code: def save_server_model(self, request, context):
      aggregator = self.aggregator_map[request.backend]
      aggregator.save_server_model(request.model_path)
      return SaveModelResponse(
          message=f"Server model saved to {request.model_path}"
      )
  
imports: from threading import Condition
  import threading
  import torch
  import bigdl.ppml.fl.nn.pytorch.aggregator
  import bigdl.ppml.fl.nn.tensorflow.aggregator
  from bigdl.ppml.fl.nn.generated.fl_base_pb2 import TensorMap
  from bigdl.ppml.fl.nn.generated.nn_service_pb2 import LoadModelResponse, SaveModelResponse, TrainRequest, TrainResponse, PredictResponse, UploadMetaResponse
  from bigdl.ppml.fl.nn.generated.nn_service_pb2_grpc import *
  from bigdl.ppml.fl.nn.utils import tensor_map_to_ndarray_map
  import tensorflow
  from bigdl.dllib.utils.log4Error import invalidInputError
  from bigdl.ppml.utils.safepickle import SafePickle
  import tempfile
  import traceback
  import os
  import logging
label_desc: Use image node_id 8 for calling the NNServiceImpl obj's underlying member method code with example usage: obj.save_server_model(request, context) and returns: SaveModelResponse