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removing function from neuron

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Shin
2016-02-18 18:53:59 +01:00
parent ce814b89b0
commit 1a55a720eb
3 changed files with 44 additions and 70 deletions
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112
include/NeuralNetwork/Neuron.h
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@@ -18,11 +18,13 @@ namespace NeuralNetwork
class NeuronInterface
{
public:
NeuronInterface(const unsigned long &_id=0): id(_id) {
NeuronInterface(const unsigned long &_id=0): id(_id), weights(1),_output(1),
_value(0) {
}
NeuronInterface(const NeuronInterface &r): id(r.id), weights(r.weights),_output(r._output) {
NeuronInterface(const NeuronInterface &r): id(r.id), weights(r.weights),_output(r._output),
_value(r._value) {
weights=weights;
}
@@ -37,20 +39,36 @@ namespace NeuralNetwork
*/
virtual std::string stringify(const std::string &prefix="") const =0;
inline virtual float weight(const NeuronInterface &n) const final {
return weights[n.id];
/**
* @brief getter for neuron weight
* @param &neuron is neuron it's weight is returned
*/
inline virtual float weight(const NeuronInterface &neuron) const final {
return weights[neuron.id];
}
inline virtual float weight(const std::size_t &n) const final {
return weights[n];
/**
* @brief getter for neuron weight
* @param &neuronID is id of neuron
*/
inline virtual float weight(const std::size_t &neuronID) const final {
return weights[neuronID];
}
inline virtual float& weight(const NeuronInterface &n) final {
return weights[n.id];
/**
* @brief This is a virtual function for storing network
* @returns json describing network and it's state
*/
inline virtual float& weight(const NeuronInterface &neuron) final {
return weights[neuron.id];
}
inline virtual float& weight(const std::size_t &n) final {
return weights[n];
/**
* @brief getter for neuron weight
* @param &neuronID is id of neuron
*/
inline virtual float& weight(const std::size_t &neuronID) final {
return weights[neuronID];
}
/**
@@ -62,22 +80,15 @@ namespace NeuralNetwork
/**
* @brief Returns input of neuron
*/
virtual float value() const=0;
/**
* @brief Function sets bias for neuron
* @param bias is new bias (initial value for neuron)
*/
virtual void setBias(const float &bias)=0;
/**
* @brief Function returns bias for neuron
*/
virtual float getBias() const=0;
inline virtual float value() const final {
return _value;
};
virtual float operator()(const std::vector<float>& inputs) =0;
/**
* @brief function resizes weighs to desired size
*/
inline virtual void setInputSize(const std::size_t &size) final {
if(weights.size()<size) {
weights.resize(size);
@@ -89,21 +100,24 @@ namespace NeuralNetwork
*/
virtual NeuronInterface* clone() const = 0;
/*
/**
* @brief getter for basis function of neuron
*/
virtual BasisFunction::BasisFunction& getBasisFunction() =0;
/*
/**
* @brief getter for activation function of neuron
*/
virtual ActivationFunction::ActivationFunction& getActivationFunction() =0;
/**
* @brief id is identificator if neuron
*/
const unsigned long id;
protected:
std::vector<float> weights= std::vector<float>(1);
float _output=1.0;
std::vector<float> weights;
float _output;
float _value;
};
/**
@@ -115,13 +129,11 @@ namespace NeuralNetwork
public:
Neuron(unsigned long _id=0, const ActivationFunction::ActivationFunction &activationFunction=ActivationFunction::Sigmoid(-4.9)):
NeuronInterface(_id), basis(new BasisFunction::Linear),
activation(activationFunction.clone()),
_value(0) {
activation(activationFunction.clone()) {
_output=0.0;
}
Neuron(const Neuron &r): NeuronInterface(r), basis(r.basis->clone()), activation(r.activation->clone()),
_value(r._value) {
Neuron(const Neuron &r): NeuronInterface(r), basis(r.basis->clone()), activation(r.activation->clone()) {
}
virtual ~Neuron() {
@@ -133,28 +145,6 @@ namespace NeuralNetwork
virtual std::string stringify(const std::string &prefix="") const override;
/**
* @brief Returns input of neuron
*/
virtual float value() const override {
return _value;
}
/**
* @brief Function sets bias for neuron
* @param _bias is new bias (initial value for neuron)
*/
virtual void setBias(const float &_bias) override {
weights[0]=_bias;
}
/**
* @brief Function returns bias for neuron
*/
virtual float getBias() const override {
return weights[0];
}
float operator()(const std::vector<float>& inputs) {
//compute value
_value=basis->operator()(weights,inputs);
@@ -181,8 +171,6 @@ namespace NeuralNetwork
BasisFunction::BasisFunction *basis;
ActivationFunction::ActivationFunction *activation;
float _value;
};
class BiasNeuron: public NeuronInterface {
@@ -200,14 +188,8 @@ namespace NeuralNetwork
std::string text;
};
virtual float getBias() const override { return 0; };
virtual void setBias(const float&) override{ }
virtual std::string stringify(const std::string& prefix = "") const override { return prefix+"{ \"class\" : \"NeuralNetwork::BiasNeuron\" }"; }
virtual float value() const override { return 1.0; }
virtual float operator()(const std::vector< float >&) override { return 1.0; }
virtual BiasNeuron* clone() const { return new BiasNeuron(); }
@@ -241,14 +223,8 @@ namespace NeuralNetwork
}
virtual float getBias() const override { return 0; };
virtual void setBias(const float&) override{ }
virtual std::string stringify(const std::string& prefix = "") const override { return prefix+"{ \"class\" : \"NeuralNetwork::InputNeuron\", \"id\": "+std::to_string(id)+" }"; }
virtual float value() const override { return 1.0; }
virtual float operator()(const std::vector< float >&) override { return 1.0; }
virtual InputNeuron* clone() const { return new InputNeuron(id); }

1
src/NeuralNetwork/Learning/BackPropagation.cpp
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@@ -76,4 +76,3 @@ void NeuralNetwork::Learning::BackPropagation::teach(FeedForward::Network &netwo
}
}
}
}

1
src/NeuralNetwork/Neuron.cpp
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@@ -7,7 +7,6 @@ std::string NeuralNetwork::Neuron::stringify(const std::string &prefix) const {
out << prefix << "{\n";
out << prefix << "\t\"class\": \"NeuralNetwork::Neuron\",\n";
out << prefix << "\t\"id\": " << id << ",\n";
out << prefix << "\t\"bias\": " << getBias() << ",\n";
out << prefix << "\t\"output\": " << output() << ",\n";
out << prefix << "\t\"value\": " << value() << ",\n";
out << prefix << "\t\"activationFunction\": " << activation->stringify() <<",\n";