mirror of
https://github.com/ceres-solver/ceres-solver.git
synced 2026-08-29 08:34:37 +08:00
Sergiu Deitsch
de96ed58f5
Resolve the following warnings issue by the latest version of the
benchmark library:
/Users/runner/work/ceres-solver/ceres-solver/internal/ceres/small_blas_gemv_benchmark.cc:71:54: warning: 'Benchmark' is deprecated: Use ::benchmark::Benchmark instead [-Wdeprecated-declarations]
71 | static void MatrixSizeArguments(benchmark::internal::Benchmark* benchmark) {
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/Users/runner/work/ceres-solver/ceres-solver/internal/ceres/dense_linear_solver_benchmark.cc:67:46: warning: 'Benchmark' is deprecated: Use ::benchmark::Benchmark instead [-Wdeprecated-declarations]
67 | static void MatrixSizes(benchmark::internal::Benchmark* b) {
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/Users/runner/work/ceres-solver/ceres-solver/internal/ceres/invert_psd_matrix_benchmark.cc:80:37: warning: 'Benchmark' is deprecated: Use ::benchmark::Benchmark instead [-Wdeprecated-declarations]
80 | ->Apply([](benchmark::internal::Benchmark* benchmark) {
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Change-Id: Ice6fe57dc5635698809e368fda23a018f4d7df5a
88 lines
3.6 KiB
C++
88 lines
3.6 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2026 Google Inc. All rights reserved.
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// http://ceres-solver.org/
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//
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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//
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// * Redistributions of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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// * Redistributions in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// * Neither the name of Google Inc. nor the names of its contributors may be
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// used to endorse or promote products derived from this software without
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// specific prior written permission.
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//
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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// POSSIBILITY OF SUCH DAMAGE.
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//
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// Authors: sameeragarwal@google.com (Sameer Agarwal)
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#include "Eigen/Dense"
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#include "benchmark/benchmark.h"
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#include "ceres/invert_psd_matrix.h"
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namespace ceres::internal {
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template <int kSize>
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void BenchmarkFixedSizedInvertPSDMatrix(benchmark::State& state) {
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using MatrixType = typename EigenTypes<kSize, kSize>::Matrix;
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MatrixType input = MatrixType::Random();
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input += input.transpose() + MatrixType::Identity();
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MatrixType output;
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constexpr bool kAssumeFullRank = true;
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for (auto _ : state) {
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benchmark::DoNotOptimize(
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output = InvertPSDMatrix<kSize>(kAssumeFullRank, input));
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}
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}
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BENCHMARK_TEMPLATE(BenchmarkFixedSizedInvertPSDMatrix, 1);
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BENCHMARK_TEMPLATE(BenchmarkFixedSizedInvertPSDMatrix, 2);
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BENCHMARK_TEMPLATE(BenchmarkFixedSizedInvertPSDMatrix, 3);
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BENCHMARK_TEMPLATE(BenchmarkFixedSizedInvertPSDMatrix, 4);
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BENCHMARK_TEMPLATE(BenchmarkFixedSizedInvertPSDMatrix, 5);
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BENCHMARK_TEMPLATE(BenchmarkFixedSizedInvertPSDMatrix, 6);
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BENCHMARK_TEMPLATE(BenchmarkFixedSizedInvertPSDMatrix, 7);
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BENCHMARK_TEMPLATE(BenchmarkFixedSizedInvertPSDMatrix, 8);
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BENCHMARK_TEMPLATE(BenchmarkFixedSizedInvertPSDMatrix, 9);
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BENCHMARK_TEMPLATE(BenchmarkFixedSizedInvertPSDMatrix, 10);
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BENCHMARK_TEMPLATE(BenchmarkFixedSizedInvertPSDMatrix, 11);
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BENCHMARK_TEMPLATE(BenchmarkFixedSizedInvertPSDMatrix, 12);
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static void BenchmarkDynamicallyInvertPSDMatrix(benchmark::State& state) {
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using MatrixType =
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typename EigenTypes<Eigen::Dynamic, Eigen::Dynamic>::Matrix;
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const int size = static_cast<int>(state.range(0));
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MatrixType input = MatrixType::Random(size, size);
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input += input.transpose() + MatrixType::Identity(size, size);
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MatrixType output;
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constexpr bool kAssumeFullRank = true;
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for (auto _ : state) {
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benchmark::DoNotOptimize(
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output = InvertPSDMatrix<Eigen::Dynamic>(kAssumeFullRank, input));
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}
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}
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BENCHMARK(BenchmarkDynamicallyInvertPSDMatrix)->Apply([](auto* benchmark) {
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for (int i = 1; i < 13; ++i) {
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benchmark->Args({i});
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}
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});
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} // namespace ceres::internal
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BENCHMARK_MAIN();
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