Benchmarks for dynamic autodiff.
This patch is from Clement Courbet. courbet@google.com
Change-Id: I886390663644733bfa5b7b52b0c883079e793726
diff --git a/internal/ceres/autodiff_benchmarks/autodiff_benchmarks.cc b/internal/ceres/autodiff_benchmarks/autodiff_benchmarks.cc
index f8b2a21..2533ba6 100644
--- a/internal/ceres/autodiff_benchmarks/autodiff_benchmarks.cc
+++ b/internal/ceres/autodiff_benchmarks/autodiff_benchmarks.cc
@@ -30,6 +30,7 @@
#include <memory>
#include <random>
+#include <utility>
#include "benchmark/benchmark.h"
#include "ceres/autodiff_benchmarks/brdf_cost_function.h"
@@ -41,31 +42,33 @@
#include "ceres/ceres.h"
namespace ceres {
-namespace internal {
-// If we want to use functors with both operator() and an Evaluate() method
-// with AutoDiff then this wrapper class here has to be used. Autodiff doesn't
-// support functors that have an Evaluate() function.
-//
-// CostFunctionToFunctor hides the Evaluate() function, because it doesn't
-// derive from CostFunction. Autodiff sees it as a simple functor and will use
-// the operator() as expected.
-template <typename CostFunction>
-struct CostFunctionToFunctor {
- template <typename... _Args>
- explicit CostFunctionToFunctor(_Args&&... __args)
- : cost_function(std::forward<_Args>(__args)...) {}
+enum Dynamic { kNotDynamic, kDynamic };
- template <typename... _Args>
- inline bool operator()(_Args&&... __args) const {
- return cost_function(std::forward<_Args>(__args)...);
- }
+// Transforms a static functor into a dynamic one.
+template <typename CostFunctionType, int kNumParameterBlocks>
+class ToDynamic {
+ public:
+ template <typename... _Args>
+ explicit ToDynamic(_Args&&... __args)
+ : cost_function_(std::forward<_Args>(__args)...) {}
- CostFunction cost_function;
+ template <typename T>
+ bool operator()(const T* const* parameters, T* residuals) const {
+ return Apply(parameters, residuals,
+ std::make_index_sequence<kNumParameterBlocks>());
+ }
+
+ private:
+ template <typename T, size_t... Indices>
+ bool Apply(const T* const* parameters, T* residuals,
+ std::index_sequence<Indices...>) const {
+ return cost_function_(parameters[Indices]..., residuals);
+ }
+
+ CostFunctionType cost_function_;
};
-} // namespace internal
-
template <int kParameterBlockSize>
static void BM_ConstantAnalytic(benchmark::State& state) {
constexpr int num_residuals = 1;
@@ -79,14 +82,59 @@
double* jacobians[] = {jacobian_values.data()};
std::unique_ptr<ceres::CostFunction> cost_function(
- new ConstantCostFunction<kParameterBlockSize>());
+ new AnalyticConstantCostFunction<kParameterBlockSize>());
for (auto _ : state) {
cost_function->Evaluate(parameters, residuals.data(), jacobians);
}
}
-template <int kParameterBlockSize>
+// Helpers for CostFunctionFactory.
+template <typename DynamicCostFunctionType>
+void AddParameterBlocks(DynamicCostFunctionType*) {}
+
+template <int HeadN, int... TailNs, typename DynamicCostFunctionType>
+void AddParameterBlocks(DynamicCostFunctionType* dynamic_function) {
+ dynamic_function->AddParameterBlock(HeadN);
+ AddParameterBlocks<TailNs...>(dynamic_function);
+}
+
+// Creates an autodiff cost function wrapping `CostFunctor`, with
+// `kNumResiduals` residuals and parameter blocks with sized `Ns..`.
+// Depending on `kIsDynamic`, either a static or dynamic cost function is
+// created.
+// `args` are forwarded to the `CostFunctor` constructor.
+template <Dynamic kIsDynamic>
+struct CostFunctionFactory {};
+
+template <>
+struct CostFunctionFactory<kNotDynamic> {
+ template <typename CostFunctor, int kNumResiduals, int... Ns,
+ typename... Args>
+ static std::unique_ptr<ceres::CostFunction> Create(Args&&... args) {
+ return std::make_unique<
+ ceres::AutoDiffCostFunction<CostFunctor, kNumResiduals, Ns...>>(
+ new CostFunctor(std::forward<Args>(args)...));
+ }
+};
+
+template <>
+struct CostFunctionFactory<kDynamic> {
+ template <typename CostFunctor, int kNumResiduals, int... Ns,
+ typename... Args>
+ static std::unique_ptr<ceres::CostFunction> Create(Args&&... args) {
+ constexpr const int kNumParameterBlocks = sizeof...(Ns);
+ auto dynamic_function = std::make_unique<ceres::DynamicAutoDiffCostFunction<
+ ToDynamic<CostFunctor, kNumParameterBlocks>>>(
+ new ToDynamic<CostFunctor, kNumParameterBlocks>(
+ std::forward<Args>(args)...));
+ dynamic_function->SetNumResiduals(kNumResiduals);
+ AddParameterBlocks<Ns...>(dynamic_function.get());
+ return dynamic_function;
+ }
+};
+
+template <int kParameterBlockSize, Dynamic kIsDynamic>
static void BM_ConstantAutodiff(benchmark::State& state) {
constexpr int num_residuals = 1;
std::array<double, kParameterBlockSize> parameters_values;
@@ -98,11 +146,9 @@
std::array<double, num_residuals * kParameterBlockSize> jacobian_values;
double* jacobians[] = {jacobian_values.data()};
- using AutoDiffFunctor = ceres::internal::CostFunctionToFunctor<
- ConstantCostFunction<kParameterBlockSize>>;
- std::unique_ptr<ceres::CostFunction> cost_function(
- new ceres::AutoDiffCostFunction<AutoDiffFunctor, 1, kParameterBlockSize>(
- new AutoDiffFunctor()));
+ std::unique_ptr<ceres::CostFunction> cost_function =
+ CostFunctionFactory<kIsDynamic>::template Create<
+ ConstantCostFunction<kParameterBlockSize>, 1, 1>();
for (auto _ : state) {
cost_function->Evaluate(parameters, residuals.data(), jacobians);
@@ -110,24 +156,29 @@
}
BENCHMARK_TEMPLATE(BM_ConstantAnalytic, 1);
-BENCHMARK_TEMPLATE(BM_ConstantAutodiff, 1);
+BENCHMARK_TEMPLATE(BM_ConstantAutodiff, 1, kNotDynamic);
+BENCHMARK_TEMPLATE(BM_ConstantAutodiff, 1, kDynamic);
BENCHMARK_TEMPLATE(BM_ConstantAnalytic, 10);
-BENCHMARK_TEMPLATE(BM_ConstantAutodiff, 10);
+BENCHMARK_TEMPLATE(BM_ConstantAutodiff, 10, kNotDynamic);
+BENCHMARK_TEMPLATE(BM_ConstantAutodiff, 10, kDynamic);
BENCHMARK_TEMPLATE(BM_ConstantAnalytic, 20);
-BENCHMARK_TEMPLATE(BM_ConstantAutodiff, 20);
+BENCHMARK_TEMPLATE(BM_ConstantAutodiff, 20, kNotDynamic);
+BENCHMARK_TEMPLATE(BM_ConstantAutodiff, 20, kDynamic);
BENCHMARK_TEMPLATE(BM_ConstantAnalytic, 30);
-BENCHMARK_TEMPLATE(BM_ConstantAutodiff, 30);
+BENCHMARK_TEMPLATE(BM_ConstantAutodiff, 30, kNotDynamic);
+BENCHMARK_TEMPLATE(BM_ConstantAutodiff, 30, kDynamic);
BENCHMARK_TEMPLATE(BM_ConstantAnalytic, 40);
-BENCHMARK_TEMPLATE(BM_ConstantAutodiff, 40);
+BENCHMARK_TEMPLATE(BM_ConstantAutodiff, 40, kNotDynamic);
+BENCHMARK_TEMPLATE(BM_ConstantAutodiff, 40, kDynamic);
BENCHMARK_TEMPLATE(BM_ConstantAnalytic, 50);
-BENCHMARK_TEMPLATE(BM_ConstantAutodiff, 50);
+BENCHMARK_TEMPLATE(BM_ConstantAutodiff, 50, kNotDynamic);
+BENCHMARK_TEMPLATE(BM_ConstantAutodiff, 50, kDynamic);
BENCHMARK_TEMPLATE(BM_ConstantAnalytic, 60);
-BENCHMARK_TEMPLATE(BM_ConstantAutodiff, 60);
+BENCHMARK_TEMPLATE(BM_ConstantAutodiff, 60, kNotDynamic);
+BENCHMARK_TEMPLATE(BM_ConstantAutodiff, 60, kDynamic);
+template <Dynamic kIsDynamic>
static void BM_Linear1AutoDiff(benchmark::State& state) {
- using FunctorType =
- ceres::internal::CostFunctionToFunctor<Linear1CostFunction>;
-
double parameter_block1[] = {1.};
double* parameters[] = {parameter_block1};
@@ -135,20 +186,20 @@
double residuals[1];
double* jacobians[] = {jacobian1};
- std::unique_ptr<ceres::CostFunction> cost_function(
- new ceres::AutoDiffCostFunction<FunctorType, 1, 1>(new FunctorType()));
+ std::unique_ptr<ceres::CostFunction> cost_function =
+ CostFunctionFactory<kIsDynamic>::template Create<Linear1CostFunction, 1,
+ 1>();
for (auto _ : state) {
- cost_function->Evaluate(
- parameters, residuals, state.range(0) ? jacobians : nullptr);
+ cost_function->Evaluate(parameters, residuals,
+ state.range(0) ? jacobians : nullptr);
}
}
-BENCHMARK(BM_Linear1AutoDiff)->Arg(0)->Arg(1);
+BENCHMARK_TEMPLATE(BM_Linear1AutoDiff, kNotDynamic)->Arg(0)->Arg(1);
+BENCHMARK_TEMPLATE(BM_Linear1AutoDiff, kDynamic)->Arg(0)->Arg(1);
+template <Dynamic kIsDynamic>
static void BM_Linear10AutoDiff(benchmark::State& state) {
- using FunctorType =
- ceres::internal::CostFunctionToFunctor<Linear10CostFunction>;
-
double parameter_block1[] = {1., 2., 3., 4., 5., 6., 7., 8., 9., 10.};
double* parameters[] = {parameter_block1};
@@ -156,15 +207,17 @@
double residuals[10];
double* jacobians[] = {jacobian1};
- std::unique_ptr<ceres::CostFunction> cost_function(
- new ceres::AutoDiffCostFunction<FunctorType, 10, 10>(new FunctorType()));
+ std::unique_ptr<ceres::CostFunction> cost_function =
+ CostFunctionFactory<kIsDynamic>::template Create<Linear10CostFunction, 10,
+ 10>();
for (auto _ : state) {
- cost_function->Evaluate(
- parameters, residuals, state.range(0) ? jacobians : nullptr);
+ cost_function->Evaluate(parameters, residuals,
+ state.range(0) ? jacobians : nullptr);
}
}
-BENCHMARK(BM_Linear10AutoDiff)->Arg(0)->Arg(1);
+BENCHMARK_TEMPLATE(BM_Linear10AutoDiff, kNotDynamic)->Arg(0)->Arg(1);
+BENCHMARK_TEMPLATE(BM_Linear10AutoDiff, kDynamic)->Arg(0)->Arg(1);
// From the NIST problem collection.
struct Rat43CostFunctor {
@@ -180,11 +233,14 @@
return true;
}
+ static constexpr int kNumParameterBlocks = 1;
+
private:
const double x_;
const double y_;
};
+template <Dynamic kIsDynamic>
static void BM_Rat43AutoDiff(benchmark::State& state) {
double parameter_block1[] = {1., 2., 3., 4.};
double* parameters[] = {parameter_block1};
@@ -194,21 +250,20 @@
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)));
+ std::unique_ptr<ceres::CostFunction> cost_function =
+ CostFunctionFactory<kIsDynamic>::template Create<Rat43CostFunctor, 1, 4>(
+ x, y);
for (auto _ : state) {
- cost_function->Evaluate(
- parameters, &residuals, state.range(0) ? jacobians : nullptr);
+ cost_function->Evaluate(parameters, &residuals,
+ state.range(0) ? jacobians : nullptr);
}
}
-BENCHMARK(BM_Rat43AutoDiff)->Arg(0)->Arg(1);
+BENCHMARK_TEMPLATE(BM_Rat43AutoDiff, kNotDynamic)->Arg(0)->Arg(1);
+BENCHMARK_TEMPLATE(BM_Rat43AutoDiff, kDynamic)->Arg(0)->Arg(1);
+template <Dynamic kIsDynamic>
static void BM_SnavelyReprojectionAutoDiff(benchmark::State& state) {
- using FunctorType =
- ceres::internal::CostFunctionToFunctor<SnavelyReprojectionError>;
-
double parameter_block1[] = {1., 2., 3., 4., 5., 6., 7., 8., 9.};
double parameter_block2[] = {1., 2., 3.};
double* parameters[] = {parameter_block1, parameter_block2};
@@ -220,18 +275,20 @@
const double x = 0.2;
const double y = 0.3;
- std::unique_ptr<ceres::CostFunction> cost_function(
- new ceres::AutoDiffCostFunction<FunctorType, 2, 9, 3>(
- new FunctorType(x, y)));
+ std::unique_ptr<ceres::CostFunction> cost_function =
+ CostFunctionFactory<kIsDynamic>::template Create<SnavelyReprojectionError,
+ 2, 9, 3>(x, y);
for (auto _ : state) {
- cost_function->Evaluate(
- parameters, residuals, state.range(0) ? jacobians : nullptr);
+ cost_function->Evaluate(parameters, residuals,
+ state.range(0) ? jacobians : nullptr);
}
}
-BENCHMARK(BM_SnavelyReprojectionAutoDiff)->Arg(0)->Arg(1);
+BENCHMARK_TEMPLATE(BM_SnavelyReprojectionAutoDiff, kNotDynamic)->Arg(0)->Arg(1);
+BENCHMARK_TEMPLATE(BM_SnavelyReprojectionAutoDiff, kDynamic)->Arg(0)->Arg(1);
+template <Dynamic kIsDynamic>
static void BM_PhotometricAutoDiff(benchmark::State& state) {
constexpr int PATCH_SIZE = 8;
@@ -280,22 +337,22 @@
FunctorType::Intrinsics intrinsics;
intrinsics << 128, 128, 1, -1, 0.5, 0.5;
- std::unique_ptr<ceres::CostFunction> cost_function(
- new ceres::AutoDiffCostFunction<FunctorType,
- FunctorType::PATCH_SIZE,
- FunctorType::POSE_SIZE,
- FunctorType::POSE_SIZE,
- FunctorType::POINT_SIZE>(new FunctorType(
- intensities_host, bearings_host, image_target, intrinsics)));
+ std::unique_ptr<ceres::CostFunction> cost_function =
+ CostFunctionFactory<kIsDynamic>::template Create<
+ FunctorType, FunctorType::PATCH_SIZE, FunctorType::POSE_SIZE,
+ FunctorType::POSE_SIZE, FunctorType::POINT_SIZE>(
+ intensities_host, bearings_host, image_target, intrinsics);
for (auto _ : state) {
- cost_function->Evaluate(
- parameters, residuals, state.range(0) ? jacobians : nullptr);
+ cost_function->Evaluate(parameters, residuals,
+ state.range(0) ? jacobians : nullptr);
}
}
-BENCHMARK(BM_PhotometricAutoDiff)->Arg(0)->Arg(1);
+BENCHMARK_TEMPLATE(BM_PhotometricAutoDiff, kNotDynamic)->Arg(0)->Arg(1);
+BENCHMARK_TEMPLATE(BM_PhotometricAutoDiff, kDynamic)->Arg(0)->Arg(1);
+template <Dynamic kIsDynamic>
static void BM_RelativePoseAutoDiff(benchmark::State& state) {
using FunctorType = RelativePoseError;
@@ -314,20 +371,22 @@
Eigen::Quaterniond q_i_j = Eigen::Quaterniond(1, 2, 3, 4).normalized();
Eigen::Vector3d t_i_j(1, 2, 3);
- std::unique_ptr<ceres::CostFunction> cost_function(
- new ceres::AutoDiffCostFunction<FunctorType, 6, 7, 7>(
- new FunctorType(q_i_j, t_i_j)));
+ std::unique_ptr<ceres::CostFunction> cost_function =
+ CostFunctionFactory<kIsDynamic>::template Create<FunctorType, 6, 7, 7>(
+ q_i_j, t_i_j);
for (auto _ : state) {
- cost_function->Evaluate(
- parameters, residuals, state.range(0) ? jacobians : nullptr);
+ cost_function->Evaluate(parameters, residuals,
+ state.range(0) ? jacobians : nullptr);
}
}
-BENCHMARK(BM_RelativePoseAutoDiff)->Arg(0)->Arg(1);
+BENCHMARK_TEMPLATE(BM_RelativePoseAutoDiff, kNotDynamic)->Arg(0)->Arg(1);
+BENCHMARK_TEMPLATE(BM_RelativePoseAutoDiff, kDynamic)->Arg(0)->Arg(1);
+template <Dynamic kIsDynamic>
static void BM_BrdfAutoDiff(benchmark::State& state) {
- using FunctorType = ceres::internal::CostFunctionToFunctor<Brdf>;
+ using FunctorType = Brdf;
double material[] = {1., 2., 3., 4., 5., 6., 7., 8., 9., 10.};
auto c = Eigen::Vector3d(0.1, 0.2, 0.3);
@@ -337,32 +396,29 @@
auto x = Eigen::Vector3d(0.5, 0.7, -0.1).normalized();
auto y = Eigen::Vector3d(0.2, -0.2, -0.2).normalized();
- double* parameters[7] = {
- material, c.data(), n.data(), v.data(), l.data(), x.data(), y.data()};
+ double* parameters[7] = {material, c.data(), n.data(), v.data(),
+ l.data(), x.data(), y.data()};
double jacobian[(10 + 6 * 3) * 3];
double residuals[3];
double* jacobians[7] = {
- jacobian + 0,
- jacobian + 10 * 3,
- jacobian + 13 * 3,
- jacobian + 16 * 3,
- jacobian + 19 * 3,
- jacobian + 22 * 3,
+ jacobian + 0, jacobian + 10 * 3, jacobian + 13 * 3,
+ jacobian + 16 * 3, jacobian + 19 * 3, jacobian + 22 * 3,
jacobian + 25 * 3,
};
- std::unique_ptr<ceres::CostFunction> cost_function(
- new ceres::AutoDiffCostFunction<FunctorType, 3, 10, 3, 3, 3, 3, 3, 3>(
- new FunctorType));
+ std::unique_ptr<ceres::CostFunction> cost_function =
+ CostFunctionFactory<kIsDynamic>::template Create<FunctorType, 3, 10, 3, 3,
+ 3, 3, 3, 3>();
for (auto _ : state) {
- cost_function->Evaluate(
- parameters, residuals, state.range(0) ? jacobians : nullptr);
+ cost_function->Evaluate(parameters, residuals,
+ state.range(0) ? jacobians : nullptr);
}
}
-BENCHMARK(BM_BrdfAutoDiff)->Arg(0)->Arg(1);
+BENCHMARK_TEMPLATE(BM_BrdfAutoDiff, kNotDynamic)->Arg(0)->Arg(1);
+BENCHMARK_TEMPLATE(BM_BrdfAutoDiff, kDynamic)->Arg(0)->Arg(1);
} // namespace ceres
diff --git a/internal/ceres/autodiff_benchmarks/constant_cost_function.h b/internal/ceres/autodiff_benchmarks/constant_cost_function.h
index caa0431..2bbe4cb 100644
--- a/internal/ceres/autodiff_benchmarks/constant_cost_function.h
+++ b/internal/ceres/autodiff_benchmarks/constant_cost_function.h
@@ -37,14 +37,17 @@
namespace ceres {
template <int kParameterBlockSize>
-struct ConstantCostFunction
- : public ceres::SizedCostFunction<1, kParameterBlockSize> {
+struct ConstantCostFunction {
template <typename T>
inline bool operator()(const T* const x, T* residuals) const {
residuals[0] = T(5);
return true;
}
+};
+template <int kParameterBlockSize>
+struct AnalyticConstantCostFunction
+ : public ceres::SizedCostFunction<1, kParameterBlockSize> {
virtual bool Evaluate(double const* const* parameters,
double* residuals,
double** jacobians) const {
