public virtual void Load(BinaryReader br, LayerType layerType, bool forTraining = false) { LayerConfig = new LayerConfig(); LayerConfig.LayerSize = br.ReadInt32(); LayerConfig.LayerType = layerType; Cells = new float[LayerSize]; Errs = new float[LayerSize]; LabelShortList = new List <int>(); SparseFeatureSize = br.ReadInt32(); DenseFeatureSize = br.ReadInt32(); if (SparseFeatureSize > 0) { Logger.WriteLine("Loading sparse feature weights..."); SparseWeights = RNNHelper.LoadMatrix(br); } if (DenseFeatureSize > 0) { Logger.WriteLine("Loading dense feature weights..."); DenseWeights = RNNHelper.LoadMatrix(br); } if (forTraining) { InitializeInternalTrainingParameters(); } }
public static SimpleLayer Load(BinaryReader br, LayerType layerType) { LayerConfig config = new LayerConfig(); config.LayerSize = br.ReadInt32(); config.LayerType = layerType; SimpleLayer layer = new SimpleLayer(config); layer.SparseFeatureSize = br.ReadInt32(); layer.DenseFeatureSize = br.ReadInt32(); if (layer.SparseFeatureSize > 0) { Logger.WriteLine("Loading sparse feature weights..."); layer.SparseWeights = RNNHelper.LoadMatrix(br); } if (layer.DenseFeatureSize > 0) { Logger.WriteLine("Loading dense feature weights..."); layer.DenseWeights = RNNHelper.LoadMatrix(br); } return(layer); }
public virtual void Load(BinaryReader br) { //Load basic parameters LayerSize = br.ReadInt32(); DenseFeatureSize = br.ReadInt32(); AllocateMemoryForCells(); DenseWeights = RNNHelper.LoadMatrix(br); }
public override void LoadModel(string filename) { Logger.WriteLine("Loading SimpleRNN model: {0}", filename); StreamReader sr = new StreamReader(filename); BinaryReader br = new BinaryReader(sr.BaseStream); int modelType = br.ReadInt32(); ModelDirection = (MODELDIRECTION)br.ReadInt32(); int iflag = br.ReadInt32(); if (iflag == 1) { IsCRFTraining = true; } else { IsCRFTraining = false; } //Create cells of each layer int layerSize = br.ReadInt32(); HiddenLayerList = new List <SimpleLayer>(); for (int i = 0; i < layerSize; i++) { SimpleLayer layer = null; if (modelType == 0) { layer = new BPTTLayer(); } else { layer = new LSTMLayer(); } layer.Load(br); HiddenLayerList.Add(layer); } OutputLayer = new SimpleLayer(); OutputLayer.Load(br); if (iflag == 1) { Logger.WriteLine("Loading CRF tag trans weights..."); CRFTagTransWeights = RNNHelper.LoadMatrix(br); } sr.Close(); }
public override void LoadModel(string filename) { Logger.WriteLine("Loading SimpleRNN model: {0}", filename); var sr = new StreamReader(filename); var br = new BinaryReader(sr.BaseStream); var layerType = (LAYERTYPE)br.ReadInt32(); IsCRFTraining = br.ReadBoolean(); //Create cells of each layer var layerSize = br.ReadInt32(); HiddenLayerList = new List <SimpleLayer>(); for (var i = 0; i < layerSize; i++) { SimpleLayer layer; if (layerType == LAYERTYPE.BPTT) { layer = new BPTTLayer(); } else { layer = new LSTMLayer(); } layer.Load(br); HiddenLayerList.Add(layer); } Logger.WriteLine("Create output layer"); OutputLayer = new SimpleLayer(); OutputLayer.Load(br); if (IsCRFTraining) { Logger.WriteLine("Loading CRF tag trans weights..."); CRFTagTransWeights = RNNHelper.LoadMatrix(br); } sr.Close(); }
public virtual void Load(BinaryReader br) { //Load basic parameters LayerSize = br.ReadInt32(); SparseFeatureSize = br.ReadInt32(); DenseFeatureSize = br.ReadInt32(); AllocateMemoryForCells(); if (SparseFeatureSize > 0) { Logger.WriteLine("Loading input2hidden weights..."); SparseWeights = RNNHelper.LoadMatrix(br); } if (DenseFeatureSize > 0) { Logger.WriteLine("Loading feature2hidden weights..."); DenseWeights = RNNHelper.LoadMatrix(br); } }
public override void Load(BinaryReader br) { //Load basic parameters LayerSize = br.ReadInt32(); SparseFeatureSize = br.ReadInt32(); DenseFeatureSize = br.ReadInt32(); AllocateMemoryForCells(); Logger.WriteLine("Loading bptt hidden weights..."); BpttWeights = RNNHelper.LoadMatrix(br); if (SparseFeatureSize > 0) { Logger.WriteLine("Loading sparse feature weights..."); SparseWeights = RNNHelper.LoadMatrix(br); } if (DenseFeatureSize > 0) { Logger.WriteLine("Loading dense feature weights..."); DenseWeights = RNNHelper.LoadMatrix(br); } }
public override void LoadModel(string filename) { Logger.WriteLine(Logger.Level.info, "Loading bi-directional model: {0}", filename); using (StreamReader sr = new StreamReader(filename)) { BinaryReader br = new BinaryReader(sr.BaseStream); int modelType = br.ReadInt32(); ModelDirection = (MODELDIRECTION)br.ReadInt32(); int iflag = br.ReadInt32(); if (iflag == 1) { IsCRFTraining = true; } else { IsCRFTraining = false; } int layerSize = br.ReadInt32(); //Load forward layers from file forwardHiddenLayers = new List <SimpleLayer>(); for (int i = 0; i < layerSize; i++) { SimpleLayer layer = null; if (modelType == 0) { Logger.WriteLine("Create BPTT hidden layer"); layer = new BPTTLayer(); } else { Logger.WriteLine("Crate LSTM hidden layer"); layer = new LSTMLayer(); } layer.Load(br); forwardHiddenLayers.Add(layer); } //Load backward layers from file backwardHiddenLayers = new List <SimpleLayer>(); for (int i = 0; i < layerSize; i++) { SimpleLayer layer = null; if (modelType == 0) { Logger.WriteLine("Create BPTT hidden layer"); layer = new BPTTLayer(); } else { Logger.WriteLine("Crate LSTM hidden layer"); layer = new LSTMLayer(); } layer.Load(br); backwardHiddenLayers.Add(layer); } OutputLayer = new SimpleLayer(); OutputLayer.Load(br); if (iflag == 1) { Logger.WriteLine("Loading CRF tag trans weights..."); CRFTagTransWeights = RNNHelper.LoadMatrix(br); } } }
public override void LoadModel(string filename) { Logger.WriteLine(Logger.Level.info, "Loading bi-directional model: {0}", filename); using (var sr = new StreamReader(filename)) { var br = new BinaryReader(sr.BaseStream); var layerType = (LAYERTYPE)br.ReadInt32(); IsCRFTraining = br.ReadBoolean(); var layerSize = br.ReadInt32(); //Load forward layers from file forwardHiddenLayers = new List <SimpleLayer>(); for (var i = 0; i < layerSize; i++) { SimpleLayer layer; if (layerType == LAYERTYPE.BPTT) { Logger.WriteLine("Create BPTT hidden layer"); layer = new BPTTLayer(); } else { Logger.WriteLine("Create LSTM hidden layer"); layer = new LSTMLayer(); } layer.Load(br); forwardHiddenLayers.Add(layer); } //Load backward layers from file backwardHiddenLayers = new List <SimpleLayer>(); for (var i = 0; i < layerSize; i++) { SimpleLayer layer; if (layerType == LAYERTYPE.BPTT) { Logger.WriteLine("Create BPTT hidden layer"); layer = new BPTTLayer(); } else { Logger.WriteLine("Create LSTM hidden layer"); layer = new LSTMLayer(); } layer.Load(br); backwardHiddenLayers.Add(layer); } Logger.WriteLine("Create output layer"); OutputLayer = new SimpleLayer(); OutputLayer.Load(br); if (IsCRFTraining) { Logger.WriteLine("Loading CRF tag trans weights..."); CRFTagTransWeights = RNNHelper.LoadMatrix(br); } } }