code: def __init__(self, globals_dict: dict) -> None:
      args = {"average": "weighted", "multi_class": "ovr"}
      score_func = pycaret.internal.metrics.BinaryMulticlassScoreFunc(
          metrics.roc_auc_score,
          kwargs_if_binary={"average": "macro", "multi_class": "raise"},
      )
      super().__init__(
          id="auc",
          name="AUC",
          score_func=score_func,
          scorer=pycaret.internal.metrics.make_scorer_with_error_score(
              score_func, needs_proba=True, error_score=0.0, **args
          ),
          target="pred_proba",
          args=args,
      )
  
imports: from typing import Any, Dict, Optional, Union
  from sklearn import metrics
  from sklearn.metrics._scorer import _BaseScorer
  import pycaret.containers.base_container
  import pycaret.internal.metrics
  from pycaret.containers.metrics.base_metric import MetricContainer
label_desc: Use image node_id 1 to create a new ROCAUCMetricContainer object from inherited base classes: ClassificationMetricContainer with example: obj = ROCAUCMetricContainer(globals_dict)