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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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// Auto-generated file for double |
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#include "crocoddyl/core/activations/smooth-1norm.hpp" |
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#include "python/crocoddyl/core/activation-base.hpp" |
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#include "python/crocoddyl/core/core.hpp" |
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namespace crocoddyl { |
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namespace python { |
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template <typename Model> |
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struct ActivationModelSmooth1NormVisitor |
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: public bp::def_visitor<ActivationModelSmooth1NormVisitor<Model>> { |
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typedef typename Model::Scalar Scalar; |
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template <class PyClass> |
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void visit(PyClass& cl) const { |
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cl.def("calc", &Model::calc, bp::args("self", "data", "r"), |
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"Compute the smooth-abs function.\n\n" |
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":param data: activation data\n" |
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":param r: residual vector") |
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.def("calcDiff", &Model::calcDiff, bp::args("self", "data", "r"), |
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"Compute the derivatives of a smooth-abs function.\n\n" |
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"It assumes that calc has been run first.\n" |
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":param data: activation data\n" |
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":param r: residual vector \n") |
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.def("createData", &Model::createData, bp::args("self"), |
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"Create the smooth-abs activation data.\n\n"); |
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} |
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}; |
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template <typename Data> |
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struct ActivationDataSmooth1NormVisitor |
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: public bp::def_visitor<ActivationDataSmooth1NormVisitor<Data>> { |
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typedef typename Data::Scalar Scalar; |
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template <class PyClass> |
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void visit(PyClass& cl) const { |
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cl.add_property( |
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"a", bp::make_getter(&Data::a, bp::return_internal_reference<>()), |
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"sqrt{eps + ||ri||^2} value"); |
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} |
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}; |
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#define CROCODDYL_ACTIVATION_MODEL_SMOOTH1NORM_PYTHON_BINDINGS(Scalar) \ |
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typedef ActivationModelSmooth1NormTpl<Scalar> Model; \ |
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typedef ActivationModelAbstractTpl<Scalar> ModelBase; \ |
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bp::register_ptr_to_python<std::shared_ptr<Model>>(); \ |
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bp::class_<Model, bp::bases<ModelBase>>( \ |
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"ActivationModelSmooth1Norm", \ |
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"Smooth-absolute activation model.\n\n" \ |
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"It describes a smooth representation of an absolute activation " \ |
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"(1-norm), i.e., sum^nr_{i=0} sqrt{eps + ||ri||^2}, where ri is the " \ |
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"scalar residual for the i constraints, and nr is the dimension of the " \ |
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"residual vector.", \ |
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bp::init<std::size_t, bp::optional<Scalar>>( \ |
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bp::args("self", "nr", "eps"), \ |
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"Initialize the activation model.\n\n" \ |
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":param nr: dimension of the residual vector\n" \ |
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":param eps: smoothing factor (default: 1.)")) \ |
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.def(ActivationModelSmooth1NormVisitor<Model>()) \ |
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.def(CastVisitor<Model>()) \ |
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.def(PrintableVisitor<Model>()) \ |
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.def(CopyableVisitor<Model>()); |
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#define CROCODDYL_ACTIVATION_DATA_SMOOTH1NORM_PYTHON_BINDINGS(Scalar) \ |
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typedef ActivationDataSmooth1NormTpl<Scalar> Data; \ |
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typedef ActivationDataAbstractTpl<Scalar> DataBase; \ |
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typedef ActivationModelSmooth1NormTpl<Scalar> Model; \ |
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bp::register_ptr_to_python<std::shared_ptr<Data>>(); \ |
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bp::class_<Data, bp::bases<DataBase>>( \ |
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"ActivationDataSmooth1Norm", "Data for smooth-abs activation.\n\n", \ |
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bp::init<Model*>(bp::args("self", "model"), \ |
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"Create smooth-abs activation data.\n\n" \ |
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":param model: smooth-abs activation model")) \ |
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.def(ActivationDataSmooth1NormVisitor<Data>()) \ |
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.def(CopyableVisitor<Data>()); |
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void exposeActivationSmooth1Norm() { |
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CROCODDYL_ACTIVATION_MODEL_SMOOTH1NORM_PYTHON_BINDINGS(double) |
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CROCODDYL_ACTIVATION_DATA_SMOOTH1NORM_PYTHON_BINDINGS(double) |
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} |
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} // namespace python |
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} // namespace crocoddyl |
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