src/test/java/org/apache/sysds/test/functions/codegenalg/partone/AlgorithmAutoEncoder.java - systemds - Git at Google

 /*
  * 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.codegenalg.partone;

 import java.io.File;
 import java.util.HashMap;

 import org.apache.sysds.runtime.matrix.data.MatrixValue;
 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.hops.OptimizerUtils;
 import org.apache.sysds.lops.LopProperties.ExecType;
 import org.apache.sysds.test.AutomatedTestBase;
 import org.apache.sysds.test.TestConfiguration;
 import org.apache.sysds.test.TestUtils;

 public class AlgorithmAutoEncoder extends AutomatedTestBase
 {
 	private final static String TEST_NAME1 = "Algorithm_AutoEncoder";
 	private final static String TEST_DIR = "functions/codegenalg/";
 	private final static String TEST_CLASS_DIR = TEST_DIR + AlgorithmAutoEncoder.class.getSimpleName() + "/";

 	private final static int rows = 1068;
 	private final static int cols = 784;

 	private final static double sparsity1 = 0.7; //dense
 	private final static double sparsity2 = 0.1; //sparse
 	private final static double eps       = 1e-5;

 	private final static int H1 = 500;
 	private final static int H2 = 2;
 	private final static double epochs = 2;

 	private CodegenTestType currentTestType = CodegenTestType.DEFAULT;

 	@Override
 	public void setUp() {
 		TestUtils.clearAssertionInformation();
 		addTestConfiguration(TEST_NAME1, new TestConfiguration(TEST_CLASS_DIR, TEST_NAME1, new String[] { "w" }));
 	}

 	//Note: limited cases for SPARK, as lazy evaluation
 	//causes very long execution time for this algorithm

 	@Test
 	public void testAutoEncoder256DenseCP() {
 		runAutoEncoderTest(256, false, false, ExecType.CP, CodegenTestType.DEFAULT);
 	}

 	@Test
 	public void testAutoEncoder256DenseRewritesCP() {
 		runAutoEncoderTest(256, false, true, ExecType.CP, CodegenTestType.DEFAULT);
 	}

 	@Test
 	public void testAutoEncoder256SparseCP() {
 		runAutoEncoderTest(256, true, false, ExecType.CP, CodegenTestType.DEFAULT);
 	}

 	@Test
 	public void testAutoEncoder256SparseRewritesCP() {
 		runAutoEncoderTest(256, true, true, ExecType.CP, CodegenTestType.DEFAULT);
 	}

 	@Test
 	public void testAutoEncoder512DenseCP() {
 		runAutoEncoderTest(512, false, false, ExecType.CP, CodegenTestType.DEFAULT);
 	}

 	@Test
 	public void testAutoEncoder512DenseRewritesCP() {
 		runAutoEncoderTest(512, false, true, ExecType.CP, CodegenTestType.DEFAULT);
 	}

 	@Test
 	public void testAutoEncoder512SparseCP() {
 		runAutoEncoderTest(512, true, false, ExecType.CP, CodegenTestType.DEFAULT);
 	}

 	@Test
 	public void testAutoEncoder512SparseRewritesCP() {
 		runAutoEncoderTest(512, true, true, ExecType.CP, CodegenTestType.DEFAULT);
 	}

 	@Test
 	public void testAutoEncoder256DenseRewritesSpark() {
 		runAutoEncoderTest(256, false, true, ExecType.SPARK, CodegenTestType.DEFAULT);
 	}

 	@Test
 	public void testAutoEncoder256SparseRewritesSpark() {
 		runAutoEncoderTest(256, true, true, ExecType.SPARK, CodegenTestType.DEFAULT);
 	}

 	@Test
 	public void testAutoEncoder512DenseRewritesSpark() {
 		runAutoEncoderTest(512, false, true, ExecType.SPARK, CodegenTestType.DEFAULT);
 	}

 	@Test
 	public void testAutoEncoder512SparseRewritesSpark() {
 		runAutoEncoderTest(512, true, true, ExecType.SPARK, CodegenTestType.DEFAULT);
 	}

 	@Test
 	public void testAutoEncoder512DenseRewritesCPFuseAll() {
 		runAutoEncoderTest(512, false, true, ExecType.CP, CodegenTestType.FUSE_ALL);
 	}

 	@Test
 	public void testAutoEncoder512SparseRewritesCPFuseAll() {
 		runAutoEncoderTest(512, true, true, ExecType.CP, CodegenTestType.FUSE_ALL);
 	}

 	@Test
 	public void testAutoEncoder512DenseRewritesSparkFuseAll() {
 		runAutoEncoderTest(512, false, true, ExecType.SPARK, CodegenTestType.FUSE_ALL);
 	}

 	@Test
 	public void testAutoEncoder512SparseRewritesSparkFuseAll() {
 		runAutoEncoderTest(512, true, true, ExecType.SPARK, CodegenTestType.FUSE_ALL);
 	}

 	@Test
 	public void testAutoEncoder512DenseRewritesCPFuseNoRedundancy() {
 		runAutoEncoderTest(512, false, true, ExecType.CP, CodegenTestType.FUSE_NO_REDUNDANCY);
 	}

 	@Test
 	public void testAutoEncoder512SparseRewritesCPFuseNoRedundancy() {
 		runAutoEncoderTest(512, true, true, ExecType.CP, CodegenTestType.FUSE_NO_REDUNDANCY);
 	}

 	@Test
 	public void testAutoEncoder512DenseRewritesSparkFuseNoRedundancy() {
 		runAutoEncoderTest(512, false, true, ExecType.SPARK, CodegenTestType.FUSE_NO_REDUNDANCY);
 	}

 	@Test
 	public void testAutoEncoder512SparseRewritesSparkFuseNoRedundancy() {
 		runAutoEncoderTest(512, true, true, ExecType.SPARK, CodegenTestType.FUSE_NO_REDUNDANCY);
 	}

 	private void runAutoEncoderTest(int batchsize, boolean sparse, boolean rewrites, ExecType instType, CodegenTestType CodegenTestType)
 	{
 		boolean oldFlag = OptimizerUtils.ALLOW_ALGEBRAIC_SIMPLIFICATION;
 		ExecMode platformOld = rtplatform;
 		switch( instType ){
 			case SPARK: rtplatform = ExecMode.SPARK; break;
 			default: rtplatform = ExecMode.HYBRID; break;
 		}

 		currentTestType = CodegenTestType;

 		boolean sparkConfigOld = DMLScript.USE_LOCAL_SPARK_CONFIG;
 		if( rtplatform == ExecMode.SPARK || rtplatform == ExecMode.HYBRID )
 			DMLScript.USE_LOCAL_SPARK_CONFIG = true;

 		try
 		{
 			String TEST_NAME = TEST_NAME1;
 			TestConfiguration config = getTestConfiguration(TEST_NAME);
 			loadTestConfiguration(config);

 			fullDMLScriptName = SCRIPT_DIR + TEST_DIR + "/Algorithm_AutoEncoder.dml";
 			//"scripts/staging/autoencoder-2layer.dml";
 			programArgs = new String[]{ "-stats", "-nvargs", "X="+input("X"),
 				"H1="+H1, "H2="+H2, "EPOCH="+epochs, "BATCH="+batchsize,
 				"W1_rand="+input("W1_rand"),"W2_rand="+input("W2_rand"),
 				"W3_rand="+input("W3_rand"), "W4_rand="+input("W4_rand"),
 				"order_rand="+input("order_rand"),
 				"W1_out="+output("W1"), "b1_out="+output("b1"),
 				"W2_out="+output("W2"), "b2_out="+output("b2"),
 				"W3_out="+output("W3"), "b3_out="+output("b3"),
 				"W4_out="+output("W4"), "b4_out="+output("b4")};

 			rCmd = getRCmd(inputDir(), String.valueOf(H1), String.valueOf(H2),
 					String.valueOf(epochs), String.valueOf(batchsize), expectedDir());
 			OptimizerUtils.ALLOW_ALGEBRAIC_SIMPLIFICATION = rewrites;

 			//generate actual datasets
 			double[][] X = getRandomMatrix(rows, cols, 0, 1, sparse?sparsity2:sparsity1, 714);
 			writeInputMatrixWithMTD("X", X, true);

 			//generate rand matrices for W1, W2, W3, W4 here itself for passing onto both DML and R scripts
 			double[][] W1_rand = getRandomMatrix(H1, cols, 0, 1, sparse?sparsity2:sparsity1, 800);
 			writeInputMatrixWithMTD("W1_rand", W1_rand, true);
 			double[][] W2_rand = getRandomMatrix(H2, H1, 0, 1, sparse?sparsity2:sparsity1, 900);
 			writeInputMatrixWithMTD("W2_rand", W2_rand, true);
 			double[][] W3_rand = getRandomMatrix(H1, H2, 0, 1, sparse?sparsity2:sparsity1, 589);
 			writeInputMatrixWithMTD("W3_rand", W3_rand, true);
 			double[][] W4_rand = getRandomMatrix(cols, H1, 0, 1, sparse?sparsity2:sparsity1, 150);
 			writeInputMatrixWithMTD("W4_rand", W4_rand, true);
 			double[][] order_rand = getRandomMatrix(rows, 1, 0, 1, sparse?sparsity2:sparsity1, 143);
 			writeInputMatrixWithMTD("order_rand", order_rand, true); //for the permut operation on input X

 			//run script
 			runTest(true, false, null, -1);
 			runRScript(true);

 			HashMap<MatrixValue.CellIndex, Double> dmlW1 = readDMLMatrixFromOutputDir("W1");
 			HashMap<MatrixValue.CellIndex, Double> dmlW2 = readDMLMatrixFromOutputDir("W2");
 			HashMap<MatrixValue.CellIndex, Double> dmlW3 = readDMLMatrixFromOutputDir("W3");
 			HashMap<MatrixValue.CellIndex, Double> dmlW4 = readDMLMatrixFromOutputDir("W4");
 			HashMap<MatrixValue.CellIndex, Double> dmlb1 = readDMLMatrixFromOutputDir("b1");
 			HashMap<MatrixValue.CellIndex, Double> dmlb2 = readDMLMatrixFromOutputDir("b2");
 			HashMap<MatrixValue.CellIndex, Double> dmlb3 = readDMLMatrixFromOutputDir("b3");
 			HashMap<MatrixValue.CellIndex, Double> dmlb4 = readDMLMatrixFromOutputDir("b4");
 			HashMap<MatrixValue.CellIndex, Double> rW1  = readRMatrixFromExpectedDir("W1");
 			HashMap<MatrixValue.CellIndex, Double> rW2  = readRMatrixFromExpectedDir("W2");
 			HashMap<MatrixValue.CellIndex, Double> rW3  = readRMatrixFromExpectedDir("W3");
 			HashMap<MatrixValue.CellIndex, Double> rW4  = readRMatrixFromExpectedDir("W4");
 			HashMap<MatrixValue.CellIndex, Double> rb1  = readRMatrixFromExpectedDir("b1");
 			HashMap<MatrixValue.CellIndex, Double> rb2  = readRMatrixFromExpectedDir("b2");
 			HashMap<MatrixValue.CellIndex, Double> rb3  = readRMatrixFromExpectedDir("b3");
 			HashMap<MatrixValue.CellIndex, Double> rb4  = readRMatrixFromExpectedDir("b4");
 			TestUtils.compareMatrices(dmlW1, rW1, eps, "Stat-DML", "Stat-R");
 			TestUtils.compareMatrices(dmlW2, rW2, eps, "Stat-DML", "Stat-R");
 			TestUtils.compareMatrices(dmlW3, rW3, eps, "Stat-DML", "Stat-R");
 			TestUtils.compareMatrices(dmlW4, rW4, eps, "Stat-DML", "Stat-R");
 			TestUtils.compareMatrices(dmlb1, rb1, eps, "Stat-DML", "Stat-R");
 			TestUtils.compareMatrices(dmlb2, rb2, eps, "Stat-DML", "Stat-R");
 			TestUtils.compareMatrices(dmlb3, rb3, eps, "Stat-DML", "Stat-R");
 			TestUtils.compareMatrices(dmlb4, rb4, eps, "Stat-DML", "Stat-R");

 			Assert.assertTrue(heavyHittersContainsSubString("spoof")
 				|| heavyHittersContainsSubString("sp_spoof"));
 		}
 		finally {
 			rtplatform = platformOld;
 			DMLScript.USE_LOCAL_SPARK_CONFIG = sparkConfigOld;
 			OptimizerUtils.ALLOW_ALGEBRAIC_SIMPLIFICATION = oldFlag;
 			OptimizerUtils.ALLOW_AUTO_VECTORIZATION = true;
 			OptimizerUtils.ALLOW_OPERATOR_FUSION = true;
 		}
 	}

 	/**
 	 * Override default configuration with custom test configuration to ensure
 	 * scratch space and local temporary directory locations are also updated.
 	 */
 	@Override
 	protected File getConfigTemplateFile() {
 		return getCodegenConfigFile(SCRIPT_DIR + TEST_DIR, currentTestType);
 	}
 }
	/*
	* 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.codegenalg.partone;

	import java.io.File;
	import java.util.HashMap;

	import org.apache.sysds.runtime.matrix.data.MatrixValue;
	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.hops.OptimizerUtils;
	import org.apache.sysds.lops.LopProperties.ExecType;
	import org.apache.sysds.test.AutomatedTestBase;
	import org.apache.sysds.test.TestConfiguration;
	import org.apache.sysds.test.TestUtils;

	public class AlgorithmAutoEncoder extends AutomatedTestBase
	{
	private final static String TEST_NAME1 = "Algorithm_AutoEncoder";
	private final static String TEST_DIR = "functions/codegenalg/";
	private final static String TEST_CLASS_DIR = TEST_DIR + AlgorithmAutoEncoder.class.getSimpleName() + "/";

	private final static int rows = 1068;
	private final static int cols = 784;

	private final static double sparsity1 = 0.7; //dense
	private final static double sparsity2 = 0.1; //sparse
	private final static double eps = 1e-5;

	private final static int H1 = 500;
	private final static int H2 = 2;
	private final static double epochs = 2;

	private CodegenTestType currentTestType = CodegenTestType.DEFAULT;

	@Override
	public void setUp() {
	TestUtils.clearAssertionInformation();
	addTestConfiguration(TEST_NAME1, new TestConfiguration(TEST_CLASS_DIR, TEST_NAME1, new String[] { "w" }));
	}

	//Note: limited cases for SPARK, as lazy evaluation
	//causes very long execution time for this algorithm

	@Test
	public void testAutoEncoder256DenseCP() {
	runAutoEncoderTest(256, false, false, ExecType.CP, CodegenTestType.DEFAULT);
	}

	@Test
	public void testAutoEncoder256DenseRewritesCP() {
	runAutoEncoderTest(256, false, true, ExecType.CP, CodegenTestType.DEFAULT);
	}

	@Test
	public void testAutoEncoder256SparseCP() {
	runAutoEncoderTest(256, true, false, ExecType.CP, CodegenTestType.DEFAULT);
	}

	@Test
	public void testAutoEncoder256SparseRewritesCP() {
	runAutoEncoderTest(256, true, true, ExecType.CP, CodegenTestType.DEFAULT);
	}

	@Test
	public void testAutoEncoder512DenseCP() {
	runAutoEncoderTest(512, false, false, ExecType.CP, CodegenTestType.DEFAULT);
	}

	@Test
	public void testAutoEncoder512DenseRewritesCP() {
	runAutoEncoderTest(512, false, true, ExecType.CP, CodegenTestType.DEFAULT);
	}

	@Test
	public void testAutoEncoder512SparseCP() {
	runAutoEncoderTest(512, true, false, ExecType.CP, CodegenTestType.DEFAULT);
	}

	@Test
	public void testAutoEncoder512SparseRewritesCP() {
	runAutoEncoderTest(512, true, true, ExecType.CP, CodegenTestType.DEFAULT);
	}

	@Test
	public void testAutoEncoder256DenseRewritesSpark() {
	runAutoEncoderTest(256, false, true, ExecType.SPARK, CodegenTestType.DEFAULT);
	}

	@Test
	public void testAutoEncoder256SparseRewritesSpark() {
	runAutoEncoderTest(256, true, true, ExecType.SPARK, CodegenTestType.DEFAULT);
	}

	@Test
	public void testAutoEncoder512DenseRewritesSpark() {
	runAutoEncoderTest(512, false, true, ExecType.SPARK, CodegenTestType.DEFAULT);
	}

	@Test
	public void testAutoEncoder512SparseRewritesSpark() {
	runAutoEncoderTest(512, true, true, ExecType.SPARK, CodegenTestType.DEFAULT);
	}

	@Test
	public void testAutoEncoder512DenseRewritesCPFuseAll() {
	runAutoEncoderTest(512, false, true, ExecType.CP, CodegenTestType.FUSE_ALL);
	}

	@Test
	public void testAutoEncoder512SparseRewritesCPFuseAll() {
	runAutoEncoderTest(512, true, true, ExecType.CP, CodegenTestType.FUSE_ALL);
	}

	@Test
	public void testAutoEncoder512DenseRewritesSparkFuseAll() {
	runAutoEncoderTest(512, false, true, ExecType.SPARK, CodegenTestType.FUSE_ALL);
	}

	@Test
	public void testAutoEncoder512SparseRewritesSparkFuseAll() {
	runAutoEncoderTest(512, true, true, ExecType.SPARK, CodegenTestType.FUSE_ALL);
	}

	@Test
	public void testAutoEncoder512DenseRewritesCPFuseNoRedundancy() {
	runAutoEncoderTest(512, false, true, ExecType.CP, CodegenTestType.FUSE_NO_REDUNDANCY);
	}

	@Test
	public void testAutoEncoder512SparseRewritesCPFuseNoRedundancy() {
	runAutoEncoderTest(512, true, true, ExecType.CP, CodegenTestType.FUSE_NO_REDUNDANCY);
	}

	@Test
	public void testAutoEncoder512DenseRewritesSparkFuseNoRedundancy() {
	runAutoEncoderTest(512, false, true, ExecType.SPARK, CodegenTestType.FUSE_NO_REDUNDANCY);
	}

	@Test
	public void testAutoEncoder512SparseRewritesSparkFuseNoRedundancy() {
	runAutoEncoderTest(512, true, true, ExecType.SPARK, CodegenTestType.FUSE_NO_REDUNDANCY);
	}

	private void runAutoEncoderTest(int batchsize, boolean sparse, boolean rewrites, ExecType instType, CodegenTestType CodegenTestType)
	{
	boolean oldFlag = OptimizerUtils.ALLOW_ALGEBRAIC_SIMPLIFICATION;
	ExecMode platformOld = rtplatform;
	switch( instType ){
	case SPARK: rtplatform = ExecMode.SPARK; break;
	default: rtplatform = ExecMode.HYBRID; break;
	}

	currentTestType = CodegenTestType;

	boolean sparkConfigOld = DMLScript.USE_LOCAL_SPARK_CONFIG;
	if( rtplatform == ExecMode.SPARK \|\| rtplatform == ExecMode.HYBRID )
	DMLScript.USE_LOCAL_SPARK_CONFIG = true;

	try
	{
	String TEST_NAME = TEST_NAME1;
	TestConfiguration config = getTestConfiguration(TEST_NAME);
	loadTestConfiguration(config);

	fullDMLScriptName = SCRIPT_DIR + TEST_DIR + "/Algorithm_AutoEncoder.dml";
	//"scripts/staging/autoencoder-2layer.dml";
	programArgs = new String[]{ "-stats", "-nvargs", "X="+input("X"),
	"H1="+H1, "H2="+H2, "EPOCH="+epochs, "BATCH="+batchsize,
	"W1_rand="+input("W1_rand"),"W2_rand="+input("W2_rand"),
	"W3_rand="+input("W3_rand"), "W4_rand="+input("W4_rand"),
	"order_rand="+input("order_rand"),
	"W1_out="+output("W1"), "b1_out="+output("b1"),
	"W2_out="+output("W2"), "b2_out="+output("b2"),
	"W3_out="+output("W3"), "b3_out="+output("b3"),
	"W4_out="+output("W4"), "b4_out="+output("b4")};

	rCmd = getRCmd(inputDir(), String.valueOf(H1), String.valueOf(H2),
	String.valueOf(epochs), String.valueOf(batchsize), expectedDir());
	OptimizerUtils.ALLOW_ALGEBRAIC_SIMPLIFICATION = rewrites;

	//generate actual datasets
	double[][] X = getRandomMatrix(rows, cols, 0, 1, sparse?sparsity2:sparsity1, 714);
	writeInputMatrixWithMTD("X", X, true);

	//generate rand matrices for W1, W2, W3, W4 here itself for passing onto both DML and R scripts
	double[][] W1_rand = getRandomMatrix(H1, cols, 0, 1, sparse?sparsity2:sparsity1, 800);
	writeInputMatrixWithMTD("W1_rand", W1_rand, true);
	double[][] W2_rand = getRandomMatrix(H2, H1, 0, 1, sparse?sparsity2:sparsity1, 900);
	writeInputMatrixWithMTD("W2_rand", W2_rand, true);
	double[][] W3_rand = getRandomMatrix(H1, H2, 0, 1, sparse?sparsity2:sparsity1, 589);
	writeInputMatrixWithMTD("W3_rand", W3_rand, true);
	double[][] W4_rand = getRandomMatrix(cols, H1, 0, 1, sparse?sparsity2:sparsity1, 150);
	writeInputMatrixWithMTD("W4_rand", W4_rand, true);
	double[][] order_rand = getRandomMatrix(rows, 1, 0, 1, sparse?sparsity2:sparsity1, 143);
	writeInputMatrixWithMTD("order_rand", order_rand, true); //for the permut operation on input X

	//run script
	runTest(true, false, null, -1);
	runRScript(true);

	HashMap<MatrixValue.CellIndex, Double> dmlW1 = readDMLMatrixFromOutputDir("W1");
	HashMap<MatrixValue.CellIndex, Double> dmlW2 = readDMLMatrixFromOutputDir("W2");
	HashMap<MatrixValue.CellIndex, Double> dmlW3 = readDMLMatrixFromOutputDir("W3");
	HashMap<MatrixValue.CellIndex, Double> dmlW4 = readDMLMatrixFromOutputDir("W4");
	HashMap<MatrixValue.CellIndex, Double> dmlb1 = readDMLMatrixFromOutputDir("b1");
	HashMap<MatrixValue.CellIndex, Double> dmlb2 = readDMLMatrixFromOutputDir("b2");
	HashMap<MatrixValue.CellIndex, Double> dmlb3 = readDMLMatrixFromOutputDir("b3");
	HashMap<MatrixValue.CellIndex, Double> dmlb4 = readDMLMatrixFromOutputDir("b4");
	HashMap<MatrixValue.CellIndex, Double> rW1 = readRMatrixFromExpectedDir("W1");
	HashMap<MatrixValue.CellIndex, Double> rW2 = readRMatrixFromExpectedDir("W2");
	HashMap<MatrixValue.CellIndex, Double> rW3 = readRMatrixFromExpectedDir("W3");
	HashMap<MatrixValue.CellIndex, Double> rW4 = readRMatrixFromExpectedDir("W4");
	HashMap<MatrixValue.CellIndex, Double> rb1 = readRMatrixFromExpectedDir("b1");
	HashMap<MatrixValue.CellIndex, Double> rb2 = readRMatrixFromExpectedDir("b2");
	HashMap<MatrixValue.CellIndex, Double> rb3 = readRMatrixFromExpectedDir("b3");
	HashMap<MatrixValue.CellIndex, Double> rb4 = readRMatrixFromExpectedDir("b4");
	TestUtils.compareMatrices(dmlW1, rW1, eps, "Stat-DML", "Stat-R");
	TestUtils.compareMatrices(dmlW2, rW2, eps, "Stat-DML", "Stat-R");
	TestUtils.compareMatrices(dmlW3, rW3, eps, "Stat-DML", "Stat-R");
	TestUtils.compareMatrices(dmlW4, rW4, eps, "Stat-DML", "Stat-R");
	TestUtils.compareMatrices(dmlb1, rb1, eps, "Stat-DML", "Stat-R");
	TestUtils.compareMatrices(dmlb2, rb2, eps, "Stat-DML", "Stat-R");
	TestUtils.compareMatrices(dmlb3, rb3, eps, "Stat-DML", "Stat-R");
	TestUtils.compareMatrices(dmlb4, rb4, eps, "Stat-DML", "Stat-R");

	Assert.assertTrue(heavyHittersContainsSubString("spoof")
	\|\| heavyHittersContainsSubString("sp_spoof"));
	}
	finally {
	rtplatform = platformOld;
	DMLScript.USE_LOCAL_SPARK_CONFIG = sparkConfigOld;
	OptimizerUtils.ALLOW_ALGEBRAIC_SIMPLIFICATION = oldFlag;
	OptimizerUtils.ALLOW_AUTO_VECTORIZATION = true;
	OptimizerUtils.ALLOW_OPERATOR_FUSION = true;
	}
	}

	/**
	* Override default configuration with custom test configuration to ensure
	* scratch space and local temporary directory locations are also updated.
	*/
	@Override
	protected File getConfigTemplateFile() {
	return getCodegenConfigFile(SCRIPT_DIR + TEST_DIR, currentTestType);
	}
	}