import java.util.Random; import model.Model; import trainer.Trainer; import util.NeuralNetworkHelper; import datasets.TextGenerationUnbroken; import datastructs.DataSet; public class ExampleLilDicky { public static void main(String[] args) throws Exception { Random rng = new Random(); int totalSequences = 2000; int sequenceMinLength = 10; int sequenceMaxLength = 100; String textSource = "LilDicky"; DataSet data = new TextGenerationUnbroken("datasets/text/"+textSource+".txt", totalSequences, sequenceMinLength, sequenceMaxLength, rng); String savePath = "saved_models/"+textSource+".ser"; boolean initFromSaved = true; //set this to false to start with a fresh model boolean overwriteSaved = true; TextGenerationUnbroken.reportSequenceLength = 500; int bottleneckSize = 10; //one-hot input is squeezed through this int hiddenDimension = 200; int hiddenLayers = 1; double learningRate = 0.001; double initParamsStdDev = 0.08; Model lstm = NeuralNetworkHelper.makeLstmWithInputBottleneck( data.inputDimension, bottleneckSize, hiddenDimension, hiddenLayers, data.outputDimension, data.getModelOutputUnitToUse(), initParamsStdDev, rng); int reportEveryNthEpoch = 10; int trainingEpochs = 1000; Trainer.train(trainingEpochs, learningRate, lstm, data, reportEveryNthEpoch, initFromSaved, overwriteSaved, savePath, rng); System.out.println("done."); } }