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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.
// Copyright 2007 Google Inc. All Rights Reserved.
//
// Authors: wjr@google.com (William Rucklidge),
// keir@google.com (Keir Mierle),
// dgossow@google.com (David Gossow)
#ifndef CERES_PUBLIC_GRADIENT_CHECKER_H_
#define CERES_PUBLIC_GRADIENT_CHECKER_H_
#include <memory>
#include <string>
#include <vector>
#include "ceres/cost_function.h"
#include "ceres/dynamic_numeric_diff_cost_function.h"
#include "ceres/internal/eigen.h"
#include "ceres/internal/fixed_array.h"
#include "ceres/local_parameterization.h"
#include "glog/logging.h"
namespace ceres {
// GradientChecker compares the Jacobians returned by a cost function against
// derivatives estimated using finite differencing.
//
// The condition enforced is that
//
// (J_actual(i, j) - J_numeric(i, j))
// ------------------------------------ < relative_precision
// max(J_actual(i, j), J_numeric(i, j))
//
// where J_actual(i, j) is the jacobian as computed by the supplied cost
// function (by the user) multiplied by the local parameterization Jacobian
// and J_numeric is the jacobian as computed by finite differences, multiplied
// by the local parameterization Jacobian as well.
//
// How to use: Fill in an array of pointers to parameter blocks for your
// CostFunction, and then call Probe(). Check that the return value is 'true'.
class CERES_EXPORT GradientChecker {
public:
// This will not take ownership of the cost function or local
// parameterizations.
//
// function: The cost function to probe.
// local_parameterizations: A vector of local parameterizations for each
// parameter. May be NULL or contain NULL pointers to indicate that the
// respective parameter does not have a local parameterization.
// options: Options to use for numerical differentiation.
GradientChecker(
const CostFunction* function,
const std::vector<const LocalParameterization*>* local_parameterizations,
const NumericDiffOptions& options);
// Contains results from a call to Probe for later inspection.
struct CERES_EXPORT ProbeResults {
// The return value of the cost function.
bool return_value;
// Computed residual vector.
Vector residuals;
// The sizes of the Jacobians below are dictated by the cost function's
// parameter block size and residual block sizes. If a parameter block
// has a local parameterization associated with it, the size of the "local"
// Jacobian will be determined by the local parameterization dimension and
// residual block size, otherwise it will be identical to the regular
// Jacobian.
// Derivatives as computed by the cost function.
std::vector<Matrix> jacobians;
// Derivatives as computed by the cost function in local space.
std::vector<Matrix> local_jacobians;
// Derivatives as computed by numerical differentiation in local space.
std::vector<Matrix> numeric_jacobians;
// Derivatives as computed by numerical differentiation in local space.
std::vector<Matrix> local_numeric_jacobians;
// Contains the maximum relative error found in the local Jacobians.
double maximum_relative_error;
// If an error was detected, this will contain a detailed description of
// that error.
std::string error_log;
};
// Call the cost function, compute alternative Jacobians using finite
// differencing and compare results. If local parameterizations are given,
// the Jacobians will be multiplied by the local parameterization Jacobians
// before performing the check, which effectively means that all errors along
// the null space of the local parameterization will be ignored.
// Returns false if the Jacobians don't match, the cost function return false,
// or if the cost function returns different residual when called with a
// Jacobian output argument vs. calling it without. Otherwise returns true.
//
// parameters: The parameter values at which to probe.
// relative_precision: A threshold for the relative difference between the
// Jacobians. If the Jacobians differ by more than this amount, then the
// probe fails.
// results: On return, the Jacobians (and other information) will be stored
// here. May be NULL.
//
// Returns true if no problems are detected and the difference between the
// Jacobians is less than error_tolerance.
bool Probe(double const* const* parameters,
double relative_precision,
ProbeResults* results) const;
private:
GradientChecker() = delete;
GradientChecker(const GradientChecker&) = delete;
void operator=(const GradientChecker&) = delete;
std::vector<const LocalParameterization*> local_parameterizations_;
const CostFunction* function_;
std::unique_ptr<CostFunction> finite_diff_cost_function_;
};
} // namespace ceres
#endif // CERES_PUBLIC_GRADIENT_CHECKER_H_
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