code: def rouge2_mecab(refs, preds, tokenizer):
      """This uses a MeCab tokenizer for Japanese text.
  
      Besides specifying the tokenizer, this does not perform the rougeLsum
      related sentence/newline normalization, and only calculates rouge2.
      Otherwise it is the same as the generic rouge scoring.
      """
      rouge_types = ["rouge2"]
      # mecab-based rouge
      scorer = rouge_scorer.RougeScorer(
          rouge_types,
          tokenizer=tokenizer,
      )
  
      # Accumulate confidence intervals.
      aggregator = scoring.BootstrapAggregator()
      for ref, pred in zip(refs, preds):
          aggregator.add_scores(scorer.score(ref, pred))
      result = aggregator.aggregate()
      return {
          type: result[type].mid.fmeasure * 100 for type in rouge_types
      }
  
imports: import os
  import pathlib
  import re
  import collections
  import functools
  import inspect
  import sys
  from typing import List, Union
  import torch
  from omegaconf import OmegaConf
  import sacrebleu
  from rouge_score import rouge_scorer, scoring
label_desc: Use image node_id 15 for calling a global function with example usage: rouge2_mecab(refs, preds, tokenizer) and returns: unknown