private static void SampleHutter()
{
const long timeWindowSize = 10L;
SigmaEnvironment sigma = SigmaEnvironment.Create("recurrent");
IDataSource source = new MultiSource(new FileSource("enwik8"), new CompressedSource(new MultiSource(new FileSource("enwik8.zip"), new UrlSource("http://mattmahoney.net/dc/enwik8.zip"))));
IRecordExtractor extractor = new CharacterRecordReader(source, (int)(timeWindowSize + 1), Encoding.ASCII)
.Extractor(new ArrayRecordExtractor <short>(ArrayRecordExtractor <short>
.ParseExtractorParameters("inputs", new[] { 0L }, new[] { timeWindowSize }, "targets", new[] { 0L }, new[] { timeWindowSize }))
.Offset("targets", 1L))
.Preprocess(new PermutePreprocessor(0, 2, 1))
.Preprocess(new OneHotPreprocessor(0, 255));
IDataset dataset = new ExtractedDataset("hutter", ExtractedDataset.BlockSizeAuto, false, extractor);
ITrainer trainer = sigma.CreateTrainer("hutter");
trainer.Network.Architecture = InputLayer.Construct(256) + RecurrentLayer.Construct(256) + OutputLayer.Construct(256) + SoftMaxCrossEntropyCostLayer.Construct();
trainer.TrainingDataIterator = new MinibatchIterator(32, dataset);
trainer.AddNamedDataIterator("validation", new MinibatchIterator(100, dataset));
trainer.Optimiser = new AdagradOptimiser(baseLearningRate: 0.07);
trainer.Operator = new CudaSinglethreadedOperator();
trainer.AddInitialiser("*.*", new GaussianInitialiser(standardDeviation: 0.05));
trainer.AddLocalHook(new AccumulatedValueReporter("optimiser.cost_total", TimeStep.Every(1, TimeScale.Iteration), averageValues: true));
trainer.AddLocalHook(new RunningTimeReporter(TimeStep.Every(10, TimeScale.Iteration)));
sigma.PrepareAndRun();
}
public void TestByteRecordExtractorExtract()
{
ArrayRecordExtractor <byte> extractor = new ArrayRecordExtractor <byte>(ArrayRecordExtractor <byte> .ParseExtractorParameters("inputs", new[] { 0L }, new[] { 1L }));
IComputationHandler handler = new CpuFloat32Handler();
Assert.Throws <InvalidOperationException>(() => extractor.ExtractDirect(10, handler));
byte[][] rawData = new[] { new byte[] { 0 }, new byte[] { 1 } };
Assert.AreEqual(new float[] { 0, 1 }, extractor.ExtractDirectFrom(rawData, 2, handler)["inputs"].GetDataAs <float>().GetValuesArrayAs <float>(0L, 2L));
}
public void TestByteRecordExtractorCreate()
{
string filename = ".unittestfile" + nameof(TestByteRecordExtractorCreate);
CreateCsvTempFile(filename);
FileSource source = new FileSource(filename, Path.GetTempPath());
Assert.Throws <ArgumentNullException>(() => new ArrayRecordExtractor <byte>(null));
Assert.Throws <ArgumentException>(() => new ArrayRecordExtractor <byte>(new Dictionary <string, long[][]>()
{
["test"] = new long[1][] { new long[] { 1, 2, 3 } }
}));
ArrayRecordExtractor <byte> extractor = new ArrayRecordExtractor <byte>(ArrayRecordExtractor <byte> .ParseExtractorParameters("inputs", new[] { 0L }, new[] { 1L }));
Assert.AreEqual(new[] { "inputs" }, extractor.SectionNames);
source.Dispose();
DeleteTempFile(filename);
}
public ArrayRecordExtractor <byte> Extractor(params object[] parameters)
{
return((ArrayRecordExtractor <byte>)Extractor(ArrayRecordExtractor <byte> .ParseExtractorParameters(parameters)));
}
