| /* |
| * 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.io.IOException; |
| import java.util.HashMap; |
| |
| import org.junit.AfterClass; |
| import org.junit.BeforeClass; |
| import org.junit.Test; |
| import org.apache.sysds.common.Types.ExecMode; |
| import org.apache.sysds.hops.OptimizerUtils; |
| import org.apache.sysds.lops.LopProperties.ExecType; |
| import org.apache.sysds.common.Types.DataType; |
| import org.apache.sysds.common.Types.ValueType; |
| import org.apache.sysds.runtime.matrix.data.MatrixValue.CellIndex; |
| import org.apache.sysds.runtime.meta.MatrixCharacteristics; |
| import org.apache.sysds.runtime.util.HDFSTool; |
| import org.apache.sysds.test.AutomatedTestBase; |
| import org.apache.sysds.test.TestConfiguration; |
| import org.apache.sysds.test.TestUtils; |
| |
| public class FullPowerTest extends AutomatedTestBase |
| { |
| |
| private final static String TEST_NAME1 = "FullPower"; |
| |
| private final static String TEST_DIR = "functions/binary/matrix_full_other/"; |
| private final static String TEST_CLASS_DIR = TEST_DIR + FullPowerTest.class.getSimpleName() + "/"; |
| private final static double eps = 1e-10; |
| |
| private final static int rows = 1100; |
| private final static int cols = 300; |
| private final static double sparsity1 = 0.7; |
| private final static double sparsity2 = 0.1; |
| |
| private final static double min = 0.0; |
| private final static double max = 2.0; |
| |
| @Override |
| public void setUp() |
| { |
| TestUtils.clearAssertionInformation(); |
| addTestConfiguration(TEST_NAME1,new TestConfiguration(TEST_CLASS_DIR, TEST_NAME1,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 testPowMMDenseCP() |
| { |
| runPowerTest(DataType.MATRIX, DataType.MATRIX, false, ExecType.CP); |
| } |
| |
| @Test |
| public void testPowMSDenseCP() |
| { |
| runPowerTest(DataType.MATRIX, DataType.SCALAR, false, ExecType.CP); |
| } |
| |
| @Test |
| public void testPowSMDenseCP() |
| { |
| runPowerTest(DataType.SCALAR, DataType.MATRIX, false, ExecType.CP); |
| } |
| |
| @Test |
| public void testPowSSDenseCP() |
| { |
| runPowerTest(DataType.SCALAR, DataType.SCALAR, false, ExecType.CP); |
| } |
| |
| @Test |
| public void testPowMMSparseCP() |
| { |
| runPowerTest(DataType.MATRIX, DataType.MATRIX, true, ExecType.CP); |
| } |
| |
| @Test |
| public void testPowMSSparseCP() |
| { |
| runPowerTest(DataType.MATRIX, DataType.SCALAR, true, ExecType.CP); |
| } |
| |
| @Test |
| public void testPowSMSparseCP() |
| { |
| runPowerTest(DataType.SCALAR, DataType.MATRIX, true, ExecType.CP); |
| } |
| |
| @Test |
| public void testPowSSSparseCP() |
| { |
| runPowerTest(DataType.SCALAR, DataType.SCALAR, true, ExecType.CP); |
| } |
| |
| private void runPowerTest( DataType dt1, DataType dt2, boolean sparse, ExecType instType) |
| { |
| //rtplatform for MR |
| ExecMode platformOld = rtplatform; |
| rtplatform = ExecMode.HYBRID; |
| |
| double sparsity = sparse?sparsity2:sparsity1; |
| |
| String TEST_CACHE_DIR = ""; |
| if (TEST_CACHE_ENABLED) |
| { |
| double sparsityLeft = 1.0; |
| if (dt1 == DataType.MATRIX) |
| { |
| sparsityLeft = sparsity; |
| } |
| double sparsityRight = 1.0; |
| if (dt2 == DataType.MATRIX) |
| { |
| sparsityRight = sparsity; |
| } |
| TEST_CACHE_DIR = sparsityLeft + "_" + sparsityRight + "/"; |
| } |
| |
| try |
| { |
| String TEST_NAME = TEST_NAME1; |
| 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[]{"-args", input("A"), input("B"), output("C") }; |
| |
| fullRScriptName = HOME + TEST_NAME + ".R"; |
| rCmd = "Rscript" + " " + fullRScriptName + " " + inputDir() + " " + expectedDir(); |
| |
| if( dt1 == DataType.SCALAR && dt2 == DataType.SCALAR ) |
| { |
| // Clear OUT folder to prevent access denied errors running DML script |
| // for tests testPowSSSparseCP, testPowSSSparseMR, testPowSSDenseCP, testPowSSDenseMR |
| // due to setOutAndExpectedDeletionDisabled(true). |
| TestUtils.clearDirectory(outputDir()); |
| } |
| |
| //generate dataset A |
| if( dt1 == DataType.MATRIX ){ |
| double[][] A = getRandomMatrix(rows, cols, min, max, sparsity, 7); |
| MatrixCharacteristics mcA = new MatrixCharacteristics(rows, cols, OptimizerUtils.DEFAULT_BLOCKSIZE, (long) (rows*cols*sparsity)); |
| writeInputMatrixWithMTD("A", A, true, mcA); |
| } |
| else{ |
| double[][] A = getRandomMatrix(1, 1, min, max, 1.0, 7); |
| writeScalarInputMatrixWithMTD( "A", A, true ); |
| } |
| |
| //generate dataset B |
| if( dt2 == DataType.MATRIX ){ |
| MatrixCharacteristics mcB = new MatrixCharacteristics(rows, cols, OptimizerUtils.DEFAULT_BLOCKSIZE, (long) (rows*cols*sparsity)); |
| double[][] B = getRandomMatrix(rows, cols, min, max, sparsity, 3); |
| writeInputMatrixWithMTD("B", B, true, mcB); |
| } |
| else{ |
| double[][] B = getRandomMatrix(1, 1, min, max, 1.0, 3); |
| writeScalarInputMatrixWithMTD( "B", B, true ); |
| } |
| |
| runTest(true, false, null, -1); |
| runRScript(true); |
| |
| //compare matrices |
| HashMap<CellIndex, Double> dmlfile = null; |
| HashMap<CellIndex, Double> rfile = readRMatrixFromExpectedDir("C"); |
| if( dt1==DataType.SCALAR&&dt2==DataType.SCALAR ) |
| dmlfile = readScalarMatrixFromHDFS("C"); |
| else |
| dmlfile = readDMLMatrixFromOutputDir("C"); |
| |
| TestUtils.compareMatrices(dmlfile, rfile, eps, "Stat-DML", "Stat-R", true); |
| } |
| finally |
| { |
| rtplatform = platformOld; |
| } |
| } |
| |
| private static void writeScalarInputMatrixWithMTD(String name, double[][] matrix, boolean includeR) |
| { |
| try |
| { |
| //write DML scalar |
| String fname = baseDirectory + INPUT_DIR + name; // + "/in"; |
| HDFSTool.deleteFileIfExistOnHDFS(fname); |
| HDFSTool.writeDoubleToHDFS(matrix[0][0], fname); |
| HDFSTool.writeScalarMetaDataFile(baseDirectory + INPUT_DIR + name + ".mtd", ValueType.FP64); |
| |
| |
| //write R matrix |
| if( includeR ){ |
| String completeRPath = baseDirectory + INPUT_DIR + name + ".mtx"; |
| TestUtils.writeTestMatrix(completeRPath, matrix, true); |
| } |
| } |
| catch(IOException e) |
| { |
| e.printStackTrace(); |
| throw new RuntimeException(e); |
| } |
| } |
| |
| private static HashMap<CellIndex,Double> readScalarMatrixFromHDFS(String name) |
| { |
| HashMap<CellIndex,Double> dmlfile = new HashMap<>(); |
| try { |
| Double val = HDFSTool.readDoubleFromHDFSFile(baseDirectory + OUTPUT_DIR + name); |
| dmlfile.put(new CellIndex(1,1), val); |
| } |
| catch(IOException e) { |
| e.printStackTrace(); |
| throw new RuntimeException(e); |
| } |
| return dmlfile; |
| } |
| } |