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https://github.com/ceres-solver/ceres-solver.git
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487c1aa51f
https://github.com/ceres-solver/ceres-solver/issues/270 Detailed list of changes: 1. Add SUBSET to the PreconditionerType enum. 2. Add Solver::Options::residual_blocks_for_subset_preconditioner 3. Integrate SubsetPreconditioner into the CGNR solver. 4. Add the reordering logic needed for this to TrustRegionPreprocessor. 5. Expect CreateJacobianBlockTranspose to take the starting row block so that we can work with subparts of the Jacobian matrix. 6. Extend the denoising example to use this preconditioner. As an illustration of its performance, we consider the performance of denoising -input ../data/ceres_noisy.pgm --foe_file ../data/5x5.foe tl;dr For the same cost, SPARSE_NORMAL_CHOLESKY - 81s CGNR + JACOBI - 718s CGNR + SUBSET - 57s SPARSE_NORMAL_CHOLESKY ====================== Cost: Initial 2.317806e+05 Final 2.232323e+04 Change 2.094574e+05 Minimizer iterations 10 Successful steps 10 Unsuccessful steps 0 Time (in seconds): Preprocessor 2.999746 Residual only evaluation 2.306811 (10) Jacobian & residual evaluation 7.421727 (10) Linear solver 65.517273 (10) Minimizer 78.731011 Postprocessor 0.026079 Total 81.756836 Termination: CONVERGENCE (Function tolerance reached. |cost_change|/cost: 8.573046e-04 <= 1.000000e-03) CGNR + JACOBI ============= Cost: Initial 2.317806e+05 Final 2.232344e+04 Change 2.094572e+05 Minimizer iterations 10 Successful steps 10 Unsuccessful steps 0 Time (in seconds): Preprocessor 0.648814 Residual only evaluation 2.297607 (10) Jacobian & residual evaluation 7.327886 (10) Linear solver 699.601248 (10) Minimizer 712.419493 Postprocessor 0.024014 Total 713.092321 Termination: CONVERGENCE (Function tolerance reached. |cost_change|/cost: 8.528538e-04 <= 1.000000e-03) CGNR + SUBSET (random 20% residuals used for the preconditioner) =============================================================== Cost: Initial 2.317806e+05 Final 2.232327e+04 Change 2.094574e+05 Minimizer iterations 10 Successful steps 10 Unsuccessful steps 0 Time (in seconds): Preprocessor 1.472743 Residual only evaluation 2.428315 (10) Jacobian & residual evaluation 7.367796 (10) Linear solver 42.585999 (10) Minimizer 55.664459 Postprocessor 0.024098 Total 57.161301 Termination: CONVERGENCE (Function tolerance reached. |cost_change|/cost: 8.538277e-04 <= 1.000000e-03) Change-Id: Ifb011408bd53edbb9439b0b7345649a38f999e18
534 lines
18 KiB
C++
534 lines
18 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2015 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/program.h"
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#include <algorithm>
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#include <map>
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#include <memory>
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#include <vector>
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#include "ceres/array_utils.h"
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#include "ceres/casts.h"
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#include "ceres/compressed_row_sparse_matrix.h"
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#include "ceres/cost_function.h"
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#include "ceres/evaluator.h"
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#include "ceres/internal/port.h"
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#include "ceres/local_parameterization.h"
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#include "ceres/loss_function.h"
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#include "ceres/map_util.h"
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#include "ceres/parameter_block.h"
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#include "ceres/problem.h"
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#include "ceres/residual_block.h"
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#include "ceres/stl_util.h"
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#include "ceres/triplet_sparse_matrix.h"
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namespace ceres {
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namespace internal {
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using std::max;
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using std::set;
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using std::string;
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using std::vector;
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Program::Program() {}
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Program::Program(const Program& program)
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: parameter_blocks_(program.parameter_blocks_),
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residual_blocks_(program.residual_blocks_),
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evaluation_callback_(program.evaluation_callback_){
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}
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const vector<ParameterBlock*>& Program::parameter_blocks() const {
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return parameter_blocks_;
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}
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const vector<ResidualBlock*>& Program::residual_blocks() const {
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return residual_blocks_;
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}
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vector<ParameterBlock*>* Program::mutable_parameter_blocks() {
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return ¶meter_blocks_;
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}
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vector<ResidualBlock*>* Program::mutable_residual_blocks() {
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return &residual_blocks_;
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}
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EvaluationCallback* Program::mutable_evaluation_callback() {
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return evaluation_callback_;
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}
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bool Program::StateVectorToParameterBlocks(const double *state) {
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for (int i = 0; i < parameter_blocks_.size(); ++i) {
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if (!parameter_blocks_[i]->IsConstant() &&
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!parameter_blocks_[i]->SetState(state)) {
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return false;
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}
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state += parameter_blocks_[i]->Size();
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}
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return true;
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}
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void Program::ParameterBlocksToStateVector(double *state) const {
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for (int i = 0; i < parameter_blocks_.size(); ++i) {
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parameter_blocks_[i]->GetState(state);
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state += parameter_blocks_[i]->Size();
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}
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}
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void Program::CopyParameterBlockStateToUserState() {
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for (int i = 0; i < parameter_blocks_.size(); ++i) {
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parameter_blocks_[i]->GetState(parameter_blocks_[i]->mutable_user_state());
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}
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}
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bool Program::SetParameterBlockStatePtrsToUserStatePtrs() {
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for (int i = 0; i < parameter_blocks_.size(); ++i) {
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if (!parameter_blocks_[i]->IsConstant() &&
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!parameter_blocks_[i]->SetState(parameter_blocks_[i]->user_state())) {
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return false;
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}
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}
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return true;
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}
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bool Program::Plus(const double* state,
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const double* delta,
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double* state_plus_delta) const {
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for (int i = 0; i < parameter_blocks_.size(); ++i) {
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if (!parameter_blocks_[i]->Plus(state, delta, state_plus_delta)) {
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return false;
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}
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state += parameter_blocks_[i]->Size();
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delta += parameter_blocks_[i]->LocalSize();
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state_plus_delta += parameter_blocks_[i]->Size();
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}
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return true;
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}
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void Program::SetParameterOffsetsAndIndex() {
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// Set positions for all parameters appearing as arguments to residuals to one
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// past the end of the parameter block array.
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for (int i = 0; i < residual_blocks_.size(); ++i) {
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ResidualBlock* residual_block = residual_blocks_[i];
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for (int j = 0; j < residual_block->NumParameterBlocks(); ++j) {
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residual_block->parameter_blocks()[j]->set_index(-1);
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}
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}
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// For parameters that appear in the program, set their position and offset.
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int state_offset = 0;
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int delta_offset = 0;
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for (int i = 0; i < parameter_blocks_.size(); ++i) {
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parameter_blocks_[i]->set_index(i);
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parameter_blocks_[i]->set_state_offset(state_offset);
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parameter_blocks_[i]->set_delta_offset(delta_offset);
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state_offset += parameter_blocks_[i]->Size();
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delta_offset += parameter_blocks_[i]->LocalSize();
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}
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}
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bool Program::IsValid() const {
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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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if (residual_block->index() != i) {
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LOG(WARNING) << "Residual block: " << i
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<< " has incorrect index: " << residual_block->index();
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return false;
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}
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}
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int state_offset = 0;
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int delta_offset = 0;
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for (int i = 0; i < parameter_blocks_.size(); ++i) {
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const ParameterBlock* parameter_block = parameter_blocks_[i];
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if (parameter_block->index() != i ||
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parameter_block->state_offset() != state_offset ||
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parameter_block->delta_offset() != delta_offset) {
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LOG(WARNING) << "Parameter block: " << i
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<< "has incorrect indexing information: "
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<< parameter_block->ToString();
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return false;
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}
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state_offset += parameter_blocks_[i]->Size();
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delta_offset += parameter_blocks_[i]->LocalSize();
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}
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return true;
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}
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bool Program::ParameterBlocksAreFinite(string* message) const {
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CHECK(message != nullptr);
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for (int i = 0; i < parameter_blocks_.size(); ++i) {
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const ParameterBlock* parameter_block = parameter_blocks_[i];
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const double* array = parameter_block->user_state();
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const int size = parameter_block->Size();
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const int invalid_index = FindInvalidValue(size, array);
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if (invalid_index != size) {
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*message = StringPrintf(
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"ParameterBlock: %p with size %d has at least one invalid value.\n"
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"First invalid value is at index: %d.\n"
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"Parameter block values: ",
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array, size, invalid_index);
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AppendArrayToString(size, array, message);
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return false;
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}
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}
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return true;
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}
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bool Program::IsBoundsConstrained() const {
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for (int i = 0; i < parameter_blocks_.size(); ++i) {
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const ParameterBlock* parameter_block = parameter_blocks_[i];
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if (parameter_block->IsConstant()) {
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continue;
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}
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const int size = parameter_block->Size();
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for (int j = 0; j < size; ++j) {
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const double lower_bound = parameter_block->LowerBoundForParameter(j);
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const double upper_bound = parameter_block->UpperBoundForParameter(j);
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if (lower_bound > -std::numeric_limits<double>::max() ||
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upper_bound < std::numeric_limits<double>::max()) {
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return true;
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}
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}
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}
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return false;
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}
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bool Program::IsFeasible(string* message) const {
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CHECK(message != nullptr);
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for (int i = 0; i < parameter_blocks_.size(); ++i) {
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const ParameterBlock* parameter_block = parameter_blocks_[i];
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const double* parameters = parameter_block->user_state();
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const int size = parameter_block->Size();
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if (parameter_block->IsConstant()) {
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// Constant parameter blocks must start in the feasible region
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// to ultimately produce a feasible solution, since Ceres cannot
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// change them.
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for (int j = 0; j < size; ++j) {
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const double lower_bound = parameter_block->LowerBoundForParameter(j);
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const double upper_bound = parameter_block->UpperBoundForParameter(j);
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if (parameters[j] < lower_bound || parameters[j] > upper_bound) {
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*message = StringPrintf(
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"ParameterBlock: %p with size %d has at least one infeasible "
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"value."
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"\nFirst infeasible value is at index: %d."
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"\nLower bound: %e, value: %e, upper bound: %e"
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"\nParameter block values: ",
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parameters, size, j, lower_bound, parameters[j], upper_bound);
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AppendArrayToString(size, parameters, message);
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return false;
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}
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}
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} else {
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// Variable parameter blocks must have non-empty feasible
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// regions, otherwise there is no way to produce a feasible
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// solution.
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for (int j = 0; j < size; ++j) {
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const double lower_bound = parameter_block->LowerBoundForParameter(j);
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const double upper_bound = parameter_block->UpperBoundForParameter(j);
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if (lower_bound >= upper_bound) {
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*message = StringPrintf(
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"ParameterBlock: %p with size %d has at least one infeasible "
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"bound."
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"\nFirst infeasible bound is at index: %d."
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"\nLower bound: %e, upper bound: %e"
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"\nParameter block values: ",
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parameters, size, j, lower_bound, upper_bound);
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AppendArrayToString(size, parameters, message);
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return false;
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}
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}
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}
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}
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return true;
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}
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Program* Program::CreateReducedProgram(
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vector<double*>* removed_parameter_blocks,
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double* fixed_cost,
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string* error) const {
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CHECK(removed_parameter_blocks != nullptr);
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CHECK(fixed_cost != nullptr);
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CHECK(error != nullptr);
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std::unique_ptr<Program> reduced_program(new Program(*this));
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if (!reduced_program->RemoveFixedBlocks(removed_parameter_blocks,
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fixed_cost,
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error)) {
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return NULL;
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}
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reduced_program->SetParameterOffsetsAndIndex();
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return reduced_program.release();
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}
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bool Program::RemoveFixedBlocks(vector<double*>* removed_parameter_blocks,
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double* fixed_cost,
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string* error) {
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CHECK(removed_parameter_blocks != nullptr);
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CHECK(fixed_cost != nullptr);
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CHECK(error != nullptr);
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std::unique_ptr<double[]> residual_block_evaluate_scratch;
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residual_block_evaluate_scratch.reset(
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new double[MaxScratchDoublesNeededForEvaluate()]);
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*fixed_cost = 0.0;
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// Mark all the parameters as unused. Abuse the index member of the
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// parameter blocks for the marking.
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for (int i = 0; i < parameter_blocks_.size(); ++i) {
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parameter_blocks_[i]->set_index(-1);
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}
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// Filter out residual that have all-constant parameters, and mark
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// all the parameter blocks that appear in residuals.
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int num_active_residual_blocks = 0;
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for (int i = 0; i < residual_blocks_.size(); ++i) {
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ResidualBlock* residual_block = residual_blocks_[i];
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int num_parameter_blocks = residual_block->NumParameterBlocks();
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// Determine if the residual block is fixed, and also mark varying
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// parameters that appear in the residual block.
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bool all_constant = true;
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for (int k = 0; k < num_parameter_blocks; k++) {
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ParameterBlock* parameter_block = residual_block->parameter_blocks()[k];
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if (!parameter_block->IsConstant()) {
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all_constant = false;
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parameter_block->set_index(1);
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}
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}
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if (!all_constant) {
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residual_blocks_[num_active_residual_blocks++] = residual_block;
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continue;
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}
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// The residual is constant and will be removed, so its cost is
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// added to the variable fixed_cost.
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double cost = 0.0;
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if (!residual_block->Evaluate(true,
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&cost,
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NULL,
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NULL,
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residual_block_evaluate_scratch.get())) {
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*error = StringPrintf("Evaluation of the residual %d failed during "
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"removal of fixed residual blocks.", i);
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return false;
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}
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*fixed_cost += cost;
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}
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residual_blocks_.resize(num_active_residual_blocks);
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// Filter out unused or fixed parameter blocks.
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int num_active_parameter_blocks = 0;
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removed_parameter_blocks->clear();
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for (int i = 0; i < parameter_blocks_.size(); ++i) {
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ParameterBlock* parameter_block = parameter_blocks_[i];
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if (parameter_block->index() == -1) {
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removed_parameter_blocks->push_back(
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parameter_block->mutable_user_state());
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} else {
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parameter_blocks_[num_active_parameter_blocks++] = parameter_block;
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}
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}
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parameter_blocks_.resize(num_active_parameter_blocks);
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if (!(((NumResidualBlocks() == 0) &&
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(NumParameterBlocks() == 0)) ||
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((NumResidualBlocks() != 0) &&
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(NumParameterBlocks() != 0)))) {
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*error = "Congratulations, you found a bug in Ceres. Please report it.";
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return false;
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}
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return true;
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}
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bool Program::IsParameterBlockSetIndependent(
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const set<double*>& independent_set) const {
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// Loop over each residual block and ensure that no two parameter
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// blocks in the same residual block are part of
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// parameter_block_ptrs as that would violate the assumption that it
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// is an independent set in the Hessian matrix.
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for (const ResidualBlock* residual_block : residual_blocks_) {
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ParameterBlock* const* parameter_blocks =
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residual_block->parameter_blocks();
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const int num_parameter_blocks = residual_block->NumParameterBlocks();
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int count = 0;
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for (int i = 0; i < num_parameter_blocks; ++i) {
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count += independent_set.count(
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parameter_blocks[i]->mutable_user_state());
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}
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if (count > 1) {
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return false;
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}
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}
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return true;
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}
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std::unique_ptr<TripletSparseMatrix>
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Program::CreateJacobianBlockSparsityTranspose(int start_residual_block) const {
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// Matrix to store the block sparsity structure of the Jacobian.
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const int num_rows = NumParameterBlocks();
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const int num_cols = NumResidualBlocks() - start_residual_block;
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std::unique_ptr<TripletSparseMatrix> tsm(
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new TripletSparseMatrix(num_rows, num_cols, 10 * num_cols));
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int num_nonzeros = 0;
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int* rows = tsm->mutable_rows();
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int* cols = tsm->mutable_cols();
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double* values = tsm->mutable_values();
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for (int c = start_residual_block; c < residual_blocks_.size(); ++c) {
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const ResidualBlock* residual_block = residual_blocks_[c];
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const int num_parameter_blocks = residual_block->NumParameterBlocks();
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ParameterBlock* const* parameter_blocks =
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residual_block->parameter_blocks();
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for (int j = 0; j < num_parameter_blocks; ++j) {
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if (parameter_blocks[j]->IsConstant()) {
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continue;
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}
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// Re-size the matrix if needed.
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if (num_nonzeros >= tsm->max_num_nonzeros()) {
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tsm->set_num_nonzeros(num_nonzeros);
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tsm->Reserve(2 * num_nonzeros);
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rows = tsm->mutable_rows();
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cols = tsm->mutable_cols();
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values = tsm->mutable_values();
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}
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const int r = parameter_blocks[j]->index();
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rows[num_nonzeros] = r;
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cols[num_nonzeros] = c - start_residual_block;
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values[num_nonzeros] = 1.0;
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++num_nonzeros;
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}
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}
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tsm->set_num_nonzeros(num_nonzeros);
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return tsm;
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}
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int Program::NumResidualBlocks() const {
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return residual_blocks_.size();
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}
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int Program::NumParameterBlocks() const {
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return parameter_blocks_.size();
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}
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int Program::NumResiduals() const {
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int num_residuals = 0;
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|
for (int i = 0; i < residual_blocks_.size(); ++i) {
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|
num_residuals += residual_blocks_[i]->NumResiduals();
|
|
}
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|
return num_residuals;
|
|
}
|
|
|
|
int Program::NumParameters() const {
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|
int num_parameters = 0;
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|
for (int i = 0; i < parameter_blocks_.size(); ++i) {
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|
num_parameters += parameter_blocks_[i]->Size();
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|
}
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|
return num_parameters;
|
|
}
|
|
|
|
int Program::NumEffectiveParameters() const {
|
|
int num_parameters = 0;
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|
for (int i = 0; i < parameter_blocks_.size(); ++i) {
|
|
num_parameters += parameter_blocks_[i]->LocalSize();
|
|
}
|
|
return num_parameters;
|
|
}
|
|
|
|
int Program::MaxScratchDoublesNeededForEvaluate() const {
|
|
// Compute the scratch space needed for evaluate.
|
|
int max_scratch_bytes_for_evaluate = 0;
|
|
for (int i = 0; i < residual_blocks_.size(); ++i) {
|
|
max_scratch_bytes_for_evaluate =
|
|
max(max_scratch_bytes_for_evaluate,
|
|
residual_blocks_[i]->NumScratchDoublesForEvaluate());
|
|
}
|
|
return max_scratch_bytes_for_evaluate;
|
|
}
|
|
|
|
int Program::MaxDerivativesPerResidualBlock() const {
|
|
int max_derivatives = 0;
|
|
for (int i = 0; i < residual_blocks_.size(); ++i) {
|
|
int derivatives = 0;
|
|
ResidualBlock* residual_block = residual_blocks_[i];
|
|
int num_parameters = residual_block->NumParameterBlocks();
|
|
for (int j = 0; j < num_parameters; ++j) {
|
|
derivatives += residual_block->NumResiduals() *
|
|
residual_block->parameter_blocks()[j]->LocalSize();
|
|
}
|
|
max_derivatives = max(max_derivatives, derivatives);
|
|
}
|
|
return max_derivatives;
|
|
}
|
|
|
|
int Program::MaxParametersPerResidualBlock() const {
|
|
int max_parameters = 0;
|
|
for (int i = 0; i < residual_blocks_.size(); ++i) {
|
|
max_parameters = max(max_parameters,
|
|
residual_blocks_[i]->NumParameterBlocks());
|
|
}
|
|
return max_parameters;
|
|
}
|
|
|
|
int Program::MaxResidualsPerResidualBlock() const {
|
|
int max_residuals = 0;
|
|
for (int i = 0; i < residual_blocks_.size(); ++i) {
|
|
max_residuals = max(max_residuals, residual_blocks_[i]->NumResiduals());
|
|
}
|
|
return max_residuals;
|
|
}
|
|
|
|
string Program::ToString() const {
|
|
string ret = "Program dump\n";
|
|
ret += StringPrintf("Number of parameter blocks: %d\n", NumParameterBlocks());
|
|
ret += StringPrintf("Number of parameters: %d\n", NumParameters());
|
|
ret += "Parameters:\n";
|
|
for (int i = 0; i < parameter_blocks_.size(); ++i) {
|
|
ret += StringPrintf("%d: %s\n",
|
|
i, parameter_blocks_[i]->ToString().c_str());
|
|
}
|
|
return ret;
|
|
}
|
|
|
|
} // namespace internal
|
|
} // namespace ceres
|