| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239 | // 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::adjacent_find;using std::make_pair;using std::pair;using std::vector;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
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