def forward(self, batch: torch.Tensor) -> torch.Tensor:
        """Reconstruct non-quantized representation from batch.

        Generate non-quantized feature maps from potentially anomalous images, to
        be quantized into non-anomalous quantized representations.

        Args:
            batch (torch.Tensor): Batch of input images.

        Returns:
            Reconstructed non-quantized representation.
        """
        b1, b2, b3 = self.encoder(batch)
        return self.decoder(b1, b2, b3)
Reconstruct non-quantized representation from batch.

        Generate non-quantized feature maps from potentially anomalous images, to
        be quantized into non-anomalous quantized representations.

        Args:
            batch (torch.Tensor): Batch of input images.

        Returns:
            Reconstructed non-quantized representation.
        
src/anomalib/models/image/dsr/torch_model.py