class_docstr: Generic AutoDist Interface.
  
  Ancestor of _V1Graph, _V2Graph, and _V2Eager -- the different ways to run TF code.
docstr: Build distributed strategy based on the default graph in the scope.
  
  Returns:
      base.Strategy: Distributed strategy representation object.
docstr_tok: ["Build","distributed","strategy","based","on","the","default","graph","in","the","scope",".","Returns",":","base.Strategy",":","Distributed","strategy","representation","object","."]
code: def build_strategy(self):
      """
      Build distributed strategy based on the default graph in the scope.
  
      Returns:
          base.Strategy: Distributed strategy representation object.
      """
      return self._strategy_builder.build(
          self._original_graph_item, self._resource_spec
      )
  
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 3 for calling the _AutoDistInterface obj's underlying member method code with example usage: obj.build_strategy() and returns: self