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// 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
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//
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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//
// 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) << "Overflow 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)
<< "Overflow 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