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); } } }