9d22742baeeb608bac5594c3ece96f62f0734dce,qanta/buzzer/trainer.py,Trainer,test,#Trainer#Any#,62

Before Change

                    qnum = qnum.tolist()
                finals[qnum] = np.argmax(ys[i][-1][:N_GUESSERS]).tolist()
                buzzes[qnum] = [-1, -1]
                for pos, chosen in enumerate(action):
                    if chosen < N_GUESSERS:
                        buzzes[qnum] = (pos, chosen)
                        break
            progress_bar(*test_iter.epoch_detail)
        test_iter.finalize(reset=True)
        progress_bar.finalize()
        return buzzes, finals

After Change

            ys = F.softmax(ys) // length * batch_size, n_guessers
            ys = F.swapaxes(F.reshape(ys, (length, batch_size, -1)), 0, 1)
            ys.to_cpu()
            masks = batch.mask.T.tolist()
            assert len(masks) == batch_size
            for qnum, scores, mask in zip(batch.qids, ys.data, masks):
                if isinstance(qnum, np.ndarray):
                    qnum = qnum.tolist()
                total = int(sum(mask))
                buzzes[qnum] = scores[:total].tolist()
            progress_bar(*test_iter.epoch_detail)
        test_iter.finalize(reset=True)
        progress_bar.finalize()
        return buzzes

Instances