def compute(self) -> torch.Tensor:
        """First compute PRO curve, then compute and scale area under the curve.

        Returns:
            Tensor: Value of the AUPRO metric
        """
        fpr, tpr = self._compute()

        aupro = auc(fpr, tpr, reorder=True)
        return aupro / fpr[-1]  # normalize the area
First compute PRO curve, then compute and scale area under the curve.

        Returns:
            Tensor: Value of the AUPRO metric
        
src/anomalib/metrics/aupro.py