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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:
//
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// this list of conditions and the following disclaimer.
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// this list of conditions and the following disclaimer in the documentation
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// Author: sameeragarwal@google.com (Sameer Agarwal)
#include "ceres/iterative_schur_complement_solver.h"
#include <algorithm>
#include <cstring>
#include <utility>
#include <vector>
#include "Eigen/Dense"
#include "absl/log/check.h"
#include "absl/log/log.h"
#include "ceres/block_sparse_matrix.h"
#include "ceres/block_structure.h"
#include "ceres/conjugate_gradients_solver.h"
#include "ceres/detect_structure.h"
#include "ceres/implicit_schur_complement.h"
#include "ceres/internal/eigen.h"
#include "ceres/linear_solver.h"
#include "ceres/power_series_expansion_preconditioner.h"
#include "ceres/preconditioner.h"
#include "ceres/schur_jacobi_preconditioner.h"
#include "ceres/triplet_sparse_matrix.h"
#include "ceres/types.h"
#include "ceres/visibility_based_preconditioner.h"
#include "ceres/wall_time.h"
namespace ceres::internal {
IterativeSchurComplementSolver::IterativeSchurComplementSolver(
LinearSolver::Options options)
: options_(std::move(options)) {}
IterativeSchurComplementSolver::~IterativeSchurComplementSolver() = default;
LinearSolver::Summary IterativeSchurComplementSolver::SolveImpl(
BlockSparseMatrix* A,
const double* b,
const LinearSolver::PerSolveOptions& per_solve_options,
double* x) {
EventLogger event_logger("IterativeSchurComplementSolver::Solve");
CHECK(A->block_structure() != nullptr);
CHECK(A->transpose_block_structure() != nullptr);
const int num_eliminate_blocks = options_.elimination_groups[0];
// Initialize a ImplicitSchurComplement object.
if (schur_complement_ == nullptr) {
DetectStructure(*(A->block_structure()),
num_eliminate_blocks,
&options_.row_block_size,
&options_.e_block_size,
&options_.f_block_size);
schur_complement_ = std::make_unique<ImplicitSchurComplement>(options_);
}
schur_complement_->Init(*A, per_solve_options.D, b);
const int num_schur_complement_blocks =
A->block_structure()->cols.size() - num_eliminate_blocks;
if (num_schur_complement_blocks == 0) {
VLOG(2) << "No parameter blocks left in the schur complement.";
LinearSolver::Summary summary;
summary.num_iterations = 0;
summary.termination_type = LinearSolverTerminationType::SUCCESS;
schur_complement_->BackSubstitute(nullptr, x);
return summary;
}
// Initialize the solution to the Schur complement system.
reduced_linear_system_solution_.resize(schur_complement_->num_rows());
reduced_linear_system_solution_.setZero();
if (options_.use_spse_initialization) {
Preconditioner::Options preconditioner_options(options_);
preconditioner_options.type = SCHUR_POWER_SERIES_EXPANSION;
PowerSeriesExpansionPreconditioner pse_solver(
schur_complement_.get(),
options_.max_num_spse_iterations,
options_.spse_tolerance,
preconditioner_options);
pse_solver.RightMultiplyAndAccumulate(
schur_complement_->rhs().data(),
reduced_linear_system_solution_.data());
}
CreatePreconditioner(A);
if (preconditioner_ != nullptr) {
if (!preconditioner_->Update(*A, per_solve_options.D)) {
LinearSolver::Summary summary;
summary.num_iterations = 0;
summary.termination_type = LinearSolverTerminationType::FAILURE;
summary.message = "Preconditioner update failed.";
return summary;
}
}
ConjugateGradientsSolverOptions cg_options;
cg_options.min_num_iterations = options_.min_num_iterations;
cg_options.max_num_iterations = options_.max_num_iterations;
cg_options.residual_reset_period = options_.residual_reset_period;
cg_options.q_tolerance = per_solve_options.q_tolerance;
cg_options.r_tolerance = per_solve_options.r_tolerance;
LinearOperatorAdapter lhs(*schur_complement_);
LinearOperatorAdapter preconditioner(*preconditioner_);
Vector scratch[4];
for (int i = 0; i < 4; ++i) {
scratch[i].resize(schur_complement_->num_cols());
}
Vector* scratch_ptr[4] = {&scratch[0], &scratch[1], &scratch[2], &scratch[3]};
event_logger.AddEvent("Setup");
LinearSolver::Summary summary =
ConjugateGradientsSolver(cg_options,
lhs,
schur_complement_->rhs(),
preconditioner,
scratch_ptr,
reduced_linear_system_solution_);
if (summary.termination_type != LinearSolverTerminationType::FAILURE &&
summary.termination_type != LinearSolverTerminationType::FATAL_ERROR) {
schur_complement_->BackSubstitute(reduced_linear_system_solution_.data(),
x);
}
event_logger.AddEvent("Solve");
return summary;
}
void IterativeSchurComplementSolver::CreatePreconditioner(
BlockSparseMatrix* A) {
if (preconditioner_ != nullptr) {
return;
}
Preconditioner::Options preconditioner_options(options_);
CHECK(options_.context != nullptr);
switch (options_.preconditioner_type) {
case IDENTITY:
preconditioner_ = std::make_unique<IdentityPreconditioner>(
schur_complement_->num_cols());
break;
case JACOBI:
preconditioner_ = std::make_unique<SparseMatrixPreconditionerWrapper>(
schur_complement_->block_diagonal_FtF_inverse(),
preconditioner_options);
break;
case SCHUR_POWER_SERIES_EXPANSION:
// Ignoring the value of spse_tolerance to ensure preconditioner stays
// fixed during the iterations of cg.
preconditioner_ = std::make_unique<PowerSeriesExpansionPreconditioner>(
schur_complement_.get(),
options_.max_num_spse_iterations,
0,
preconditioner_options);
break;
case SCHUR_JACOBI:
preconditioner_ = std::make_unique<SchurJacobiPreconditioner>(
*A->block_structure(), preconditioner_options);
break;
case CLUSTER_JACOBI:
case CLUSTER_TRIDIAGONAL:
preconditioner_ = std::make_unique<VisibilityBasedPreconditioner>(
*A->block_structure(), preconditioner_options);
break;
default:
LOG(FATAL) << "Unknown Preconditioner Type";
}
};
} // namespace ceres::internal