19 instantiations of SweepablePipeline
Microsoft.ML.AutoML (19)
API\AutoCatalog.cs (8)
403return new SweepablePipeline().Append(res.ToArray()); 526return new SweepablePipeline().Append(res.ToArray()); 618return new SweepablePipeline().Append(res.ToArray()); 634return new SweepablePipeline().Append(new[] { SweepableEstimatorFactory.CreateFeaturizeText(option) }); 653return new SweepablePipeline().Append(new[] { SweepableEstimatorFactory.CreateReplaceMissingValues(replaceMissingValueOption) }); 694return new SweepablePipeline().Append(new SweepableEstimator[] { SweepableEstimatorFactory.CreateOneHotEncoding(option), SweepableEstimatorFactory.CreateOneHotHashEncoding(option) }); 727var pipeline = new SweepablePipeline(); 834var pipeline = new SweepablePipeline();
API\MulticlassClassificationExperiment.cs (1)
323SweepablePipeline pipeline = new SweepablePipeline();
API\RegressionExperiment.cs (1)
305SweepablePipeline pipeline = new SweepablePipeline();
API\SweepableExtension.cs (6)
11return new SweepablePipeline().Append(estimator).Append(estimator1); 21return new SweepablePipeline().Append(estimator).Append(estimator1); 26return new SweepablePipeline().Append(estimator).Append(estimator1); 32var res = new SweepablePipeline().Append(sweepableEstimator).Append(pipeline); 39var pipeline = new SweepablePipeline(); 48var pipeline = new SweepablePipeline().Append(sweepableEstimator).Append(estimators);
SweepableEstimator\Converter\SweepablePipelineConverter.cs (1)
22return new SweepablePipeline(estimators, Entity.FromExpression(schema), currentSchema);
SweepableEstimator\SweepablePipeline.cs (2)
114return new SweepablePipeline(pipelineNodes, entity, schema); 191return new SweepablePipeline(estimators, schema);
130 references to SweepablePipeline
Microsoft.ML.AutoML (83)
API\AutoCatalog.cs (14)
337public SweepablePipeline BinaryClassification(string labelColumnName = DefaultColumnNames.Label, 434public SweepablePipeline MultiClassification( 551public SweepablePipeline Regression( 626internal SweepablePipeline TextFeaturizer(string outputColumnName, string inputColumnName) 638/// Create a <see cref="SweepablePipeline"/> for featurizing numeric columns. 642internal SweepablePipeline NumericFeaturizer(string[] outputColumnNames, string[] inputColumnNames) 657/// Create a <see cref="SweepablePipeline"/> for featurizing boolean columns. This pipeline convert all boolean column 684internal SweepablePipeline CatalogFeaturizer(string[] outputColumnNames, string[] inputColumnNames) 697internal SweepablePipeline ImagePathFeaturizer(string outputColumnName, string inputColumnName) 727var pipeline = new SweepablePipeline(); 747public SweepablePipeline Featurizer(IDataView data, string outputColumnName = "Features", string[] catelogicalColumns = null, string[] numericColumns = null, string[] textColumns = null, string[] imagePathColumns = null, string[] excludeColumns = null) 814/// <returns>A <see cref="SweepablePipeline"/> for featurization.</returns> 815public SweepablePipeline Featurizer(IDataView data, ColumnInformation columnInformation, string outputColumnName = "Features") 834var pipeline = new SweepablePipeline();
API\AutoMLExperimentExtension.cs (3)
139/// <param name="pipeline"><see cref="SweepablePipeline"/></param> 141public static AutoMLExperiment SetPipeline(this AutoMLExperiment experiment, SweepablePipeline pipeline) 338/// set <see cref="EciCostFrugalTuner"/> as tuner for hyper-parameter optimization. This tuner only works with search space from <see cref="SweepablePipeline"/>.
API\BinaryClassificationExperiment.cs (10)
145private SweepablePipeline _pipeline; 194var pipeline = provider.GetService<SweepablePipeline>(); 227var pipeline = provider.GetService<SweepablePipeline>(); 281var pipeline = provider.GetService<SweepablePipeline>(); 324private SweepablePipeline CreateBinaryClassificationPipeline(IDataView trainData, ColumnInformation columnInformation, IEstimator<ITransformer> preFeaturizer = null) 362private readonly SweepablePipeline _pipeline; 364public BinaryClassificationRunner(IMLContextManager contextManager, IDatasetManager datasetManager, IMetricManager metricManager, SweepablePipeline pipeline, AutoMLExperiment.AutoMLExperimentSettings settings)
API\MulticlassClassificationExperiment.cs (11)
129private SweepablePipeline _pipeline; 179var pipeline = provider.GetService<SweepablePipeline>(); 214var pipeline = provider.GetService<SweepablePipeline>(); 271var pipeline = provider.GetService<SweepablePipeline>(); 314private SweepablePipeline CreateMulticlassClassificationPipeline(IDataView trainData, ColumnInformation columnInformation, IEstimator<ITransformer> preFeaturizer = null) 323SweepablePipeline pipeline = new SweepablePipeline(); 347private readonly SweepablePipeline _pipeline; 350public MulticlassClassificationRunner(IMLContextManager contextManager, IDatasetManager datasetManager, IMetricManager metricManager, SweepablePipeline pipeline, AutoMLExperiment.AutoMLExperimentSettings settings)
API\RegressionExperiment.cs (11)
124private SweepablePipeline _pipeline; 167var pipeline = provider.GetService<SweepablePipeline>(); 208var pipeline = provider.GetService<SweepablePipeline>(); 264var pipeline = provider.GetService<SweepablePipeline>(); 297private SweepablePipeline CreateRegressionPipeline(IDataView trainData, ColumnInformation columnInformation, IEstimator<ITransformer> preFeaturizer = null) 305SweepablePipeline pipeline = new SweepablePipeline(); 367private readonly SweepablePipeline _pipeline; 370public RegressionTrialRunner(IMLContextManager contextManager, IDatasetManager datasetManager, IMetricManager metricManager, SweepablePipeline pipeline, AutoMLExperiment.AutoMLExperimentSettings settings)
API\SweepableExtension.cs (13)
9public static SweepablePipeline Append(this IEstimator<ITransformer> estimator, SweepableEstimator estimator1) 14public static SweepablePipeline Append(this SweepablePipeline pipeline, IEstimator<ITransformer> estimator) 19public static SweepablePipeline Append(this SweepableEstimator estimator, SweepablePipeline estimator1) 24public static SweepablePipeline Append(this SweepableEstimator estimator, IEstimator<ITransformer> estimator1) 29public static SweepablePipeline Append(this IEstimator<ITransformer> estimator, SweepablePipeline pipeline) 32var res = new SweepablePipeline().Append(sweepableEstimator).Append(pipeline); 37public static SweepablePipeline Append(this SweepableEstimator estimator, params SweepableEstimator[] estimators) 39var pipeline = new SweepablePipeline(); 45public static SweepablePipeline Append(this IEstimator<ITransformer> estimator, params SweepableEstimator[] estimators) 48var pipeline = new SweepablePipeline().Append(sweepableEstimator).Append(estimators);
AutoMLExperiment\IMonitor.cs (3)
32private readonly SweepablePipeline _pipeline; 34public MLContextMonitor(IChannel logger, SweepablePipeline pipeline) 74public TrialResultMonitor(IChannel channel, SweepablePipeline pipeline)
AutoMLExperiment\Runner\SweepablePipelineRunner.cs (2)
23private readonly SweepablePipeline _pipeline; 26public SweepablePipelineRunner(MLContext context, SweepablePipeline pipeline, IEvaluateMetricManager metricManager, IDatasetManager datasetManager, IChannel? logger = null)
SweepableEstimator\Converter\SweepablePipelineConverter.cs (3)
13internal class SweepablePipelineConverter : JsonConverter<SweepablePipeline> 15public override SweepablePipeline Read(ref Utf8JsonReader reader, Type typeToConvert, JsonSerializerOptions options) 25public override void Write(Utf8JsonWriter writer, SweepablePipeline value, JsonSerializerOptions options)
SweepableEstimator\SweepablePipeline.cs (4)
107public SweepablePipeline BuildSweepableEstimatorPipeline(string schema) 117public SweepablePipeline Append(params ISweepable<IEstimator<ITransformer>>[] sweepables) 134else if (sweepable is SweepablePipeline pipeline) 172private SweepablePipeline AppendEntity(bool allowSkip, Entity entity)
Tuner\AutoZeroTuner.cs (3)
23private readonly SweepablePipeline _sweepablePipeline; 27public AutoZeroTuner(SweepablePipeline pipeline, AggregateTrainingStopManager aggregateTrainingStopManager, IEvaluateMetricManager evaluateMetricManager, AutoMLExperiment.AutoMLExperimentSettings settings) 96var pipeline = _sweepablePipeline.BuildSweepableEstimatorPipeline(pipelineSchema);
Tuner\EciCfoTuner.cs (1)
26public EciCostFrugalTuner(SweepablePipeline sweepablePipeline, AutoMLExperiment.AutoMLExperimentSettings settings, ITrialResultManager trialResultManager = null)
Tuner\PipelineProposer.cs (3)
42private readonly SweepablePipeline _sweepablePipeline; 46public PipelineProposer(SweepablePipeline sweepablePipeline, AutoMLExperimentSettings settings) 196private double GetEstimatedCostForPipeline(string schema, SweepablePipeline pipeline)
Utils\BestResultUtil.cs (2)
99public static RunDetail<TMetrics> ToRunDetail<TMetrics>(MLContext context, TrialResult<TMetrics> result, SweepablePipeline pipeline) 111public static CrossValidationRunDetail<TMetrics> ToCrossValidationRunDetail<TMetrics>(MLContext context, TrialResult<TMetrics> result, SweepablePipeline pipeline)
Microsoft.ML.AutoML.Interactive (2)
NotebookMonitor.cs (2)
20public SweepablePipeline SweepablePipeline { get; private set; } 27public NotebookMonitor(SweepablePipeline pipeline)
Microsoft.ML.AutoML.Samples (3)
AutoMLExperiment.cs (1)
29var pipeline = context.Auto().BinaryClassification(labelColumnName: "Label", featureColumnName: "Features");
Cifar10.cs (1)
38var pipeline = context.Auto().Featurizer(trainDataset)
Sweepable\SweepableLightGBMBinaryExperiment.cs (1)
55var pipeline = new EstimatorChain<ITransformer>().Append(lgbm);
Microsoft.ML.AutoML.Tests (35)
AutoFeaturizerTests.cs (6)
48var pipeline = context.Auto().Featurizer(dataset, outputColumnName: "OutputFeature", excludeColumns: new[] { "Label" }); 60var pipeline = context.Auto().Featurizer(dataset, excludeColumns: new[] { "Label" }); 72var pipeline = context.Auto().Featurizer(dataset, excludeColumns: new[] { DatasetUtil.NewspaperChurnLabel }); 85var pipeline = context.Auto().Featurizer(dataset, excludeColumns: new[] { "A16" }); 95var pipeline = context.Auto().ImagePathFeaturizer("imagePath", "imagePath"); 111var pipeline = context.Auto().Featurizer(trainData, columnInference.ColumnInformation);
AutoMLExperimentTests.cs (9)
105var pipeline = context.Auto().Featurizer(data, "_Features_", excludeColumns: new[] { DatasetUtil.UciAdultLabel }) 222var pipeline = context.Auto().Featurizer(data, "_Features_", excludeColumns: new[] { DatasetUtil.UciAdultLabel }) 247var pipeline = context.Auto().Featurizer(data, "_Features_", excludeColumns: new[] { DatasetUtil.UciAdultLabel }) 272var pipeline = context.Auto().Featurizer(data, "_Features_", excludeColumns: new[] { DatasetUtil.UciAdultLabel }) 298var pipeline = context.Auto().Featurizer(data, excludeColumns: new[] { label }) 325var pipeline = context.Auto().Featurizer(data, excludeColumns: new[] { label }) 353var pipeline = context.Auto().Featurizer(train, excludeColumns: new[] { label }) 383var pipeline = context.Auto().Featurizer(train, excludeColumns: new[] { label }) 402var pipeline = context.Auto().Featurizer(train, excludeColumns: new[] { label })
SweepableExtensionTest.cs (16)
51var pipeline = estimator.Append(SweepableEstimatorFactory.CreateFastForestBinary(new FastForestOption())); 53pipeline.Should().BeOfType<SweepablePipeline>(); 60var pipeline = estimator.Append(estimator); 62pipeline.Should().BeOfType<SweepablePipeline>(); 70var pipeline = estimator.Append(context.Transforms.Concatenate("output", "input")); 72pipeline.Should().BeOfType<SweepablePipeline>(); 81SweepablePipeline pipeline = context.Transforms.Concatenate("output", "input") 94SweepablePipeline pipeline = context.Transforms.Concatenate("output", "input") 107SweepablePipeline pipeline = context.Transforms.Concatenate("output", "input") 120var pipeline = SweepableEstimatorFactory.CreateFastForestBinary(new FastForestOption()) 133SweepablePipeline pipeline = context.Transforms.Concatenate("output", "input") 147SweepablePipeline pipeline = context.Transforms.Concatenate("output", "input") 161SweepablePipeline pipeline = SweepableEstimatorFactory.CreateFeaturizeText(new FeaturizeTextOption()) 174SweepablePipeline pipeline = context.Transforms.Concatenate("output", "input") 188var pipeline = estimator.Append(SweepableEstimatorFactory.CreateFastForestBinary(new FastForestOption()), SweepableEstimatorFactory.CreateFastForestBinary(new FastForestOption())); 191pipeline.Should().BeOfType<SweepablePipeline>();
SweepablePipelineTests.cs (1)
46var pipeline = new SweepablePipeline();
TunerTests.cs (3)
168var pipeline = this.CreateDummySweepablePipeline(context); 203var pipeline = this.CreateDummySweepablePipeline(context); 453private SweepablePipeline CreateDummySweepablePipeline(MLContext context)
Microsoft.ML.Fairlearn (6)
AutoML\AutoMLExperimentExtension.cs (2)
78var pipeline = serviceProvider.GetRequiredService<SweepablePipeline>();
AutoML\TunerFactory.cs (2)
21private readonly SweepablePipeline _pipeline; 31_pipeline = provider.GetRequiredService<SweepablePipeline>();
Reductions\GridSearchTrialRunner.cs (2)
32private readonly SweepablePipeline _pipeline; 36public GridSearchTrailRunner(MLContext context, ITrainValidateDatasetManager datasetManager, string labelColumn, string sensitiveColumn, SweepablePipeline pipeline, ClassificationMoment moment)
Microsoft.ML.Fairlearn.Tests (1)
GridSearchTest.cs (1)
95var pipeline = context.Transforms.Categorical.OneHotHashEncoding("sensitiveFeature_encode", "sensitiveFeature")