107 references to PipelineNodeType
Microsoft.ML.AutoML (23)
API\Pipeline.cs (4)
35public PipelineNodeType NodeType { get; set; } 40public PipelineNode(string name, PipelineNodeType nodeType, 51public PipelineNode(string name, PipelineNodeType nodeType, 57public PipelineNode(string name, PipelineNodeType nodeType,
EstimatorExtensions\EstimatorExtensions.cs (14)
19PipelineNodeType.Transform, inColumns, outColumn); 40PipelineNodeType.Transform, inColumn, outColumn); 61PipelineNodeType.Transform, inColumn, outColumn); 82PipelineNodeType.Transform, inColumn, outColumn); 103PipelineNodeType.Transform, inColumns, outColumns); 130PipelineNodeType.Transform, inColumns, outColumns); 157PipelineNodeType.Transform, inColumn, outColumn); 178PipelineNodeType.Transform, inColumns, outColumns); 209PipelineNodeType.Transform, inColumns, outColumns); 235PipelineNodeType.Transform, inColumn, outColumn); 256PipelineNodeType.Transform, inColumns, outColumns); 282PipelineNodeType.Transform, inColumn, outColumn); 308var pipelineNode = new PipelineNode(EstimatorName.RawByteImageLoading.ToString(), PipelineNodeType.Transform, inColumn, outColumn, pipelineNodeProperty); 333var pipelineNode = new PipelineNode(EstimatorName.ImageLoading.ToString(), PipelineNodeType.Transform, inColumn, outColumn, pipelineNodeProperty);
Experiment\SuggestedPipeline.cs (2)
84if (pipelineNode.NodeType == PipelineNodeType.Trainer) 93else if (pipelineNode.NodeType == PipelineNodeType.Transform)
TrainerExtensions\TrainerExtensionUtil.cs (3)
106NodeType = PipelineNodeType.Trainer, 130return new PipelineNode(trainerName.ToString(), PipelineNodeType.Trainer, DefaultColumnNames.Features, 137return new PipelineNode(trainerName.ToString(), PipelineNodeType.Trainer, DefaultColumnNames.Features,
Microsoft.ML.CodeGenerator (11)
CodeGenerator\CSharp\CodeGenerator.cs (6)
46var trainerNodes = _pipeline.Nodes.Where(t => t.NodeType == PipelineNodeType.Trainer); 204var nodes = _pipeline.Nodes.TakeWhile(t => t.NodeType == PipelineNodeType.Transform); 208nodes = _pipeline.Nodes.SkipWhile(t => t.NodeType == PipelineNodeType.Transform) 209.SkipWhile(t => t.NodeType == PipelineNodeType.Trainer) //skip the trainer 210.TakeWhile(t => t.NodeType == PipelineNodeType.Transform); //post trainer transforms 256var node = _pipeline.Nodes.Where(t => t.NodeType == PipelineNodeType.Trainer).First();
CodeGenerator\CSharp\PipelineExtension.cs (5)
22var nodes = pipeline.Nodes.TakeWhile(t => t.NodeType == PipelineNodeType.Transform); 26nodes = pipeline.Nodes.SkipWhile(t => t.NodeType == PipelineNodeType.Transform) 27.SkipWhile(t => t.NodeType == PipelineNodeType.Trainer) //skip the trainer 28.TakeWhile(t => t.NodeType == PipelineNodeType.Transform); //post trainer transforms 76var node = pipeline.Nodes.Where(t => t.NodeType == PipelineNodeType.Trainer).First();
Microsoft.ML.CodeGenerator.Tests (73)
ApprovalTests\ConsoleCodeGeneratorTests.cs (15)
558var valueToKeyPipelineNode1 = new PipelineNode(nameof(EstimatorName.ValueToKeyMapping), PipelineNodeType.Transform, "userId", "userId"); 559var valueToKeyPipelineNode2 = new PipelineNode(nameof(EstimatorName.ValueToKeyMapping), PipelineNodeType.Transform, "movieId", "movieId"); 560var matrixPipelineNode = new PipelineNode(nameof(TrainerName.MatrixFactorization), PipelineNodeType.Trainer, "Features", "Score", hyperParam); 674PipelineNodeType.Transform, 678var loadImageNode = new PipelineNode(EstimatorName.ImageLoading.ToString(), PipelineNodeType.Transform, "ImagePath", "input"); 681PipelineNodeType.Transform, 689var extractPixelsNode = new PipelineNode(nameof(SpecialTransformer.ExtractPixel), PipelineNodeType.Transform, "input", "input"); 728var hashPipelineNode = new PipelineNode(nameof(EstimatorName.Hashing), PipelineNodeType.Transform, "GroupId", "GroupId"); 729var lightGbmPipelineNode = new PipelineNode(nameof(TrainerName.LightGbmRanking), PipelineNodeType.Trainer, "Features", "Score", hyperParam); 765var onnxPipeLineNode = new PipelineNode(nameof(SpecialTransformer.ApplyOnnxModel), PipelineNodeType.Transform, string.Empty, string.Empty); 766var loadImageNode = new PipelineNode(EstimatorName.ImageLoading.ToString(), PipelineNodeType.Transform, "ImageSource", "ImageSource_featurized"); 769PipelineNodeType.Transform, 777var extractPixelsNode = new PipelineNode(nameof(SpecialTransformer.ExtractPixel), PipelineNodeType.Transform, "ImageSource_featurized", "input1"); 811var onnxPipeLineNode = new PipelineNode(nameof(SpecialTransformer.ApplyOnnxModel), PipelineNodeType.Transform, string.Empty, string.Empty); 981var onnxPipeLineNode = new PipelineNode(nameof(SpecialTransformer.ApplyOnnxModel), PipelineNodeType.Transform, new[] { "input.1" }, new[] { "output.1" },
CodeGenTests.cs (5)
33PipelineNode node = new PipelineNode("LightGbmBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 54PipelineNode node = new PipelineNode("LightGbmBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 69PipelineNode node = new PipelineNode("Normalizing", PipelineNodeType.Transform, new string[] { "Label" }, new string[] { "Label" }, elementProperties); 83PipelineNode node = new PipelineNode("OneHotEncoding", PipelineNodeType.Transform, new string[] { "Label" }, new string[] { "Label" }, elementProperties); 127PipelineNode node = new PipelineNode("LightGbmBinary", PipelineNodeType.Trainer, new string[] { "Label" }, default(string), elementProperties);
TrainerGeneratorTests.cs (40)
35PipelineNode node = new PipelineNode("LightGbmBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 63PipelineNode node = new PipelineNode("LightGbmBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 85PipelineNode node = new PipelineNode("LightGbmBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 103PipelineNode node = new PipelineNode("SymbolicSgdLogisticRegressionBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 123PipelineNode node = new PipelineNode("SymbolicSgdLogisticRegressionBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 140PipelineNode node = new PipelineNode("SgdCalibratedBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 160PipelineNode node = new PipelineNode("SgdCalibratedBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 177PipelineNode node = new PipelineNode("SdcaLogisticRegressionBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 197PipelineNode node = new PipelineNode("SdcaLogisticRegressionBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 214PipelineNode node = new PipelineNode("SdcaMaximumEntropyMulti", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 234PipelineNode node = new PipelineNode("SdcaMaximumEntropyMulti", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 251PipelineNode node = new PipelineNode("SdcaRegression", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 271PipelineNode node = new PipelineNode("SdcaRegression", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 287PipelineNode node = new PipelineNode("MatrixFactorization", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 313PipelineNode node = new PipelineNode("MatrixFactorization", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 328PipelineNode node = new PipelineNode("LbfgsPoissonRegression", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 348PipelineNode node = new PipelineNode("LbfgsPoissonRegression", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 365PipelineNode node = new PipelineNode("OlsRegression", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 385PipelineNode node = new PipelineNode("OlsRegression", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 402PipelineNode node = new PipelineNode("OnlineGradientDescentRegression", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 422PipelineNode node = new PipelineNode("OnlineGradientDescentRegression", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 439PipelineNode node = new PipelineNode("LbfgsLogisticRegressionBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 459PipelineNode node = new PipelineNode("LbfgsLogisticRegressionBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 476PipelineNode node = new PipelineNode("LbfgsMaximumEntropyMulti", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 496PipelineNode node = new PipelineNode("LbfgsMaximumEntropyMulti", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 513PipelineNode node = new PipelineNode("LinearSvmBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 533PipelineNode node = new PipelineNode("LinearSvmBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 551PipelineNode node = new PipelineNode("FastTreeTweedieRegression", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 571PipelineNode node = new PipelineNode("OnlineGradientDescentRegression", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 589PipelineNode node = new PipelineNode("FastTreeRegression", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 609PipelineNode node = new PipelineNode("FastTreeRegression", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 627PipelineNode node = new PipelineNode("FastTreeBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 647PipelineNode node = new PipelineNode("FastTreeBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 665PipelineNode node = new PipelineNode("FastForestRegression", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 684PipelineNode node = new PipelineNode("FastForestRegression", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 702PipelineNode node = new PipelineNode("FastForestBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 722PipelineNode node = new PipelineNode("FastForestBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 740PipelineNode node = new PipelineNode("AveragedPerceptronBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 760PipelineNode node = new PipelineNode("AveragedPerceptronBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties); 775PipelineNode node = new PipelineNode("ImageClassification", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties);
TransformGeneratorTests.cs (13)
26PipelineNode node = new PipelineNode("MissingValueReplacing", PipelineNodeType.Transform, new string[] { "categorical_column_1" }, new string[] { "categorical_column_1" }, elementProperties); 40PipelineNode node = new PipelineNode("OneHotEncoding", PipelineNodeType.Transform, new string[] { "categorical_column_1" }, new string[] { "categorical_column_1" }, elementProperties); 54PipelineNode node = new PipelineNode("Normalizing", PipelineNodeType.Transform, new string[] { "numeric_column_1" }, new string[] { "numeric_column_1_copy" }, elementProperties); 68PipelineNode node = new PipelineNode("ColumnConcatenating", PipelineNodeType.Transform, new string[] { "numeric_column_1", "numeric_column_2" }, new string[] { "Features" }, elementProperties); 82PipelineNode node = new PipelineNode("ColumnCopying", PipelineNodeType.Transform, new string[] { "numeric_column_1" }, new string[] { "numeric_column_2" }, elementProperties); 96PipelineNode node = new PipelineNode("KeyToValueMapping", PipelineNodeType.Transform, new string[] { "Label" }, new string[] { "Label" }, elementProperties); 110PipelineNode node = new PipelineNode("MissingValueIndicating", PipelineNodeType.Transform, new string[] { "numeric_column_1" }, new string[] { "numeric_column_1" }, elementProperties); 124PipelineNode node = new PipelineNode("OneHotHashEncoding", PipelineNodeType.Transform, new string[] { "Categorical_column_1" }, new string[] { "Categorical_column_1" }, elementProperties); 138PipelineNode node = new PipelineNode("TextFeaturizing", PipelineNodeType.Transform, new string[] { "Text_column_1" }, new string[] { "Text_column_1" }, elementProperties); 152PipelineNode node = new PipelineNode("TypeConverting", PipelineNodeType.Transform, new string[] { "I4_column_1" }, new string[] { "R4_column_1" }, elementProperties); 166PipelineNode node = new PipelineNode("ValueToKeyMapping", PipelineNodeType.Transform, new string[] { "Label" }, new string[] { "Label" }, elementProperties); 178PipelineNode node = new PipelineNode("ImageLoading", PipelineNodeType.Transform, 192PipelineNode node = new PipelineNode("RawByteImageLoading", PipelineNodeType.Transform,