// Might want to move into a co-routine as this might become very large and expensive.
private IEnumerator CoFeedForward()
{
yield return(new WaitForEndOfFrame());
// Update the Input layer with updated inputs.
for (int i = 0; i < LayerNeuronCounts[0]; ++i)
{
NetLayers[0].Nodes[i].Activation = Inputs[i];
if (ShouldYield())
{
yield return(new WaitForEndOfFrame());
}
}
// Go through each layer that isn't the input layer.
for (int i = 1; i < NumLayers; ++i)
{
// Go through each node in this layer and calculate it's activation value.
for (int j = 0; j < LayerNeuronCounts[i]; ++j)
{
SigmoidNeuron tempNeuron = NetLayers[i].Nodes[j];
tempNeuron.Activation = Sigmoid(tempNeuron.GetZ());
if (ShouldYield())
{
yield return(new WaitForEndOfFrame());
}
}
}
// Update the outputs from the output layer.
for (int i = 0; i < LayerNeuronCounts[NumLayers - 1]; ++i)
{
Outputs[i] = NetLayers[NumLayers - 1].Nodes[i].Activation;
if (ShouldYield())
{
yield return(new WaitForEndOfFrame());
}
}
for (int i = 0; i < FeedforwardCallBacks.Count; ++i)
{
if (FeedforwardCallBacks[i] != null)
{
FeedforwardCallBacks[i]();
}
}
}
public void FeedForward()
{
for (int i = 0; i < LayerNeuronCounts[0]; ++i)
{
NetLayers[0].Nodes[i].Activation = Inputs[i];
}
// Go through each layer that isn't the input layer.
for (int i = 1; i < NumLayers; ++i)
{
// Go through each node in this layer and calculate it's activation value.
for (int j = 0; j < LayerNeuronCounts[i]; ++j)
{
SigmoidNeuron tempNeuron = NetLayers[i].Nodes[j];
tempNeuron.Activation = Sigmoid(tempNeuron.GetZ());
}
}
// Update the outputs from the output layer.
for (int i = 0; i < LayerNeuronCounts[NumLayers - 1]; ++i)
{
Outputs[i] = NetLayers[NumLayers - 1].Nodes[i].Activation;
}
}
