blacklight
/
neuralpp
mirror of https://github.com/BlackLight/neuralpp.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Trying to fix, again...

This commit is contained in:
blacklight 2009-08-10 18:06:52 +02:00
parent 3f56c8404c
commit 37995f75c2
5 changed files with 147 additions and 65 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

28
include/neural++.hpp
View File

@ -26,10 +26,10 @@
using namespace std;
//! Default rand value: |sin(rand)|, always >= 0 and <= 1
#define RAND ( abs( sin(rand()) ) )
#define RAND (double) ( (rand() / (RAND_MAX/2)) - 1)
//! Initial value for the inertial momentum of the synapses
#define BETA0 0.7
#define BETA0 0.8
/**
* @namespace neuralpp
@ -40,8 +40,6 @@ namespace neuralpp {
class Neuron;
class Layer;
class NeuralNet;
class NetworkFileNotFoundException;
class InvalidXMLException;
/**
* @class NeuralNet
@ -67,11 +65,11 @@ namespace neuralpp {
void commitChanges (Layer *l);
/**
* @brief It get the error made on the expected result as |v-v'|/v
* @brief Get the error made on the expected result as |v-v'|/v
* @param ex Expected value
* @return Mean error
*/
double error(double ex);
double error(double ex) const;
/**
* @brief Private pointer to function, containing the function to
@ -117,7 +115,7 @@ namespace neuralpp {
* @param file Binary file containing a neural network previously saved by save() method
* @throw NetworkFileNotFoundException
*/
NeuralNet (const char* file) throw(NetworkFileNotFoundException);
NeuralNet (const string file) throw(NetworkFileNotFoundException);
/**
@ -140,7 +138,7 @@ namespace neuralpp {
* an only neuron)
* @return The output value of the network
*/
double getOutput();
double getOutput() const;
/**
* @brief It gets the output of the network in case the output layer contains more neurons
@ -153,7 +151,7 @@ namespace neuralpp {
* build your network by using setExpected.
* @return The expected output value for a certain training phase
*/
double expected();
double expected() const;
/**
* @brief It sets the value you expect from your network
@ -189,8 +187,10 @@ namespace neuralpp {
/**
* @brief Save a trained neural network to a binary file
* @param fname Binary file where you're going to save your network
* @throws NetworkFileWriteException When you get an error writing the network's information to
* a file
*/
bool save(const char* fname);
void save(const char* fname) throw(NetworkFileWriteException);
/**
* @brief Train a network using a training set loaded from an XML file. A sample XML file
@ -296,14 +296,14 @@ namespace neuralpp {
* @brief Set the weight of the synapsis
* @param w Weight to be set
*/
void setWeight(double w);
void setWeight(double w) throw(InvalidSynapticalWeightException);
/**
* @brief It sets the delta (how much to change the weight after an update)
* of the synapsis
* @param d Delta to be set
*/
void setDelta(double d);
void setDelta(double d) throw(InvalidSynapticalWeightException);
/**
* @brief Return the weight of the synapsis
@ -476,7 +476,7 @@ namespace neuralpp {
* @param i Index of the neuron to get in the layer
* @return Reference to the i-th neuron
*/
Neuron& operator[] (size_t i);
Neuron& operator[] (size_t i) throw(NetworkIndexOutOfBoundsException);
/**
* @brief It links a layer to another
@ -504,7 +504,7 @@ namespace neuralpp {
/**
* @return Number of neurons in the layer
*/
size_t size();
size_t size() const;
};
struct netrecord {

33
include/neural++_exception.hpp
View File

@ -31,6 +31,17 @@ namespace neuralpp {
const char* what() const throw() { return "Attempt to load a neural network from an invalid network file"; }
};
/**
* @class NetworkFileWriteException
* @brief Exception thrown when trying to write the network's information to a file that cannot
* be written
*/
class NetworkFileWriteException : public std::exception {
public:
NetworkFileWriteException() {}
const char* what() const throw() { return "There was an error while writing the network file"; }
};
/**
* @class InvalidXMLException
* @brief Exception thrown when trying parsing an invalid XML
@ -40,6 +51,28 @@ namespace neuralpp {
InvalidXMLException() {}
const char* what() const throw() { return "Attempt to load an invalid XML file"; }
};
/**
* @class NetworkIndexOutOfBoundsException
* @brief Exception raised when trying to access a neuron whose index is larger than the number
* of neurons in the network
*/
class NetworkIndexOutOfBoundsException : public std::exception {
public:
NetworkIndexOutOfBoundsException() {}
const char* what() const throw() { return "Attempt to access a non-existing neuron"; }
};
/**
* @class InvalidSynapticalWeightException
* @brief Exception raised when, while trying the network or directly, the weight of a synapsis is
* set to a value |w| > 1
*/
class InvalidSynapticalWeightException : public std::exception {
public:
InvalidSynapticalWeightException() {}
const char* what() const throw() { return "Attempt to set an invalid weight for the synapsis"; }
};
}
#endif

11
src/layer.cpp
View File

@ -19,7 +19,9 @@ namespace neuralpp {
for (size_t i = 0; i < sz; i++) {
Neuron n(a, d);
elements.push_back(n);
} actv_f = a;
}
actv_f = a;
deriv = d;
}
@ -30,11 +32,14 @@ namespace neuralpp {
deriv = d;
}
size_t Layer::size() {
size_t Layer::size() const {
return elements.size();
}
Neuron & Layer::operator[](size_t i) {
Neuron & Layer::operator[](size_t i) throw(NetworkIndexOutOfBoundsException) {
if (i > size())
throw NetworkIndexOutOfBoundsException();
return elements[i];
}

127
src/neuralnet.cpp
View File

@ -11,7 +11,9 @@
* this program. If not, see <http://www.gnu.org/licenses/>. *
**************************************************************************************************/
#include <fstream>
#include <sstream>
#include "neural++.hpp"
#include "Markup.h"
@ -56,7 +58,7 @@ namespace neuralpp {
link();
}
double NeuralNet::getOutput() {
double NeuralNet::getOutput() const {
return (*output)[0].getActv();
}
@ -68,7 +70,7 @@ namespace neuralpp {
return v;
}
double NeuralNet::error(double expected) {
double NeuralNet::error(double expected) const {
return abs((getOutput() - expected *
deriv(getOutput())) / (abs(expected)));
}
@ -92,7 +94,7 @@ namespace neuralpp {
ex = e;
}
double NeuralNet::expected() {
double NeuralNet::expected() const {
return ex;
}
@ -168,12 +170,12 @@ namespace neuralpp {
}
}
bool NeuralNet::save(const char *fname) {
FILE *fp;
void NeuralNet::save (const char *fname) throw(NetworkFileWriteException) {
struct netrecord record;
ofstream out(fname);
if (!(fp = fopen(fname, "wb")))
return false;
if (!out)
throw NetworkFileWriteException();
record.input_size = input->size();
record.hidden_size = hidden->size();
@ -183,96 +185,113 @@ namespace neuralpp {
record.l_rate = l_rate;
record.ex = ex;
if (fwrite(&record, sizeof(struct netrecord), 1, fp) <= 0)
return false;
if (out.write((char*) &record, sizeof(struct netrecord)) <= 0)
throw NetworkFileWriteException();
// Saving neurons' state
for (unsigned int i = 0; i < input->size(); i++) {
struct neuronrecord r;
r.prop = (*input)[i].getProp();
r.actv = (*input)[i].getActv();
fwrite(&r, sizeof(struct neuronrecord), 1, fp);
if (out.write((char*) &r, sizeof(struct neuronrecord)) <= 0)
throw NetworkFileWriteException();
}
for (unsigned int i = 0; i < hidden->size(); i++) {
struct neuronrecord r;
r.prop = (*hidden)[i].getProp();
r.actv = (*hidden)[i].getActv();
fwrite(&r, sizeof(struct neuronrecord), 1, fp);
if (out.write((char*) &r, sizeof(struct neuronrecord)) <= 0)
throw NetworkFileWriteException();
}
for (unsigned int i = 0; i < output->size(); i++) {
struct neuronrecord r;
r.prop = (*output)[i].getProp();
r.actv = (*output)[i].getActv();
fwrite(&r, sizeof(struct neuronrecord), 1, fp);
if (out.write((char*) &r, sizeof(struct neuronrecord)) <= 0)
throw NetworkFileWriteException();
}
// Saving synapsis' state
for (unsigned int i = 0; i < input->size(); i++) {
int nout = (*input)[i].nOut();
fwrite(&nout, sizeof(int), 1, fp);
if (out.write((char*) &nout, sizeof(int)) <= 0)
throw NetworkFileWriteException();
for (int j = 0; j < nout; j++) {
struct synrecord r;
r.w = (*input)[i].synOut(j).getWeight();
r.d = (*input)[i].synOut(j).getDelta();
fwrite(&r, sizeof(struct synrecord), 1,
fp);
if (out.write((char*) &r, sizeof(struct synrecord)) <= 0)
throw NetworkFileWriteException();
}
}
for (unsigned int i = 0; i < output->size(); i++) {
int nin = (*output)[i].nIn();
fwrite(&nin, sizeof(int), 1, fp);
if (out.write((char*) &nin, sizeof(int)) <= 0)
throw NetworkFileWriteException();
for (int j = 0; j < nin; j++) {
struct synrecord r;
r.w = (*output)[i].synIn(j).getWeight();
r.d = (*output)[i].synIn(j).getDelta();
fwrite(&r, sizeof(struct synrecord), 1,
fp);
if (out.write((char*) &r, sizeof(struct synrecord)) <= 0)
throw NetworkFileWriteException();
}
}
for (unsigned int i = 0; i < hidden->size(); i++) {
int nin = (*hidden)[i].nIn();
fwrite(&nin, sizeof(int), 1, fp);
if (out.write((char*) &nin, sizeof(int)) <= 0)
throw NetworkFileWriteException();
for (int j = 0; j < nin; j++) {
struct synrecord r;
r.w = (*hidden)[i].synIn(j).getWeight();
r.d = (*hidden)[i].synIn(j).getDelta();
fwrite(&r, sizeof(struct synrecord), 1,
fp);
if (out.write((char*) &r, sizeof(struct synrecord)) <= 0)
throw NetworkFileWriteException();
}
}
for (unsigned int i = 0; i < hidden->size(); i++) {
int nout = (*hidden)[i].nOut();
fwrite(&nout, sizeof(int), 1, fp);
if (out.write((char*) &nout, sizeof(int)) <= 0)
throw NetworkFileWriteException();
for (int j = 0; j < nout; j++) {
struct synrecord r;
r.w = (*hidden)[i].synOut(j).getWeight();
r.d = (*hidden)[i].synOut(j).getDelta();
fwrite(&r, sizeof(struct synrecord), 1,
fp);
if (out.write((char*) &r, sizeof(struct synrecord)) <= 0)
throw NetworkFileWriteException();
}
}
fclose(fp);
return true;
out.close();
}
NeuralNet::NeuralNet(const char *fname) throw(NetworkFileNotFoundException) {
NeuralNet::NeuralNet(const string fname) throw(NetworkFileNotFoundException) {
struct netrecord record;
FILE *fp;
ifstream in(fname.c_str());
if (!(fp = fopen(fname, "rb")))
if (!in)
throw NetworkFileNotFoundException();
if (fread(&record, sizeof(struct netrecord), 1, fp) <= 0)
if (in.read((char*) &record, sizeof(struct netrecord)) <= 0)
throw NetworkFileNotFoundException();
*this =
@ -283,7 +302,9 @@ namespace neuralpp {
// Restore neurons
for (unsigned int i = 0; i < input->size(); i++) {
struct neuronrecord r;
fread(&r, sizeof(struct neuronrecord), 1, fp);
if (in.read((char*) &r, sizeof(struct neuronrecord)) <= 0)
throw NetworkFileNotFoundException();
(*input)[i].setProp(r.prop);
(*input)[i].setActv(r.actv);
@ -292,7 +313,9 @@ namespace neuralpp {
for (unsigned int i = 0; i < hidden->size(); i++) {
struct neuronrecord r;
fread(&r, sizeof(struct neuronrecord), 1, fp);
if (in.read((char*) &r, sizeof(struct neuronrecord)) <= 0)
throw NetworkFileNotFoundException();
(*hidden)[i].setProp(r.prop);
(*hidden)[i].setActv(r.actv);
@ -301,7 +324,9 @@ namespace neuralpp {
for (unsigned int i = 0; i < output->size(); i++) {
struct neuronrecord r;
fread(&r, sizeof(struct neuronrecord), 1, fp);
if (in.read((char*) &r, sizeof(struct neuronrecord)) <= 0)
throw NetworkFileNotFoundException();
(*output)[i].setProp(r.prop);
(*output)[i].setActv(r.actv);
@ -323,12 +348,16 @@ namespace neuralpp {
// Restore synapsis
for (unsigned int i = 0; i < input->size(); i++) {
int nout;
fread(&nout, sizeof(int), 1, fp);
if (in.read((char*) &nout, sizeof(int)) <= 0 )
throw NetworkFileNotFoundException();
for (int j = 0; j < nout; j++) {
struct synrecord r;
fread(&r, sizeof(struct synrecord), 1, fp);
if (in.read((char*) &r, sizeof(struct synrecord)) <= 0)
throw NetworkFileNotFoundException();
(*input)[i].synOut(j).setWeight(r.w);
(*input)[i].synOut(j).setDelta(r.d);
}
@ -336,11 +365,15 @@ namespace neuralpp {
for (unsigned int i = 0; i < output->size(); i++) {
int nin;
fread(&nin, sizeof(int), 1, fp);
if (in.read((char*) &nin, sizeof(int)) <= 0)
throw NetworkFileNotFoundException();
for (int j = 0; j < nin; j++) {
struct synrecord r;
fread(&r, sizeof(struct synrecord), 1, fp);
if (in.read((char*) &r, sizeof(struct synrecord)) <= 0)
throw NetworkFileNotFoundException();
(*output)[i].synIn(j).setWeight(r.w);
(*output)[i].synIn(j).setDelta(r.d);
@ -349,11 +382,15 @@ namespace neuralpp {
for (unsigned int i = 0; i < hidden->size(); i++) {
int nin;
fread(&nin, sizeof(int), 1, fp);
if (in.read((char*) &nin, sizeof(int)) <= 0)
throw NetworkFileNotFoundException();
for (int j = 0; j < nin; j++) {
struct synrecord r;
fread(&r, sizeof(struct synrecord), 1, fp);
if (in.read((char*) &r, sizeof(struct synrecord)) <= 0)
throw NetworkFileNotFoundException();
(*hidden)[i].synIn(j).setWeight(r.w);
(*hidden)[i].synIn(j).setDelta(r.d);
@ -362,18 +399,22 @@ namespace neuralpp {
for (unsigned int i = 0; i < hidden->size(); i++) {
int nout;
fread(&nout, sizeof(int), 1, fp);
if (in.read((char*) &nout, sizeof(int)) <= 0)
throw NetworkFileNotFoundException();
for (int j = 0; j < nout; j++) {
struct synrecord r;
fread(&r, sizeof(struct synrecord), 1, fp);
if (in.read((char*) &r, sizeof(struct synrecord)) <= 0)
throw NetworkFileNotFoundException();
(*hidden)[i].synOut(j).setWeight(r.w);
(*hidden)[i].synOut(j).setDelta(r.d);
}
}
fclose(fp);
in.close();
}
void NeuralNet::train(string xmlsrc, NeuralNet::source src =
@ -438,7 +479,7 @@ namespace neuralpp {
return;
}
void NeuralNet::initXML(string & xml) {
void NeuralNet::initXML(string& xml) {
xml.append
("<?xml version=\"1.0\" encoding=\"iso-8859-1\"?>\n"
"<!DOCTYPE NETWORK SYSTEM \"http://blacklight.gotdns.org/prog/neuralpp/trainer.dtd\">\n"

13
src/synapsis.cpp
View File

@ -72,14 +72,17 @@ namespace neuralpp {
return prev_delta;
}
void Synapsis::setWeight(double w) {
void Synapsis::setWeight(double w) throw(InvalidSynapticalWeightException) {
if (weight > 1.0)
weight = 1.0;
else
weight = w;
throw InvalidSynapticalWeightException();
weight = w;
}
void Synapsis::setDelta(double d) {
void Synapsis::setDelta(double d) throw(InvalidSynapticalWeightException) {
if (d > 1.0)
throw InvalidSynapticalWeightException();
prev_delta = delta;
delta = d;
}