code: def __init__(self, ctx):
      aggregator = [ctx.guest.get("agg_type")]
      aggregator.extend(ctx.hosts.get("agg_type"))
      aggregator = set(aggregator)
      if len(aggregator) > 1:
          raise ValueError(
              "Aggregator type should be the same between clients, but got {}".format(
                  aggregator
              )
          )
      aggregator = aggregator.pop()
      aggregator_name = "fedavg"
      aggregator_server = aggregator_map[aggregator][1]
      logger.info(f"Using {aggregator} aggregator")
      aggregator = aggregator_server(
          ctx, aggregator_name=aggregator_name
      )
  
      self._aggregator = aggregator
  
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 1 to create a new AggregatorServerWrapper object from inherited base classes: object with example: obj = AggregatorServerWrapper(ctx)