainer_builder import MegatronTrainerBuilder
  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