code: def run_treebank(
      mode,
      paths,
      treebank,
      short_name,
      temp_output_file,
      command_args,
      extra_args,
  ):
      if mode == Mode.TRAIN:
          dataset = "train"
      elif mode == Mode.SCORE_DEV:
          dataset = "dev"
      elif mode == Mode.SCORE_TEST:
          dataset = "test"
  
      if command_args.temp_output:
          with tempfile.TemporaryDirectory() as ete_dir:
              paths = dict(paths)
              paths["ETE_DATA_DIR"] = ete_dir
              run_ete(
                  paths, dataset, short_name, command_args, extra_args
              )
      else:
          os.makedirs(paths["ETE_DATA_DIR"], exist_ok=True)
          run_ete(paths, dataset, short_name, command_args, extra_args)
  
file_path: stanza/stanza/utils/training/run_ete.py
imports: import logging
  import os
  import tempfile
  from stanza.models import identity_lemmatizer
  from stanza.models import lemmatizer
  from stanza.models import mwt_expander
  from stanza.models import parser
  from stanza.models import tagger
  from stanza.models import tokenizer
  from stanza.models.common.constant import treebank_to_short_name
  from stanza.utils.training import common
  from stanza.utils.training.common import Mode, build_pos_charlm_args, build_lemma_charlm_args, build_depparse_charlm_args
  from stanza.utils.training.run_lemma import check_lemmas
  from stanza.utils.training.run_mwt import check_mwt
  from stanza.utils.training.run_pos import wordvec_args
label_desc: Use image node_id 3 for calling a global function with example usage: run_treebank(mode, paths, treebank, short_name, temp_output_file, command_args, extra_args) without return types