1 // This file is part of Eigen, a lightweight C++ template library 2 // for linear algebra. 3 // 4 // Copyright (C) 2016 Igor Babuschkin <igor (at) babuschk.in> 5 // 6 // This Source Code Form is subject to the terms of the Mozilla 7 // Public License v. 2.0. If a copy of the MPL was not distributed 8 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. 9 10 #include "main.h" 11 #include <limits> 12 #include <numeric> 13 #include <Eigen/CXX11/Tensor> 14 15 using Eigen::Tensor; 16 17 template <int DataLayout, typename Type=float, bool Exclusive = false> 18 static void test_1d_scan() 19 { 20 int size = 50; 21 Tensor<Type, 1, DataLayout> tensor(size); 22 tensor.setRandom(); 23 Tensor<Type, 1, DataLayout> result = tensor.cumsum(0, Exclusive); 24 25 VERIFY_IS_EQUAL(tensor.dimension(0), result.dimension(0)); 26 27 float accum = 0; 28 for (int i = 0; i < size; i++) { 29 if (Exclusive) { 30 VERIFY_IS_EQUAL(result(i), accum); 31 accum += tensor(i); 32 } else { 33 accum += tensor(i); 34 VERIFY_IS_EQUAL(result(i), accum); 35 } 36 } 37 38 accum = 1; 39 result = tensor.cumprod(0, Exclusive); 40 for (int i = 0; i < size; i++) { 41 if (Exclusive) { 42 VERIFY_IS_EQUAL(result(i), accum); 43 accum *= tensor(i); 44 } else { 45 accum *= tensor(i); 46 VERIFY_IS_EQUAL(result(i), accum); 47 } 48 } 49 } 50 51 template <int DataLayout, typename Type=float> 52 static void test_4d_scan() 53 { 54 int size = 5; 55 Tensor<Type, 4, DataLayout> tensor(size, size, size, size); 56 tensor.setRandom(); 57 58 Tensor<Type, 4, DataLayout> result(size, size, size, size); 59 60 result = tensor.cumsum(0); 61 float accum = 0; 62 for (int i = 0; i < size; i++) { 63 accum += tensor(i, 1, 2, 3); 64 VERIFY_IS_EQUAL(result(i, 1, 2, 3), accum); 65 } 66 result = tensor.cumsum(1); 67 accum = 0; 68 for (int i = 0; i < size; i++) { 69 accum += tensor(1, i, 2, 3); 70 VERIFY_IS_EQUAL(result(1, i, 2, 3), accum); 71 } 72 result = tensor.cumsum(2); 73 accum = 0; 74 for (int i = 0; i < size; i++) { 75 accum += tensor(1, 2, i, 3); 76 VERIFY_IS_EQUAL(result(1, 2, i, 3), accum); 77 } 78 result = tensor.cumsum(3); 79 accum = 0; 80 for (int i = 0; i < size; i++) { 81 accum += tensor(1, 2, 3, i); 82 VERIFY_IS_EQUAL(result(1, 2, 3, i), accum); 83 } 84 } 85 86 template <int DataLayout> 87 static void test_tensor_maps() { 88 int inputs[20]; 89 TensorMap<Tensor<int, 1, DataLayout> > tensor_map(inputs, 20); 90 tensor_map.setRandom(); 91 92 Tensor<int, 1, DataLayout> result = tensor_map.cumsum(0); 93 94 int accum = 0; 95 for (int i = 0; i < 20; ++i) { 96 accum += tensor_map(i); 97 VERIFY_IS_EQUAL(result(i), accum); 98 } 99 } 100 101 void test_cxx11_tensor_scan() { 102 CALL_SUBTEST((test_1d_scan<ColMajor, float, true>())); 103 CALL_SUBTEST((test_1d_scan<ColMajor, float, false>())); 104 CALL_SUBTEST((test_1d_scan<RowMajor, float, true>())); 105 CALL_SUBTEST((test_1d_scan<RowMajor, float, false>())); 106 CALL_SUBTEST(test_4d_scan<ColMajor>()); 107 CALL_SUBTEST(test_4d_scan<RowMajor>()); 108 CALL_SUBTEST(test_tensor_maps<ColMajor>()); 109 CALL_SUBTEST(test_tensor_maps<RowMajor>()); 110 } 111
