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