/// <summary>
/// Writes a trainer parameters to event log.
/// </summary>
/// <param name="logFile">The log file to write to.</param>
/// <param name="trainer">The trainer which parameters to write.</param>
/// <param name="algorithm">The training algorithm.</param>
/// <param name="loss">The loss function.</param>
private void WriteTrainerParameters(
StreamWriter logFile,
ClassificationNetworkTrainer trainer,
ITrainingAlgorithm algorithm,
ILoss <int[]> loss)
{
this.WriteLine(logFile, "Trainer parameters:");
this.WriteLine(logFile, " Batch Size: {0}", trainer.BatchSize);
this.WriteLine(logFile, " L1 Rate: {0}", trainer.RateL1);
this.WriteLine(logFile, " L2 Rate: {0}", trainer.RateL2);
this.WriteLine(logFile, " Clip Value: {0}", trainer.ClipValue);
this.WriteLine(logFile, "Algorithm parameters:");
this.WriteLine(logFile, " Algorithm: {0}", algorithm.GetType().Name);
if (algorithm is Adadelta adadelta)
{
this.WriteLine(logFile, " Learning Rate: {0}", adadelta.LearningRate);
this.WriteLine(logFile, " Decay: {0}", adadelta.Decay);
this.WriteLine(logFile, " Rho: {0}", adadelta.Rho);
this.WriteLine(logFile, " Eps: {0}", adadelta.Eps);
}
if (algorithm is Adagrad adagrad)
{
this.WriteLine(logFile, " Learning Rate: {0}", adagrad.LearningRate);
this.WriteLine(logFile, " Eps: {0}", adagrad.Eps);
}
if (algorithm is Adam adam)
{
this.WriteLine(logFile, " Learning Rate: {0}", adam.LearningRate);
this.WriteLine(logFile, " Beta1: {0}", adam.Beta1);
this.WriteLine(logFile, " Beta2: {0}", adam.Beta2);
this.WriteLine(logFile, " Eps: {0}", adam.Eps);
}
if (algorithm is RMSProp rmsProp)
{
this.WriteLine(logFile, " Learning Rate: {0}", rmsProp.LearningRate);
this.WriteLine(logFile, " Rho: {0}", rmsProp.Rho);
this.WriteLine(logFile, " Eps: {0}", rmsProp.Eps);
}
if (algorithm is SGD sgd)
{
this.WriteLine(logFile, " Learning Rate: {0}", sgd.LearningRate);
this.WriteLine(logFile, " Decay: {0}", sgd.Decay);
this.WriteLine(logFile, " Momentum: {0}", sgd.Momentum);
this.WriteLine(logFile, " Nesterov: {0}", sgd.Nesterov);
}
this.WriteLine(logFile, "Loss parameters:");
this.WriteLine(logFile, " Loss: {0}", loss.GetType().Name);
if (loss is LogLikelihoodLoss logLikelihoodLoss)
{
this.WriteLine(logFile, " LSR: {0}", logLikelihoodLoss.LSR);
}
}
public NetworkTopology()
{
hiddenLayers = null;
inputLayer = null;
outputLayer = null;
preProcessor = null;
postProcessor = null;
TrainingPreProcessor = null;
TrainingAlgorithm = null;
}
private ITrainingAlgorithm CreateAlgorithm()
{
ITrainingAlgorithm algorithm = null;
switch (this.TaskParameters.Algorithm.Name)
{
case "Adadelta":
default:
algorithm = new Adadelta();
break;
case "Adagrad":
algorithm = new Adagrad();
break;
case "Adam":
algorithm = new Adam();
break;
case "RMSProp":
algorithm = new RMSProp();
break;
case "SGD":
algorithm = new SGD();
break;
}
JsonSerializer jsonSerializer = new JsonSerializer();
using (JTokenReader jtokenReader = new JTokenReader(this.TaskParameters.Algorithm.Parameters))
{
jsonSerializer.Populate(jtokenReader, algorithm);
}
return(algorithm);
}
