def forward(self, inputs: torch.Tensor) -> torch.Tensor:
        """Reconstructs an image from a quantized representation.

        Args:
            inputs (torch.Tensor): Quantized features.

        Returns:
            Reconstructed image.
        """
        batch = self.block1(inputs)
        batch = self.mp1(batch)
        batch = self.block2(batch)
        batch = self.mp2(batch)
        batch = self.pre_vq_conv(batch)

        batch = self.upblock1(batch)
        batch = F.relu(batch)
        batch = self.upblock2(batch)
        batch = F.relu(batch)
        batch = self._conv_1(batch)

        batch = self._residual_stack(batch)

        batch = self._conv_trans_1(batch)
        batch = F.relu(batch)

        return self._conv_trans_2(batch)
Reconstructs an image from a quantized representation.

        Args:
            inputs (torch.Tensor): Quantized features.

        Returns:
            Reconstructed image.
        
src/anomalib/models/image/dsr/torch_model.py