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ceres-solver/internal/ceres/program_evaluator.h
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Keir Mierle 7492b0d8de Update copyright headers with new year and URL
Since Ceres is moving to using GitHub for issues, and the Google
Code URL in the current copyright header will soon become invalid,
update all the headers.

Change-Id: I1fce70375d1bcf098591f07b4d8f01a5c1e0789c
2015-03-18 05:43:23 +00:00

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C++

// 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.
//
// 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"
#ifdef CERES_USE_OPENMP
#include <omp.h>
#endif
#include <map>
#include <string>
#include <vector>
#include "ceres/execution_summary.h"
#include "ceres/internal/eigen.h"
#include "ceres/internal/scoped_ptr.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)) {
#ifndef CERES_USE_OPENMP
if (options_.num_threads > 1) {
LOG(WARNING)
<< "OpenMP support is not compiled into this binary; "
<< "only options.num_threads = 1 is supported. Switching "
<< "to single threaded mode.";
options_.num_threads = 1;
}
#endif
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;
}
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();
}
}
// 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.
bool abort = false;
int num_residual_blocks = program_->NumResidualBlocks();
#pragma omp parallel for num_threads(options_.num_threads)
for (int i = 0; i < num_residual_blocks; ++i) {
// Disable the loop instead of breaking, as required by OpenMP.
#pragma omp flush(abort)
if (abort) {
continue;
}
#ifdef CERES_USE_OPENMP
int thread_id = omp_get_thread_num();
#else
int thread_id = 0;
#endif
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;
// This ensures that the OpenMP threads have a consistent view of 'abort'. Do
// the flush inside the failure case so that there is usually only one
// synchronization point per loop iteration instead of two.
#pragma omp flush(abort)
continue;
}
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, int> CallStatistics() const {
return execution_summary_.calls();
}
virtual std::map<std::string, double> TimeStatistics() const {
return execution_summary_.times();
}
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;
scoped_array<double> residual_block_evaluate_scratch;
// The gradient in the local parameterization.
scoped_array<double> gradient;
// Enough space to store the residual for the largest residual block.
scoped_array<double> residual_block_residuals;
scoped_array<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_;
scoped_array<EvaluatePreparer> evaluate_preparers_;
scoped_array<EvaluateScratch> evaluate_scratch_;
std::vector<int> residual_layout_;
::ceres::internal::ExecutionSummary execution_summary_;
};
} // namespace internal
} // namespace ceres
#endif // CERES_INTERNAL_PROGRAM_EVALUATOR_H_