public static List <Sweep> GenerateCandidates(IHostEnvironment env, string dataFile, string schemaDefinitionFile)
{
var patterns = new List <Sweep>();
string loaderSettings;
Type predictorType;
TransformInference.InferenceResult inferenceResult;
// Get the initial recipes for this data.
RecipeInference.SuggestedRecipe[] recipes = RecipeInference.InferRecipesFromData(env, dataFile, schemaDefinitionFile, out predictorType, out loaderSettings, out inferenceResult);
//get all the trainers for this task, and generate the initial set of candidates.
// Exclude the hidden learners, and the metalinear learners.
var trainers = env.ComponentCatalog.GetAllDerivedClasses(typeof(ITrainer), predictorType).Where(cls => !cls.IsHidden);
if (!string.IsNullOrEmpty(loaderSettings))
{
StringBuilder sb = new StringBuilder();
CmdQuoter.QuoteValue(loaderSettings, sb, true);
loaderSettings = sb.ToString();
}
string loader = $" loader=TextLoader{loaderSettings}";
// REVIEW: there are more learners than recipes atm.
// Flip looping through recipes, then through learners if the cardinality changes.
foreach (ComponentCatalog.LoadableClassInfo cl in trainers)
{
string learnerSettings;
TrainerSweeper trainerSweeper = new TrainerSweeper();
trainerSweeper.Parameters.AddRange(RecipeInference.GetLearnerSettingsAndSweepParams(env, cl, out learnerSettings));
foreach (var recipe in recipes)
{
RecipeInference.SuggestedRecipe.SuggestedLearner learner = new RecipeInference.SuggestedRecipe.SuggestedLearner
{
LoadableClassInfo = cl,
Settings = learnerSettings
};
Pattern pattern = new Pattern(recipe.Transforms, learner, loader);
Sweep sweep = new Sweep(pattern, trainerSweeper);
patterns.Add(sweep);
}
}
return(patterns);
}
internal Sweep(Pattern pattern, TrainerSweeper trainerSweeper)
{
Pattern = pattern;
TrainerSweeper = trainerSweeper;
}
