public void TestSeq2SeqTraining()
{
// Build configs for training
Seq2SeqOptions opts = CreateOptions(trainFolderPath, validFolderPath);
DecodingOptions decodingOptions = opts.CreateDecodingOptions();
// Load training corpus
var trainCorpus = new Seq2SeqCorpus(corpusFilePath: opts.TrainCorpusPath, srcLangName: opts.SrcLang, tgtLangName: opts.TgtLang, batchSize: opts.BatchSize, shuffleBlockSize: opts.ShuffleBlockSize, maxSrcSentLength: opts.MaxTrainSrcSentLength, maxTgtSentLength: opts.MaxTrainTgtSentLength, shuffleEnums: opts.ShuffleType, tooLongSequence: opts.TooLongSequence);
// Load valid corpus
var validCorpusList = new List <Seq2SeqCorpus>();
if (!opts.ValidCorpusPaths.IsNullOrEmpty())
{
string[] validCorpusPathList = opts.ValidCorpusPaths.Split(';');
foreach (var validCorpusPath in validCorpusPathList)
{
validCorpusList.Add(new Seq2SeqCorpus(validCorpusPath, opts.SrcLang, opts.TgtLang, opts.ValBatchSize, opts.ShuffleBlockSize, opts.MaxTestSrcSentLength, opts.MaxTestTgtSentLength, shuffleEnums: opts.ShuffleType, tooLongSequence: opts.TooLongSequence));
}
}
// Create learning rate
ILearningRate learningRate = new DecayLearningRate(opts.StartLearningRate, opts.WarmUpSteps, opts.WeightsUpdateCount);
// Create optimizer
IOptimizer optimizer = Misc.CreateOptimizer(opts);
// Build vocabularies for training
(var srcVocab, var tgtVocab) = trainCorpus.BuildVocabs(opts.SrcVocabSize, opts.TgtVocabSize, opts.SharedEmbeddings);
// Create metrics
List <IMetric> metrics = new List <IMetric> {
new BleuMetric()
};
//New training
var ss = new Seq2Seq(opts, srcVocab, tgtVocab);
// Add event handler for monitoring
ss.StatusUpdateWatcher += Ss_StatusUpdateWatcher;
ss.EpochEndWatcher += Ss_EpochEndWatcher;
// Kick off training
ss.Train(maxTrainingEpoch: opts.MaxEpochNum, trainCorpus: trainCorpus, validCorpusList: validCorpusList.ToArray(), learningRate: learningRate, optimizer: optimizer, metrics: metrics, decodingOptions: decodingOptions);
ss.SaveModel(suffix: ".test");
// Check if model file exists
Assert.IsTrue(File.Exists(opts.ModelFilePath + ".test"));
}
public void TestSeq2SeqBuildSharedVocabs()
{
// Build configs for training
Seq2SeqOptions opts = CreateOptions(trainFolderPath, validFolderPath);
// Load training corpus
var trainCorpus = new Seq2SeqCorpus(corpusFilePath: opts.TrainCorpusPath, srcLangName: opts.SrcLang, tgtLangName: opts.TgtLang, batchSize: opts.BatchSize, shuffleBlockSize: opts.ShuffleBlockSize, maxSrcSentLength: opts.MaxTrainSrcSentLength, maxTgtSentLength: opts.MaxTrainTgtSentLength, shuffleEnums: opts.ShuffleType, tooLongSequence: opts.TooLongSequence);
// Build vocabularies for training
(var srcVocab, var tgtVocab) = trainCorpus.BuildVocabs(opts.SrcVocabSize, opts.TgtVocabSize, sharedVocab: true);
Assert.IsTrue(srcVocab.Count == tgtVocab.Count);
var srcTokens = srcVocab.GetAllTokens();
var tgtTokens = tgtVocab.GetAllTokens();
for (int i = 0; i < srcTokens.Count; i++)
{
Assert.IsTrue(srcTokens[i] == tgtTokens[i]);
}
}
private static void Main(string[] args)
{
try
{
//Parse command line
ArgParser argParser = new ArgParser(args, opts);
if (!opts.ConfigFilePath.IsNullOrEmpty())
{
Console.WriteLine($"Loading config file from '{opts.ConfigFilePath}'");
opts = JsonConvert.DeserializeObject <Seq2SeqOptions>(File.ReadAllText(opts.ConfigFilePath));
}
Logger.LogFile = $"{nameof(Seq2SeqConsole)}_{opts.Task}_{Utils.GetTimeStamp(DateTime.Now)}.log";
ShowOptions(args, opts);
DecodingOptions decodingOptions = opts.CreateDecodingOptions();
Seq2Seq ss = null;
if (opts.Task == ModeEnums.Train)
{
// Load train corpus
var trainCorpus = new Seq2SeqCorpus(corpusFilePath: opts.TrainCorpusPath, srcLangName: opts.SrcLang, tgtLangName: opts.TgtLang, batchSize: opts.BatchSize, shuffleBlockSize: opts.ShuffleBlockSize,
maxSrcSentLength: opts.MaxTrainSrcSentLength, maxTgtSentLength: opts.MaxTrainTgtSentLength, shuffleEnums: opts.ShuffleType, tooLongSequence: opts.TooLongSequence);
// Load valid corpus
var validCorpusList = new List <Seq2SeqCorpus>();
if (!opts.ValidCorpusPaths.IsNullOrEmpty())
{
string[] validCorpusPathList = opts.ValidCorpusPaths.Split(';');
foreach (var validCorpusPath in validCorpusPathList)
{
validCorpusList.Add(new Seq2SeqCorpus(validCorpusPath, opts.SrcLang, opts.TgtLang, opts.ValBatchSize, opts.ShuffleBlockSize, opts.MaxTestSrcSentLength, opts.MaxTestTgtSentLength, shuffleEnums: opts.ShuffleType, tooLongSequence: opts.TooLongSequence));
}
}
// Create learning rate
ILearningRate learningRate = new DecayLearningRate(opts.StartLearningRate, opts.WarmUpSteps, opts.WeightsUpdateCount);
// Create optimizer
IOptimizer optimizer = Misc.CreateOptimizer(opts);
// Create metrics
List <IMetric> metrics = CreateMetrics();
if (!opts.ModelFilePath.IsNullOrEmpty() && File.Exists(opts.ModelFilePath))
{
//Incremental training
Logger.WriteLine($"Loading model from '{opts.ModelFilePath}'...");
ss = new Seq2Seq(opts);
}
else
{
// Load or build vocabulary
Vocab srcVocab = null;
Vocab tgtVocab = null;
if (!opts.SrcVocab.IsNullOrEmpty() && !opts.TgtVocab.IsNullOrEmpty())
{
Logger.WriteLine($"Loading source vocabulary from '{opts.SrcVocab}' and target vocabulary from '{opts.TgtVocab}'. Shared vocabulary is '{opts.SharedEmbeddings}'");
if (opts.SharedEmbeddings == true && (opts.SrcVocab != opts.TgtVocab))
{
throw new ArgumentException("The source and target vocabularies must be identical if their embeddings are shared.");
}
// Vocabulary files are specified, so we load them
srcVocab = new Vocab(opts.SrcVocab);
tgtVocab = new Vocab(opts.TgtVocab);
}
else
{
Logger.WriteLine($"Building vocabulary from training corpus. Shared vocabulary is '{opts.SharedEmbeddings}'");
// We don't specify vocabulary, so we build it from train corpus
(srcVocab, tgtVocab) = trainCorpus.BuildVocabs(opts.SrcVocabSize, opts.TgtVocabSize, opts.SharedEmbeddings);
}
//New training
ss = new Seq2Seq(opts, srcVocab, tgtVocab);
}
// Add event handler for monitoring
ss.StatusUpdateWatcher += Misc.Ss_StatusUpdateWatcher;
ss.EvaluationWatcher += Ss_EvaluationWatcher;
// Kick off training
ss.Train(maxTrainingEpoch: opts.MaxEpochNum, trainCorpus: trainCorpus, validCorpusList: validCorpusList.ToArray(), learningRate: learningRate, optimizer: optimizer, metrics: metrics, decodingOptions: decodingOptions);
}
else if (opts.Task == ModeEnums.Valid)
{
Logger.WriteLine($"Evaluate model '{opts.ModelFilePath}' by valid corpus '{opts.ValidCorpusPaths}'");
// Create metrics
List <IMetric> metrics = CreateMetrics();
// Load valid corpus
Seq2SeqCorpus validCorpus = new Seq2SeqCorpus(opts.ValidCorpusPaths, opts.SrcLang, opts.TgtLang, opts.ValBatchSize, opts.ShuffleBlockSize, opts.MaxTestSrcSentLength, opts.MaxTestTgtSentLength, shuffleEnums: opts.ShuffleType, tooLongSequence: opts.TooLongSequence);
ss = new Seq2Seq(opts);
ss.EvaluationWatcher += Ss_EvaluationWatcher;
ss.Valid(validCorpus: validCorpus, metrics: metrics, decodingOptions: decodingOptions);
}
else if (opts.Task == ModeEnums.Test)
{
if (File.Exists(opts.OutputFile))
{
Logger.WriteLine(Logger.Level.err, ConsoleColor.Yellow, $"Output file '{opts.OutputFile}' exist. Delete it.");
File.Delete(opts.OutputFile);
}
//Test trained model
ss = new Seq2Seq(opts);
Stopwatch stopwatch = Stopwatch.StartNew();
if (String.IsNullOrEmpty(opts.OutputPromptFile))
{
ss.Test <Seq2SeqCorpusBatch>(opts.InputTestFile, opts.OutputFile, opts.BatchSize, decodingOptions, opts.SrcSentencePieceModelPath, opts.TgtSentencePieceModelPath);
}
else
{
Logger.WriteLine($"Test with prompt file '{opts.OutputPromptFile}'");
ss.Test <Seq2SeqCorpusBatch>(opts.InputTestFile, opts.OutputPromptFile, opts.OutputFile, opts.BatchSize, decodingOptions, opts.SrcSentencePieceModelPath, opts.TgtSentencePieceModelPath);
}
stopwatch.Stop();
Logger.WriteLine($"Test mode execution time elapsed: '{stopwatch.Elapsed}'");
}
else if (opts.Task == ModeEnums.DumpVocab)
{
ss = new Seq2Seq(opts);
ss.DumpVocabToFiles(opts.SrcVocab, opts.TgtVocab);
}
else
{
Logger.WriteLine(Logger.Level.err, ConsoleColor.Red, $"Task '{opts.Task}' is not supported.");
argParser.Usage();
}
}
catch (Exception err)
{
Logger.WriteLine($"Exception: '{err.Message}'");
Logger.WriteLine($"Call stack: '{err.StackTrace}'");
}
}