    def cache_to_batch(self, cache: List[List[torch.Tensor]]) -> List[torch.Tensor]:
        """
        Args:
            cache : [[state_m_1, state_c_1], [state_m_1, state_c_1]...]

        Returns:
            new_caceh: [state_ms, state_cs],
                state_ms: [1*n_layers, bs, ...]
                state_cs: [1*n_layers, bs, ...]
        """
        state_ms = torch.cat([states[0] for states in cache], dim=1)
        state_cs = torch.cat([states[1] for states in cache], dim=1)
        return [state_ms, state_cs]
Args:
cache : [[state_m_1, state_c_1], [state_m_1, state_c_1]...]

Returns:
new_caceh: [state_ms, state_cs],
state_ms: [1*n_layers, bs, ...]
state_cs: [1*n_layers, bs, ...]
modules/wenet_extractor/transducer/predictor.py