public virtual void Save(BinaryWriter fo)
{
fo.Write(LayerSize);
fo.Write(DenseFeatureSize);
RNNHelper.SaveMatrix(DenseWeights, fo);
}
// save model as binary format
public override void SaveModel(string filename)
{
StreamWriter sw = new StreamWriter(filename);
BinaryWriter fo = new BinaryWriter(sw.BaseStream);
if (HiddenLayerList[0] is BPTTLayer)
{
fo.Write(0);
}
else
{
fo.Write(1);
}
fo.Write((int)ModelDirection);
fo.Write(IsCRFTraining);
fo.Write(HiddenLayerList.Count);
foreach (SimpleLayer layer in HiddenLayerList)
{
layer.Save(fo);
}
OutputLayer.Save(fo);
if (IsCRFTraining == true)
{
//Save CRF feature weights
RNNHelper.SaveMatrix(CRFTagTransWeights, fo);
}
fo.Close();
}
// save model as binary format
public override void SaveModel(string filename)
{
var sw = new StreamWriter(filename);
var fo = new BinaryWriter(sw.BaseStream);
if (HiddenLayerList[0] is BPTTLayer)
{
fo.Write((int)LAYERTYPE.BPTT);
}
else
{
fo.Write((int)LAYERTYPE.LSTM);
}
fo.Write(IsCRFTraining);
fo.Write(HiddenLayerList.Count);
foreach (var layer in HiddenLayerList)
{
layer.Save(fo);
}
OutputLayer.Save(fo);
if (IsCRFTraining)
{
//Save CRF feature weights
RNNHelper.SaveMatrix(CRFTagTransWeights, fo);
}
fo.Close();
}
public override void SaveModel(string filename)
{
//Save meta data
using (StreamWriter sw = new StreamWriter(filename))
{
BinaryWriter fo = new BinaryWriter(sw.BaseStream);
if (forwardHiddenLayers[0] is BPTTLayer)
{
fo.Write(0);
}
else
{
fo.Write(1);
}
fo.Write((int)ModelDirection);
// Signiture , 0 is for RNN or 1 is for RNN-CRF
int iflag = 0;
if (IsCRFTraining == true)
{
iflag = 1;
}
fo.Write(iflag);
fo.Write(forwardHiddenLayers.Count);
//Save forward layers
foreach (SimpleLayer layer in forwardHiddenLayers)
{
layer.Save(fo);
}
//Save backward layers
foreach (SimpleLayer layer in backwardHiddenLayers)
{
layer.Save(fo);
}
//Save output layer
OutputLayer.Save(fo);
if (iflag == 1)
{
// Save Bigram
RNNHelper.SaveMatrix(CRFTagTransWeights, fo);
}
}
}
public virtual void Save(BinaryWriter fo)
{
fo.Write(LayerSize);
fo.Write(SparseFeatureSize);
fo.Write(DenseFeatureSize);
if (SparseFeatureSize > 0)
{
Logger.WriteLine("Saving input2hidden weights...");
RNNHelper.SaveMatrix(SparseWeights, fo);
}
if (DenseFeatureSize > 0)
{
//weight fea->hidden
Logger.WriteLine("Saving feature2hidden weights...");
RNNHelper.SaveMatrix(DenseWeights, fo);
}
}
public override void SaveModel(string filename)
{
//Save meta data
using (StreamWriter sw = new StreamWriter(filename))
{
BinaryWriter fo = new BinaryWriter(sw.BaseStream);
if (forwardHiddenLayers[0] is BPTTLayer)
{
fo.Write((int)LAYERTYPE.BPTT);
}
else
{
fo.Write((int)LAYERTYPE.LSTM);
}
fo.Write((int)ModelDirection);
//Bi-directional model doesn't support sequence-to-sequence
fo.Write((int)MODELTYPE.SEQLABEL);
fo.Write(IsCRFTraining);
fo.Write(forwardHiddenLayers.Count);
//Save forward layers
foreach (SimpleLayer layer in forwardHiddenLayers)
{
layer.Save(fo);
}
//Save backward layers
foreach (SimpleLayer layer in backwardHiddenLayers)
{
layer.Save(fo);
}
//Save output layer
OutputLayer.Save(fo);
if (IsCRFTraining == true)
{
// Save CRF features weights
RNNHelper.SaveMatrix(CRFTagTransWeights, fo);
}
}
}
// save model as binary format
public override void SaveModel(string filename)
{
StreamWriter sw = new StreamWriter(filename);
BinaryWriter fo = new BinaryWriter(sw.BaseStream);
if (HiddenLayerList[0] is BPTTLayer)
{
fo.Write(0);
}
else
{
fo.Write(1);
}
fo.Write((int)ModelDirection);
// Signiture , 0 is for RNN or 1 is for RNN-CRF
int iflag = 0;
if (IsCRFTraining == true)
{
iflag = 1;
}
fo.Write(iflag);
fo.Write(HiddenLayerList.Count);
foreach (SimpleLayer layer in HiddenLayerList)
{
layer.Save(fo);
}
OutputLayer.Save(fo);
if (iflag == 1)
{
// Save Bigram
RNNHelper.SaveMatrix(CRFTagTransWeights, fo);
}
fo.Close();
}
public virtual void Save(BinaryWriter fo)
{
fo.Write(LayerSize);
fo.Write(SparseFeatureSize);
fo.Write(DenseFeatureSize);
Logger.WriteLine(
$"Saving simple layer, size = '{LayerSize}', sparse feature size = '{SparseFeatureSize}', dense feature size = '{DenseFeatureSize}'");
if (SparseFeatureSize > 0)
{
Logger.WriteLine("Saving sparse feature weights...");
RNNHelper.SaveMatrix(SparseWeights, fo);
}
if (DenseFeatureSize > 0)
{
//weight fea->hidden
Logger.WriteLine("Saving dense feature weights...");
RNNHelper.SaveMatrix(DenseWeights, fo);
}
}
public override void SaveModel(string filename)
{
//Save meta data
using (var sw = new StreamWriter(filename))
{
var fo = new BinaryWriter(sw.BaseStream);
if (forwardHiddenLayers[0] is BPTTLayer)
{
fo.Write((int)LAYERTYPE.BPTT);
}
else
{
fo.Write((int)LAYERTYPE.LSTM);
}
fo.Write(IsCRFTraining);
fo.Write(forwardHiddenLayers.Count);
//Save forward layers
foreach (var layer in forwardHiddenLayers)
{
layer.Save(fo);
}
//Save backward layers
foreach (var layer in backwardHiddenLayers)
{
layer.Save(fo);
}
//Save output layer
OutputLayer.Save(fo);
if (IsCRFTraining)
{
// Save CRF features weights
RNNHelper.SaveMatrix(CRFTagTransWeights, fo);
}
}
}