class_docstr: Indicates a position within a `_CheckpointRestoreCoordinator`.
class_docstr_tok: ["Indicates","a","position","within","a","`","_CheckpointRestoreCoordinator","`","."]
docstr: Returns the registered saver name defined in the Checkpoint.
docstr_tok: ["Returns","the","registered","saver","name","defined","in","the","Checkpoint","."]
code: def get_registered_saver_name(self):
      """Returns the registered saver name defined in the Checkpoint."""
      if self._has_registered_saver():
          saver_name = self.object_proto.registered_saver.name
          try:
              registration.validate_restore_function(
                  self.trackable, saver_name
              )
          except ValueError as e:
              if registration.get_strict_predicate_restore(saver_name):
                  raise e
              self.skip_restore = True
          return saver_name
      return None
  
imports: import collections
  from tensorflow.python.checkpoint import checkpoint_view
  from tensorflow.python.checkpoint import functional_saver
  from tensorflow.python.checkpoint import save_util_v1
  from tensorflow.python.checkpoint import saveable_compat
  from tensorflow.python.eager import context
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_io_ops
  from tensorflow.python.ops import io_ops
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.saved_model import registration
  from tensorflow.python.trackable import base
  from tensorflow.python.trackable import constants
  from tensorflow.python.trackable import python_state
  from tensorflow.python.trackable import trackable_utils
  from tensorflow.python.training.saving import saveable_object_util
  from tensorflow.python.util import object_identity
label_desc: Use image node_id 18 for calling the CheckpointPosition obj's underlying member method code with example usage: obj.get_registered_saver_name() and returns: None, saver_name