public override int Run(string[] remainingArguments)
{
this.CheckRequiredArguments();
if (remainingArguments.Length < 1)
{
throw new ArgumentNullException("dataset");
}
string datasetName = remainingArguments[0];
string checkpoint = Gpt2Checkpoints.ProcessCheckpointConfig(
gpt2Root: Environment.CurrentDirectory,
checkpoint: this.Checkpoint,
modelName: this.ModelName,
runName: this.RunName);
var encoder = Gpt2Encoder.LoadEncoder(this.ModelName);
string searchPattern = this.Include ?? "*";
var dataset = searchPattern.EndsWith("*.csv")
? LoadCsv(encoder, root: datasetName, field: this.ColumnName)
: Gpt2Dataset.LoadDataset(encoder, path: datasetName, pattern: searchPattern);
if (dataset.Count == 0)
{
Console.Error.WriteLine("The dataset is empty!");
return(-1);
}
var hParams = Gpt2Model.LoadHParams(this.ModelName);
var random = this.Seed == null ? new Random() : new Random(this.Seed.Value);
var stop = new CancellationTokenSource();
Console.CancelKeyPress += delegate { stop.Cancel(); };
dynamic config = config_pb2.ConfigProto();
config.gpu_options.allow_growth = true;
new Gpt2Trainer(dataset, encoder, hParams, this.BatchSize, this.SampleLength, random)
{
SaveEvery = this.SaveEvery,
SampleNum = this.SampleNum,
SampleEvery = this.SampleEvery,
}
.Train(checkpoint, this.RunName,
sessionConfig: config,
counter: checkpoint == "fresh" ? 1 : (int?)null,
cancellation: stop.Token);
return(0);
}
public override int Run(string[] remainingArguments)
{
string checkpoint = Gpt2Checkpoints.ProcessCheckpointConfig(
gpt2Root: Environment.CurrentDirectory,
checkpoint: this.Checkpoint,
modelName: this.ModelName,
runName: this.RunName);
Run(modelName: this.ModelName,
checkpoint: checkpoint,
seed: this.Seed,
sampleCount: this.SampleCount,
batchSize: this.BatchSize,
length: this.Length,
temperature: this.Temperature,
topK: this.TopK);
return(0);
}
