class_docstr: Represents variables that are replicated.
  
  It behaves exactly as a normal variable, but uses corresponding variable
  handle based on the context.
  - In each replica, it uses the handle from that replica.
  - In tpu.replicate(), it uses the replicated handle.
  - Otherwise, it uses the handle from the primary replica.
  
  Note that it doesn't synchronize automatically as the old DistributedVariable
  in values.py.
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code: def handle(self):
      if values_util.is_saving_non_distributed():
          return self._primary_handle
      tpu_context = tpu_util.enclosing_tpu_context()
      if tpu_context and not context.executing_eagerly():
          is_mirrored = (
              self._variables[0].synchronization
              != variables_lib.VariableSynchronization.ON_READ
          )
          if self._packed_handle is None:
              handles = [v.handle for v in self._variables]
              is_packed = False
          else:
              handles = [self._packed_handle]
              is_packed = True
          common_name = self._handle_name
          # BaseResourceVariable appends ":0" to the handle name, which makes it not
          # a valid root scope name.
          if ":" in common_name:
              common_name = common_name.split(":")[0]
          return tpu_context.get_replicated_var_handle(
              common_name,
              self._unique_id,
              handles,
              is_mirrored,
              is_packed,
          )
      if (
          self._packed_handle is not None
          and not context.executing_eagerly()
      ):
          return self._packed_handle
      device = device_util.canonicalize(device_util.current())
      return self._device_to_handle.get(device, self._primary_handle)
  
imports: import copy
  import weakref
  from tensorflow.python.distribute import device_util
  from tensorflow.python.distribute import tpu_util
  from tensorflow.python.distribute import values_util
  from tensorflow.python.eager import context
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_conversion_registry
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.ops import variables
label_desc: Use image node_id 2 for calling the DistributedVariable obj's underlying member method code with example usage: obj.handle() and returns: self, self, tpu_context, self