code: def _gather_model(self, model):
      if (
          not self._args.deepspeed
          or not self._args.hf_deepspeed_config.is_zero3()
      ):
          return
  
      while hasattr(model, "module"):
          model = model.module
  
      for _, p in model.named_parameters():
          p.all_gather()
  
imports: import logging
  import numpy
  import torch
  import torch.distributed
  from transformers.training_args import TrainingArguments
  from fate.ml.aggregator import AggregatorType, aggregator_map
label_desc: Use image node_id 6 for calling the AggregatorClientWrapper obj's underlying member method code with example usage: obj._gather_model(model) without return types