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);
}
}
}