code: def __init__(self, conf) -> None:
      self.model = None
      self.client_data = {"train": {}, "eval": {}, "pred": {}}
      self.server_data = {"train": {}, "eval": {}, "pred": {}}
      self.client_num = conf["clientNum"]
      self.condition = Condition()
      self._lock = threading.Lock()
      self.optimizer_cls = None
      self.optimizer_args = None
      self.secret_key = (
          conf["secretKey"] if "secretKey" in conf.keys() else None
      )
      self.salt = conf["salt"] if "salt" in conf.keys() else None
      logging.info(
          f"Initialized Tensorflow aggregator [client_num: {self.client_num}]"
      )
  
file_path: BigDL/python/ppml/src/bigdl/ppml/fl/nn/tensorflow/aggregator.py
imports: import os
  from bigdl.ppml.utils.safepickle import SafePickle
  import logging
  import threading
  from bigdl.dllib.utils.log4Error import invalidInputError, invalidOperationError
  from bigdl.ppml.fl.nn.utils import ndarray_map_to_tensor_map
  from threading import Condition
  import numpy
  import tensorflow
label_desc: Use image node_id 1 to create a new Aggregator object from inherited base classes: object with example: obj = Aggregator(conf)