def METHOD_NAME(preds: Tensor, target: Tensor, fs: int, mode: str):
    """Comparison function."""
    # shape: preds [BATCH_SIZE, Time] , target [BATCH_SIZE, Time]
    # or shape: preds [NUM_BATCHES*BATCH_SIZE, Time] , target [NUM_BATCHES*BATCH_SIZE, Time]
    target = target.detach().cpu().numpy()
    preds = preds.detach().cpu().numpy()
    mss = []
    for b in range(preds.shape[0]):
        pesq_val = pesq_backend(fs, target[b, ...], preds[b, ...], mode)
        mss.append(pesq_val)
    return torch.tensor(mss)