static void Main(string[] args)
{
//MLPWithBiasTest test = new MLPWithBiasTest();
//MLPTest test = new MLPTest();
//test.TestXOR();
//test.TestDigit();
//return;
/*
* CsvMgrTest test = new CsvMgrTest();
* test.LoadTest("test.csv");
*/
string filename = "MLP-";
filename += DateTime.Now.Ticks;
filename += ".txt";
StreamWriter sw = new StreamWriter(filename);
Console.SetOut(sw);
sw.AutoFlush = true;
MnistDataMgr trainDataMgr = new MnistDataMgr("train.csv");
trainDataMgr.Load();
Console.WriteLine("Train data loaded");
MnistDataMgr testDataMgr = new MnistDataMgr("test.csv");
testDataMgr.Load();
Console.WriteLine("Test data loaded");
MnistMLPTrainer trainer = new MnistMLPTrainer(trainDataMgr);
//int[] layerStruct = { trainDataMgr.inputNum, 100, 50, 20, 10 };
//int[] layerStruct = { trainDataMgr.inputNum, 150, 50, 10 };
//int[] layerStruct = { trainDataMgr.inputNum, 100, 50, 10 };
int[] layerStruct = { trainDataMgr.inputNum, 80, 30, 10 };
trainer.InitMLP(layerStruct, 0.8);
//trainer.InitMLP(200, 0.8);
trainer.OnlineTrain();
//trainer.BatchTrain();
//dataMgr.Dump("test2.csv");
MnistMLPTester tester = new MnistMLPTester(trainer.GetNetwork(), testDataMgr);
tester.Test();
trainer.GetNetwork().DumpToFile();
sw.Flush();
sw.Close();
return;
}
static void Main(string[] args)
{
string filename = "DBN-";
filename += DateTime.Now.Ticks;
filename += ".txt";
StreamWriter sw = new StreamWriter(filename);
Console.SetOut(sw);
sw.AutoFlush = true;
MnistDataMgr trainDataMgr = new MnistDataMgr("train.csv");
trainDataMgr.Load();
Console.WriteLine("Train data loaded");
MnistDataMgr testDataMgr = new MnistDataMgr("test.csv");
testDataMgr.Load();
Console.WriteLine("Test data loaded");
//int [] netStruct = {trainDataMgr.inputNum, 100, 50, 20};
//int[] netStruct = { trainDataMgr.inputNum, 200 };
int[] netStruct = { trainDataMgr.inputNum, 200 };
LRBM lrbm = new LRBM(1, netStruct);
LRBMTrainer lrbmTrainer = new LRBMTrainer(trainDataMgr, lrbm);
lrbmTrainer.BatchTrain();
//lrbmTrainer.OnlineTrain();
lrbm.DumpToFile();
//DeepBeliefNet dbn = new DeepBeliefNet(0.8, lrbm, 10);
DeepBeliefNet dbn = new DeepBeliefNet(0.8, lrbm, new int[] { 200, 10 });
dbn.DumpToFile();
dbn.GetMLP().DumpToFile();
//dbn.GetMLP().ClearBias();
//dbn.GetMLP()._trainType = MLP.TrainType.TRAIN_ONLY_OUTPUT_LAYER;
dbn.GetMLP()._trainType = MLP.TrainType.NORMAL_BP;
dbn.GetMLP().learningDepth = 2;
MnistMLPTrainer trainer = new MnistMLPTrainer(trainDataMgr, dbn.GetMLP());
trainer.OnlineTrain();
MnistMLPTester tester = new MnistMLPTester(dbn.GetMLP(), testDataMgr);
tester.Test();
sw.Flush();
sw.Close();
}
