class_docstr: `Saver` with a different default `latest_filename`.
  
  This is used in the `CheckpointInputPipelineHook` to avoid conflicts with
  the model ckpt saved by the `CheckpointSaverHook`.
class_docstr_tok: ["`","Saver","`","with","a","different","default","`","latest_filename","`",".","This","is","used","in","the","`","CheckpointInputPipelineHook","`","to","avoid","conflicts","with","the","model","ckpt","saved","by","the","`","CheckpointSaverHook","`","."]
code: def __init__(self, var_list, latest_filename, sharded=False):
      super(_CustomSaver, self).__init__(var_list, sharded=sharded)
      self._latest_filename = latest_filename
  
imports: from tensorflow.python.checkpoint import checkpoint_management
  from tensorflow.python.data.ops import iterator_ops
  from tensorflow.python.data.ops import options
  from tensorflow.python.framework import ops
  from tensorflow.python.training import basic_session_run_hooks
  from tensorflow.python.training import saver
  from tensorflow.python.training import session_run_hook
  from tensorflow.python.util import deprecation
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 1 to create a new _CustomSaver object from inherited base classes: saver_lib with example: obj = _CustomSaver(var_list, latest_filename, sharded)