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/////////////////////////////////////////////////////////////////////////////// |
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// BSD 3-Clause License |
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// |
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// Copyright (C) 2020, LAAS-CNRS |
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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_2NORM_HPP_ |
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#define CROCODDYL_CORE_ACTIVATIONS_SMOOTH_2NORM_HPP_ |
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#include <stdexcept> |
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#include "crocoddyl/core/activation-base.hpp" |
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#include "crocoddyl/core/fwd.hpp" |
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#include "crocoddyl/core/utils/exception.hpp" |
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namespace crocoddyl { |
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/** |
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* @brief Smooth-2Norm activation |
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* |
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* This activation function describes a smooth representation of a 2-norm of a |
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* residual vector, i.e. \f[ \begin{equation} \sqrt{\epsilon + sum^nr_{i=0} |
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* \|r_i\|^2} \end{equation} \f] where \f$\epsilon\f$ defines the smoothing |
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* factor, \f$r_i\f$ is the scalar residual for the \f$i\f$ constraints, |
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* \f$nr\f$ is the dimension of the 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 ActivationModelSmooth2NormTpl |
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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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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 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-2Norm 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 ActivationModelSmooth2NormTpl(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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✗✓ |
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if (eps < Scalar(0.)) { |
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throw_pretty("Invalid argument: " |
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<< "eps should be a positive value"); |
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} |
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}; |
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virtual ~ActivationModelSmooth2NormTpl(){}; |
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/** |
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* @brief Compute the smooth-2Norm function |
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* |
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* @param[in] data Smooth-2Norm 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 boost::shared_ptr<ActivationDataAbstract>& data, |
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const Eigen::Ref<const VectorXs>& r) { |
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✗✓ |
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if (static_cast<std::size_t>(r.size()) != nr_) { |
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throw_pretty("Invalid argument: " |
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<< "r has wrong dimension (it should be " + |
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std::to_string(nr_) + ")"); |
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} |
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using std::sqrt; |
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data->a_value = sqrt(r.squaredNorm() + eps_); |
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}; |
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/** |
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* @brief Compute the derivatives of the smooth-2Norm function |
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* |
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* @param[in] data Smooth-2Norm 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 boost::shared_ptr<ActivationDataAbstract>& data, |
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const Eigen::Ref<const VectorXs>& r) { |
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✗✓ |
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if (static_cast<std::size_t>(r.size()) != nr_) { |
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throw_pretty("Invalid argument: " |
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<< "r has wrong dimension (it should be " + |
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std::to_string(nr_) + ")"); |
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} |
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✓✗ |
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data->Ar = r / data->a_value; |
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using std::pow; |
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✓✗✓✗
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data->Arr.diagonal().array() = Scalar(1) / pow(data->a_value, 3); |
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}; |
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/** |
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* @brief Create the smooth-2Norm activation data |
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* |
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* @return the activation data |
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*/ |
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virtual boost::shared_ptr<ActivationDataAbstract> createData() { |
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return boost::allocate_shared<ActivationDataAbstract>( |
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✓✗ |
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Eigen::aligned_allocator<ActivationDataAbstract>(), this); |
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}; |
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protected: |
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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 { |
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os << "ActivationModelSmooth2Norm {nr=" << nr_ << ", eps=" << eps_ << "}"; |
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} |
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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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} // namespace crocoddyl |
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#endif // CROCODDYL_CORE_ACTIVATIONS_SMOOTH_2NORM_HPP_ |