public PipelineNode CreatePipelineNode(IEnumerable <SweepableParam> sweepParams, ColumnInformation columnInfo)
{
var property = new Dictionary <string, object>();
property.Add(nameof(MatrixFactorizationTrainer.Options.MatrixColumnIndexColumnName), columnInfo.UserIdColumnName);
property.Add(nameof(MatrixFactorizationTrainer.Options.MatrixRowIndexColumnName), columnInfo.ItemIdColumnName);
return(TrainerExtensionUtil.BuildPipelineNode(TrainerExtensionCatalog.GetTrainerName(this), sweepParams, columnInfo.LabelColumnName, additionalProperties: property));
}
public PipelineNode CreatePipelineNode(IEnumerable <SweepableParam> sweepParams, ColumnInformation columnInfo)
{
var property = new Dictionary <string, object>();
property.Add(nameof(FastTreeRankingTrainer.Options.RowGroupColumnName), columnInfo.GroupIdColumnName);
return(TrainerExtensionUtil.BuildPipelineNode(TrainerExtensionCatalog.GetTrainerName(this), sweepParams,
columnInfo.LabelColumnName, additionalProperties: property));
}
internal SuggestedTrainer(MLContext mlContext, ITrainerExtension trainerExtension,
ColumnInformation columnInfo,
ParameterSet hyperParamSet = null)
{
_mlContext = mlContext;
_trainerExtension = trainerExtension;
_columnInfo = columnInfo;
SweepParams = _trainerExtension.GetHyperparamSweepRanges();
TrainerName = TrainerExtensionCatalog.GetTrainerName(_trainerExtension);
SetHyperparamValues(hyperParamSet);
}
/// <summary>
/// Given a predictor type, return a set of all permissible trainers (with their sweeper params, if defined).
/// </summary>
/// <returns>Array of viable learners.</returns>
public static IEnumerable <SuggestedTrainer> AllowedTrainers(MLContext mlContext, TaskKind task,
ColumnInformation columnInfo, IEnumerable <TrainerName> trainerWhitelist)
{
var trainerExtensions = TrainerExtensionCatalog.GetTrainers(task, trainerWhitelist, columnInfo);
var trainers = new List <SuggestedTrainer>();
foreach (var trainerExtension in trainerExtensions)
{
var learner = new SuggestedTrainer(mlContext, trainerExtension, columnInfo);
trainers.Add(learner);
}
return(trainers.ToArray());
}
public PipelineNode CreatePipelineNode(IEnumerable <SweepableParam> sweepParams, ColumnInformation columnInfo)
{
Dictionary <string, object> additionalProperties = null;
if (sweepParams == null || !sweepParams.Any(p => p.Name != "NumberOfIterations"))
{
additionalProperties = new Dictionary <string, object>()
{
{ "NumberOfIterations", DefaultNumIterations }
};
}
return(TrainerExtensionUtil.BuildPipelineNode(TrainerExtensionCatalog.GetTrainerName(this), sweepParams,
columnInfo.LabelColumnName, additionalProperties: additionalProperties));
}
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));
}
public PipelineNode CreatePipelineNode(IEnumerable <SweepableParam> sweepParams, ColumnInformation columnInfo)
{
return(TrainerExtensionUtil.BuildLightGbmPipelineNode(TrainerExtensionCatalog.GetTrainerName(this), sweepParams,
columnInfo.LabelColumnName, columnInfo.ExampleWeightColumnName, columnInfo.GroupIdColumnName));
}
public PipelineNode CreatePipelineNode(IEnumerable <SweepableParam> sweepParams, ColumnInformation columnInfo)
{
return(TrainerExtensionUtil.BuildPipelineNode(TrainerExtensionCatalog.GetTrainerName(this), sweepParams,
columnInfo.LabelColumnName, null));
}
