public virtual async Task <TrainingOperation> StartTrainingAsync(Uri trainingFilesUri, bool useTrainingLabels, TrainingFileFilter trainingFileFilter = default, CancellationToken cancellationToken = default)
{
Argument.AssertNotNull(trainingFilesUri, nameof(trainingFilesUri));
var trainRequest = new TrainRequest_internal(trainingFilesUri.AbsoluteUri, trainingFileFilter, useTrainingLabels);
ResponseWithHeaders <ServiceTrainCustomModelAsyncHeaders> response = await ServiceClient.TrainCustomModelAsyncAsync(trainRequest).ConfigureAwait(false);
return(new TrainingOperation(response.Headers.Location, ServiceClient, Diagnostics));
}
public virtual TrainingOperation StartTraining(Uri trainingFilesUri, bool useTrainingLabels = false, TrainingFileFilter filter = default, CancellationToken cancellationToken = default)
{
Argument.AssertNotNull(trainingFilesUri, nameof(trainingFilesUri));
var trainRequest = new TrainRequest_internal(trainingFilesUri.AbsoluteUri, filter, useTrainingLabels);
ResponseWithHeaders <ServiceTrainCustomModelAsyncHeaders> response = ServiceClient.TrainCustomModelAsync(trainRequest);
return(new TrainingOperation(response.Headers.Location, ServiceClient));
}
/// <summary>
/// Trains a model from a collection of custom forms in a blob storage container.
/// </summary>
/// <param name="trainingFilesUri">An externally accessible Azure storage blob container Uri.
/// For more information see <a href="https://docs.microsoft.com/azure/cognitive-services/form-recognizer/build-training-data-set#upload-your-training-data"/>.</param>
/// <param name="useTrainingLabels">If <c>true</c>, use a label file created in the <link-to-label-tool-doc> to provide training-time labels for training a model. If <c>false</c>, the model will be trained from forms only.</param>
/// <param name="trainingFileFilter">Filter to apply to the documents in the source path for training.</param>
/// <param name="cancellationToken">A <see cref="CancellationToken"/> controlling the request lifetime.</param>
/// <returns>
/// <para>A <see cref="TrainingOperation"/> to wait on this long-running operation. Its <see cref="TrainingOperation.Value"/> upon successful
/// completion will contain meta-data about the trained model.</para>
/// <para>Even if training fails, a model is created in the Form Recognizer account with an "invalid" status.
/// A <see cref="RequestFailedException"/> will be raised containing the modelId to access this invalid model.</para>
/// </returns>
public virtual async Task <TrainingOperation> StartTrainingAsync(Uri trainingFilesUri, bool useTrainingLabels, TrainingFileFilter trainingFileFilter = default, CancellationToken cancellationToken = default)
{
Argument.AssertNotNull(trainingFilesUri, nameof(trainingFilesUri));
using DiagnosticScope scope = Diagnostics.CreateScope($"{nameof(FormTrainingClient)}.{nameof(StartTraining)}");
scope.Start();
try
{
var trainRequest = new TrainRequest(trainingFilesUri.AbsoluteUri)
{
SourceFilter = trainingFileFilter, UseLabelFile = useTrainingLabels
};
ResponseWithHeaders <ServiceTrainCustomModelAsyncHeaders> response = await ServiceClient.TrainCustomModelAsyncAsync(trainRequest).ConfigureAwait(false);
return(new TrainingOperation(response.Headers.Location, ServiceClient, Diagnostics));
}
catch (Exception e)
{
scope.Failed(e);
throw;
}
}
public virtual async Task <TrainingOperation> StartTrainingAsync(Uri trainingFiles, bool useLabels = false, TrainingFileFilter filter = default, CancellationToken cancellationToken = default)
{
var trainRequest = new TrainRequest_internal(trainingFiles.AbsoluteUri, filter, useLabels);
ResponseWithHeaders <ServiceTrainCustomModelAsyncHeaders> response = await ServiceClient.RestClient.TrainCustomModelAsyncAsync(trainRequest).ConfigureAwait(false);
return(new TrainingOperation(response.Headers.Location, ServiceClient));
}
public virtual async Task <TrainingOperation> StartTrainingAsync(Uri trainingFiles, bool useLabels = false, TrainingFileFilter filter = default, CancellationToken cancellationToken = default)
{
await Task.Run(() => { }).ConfigureAwait(false);
throw new NotImplementedException();
//TrainRequest_internal trainRequest = new TrainRequest_internal() { Source = trainingFiles.AbsoluteUri };
//// TODO: Q1 - if there's a way to default a property value, set filter.Path ="" and set it here in a nicer way.
//// https://github.com/Azure/azure-sdk-for-net/issues/10359
//if (filter != default)
//{
// trainRequest.SourceFilter = filter;
//}
//ResponseWithHeaders<TrainCustomModelAsyncHeaders> response = await ServiceClient.RestClient.TrainCustomModelAsyncAsync(trainRequest).ConfigureAwait(false);
//return new TrainingOperation(ServiceClient, response.Headers.Location);
}
public virtual TrainingOperation StartTraining(Uri trainingFiles, bool useLabels = false, TrainingFileFilter filter = default, CancellationToken cancellationToken = default)
{
throw new NotImplementedException();
//TrainRequest_internal trainRequest = new TrainRequest_internal() { Source = trainingFiles.AbsoluteUri };
//// TODO: Q1 - if there's a way to default a property value, set filter.Path ="" and set it here in a nicer way.
//// https://github.com/Azure/autorest.csharp/issues/467
//// When this is complete, we will be able to default filter.Path to "".
//// Decision to make, do we always send filter, or only if needed?
//// Tracking with https://github.com/Azure/azure-sdk-for-net/issues/10359
//if (filter != default)
//{
// trainRequest.SourceFilter = filter;
//}
//ResponseWithHeaders<TrainCustomModelAsyncHeaders> response = ServiceClient.RestClient.TrainCustomModelAsync(trainRequest);
//return new TrainingOperation(ServiceClient, response.Headers.Location);
}
