| // Ceres Solver - A fast non-linear least squares minimizer | |
| // Copyright 2023 Google Inc. All rights reserved. | |
| // http://ceres-solver.org/ | |
| // | |
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| // modification, are permitted provided that the following conditions are met: | |
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| // | |
| // Author: sameeragarwal@google.com (Sameer Agarwal) | |
| #include "ceres/subset_preconditioner.h" | |
| #include <memory> | |
| #include <string> | |
| #include <utility> | |
| #include "absl/log/check.h" | |
| #include "absl/log/log.h" | |
| #include "ceres/compressed_row_sparse_matrix.h" | |
| #include "ceres/inner_product_computer.h" | |
| #include "ceres/linear_solver.h" | |
| #include "ceres/sparse_cholesky.h" | |
| #include "ceres/types.h" | |
| namespace ceres::internal { | |
| SubsetPreconditioner::SubsetPreconditioner(Preconditioner::Options options, | |
| const BlockSparseMatrix& A) | |
| : options_(std::move(options)), num_cols_(A.num_cols()) { | |
| CHECK_GE(options_.subset_preconditioner_start_row_block, 0) | |
| << "Congratulations, you found a bug in Ceres. Please report it."; | |
| LinearSolver::Options sparse_cholesky_options; | |
| sparse_cholesky_options.sparse_linear_algebra_library_type = | |
| options_.sparse_linear_algebra_library_type; | |
| sparse_cholesky_options.ordering_type = options_.ordering_type; | |
| sparse_cholesky_ = SparseCholesky::Create(sparse_cholesky_options); | |
| } | |
| SubsetPreconditioner::~SubsetPreconditioner() = default; | |
| void SubsetPreconditioner::RightMultiplyAndAccumulate(const double* x, | |
| double* y) const { | |
| CHECK(x != nullptr); | |
| CHECK(y != nullptr); | |
| std::string message; | |
| sparse_cholesky_->Solve(x, y, &message); | |
| } | |
| bool SubsetPreconditioner::UpdateImpl(const BlockSparseMatrix& A, | |
| const double* D) { | |
| auto* m = const_cast<BlockSparseMatrix*>(&A); | |
| const CompressedRowBlockStructure* bs = m->block_structure(); | |
| // A = [P] | |
| // [Q] | |
| // Now add D to A if needed. | |
| if (D != nullptr) { | |
| // A = [P] | |
| // [Q] | |
| // [D] | |
| std::unique_ptr<BlockSparseMatrix> regularizer( | |
| BlockSparseMatrix::CreateDiagonalMatrix(D, bs->cols)); | |
| m->AppendRows(*regularizer); | |
| } | |
| if (inner_product_computer_ == nullptr) { | |
| inner_product_computer_ = InnerProductComputer::Create( | |
| *m, | |
| options_.subset_preconditioner_start_row_block, | |
| bs->rows.size(), | |
| sparse_cholesky_->StorageType()); | |
| } | |
| // Compute inner_product = [Q'*Q + D'*D] | |
| inner_product_computer_->Compute(); | |
| // Unappend D if needed. | |
| if (D != nullptr) { | |
| // A = [P] | |
| // [Q] | |
| m->DeleteRowBlocks(bs->cols.size()); | |
| } | |
| std::string message; | |
| // Compute L. s.t., LL' = Q'*Q + D'*D | |
| const LinearSolverTerminationType termination_type = | |
| sparse_cholesky_->Factorize(inner_product_computer_->mutable_result(), | |
| &message); | |
| if (termination_type != LinearSolverTerminationType::SUCCESS) { | |
| LOG(ERROR) << "Preconditioner factorization failed: " << message; | |
| return false; | |
| } | |
| return true; | |
| } | |
| } // namespace ceres::internal |