class_docstr: A mixin that delegates all Trackable methods to another trackable object.
  
  DO NOT USE THIS UNLESS YOU ARE THE KERAS LOSS SCALE OPTIMIZER.
  
  This class must be used with multiple inheritance. A class that subclasses
  Trackable can also subclass this class, which causes all Trackable methods to
  be delegated to the trackable object passed in the constructor.
  
  A subclass can use this mixin to appear as if it were the trackable passed to
  the constructor, from a Checkpoint's perspective. LossScaleOptimizer uses this
  mixin, so that the checkpoint format for a LossScaleOptimizer is identical to
  the checkpoint format for a normal optimizer. This allows a model to be saved
  with a normal Optimizer and restored with a LossScaleOptimizer, or vice versa.
  The only difference in checkpoint format is that the loss scale is also saved
  with a LossScaleOptimizer.
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code: def _copy_trackable_to_cpu(self, object_map):
      self._trackable._copy_trackable_to_cpu(object_map)
      if self not in object_map:
          object_map[self] = DelegatingTrackableMixin(
              object_map[self._trackable]
          )
  
imports: from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 27 for calling the DelegatingTrackableMixin obj's underlying member method code with example usage: obj._copy_trackable_to_cpu(object_map) without return types