|  | // Ceres Solver - A fast non-linear least squares minimizer | 
|  | // Copyright 2015 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: keir@google.com (Keir Mierle) | 
|  | // | 
|  | // The ProgramEvaluator runs the cost functions contained in each residual block | 
|  | // and stores the result into a jacobian. The particular type of jacobian is | 
|  | // abstracted out using two template parameters: | 
|  | // | 
|  | //   - An "EvaluatePreparer" that is responsible for creating the array with | 
|  | //     pointers to the jacobian blocks where the cost function evaluates to. | 
|  | //   - A "JacobianWriter" that is responsible for storing the resulting | 
|  | //     jacobian blocks in the passed sparse matrix. | 
|  | // | 
|  | // This abstraction affords an efficient evaluator implementation while still | 
|  | // supporting writing to multiple sparse matrix formats. For example, when the | 
|  | // ProgramEvaluator is parameterized for writing to block sparse matrices, the | 
|  | // residual jacobians are written directly into their final position in the | 
|  | // block sparse matrix by the user's CostFunction; there is no copying. | 
|  | // | 
|  | // The evaluation is threaded with OpenMP or C++11 threads. | 
|  | // | 
|  | // The EvaluatePreparer and JacobianWriter interfaces are as follows: | 
|  | // | 
|  | //   class EvaluatePreparer { | 
|  | //     // Prepare the jacobians array for use as the destination of a call to | 
|  | //     // a cost function's evaluate method. | 
|  | //     void Prepare(const ResidualBlock* residual_block, | 
|  | //                  int residual_block_index, | 
|  | //                  SparseMatrix* jacobian, | 
|  | //                  double** jacobians); | 
|  | //   } | 
|  | // | 
|  | //   class JacobianWriter { | 
|  | //     // Create a jacobian that this writer can write. Same as | 
|  | //     // Evaluator::CreateJacobian. | 
|  | //     SparseMatrix* CreateJacobian() const; | 
|  | // | 
|  | //     // Create num_threads evaluate preparers. Caller owns result which must | 
|  | //     // be freed with delete[]. Resulting preparers are valid while *this is. | 
|  | //     EvaluatePreparer* CreateEvaluatePreparers(int num_threads); | 
|  | // | 
|  | //     // Write the block jacobians from a residual block evaluation to the | 
|  | //     // larger sparse jacobian. | 
|  | //     void Write(int residual_id, | 
|  | //                int residual_offset, | 
|  | //                double** jacobians, | 
|  | //                SparseMatrix* jacobian); | 
|  | //   } | 
|  | // | 
|  | // Note: The ProgramEvaluator is not thread safe, since internally it maintains | 
|  | // some per-thread scratch space. | 
|  |  | 
|  | #ifndef CERES_INTERNAL_PROGRAM_EVALUATOR_H_ | 
|  | #define CERES_INTERNAL_PROGRAM_EVALUATOR_H_ | 
|  |  | 
|  | // This include must come before any #ifndef check on Ceres compile options. | 
|  | #include "ceres/internal/port.h" | 
|  |  | 
|  | #include <atomic> | 
|  | #include <map> | 
|  | #include <memory> | 
|  | #include <string> | 
|  | #include <vector> | 
|  |  | 
|  | #include "ceres/evaluation_callback.h" | 
|  | #include "ceres/execution_summary.h" | 
|  | #include "ceres/internal/eigen.h" | 
|  | #include "ceres/parallel_for.h" | 
|  | #include "ceres/parameter_block.h" | 
|  | #include "ceres/program.h" | 
|  | #include "ceres/residual_block.h" | 
|  | #include "ceres/small_blas.h" | 
|  |  | 
|  | namespace ceres { | 
|  | namespace internal { | 
|  |  | 
|  | struct NullJacobianFinalizer { | 
|  | void operator()(SparseMatrix* jacobian, int num_parameters) {} | 
|  | }; | 
|  |  | 
|  | template<typename EvaluatePreparer, | 
|  | typename JacobianWriter, | 
|  | typename JacobianFinalizer = NullJacobianFinalizer> | 
|  | class ProgramEvaluator : public Evaluator { | 
|  | public: | 
|  | ProgramEvaluator(const Evaluator::Options &options, Program* program) | 
|  | : options_(options), | 
|  | program_(program), | 
|  | jacobian_writer_(options, program), | 
|  | evaluate_preparers_( | 
|  | jacobian_writer_.CreateEvaluatePreparers(options.num_threads)) { | 
|  | #ifdef CERES_NO_THREADS | 
|  | if (options_.num_threads > 1) { | 
|  | LOG(WARNING) | 
|  | << "No threading support is compiled into this binary; " | 
|  | << "only options.num_threads = 1 is supported. Switching " | 
|  | << "to single threaded mode."; | 
|  | options_.num_threads = 1; | 
|  | } | 
|  | #endif // CERES_NO_THREADS | 
|  |  | 
|  | BuildResidualLayout(*program, &residual_layout_); | 
|  | evaluate_scratch_.reset(CreateEvaluatorScratch(*program, | 
|  | options.num_threads)); | 
|  | } | 
|  |  | 
|  | // Implementation of Evaluator interface. | 
|  | SparseMatrix* CreateJacobian() const { | 
|  | return jacobian_writer_.CreateJacobian(); | 
|  | } | 
|  |  | 
|  | bool Evaluate(const Evaluator::EvaluateOptions& evaluate_options, | 
|  | const double* state, | 
|  | double* cost, | 
|  | double* residuals, | 
|  | double* gradient, | 
|  | SparseMatrix* jacobian) { | 
|  | ScopedExecutionTimer total_timer("Evaluator::Total", &execution_summary_); | 
|  | ScopedExecutionTimer call_type_timer(gradient == NULL && jacobian == NULL | 
|  | ? "Evaluator::Residual" | 
|  | : "Evaluator::Jacobian", | 
|  | &execution_summary_); | 
|  |  | 
|  | // The parameters are stateful, so set the state before evaluating. | 
|  | if (!program_->StateVectorToParameterBlocks(state)) { | 
|  | return false; | 
|  | } | 
|  |  | 
|  | // Notify the user about a new evaluation point if they are interested. | 
|  | if (options_.evaluation_callback != NULL) { | 
|  | program_->CopyParameterBlockStateToUserState(); | 
|  | options_.evaluation_callback->PrepareForEvaluation( | 
|  | /*jacobians=*/(gradient != NULL || jacobian != NULL), | 
|  | evaluate_options.new_evaluation_point); | 
|  | } | 
|  |  | 
|  | if (residuals != NULL) { | 
|  | VectorRef(residuals, program_->NumResiduals()).setZero(); | 
|  | } | 
|  |  | 
|  | if (jacobian != NULL) { | 
|  | jacobian->SetZero(); | 
|  | } | 
|  |  | 
|  | // Each thread gets it's own cost and evaluate scratch space. | 
|  | for (int i = 0; i < options_.num_threads; ++i) { | 
|  | evaluate_scratch_[i].cost = 0.0; | 
|  | if (gradient != NULL) { | 
|  | VectorRef(evaluate_scratch_[i].gradient.get(), | 
|  | program_->NumEffectiveParameters()).setZero(); | 
|  | } | 
|  | } | 
|  |  | 
|  | const int num_residual_blocks = program_->NumResidualBlocks(); | 
|  | // This bool is used to disable the loop if an error is encountered without | 
|  | // breaking out of it. The remaining loop iterations are still run, but with | 
|  | // an empty body, and so will finish quickly. | 
|  | std::atomic_bool abort(false); | 
|  | ParallelFor( | 
|  | options_.context, | 
|  | 0, | 
|  | num_residual_blocks, | 
|  | options_.num_threads, | 
|  | [&](int thread_id, int i) { | 
|  | if (abort) { | 
|  | return; | 
|  | } | 
|  |  | 
|  | EvaluatePreparer* preparer = &evaluate_preparers_[thread_id]; | 
|  | EvaluateScratch* scratch = &evaluate_scratch_[thread_id]; | 
|  |  | 
|  | // Prepare block residuals if requested. | 
|  | const ResidualBlock* residual_block = program_->residual_blocks()[i]; | 
|  | double* block_residuals = NULL; | 
|  | if (residuals != NULL) { | 
|  | block_residuals = residuals + residual_layout_[i]; | 
|  | } else if (gradient != NULL) { | 
|  | block_residuals = scratch->residual_block_residuals.get(); | 
|  | } | 
|  |  | 
|  | // Prepare block jacobians if requested. | 
|  | double** block_jacobians = NULL; | 
|  | if (jacobian != NULL || gradient != NULL) { | 
|  | preparer->Prepare(residual_block, | 
|  | i, | 
|  | jacobian, | 
|  | scratch->jacobian_block_ptrs.get()); | 
|  | block_jacobians = scratch->jacobian_block_ptrs.get(); | 
|  | } | 
|  |  | 
|  | // Evaluate the cost, residuals, and jacobians. | 
|  | double block_cost; | 
|  | if (!residual_block->Evaluate( | 
|  | evaluate_options.apply_loss_function, | 
|  | &block_cost, | 
|  | block_residuals, | 
|  | block_jacobians, | 
|  | scratch->residual_block_evaluate_scratch.get())) { | 
|  | abort = true; | 
|  | return; | 
|  | } | 
|  |  | 
|  | scratch->cost += block_cost; | 
|  |  | 
|  | // Store the jacobians, if they were requested. | 
|  | if (jacobian != NULL) { | 
|  | jacobian_writer_.Write(i, | 
|  | residual_layout_[i], | 
|  | block_jacobians, | 
|  | jacobian); | 
|  | } | 
|  |  | 
|  | // Compute and store the gradient, if it was requested. | 
|  | if (gradient != NULL) { | 
|  | int num_residuals = residual_block->NumResiduals(); | 
|  | int num_parameter_blocks = residual_block->NumParameterBlocks(); | 
|  | for (int j = 0; j < num_parameter_blocks; ++j) { | 
|  | const ParameterBlock* parameter_block = | 
|  | residual_block->parameter_blocks()[j]; | 
|  | if (parameter_block->IsConstant()) { | 
|  | continue; | 
|  | } | 
|  |  | 
|  | MatrixTransposeVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>( | 
|  | block_jacobians[j], | 
|  | num_residuals, | 
|  | parameter_block->LocalSize(), | 
|  | block_residuals, | 
|  | scratch->gradient.get() + parameter_block->delta_offset()); | 
|  | } | 
|  | } | 
|  | }); | 
|  |  | 
|  | if (!abort) { | 
|  | const int num_parameters = program_->NumEffectiveParameters(); | 
|  |  | 
|  | // Sum the cost and gradient (if requested) from each thread. | 
|  | (*cost) = 0.0; | 
|  | if (gradient != NULL) { | 
|  | VectorRef(gradient, num_parameters).setZero(); | 
|  | } | 
|  | for (int i = 0; i < options_.num_threads; ++i) { | 
|  | (*cost) += evaluate_scratch_[i].cost; | 
|  | if (gradient != NULL) { | 
|  | VectorRef(gradient, num_parameters) += | 
|  | VectorRef(evaluate_scratch_[i].gradient.get(), num_parameters); | 
|  | } | 
|  | } | 
|  |  | 
|  | // Finalize the Jacobian if it is available. | 
|  | // `num_parameters` is passed to the finalizer so that additional | 
|  | // storage can be reserved for additional diagonal elements if | 
|  | // necessary. | 
|  | if (jacobian != NULL) { | 
|  | JacobianFinalizer f; | 
|  | f(jacobian, num_parameters); | 
|  | } | 
|  | } | 
|  | return !abort; | 
|  | } | 
|  |  | 
|  | bool Plus(const double* state, | 
|  | const double* delta, | 
|  | double* state_plus_delta) const { | 
|  | return program_->Plus(state, delta, state_plus_delta); | 
|  | } | 
|  |  | 
|  | int NumParameters() const { | 
|  | return program_->NumParameters(); | 
|  | } | 
|  | int NumEffectiveParameters() const { | 
|  | return program_->NumEffectiveParameters(); | 
|  | } | 
|  |  | 
|  | int NumResiduals() const { | 
|  | return program_->NumResiduals(); | 
|  | } | 
|  |  | 
|  | virtual std::map<std::string, CallStatistics> Statistics() const { | 
|  | return execution_summary_.statistics(); | 
|  | } | 
|  |  | 
|  | private: | 
|  | // Per-thread scratch space needed to evaluate and store each residual block. | 
|  | struct EvaluateScratch { | 
|  | void Init(int max_parameters_per_residual_block, | 
|  | int max_scratch_doubles_needed_for_evaluate, | 
|  | int max_residuals_per_residual_block, | 
|  | int num_parameters) { | 
|  | residual_block_evaluate_scratch.reset( | 
|  | new double[max_scratch_doubles_needed_for_evaluate]); | 
|  | gradient.reset(new double[num_parameters]); | 
|  | VectorRef(gradient.get(), num_parameters).setZero(); | 
|  | residual_block_residuals.reset( | 
|  | new double[max_residuals_per_residual_block]); | 
|  | jacobian_block_ptrs.reset( | 
|  | new double*[max_parameters_per_residual_block]); | 
|  | } | 
|  |  | 
|  | double cost; | 
|  | std::unique_ptr<double[]> residual_block_evaluate_scratch; | 
|  | // The gradient in the local parameterization. | 
|  | std::unique_ptr<double[]> gradient; | 
|  | // Enough space to store the residual for the largest residual block. | 
|  | std::unique_ptr<double[]> residual_block_residuals; | 
|  | std::unique_ptr<double*[]> jacobian_block_ptrs; | 
|  | }; | 
|  |  | 
|  | static void BuildResidualLayout(const Program& program, | 
|  | std::vector<int>* residual_layout) { | 
|  | const std::vector<ResidualBlock*>& residual_blocks = | 
|  | program.residual_blocks(); | 
|  | residual_layout->resize(program.NumResidualBlocks()); | 
|  | int residual_pos = 0; | 
|  | for (int i = 0; i < residual_blocks.size(); ++i) { | 
|  | const int num_residuals = residual_blocks[i]->NumResiduals(); | 
|  | (*residual_layout)[i] = residual_pos; | 
|  | residual_pos += num_residuals; | 
|  | } | 
|  | } | 
|  |  | 
|  | // Create scratch space for each thread evaluating the program. | 
|  | static EvaluateScratch* CreateEvaluatorScratch(const Program& program, | 
|  | int num_threads) { | 
|  | int max_parameters_per_residual_block = | 
|  | program.MaxParametersPerResidualBlock(); | 
|  | int max_scratch_doubles_needed_for_evaluate = | 
|  | program.MaxScratchDoublesNeededForEvaluate(); | 
|  | int max_residuals_per_residual_block = | 
|  | program.MaxResidualsPerResidualBlock(); | 
|  | int num_parameters = program.NumEffectiveParameters(); | 
|  |  | 
|  | EvaluateScratch* evaluate_scratch = new EvaluateScratch[num_threads]; | 
|  | for (int i = 0; i < num_threads; i++) { | 
|  | evaluate_scratch[i].Init(max_parameters_per_residual_block, | 
|  | max_scratch_doubles_needed_for_evaluate, | 
|  | max_residuals_per_residual_block, | 
|  | num_parameters); | 
|  | } | 
|  | return evaluate_scratch; | 
|  | } | 
|  |  | 
|  | Evaluator::Options options_; | 
|  | Program* program_; | 
|  | JacobianWriter jacobian_writer_; | 
|  | std::unique_ptr<EvaluatePreparer[]> evaluate_preparers_; | 
|  | std::unique_ptr<EvaluateScratch[]> evaluate_scratch_; | 
|  | std::vector<int> residual_layout_; | 
|  | ::ceres::internal::ExecutionSummary execution_summary_; | 
|  | }; | 
|  |  | 
|  | }  // namespace internal | 
|  | }  // namespace ceres | 
|  |  | 
|  | #endif  // CERES_INTERNAL_PROGRAM_EVALUATOR_H_ |