eval_metrics.py 文件源码

def _batch_MAP_MRR(self,
                     s_label, # [batch_size, sent_num]
                     s_preds, # [batch_size, sent_num]
                     mask):   # [batch_size, sent_num]
    """ Calcualte the Mean Average Precision and Mean Reciprocal Rank
    """
    average_precisions = []
    reciprocal_ranks = []
    for i in xrange(s_label.shape[0]): # For each question in the batch

      # Only keep those not padded
      label = np.take(s_label[i], np.where(mask[i] == 1)[0])
      preds = np.take(s_preds[i], np.where(mask[i] == 1)[0])
      assert(label.shape == preds.shape)

      # MAP only makes sense for positive bags
      try:
        assert(np.max(label) > 0)
      except AssertionError as e:
        print(s_label)
        raise e

      # TODO: is this correct???
      ap = label_ranking_average_precision_score([label], # true binary label
                                                 [preds]) # target scores
      rr = label_ranking_reciprocal_rank(label, preds)

      try: assert(not np.isnan(ap) and not np.isnan(rr))
      except: pdb.set_trace()

      average_precisions.append(ap)
      reciprocal_ranks.append(rr)
    return average_precisions, reciprocal_ranks