public void Train(string inputPath, string outputPath, FastTextArgs args)
{
ValidatePaths(inputPath, outputPath, args.PretrainedVectors);
var argsStruct = _mapper.Map <FastTextArgsStruct>(args);
CheckForErrors(Train(_fastText, inputPath, outputPath, argsStruct, args.LabelPrefix, args.PretrainedVectors));
_maxLabelLen = GetMaxLabelLength(_fastText);
}
/// <summary>
/// Returns the same supervised args defaults as in
/// https://github.com/olegtarasov/fastText/blob/b0a32d744f4d16d8f9834649f6f178ff79b5a4ce/src/fasttext_api.cc#L41
/// </summary>
/// <returns></returns>
public static unsafe FastTextArgs SupervisedDefaults()
{
var result = new FastTextArgs(false);
FastTextWrapper.FastTextArgsStruct *argsPtr;
GetDefaultSupervisedArgs(new IntPtr(&argsPtr));
Mapper.Map(*argsPtr, result);
DestroyArgs(new IntPtr(argsPtr));
return(result);
}
/// <summary>
/// Trains a new supervised model.
/// Use <see cref="FastTextArgs.SupervisedDefaults"/> to get reasonable default args for
/// supervised training.
/// </summary>
/// <param name="inputPath">Path to a training set.</param>
/// <param name="outputPath">Path to write the model to (excluding extension).</param>
/// <param name="args">Low-level training arguments.</param>
/// <remarks>Trained model will consist of two files: .bin (main model) and .vec (word vectors).</remarks>
public void Supervised(string inputPath, string outputPath, FastTextArgs args)
{
ValidatePaths(inputPath, outputPath, args.PretrainedVectors);
if (args.model != ModelName.Supervised)
{
_logger?.LogWarning($"{args.model} model type specified in a Supervised() call. Model type will be changed to Supervised.");
}
var argsStruct = _mapper.Map <FastTextArgsStruct>(args);
argsStruct.model = model_name.sup;
CheckForErrors(Supervised(_fastText, inputPath, outputPath, argsStruct, args.LabelPrefix, args.PretrainedVectors));
_maxLabelLen = CheckForErrors(GetMaxLabelLength(_fastText));
}
/// <summary>
/// Trains a new model using low-level FastText arguments.
/// </summary>
/// <param name="inputPath">Path to a training set.</param>
/// <param name="outputPath">Path to write the model to (excluding extension).</param>
/// <param name="args">Low-level training arguments.</param>
/// <remarks>Trained model will consist of two files: .bin (main model) and .vec (word vectors).</remarks>
public void Train(string inputPath, string outputPath, FastTextArgs args)
{
ValidatePaths(inputPath, outputPath, args.PretrainedVectors);
var argsStruct = new TrainingArgsStruct
{
bucket = args.bucket,
cutoff = args.cutoff,
dim = args.dim,
dsub = args.dsub,
epoch = args.epoch,
loss = (loss_name)args.loss,
lr = args.lr,
lrUpdateRate = args.lrUpdateRate,
maxn = args.maxn,
minCount = args.minCount,
minCountLabel = args.minCountLabel,
minn = args.minn,
model = (model_name)args.model,
neg = args.neg,
qnorm = args.qnorm,
qout = args.qout,
retrain = args.retrain,
saveOutput = args.saveOutput,
t = args.t,
thread = args.thread,
verbose = args.verbose,
wordNgrams = args.wordNgrams,
ws = args.ws,
};
Train(_fastText, inputPath, outputPath, argsStruct, args.LabelPrefix, args.PretrainedVectors);
_maxLabelLen = GetMaxLabelLength(_fastText);
_modelLoaded = true;
}