|  | // 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/parameter_block_ordering.h" | 
|  |  | 
|  | #include <map> | 
|  | #include <memory> | 
|  | #include <set> | 
|  | #include <unordered_set> | 
|  | #include <vector> | 
|  |  | 
|  | #include "absl/log/check.h" | 
|  | #include "ceres/event_logger.h" | 
|  | #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" | 
|  |  | 
|  | namespace ceres::internal { | 
|  |  | 
|  | int ComputeStableSchurOrdering(const Program& program, | 
|  | std::vector<ParameterBlock*>* ordering) { | 
|  | CHECK(ordering != nullptr); | 
|  | ordering->clear(); | 
|  | EventLogger event_logger("ComputeStableSchurOrdering"); | 
|  | auto graph = CreateHessianGraph(program); | 
|  | event_logger.AddEvent("CreateHessianGraph"); | 
|  |  | 
|  | const std::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, | 
|  | std::vector<ParameterBlock*>* ordering) { | 
|  | CHECK(ordering != nullptr); | 
|  | ordering->clear(); | 
|  |  | 
|  | auto graph = CreateHessianGraph(program); | 
|  | int independent_set_size = IndependentSetOrdering(*graph, ordering); | 
|  | const std::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 std::vector<ParameterBlock*> parameter_blocks = | 
|  | program.parameter_blocks(); | 
|  | auto graph = CreateHessianGraph(program); | 
|  |  | 
|  | int num_covered = 0; | 
|  | int round = 0; | 
|  | while (num_covered < parameter_blocks.size()) { | 
|  | std::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 std::vector<ParameterBlock*>& parameter_blocks = | 
|  | program.parameter_blocks(); | 
|  | for (auto* parameter_block : parameter_blocks) { | 
|  | if (!parameter_block->IsConstant()) { | 
|  | graph->AddVertex(parameter_block); | 
|  | } | 
|  | } | 
|  |  | 
|  | const std::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, | 
|  | std::vector<int>* group_sizes) { | 
|  | CHECK(group_sizes != nullptr); | 
|  | group_sizes->clear(); | 
|  | if (ordering == nullptr) { | 
|  | return; | 
|  | } | 
|  |  | 
|  | // TODO(sameeragarwal): Investigate if this should be a set or an | 
|  | // unordered_set. | 
|  | const std::map<int, std::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 ceres::internal |