public static SuggestedPipeline FromPipeline(MLContext context, Pipeline pipeline)
{
var transforms = new List <SuggestedTransform>();
var transformsPostTrainer = new List <SuggestedTransform>();
SuggestedTrainer trainer = null;
var trainerEncountered = false;
foreach (var pipelineNode in pipeline.Nodes)
{
if (pipelineNode.NodeType == PipelineNodeType.Trainer)
{
var trainerName = (TrainerName)Enum.Parse(typeof(TrainerName), pipelineNode.Name);
var trainerExtension = TrainerExtensionCatalog.GetTrainerExtension(trainerName);
var hyperParamSet = TrainerExtensionUtil.BuildParameterSet(trainerName, pipelineNode.Properties);
var columnInfo = TrainerExtensionUtil.BuildColumnInfo(pipelineNode.Properties);
trainer = new SuggestedTrainer(context, trainerExtension, columnInfo, hyperParamSet);
trainerEncountered = true;
}
else if (pipelineNode.NodeType == PipelineNodeType.Transform)
{
var estimatorName = (EstimatorName)Enum.Parse(typeof(EstimatorName), pipelineNode.Name);
var estimatorExtension = EstimatorExtensionCatalog.GetExtension(estimatorName);
var estimator = estimatorExtension.CreateInstance(context, pipelineNode);
var transform = new SuggestedTransform(pipelineNode, estimator);
if (!trainerEncountered)
{
transforms.Add(transform);
}
else
{
transformsPostTrainer.Add(transform);
}
}
}
return(new SuggestedPipeline(transforms, transformsPostTrainer, trainer, context, pipeline.CacheBeforeTrainer));
}