code: def partial_eval(self, pos_scores, neg_scores):
      results = {}
      rank_above, negative_num = self._partial_rank(
          pos_scores, neg_scores
      )
      for evaluator in self.evaluators:
          if evaluator.etype == "rank":
              results[evaluator.name] = evaluator.compute(
                  rank_above=rank_above, negative_num=negative_num
              )
  
      return results
  
file_path: openrec/openrec/tf1/legacy/utils/evaluators/implicit_eval_manager.py
imports: import numpy
  from tqdm import tqdm
label_desc: Use image node_id 5 for calling the ImplicitEvalManager obj's underlying member method code with example usage: obj.partial_eval(pos_scores, neg_scores) and returns: results