Bert文本对回归预测 (BertTextPairRegressorPredictBatchOp)

Java 类名：com.alibaba.alink.operator.batch.regression.BertTextPairRegressorPredictBatchOp

Python 类名：BertTextPairRegressorPredictBatchOp

功能介绍

与 BERT 文本对回归训练组件对应的预测组件。

参数说明

名称	中文名称	描述	类型	是否必须？	取值范围	默认值
predictionCol	预测结果列名	预测结果列名	String	✓
inferBatchSize	推理数据批大小	推理数据批大小	Integer			256
reservedCols	算法保留列名	算法保留列	String[]			null

代码示例

** 以下代码仅用于示意，可能需要修改部分代码或者配置环境后才能正常运行！**

Python 代码

url = "http://alink-algo-packages.oss-cn-hangzhou-zmf.aliyuncs.com/data/MRPC/train.tsv"
schemaStr = "f_quality double, f_id_1 string, f_id_2 string, f_string_1 string, f_string_2 string"
data = CsvSourceBatchOp() \
    .setFilePath(url) \
    .setSchemaStr(schemaStr) \
    .setFieldDelimiter("\t") \
    .setIgnoreFirstLine(True) \
    .setQuoteChar(None)
data = data.firstN(300)
model = CsvSourceBatchOp() \
    .setFilePath("http://alink-test.oss-cn-beijing.aliyuncs.com/jiqi-temp/tf_ut_files/bert_text_pair_regressor_model.csv") \
    .setSchemaStr("model_id bigint, model_info string, label_value double")
predict = BertTextPairRegressorPredictBatchOp() \
    .setPredictionCol("pred") \
    .setReservedCols(["f_quality"]) \
    .linkFrom(model, data)
predict.print()

Java 代码

import com.alibaba.alink.operator.batch.BatchOperator;
import com.alibaba.alink.operator.batch.regression.BertTextPairRegressorPredictBatchOp;
import com.alibaba.alink.operator.batch.source.CsvSourceBatchOp;
import org.junit.Test;

public class BertTextPairRegressorPredictBatchOpTest {

	@Test
	public void test() throws Exception {
		String url = "http://alink-algo-packages.oss-cn-hangzhou-zmf.aliyuncs.com/data/MRPC/train.tsv";
		String schemaStr = "f_quality double, f_id_1 string, f_id_2 string, f_string_1 string, f_string_2 string";
		BatchOperator <?> data = new CsvSourceBatchOp()
			.setFilePath(url)
			.setSchemaStr(schemaStr)
			.setFieldDelimiter("\t")
			.setIgnoreFirstLine(true)
			.setQuoteChar(null);
		data = data.firstN(300);
		BatchOperator <?> model = new CsvSourceBatchOp()
			.setFilePath("http://alink-test.oss-cn-beijing.aliyuncs.com/jiqi-temp/tf_ut_files/bert_text_pair_regressor_model.csv")
			.setSchemaStr("model_id bigint, model_info string, label_value double");
		BertTextPairRegressorPredictBatchOp predict = new BertTextPairRegressorPredictBatchOp()
			.setPredictionCol("pred")
			.setReservedCols("f_quality")
			.linkFrom(model, data);
		predict.print();
	}
}

运行结果

f_quality	pred
0.0	1.404307
0.0	1.404307
1.0	1.404307
0.0	1.404307
1.0	1.404307
…	…
0.0	1.404392
1.0	1.404392
0.0	1.404392
1.0	1.404392
1.0	1.404392