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							- // Ceres Solver - A fast non-linear least squares minimizer
 
- // Copyright 2019 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 materils 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 {
 
- namespace internal {
 
- template <int kSize>
 
- void BenchmarkFixedSizedInvertPSDMatrix(benchmark::State& state) {
 
-   using MatrixType = typename EigenTypes<kSize, kSize>::Matrix;
 
-   MatrixType input = MatrixType::Random();
 
-   input += input.transpose() + MatrixType::Identity();
 
-   MatrixType output;
 
-   constexpr bool kAssumeFullRank = true;
 
-   for (auto _ : state) {
 
-     benchmark::DoNotOptimize(
 
-         output = InvertPSDMatrix<kSize>(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);
 
- void BenchmarkDynamicallyInvertPSDMatrix(benchmark::State& state) {
 
-   using MatrixType =
 
-       typename EigenTypes<Eigen::Dynamic, Eigen::Dynamic>::Matrix;
 
-   const int size = 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<Eigen::Dynamic>(kAssumeFullRank, input));
 
-   }
 
- }
 
- BENCHMARK(BenchmarkDynamicallyInvertPSDMatrix)
 
-     ->Apply([](benchmark::internal::Benchmark* benchmark) {
 
-       for (int i = 1; i < 13; ++i) {
 
-         benchmark->Args({i});
 
-       }
 
-     });
 
- }  // namespace internal
 
- }  // namespace ceres
 
- BENCHMARK_MAIN();
 
 
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