src/evaluator.py [459:464]:
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            alen = torch.arange(len2.max(), dtype=torch.long, device=len2.device)
            pred_mask = (
                alen[:, None] < len2[None] - 1
            )  # do not predict anything given the last target word
            y = x2[1:].masked_select(pred_mask[:-1])
            assert len(y) == (len2 - 1).sum().item()
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src/trainer.py [515:520]:
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        alen = torch.arange(len2.max(), dtype=torch.long, device=len2.device)
        pred_mask = (
            alen[:, None] < len2[None] - 1
        )  # do not predict anything given the last target word
        y = x2[1:].masked_select(pred_mask[:-1])
        assert len(y) == (len2 - 1).sum().item()
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