mirror of
https://github.com/ceres-solver/ceres-solver.git
synced 2026-08-29 08:34:37 +08:00
03caeed1c6
Replace ceres::String* with their more modern and performant absl strings library equivalent and delete our string manipulation library. Change-Id: Iecbdba9864e0abf329778f81fdc0708f78f7594f
570 lines
20 KiB
C++
570 lines
20 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/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 <string>
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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 "absl/strings/str_cat.h"
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#include "absl/strings/str_format.h"
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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/export.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/parallel_for.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::internal {
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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 (auto* parameter_block : parameter_blocks_) {
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if (!parameter_block->IsConstant() && !parameter_block->SetState(state)) {
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return false;
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}
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state += parameter_block->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 (auto* parameter_block : parameter_blocks_) {
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parameter_block->GetState(state);
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state += parameter_block->Size();
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}
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}
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void Program::CopyParameterBlockStateToUserState() {
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for (auto* parameter_block : parameter_blocks_) {
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parameter_block->GetState(parameter_block->mutable_user_state());
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}
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}
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bool Program::SetParameterBlockStatePtrsToUserStatePtrs() {
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for (auto* parameter_block : parameter_blocks_) {
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if (!parameter_block->IsConstant() &&
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!parameter_block->SetState(parameter_block->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,
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ContextImpl* context,
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int num_threads) const {
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std::atomic<bool> abort(false);
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auto* parameter_blocks = parameter_blocks_.data();
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ParallelFor(
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context,
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0,
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parameter_blocks_.size(),
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num_threads,
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[&abort, state, delta, state_plus_delta, parameter_blocks](int block_id) {
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if (abort) {
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return;
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}
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auto parameter_block = parameter_blocks[block_id];
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auto block_state = state + parameter_block->state_offset();
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auto block_delta = delta + parameter_block->delta_offset();
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auto block_state_plus_delta =
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state_plus_delta + parameter_block->state_offset();
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if (!parameter_block->Plus(
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block_state, block_delta, block_state_plus_delta)) {
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abort = true;
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}
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});
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return abort == false;
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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 (auto* residual_block : residual_blocks_) {
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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 (auto* parameter_block : parameter_blocks_) {
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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 = absl::StrFormat(
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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 (auto* parameter_block : parameter_blocks_) {
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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 (auto* parameter_block : parameter_blocks_) {
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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 = absl::StrFormat(
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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 = absl::StrFormat(
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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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std::unique_ptr<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 = std::make_unique<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;
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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 =
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std::make_unique<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 (auto* parameter_block : parameter_blocks_) {
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parameter_block->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 = absl::StrFormat(
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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 (auto* parameter_block : parameter_blocks_) {
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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 (auto* residual_block : residual_blocks_) {
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num_residuals += residual_block->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 (auto* parameter_block : parameter_blocks_) {
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|
num_parameters += parameter_block->Size();
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|
}
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|
return num_parameters;
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|
}
|
|
|
|
int Program::NumEffectiveParameters() const {
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|
int num_parameters = 0;
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|
for (auto* parameter_block : parameter_blocks_) {
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|
num_parameters += parameter_block->TangentSize();
|
|
}
|
|
return num_parameters;
|
|
}
|
|
|
|
// TODO(sameeragarwal): The following methods should just be updated
|
|
// incrementally and the values cached, rather than the linear
|
|
// complexity we have right now on every call.
|
|
int Program::MaxScratchDoublesNeededForEvaluate() const {
|
|
// Compute the scratch space needed for evaluate.
|
|
int max_scratch_bytes_for_evaluate = 0;
|
|
for (auto* residual_block : residual_blocks_) {
|
|
max_scratch_bytes_for_evaluate =
|
|
std::max(max_scratch_bytes_for_evaluate,
|
|
residual_block->NumScratchDoublesForEvaluate());
|
|
}
|
|
return max_scratch_bytes_for_evaluate;
|
|
}
|
|
|
|
int Program::MaxDerivativesPerResidualBlock() const {
|
|
int max_derivatives = 0;
|
|
for (auto* residual_block : residual_blocks_) {
|
|
int derivatives = 0;
|
|
int num_parameters = residual_block->NumParameterBlocks();
|
|
for (int j = 0; j < num_parameters; ++j) {
|
|
derivatives += residual_block->NumResiduals() *
|
|
residual_block->parameter_blocks()[j]->TangentSize();
|
|
}
|
|
max_derivatives = std::max(max_derivatives, derivatives);
|
|
}
|
|
return max_derivatives;
|
|
}
|
|
|
|
int Program::MaxParametersPerResidualBlock() const {
|
|
int max_parameters = 0;
|
|
for (auto* residual_block : residual_blocks_) {
|
|
max_parameters =
|
|
std::max(max_parameters, residual_block->NumParameterBlocks());
|
|
}
|
|
return max_parameters;
|
|
}
|
|
|
|
int Program::MaxResidualsPerResidualBlock() const {
|
|
int max_residuals = 0;
|
|
for (auto* residual_block : residual_blocks_) {
|
|
max_residuals = std::max(max_residuals, residual_block->NumResiduals());
|
|
}
|
|
return max_residuals;
|
|
}
|
|
|
|
std::string Program::ToString() const {
|
|
std::string ret = "Program dump\n";
|
|
absl::StrAppendFormat(
|
|
&ret, "Number of parameter blocks: %d\n", NumParameterBlocks());
|
|
absl::StrAppendFormat(&ret, "Number of parameters: %d\n", NumParameters());
|
|
absl::StrAppend(&ret, "Parameters:\n");
|
|
for (int i = 0; i < parameter_blocks_.size(); ++i) {
|
|
absl::StrAppendFormat(
|
|
&ret, "%d: %s\n", i, parameter_blocks_[i]->ToString());
|
|
}
|
|
return ret;
|
|
}
|
|
|
|
} // namespace ceres::internal
|