class_docstr: ReplicaContext for strategy that is backed by DTensor.
  
  Since the DTensor is operated in the global context, most of the methods from
  existing strategy ReplicaContext is not applicable since they need to access
  local values. For now most of the methods in this class will raise explicit
  error to user, and we will add more support for local values in future.
code: def __init__(self, strategy):
      # Since DTensor strategy only runs in a global context, and we can't have
      # a local replica ID in the sync group. For now we pass None to parent, and
      # raise an explicit error when it is accessed.
      super().__init__(strategy, replica_id_in_sync_group=None)
  
imports: from tensorflow.dtensor.python import accelerator_util
  from tensorflow.dtensor.python import api
  from tensorflow.dtensor.python import input_util
  from tensorflow.dtensor.python import layout
  from tensorflow.python.distribute import cross_device_ops
  from tensorflow.python.distribute import device_util
  from tensorflow.python.distribute import distribute_lib
  from tensorflow.python.distribute import reduce_util
  from tensorflow.python.distribute import values
  from tensorflow.python.eager import context
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_conversion_registry
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import summary_ops_v2
label_desc: Use image node_id 1 to create a new DTensorReplicaContext object from inherited base classes: distribute_lib with example: obj = DTensorReplicaContext(strategy)