code: def roc_auc_score(
      conditions, prediction_scores, average="micro", sample_weight=None
  ):
      try:
          return metrics.roc_auc_score(
              conditions,
              prediction_scores,
              average=average,
              sample_weight=sample_weight,
          )
      except ValueError as ve:
          logger.info(ve)
  
imports: import logging
  from collections import OrderedDict
  import numpy
  from sklearn import metrics
  from sklearn.metrics import confusion_matrix
label_desc: Use image node_id 2 for calling a global function with example usage: roc_auc_score(conditions, prediction_scores, average, sample_weight) and returns: metrics