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Shin
2014-12-10 16:01:53 +01:00
parent 993b4d3f04
commit aab9a073e9
35 changed files with 725 additions and 100 deletions
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6
tests/Makefile
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@@ -3,12 +3,14 @@ include ../Makefile.const
OPTIMALIZATION=
LIB_DIR = ../lib
GEN_TESTS=g-01 g-02
NN_TESTS= \
NN_TESTS=\
nn-01 nn-02 nn-03 nn-bp-sppeed \
nn-bp-xor \
nn-obp-xor \
nn-rl-xor nn-rl-and \
nn-rl-xor nn-rl-and nn-rl-qfun\
nn-reinforcement nn-04
# nn-test nn-rl-qfun\
ALL_TESTS=$(NN_TESTS) $(GEN_TESTS)
LIBS=$(LIB_DIR)/Genetics.a $(LIB_DIR)/NeuronNetwork.a

13
tests/nn-01.cpp
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@@ -5,20 +5,15 @@
#include <iostream>
#include <vector>
//typedef Shin::NeuronNetwork::Problem X;
class X: public Shin::NeuronNetwork::Problem
{
public:
X(const X& a) :q(a.q) {}
X(const std::vector<float> &a):q(a) {}
X(const std::vector<bool> &a):q() {for(bool s:a) q.push_back((float)s);}
std::vector<float> representation() const
{
return q;
}
X(const X& a) :Problem(a) {}
X(const std::vector<bool> &a):Problem() { for (bool s:a) data.push_back((float)s);}
protected:
std::vector<float> q;
};
int main(int argc,char**)
{
srand(time(NULL));

7
tests/nn-03.cpp
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@@ -8,7 +8,7 @@
class X: public Shin::NeuronNetwork::Problem
{
public:
X(const X& a) :q(a.q) {}
X(const X& a) :Problem(),q(a.q) {}
X(const std::vector<float> &a):q(a) {}
std::vector<float> representation() const
{
@@ -33,8 +33,9 @@ int main()
s.push_back(Shin::NeuronNetwork::Solution(std::vector<float>({1})));
p.push_back(X(std::vector<float>({1,1})));
Shin::NeuronNetwork::FeedForwardNetworkQuick q({2,2,4,1});
Shin::NeuronNetwork::FeedForwardNetworkQuick q({2,4,1});
Shin::NeuronNetwork::Learning::BackPropagation b(q);
b.setLearningCoeficient(10);
b.debugOn();
for(int i=0;i<4;i++)
@@ -45,7 +46,7 @@ int main()
}
b.debugOff();
for(int i=0;i<4000;i++)
for(int i=0;i<40000;i++)
{
b.teach(p[i%4],s[i%4]);
}

12
tests/nn-bp-xor.cpp
View File

@@ -7,14 +7,8 @@
class X: public Shin::NeuronNetwork::Problem
{
public:
X(const X& a) :q(a.q) {}
X(const std::vector<float> &a):q(a) {}
std::vector<float> representation() const
{
return q;
}
protected:
std::vector<float> q;
X(const X& a) :Problem(a) {}
X(const std::vector<float> &a):Problem() {data=a;}
};
int main()
@@ -66,7 +60,7 @@ int main()
std::cerr << j << "(" << err <<"):\n";
for(int i=0;i<4;i++)
{
std::cerr << "\t" << i%4 <<". FOR: [" << p[i%4]->representation()[0] << "," <<p[i%4]->representation()[1] << "] res: " <<
std::cerr << "\t" << i%4 <<". FOR: [" << p[i%4]->operator[](0) << "," <<p[i%4]->operator[](1) << "] res: " <<
q.solve(*p[i%4])[0] << " should be " << s[i%4]->operator[](0)<<"\n";
}
}

12
tests/nn-obp-xor.cpp
View File

@@ -7,14 +7,8 @@
class X: public Shin::NeuronNetwork::Problem
{
public:
X(const X& a) :q(a.q) {}
X(const std::vector<float> &a):q(a) {}
std::vector<float> representation() const
{
return q;
}
protected:
std::vector<float> q;
X(const X& a) :Problem(a) {}
X(const std::vector<float> &a):Problem() {data=a;}
};
int main()
@@ -67,7 +61,7 @@ int main()
std::cerr << j << "(" << err <<"):\n";
for(int i=0;i<4;i++)
{
std::cerr << "\t" << i%4 <<". FOR: [" << p[i%4]->representation()[0] << "," <<p[i%4]->representation()[1] << "] res: " <<
std::cerr << "\t" << i%4 <<". FOR: [" << p[i%4]->operator[](0) << "," <<p[i%4]->operator[](1) << "] res: " <<
q.solve(*p[i%4])[0] << " should be " << s[i%4]->operator[](0)<<"\n";
}
}

25
tests/nn-rl-and.cpp
View File

@@ -8,14 +8,8 @@
class X: public Shin::NeuronNetwork::Problem
{
public:
X(const X& a) :q(a.q) {}
X(const std::vector<float> &a):q(a) {}
std::vector<float> representation() const
{
return q;
}
protected:
std::vector<float> q;
X(const X& a) :Problem(a) {}
X(const std::vector<float> &a):Problem() {data=a;}
};
int main()
@@ -28,14 +22,17 @@ int main()
p.push_back(new X(std::vector<float>({1,1})));
Shin::NeuronNetwork::FeedForwardNetworkQuick q({1,1});
p.push_back(new X(std::vector<float>({1,0})));
p.push_back(new X(std::vector<float>({0,1})));
Shin::NeuronNetwork::FeedForwardNetworkQuick q({2,1});
Shin::NeuronNetwork::Learning::Reinforcement b(q);
int i=0;
double targetQuality=1.4;
double targetQuality=0.5;
b.setQualityFunction(
[](const Shin::NeuronNetwork::Problem &pr,const Shin::NeuronNetwork::Solution &s)->float
{
if(pr.representation()[0]==0)
if(pr[0]==1 && pr[1]==1)
{
//ocekavame 1
int e=(s[0]-0.80)*15.0;//+(abs(s[1])-0.5)*100.0;
@@ -54,12 +51,12 @@ int main()
if(i%100000==0)
srand(time(NULL));
if(err > targetQuality)
if(err > targetQuality||i%1000==0)
{
std::cerr << i << " ("<< err <<").\n";
for(int j=0;j<2;j++)
for(int j=0;j<4;j++)
{
std::cerr << j%4 <<". FOR: [" << p[j%4]->representation()[0] << "," <<p[j%4]->representation()[0] << "] res: " << q.solve(*p[j%4])[0] << "\n";
std::cerr << j%4 <<". FOR: [" << p[j%4]->operator[](0) << "," <<p[j%4]->operator[](0) << "] res: " << q.solve(*p[j%4])[0] << "\n";
}
}
if(err >targetQuality)

25
tests/nn-rl-xor.cpp
View File

@@ -5,19 +5,15 @@
#include <iostream>
#include <vector>
class X: public Shin::NeuronNetwork::Problem
{
public:
X(const X& a) :q(a.q) {}
X(const std::vector<float> &a):q(a) {}
std::vector<float> representation() const
{
return q;
}
protected:
std::vector<float> q;
X(const X& a) :Problem(a) {}
X(const std::vector<float> &a):Problem() {data=a;}
};
int main()
{
srand(time(NULL));
@@ -26,9 +22,9 @@ int main()
Shin::NeuronNetwork::FeedForwardNetworkQuick q({2,4,1});
Shin::NeuronNetwork::Learning::Reinforcement b(q);
//b.setPropagator(new Shin::NeuronNetwork::Learning::OpticalBackPropagation(q));
b.getPropagator().setLearningCoeficient(3);
b.getPropagator().setLearningCoeficient(0.4);
//b.getPropagator().allowEntropy();
double targetQuality =1;
double targetQuality =2.9;
if(test==2)
{
targetQuality =1.62;
@@ -38,9 +34,8 @@ int main()
b.getPropagator().setLearningCoeficient(0.5);
}
b.setQualityFunction(
[](const Shin::NeuronNetwork::Problem &pr,const Shin::NeuronNetwork::Solution &s)->float
[](const Shin::NeuronNetwork::Problem &p,const Shin::NeuronNetwork::Solution &s)->float
{
std::vector <float> p=pr;
float expect=0.0;
if(p[0] && p[1])
expect=0;
@@ -55,10 +50,10 @@ int main()
if(expect==0)
{
expect=0.1-abs(s[0]);
expect=0.3-abs(s[0]);
}else
{
expect=s[0]-0.9;
expect=s[0]-0.7;
}
// std::cerr << " returnning " << expect*5.0 << "\n";
@@ -93,7 +88,7 @@ int main()
std::cerr << i << " ("<< err <<").\n";
for(int j=0;j<4;j++)
{
std::cerr << "\t" << j%4 << ". FOR: [" << p[j%4]->representation()[0] << "," <<p[j%4]->representation()[1] << "] res: " <<
std::cerr << "\t" << i%4 <<". FOR: [" << p[j%4]->operator[](0) << "," <<p[j%4]->operator[](1) << "] res: " <<
q.solve(*p[j%4])[0] << "\n";
}
}