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;
}
