/// <summary>
/// Creates and trains the State Machine readout layer.
/// </summary>
/// <param name="regressionInput">
/// RegressionInput object prepared by PrepareRegressionData function
/// </param>
/// <param name="regressionController">
/// Optional. see Regression.RegressionCallbackDelegate
/// </param>
/// <param name="regressionControllerData">
/// Optional custom object to be passed to regressionController together with other standard information
/// </param>
public ResultComparativeBundle BuildReadoutLayer(RegressionInput regressionInput,
ReadoutUnit.RegressionCallbackDelegate regressionController = null,
Object regressionControllerData = null
)
{
//Readout layer instance
RL = new ReadoutLayer(_settings.ReadoutLayerConfig);
//Optional mapper of predictors to readout units
ReadoutLayer.PredictorsMapper mapper = null;
if (_settings.MapperConfig != null)
{
//Create empty instance of the mapper
mapper = new ReadoutLayer.PredictorsMapper(NP.NumOfPredictors);
//Expand list of predicting neurons to array of predictor origin
StateMachineSettings.MapperSettings.PoolRef[] neuronPoolRefCollection = new StateMachineSettings.MapperSettings.PoolRef[NP.NumOfPredictors];
int idx = 0;
foreach (Reservoir.PredictorNeuron pn in NP.PredictorNeuronCollection)
{
neuronPoolRefCollection[idx] = new StateMachineSettings.MapperSettings.PoolRef {
_reservoirInstanceIdx = pn.Neuron.Placement.ReservoirID, _poolIdx = pn.Neuron.Placement.PoolID
};
++idx;
if (pn.UseSecondaryPredictor)
{
neuronPoolRefCollection[idx] = neuronPoolRefCollection[idx - 1];
++idx;
}
}
//Iterate readout units having specific predictors mapping
foreach (string readoutUnitName in _settings.MapperConfig.Map.Keys)
{
bool[] switches = new bool[NP.NumOfPredictors];
switches.Populate(false);
foreach (StateMachineSettings.MapperSettings.PoolRef allowedPool in _settings.MapperConfig.Map[readoutUnitName])
{
//Enable specific predictors from allowed pool (origin)
for (int i = 0; i < neuronPoolRefCollection.Length; i++)
{
if (neuronPoolRefCollection[i]._reservoirInstanceIdx == allowedPool._reservoirInstanceIdx && neuronPoolRefCollection[i]._poolIdx == allowedPool._poolIdx)
{
switches[i] = true;
}
}
}
//Add mapping to mapper
mapper.Add(readoutUnitName, switches);
}
}
//Training
return(RL.Build(regressionInput.PreprocessedData,
regressionController,
regressionControllerData,
mapper
));
}
public static CommonOutputs.RegressionOutput CreateRegressionEnsemble(IHostEnvironment env, RegressionInput input)
{
Contracts.CheckValue(env, nameof(env));
var host = env.Register("CombineModels");
host.CheckValue(input, nameof(input));
host.CheckNonEmpty(input.Models, nameof(input.Models));
GetPipeline(host, input, out IDataView startingData, out RoleMappedData transformedData);
var args = new RegressionEnsembleTrainer.Arguments();
switch (input.ModelCombiner)
{
case ScoreCombiner.Median:
args.OutputCombiner = new MedianFactory();
break;
case ScoreCombiner.Average:
args.OutputCombiner = new AverageFactory();
break;
default:
throw host.Except("Unknown combiner kind");
}
var trainer = new RegressionEnsembleTrainer(host, args);
var ensemble = trainer.CombineModels(input.Models.Select(pm => pm.Predictor as IPredictorProducing <float>));
var predictorModel = new PredictorModel(host, transformedData, startingData, ensemble);
var output = new CommonOutputs.RegressionOutput {
PredictorModel = predictorModel
};
return(output);
}
/// <summary>
/// Creates and trains the State Machine readout layer.
/// Function uses specific mapping of predictors to readout units, if available.
/// Function also rejects unusable predictors having no reasonable fluctuation of values.
/// </summary>
/// <param name="regressionInput">
/// RegressionInput object prepared by PrepareRegressionData function
/// </param>
/// <param name="regressionController">
/// Optional. see Regression.RegressionCallbackDelegate
/// </param>
/// <param name="regressionControllerData">
/// Optional custom object to be passed to regressionController together with other standard information
/// </param>
public ResultBundle BuildReadoutLayer(RegressionInput regressionInput,
ReadoutUnit.RegressionCallbackDelegate regressionController = null,
Object regressionControllerData = null
)
{
//Readout layer instance
RL = new ReadoutLayer(_settings.ReadoutLayerConfig);
//Create empty instance of the mapper
ReadoutLayer.PredictorsMapper mapper = new ReadoutLayer.PredictorsMapper(PredictorGeneralSwitchCollection);
if (_settings.MapperCfg != null)
{
//Expand list of predicting neurons to array of predictor origin
StateMachineSettings.MapperSettings.AllowedPool[] neuronPoolRefCollection = new StateMachineSettings.MapperSettings.AllowedPool[NP.NumOfPredictors];
int idx = 0;
foreach (HiddenNeuron neuron in NP.PredictorNeuronCollection)
{
StateMachineSettings.MapperSettings.AllowedPool poolRef = new StateMachineSettings.MapperSettings.AllowedPool {
_reservoirInstanceIdx = neuron.Placement.ReservoirID, _poolIdx = neuron.Placement.PoolID
};
for (int i = 0; i < neuron.PredictorsCfg.NumOfEnabledPredictors; i++)
{
neuronPoolRefCollection[idx] = poolRef;
++idx;
}
}
//Iterate all readout units
foreach (string readoutUnitName in _settings.ReadoutLayerConfig.OutputFieldNameCollection)
{
bool[] switches = new bool[NP.NumOfPredictors];
//Initially allow all valid predictors
PredictorGeneralSwitchCollection.CopyTo(switches, 0);
//Exists specific mapping?
if (_settings.MapperCfg != null && (_settings.MapperCfg.PoolsMap.ContainsKey(readoutUnitName) || _settings.MapperCfg.RoutedInputFieldsMap.ContainsKey(readoutUnitName)))
{
//Routed input fields
if (_settings.MapperCfg.RoutedInputFieldsMap.ContainsKey(readoutUnitName))
{
//Initially disable all routed input fields
for (int i = NP.PredictorNeuronCollection.Count; i < NP.NumOfPredictors; i++)
{
switches[i] = false;
}
//Enable enabled routed input fields
List <int> enabledRoutedFieldsIdxs = _settings.MapperCfg.RoutedInputFieldsMap[readoutUnitName];
for (int i = 0; i < enabledRoutedFieldsIdxs.Count; i++)
{
switches[NP.PredictorNeuronCollection.Count + enabledRoutedFieldsIdxs[i]] = PredictorGeneralSwitchCollection[NP.PredictorNeuronCollection.Count + enabledRoutedFieldsIdxs[i]];
}
}
//Neuron predictors
if (_settings.MapperCfg.PoolsMap.ContainsKey(readoutUnitName))
{
//Initially disable all neuron predictors
for (int i = 0; i < NP.PredictorNeuronCollection.Count; i++)
{
switches[i] = false;
}
//Enable allowed neuron predictors
foreach (StateMachineSettings.MapperSettings.AllowedPool allowedPool in _settings.MapperCfg.PoolsMap[readoutUnitName])
{
//Enable specific predictors from allowed pool (origin)
for (int i = 0; i < NP.PredictorNeuronCollection.Count; i++)
{
if (neuronPoolRefCollection[i]._reservoirInstanceIdx == allowedPool._reservoirInstanceIdx && neuronPoolRefCollection[i]._poolIdx == allowedPool._poolIdx)
{
//Enable predictor if it is valid
switches[i] = PredictorGeneralSwitchCollection[i];
}
}
}
}
}
//Add mapping to mapper
mapper.Add(readoutUnitName, switches);
}
}
//Training
return(RL.Build(regressionInput.PreprocessedData,
regressionController,
regressionControllerData,
mapper
));
}
