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// 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:
//
// * 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
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//
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// Author: sameeragarwal@google.com (Sameer Agarwal)
#include "ceres/subset_preconditioner.h"
#include <memory>
#include <string>
#include <utility>
#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