Files
ceres-solver/internal/ceres/problem_impl.cc
T
Sameer Agarwal 06bfe6ffac Remove OpenMP and No threading backends.
Since c++11, we can depend on C++ threads always being available.
With the recent work on the performance of CXX threading, the
additional complexity of maintaining multiple backends for some
minor performance delta is not worth it

https://github.com/ceres-solver/ceres-solver/issues/886

Change-Id: Idee480b22a498daec9c4366da8589aa58eaf36a1
2022-11-27 21:06:33 -08:00

904 lines
35 KiB
C++

// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2022 Google Inc. All rights reserved.
// http://ceres-solver.org/
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are met:
//
// * Redistributions of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
// * Redistributions in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
// * Neither the name of Google Inc. nor the names of its contributors may be
// used to endorse or promote products derived from this software without
// specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
// POSSIBILITY OF SUCH DAMAGE.
//
// Author: sameeragarwal@google.com (Sameer Agarwal)
// mierle@gmail.com (Keir Mierle)
#include "ceres/problem_impl.h"
#include <algorithm>
#include <cstddef>
#include <cstdint>
#include <iterator>
#include <memory>
#include <set>
#include <string>
#include <utility>
#include <vector>
#include "ceres/casts.h"
#include "ceres/compressed_row_jacobian_writer.h"
#include "ceres/compressed_row_sparse_matrix.h"
#include "ceres/context_impl.h"
#include "ceres/cost_function.h"
#include "ceres/crs_matrix.h"
#include "ceres/evaluation_callback.h"
#include "ceres/evaluator.h"
#include "ceres/internal/export.h"
#include "ceres/internal/fixed_array.h"
#include "ceres/loss_function.h"
#include "ceres/manifold.h"
#include "ceres/map_util.h"
#include "ceres/parameter_block.h"
#include "ceres/program.h"
#include "ceres/program_evaluator.h"
#include "ceres/residual_block.h"
#include "ceres/scratch_evaluate_preparer.h"
#include "ceres/stl_util.h"
#include "ceres/stringprintf.h"
#include "glog/logging.h"
namespace ceres::internal {
namespace {
// Returns true if two regions of memory, a and b, with sizes size_a and size_b
// respectively, overlap.
bool RegionsAlias(const double* a, int size_a, const double* b, int size_b) {
return (a < b) ? b < (a + size_a) : a < (b + size_b);
}
void CheckForNoAliasing(double* existing_block,
int existing_block_size,
double* new_block,
int new_block_size) {
CHECK(!RegionsAlias(
existing_block, existing_block_size, new_block, new_block_size))
<< "Aliasing detected between existing parameter block at memory "
<< "location " << existing_block << " and has size "
<< existing_block_size << " with new parameter "
<< "block that has memory address " << new_block << " and would have "
<< "size " << new_block_size << ".";
}
template <typename KeyType>
void DecrementValueOrDeleteKey(const KeyType key,
std::map<KeyType, int>* container) {
auto it = container->find(key);
if (it->second == 1) {
delete key;
container->erase(it);
} else {
--it->second;
}
}
template <typename ForwardIterator>
void STLDeleteContainerPairFirstPointers(ForwardIterator begin,
ForwardIterator end) {
while (begin != end) {
delete begin->first;
++begin;
}
}
void InitializeContext(Context* context,
ContextImpl** context_impl,
bool* context_impl_owned) {
if (context == nullptr) {
*context_impl_owned = true;
*context_impl = new ContextImpl;
} else {
*context_impl_owned = false;
*context_impl = down_cast<ContextImpl*>(context);
}
}
} // namespace
ParameterBlock* ProblemImpl::InternalAddParameterBlock(double* values,
int size) {
CHECK(values != nullptr) << "Null pointer passed to AddParameterBlock "
<< "for a parameter with size " << size;
// Ignore the request if there is a block for the given pointer already.
auto it = parameter_block_map_.find(values);
if (it != parameter_block_map_.end()) {
if (!options_.disable_all_safety_checks) {
int existing_size = it->second->Size();
CHECK(size == existing_size)
<< "Tried adding a parameter block with the same double pointer, "
<< values << ", twice, but with different block sizes. Original "
<< "size was " << existing_size << " but new size is " << size;
}
return it->second;
}
if (!options_.disable_all_safety_checks) {
// Before adding the parameter block, also check that it doesn't alias any
// other parameter blocks.
if (!parameter_block_map_.empty()) {
auto lb = parameter_block_map_.lower_bound(values);
// If lb is not the first block, check the previous block for aliasing.
if (lb != parameter_block_map_.begin()) {
auto previous = lb;
--previous;
CheckForNoAliasing(
previous->first, previous->second->Size(), values, size);
}
// If lb is not off the end, check lb for aliasing.
if (lb != parameter_block_map_.end()) {
CheckForNoAliasing(lb->first, lb->second->Size(), values, size);
}
}
}
// Pass the index of the new parameter block as well to keep the index in
// sync with the position of the parameter in the program's parameter vector.
auto* new_parameter_block =
new ParameterBlock(values, size, program_->parameter_blocks_.size());
// For dynamic problems, add the list of dependent residual blocks, which is
// empty to start.
if (options_.enable_fast_removal) {
new_parameter_block->EnableResidualBlockDependencies();
}
parameter_block_map_[values] = new_parameter_block;
program_->parameter_blocks_.push_back(new_parameter_block);
return new_parameter_block;
}
void ProblemImpl::InternalRemoveResidualBlock(ResidualBlock* residual_block) {
CHECK(residual_block != nullptr);
// Perform no check on the validity of residual_block, that is handled in
// the public method: RemoveResidualBlock().
// If needed, remove the parameter dependencies on this residual block.
if (options_.enable_fast_removal) {
const int num_parameter_blocks_for_residual =
residual_block->NumParameterBlocks();
for (int i = 0; i < num_parameter_blocks_for_residual; ++i) {
residual_block->parameter_blocks()[i]->RemoveResidualBlock(
residual_block);
}
auto it = residual_block_set_.find(residual_block);
residual_block_set_.erase(it);
}
DeleteBlockInVector(program_->mutable_residual_blocks(), residual_block);
}
// Deletes the residual block in question, assuming there are no other
// references to it inside the problem (e.g. by another parameter). Referenced
// cost and loss functions are tucked away for future deletion, since it is not
// possible to know whether other parts of the problem depend on them without
// doing a full scan.
void ProblemImpl::DeleteBlock(ResidualBlock* residual_block) {
// The const casts here are legit, since ResidualBlock holds these
// pointers as const pointers but we have ownership of them and
// have the right to destroy them when the destructor is called.
auto* cost_function =
const_cast<CostFunction*>(residual_block->cost_function());
if (options_.cost_function_ownership == TAKE_OWNERSHIP) {
DecrementValueOrDeleteKey(cost_function, &cost_function_ref_count_);
}
auto* loss_function =
const_cast<LossFunction*>(residual_block->loss_function());
if (options_.loss_function_ownership == TAKE_OWNERSHIP &&
loss_function != nullptr) {
DecrementValueOrDeleteKey(loss_function, &loss_function_ref_count_);
}
delete residual_block;
}
// Deletes the parameter block in question, assuming there are no other
// references to it inside the problem (e.g. by any residual blocks).
void ProblemImpl::DeleteBlock(ParameterBlock* parameter_block) {
parameter_block_map_.erase(parameter_block->mutable_user_state());
delete parameter_block;
}
ProblemImpl::ProblemImpl()
: options_(Problem::Options()), program_(new internal::Program) {
InitializeContext(options_.context, &context_impl_, &context_impl_owned_);
}
ProblemImpl::ProblemImpl(const Problem::Options& options)
: options_(options), program_(new internal::Program) {
program_->evaluation_callback_ = options.evaluation_callback;
InitializeContext(options_.context, &context_impl_, &context_impl_owned_);
}
ProblemImpl::~ProblemImpl() {
STLDeleteContainerPointers(program_->residual_blocks_.begin(),
program_->residual_blocks_.end());
if (options_.cost_function_ownership == TAKE_OWNERSHIP) {
STLDeleteContainerPairFirstPointers(cost_function_ref_count_.begin(),
cost_function_ref_count_.end());
}
if (options_.loss_function_ownership == TAKE_OWNERSHIP) {
STLDeleteContainerPairFirstPointers(loss_function_ref_count_.begin(),
loss_function_ref_count_.end());
}
// Collect the unique parameterizations and delete the parameters.
for (auto* parameter_block : program_->parameter_blocks_) {
DeleteBlock(parameter_block);
}
// Delete the owned manifolds.
STLDeleteUniqueContainerPointers(manifolds_to_delete_.begin(),
manifolds_to_delete_.end());
if (context_impl_owned_) {
delete context_impl_;
}
}
ResidualBlockId ProblemImpl::AddResidualBlock(
CostFunction* cost_function,
LossFunction* loss_function,
double* const* const parameter_blocks,
int num_parameter_blocks) {
CHECK(cost_function != nullptr);
CHECK_EQ(num_parameter_blocks, cost_function->parameter_block_sizes().size());
// Check the sizes match.
const std::vector<int32_t>& parameter_block_sizes =
cost_function->parameter_block_sizes();
if (!options_.disable_all_safety_checks) {
CHECK_EQ(parameter_block_sizes.size(), num_parameter_blocks)
<< "Number of blocks input is different than the number of blocks "
<< "that the cost function expects.";
// Check for duplicate parameter blocks.
std::vector<double*> sorted_parameter_blocks(
parameter_blocks, parameter_blocks + num_parameter_blocks);
sort(sorted_parameter_blocks.begin(), sorted_parameter_blocks.end());
const bool has_duplicate_items =
(std::adjacent_find(sorted_parameter_blocks.begin(),
sorted_parameter_blocks.end()) !=
sorted_parameter_blocks.end());
if (has_duplicate_items) {
std::string blocks;
for (int i = 0; i < num_parameter_blocks; ++i) {
blocks += StringPrintf(" %p ", parameter_blocks[i]);
}
LOG(FATAL) << "Duplicate parameter blocks in a residual parameter "
<< "are not allowed. Parameter block pointers: [" << blocks
<< "]";
}
}
// Add parameter blocks and convert the double*'s to parameter blocks.
std::vector<ParameterBlock*> parameter_block_ptrs(num_parameter_blocks);
for (int i = 0; i < num_parameter_blocks; ++i) {
parameter_block_ptrs[i] = InternalAddParameterBlock(
parameter_blocks[i], parameter_block_sizes[i]);
}
if (!options_.disable_all_safety_checks) {
// Check that the block sizes match the block sizes expected by the
// cost_function.
for (int i = 0; i < parameter_block_ptrs.size(); ++i) {
CHECK_EQ(cost_function->parameter_block_sizes()[i],
parameter_block_ptrs[i]->Size())
<< "The cost function expects parameter block " << i << " of size "
<< cost_function->parameter_block_sizes()[i]
<< " but was given a block of size "
<< parameter_block_ptrs[i]->Size();
}
}
auto* new_residual_block =
new ResidualBlock(cost_function,
loss_function,
parameter_block_ptrs,
program_->residual_blocks_.size());
// Add dependencies on the residual to the parameter blocks.
if (options_.enable_fast_removal) {
for (int i = 0; i < num_parameter_blocks; ++i) {
parameter_block_ptrs[i]->AddResidualBlock(new_residual_block);
}
}
program_->residual_blocks_.push_back(new_residual_block);
if (options_.enable_fast_removal) {
residual_block_set_.insert(new_residual_block);
}
if (options_.cost_function_ownership == TAKE_OWNERSHIP) {
// Increment the reference count, creating an entry in the table if
// needed. Note: C++ maps guarantee that new entries have default
// constructed values; this implies integers are zero initialized.
++cost_function_ref_count_[cost_function];
}
if (options_.loss_function_ownership == TAKE_OWNERSHIP &&
loss_function != nullptr) {
++loss_function_ref_count_[loss_function];
}
return new_residual_block;
}
void ProblemImpl::AddParameterBlock(double* values, int size) {
InternalAddParameterBlock(values, size);
}
void ProblemImpl::InternalSetManifold(double* values,
ParameterBlock* parameter_block,
Manifold* manifold) {
if (manifold != nullptr && options_.manifold_ownership == TAKE_OWNERSHIP) {
manifolds_to_delete_.push_back(manifold);
}
parameter_block->SetManifold(manifold);
}
void ProblemImpl::AddParameterBlock(double* values,
int size,
Manifold* manifold) {
ParameterBlock* parameter_block = InternalAddParameterBlock(values, size);
InternalSetManifold(values, parameter_block, manifold);
}
// Delete a block from a vector of blocks, maintaining the indexing invariant.
// This is done in constant time by moving an element from the end of the
// vector over the element to remove, then popping the last element. It
// destroys the ordering in the interest of speed.
template <typename Block>
void ProblemImpl::DeleteBlockInVector(std::vector<Block*>* mutable_blocks,
Block* block_to_remove) {
CHECK_EQ((*mutable_blocks)[block_to_remove->index()], block_to_remove)
<< "You found a Ceres bug! \n"
<< "Block requested: " << block_to_remove->ToString() << "\n"
<< "Block present: "
<< (*mutable_blocks)[block_to_remove->index()]->ToString();
// Prepare the to-be-moved block for the new, lower-in-index position by
// setting the index to the blocks final location.
Block* tmp = mutable_blocks->back();
tmp->set_index(block_to_remove->index());
// Overwrite the to-be-deleted residual block with the one at the end.
(*mutable_blocks)[block_to_remove->index()] = tmp;
DeleteBlock(block_to_remove);
// The block is gone so shrink the vector of blocks accordingly.
mutable_blocks->pop_back();
}
void ProblemImpl::RemoveResidualBlock(ResidualBlock* residual_block) {
CHECK(residual_block != nullptr);
// Verify that residual_block identifies a residual in the current problem.
const std::string residual_not_found_message = StringPrintf(
"Residual block to remove: %p not found. This usually means "
"one of three things have happened:\n"
" 1) residual_block is uninitialised and points to a random "
"area in memory.\n"
" 2) residual_block represented a residual that was added to"
" the problem, but referred to a parameter block which has "
"since been removed, which removes all residuals which "
"depend on that parameter block, and was thus removed.\n"
" 3) residual_block referred to a residual that has already "
"been removed from the problem (by the user).",
residual_block);
if (options_.enable_fast_removal) {
CHECK(residual_block_set_.find(residual_block) != residual_block_set_.end())
<< residual_not_found_message;
} else {
// Perform a full search over all current residuals.
CHECK(std::find(program_->residual_blocks().begin(),
program_->residual_blocks().end(),
residual_block) != program_->residual_blocks().end())
<< residual_not_found_message;
}
InternalRemoveResidualBlock(residual_block);
}
void ProblemImpl::RemoveParameterBlock(const double* values) {
ParameterBlock* parameter_block = FindWithDefault(
parameter_block_map_, const_cast<double*>(values), nullptr);
if (parameter_block == nullptr) {
LOG(FATAL) << "Parameter block not found: " << values
<< ". You must add the parameter block to the problem before "
<< "it can be removed.";
}
if (options_.enable_fast_removal) {
// Copy the dependent residuals from the parameter block because the set of
// dependents will change after each call to RemoveResidualBlock().
std::vector<ResidualBlock*> residual_blocks_to_remove(
parameter_block->mutable_residual_blocks()->begin(),
parameter_block->mutable_residual_blocks()->end());
for (auto* residual_block : residual_blocks_to_remove) {
InternalRemoveResidualBlock(residual_block);
}
} else {
// Scan all the residual blocks to remove ones that depend on the parameter
// block. Do the scan backwards since the vector changes while iterating.
const int num_residual_blocks = NumResidualBlocks();
for (int i = num_residual_blocks - 1; i >= 0; --i) {
ResidualBlock* residual_block =
(*(program_->mutable_residual_blocks()))[i];
const int num_parameter_blocks = residual_block->NumParameterBlocks();
for (int j = 0; j < num_parameter_blocks; ++j) {
if (residual_block->parameter_blocks()[j] == parameter_block) {
InternalRemoveResidualBlock(residual_block);
// The parameter blocks are guaranteed unique.
break;
}
}
}
}
DeleteBlockInVector(program_->mutable_parameter_blocks(), parameter_block);
}
void ProblemImpl::SetParameterBlockConstant(const double* values) {
ParameterBlock* parameter_block = FindWithDefault(
parameter_block_map_, const_cast<double*>(values), nullptr);
if (parameter_block == nullptr) {
LOG(FATAL) << "Parameter block not found: " << values
<< ". You must add the parameter block to the problem before "
<< "it can be set constant.";
}
parameter_block->SetConstant();
}
bool ProblemImpl::IsParameterBlockConstant(const double* values) const {
const ParameterBlock* parameter_block = FindWithDefault(
parameter_block_map_, const_cast<double*>(values), nullptr);
CHECK(parameter_block != nullptr)
<< "Parameter block not found: " << values << ". You must add the "
<< "parameter block to the problem before it can be queried.";
return parameter_block->IsConstant();
}
void ProblemImpl::SetParameterBlockVariable(double* values) {
ParameterBlock* parameter_block =
FindWithDefault(parameter_block_map_, values, nullptr);
if (parameter_block == nullptr) {
LOG(FATAL) << "Parameter block not found: " << values
<< ". You must add the parameter block to the problem before "
<< "it can be set varying.";
}
parameter_block->SetVarying();
}
void ProblemImpl::SetManifold(double* values, Manifold* manifold) {
ParameterBlock* parameter_block =
FindWithDefault(parameter_block_map_, values, nullptr);
if (parameter_block == nullptr) {
LOG(FATAL) << "Parameter block not found: " << values
<< ". You must add the parameter block to the problem before "
<< "you can set its manifold.";
}
InternalSetManifold(values, parameter_block, manifold);
}
const Manifold* ProblemImpl::GetManifold(const double* values) const {
ParameterBlock* parameter_block = FindWithDefault(
parameter_block_map_, const_cast<double*>(values), nullptr);
if (parameter_block == nullptr) {
LOG(FATAL) << "Parameter block not found: " << values
<< ". You must add the parameter block to the problem before "
<< "you can get its manifold.";
}
return parameter_block->manifold();
}
bool ProblemImpl::HasManifold(const double* values) const {
return GetManifold(values) != nullptr;
}
void ProblemImpl::SetParameterLowerBound(double* values,
int index,
double lower_bound) {
ParameterBlock* parameter_block =
FindWithDefault(parameter_block_map_, values, nullptr);
if (parameter_block == nullptr) {
LOG(FATAL) << "Parameter block not found: " << values
<< ". You must add the parameter block to the problem before "
<< "you can set a lower bound on one of its components.";
}
parameter_block->SetLowerBound(index, lower_bound);
}
void ProblemImpl::SetParameterUpperBound(double* values,
int index,
double upper_bound) {
ParameterBlock* parameter_block =
FindWithDefault(parameter_block_map_, values, nullptr);
if (parameter_block == nullptr) {
LOG(FATAL) << "Parameter block not found: " << values
<< ". You must add the parameter block to the problem before "
<< "you can set an upper bound on one of its components.";
}
parameter_block->SetUpperBound(index, upper_bound);
}
double ProblemImpl::GetParameterLowerBound(const double* values,
int index) const {
ParameterBlock* parameter_block = FindWithDefault(
parameter_block_map_, const_cast<double*>(values), nullptr);
if (parameter_block == nullptr) {
LOG(FATAL) << "Parameter block not found: " << values
<< ". You must add the parameter block to the problem before "
<< "you can get the lower bound on one of its components.";
}
return parameter_block->LowerBound(index);
}
double ProblemImpl::GetParameterUpperBound(const double* values,
int index) const {
ParameterBlock* parameter_block = FindWithDefault(
parameter_block_map_, const_cast<double*>(values), nullptr);
if (parameter_block == nullptr) {
LOG(FATAL) << "Parameter block not found: " << values
<< ". You must add the parameter block to the problem before "
<< "you can set an upper bound on one of its components.";
}
return parameter_block->UpperBound(index);
}
bool ProblemImpl::Evaluate(const Problem::EvaluateOptions& evaluate_options,
double* cost,
std::vector<double>* residuals,
std::vector<double>* gradient,
CRSMatrix* jacobian) {
if (cost == nullptr && residuals == nullptr && gradient == nullptr &&
jacobian == nullptr) {
return true;
}
// If the user supplied residual blocks, then use them, otherwise
// take the residual blocks from the underlying program.
Program program;
*program.mutable_residual_blocks() =
((evaluate_options.residual_blocks.size() > 0)
? evaluate_options.residual_blocks
: program_->residual_blocks());
const std::vector<double*>& parameter_block_ptrs =
evaluate_options.parameter_blocks;
std::vector<ParameterBlock*> variable_parameter_blocks;
std::vector<ParameterBlock*>& parameter_blocks =
*program.mutable_parameter_blocks();
if (parameter_block_ptrs.size() == 0) {
// The user did not provide any parameter blocks, so default to
// using all the parameter blocks in the order that they are in
// the underlying program object.
parameter_blocks = program_->parameter_blocks();
} else {
// The user supplied a vector of parameter blocks. Using this list
// requires a number of steps.
// 1. Convert double* into ParameterBlock*
parameter_blocks.resize(parameter_block_ptrs.size());
for (int i = 0; i < parameter_block_ptrs.size(); ++i) {
parameter_blocks[i] = FindWithDefault(
parameter_block_map_, parameter_block_ptrs[i], nullptr);
if (parameter_blocks[i] == nullptr) {
LOG(FATAL) << "No known parameter block for "
<< "Problem::Evaluate::Options.parameter_blocks[" << i << "]"
<< " = " << parameter_block_ptrs[i];
}
}
// 2. The user may have only supplied a subset of parameter
// blocks, so identify the ones that are not supplied by the user
// and are NOT constant. These parameter blocks are stored in
// variable_parameter_blocks.
//
// To ensure that the parameter blocks are not included in the
// columns of the jacobian, we need to make sure that they are
// constant during evaluation and then make them variable again
// after we are done.
std::vector<ParameterBlock*> all_parameter_blocks(
program_->parameter_blocks());
std::vector<ParameterBlock*> included_parameter_blocks(
program.parameter_blocks());
std::vector<ParameterBlock*> excluded_parameter_blocks;
sort(all_parameter_blocks.begin(), all_parameter_blocks.end());
sort(included_parameter_blocks.begin(), included_parameter_blocks.end());
set_difference(all_parameter_blocks.begin(),
all_parameter_blocks.end(),
included_parameter_blocks.begin(),
included_parameter_blocks.end(),
back_inserter(excluded_parameter_blocks));
variable_parameter_blocks.reserve(excluded_parameter_blocks.size());
for (auto* parameter_block : excluded_parameter_blocks) {
if (!parameter_block->IsConstant()) {
variable_parameter_blocks.push_back(parameter_block);
parameter_block->SetConstant();
}
}
}
// Setup the Parameter indices and offsets before an evaluator can
// be constructed and used.
program.SetParameterOffsetsAndIndex();
Evaluator::Options evaluator_options;
// Even though using SPARSE_NORMAL_CHOLESKY requires SuiteSparse or
// CXSparse, here it just being used for telling the evaluator to
// use a SparseRowCompressedMatrix for the jacobian. This is because
// the Evaluator decides the storage for the Jacobian based on the
// type of linear solver being used.
evaluator_options.linear_solver_type = SPARSE_NORMAL_CHOLESKY;
evaluator_options.num_threads = evaluate_options.num_threads;
// The main thread also does work so we only need to launch num_threads - 1.
context_impl_->EnsureMinimumThreads(evaluator_options.num_threads - 1);
evaluator_options.context = context_impl_;
evaluator_options.evaluation_callback =
program_->mutable_evaluation_callback();
std::unique_ptr<Evaluator> evaluator(
new ProgramEvaluator<ScratchEvaluatePreparer,
CompressedRowJacobianWriter>(evaluator_options,
&program));
if (residuals != nullptr) {
residuals->resize(evaluator->NumResiduals());
}
if (gradient != nullptr) {
gradient->resize(evaluator->NumEffectiveParameters());
}
std::unique_ptr<CompressedRowSparseMatrix> tmp_jacobian;
if (jacobian != nullptr) {
tmp_jacobian.reset(down_cast<CompressedRowSparseMatrix*>(
evaluator->CreateJacobian().release()));
}
// Point the state pointers to the user state pointers. This is
// needed so that we can extract a parameter vector which is then
// passed to Evaluator::Evaluate.
program.SetParameterBlockStatePtrsToUserStatePtrs();
// Copy the value of the parameter blocks into a vector, since the
// Evaluate::Evaluate method needs its input as such. The previous
// call to SetParameterBlockStatePtrsToUserStatePtrs ensures that
// these values are the ones corresponding to the actual state of
// the parameter blocks, rather than the temporary state pointer
// used for evaluation.
Vector parameters(program.NumParameters());
program.ParameterBlocksToStateVector(parameters.data());
double tmp_cost = 0;
Evaluator::EvaluateOptions evaluator_evaluate_options;
evaluator_evaluate_options.apply_loss_function =
evaluate_options.apply_loss_function;
bool status =
evaluator->Evaluate(evaluator_evaluate_options,
parameters.data(),
&tmp_cost,
residuals != nullptr ? &(*residuals)[0] : nullptr,
gradient != nullptr ? &(*gradient)[0] : nullptr,
tmp_jacobian.get());
// Make the parameter blocks that were temporarily marked constant,
// variable again.
for (auto* parameter_block : variable_parameter_blocks) {
parameter_block->SetVarying();
}
if (status) {
if (cost != nullptr) {
*cost = tmp_cost;
}
if (jacobian != nullptr) {
tmp_jacobian->ToCRSMatrix(jacobian);
}
}
program_->SetParameterBlockStatePtrsToUserStatePtrs();
program_->SetParameterOffsetsAndIndex();
return status;
}
bool ProblemImpl::EvaluateResidualBlock(ResidualBlock* residual_block,
bool apply_loss_function,
bool new_point,
double* cost,
double* residuals,
double** jacobians) const {
auto evaluation_callback = program_->mutable_evaluation_callback();
if (evaluation_callback) {
evaluation_callback->PrepareForEvaluation(jacobians != nullptr, new_point);
}
ParameterBlock* const* parameter_blocks = residual_block->parameter_blocks();
const int num_parameter_blocks = residual_block->NumParameterBlocks();
for (int i = 0; i < num_parameter_blocks; ++i) {
ParameterBlock* parameter_block = parameter_blocks[i];
if (parameter_block->IsConstant()) {
if (jacobians != nullptr && jacobians[i] != nullptr) {
LOG(ERROR) << "Jacobian requested for parameter block : " << i
<< ". But the parameter block is marked constant.";
return false;
}
} else {
CHECK(parameter_block->SetState(parameter_block->user_state()))
<< "Congratulations, you found a Ceres bug! Please report this error "
<< "to the developers.";
}
}
double dummy_cost = 0.0;
FixedArray<double, 32> scratch(
residual_block->NumScratchDoublesForEvaluate());
return residual_block->Evaluate(apply_loss_function,
cost ? cost : &dummy_cost,
residuals,
jacobians,
scratch.data());
}
int ProblemImpl::NumParameterBlocks() const {
return program_->NumParameterBlocks();
}
int ProblemImpl::NumParameters() const { return program_->NumParameters(); }
int ProblemImpl::NumResidualBlocks() const {
return program_->NumResidualBlocks();
}
int ProblemImpl::NumResiduals() const { return program_->NumResiduals(); }
int ProblemImpl::ParameterBlockSize(const double* values) const {
ParameterBlock* parameter_block = FindWithDefault(
parameter_block_map_, const_cast<double*>(values), nullptr);
if (parameter_block == nullptr) {
LOG(FATAL) << "Parameter block not found: " << values
<< ". You must add the parameter block to the problem before "
<< "you can get its size.";
}
return parameter_block->Size();
}
int ProblemImpl::ParameterBlockTangentSize(const double* values) const {
ParameterBlock* parameter_block = FindWithDefault(
parameter_block_map_, const_cast<double*>(values), nullptr);
if (parameter_block == nullptr) {
LOG(FATAL) << "Parameter block not found: " << values
<< ". You must add the parameter block to the problem before "
<< "you can get its tangent size.";
}
return parameter_block->TangentSize();
}
bool ProblemImpl::HasParameterBlock(const double* values) const {
return (parameter_block_map_.find(const_cast<double*>(values)) !=
parameter_block_map_.end());
}
void ProblemImpl::GetParameterBlocks(
std::vector<double*>* parameter_blocks) const {
CHECK(parameter_blocks != nullptr);
parameter_blocks->resize(0);
parameter_blocks->reserve(parameter_block_map_.size());
for (const auto& entry : parameter_block_map_) {
parameter_blocks->push_back(entry.first);
}
}
void ProblemImpl::GetResidualBlocks(
std::vector<ResidualBlockId>* residual_blocks) const {
CHECK(residual_blocks != nullptr);
*residual_blocks = program().residual_blocks();
}
void ProblemImpl::GetParameterBlocksForResidualBlock(
const ResidualBlockId residual_block,
std::vector<double*>* parameter_blocks) const {
int num_parameter_blocks = residual_block->NumParameterBlocks();
CHECK(parameter_blocks != nullptr);
parameter_blocks->resize(num_parameter_blocks);
for (int i = 0; i < num_parameter_blocks; ++i) {
(*parameter_blocks)[i] =
residual_block->parameter_blocks()[i]->mutable_user_state();
}
}
const CostFunction* ProblemImpl::GetCostFunctionForResidualBlock(
const ResidualBlockId residual_block) const {
return residual_block->cost_function();
}
const LossFunction* ProblemImpl::GetLossFunctionForResidualBlock(
const ResidualBlockId residual_block) const {
return residual_block->loss_function();
}
void ProblemImpl::GetResidualBlocksForParameterBlock(
const double* values, std::vector<ResidualBlockId>* residual_blocks) const {
ParameterBlock* parameter_block = FindWithDefault(
parameter_block_map_, const_cast<double*>(values), nullptr);
if (parameter_block == nullptr) {
LOG(FATAL) << "Parameter block not found: " << values
<< ". You must add the parameter block to the problem before "
<< "you can get the residual blocks that depend on it.";
}
if (options_.enable_fast_removal) {
// In this case the residual blocks that depend on the parameter block are
// stored in the parameter block already, so just copy them out.
CHECK(residual_blocks != nullptr);
residual_blocks->resize(parameter_block->mutable_residual_blocks()->size());
std::copy(parameter_block->mutable_residual_blocks()->begin(),
parameter_block->mutable_residual_blocks()->end(),
residual_blocks->begin());
return;
}
// Find residual blocks that depend on the parameter block.
CHECK(residual_blocks != nullptr);
residual_blocks->clear();
const int num_residual_blocks = NumResidualBlocks();
for (int i = 0; i < num_residual_blocks; ++i) {
ResidualBlock* residual_block = (*(program_->mutable_residual_blocks()))[i];
const int num_parameter_blocks = residual_block->NumParameterBlocks();
for (int j = 0; j < num_parameter_blocks; ++j) {
if (residual_block->parameter_blocks()[j] == parameter_block) {
residual_blocks->push_back(residual_block);
// The parameter blocks are guaranteed unique.
break;
}
}
}
}
} // namespace ceres::internal