protected MockTrainer(string name) : base(name)
{
Network = new Network("test");
Network.Architecture = new LinearNetworkArchitecture(MockLayer.Construct());
Optimiser = new GradientDescentOptimiser(0.0);
IRecordExtractor extractor = new MockRecordExtractor();
extractor.SectionNames = new[] { "targets", "inputs" };
extractor.Reader = new MockRecordReader();
Sigma = SigmaEnvironment.GetOrCreate("testificate-mocktrainer");
TrainingDataIterator = new UndividedIterator(new ExtractedDataset("testificate", extractor));
}
public void TestUndividedIteratorYield()
{
string filename = ".unittestfile" + nameof(TestUndividedIteratorCreate);
CreateCsvTempFile(filename);
SigmaEnvironment.Clear();
FileSource source = new FileSource(filename, Path.GetTempPath());
CsvRecordExtractor extractor = (CsvRecordExtractor) new CsvRecordReader(source).Extractor(new CsvRecordExtractor(new Dictionary <string, int[][]> {
["inputs"] = new[] { new[] { 0 } }
}));
ExtractedDataset dataset = new ExtractedDataset("test", 2, new DiskCacheProvider(Path.GetTempPath() + "/" + nameof(TestUndividedIteratorCreate)), true, extractor);
UndividedIterator iterator = new UndividedIterator(dataset);
SigmaEnvironment sigma = SigmaEnvironment.Create("test");
IComputationHandler handler = new CpuFloat32Handler();
int index = 0;
foreach (var block in iterator.Yield(handler, sigma))
{
if (index == 0)
{
Assert.AreEqual(new float[] { 5.1f, 4.9f }, block["inputs"].GetDataAs <float>().GetValuesArrayAs <float>(0, 2));
}
else if (index == 1)
{
Assert.AreEqual(new float[] { 4.7f }, block["inputs"].GetDataAs <float>().GetValuesArrayAs <float>(0, 1));
}
else
{
Assert.Fail("There can be a maximum of two iterations, but this is yield iteration 3 (index 2).");
}
index++;
}
dataset.Dispose();
DeleteTempFile(filename);
}
