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https://github.com/ceres-solver/ceres-solver.git
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125a0e9be5
Manifolds are now part of the public API and co-exist with LocalParameterizations. 1. Add Manifolds to the Problem API. a. AddParameterBlock(double*, int, Manifold*) b. SetParameterization(double*, Manifold*) b. GetManifold(const double*) c. HasManifold(const double*) 2. Internally Ceres now only uses Manifolds. When the user uses a LocalParameterization, it is wrapped in a ManifoldAdapter. 3. To preserve the API semantics while keeping the internals clean we need a new map in ProblemImpl which stores the association between parameter blocks and local parameterizations. This is temporary, it will go away once this transition is complete. 4. There are NO algorithmic changes, as in we are not using any of the expanded interface of the Manifold objects yet. That will come later. 5. All tests that use LocalParameterization have been duplicated to use Manifolds, and when this transition is complete the LocalParameterization based tests will be deleted. 6. Public documentation for the API has been updated. Deprecation notices to the documentation as well as C++ annotations will come later. 7. Similar changes have been made to GradientProblem. Change-Id: I8e03c8ced6e141876ef3eca5740c113afa788f0c
564 lines
20 KiB
C++
564 lines
20 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/loss_function.h"
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#include "ceres/manifold.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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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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const std::vector<ParameterBlock*>& Program::parameter_blocks() const {
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return parameter_blocks_;
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}
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const std::vector<ResidualBlock*>& Program::residual_blocks() const {
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return residual_blocks_;
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}
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std::vector<ParameterBlock*>* Program::mutable_parameter_blocks() {
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return ¶meter_blocks_;
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}
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std::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]->TangentSize();
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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]->TangentSize();
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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]->TangentSize();
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}
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return true;
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}
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bool Program::ParameterBlocksAreFinite(std::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,
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size,
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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(std::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,
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size,
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j,
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lower_bound,
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parameters[j],
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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,
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size,
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j,
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lower_bound,
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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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std::vector<double*>* removed_parameter_blocks,
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double* fixed_cost,
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std::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(
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removed_parameter_blocks, fixed_cost, error)) {
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return nullptr;
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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(std::vector<double*>* removed_parameter_blocks,
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double* fixed_cost,
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std::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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bool need_to_call_prepare_for_evaluation = evaluation_callback_ != nullptr;
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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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// This is an exceedingly rare case, where the user has residual
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// blocks which are effectively constant but they are also
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// performance sensitive enough to add an EvaluationCallback.
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//
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// In this case before we evaluate the cost of the constant
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// residual blocks, we must call
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// EvaluationCallback::PrepareForEvaluation(). Because this call
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// can be costly, we only call this if we actually encounter a
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// residual block with all constant parameter blocks.
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//
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// It is worth nothing that there is a minor inefficiency here,
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// that the iteration 0 of TrustRegionMinimizer will also cause
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// PrepareForEvaluation to be called on the same point, but with
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// evaluate_jacobians = true. We could try and optimize this here,
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// but given the rarity of this case, the additional complexity
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// and long range dependency is not worth it.
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if (need_to_call_prepare_for_evaluation) {
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constexpr bool kNewPoint = true;
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constexpr bool kDoNotEvaluateJacobians = false;
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evaluation_callback_->PrepareForEvaluation(kDoNotEvaluateJacobians,
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kNewPoint);
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need_to_call_prepare_for_evaluation = false;
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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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nullptr,
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nullptr,
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residual_block_evaluate_scratch.get())) {
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*error = StringPrintf(
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"Evaluation of the residual %d failed during "
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"removal of fixed residual blocks.",
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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) && (NumParameterBlocks() == 0)) ||
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((NumResidualBlocks() != 0) && (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 std::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(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 { return residual_blocks_.size(); }
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int Program::NumParameterBlocks() const { return parameter_blocks_.size(); }
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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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}
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return num_residuals;
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}
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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;
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}
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|
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int Program::NumEffectiveParameters() 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]->TangentSize();
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}
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return num_parameters;
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|
}
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|
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// TODO(sameeragarwal): The following methods should just be updated
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// incrementally and the values cached, rather than the linear
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// complexity we have right now on every call.
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int Program::MaxScratchDoublesNeededForEvaluate() const {
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|
// Compute the scratch space needed for evaluate.
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|
int max_scratch_bytes_for_evaluate = 0;
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|
for (int i = 0; i < residual_blocks_.size(); ++i) {
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|
max_scratch_bytes_for_evaluate =
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|
std::max(max_scratch_bytes_for_evaluate,
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|
residual_blocks_[i]->NumScratchDoublesForEvaluate());
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|
}
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return max_scratch_bytes_for_evaluate;
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|
}
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|
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int Program::MaxDerivativesPerResidualBlock() const {
|
|
int max_derivatives = 0;
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|
for (int i = 0; i < residual_blocks_.size(); ++i) {
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|
int derivatives = 0;
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|
ResidualBlock* residual_block = residual_blocks_[i];
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|
int num_parameters = residual_block->NumParameterBlocks();
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|
for (int j = 0; j < num_parameters; ++j) {
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derivatives += residual_block->NumResiduals() *
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|
residual_block->parameter_blocks()[j]->TangentSize();
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|
}
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|
max_derivatives = std::max(max_derivatives, derivatives);
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|
}
|
|
return max_derivatives;
|
|
}
|
|
|
|
int Program::MaxParametersPerResidualBlock() const {
|
|
int max_parameters = 0;
|
|
for (int i = 0; i < residual_blocks_.size(); ++i) {
|
|
max_parameters =
|
|
std::max(max_parameters, residual_blocks_[i]->NumParameterBlocks());
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|
}
|
|
return max_parameters;
|
|
}
|
|
|
|
int Program::MaxResidualsPerResidualBlock() const {
|
|
int max_residuals = 0;
|
|
for (int i = 0; i < residual_blocks_.size(); ++i) {
|
|
max_residuals =
|
|
std::max(max_residuals, residual_blocks_[i]->NumResiduals());
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|
}
|
|
return max_residuals;
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|
}
|
|
|
|
std::string Program::ToString() const {
|
|
std::string ret = "Program dump\n";
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|
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
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