public void T2D_Detects_Repository_Commits()
{
Monitor.Expect(() =>
{
_cloneA.Commit("Commit #1 on A");
},
changes => changes >= 1,
deletes => deletes == 0);
}
/// <summary>
/// Train a model on a single example,
/// </summary>
/// <typeparam name="TOutput"></typeparam>
/// <param name="trainerMaker"></param>
/// <param name="checker"></param>
private static void TrivialHelper <TOutput>(Func <ITrainerHost, ITrainer <Instances, IPredictorProducing <TOutput> > > trainerMaker, Action <TOutput, TOutput> checker)
{
// The following simple instance should result in a "trivial" predictor for binary classification, regression, and multiclass, I think.
ListInstances instances = new ListInstances();
instances.AddInst(new Float[] { (Float)0.0 }, (Float)0);
instances.CopyMetadata(null);
ITrainerHost host = new TrainHost(new Random(1), 0);
var trainer = trainerMaker(host);
trainer.Train(instances);
IPredictor <Instance, TOutput> predictor = (IPredictor <Instance, TOutput>)trainer.CreatePredictor();
IPredictor <Instance, TOutput> loadedPredictor = default(IPredictor <Instance, TOutput>);
using (Stream stream = new MemoryStream())
{
using (RepositoryWriter writer = RepositoryWriter.CreateNew(stream, false))
{
ModelSaveContext.SaveModel(writer, predictor, "foo");
writer.Commit();
}
stream.Position = 0;
using (RepositoryReader reader = RepositoryReader.Open(stream, false))
{
ModelLoadContext.LoadModel(out loadedPredictor, reader, "foo");
}
Assert.AreNotEqual(default(IPredictor <Instance, TOutput>), loadedPredictor, "did not load expected model");
}
TOutput result = predictor.Predict(instances[0]);
TOutput loadedResult = loadedPredictor.Predict(instances[0]);
checker(result, loadedResult);
}
public void T4C_Preparation_Add_Changes_To_B()
{
_cloneB.CreateFile("First.B", "First file on clone B");
_cloneB.Stage("First.B");
_cloneB.Commit("Commit #1 on B");
}