class_docstr: Main class for model parallel with data parallel training.
code: def clip_grad_norm(self, clip_norm):
      def _aggregate_model_parallel_grad_norm(total_norm):
          total_norm = total_norm**2
          distributed_utils.all_reduce(
              total_norm,
              group=distributed_utils.get_model_parallel_group(),
          )
          total_norm = total_norm**0.5
          return total_norm
  
      return self.optimizer.clip_grad_norm(
          clip_norm,
          aggregate_norm_fn=_aggregate_model_parallel_grad_norm,
      )
  
file_path: fairseq/fairseq/model_parallel/megatron_trainer.py
imports: from fairseq.dataclass.configs import FairseqConfig
  from fairseq.distributed import utils
  from fairseq.trainer import Trainer
label_desc: Use image node_id 2 for calling the MegatronTrainer obj's underlying member method code with example usage: obj.clip_grad_norm(clip_norm) and returns: self, total_norm