def decode_normals(self, normals_latent: torch.Tensor) -> torch.Tensor:
        """
        Decode normals latent into normals map.

        Args:
            normals_latent (`torch.Tensor`):
                Normals latent to be decoded.

        Returns:
            `torch.Tensor`: Decoded normals map.
        """
        # scale latent
        normals_latent = normals_latent / self.latent_scale_factor
        # decode
        z = self.vae.post_quant_conv(normals_latent)
        stacked = self.vae.decoder(z)
        return stacked

        Decode normals latent into normals map.

        Args:
            normals_latent (`torch.Tensor`):
                Normals latent to be decoded.

        Returns:
            `torch.Tensor`: Decoded normals map.
        
marigold/marigold_normals_pipeline.py