Baunsgaard commented on code in PR #1845: URL: https://github.com/apache/systemds/pull/1845#discussion_r1325954130
########## src/test/java/org/apache/sysds/test/functions/builtin/part1/BuiltinImageCutoutLinTest.java: ########## @@ -0,0 +1,133 @@ +/* + * 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.builtin.part1; + +import org.apache.sysds.common.Types.ExecMode; +import org.apache.sysds.common.Types.ExecType; +import org.apache.sysds.runtime.matrix.data.MatrixValue; +import org.apache.sysds.test.AutomatedTestBase; +import org.apache.sysds.test.TestConfiguration; +import org.apache.sysds.test.TestUtils; +import org.junit.Test; + +import java.util.HashMap; +import java.util.Random; +// if A should be generated one row at a time +//import java.util.stream.Stream; +//import java.util.stream.DoubleStream; + +public class BuiltinImageCutoutLinTest extends AutomatedTestBase { + private final static String TEST_NAME = "image_cutout_linearized"; + private final static String TEST_DIR = "functions/builtin/"; + private final static String TEST_CLASS_DIR = TEST_DIR + BuiltinImageCutoutLinTest.class.getSimpleName() + "/"; + + private final static double eps = 1e-10; + private final static double spSparse = 0.1; + private final static double spDense = 0.9; + private final static Random random = new Random(); + + @Override + public void setUp() { + addTestConfiguration(TEST_NAME, new TestConfiguration(TEST_CLASS_DIR, TEST_NAME, new String[] { "B" })); + } + + @Test + public void testImageTranslateMatrixDenseCP() { + runImageCutoutLinTest(false, ExecType.CP); + } + + @Test + public void testImageTranslateMatrixSparseCP() { + runImageCutoutLinTest(true, ExecType.CP); + } + + @Test + public void testImageTranslateMatrixDenseSP() { + runImageCutoutLinTest(false, ExecType.SPARK); + } + + @Test + public void testImageTranslateMatrixSparseSP() { + runImageCutoutLinTest(false, ExecType.SPARK); + } + + private void runImageCutoutLinTest(boolean sparse, ExecType instType) { + ExecMode platformOld = setExecMode(instType); + disableOutAndExpectedDeletion(); + + setOutputBuffering(true); + + int s_rows = random.nextInt(100) + 1; + int s_cols = random.nextInt(100) + 1; + int x = random.nextInt(s_cols); + int y = random.nextInt(s_rows); + int width = random.nextInt(s_cols - x) + 1; + int height = random.nextInt(s_rows - y) + 1; + int fill_color = random.nextInt(256); + int n_imgs = random.nextInt(100) + 1; + + try { + loadTestConfiguration(getTestConfiguration(TEST_NAME)); + double sparsity = sparse ? spSparse : spDense; + + String HOME = SCRIPT_DIR + TEST_DIR; + fullDMLScriptName = HOME + TEST_NAME + ".dml"; + programArgs = new String[] { "-nvargs", "in_file=" + input("A"), "out_file=" + output("B"), + "width=" + (s_cols * s_rows), + "height=" + n_imgs, "x=" + (x + 1), "y=" + (y + 1), "w=" + width, "h=" + height, + "fill_color=" + fill_color, "s_cols=" + s_cols, "s_rows=" + s_rows }; + + // overall sparsity of the dataset or a single image/row? + double[][] A = getRandomMatrix(n_imgs, s_cols * s_rows, 0, 255, sparsity, 7); + /* + * double[][] A = new double[n_imgs][s_cols*s_rows]; + * for (int i = 0; i < n_imgs; i++) { + * double[][] matrix = getRandomMatrix(s_cols, s_rows, 0, 255, sparsity, 7); + * double[] row = Stream.of(matrix).flatMapToDouble(DoubleStream::of).toArray(); + * A[i] = row; + * } + */ Review Comment: sparsity refer to the entire matrix generated, The generated matrix is trying to get the sparsity you request, but will most likely never hit it exactly. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
