def _render_batch(self, reps: List[Gaussian], extrinsics: torch.Tensor, intrinsics: torch.Tensor) -> torch.Tensor:
        """
        Render a batch of representations.

        Args:
            reps: The dictionary of lists of representations.
            extrinsics: The [N x 4 x 4] tensor of extrinsics.
            intrinsics: The [N x 3 x 3] tensor of intrinsics.
        """
        ret = None
        for i, representation in enumerate(reps):
            render_pack = self.renderer.render(representation, extrinsics[i], intrinsics[i])
            if ret is None:
                ret = {k: [] for k in list(render_pack.keys()) + ['bg_color']}
            for k, v in render_pack.items():
                ret[k].append(v)
            ret['bg_color'].append(self.renderer.bg_color)
        for k, v in ret.items():
            ret[k] = torch.stack(v, dim=0) 
        return ret

        Render a batch of representations.

        Args:
            reps: The dictionary of lists of representations.
            extrinsics: The [N x 4 x 4] tensor of extrinsics.
            intrinsics: The [N x 3 x 3] tensor of intrinsics.
        
trellis/trainers/vae/structured_latent_vae_gaussian.py