internal/ceres/block_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/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) << "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<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)
               << "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<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
	// 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 <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) << "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<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)
	<< "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<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