public void SetUp()
{
GlobalSettings.Random = new Random(48);
vectorSource = new EmbeddingVectorSource(WordModel.Load(Path.Combine(TestContext.CurrentContext.TestDirectory, @"Data\model.bin")));
pageDetector = new SvmAnomalyDetector(vectorSource, new NullLoggerFactory(), null);
document = new DocumentBlock(JsonConvert.DeserializeObject <Document[]>(File.ReadAllText(Path.Combine(TestContext.CurrentContext.TestDirectory, "Data", "docs.json"))));
}
public void TestLoadingTextInAnotherCulture()
{
CultureInfo.DefaultThreadCurrentCulture = CultureInfo.CreateSpecificCulture("fr-FR");
var model = WordModel.Load(GetPath("model.txt"));
TestLoadedModel(model);
}
private void SetupAnomaly(ContainerBuilder builder)
{
logger.LogInformation("Setting up lexicon libraries");
var tagger = new NaivePOSTagger(new BNCList(), WordTypeResolver.Instance);
builder.RegisterInstance(tagger).As <IPOSTagger>();
var dictionary = new NRCDictionary();
dictionary.Load();
builder.RegisterInstance(dictionary).As <INRCDictionary>();
var inquirer = new InquirerManager();
inquirer.Load();
builder.RegisterInstance(inquirer).As <IInquirerManager>();
builder.RegisterType <FrequencyListManager>().As <IFrequencyListManager>().SingleInstance();
builder.RegisterType <StyleFactory>().As <IStyleFactory>();
builder.RegisterType <AnomalyFactory>().As <IAnomalyFactory>();
builder.RegisterType <SupervisedAnomaly>().As <ISupervisedAnomaly>();
builder.RegisterType <DocumentReconstructor>().As <IDocumentReconstructor>();
builder.RegisterType <DocumentExtractor>().As <IDocumentExtractor>();
builder.RegisterType <EmbeddingVectorSource>().As <IDocumentVectorSource>();
builder.RegisterType <SvmModelStorageFactory>().As <IModelStorageFactory>();
logger.LogInformation("Downloading model...");
var model = new Uri(Configuration["Anomaly:model"]);
new DataDownloader(loggerFactory).DownloadFile(model, "resources").Wait();
builder.Register(context => WordModel.Load("resources/model.bin")).SingleInstance();
}
public void SetUp()
{
loggerFactory = new NullLoggerFactory();
vectorSource = new EmbeddingVectorSource(WordModel.Load(Path.Combine(TestContext.CurrentContext.TestDirectory, @"Data\model.bin")));
documentReconstructor = new DocumentReconstructor();
documents = JsonConvert.DeserializeObject <Document[]>(File.ReadAllText(Path.Combine(TestContext.CurrentContext.TestDirectory, "Data", "docs.json")));
instance = CreateModelStorage();
}
public void TestUnknown()
{
var model = WordModel.Load(GetPath(@"model.bin"));
var sentences = new[] { new SentenceItem(), new SentenceItem() };
sentences[0].Words.Add(new WordEx("ssd"));
sentences[1].Words.Add(new WordEx("gfgf"));
var paragraph = model.GetParagraphVector(sentences);
var paragraph2 = model.GetParagraphVector(sentences.Take(1).ToArray());
Assert.AreEqual(paragraph2, paragraph);
}
public void TestReLoadingBinary()
{
var model = WordModel.Load(GetPath("model.txt"));
WordModel m2;
using (var s = new MemoryStream())
{
using (var writer = new BinaryModelWriter(s, true))
{
writer.Write(model);
}
s.Seek(0, SeekOrigin.Begin);
var tmr = new BinaryModelReader(s);
m2 = WordModel.Load(tmr);
}
Assert.AreEqual(model.Words, m2.Words);
Assert.AreEqual(model.Size, m2.Size);
}
public void TestLoadingTextFileWithNoHeader()
{
var model = WordModel.Load(GetPath("modelWithNoHeader.txt"));
Assert.AreEqual(2, model.Words);
}
public void TestLoadingCompressedBinary()
{
var model = WordModel.Load(GetPath(@"model.bin.gz"));
TestLoadedModel(model);
}
public void TestLoadingBinary()
{
var model = WordModel.Load(GetPath(@"model.bin"));
TestLoadedModel(model);
}
public void TestLoadingCompressedText()
{
var model = WordModel.Load(GetPath("model.txt.gz"));
TestLoadedModel(model);
}
public void TestLoadingText()
{
var model = WordModel.Load(GetPath("model.txt"));
TestLoadedModel(model);
}
public void Setup()
{
document = new DocumentBlock(Global.InitDocument("cv002_17424.txt"));
instance = new AnomalyFactory(new EmbeddingVectorSource(WordModel.Load(Path.Combine(TestContext.CurrentContext.TestDirectory, @"Data\model.bin"))));
}
