def forward(self, x: sp.SparseTensor) -> sp.SparseTensor:
        """
        Apply the block to a Tensor, conditioned on a timestep embedding.

        Args:
            x: an [N x C x ...] Tensor of features.
        Returns:
            an [N x C x ...] Tensor of outputs.
        """
        h = self.act_layers(x)
        h = self.sub(h)
        x = self.sub(x)
        h = self.out_layers(h)
        h = h + self.skip_connection(x)
        return h

        Apply the block to a Tensor, conditioned on a timestep embedding.

        Args:
            x: an [N x C x ...] Tensor of features.
        Returns:
            an [N x C x ...] Tensor of outputs.
        
trellis/models/structured_latent_vae/decoder_mesh.py