public void Setup(bool debug)
{
var readModel = new ReadModel(InputModelFile);
var temp = new ReadModel(string.Concat(InputModelFile, ".featuresToK"));
_weightVector = new WeightVector(temp.GetFeatureToKdDictionary());
foreach (var pair in readModel.ModelIterator())
{
_weightVector.Add(pair);
}
_tags = new Tags(_tagList);
_viterbiForGlobalLinearModel = new ViterbiForGlobalLinearModel(_weightVector, _tags);
// read input file in a class and per line iterator.
var inputData = new ReadInputData(InputTestFile);
var writeModel = new WriteModel(_outputTestFile);
foreach (var line in inputData.GetSentence())
{
List<string> debugList;
var outputTags = _viterbiForGlobalLinearModel.Decode(line, debug, out debugList);
if (debug)
{
writeModel.WriteDataWithTagDebug(line, outputTags, debugList);
}
else
{
writeModel.WriteDataWithTag(line, outputTags);
}
}
writeModel.Flush();
}
public void Init()
{
var readModel = new ReadModel(InputModelFile + ".preceptron");
var temp = new ReadModel(string.Concat(InputModelFile, ".featuresToK"));
var dict = temp.GetFeatureToKdDictionary();
_weightVector = new WeightVector(dict, dict.Count);
foreach (var pair in readModel.ModelIterator())
{
_weightVector.Add(pair);
}
_tags = new Tags(_tagList);
ViterbiForGLM = new ViterbiForGlobalLinearModel(_weightVector, _tags);
}