| // Ceres Solver - A fast non-linear least squares minimizer |
| // Copyright 2015 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 |
| // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE |
| // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE |
| // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR |
| // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF |
| // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS |
| // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN |
| // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) |
| // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE |
| // POSSIBILITY OF SUCH DAMAGE. |
| // |
| // Author: sameeragarwal@google.com (Sameer Agarwal) |
| |
| #include "ceres/implicit_schur_complement.h" |
| |
| #include <cstddef> |
| #include <memory> |
| |
| #include "Eigen/Dense" |
| #include "ceres/block_random_access_dense_matrix.h" |
| #include "ceres/block_sparse_matrix.h" |
| #include "ceres/casts.h" |
| #include "ceres/context_impl.h" |
| #include "ceres/internal/eigen.h" |
| #include "ceres/linear_least_squares_problems.h" |
| #include "ceres/linear_solver.h" |
| #include "ceres/schur_eliminator.h" |
| #include "ceres/triplet_sparse_matrix.h" |
| #include "ceres/types.h" |
| #include "glog/logging.h" |
| #include "gtest/gtest.h" |
| |
| namespace ceres::internal { |
| |
| using testing::AssertionResult; |
| |
| const double kEpsilon = 1e-14; |
| |
| class ImplicitSchurComplementTest : public ::testing::Test { |
| protected: |
| void SetUp() final { |
| auto problem = CreateLinearLeastSquaresProblemFromId(2); |
| |
| CHECK(problem != nullptr); |
| A_.reset(down_cast<BlockSparseMatrix*>(problem->A.release())); |
| b_ = std::move(problem->b); |
| D_ = std::move(problem->D); |
| |
| num_cols_ = A_->num_cols(); |
| num_rows_ = A_->num_rows(); |
| num_eliminate_blocks_ = problem->num_eliminate_blocks; |
| } |
| |
| void ReducedLinearSystemAndSolution(double* D, |
| Matrix* lhs, |
| Vector* rhs, |
| Vector* solution) { |
| const CompressedRowBlockStructure* bs = A_->block_structure(); |
| const int num_col_blocks = bs->cols.size(); |
| auto blocks = Tail(bs->cols, num_col_blocks - num_eliminate_blocks_); |
| BlockRandomAccessDenseMatrix blhs(blocks); |
| const int num_schur_rows = blhs.num_rows(); |
| |
| LinearSolver::Options options; |
| options.elimination_groups.push_back(num_eliminate_blocks_); |
| options.type = DENSE_SCHUR; |
| ContextImpl context; |
| options.context = &context; |
| |
| std::unique_ptr<SchurEliminatorBase> eliminator = |
| SchurEliminatorBase::Create(options); |
| CHECK(eliminator != nullptr); |
| const bool kFullRankETE = true; |
| eliminator->Init(num_eliminate_blocks_, kFullRankETE, bs); |
| |
| lhs->resize(num_schur_rows, num_schur_rows); |
| rhs->resize(num_schur_rows); |
| |
| eliminator->Eliminate( |
| BlockSparseMatrixData(*A_), b_.get(), D, &blhs, rhs->data()); |
| |
| MatrixRef lhs_ref(blhs.mutable_values(), num_schur_rows, num_schur_rows); |
| |
| // lhs_ref is an upper triangular matrix. Construct a full version |
| // of lhs_ref in lhs by transposing lhs_ref, choosing the strictly |
| // lower triangular part of the matrix and adding it to lhs_ref. |
| *lhs = lhs_ref; |
| lhs->triangularView<Eigen::StrictlyLower>() = |
| lhs_ref.triangularView<Eigen::StrictlyUpper>().transpose(); |
| |
| solution->resize(num_cols_); |
| solution->setZero(); |
| VectorRef schur_solution(solution->data() + num_cols_ - num_schur_rows, |
| num_schur_rows); |
| schur_solution = lhs->selfadjointView<Eigen::Upper>().llt().solve(*rhs); |
| eliminator->BackSubstitute(BlockSparseMatrixData(*A_), |
| b_.get(), |
| D, |
| schur_solution.data(), |
| solution->data()); |
| } |
| |
| AssertionResult TestImplicitSchurComplement(double* D) { |
| Matrix lhs; |
| Vector rhs; |
| Vector reference_solution; |
| ReducedLinearSystemAndSolution(D, &lhs, &rhs, &reference_solution); |
| |
| LinearSolver::Options options; |
| options.elimination_groups.push_back(num_eliminate_blocks_); |
| options.preconditioner_type = JACOBI; |
| ContextImpl context; |
| options.context = &context; |
| ImplicitSchurComplement isc(options); |
| isc.Init(*A_, D, b_.get()); |
| |
| const int num_f_cols = lhs.cols(); |
| const int num_e_cols = num_cols_ - num_f_cols; |
| |
| Matrix A_dense, E, F, DE, DF; |
| A_->ToDenseMatrix(&A_dense); |
| E = A_dense.leftCols(A_->num_cols() - num_f_cols); |
| F = A_dense.rightCols(num_f_cols); |
| if (D) { |
| DE = VectorRef(D, num_e_cols).asDiagonal(); |
| DF = VectorRef(D + num_e_cols, num_f_cols).asDiagonal(); |
| } else { |
| DE = Matrix::Zero(num_e_cols, num_e_cols); |
| DF = Matrix::Zero(num_f_cols, num_f_cols); |
| } |
| |
| // Z = (block_diagonal(F'F))^-1 F'E (E'E)^-1 E'F |
| // Here, assuming that block_diagonal(F'F) == diagonal(F'F) |
| Matrix Z_reference = |
| (F.transpose() * F + DF).diagonal().asDiagonal().inverse() * |
| F.transpose() * E * (E.transpose() * E + DE).inverse() * E.transpose() * |
| F; |
| |
| for (int i = 0; i < num_f_cols; ++i) { |
| Vector x(num_f_cols); |
| x.setZero(); |
| x(i) = 1.0; |
| |
| Vector y(num_f_cols); |
| y = lhs * x; |
| |
| Vector z(num_f_cols); |
| isc.RightMultiplyAndAccumulate(x.data(), z.data()); |
| |
| // The i^th column of the implicit schur complement is the same as |
| // the explicit schur complement. |
| if ((y - z).norm() > kEpsilon) { |
| return testing::AssertionFailure() |
| << "Explicit and Implicit SchurComplements differ in " |
| << "column " << i << ". explicit: " << y.transpose() |
| << " implicit: " << z.transpose(); |
| } |
| |
| y.setZero(); |
| y = Z_reference * x; |
| z.setZero(); |
| isc.InversePowerSeriesOperatorRightMultiplyAccumulate(x.data(), z.data()); |
| |
| // The i^th column of operator Z stored implicitly is the same as its |
| // explicit version. |
| if ((y - z).norm() > kEpsilon) { |
| return testing::AssertionFailure() |
| << "Explicit and Implicit operators used to approximate the " |
| "inversion of schur complement via power series expansion " |
| "differ in column " |
| << i << ". explicit: " << y.transpose() |
| << " implicit: " << z.transpose(); |
| } |
| } |
| |
| // Compare the rhs of the reduced linear system |
| if ((isc.rhs() - rhs).norm() > kEpsilon) { |
| return testing::AssertionFailure() |
| << "Explicit and Implicit SchurComplements differ in " |
| << "rhs. explicit: " << rhs.transpose() |
| << " implicit: " << isc.rhs().transpose(); |
| } |
| |
| // Reference solution to the f_block. |
| const Vector reference_f_sol = |
| lhs.selfadjointView<Eigen::Upper>().llt().solve(rhs); |
| |
| // Backsubstituted solution from the implicit schur solver using the |
| // reference solution to the f_block. |
| Vector sol(num_cols_); |
| isc.BackSubstitute(reference_f_sol.data(), sol.data()); |
| if ((sol - reference_solution).norm() > kEpsilon) { |
| return testing::AssertionFailure() |
| << "Explicit and Implicit SchurComplements solutions differ. " |
| << "explicit: " << reference_solution.transpose() |
| << " implicit: " << sol.transpose(); |
| } |
| |
| return testing::AssertionSuccess(); |
| } |
| |
| int num_rows_; |
| int num_cols_; |
| int num_eliminate_blocks_; |
| |
| std::unique_ptr<BlockSparseMatrix> A_; |
| std::unique_ptr<double[]> b_; |
| std::unique_ptr<double[]> D_; |
| }; |
| |
| // Verify that the Schur Complement matrix implied by the |
| // ImplicitSchurComplement class matches the one explicitly computed |
| // by the SchurComplement solver. |
| // |
| // We do this with and without regularization to check that the |
| // support for the LM diagonal is correct. |
| TEST_F(ImplicitSchurComplementTest, SchurMatrixValuesTest) { |
| EXPECT_TRUE(TestImplicitSchurComplement(nullptr)); |
| EXPECT_TRUE(TestImplicitSchurComplement(D_.get())); |
| } |
| |
| } // namespace ceres::internal |