/// <summary>
/// Samples new hyperparameters for the trainer, and sets them.
/// Returns true if success (new hyperparameters were suggested and set). Else, returns false.
/// </summary>
private static bool SampleHyperparameters(MLContext context, SuggestedTrainer trainer, IEnumerable <SuggestedPipelineRunDetail> history, bool isMaximizingMetric)
{
var sps = ConvertToValueGenerators(trainer.SweepParams);
var sweeper = new SmacSweeper(context,
new SmacSweeper.Arguments
{
SweptParameters = sps
});
IEnumerable <SuggestedPipelineRunDetail> historyToUse = history
.Where(r => r.RunSucceeded && r.Pipeline.Trainer.TrainerName == trainer.TrainerName && r.Pipeline.Trainer.HyperParamSet != null && r.Pipeline.Trainer.HyperParamSet.Any());
// get new set of hyperparameter values
var proposedParamSet = sweeper.ProposeSweeps(1, historyToUse.Select(h => h.ToRunResult(isMaximizingMetric))).First();
if (!proposedParamSet.Any())
{
return(false);
}
// associate proposed parameter set with trainer, so that smart hyperparameter
// sweepers (like KDO) can map them back.
trainer.SetHyperparamValues(proposedParamSet);
return(true);
}
/// <summary>
/// Samples new hyperparameters for the trainer, and sets them.
/// Returns true if success (new hyperparameters were suggested and set). Else, returns false.
/// </summary>
private static bool SampleHyperparameters(MLContext context, SuggestedTrainer trainer,
IEnumerable <SuggestedPipelineRunDetail> history, bool isMaximizingMetric, IChannel logger)
{
try
{
var sps = ConvertToValueGenerators(trainer.SweepParams);
var sweeper = new SmacSweeper(context,
new SmacSweeper.Arguments
{
SweptParameters = sps
});
IEnumerable <SuggestedPipelineRunDetail> historyToUse = history
.Where(r => r.RunSucceeded && r.Pipeline.Trainer.TrainerName == trainer.TrainerName &&
r.Pipeline.Trainer.HyperParamSet != null &&
r.Pipeline.Trainer.HyperParamSet.Any() &&
FloatUtils.IsFinite(r.Score));
// get new set of hyperparameter values
var proposedParamSet = sweeper.ProposeSweeps(1, historyToUse.Select(h => h.ToRunResult(isMaximizingMetric))).FirstOrDefault();
if (!proposedParamSet.Any())
{
return(false);
}
// associate proposed parameter set with trainer, so that smart hyperparameter
// sweepers (like KDO) can map them back.
trainer.SetHyperparamValues(proposedParamSet);
return(true);
}
catch (Exception ex)
{
logger.Error($"SampleHyperparameters failed with exception: {ex}");
throw;
}
}
