code: def get_eval_type(dev_batch):
      """
      If there is only one column to score in the dev set, use that instead of AllTags
      """
      if (
          dev_batch.has_xpos
          and not dev_batch.has_upos
          and not dev_batch.has_feats
      ):
          return "XPOS"
      elif (
          dev_batch.has_upos
          and not dev_batch.has_xpos
          and not dev_batch.has_feats
      ):
          return "UPOS"
      else:
          return "AllTags"
  
imports: import sys
  import os
  import shutil
  import time
  from datetime import datetime
  import argparse
  import logging
  import numpy
  import random
  import torch
  from torch import nn, optim
  import stanza.models.pos.data
  from stanza.models.pos.data import Dataset, ShuffledDataset
  from stanza.models.pos.trainer import Trainer
  from stanza.models.pos import scorer
  from stanza.models.common import utils
  from stanza.models.common import pretrain
  from stanza.models.common.data import augment_punct
  from stanza.models.common.doc import *
  from stanza.models.common.foundation_cache import FoundationCache
  from stanza.utils.conll import CoNLL
  from stanza.models import _training_logging
label_desc: Use image node_id 7 for calling a global function with example usage: get_eval_type(dev_batch) and returns: str, str, str