code: def levenshtein(short_seq, long_seq):
      """levenshtein distance
      :param short_seq: (shape=[T], type=int), the shorter sequence
      :param long_seq: (shape=[T], tpye=int), the longer sequence
      return: (type=float), the levenshtein distance between short_seq and long_seq
      """
      min_len, max_len = len(short_seq), len(long_seq)
      if min_len > max_len:
          short_seq, long_seq = long_seq, short_seq
          min_len, max_len = max_len, min_len
  
      current = list(range(min_len + 1))
      for index in range(1, max_len + 1):
          previous, current = current, [index] + [0] * min_len
          for index_1 in range(1, min_len + 1):
              add, delete = (
                  previous[index_1] + 1,
                  current[index_1 - 1] + 1,
              )
              change = previous[index_1 - 1]
              # string index from zero, but editditance from one
              if short_seq[index_1 - 1] != long_seq[index - 1]:
                  change += 1
              current[index_1] = min(change, add, delete)
      return current[min_len]
  
imports: import numpy
label_desc: Use image node_id 4 for calling a global function with example usage: levenshtein(short_seq, long_seq) and returns: current