code: def model_aggregation(self, ctx, model):
      logger.info(f"begin to agg model")
      self._gather_model(model)
  
      if self._is_master():
          self._aggregator.model_aggregation(ctx, model)
  
      self._sync_model(model)
      logger.info(f"begin to agg model")
  
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 2 for calling the AggregatorClientWrapper obj's underlying member method code with example usage: obj.model_aggregation(ctx, model) without return types