class_docstr: Cluster Resolver for Google Cloud TPUs.
  
  This is an implementation of cluster resolvers for the Google Cloud TPU
  service.
  
  TPUClusterResolver supports the following distinct environments:
  Google Compute Engine
  Google Kubernetes Engine
  Google internal
  
  It can be passed into `tf.distribute.TPUStrategy` to support TF2 training on
  Cloud TPUs.
docstr: Returns the location for coordination service.
  
  The coordination service should be located on TPU worker0.
  
  Returns:
    A string indicate the location path.
docstr_tok: ["Returns","the","location","for","coordination","service",".","The","coordination","service","should","be","located","on","TPU","worker0",".","Returns",":","A","string","indicate","the","location","path","."]
code: def get_coordination_service_leader(self):
      """Returns the location for coordination service.
  
      The coordination service should be located on TPU worker0.
  
      Returns:
        A string indicate the location path.
      """
      return "/job:" + self.get_job_name() + "/task:0"
  
imports: import collections
  import re
  from tensorflow.core.protobuf.tpu import topology_pb2
  from tensorflow.python.distribute.cluster_resolver import cluster_resolver
  from tensorflow.python.eager import remote
  from tensorflow.python.framework import config
  from tensorflow.python.framework import errors
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.tpu import tpu_strategy_util
  from tensorflow.python.tpu import tpu_system_metadata
  from tensorflow.python.training import server_lib
  from tensorflow.python.util import compat
label_desc: Use image node_id 10 for calling the TPUClusterResolver obj's underlying member method code with example usage: obj.get_coordination_service_leader() and returns: unknown