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Added transfer function support, yet not colplete

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Shin
2014-12-13 17:41:11 +01:00
parent 2daac8b652
commit d63a72d82a
9 changed files with 143 additions and 12 deletions
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2
Makefile.const
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@@ -5,7 +5,7 @@ CXXFLAGS+= -std=c++14
CXXFLAGS+= -pg -fPIC
CXXFLAGS+= -g
CXXFLAGS+= -fPIC -pthread
CXXFLAGS+= -DUSE_SSE2
#CXXFLAGS+= -DUSE_SSE2
OPTIMALIZATION = -O3 -march=native -mtune=native
%.o : %.cpp %.h

19
src/NeuralNetwork/FeedForward.cpp
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@@ -35,6 +35,7 @@ FFNeuron& FFLayer::operator[](const size_t& neuron)
FeedForward::FeedForward(std::initializer_list<size_t> s, double lam): ACyclicNetwork(lam),layers(s.size())
{
transfer = new TransferFunction::TransferFunction*[s.size()];
weights= new float**[s.size()];
potentials= new float*[s.size()];
layerSizes= new size_t[s.size()];
@@ -44,6 +45,7 @@ FeedForward::FeedForward(std::initializer_list<size_t> s, double lam): ACyclicNe
int prev_size=1;
for(int layeSize:s) // TODO rename
{
transfer[i]= new TransferFunction::Sigmoid(lam);
layeSize+=1;
if(i==0)
{
@@ -103,13 +105,12 @@ FeedForward::~FeedForward()
void FeedForward::solvePart(float *newSolution, register size_t begin, size_t end,size_t prevSize, float *sol,size_t layer)
{
if(prevSize >4)
TransferFunction::StreamingTransferFunction *function=dynamic_cast<TransferFunction::StreamingTransferFunction*>(transfer[layer]);
if(prevSize >=4 && function !=nullptr)
{
__m128 partialSolution;
__m128 w;
__m128 sols;
__m128 temporaryConst1=_mm_set1_ps(1.0);
__m128 temporaryConstLambda=_mm_set1_ps(-lambda);
register size_t alignedPrev=prevSize>16?(prevSize-(prevSize%16)):0;
for( size_t j=begin;j<end;j++)
{
@@ -122,9 +123,10 @@ void FeedForward::solvePart(float *newSolution, register size_t begin, size_t en
w=_mm_mul_ps(w,sols);
partialSolution=_mm_add_ps(partialSolution,w);
}
register float* memory=this->weights[layer][j];
for(register size_t k=0;k<alignedPrev;k+=4)
{
w = _mm_load_ps(this->weights[layer][j]+k);
w = _mm_load_ps(memory+k);
sols = _mm_load_ps(sol+k);
w=_mm_mul_ps(w,sols);
partialSolution=_mm_add_ps(partialSolution,w);
@@ -142,22 +144,19 @@ void FeedForward::solvePart(float *newSolution, register size_t begin, size_t en
partialSolution = _mm_hadd_ps(partialSolution, partialSolution);
#endif
_mm_store_ss(inputs[layer]+j,partialSolution);
partialSolution=_mm_mul_ps(temporaryConstLambda,partialSolution); //-lambda*sol[k]
partialSolution=exp_ps(partialSolution); //exp(sols)
partialSolution= _mm_add_ps(partialSolution,temporaryConst1); //1+exp()
partialSolution= _mm_div_ps(temporaryConst1,partialSolution);//1/....*/
partialSolution=function->operator()(partialSolution);
_mm_store_ss(newSolution+j,partialSolution);
}
}else
{
for( size_t j=begin;j<end;j++)
{
register float tmp=0;
float tmp=0;
for(register size_t k=0;k<prevSize;k++)
{
tmp+=sol[k]*weights[layer][j][k];
}
newSolution[j]=(1.0/(1.0+exp(-lambda*tmp)));
newSolution[j]=transfer[layer]->operator()(tmp);
inputs[layer][j]=tmp;
}
}

3
src/NeuralNetwork/FeedForward.h
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@@ -4,6 +4,8 @@
#include "../Problem"
#include "../Solution"
#include "Network"
#include "TransferFunction/Sigmoid.h"
#include "TransferFunction/TransferFunction.h"
#include <vector>
#include <initializer_list>
@@ -93,6 +95,7 @@ namespace NeuralNetwork
float **potentials=nullptr;
float **sums=nullptr;
float **inputs=nullptr;
TransferFunction::TransferFunction **transfer=nullptr;
size_t *layerSizes=nullptr;
size_t layers;
};

2
src/NeuralNetwork/Makefile
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@@ -15,7 +15,7 @@ lib: $(LIBNAME).so $(LIBNAME).a
$(LIBNAME).so: $(OBJFILES)
$(CXX) -shared $(CXXFLAGS) $(OBJFILES) $(LINKFILES) -o $(LIBNAME).so
$(LIBNAME).a: $(OBJFILES) ./Neuron.h ./Network.h ../Solution.h ../Problem.h
$(LIBNAME).a: $(OBJFILES) ./Neuron.h ./Network.h ../Solution.h ../Problem.h ./TransferFunction/TransferFunction.h ./TransferFunction/Sigmoid.h
rm -f $(LIBNAME).a # create new library
ar rcv $(LIBNAME).a $(OBJFILES) $(LINKFILES)
ranlib $(LIBNAME).a

25
src/NeuralNetwork/TransferFunction/Heaviside.h Normal file
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@@ -0,0 +1,25 @@
#ifndef __TRAN_HEAVISIDE_H_
#define __TRAN_HEAVISIDE_H_
#include "./TransferFunction.h"
namespace Shin
{
namespace NeuralNetwork
{
namespace TransferFunction
{
class Heaviside: public TransferFunction
{
public:
Sigmoid(const float &lambdaP): lambda(lambdaP) {}
inline virtual float derivatedOutput(const float &input,const float &output) override { return 1.0; }
inline virtual float operator()(const float &x) override { return x>k ? 1.0f : 0.0f; };
protected:
float lambda;
};
}
}
}
#endif

23
src/NeuralNetwork/TransferFunction/HyperbolicTangent.h Normal file
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@@ -0,0 +1,23 @@
#ifndef __TRAN_SIGMOID_H_
#define __TRAN_SIGMOID_H_
#include "./TransferFunction.h"
namespace Shin
{
namespace NeuralNetwork
{
namespace TransferFunction
{
class HyperbolicTangent: public TransferFunction
{
public:
HyperbolicTangent() {}
inline virtual float derivatedOutput(const float&,const float &output) override { return 1-pow(output); }
inline virtual float operator()(const float &x) override { return tanh(x); };
protected:
};
}
}
}
#endif

33
src/NeuralNetwork/TransferFunction/Sigmoid.h Normal file
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@@ -0,0 +1,33 @@
#ifndef __TRAN_SIGMOID_H_
#define __TRAN_SIGMOID_H_
#include "./StreamingTransferFunction.h"
namespace Shin
{
namespace NeuralNetwork
{
namespace TransferFunction
{
class Sigmoid: public StreamingTransferFunction
{
public:
Sigmoid(const float lambdaP = 0.8): lambda(lambdaP) {}
inline virtual float derivatedOutput(const float&,const float &output) override { return lambda*output*(1.0f-output); }
inline virtual float operator()(const float &x) override { return 1.0f / (1.0f +exp(-lambda*x) ); };
inline virtual __m128 operator()(__m128 x) override {
x=_mm_mul_ps(temporaryConstLambda,x); //-lambda*sol[k]
x=exp_ps(x); //exp(x)
x= _mm_add_ps(x,temporaryConst1); //1+exp()
x= _mm_div_ps(temporaryConst1,x);//1/....
return x;
}
protected:
float lambda;
__m128 temporaryConst1=_mm_set1_ps(1.0);
__m128 temporaryConstLambda=_mm_set1_ps(-lambda);
};
}
}
}
#endif

26
src/NeuralNetwork/TransferFunction/StreamingTransferFunction.h Normal file
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@@ -0,0 +1,26 @@
#ifndef __STREAMINGTRAN_FUN_H_
#define __STREAMINGTRAN_FUN_H_
#include <xmmintrin.h>
#include "../../sse_mathfun.h"
#include "./TransferFunction.h"
namespace Shin
{
namespace NeuralNetwork
{
namespace TransferFunction
{
class StreamingTransferFunction : public TransferFunction
{
public:
virtual float derivatedOutput(const float &input,const float &output)=0;
virtual float operator()(const float &x)=0;
virtual __m128 operator()(__m128)=0; // it must be overriden to be used!
};
}
}
}
#endif

22
src/NeuralNetwork/TransferFunction/TransferFunction.h Normal file
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@@ -0,0 +1,22 @@
#ifndef __TRAN_FUN_H_
#define __TRAN_FUN_H_
#include <math.h>
namespace Shin
{
namespace NeuralNetwork
{
namespace TransferFunction
{
class TransferFunction
{
public:
virtual ~TransferFunction() {}
virtual float derivatedOutput(const float &input,const float &output)=0;
virtual float operator()(const float &x)=0;
};
}
}
}
#endif