def __init__(
        self,
        num_thresholds: int = 300_000,
        fpr_bounds: tuple[float, float] = (1e-5, 1e-4),
        return_average: bool = True,
        force: bool = False,
    ) -> None:
        """Initialize AUPIMO metric.

        Args:
            num_thresholds: Number of thresholds for curve computation
            fpr_bounds: FPR integration bounds as ``(min, max)``
            return_average: If True, return mean score across anomalous images
            force: If True, compute scores even in suboptimal conditions
        """
        super().__init__(num_thresholds=num_thresholds)

        _validate.is_rate_range(fpr_bounds)
        self.fpr_bounds = fpr_bounds
        self.return_average = return_average
        self.force = force
Initialize AUPIMO metric.

        Args:
            num_thresholds: Number of thresholds for curve computation
            fpr_bounds: FPR integration bounds as ``(min, max)``
            return_average: If True, return mean score across anomalous images
            force: If True, compute scores even in suboptimal conditions
        
src/anomalib/metrics/pimo/pimo.py