// Ceres Solver - A fast non-linear least squares minimizer // Copyright 2023 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. // // Authors: sameeragarwal@google.com (Sameer Agarwal) #include "Eigen/Dense" #include "benchmark/benchmark.h" #include "ceres/invert_psd_matrix.h" namespace ceres::internal { template void BenchmarkFixedSizedInvertPSDMatrix(benchmark::State& state) { using MatrixType = typename EigenTypes::Matrix; MatrixType input = MatrixType::Random(); input += input.transpose() + MatrixType::Identity(); MatrixType output; constexpr bool kAssumeFullRank = true; for (auto _ : state) { benchmark::DoNotOptimize( output = InvertPSDMatrix(kAssumeFullRank, input)); } } BENCHMARK_TEMPLATE(BenchmarkFixedSizedInvertPSDMatrix, 1); BENCHMARK_TEMPLATE(BenchmarkFixedSizedInvertPSDMatrix, 2); BENCHMARK_TEMPLATE(BenchmarkFixedSizedInvertPSDMatrix, 3); BENCHMARK_TEMPLATE(BenchmarkFixedSizedInvertPSDMatrix, 4); BENCHMARK_TEMPLATE(BenchmarkFixedSizedInvertPSDMatrix, 5); BENCHMARK_TEMPLATE(BenchmarkFixedSizedInvertPSDMatrix, 6); BENCHMARK_TEMPLATE(BenchmarkFixedSizedInvertPSDMatrix, 7); BENCHMARK_TEMPLATE(BenchmarkFixedSizedInvertPSDMatrix, 8); BENCHMARK_TEMPLATE(BenchmarkFixedSizedInvertPSDMatrix, 9); BENCHMARK_TEMPLATE(BenchmarkFixedSizedInvertPSDMatrix, 10); BENCHMARK_TEMPLATE(BenchmarkFixedSizedInvertPSDMatrix, 11); BENCHMARK_TEMPLATE(BenchmarkFixedSizedInvertPSDMatrix, 12); static void BenchmarkDynamicallyInvertPSDMatrix(benchmark::State& state) { using MatrixType = typename EigenTypes::Matrix; const int size = static_cast(state.range(0)); MatrixType input = MatrixType::Random(size, size); input += input.transpose() + MatrixType::Identity(size, size); MatrixType output; constexpr bool kAssumeFullRank = true; for (auto _ : state) { benchmark::DoNotOptimize( output = InvertPSDMatrix(kAssumeFullRank, input)); } } BENCHMARK(BenchmarkDynamicallyInvertPSDMatrix) ->Apply([](benchmark::internal::Benchmark* benchmark) { for (int i = 1; i < 13; ++i) { benchmark->Args({i}); } }); } // namespace ceres::internal BENCHMARK_MAIN();