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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2019 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: mierle@gmail.com (Keir Mierle)
// sameeragarwal@google.com (Sameer Agarwal)
// thadh@gmail.com (Thad Hughes)
// tbennun@gmail.com (Tal Ben-Nun)
#ifndef CERES_PUBLIC_DYNAMIC_NUMERIC_DIFF_COST_FUNCTION_H_
#define CERES_PUBLIC_DYNAMIC_NUMERIC_DIFF_COST_FUNCTION_H_
#include <cmath>
#include <memory>
#include <numeric>
#include <vector>
#include "ceres/dynamic_cost_function.h"
#include "ceres/internal/eigen.h"
#include "ceres/internal/numeric_diff.h"
#include "ceres/internal/parameter_dims.h"
#include "ceres/numeric_diff_options.h"
#include "glog/logging.h"
namespace ceres {
// This numeric diff implementation differs from the one found in
// numeric_diff_cost_function.h by supporting numericdiff on cost
// functions with variable numbers of parameters with variable
// sizes. With the other implementation, all the sizes (both the
// number of parameter blocks and the size of each block) must be
// fixed at compile time.
//
// The functor API differs slightly from the API for fixed size
// numeric diff; the expected interface for the cost functors is:
//
// struct MyCostFunctor {
// bool operator()(double const*
// const* parameters,
// double* residuals) const {
// // Use parameters[i] to access the i'th parameter block.
// }
// }
//
// Since the sizing of the parameters is done at runtime, you must
// also specify the sizes after creating the
// DynamicNumericDiffCostFunction. For example:
//
// DynamicAutoDiffCostFunction<MyCostFunctor, CENTRAL> cost_function(
// new MyCostFunctor());
// cost_function.AddParameterBlock(5);
// cost_function.AddParameterBlock(10);
// cost_function.SetNumResiduals(21);
template <typename CostFunctor, NumericDiffMethodType method = CENTRAL>
class DynamicNumericDiffCostFunction : public DynamicCostFunction {
public:
explicit DynamicNumericDiffCostFunction(
const CostFunctor* functor,
Ownership ownership = TAKE_OWNERSHIP,
const NumericDiffOptions& options = NumericDiffOptions())
: functor_(functor), ownership_(ownership), options_(options) {}
virtual ~DynamicNumericDiffCostFunction() {
if (ownership_ != TAKE_OWNERSHIP) {
functor_.release();
}
}
bool Evaluate(double const* const* parameters,
double* residuals,
double** jacobians) const override {
using internal::NumericDiff;
CHECK_GT(num_residuals(), 0)
<< "You must call DynamicNumericDiffCostFunction::SetNumResiduals() "
<< "before DynamicNumericDiffCostFunction::Evaluate().";
const std::vector<int32_t>& block_sizes = parameter_block_sizes();
CHECK(!block_sizes.empty())
<< "You must call DynamicNumericDiffCostFunction::AddParameterBlock() "
<< "before DynamicNumericDiffCostFunction::Evaluate().";
const bool status =
internal::VariadicEvaluate<internal::DynamicParameterDims>(
*functor_.get(), parameters, residuals);
if (jacobians == NULL || !status) {
return status;
}
// Create local space for a copy of the parameters which will get mutated.
int parameters_size = accumulate(block_sizes.begin(), block_sizes.end(), 0);
std::vector<double> parameters_copy(parameters_size);
std::vector<double*> parameters_references_copy(block_sizes.size());
parameters_references_copy[0] = &parameters_copy[0];
for (size_t block = 1; block < block_sizes.size(); ++block) {
parameters_references_copy[block] =
parameters_references_copy[block - 1] + block_sizes[block - 1];
}
// Copy the parameters into the local temp space.
for (size_t block = 0; block < block_sizes.size(); ++block) {
memcpy(parameters_references_copy[block],
parameters[block],
block_sizes[block] * sizeof(*parameters[block]));
}
for (size_t block = 0; block < block_sizes.size(); ++block) {
if (jacobians[block] != NULL &&
!NumericDiff<CostFunctor,
method,
ceres::DYNAMIC,
internal::DynamicParameterDims,
ceres::DYNAMIC,
ceres::DYNAMIC>::
EvaluateJacobianForParameterBlock(functor_.get(),
residuals,
options_,
this->num_residuals(),
block,
block_sizes[block],
&parameters_references_copy[0],
jacobians[block])) {
return false;
}
}
return true;
}
private:
std::unique_ptr<const CostFunctor> functor_;
Ownership ownership_;
NumericDiffOptions options_;
};
} // namespace ceres
#endif // CERES_PUBLIC_DYNAMIC_AUTODIFF_COST_FUNCTION_H_