public void SubtractGrads(List <NeuronValues> grads, double biasGrad)
{
if (grads.Count != Lenght)
{
throw new IndexOutOfRangeException();
}
for (int i = 0; i < NeuronsInfo.Count; i++)
{
NeuronInfo neuronInfo = NeuronsInfo[i];
int arrayIndex = neuronInfo.ArrayIndex;
NeuronTypes type = neuronInfo.neuronType;
switch (type)
{
case NeuronTypes.feedForward:
Neurons[arrayIndex].SubtractGrads(grads[i]);
break;
case NeuronTypes.lSTM:
LSTMCells[arrayIndex].SubtractGrads(grads[i]);
break;
case NeuronTypes.recurrent:
RecurrentNeurons[arrayIndex].SubtractGrads(grads[i]);
break;
default:
throw new NotImplementedException();
}
}
bias -= biasGrad;
}
public override Neuron[] CreateNeurons()
{
int len = info.neurons.Count;
Neuron[] neurons = new Neuron[len];
for (int i = 0; i < len; i++)
{
NeuronInfo n = info.neurons[i];
neurons[i] = new OutputNeuron(n.activation, n.cost);
}
return(neurons);
}
internal static NeuronInfo ToInternalType(this Graph.Common.NeuronInfo value)
{
NeuronInfo result = null;
if (value != null)
{
result = new NeuronInfo()
{
Id = value.Id,
Tag = value.Tag
}
}
;
return(result);
}
public override Neuron[] CreateNeurons()
{
int len = info.hasBias ? info.neurons.Count + 1 : info.neurons.Count;
Neuron[] neurons = new Neuron[len];
for (int i = 0; i < info.neurons.Count; i++)
{
NeuronInfo n = info.neurons[i];
neurons[i] = new Neuron(n.activation, n.cost);
}
if (info.hasBias)
{
neurons[len - 1] = new Bias(info.biasValue);
}
return(neurons);
}
internal void SetWeigthsAndStates(List <NeuronValues> neuronValues = null)
{
if (neuronValues != null)
{
for (int i = 0; i < Math.Min(neuronValues.Count, NeuronsInfo.Count); i++)
{
NeuronInfo info = NeuronsInfo[i];
NeuronValues values = neuronValues[i];
switch (info.neuronType)
{
case NeuronTypes.feedForward:
Neurons[info.ArrayIndex].Weigths = neuronValues[i].weigths;
break;
case NeuronTypes.lSTM:
LSTMCells[info.ArrayIndex].Weigths = values.weigths;
LSTMCells[info.ArrayIndex].recurrent.storeWeigth = values.lstmWeigths.storeWeigth;
LSTMCells[info.ArrayIndex].recurrent.forgetWeigth = values.lstmWeigths.forgetWeigth;
LSTMCells[info.ArrayIndex].recurrent.outputWeigth = values.lstmWeigths.outputWeigth;
LSTMCells[info.ArrayIndex].recurrent.hiddenState = values.lstmWeigths.hiddenState;
LSTMCells[info.ArrayIndex].recurrent.cellState = values.lstmWeigths.cellState;
break;
case NeuronTypes.recurrent:
RecurrentNeurons[info.ArrayIndex].recurrentWeigth = values.recurrentWeigth;
if (values.lstmWeigths != null)
{
RecurrentNeurons[info.ArrayIndex].hiddenState = values.lstmWeigths.hiddenState;
}
break;
default:
throw new NotImplementedException();
}
}
}
else
{
neuronValues = new List <NeuronValues>();
for (int i = 0; i < NeuronsInfo.Count; i++)
{
neuronValues.Add(new NeuronValues(previousLayerLenght, NeuronsInfo[i].neuronType));
}
SetWeigthsAndStates(neuronValues);
}
}
