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https://github.com/ceres-solver/ceres-solver.git
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0ca2db57c7
Change-Id: I0038f9c91dc70c422c01305dc10fca5a22a2f0d0
266 lines
11 KiB
C++
266 lines
11 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2023 Google Inc. All rights reserved.
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// http://ceres-solver.org/
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//
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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//
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// * Redistributions of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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// * Redistributions in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// * Neither the name of Google Inc. nor the names of its contributors may be
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// used to endorse or promote products derived from this software without
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// specific prior written permission.
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//
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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// POSSIBILITY OF SUCH DAMAGE.
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//
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// Author: keir@google.com (Keir Mierle)
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#include "ceres/block_jacobian_writer.h"
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#include <algorithm>
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#include <memory>
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#include <vector>
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#include "absl/log/check.h"
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#include "absl/log/log.h"
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#include "ceres/block_evaluate_preparer.h"
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#include "ceres/block_sparse_matrix.h"
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#include "ceres/internal/eigen.h"
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#include "ceres/internal/export.h"
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#include "ceres/parameter_block.h"
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#include "ceres/program.h"
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#include "ceres/residual_block.h"
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namespace ceres::internal {
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namespace {
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// Given the residual block ordering, build a lookup table to determine which
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// per-parameter jacobian goes where in the overall program jacobian.
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//
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// Since we expect to use a Schur type linear solver to solve the LM step, take
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// extra care to place the E blocks and the F blocks contiguously. E blocks are
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// the first num_eliminate_blocks parameter blocks as indicated by the parameter
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// block ordering. The remaining parameter blocks are the F blocks.
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//
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// In order to simplify handling block-sparse to CRS conversion, cells within
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// the row-block of non-partitioned matrix are stored in memory sequentially in
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// the order of increasing column-block id. In case of partitioned matrices,
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// cells corresponding to F sub-matrix are stored sequentially in the order of
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// increasing column-block id (with cells corresponding to E sub-matrix stored
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// separately).
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//
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// TODO(keir): Consider if we should use a boolean for each parameter block
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// instead of num_eliminate_blocks.
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bool BuildJacobianLayout(const Program& program,
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int num_eliminate_blocks,
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std::vector<int*>* jacobian_layout,
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std::vector<int>* jacobian_layout_storage) {
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const std::vector<ResidualBlock*>& residual_blocks =
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program.residual_blocks();
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// Iterate over all the active residual blocks and determine how many E blocks
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// are there. This will determine where the F blocks start in the jacobian
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// matrix. Also compute the number of jacobian blocks.
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unsigned int f_block_pos = 0;
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unsigned int num_jacobian_blocks = 0;
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for (auto* residual_block : residual_blocks) {
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const int num_residuals = residual_block->NumResiduals();
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const int num_parameter_blocks = residual_block->NumParameterBlocks();
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// Advance f_block_pos over each E block for this residual.
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for (int j = 0; j < num_parameter_blocks; ++j) {
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ParameterBlock* parameter_block = residual_block->parameter_blocks()[j];
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if (!parameter_block->IsConstant()) {
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// Only count blocks for active parameters.
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num_jacobian_blocks++;
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if (parameter_block->index() < num_eliminate_blocks) {
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f_block_pos += num_residuals * parameter_block->TangentSize();
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}
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}
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}
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if (num_jacobian_blocks > std::numeric_limits<int>::max()) {
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LOG(ERROR) << "Overflow error. Too many blocks in the jacobian matrix : "
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<< num_jacobian_blocks;
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return false;
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}
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}
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// We now know that the E blocks are laid out starting at zero, and the F
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// blocks are laid out starting at f_block_pos. Iterate over the residual
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// blocks again, and this time fill the jacobian_layout array with the
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// position information.
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jacobian_layout->resize(program.NumResidualBlocks());
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jacobian_layout_storage->resize(num_jacobian_blocks);
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int e_block_pos = 0;
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int* jacobian_pos = jacobian_layout_storage->data();
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std::vector<std::pair<int, int>> active_parameter_blocks;
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for (int i = 0; i < residual_blocks.size(); ++i) {
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const ResidualBlock* residual_block = residual_blocks[i];
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const int num_residuals = residual_block->NumResiduals();
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const int num_parameter_blocks = residual_block->NumParameterBlocks();
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(*jacobian_layout)[i] = jacobian_pos;
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// Cells from F sub-matrix are to be stored sequentially with increasing
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// column block id. For each non-constant parameter block, a pair of indices
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// (index in the list of active parameter blocks and index in the list of
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// all parameter blocks) is computed, and index pairs are sorted by the
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// index of corresponding column block id.
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active_parameter_blocks.clear();
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active_parameter_blocks.reserve(num_parameter_blocks);
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for (int j = 0; j < num_parameter_blocks; ++j) {
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ParameterBlock* parameter_block = residual_block->parameter_blocks()[j];
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if (parameter_block->IsConstant()) {
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continue;
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}
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const int k = active_parameter_blocks.size();
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active_parameter_blocks.emplace_back(k, j);
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}
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std::sort(active_parameter_blocks.begin(),
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active_parameter_blocks.end(),
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[&residual_block](const std::pair<int, int>& a,
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const std::pair<int, int>& b) {
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return residual_block->parameter_blocks()[a.second]->index() <
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residual_block->parameter_blocks()[b.second]->index();
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});
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// Cell positions for each active parameter block are filled in the order of
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// active parameter block indices sorted by columnd block index. This
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// guarantees that cells are laid out sequentially with increasing column
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// block indices.
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for (const auto& indices : active_parameter_blocks) {
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const auto [k, j] = indices;
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ParameterBlock* parameter_block = residual_block->parameter_blocks()[j];
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const int parameter_block_index = parameter_block->index();
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const int jacobian_block_size =
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num_residuals * parameter_block->TangentSize();
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if (parameter_block_index < num_eliminate_blocks) {
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jacobian_pos[k] = e_block_pos;
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e_block_pos += jacobian_block_size;
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} else {
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jacobian_pos[k] = static_cast<int>(f_block_pos);
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f_block_pos += jacobian_block_size;
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if (f_block_pos > std::numeric_limits<int>::max()) {
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LOG(ERROR)
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<< "Overflow error. Too many entries in the Jacobian matrix.";
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return false;
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}
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}
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}
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jacobian_pos += active_parameter_blocks.size();
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}
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return true;
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}
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} // namespace
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BlockJacobianWriter::BlockJacobianWriter(const Evaluator::Options& options,
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Program* program)
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: options_(options), program_(program) {
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CHECK_GE(options.num_eliminate_blocks, 0)
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<< "num_eliminate_blocks must be greater than 0.";
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jacobian_layout_is_valid_ = BuildJacobianLayout(*program,
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options.num_eliminate_blocks,
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&jacobian_layout_,
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&jacobian_layout_storage_);
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}
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// Create evaluate preparers that point directly into the final jacobian. This
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// makes the final Write() a nop.
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std::unique_ptr<BlockEvaluatePreparer[]>
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BlockJacobianWriter::CreateEvaluatePreparers(unsigned num_threads) {
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const int max_derivatives_per_residual_block =
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program_->MaxDerivativesPerResidualBlock();
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auto preparers = std::make_unique<BlockEvaluatePreparer[]>(num_threads);
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for (unsigned i = 0; i < num_threads; i++) {
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preparers[i].Init(jacobian_layout_.data(),
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max_derivatives_per_residual_block);
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}
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return preparers;
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}
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std::unique_ptr<SparseMatrix> BlockJacobianWriter::CreateJacobian() const {
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if (!jacobian_layout_is_valid_) {
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LOG(ERROR) << "Unable to create Jacobian matrix. Too many entries in the "
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"Jacobian matrix.";
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return nullptr;
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}
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auto* bs = new CompressedRowBlockStructure;
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const std::vector<ParameterBlock*>& parameter_blocks =
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program_->parameter_blocks();
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// Construct the column blocks.
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bs->cols.resize(parameter_blocks.size());
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for (int i = 0, cursor = 0; i < parameter_blocks.size(); ++i) {
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CHECK_NE(parameter_blocks[i]->index(), -1);
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CHECK(!parameter_blocks[i]->IsConstant());
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bs->cols[i].size = parameter_blocks[i]->TangentSize();
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bs->cols[i].position = cursor;
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cursor += bs->cols[i].size;
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}
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// Construct the cells in each row.
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const std::vector<ResidualBlock*>& residual_blocks =
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program_->residual_blocks();
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int row_block_position = 0;
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bs->rows.resize(residual_blocks.size());
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for (int i = 0; i < residual_blocks.size(); ++i) {
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const ResidualBlock* residual_block = residual_blocks[i];
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CompressedRow* row = &bs->rows[i];
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row->block.size = residual_block->NumResiduals();
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row->block.position = row_block_position;
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row_block_position += row->block.size;
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// Size the row by the number of active parameters in this residual.
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const int num_parameter_blocks = residual_block->NumParameterBlocks();
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int num_active_parameter_blocks = 0;
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for (int j = 0; j < num_parameter_blocks; ++j) {
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if (residual_block->parameter_blocks()[j]->index() != -1) {
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num_active_parameter_blocks++;
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}
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}
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row->cells.resize(num_active_parameter_blocks);
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// Add layout information for the active parameters in this row.
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for (int j = 0, k = 0; j < num_parameter_blocks; ++j) {
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const ParameterBlock* parameter_block =
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residual_block->parameter_blocks()[j];
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if (!parameter_block->IsConstant()) {
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Cell& cell = row->cells[k];
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cell.block_id = parameter_block->index();
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cell.position = jacobian_layout_[i][k];
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// Only increment k for active parameters, since there is only layout
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// information for active parameters.
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k++;
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}
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}
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std::sort(row->cells.begin(), row->cells.end(), CellLessThan);
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}
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return std::make_unique<BlockSparseMatrix>(
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bs, options_.sparse_linear_algebra_library_type == CUDA_SPARSE);
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}
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} // namespace ceres::internal
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