code: def loss_aggregation(self, ctx, loss):
      logger.info(f"begin to agg loss")
      loss = self._gather_loss(loss)
  
      logger.info(f"end to gather loss")
  
      if isinstance(loss, (int, float)):
          loss_type = "single"
      else:
          loss_type = "multi"
  
      if self._is_master():
          loss = self._aggregator.loss_aggregation(ctx, loss)
          self._sync_loss(loss, loss_type=loss_type)
      else:
          loss = self._sync_loss(loss, loss_type=loss_type)
  
      logger.info(f"end to agg loss")
      return loss
  
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 3 for calling the AggregatorClientWrapper obj's underlying member method code with example usage: obj.loss_aggregation(ctx, loss) and returns: loss