code: def word_error_rate(x, y):
      scores = words = 0
      for h, r in zip(x, y):
          h_list = h.split()
          r_list = r.split()
          words += len(r_list)
          scores += levenshtein(h_list, r_list)
      return float(scores) / words, float(scores), words
  
file_path: tinygrad/examples/mlperf/metrics.py
imports: import re
  import string
  from collections import Counter
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: word_error_rate(x, y) and returns: unknown,  float,  words