def validation_step(self, batch: Batch, *args, **kwargs) -> STEP_OUTPUT:
        """Validation step of DSR.

        The Softmax predictions of the anomalous class are used as anomaly map.

        Args:
            batch (Batch): Input batch containing image, label and mask
            *args: Additional positional arguments (unused)
            **kwargs: Additional keyword arguments (unused)

        Returns:
            STEP_OUTPUT: Dictionary containing predictions and batch information

        Example:
            >>> from anomalib.data import Batch
            >>> model = Dsr()
            >>> batch = Batch(
            ...     image=torch.randn(8, 3, 256, 256),
            ...     label=torch.zeros(8)
            ... )
            >>> output = model.validation_step(batch)
            >>> isinstance(output, Batch)
            True
        """
        del args, kwargs  # These variables are not used.

        predictions = self.model(batch.image)
        return batch.update(**predictions._asdict())
Validation step of DSR.

        The Softmax predictions of the anomalous class are used as anomaly map.

        Args:
            batch (Batch): Input batch containing image, label and mask
            *args: Additional positional arguments (unused)
            **kwargs: Additional keyword arguments (unused)

        Returns:
            STEP_OUTPUT: Dictionary containing predictions and batch information

        Example:
            >>> from anomalib.data import Batch
            >>> model = Dsr()
            >>> batch = Batch(
            ...     image=torch.randn(8, 3, 256, 256),
            ...     label=torch.zeros(8)
            ... )
            >>> output = model.validation_step(batch)
            >>> isinstance(output, Batch)
            True
        
src/anomalib/models/image/dsr/lightning_model.py