def decode_slat(
        self,
        slat: sp.SparseTensor,
        formats: List[str] = ['mesh', 'gaussian', 'radiance_field'],
    ) -> dict:
        """
        Decode the structured latent.

        Args:
            slat (sp.SparseTensor): The structured latent.
            formats (List[str]): The formats to decode the structured latent to.

        Returns:
            dict: The decoded structured latent.
        """
        ret = {}
        if 'mesh' in formats:
            ret['mesh'] = self.models['slat_decoder_mesh'](slat)
        if 'gaussian' in formats:
            ret['gaussian'] = self.models['slat_decoder_gs'](slat)
        if 'radiance_field' in formats:
            ret['radiance_field'] = self.models['slat_decoder_rf'](slat)
        return ret

        Decode the structured latent.

        Args:
            slat (sp.SparseTensor): The structured latent.
            formats (List[str]): The formats to decode the structured latent to.

        Returns:
            dict: The decoded structured latent.
        
trellis/pipelines/trellis_image_to_3d.py