internal/ceres/compressed_row_jacobian_writer.cc - ceres-solver - Git at Google

 // 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/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();

   const int total_num_residuals = program_->NumResiduals();
   const int total_num_effective_parameters = program_->NumEffectiveParameters();

   // Count the number of jacobian nonzeros.
   //
   // We used an unsigned int here, so that we can compare it INT_MAX without
   // triggering overflow behaviour.
   unsigned int num_jacobian_nonzeros = total_num_effective_parameters;
   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();
         if (num_jacobian_nonzeros > std::numeric_limits<int>::max()) {
           LOG(ERROR) << "Unable to create Jacobian matrix: Too many entries in "
                         "the Jacobian matrix. num_jacobian_nonzeros = "
                      << num_jacobian_nonzeros;
           return nullptr;
         }
       }
     }
   }

   // 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,
       static_cast<int>(num_jacobian_nonzeros));

   // 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 - total_num_effective_parameters,
            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
	// 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/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();

	const int total_num_residuals = program_->NumResiduals();
	const int total_num_effective_parameters = program_->NumEffectiveParameters();

	// Count the number of jacobian nonzeros.
	//
	// We used an unsigned int here, so that we can compare it INT_MAX without
	// triggering overflow behaviour.
	unsigned int num_jacobian_nonzeros = total_num_effective_parameters;
	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();
	if (num_jacobian_nonzeros > std::numeric_limits<int>::max()) {
	LOG(ERROR) << "Unable to create Jacobian matrix: Too many entries in "
	"the Jacobian matrix. num_jacobian_nonzeros = "
	<< num_jacobian_nonzeros;
	return nullptr;
	}
	}
	}
	}

	// 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,
	static_cast<int>(num_jacobian_nonzeros));

	// 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 - total_num_effective_parameters,
	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