code: def build_default_args(
      paths, short_language, dataset, command_args, extra_args
  ):
      if short_language in RETAG_METHOD:
          retag_args = ["--retag_method", RETAG_METHOD[short_language]]
      else:
          retag_args = []
  
      wordvec_args = build_wordvec_args(
          short_language, dataset, extra_args
      )
  
      charlm = choose_charlm(
          short_language,
          dataset,
          command_args.charlm,
          default_charlms,
          {},
      )
      charlm_args = build_charlm_args(
          short_language, charlm, base_args=False
      )
  
      bert_args = common.choose_transformer(
          short_language,
          command_args,
          extra_args,
          warn=True,
          layers=True,
      )
      default_args = retag_args + wordvec_args + charlm_args + bert_args
  
      return default_args
  
file_path: stanza/stanza/utils/training/run_constituency.py
imports: import logging
  import os
  from stanza.models import constituency_parser
  from stanza.models.constituency.retagging import RETAG_METHOD
  from stanza.utils.datasets.constituency import prepare_con_dataset
  from stanza.utils.training import common
  from stanza.utils.training.common import Mode, add_charlm_args, build_charlm_args, choose_charlm, find_wordvec_pretrain
  from stanza.resources.default_packages import default_charlms, default_pretrains
label_desc: Use image node_id 3 for calling a global function with example usage: build_default_args(paths, short_language, dataset, command_args, extra_args) and returns: default_args