class_docstr: A wrapper upon tf.compat.v1.train.Saver.
docstr: Save the checkpoint to "save_path" using the saver managed by AutoDist.
  
  Follows the same signature with tf.saver save().
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,
      save_debug_info=False,
  ):
      # pylint: disable=too-many-arguments, too-many-locals
      """
      Save the checkpoint to "save_path" using the saver managed by AutoDist.
  
      Follows the same signature with tf.saver save().
      """
      # sess is a WrappedSession instead of a tensorflow session.
      if not sess:
          raise ValueError(
              "Saver must be used before create_distributed_session()."
          )
      with sess._graph_item.graph.as_default():
          if not sess._graph_item.info.savers:
              raise ValueError("No saver captured by AutoDist.")
          super(Saver, self).save(
              sess,
              save_path,
              global_step=global_step,
              latest_filename=latest_filename,
              meta_graph_suffix=meta_graph_suffix,
              write_meta_graph=write_meta_graph,
              write_state=write_state,
              strip_default_attrs=strip_default_attrs,
              save_debug_info=save_debug_info,
          )
  
file_path: autodist/autodist/checkpoint/saver.py
imports: from tensorflow.core.protobuf import saver_pb2
  from tensorflow.python.training import saver
  import autodist.autodist
  from autodist.graph_item import get_default_graph_item
label_desc: Use image node_id 2 for calling the Saver 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, save_debug_info) without return types