/// <summary>
/// This is the callback control function of the regression process and is called by State Machine
/// after the completion of each regression training epoch.
///
/// The goal of the regression process is for each output field to train a readout network(s)
/// that will give good results both on the training data and the test data. An instance of the
/// Regression.RegressionControlInArgs class passed to this function contains the best error statistics so far
/// and the latest statistics. The primary purpose of this function is to decide whether the latest statistics
/// are better than the best statistics so far. Here is used simply the default implementation of the decision, but
/// the logic can be much more complicated in real-world situations.
/// The function can also tell the regression process that it does not make any sense to continue the regression.
/// It can terminate the current regression attempt or whole readout unit regression process.
///
/// The secondary purpose of this function is to inform about the regression process progress.
/// </summary>
/// <param name="inArgs">Contains all the necessary information to control the regression.</param>
/// <returns>Instructions for the regression process.</returns>
public static ReadoutUnit.RegressionControlOutArgs RegressionControl(ReadoutUnit.RegressionControlInArgs inArgs)
{
//Instantiate output object.
ReadoutUnit.RegressionControlOutArgs outArgs = new ReadoutUnit.RegressionControlOutArgs
{
//Call the default implementation of the judgement.
CurrentIsBetter = ReadoutUnit.IsBetter(inArgs.TaskType, inArgs.CurrReadoutUnit, inArgs.BestReadoutUnit)
};
//Report the progress
if (outArgs.CurrentIsBetter || (inArgs.Epoch % 10) == 0 || inArgs.Epoch == inArgs.MaxEpochs || (inArgs.Epoch == 1 && inArgs.RegrAttemptNumber == 1))
{
//Mark the currently best readout unit
ReadoutUnit bestReadoutUnit = outArgs.CurrentIsBetter ? inArgs.CurrReadoutUnit : inArgs.BestReadoutUnit;
//Build progress text message
StringBuilder progressText = new StringBuilder();
progressText.Append(" OutputField: ");
progressText.Append(inArgs.OutputFieldName);
progressText.Append(", Fold/Attempt/Epoch: ");
progressText.Append(inArgs.FoldNum.ToString().PadLeft(inArgs.NumOfFolds.ToString().Length, '0') + "/");
progressText.Append(inArgs.RegrAttemptNumber.ToString().PadLeft(inArgs.RegrMaxAttempts.ToString().Length, '0') + "/");
progressText.Append(inArgs.Epoch.ToString().PadLeft(inArgs.MaxEpochs.ToString().Length, '0'));
progressText.Append(", DSet-Sizes: (");
progressText.Append(inArgs.CurrReadoutUnit.TrainingErrorStat.NumOfSamples.ToString() + ", ");
progressText.Append(inArgs.CurrReadoutUnit.TestingErrorStat.NumOfSamples.ToString() + ")");
progressText.Append(", Best-Train: ");
progressText.Append(bestReadoutUnit.TrainingErrorStat.ArithAvg.ToString("E3", CultureInfo.InvariantCulture));
if (inArgs.TaskType == CommonEnums.TaskType.Classification)
{
//Append binary errors
progressText.Append("/" + bestReadoutUnit.TrainingBinErrorStat.TotalErrStat.Sum.ToString(CultureInfo.InvariantCulture));
progressText.Append("/" + bestReadoutUnit.TrainingBinErrorStat.BinValErrStat[1].Sum.ToString(CultureInfo.InvariantCulture));
}
progressText.Append(", Best-Test: ");
progressText.Append(bestReadoutUnit.TestingErrorStat.ArithAvg.ToString("E3", CultureInfo.InvariantCulture));
if (inArgs.TaskType == CommonEnums.TaskType.Classification)
{
//Append binary errors
progressText.Append("/" + bestReadoutUnit.TestingBinErrorStat.TotalErrStat.Sum.ToString(CultureInfo.InvariantCulture));
progressText.Append("/" + bestReadoutUnit.TestingBinErrorStat.BinValErrStat[1].Sum.ToString(CultureInfo.InvariantCulture));
}
progressText.Append(", Curr-Train: ");
progressText.Append(inArgs.CurrReadoutUnit.TrainingErrorStat.ArithAvg.ToString("E3", CultureInfo.InvariantCulture));
if (inArgs.TaskType == CommonEnums.TaskType.Classification)
{
//Append binary errors
progressText.Append("/" + inArgs.CurrReadoutUnit.TrainingBinErrorStat.TotalErrStat.Sum.ToString(CultureInfo.InvariantCulture));
progressText.Append("/" + inArgs.CurrReadoutUnit.TrainingBinErrorStat.BinValErrStat[1].Sum.ToString(CultureInfo.InvariantCulture));
}
progressText.Append(", Curr-Test: ");
progressText.Append(inArgs.CurrReadoutUnit.TestingErrorStat.ArithAvg.ToString("E3", CultureInfo.InvariantCulture));
if (inArgs.TaskType == CommonEnums.TaskType.Classification)
{
//Append binary errors
progressText.Append("/" + inArgs.CurrReadoutUnit.TestingBinErrorStat.TotalErrStat.Sum.ToString(CultureInfo.InvariantCulture));
progressText.Append("/" + inArgs.CurrReadoutUnit.TestingBinErrorStat.BinValErrStat[1].Sum.ToString(CultureInfo.InvariantCulture));
}
((IOutputLog)inArgs.UserObject).Write(progressText.ToString(), !(inArgs.Epoch == 1 && inArgs.RegrAttemptNumber == 1));
}
return(outArgs);
}
/// <summary>
/// This is the callback control function of the regression process and is called by State Machine
/// after the completion of each training epoch.
///
/// The goal of the regression process is to train for each output field the readout network(s)
/// that will give good results both on the training data and the test data. An instance of the
/// Regression.RegressionControlInArgs class passed to this function contains the best error statistics so far
/// and the latest statistics. The primary purpose of this function is to decide whether the latest statistics
/// are better than the best statistics so far. Here is used simply the default implementation of the decision, but
/// the logic can be much more complicated in real-world situations.
/// The function can also tell the regression process that it does not make any sense to continue the regression.
/// It can terminate the current regression attempt or whole readout unit regression process.
///
/// The secondary purpose of this function is to inform about the regression process progress.
/// </summary>
/// <param name="inArgs">Contains all the necessary information to control the regression.</param>
/// <returns>Instructions for the regression process.</returns>
public static ReadoutUnit.RegressionControlOutArgs RegressionControl(ReadoutUnit.RegressionControlInArgs inArgs)
{
const int reportEpochsInterval = 10;
//Instantiate output object to set instructions for the regression process.
ReadoutUnit.RegressionControlOutArgs outArgs = new ReadoutUnit.RegressionControlOutArgs
{
//Call the default implementation of the judgement.
CurrentIsBetter = ReadoutUnit.IsBetter(inArgs.TaskType, inArgs.CurrReadoutUnit, inArgs.BestReadoutUnit),
StopRegression = (inArgs.TaskType == ReadoutUnit.TaskType.Classification &&
inArgs.CurrReadoutUnit.TrainingBinErrorStat.TotalErrStat.Sum == 0 &&
inArgs.CurrReadoutUnit.TestingBinErrorStat.TotalErrStat.Sum == 0
)
};
//Progress info
if (outArgs.CurrentIsBetter ||
(inArgs.Epoch % reportEpochsInterval) == 0 ||
inArgs.Epoch == inArgs.MaxEpochs ||
(inArgs.Epoch == 1 && inArgs.RegrAttemptNumber == 1)
)
{
//Build progress report message
string progressText = ReadoutLayer.GetProgressReport(inArgs,
outArgs.CurrentIsBetter ? inArgs.CurrReadoutUnit : inArgs.BestReadoutUnit,
6);
//Report the progress
((IOutputLog)inArgs.UserObject).Write(progressText, !(inArgs.Epoch == 1 && inArgs.RegrAttemptNumber == 1));
}
return(outArgs);
}
/// <summary>
/// This is the control function of the regression process and is called
/// after the completion of each regression training epoch.
/// The goal of the regression process is for each output field to train a readout network
/// that will give good results both on the training data and the test data.
/// Regression.RegressionControlInArgs object passed to the function contains the best error statistics so far
/// and the latest statistics. The primary purpose of the function is to decide whether the latest statistics
/// are better than the best statistics so far.
/// Here is used simply the default implementation of the decision, but
/// the the implemented logic can be much more complicated in real-world situations.
/// The function can also tell the regression process that it does not make any sense to continue the regression.
/// It can terminate the current regression attempt or whole readout unit regression process.
/// </summary>
/// <param name="inArgs">Contains all the necessary information to control the progress of the regression.</param>
/// <returns>Instructions for the regression process.</returns>
public static ReadoutUnit.RegressionControlOutArgs RegressionControl(ReadoutUnit.RegressionControlInArgs inArgs)
{
//Instantiate output object.
ReadoutUnit.RegressionControlOutArgs outArgs = new ReadoutUnit.RegressionControlOutArgs();
//Call the default implementation of the judgement.
outArgs.CurrentIsBetter = ReadoutUnit.IsBetter(inArgs.TaskType, inArgs.CurrReadoutUnit, inArgs.BestReadoutUnit);
//Report the progress
int reportInterval = Math.Max(inArgs.MaxEpochs / 100, 1);
ReadoutUnit bestReadoutUnit = outArgs.CurrentIsBetter ? inArgs.CurrReadoutUnit : inArgs.BestReadoutUnit;
if (outArgs.CurrentIsBetter || (inArgs.Epoch % reportInterval) == 0 || inArgs.Epoch == inArgs.MaxEpochs || (inArgs.Epoch == 1 && inArgs.RegrAttemptNumber == 1))
{
((IOutputLog)inArgs.UserObject).Write(
" OutputField: " + inArgs.OutputFieldName +
", Fold/Attempt/Epoch: " + inArgs.FoldNum.ToString().PadLeft(inArgs.NumOfFolds.ToString().Length, '0') + "/" +
inArgs.RegrAttemptNumber.ToString().PadLeft(inArgs.RegrMaxAttempts.ToString().Length, '0') + "/" +
inArgs.Epoch.ToString().PadLeft(inArgs.MaxEpochs.ToString().Length, '0') +
", DSet-Sizes: (" + inArgs.CurrReadoutUnit.TrainingErrorStat.NumOfSamples.ToString() + ", " +
inArgs.CurrReadoutUnit.TestingErrorStat.NumOfSamples.ToString() + ")" +
", Best-Train: " + bestReadoutUnit.TrainingErrorStat.ArithAvg.ToString("E3", CultureInfo.InvariantCulture) +
(inArgs.TaskType == CommonEnums.TaskType.Classification ? "/" : string.Empty) +
(inArgs.TaskType == CommonEnums.TaskType.Classification ? bestReadoutUnit.TrainingBinErrorStat.TotalErrStat.Sum.ToString(CultureInfo.InvariantCulture) : string.Empty) +
(inArgs.TaskType == CommonEnums.TaskType.Classification ? "/" : string.Empty) +
(inArgs.TaskType == CommonEnums.TaskType.Classification ? bestReadoutUnit.TrainingBinErrorStat.BinValErrStat[1].Sum.ToString(CultureInfo.InvariantCulture) : string.Empty) +
", Best-Test: " + bestReadoutUnit.TestingErrorStat.ArithAvg.ToString("E3", CultureInfo.InvariantCulture) +
(inArgs.TaskType == CommonEnums.TaskType.Classification ? "/" : string.Empty) +
(inArgs.TaskType == CommonEnums.TaskType.Classification ? bestReadoutUnit.TestingBinErrorStat.TotalErrStat.Sum.ToString(CultureInfo.InvariantCulture) : string.Empty) +
(inArgs.TaskType == CommonEnums.TaskType.Classification ? "/" : string.Empty) +
(inArgs.TaskType == CommonEnums.TaskType.Classification ? bestReadoutUnit.TestingBinErrorStat.BinValErrStat[1].Sum.ToString(CultureInfo.InvariantCulture) : string.Empty) +
", Curr-Train: " + inArgs.CurrReadoutUnit.TrainingErrorStat.ArithAvg.ToString("E3", CultureInfo.InvariantCulture) +
(inArgs.TaskType == CommonEnums.TaskType.Classification ? "/" : string.Empty) +
(inArgs.TaskType == CommonEnums.TaskType.Classification ? inArgs.CurrReadoutUnit.TrainingBinErrorStat.TotalErrStat.Sum.ToString(CultureInfo.InvariantCulture) : string.Empty) +
(inArgs.TaskType == CommonEnums.TaskType.Classification ? "/" : string.Empty) +
(inArgs.TaskType == CommonEnums.TaskType.Classification ? inArgs.CurrReadoutUnit.TrainingBinErrorStat.BinValErrStat[1].Sum.ToString(CultureInfo.InvariantCulture) : string.Empty) +
", Curr-Test: " + inArgs.CurrReadoutUnit.TestingErrorStat.ArithAvg.ToString("E3", CultureInfo.InvariantCulture) +
(inArgs.TaskType == CommonEnums.TaskType.Classification ? "/" : string.Empty) +
(inArgs.TaskType == CommonEnums.TaskType.Classification ? inArgs.CurrReadoutUnit.TestingBinErrorStat.TotalErrStat.Sum.ToString(CultureInfo.InvariantCulture) : string.Empty) +
(inArgs.TaskType == CommonEnums.TaskType.Classification ? "/" : string.Empty) +
(inArgs.TaskType == CommonEnums.TaskType.Classification ? inArgs.CurrReadoutUnit.TestingBinErrorStat.BinValErrStat[1].Sum.ToString(CultureInfo.InvariantCulture) : string.Empty)
, !(inArgs.Epoch == 1 && inArgs.RegrAttemptNumber == 1));
}
return(outArgs);
}
