// 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: keir@google.com (Keir Mierle) #include "ceres/block_jacobian_writer.h" #include #include #include #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* jacobian_layout, std::vector* jacobian_layout_storage) { const std::vector& 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::max()) { LOG(ERROR) << "Overlow 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> 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& a, const std::pair& 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(f_block_pos); f_block_pos += jacobian_block_size; if (f_block_pos > std::numeric_limits::max()) { LOG(ERROR) << "Overlow 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 BlockJacobianWriter::CreateEvaluatePreparers(unsigned num_threads) { const int max_derivatives_per_residual_block = program_->MaxDerivativesPerResidualBlock(); auto preparers = std::make_unique(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 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& 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& 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( bs, options_.sparse_linear_algebra_library_type == CUDA_SPARSE); } } // namespace ceres::internal