def forward(self, x: torch.Tensor, t: torch.Tensor):
        """
        :param x: an [N x C x T] tensor.
        :param t: an [N] tensor.
        :return: an [N x C' x T] tensor.
        """
        assert x.shape[-1] == self.n_ctx
        t_embed = self.time_embed(timestep_embedding(t, self.backbone.width))
        return self._forward_with_cond(x, [(t_embed, self.time_token_cond)])

        :param x: an [N x C x T] tensor.
        :param t: an [N] tensor.
        :return: an [N x C' x T] tensor.
        
shap_e/models/generation/transformer.py