code: def nearest_neighbors(self, word, top_k=10):
      
      #TODO(rmyeid): Use scikit ball tree, if scikit is available
      point = self[word]
      diff = self.vectors - point
      distances = np.linalg.norm(diff, axis=1)
      top_ids = distances.argsort()[1:top_k+1]
      return [self.vocabulary.id_word[i] for i in top_ids]
docs: Return the nearest k words to the given `word`.
  
      Args:
        word (string): single word.
        top_k (integer): decides how many neighbors to report.
  
      Returns:
        A list of words sorted by the distances. The closest is the first.
  
      Note:
        L2 metric is used to calculate distances.