def METHOD_NAME(self, dy_model, metrics_list, batch_data, config):
    label, sparse_tensor, dense_tensor = self.create_feeds(batch_data,
                                                           config)
    pred = dy_model.forward(sparse_tensor, dense_tensor)
    # update metrics
    predict_2d = paddle.concat(x=[1 - pred, pred], axis=1)
    metrics_list[0].update(preds=predict_2d.numpy(), labels=label.numpy())
    return metrics_list, None