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* 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.sysds.test.functions.builtin;
import org.apache.sysds.common.Types;
import org.apache.sysds.hops.OptimizerUtils;
import org.apache.sysds.lops.LopProperties;
import org.apache.sysds.test.AutomatedTestBase;
import org.apache.sysds.test.TestConfiguration;
import org.apache.sysds.test.TestUtils;
import org.junit.Assert;
import org.junit.Test;
public class BuiltinGMMPredictTest extends AutomatedTestBase {
private final static String TEST_NAME = "GMM_Predict";
private final static String TEST_DIR = "functions/builtin/";
private static final String TEST_CLASS_DIR = TEST_DIR + BuiltinGMMPredictTest.class.getSimpleName() + "/";
private final static double eps = 2;
private final static double tol = 1e-3;
private final static double tol2 = 1e-5;
private final static String DATASET = SCRIPT_DIR + "functions/transform/input/iris/iris.csv";
@Override
public void setUp() {
addTestConfiguration(TEST_NAME, new TestConfiguration(TEST_CLASS_DIR, TEST_NAME, new String[] {"B"}));
}
@Test
public void testGMMMPredictCP1() {
runGMMPredictTest(3, "VVI", "random", 10,
0.000000001, tol,42,true, LopProperties.ExecType.CP);
}
@Test
public void testGMMMPredictCP2() {
runGMMPredictTest(3, "VII", "random", 50,
0.000001, tol2,42,true, LopProperties.ExecType.CP);
}
@Test
public void testGMMMPredictCPKmean1() {
runGMMPredictTest(3, "VVV", "kmeans", 10,
0.0000001, tol,42,true, LopProperties.ExecType.CP);
}
@Test
public void testGMMMPredictCPKmean2() {
runGMMPredictTest(3, "EEE", "kmeans", 150,
0.000001, tol,42,true, LopProperties.ExecType.CP);
}
@Test
public void testGMMMPredictCPKmean3() {
runGMMPredictTest(3, "VII", "kmeans", 50,
0.000001, tol2,42,true, LopProperties.ExecType.CP);
}
// @Test
// public void testGMMM1Spark() {
// runGMMPredictTest(3, "VVV", "random", 10,
// 0.0000001, tol,42,true, LopProperties.ExecType.SPARK); }
//
// @Test
// public void testGMMM2Spark() {
// runGMMPredictTest(3, "EEE", "random", 50,
// 0.0000001, tol,42,true, LopProperties.ExecType.CP);
// }
//
// @Test
// public void testGMMMS3Spark() {
// runGMMPredictTest(3, "VVI", "random", 100,
// 0.000001, tol,42,true, LopProperties.ExecType.CP);
// }
//
// @Test
// public void testGMMM4Spark() {
// runGMMPredictTest(3, "VII", "random", 100,
// 0.000001, tol1,42,true, LopProperties.ExecType.CP);
// }
//
// @Test
// public void testGMMM1KmeanSpark() {
// runGMMPredictTest(3, "VVV", "kmeans", 100,
// 0.000001, tol2,42,false, LopProperties.ExecType.SPARK);
// }
//
// @Test
// public void testGMMM2KmeanSpark() {
// runGMMPredictTest(3, "EEE", "kmeans", 50,
// 0.00000001, tol1,42,false, LopProperties.ExecType.SPARK);
// }
//
// @Test
// public void testGMMM3KmeanSpark() {
// runGMMPredictTest(3, "VVI", "kmeans", 100,
// 0.000001, tol,42,false, LopProperties.ExecType.SPARK);
// }
//
// @Test
// public void testGMMM4KmeanSpark() {
// runGMMPredictTest(3, "VII", "kmeans", 100,
// 0.000001, tol,42,false, LopProperties.ExecType.SPARK);
// }
private void runGMMPredictTest(int G_mixtures, String model, String init_param, int iter,
double reg, double tol, int seed, boolean rewrite, LopProperties.ExecType instType) {
Types.ExecMode platformOld = setExecMode(instType);
boolean rewriteOld = OptimizerUtils.ALLOW_ALGEBRAIC_SIMPLIFICATION;
OptimizerUtils.ALLOW_ALGEBRAIC_SIMPLIFICATION = rewrite;
try {
loadTestConfiguration(getTestConfiguration(TEST_NAME));
String HOME = SCRIPT_DIR + TEST_DIR;
fullDMLScriptName = HOME + TEST_NAME + ".dml";
String outFile = output("O");
System.out.println(outFile);
programArgs = new String[] {"-args", DATASET,
String.valueOf(G_mixtures), model, init_param, String.valueOf(iter), String.valueOf(reg),
String.valueOf(tol), String.valueOf(seed), outFile};
runTest(true, false, null, -1);
// compare results
double accuracy = TestUtils.readDMLScalar(outFile);
Assert.assertEquals(1, accuracy, eps);
}
finally {
resetExecMode(platformOld);
OptimizerUtils.ALLOW_ALGEBRAIC_SIMPLIFICATION = rewriteOld;
}
}
}