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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.binary.matrix;
import java.util.HashMap;
import org.junit.Test;
import org.apache.sysds.api.DMLScript;
import org.apache.sysds.common.Types.ExecMode;
import org.apache.sysds.hops.AggBinaryOp;
import org.apache.sysds.hops.AggBinaryOp.MMultMethod;
import org.apache.sysds.lops.LopProperties.ExecType;
import org.apache.sysds.runtime.matrix.data.MatrixValue.CellIndex;
import org.apache.sysds.test.AutomatedTestBase;
import org.apache.sysds.test.TestConfiguration;
import org.apache.sysds.test.TestUtils;
/**
* Test for MMCJ MR because otherwise seldom (if at all) executed in our testsuite, ultrasparse
* in order to account for 'empty block rejection' optimization.
*
* Furthermore, it is at the same time a test for removeEmpty-diag which has special
* physical operators.
*/
public class UltraSparseMRMatrixMultiplicationTest extends AutomatedTestBase
{
private final static String TEST_NAME1 = "UltraSparseMatrixMultiplication";
private final static String TEST_NAME2 = "UltraSparseMatrixMultiplication2";
private final static String TEST_DIR = "functions/binary/matrix/";
private final static String TEST_CLASS_DIR = TEST_DIR +
UltraSparseMRMatrixMultiplicationTest.class.getSimpleName() + "/";
private final static double eps = 1e-10;
private final static int rows = 4045;
private final static int cols = 23;
private final static double sparsity1 = 0.7;
private final static double sparsity2 = 0.1;
@Override
public void setUp()
{
addTestConfiguration(TEST_NAME1,
new TestConfiguration(TEST_CLASS_DIR, TEST_NAME1, new String[] { "C" }) );
addTestConfiguration(TEST_NAME2,
new TestConfiguration(TEST_CLASS_DIR, TEST_NAME2, new String[] { "C" }) );
}
@Test
public void testMMRowDenseCP()
{
runMatrixMatrixMultiplicationTest(false, false, ExecType.CP, true, false);
}
@Test
public void testMMRowSparseCP()
{
runMatrixMatrixMultiplicationTest(false, true, ExecType.CP, true, false);
}
@Test
public void testMMColDenseCP()
{
runMatrixMatrixMultiplicationTest(false, false, ExecType.CP, false, false);
}
@Test
public void testMMColSparseCP()
{
runMatrixMatrixMultiplicationTest(false, true, ExecType.CP, false, false);
}
@Test
public void testMMRowDenseSpark_PMMJ()
{
runMatrixMatrixMultiplicationTest(false, false, ExecType.SPARK, true, true);
}
@Test
public void testMMRowSparseSpark_PMMJ()
{
runMatrixMatrixMultiplicationTest(false, true, ExecType.SPARK, true, true);
}
private void runMatrixMatrixMultiplicationTest( boolean sparseM1, boolean sparseM2, ExecType instType, boolean rowwise, boolean forcePMMJ)
{
//setup exec type, rows, cols
//rtplatform for MR
ExecMode platformOld = rtplatform;
switch( instType ){
case SPARK: rtplatform = ExecMode.SPARK; break;
default: rtplatform = ExecMode.HYBRID; break;
}
boolean sparkConfigOld = DMLScript.USE_LOCAL_SPARK_CONFIG;
if( rtplatform == ExecMode.SPARK )
DMLScript.USE_LOCAL_SPARK_CONFIG = true;
if(forcePMMJ)
AggBinaryOp.FORCED_MMULT_METHOD = MMultMethod.PMM;
try
{
String TEST_NAME = (rowwise) ? TEST_NAME1 : TEST_NAME2;
getAndLoadTestConfiguration(TEST_NAME);
/* This is for running the junit test the new way, i.e., construct the arguments directly */
String HOME = SCRIPT_DIR + TEST_DIR;
fullDMLScriptName = HOME + TEST_NAME + ".dml";
programArgs = new String[]{"-explain","-args", input("A"),
Integer.toString(rows), Integer.toString(cols), input("B"), output("C") };
fullRScriptName = HOME + TEST_NAME + ".R";
rCmd = "Rscript" + " " + fullRScriptName + " " + inputDir() + " " + expectedDir();
//generate actual dataset
double[][] A = getRandomMatrix(rows, cols, 0, 1, sparseM1?sparsity2:sparsity1, 7);
writeInputMatrix("A", A, true);
double[][] B = getRandomMatrix(rows, 1, 0.51, 3.49, 1.0, 3);
B = TestUtils.round(B);
writeInputMatrix("B", B, true);
boolean exceptionExpected = false;
runTest(true, exceptionExpected, null, -1);
runRScript(true);
//compare matrices
HashMap<CellIndex, Double> dmlfile = readDMLMatrixFromOutputDir("C");
HashMap<CellIndex, Double> rfile = readRMatrixFromExpectedDir("C");
TestUtils.compareMatrices(dmlfile, rfile, eps, "Stat-DML", "Stat-R");
}
finally {
rtplatform = platformOld;
DMLScript.USE_LOCAL_SPARK_CONFIG = sparkConfigOld;
AggBinaryOp.FORCED_MMULT_METHOD = null;
}
}
}