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https://github.com/ceres-solver/ceres-solver.git
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0a53aa9054
1. Add abseil-cpp as a submodule. We are tracking the latest LTS release, which is lts_2024_01_16. 2. Replace glog/gflags with absl::log and absl::flags. 3. Remove miniglog 4. Also take a whack at making the bazel build work with abseil-cpp and gtest. There are a number of TODOs in this CL that still need to be resolved. Change-Id: I39355ed7d61375be4ebcbc8596d9cc70acc1c678
153 lines
5.6 KiB
C++
153 lines
5.6 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2023 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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// Author: sameeragarwal@google.com (Sameer Agarwal)
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//
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// TODO(sameeragarwal): Add support for larger, more complicated and
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// poorly conditioned problems both for correctness testing as well as
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// benchmarking.
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#include "ceres/iterative_schur_complement_solver.h"
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#include <cstddef>
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#include <memory>
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#include "Eigen/Dense"
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#include "ceres/block_random_access_dense_matrix.h"
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#include "ceres/block_sparse_matrix.h"
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#include "ceres/casts.h"
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#include "ceres/context_impl.h"
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#include "ceres/internal/eigen.h"
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#include "ceres/linear_least_squares_problems.h"
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#include "ceres/linear_solver.h"
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#include "ceres/schur_eliminator.h"
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#include "ceres/triplet_sparse_matrix.h"
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#include "ceres/types.h"
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#include "gtest/gtest.h"
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namespace ceres {
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namespace internal {
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using testing::AssertionResult;
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const double kEpsilon = 1e-14;
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class IterativeSchurComplementSolverTest : public ::testing::Test {
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protected:
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void SetUpProblem(int problem_id) {
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std::unique_ptr<LinearLeastSquaresProblem> problem =
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CreateLinearLeastSquaresProblemFromId(problem_id);
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ASSERT_TRUE(problem != nullptr);
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A_.reset(down_cast<BlockSparseMatrix*>(problem->A.release()));
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b_ = std::move(problem->b);
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D_ = std::move(problem->D);
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num_cols_ = A_->num_cols();
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num_rows_ = A_->num_rows();
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num_eliminate_blocks_ = problem->num_eliminate_blocks;
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}
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AssertionResult TestSolver(double* D,
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PreconditionerType preconditioner_type,
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bool use_spse_initialization) {
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TripletSparseMatrix triplet_A(
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A_->num_rows(), A_->num_cols(), A_->num_nonzeros());
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A_->ToTripletSparseMatrix(&triplet_A);
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DenseSparseMatrix dense_A(triplet_A);
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LinearSolver::Options options;
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options.type = DENSE_QR;
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ContextImpl context;
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options.context = &context;
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std::unique_ptr<LinearSolver> qr(LinearSolver::Create(options));
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LinearSolver::PerSolveOptions per_solve_options;
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per_solve_options.D = D;
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Vector reference_solution(num_cols_);
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qr->Solve(&dense_A, b_.get(), per_solve_options, reference_solution.data());
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options.elimination_groups.push_back(num_eliminate_blocks_);
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options.elimination_groups.push_back(0);
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options.max_num_iterations = num_cols_;
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options.max_num_spse_iterations = 1;
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options.use_spse_initialization = use_spse_initialization;
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options.preconditioner_type = preconditioner_type;
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IterativeSchurComplementSolver isc(options);
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Vector isc_sol(num_cols_);
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per_solve_options.r_tolerance = 1e-12;
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isc.Solve(A_.get(), b_.get(), per_solve_options, isc_sol.data());
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double diff = (isc_sol - reference_solution).norm();
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if (diff < kEpsilon) {
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return testing::AssertionSuccess();
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} else {
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return testing::AssertionFailure()
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<< "The reference solution differs from the ITERATIVE_SCHUR"
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<< " solution by " << diff << " which is more than " << kEpsilon;
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}
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}
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int num_rows_;
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int num_cols_;
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int num_eliminate_blocks_;
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std::unique_ptr<BlockSparseMatrix> A_;
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std::unique_ptr<double[]> b_;
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std::unique_ptr<double[]> D_;
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};
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TEST_F(IterativeSchurComplementSolverTest, NormalProblemSchurJacobi) {
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SetUpProblem(2);
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EXPECT_TRUE(TestSolver(nullptr, SCHUR_JACOBI, false));
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EXPECT_TRUE(TestSolver(D_.get(), SCHUR_JACOBI, false));
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}
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TEST_F(IterativeSchurComplementSolverTest,
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NormalProblemSchurJacobiWithPowerSeriesExpansionInitialization) {
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SetUpProblem(2);
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EXPECT_TRUE(TestSolver(nullptr, SCHUR_JACOBI, true));
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EXPECT_TRUE(TestSolver(D_.get(), SCHUR_JACOBI, true));
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}
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TEST_F(IterativeSchurComplementSolverTest,
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NormalProblemPowerSeriesExpansionPreconditioner) {
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SetUpProblem(5);
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EXPECT_TRUE(TestSolver(nullptr, SCHUR_POWER_SERIES_EXPANSION, false));
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EXPECT_TRUE(TestSolver(D_.get(), SCHUR_POWER_SERIES_EXPANSION, false));
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}
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TEST_F(IterativeSchurComplementSolverTest, ProblemWithNoFBlocks) {
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SetUpProblem(3);
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EXPECT_TRUE(TestSolver(nullptr, SCHUR_JACOBI, false));
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EXPECT_TRUE(TestSolver(D_.get(), SCHUR_JACOBI, false));
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}
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} // namespace internal
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} // namespace ceres
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