code: def get_wer(reference: List[str], hypothesis: str) -> WerScore:
      all_scores = [
          _get_wer(r.split(), hypothesis.split()) for r in reference
      ]
      return WerScore(
          wer=np.min([s.wer for s in all_scores]),
          len_r=np.max([s.len_r for s in all_scores]),
          deletion=np.min([s.deletion for s in all_scores]),
          substitution=np.min([s.substitution for s in all_scores]),
          insertion=np.min([s.insertion for s in all_scores]),
      )
  
file_path: vizseq/vizseq/scorers/_wer.py
imports: from typing import List, NamedTuple
  from enum import Enum
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: get_wer(reference, hypothesis) and returns: WerScore