[SYSTEMDS-3545] img_mirror_linearized

scripts/builtin/img_mirror_linearized.dml

@@ -0,0 +1,78 @@
+#-------------------------------------------------------------
+#
+# 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.
+#
+#-------------------------------------------------------------
+
+# This function has  the same functionality with img_mirror but it handles multiple images at
+# the same time. Each row of the input and output matrix represents a linearized image/matrix
+# It flips an image on the X (horizontal) or Y (vertical) axis.
+# INPUT:
+# -----------------------------------------------------------------------------------------
+# img_matrix           Input matrix/image (every row represents a linearized matrix/image)
+# horizontal_axis      flip either in X or Y axis
+# original_rows        number of rows in the original 2-D images 
+# original_cols        number of cols in the original 2-D images 
+# -----------------------------------------------------------------------------------------
+#
+# OUTPUT:
+# -----------------------------------------------------------------------------------------
+# R            Output matrix/image  (every row represents a linearized matrix/image)
+# -----------------------------------------------------------------------------------------
+
+m_img_mirror_linearized = function(matrix[double] img_matrix, Boolean horizontal_axis, 
+Integer original_rows, Integer original_cols) return (matrix[double] R) {
+  n = ncol(img_matrix);
+  R = matrix(0, rows=nrow(img_matrix), cols=n);
+  rows = original_rows;
+  cols = original_cols;
+
+  if (horizontal_axis) {
+    parfor (i in seq(1, (rows %/% 2) * cols, cols),check=0) {
+      start = i;
+      end = i + cols - 1;
+      mirrorStart = (n - end) + 1;
+      mirrorEnd = (n - start) + 1;
+      R[, start:end] = img_matrix[, mirrorStart:mirrorEnd];
+      R[, mirrorStart:mirrorEnd] = img_matrix[, start:end];
+    }
+    if (rows %% 2 == 1) {
+      midStart = ((rows %/% 2)) * cols + 1;
+      midEnd = midStart + cols - 1;
+      R[, midStart:midEnd] = img_matrix[, midStart:midEnd];
+    }
+  } 
+  else {
+      offset = 1;
+      while (offset <= n) {
+        end = min(n, offset + cols - 1);
+        reversed_sub_matrix = matrix(0, rows=nrow(img_matrix), cols=cols);
+        idx = 1;
+        for (j in offset:end) {
+          reversed_sub_matrix[, cols - idx + 1] = img_matrix[, j];
+          idx = idx + 1;
+        }
+        R[, offset:end] = reversed_sub_matrix;
+        offset = end + 1;
+      }
+  }
+}
+
+
+
+

src/main/java/org/apache/sysds/common/Builtins.java

@@ -155,6 +155,7 @@ public enum Builtins {
 	HYPERBAND("hyperband", true),
 	IFELSE("ifelse", false),
 	IMG_MIRROR("img_mirror", true),
+	IMG_MIRROR_LINEARIZED("img_mirror_linearized", true),
 	IMG_BRIGHTNESS("img_brightness", true),
 	IMG_CROP("img_crop", true),
 	IMG_TRANSFORM("img_transform", true),

src/test/java/org/apache/sysds/test/functions/builtin/part1/BuiltinImageMirrorLinearizedTest.java

@@ -0,0 +1,129 @@
+/*
+ * 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.junit.Ignore;
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.junit.runners.Parameterized;
+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 java.util.Arrays;
+import java.util.Collection;
+import java.util.HashMap;
+
+@RunWith(Parameterized.class)
+@net.jcip.annotations.NotThreadSafe
+public class BuiltinImageMirrorLinearizedTest extends AutomatedTestBase {
+
+    private final static String TEST_NAME_LINEARIZED = "image_mirror_linearized";
+    private final static String TEST_DIR = "functions/builtin/";
+    private final static String TEST_CLASS_DIR = TEST_DIR + BuiltinImageMirrorLinearizedTest.class.getSimpleName() + "/";
+    private final static double eps = 1e-10;
+    private final static double spSparse = 0.05; 
+    private final static double spDense = 0.5; 
+
+    @Parameterized.Parameter()
+    public int img_rows;
+    @Parameterized.Parameter(1)
+    public int img_cols;
+    @Parameterized.Parameter(2)
+    public int rows;  // number of images
+    public int cols;  // Initialized based on img_rows * img_cols
+
+    @Parameterized.Parameters
+    public static Collection<Object[]> data() {
+        return Arrays.asList(new Object[][] {
+            {12, 12, 4},
+            {13, 11, 5},
+            {64, 64, 32},
+            {256, 256, 5},
+            {256, 253, 5},
+            {1024, 1024, 5},
+            {1024, 1048, 5}
+        });
+    }
+
+    @Override
+    public void setUp() {
+        cols = img_rows * img_cols;
+        addTestConfiguration(TEST_NAME_LINEARIZED, new TestConfiguration(TEST_CLASS_DIR, TEST_NAME_LINEARIZED, new String[]{"B_x", "B_y"}));
+    }
+
+    @Test
+    public void testImageMirrorLinearized() {
+        runImageMirrorLinearizedTest(false, ExecType.CP);
+    }
+
+     @Test
+    public void testImageMirrorLinearizedSparse() {
+        runImageMirrorLinearizedTest(true, ExecType.CP);
+    }
+
+    @Test
+    @Ignore
+    public void testImageMirrorLinearizedSP() {
+        runImageMirrorLinearizedTest(false, ExecType.SPARK);
+    }
+
+    private void runImageMirrorLinearizedTest(boolean sparse, ExecType instType) {
+        ExecMode platformOld = setExecMode(instType);
+        disableOutAndExpectedDeletion();
+
+        try {
+            loadTestConfiguration(getTestConfiguration(TEST_NAME_LINEARIZED));
+
+            double sparsity = sparse ? spSparse : spDense;
+            String HOME = SCRIPT_DIR + TEST_DIR;
+
+            fullDMLScriptName = HOME + TEST_NAME_LINEARIZED + ".dml";
+            programArgs = new String[]{"-nvargs",
+                "in_file=" + input("A"), 
+                "x_out_reshape_file=" + output("B_x_reshape"), 
+                "y_out_reshape_file=" + output("B_y_reshape"),
+                "x_out_file=" + output("B_x"), 
+                "y_out_file=" + output("B_y"),
+                "img_rows=" + img_rows, 
+                "img_cols=" + img_cols    
+            };
+
+            double[][] A = getRandomMatrix(rows, cols, 0, 255, sparsity, 7);
+            writeInputMatrixWithMTD("A", A, true);
+
+            runTest(true, false, null, -1);
+
+            HashMap<MatrixValue.CellIndex, Double> dmlfileLinearizedX = readDMLMatrixFromOutputDir("B_x");
+            HashMap<MatrixValue.CellIndex, Double> dmlfileLinearizedY = readDMLMatrixFromOutputDir("B_y");
+
+            HashMap<MatrixValue.CellIndex, Double> dmlfileX = readDMLMatrixFromOutputDir("B_x_reshape");
+            HashMap<MatrixValue.CellIndex, Double> dmlfileY = readDMLMatrixFromOutputDir("B_y_reshape");
+
+            TestUtils.compareMatrices(dmlfileLinearizedX, dmlfileX, eps, "Stat-DML-LinearizedX", "Stat-DML-X");
+            TestUtils.compareMatrices(dmlfileLinearizedY, dmlfileY, eps, "Stat-DML-LinearizedY", "Stat-DML-Y");
+
+        } finally {
+            rtplatform = platformOld;
+        }
+    }
+}

src/test/scripts/functions/builtin/image_mirror_linearized.dml

@@ -0,0 +1,43 @@
+#-------------------------------------------------------------
+#
+# 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.
+#
+#-------------------------------------------------------------
+
+input_batched = read($in_file);
+num_images = nrow(input_batched);
+m_batched = ncol(input_batched);
+img_rows = $img_rows;
+img_cols = $img_cols;
+img_out_flattened_x = matrix(0, rows=num_images, cols=m_batched);
+img_out_flattened_y = matrix(0, rows=num_images, cols=m_batched);
+input_matrix = matrix(input_batched, rows=num_images, cols=m_batched);
+for(i in 1:num_images) {
+    image_i = matrix(input_matrix[i,], rows=img_rows, cols=img_cols);
+    img_out_x = img_mirror(image_i, TRUE);
+    img_out_y = img_mirror(image_i, FALSE);
+    img_out_flattened_x[i,] = matrix(img_out_x, rows=1, cols=m_batched);
+    img_out_flattened_y[i,] = matrix(img_out_y, rows=1, cols=m_batched);
+}
+write(img_out_flattened_x, $x_out_reshape_file);
+write(img_out_flattened_y, $y_out_reshape_file);
+imgs = matrix(input_batched, rows=num_images, cols=m_batched);
+img_out_x_linearized = img_mirror_linearized(imgs, TRUE, img_rows, img_cols);
+img_out_y_linearized = img_mirror_linearized(imgs, FALSE, img_rows, img_cols);
+write(img_out_x_linearized, $x_out_file);
+write(img_out_y_linearized, $y_out_file);