// 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 #include #include #include #include #include #include #include #include #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 void DecrementValueOrDeleteKey(const KeyType key, std::map* container) { auto it = container->find(key); if (it->second == 1) { delete key; container->erase(it); } else { --it->second; } } template 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(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(residual_block->cost_function()); if (options_.cost_function_ownership == TAKE_OWNERSHIP) { DecrementValueOrDeleteKey(cost_function, &cost_function_ref_count_); } auto* loss_function = const_cast(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& 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 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 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 void ProblemImpl::DeleteBlockInVector(std::vector* 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(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 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(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(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(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(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(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* residuals, std::vector* 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& parameter_block_ptrs = evaluate_options.parameter_blocks; std::vector variable_parameter_blocks; std::vector& 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 all_parameter_blocks( program_->parameter_blocks()); std::vector included_parameter_blocks( program.parameter_blocks()); std::vector 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( new ProgramEvaluator(evaluator_options, &program)); if (residuals != nullptr) { residuals->resize(evaluator->NumResiduals()); } if (gradient != nullptr) { gradient->resize(evaluator->NumEffectiveParameters()); } std::unique_ptr tmp_jacobian; if (jacobian != nullptr) { tmp_jacobian.reset(down_cast( 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 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(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(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(values)) != parameter_block_map_.end()); } void ProblemImpl::GetParameterBlocks( std::vector* 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* residual_blocks) const { CHECK(residual_blocks != nullptr); *residual_blocks = program().residual_blocks(); } void ProblemImpl::GetParameterBlocksForResidualBlock( const ResidualBlockId residual_block, std::vector* 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* residual_blocks) const { ParameterBlock* parameter_block = FindWithDefault( parameter_block_map_, const_cast(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