| // 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: keir@google.com (Keir Mierle) |
| |
| #include "ceres/compressed_row_jacobian_writer.h" |
| |
| #include <algorithm> |
| #include <iterator> |
| #include <memory> |
| #include <string> |
| #include <utility> |
| #include <vector> |
| |
| #include "ceres/casts.h" |
| #include "ceres/compressed_row_sparse_matrix.h" |
| #include "ceres/parameter_block.h" |
| #include "ceres/program.h" |
| #include "ceres/residual_block.h" |
| #include "ceres/scratch_evaluate_preparer.h" |
| |
| namespace ceres::internal { |
| void CompressedRowJacobianWriter::PopulateJacobianRowAndColumnBlockVectors( |
| const Program* program, CompressedRowSparseMatrix* jacobian) { |
| const auto& parameter_blocks = program->parameter_blocks(); |
| auto& col_blocks = *(jacobian->mutable_col_blocks()); |
| col_blocks.resize(parameter_blocks.size()); |
| int col_pos = 0; |
| for (int i = 0; i < parameter_blocks.size(); ++i) { |
| col_blocks[i].size = parameter_blocks[i]->TangentSize(); |
| col_blocks[i].position = col_pos; |
| col_pos += col_blocks[i].size; |
| } |
| |
| const auto& residual_blocks = program->residual_blocks(); |
| auto& row_blocks = *(jacobian->mutable_row_blocks()); |
| row_blocks.resize(residual_blocks.size()); |
| int row_pos = 0; |
| for (int i = 0; i < residual_blocks.size(); ++i) { |
| row_blocks[i].size = residual_blocks[i]->NumResiduals(); |
| row_blocks[i].position = row_pos; |
| row_pos += row_blocks[i].size; |
| } |
| } |
| |
| void CompressedRowJacobianWriter::GetOrderedParameterBlocks( |
| const Program* program, |
| int residual_id, |
| std::vector<std::pair<int, int>>* evaluated_jacobian_blocks) { |
| auto residual_block = program->residual_blocks()[residual_id]; |
| const int num_parameter_blocks = residual_block->NumParameterBlocks(); |
| |
| for (int j = 0; j < num_parameter_blocks; ++j) { |
| auto parameter_block = residual_block->parameter_blocks()[j]; |
| if (!parameter_block->IsConstant()) { |
| evaluated_jacobian_blocks->push_back( |
| std::make_pair(parameter_block->index(), j)); |
| } |
| } |
| std::sort(evaluated_jacobian_blocks->begin(), |
| evaluated_jacobian_blocks->end()); |
| } |
| |
| std::unique_ptr<SparseMatrix> CompressedRowJacobianWriter::CreateJacobian() |
| const { |
| const auto& residual_blocks = program_->residual_blocks(); |
| |
| int total_num_residuals = program_->NumResiduals(); |
| int total_num_effective_parameters = program_->NumEffectiveParameters(); |
| |
| // Count the number of jacobian nonzeros. |
| int num_jacobian_nonzeros = 0; |
| for (auto* residual_block : residual_blocks) { |
| const int num_residuals = residual_block->NumResiduals(); |
| const int num_parameter_blocks = residual_block->NumParameterBlocks(); |
| for (int j = 0; j < num_parameter_blocks; ++j) { |
| auto parameter_block = residual_block->parameter_blocks()[j]; |
| if (!parameter_block->IsConstant()) { |
| num_jacobian_nonzeros += num_residuals * parameter_block->TangentSize(); |
| } |
| } |
| } |
| |
| // Allocate storage for the jacobian with some extra space at the end. |
| // Allocate more space than needed to store the jacobian so that when the LM |
| // algorithm adds the diagonal, no reallocation is necessary. This reduces |
| // peak memory usage significantly. |
| auto jacobian = std::make_unique<CompressedRowSparseMatrix>( |
| total_num_residuals, |
| total_num_effective_parameters, |
| num_jacobian_nonzeros + total_num_effective_parameters); |
| |
| // At this stage, the CompressedRowSparseMatrix is an invalid state. But |
| // this seems to be the only way to construct it without doing a memory |
| // copy. |
| int* rows = jacobian->mutable_rows(); |
| int* cols = jacobian->mutable_cols(); |
| |
| int row_pos = 0; |
| rows[0] = 0; |
| for (auto* residual_block : residual_blocks) { |
| const int num_parameter_blocks = residual_block->NumParameterBlocks(); |
| |
| // Count the number of derivatives for a row of this residual block and |
| // build a list of active parameter block indices. |
| int num_derivatives = 0; |
| std::vector<int> parameter_indices; |
| for (int j = 0; j < num_parameter_blocks; ++j) { |
| auto parameter_block = residual_block->parameter_blocks()[j]; |
| if (!parameter_block->IsConstant()) { |
| parameter_indices.push_back(parameter_block->index()); |
| num_derivatives += parameter_block->TangentSize(); |
| } |
| } |
| |
| // Sort the parameters by their position in the state vector. |
| std::sort(parameter_indices.begin(), parameter_indices.end()); |
| if (adjacent_find(parameter_indices.begin(), parameter_indices.end()) != |
| parameter_indices.end()) { |
| std::string parameter_block_description; |
| for (int j = 0; j < num_parameter_blocks; ++j) { |
| auto parameter_block = residual_block->parameter_blocks()[j]; |
| parameter_block_description += parameter_block->ToString() + "\n"; |
| } |
| LOG(FATAL) << "Ceres internal error: " |
| << "Duplicate parameter blocks detected in a cost function. " |
| << "This should never happen. Please report this to " |
| << "the Ceres developers.\n" |
| << "Residual Block: " << residual_block->ToString() << "\n" |
| << "Parameter Blocks: " << parameter_block_description; |
| } |
| |
| // Update the row indices. |
| const int num_residuals = residual_block->NumResiduals(); |
| for (int j = 0; j < num_residuals; ++j) { |
| rows[row_pos + j + 1] = rows[row_pos + j] + num_derivatives; |
| } |
| |
| // Iterate over parameter blocks in the order which they occur in the |
| // parameter vector. This code mirrors that in Write(), where jacobian |
| // values are updated. |
| int col_pos = 0; |
| for (int parameter_index : parameter_indices) { |
| auto parameter_block = program_->parameter_blocks()[parameter_index]; |
| const int parameter_block_size = parameter_block->TangentSize(); |
| |
| for (int r = 0; r < num_residuals; ++r) { |
| // This is the position in the values array of the jacobian where this |
| // row of the jacobian block should go. |
| const int column_block_begin = rows[row_pos + r] + col_pos; |
| for (int c = 0; c < parameter_block_size; ++c) { |
| cols[column_block_begin + c] = parameter_block->delta_offset() + c; |
| } |
| } |
| col_pos += parameter_block_size; |
| } |
| row_pos += num_residuals; |
| } |
| CHECK_EQ(num_jacobian_nonzeros, rows[total_num_residuals]); |
| |
| PopulateJacobianRowAndColumnBlockVectors(program_, jacobian.get()); |
| |
| return jacobian; |
| } |
| |
| void CompressedRowJacobianWriter::Write(int residual_id, |
| int residual_offset, |
| double** jacobians, |
| SparseMatrix* base_jacobian) { |
| auto* jacobian = down_cast<CompressedRowSparseMatrix*>(base_jacobian); |
| |
| double* jacobian_values = jacobian->mutable_values(); |
| const int* jacobian_rows = jacobian->rows(); |
| |
| auto residual_block = program_->residual_blocks()[residual_id]; |
| const int num_residuals = residual_block->NumResiduals(); |
| |
| std::vector<std::pair<int, int>> evaluated_jacobian_blocks; |
| GetOrderedParameterBlocks(program_, residual_id, &evaluated_jacobian_blocks); |
| |
| // Where in the current row does the jacobian for a parameter block begin. |
| int col_pos = 0; |
| |
| // Iterate over the jacobian blocks in increasing order of their |
| // positions in the reduced parameter vector. |
| for (auto& evaluated_jacobian_block : evaluated_jacobian_blocks) { |
| auto parameter_block = |
| program_->parameter_blocks()[evaluated_jacobian_block.first]; |
| const int argument = evaluated_jacobian_block.second; |
| const int parameter_block_size = parameter_block->TangentSize(); |
| |
| // Copy one row of the jacobian block at a time. |
| for (int r = 0; r < num_residuals; ++r) { |
| // Position of the r^th row of the current jacobian block. |
| const double* block_row_begin = |
| jacobians[argument] + r * parameter_block_size; |
| |
| // Position in the values array of the jacobian where this |
| // row of the jacobian block should go. |
| double* column_block_begin = |
| jacobian_values + jacobian_rows[residual_offset + r] + col_pos; |
| |
| std::copy(block_row_begin, |
| block_row_begin + parameter_block_size, |
| column_block_begin); |
| } |
| col_pos += parameter_block_size; |
| } |
| } |
| |
| } // namespace ceres::internal |