docstr: Take a single document and the LM results and evaluates, returning a
  dict where keys are the names of submetrics and values are the values of
  the metric for that one document
  
  :param doc:
      The document as returned from training_docs, validation_docs, or test_docs.
  :param results:
      The results of the requests created in construct_requests.
docstr_tok: ["Take","a","single","document","and","the","LM","results","and","evaluates",",","returning","a","dict","where","keys","are","the","names","of","submetrics","and","values","are","the","values","of","the","metric","for","that","one","document",":","param","doc",":","The","document","as","returned","from","training_docs",",","validation_docs",",","or","test_docs",".",":","param","results",":","The","results","of","the","requests","created","in","construct_requests","."]
code: def process_results(self, doc, results):
      """Take a single document and the LM results and evaluates, returning a
      dict where keys are the names of submetrics and values are the values of
      the metric for that one document
  
      :param doc:
          The document as returned from training_docs, validation_docs, or test_docs.
      :param results:
          The results of the requests created in construct_requests.
      """
      completion = results[0]
      answer = doc["answer"]
      return {"acc": self._is_correct(completion, answer)}
  
file_path: lm-evaluation-harness/lm_eval/tasks/gsm8k.py
imports: import re
  from lm_eval.base import Task, rf
  from lm_eval.metrics import mean
label_desc: Use image node_id 12 for calling the GradeSchoolMath8K obj's underlying member method code with example usage: obj.process_results(doc, results) and returns: dict