5ea0c27f524a3e684d9a2e6f012e30e6da2de8aa,scripts/bert/finetune_classifier.py,,test,#Any#Any#,334

Before Change

                    type_ids.as_in_context(ctx),
                    valid_length.astype("float32").as_in_context(ctx))
        values, indices = mx.nd.topk(out, k=1, ret_typ="both")
        value_list.extend(values.asnumpy().reshape(-1).tolist())
        index_list.extend(indices.asnumpy().reshape(-1).tolist())

    mx.nd.waitall()

After Change

        if not task.class_labels:
            // regression task
            for result in out.asnumpy().reshape(-1).tolist():
                results.append("{:.3f}".format(result))
        else:
            // classification task
            indices = mx.nd.topk(out, k=1, ret_typ="indices", dtype="int32").asnumpy()

Instances