/// <summary>
/// Initializes a new instance of the <see cref="NeuralNetworkEnsemble"/> class.
/// Constructor
/// </summary>
/// <param name="networks">
/// An array of trained networks that will work as hash functions
/// </param>
/// <exception cref="NeuralNetworkHashingException">
/// Can not create a NN Ensemble out of no networks
/// </exception>
public NeuralNetworkEnsemble(Network[] networks)
{
if (networks == null || networks.Length == 0)
{
throw new NeuralNetworkHashingException("Can not create a NN Ensemble out of no networks");
}
inputsCount = networks[0].InputCount;
// Check all inputs
foreach (Network network in networks)
{
if (network.InputCount != inputsCount)
{
throw new NeuralNetworkHashingException("All networks should have the same inputs count");
}
if (network.MedianResponces == null)
{
throw new NeuralNetworkHashingException(
"Median responses of one of the networks is null," + " please run Median Responses computation for each of the networks and try again");
}
}
this.networks = networks;
foreach (Network network in this.networks)
{
totalOutputs += network.GetLayerNeuronCount(network.LayerCount - 1);
}
outputVector = new byte[totalOutputs];
}
protected override void Load()
{
base.Load();
_port = LoadPort();
_master = LoadMaster();
_networks = LoadNetworks();
_queen = new QueenAnt(this);
}
private QueenAnt(AntConfig config)
{
_instance = this;
_config = config;
_port = LoadPort();
//LoadMaster();
_networks = LoadNetworks();
InitAnts();
AntPacketHandler.Init();
}
private void InitPopulation()
{
_population = new Network[_popSize];
for (int i = 0; i < _popSize; i++){
_population[i] = new Network();
}
}
