029fdb5624fafee03a59f49d86b676f25851febf,python/baseline/pytorch/tagger/train.py,TaggerTrainerPyTorch,_test,#TaggerTrainerPyTorch#Any#,75

Before Change

        metrics = {}
        steps = len(ts)
        pg = create_progress_bar(steps)
        for x, xch, y, lengths, ids in ts:
            x, xch, y = self._wrap(x, xch, y)
            pred = self.model((x, xch, lengths))
            correct, count, overlaps, golds, guesses = self.process_output(pred, y.data, lengths, ids, None, None)
            total_correct += correct
            total_sum += count
            total_gold_count += golds
            total_guess_count += guesses
            total_overlap_count += overlaps
            pg.update()

        pg.done()
        total_acc = total_correct / float(total_sum)
        // Only show the fscore if requested
        metrics["f1"] = f_score(total_overlap_count, total_gold_count, total_guess_count)

After Change

        metrics = {}
        steps = len(ts)
        pg = create_progress_bar(steps)
        for batch_dict in ts:

            fx = self.model.make_input(batch_dict)
            inputs = fx[:-1]
            y = fx[-1]
            lengths = batch_dict["lengths"]
            ids = batch_dict["ids"]
            pred = self.model(inputs)
            correct, count, overlaps, golds, guesses = self.process_output(pred, y.data, lengths, ids, None, None)
            total_correct += correct
            total_sum += count
            total_gold_count += golds
            total_guess_count += guesses
            total_overlap_count += overlaps
            pg.update()

        pg.done()
        total_acc = total_correct / float(total_sum)
        // Only show the fscore if requested
        metrics["f1"] = f_score(total_overlap_count, total_gold_count, total_guess_count)

Instances