| /* |
| * 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_full_other; |
| |
| import java.util.HashMap; |
| |
| import org.junit.AfterClass; |
| 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.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; |
| |
| public class FullMatrixMultiplicationUltraSparseTest extends AutomatedTestBase |
| { |
| private final static String TEST_NAME = "FullMatrixMultiplication"; |
| private final static String TEST_DIR = "functions/binary/matrix_full_other/"; |
| private final static String TEST_CLASS_DIR = TEST_DIR + FullMatrixMultiplicationUltraSparseTest.class.getSimpleName() + "/"; |
| private final static double eps = 1e-10; |
| |
| private final static int rowsA = 1501; |
| private final static int colsA = 1603; |
| private final static int rowsB = 1603; |
| private final static int colsB = 1107; |
| |
| private final static double sparsity1 = 0.7; |
| private final static double sparsity2 = 0.1; |
| private final static double sparsity3 = 0.000005; |
| |
| private enum SparsityType{ |
| DENSE, |
| SPARSE, |
| ULTRA_SPARSE, |
| } |
| |
| @Override |
| public void setUp() |
| { |
| TestUtils.clearAssertionInformation(); |
| addTestConfiguration( |
| TEST_NAME, |
| new TestConfiguration(TEST_CLASS_DIR, TEST_NAME, |
| new String[] { "C" }) ); |
| 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 testMMDenseUltraSparseCP() { |
| runMatrixMatrixMultiplicationTest(SparsityType.DENSE, SparsityType.ULTRA_SPARSE, ExecType.CP); |
| } |
| |
| @Test |
| public void testMMSparseUltraSparseCP() { |
| runMatrixMatrixMultiplicationTest(SparsityType.SPARSE, SparsityType.ULTRA_SPARSE, ExecType.CP); |
| } |
| |
| @Test |
| public void testMMUltraSparseDenseCP() { |
| runMatrixMatrixMultiplicationTest(SparsityType.ULTRA_SPARSE, SparsityType.DENSE, ExecType.CP); |
| } |
| |
| @Test |
| public void testMMUltraSparseSparseCP() { |
| runMatrixMatrixMultiplicationTest(SparsityType.ULTRA_SPARSE, SparsityType.SPARSE, ExecType.CP); |
| } |
| |
| @Test |
| public void testMMUltraSparseUltraSparseCP() { |
| runMatrixMatrixMultiplicationTest(SparsityType.ULTRA_SPARSE, SparsityType.ULTRA_SPARSE, ExecType.CP); |
| } |
| |
| @Test |
| public void testMMDenseUltraSparseSP() { |
| runMatrixMatrixMultiplicationTest(SparsityType.DENSE, SparsityType.ULTRA_SPARSE, ExecType.SPARK); |
| } |
| |
| @Test |
| public void testMMSparseUltraSparseSP() { |
| runMatrixMatrixMultiplicationTest(SparsityType.SPARSE, SparsityType.ULTRA_SPARSE, ExecType.SPARK); |
| } |
| |
| @Test |
| public void testMMUltraSparseDenseSP() { |
| runMatrixMatrixMultiplicationTest(SparsityType.ULTRA_SPARSE, SparsityType.DENSE, ExecType.SPARK); |
| } |
| |
| @Test |
| public void testMMUltraSparseSparseSP() { |
| runMatrixMatrixMultiplicationTest(SparsityType.ULTRA_SPARSE, SparsityType.SPARSE, ExecType.SPARK); |
| } |
| |
| @Test |
| public void testMMUltraSparseUltraSparseSP() { |
| runMatrixMatrixMultiplicationTest(SparsityType.ULTRA_SPARSE, SparsityType.ULTRA_SPARSE, ExecType.SPARK); |
| } |
| |
| private void runMatrixMatrixMultiplicationTest( SparsityType sparseM1, SparsityType sparseM2, ExecType instType) |
| { |
| 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; |
| |
| try |
| { |
| TestConfiguration config = getTestConfiguration(TEST_NAME); |
| |
| double sparsityLeft = (sparseM1==SparsityType.DENSE)? sparsity1 : (sparseM1==SparsityType.SPARSE)? sparsity2 : sparsity3; |
| double sparsityRight = (sparseM2==SparsityType.DENSE)? sparsity1 : (sparseM2==SparsityType.SPARSE)? sparsity2 : sparsity3; |
| |
| String TEST_CACHE_DIR = ""; |
| if (TEST_CACHE_ENABLED) { |
| TEST_CACHE_DIR = String.valueOf(sparsityLeft) + "_" + String.valueOf(sparsityRight) + "/"; |
| } |
| |
| 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[]{"-args", input("A"), Integer.toString(rowsA), Integer.toString(colsA), |
| input("B"), Integer.toString(rowsB), Integer.toString(colsB), output("C") }; |
| |
| fullRScriptName = HOME + TEST_NAME + ".R"; |
| rCmd = "Rscript" + " " + fullRScriptName + " " + inputDir() + " " + expectedDir(); |
| |
| //generate actual dataset |
| double[][] A = getRandomMatrix(rowsA, colsA, 0, 1, sparsityLeft, 7); |
| writeInputMatrix("A", A, true); |
| double[][] B = getRandomMatrix(rowsB, colsB, 0, 1, sparsityRight, 3); |
| writeInputMatrix("B", B, true); |
| |
| setOutputBuffering(false); |
| runTest(true, false, null, -1); |
| runRScript(true); |
| |
| //compare matrices |
| HashMap<CellIndex, Double> dmlfile = readDMLMatrixFromHDFS("C"); |
| HashMap<CellIndex, Double> rfile = readRMatrixFromFS("C"); |
| TestUtils.compareMatrices(dmlfile, rfile, eps, "Stat-DML", "Stat-R"); |
| } |
| finally { |
| DMLScript.USE_LOCAL_SPARK_CONFIG = sparkConfigOld; |
| rtplatform = platformOld; |
| } |
| } |
| } |