def METHOD_NAME(self, cmndfs: torch.Tensor) -> torch.Tensor:
    """yingram calculator from cMNDFs
    (cumulative Mean Normalized Difference Functions)
    Args:
        cmndfs: torch.Tensor
            calculated cumulative mean normalized difference function
            for details, see models/yin.py or eq. (1) and (2)
        ms: list of midi(int)
        fs: sampling rate
    Returns:
        y:
            calculated batch yingram
    """
    # c_ms = np.asarray([Pitch.midi_to_lag(m, fs) for m in ms])
    # c_ms = torch.from_numpy(c_ms).to(cmndfs.device)
    y = (cmndfs[:, self.c_ms_ceil] - cmndfs[:, self.c_ms_floor]) / (
        self.c_ms_ceil - self.c_ms_floor
    ).unsqueeze(0) * (self.c_ms - self.c_ms_floor).unsqueeze(0) + cmndfs[
        :, self.c_ms_floor
    ]
    return y