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); } } }