| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. |
| // |
| // Copyright (C) 2016 Igor Babuschkin <igor@babuschk.in> |
| // |
| // This Source Code Form is subject to the terms of the Mozilla |
| // Public License v. 2.0. If a copy of the MPL was not distributed |
| // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. |
| |
| #include "main.h" |
| #include <limits> |
| #include <numeric> |
| #include <Eigen/CXX11/Tensor> |
| |
| using Eigen::Tensor; |
| |
| template <int DataLayout, typename Type = float, bool Exclusive = false> |
| static void test_1d_scan() { |
| int size = 50; |
| Tensor<Type, 1, DataLayout> tensor(size); |
| tensor.setRandom(); |
| Tensor<Type, 1, DataLayout> result = tensor.cumsum(0, Exclusive); |
| |
| VERIFY_IS_EQUAL(tensor.dimension(0), result.dimension(0)); |
| |
| float accum = 0; |
| for (int i = 0; i < size; i++) { |
| if (Exclusive) { |
| VERIFY_IS_EQUAL(result(i), accum); |
| accum += tensor(i); |
| } else { |
| accum += tensor(i); |
| VERIFY_IS_EQUAL(result(i), accum); |
| } |
| } |
| |
| accum = 1; |
| result = tensor.cumprod(0, Exclusive); |
| for (int i = 0; i < size; i++) { |
| if (Exclusive) { |
| VERIFY_IS_EQUAL(result(i), accum); |
| accum *= tensor(i); |
| } else { |
| accum *= tensor(i); |
| VERIFY_IS_EQUAL(result(i), accum); |
| } |
| } |
| } |
| |
| template <int DataLayout, typename Type = float> |
| static void test_4d_scan() { |
| int size = 5; |
| Tensor<Type, 4, DataLayout> tensor(size, size, size, size); |
| tensor.setRandom(); |
| |
| Tensor<Type, 4, DataLayout> result(size, size, size, size); |
| |
| result = tensor.cumsum(0); |
| float accum = 0; |
| for (int i = 0; i < size; i++) { |
| accum += tensor(i, 1, 2, 3); |
| VERIFY_IS_EQUAL(result(i, 1, 2, 3), accum); |
| } |
| result = tensor.cumsum(1); |
| accum = 0; |
| for (int i = 0; i < size; i++) { |
| accum += tensor(1, i, 2, 3); |
| VERIFY_IS_EQUAL(result(1, i, 2, 3), accum); |
| } |
| result = tensor.cumsum(2); |
| accum = 0; |
| for (int i = 0; i < size; i++) { |
| accum += tensor(1, 2, i, 3); |
| VERIFY_IS_EQUAL(result(1, 2, i, 3), accum); |
| } |
| result = tensor.cumsum(3); |
| accum = 0; |
| for (int i = 0; i < size; i++) { |
| accum += tensor(1, 2, 3, i); |
| VERIFY_IS_EQUAL(result(1, 2, 3, i), accum); |
| } |
| } |
| |
| template <int DataLayout> |
| static void test_tensor_maps() { |
| int inputs[20]; |
| TensorMap<Tensor<int, 1, DataLayout> > tensor_map(inputs, 20); |
| tensor_map.setRandom(); |
| |
| Tensor<int, 1, DataLayout> result = tensor_map.cumsum(0); |
| |
| int accum = 0; |
| for (int i = 0; i < 20; ++i) { |
| accum += tensor_map(i); |
| VERIFY_IS_EQUAL(result(i), accum); |
| } |
| } |
| |
| EIGEN_DECLARE_TEST(cxx11_tensor_scan) { |
| CALL_SUBTEST((test_1d_scan<ColMajor, float, true>())); |
| CALL_SUBTEST((test_1d_scan<ColMajor, float, false>())); |
| CALL_SUBTEST((test_1d_scan<RowMajor, float, true>())); |
| CALL_SUBTEST((test_1d_scan<RowMajor, float, false>())); |
| CALL_SUBTEST(test_4d_scan<ColMajor>()); |
| CALL_SUBTEST(test_4d_scan<RowMajor>()); |
| CALL_SUBTEST(test_tensor_maps<ColMajor>()); |
| CALL_SUBTEST(test_tensor_maps<RowMajor>()); |
| } |