private static void ComputeMetrics(string configFileForTest, ModelMetricTypes metricsType)
{
// Compute metrics.
bool needComputePerplexity = (metricsType == ModelMetricTypes.Intr ||
metricsType == ModelMetricTypes.Both);
var tuner = new LDAParameterTuner("getmetrics", TestSampleName, configFileForTest, "", needComputePerplexity);
tuner.Run();
ConsoleColor color;
FileManager.DeleteFile(Path.Combine(Path.GetDirectoryName(configFileForTest), @"build\DocumentTopicAllocations.txt"), out color);
}
/// <summary>
/// Compute corpus vocabulary, document vocabularies, and featurized documents
/// for each combination of min/max(relative) word document frequency.
/// </summary>
/// <param name="listOfLDAConfigFilesForFeaturization">a list of LDAConfig files for featurization.</param>
/// <param name="sampleName">the name of the sample to be featurized</param>
private static void FeaturizeSample(List <string> listOfLDAConfigFilesForFeaturization, string sampleName, int numOfThreads)
{
var tuner = new LDAParameterTuner("featurizedocs", sampleName, listOfLDAConfigFilesForFeaturization.First());
tuner.Run();
Parallel.ForEach(listOfLDAConfigFilesForFeaturization.Skip(1), new ParallelOptions {
MaxDegreeOfParallelism = numOfThreads * 2 / 3
}, config =>
{
tuner = new LDAParameterTuner("featurizedocs", sampleName, config);
tuner.Run();
});
}
/// <summary>
/// Generate doc vector given a LDA config file.
/// </summary>
/// <param name="configFileForTest"></param>
private static void GenerateDV(string configFileForTest)
{
// Run DvGen for training corpus.
LDAConfig ldaConfig;
try
{
ldaConfig = JsonConvert.DeserializeObject <LDAConfig>(File.ReadAllText(configFileForTest));
}
catch (Exception)
{
throw;
}
string corpusPrefix = Path.Combine(ModelRepositoryPath, string.Format(@"Corpora\{0}\{1}", ldaConfig.Locale, ldaConfig.Corpus));
string sampleFileFullPath = Path.Combine(corpusPrefix, TrainingSampleName);
var tuner = new LDAParameterTuner("generatedocvectors", sampleFileFullPath, configFileForTest);
tuner.Run();
// Copy dv to model directory.
string src = Path.Combine(corpusPrefix,
string.Format("{0}.dv", TrainingSampleName),
TrainingSampleName + "." + ldaConfig.modelName,
"DocumentVectors.L1.dv");
string dest = ldaConfig.DocumentTopicAllocations;
StatusMessage.Write(string.Format("Waiting DV file ready: {0}", src));
do
{
Thread.Sleep(5);
} while (!File.Exists(src) || FileManager.IsFileLocked(src));
StatusMessage.Write(string.Format("DV file ready. Copying from {0} to {1}", src, dest));
try
{
File.Copy(src, dest, true);
}
catch (Exception)
{
throw;
}
StatusMessage.Write(string.Format("Successfully copied file\r\n<---{0}\r\n--->{1}", src, dest));
}
private static void TrainLDAModels(List <string> listOfLDAConfigFilesForTrain, List <string> listOfLDAConfigFilesForTest, int numOfThreads)
{
// Generate a list of indexes
// for accessing each element of listOfLDAConfigFilesForTraining and listOfLDAConfigFilesForTest
List <int> indexes = Enumerable.Range(0, listOfLDAConfigFilesForTrain.Count).ToList();
long totalNumber = listOfLDAConfigFilesForTrain.Count;
long numOfModelsTrained = 0;
// Spawn multiple threads for training
Parallel.ForEach(indexes, new ParallelOptions {
MaxDegreeOfParallelism = numOfThreads
}, index =>
{
string configFileForTrain = listOfLDAConfigFilesForTrain[index];
string configFileForTest = listOfLDAConfigFilesForTest[index];
var tuner = new LDAParameterTuner("learnlda", TrainingSampleName, configFileForTrain, configFileForTest);
int retVal = tuner.Run();
if (retVal == 0)
{
// Push the configFileForTest into queue once the model training is done.
configFileQueue.Enqueue(configFileForTest);
Interlocked.Increment(ref numOfModelsTrained);
StatusMessage.Write(string.Format("Model #{0} out of {1} has been trained.", Interlocked.Read(ref numOfModelsTrained), totalNumber), ConsoleColor.Green);
if (NeedDeleteConfig)
{
ConsoleColor color;
var message = FileManager.DeleteFile(configFileForTrain, out color);
StatusMessage.Write(message);
}
}
else
{
StatusMessage.Write("Learn LDA failed! config = " + configFileForTrain, ConsoleColor.Red);
}
});
// Tell the copy thread that no more models to be generated.
Interlocked.Decrement(ref flag);
}