17 instantiations of ParameterSet
Microsoft.ML.AutoML (5)
Sweepers\ISweeper.cs (1)
141new ParameterSet(new Dictionary<string, IParameterValue>(_parameterValues), _hash);
Sweepers\Random.cs (1)
26return new ParameterSet(SweepParameters.Select(sweepParameter => sweepParameter.CreateFromNormalized(AutoMlUtils.Random.Value.NextDouble())));
Sweepers\SweeperProbabilityUtils.cs (1)
164return new ParameterSet(parameters);
TrainerExtensions\TrainerExtensionUtil.cs (2)
205return new ParameterSet(paramVals); 234return new ParameterSet(parameters);
Microsoft.ML.AutoML.Tests (9)
InferredPipelineTests.cs (3)
35var hyperparams1 = new ParameterSet(new List<IParameterValue>() { new LongParameterValue("NumberOfLeaves", 2) }); 43hyperparams1 = new ParameterSet(new List<IParameterValue>() { new LongParameterValue("NumberOfLeaves", 2) }); 44var hyperparams2 = new ParameterSet(new List<IParameterValue>() { new LongParameterValue("NumberOfLeaves", 6) });
SweeperTests.cs (6)
253var parameterSet = new ParameterSet(new[] { value1 }); 257var parameterSetNewHash = new ParameterSet(new IParameterValue[] { value1 }.ToDictionary(x => x.Name), hash: parameterSet.GetHashCode() + 1); 262var parameterSetMoreValues = new ParameterSet(new IParameterValue[] { value1, value2 }.ToDictionary(x => x.Name), hash: parameterSet.GetHashCode()); 267var parameterSetDifferentName = new ParameterSet(new IParameterValue[] { value2 }.ToDictionary(x => x.Name), hash: parameterSet.GetHashCode()); 272var parameterSetDifferentValue = new ParameterSet(new IParameterValue[] { stringValue1 }.ToDictionary(x => x.Name), hash: parameterSet.GetHashCode()); 277var parameterSetSameHash = new ParameterSet(new IParameterValue[] { value1 }.ToDictionary(x => x.Name), hash: parameterSet.GetHashCode());
Microsoft.ML.CodeGenerator.Tests (3)
ApprovalTests\ConsoleCodeGeneratorTests.cs (3)
602var hyperparams1 = new Microsoft.ML.AutoML.ParameterSet(new List<Microsoft.ML.AutoML.IParameterValue>() { new LongParameterValue("NumLeaves", 2) }); 639var hyperparams1 = new Microsoft.ML.AutoML.ParameterSet(new List<Microsoft.ML.AutoML.IParameterValue>() { new LongParameterValue("NumLeaves", 2) }); 1097var hyperparams1 = new Microsoft.ML.AutoML.ParameterSet(new List<Microsoft.ML.AutoML.IParameterValue>() { new LongParameterValue("NumLeaves", 2) });
84 references to ParameterSet
Microsoft.ML.AutoML (60)
Experiment\SuggestedPipeline.cs (1)
88var hyperParamSet = TrainerExtensionUtil.BuildParameterSet(trainerName, pipelineNode.Properties);
Experiment\SuggestedTrainer.cs (3)
15public ParameterSet HyperParamSet { get; set; } 23ParameterSet hyperParamSet = null) 33public void SetHyperparamValues(ParameterSet hyperParamSet)
PipelineSuggesters\PipelineSuggester.cs (1)
213var proposedParamSet = sweeper.ProposeSweeps(1, historyToUse.Select(h => h.ToRunResult(isMaximizingMetric))).FirstOrDefault();
Sweepers\ISweeper.cs (8)
24ParameterSet[] ProposeSweeps(int maxSweeps, IEnumerable<IRunResult> previousRuns = null); 78internal sealed class ParameterSet : IEquatable<ParameterSet>, IEnumerable<IParameterValue> 133public bool Equals(ParameterSet other) 140public ParameterSet Clone() => 162ParameterSet ParameterSet { get; } 178private readonly ParameterSet _parameterSet; 188public ParameterSet ParameterSet 193public RunResult(ParameterSet parameterSet, Double metricValue, bool isMetricMaximizing)
Sweepers\Random.cs (1)
24protected override ParameterSet CreateParamSet()
Sweepers\SmacSweeper.cs (34)
82public ParameterSet[] ProposeSweeps(int maxSweeps, IEnumerable<IRunResult> previousRuns = null) 151private ParameterSet[] GenerateCandidateConfigurations(int numOfCandidates, IEnumerable<IRunResult> previousRuns, FastForestRegressionModelParameters forest) 154ParameterSet[] bestKParamSets = GetKBestConfigurations(previousRuns, _args.LocalSearchParentCount); 157ParameterSet[] eiChallengers = GreedyPlusRandomSearch(bestKParamSets, forest, (int)Math.Ceiling(numOfCandidates / 2.0F), previousRuns); 160ParameterSet[] randomChallengers = _randomSweeper.ProposeSweeps(numOfCandidates - eiChallengers.Length, previousRuns); 164ParameterSet[] configs = new ParameterSet[eiChallengers.Length + randomChallengers.Length]; 179private ParameterSet[] GreedyPlusRandomSearch(ParameterSet[] parents, FastForestRegressionModelParameters forest, int numOfCandidates, IEnumerable<IRunResult> previousRuns) 185HashSet<Tuple<double, ParameterSet>> configurations = new HashSet<Tuple<double, ParameterSet>>(); 188foreach (ParameterSet c in parents) 190Tuple<double, ParameterSet> bestChildKvp = LocalSearch(c, forest, bestVal, _args.Epsilon, bestRun.IsMetricMaximizing); 195ParameterSet[] randomConfigs = _randomSweeper.ProposeSweeps(_args.NumRandomEISearchConfigurations, previousRuns); 200configurations.Add(new Tuple<double, ParameterSet>(randomEIs[i], randomConfigs[i])); 202IOrderedEnumerable<Tuple<double, ParameterSet>> bestConfigurations = configurations.OrderByDescending(x => x.Item1); 204var retainedConfigs = new HashSet<ParameterSet>(bestConfigurations.Select(x => x.Item2)); 224private Tuple<double, ParameterSet> LocalSearch(ParameterSet parent, FastForestRegressionModelParameters forest, double bestVal, double epsilon, bool isMetricMaximizing) 228double currentBestEI = EvaluateConfigurationsByEI(forest, bestVal, new ParameterSet[] { parent }, isMetricMaximizing)[0]; 229ParameterSet currentBestConfig = parent; 233ParameterSet[] neighborhood = GetOneMutationNeighborhood(currentBestConfig); 245return new Tuple<double, ParameterSet>(currentBestEI, currentBestConfig); 259private ParameterSet[] GetOneMutationNeighborhood(ParameterSet parent) 261List<ParameterSet> neighbors = new List<ParameterSet>(); 311ParameterSet neighbor = SweeperProbabilityUtils.FloatArrayAsParameterSet(_sweepParameters, neigh, false); 325private double[][] GetForestRegressionLeafValues(FastForestRegressionModelParameters forest, ParameterSet[] configs) 328foreach (ParameterSet config in configs) 380private double[] EvaluateConfigurationsByEI(FastForestRegressionModelParameters forest, double bestVal, ParameterSet[] configs, bool isMetricMaximizing) 387private ParameterSet[] GetKBestConfigurations(IEnumerable<IRunResult> previousRuns, int k = 10) 405List<ParameterSet> outSet = new List<ParameterSet>();
Sweepers\SweeperBase.cs (8)
49public virtual ParameterSet[] ProposeSweeps(int maxSweeps, IEnumerable<IRunResult> previousRuns = null) 51var prevParamSets = new HashSet<ParameterSet>(previousRuns?.Select(r => r.ParameterSet).ToList() ?? new List<ParameterSet>()); 52var result = new HashSet<ParameterSet>(); 55ParameterSet paramSet; 71protected abstract ParameterSet CreateParamSet(); 73protected static bool AlreadyGenerated(ParameterSet paramSet, ISet<ParameterSet> previousRuns)
Sweepers\SweeperProbabilityUtils.cs (2)
65public static float[] ParameterSetAsFloatArray(IValueGenerator[] sweepParams, ParameterSet ps, bool expandCategoricals = true) 125public static ParameterSet FloatArrayAsParameterSet(IValueGenerator[] sweepParams, float[] array, bool expandedCategoricals = true)
TrainerExtensions\TrainerExtensionUtil.cs (2)
193public static ParameterSet BuildParameterSet(TrainerName trainerName, IDictionary<string, object> props) 220private static ParameterSet BuildLightGbmParameterSet(IDictionary<string, object> props)
Microsoft.ML.AutoML.Tests (21)
InferredPipelineTests.cs (2)
35var hyperparams1 = new ParameterSet(new List<IParameterValue>() { new LongParameterValue("NumberOfLeaves", 2) }); 44var hyperparams2 = new ParameterSet(new List<IParameterValue>() { new LongParameterValue("NumberOfLeaves", 6) });
SweeperTests.cs (12)
56ParameterSet[] pars = sweeper.ProposeSweeps(1, results); 58foreach (ParameterSet p in pars) 104ParameterSet[] pars = sweeper.ProposeSweeps(1, results); 112foreach (ParameterSet p in pars) 156ParameterSet[] pars = sweeper.ProposeSweeps(1, results); 161foreach (ParameterSet p in pars) 253var parameterSet = new ParameterSet(new[] { value1 }); 257var parameterSetNewHash = new ParameterSet(new IParameterValue[] { value1 }.ToDictionary(x => x.Name), hash: parameterSet.GetHashCode() + 1); 262var parameterSetMoreValues = new ParameterSet(new IParameterValue[] { value1, value2 }.ToDictionary(x => x.Name), hash: parameterSet.GetHashCode()); 267var parameterSetDifferentName = new ParameterSet(new IParameterValue[] { value2 }.ToDictionary(x => x.Name), hash: parameterSet.GetHashCode()); 272var parameterSetDifferentValue = new ParameterSet(new IParameterValue[] { stringValue1 }.ToDictionary(x => x.Name), hash: parameterSet.GetHashCode()); 277var parameterSetSameHash = new ParameterSet(new IParameterValue[] { value1 }.ToDictionary(x => x.Name), hash: parameterSet.GetHashCode());
TrainerExtensionsTests.cs (7)
325var binaryParams = TrainerExtensionUtil.BuildParameterSet(TrainerName.LightGbmBinary, props); 326var multiParams = TrainerExtensionUtil.BuildParameterSet(TrainerName.LightGbmMulti, props); 327var regressionParams = TrainerExtensionUtil.BuildParameterSet(TrainerName.LightGbmRegression, props); 328var rankingParams = TrainerExtensionUtil.BuildParameterSet(TrainerName.LightGbmRanking, props); 330foreach (var paramSet in new ParameterSet[] { binaryParams, multiParams, regressionParams, rankingParams }) 348var sdcaParams = TrainerExtensionUtil.BuildParameterSet(TrainerName.SdcaLogisticRegressionBinary, props);
Microsoft.ML.CodeGenerator.Tests (3)
ApprovalTests\ConsoleCodeGeneratorTests.cs (3)
602var hyperparams1 = new Microsoft.ML.AutoML.ParameterSet(new List<Microsoft.ML.AutoML.IParameterValue>() { new LongParameterValue("NumLeaves", 2) }); 639var hyperparams1 = new Microsoft.ML.AutoML.ParameterSet(new List<Microsoft.ML.AutoML.IParameterValue>() { new LongParameterValue("NumLeaves", 2) }); 1097var hyperparams1 = new Microsoft.ML.AutoML.ParameterSet(new List<Microsoft.ML.AutoML.IParameterValue>() { new LongParameterValue("NumLeaves", 2) });