//Constructor
/// <summary>
/// Constructs an instance of Neural Preprocessor
/// </summary>
/// <param name="settings">Neural Preprocessor settings</param>
/// A value greater than or equal to 0 will always ensure the same initialization of the internal
/// random number generator and therefore the same network structure, which is good for tuning
/// network parameters. A value less than 0 causes a fully random initialization when creating a network instance.
/// <param name="randomizerSeek">
/// </param>
public NeuralPreprocessor(NeuralPreprocessorSettings settings, int randomizerSeek)
{
_settings = settings.DeepClone();
_inputNormalizerCollection = null;
//Internal input generators
_internalInputGeneratorCollection = new List <IGenerator>();
foreach (NeuralPreprocessorSettings.InputSettings.InternalField field in _settings.InputConfig.InternalFieldCollection)
{
if (field.GeneratorSettings.GetType() == typeof(ConstGeneratorSettings))
{
_internalInputGeneratorCollection.Add(new ConstGenerator((ConstGeneratorSettings)field.GeneratorSettings));
}
else if (field.GeneratorSettings.GetType() == typeof(RandomValueSettings))
{
_internalInputGeneratorCollection.Add(new RandomGenerator((RandomValueSettings)field.GeneratorSettings));
}
else if (field.GeneratorSettings.GetType() == typeof(SinusoidalGeneratorSettings))
{
_internalInputGeneratorCollection.Add(new SinusoidalGenerator((SinusoidalGeneratorSettings)field.GeneratorSettings));
}
else if (field.GeneratorSettings.GetType() == typeof(MackeyGlassGeneratorSettings))
{
_internalInputGeneratorCollection.Add(new MackeyGlassGenerator((MackeyGlassGeneratorSettings)field.GeneratorSettings));
}
else
{
throw new Exception($"Unsupported internal signal generator for field {field.Name}");
}
}
//Reservoir instance(s)
//Random generator used for reservoir structure initialization
Random rand = (randomizerSeek < 0 ? new Random() : new Random(randomizerSeek));
PredictorNeuronCollection = new List <Reservoir.PredictorNeuron>();
NumOfNeurons = 0;
NumOfPredictors = 0;
NumOfInternalSynapses = 0;
ReservoirCollection = new List <Reservoir>(_settings.ReservoirInstanceDefinitionCollection.Count);
foreach (NeuralPreprocessorSettings.ReservoirInstanceDefinition instanceDefinition in _settings.ReservoirInstanceDefinitionCollection)
{
Reservoir reservoir = new Reservoir(instanceDefinition, _dataRange, rand);
ReservoirCollection.Add(reservoir);
PredictorNeuronCollection.AddRange(reservoir.PredictorNeuronCollection);
NumOfNeurons += reservoir.Size;
NumOfPredictors += reservoir.NumOfOutputPredictors;
NumOfInternalSynapses += reservoir.NumOfInternalSynapses;
}
if (_settings.InputConfig.RouteExternalInputToReadout)
{
NumOfPredictors += _settings.InputConfig.ExternalFieldCollection.Count;
}
return;
}
//Constructor
/// <summary>
/// Creates an initialized instance.
/// </summary>
/// <param name="preprocessorCfg">The configuration of the neural preprocessor.</param>
/// <param name="randomizerSeek">The random number generator initial seek.</param>
public NeuralPreprocessor(NeuralPreprocessorSettings preprocessorCfg, int randomizerSeek)
{
_preprocessorCfg = (NeuralPreprocessorSettings)preprocessorCfg.DeepClone();
TotalNumOfHiddenNeurons = 0;
///////////////////////////////////////////////////////////////////////////////////
//Input encoder
_inputEncoder = new InputEncoder(_preprocessorCfg.InputEncoderCfg);
///////////////////////////////////////////////////////////////////////////////////
//Reservoir instance(s)
BootCycles = 0;
//Random generator used for reservoir structure initialization
Random rand = (randomizerSeek < 0 ? new Random() : new Random(randomizerSeek));
ReservoirCollection = new List <ReservoirInstance>(_preprocessorCfg.ReservoirInstancesCfg.ReservoirInstanceCfgCollection.Count);
int reservoirInstanceID = 0;
int defaultBootCycles = 0;
foreach (ReservoirInstanceSettings reservoirInstanceCfg in _preprocessorCfg.ReservoirInstancesCfg.ReservoirInstanceCfgCollection)
{
ReservoirStructureSettings structCfg = _preprocessorCfg.ReservoirStructuresCfg.GetReservoirStructureCfg(reservoirInstanceCfg.StructureCfgName);
ReservoirInstance reservoir = new ReservoirInstance(reservoirInstanceID++,
structCfg,
reservoirInstanceCfg,
_inputEncoder,
rand
);
ReservoirCollection.Add(reservoir);
TotalNumOfHiddenNeurons += reservoir.Size;
defaultBootCycles = Math.Max(defaultBootCycles, reservoir.GetDefaultBootCycles());
}
//Boot cycles setup
if (_preprocessorCfg.InputEncoderCfg.FeedingCfg.FeedingType == InputEncoder.InputFeedingType.Continuous)
{
FeedingContinuousSettings feedingCfg = (FeedingContinuousSettings)preprocessorCfg.InputEncoderCfg.FeedingCfg;
BootCycles = feedingCfg.BootCycles == FeedingContinuousSettings.AutoBootCyclesNum ? defaultBootCycles : feedingCfg.BootCycles;
}
else
{
BootCycles = 0;
}
//Output features
_totalNumOfReservoirsPredictors = 0;
_predictorsTimePointSlicesPlan = null;
PredictorDescriptorCollection = null;
OutputFeatureGeneralSwitchCollection = null;
NumOfActivePredictors = 0;
return;
}