code: def get_word_vectors(vocab):
      
      wv = get_data('word2vec')
      vectors = np.array(len(vocab), len(wv['the']))
      for i, tok in enumerate(vocab):
          word = tok[0]
          variations = (word, word.lower(), word.lower()[:-1])
          for w in variations:
              if w in wv:
                  vectors[i, :] = wv[w]
          if not np.sum(np.abs(vectors[i])):
              logger.warning('Unable to find {}, {}, or {} in word2vec.'.format(*variations))
      return vectors
docs: Create a word2vec embedding matrix for all the words in the vocab