| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. |
| // |
| // Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com> |
| // |
| // 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 <Eigen/CXX11/Tensor> |
| |
| using Eigen::Tensor; |
| using Eigen::TensorMap; |
| |
| static void test_assign() { |
| std::string data1[6]; |
| TensorMap<Tensor<std::string, 2>> mat1(data1, 2, 3); |
| std::string data2[6]; |
| const TensorMap<Tensor<const std::string, 2>> mat2(data2, 2, 3); |
| |
| for (int i = 0; i < 6; ++i) { |
| std::ostringstream s1; |
| s1 << "abc" << i * 3; |
| data1[i] = s1.str(); |
| std::ostringstream s2; |
| s2 << "def" << i * 5; |
| data2[i] = s2.str(); |
| } |
| |
| Tensor<std::string, 2> rslt1; |
| rslt1 = mat1; |
| Tensor<std::string, 2> rslt2; |
| rslt2 = mat2; |
| |
| Tensor<std::string, 2> rslt3 = mat1; |
| Tensor<std::string, 2> rslt4 = mat2; |
| |
| Tensor<std::string, 2> rslt5(mat1); |
| Tensor<std::string, 2> rslt6(mat2); |
| |
| for (int i = 0; i < 2; ++i) { |
| for (int j = 0; j < 3; ++j) { |
| VERIFY_IS_EQUAL(rslt1(i, j), data1[i + 2 * j]); |
| VERIFY_IS_EQUAL(rslt2(i, j), data2[i + 2 * j]); |
| VERIFY_IS_EQUAL(rslt3(i, j), data1[i + 2 * j]); |
| VERIFY_IS_EQUAL(rslt4(i, j), data2[i + 2 * j]); |
| VERIFY_IS_EQUAL(rslt5(i, j), data1[i + 2 * j]); |
| VERIFY_IS_EQUAL(rslt6(i, j), data2[i + 2 * j]); |
| } |
| } |
| } |
| |
| static void test_concat() { |
| Tensor<std::string, 2> t1(2, 3); |
| Tensor<std::string, 2> t2(2, 3); |
| |
| for (int i = 0; i < 2; ++i) { |
| for (int j = 0; j < 3; ++j) { |
| std::ostringstream s1; |
| s1 << "abc" << i + j * 2; |
| t1(i, j) = s1.str(); |
| std::ostringstream s2; |
| s2 << "def" << i * 5 + j * 32; |
| t2(i, j) = s2.str(); |
| } |
| } |
| |
| Tensor<std::string, 2> result = t1.concatenate(t2, 1); |
| VERIFY_IS_EQUAL(result.dimension(0), 2); |
| VERIFY_IS_EQUAL(result.dimension(1), 6); |
| |
| for (int i = 0; i < 2; ++i) { |
| for (int j = 0; j < 3; ++j) { |
| VERIFY_IS_EQUAL(result(i, j), t1(i, j)); |
| VERIFY_IS_EQUAL(result(i, j + 3), t2(i, j)); |
| } |
| } |
| } |
| |
| static void test_slices() { |
| Tensor<std::string, 2> data(2, 6); |
| for (int i = 0; i < 2; ++i) { |
| for (int j = 0; j < 3; ++j) { |
| std::ostringstream s1; |
| s1 << "abc" << i + j * 2; |
| data(i, j) = s1.str(); |
| } |
| } |
| |
| const Eigen::DSizes<ptrdiff_t, 2> half_size(2, 3); |
| const Eigen::DSizes<ptrdiff_t, 2> first_half(0, 0); |
| const Eigen::DSizes<ptrdiff_t, 2> second_half(0, 3); |
| |
| Tensor<std::string, 2> t1 = data.slice(first_half, half_size); |
| Tensor<std::string, 2> t2 = data.slice(second_half, half_size); |
| |
| for (int i = 0; i < 2; ++i) { |
| for (int j = 0; j < 3; ++j) { |
| VERIFY_IS_EQUAL(data(i, j), t1(i, j)); |
| VERIFY_IS_EQUAL(data(i, j + 3), t2(i, j)); |
| } |
| } |
| } |
| |
| static void test_additions() { |
| Tensor<std::string, 1> data1(3); |
| Tensor<std::string, 1> data2(3); |
| for (int i = 0; i < 3; ++i) { |
| data1(i) = "abc"; |
| std::ostringstream s1; |
| s1 << i; |
| data2(i) = s1.str(); |
| } |
| |
| Tensor<std::string, 1> sum = data1 + data2; |
| for (int i = 0; i < 3; ++i) { |
| std::ostringstream concat; |
| concat << "abc" << i; |
| std::string expected = concat.str(); |
| VERIFY_IS_EQUAL(sum(i), expected); |
| } |
| } |
| |
| static void test_initialization() { |
| Tensor<std::string, 2> a(2, 3); |
| a.setConstant(std::string("foo")); |
| for (int i = 0; i < 2 * 3; ++i) { |
| VERIFY_IS_EQUAL(a(i), std::string("foo")); |
| } |
| } |
| |
| EIGEN_DECLARE_TEST(cxx11_tensor_of_strings) { |
| // Beware: none of this is likely to ever work on a GPU. |
| CALL_SUBTEST(test_assign()); |
| CALL_SUBTEST(test_concat()); |
| CALL_SUBTEST(test_slices()); |
| CALL_SUBTEST(test_additions()); |
| CALL_SUBTEST(test_initialization()); |
| } |