`k` largest(/smallest) losses and indexes, defaulting to all losses (sorted by `largest`).

def top_losses(self, k:int=None, largest=True):
        "`k` largest(/smallest) losses and indexes, defaulting to all losses (sorted by `largest`)."
        return self.losses.topk(ifnone(k, len(self.losses)), largest=largest)