class_docstr: Area under the ROC curve.
docstr: Compute fpr/tpr value pairs.
  
  Returns:
      Tuple containing Tensors for fpr and tpr
code: def _compute(self) -> tuple[Tensor, Tensor]:
      """Compute fpr/tpr value pairs.
  
      Returns:
          Tuple containing Tensors for fpr and tpr
      """
      tpr: Tensor
      fpr: Tensor
      fpr, tpr, _thresholds = super().compute()
      return (fpr, tpr)
  
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 3 for calling the AUROC obj's underlying member method code with example usage: obj._compute() and returns: fpr,  tpr