diff options
Diffstat (limited to 'extern/ceres/include/ceres/loss_function.h')
| -rw-r--r-- | extern/ceres/include/ceres/loss_function.h | 48 |
1 files changed, 25 insertions, 23 deletions
diff --git a/extern/ceres/include/ceres/loss_function.h b/extern/ceres/include/ceres/loss_function.h index 7aabf7dfce1..8a5a37ff665 100644 --- a/extern/ceres/include/ceres/loss_function.h +++ b/extern/ceres/include/ceres/loss_function.h @@ -35,7 +35,7 @@ // // For least squares problem where there are no outliers and standard // squared loss is expected, it is not necessary to create a loss -// function; instead passing a NULL to the problem when adding +// function; instead passing a nullptr to the problem when adding // residuals implies a standard squared loss. // // For least squares problems where the minimization may encounter @@ -78,6 +78,7 @@ #include <memory> #include "ceres/internal/disable_warnings.h" +#include "ceres/internal/export.h" #include "ceres/types.h" #include "glog/logging.h" @@ -85,7 +86,7 @@ namespace ceres { class CERES_EXPORT LossFunction { public: - virtual ~LossFunction() {} + virtual ~LossFunction(); // For a residual vector with squared 2-norm 'sq_norm', this method // is required to fill in the value and derivatives of the loss @@ -125,10 +126,10 @@ class CERES_EXPORT LossFunction { // // At s = 0: rho = [0, 1, 0]. // -// It is not normally necessary to use this, as passing NULL for the +// It is not normally necessary to use this, as passing nullptr for the // loss function when building the problem accomplishes the same // thing. -class CERES_EXPORT TrivialLoss : public LossFunction { +class CERES_EXPORT TrivialLoss final : public LossFunction { public: void Evaluate(double, double*) const override; }; @@ -171,7 +172,7 @@ class CERES_EXPORT TrivialLoss : public LossFunction { // // The scaling parameter 'a' corresponds to 'delta' on this page: // http://en.wikipedia.org/wiki/Huber_Loss_Function -class CERES_EXPORT HuberLoss : public LossFunction { +class CERES_EXPORT HuberLoss final : public LossFunction { public: explicit HuberLoss(double a) : a_(a), b_(a * a) {} void Evaluate(double, double*) const override; @@ -187,7 +188,7 @@ class CERES_EXPORT HuberLoss : public LossFunction { // rho(s) = 2 (sqrt(1 + s) - 1). // // At s = 0: rho = [0, 1, -1 / (2 * a^2)]. -class CERES_EXPORT SoftLOneLoss : public LossFunction { +class CERES_EXPORT SoftLOneLoss final : public LossFunction { public: explicit SoftLOneLoss(double a) : b_(a * a), c_(1 / b_) {} void Evaluate(double, double*) const override; @@ -204,7 +205,7 @@ class CERES_EXPORT SoftLOneLoss : public LossFunction { // rho(s) = log(1 + s). // // At s = 0: rho = [0, 1, -1 / a^2]. -class CERES_EXPORT CauchyLoss : public LossFunction { +class CERES_EXPORT CauchyLoss final : public LossFunction { public: explicit CauchyLoss(double a) : b_(a * a), c_(1 / b_) {} void Evaluate(double, double*) const override; @@ -225,7 +226,7 @@ class CERES_EXPORT CauchyLoss : public LossFunction { // rho(s) = a atan(s / a). // // At s = 0: rho = [0, 1, 0]. -class CERES_EXPORT ArctanLoss : public LossFunction { +class CERES_EXPORT ArctanLoss final : public LossFunction { public: explicit ArctanLoss(double a) : a_(a), b_(1 / (a * a)) {} void Evaluate(double, double*) const override; @@ -264,7 +265,7 @@ class CERES_EXPORT ArctanLoss : public LossFunction { // concentrated in the range a - b to a + b. // // At s = 0: rho = [0, ~0, ~0]. -class CERES_EXPORT TolerantLoss : public LossFunction { +class CERES_EXPORT TolerantLoss final : public LossFunction { public: explicit TolerantLoss(double a, double b); void Evaluate(double, double*) const override; @@ -283,7 +284,7 @@ class CERES_EXPORT TolerantLoss : public LossFunction { // rho(s) = a^2 / 3 for s > a^2. // // At s = 0: rho = [0, 1, -2 / a^2] -class CERES_EXPORT TukeyLoss : public ceres::LossFunction { +class CERES_EXPORT TukeyLoss final : public ceres::LossFunction { public: explicit TukeyLoss(double a) : a_squared_(a * a) {} void Evaluate(double, double*) const override; @@ -294,14 +295,14 @@ class CERES_EXPORT TukeyLoss : public ceres::LossFunction { // Composition of two loss functions. The error is the result of first // evaluating g followed by f to yield the composition f(g(s)). -// The loss functions must not be NULL. -class CERES_EXPORT ComposedLoss : public LossFunction { +// The loss functions must not be nullptr. +class CERES_EXPORT ComposedLoss final : public LossFunction { public: explicit ComposedLoss(const LossFunction* f, Ownership ownership_f, const LossFunction* g, Ownership ownership_g); - virtual ~ComposedLoss(); + ~ComposedLoss() override; void Evaluate(double, double*) const override; private: @@ -322,11 +323,11 @@ class CERES_EXPORT ComposedLoss : public LossFunction { // s -> a * rho'(s) // s -> a * rho''(s) // -// Since we treat the a NULL Loss function as the Identity loss -// function, rho = NULL is a valid input and will result in the input +// Since we treat the a nullptr Loss function as the Identity loss +// function, rho = nullptr is a valid input and will result in the input // being scaled by a. This provides a simple way of implementing a // scaled ResidualBlock. -class CERES_EXPORT ScaledLoss : public LossFunction { +class CERES_EXPORT ScaledLoss final : public LossFunction { public: // Constructs a ScaledLoss wrapping another loss function. Takes // ownership of the wrapped loss function or not depending on the @@ -336,7 +337,7 @@ class CERES_EXPORT ScaledLoss : public LossFunction { ScaledLoss(const ScaledLoss&) = delete; void operator=(const ScaledLoss&) = delete; - virtual ~ScaledLoss() { + ~ScaledLoss() override { if (ownership_ == DO_NOT_TAKE_OWNERSHIP) { rho_.release(); } @@ -361,8 +362,8 @@ class CERES_EXPORT ScaledLoss : public LossFunction { // whose scale can be mutated after an optimization problem has been // constructed. // -// Since we treat the a NULL Loss function as the Identity loss -// function, rho = NULL is a valid input. +// Since we treat the a nullptr Loss function as the Identity loss +// function, rho = nullptr is a valid input. // // Example usage // @@ -374,7 +375,8 @@ class CERES_EXPORT ScaledLoss : public LossFunction { // new AutoDiffCostFunction < UW_Camera_Mapper, 2, 9, 3>( // new UW_Camera_Mapper(feature_x, feature_y)); // -// LossFunctionWrapper* loss_function(new HuberLoss(1.0), TAKE_OWNERSHIP); +// LossFunctionWrapper* loss_function = new LossFunctionWrapper( +// new HuberLoss(1.0), TAKE_OWNERSHIP); // // problem.AddResidualBlock(cost_function, loss_function, parameters); // @@ -387,7 +389,7 @@ class CERES_EXPORT ScaledLoss : public LossFunction { // // Solve(options, &problem, &summary) // -class CERES_EXPORT LossFunctionWrapper : public LossFunction { +class CERES_EXPORT LossFunctionWrapper final : public LossFunction { public: LossFunctionWrapper(LossFunction* rho, Ownership ownership) : rho_(rho), ownership_(ownership) {} @@ -395,14 +397,14 @@ class CERES_EXPORT LossFunctionWrapper : public LossFunction { LossFunctionWrapper(const LossFunctionWrapper&) = delete; void operator=(const LossFunctionWrapper&) = delete; - virtual ~LossFunctionWrapper() { + ~LossFunctionWrapper() override { if (ownership_ == DO_NOT_TAKE_OWNERSHIP) { rho_.release(); } } void Evaluate(double sq_norm, double out[3]) const override { - if (rho_.get() == NULL) { + if (rho_.get() == nullptr) { out[0] = sq_norm; out[1] = 1.0; out[2] = 0.0; |