static FeedForwardLayer loadFFLayer(string dir)
{
try
{
//loading noLinearity
string noLinearity = "";
using (StreamReader sr = new StreamReader(Path.Combine(dir, "info.csv")))
{
noLinearity = sr.ReadLine();
}
INonlinearity lin = null;
if (noLinearity == "LinearUnit")
{
lin = new LinearUnit();
}
if (noLinearity == "RectifiedLinearUnit")
{
lin = new RectifiedLinearUnit();
}
if (noLinearity == "SigmoidUnit")
{
lin = new SigmoidUnit();
}
if (noLinearity == "SineUnit")
{
lin = new SineUnit();
}
if (noLinearity == "TanhUnit")
{
lin = new TanhUnit();
}
Matrix w = loadMatrix(Path.Combine(dir, "W.csv"));
Matrix b = loadMatrix(Path.Combine(dir, "B.csv"));
return(new FeedForwardLayer(w, b, lin));
}
catch (Exception ex)
{
Console.WriteLine(ex.Message);
}
return(null);
}
public static void Run()
{
Random rnd = new Random();
FieldLetterTranslator.addChar((char)10);
Console.WriteLine("Generate started");
DataSet data = new TextDataSetGenerator(@"C:\Users\Kubik.HOME-PC\Dropbox\shakespear.txt");
Console.WriteLine("Generate comlpeat");
int inputDimension = FieldLetterTranslator.Letters.Length;
int hiddenDimension = 128;
int outputDimension = FieldLetterTranslator.Letters.Length;
int hiddenLayers = 2;
double learningRate = 0.0012;
double initPatStdDev = 0.08;
INonlinearity lin = new SigmoidUnit();
NeuralNetwork network = NetworkBuilder.MakeLstm(inputDimension, hiddenDimension, hiddenLayers, outputDimension, lin, initPatStdDev, rnd);
string output;
int reportEveryNthEpoch = 50;
int trainingEpochs = 50;
for (int i = 0; i < trainingEpochs; i++)
{
Trainer.train <NeuralNetwork>(1, learningRate, network, data, reportEveryNthEpoch, rnd);
if (Directory.Exists(@"C:\Users\Kubik.HOME-PC\Documents\NeuralsTraing4\step" + i.ToString()))
{
Directory.Delete(@"C:\Users\Kubik.HOME-PC\Documents\NeuralsTraing4\step" + i.ToString(), true);
}
learningRate *= 0.85;
Directory.CreateDirectory(@"C:\Users\Kubik.HOME-PC\Documents\NeuralsTraing4\step" + i.ToString());
NetworkBuilder.SaveLSTM(network, @"C:\Users\Kubik.HOME-PC\Documents\NeuralsTraing4\step" + i.ToString());
output = generateOutput(network, 'a', 1000);
using (StreamWriter sw = new StreamWriter(Path.Combine(@"C:\Users\Kubik.HOME-PC\Documents\NeuralsTraing4\outputs", "output" + i.ToString() + ".txt")))
{
sw.WriteLine(output);
}
}
}
