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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 java.util.HashMap;
import org.junit.AfterClass;
import org.junit.Assert;
import org.junit.BeforeClass;
import org.junit.Test;
import org.apache.sysds.api.DMLScript;
import org.apache.sysds.common.Types.ExecMode;
import org.apache.sysds.hops.OptimizerUtils;
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;
import org.apache.sysds.utils.Statistics;
/**
*
*
*/
public class FullCummaxTest extends AutomatedTestBase
{
private final static String TEST_NAME = "Cummax";
private final static String TEST_DIR = "functions/unary/matrix/";
private static final String TEST_CLASS_DIR = TEST_DIR + FullCummaxTest.class.getSimpleName() + "/";
private final static double eps = 1e-10;
private final static int rowsMatrix = 1201;
private final static int colsMatrix = 1103;
private final static double spSparse = 0.1;
private final static double spDense = 0.9;
private enum InputType {
COL_VECTOR,
ROW_VECTOR,
MATRIX
}
@Override
public void setUp()
{
addTestConfiguration(TEST_NAME,new TestConfiguration(TEST_CLASS_DIR, TEST_NAME,new String[]{"B"}));
if (TEST_CACHE_ENABLED) {
setOutAndExpectedDeletionDisabled(true);
}
}
@BeforeClass
public static void init()
{
TestUtils.clearDirectory(TEST_DATA_DIR + TEST_CLASS_DIR);
}
@AfterClass
public static void cleanUp()
{
if (TEST_CACHE_ENABLED) {
TestUtils.clearDirectory(TEST_DATA_DIR + TEST_CLASS_DIR);
}
}
@Test
public void testCummaxColVectorDenseCP()
{
runColAggregateOperationTest(InputType.COL_VECTOR, false, ExecType.CP);
}
@Test
public void testCummaxRowVectorDenseCP()
{
runColAggregateOperationTest(InputType.ROW_VECTOR, false, ExecType.CP);
}
@Test
public void testCummaxRowVectorDenseNoRewritesCP()
{
runColAggregateOperationTest(InputType.ROW_VECTOR, false, ExecType.CP, false);
}
@Test
public void testCummaxMatrixDenseCP()
{
runColAggregateOperationTest(InputType.MATRIX, false, ExecType.CP);
}
@Test
public void testCummaxColVectorSparseCP()
{
runColAggregateOperationTest(InputType.COL_VECTOR, true, ExecType.CP);
}
@Test
public void testCummaxRowVectorSparseCP()
{
runColAggregateOperationTest(InputType.ROW_VECTOR, true, ExecType.CP);
}
@Test
public void testCummaxRowVectorSparseNoRewritesCP()
{
runColAggregateOperationTest(InputType.ROW_VECTOR, true, ExecType.CP, false);
}
@Test
public void testCummaxMatrixSparseCP()
{
runColAggregateOperationTest(InputType.MATRIX, true, ExecType.CP);
}
@Test
public void testCummaxColVectorDenseSP()
{
runColAggregateOperationTest(InputType.COL_VECTOR, false, ExecType.SPARK);
}
@Test
public void testCummaxRowVectorDenseSP()
{
runColAggregateOperationTest(InputType.ROW_VECTOR, false, ExecType.SPARK);
}
@Test
public void testCummaxRowVectorDenseNoRewritesSP()
{
runColAggregateOperationTest(InputType.ROW_VECTOR, false, ExecType.SPARK, false);
}
@Test
public void testCummaxMatrixDenseSP()
{
runColAggregateOperationTest(InputType.MATRIX, false, ExecType.SPARK);
}
@Test
public void testCummaxColVectorSparseSP()
{
runColAggregateOperationTest(InputType.COL_VECTOR, true, ExecType.SPARK);
}
@Test
public void testCummaxRowVectorSparseSP()
{
runColAggregateOperationTest(InputType.ROW_VECTOR, true, ExecType.SPARK);
}
@Test
public void testCummaxRowVectorSparseNoRewritesSP()
{
runColAggregateOperationTest(InputType.ROW_VECTOR, true, ExecType.SPARK, false);
}
@Test
public void testCummaxMatrixSparseSP()
{
runColAggregateOperationTest(InputType.MATRIX, true, ExecType.SPARK);
}
private void runColAggregateOperationTest( InputType type, boolean sparse, ExecType instType)
{
//by default we apply algebraic simplification rewrites
runColAggregateOperationTest(type, sparse, instType, true);
}
private void runColAggregateOperationTest( InputType type, boolean sparse, ExecType instType, boolean rewrites)
{
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;
//rewrites
boolean oldFlagRewrites = OptimizerUtils.ALLOW_ALGEBRAIC_SIMPLIFICATION;
OptimizerUtils.ALLOW_ALGEBRAIC_SIMPLIFICATION = rewrites;
try
{
int cols = (type==InputType.COL_VECTOR) ? 1 : colsMatrix;
int rows = (type==InputType.ROW_VECTOR) ? 1 : rowsMatrix;
double sparsity = (sparse) ? spSparse : spDense;
String TEST_CACHE_DIR = "";
if (TEST_CACHE_ENABLED)
{
TEST_CACHE_DIR = type.ordinal() + "_" + sparsity + "/";
}
TestConfiguration config = getTestConfiguration(TEST_NAME);
loadTestConfiguration(config, TEST_CACHE_DIR);
// 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"), output("B") };
fullRScriptName = HOME + TEST_NAME + ".R";
rCmd = "Rscript" + " " + fullRScriptName + " " + inputDir() + " " + expectedDir();
//generate actual dataset
double[][] A = getRandomMatrix(rows, cols, -0.05, 1, sparsity, 7);
writeInputMatrixWithMTD("A", A, true);
runTest(true, false, null, -1);
if( instType==ExecType.CP ) //in CP no Spark jobs should be executed
Assert.assertEquals("Unexpected number of executed Spark jobs.", 0, Statistics.getNoOfExecutedSPInst());
runRScript(true);
//compare matrices
HashMap<CellIndex, Double> dmlfile = readDMLMatrixFromOutputDir("B");
HashMap<CellIndex, Double> rfile = readRMatrixFromExpectedDir("B");
TestUtils.compareMatrices(dmlfile, rfile, eps, "Stat-DML", "Stat-R");
}
finally
{
rtplatform = platformOld;
DMLScript.USE_LOCAL_SPARK_CONFIG = sparkConfigOld;
OptimizerUtils.ALLOW_ALGEBRAIC_SIMPLIFICATION = oldFlagRewrites;
}
}
}