def METHOD_NAME(self, dy_model, metrics_list, batch_data, config):
    labels, sparse_tensor = self.create_feeds(batch_data, config)
    raw = dy_model.forward(sparse_tensor)
    #predict_raw = paddle.nn.functional.softmax(raw)
    soft_predict = paddle.nn.functional.sigmoid(
        paddle.reshape(raw, [-1, 1]))
    predict_2d = paddle.concat(x=[1 - soft_predict, soft_predict], axis=-1)
    labels = paddle.reshape(labels, [-1, 1])
    metrics_list[0].update(preds=predict_2d.numpy(), labels=labels.numpy())
    return metrics_list, None