mirror of
https://github.com/ceres-solver/ceres-solver.git
synced 2026-08-30 09:00:37 +08:00
Sameer Agarwal
f973e107d2
1. Add Solver::Options::use_mixed_precision_solves, and Solver::Options::max_num_refinement_iterations. 2. Make SparseCholesky::Create return a unique_ptr. 3. SparseCholesky::Create now takes LinearSolver::Options as an argument. 4. IterativeRefiner's constructor does not require num_cols as an argument. 5. SparseNormalCholeskySolver now uses a separate rhs vector. This basic implementation results in a 10% reduction in solver time and 30% reduction in linear solver memory usage. Change-Id: I6830f32cae2febf082d2733262eb2c9f0482b0ea
116 lines
4.1 KiB
C++
116 lines
4.1 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2017 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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#include "ceres/subset_preconditioner.h"
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#include <memory>
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#include <string>
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#include "ceres/compressed_row_sparse_matrix.h"
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#include "ceres/inner_product_computer.h"
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#include "ceres/linear_solver.h"
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#include "ceres/sparse_cholesky.h"
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#include "ceres/types.h"
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namespace ceres {
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namespace internal {
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SubsetPreconditioner::SubsetPreconditioner(
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const Preconditioner::Options& options, const BlockSparseMatrix& A)
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: options_(options), num_cols_(A.num_cols()) {
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CHECK_GE(options_.subset_preconditioner_start_row_block, 0);
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LinearSolver::Options sparse_cholesky_options;
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sparse_cholesky_options.sparse_linear_algebra_library_type =
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options_.sparse_linear_algebra_library_type;
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sparse_cholesky_options.use_postordering =
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options_.use_postordering;
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sparse_cholesky_ = SparseCholesky::Create(sparse_cholesky_options);
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}
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SubsetPreconditioner::~SubsetPreconditioner() {}
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void SubsetPreconditioner::RightMultiply(const double* x, double* y) const {
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CHECK_NOTNULL(x);
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CHECK_NOTNULL(y);
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std::string message;
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sparse_cholesky_->Solve(x, y, &message);
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}
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bool SubsetPreconditioner::UpdateImpl(const BlockSparseMatrix& A,
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const double* D) {
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BlockSparseMatrix* m = const_cast<BlockSparseMatrix*>(&A);
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const CompressedRowBlockStructure* bs = m->block_structure();
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// A = [P]
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// [Q]
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// Now add D to A if needed.
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if (D != NULL) {
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// A = [P]
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// [Q]
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// [D]
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std::unique_ptr<BlockSparseMatrix> regularizer(
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BlockSparseMatrix::CreateDiagonalMatrix(D, bs->cols));
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m->AppendRows(*regularizer);
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}
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if (inner_product_computer_.get() == NULL) {
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inner_product_computer_.reset(InnerProductComputer::Create(
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*m,
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options_.subset_preconditioner_start_row_block,
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bs->rows.size(),
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sparse_cholesky_->StorageType()));
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}
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// Compute inner_product = [Q'*Q + D'*D]
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inner_product_computer_->Compute();
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// Unappend D if needed.
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if (D != NULL) {
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// A = [P]
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// [Q]
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m->DeleteRowBlocks(bs->cols.size());
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}
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std::string message;
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// Compute L. s.t., LL' = Q'*Q + D'*D
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const LinearSolverTerminationType termination_type =
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sparse_cholesky_->Factorize(inner_product_computer_->mutable_result(),
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&message);
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if (termination_type != LINEAR_SOLVER_SUCCESS) {
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LOG(ERROR) << "Preconditioner factorization failed: " << message;
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return false;
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}
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return true;
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}
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} // namespace internal
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} // namespace ceres
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