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: Sets the tpu topology info stored in this resolver.
docstr_tok: ["Sets","the","tpu","topology","info","stored","in","this","resolver","."]
code: def set_tpu_topology(self, serialized_tpu_topology):
      """Sets the tpu topology info stored in this resolver."""
      self._tpu_topology = topology_pb2.TopologyProto()
      self._tpu_topology.ParseFromString(serialized_tpu_topology)
  
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 14 for calling the TPUClusterResolver obj's underlying member method code with example usage: obj.set_tpu_topology(serialized_tpu_topology) without return types