code: def build_combined_dataset(paths, short_name, model_type, augment):
      random.seed(1234)
      tokenizer_dir = paths["TOKENIZE_DATA_DIR"]
      build_fn = COMBINED_FNS[short_name]
      extra_fn = COMBINED_EXTRA_FNS.get(short_name, None)
      for dataset in ("train", "dev", "test"):
          output_conllu = common.tokenizer_conllu_name(
              tokenizer_dir, short_name, dataset
          )
          sents = build_fn(paths, model_type, dataset)
          if dataset == "train" and augment:
              sents = augment_punct(sents)
          if extra_fn is not None:
              sents.extend(extra_fn(paths, dataset))
          write_sentences_to_conllu(output_conllu, sents)
  
imports: import argparse
  import glob
  import os
  import random
  import re
  import tempfile
  from collections import Counter
  from stanza.models.common.constant import treebank_to_short_name
  import stanza.utils.datasets.common
  from stanza.utils.datasets.common import read_sentences_from_conllu, write_sentences_to_conllu, INT_RE, MWT_RE, MWT_OR_COPY_RE
  import stanza.utils.datasets.tokenization.convert_ml_cochin
  import stanza.utils.datasets.tokenization.convert_my_alt
  import stanza.utils.datasets.tokenization.convert_vi_vlsp
  import stanza.utils.datasets.tokenization.convert_th_best
  import stanza.utils.datasets.tokenization.convert_th_lst20
  import stanza.utils.datasets.tokenization.convert_th_orchid
label_desc: Use image node_id 33 for calling a global function with example usage: build_combined_dataset(paths, short_name, model_type, augment) without return types