| // This file is part of Eigen, a lightweight C++ template library | |
| // for linear algebra. | |
| // | |
| // Copyright (C) 2010 Hauke Heibel <hauke.heibel@gmail.com> | |
| // Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr> | |
| // | |
| // 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/. | |
| // SPDX-License-Identifier: MPL-2.0 | |
| #define TEST_ENABLE_TEMPORARY_TRACKING | |
| #include "main.h" | |
| template <int N, typename XprType> | |
| void use_n_times(const XprType& xpr) { | |
| typename internal::nested_eval<XprType, N>::type mat(xpr); | |
| typename XprType::PlainObject res(mat.rows(), mat.cols()); | |
| nb_temporaries--; // remove res | |
| res.setZero(); | |
| for (int i = 0; i < N; ++i) res += mat; | |
| } | |
| template <int N, typename ReferenceType, typename XprType> | |
| bool verify_eval_type(const XprType&, const ReferenceType&) { | |
| typedef typename internal::nested_eval<XprType, N>::type EvalType; | |
| return std::is_same<internal::remove_all_t<EvalType>, internal::remove_all_t<ReferenceType>>::value; | |
| } | |
| template <typename MatrixType> | |
| void run_nesting_ops_1(const MatrixType& _m) { | |
| typename internal::nested_eval<MatrixType, 2>::type m(_m); | |
| // Make really sure that we are in debug mode! | |
| VERIFY_RAISES_ASSERT(eigen_assert(false)); | |
| // The only intention of these tests is to ensure that this code does | |
| // not trigger any asserts or segmentation faults... more to come. | |
| VERIFY_IS_APPROX((m.transpose() * m).diagonal().sum(), (m.transpose() * m).diagonal().sum()); | |
| VERIFY_IS_APPROX((m.transpose() * m).diagonal().array().abs().sum(), | |
| (m.transpose() * m).diagonal().array().abs().sum()); | |
| VERIFY_IS_APPROX((m.transpose() * m).array().abs().sum(), (m.transpose() * m).array().abs().sum()); | |
| } | |
| template <typename MatrixType> | |
| void run_nesting_ops_2(const MatrixType& _m) { | |
| typedef typename MatrixType::Scalar Scalar; | |
| Index rows = _m.rows(); | |
| Index cols = _m.cols(); | |
| MatrixType m1 = MatrixType::Random(rows, cols); | |
| Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::ColsAtCompileTime, ColMajor> m2; | |
| if ((MatrixType::SizeAtCompileTime == Dynamic)) { | |
| VERIFY_EVALUATION_COUNT(use_n_times<1>(m1 + m1 * m1), 1); | |
| VERIFY_EVALUATION_COUNT(use_n_times<10>(m1 + m1 * m1), 1); | |
| VERIFY_EVALUATION_COUNT(use_n_times<1>(m1.template triangularView<Lower>().solve(m1.col(0))), 1); | |
| VERIFY_EVALUATION_COUNT(use_n_times<10>(m1.template triangularView<Lower>().solve(m1.col(0))), 1); | |
| VERIFY_EVALUATION_COUNT(use_n_times<1>(Scalar(2) * m1.template triangularView<Lower>().solve(m1.col(0))), | |
| 2); // FIXME could be one by applying the scaling in-place on the solve result | |
| VERIFY_EVALUATION_COUNT(use_n_times<1>(m1.col(0) + m1.template triangularView<Lower>().solve(m1.col(0))), | |
| 2); // FIXME could be one by adding m1.col() inplace | |
| VERIFY_EVALUATION_COUNT(use_n_times<10>(m1.col(0) + m1.template triangularView<Lower>().solve(m1.col(0))), 2); | |
| } | |
| { | |
| VERIFY(verify_eval_type<10>(m1, m1)); | |
| if (!NumTraits<Scalar>::IsComplex) { | |
| VERIFY(verify_eval_type<3>(2 * m1, 2 * m1)); | |
| VERIFY(verify_eval_type<4>(2 * m1, m1)); | |
| } else { | |
| VERIFY(verify_eval_type<2>(2 * m1, 2 * m1)); | |
| VERIFY(verify_eval_type<3>(2 * m1, m1)); | |
| } | |
| VERIFY(verify_eval_type<2>(m1 + m1, m1 + m1)); | |
| VERIFY(verify_eval_type<3>(m1 + m1, m1)); | |
| VERIFY(verify_eval_type<1>(m1 * m1.transpose(), m2)); | |
| VERIFY(verify_eval_type<1>(m1 * (m1 + m1).transpose(), m2)); | |
| VERIFY(verify_eval_type<2>(m1 * m1.transpose(), m2)); | |
| VERIFY(verify_eval_type<1>(m1 + m1 * m1, m1)); | |
| VERIFY(verify_eval_type<1>(m1.template triangularView<Lower>().solve(m1), m1)); | |
| VERIFY(verify_eval_type<1>(m1 + m1.template triangularView<Lower>().solve(m1), m1)); | |
| } | |
| } | |
| EIGEN_DECLARE_TEST(nesting_ops) { | |
| CALL_SUBTEST_1(run_nesting_ops_1(MatrixXf::Random(25, 25))); | |
| CALL_SUBTEST_2(run_nesting_ops_1(MatrixXcd::Random(25, 25))); | |
| CALL_SUBTEST_3(run_nesting_ops_1(Matrix4f::Random())); | |
| CALL_SUBTEST_4(run_nesting_ops_1(Matrix2d::Random())); | |
| Index s = internal::random<int>(1, EIGEN_TEST_MAX_SIZE); | |
| CALL_SUBTEST_1(run_nesting_ops_2(MatrixXf(s, s))); | |
| CALL_SUBTEST_2(run_nesting_ops_2(MatrixXcd(s, s))); | |
| CALL_SUBTEST_3(run_nesting_ops_2(Matrix4f())); | |
| CALL_SUBTEST_4(run_nesting_ops_2(Matrix2d())); | |
| TEST_SET_BUT_UNUSED_VARIABLE(s); | |
| } |