def on_validation_epoch_end(self, trainer: Trainer, pl_module: LightningModule) -> None:
        """Compute final threshold and normalization values.

        Args:
            trainer (Trainer): PyTorch Lightning trainer instance.
            pl_module (LightningModule): PyTorch Lightning module instance.
        """
        del trainer, pl_module
        if self.enable_thresholding:
            # compute threshold values
            if self._image_threshold_metric.update_called:
                self._image_threshold = self._image_threshold_metric.compute()
                self._image_threshold_metric.reset()
            if self._pixel_threshold_metric.update_called:
                self._pixel_threshold = self._pixel_threshold_metric.compute()
                self._pixel_threshold_metric.reset()
        if self.enable_normalization:
            # compute normalization values
            if self._image_min_max_metric.update_called:
                self.image_min, self.image_max = self._image_min_max_metric.compute()
                self._image_min_max_metric.reset()
            if self._pixel_min_max_metric.update_called:
                self.pixel_min, self.pixel_max = self._pixel_min_max_metric.compute()
                self._pixel_min_max_metric.reset()
Compute final threshold and normalization values.

        Args:
            trainer (Trainer): PyTorch Lightning trainer instance.
            pl_module (LightningModule): PyTorch Lightning module instance.
        
src/anomalib/post_processing/one_class.py