lindong28 commented on code in PR #219: URL: https://github.com/apache/flink-ml/pull/219#discussion_r1141624836
########## flink-ml-servable-lib/src/test/java/org/apache/flink/ml/classification/LogisticRegressionModelServableTest.java: ########## @@ -0,0 +1,142 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.flink.ml.classification; + +import org.apache.flink.ml.classification.logisticregression.LogisticRegressionModelData; +import org.apache.flink.ml.classification.logisticregression.LogisticRegressionModelServable; +import org.apache.flink.ml.linalg.DenseVector; +import org.apache.flink.ml.linalg.Vector; +import org.apache.flink.ml.linalg.Vectors; +import org.apache.flink.ml.servable.api.DataFrame; +import org.apache.flink.ml.servable.api.Row; +import org.apache.flink.ml.servable.types.BasicType; +import org.apache.flink.ml.servable.types.DataTypes; + +import org.junit.Test; + +import java.io.ByteArrayInputStream; +import java.io.ByteArrayOutputStream; +import java.io.IOException; +import java.util.ArrayList; +import java.util.Arrays; + +import static org.junit.Assert.assertEquals; +import static org.junit.Assert.assertTrue; + +/** Tests the {@link LogisticRegressionModelServable}. */ +public class LogisticRegressionModelServableTest { + + protected static final DataFrame PREDICT_DATA = + new DataFrame( + new ArrayList<>(Arrays.asList("features", "label", "weight")), + new ArrayList<>( + Arrays.asList( + DataTypes.VECTOR(BasicType.DOUBLE), + DataTypes.DOUBLE, + DataTypes.DOUBLE)), + Arrays.asList( + new Row( + new ArrayList<>( + Arrays.asList(Vectors.dense(1, 2, 3, 4), 0., 1.))), + new Row( + new ArrayList<>( + Arrays.asList(Vectors.dense(1, 2, 3, 4), 0., 2.))), + new Row( + new ArrayList<>( + Arrays.asList(Vectors.dense(2, 2, 3, 4), 0., 3.))), + new Row( + new ArrayList<>( + Arrays.asList(Vectors.dense(3, 2, 3, 4), 0., 4.))), + new Row( + new ArrayList<>( + Arrays.asList(Vectors.dense(4, 2, 3, 4), 0., 5.))), + new Row( + new ArrayList<>( + Arrays.asList(Vectors.dense(11, 2, 3, 4), 1., 1.))), + new Row( + new ArrayList<>( + Arrays.asList(Vectors.dense(12, 2, 3, 4), 1., 2.))), + new Row( + new ArrayList<>( + Arrays.asList(Vectors.dense(13, 2, 3, 4), 1., 3.))), + new Row( + new ArrayList<>( + Arrays.asList(Vectors.dense(14, 2, 3, 4), 1., 4.))), + new Row( + new ArrayList<>( + Arrays.asList(Vectors.dense(15, 2, 3, 4), 1., 5.))))); + + private static final DenseVector COEFFICIENT = Vectors.dense(0.525, -0.283, -0.425, -0.567); + + private static final double TOLERANCE = 1e-7; + + @Test + public void testParam() { + LogisticRegressionModelServable servable = new LogisticRegressionModelServable(); + assertEquals("features", servable.getFeaturesCol()); + assertEquals("prediction", servable.getPredictionCol()); + assertEquals("rawPrediction", servable.getRawPredictionCol()); + + servable.setFeaturesCol("test_features") + .setPredictionCol("test_predictionCol") + .setRawPredictionCol("test_rawPredictionCol"); + assertEquals("test_features", servable.getFeaturesCol()); + assertEquals("test_predictionCol", servable.getPredictionCol()); + assertEquals("test_rawPredictionCol", servable.getRawPredictionCol()); + } + + @Test + public void testTransform() throws IOException { + LogisticRegressionModelData modelData = new LogisticRegressionModelData(COEFFICIENT); Review Comment: The separation of `flink-ml-lib` and `flink-ml-servable-lib` modules is mostly an implementation detail and should not affect how users use `Model` and `Servable` classes, right? -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@flink.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
