modified BP interface
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@@ -2,7 +2,9 @@
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#include <vector>
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#include <cmath>
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#include <NeuralNetwork/FeedForward/Network.h>
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#include "CorrectionFunction/Linear.h"
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namespace NeuralNetwork {
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namespace Learning {
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@@ -13,21 +15,23 @@ namespace Learning {
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class BackPropagation {
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public:
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inline BackPropagation(FeedForward::Network &feedForwardNetwork): network(feedForwardNetwork), learningCoefficient(0.4), deltas() {
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inline BackPropagation(FeedForward::Network &feedForwardNetwork, CorrectionFunction::CorrectionFunction *correction = new CorrectionFunction::Linear()):
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network(feedForwardNetwork), correctionFunction(correction),learningCoefficient(0.4), deltas() {
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resize();
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}
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virtual ~BackPropagation() {
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delete correctionFunction;
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}
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BackPropagation(const BackPropagation&)=delete;
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BackPropagation& operator=(const NeuralNetwork::Learning::BackPropagation&) = delete;
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void teach(const std::vector<float> &input, const std::vector<float> &output);
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inline virtual void setLearningCoefficient (const float& coefficient) { learningCoefficient=coefficient; }
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protected:
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inline virtual float correction(const float & expected, const float &computed) const {
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return expected-computed;
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};
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inline void resize() {
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if(deltas.size()!=network.size())
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@@ -41,6 +45,8 @@ namespace Learning {
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FeedForward::Network &network;
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CorrectionFunction::CorrectionFunction *correctionFunction;
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float learningCoefficient;
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std::vector<std::vector<float>> deltas;
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@@ -0,0 +1,29 @@
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#pragma once
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#include "CorrectionFunction.h"
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#include <iostream>
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namespace NeuralNetwork {
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namespace Learning {
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namespace CorrectionFunction {
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class ArcTangent : public CorrectionFunction {
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public:
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ArcTangent (const float &c=1.0): coefficient(c) {
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}
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/**
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* @brief operator returns error for values
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*
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*/
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inline virtual float operator()(const float &expected, const float &computed) const override final {
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//std::cout << (expected-computed) << ":" << atan(expected-computed) << "\n";
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return atan(coefficient*(expected-computed));
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}
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private:
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const float coefficient;
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};
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}
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}
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}
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@@ -0,0 +1,19 @@
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#pragma once
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namespace NeuralNetwork {
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namespace Learning {
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namespace CorrectionFunction {
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class CorrectionFunction {
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public:
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virtual ~ CorrectionFunction() {
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}
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/**
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* @brief operator returns error for values
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*
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*/
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virtual float operator()(const float & expected, const float &computed) const = 0;
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};
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}
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}
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}
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20
include/NeuralNetwork/Learning/CorrectionFunction/Linear.h
Normal file
20
include/NeuralNetwork/Learning/CorrectionFunction/Linear.h
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@@ -0,0 +1,20 @@
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#pragma once
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#include "CorrectionFunction.h"
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namespace NeuralNetwork {
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namespace Learning {
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namespace CorrectionFunction {
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class Linear : public CorrectionFunction {
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public:
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/**
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* @brief operator returns error for values
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*
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*/
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inline virtual float operator()(const float &expected, const float &computed) const override final {
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return expected-computed;
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}
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};
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}
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}
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}
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22
include/NeuralNetwork/Learning/CorrectionFunction/Optical.h
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22
include/NeuralNetwork/Learning/CorrectionFunction/Optical.h
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@@ -0,0 +1,22 @@
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#pragma once
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#include "CorrectionFunction.h"
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namespace NeuralNetwork {
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namespace Learning {
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namespace CorrectionFunction {
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class Optical : public CorrectionFunction {
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public:
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/**
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* @brief operator returns error for values
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*
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*/
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inline virtual float operator()(const float &expected, const float &computed) const override final {
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register float tmp=(expected-computed);
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register float ret=1+exp(tmp*tmp);
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return tmp < 0? -ret:ret;
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}
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};
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}
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}
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}
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@@ -1,6 +1,7 @@
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#pragma once
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#include "./BackPropagation.h"
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#include "./CorrectionFunction/Optical.h"
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namespace NeuralNetwork {
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namespace Learning {
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@@ -11,18 +12,12 @@ namespace Learning {
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class OpticalBackPropagation : public BackPropagation {
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public:
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OpticalBackPropagation(FeedForward::Network &feedForwardNetwork): BackPropagation(feedForwardNetwork) {
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OpticalBackPropagation(FeedForward::Network &feedForwardNetwork): BackPropagation(feedForwardNetwork,new CorrectionFunction::Optical()) {
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}
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virtual ~OpticalBackPropagation() {
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}
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protected:
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inline virtual float correction(const float & expected, const float &computed) const override {
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register float tmp=(expected-computed);
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register float ret=1+exp(tmp*tmp);
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return tmp < 0? -ret:ret;
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};
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};
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}
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}
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