Rewrite
This commit is contained in:
Asrın Doğan
parent
8a8d56cc02
commit
e9defa3b86
799
main.cpp
799
main.cpp
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@ -1,7 +1,12 @@
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#include <iostream>
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#include <cstdlib>
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#include <time.h>
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class Synapse;
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class Neuron;
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class Layer;
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class Input;
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class Output;
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class NeuralNetwork;
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float RandomFloat(int min, int max)
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{
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@ -11,473 +16,273 @@ float RandomFloat(int min, int max)
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srand(time(0) + counter++ * 50);
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value = (rand() % ((max - min) * 100));
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result = (float)value / 100.0 + (float)min;
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std::clog << "Function RandomFloat: Between " << min << " and " << max << " returned value is " << result << "\n";
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return 1.0;
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return result;
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}
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#pragma region Sinaps
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class Sinaps
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#pragma region Synapse
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class Synapse
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{
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private:
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float weight; // Ağırlık
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float value; // Değer
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float bias; // Öteleme
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float weight;
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float value;
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float bias;
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public:
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Sinaps();
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~Sinaps();
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Sinaps(float, float, float); // Kaydedilen değerleri yeniden yazabilmek için
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void SetSinaps(float, float, float); // Sonradan tamamen değiştirebilmek için
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void SetWeight(float);
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Synapse();
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void SetValue(float);
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void SetWeight(float);
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void SetBias(float);
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float Fire();
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};
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Sinaps::Sinaps()
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Synapse::Synapse()
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{
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// weight = value = bias = 0.0;
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this -> weight = RandomFloat(-1, 1);
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this -> value = RandomFloat(-1, 1);
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this -> bias = RandomFloat(-1, 1);
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std::clog << "Create Sinaps: Weight = " << weight
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<< " Value = " << value
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<< " Bias = " << bias << "\n" << "\n";
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this -> value = this -> weight = this -> bias = 1.0;
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}
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Sinaps::~Sinaps()
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void Synapse::SetValue(float value)
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{
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std::clog << "Delete Sinaps: Weight = " << weight
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<< " Value = " << value
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<< " Bias = " << bias << "\n";
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this -> value = value;
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}
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Sinaps::Sinaps(float weight, float value, float bias)
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void Synapse::SetWeight(float weight)
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{
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this -> weight = weight;
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this -> value = value;
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this -> bias = bias;
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std::clog << "Create Sinaps: Weight = " << weight
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<< " Value = " << value
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<< " Bias = " << bias << "\n";
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}
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void Sinaps::SetSinaps(float weight, float value, float bias)
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void Synapse::SetBias(float bias)
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{
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this -> weight = weight;
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this -> value = value;
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this -> bias = bias;
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std::clog << "\n" << "Set Sinaps: Weight = " << weight
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<< " Value = " << value
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<< " Bias = " << bias << "\n";
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}
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void Sinaps::SetWeight(float weight) { std::clog << "Set Sinaps Weight: " << weight << "\n"; this -> weight = weight; }
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void Sinaps::SetValue(float value) { std::clog << "Set Sinaps Value: " << value << "\n"; this -> value = value; }
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void Sinaps::SetBias(float bias) { std::clog << "Set Sinaps Bias: " << bias << "\n"; this -> bias = bias; }
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}
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float Sinaps::Fire()
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float Synapse::Fire()
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{
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float result = weight * value + bias;
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std::clog << "Return Sinaps Fire: " << weight << " * " <<
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value << " + " <<
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bias << " = " <<
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result << "\n";
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float result = 0.0;
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result = this -> value * this -> weight + this -> bias;
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return result;
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}
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#pragma endregion
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#pragma region Noron
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class Noron
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#pragma region Neuron
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class Neuron
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{
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private:
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Sinaps *forwards;
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Sinaps *incoming;
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int forwardsCount;
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int incomingCount;
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Synapse *incomings;
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Synapse *forwards;
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int incomingsSize;
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int forwardsSize;
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int layerSize;
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float value;
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public:
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Noron();
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~Noron();
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bool SetForwards(Sinaps *, int);
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bool SetIncoming(Sinaps *, int);
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float GetStatus();
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Neuron();
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void ConnectIncomings(Synapse *, int);
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void ConnectForwards(Synapse *, int, int);
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void SetValue(float);
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float GetValue();
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};
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Noron::Noron()
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Neuron::Neuron()
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{
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forwards = incoming = NULL;
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forwardsCount = incomingCount = 0;
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std::clog << "Create Noron: NULL" << "\n";
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incomings = forwards = NULL;
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incomingsSize = forwardsSize = layerSize = 0;
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value = 0.0;
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}
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Noron::~Noron()
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void Neuron::SetValue(float value)
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{
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delete forwards;
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delete incoming;
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this -> value = value;
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}
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bool Noron::SetForwards(Sinaps *newForwards, int size)
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void Neuron::ConnectIncomings(Synapse *incomings, int incomingsSize)
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{
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std::clog << "\n" << "SetForwards: Allocating Memory of Size " << size << " Sinapses" << "\n";
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if(forwards)
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{
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delete forwards;
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forwards = NULL;
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std::clog << "SetForwards: Old Forwards Has Been Deleted!" << "\n";
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}
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forwards = (Sinaps *)new char[sizeof(Sinaps) * size];
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if(!forwards)
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{
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std::clog << "SetForwards: Memory Couldn't Allocated!" << "\n";
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return false;
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}
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std::clog << "SetForwards: Memory Allocated!" << "\n";
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for (int i = 0; i < size; i++)
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*(forwards+i) = *(newForwards+i);
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forwardsCount = size;
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std::clog << "SetForwards: Successfull!" << "\n";
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return true;
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this -> incomings = incomings;
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this -> incomingsSize = incomingsSize;
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}
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bool Noron::SetIncoming(Sinaps *newIncoming, int size)
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void Neuron::ConnectForwards(Synapse *forwards, int forwardsSize, int layerSize)
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{
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std::clog << "\n" << "SetIncoming: Allocating Memory of Size " << size << " Sinapses" << "\n";
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if(incoming)
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{
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delete incoming;
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incoming = NULL;
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std::clog << "SetIncoming: Old Incoming Has Been Deleted!" << "\n";
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}
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incoming = (Sinaps *)new char[sizeof(Sinaps) * size];
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if(!incoming)
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{
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std::clog << "SetIncoming: Memory Couldn't Allocated!" << "\n";
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return false;
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}
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std::clog << "SetIncoming: Memory Allocated!" << "\n";
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for (int i = 0; i < size; i++)
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*(incoming+i) = *(newIncoming+i);
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incomingCount = size;
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std::clog << "SetIncoming: Successfull!" << "\n";
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return true;
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this -> forwards = forwards;
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this -> forwardsSize = forwardsSize;
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this -> layerSize = layerSize;
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}
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float Noron::GetStatus()
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float Neuron::GetValue()
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{
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std::clog << "\n" << "GetStatus: Called!" << "\n";
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float toplam = 0.0;
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float result = 0.0;
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std::clog << "GetStatus: Firing All Sinapses!" << "\n" << "\n";
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for (int i = 0; i < incomingCount; i++)
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{
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std::clog << "GetStatus: Firing Sinaps " << i << "\n";
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toplam += (incoming + i) -> Fire();
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}
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if(!incomings) return (value = result);
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for (int i = 0; i < forwardsCount; i++)
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{
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std::clog << "GetStatus: Setting Value of Sinaps " << i << " to " << toplam << "\n";
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(forwards + i) -> SetValue(toplam);
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}
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for (int i = 0; i < incomingsSize; i++)
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result += (incomings + i) -> Fire();
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std::clog << "Get Noron Status: Sum = " << toplam << "\n";
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return toplam;
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if(!forwards) return (value = result);
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for (int i = 0; i < forwardsSize; i++)
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// currentSynapse = (forwards -> synapses + (forwardNeuron * this -> neuronSize));
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// (forwards + i) -> SetValue(result);
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//BAK BURAYA
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(forwards + i * layerSize) -> SetValue(result);
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value = result;
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return result;
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}
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#pragma endregion
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#pragma region Katman
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class Katman
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#pragma region Layer
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class Layer
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{
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protected:
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Noron *neurons;
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Katman *forward;
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Sinaps *layerSinapses;
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int size;
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Sinaps *CreateSinapsSet(int size);
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Neuron *neurons;
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Synapse *synapses;
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int neuronSize;
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int synapseSize;
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Neuron *_CreateNeurons(int);
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public:
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Katman();
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Katman(int);
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~Katman();
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Layer();
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Layer(int);
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~Layer();
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void FireLayer();
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void RandomizeSinapsValues();
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bool SetForward(Katman *);
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bool SetIncoming(Sinaps *sinapsSet, int backwardsNeuronCount);
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bool SetNoron(Noron *, int);
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bool CreateNoron(int);
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bool CreateNeurons(int);
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bool ConnectPrevious(Layer *);
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bool ConnectForwards(Layer *);
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int GetSize();
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};
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Katman::Katman()
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Layer::Layer()
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{
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neuronSize = synapseSize = 0;
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neurons = NULL;
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forward = NULL;
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layerSinapses = NULL;
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this -> size = 0;
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std::clog << "Create Layer: NULL" << "\n";
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}
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Katman::Katman(int size)
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{
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neurons = NULL;
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forward = NULL;
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layerSinapses = NULL;
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this -> size = 0;
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if(!CreateNoron(size))
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{
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std::clog << "Error Create Layer: Neurons Couldn't Created!" << "\n";
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std::cout << "Katman Oluşturulamadı!" << "\n";
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return;
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}
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std::clog << "Create Layer: " << size << " Neurons Has Been Created!" << "\n";
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this -> size = size;
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}
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Katman::~Katman() { delete neurons; }
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Sinaps *Katman::CreateSinapsSet(int size)
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{
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std::clog << "\n" << "CreateSinapsSet: Allocating Memory Size of " << size << " Sinapses" << "\n";
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Sinaps* sinapses = new Sinaps[size];
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if(sinapses)
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std::clog << "Create Sinaps Set: Memory Size of " << size << " Sinapses Allocated!" << "\n";
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else
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std::clog << "Error Create Sinaps Set!" << "\n";
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return sinapses;
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}
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void Katman::RandomizeSinapsValues()
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{
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if(!forward)
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return;
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float weight = 0;
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float value = 0;
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float bias = 0;
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int sinapsCount = size * (forward -> GetSize());
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for (int i = 0; i < sinapsCount; i++)
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{
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weight = RandomFloat(-1, 1);
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value = RandomFloat(-1, 1);
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bias = RandomFloat(-1, 1);
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(layerSinapses + i) -> SetSinaps(weight, value, bias);
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std::clog << "RandomizeSinapsValues: SetSinaps Called With Values of SetSinaps(" << weight << ", " << value << ", " << bias << ")" << "\n";
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}
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synapses = NULL;
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}
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void Katman::FireLayer()
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Layer::Layer(int size)
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{
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std::clog << "\n" << "FireLayer: Number of " << size << " Neurons' GetStatus is Being Called!" << "\n";
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for (int i = 0; i < size; i++)
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std::clog << i << ". Neuron Status: " << (neurons + i) -> GetStatus() << "\n";
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neuronSize = synapseSize = 0;
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synapses = NULL;
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neurons = _CreateNeurons(size);
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}
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bool Katman::SetForward(Katman *forward)
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Layer::~Layer()
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{
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std::clog << "\n" << "SetForward: Called!" << "\n";
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Sinaps *sinapses = NULL; // Pointer to store all created sinapses
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Sinaps *newSinapses = NULL; // Temporary Pointer for creating each neurons' s1inapses
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int forwardSize = 0;
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if(layerSinapses)
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if(neurons) delete neurons;
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if(synapses) delete synapses;
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}
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Neuron *Layer::_CreateNeurons(int size)
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{
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Neuron *newNeurons = NULL;
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newNeurons = (Neuron *) new char[sizeof(Neuron) * size];
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if(newNeurons)
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for (int i = 0; i < size; i++)
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*(newNeurons + i) = Neuron();
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return newNeurons;
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}
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void Layer::FireLayer()
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{
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for (int i = 0; i < neuronSize; i++)
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(neurons + i) -> GetValue();
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}
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bool Layer::CreateNeurons(int size)
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{
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if(neurons = _CreateNeurons(size))
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neuronSize = size;
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return neurons;
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}
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bool Layer::ConnectPrevious(Layer *previous)
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{
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int previousSize = previous -> GetSize();
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int synapseCount = (this -> neuronSize) * previousSize;
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int currentIndex = 0;
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Synapse *currentSynapse = NULL;
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Neuron *currentNeuron = NULL;
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// Synapse *connectSynapses = NULL;
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if(synapses) delete synapses;
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synapses = (Synapse *) new char[sizeof(Synapse) * synapseCount];
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if(!synapses) return false;
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// connectSynapses = (Synapse *) new char[sizeof(Synapse) * previousSize];
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for (int thisNeuron = 0; thisNeuron < this -> neuronSize; thisNeuron++)
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{
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delete layerSinapses;
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layerSinapses = NULL;
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std::clog << "SetForward: Old layerSinapses Has Been Deleted!" << "\n";
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}
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this -> forward = forward;
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if(!forward)
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{
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std::clog << "SetForward: Forward is NULL" << "\n";
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return true;
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}
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forwardSize = forward -> GetSize();
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std::clog << "SetForward: Creating Sinaps Set with Number of " << (size * forwardSize) << "\n";
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if(sinapses)
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{
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delete sinapses;
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sinapses = NULL;
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std::clog << "SetForward: Old Sinapses Has Been Deleted!" << "\n";
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}
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sinapses = (Sinaps *)new char[sizeof(Sinaps) * size * forwardSize];
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if(!sinapses)
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{
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std::clog << "Error SetForward: Couldn't Allocate Memory for Sinapses!" << "\n";
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return false;
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}
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std::clog << "SetForward: SinapsSet Created!" << "\n";
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// Set Forwards of each neuron in the Layer
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for (int thisCounter = 0; thisCounter < size; thisCounter++)
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{
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newSinapses = CreateSinapsSet(forwardSize);
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if(!newSinapses)
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for (int prevNeuron = 0; prevNeuron < previousSize; prevNeuron++)
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{
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std::clog << "SetForward -> CreateSinapsSet: Couldn't Allocate Memory for Sinapses!" << "\n";
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return false;
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currentIndex = thisNeuron * previousSize + prevNeuron;
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currentSynapse = (synapses + currentIndex);
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currentNeuron = (previous -> neurons) + prevNeuron;
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*currentSynapse = Synapse();
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// currentSynapse = (Synapse *) new char[sizeof(Synapse)];
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// currentSynapse -> SetWeight(1);
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// currentSynapse -> SetValue(2);
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// currentSynapse -> SetBias(3);
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// currentSynapse -> SetRoot(currentNeuron);
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}
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std::clog << "SetForward -> CreateSinapsSet: SinapsSet Created!" << "\n";
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std::clog << "SetForward -> SetForwards: " <<
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(neurons + thisCounter) -> SetForwards(newSinapses, forwardSize)
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<< "\n";;
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// Add each sinaps to the array
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for (int forwardCounter = 0; forwardCounter < forwardSize; forwardCounter++)
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*(sinapses + forwardCounter) = *(newSinapses + forwardCounter);
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std::clog << "SetForward: Sinapses Are Added to the Array!" << "\n";
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currentNeuron = (neurons + thisNeuron);
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currentNeuron -> ConnectIncomings((synapses + thisNeuron * previousSize), previousSize);
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}
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layerSinapses = sinapses;
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std::clog << "SetForward: Sinaps Array Has Been Set to the Class' Pointer!" << "\n";
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// Send the sinapses to the forward layer
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return forward -> SetIncoming(sinapses, size);
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return previous -> ConnectForwards(this);
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}
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bool Katman::SetIncoming(Sinaps *sinapsSet, int backwardsNeuronCount)
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bool Layer::ConnectForwards(Layer *forwards)
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{
|
||||
Sinaps *sinapses = NULL;
|
||||
int sinapcCounter = 0;
|
||||
int forwardsSize = forwards -> neuronSize;
|
||||
Neuron *currentNeuron = NULL;
|
||||
|
||||
std::clog << "\n" << "SetIncoming: Creating Sinaps Set with Number of " << backwardsNeuronCount << "\n";
|
||||
if(sinapses)
|
||||
for (int thisNeuron = 0; thisNeuron < this -> neuronSize; thisNeuron++)
|
||||
{
|
||||
delete sinapses;
|
||||
sinapses = NULL;
|
||||
std::clog << "SetIncoming: Old Sinapses Has Been Deleted!" << "\n";
|
||||
currentNeuron = (neurons + thisNeuron);
|
||||
for (int forwardNeuron = 0; forwardNeuron < forwardsSize; forwardNeuron++)
|
||||
currentNeuron -> ConnectForwards(forwards -> synapses + thisNeuron, forwardsSize, this -> neuronSize);
|
||||
// currentSynapse = (forwards -> synapses + (thisNeuron + forwardNeuron * this -> neuronSize));
|
||||
}
|
||||
sinapses = (Sinaps *)new char[sizeof(Sinaps) * backwardsNeuronCount];
|
||||
|
||||
if(!sinapses)
|
||||
{
|
||||
std::clog << "Error SetIncoming: Couldn't Allocate Memory for Sinapses!" << "\n";
|
||||
return false;
|
||||
}
|
||||
std::clog << "SetIncoming: SinapsSet Created!" << "\n";
|
||||
|
||||
for (int thisCounter = 0; thisCounter < size; thisCounter++)
|
||||
{
|
||||
std::clog << "SetIncoming: Sinapses Are Being Added to the Array!" << "\n";
|
||||
// Add each sinaps to the array
|
||||
for (int incomingCounter = 0; incomingCounter < backwardsNeuronCount; incomingCounter++)
|
||||
*(sinapses + incomingCounter) = *(sinapsSet + sinapcCounter++);
|
||||
|
||||
std::clog << "SetIncoming -> Neuron SetIncoming: " <<
|
||||
(neurons + thisCounter) -> SetIncoming(sinapses, backwardsNeuronCount)
|
||||
<< "\n";
|
||||
}
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
bool Katman::SetNoron(Noron *newNeurons, int size)
|
||||
int Layer::GetSize()
|
||||
{
|
||||
std::clog << "\n" << "SetNoron: Creating Neurons with Number of " << size << "\n";
|
||||
if(neurons)
|
||||
{
|
||||
delete neurons;
|
||||
neurons = NULL;
|
||||
std::clog << "SetNoron: Old Neurons Has Been Deleted!" << "\n";
|
||||
}
|
||||
neurons = (Noron *) new char[sizeof(Noron) * size];
|
||||
|
||||
if(!neurons)
|
||||
{
|
||||
std::clog << "Error SetNoron: Creating Neurons Failed!" << "\n";
|
||||
return false;
|
||||
}
|
||||
std::clog << "SetNoron: Neurons Created Successfully!" << "\n";
|
||||
|
||||
std::clog << "SetNoron: Setting Neurons to the Class' Neurons!" << "\n";
|
||||
for (int i = 0; i < size; i++)
|
||||
*(neurons+i) = *(newNeurons+i);
|
||||
|
||||
std::clog << "SetNoron: Neurons are Set Successfully!" << "\n";
|
||||
this -> size = size;
|
||||
return true;
|
||||
return neuronSize;
|
||||
}
|
||||
|
||||
bool Katman::CreateNoron(int size)
|
||||
{
|
||||
std::clog << "\n" << "CreateNoron: Creating Neurons with Number of " << size << "\n";
|
||||
if(neurons)
|
||||
{
|
||||
delete neurons;
|
||||
neurons = NULL;
|
||||
std::clog << "CreateNoron: Old Neurons Has Been Deleted!" << "\n";
|
||||
}
|
||||
neurons = new Noron[size];
|
||||
|
||||
if(!neurons)
|
||||
{
|
||||
std::clog << "Error CreateNoron: Creating Neurons Failed!" << "\n";
|
||||
return false;
|
||||
}
|
||||
std::clog << "CreateNoron: Neurons Created Successfully!" << "\n";
|
||||
|
||||
std::clog << "CreateNoron: Neurons are Set Successfully!" << "\n";
|
||||
this -> size = size;
|
||||
return true;
|
||||
}
|
||||
|
||||
int Katman::GetSize() { return size; }
|
||||
#pragma endregion
|
||||
#pragma region Girdi-Cikti
|
||||
#pragma region Girdi
|
||||
class Girdi : public Katman
|
||||
#pragma region Input-Output
|
||||
class Input : public Layer
|
||||
{
|
||||
public:
|
||||
Girdi();
|
||||
Girdi(int);
|
||||
Input();
|
||||
void SetValue(int, float);
|
||||
};
|
||||
|
||||
Girdi::Girdi() : Katman(1) { std::clog << "\n" << "Create Input Layer: Called!" << "\n"; }
|
||||
Girdi::Girdi(int size) : Katman(size) {}
|
||||
|
||||
void Girdi::SetValue(int index, float value)
|
||||
Input::Input() : Layer() {}
|
||||
void Input::SetValue(int index, float value)
|
||||
{
|
||||
Sinaps *editedSinaps = NULL;
|
||||
int forwardNeuronCount = forward -> GetSize();
|
||||
std::clog << "\n" << "SetValue: Index of " << index << " Neuron's Sinapses Values are Getting Set to Value of " << value << "\n";
|
||||
if(index >= this -> neuronSize || index < 0)
|
||||
return;
|
||||
|
||||
for (int i = 0; i < forwardNeuronCount; i++)
|
||||
{
|
||||
std::clog << "SetValue -> Sinaps SetValue: Index of " << index << " Neuron's " << i << " Sinaps Value is Getting Set to Value of " << value << "\n";
|
||||
editedSinaps = (layerSinapses + index * forwardNeuronCount + i);
|
||||
editedSinaps -> SetValue(value);
|
||||
std::clog << "SetValue -> Sinaps SetValue: Successfull" << "\n";
|
||||
}
|
||||
std::clog << "SetValue: Successfull" << "\n";
|
||||
(neurons + index) -> SetValue(value);
|
||||
}
|
||||
#pragma endregion
|
||||
#pragma region Cikti
|
||||
class Cikti : public Katman
|
||||
|
||||
class Output : public Layer
|
||||
{
|
||||
public:
|
||||
Cikti();
|
||||
Cikti(int);
|
||||
Output();
|
||||
float GetValue(int);
|
||||
};
|
||||
|
||||
Cikti::Cikti() : Katman(1) { std::clog << "\n" << "Create Output Layer: Called!" << "\n"; }
|
||||
Cikti::Cikti(int size) : Katman(size) {}
|
||||
|
||||
float Cikti::GetValue(int index)
|
||||
Output::Output() : Layer() {}
|
||||
float Output::GetValue(int index)
|
||||
{
|
||||
std::clog << "\n" << "Call GetValue!" << "\n";
|
||||
float result = (neurons + index) -> GetStatus();
|
||||
std::clog << "GetValue: " << result << "\n";
|
||||
float result = 0.0;
|
||||
|
||||
if(index >= this -> neuronSize || index < 0)
|
||||
return result;
|
||||
|
||||
result = (neurons + index) -> GetValue();
|
||||
return result;
|
||||
}
|
||||
#pragma endregion
|
||||
|
|
@ -486,244 +291,110 @@ float RandomFloat(int min, int max)
|
|||
class NeuralNetwork
|
||||
{
|
||||
private:
|
||||
Girdi *input;
|
||||
Katman *hiddenLayers;
|
||||
Cikti *output;
|
||||
Input *input;
|
||||
Layer *hidden;
|
||||
Output *output;
|
||||
int hiddenSize;
|
||||
|
||||
public:
|
||||
NeuralNetwork();
|
||||
NeuralNetwork(int);
|
||||
~NeuralNetwork();
|
||||
void SetInput(int, float);
|
||||
void RandomizeNetworkValues();
|
||||
void FireNetwork();
|
||||
bool SetInputNeurons(int);
|
||||
bool SetHiddenLayerNeurons(int, int);
|
||||
bool SetHiddenNeurons(int, int);
|
||||
bool SetOutputNeurons(int);
|
||||
bool ConnectLayers();
|
||||
float GetOutputValue(int);
|
||||
float GetOutput(int);
|
||||
void SetInput(int, float);
|
||||
};
|
||||
|
||||
NeuralNetwork::NeuralNetwork()
|
||||
{
|
||||
std::clog << "\n" << "Create NeuralNetwork: NULL" << "\n";
|
||||
hiddenSize = 0;
|
||||
input = NULL;
|
||||
hiddenLayers = NULL;
|
||||
hidden = NULL;
|
||||
output = NULL;
|
||||
}
|
||||
|
||||
NeuralNetwork::NeuralNetwork(int hiddenSize)
|
||||
{
|
||||
std::clog << "\n" << "Create NeuralNetwork: Called" << "\n";
|
||||
input = new Girdi();
|
||||
hiddenLayers = new Katman[hiddenSize];
|
||||
output = new Cikti();
|
||||
std::clog << "\n" << "Create NeuralNetwork: New Neural Network Created with " << hiddenSize << " Layers!" << "\n";
|
||||
|
||||
if(!input)
|
||||
{
|
||||
std::clog << "Error Create NeuralNetwork: Memory Couldn't Allocated for Input Layer!" << "\n";
|
||||
std::cout << "Girdi Katmani Olusturulamadi!" << "\n";
|
||||
}
|
||||
if(!hiddenLayers)
|
||||
{
|
||||
std::clog << "Error Create NeuralNetwork: Memory Couldn't Allocated for Hidden Layers!" << "\n";
|
||||
std::cout << "Ara Katmanlar Olusturulamadi!" << "\n";
|
||||
}
|
||||
if(!output)
|
||||
{
|
||||
std::clog << "Error Create NeuralNetwork: Memory Couldn't Allocated for Output Layer!" << "\n";
|
||||
std::cout << "Cikti Katmani Olusturulamadi!" << "\n";
|
||||
}
|
||||
|
||||
if(!input || !hiddenLayers || !output)
|
||||
return;
|
||||
|
||||
std::clog << "Create NeuralNetwork: Succesfull!" << "\n";
|
||||
this -> hiddenSize = hiddenSize;
|
||||
input = new Input();
|
||||
hidden = new Layer(hiddenSize);
|
||||
output = new Output();
|
||||
}
|
||||
|
||||
NeuralNetwork::~NeuralNetwork()
|
||||
{
|
||||
delete input;
|
||||
delete hiddenLayers;
|
||||
delete output;
|
||||
}
|
||||
|
||||
bool NeuralNetwork::SetHiddenLayerNeurons(int index, int size)
|
||||
{
|
||||
bool result;
|
||||
std::clog << "\n" << "SetHiddenLayerNeurons: Size of " << size << " at Index of " << index << "\n";
|
||||
std::clog << "SetHiddenLayerNeurons: Allocating Memory Size of " << size << " Neurons!" << "\n";
|
||||
Noron *neurons = (Noron *) new char[sizeof(Noron) * size];
|
||||
|
||||
if(!neurons)
|
||||
{
|
||||
std::clog << "Error SetHiddenLayerNeurons: Couldn't Allocate Memory for Neurons!" << "\n";
|
||||
return false;
|
||||
}
|
||||
std::clog << "SetHiddenLayerNeurons: Memory Allocated!" << "\n";
|
||||
std::clog << "SetHiddenLayerNeurons -> CreateNoron: Called!" << "\n";
|
||||
result = (hiddenLayers + index) -> CreateNoron(size);
|
||||
std::clog << "SetHiddenLayerNeurons -> CreateNoron: " << result << "\n";
|
||||
// if(result)
|
||||
// return (hiddenLayers + index) -> SetNoron(neurons, size);
|
||||
return result;
|
||||
}
|
||||
|
||||
bool NeuralNetwork::SetInputNeurons(int size)
|
||||
{
|
||||
bool result;
|
||||
std::clog << "\n" << "SetInputNeurons: Size of " << size << "\n";
|
||||
std::clog << "SetInputNeurons: Allocating Memory Size of " << size << " Neurons!" << "\n";
|
||||
Noron *neurons = (Noron *) new char[sizeof(Noron) * size];
|
||||
|
||||
if(!neurons)
|
||||
{
|
||||
std::clog << "Error SetInputNeurons: Couldn't Allocate Memory for Neurons!" << "\n";
|
||||
return false;
|
||||
}
|
||||
std::clog << "SetInputNeurons: Memory Allocated!" << "\n";
|
||||
std::clog << "SetInputNeurons -> CreateNoron: Called!" << "\n";
|
||||
result = input -> CreateNoron(size);
|
||||
std::clog << "SetInputNeurons -> CreateNoron: " << result << "\n";
|
||||
// return output -> SetNoron(neurons, size);
|
||||
return result;
|
||||
}
|
||||
|
||||
bool NeuralNetwork::SetOutputNeurons(int size)
|
||||
{
|
||||
bool result;
|
||||
std::clog << "\n" << "SetOutputNeurons: Size of " << size << "\n";
|
||||
std::clog << "SetOutputNeurons: Allocating Memory Size of " << size << " Neurons!" << "\n";
|
||||
Noron *neurons = (Noron *) new char[sizeof(Noron) * size];
|
||||
|
||||
if(!neurons)
|
||||
{
|
||||
std::clog << "Error SetOutputNeurons: Couldn't Allocate Memory for Neurons!" << "\n";
|
||||
return false;
|
||||
}
|
||||
std::clog << "SetOutputNeurons: Memory Allocated!" << "\n";
|
||||
|
||||
std::clog << "SetOutputNeurons -> CreateNoron: Called!" << "\n";
|
||||
result = input -> CreateNoron(size);
|
||||
std::clog << "SetOutputNeurons -> CreateNoron: " << result << "\n";
|
||||
// return input -> SetNoron(neurons, size);
|
||||
return result;
|
||||
}
|
||||
|
||||
bool NeuralNetwork::ConnectLayers()
|
||||
{
|
||||
if(!input -> SetForward(hiddenLayers))
|
||||
{
|
||||
std::clog << "\n" << "Error ConnectLayers: Input Couldn't Set to Forward!" << "\n";
|
||||
return false;
|
||||
}
|
||||
std::clog << "\n" << "ConnectLayers: Input is Set to Forward Successfully!" << "\n";
|
||||
|
||||
for (int i = 0; i < hiddenSize - 1; i++)
|
||||
if(!(hiddenLayers + i) -> SetForward(hiddenLayers + i + 1))
|
||||
{
|
||||
std::clog << "Error ConnectLayers: Hidden Layer " << i << " Couldn't Set to Forward!" << "\n";
|
||||
return false;
|
||||
}
|
||||
else
|
||||
std::clog << "ConnectLayers: Hidden Layer " << i << " is Set to Forward Successfully!" << "\n";
|
||||
|
||||
std::clog << "ConnectLayers: Hidden Layers are Set to Forward Successfully!" << "\n";
|
||||
|
||||
if(!(hiddenLayers + hiddenSize - 1) -> SetForward(output))
|
||||
{
|
||||
std::clog << "Error ConnectLayers: Output Couldn't Set to Forward!" << "\n";
|
||||
return false;
|
||||
}
|
||||
std::clog << "ConnectLayers: Output is Set to Forward Successfully!" << "\n";
|
||||
|
||||
return output -> SetForward(NULL);
|
||||
if(input) delete input;
|
||||
if(hidden) delete hidden;
|
||||
if(output) delete output;
|
||||
}
|
||||
|
||||
void NeuralNetwork::FireNetwork()
|
||||
{
|
||||
// input -> FireLayer();
|
||||
// std::clog << "\n" << "FireNetwork: Input Fired!" << "\n";
|
||||
|
||||
for (int i = 0; i < hiddenSize; i++)
|
||||
{
|
||||
(hiddenLayers + i) -> FireLayer();
|
||||
std::clog << "FireNetwork: Hidden Layer " << i << " Fired!" << "\n";
|
||||
}
|
||||
(hidden + i) -> FireLayer();
|
||||
|
||||
output -> FireLayer();
|
||||
std::clog << "FireNetwork: Output Fired!" << "\n";
|
||||
}
|
||||
|
||||
bool NeuralNetwork::SetInputNeurons(int size)
|
||||
{
|
||||
return input -> CreateNeurons(size);
|
||||
}
|
||||
|
||||
bool NeuralNetwork::SetHiddenNeurons(int index, int size)
|
||||
{
|
||||
return (hidden + index) -> CreateNeurons(size);
|
||||
}
|
||||
|
||||
bool NeuralNetwork::SetOutputNeurons(int size)
|
||||
{
|
||||
return output -> CreateNeurons(size);
|
||||
}
|
||||
|
||||
bool NeuralNetwork::ConnectLayers()
|
||||
{
|
||||
if(!hidden -> ConnectPrevious(input))
|
||||
return false;
|
||||
|
||||
for (int i = 1; i < hiddenSize; i++)
|
||||
if(!(hidden + i) -> ConnectPrevious((hidden + i - 1)))
|
||||
return false;
|
||||
|
||||
if(output -> ConnectPrevious((hidden + hiddenSize - 1)))
|
||||
return false;
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
float NeuralNetwork::GetOutput(int index)
|
||||
{
|
||||
return output -> GetValue(index);
|
||||
}
|
||||
|
||||
void NeuralNetwork::SetInput(int index, float value)
|
||||
{
|
||||
if(!input)
|
||||
{
|
||||
std::clog << "\n" << "SetInput: There's no Input Layer Set!" << "\n";
|
||||
return;
|
||||
}
|
||||
|
||||
std::clog << "\n" << "SetInput -> Input SetValue: SetValue(" << index << ", " << value << ")!" << "\n";
|
||||
input -> SetValue(index, value);
|
||||
}
|
||||
|
||||
void NeuralNetwork::RandomizeNetworkValues()
|
||||
{
|
||||
std::clog << "\n" << "RandomizeNetworkValues: Input Sinapses Are Getting Randomized!" << "\n";
|
||||
input -> RandomizeSinapsValues();
|
||||
|
||||
for (int i = 0; i < hiddenSize; i++)
|
||||
{
|
||||
std::clog << "RandomizeNetworkValues: Hidden Layer " << i << " Sinapses Are Getting Randomized!" << "\n";
|
||||
(hiddenLayers + i) -> RandomizeSinapsValues();
|
||||
}
|
||||
|
||||
std::clog << "RandomizeNetworkValues: Output Sinapses Are Getting Randomized!" << "\n";
|
||||
output -> RandomizeSinapsValues();
|
||||
}
|
||||
|
||||
float NeuralNetwork::GetOutputValue(int index)
|
||||
{
|
||||
float result = output -> GetValue(index);
|
||||
std::clog << "\n" << "GetOutputValue: " << result << "\n";
|
||||
return result;
|
||||
}
|
||||
#pragma endregion
|
||||
|
||||
|
||||
int main(int argc, char const *argv[])
|
||||
{
|
||||
float result;
|
||||
FILE *file;
|
||||
NeuralNetwork network(3);
|
||||
|
||||
network.SetInputNeurons(1);
|
||||
network.SetHiddenLayerNeurons(0, 2);
|
||||
network.SetHiddenLayerNeurons(1, 3);
|
||||
network.SetHiddenLayerNeurons(2, 2);
|
||||
network.SetHiddenNeurons(0, 2);
|
||||
network.SetHiddenNeurons(1, 3);
|
||||
network.SetHiddenNeurons(2, 2);
|
||||
network.SetOutputNeurons(1);
|
||||
|
||||
network.ConnectLayers();
|
||||
std::cout << "m1\n";
|
||||
network.RandomizeNetworkValues();
|
||||
std::cout << "m2\n";
|
||||
|
||||
network.SetInput(0, 1);
|
||||
std::cout << "m3\n";
|
||||
|
||||
network.SetInput(0, 2);
|
||||
network.FireNetwork();
|
||||
result = network.GetOutputValue(0);
|
||||
std::cout << "Output is " << result << "\n";
|
||||
file = fopen("result.txt", "w");
|
||||
fprintf(file, "%f", result);
|
||||
fclose(file);
|
||||
|
||||
// std::cout << "Sinaps = " << sizeof(Sinaps) * 30 << "\n";
|
||||
// std::cout << "Noron = " << sizeof(Noron) * 9 << "\n";
|
||||
// std::cout << "Katman = " << sizeof(Katman) * 3 << "\n";
|
||||
// std::cout << "Girdi = " << sizeof(Girdi) * 1 << "\n";
|
||||
// std::cout << "Cikti = " << sizeof(Cikti) * 1 << "\n";
|
||||
// std::cout << "NeuralNetwork = " << sizeof(NeuralNetwork) * 1 << "\n";
|
||||
std::cout << "Result = " << network.GetOutput(0) << "\n";
|
||||
return 0;
|
||||
}
|
||||
|
|
|
|||
Loading…
Reference in New Issue