def METHOD_NAME(self, sources, predictions, references, gpus=None, progress_bar=False):
    if gpus is None:
        gpus = 1 if torch.cuda.is_available() else 0
    data = {"src": sources, "mt": predictions, "ref": references}
    data = [dict(zip(data, t)) for t in zip(*data.values())]
    scores, mean_score = self.scorer.predict(data, gpus=gpus, progress_bar=progress_bar)
    return {"mean_score": mean_score, "scores": scores}