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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def load_from_checkpoint(self, sess, latest_filename=None):
 """Loads the model from the most recent checkpoint. This gets the most current list of checkpoints each time it is called. Args: sess: The current session. latest_filename: The filename for the latest set of checkpoints, defaults to 'checkpoints'. Returns: The loaded checkpoint or None if it failed to load. """

    # Set list of not-yet-deleted checkpoints.
    self._create_initializers()
    if self._save_path:
      ckpt = tf.train.get_checkpoint_state(
          os.path.dirname(self._save_path), latest_filename)
      if ckpt and ckpt.all_model_checkpoint_paths:
        # Copy it because last_checkpoints is immutable.
        # Manually configure a new Saver so that we get the latest snapshots.
        self._saver = tf.train.Saver(saver_def=self._saver.as_saver_def())
        self._saver.set_last_checkpoints(list(ckpt.all_model_checkpoint_paths))
    if self._saver.last_checkpoints:
      self._saver.restore(sess, self._saver.last_checkpoints[-1])
      return self._saver.last_checkpoints[-1]
    else:
      return None