code: def wordvec_args(short_language, dataset, extra_args):
      if (
          "--wordvec_pretrain_file" in extra_args
          or "--no_pretrain" in extra_args
      ):
          return []
  
      if short_language in no_pretrain_languages:
          # we couldn't find word vectors for a few languages...:
          # coptic, naija, old russian, turkish german, swedish sign language
          logger.warning(
              "No known word vectors for language {}  If those vectors can be found, please update the training scripts.".format(
                  short_language
              )
          )
          return ["--no_pretrain"]
      else:
          if (
              short_language in pos_pretrains
              and dataset in pos_pretrains[short_language]
          ):
              dataset_pretrains = pos_pretrains
          else:
              dataset_pretrains = {}
          wordvec_pretrain = find_wordvec_pretrain(
              short_language,
              default_pretrains,
              dataset_pretrains,
              dataset,
          )
          return ["--wordvec_pretrain_file", wordvec_pretrain]
  
file_path: stanza/stanza/utils/training/run_pos.py
imports: import logging
  import os
  from stanza.models import tagger
  from stanza.resources.default_packages import no_pretrain_languages, pos_pretrains, default_pretrains
  from stanza.utils.training import common
  from stanza.utils.training.common import Mode, add_charlm_args, build_pos_charlm_args, choose_pos_charlm, find_wordvec_pretrain
label_desc: Use image node_id 2 for calling a global function with example usage: wordvec_args(short_language, dataset, extra_args) and returns: list, list, list