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// 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
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// POSSIBILITY OF SUCH DAMAGE.
//
// Author: sameeragarwal@google.com (Sameer Agarwal)
#ifndef CERES_INTERNAL_COORDINATE_DESCENT_MINIMIZER_H_
#define CERES_INTERNAL_COORDINATE_DESCENT_MINIMIZER_H_
#include <memory>
#include <string>
#include <vector>
#include "ceres/context_impl.h"
#include "ceres/evaluator.h"
#include "ceres/minimizer.h"
#include "ceres/problem_impl.h"
#include "ceres/solver.h"
namespace ceres::internal {
class Program;
class LinearSolver;
// Given a Program, and a ParameterBlockOrdering which partitions
// (non-exhaustively) the Hessian matrix into independent sets,
// perform coordinate descent on the parameter blocks in the
// ordering. The independent set structure allows for all parameter
// blocks in the same independent set to be optimized in parallel, and
// the order of the independent set determines the order in which the
// parameter block groups are optimized.
//
// The minimizer assumes that none of the parameter blocks in the
// program are constant.
class CERES_NO_EXPORT CoordinateDescentMinimizer final : public Minimizer {
public:
explicit CoordinateDescentMinimizer(ContextImpl* context);
bool Init(const Program& program,
const ProblemImpl::ParameterMap& parameter_map,
const ParameterBlockOrdering& ordering,
std::string* error);
// Minimizer interface.
~CoordinateDescentMinimizer() override;
void Minimize(const Minimizer::Options& options,
double* parameters,
Solver::Summary* summary) final;
// Verify that each group in the ordering forms an independent set.
static bool IsOrderingValid(const Program& program,
const ParameterBlockOrdering& ordering,
std::string* message);
// Find a recursive decomposition of the Hessian matrix as a set
// of independent sets of decreasing size and invert it. This
// seems to work better in practice, i.e., Cameras before
// points.
static std::shared_ptr<ParameterBlockOrdering> CreateOrdering(
const Program& program);
private:
void Solve(Program* program,
LinearSolver* linear_solver,
double* parameters,
Solver::Summary* summary);
std::vector<ParameterBlock*> parameter_blocks_;
std::vector<std::vector<ResidualBlock*>> residual_blocks_;
// The optimization is performed in rounds. In each round all the
// parameter blocks that form one independent set are optimized in
// parallel. This array, marks the boundaries of the independent
// sets in parameter_blocks_.
std::vector<int> independent_set_offsets_;
Evaluator::Options evaluator_options_;
ContextImpl* context_;
};
} // namespace ceres::internal
#endif // CERES_INTERNAL_COORDINATE_DESCENT_MINIMIZER_H_