public PipelinePattern[] GetNextCandidates(int numberOfCandidates)
{
if (_terminator.ShouldTerminate(_history))
{
return new PipelinePattern[] { }
}
;
var currentBatchSize = numberOfCandidates;
if (_terminator is IterationTerminator itr)
{
currentBatchSize = Math.Min(itr.RemainingIterations(_history), numberOfCandidates);
}
BatchCandidates = AutoMlEngine.GetNextCandidates(_sortedSampledElements.Select(kvp => kvp.Value), currentBatchSize, _dataRoles);
using (var ch = _host.Start("Suggested Pipeline"))
{
foreach (var pipeline in BatchCandidates)
{
ch.Info($"AutoInference Pipeline Id : {pipeline.UniqueId}");
foreach (var transform in pipeline.Transforms)
{
ch.Info($"AutoInference Transform : {transform.Transform}");
}
ch.Info($"AutoInference Learner : {pipeline.Learner}");
}
}
return(BatchCandidates);
}
public PipelinePattern[] GetNextCandidates(int numberOfCandidates)
{
if (_terminator.ShouldTerminate(_history))
{
return new PipelinePattern[] { }
}
;
var currentBatchSize = numberOfCandidates;
if (_terminator is IterationTerminator itr)
{
currentBatchSize = Math.Min(itr.RemainingIterations(_history), numberOfCandidates);
}
BatchCandidates = AutoMlEngine.GetNextCandidates(_sortedSampledElements.Select(kvp => kvp.Value), currentBatchSize);
return(BatchCandidates);
}
private void MainLearningLoop(int batchSize, int numOfTrainingRows)
{
var stopwatch = new Stopwatch();
var probabilityUtils = new Sweeper.Algorithms.SweeperProbabilityUtils(_host);
while (!_terminator.ShouldTerminate(_history))
{
// Get next set of candidates
var currentBatchSize = batchSize;
if (_terminator is IterationTerminator itr)
{
currentBatchSize = Math.Min(itr.RemainingIterations(_history), batchSize);
}
var candidates = AutoMlEngine.GetNextCandidates(_sortedSampledElements.Values, currentBatchSize);
// Break if no candidates returned, means no valid pipeline available.
if (candidates.Length == 0)
{
break;
}
// Evaluate them on subset of data
foreach (var candidate in candidates)
{
try
{
ProcessPipeline(probabilityUtils, stopwatch, candidate, numOfTrainingRows);
}
catch (Exception)
{
stopwatch.Stop();
return;
}
}
}
}