public void TestRPROPCont()
{
IMLDataSet trainingSet = XOR.CreateXORDataSet();
BasicNetwork net1 = XOR.CreateUnTrainedXOR();
BasicNetwork net2 = XOR.CreateUnTrainedXOR();
ResilientPropagation rprop1 = new ResilientPropagation(net1, trainingSet);
ResilientPropagation rprop2 = new ResilientPropagation(net2, trainingSet);
rprop1.Iteration();
rprop1.Iteration();
rprop2.Iteration();
rprop2.Iteration();
TrainingContinuation cont = rprop2.Pause();
ResilientPropagation rprop3 = new ResilientPropagation(net2, trainingSet);
rprop3.Resume(cont);
rprop1.Iteration();
rprop3.Iteration();
for (int i = 0; i < net1.Flat.Weights.Length; i++)
{
Assert.AreEqual(net1.Flat.Weights[i], net2.Flat.Weights[i], 0.0001);
}
}
public void TestRPROPContPersistEG()
{
IMLDataSet trainingSet = XOR.CreateXORDataSet();
BasicNetwork net1 = XOR.CreateUnTrainedXOR();
BasicNetwork net2 = XOR.CreateUnTrainedXOR();
ResilientPropagation rprop1 = new ResilientPropagation(net1, trainingSet);
ResilientPropagation rprop2 = new ResilientPropagation(net2, trainingSet);
rprop1.Iteration();
rprop1.Iteration();
rprop2.Iteration();
rprop2.Iteration();
TrainingContinuation cont = rprop2.Pause();
EncogDirectoryPersistence.SaveObject(EG_FILENAME, cont);
TrainingContinuation cont2 = (TrainingContinuation)EncogDirectoryPersistence.LoadObject(EG_FILENAME);
ResilientPropagation rprop3 = new ResilientPropagation(net2, trainingSet);
rprop3.Resume(cont2);
rprop1.Iteration();
rprop3.Iteration();
for (int i = 0; i < net1.Flat.Weights.Length; i++)
{
Assert.AreEqual(net1.Flat.Weights[i], net2.Flat.Weights[i], 0.0001);
}
}
static void Main(string[] args)
{
using (var p = Process.GetCurrentProcess())
p.PriorityClass = ProcessPriorityClass.Idle;
FileInfo dataSetFile = new FileInfo("dataset.egb");
FileInfo networkFile = new FileInfo($"network{networkID}.nn");
FileInfo trainFile = new FileInfo($"train{networkID}.tr");
Console.WriteLine("Loading dataset.");
if (!dataSetFile.Exists)
{
ExtractTrainData(dataSetFile);
Console.WriteLine(@"Extracting dataset from database: " + dataSetFile);
return;
}
var trainingSet = EncogUtility.LoadEGB2Memory(dataSetFile);
Console.WriteLine($"Loaded {trainingSet.Count} samples. Input size: {trainingSet.InputSize}, Output size: {trainingSet.IdealSize}");
BasicNetwork network;
if (networkFile.Exists)
{
Console.WriteLine($"Loading network {networkFile.FullName}");
network = (BasicNetwork)EncogDirectoryPersistence.LoadObject(networkFile);
}
else
{
Console.WriteLine("Creating NN.");
network = EncogUtility.SimpleFeedForward(trainingSet.InputSize, 1000, 200, trainingSet.IdealSize, true);
network.Reset();
}
using (var p = Process.GetCurrentProcess())
Console.WriteLine($"RAM usage: {p.WorkingSet64 / 1024 / 1024} MB.");
ResilientPropagation train = new ResilientPropagation(network, trainingSet)
{
ThreadCount = 0
};
if (trainFile.Exists)
{
TrainingContinuation cont = (TrainingContinuation)EncogDirectoryPersistence.LoadObject(trainFile);
train.Resume(cont);
}
MyTrainConsole(train, network, trainingSet, minutes, networkFile, trainFile);
Console.WriteLine(@"Final Error: " + train.Error);
Console.WriteLine(@"Training complete, saving network.");
EncogDirectoryPersistence.SaveObject(networkFile, network);
Console.WriteLine(@"Network saved. Press s to stop.");
ConsoleKeyInfo key;
do
{
key = Console.ReadKey();
}while (key.KeyChar != 's');
}
