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/////////////////////////////////////////////////////////////////////////////// |
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// BSD 3-Clause License |
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// |
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// Copyright (C) 2019-2025, LAAS-CNRS, University of Edinburgh, |
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// Heriot-Watt University |
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// Copyright note valid unless otherwise stated in individual files. |
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// All rights reserved. |
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/////////////////////////////////////////////////////////////////////////////// |
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#ifndef CROCODDYL_CORE_ACTIVATIONS_SMOOTH_1NORM_HPP_ |
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#define CROCODDYL_CORE_ACTIVATIONS_SMOOTH_1NORM_HPP_ |
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#include "crocoddyl/core/activation-base.hpp" |
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#include "crocoddyl/core/fwd.hpp" |
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namespace crocoddyl { |
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/** |
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* @brief Smooth-abs activation |
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* |
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* This activation function describes a smooth representation of an absolute |
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* activation (1-norm) for each element of a residual vector, i.e. \f[ |
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* \begin{equation} sum^nr_{i=0} \sqrt{\epsilon + \|r_i\|^2} \end{equation} \f] |
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* where \f$\epsilon\f$ defines the smoothing factor, \f$r_i\f$ is the scalar |
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* residual for the \f$i\f$ constraints, \f$nr\f$ is the dimension of the |
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* residual vector. |
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* |
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* The computation of the function and it derivatives are carried out in |
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* `calc()` and `caldDiff()`, respectively. |
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* |
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* \sa `calc()`, `calcDiff()`, `createData()` |
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*/ |
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template <typename _Scalar> |
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class ActivationModelSmooth1NormTpl |
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: public ActivationModelAbstractTpl<_Scalar> { |
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public: |
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EIGEN_MAKE_ALIGNED_OPERATOR_NEW |
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CROCODDYL_DERIVED_CAST(ActivationModelBase, ActivationModelSmooth1NormTpl) |
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typedef _Scalar Scalar; |
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typedef MathBaseTpl<Scalar> MathBase; |
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typedef ActivationModelAbstractTpl<Scalar> Base; |
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typedef ActivationDataAbstractTpl<Scalar> ActivationDataAbstract; |
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typedef ActivationDataSmooth1NormTpl<Scalar> Data; |
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typedef typename MathBase::VectorXs VectorXs; |
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typedef typename MathBase::MatrixXs MatrixXs; |
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/** |
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* @brief Initialize the smooth-abs activation model |
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* |
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* The default `eps` value is defined as 1. |
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* |
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* @param[in] nr Dimension of the residual vector |
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* @param[in] eps Smoothing factor (default: 1.) |
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*/ |
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explicit ActivationModelSmooth1NormTpl(const std::size_t nr, |
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const Scalar eps = Scalar(1.)) |
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: Base(nr), eps_(eps) { |
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if (eps < Scalar(0.)) { |
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throw_pretty("Invalid argument: " << "eps should be a positive value"); |
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} |
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if (eps == Scalar(0.)) { |
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std::cerr << "Warning: eps=0 leads to derivatives discontinuities in the " |
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"origin, it becomes the absolute function" |
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<< std::endl; |
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} |
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}; |
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virtual ~ActivationModelSmooth1NormTpl() = default; |
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/** |
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* @brief Compute the smooth-abs function |
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* |
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* @param[in] data Smooth-abs activation data |
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* @param[in] r Residual vector \f$\mathbf{r}\in\mathbb{R}^{nr}\f$ |
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*/ |
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virtual void calc(const std::shared_ptr<ActivationDataAbstract>& data, |
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const Eigen::Ref<const VectorXs>& r) override { |
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if (static_cast<std::size_t>(r.size()) != nr_) { |
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throw_pretty( |
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"Invalid argument: " << "r has wrong dimension (it should be " + |
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std::to_string(nr_) + ")"); |
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} |
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std::shared_ptr<Data> d = std::static_pointer_cast<Data>(data); |
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d->a = (r.array().cwiseAbs2().array() + eps_).array().cwiseSqrt(); |
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data->a_value = d->a.sum(); |
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}; |
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/** |
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* @brief Compute the derivatives of the smooth-abs function |
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* |
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* @param[in] data Smooth-abs activation data |
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* @param[in] r Residual vector \f$\mathbf{r}\in\mathbb{R}^{nr}\f$ |
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*/ |
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virtual void calcDiff(const std::shared_ptr<ActivationDataAbstract>& data, |
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const Eigen::Ref<const VectorXs>& r) override { |
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if (static_cast<std::size_t>(r.size()) != nr_) { |
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throw_pretty( |
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"Invalid argument: " << "r has wrong dimension (it should be " + |
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std::to_string(nr_) + ")"); |
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} |
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std::shared_ptr<Data> d = std::static_pointer_cast<Data>(data); |
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data->Ar = r.cwiseProduct(d->a.cwiseInverse()); |
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data->Arr.diagonal() = |
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d->a.cwiseProduct(d->a).cwiseProduct(d->a).cwiseInverse(); |
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}; |
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/** |
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* @brief Create the smooth-abs activation data |
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* |
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* @return the activation data |
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*/ |
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virtual std::shared_ptr<ActivationDataAbstract> createData() override { |
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return std::allocate_shared<Data>(Eigen::aligned_allocator<Data>(), this); |
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}; |
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template <typename NewScalar> |
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ActivationModelSmooth1NormTpl<NewScalar> cast() const { |
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typedef ActivationModelSmooth1NormTpl<NewScalar> ReturnType; |
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ReturnType res(nr_, scalar_cast<NewScalar>(eps_)); |
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return res; |
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} |
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/** |
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* @brief Print relevant information of the smooth-1norm model |
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* |
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* @param[out] os Output stream object |
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*/ |
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virtual void print(std::ostream& os) const override { |
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os << "ActivationModelSmooth1Norm {nr=" << nr_ << ", eps=" << eps_ << "}"; |
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} |
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protected: |
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using Base::nr_; //!< Dimension of the residual vector |
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Scalar eps_; //!< Smoothing factor |
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}; |
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template <typename _Scalar> |
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struct ActivationDataSmooth1NormTpl |
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: public ActivationDataAbstractTpl<_Scalar> { |
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EIGEN_MAKE_ALIGNED_OPERATOR_NEW |
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typedef _Scalar Scalar; |
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typedef ActivationDataAbstractTpl<Scalar> Base; |
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typedef MathBaseTpl<Scalar> MathBase; |
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typedef typename MathBase::VectorXs VectorXs; |
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typedef typename MathBase::MatrixXs MatrixXs; |
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typedef typename MathBase::DiagonalMatrixXs DiagonalMatrixXs; |
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template <typename Activation> |
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explicit ActivationDataSmooth1NormTpl(Activation* const activation) |
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: Base(activation), a(VectorXs::Zero(activation->get_nr())) {} |
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virtual ~ActivationDataSmooth1NormTpl() = default; |
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VectorXs a; |
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using Base::a_value; |
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using Base::Ar; |
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using Base::Arr; |
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}; |
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} // namespace crocoddyl |
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CROCODDYL_DECLARE_EXTERN_TEMPLATE_CLASS( |
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crocoddyl::ActivationModelSmooth1NormTpl) |
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CROCODDYL_DECLARE_EXTERN_TEMPLATE_STRUCT( |
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crocoddyl::ActivationDataSmooth1NormTpl) |
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#endif // CROCODDYL_CORE_ACTIVATIONS_SMOOTH_1NORM_HPP_ |
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