def METHOD_NAME(batch, LFR_m=1, LFR_n=1):
    """
    Args:
        batch: list, len(batch) = 1. See AudioDataset.__getitem__()
    Returns:
        xs_pad: N x Ti x D, torch.Tensor
        ilens : N, torch.Tentor
        ys_pad: N x To, torch.Tensor
    """
    # batch should be located in list
    assert len(batch) == 1
    batch = load_inputs_and_targets(batch[0], LFR_m=LFR_m, LFR_n=LFR_n)
    xs, ys = batch
    # TODO: perform subsamping
    # get batch of lengths of input sequences
    ilens = np.array([x.shape[0] for x in xs])
    # perform padding and convert to tensor
    xs_pad = pad_list([torch.from_numpy(x).float() for x in xs], 0)
    ilens = torch.from_numpy(ilens)
    ys_pad = pad_list([torch.from_numpy(y).long() for y in ys], IGNORE_ID)
    return xs_pad, ilens, ys_pad