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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2018 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
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//
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//
// Authors: sameeragarwal@google.com (Sameer Agarwal)
#include <memory>
#include "benchmark/benchmark.h"
#include "ceres/ceres.h"
#include "ceres/jet.h"
namespace ceres {
// From the NIST problem collection.
struct Rat43CostFunctor {
Rat43CostFunctor(const double x, const double y) : x_(x), y_(y) {}
template <typename T>
bool operator()(const T* parameters, T* residuals) const {
const T& b1 = parameters[0];
const T& b2 = parameters[1];
const T& b3 = parameters[2];
const T& b4 = parameters[3];
residuals[0] = b1 * pow(1.0 + exp(b2 - b3 * x_), -1.0 / b4) - y_;
return true;
}
private:
const double x_;
const double y_;
};
// Simple implementation of autodiff using Jets directly instead of
// going through the machineary of AutoDiffCostFunction, which does
// the same thing, but much more generically.
class Rat43Automatic : public ceres::SizedCostFunction<1, 4> {
public:
Rat43Automatic(const Rat43CostFunctor* functor) : functor_(functor) {}
virtual ~Rat43Automatic() {}
virtual bool Evaluate(double const* const* parameters,
double* residuals,
double** jacobians) const {
if (!jacobians) {
return (*functor_)(parameters[0], residuals);
}
typedef ceres::Jet<double, 4> JetT;
JetT jets[4];
for (int i = 0; i < 4; ++i) {
jets[i].a = parameters[0][i];
jets[i].v.setZero();
jets[i].v[i] = 1.0;
}
JetT result;
(*functor_)(jets, &result);
residuals[0] = result.a;
for (int i = 0; i < 4; ++i) {
jacobians[0][i] = result.v[i];
}
return true;
}
private:
std::unique_ptr<const Rat43CostFunctor> functor_;
};
static void BM_Rat43AutoDiff(benchmark::State& state) {
double parameter_block1[] = {1., 2., 3., 4.};
double* parameters[] = {parameter_block1};
double jacobian1[] = {0.0, 0.0, 0.0, 0.0};
double residuals;
double* jacobians[] = {jacobian1};
const double x = 0.2;
const double y = 0.3;
std::unique_ptr<ceres::CostFunction> cost_function(
new ceres::AutoDiffCostFunction<Rat43CostFunctor, 1, 4>(
new Rat43CostFunctor(x, y)));
while (state.KeepRunning()) {
cost_function->Evaluate(
parameters, &residuals, state.range(0) ? jacobians : nullptr);
}
}
BENCHMARK(BM_Rat43AutoDiff)->Arg(0)->Arg(1);
} // namespace ceres
BENCHMARK_MAIN();