internal/ceres/iterative_schur_complement_solver.cc - ceres-solver - Git at Google

 // Ceres Solver - A fast non-linear least squares minimizer
 // Copyright 2023 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/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/event_logger.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"

 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
	// Ceres Solver - A fast non-linear least squares minimizer
	// Copyright 2023 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/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/event_logger.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"

	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