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")))); }