shin/NeuralNetworkLib
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

renamed TransferFunction to ActivationFunction

Browse Source
This commit is contained in:
Shin
2015-08-28 18:11:09 +02:00
parent b6934fb161
commit ab089b636d
8 changed files with 26 additions and 26 deletions
Download Patch File Download Diff File Expand all files Collapse all files

6
src/NeuralNetwork/TransferFunction/TransferFunction.h → src/NeuralNetwork/ActivationFunction/ActivationFunction.h
View File

@@ -5,12 +5,12 @@
namespace NeuralNetwork namespace NeuralNetwork
{ {
namespace TransferFunction namespace ActivationFunction
{ {
class TransferFunction class ActivationFunction
{ {
public: public:
virtual ~TransferFunction() {} virtual ~ActivationFunction() {}
virtual float derivatedOutput(const float &input,const float &output)=0; virtual float derivatedOutput(const float &input,const float &output)=0;
virtual float operator()(const float &x)=0; virtual float operator()(const float &x)=0;
}; };

6
src/NeuralNetwork/TransferFunction/Heaviside.h → src/NeuralNetwork/ActivationFunction/Heaviside.h
View File

@@ -1,13 +1,13 @@
#ifndef __TRAN_HEAVISIDE_H_ #ifndef __TRAN_HEAVISIDE_H_
#define __TRAN_HEAVISIDE_H_ #define __TRAN_HEAVISIDE_H_
#include "./TransferFunction.h" #include "./ActivationFunction.h"
namespace NeuralNetwork namespace NeuralNetwork
{ {
namespace TransferFunction namespace ActivationFunction
{ {
class Heaviside: public TransferFunction class Heaviside: public ActivationFunction
{ {
public: public:
Sigmoid(const float &lambdaP): lambda(lambdaP) {} Sigmoid(const float &lambdaP): lambda(lambdaP) {}

6
src/NeuralNetwork/TransferFunction/HyperbolicTangent.h → src/NeuralNetwork/ActivationFunction/HyperbolicTangent.h
View File

@@ -1,13 +1,13 @@
#ifndef __TRAN_HYPTAN_H_ #ifndef __TRAN_HYPTAN_H_
#define __TRAN_HYPTAN_H_ #define __TRAN_HYPTAN_H_
#include "./TransferFunction.h" #include "./ActivationFunction.h"
namespace NeuralNetwork namespace NeuralNetwork
{ {
namespace TransferFunction namespace ActivationFunction
{ {
class HyperbolicTangent: public TransferFunction class HyperbolicTangent: public ActivationFunction
{ {
public: public:
HyperbolicTangent(const float& lam=1):lambda(lam) {} HyperbolicTangent(const float& lam=1):lambda(lam) {}

6
src/NeuralNetwork/TransferFunction/Sigmoid.h → src/NeuralNetwork/ActivationFunction/Sigmoid.h
View File

@@ -1,13 +1,13 @@
#ifndef __TRAN_SIGMOID_H_ #ifndef __TRAN_SIGMOID_H_
#define __TRAN_SIGMOID_H_ #define __TRAN_SIGMOID_H_
#include "./StreamingTransferFunction.h" #include "./StreamingActivationFunction.h"
namespace NeuralNetwork namespace NeuralNetwork
{ {
namespace TransferFunction namespace ActivationFunction
{ {
class Sigmoid: public StreamingTransferFunction class Sigmoid: public StreamingActivationFunction
{ {
public: public:
Sigmoid(const float lambdaP = 0.8): lambda(lambdaP) {} Sigmoid(const float lambdaP = 0.8): lambda(lambdaP) {}

6
src/NeuralNetwork/TransferFunction/StreamingTransferFunction.h → src/NeuralNetwork/ActivationFunction/StreamingActivationFunction.h
View File

@@ -5,13 +5,13 @@
#include "../../sse_mathfun.h" #include "../../sse_mathfun.h"
#include "./TransferFunction.h" #include "./ActivationFunction.h"
namespace NeuralNetwork namespace NeuralNetwork
{ {
namespace TransferFunction namespace ActivationFunction
{ {
class StreamingTransferFunction : public TransferFunction class StreamingActivationFunction : public ActivationFunction
{ {
public: public:
virtual float derivatedOutput(const float &input,const float &output)=0; virtual float derivatedOutput(const float &input,const float &output)=0;

6
src/NeuralNetwork/FeedForward.cpp
View File

@@ -34,7 +34,7 @@ FFNeuron& FFLayer::operator[](const size_t& neuron)
FeedForward::FeedForward(std::initializer_list<size_t> s, double lam, FeedForwardInitializer weightInit): ACyclicNetwork(lam),layers(s.size()) FeedForward::FeedForward(std::initializer_list<size_t> s, double lam, FeedForwardInitializer weightInit): ACyclicNetwork(lam),layers(s.size())
{ {
transfer = new TransferFunction::TransferFunction*[s.size()]; transfer = new ActivationFunction::ActivationFunction*[s.size()];
weights= new float**[s.size()]; weights= new float**[s.size()];
potentials= new float*[s.size()]; potentials= new float*[s.size()];
layerSizes= new size_t[s.size()]; layerSizes= new size_t[s.size()];
@@ -44,7 +44,7 @@ FeedForward::FeedForward(std::initializer_list<size_t> s, double lam, FeedForwar
register int prev_size=1; register int prev_size=1;
for(int layeSize:s) // TODO rename for(int layeSize:s) // TODO rename
{ {
transfer[i]= new TransferFunction::Sigmoid(lam); transfer[i]= new ActivationFunction::Sigmoid(lam);
layeSize+=1; layeSize+=1;
if(i==0) if(i==0)
{ {
@@ -106,7 +106,7 @@ FeedForward::~FeedForward()
void FeedForward::solvePart(float *newSolution, register size_t begin, size_t end,size_t prevSize, float *sol,size_t layer) void FeedForward::solvePart(float *newSolution, register size_t begin, size_t end,size_t prevSize, float *sol,size_t layer)
{ {
TransferFunction::StreamingTransferFunction *function=dynamic_cast<TransferFunction::StreamingTransferFunction*>(transfer[layer]); ActivationFunction::StreamingActivationFunction *function=dynamic_cast<ActivationFunction::StreamingActivationFunction*>(transfer[layer]);
if(prevSize >=4 && function !=nullptr) if(prevSize >=4 && function !=nullptr)
{ {
__m128 partialSolution; __m128 partialSolution;

14
src/NeuralNetwork/FeedForward.h
View File

@@ -5,8 +5,8 @@
#include "../Solution" #include "../Solution"
#include "Network" #include "Network"
#include "TransferFunction/Sigmoid.h" #include "ActivationFunction/Sigmoid.h"
#include "TransferFunction/TransferFunction.h" #include "ActivationFunction/ActivationFunction.h"
#include <vector> #include <vector>
#include <initializer_list> #include <initializer_list>
@@ -29,7 +29,7 @@ namespace NeuralNetwork
class FFNeuron : public Neuron class FFNeuron : public Neuron
{ {
public: public:
inline FFNeuron(float &pot, float *w, float &outputF, float &i,float lam,TransferFunction::TransferFunction &fun):function(fun),potential(pot),weights(w),out(outputF),inputs(i),lambda(lam) { } inline FFNeuron(float &pot, float *w, float &outputF, float &i,float lam,ActivationFunction::ActivationFunction &fun):function(fun),potential(pot),weights(w),out(outputF),inputs(i),lambda(lam) { }
FFNeuron() = delete; FFNeuron() = delete;
FFNeuron(const FFNeuron&) = delete; FFNeuron(const FFNeuron&) = delete;
@@ -45,7 +45,7 @@ namespace NeuralNetwork
inline virtual float input() const override { return inputs; } inline virtual float input() const override { return inputs; }
inline virtual float derivatedOutput() const override { return function.derivatedOutput(inputs,out); } inline virtual float derivatedOutput() const override { return function.derivatedOutput(inputs,out); }
protected: protected:
TransferFunction::TransferFunction &function; ActivationFunction::ActivationFunction &function;
float &potential; float &potential;
float *weights; float *weights;
float &out; float &out;
@@ -57,7 +57,7 @@ namespace NeuralNetwork
class FFLayer: public Layer class FFLayer: public Layer
{ {
public: public:
inline FFLayer(size_t s, float *p,float **w,float *out,float *in,float lam,TransferFunction::TransferFunction &fun): function(fun), layerSize(s),potentials(p),weights(w),outputs(out),inputs(in),lambda(lam) {} inline FFLayer(size_t s, float *p,float **w,float *out,float *in,float lam,ActivationFunction::ActivationFunction &fun): function(fun), layerSize(s),potentials(p),weights(w),outputs(out),inputs(in),lambda(lam) {}
~FFLayer(); ~FFLayer();
FFLayer(const FFLayer &) = delete; FFLayer(const FFLayer &) = delete;
@@ -66,7 +66,7 @@ namespace NeuralNetwork
virtual FFNeuron& operator[](const size_t& layer) override; virtual FFNeuron& operator[](const size_t& layer) override;
inline virtual size_t size() const override {return layerSize;}; inline virtual size_t size() const override {return layerSize;};
protected: protected:
TransferFunction::TransferFunction &function; ActivationFunction::ActivationFunction &function;
FFNeuron **neurons=nullptr; FFNeuron **neurons=nullptr;
size_t layerSize; size_t layerSize;
float *potentials; float *potentials;
@@ -131,7 +131,7 @@ namespace NeuralNetwork
float **potentials=nullptr; float **potentials=nullptr;
float **outputs=nullptr; float **outputs=nullptr;
float **inputs=nullptr; float **inputs=nullptr;
TransferFunction::TransferFunction **transfer=nullptr; ActivationFunction::ActivationFunction **transfer=nullptr;
size_t *layerSizes=nullptr; size_t *layerSizes=nullptr;
size_t layers;/**< Number of layers */ size_t layers;/**< Number of layers */
}; };

2
src/NeuralNetwork/Makefile
View File

@@ -18,7 +18,7 @@ lib: $(LIBNAME).so $(LIBNAME).a
$(LIBNAME).so: $(OBJFILES) $(LIBNAME).so: $(OBJFILES)
$(CXX) -shared $(CXXFLAGS) $(OBJFILES) $(LINKFILES) -o $(LIBNAME).so $(CXX) -shared $(CXXFLAGS) $(OBJFILES) $(LINKFILES) -o $(LIBNAME).so
$(LIBNAME).a: $(OBJFILES) ./Neuron.h ./Network.h ../Solution.h ../Problem.h ./TransferFunction/TransferFunction.h ./TransferFunction/Sigmoid.h $(LIBNAME).a: $(OBJFILES) ./Neuron.h ./Network.h ../Solution.h ../Problem.h ./ActivationFunction/ActivationFunction.h ./ActivationFunction/Sigmoid.h
rm -f $(LIBNAME).a # create new library rm -f $(LIBNAME).a # create new library
ar rcv $(LIBNAME).a $(OBJFILES) $(LINKFILES) ar rcv $(LIBNAME).a $(OBJFILES) $(LINKFILES)
ranlib $(LIBNAME).a ranlib $(LIBNAME).a