23 instantiations of EstimatorChain
Microsoft.ML.AutoML (3)
Experiment\SuggestedPipeline.cs (1)
116
IEstimator<ITransformer> pipeline = new
EstimatorChain
<ITransformer>();
SweepableEstimator\SweepableEstimatorPipeline.cs (1)
78
var pipeline = new
EstimatorChain
<ITransformer>();
SweepableEstimator\SweepablePipeline.cs (1)
87
var pipeline = new
EstimatorChain
<ITransformer>();
Microsoft.ML.AutoML.Samples (1)
Sweepable\SweepableLightGBMBinaryExperiment.cs (1)
55
var pipeline = new
EstimatorChain
<ITransformer>().Append(lgbm);
Microsoft.ML.Data (5)
DataLoadSave\CompositeLoaderEstimator.cs (1)
24
_estimatorChain = estimatorChain ?? new
EstimatorChain
<TLastTransformer>();
DataLoadSave\EstimatorChain.cs (2)
95
return new
EstimatorChain
<TNewTrans>(_host, _estimators.AppendElement(estimator), _scopes.AppendElement(scope), _needCacheAfter.AppendElement(false));
123
return new
EstimatorChain
<TLastTransformer>(env, _estimators, _scopes, newNeedCache);
DataLoadSave\EstimatorExtensions.cs (2)
57
return new
EstimatorChain
<ITransformer>().Append(start).Append(estimator, scope);
71
return new
EstimatorChain
<ITransformer>().Append(start).AppendCacheCheckpoint(env);
Microsoft.ML.DnnImageFeaturizer.AlexNet (1)
AlexNetExtension.cs (1)
39
var modelChain = new
EstimatorChain
<ColumnCopyingTransformer>();
Microsoft.ML.DnnImageFeaturizer.ResNet101 (1)
ResNet101Extension.cs (1)
39
var modelChain = new
EstimatorChain
<ColumnCopyingTransformer>();
Microsoft.ML.DnnImageFeaturizer.ResNet18 (1)
ResNet18Extension.cs (1)
39
var modelChain = new
EstimatorChain
<ColumnCopyingTransformer>();
Microsoft.ML.DnnImageFeaturizer.ResNet50 (1)
ResNet50Extension.cs (1)
39
var modelChain = new
EstimatorChain
<ColumnCopyingTransformer>();
Microsoft.ML.Tests (2)
CachingTests.cs (1)
74
new
EstimatorChain
<ITransformer>().AppendCacheCheckpoint(ML)
OnnxConversionTest.cs (1)
2202
var chain = new
EstimatorChain
<ITransformer>().Append(pipeline);
Microsoft.ML.TorchSharp.Tests (6)
NerTests.cs (3)
69
var chain = new
EstimatorChain
<ITransformer>();
148
var chain = new
EstimatorChain
<ITransformer>();
222
var chain = new
EstimatorChain
<ITransformer>();
ObjectDetectionTests.cs (1)
44
var chain = new
EstimatorChain
<ITransformer>();
QATests.cs (1)
42
var chain = new
EstimatorChain
<ITransformer>();
TextClassificationTests.cs (1)
97
var chain = new
EstimatorChain
<ITransformer>();
Microsoft.ML.Transforms (2)
Text\WordBagTransform.cs (2)
464
var chain = new
EstimatorChain
<ITransformer>();
682
var estimator = new
EstimatorChain
<ITransformer>();
283 references to EstimatorChain
Microsoft.ML.AutoML (13)
API\BinaryClassificationExperiment.cs (2)
385
var
pipeline = _pipeline.BuildFromOption(_context, parameter);
389
var
refitPipeline = _pipeline.BuildFromOption(refitContext, parameter);
API\MulticlassClassificationExperiment.cs (2)
365
var
pipeline = _pipeline.BuildFromOption(_context, parameter);
367
var
refitPipeline = _pipeline.BuildFromOption(refitContext, parameter);
API\RegressionExperiment.cs (2)
392
var
pipeline = _pipeline.BuildFromOption(_context, parameter);
394
var
refitPipeline = _pipeline.BuildFromOption(refitContext, parameter);
AutoMLExperiment\Runner\SweepablePipelineRunner.cs (1)
40
var
mlnetPipeline = _pipeline.BuildFromOption(_mLContext, parameter);
AutoMLExperiment\TrialResult.cs (1)
67
public
EstimatorChain
<ITransformer> Pipeline { get; set; }
SweepableEstimator\SweepableEstimatorPipeline.cs (2)
75
public
EstimatorChain
<ITransformer> BuildTrainingPipeline(MLContext context, Parameter parameter)
78
var
pipeline = new EstimatorChain<ITransformer>();
SweepableEstimator\SweepablePipeline.cs (3)
17
public class SweepablePipeline : ISweepable<
EstimatorChain
<ITransformer>>
84
public
EstimatorChain
<ITransformer> BuildFromOption(MLContext context, Parameter parameter)
87
var
pipeline = new EstimatorChain<ITransformer>();
Microsoft.ML.Data (11)
DataLoadSave\CompositeLoaderEstimator.cs (2)
16
private readonly
EstimatorChain
<TLastTransformer> _estimatorChain;
18
public CompositeLoaderEstimator(IDataLoaderEstimator<TSource, IDataLoader<TSource>> start,
EstimatorChain
<TLastTransformer> estimatorChain = null)
DataLoadSave\EstimatorChain.cs (4)
36
_host = env?.Register(nameof(
EstimatorChain
<TLastTransformer>));
91
public
EstimatorChain
<TNewTrans> Append<TNewTrans>(IEstimator<TNewTrans> estimator, TransformerScope scope = TransformerScope.Everything)
103
/// Adding a cache checkpoint at the begin or end of an <see cref="
EstimatorChain
{TLastTransformer}"/> is meaningless and should be avoided.
108
public
EstimatorChain
<TLastTransformer> AppendCacheCheckpoint(IHostEnvironment env)
DataLoadSave\EstimatorExtensions.cs (4)
46
public static
EstimatorChain
<TTrans> Append<TTrans>(
54
if (start is
EstimatorChain
<ITransformer> est)
67
public static
EstimatorChain
<TTrans> AppendCacheCheckpoint<TTrans>(this IEstimator<TTrans> start, IHostEnvironment env)
128
/// with many objects, so we may need to build a chain of estimators via <see cref="
EstimatorChain
{TLastTransformer}"/> where the
Training\TrainerInputBase.cs (1)
45
/// like <see cref="
EstimatorChain
{TLastTransformer}.AppendCacheCheckpoint(IHostEnvironment)"/>.
Microsoft.ML.DnnImageFeaturizer.AlexNet (4)
AlexNetExtension.cs (4)
26
public static
EstimatorChain
<ColumnCopyingTransformer> AlexNet(this DnnImageModelSelector dnnModelContext, IHostEnvironment env, string outputColumnName, string inputColumnName)
37
public static
EstimatorChain
<ColumnCopyingTransformer> AlexNet(this DnnImageModelSelector dnnModelContext, IHostEnvironment env, string outputColumnName, string inputColumnName, string modelDir)
39
var
modelChain = new EstimatorChain<ColumnCopyingTransformer>();
49
var
modelChain2 = modelChain.Append(prepEstimator);
Microsoft.ML.DnnImageFeaturizer.ResNet101 (4)
ResNet101Extension.cs (4)
26
public static
EstimatorChain
<ColumnCopyingTransformer> ResNet101(this DnnImageModelSelector dnnModelContext, IHostEnvironment env, string outputColumnName, string inputColumnName)
37
public static
EstimatorChain
<ColumnCopyingTransformer> ResNet101(this DnnImageModelSelector dnnModelContext, IHostEnvironment env, string outputColumnName, string inputColumnName, string modelDir)
39
var
modelChain = new EstimatorChain<ColumnCopyingTransformer>();
49
var
modelChain2 = modelChain.Append(prepEstimator);
Microsoft.ML.DnnImageFeaturizer.ResNet18 (4)
ResNet18Extension.cs (4)
26
public static
EstimatorChain
<ColumnCopyingTransformer> ResNet18(this DnnImageModelSelector dnnModelContext, IHostEnvironment env, string outputColumnName, string inputColumnName)
37
public static
EstimatorChain
<ColumnCopyingTransformer> ResNet18(this DnnImageModelSelector dnnModelContext, IHostEnvironment env, string outputColumnName, string inputColumnName, string modelDir)
39
var
modelChain = new EstimatorChain<ColumnCopyingTransformer>();
49
var
modelChain2 = modelChain.Append(prepEstimator);
Microsoft.ML.DnnImageFeaturizer.ResNet50 (4)
ResNet50Extension.cs (4)
26
public static
EstimatorChain
<ColumnCopyingTransformer> ResNet50(this DnnImageModelSelector dnnModelContext, IHostEnvironment env, string outputColumnName, string inputColumnName)
37
public static
EstimatorChain
<ColumnCopyingTransformer> ResNet50(this DnnImageModelSelector dnnModelContext, IHostEnvironment env, string outputColumnName, string inputColumnName, string modelDir)
39
var
modelChain = new EstimatorChain<ColumnCopyingTransformer>();
49
var
modelChain2 = modelChain.Append(prepEstimator);
Microsoft.ML.Fairlearn (1)
Reductions\GridSearchTrialRunner.cs (1)
55
var
pipeline = _pipeline.BuildFromOption(_context, settings.Parameter["_pipeline_"]);
Microsoft.ML.IntegrationTests (38)
Datasets\Iris.cs (1)
55
var
pipeline = mlContext.Transforms.CustomMapping(generateGroupId, null)
Datasets\TrivialMatrixFactorization.cs (1)
30
var
pipeline = mlContext.Transforms.Conversion.MapValueToKey("MatrixColumnIndex")
DataTransformation.cs (3)
137
var
pipeline = mlContext.Transforms.Text.FeaturizeText("Features",
175
var
pipeline = mlContext.Transforms.Concatenate("Features", Iris.Features)
202
var
pipeline = mlContext.Transforms.Concatenate("Features", Iris.Features)
Debugging.cs (2)
107
var
pipeline = mlContext.Transforms.Concatenate("Features", HousingRegression.Features)
174
var
pipeline = mlContext.Transforms.Concatenate("Features", HousingRegression.Features)
Evaluation.cs (5)
65
var
pipeline = mlContext.Transforms.Text.FeaturizeText("Features", "SentimentText")
94
var
pipeline = mlContext.Transforms.Text.FeaturizeText("Features", "SentimentText")
123
var
pipeline = mlContext.Transforms.Concatenate("Features", Iris.Features)
151
var
pipeline = mlContext.Transforms.Concatenate("Features", Iris.Features)
300
var
pipeline = mlContext.Transforms.Text.FeaturizeText("Features", "SentimentText")
IntrospectiveTraining.cs (6)
81
var
pipeline = mlContext.Transforms.Text.FeaturizeText("Features", "SentimentText")
184
var
pipeline = mlContext.Transforms.Text.ProduceWordBags("SentimentBag", "SentimentText")
225
var
pipeline = mlContext.Transforms.Text.FeaturizeText("Features", "SentimentText")
264
var
pipeline = mlContext.Transforms.Concatenate("Features", Iris.Features)
337
var
pipeline = mlContext.Transforms.Concatenate("NumericalFeatures", Adult.NumericalFeatures)
394
var
pipeline = mlContext.Transforms.Concatenate("Features", Iris.Features)
ONNX.cs (3)
40
var
pipeline = mlContext.Transforms.Concatenate("Features", HousingRegression.Features)
90
var
pipeline = mlContext.Transforms.Concatenate("Features", HousingRegression.Features)
142
var
pipeline = mlContext.Transforms.Concatenate("Features", HousingRegression.Features)
Prediction.cs (1)
50
var
pipeline = mlContext.Transforms.Text.FeaturizeText("Features", "SentimentText")
SchemaDefinitionTests.cs (3)
36
var
pipeline1 = _ml.Transforms.Categorical.OneHotEncoding("Cat", "Workclass", maximumNumberOfKeys: 3)
40
var
pipeline2 = _ml.Transforms.Categorical.OneHotEncoding("Cat", "Workclass", maximumNumberOfKeys: 4)
66
var
pipeline = _ml.Transforms.Categorical.OneHotEncoding("Categories")
Training.cs (11)
41
var
featurizationPipeline = mlContext.Transforms.Text.FeaturizeText("Features", "SentimentText")
92
var
featurizationPipeline = mlContext.Transforms.Text.FeaturizeText("Features", "SentimentText")
136
var
featurizationPipeline = mlContext.Transforms.Text.FeaturizeText("Features", "SentimentText")
180
var
featurizationPipeline = mlContext.Transforms.Text.FeaturizeText("Features", "SentimentText")
224
var
featurizationPipeline = mlContext.Transforms.Text.FeaturizeText("Features", "SentimentText")
266
var
featurizationPipeline = mlContext.Transforms.Concatenate("Features", Iris.Features)
317
var
featurizationPipeline = mlContext.Transforms.Concatenate("Features", HousingRegression.Features)
361
var
featurizationPipeline = mlContext.Transforms.Concatenate("Features", HousingRegression.Features)
406
var
featurizationPipeline = mlContext.Transforms.Text.FeaturizeText("Features", "SentimentText")
455
var
binaryClassificationPipeline = mlContext.Transforms.Concatenate("Features", Iris.Features)
486
var
binaryClassificationPipeline = mlContext.Transforms.Concatenate("Features", Iris.Features)
Validation.cs (2)
68
var
dataProcessPipeline = mlContext.Transforms.Concatenate("Features", new[] { "FeatureVectorA", "FeatureVectorB" }).Append(
86
var
trainingPipeline = dataProcessPipeline.Append(trainer);
Microsoft.ML.OnnxTransformer (5)
DnnImageFeaturizerTransform.cs (4)
18
/// <seealso cref="OnnxCatalog.DnnFeaturizeImage(TransformsCatalog, string, Func{DnnImageFeaturizerInput,
EstimatorChain
{ColumnCopyingTransformer}}, string)"/>
82
/// <seealso cref="OnnxCatalog.DnnFeaturizeImage(TransformsCatalog, string, Func{DnnImageFeaturizerInput,
EstimatorChain
{ColumnCopyingTransformer}}, string)"/>
85
private readonly
EstimatorChain
<ColumnCopyingTransformer> _modelChain;
98
internal DnnImageFeaturizerEstimator(IHostEnvironment env, string outputColumnName, Func<DnnImageFeaturizerInput,
EstimatorChain
<ColumnCopyingTransformer>> modelFactory, string inputColumnName = null)
OnnxCatalog.cs (1)
540
Func<DnnImageFeaturizerInput,
EstimatorChain
<ColumnCopyingTransformer>> modelFactory,
Microsoft.ML.OnnxTransformerTest (7)
DnnImageFeaturizerTest.cs (3)
109
var
pipe = ML.Transforms.LoadImages("data_0", imageFolder, "imagePath")
221
var
dataProcessPipeline = ML.Transforms.Conversion.MapValueToKey("Label", "Label")
233
var
trainingPipeline = dataProcessPipeline.Append(trainer);
OnnxTransformTests.cs (4)
254
var
pipe = ML.Transforms.LoadImages("data_0", imageFolder, "imagePath")
305
var
pipe = ML.Transforms.LoadImages("data_0", imageFolder, "imagePath")
643
var
pipeline = ML.Transforms.ExtractPixels("data_0", "Image") // Map column "Image" to column "data_0"
1134
var
pipe = ML.Transforms.LoadImages("data_0", imageFolder, "imagePath")
Microsoft.ML.PerformanceTests (5)
KMeansAndLogisticRegressionBench.cs (1)
36
var
estimatorPipeline = ml.Transforms.Categorical.OneHotEncoding("CatFeatures")
PredictionEngineBench.cs (1)
57
var
pipeline = new ColumnConcatenatingEstimator(env, "Features", new[] { "SepalLength", "SepalWidth", "PetalLength", "PetalWidth" })
RffTransform.cs (1)
45
var
pipeline = mlContext.Transforms.ApproximatedKernelMap("FeaturesRFF", "Features")
StochasticDualCoordinateAscentClassifierBench.cs (1)
78
var
pipeline = new ColumnConcatenatingEstimator(_mlContext, "Features", new[] { "SepalLength", "SepalWidth", "PetalLength", "PetalWidth" })
TextPredictionEngineCreation.cs (1)
28
var
pipeline = _context.Transforms.Text.FeaturizeText("Features", "SentimentText")
Microsoft.ML.Samples (36)
Dynamic\ModelOperations\OnnxConversion.cs (1)
49
var
wholePipeline = mlContext.Transforms.CopyColumns("Label", "IsOver50K")
Dynamic\NgramExtraction.cs (2)
52
var
oneCharsPipeline = charsPipeline
55
var
twoCharsPipeline = charsPipeline
Dynamic\Trainers\BinaryClassification\PermutationFeatureImportance.cs (1)
27
var
pipeline = mlContext.Transforms
Dynamic\Trainers\BinaryClassification\PermutationFeatureImportanceLoadFromDisk.cs (1)
23
var
pipeline = mlContext.Transforms
Dynamic\Trainers\MulticlassClassification\PermutationFeatureImportance.cs (1)
28
var
pipeline = mlContext.Transforms
Dynamic\Trainers\MulticlassClassification\PermutationFeatureImportanceLoadFromDisk.cs (1)
31
var
pipeline = mlContext.Transforms
Dynamic\Trainers\Ranking\PermutationFeatureImportance.cs (1)
27
var
pipeline = mlContext.Transforms.Concatenate("Features",
Dynamic\Trainers\Ranking\PermutationFeatureImportanceLoadFromDisk.cs (1)
29
var
pipeline = mlContext.Transforms.Concatenate("Features",
Dynamic\Trainers\Regression\PermutationFeatureImportance.cs (1)
28
var
pipeline = mlContext.Transforms.Concatenate(
Dynamic\Trainers\Regression\PermutationFeatureImportanceLoadFromDisk.cs (1)
30
var
pipeline = mlContext.Transforms.Concatenate(
Dynamic\Transforms\ApplyONNXModelWithInMemoryImages.cs (1)
45
var
pipeline = mlContext.Transforms.ExtractPixels("data_0", "Image")
Dynamic\Transforms\CalculateFeatureContribution.cs (1)
25
var
transformPipeline = mlContext.Transforms.Concatenate("Features",
Dynamic\Transforms\CalculateFeatureContributionCalibrated.cs (1)
25
var
transformPipeline = mlContext.Transforms.Concatenate("Features",
Dynamic\Transforms\Concatenate.cs (1)
49
var
pipeline = mlContext.Transforms.Conversion.ConvertType("Feature3",
Dynamic\Transforms\Conversion\Hash.cs (1)
43
var
pipeline = mlContext.Transforms.Conversion.Hash("CategoryHashed",
Dynamic\Transforms\Conversion\KeyToValueToKey.cs (3)
30
var
defaultPipeline = mlContext.Transforms.Text.TokenizeIntoWords(
41
var
customizedPipeline = mlContext.Transforms.Text.TokenizeIntoWords(
85
var
pipeline = defaultPipeline.Append(mlContext.Transforms.Conversion
Dynamic\Transforms\Conversion\MapKeyToVector.cs (1)
42
var
pipeline = mlContext.Transforms.Conversion.MapKeyToVector(
Dynamic\Transforms\Conversion\MapValue.cs (1)
56
var
pipeline = mlContext.Transforms.Conversion.MapValue(
Dynamic\Transforms\Expression.cs (1)
32
var
pipeline = mlContext.Transforms.Expression("Expr1", "(x,y)=>log(y)+x",
Dynamic\Transforms\FeatureSelection\SelectFeaturesBasedOnCount.cs (1)
36
var
pipeline =
Dynamic\Transforms\ImageAnalytics\ConvertToGrayScale.cs (1)
45
var
pipeline = mlContext.Transforms.LoadImages("ImageObject",
Dynamic\Transforms\ImageAnalytics\ConvertToImage.cs (1)
32
var
pipeline = mlContext.Transforms.ConvertToImage(imageHeight,
Dynamic\Transforms\ImageAnalytics\DnnFeaturizeImage.cs (1)
47
var
pipeline = mlContext.Transforms.LoadImages("ImageObject",
Dynamic\Transforms\ImageAnalytics\ExtractPixels.cs (1)
47
var
pipeline = mlContext.Transforms.LoadImages("ImageObject",
Dynamic\Transforms\ImageAnalytics\ResizeImages.cs (1)
44
var
pipeline = mlContext.Transforms.LoadImages("ImageObject",
Dynamic\Transforms\Text\ApplyCustomWordEmbedding.cs (1)
47
var
textPipeline = mlContext.Transforms.Text.NormalizeText("Text")
Dynamic\Transforms\Text\ApplyWordEmbedding.cs (1)
36
var
textPipeline = mlContext.Transforms.Text.NormalizeText("Text")
Dynamic\Transforms\Text\LatentDirichletAllocation.cs (1)
40
var
pipeline = mlContext.Transforms.Text.NormalizeText("NormalizedText",
Dynamic\Transforms\Text\ProduceHashedNgrams.cs (1)
45
var
textPipeline = mlContext.Transforms.Text.TokenizeIntoWords("Tokens",
Dynamic\Transforms\Text\ProduceNgrams.cs (1)
52
var
textPipeline = mlContext.Transforms.Text.TokenizeIntoWords("Tokens",
Dynamic\Transforms\Text\RemoveDefaultStopWords.cs (1)
30
var
textPipeline = mlContext.Transforms.Text.TokenizeIntoWords("Words",
Dynamic\Transforms\Text\RemoveStopWords.cs (1)
29
var
textPipeline = mlContext.Transforms.Text.TokenizeIntoWords("Words",
Dynamic\Transforms\Text\TokenizeIntoCharactersAsKeys.cs (1)
28
var
textPipeline = mlContext.Transforms.Text
Microsoft.ML.SamplesUtils (1)
SamplesDatasetUtils.cs (1)
91
var
pipeline = mlContext.Transforms.CopyColumns("Label", "IsOver50K")
Microsoft.ML.TensorFlow.Tests (12)
TensorFlowEstimatorTests.cs (3)
162
var
pipe = ML.Transforms.LoadImages("Input", imageFolder, "imagePath")
205
var
pipe = ML.Transforms.LoadImages("Input", imageFolder, "imagePath")
257
var
pipe = ML.Transforms.LoadImages("Input", imageFolder, "imagePath")
TensorflowTests.cs (9)
133
var
pipeEstimator = new ImageLoadingEstimator(_mlContext, imageFolder, ("ImageReal", "ImagePath"))
653
var
pipe = _mlContext.Transforms.CopyColumns("reshape_input", "Placeholder")
808
var
pipe = _mlContext.Transforms.CopyColumns("Features", "Placeholder")
877
var
pipe = _mlContext.Transforms.CopyColumns("reshape_input", "Placeholder")
1004
var
pipeEstimator = new ImageLoadingEstimator(_mlContext, imageFolder,
1101
var
pipeline = _mlContext.Transforms.ResizeImages("ResizedImage", imageWidth, imageHeight, nameof(InMemoryImage.LoadedImage))
1143
var
pipeEstimator = new ImageLoadingEstimator(_mlContext, imageFolder, ("ImageReal", "ImagePath"))
1337
var
pipeline = tensorFlowModel.ScoreTensorFlowModel(new[] { "Original_A", "Joined_Splited_Text" }, new[] { "A", "B" })
2036
var
pipeline = _mlContext.Transforms.LoadImages("Input", imageFolder, "imagePath")
Microsoft.ML.Tests (116)
CachingTests.cs (1)
45
var
pipe = ML.Transforms.CopyColumns("F1", "Features")
CalibratedModelParametersTests.cs (1)
133
var
pipeline = ML.Transforms.Concatenate("Features", "X1", "X2Important", "X3", "X4Rand")
DatabaseLoaderTests.cs (1)
264
var
pipeline = mlContext.Transforms.Conversion.MapValueToKey("Label")
FeatureContributionTests.cs (5)
33
var
estPipe = ML.Transforms.CalculateFeatureContribution(model)
201
var
est = ML.Transforms.CalculateFeatureContribution(model, numberOfPositiveContributions: 3, numberOfNegativeContributions: 0)
225
var
est = ML.Transforms.CalculateFeatureContribution(model, numberOfPositiveContributions: 3, numberOfNegativeContributions: 0)
314
var
pipeline = ML.Transforms.Concatenate("Features", "X1", "X2VBuffer", "X3Important")
424
var
dataProcessPipeline = ML.Transforms.CopyColumns(outputColumnName: DefaultColumnNames.Label, inputColumnName: nameof(TaxiTrip.FareAmount))
ImagesTests.cs (3)
50
var
pipe = new ImageLoadingEstimator(env, imageFolder, ("ImageReal", "ImagePath"))
74
var
pipe = new ImageLoadingEstimator(env, imageFolder, ("ImageReal", "ImagePath"))
1021
var
pipe = new ImageLoadingEstimator(env, imageFolder, ("ImageReal", "ImagePath"))
OnnxConversionTest.cs (25)
76
var
dynamicPipeline =
245
var
initialPipeline = mlContext.Transforms.ReplaceMissingValues("Features").
249
var
pipeline = initialPipeline.Append(estimator);
267
var
pipeline = new VectorWhiteningEstimator(mlContext, "whitened1", "features")
276
private (IDataView, List<IEstimator<ITransformer>>,
EstimatorChain
<NormalizingTransformer>) GetEstimatorsForOnnxConversionTests()
300
var
initialPipeline = ML.Transforms.ReplaceMissingValues("Features").
313
var
pipelineEstimators = initialPipeline.Append(estimator).Append(calibrator);
390
var
pipeline = new TextNormalizingEstimator(mlContext, keepDiacritics: true, columns: new[] { ("NormText", "text") }).Append(
572
var
pipeline =
603
var
pipeline =
628
var
pipeline = mlContext.Transforms.ReplaceMissingValues("Features").
792
var
pipeline = mlContext.Transforms.Categorical.OneHotEncoding("F2", "F2", Transforms.OneHotEncodingEstimator.OutputKind.Bag)
1167
var
pipeline = mlContext.Transforms.IndicateMissingValues(new[] { new InputOutputColumnPair("MissingIndicator", "Features"), })
1541
var
pipeline = mlContext.Transforms.Text.TokenizeIntoWords("Words", "Text")
1565
var
pipeline = mlContext.Transforms.Text.TokenizeIntoWords("Words", "Text")
1680
var
initialPipeline = mlContext.Transforms.ReplaceMissingValues("Features")
1686
var
pipeline = initialPipeline.Append(estimator);
1898
var
pipeline = mlContext.Transforms.ReplaceMissingValues("Size").Append(mlContext.Transforms.SelectColumns(new[] { "Size", "Shape", "Thickness", "Label" }));
1956
var
initialPipeline = mlContext.Transforms.ReplaceMissingValues("MyFeatureVector").
1960
var
pipeline = initialPipeline.Append(estimator);
2005
var
initialPipeline = mlContext.Transforms.ReplaceMissingValues("MyFeatureVector")
2011
var
pipeline = initialPipeline.Append(estimator);
2202
var
chain = new EstimatorChain<ITransformer>().Append(pipeline);
2219
private void TestPipeline<TLastTransformer, TRow>(
EstimatorChain
<TLastTransformer> pipeline, IEnumerable<TRow> data, string onnxFileName, ColumnComparison[] columnsToCompare, SchemaDefinition schemaDefinition = null, string onnxTxtName = null, string onnxTxtSubDir = null)
2238
private void TestPipeline<TLastTransformer>(
EstimatorChain
<TLastTransformer> pipeline, IDataView dataView, string onnxFileName, ColumnComparison[] columnsToCompare, string onnxTxtName = null, string onnxTxtSubDir = null)
PermutationFeatureImportanceTests.cs (2)
858
var
pipeline = ML.Transforms.Concatenate("Features", "X1", "X2Important", "X3", "X4Rand")
938
var
pipeline = ML.Transforms.Concatenate("Features", "X1", "X2VBuffer", "X3Important")
Scenarios\Api\CookbookSamples\CookbookSamplesDynamicApi.cs (8)
167
var
pipeline =
228
var
pipeline =
264
var
finalPipeline = pipeline.Append(mlContext.Transforms.Conversion.MapKeyToValue("Data", "PredictedLabel"));
519
var
pipeline =
593
var
pipeline =
612
var
fullLearningPipeline = pipeline
642
var
pipeline =
779
var
estimator = mlContext.Transforms.CustomMapping(mapping, null)
Scenarios\Api\Estimators\DecomposableTrainAndPredict.cs (1)
33
var
pipeline = new ColumnConcatenatingEstimator(ml, "Features", "SepalLength", "SepalWidth", "PetalLength", "PetalWidth")
Scenarios\Api\Estimators\Extensibility.cs (1)
41
var
pipeline = new ColumnConcatenatingEstimator(ml, "Features", "SepalLength", "SepalWidth", "PetalLength", "PetalWidth")
Scenarios\Api\Estimators\MultithreadedPrediction.cs (1)
31
var
pipeline = ml.Transforms.Text.FeaturizeText("Features", "SentimentText")
Scenarios\Api\Estimators\PredictAndMetadata.cs (2)
31
var
pipeline = ml.Transforms.Concatenate("Features", "SepalLength", "SepalWidth", "PetalLength", "PetalWidth")
80
var
pipeline = mlContext.Transforms.Concatenate("Features", "SepalLength", "SepalWidth", "PetalLength", "PetalWidth")
Scenarios\Api\Estimators\SimpleTrainAndPredict.cs (2)
29
var
pipeline = ml.Transforms.Text.FeaturizeText("Features", "SentimentText")
66
var
pipeline = ml.Transforms.Text.FeaturizeText("Features", "SentimentText")
Scenarios\IrisPlantClassificationTests.cs (1)
32
var
pipe = mlContext.Transforms.Concatenate("Features", "SepalLength", "SepalWidth", "PetalLength", "PetalWidth")
Scenarios\IrisPlantClassificationWithStringLabelTests.cs (1)
36
var
pipe = mlContext.Transforms.Concatenate("Features", "SepalLength", "SepalWidth", "PetalLength", "PetalWidth")
Scenarios\RegressionTest.cs (2)
27
var
dataProcessPipeline = context.Transforms.CopyColumns(outputColumnName: "Label", inputColumnName: "FareAmount")
38
var
trainingPipeline = dataProcessPipeline.Append(trainer);
Scenarios\WordBagTest.cs (2)
31
var
textPipeline =
68
var
textPipeline =
ScenariosWithDirectInstantiation\IrisPlantClassificationTests.cs (1)
30
var
pipe = mlContext.Transforms.Concatenate("Features", "SepalLength", "SepalWidth", "PetalLength", "PetalWidth")
TrainerEstimators\MetalinearEstimators.cs (1)
97
var
pipeline = new ColumnConcatenatingEstimator(Env, "Vars", "SepalLength", "SepalWidth", "PetalLength", "PetalWidth")
TrainerEstimators\TrainerEstimators.cs (4)
99
var
pipeWithTrainer = pipe.AppendCacheCheckpoint(Env).Append(trainer);
130
var
pipeWithTrainer = pipe.AppendCacheCheckpoint(Env).Append(trainer);
172
var
pipeWithTrainer = pipe.AppendCacheCheckpoint(Env).Append(trainer);
218
var
oneHotPipeline = pipeline.Append(ML.Transforms.Categorical.OneHotEncoding("LoggedIn"));
TrainerEstimators\TreeEnsembleFeaturizerTest.cs (13)
330
var
pipeline = ML.Transforms.FeaturizeByPretrainTreeEnsemble(options)
376
var
pipeline = ML.Transforms.FeaturizeByFastTreeBinary(options)
415
var
pipeline = ML.Transforms.FeaturizeByFastForestBinary(options)
454
var
pipeline = ML.Transforms.FeaturizeByFastTreeRegression(options)
492
var
pipeline = ML.Transforms.FeaturizeByFastForestRegression(options)
530
var
pipeline = ML.Transforms.FeaturizeByFastTreeTweedie(options)
568
var
pipeline = ML.Transforms.FeaturizeByFastTreeRanking(options)
606
var
pipeline = ML.Transforms.FeaturizeByFastForestRegression(options)
662
var
pipeline = ML.Transforms.CopyColumns("CopiedFeatures", "Features")
693
var
secondPipeline = ML.Transforms.CopyColumns("CopiedFeatures", "Features")
739
var
wrongPipeline = ML.Transforms.FeaturizeByFastTreeBinary(options)
750
var
pipeline = ML.Transforms.FeaturizeByFastTreeBinary(options)
803
var
pipeline = ML.Transforms.Conversion.MapValueToKey("KeyLabel", "Label")
Transformers\CategoricalHashTests.cs (1)
89
var
est = ML.Transforms.Text.TokenizeIntoWords("VarVectorString", "ScalarString")
Transformers\CategoricalTests.cs (2)
109
var
pipe = mlContext.Transforms.Conversion.ConvertType("A", outputKind: DataKind.Single)
164
var
est = ML.Transforms.Text.TokenizeIntoWords("VarVectorString", "ScalarString")
Transformers\ConcatTests.cs (1)
65
var
pipe = ML.Transforms.Concatenate("f1", "float1")
Transformers\ConvertTests.cs (1)
338
var
pipe = ML.Transforms.Categorical.OneHotEncoding(new[] {
Transformers\ExpressionTransformerTests.cs (1)
40
var
expr = ML.Transforms.Expression("Expr1", "x=>x/2", "Double").
Transformers\FeatureSelectionTests.cs (6)
41
var
est = new WordBagEstimator(ML, "bag_of_words", "text")
120
var
est = ML.Transforms.FeatureSelection.SelectFeaturesBasedOnCount("FeatureSelect", "VectorFloat", count: 1)
177
var
est = ML.Transforms.FeatureSelection.SelectFeaturesBasedOnMutualInformation("FeatureSelect", "VectorFloat", slotsInOutput: 1, labelColumnName: "Label")
238
var
pipeline = ML.Transforms.Text.TokenizeIntoWords("Features")
246
var
pipeline = ML.Transforms.Text.TokenizeIntoWords("Features")
254
var
pipeline = ML.Transforms.Text.TokenizeIntoWords("Features")
Transformers\HashTests.cs (1)
383
var
pipeline = ML.Transforms.Concatenate("D", "A")
Transformers\KeyToBinaryVectorEstimatorTest.cs (1)
74
var
est = ML.Transforms.Conversion.MapKeyToBinaryVector("ScalarString", "A")
Transformers\KeyToValueTests.cs (1)
78
var
est = ML.Transforms.Conversion.MapKeyToValue("ScalarString", "A")
Transformers\KeyToVectorEstimatorTests.cs (2)
83
var
est = ML.Transforms.Conversion.MapKeyToVector("ScalarString", "A")
256
var
pipeline = mlContext.Transforms.Conversion.MapValueToKey("Label")
Transformers\NAIndicatorTests.cs (1)
139
var
newpipe = pipe.Append(ML.Transforms.IndicateMissingValues("NAA", "CatA"));
Transformers\NAReplaceTests.cs (1)
135
var
est = ML.Transforms.ReplaceMissingValues("A", "ScalarFloat", replacementMode: MissingValueReplacingEstimator.ReplacementMode.Maximum)
Transformers\NormalizerTests.cs (5)
238
var
est = context.Transforms.NormalizeMinMax(
666
var
est = ML.Transforms.NormalizeLpNorm("lpnorm", "features")
701
var
est = new VectorWhiteningEstimator(ML, "whitened1", "features")
764
var
est = ML.Transforms.NormalizeLpNorm("lpNorm1", "features")
824
var
est = ML.Transforms.NormalizeGlobalContrast("gcnNorm1", "features")
Transformers\SelectColumnsTests.cs (3)
134
var
chain = est.Append(ColumnSelectingEstimator.KeepColumns(Env, "C", "A"));
157
var
chain = est.Append(ML.Transforms.SelectColumns(new[] { "B", "A" }, true));
198
var
est = new ColumnCopyingEstimator(Env, new[] { ("A", "A"), ("B", "B") }).Append(
Transformers\TextFeaturizerTests.cs (5)
469
var
est = new WordTokenizingEstimator(ML, "words", "text")
536
var
est = ML.Transforms.Text.NormalizeText("text")
599
var
est = new WordBagEstimator(ML, "bag_of_words", "text").
629
var
est = new WordTokenizingEstimator(ML, "text", "text")
683
var
est = new WordBagEstimator(env, "bag_of_words", "text").
Transformers\TextNormalizer.cs (1)
56
var
pipeVariations = new TextNormalizingEstimator(ML, columns: new[] { ("NormText", "text") }).Append(
Transformers\ValueMappingTests.cs (3)
105
var
estimator = new WordTokenizingEstimator(Env, new[]{
558
var
estimator = ML.Transforms.Conversion.MapValue("D", keyValuePairs, "A", true).
640
var
est = ML.Transforms.Text.TokenizeIntoWords("TokenizeB", "B")
Transformers\WordEmbeddingsTests.cs (2)
41
var
est = ML.Transforms.Text.NormalizeText("NormalizedText", "SentimentText", keepDiacritics: false, keepPunctuations: false)
76
var
est = ML.Transforms.Text.NormalizeText("NormalizedText", "SentimentText", keepDiacritics: false, keepPunctuations: false)
Microsoft.ML.TimeSeries.Tests (2)
TimeSeriesDirectApi.cs (2)
227
var
pipeline = ml.Transforms.Text.FeaturizeText("Text_Featurized", "Text")
303
var
pipeline = ml.Transforms.Text.FeaturizeText("Text_Featurized", "Text")
Microsoft.ML.TorchSharp.Tests (16)
NerTests.cs (6)
69
var
chain = new EstimatorChain<ITransformer>();
70
var
estimator = chain.Append(ML.Transforms.Conversion.MapValueToKey("Label", keyData: labels))
148
var
chain = new EstimatorChain<ITransformer>();
149
var
estimator = chain.Append(ML.Transforms.Conversion.MapValueToKey("Label", keyData: labels))
222
var
chain = new EstimatorChain<ITransformer>();
223
var
estimator = chain.Append(ML.Transforms.Conversion.MapValueToKey("Label", keyData: labels))
ObjectDetectionTests.cs (3)
44
var
chain = new EstimatorChain<ITransformer>();
46
var
filteredPipeline = chain.Append(ML.Transforms.Text.TokenizeIntoWords("Labels", separators: new char[] { ',' }), TransformerScope.Training)
63
var
pipeline = ML.Transforms.Text.TokenizeIntoWords("Labels", separators: new char[] { ',' })
QATests.cs (2)
42
var
chain = new EstimatorChain<ITransformer>();
43
var
estimator = chain.Append(ML.MulticlassClassification.Trainers.QuestionAnswer(maxEpochs: 1));
TextClassificationTests.cs (5)
97
var
chain = new EstimatorChain<ITransformer>();
98
var
estimator = chain.Append(ML.Transforms.Conversion.MapValueToKey("Label", "Sentiment"), TransformerScope.TrainTest)
176
var
pipeline =
235
var
estimator = ML.Transforms.Conversion.MapValueToKey("Label", "Sentiment")
320
var
estimator = ML.MulticlassClassification.Trainers.TextClassification(outputColumnName: "outputColumn", sentence1ColumnName: "Sentence", sentence2ColumnName: "Sentence2", validationSet: preppedData)
Microsoft.ML.Transforms (4)
Dracula\CountTargetEncodingTransformer.cs (2)
423
/// will only be applied if the estimator is part of an <see cref="
EstimatorChain
{TLastTransformer}"/>, when fitting the next estimator in the chain.</param>
496
/// will only be applied if the estimator is part of an <see cref="
EstimatorChain
{TLastTransformer}"/>, when fitting the next estimator in the chain.</param>
Text\WordBagTransform.cs (2)
464
var
chain = new EstimatorChain<ITransformer>();
682
var
estimator = new EstimatorChain<ITransformer>();