dotnet / dotnet/machinelearning-modelbuilder
Bug in ML Model Builder 16.17.0.2332602 Data From csv file Text Classified scenario
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Descripción
**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)
Guía de contribución
No hay ninguna guía de contribución indexada para este repositorio
Línea de trabajo
Comienza en src/Microsoft.ML.ModelBuilder.AutoMLService/ServiceFactory/CodeGeneratorService.cs, especialmente en las líneas 139 y 155, y reproduce el escenario Text Classified usando datos de un archivo CSV. Compara el stack trace del logfile con los pasos de carga del modelo y generación de código; se considera terminado cuando el entrenamiento finaliza sin el error indicado y el código de consumo se genera correctamente.
Escrito por el modelo de indexación a partir del texto del issue.
Evaluación
- Stack tecnológico
- csharp, machine-learning
- Área
- machine-learning, tooling
- Tipo de issue
- Error
- Dificultad
- 4/5
- Tiempo estimado
- 3-5 días
- Estado de actividad
- Estancado
- Claridad
- Necesita aclaración
- Aptitud para principiantes
- 32/100