class_docstr: A variable which packs multiple variables distributed across devices.
  
  It's only supported when eager execution is enabled.
  For op-by-op execution, use an unpacked handle on the current device; for
  function execution, use the packed handle to reduce the overhead of function
  calls.
class_docstr_tok: ["A","variable","which","packs","multiple","variables","distributed","across","devices",".","It","'s","only","supported","when","eager","execution","is","enabled",".","For","op-by-op","execution",",","use","an","unpacked","handle","on","the","current","device",";","for","function","execution",",","use","the","packed","handle","to","reduce","the","overhead","of","function","calls","."]
code: def packed_handle(self):
      return self._handle
  
imports: from tensorflow.python.distribute import device_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 math_ops
  from tensorflow.python.ops import resource_variable_ops
label_desc: Use image node_id 8 for calling the PackedDistributedVariable obj's underlying member method code with example usage: obj.packed_handle() and returns: self