code: def process_results(self, doc, results):
      # Add spaces between words for BLEU score calculation of target languages like Chinese
      tar_lang_code = self.sacrebleu_language_pair.split("-")[-1]
      if tar_lang_code in NO_SPACE_LANG:
          doc["ref"] = NO_SPACE_LANG[tar_lang_code]([doc["ref"]])[0]
          results = NO_SPACE_LANG[tar_lang_code](results)
  
      # These metrics are corpus-level not sentence level, so we'll hide the
      # results in this dict and compute the corpus score in the aggregate method
      ref_pred = (doc["ref"], results)
      return {
          "bleu": ref_pred,
          "chrf": ref_pred,
          "ter": ref_pred,
      }
  
imports: import pycountry
  from pprint import pprint
  from sacrebleu import sacrebleu
  from lm_eval import metrics
  from lm_eval.base import Task, rf
  from typing import List
label_desc: Use image node_id 12 for calling the GeneralTranslationTask obj's underlying member method code with example usage: obj.process_results(doc, results) and returns: dict