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

 // Ceres Solver - A fast non-linear least squares minimizer
 // Copyright 2015 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 <iterator>
 #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 {
 namespace internal {

 using std::make_pair;
 using std::pair;
 using std::vector;
 using std::adjacent_find;

 void CompressedRowJacobianWriter::PopulateJacobianRowAndColumnBlockVectors(
     const Program* program, CompressedRowSparseMatrix* jacobian) {
   const vector<ParameterBlock*>& parameter_blocks =
       program->parameter_blocks();
   vector<int>& col_blocks = *(jacobian->mutable_col_blocks());
   col_blocks.resize(parameter_blocks.size());
   for (int i = 0; i < parameter_blocks.size(); ++i) {
     col_blocks[i] = parameter_blocks[i]->LocalSize();
   }

   const vector<ResidualBlock*>& residual_blocks =
       program->residual_blocks();
   vector<int>& row_blocks = *(jacobian->mutable_row_blocks());
   row_blocks.resize(residual_blocks.size());
   for (int i = 0; i < residual_blocks.size(); ++i) {
     row_blocks[i] = residual_blocks[i]->NumResiduals();
   }
 }

 void CompressedRowJacobianWriter::GetOrderedParameterBlocks(
       const Program* program,
       int residual_id,
       vector<pair<int, int>>* evaluated_jacobian_blocks) {
   const ResidualBlock* residual_block =
       program->residual_blocks()[residual_id];
   const int num_parameter_blocks = residual_block->NumParameterBlocks();

   for (int j = 0; j < num_parameter_blocks; ++j) {
     const ParameterBlock* parameter_block =
         residual_block->parameter_blocks()[j];
     if (!parameter_block->IsConstant()) {
       evaluated_jacobian_blocks->push_back(
           make_pair(parameter_block->index(), j));
     }
   }
   sort(evaluated_jacobian_blocks->begin(), evaluated_jacobian_blocks->end());
 }

 SparseMatrix* CompressedRowJacobianWriter::CreateJacobian() const {
   const vector<ResidualBlock*>& 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 (int i = 0; i < residual_blocks.size(); ++i) {
     ResidualBlock* residual_block = residual_blocks[i];
     const int num_residuals = residual_block->NumResiduals();
     const int num_parameter_blocks = residual_block->NumParameterBlocks();
     for (int j = 0; j < num_parameter_blocks; ++j) {
       ParameterBlock* parameter_block = residual_block->parameter_blocks()[j];
       if (!parameter_block->IsConstant()) {
         num_jacobian_nonzeros += num_residuals * parameter_block->LocalSize();
       }
     }
   }

   // 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.
   CompressedRowSparseMatrix* jacobian =
       new 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 (int i = 0; i < residual_blocks.size(); ++i) {
     const ResidualBlock* residual_block = residual_blocks[i];
     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;
     vector<int> parameter_indices;
     for (int j = 0; j < num_parameter_blocks; ++j) {
       ParameterBlock* parameter_block = residual_block->parameter_blocks()[j];
       if (!parameter_block->IsConstant()) {
         parameter_indices.push_back(parameter_block->index());
         num_derivatives += parameter_block->LocalSize();
       }
     }

     // Sort the parameters by their position in the state vector.
     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) {
         ParameterBlock* 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 j = 0; j < parameter_indices.size(); ++j) {
       ParameterBlock* parameter_block =
           program_->parameter_blocks()[parameter_indices[j]];
       const int parameter_block_size = parameter_block->LocalSize();

       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);

   return jacobian;
 }

 void CompressedRowJacobianWriter::Write(int residual_id,
                                         int residual_offset,
                                         double **jacobians,
                                         SparseMatrix* base_jacobian) {
   CompressedRowSparseMatrix* jacobian =
       down_cast<CompressedRowSparseMatrix*>(base_jacobian);

   double* jacobian_values = jacobian->mutable_values();
   const int* jacobian_rows = jacobian->rows();

   const ResidualBlock* residual_block =
       program_->residual_blocks()[residual_id];
   const int num_residuals = residual_block->NumResiduals();

   vector<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 (int i = 0; i < evaluated_jacobian_blocks.size(); ++i) {
     const ParameterBlock* parameter_block =
         program_->parameter_blocks()[evaluated_jacobian_blocks[i].first];
     const int argument = evaluated_jacobian_blocks[i].second;
     const int parameter_block_size = parameter_block->LocalSize();

     // 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 internal
 }  // namespace ceres
	// Ceres Solver - A fast non-linear least squares minimizer
	// Copyright 2015 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 <iterator>
	#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 {
	namespace internal {

	using std::make_pair;
	using std::pair;
	using std::vector;
	using std::adjacent_find;

	void CompressedRowJacobianWriter::PopulateJacobianRowAndColumnBlockVectors(
	const Program* program, CompressedRowSparseMatrix* jacobian) {
	const vector<ParameterBlock*>& parameter_blocks =
	program->parameter_blocks();
	vector<int>& col_blocks = *(jacobian->mutable_col_blocks());
	col_blocks.resize(parameter_blocks.size());
	for (int i = 0; i < parameter_blocks.size(); ++i) {
	col_blocks[i] = parameter_blocks[i]->LocalSize();
	}

	const vector<ResidualBlock*>& residual_blocks =
	program->residual_blocks();
	vector<int>& row_blocks = *(jacobian->mutable_row_blocks());
	row_blocks.resize(residual_blocks.size());
	for (int i = 0; i < residual_blocks.size(); ++i) {
	row_blocks[i] = residual_blocks[i]->NumResiduals();
	}
	}

	void CompressedRowJacobianWriter::GetOrderedParameterBlocks(
	const Program* program,
	int residual_id,
	vector<pair<int, int>>* evaluated_jacobian_blocks) {
	const ResidualBlock* residual_block =
	program->residual_blocks()[residual_id];
	const int num_parameter_blocks = residual_block->NumParameterBlocks();

	for (int j = 0; j < num_parameter_blocks; ++j) {
	const ParameterBlock* parameter_block =
	residual_block->parameter_blocks()[j];
	if (!parameter_block->IsConstant()) {
	evaluated_jacobian_blocks->push_back(
	make_pair(parameter_block->index(), j));
	}
	}
	sort(evaluated_jacobian_blocks->begin(), evaluated_jacobian_blocks->end());
	}

	SparseMatrix* CompressedRowJacobianWriter::CreateJacobian() const {
	const vector<ResidualBlock*>& 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 (int i = 0; i < residual_blocks.size(); ++i) {
	ResidualBlock* residual_block = residual_blocks[i];
	const int num_residuals = residual_block->NumResiduals();
	const int num_parameter_blocks = residual_block->NumParameterBlocks();
	for (int j = 0; j < num_parameter_blocks; ++j) {
	ParameterBlock* parameter_block = residual_block->parameter_blocks()[j];
	if (!parameter_block->IsConstant()) {
	num_jacobian_nonzeros += num_residuals * parameter_block->LocalSize();
	}
	}
	}

	// 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.
	CompressedRowSparseMatrix* jacobian =
	new 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 (int i = 0; i < residual_blocks.size(); ++i) {
	const ResidualBlock* residual_block = residual_blocks[i];
	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;
	vector<int> parameter_indices;
	for (int j = 0; j < num_parameter_blocks; ++j) {
	ParameterBlock* parameter_block = residual_block->parameter_blocks()[j];
	if (!parameter_block->IsConstant()) {
	parameter_indices.push_back(parameter_block->index());
	num_derivatives += parameter_block->LocalSize();
	}
	}

	// Sort the parameters by their position in the state vector.
	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) {
	ParameterBlock* 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 j = 0; j < parameter_indices.size(); ++j) {
	ParameterBlock* parameter_block =
	program_->parameter_blocks()[parameter_indices[j]];
	const int parameter_block_size = parameter_block->LocalSize();

	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);

	return jacobian;
	}

	void CompressedRowJacobianWriter::Write(int residual_id,
	int residual_offset,
	double **jacobians,
	SparseMatrix* base_jacobian) {
	CompressedRowSparseMatrix* jacobian =
	down_cast<CompressedRowSparseMatrix*>(base_jacobian);

	double* jacobian_values = jacobian->mutable_values();
	const int* jacobian_rows = jacobian->rows();

	const ResidualBlock* residual_block =
	program_->residual_blocks()[residual_id];
	const int num_residuals = residual_block->NumResiduals();

	vector<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 (int i = 0; i < evaluated_jacobian_blocks.size(); ++i) {
	const ParameterBlock* parameter_block =
	program_->parameter_blocks()[evaluated_jacobian_blocks[i].first];
	const int argument = evaluated_jacobian_blocks[i].second;
	const int parameter_block_size = parameter_block->LocalSize();

	// 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 internal
	} // namespace ceres