code: def validate_client_id(self, client_id):
      try:
          client_id = int(client_id)
      except:
          invalidInputError(
              False, f"client ID must be a number, got {client_id}"
          )
  
      if client_id <= 0 or client_id > self.client_num:
          invalidInputError(
              False,
              f"invalid client ID received: {client_id}, \
                  must be in range of client number [1, {self.client_num}]",
          )
  
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 7 for calling the NNServiceImpl obj's underlying member method code with example usage: obj.validate_client_id(client_id) without return types