1 /* Copyright 2016 The TensorFlow Authors. All Rights Reserved. 2 3 Licensed under the Apache License, Version 2.0 (the "License"); 4 you may not use this file except in compliance with the License. 5 You may obtain a copy of the License at 6 7 http://www.apache.org/licenses/LICENSE-2.0 8 9 Unless required by applicable law or agreed to in writing, software 10 distributed under the License is distributed on an "AS IS" BASIS, 11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12 See the License for the specific language governing permissions and 13 limitations under the License. 14 ==============================================================================*/ 15 16 package org.tensorflow; 17 18 import java.lang.reflect.Array; 19 import java.util.ArrayList; 20 import java.util.Collection; 21 22 /** Static utility functions. */ 23 public class TestUtil { 24 25 public static final class AutoCloseableList<E extends AutoCloseable> extends ArrayList<E> 26 implements AutoCloseable { AutoCloseableList(Collection<? extends E> c)27 public AutoCloseableList(Collection<? extends E> c) { 28 super(c); 29 } 30 31 @Override close()32 public void close() { 33 Exception toThrow = null; 34 for (AutoCloseable c : this) { 35 try { 36 c.close(); 37 } catch (Exception e) { 38 toThrow = e; 39 } 40 } 41 if (toThrow != null) { 42 throw new RuntimeException(toThrow); 43 } 44 } 45 } 46 constant(Graph g, String name, Object value)47 public static <T> Output<T> constant(Graph g, String name, Object value) { 48 try (Tensor<?> t = Tensor.create(value)) { 49 return g.opBuilder("Const", name) 50 .setAttr("dtype", t.dataType()) 51 .setAttr("value", t) 52 .build() 53 .<T>output(0); 54 } 55 } 56 placeholder(Graph g, String name, Class<T> type)57 public static <T> Output<T> placeholder(Graph g, String name, Class<T> type) { 58 return g.opBuilder("Placeholder", name) 59 .setAttr("dtype", DataType.fromClass(type)) 60 .build() 61 .<T>output(0); 62 } 63 addN(Graph g, Output<?>... inputs)64 public static <T> Output<T> addN(Graph g, Output<?>... inputs) { 65 return g.opBuilder("AddN", "AddN").addInputList(inputs).build().output(0); 66 } 67 matmul( Graph g, String name, Output<T> a, Output<T> b, boolean transposeA, boolean transposeB)68 public static <T> Output<T> matmul( 69 Graph g, String name, Output<T> a, Output<T> b, boolean transposeA, boolean transposeB) { 70 return g.opBuilder("MatMul", name) 71 .addInput(a) 72 .addInput(b) 73 .setAttr("transpose_a", transposeA) 74 .setAttr("transpose_b", transposeB) 75 .build() 76 .<T>output(0); 77 } 78 split(Graph g, String name, int[] values, int numSplit)79 public static Operation split(Graph g, String name, int[] values, int numSplit) { 80 return g.opBuilder("Split", name) 81 .addInput(constant(g, "split_dim", 0)) 82 .addInput(constant(g, "values", values)) 83 .setAttr("num_split", numSplit) 84 .build(); 85 } 86 square(Graph g, String name, Output<T> value)87 public static <T> Output<T> square(Graph g, String name, Output<T> value) { 88 return g.opBuilder("Square", name) 89 .addInput(value) 90 .build() 91 .<T>output(0); 92 } 93 transpose_A_times_X(Graph g, int[][] a)94 public static void transpose_A_times_X(Graph g, int[][] a) { 95 Output<Integer> aa = constant(g, "A", a); 96 matmul(g, "Y", aa, placeholder(g, "X", Integer.class), true, false); 97 } 98 99 /** 100 * Counts the total number of elements in an ND array. 101 * 102 * @param array the array to count the elements of 103 * @return the number of elements 104 */ flattenedNumElements(Object array)105 public static int flattenedNumElements(Object array) { 106 int count = 0; 107 for (int i = 0; i < Array.getLength(array); i++) { 108 Object e = Array.get(array, i); 109 if (!e.getClass().isArray()) { 110 count += 1; 111 } else { 112 count += flattenedNumElements(e); 113 } 114 } 115 return count; 116 } 117 118 /** 119 * Flattens an ND-array into a 1D-array with the same elements. 120 * 121 * @param array the array to flatten 122 * @param elementType the element class (e.g. {@code Integer.TYPE} for an {@code int[]}) 123 * @return a flattened array 124 */ flatten(Object array, Class<?> elementType)125 public static Object flatten(Object array, Class<?> elementType) { 126 Object out = Array.newInstance(elementType, flattenedNumElements(array)); 127 flatten(array, out, 0); 128 return out; 129 } 130 flatten(Object array, Object out, int next)131 private static int flatten(Object array, Object out, int next) { 132 for (int i = 0; i < Array.getLength(array); i++) { 133 Object e = Array.get(array, i); 134 if (!e.getClass().isArray()) { 135 Array.set(out, next++, e); 136 } else { 137 next = flatten(e, out, next); 138 } 139 } 140 return next; 141 } 142 143 /** 144 * Converts a {@code boolean[]} to a {@code byte[]}. 145 * 146 * <p>Suitable for creating tensors of type {@link DataType#BOOL} using {@link 147 * java.nio.ByteBuffer}. 148 */ bool2byte(boolean[] array)149 public static byte[] bool2byte(boolean[] array) { 150 byte[] out = new byte[array.length]; 151 for (int i = 0; i < array.length; i++) { 152 out[i] = array[i] ? (byte) 1 : (byte) 0; 153 } 154 return out; 155 } 156 157 /** 158 * Converts a {@code byte[]} to a {@code boolean[]}. 159 * 160 * <p>Suitable for reading tensors of type {@link DataType#BOOL} using {@link 161 * java.nio.ByteBuffer}. 162 */ byte2bool(byte[] array)163 public static boolean[] byte2bool(byte[] array) { 164 boolean[] out = new boolean[array.length]; 165 for (int i = 0; i < array.length; i++) { 166 out[i] = array[i] != 0; 167 } 168 return out; 169 } 170 TestUtil()171 private TestUtil() {} 172 } 173