transformation.hpp

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/*
 *  Cypress -- C++ Spiking Neural Network Simulation Framework
 *  Copyright (C) 2016  Andreas Stöckel
 *
 *  This program is free software: you can redistribute it and/or modify
 *  it under the terms of the GNU General Public License as published by
 *  the Free Software Foundation, either version 3 of the License, or
 *  (at your option) any later version.
 *
 *  This program is distributed in the hope that it will be useful,
 *  but WITHOUT ANY WARRANTY; without even the implied warranty of
 *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *  GNU General Public License for more details.
 *
 *  You should have received a copy of the GNU General Public License
 *  along with this program.  If not, see <http://www.gnu.org/licenses/>.
 */

#ifndef CYPRESS_CORE_TRANSFORMATION_HPP
#define CYPRESS_CORE_TRANSFORMATION_HPP

#include <functional>
#include <memory>
#include <typeinfo>
#include <unordered_set>
#include <vector>

#include <cypress/core/types.hpp>

namespace cypress {

// Forward declarations
class NeuronType;
class NetworkBase;
class Backend;

template <typename T>
class Population;

struct TransformationProperties {
    size_t cost = 100;

    bool lossy = false;
};

struct TransformationAuxData {
    Real duration;
};

class Transformation {
protected:
    virtual NetworkBase do_transform(const NetworkBase &src,
                                     TransformationAuxData &aux) = 0;

    virtual void do_copy_results(const NetworkBase &src,
                                 NetworkBase &tar) const;

public:
    virtual TransformationProperties properties() const
    {
        return TransformationProperties{};
    }

    virtual std::string id() const = 0;

    NetworkBase transform(const NetworkBase &src, TransformationAuxData &aux);

    void copy_results(const NetworkBase &src, NetworkBase &tar) const;

    virtual ~Transformation(){};
};

using TransformationCtor = std::function<std::unique_ptr<Transformation>()>;

using TransformationTest =
    std::function<bool(const Backend &, const NetworkBase &)>;

using RegisteredTransformation = size_t;

class Transformations {
public:
    static std::vector<TransformationCtor>
    construct_neuron_type_transformation_chain(
        const std::vector<const NeuronType *> &unsupported_types,
        const std::unordered_set<const NeuronType *> &supported_types,
        const std::vector<std::tuple<TransformationCtor, const NeuronType *,
                                     const NeuronType *>> &transformations,
        bool use_lossy);

    static void run(const Backend &backend, NetworkBase network,
                    const TransformationAuxData &aux,
                    std::unordered_set<std::string> disabled_trafo_ids =
                        std::unordered_set<std::string>(),
                    bool use_lossy = true);

    static RegisteredTransformation register_general_transformation(
        TransformationCtor ctor, TransformationTest test);

    static RegisteredTransformation register_neuron_type_transformation(
        TransformationCtor ctor, const NeuronType &src, const NeuronType &tar);

    template <typename SourceType, typename TargetType>
    static RegisteredTransformation register_neuron_type_transformation(
        TransformationCtor ctor)
    {
        return register_neuron_type_transformation(ctor, SourceType::inst(),
                                                   TargetType::inst());
    }
};
}

#endif /* CYPRESS_CORE_TRANSFORMATION_HPP */