| // Ceres Solver - A fast non-linear least squares minimizer |
| // Copyright 2022 Google Inc. All rights reserved. |
| // http://ceres-solver.org/ |
| // |
| // Redistribution and use in source and binary forms, with or without |
| // modification, are permitted provided that the following conditions are met: |
| // |
| // * Redistributions of source code must retain the above copyright notice, |
| // this list of conditions and the following disclaimer. |
| // * Redistributions in binary form must reproduce the above copyright notice, |
| // this list of conditions and the following disclaimer in the documentation |
| // and/or other materials provided with the distribution. |
| // * Neither the name of Google Inc. nor the names of its contributors may be |
| // used to endorse or promote products derived from this software without |
| // specific prior written permission. |
| // |
| // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" |
| // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE |
| // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE |
| // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE |
| // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR |
| // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF |
| // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS |
| // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN |
| // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) |
| // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE |
| // POSSIBILITY OF SUCH DAMAGE. |
| // |
| // Author: sameeragarwal@google.com (Sameer Agarwal) |
| |
| #include "ceres/dense_qr.h" |
| |
| #include <memory> |
| #include <numeric> |
| #include <string> |
| #include <tuple> |
| #include <vector> |
| |
| #include "Eigen/Dense" |
| #include "ceres/internal/eigen.h" |
| #include "ceres/linear_solver.h" |
| #include "glog/logging.h" |
| #include "gmock/gmock.h" |
| #include "gtest/gtest.h" |
| |
| namespace ceres::internal { |
| |
| using Param = DenseLinearAlgebraLibraryType; |
| |
| namespace { |
| |
| std::string ParamInfoToString(testing::TestParamInfo<Param> info) { |
| return DenseLinearAlgebraLibraryTypeToString(info.param); |
| } |
| |
| } // namespace |
| |
| class DenseQRTest : public ::testing::TestWithParam<Param> {}; |
| |
| TEST_P(DenseQRTest, FactorAndSolve) { |
| // TODO(sameeragarwal): Convert these tests into type parameterized tests so |
| // that we can test the single and double precision solvers. |
| |
| using Scalar = double; |
| using MatrixType = Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic>; |
| using VectorType = Eigen::Matrix<Scalar, Eigen::Dynamic, 1>; |
| |
| LinearSolver::Options options; |
| ContextImpl context; |
| #ifndef CERES_NO_CUDA |
| options.context = &context; |
| std::string error; |
| CHECK(context.InitCuda(&error)) << error; |
| #endif // CERES_NO_CUDA |
| options.dense_linear_algebra_library_type = GetParam(); |
| const double kEpsilon = std::numeric_limits<double>::epsilon() * 1.5e4; |
| std::unique_ptr<DenseQR> dense_qr = DenseQR::Create(options); |
| |
| const int kNumTrials = 10; |
| const int kMinNumCols = 1; |
| const int kMaxNumCols = 10; |
| const int kMinRowsFactor = 1; |
| const int kMaxRowsFactor = 3; |
| for (int num_cols = kMinNumCols; num_cols < kMaxNumCols; ++num_cols) { |
| for (int num_rows = kMinRowsFactor * num_cols; |
| num_rows < kMaxRowsFactor * num_cols; |
| ++num_rows) { |
| for (int trial = 0; trial < kNumTrials; ++trial) { |
| MatrixType lhs = MatrixType::Random(num_rows, num_cols); |
| Vector x = VectorType::Random(num_cols); |
| Vector rhs = lhs * x; |
| Vector actual = Vector::Random(num_cols); |
| LinearSolver::Summary summary; |
| summary.termination_type = dense_qr->FactorAndSolve(num_rows, |
| num_cols, |
| lhs.data(), |
| rhs.data(), |
| actual.data(), |
| &summary.message); |
| ASSERT_EQ(summary.termination_type, |
| LinearSolverTerminationType::SUCCESS); |
| ASSERT_NEAR((x - actual).norm() / x.norm(), 0.0, kEpsilon) |
| << "\nexpected: " << x.transpose() |
| << "\nactual : " << actual.transpose(); |
| } |
| } |
| } |
| } |
| |
| namespace { |
| |
| // NOTE: preprocessor directives in a macro are not standard conforming |
| decltype(auto) MakeValues() { |
| return ::testing::Values(EIGEN |
| #ifndef CERES_NO_LAPACK |
| , |
| LAPACK |
| #endif |
| #ifndef CERES_NO_CUDA |
| , |
| CUDA |
| #endif |
| ); |
| } |
| |
| } // namespace |
| |
| INSTANTIATE_TEST_SUITE_P(_, DenseQRTest, MakeValues(), ParamInfoToString); |
| |
| } // namespace ceres::internal |