public override RNN <T> Clone()
{
List <SimpleLayer> forwardLayers = new List <SimpleLayer>();
List <SimpleLayer> backwardLayers = new List <SimpleLayer>();
foreach (SimpleLayer layer in forwardHiddenLayers)
{
forwardLayers.Add(layer.CreateLayerSharedWegiths());
}
foreach (SimpleLayer layer in backwardHiddenLayers)
{
backwardLayers.Add(layer.CreateLayerSharedWegiths());
}
BiRNN <T> rnn = new BiRNN <T>();
rnn.InitCache(forwardLayers, backwardLayers, OutputLayer.CreateLayerSharedWegiths());
rnn.CRFWeights = CRFWeights;
rnn.MaxSeqLength = MaxSeqLength;
rnn.bVQ = bVQ;
rnn.IsCRFTraining = IsCRFTraining;
if (rnn.IsCRFTraining)
{
rnn.InitializeCRFVariablesForTraining();
}
return(rnn);
}
public override RNN <T> Clone()
{
List <SimpleLayer> hiddenLayers = new List <SimpleLayer>();
List <float[]>[] denseFeatureGroupsList = new List <float[]> [HiddenLayerList.Count];
int i = 0;
foreach (SimpleLayer layer in HiddenLayerList)
{
hiddenLayers.Add(layer.CreateLayerSharedWegiths());
denseFeatureGroupsList[i] = new List <float[]>();
i++;
}
List <float[]> denseFeatureGroupsOutputLayer = new List <float[]>();
ForwardRNNSeq2Seq <T> rnn = new ForwardRNNSeq2Seq <T>();
rnn.HiddenLayerList = hiddenLayers;
rnn.OutputLayer = OutputLayer.CreateLayerSharedWegiths();
rnn.CRFWeights = CRFWeights;
rnn.denseFeatureGroupsList = denseFeatureGroupsList;
rnn.denseFeatureGroupsOutputLayer = denseFeatureGroupsOutputLayer;
rnn.sparseFeatureGorups = new List <SparseVector>();
rnn.MaxSeqLength = MaxSeqLength;
rnn.bVQ = bVQ;
rnn.IsCRFTraining = IsCRFTraining;
if (rnn.IsCRFTraining)
{
rnn.InitializeCRFVariablesForTraining();
}
return(rnn);
}
public override RNN <T> Clone()
{
List <SimpleLayer> hiddenLayers = new List <SimpleLayer>();
foreach (SimpleLayer layer in HiddenLayerList)
{
hiddenLayers.Add(layer.CreateLayerSharedWegiths());
}
ForwardRNNSeq2Seq <T> rnn = new ForwardRNNSeq2Seq <T>();
rnn.HiddenLayerList = hiddenLayers;
rnn.OutputLayer = OutputLayer.CreateLayerSharedWegiths();
rnn.CRFTagTransWeights = CRFTagTransWeights;
rnn.MaxSeqLength = MaxSeqLength;
rnn.crfLocker = crfLocker;
return(rnn);
}
public override RNN <T> Clone()
{
List <SimpleLayer> hiddenLayers = new List <SimpleLayer>();
foreach (SimpleLayer layer in HiddenLayerList)
{
hiddenLayers.Add(layer.CreateLayerSharedWegiths());
}
ForwardRNN <T> rnn = new ForwardRNN <T>();
rnn.HiddenLayerList = hiddenLayers;
rnn.OutputLayer = OutputLayer.CreateLayerSharedWegiths();
rnn.CRFWeights = CRFWeights;
rnn.MaxSeqLength = MaxSeqLength;
rnn.bVQ = bVQ;
rnn.IsCRFTraining = IsCRFTraining;
if (rnn.IsCRFTraining)
{
rnn.InitializeCRFVariablesForTraining();
}
return(rnn);
}
public override RNN <T> Clone()
{
List <SimpleLayer> forwardLayers = new List <SimpleLayer>();
List <SimpleLayer> backwardLayers = new List <SimpleLayer>();
foreach (SimpleLayer layer in forwardHiddenLayers)
{
forwardLayers.Add(layer.CreateLayerSharedWegiths());
}
foreach (SimpleLayer layer in backwardHiddenLayers)
{
backwardLayers.Add(layer.CreateLayerSharedWegiths());
}
BiRNNAvg <T> rnn = new BiRNNAvg <T>();
rnn.InitCache(forwardLayers, backwardLayers, OutputLayer.CreateLayerSharedWegiths());
rnn.CRFTagTransWeights = CRFTagTransWeights;
rnn.MaxSeqLength = MaxSeqLength;
rnn.crfLocker = crfLocker;
return(rnn);
}
public override void LoadModel(string filename, bool bTrain = false)
{
Logger.WriteLine(Logger.Level.info, "Loading bi-directional model: {0}", filename);
using (var sr = new StreamReader(filename))
{
var br = new BinaryReader(sr.BaseStream);
IsCRFTraining = br.ReadBoolean();
var layerSize = br.ReadInt32();
LayerType layerType = LayerType.None;
//Load forward layers from file
forwardHiddenLayers = new List <SimpleLayer>();
for (var i = 0; i < layerSize; i++)
{
layerType = (LayerType)br.ReadInt32();
forwardHiddenLayers.Add(Load(layerType, br));
SimpleLayer layer = forwardHiddenLayers[forwardHiddenLayers.Count - 1];
if (bTrain)
{
layer.SetRunningMode(RunningMode.Training);
layer.InitializeInternalTrainingParameters();
}
else
{
layer.SetRunningMode(RunningMode.Test);
}
}
//Load backward layers from file
backwardHiddenLayers = new List <SimpleLayer>();
for (var i = 0; i < layerSize; i++)
{
layerType = (LayerType)br.ReadInt32();
backwardHiddenLayers.Add(Load(layerType, br));
SimpleLayer layer = backwardHiddenLayers[backwardHiddenLayers.Count - 1];
if (bTrain)
{
layer.SetRunningMode(RunningMode.Training);
layer.InitializeInternalTrainingParameters();
}
else
{
layer.SetRunningMode(RunningMode.Test);
}
}
Logger.WriteLine("Create output layer");
layerType = (LayerType)br.ReadInt32();
OutputLayer = Load(layerType, br);
if (bTrain)
{
OutputLayer.SetRunningMode(RunningMode.Training);
OutputLayer.InitializeInternalTrainingParameters();
}
else
{
OutputLayer.SetRunningMode(RunningMode.Test);
}
if (IsCRFTraining)
{
Logger.WriteLine("Loading CRF tag trans weights...");
CRFWeights = RNNHelper.LoadMatrix(br);
}
if (bTrain)
{
InitCache(forwardHiddenLayers, backwardHiddenLayers, OutputLayer.CreateLayerSharedWegiths());
}
}
}
