class_docstr: Area under the ROC curve.
docstr: Generate a figure containing the ROC curve, the baseline and the AUROC.
  
  Returns:
      tuple[Figure, str]: Tuple containing both the figure and the figure title to be used for logging
code: def generate_figure(self) -> tuple[Figure, str]:
      """Generate a figure containing the ROC curve, the baseline and the AUROC.
  
      Returns:
          tuple[Figure, str]: Tuple containing both the figure and the figure title to be used for logging
      """
      fpr, tpr = self._compute()
      auroc = self.compute()
  
      xlim = (0.0, 1.0)
      ylim = (0.0, 1.0)
      xlabel = "False Positive Rate"
      ylabel = "True Positive Rate"
      loc = "lower right"
      title = "ROC"
  
      fig, axis = plot_figure(
          fpr, tpr, auroc, xlim, ylim, xlabel, ylabel, loc, title
      )
  
      axis.plot(
          [0, 1],
          [0, 1],
          color="navy",
          lw=2,
          linestyle="--",
          figure=fig,
      )
  
      return fig, title
  
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 4 for calling the AUROC obj's underlying member method code with example usage: obj.generate_figure() and returns: fig,  title