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 save(
      self,
      sess,
      save_path,
      global_step=None,
      latest_filename=None,
      meta_graph_suffix="meta",
      write_meta_graph=True,
      write_state=True,
      strip_default_attrs=False,
  ):
      return super(_CustomSaver, self).save(
          sess,
          save_path,
          global_step,
          latest_filename or self._latest_filename,
          meta_graph_suffix,
          write_meta_graph,
          write_state,
          strip_default_attrs,
      )
  
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 2 for calling the _CustomSaver obj's underlying member method code with example usage: obj.save(sess, save_path, global_step, latest_filename, meta_graph_suffix, write_meta_graph, write_state, strip_default_attrs) and returns: super