code: def snapshot_object(target, filename):
      """Returns a trainer extension to take snapshots of a given object.
  
      Args:
          target (model): Object to serialize.
          filename (str): Name of the file into which the object is serialized.It can
              be a format string, where the trainer object is passed to
              the :meth: `str.format` method. For example,
              ``'snapshot_{.updater.iteration}'`` is converted to
              ``'snapshot_10000'`` at the 10,000th iteration.
  
      Returns:
          An extension function.
  
      """
      from chainer.training import extension
  
      @extension.make_extension(trigger=(1, "epoch"), priority=-100)
      def snapshot_object(trainer):
          torch_save(
              os.path.join(trainer.out, filename.format(trainer)),
              target,
          )
  
      return snapshot_object
  
imports: import argparse
  import copy
  import json
  import logging
  import os
  import shutil
  import tempfile
  import numpy
  import torch
label_desc: Use image node_id 13 for calling a global function with example usage: snapshot_object(target, filename) and returns: snapshot_object