dotnet / dotnet/machinelearning-modelbuilder
Bug in ML Model Builder 16.17.0.2332602 Data From csv file Text Classified scenario
- Lingua principale
- Dockerfile
- Stelle
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- Fork
- 66
- Metriche di merge delle PR
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Descrizione
**I am developing an Application using ML C# in Console Core**
- Model Builder Version 16.17.0.2332602:
- Visual Studio Version 2019
**Details & Bud Location**
- It takes a long time to do training.
- After completing the training, an error message appears.
- src/Microsoft.ML.ModelBuilder.AutoMLService/ServiceFactory/CodeGeneratorService.cs:line 139
- src/Microsoft.ML.ModelBuilder.AutoMLService/ServiceFactory/CodeGeneratorService.cs:line 155
**Error in logfile**
DEBUG Exception has been thrown by the target of an invocation.
at System.RuntimeMethodHandle.InvokeMethod(Object target, Object[] arguments, Signature sig, Boolean constructor)
at System.Reflection.RuntimeMethodInfo.UnsafeInvokeInternal(Object obj, Object[] parameters, Object[] arguments)
at System.Reflection.RuntimeMethodInfo.Invoke(Object obj, BindingFlags invokeAttr, Binder binder, Object[] parameters, CultureInfo culture)
at Microsoft.ML.Runtime.ComponentCatalog.LoadableClassInfo.CreateInstanceCore(Object[] ctorArgs)
at Microsoft.ML.Runtime.ComponentCatalog.TryCreateInstance[TRes](IHostEnvironment env, Type signatureType, TRes& result, String name, String options, Object[] extra)
at Microsoft.ML.Runtime.ComponentCatalog.TryCreateInstance[TRes,TSig](IHostEnvironment env, TRes& result, String name, String options, Object[] extra)
at Microsoft.ML.ModelLoadContext.TryLoadModelCore[TRes,TSig](IHostEnvironment env, TRes& result, Object[] extra)
at Microsoft.ML.ModelLoadContext.TryLoadModel[TRes,TSig](IHostEnvironment env, TRes& result, RepositoryReader rep, Entry ent, String dir, Object[] extra)
at Microsoft.ML.ModelLoadContext.LoadModel[TRes,TSig](IHostEnvironment env, TRes& result, RepositoryReader rep, Entry ent, String dir, Object[] extra)
at Microsoft.ML.ModelLoadContext.LoadModelOrNull[TRes,TSig](IHostEnvironment env, TRes& result, RepositoryReader rep, String dir, Object[] extra)
at Microsoft.ML.ModelLoadContext.LoadModel[TRes,TSig](IHostEnvironment env, TRes& result, RepositoryReader rep, String dir, Object[] extra)
at Microsoft.ML.ModelOperationsCatalog.Load(Stream stream, DataViewSchema& inputSchema)
at Microsoft.ML.ModelOperationsCatalog.Load(String filePath, DataViewSchema& inputSchema)
at Microsoft.ML.ModelBuilder.AutoMLService.ServiceFactory.CodeGeneratorService.SetTorchRunTimeFolderAndLoadModel(ITrainingConfiguration configuration, String modelPath, MLContext& context, ITransformer& model, DataViewSchema& inputSchema) in /_/src/Microsoft.ML.ModelBuilder.AutoMLService/ServiceFactory/CodeGeneratorService.cs:line 139
at Microsoft.ML.ModelBuilder.AutoMLService.ServiceFactory.CodeGeneratorService.GenerateConsumptionAsync(ITrainingConfiguration configuration, String trainingConfigurationFolder, String nameSpace, String className, TargetType target, String[] labels, CancellationToken ct) in /_/src/Microsoft.ML.ModelBuilder.AutoMLService/ServiceFactory/CodeGeneratorService.cs:line 155 at StreamJsonRpc.JsonRpc.d__139`1.MoveNext()
--- End of stack trace from previous location where exception was thrown ---
at System.Runtime.CompilerServices.TaskAwaiter.ThrowForNonSuccess(Task task)
at System.Runtime.CompilerServices.TaskAwaiter.HandleNonSuccessAndDebuggerNotification(Task task)
at System.Runtime.CompilerServices.TaskAwaiter`1.GetResult()
at Microsoft.ML.ModelBuilder.ViewModels.TrainViewModel.d__100.MoveNext() (Microsoft.ML.ModelBuilder.Utils.Logger.Debug)
Guida per i contributori
Nessuna guida per i contributori indicizzata per questo repository
Direzione di ricerca
Inizia da src/Microsoft.ML.ModelBuilder.AutoMLService/ServiceFactory/CodeGeneratorService.cs, in particolare dalle righe 139 e 155, e riproduci lo scenario Text Classified usando dati provenienti da un file CSV. Confronta lo stack trace del logfile con i passaggi di caricamento del modello e generazione del codice; il lavoro è completato quando l'addestramento termina senza l'errore segnalato e il codice di consumo viene generato correttamente.
Scritto dal modello di indicizzazione a partire dal testo della issue.
Valutazione
- Stack tecnologico
- csharp, machine-learning
- Ambito
- machine-learning, tooling
- Tipo di issue
- Bug
- Difficoltà
- 4/5
- Tempo stimato
- 3-5 giorni
- Stato di attività
- Ferma
- Chiarezza
- Da chiarire
- Idoneità per principianti
- 32/100