code: def process_results(self, doc, results):
      li1, li2 = results
  
      goal = int(doc["answer"])
      if goal == 1 and li1 > li2:
          acc = 1.0
      elif goal == 2 and li2 > li1:
          acc = 1.0
      else:
          acc = 0.0
  
      return {
          "acc": acc,
      }
  
file_path: lm-evaluation-harness/lm_eval/tasks/ja/xwinograd_ja.py
imports: from lm_eval.base import rf, Task
  from lm_eval.metrics import mean
  import numpy
label_desc: Use image node_id 8 for calling the XWinograd obj's underlying member method code with example usage: obj.process_results(doc, results) and returns: dict