from keras.preprocessing.text import Tokenizer

def vocab_creater(text_lists, VOCAB_SIZE):

  tokenizer = Tokenizer(num_words=VOCAB_SIZE)
  tokenizer.fit_on_texts(text_lists)
  dictionary = tokenizer.word_index

  word2idx = {}
  idx2word = {}
  for k, v in dictionary.items():
      if v < VOCAB_SIZE:
          word2idx[k] = v
          index2word[v] = k
      if v >= VOCAB_SIZE-1:
          continue

  return word2idx, idx2word

word2idx, idx2word = vocab_creater(text_lists=encoder_input_text+decoder_input_text, VOCAB_SIZE=14999)