class_docstr: Generic AutoDist Interface.
  
  Ancestor of _V1Graph, _V2Graph, and _V2Eager -- the different ways to run TF code.
docstr: Prepare for the execution.
docstr_tok: ["Prepare","for","the","execution","."]
code: def _setup(self, strategy):
      """Prepare for the execution."""
      if IS_AUTODIST_CHIEF:
          # we should only have one single coordinator for one single AutoDist() instance scope,
          # even though we could have multiple strategies.
          self._coordinator = Coordinator(
              strategy=strategy, cluster=self._cluster
          )
          self._cluster.start()
          self._coordinator.launch_clients()
      logging.info(
          "Current PID {} belongs to address {}".format(
              os.getpid(), self._cluster.get_local_address()
          )
      )
  
imports: import atexit
  import os
  from collections import namedtuple
  import numpy
  from tensorflow.python.eager import context
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.util import tf_contextlib
  from autodist.cluster import Cluster, SSHCluster
  from autodist.const import ENV
  from autodist.coordinator import Coordinator
  from autodist.graph_item import GraphItem
  from autodist.kernel.device.resolver import DeviceResolver
  from autodist.kernel.graph_transformer import GraphTransformer
  from autodist.patch import PatchTensorFlow
  from autodist.remapper import Remapper
  from autodist.resource_spec import ResourceSpec
  from autodist.runner import WrappedSession
  from autodist.strategy import base
  from autodist.strategy.ps_lb_strategy import PSLoadBalancing
  from autodist.utils import logging
label_desc: Use image node_id 6 for calling the _AutoDistInterface obj's underlying member method code with example usage: obj._setup(strategy) without return types