def get_maps(self, batch: torch.Tensor, normalize: bool = False) -> tuple[torch.Tensor, torch.Tensor]:
        """Compute anomaly maps for a batch of images.

        Convenience method that combines distance computation and map generation.

        Args:
            batch (torch.Tensor): Input batch of images.
            normalize (bool): Whether to normalize maps. Defaults to ``False``.

        Returns:
            tuple[torch.Tensor, torch.Tensor]:
                - Student-teacher anomaly map
                - Student-autoencoder anomaly map
        """
        student_output, distance_st = self.compute_student_teacher_distance(batch)
        return self.compute_maps(batch, student_output, distance_st, normalize)
Compute anomaly maps for a batch of images.

        Convenience method that combines distance computation and map generation.

        Args:
            batch (torch.Tensor): Input batch of images.
            normalize (bool): Whether to normalize maps. Defaults to ``False``.

        Returns:
            tuple[torch.Tensor, torch.Tensor]:
                - Student-teacher anomaly map
                - Student-autoencoder anomaly map
        
src/anomalib/models/image/efficient_ad/torch_model.py