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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 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
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//
// Authors: sameeragarwal@google.com (Sameer Agarwal)
#include "Eigen/Dense"
#include "benchmark/benchmark.h"
#include "ceres/invert_psd_matrix.h"
namespace ceres::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);
static void BenchmarkDynamicallyInvertPSDMatrix(benchmark::State& state) {
using MatrixType =
typename EigenTypes<Eigen::Dynamic, Eigen::Dynamic>::Matrix;
const int size = static_cast<int>(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 ceres::internal
BENCHMARK_MAIN();