86 lines
1.9 KiB
C++
86 lines
1.9 KiB
C++
#pragma once
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#include "../Network.h"
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#include "Layer.h"
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#include <vector>
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#include <sstream>
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#include <iomanip>
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#include <limits>
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#include <iostream>
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namespace NeuralNetwork {
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namespace FeedForward {
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/**
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* @author Tomas Cernik (Tom.Cernik@gmail.com)
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* @brief FeedForward model of Artifical neural network
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*/
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class Network: public NeuralNetwork::Network {
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public:
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/**
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* @brief Constructor for Network
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* @param _inputSize is number of inputs to network
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*/
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inline Network(size_t _inputSize):NeuralNetwork::Network(),layers() {
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appendLayer(_inputSize);
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};
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/**
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* @brief Virtual destructor for Network
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*/
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virtual ~Network() {
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for(auto &layer:layers) {
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delete layer;
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}
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}
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Layer& appendLayer(std::size_t size=1, const ActivationFunction::ActivationFunction &activationFunction=ActivationFunction::Sigmoid(-4.9)) {
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layers.push_back(new Layer(size,activationFunction));
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if(layers.size() > 1)
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layers.back()->setInputSize(layers[layers.size()-2]->size());
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return *layers[layers.size()-1];//.back();
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}
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Layer& operator[](const std::size_t &id) {
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return *layers[id];
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}
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void randomizeWeights();
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std::size_t size() const { return layers.size(); };
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/**
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* @brief This is a function to compute one iterations of network
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* @param input is input of network
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* @returns output of network
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*/
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virtual std::vector<float> computeOutput(const std::vector<float>& input) override;
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using NeuralNetwork::Network::stringify;
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void stringify(std::ostream& out) const override {
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out << "{" << std::endl;
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out << "\t \"class\": \"NeuralNetwork::FeedForward::Network\"," << std::endl;
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out << "\t \"layers\": [" << std::endl;
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bool first=true;
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for(auto &layer:layers) {
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if(!first) {
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out << ",";
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}
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out << *layer;
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first=false;
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}
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out << "]";
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out << "}";
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}
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protected:
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std::vector<Layer*> layers;
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};
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}
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} |