code: def build_vocab_multicorpus(
      corpus_langs,
      corpus_files,
      vocab_langs,
      vocab_files,
      max_vocab_size,
      tokens_with_penalty=None,
      dictionary_cls=Dictionary,
  ):
      lang2corpus = {lang: [] for lang in vocab_langs}
      for lang, corpus_file in zip(corpus_langs, corpus_files):
          lang2corpus[lang].append(corpus_file)
      return {
          lang: dictionary_cls.build_vocab_file_if_nonexistent(
              corpus_files=lang2corpus[lang],
              vocab_file=vocab_file,
              max_vocab_size=max_vocab_size,
              tokens_with_penalty=tokens_with_penalty,
          )
          for lang, vocab_file in zip(vocab_langs, vocab_files)
      }
  
imports: import argparse
  import os
  import tempfile
  from typing import Dict, List, Optional
  from pytorch_translate import constants, multilingual_utils, options, utils
  from pytorch_translate.data import char_data, data
  from pytorch_translate.data.dictionary import Dictionary
label_desc: Use image node_id 9 for calling a global function with example usage: build_vocab_multicorpus(corpus_langs, corpus_files, vocab_langs, vocab_files, max_vocab_size, tokens_with_penalty, dictionary_cls) and returns: unknown