| // 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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| // | |
| // Author: keir@google.com (Keir Mierle) | |
| #include "ceres/block_jacobian_writer.h" | |
| #include <algorithm> | |
| #include <memory> | |
| #include <vector> | |
| #include "absl/log/check.h" | |
| #include "absl/log/log.h" | |
| #include "ceres/block_evaluate_preparer.h" | |
| #include "ceres/block_sparse_matrix.h" | |
| #include "ceres/internal/eigen.h" | |
| #include "ceres/internal/export.h" | |
| #include "ceres/parameter_block.h" | |
| #include "ceres/program.h" | |
| #include "ceres/residual_block.h" | |
| namespace ceres::internal { | |
| namespace { | |
| // Given the residual block ordering, build a lookup table to determine which | |
| // per-parameter jacobian goes where in the overall program jacobian. | |
| // | |
| // Since we expect to use a Schur type linear solver to solve the LM step, take | |
| // extra care to place the E blocks and the F blocks contiguously. E blocks are | |
| // the first num_eliminate_blocks parameter blocks as indicated by the parameter | |
| // block ordering. The remaining parameter blocks are the F blocks. | |
| // | |
| // In order to simplify handling block-sparse to CRS conversion, cells within | |
| // the row-block of non-partitioned matrix are stored in memory sequentially in | |
| // the order of increasing column-block id. In case of partitioned matrices, | |
| // cells corresponding to F sub-matrix are stored sequentially in the order of | |
| // increasing column-block id (with cells corresponding to E sub-matrix stored | |
| // separately). | |
| // | |
| // TODO(keir): Consider if we should use a boolean for each parameter block | |
| // instead of num_eliminate_blocks. | |
| bool BuildJacobianLayout(const Program& program, | |
| int num_eliminate_blocks, | |
| std::vector<int*>* jacobian_layout, | |
| std::vector<int>* jacobian_layout_storage) { | |
| const std::vector<ResidualBlock*>& residual_blocks = | |
| program.residual_blocks(); | |
| // Iterate over all the active residual blocks and determine how many E blocks | |
| // are there. This will determine where the F blocks start in the jacobian | |
| // matrix. Also compute the number of jacobian blocks. | |
| unsigned int f_block_pos = 0; | |
| unsigned int num_jacobian_blocks = 0; | |
| for (auto* residual_block : residual_blocks) { | |
| const int num_residuals = residual_block->NumResiduals(); | |
| const int num_parameter_blocks = residual_block->NumParameterBlocks(); | |
| // Advance f_block_pos over each E block for this residual. | |
| for (int j = 0; j < num_parameter_blocks; ++j) { | |
| ParameterBlock* parameter_block = residual_block->parameter_blocks()[j]; | |
| if (!parameter_block->IsConstant()) { | |
| // Only count blocks for active parameters. | |
| num_jacobian_blocks++; | |
| if (parameter_block->index() < num_eliminate_blocks) { | |
| f_block_pos += num_residuals * parameter_block->TangentSize(); | |
| } | |
| } | |
| } | |
| if (num_jacobian_blocks > std::numeric_limits<int>::max()) { | |
| LOG(ERROR) << "Overflow error. Too many blocks in the jacobian matrix : " | |
| << num_jacobian_blocks; | |
| return false; | |
| } | |
| } | |
| // We now know that the E blocks are laid out starting at zero, and the F | |
| // blocks are laid out starting at f_block_pos. Iterate over the residual | |
| // blocks again, and this time fill the jacobian_layout array with the | |
| // position information. | |
| jacobian_layout->resize(program.NumResidualBlocks()); | |
| jacobian_layout_storage->resize(num_jacobian_blocks); | |
| int e_block_pos = 0; | |
| int* jacobian_pos = jacobian_layout_storage->data(); | |
| std::vector<std::pair<int, int>> active_parameter_blocks; | |
| for (int i = 0; i < residual_blocks.size(); ++i) { | |
| const ResidualBlock* residual_block = residual_blocks[i]; | |
| const int num_residuals = residual_block->NumResiduals(); | |
| const int num_parameter_blocks = residual_block->NumParameterBlocks(); | |
| (*jacobian_layout)[i] = jacobian_pos; | |
| // Cells from F sub-matrix are to be stored sequentially with increasing | |
| // column block id. For each non-constant parameter block, a pair of indices | |
| // (index in the list of active parameter blocks and index in the list of | |
| // all parameter blocks) is computed, and index pairs are sorted by the | |
| // index of corresponding column block id. | |
| active_parameter_blocks.clear(); | |
| active_parameter_blocks.reserve(num_parameter_blocks); | |
| for (int j = 0; j < num_parameter_blocks; ++j) { | |
| ParameterBlock* parameter_block = residual_block->parameter_blocks()[j]; | |
| if (parameter_block->IsConstant()) { | |
| continue; | |
| } | |
| const int k = active_parameter_blocks.size(); | |
| active_parameter_blocks.emplace_back(k, j); | |
| } | |
| std::sort(active_parameter_blocks.begin(), | |
| active_parameter_blocks.end(), | |
| [&residual_block](const std::pair<int, int>& a, | |
| const std::pair<int, int>& b) { | |
| return residual_block->parameter_blocks()[a.second]->index() < | |
| residual_block->parameter_blocks()[b.second]->index(); | |
| }); | |
| // Cell positions for each active parameter block are filled in the order of | |
| // active parameter block indices sorted by columnd block index. This | |
| // guarantees that cells are laid out sequentially with increasing column | |
| // block indices. | |
| for (const auto& indices : active_parameter_blocks) { | |
| const auto [k, j] = indices; | |
| ParameterBlock* parameter_block = residual_block->parameter_blocks()[j]; | |
| const int parameter_block_index = parameter_block->index(); | |
| const int jacobian_block_size = | |
| num_residuals * parameter_block->TangentSize(); | |
| if (parameter_block_index < num_eliminate_blocks) { | |
| jacobian_pos[k] = e_block_pos; | |
| e_block_pos += jacobian_block_size; | |
| } else { | |
| jacobian_pos[k] = static_cast<int>(f_block_pos); | |
| f_block_pos += jacobian_block_size; | |
| if (f_block_pos > std::numeric_limits<int>::max()) { | |
| LOG(ERROR) | |
| << "Overflow error. Too many entries in the Jacobian matrix."; | |
| return false; | |
| } | |
| } | |
| } | |
| jacobian_pos += active_parameter_blocks.size(); | |
| } | |
| return true; | |
| } | |
| } // namespace | |
| BlockJacobianWriter::BlockJacobianWriter(const Evaluator::Options& options, | |
| Program* program) | |
| : options_(options), program_(program) { | |
| CHECK_GE(options.num_eliminate_blocks, 0) | |
| << "num_eliminate_blocks must be greater than 0."; | |
| jacobian_layout_is_valid_ = BuildJacobianLayout(*program, | |
| options.num_eliminate_blocks, | |
| &jacobian_layout_, | |
| &jacobian_layout_storage_); | |
| } | |
| // Create evaluate preparers that point directly into the final jacobian. This | |
| // makes the final Write() a nop. | |
| std::unique_ptr<BlockEvaluatePreparer[]> | |
| BlockJacobianWriter::CreateEvaluatePreparers(unsigned num_threads) { | |
| const int max_derivatives_per_residual_block = | |
| program_->MaxDerivativesPerResidualBlock(); | |
| auto preparers = std::make_unique<BlockEvaluatePreparer[]>(num_threads); | |
| for (unsigned i = 0; i < num_threads; i++) { | |
| preparers[i].Init(jacobian_layout_.data(), | |
| max_derivatives_per_residual_block); | |
| } | |
| return preparers; | |
| } | |
| std::unique_ptr<SparseMatrix> BlockJacobianWriter::CreateJacobian() const { | |
| if (!jacobian_layout_is_valid_) { | |
| LOG(ERROR) << "Unable to create Jacobian matrix. Too many entries in the " | |
| "Jacobian matrix."; | |
| return nullptr; | |
| } | |
| auto* bs = new CompressedRowBlockStructure; | |
| const std::vector<ParameterBlock*>& parameter_blocks = | |
| program_->parameter_blocks(); | |
| // Construct the column blocks. | |
| bs->cols.resize(parameter_blocks.size()); | |
| for (int i = 0, cursor = 0; i < parameter_blocks.size(); ++i) { | |
| CHECK_NE(parameter_blocks[i]->index(), -1); | |
| CHECK(!parameter_blocks[i]->IsConstant()); | |
| bs->cols[i].size = parameter_blocks[i]->TangentSize(); | |
| bs->cols[i].position = cursor; | |
| cursor += bs->cols[i].size; | |
| } | |
| // Construct the cells in each row. | |
| const std::vector<ResidualBlock*>& residual_blocks = | |
| program_->residual_blocks(); | |
| int row_block_position = 0; | |
| bs->rows.resize(residual_blocks.size()); | |
| for (int i = 0; i < residual_blocks.size(); ++i) { | |
| const ResidualBlock* residual_block = residual_blocks[i]; | |
| CompressedRow* row = &bs->rows[i]; | |
| row->block.size = residual_block->NumResiduals(); | |
| row->block.position = row_block_position; | |
| row_block_position += row->block.size; | |
| // Size the row by the number of active parameters in this residual. | |
| const int num_parameter_blocks = residual_block->NumParameterBlocks(); | |
| int num_active_parameter_blocks = 0; | |
| for (int j = 0; j < num_parameter_blocks; ++j) { | |
| if (residual_block->parameter_blocks()[j]->index() != -1) { | |
| num_active_parameter_blocks++; | |
| } | |
| } | |
| row->cells.resize(num_active_parameter_blocks); | |
| // Add layout information for the active parameters in this row. | |
| for (int j = 0, k = 0; j < num_parameter_blocks; ++j) { | |
| const ParameterBlock* parameter_block = | |
| residual_block->parameter_blocks()[j]; | |
| if (!parameter_block->IsConstant()) { | |
| Cell& cell = row->cells[k]; | |
| cell.block_id = parameter_block->index(); | |
| cell.position = jacobian_layout_[i][k]; | |
| // Only increment k for active parameters, since there is only layout | |
| // information for active parameters. | |
| k++; | |
| } | |
| } | |
| std::sort(row->cells.begin(), row->cells.end(), CellLessThan); | |
| } | |
| return std::make_unique<BlockSparseMatrix>( | |
| bs, options_.sparse_linear_algebra_library_type == CUDA_SPARSE); | |
| } | |
| } // namespace ceres::internal |