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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2022 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/parameter_block_ordering.h"
#include <memory>
#include <unordered_set>
#include "ceres/graph.h"
#include "ceres/graph_algorithms.h"
#include "ceres/map_util.h"
#include "ceres/parameter_block.h"
#include "ceres/program.h"
#include "ceres/residual_block.h"
#include "ceres/wall_time.h"
#include "glog/logging.h"
namespace ceres {
namespace internal {
using std::map;
using std::set;
using std::vector;
int ComputeStableSchurOrdering(const Program& program,
vector<ParameterBlock*>* ordering) {
CHECK(ordering != nullptr);
ordering->clear();
EventLogger event_logger("ComputeStableSchurOrdering");
auto graph = CreateHessianGraph(program);
event_logger.AddEvent("CreateHessianGraph");
const vector<ParameterBlock*>& parameter_blocks = program.parameter_blocks();
const std::unordered_set<ParameterBlock*>& vertices = graph->vertices();
for (auto* parameter_block : parameter_blocks) {
if (vertices.count(parameter_block) > 0) {
ordering->push_back(parameter_block);
}
}
event_logger.AddEvent("Preordering");
int independent_set_size = StableIndependentSetOrdering(*graph, ordering);
event_logger.AddEvent("StableIndependentSet");
// Add the excluded blocks to back of the ordering vector.
for (auto* parameter_block : parameter_blocks) {
if (parameter_block->IsConstant()) {
ordering->push_back(parameter_block);
}
}
event_logger.AddEvent("ConstantParameterBlocks");
return independent_set_size;
}
int ComputeSchurOrdering(const Program& program,
vector<ParameterBlock*>* ordering) {
CHECK(ordering != nullptr);
ordering->clear();
auto graph = CreateHessianGraph(program);
int independent_set_size = IndependentSetOrdering(*graph, ordering);
const vector<ParameterBlock*>& parameter_blocks = program.parameter_blocks();
// Add the excluded blocks to back of the ordering vector.
for (auto* parameter_block : parameter_blocks) {
if (parameter_block->IsConstant()) {
ordering->push_back(parameter_block);
}
}
return independent_set_size;
}
void ComputeRecursiveIndependentSetOrdering(const Program& program,
ParameterBlockOrdering* ordering) {
CHECK(ordering != nullptr);
ordering->Clear();
const vector<ParameterBlock*> parameter_blocks = program.parameter_blocks();
auto graph = CreateHessianGraph(program);
int num_covered = 0;
int round = 0;
while (num_covered < parameter_blocks.size()) {
vector<ParameterBlock*> independent_set_ordering;
const int independent_set_size =
IndependentSetOrdering(*graph, &independent_set_ordering);
for (int i = 0; i < independent_set_size; ++i) {
ParameterBlock* parameter_block = independent_set_ordering[i];
ordering->AddElementToGroup(parameter_block->mutable_user_state(), round);
graph->RemoveVertex(parameter_block);
}
num_covered += independent_set_size;
++round;
}
}
std::unique_ptr<Graph<ParameterBlock*>> CreateHessianGraph(
const Program& program) {
auto graph = std::make_unique<Graph<ParameterBlock*>>();
CHECK(graph != nullptr);
const vector<ParameterBlock*>& parameter_blocks = program.parameter_blocks();
for (auto* parameter_block : parameter_blocks) {
if (!parameter_block->IsConstant()) {
graph->AddVertex(parameter_block);
}
}
const vector<ResidualBlock*>& residual_blocks = program.residual_blocks();
for (auto* residual_block : residual_blocks) {
const int num_parameter_blocks = residual_block->NumParameterBlocks();
ParameterBlock* const* parameter_blocks =
residual_block->parameter_blocks();
for (int j = 0; j < num_parameter_blocks; ++j) {
if (parameter_blocks[j]->IsConstant()) {
continue;
}
for (int k = j + 1; k < num_parameter_blocks; ++k) {
if (parameter_blocks[k]->IsConstant()) {
continue;
}
graph->AddEdge(parameter_blocks[j], parameter_blocks[k]);
}
}
}
return graph;
}
void OrderingToGroupSizes(const ParameterBlockOrdering* ordering,
vector<int>* group_sizes) {
CHECK(group_sizes != nullptr);
group_sizes->clear();
if (ordering == nullptr) {
return;
}
const map<int, set<double*>>& group_to_elements =
ordering->group_to_elements();
for (const auto& g_t_e : group_to_elements) {
group_sizes->push_back(g_t_e.second.size());
}
}
} // namespace internal
} // namespace ceres
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