code: def prepare_dicts(
      args: argparse.Namespace, langs: List[str]
  ) -> Tuple[
      Dict[str, str], Dict[str, pytorch_translate_dictionary.Dictionary]
  ]:
      """
      Uses multilingual train corpora specified in args.multilingual_train_text_file
      to build dictionaries for languages specified in `langs`.
      Vocab size is defined by args.target_max_vocab_size if lang is in the set
      of target languages, otherwise it is decided by args.target_max_vocab_size
      """
      tgt_langs = get_target_langs(args.lang_pairs.split(","))
      dict_paths = get_dict_paths(args.vocabulary, langs, args.save_dir)
      lang2corpus = defaultdict(list)
      for lang in langs:
          lang2corpus[lang] = get_corpora_for_lang(
              args.multilingual_train_text_file, lang
          )
      dict_objects = {
          lang: pytorch_translate_dictionary.Dictionary.build_vocab_file_if_nonexistent(
              corpus_files=lang2corpus[lang],
              vocab_file=dict_paths[lang],
              max_vocab_size=(
                  args.target_max_vocab_size
                  if lang in tgt_langs
                  else args.source_max_vocab_size
              ),
              tokens_with_penalty=None,
          )
          for lang in langs
      }
      return dict_paths, dict_objects
  
file_path: translate/pytorch_translate/multilingual_utils.py
imports: import argparse
  import os
  from collections import defaultdict
  from typing import Dict, List, Optional, Tuple
  from pytorch_translate.data import dictionary
label_desc: Use image node_id 7 for calling a global function with example usage: prepare_dicts(args, langs) and returns: dict_paths,  dict_objects