weibozhao commented on code in PR #135: URL: https://github.com/apache/flink-ml/pull/135#discussion_r935274102
########## flink-ml-lib/src/test/java/org/apache/flink/ml/feature/ElementwiseProductTest.java: ########## @@ -0,0 +1,207 @@ +/* + * 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.feature; + +import org.apache.flink.api.common.restartstrategy.RestartStrategies; +import org.apache.flink.configuration.Configuration; +import org.apache.flink.ml.feature.elementwiseproduct.ElementwiseProduct; +import org.apache.flink.ml.linalg.DenseVector; +import org.apache.flink.ml.linalg.SparseVector; +import org.apache.flink.ml.linalg.Vectors; +import org.apache.flink.ml.util.TestUtils; +import org.apache.flink.streaming.api.datastream.DataStream; +import org.apache.flink.streaming.api.environment.ExecutionCheckpointingOptions; +import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment; +import org.apache.flink.table.api.Table; +import org.apache.flink.table.api.bridge.java.StreamTableEnvironment; +import org.apache.flink.test.util.AbstractTestBase; +import org.apache.flink.types.Row; + +import org.apache.commons.collections.IteratorUtils; +import org.junit.Assert; +import org.junit.Before; +import org.junit.Test; + +import java.util.Arrays; +import java.util.List; + +import static org.junit.Assert.assertArrayEquals; +import static org.junit.Assert.assertEquals; +import static org.junit.Assert.assertNull; + +/** Tests {@link ElementwiseProduct}. */ +public class ElementwiseProductTest extends AbstractTestBase { + + private StreamTableEnvironment tEnv; + private Table inputDataTable; + + private static final List<Row> INPUT_DATA = + Arrays.asList( + Row.of( + 0, + Vectors.dense(2.1, 3.1), + Vectors.sparse(5, new int[] {3}, new double[] {1.0})), + Row.of( + 1, + Vectors.dense(1.1, 3.3), + Vectors.sparse( + 5, new int[] {4, 2, 3, 1}, new double[] {4.0, 2.0, 3.0, 1.0})), + Row.of(2, null, null)); + + private static final double[] EXPECTED_OUTPUT_DENSE_VEC_ARRAY_1 = new double[] {2.31, 3.41}; + private static final double[] EXPECTED_OUTPUT_DENSE_VEC_ARRAY_2 = new double[] {1.21, 3.63}; + + private static final int EXPECTED_OUTPUT_SPARSE_VEC_SIZE_1 = 5; + private static final int[] EXPECTED_OUTPUT_SPARSE_VEC_INDICES_1 = new int[] {3}; + private static final double[] EXPECTED_OUTPUT_SPARSE_VEC_VALUES_1 = new double[] {0.0}; + + private static final int EXPECTED_OUTPUT_SPARSE_VEC_SIZE_2 = 5; + private static final int[] EXPECTED_OUTPUT_SPARSE_VEC_INDICES_2 = new int[] {1, 2, 3, 4}; + private static final double[] EXPECTED_OUTPUT_SPARSE_VEC_VALUES_2 = + new double[] {1.1, 0.0, 0.0, 0.0}; + + @Before + public void before() { + Configuration config = new Configuration(); + config.set(ExecutionCheckpointingOptions.ENABLE_CHECKPOINTS_AFTER_TASKS_FINISH, true); + StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment(config); + env.setParallelism(4); + env.enableCheckpointing(100); + env.setRestartStrategy(RestartStrategies.noRestart()); + tEnv = StreamTableEnvironment.create(env); + DataStream<Row> dataStream = env.fromCollection(INPUT_DATA); + inputDataTable = tEnv.fromDataStream(dataStream).as("id", "vec", "sparseVec"); + } + + private void verifyOutputResult(Table output, String outputCol, boolean isSparse) + throws Exception { + DataStream<Row> dataStream = tEnv.toDataStream(output); + List<Row> results = IteratorUtils.toList(dataStream.executeAndCollect()); + assertEquals(3, results.size()); + for (Row result : results) { + if (result.getField(0) == (Object) 0) { + if (isSparse) { + SparseVector sparseVector = (SparseVector) result.getField(outputCol); + assertEquals(EXPECTED_OUTPUT_SPARSE_VEC_SIZE_1, sparseVector.size()); + assertArrayEquals(EXPECTED_OUTPUT_SPARSE_VEC_INDICES_1, sparseVector.indices); + assertArrayEquals( + EXPECTED_OUTPUT_SPARSE_VEC_VALUES_1, sparseVector.values, 1.0e-5); + } else { + assertArrayEquals( + EXPECTED_OUTPUT_DENSE_VEC_ARRAY_1, + ((DenseVector) result.getField(outputCol)).values, + 1.0e-5); + } + } else if (result.getField(0) == (Object) 1) { Review Comment: If we use the above code, the epsilon cannot be added. When there exists a small error, just like 1.0e-6, the assert will fail. Assertion of double value must use epsilon. -- 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: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
