code: def fetch_all_treebanks(ud_dir, languages, corpus, best_per_language):
       Fetch the txt files for all treebanks for a given set of languages """
      all_treebanks = dict()
      treebank_size = dict()
      for l in languages:
          all_treebanks[l] = []
          treebank_size[l] = 0
  
      for treebank_dir in ud_dir.iterdir():
          if treebank_dir.is_dir():
              for txt_path in treebank_dir.iterdir():
                  if txt_path.name.endswith('-ud-' + corpus + '.txt'):
                      file_lang = txt_path.name.split('_')[0]
                      if file_lang in languages:
                          gold_path = treebank_dir / txt_path.name.replace('.txt', '.conllu')
                          stats_xml = treebank_dir / "stats.xml"
                          # ignore treebanks where the texts are not publicly available
                          if not _contains_blinded_text(stats_xml):
                              if not best_per_language:
                                  all_treebanks[file_lang].append(txt_path)
                              # check the tokens in the gold annotation to keep only the biggest treebank per language
                              else:
                                  with gold_path.open(mode='r', encoding='utf-8') as gold_file:
                                      gold_ud = conll17_ud_eval.load_conllu(gold_file)
                                      gold_tokens = len(gold_ud.tokens)
                                  if treebank_size[file_lang] < gold_tokens:
                                      all_treebanks[file_lang] = [txt_path]
                                      treebank_size[file_lang] = gold_tokens
  
      return all_treebanks
docs: Fetch the txt files for all treebanks for a given set of languages