code: def evaluate_auc(pred, label):
      res = roc_auc_score(y_score=pred, y_true=label)
      return res
  
imports: import numpy
  import torch
  from sklearn.metrics import accuracy_score, average_precision_score, f1_score, log_loss, ndcg_score, roc_auc_score
label_desc: Use image node_id 1 for calling a global function with example usage: evaluate_auc(pred, label) and returns: res