code: def auprc_auroc_ap(target: torch.Tensor, score: torch.Tensor):
      """
      auprc: area under the precision-recall curve
      auroc: area under the receiver operating characteristic curve
      ap: average precision
  
      Copy-paste from https://github.com/NYXFLOWER/GripNet
      """
      y = target.detach().cpu().numpy()
      pred = score.detach().cpu().numpy()
      auroc, ave_precision = metrics.roc_auc_score(
          y, pred
      ), metrics.average_precision_score(y, pred)
      precision, recall, _ = metrics.precision_recall_curve(y, pred)
      auprc = metrics.auc(recall, precision)
  
      return auprc, auroc, ave_precision
  
label_desc: Use image node_id 2 for calling a global function with example usage: auprc_auroc_ap(target, score) and returns: auprc,  auroc,  ave_precision