class_docstr: Area under the ROC curve.
docstr: First compute ROC curve, then compute area under the curve.
  
  Returns:
      Tensor: Value of the AUROC metric
code: def compute(self) -> Tensor:
      """First compute ROC curve, then compute area under the curve.
  
      Returns:
          Tensor: Value of the AUROC metric
      """
      tpr: Tensor
      fpr: Tensor
  
      fpr, tpr = self._compute()
      return auc(fpr, tpr, reorder=True)
  
file_path: anomalib/src/anomalib/utils/metrics/auroc.py
imports: from __future__ import annotations
  from matplotlib.figure import Figure
  from torch import Tensor
  from torchmetrics import ROC
  from torchmetrics.functional import auc
  from .plotting_utils import plot_figure
label_desc: Use image node_id 1 for calling the AUROC obj's underlying member method code with example usage: obj.compute() and returns: auc