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|---|---|---|---|
| 1 | /////////////////////////////////////////////////////////////////////////////// | ||
| 2 | // BSD 3-Clause License | ||
| 3 | // | ||
| 4 | // Copyright (C) 2020-2025, LAAS-CNRS, University of Edinburgh, | ||
| 5 | // Heriot-Watt University | ||
| 6 | // Copyright note valid unless otherwise stated in individual files. | ||
| 7 | // All rights reserved. | ||
| 8 | /////////////////////////////////////////////////////////////////////////////// | ||
| 9 | |||
| 10 | #ifndef CROCODDYL_CORE_ACTIVATIONS_QUADRATIC_FLAT_LOG_HPP_ | ||
| 11 | #define CROCODDYL_CORE_ACTIVATIONS_QUADRATIC_FLAT_LOG_HPP_ | ||
| 12 | |||
| 13 | #include "crocoddyl/core/activation-base.hpp" | ||
| 14 | #include "crocoddyl/core/fwd.hpp" | ||
| 15 | |||
| 16 | namespace crocoddyl { | ||
| 17 | |||
| 18 | /** | ||
| 19 | * @brief Quadratic-flat-log activation | ||
| 20 | * | ||
| 21 | * This activation function describes a logarithmic quadratic activation | ||
| 22 | * depending on the quadratic norm of a residual vector, i.e. \f[ | ||
| 23 | * \begin{equation} log(1 + \|\mathbf{r}\|^2 / \alpha) \end{equation} \f] where | ||
| 24 | * \f$\alpha\f$ defines the width of the quadratic basin, \f$r\f$ is the scalar | ||
| 25 | * residual, \f$nr\f$ is the dimension of the residual vector. | ||
| 26 | * | ||
| 27 | * The computation of the function and it derivatives are carried out in | ||
| 28 | * `calc()` and `caldDiff()`, respectively. | ||
| 29 | * | ||
| 30 | * \sa `calc()`, `calcDiff()`, `createData()` | ||
| 31 | */ | ||
| 32 | template <typename _Scalar> | ||
| 33 | class ActivationModelQuadFlatLogTpl | ||
| 34 | : public ActivationModelAbstractTpl<_Scalar> { | ||
| 35 | public: | ||
| 36 | EIGEN_MAKE_ALIGNED_OPERATOR_NEW | ||
| 37 | ✗ | CROCODDYL_DERIVED_CAST(ActivationModelBase, ActivationModelQuadFlatLogTpl) | |
| 38 | |||
| 39 | typedef _Scalar Scalar; | ||
| 40 | typedef MathBaseTpl<Scalar> MathBase; | ||
| 41 | typedef ActivationModelAbstractTpl<Scalar> Base; | ||
| 42 | typedef ActivationDataAbstractTpl<Scalar> ActivationDataAbstract; | ||
| 43 | typedef ActivationDataQuadFlatLogTpl<Scalar> Data; | ||
| 44 | typedef typename MathBase::VectorXs VectorXs; | ||
| 45 | typedef typename MathBase::MatrixXs MatrixXs; | ||
| 46 | |||
| 47 | /* | ||
| 48 | * @brief Initialize the quadratic-flat-log activation model | ||
| 49 | * | ||
| 50 | * The default `alpha` value is defined as 1. | ||
| 51 | * | ||
| 52 | * @param[in] nr Dimension of the residual vector | ||
| 53 | * @param[in] alpha Width of quadratic basin (default: 1.) | ||
| 54 | */ | ||
| 55 | |||
| 56 | ✗ | explicit ActivationModelQuadFlatLogTpl(const std::size_t nr, | |
| 57 | const Scalar alpha = Scalar(1.)) | ||
| 58 | ✗ | : Base(nr), alpha_(alpha) { | |
| 59 | ✗ | if (alpha < Scalar(0.)) { | |
| 60 | ✗ | throw_pretty("Invalid argument: " << "alpha should be a positive value"); | |
| 61 | } | ||
| 62 | ✗ | }; | |
| 63 | ✗ | virtual ~ActivationModelQuadFlatLogTpl() = default; | |
| 64 | |||
| 65 | /* | ||
| 66 | * @brief Compute the quadratic-flat-log function | ||
| 67 | * | ||
| 68 | * @param[in] data Quadratic-log activation data | ||
| 69 | * @param[in] r Residual vector \f$\mathbf{r}\in\mathbb{R}^{nr}\f$ | ||
| 70 | */ | ||
| 71 | ✗ | virtual void calc(const std::shared_ptr<ActivationDataAbstract> &data, | |
| 72 | const Eigen::Ref<const VectorXs> &r) override { | ||
| 73 | ✗ | if (static_cast<std::size_t>(r.size()) != nr_) { | |
| 74 | ✗ | throw_pretty( | |
| 75 | "Invalid argument: " << "r has wrong dimension (it should be " + | ||
| 76 | std::to_string(nr_) + ")"); | ||
| 77 | } | ||
| 78 | ✗ | std::shared_ptr<Data> d = std::static_pointer_cast<Data>(data); | |
| 79 | ✗ | d->a0 = r.squaredNorm() / alpha_; | |
| 80 | ✗ | data->a_value = log(Scalar(1.0) + d->a0); | |
| 81 | ✗ | }; | |
| 82 | |||
| 83 | /* | ||
| 84 | * @brief Compute the derivatives of the quadratic-flat-log function | ||
| 85 | * | ||
| 86 | * @param[in] data Quadratic-log activation data | ||
| 87 | * @param[in] r Residual vector \f$\mathbf{r}\in\mathbb{R}^{nr}\f$ | ||
| 88 | */ | ||
| 89 | ✗ | virtual void calcDiff(const std::shared_ptr<ActivationDataAbstract> &data, | |
| 90 | const Eigen::Ref<const VectorXs> &r) override { | ||
| 91 | ✗ | if (static_cast<std::size_t>(r.size()) != nr_) { | |
| 92 | ✗ | throw_pretty( | |
| 93 | "Invalid argument: " << "r has wrong dimension (it should be " + | ||
| 94 | std::to_string(nr_) + ")"); | ||
| 95 | } | ||
| 96 | ✗ | std::shared_ptr<Data> d = std::static_pointer_cast<Data>(data); | |
| 97 | |||
| 98 | ✗ | d->a1 = Scalar(2.0) / (alpha_ + alpha_ * d->a0); | |
| 99 | ✗ | data->Ar = d->a1 * r; | |
| 100 | ✗ | data->Arr.diagonal() = -d->a1 * d->a1 * r.array().square(); | |
| 101 | ✗ | data->Arr.diagonal().array() += d->a1; | |
| 102 | ✗ | }; | |
| 103 | |||
| 104 | /* | ||
| 105 | * @brief Create the quadratic-flat-log activation data | ||
| 106 | * | ||
| 107 | * @return the activation data | ||
| 108 | */ | ||
| 109 | ✗ | virtual std::shared_ptr<ActivationDataAbstract> createData() override { | |
| 110 | ✗ | std::shared_ptr<Data> data = | |
| 111 | ✗ | std::allocate_shared<Data>(Eigen::aligned_allocator<Data>(), this); | |
| 112 | ✗ | return data; | |
| 113 | ✗ | }; | |
| 114 | |||
| 115 | template <typename NewScalar> | ||
| 116 | ✗ | ActivationModelQuadFlatLogTpl<NewScalar> cast() const { | |
| 117 | typedef ActivationModelQuadFlatLogTpl<NewScalar> ReturnType; | ||
| 118 | ✗ | ReturnType res(nr_, scalar_cast<NewScalar>(alpha_)); | |
| 119 | ✗ | return res; | |
| 120 | } | ||
| 121 | |||
| 122 | ✗ | Scalar get_alpha() const { return alpha_; }; | |
| 123 | ✗ | void set_alpha(const Scalar alpha) { alpha_ = alpha; }; | |
| 124 | |||
| 125 | /** | ||
| 126 | * @brief Print relevant information of the quadratic flat-log model | ||
| 127 | * | ||
| 128 | * @param[out] os Output stream object | ||
| 129 | */ | ||
| 130 | ✗ | virtual void print(std::ostream &os) const override { | |
| 131 | ✗ | os << "ActivationModelQuadFlatLog {nr=" << nr_ << ", a=" << alpha_ << "}"; | |
| 132 | ✗ | } | |
| 133 | |||
| 134 | protected: | ||
| 135 | using Base::nr_; //!< Dimension of the residual vector | ||
| 136 | |||
| 137 | private: | ||
| 138 | Scalar alpha_; //!< Width of quadratic basin | ||
| 139 | }; | ||
| 140 | |||
| 141 | /* | ||
| 142 | * @brief Data structure of the quadratic-flat-log activation | ||
| 143 | * | ||
| 144 | * @param[in] a0 computed in calc to avoid recomputation | ||
| 145 | * @param[in] a1 computed in calcDiff to avoid recomputation | ||
| 146 | */ | ||
| 147 | template <typename _Scalar> | ||
| 148 | struct ActivationDataQuadFlatLogTpl | ||
| 149 | : public ActivationDataAbstractTpl<_Scalar> { | ||
| 150 | EIGEN_MAKE_ALIGNED_OPERATOR_NEW | ||
| 151 | |||
| 152 | typedef _Scalar Scalar; | ||
| 153 | typedef MathBaseTpl<Scalar> MathBase; | ||
| 154 | typedef typename MathBase::VectorXs VectorXs; | ||
| 155 | typedef typename MathBase::DiagonalMatrixXs DiagonalMatrixXs; | ||
| 156 | typedef ActivationDataAbstractTpl<Scalar> Base; | ||
| 157 | |||
| 158 | template <typename Activation> | ||
| 159 | ✗ | explicit ActivationDataQuadFlatLogTpl(Activation *const activation) | |
| 160 | ✗ | : Base(activation), a0(Scalar(0)), a1(Scalar(0)) {} | |
| 161 | ✗ | virtual ~ActivationDataQuadFlatLogTpl() = default; | |
| 162 | |||
| 163 | Scalar a0; | ||
| 164 | Scalar a1; | ||
| 165 | |||
| 166 | using Base::a_value; | ||
| 167 | using Base::Ar; | ||
| 168 | using Base::Arr; | ||
| 169 | }; | ||
| 170 | |||
| 171 | } // namespace crocoddyl | ||
| 172 | |||
| 173 | CROCODDYL_DECLARE_EXTERN_TEMPLATE_CLASS( | ||
| 174 | crocoddyl::ActivationModelQuadFlatLogTpl) | ||
| 175 | CROCODDYL_DECLARE_EXTERN_TEMPLATE_STRUCT( | ||
| 176 | crocoddyl::ActivationDataQuadFlatLogTpl) | ||
| 177 | |||
| 178 | #endif // CROCODDYL_CORE_ACTIVATIONS_QUADRATIC_FLAT_LOG_HPP_ | ||
| 179 |