code: def create_and_start_parameters_server(
      cluster_spec: tf.train.ClusterSpec, config: tf.ConfigProto = None
  ) -> None:
      """
      Create and start a parameter server
      :param cluster_spec: the ClusterSpec object representing the cluster
      :param config: the tensorflow config to use
      :return: None
      """
      # create a server object for the parameter server
      server = tf.train.Server(
          cluster_spec, job_name="ps", task_index=0, config=config
      )
  
      # wait for the server to finish
      server.join()
  
imports: from typing import Tuple
  import tensorflow
label_desc: Use image node_id 2 for calling a global function with example usage: create_and_start_parameters_server(cluster_spec, config) without return types