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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.unary.matrix;
import org.junit.Assert;
import org.junit.Test;
import org.apache.sysds.api.DMLScript;
import org.apache.sysds.common.Types.ExecMode;
import org.apache.sysds.runtime.matrix.data.MatrixValue;
import org.apache.sysds.runtime.matrix.data.MatrixValue.CellIndex;
import org.apache.sysds.runtime.meta.MatrixCharacteristics;
import org.apache.sysds.test.AutomatedTestBase;
import org.apache.sysds.test.TestConfiguration;
import java.util.HashMap;
/**
* Tests for the Cholesky matrix factorization
* Note:
* 1. Only tested for dense configuration of matrices (small, & large)
* 2. The remaining tests for matrix dim check, positive definiteness
* already tested at commons-math.
*/
public class CholeskyTest extends AutomatedTestBase
{
private final static String TEST_NAME = "cholesky";
private final static String TEST_DIR = "functions/unary/matrix/";
private static final String TEST_CLASS_DIR = TEST_DIR + CholeskyTest.class.getSimpleName() + "/";
private final static int rows1 = 500;
private final static int rows2 = 2500;
private final static int cols1 = 500;
private final static int cols2 = 2500;
private final static double sparsity = 0.9;
@Override
public void setUp() {
addTestConfiguration(
TEST_NAME,
new TestConfiguration(TEST_CLASS_DIR, TEST_NAME,
new String[] { "D" }) );
}
@Test
public void testCholeskyDenseCP() {
runTestCholesky( rows1, cols1, ExecMode.SINGLE_NODE );
}
@Test
public void testCholeskyDenseSP() {
runTestCholesky( rows1, cols1, ExecMode.SPARK );
}
@Test
public void testCholeskyDenseHybrid() {
runTestCholesky( rows1, cols1, ExecMode.HYBRID );
}
@Test
public void testLargeCholeskyDenseCP() {
runTestCholesky( rows2, cols2, ExecMode.SINGLE_NODE );
}
@Test
public void testLargeCholeskyDenseSP() {
runTestCholesky( rows2, cols2, ExecMode.SPARK );
}
@Test
public void testLargeCholeskyDenseHybrid() {
runTestCholesky( rows2, cols2, ExecMode.HYBRID );
}
private void runTestCholesky( int rows, int cols, ExecMode rt) {
ExecMode rtold = rtplatform;
rtplatform = rt;
boolean sparkConfigOld = DMLScript.USE_LOCAL_SPARK_CONFIG;
if( rtplatform == ExecMode.SPARK )
DMLScript.USE_LOCAL_SPARK_CONFIG = true;
try {
getAndLoadTestConfiguration(TEST_NAME);
String HOME = SCRIPT_DIR + TEST_DIR;
fullDMLScriptName = HOME+ TEST_NAME + ".dml";
programArgs = new String[]{"-args", input("A"), output("D") };
double[][] A = getRandomMatrix(rows, cols, 0, 1, sparsity, 10);
MatrixCharacteristics mc = new MatrixCharacteristics(rows, cols, -1, -1);
writeInputMatrixWithMTD("A", A, false, mc);
//run tests and compare results
runTest(true, false, null, -1);
HashMap<CellIndex, Double> dmlOut = readDMLMatrixFromOutputDir("D");
MatrixValue.CellIndex index = dmlOut.keySet().iterator().next();
double d = dmlOut.get(index);
Assert.assertEquals(0, d, 1e-5);
}
finally {
DMLScript.USE_LOCAL_SPARK_CONFIG = sparkConfigOld;
rtplatform = rtold;
}
}
}