/// <summary>
/// Creates a new event array based on the outcomes predicted by the specified parameters for the specified sequence.
/// </summary>
/// <param name="sequence">The sequence to be evaluated.</param>
/// <param name="model">The model.</param>
/// <returns>The event array.</returns>
public Event[] UpdateContext(Sequence sequence, AbstractModel model)
{
var tagger = new POSTaggerME(new POSModel("x-unspecified", model, null, new POSTaggerFactory()));
var sample = sequence.GetSource <POSSample>();
var tags = tagger.Tag(sample.Sentence);
return(POSSampleEventStream.GenerateEvents(
sample.Sentence,
tags,
Array.ConvertAll(sample.AdditionalContext, input => (object)input),
contextGenerator).ToArray());
}
/// <summary>
/// Trains a Part of Speech model with the given parameters.
/// </summary>
/// <param name="languageCode">The language code.</param>
/// <param name="samples">The data samples.</param>
/// <param name="parameters">The machine learnable parameters.</param>
/// <param name="factory">The sentence detector factory.</param>
/// <param name="monitor">
/// A evaluation monitor that can be used to listen the messages during the training or it can cancel the training operation.
/// This argument can be a <c>null</c> value.
/// </param>
/// <returns>The trained <see cref="POSModel"/> object.</returns>
/// <exception cref="System.NotSupportedException">Trainer type is not supported.</exception>
public static POSModel Train(string languageCode, IObjectStream <POSSample> samples, TrainingParameters parameters, POSTaggerFactory factory, Monitor monitor)
{
//int beamSize = trainParams.Get(Parameters.BeamSize, NameFinderME.DefaultBeamSize);
var contextGenerator = factory.GetPOSContextGenerator();
var manifestInfoEntries = new Dictionary <string, string>();
var trainerType = TrainerFactory.GetTrainerType(parameters);
IMaxentModel posModel = null;
ML.Model.ISequenceClassificationModel <string> seqPosModel = null;
switch (trainerType)
{
case TrainerType.EventModelTrainer:
var es = new POSSampleEventStream(samples, contextGenerator);
var trainer = TrainerFactory.GetEventTrainer(parameters, manifestInfoEntries, monitor);
posModel = trainer.Train(es);
break;
case TrainerType.EventModelSequenceTrainer:
var ss = new POSSampleSequenceStream(samples, contextGenerator);
var trainer2 = TrainerFactory.GetEventModelSequenceTrainer(parameters, manifestInfoEntries, monitor);
posModel = trainer2.Train(ss);
break;
case TrainerType.SequenceTrainer:
var trainer3 = TrainerFactory.GetSequenceModelTrainer(parameters, manifestInfoEntries, monitor);
// TODO: This will probably cause issue, since the feature generator uses the outcomes array
var ss2 = new POSSampleSequenceStream(samples, contextGenerator);
seqPosModel = trainer3.Train(ss2);
break;
default:
throw new NotSupportedException("Trainer type is not supported.");
}
if (posModel != null)
{
return(new POSModel(languageCode, posModel, manifestInfoEntries, factory));
}
return(new POSModel(languageCode, seqPosModel, manifestInfoEntries, factory));
}
