public DbToolSyntaxParser(ISyntaxProvider syntaxProvider) { _tags = new List<Tag>(); _suggestions = new List<Suggestion>(); _syntaxProvider = syntaxProvider; _logger = DebugLogger.Instance; }
internal static BinaryClassificationResult AutoFit(this BinaryClassificationContext context, IDataView trainData, string label, IDataView validationData = null, InferredColumn[] inferredColumns = null, AutoFitSettings settings = null, CancellationToken cancellationToken = default, IProgress <BinaryClassificationItertionResult> iterationCallback = null, IDebugLogger debugLogger = null) { // run autofit & get all pipelines run in that process var(allPipelines, bestPipeline) = AutoFitApi.Fit(trainData, validationData, label, inferredColumns, settings, TaskKind.BinaryClassification, OptimizingMetric.Accuracy, debugLogger); var results = new BinaryClassificationItertionResult[allPipelines.Length]; for (var i = 0; i < results.Length; i++) { var iterationResult = allPipelines[i]; var result = new BinaryClassificationItertionResult(iterationResult.Model, (BinaryClassificationMetrics)iterationResult.EvaluatedMetrics, iterationResult.ScoredValidationData); results[i] = result; } var bestResult = new BinaryClassificationItertionResult(bestPipeline.Model, (BinaryClassificationMetrics)bestPipeline.EvaluatedMetrics, bestPipeline.ScoredValidationData); return(new BinaryClassificationResult(bestResult, results)); }
public static void LogErrorFormat(this IDebugLogger self, string format, params object[] args) { if (!self.IsEnable) { return; } self._LogErrorImpl(string.Format(format, args), null); }
public static void LogFormat(this IDebugLogger self, Object context, string format, params object[] args) { if (!self.IsEnable) { return; } self._LogImpl(string.Format(format, args), context); }
public static void LogWarning(this IDebugLogger self, object message) { if (!self.IsEnable) { return; } self._LogWarningImpl(message, null); }
public static void LogIf(this IDebugLogger self, bool condition, object message) { if (!condition) { return; } self.Log(message); }
public static void LogWarningIf(this IDebugLogger self, bool condition, object message, Object context) { if (!condition) { return; } self.LogWarning(message, context); }
public static void LogFormatIf(this IDebugLogger self, bool condition, Object context, string format, params object[] args) { if (!condition) { return; } self.LogFormat(context, format, args); }
public static void Log(this IDebugLogger self, object message, Object context) { if (!self.IsEnable) { return; } self._LogImpl(message, context); }
public DebugTimer(string name, IDebugLogger log) { #if TIMER _name = name; _log = log; _sw = new Stopwatch(); _sw.Start(); #endif }
public AppHttpClient(HttpClientHandler handler, IAppCenterLogger appCenterLogger, IDebugLogger debugLogger) { _httpClient = new HttpClient(handler) { Timeout = TimeSpan.FromSeconds(30) }; _appCenterLogger = appCenterLogger; _debugLogger = debugLogger; }
static void Main(string[] args) { // Create a debug logger logger = new FileLogger(); // Create vending machine and turn it on, showing the menu // Also inject logger to the machine Machine vMachine = new Machine("Vending Extravaganza", logger); vMachine.TurnMachineOn(); }
public Catalogue(IDebugLogger logger) { debugLogger = logger; cataloguePath = Directory.GetCurrentDirectory() + @"\catalogues\"; catalogueChoices = Directory.GetFiles(cataloguePath); debugLogger.LogMessage("Found " + catalogueChoices.Length + " catalogue choices."); foreach (string s in catalogueChoices) { debugLogger.LogMessage("Catalogue name " + s); } GetNewCatalogue(catalogueChoices[0]); }
public AutoFitter(MLContext mlContext, OptimizingMetricInfo metricInfo, AutoFitSettings settings, TaskKind task, string label, PurposeInference.Column[] puproseOverrides, IDataView trainData, IDataView validationData, IDebugLogger debugLogger) { _debugLogger = debugLogger; _history = new List <PipelineRunResult>(); _label = label; _mlContext = mlContext; _optimizingMetricInfo = metricInfo; _settings = settings ?? new AutoFitSettings(); _puproseOverrides = puproseOverrides; _trainData = trainData; _task = task; _validationData = validationData; }
public HttpService(IAppCenterLogger appCenterLogger, IDebugLogger debugLogger) { if (Cookie == null) { Cookie = new CookieContainer(); } if (HttpClientHandler == null) { HttpClientHandler = new HttpClientHandler { CookieContainer = Cookie, UseCookies = true } } ; _appCenterLogger = appCenterLogger; _debugLogger = debugLogger; AppHttpClient = new AppHttpClient(HttpClientHandler, _appCenterLogger, _debugLogger) { BaseAddress = new Uri(Server.ApiBaseAddress) }; }
public OtsuBinarizationFilter(IDebugLogger debugLogger) { _debugLogger = debugLogger; }
public DetectAndCropPlateNumberFilter(IDebugLogger debugLogger) { _debugLogger = debugLogger; }
public TeseractOcrFilter(IDebugLogger debugLogger) { _debugLogger = debugLogger; }
public void Setup() { // Setup machine with a dummy logger for each test fl = new FakeLogger(); m = new Machine("TestMachine", fl); }
public ExactlyOnceProcessor(ISideEffectsHandler[] sideEffectsHandlers, IDebugLogger log) { this.sideEffectsHandlers = sideEffectsHandlers; this.log = log; }
public static (PipelineRunResult[] allPipelines, PipelineRunResult bestPipeline) Fit(IDataView trainData, IDataView validationData, string label, InferredColumn[] inferredColumns, AutoFitSettings settings, TaskKind task, OptimizingMetric metric, IDebugLogger debugLogger) { // hack: init new MLContext var mlContext = new MLContext(); // infer pipelines var optimizingMetricfInfo = new OptimizingMetricInfo(metric); var autoFitter = new AutoFitter(mlContext, optimizingMetricfInfo, settings, task, label, ToInternalColumnPurposes(inferredColumns), trainData, validationData, debugLogger); var allPipelines = autoFitter.Fit(1); var bestScore = allPipelines.Max(p => p.Score); var bestPipeline = allPipelines.First(p => p.Score == bestScore); return(allPipelines, bestPipeline); }
public Logger(IAppCenterLogger appCenterLogger, IDebugLogger debugLogger) { _appCenterLogger = appCenterLogger; _debugLogger = debugLogger; }
public ReadImageFromBytesFilter(IDebugLogger debugLogger) { _debugLogger = debugLogger; }
public VendingMenu(Machine machineMenuIsRunningOn, IDebugLogger debugLogger) { this.machine = machineMenuIsRunningOn; this.logger = debugLogger; }
public StringAgregateFilter(IDebugLogger debugLogger) { _debugLogger = debugLogger; }
public FindContoursFilter(IDebugLogger debugLogger) { _debugLogger = debugLogger; }
public SalesforceDebugLogger( IDebugLogger debugLogger) { DebugLogger = debugLogger; }
public static void Add(IDebugLogger logger) { loggers.Add(logger); }
public HSTraceListener(IDebugLogger logger) { loggerWeakReference = new WeakReference(logger); }
public CropLettersFilter(IDebugLogger debugLogger) { _debugLogger = debugLogger; }
public Machine(string name, IDebugLogger debugLogger) { MachineName = name; logger = debugLogger; }