class_docstr: Indicates a position within a `_CheckpointRestoreCoordinator`.
class_docstr_tok: ["Indicates","a","position","within","a","`","_CheckpointRestoreCoordinator","`","."]
docstr: Create or fetch restore ops for this object's attributes.
  
  Requires that the `Trackable` Python object has been bound to an object
  ID in the checkpoint.
  
  Args:
    reader: A `CheckpointReader`. If None, a new instance will be created.
  
  Returns:
    A list of operations when graph building, or an empty list when executing
    eagerly.
docstr_tok: ["Create","or","fetch","restore","ops","for","this","object","'s","attributes",".","Requires","that","the","`","Trackable","`","Python","object","has","been","bound","to","an","object","ID","in","the","checkpoint",".","Args",":","reader",":","A","`","CheckpointReader","`",".","If","None",",","a","new","instance","will","be","created",".","Returns",":","A","list","of","operations","when","graph","building",",","or","an","empty","list","when","executing","eagerly","."]
code: def restore_ops(self, reader=None):
      """Create or fetch restore ops for this object's attributes.
  
      Requires that the `Trackable` Python object has been bound to an object
      ID in the checkpoint.
  
      Args:
        reader: A `CheckpointReader`. If None, a new instance will be created.
  
      Returns:
        A list of operations when graph building, or an empty list when executing
        eagerly.
      """
      if self._has_registered_saver():
          raise ValueError(
              "Unable to run individual checkpoint restore for objects"
              " with registered savers."
          )
      (
          restore_ops,
          tensor_saveables,
          python_positions,
          _,
      ) = self.gather_ops_or_named_saveables()
      restore_ops.extend(
          self._checkpoint.restore_saveables(
              tensor_saveables, python_positions, reader=reader
          )
      )
      return restore_ops
  
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 9 for calling the CheckpointPosition obj's underlying member method code with example usage: obj.restore_ops(reader) and returns: restore_ops