rebase fix

Author: artidoro

test/BaselineOutput/Common/EntryPoints/core_ep-list.tsv

@@ -78,9 +78,9 @@ Transforms.CategoricalOneHotVectorizer	Converts the categorical value into an in
 Transforms.CharacterTokenizer	Character-oriented tokenizer where text is considered a sequence of characters.	Microsoft.ML.Transforms.Text.TextAnalytics	CharTokenize	Microsoft.ML.Transforms.Text.TokenizingByCharactersTransformer+Options	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
 Transforms.ColumnConcatenator	Concatenates one or more columns of the same item type.	Microsoft.ML.EntryPoints.SchemaManipulation	ConcatColumns	Microsoft.ML.Data.ColumnConcatenatingTransformer+Options	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
 Transforms.ColumnCopier	Duplicates columns from the dataset	Microsoft.ML.EntryPoints.SchemaManipulation	CopyColumns	Microsoft.ML.Transforms.ColumnCopyingTransformer+Options	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
-Transforms.ColumnSelector	Selects a set of columns, dropping all others	Microsoft.ML.EntryPoints.SchemaManipulation	SelectColumns	Microsoft.ML.Transforms.ColumnSelectingTransformer+Arguments	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
+Transforms.ColumnSelector	Selects a set of columns, dropping all others	Microsoft.ML.EntryPoints.SchemaManipulation	SelectColumns	Microsoft.ML.Transforms.ColumnSelectingTransformer+Options	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
 Transforms.ColumnTypeConverter	Converts a column to a different type, using standard conversions.	Microsoft.ML.Transforms.Conversions.TypeConversion	Convert	Microsoft.ML.Transforms.Conversions.TypeConvertingTransformer+Options	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
-Transforms.CombinerByContiguousGroupId	Groups values of a scalar column into a vector, by a contiguous group ID	Microsoft.ML.Transforms.GroupingOperations	Group	Microsoft.ML.Transforms.GroupTransform+Arguments	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
+Transforms.CombinerByContiguousGroupId	Groups values of a scalar column into a vector, by a contiguous group ID	Microsoft.ML.Transforms.GroupingOperations	Group	Microsoft.ML.Transforms.GroupTransform+Options	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
 Transforms.ConditionalNormalizer	Normalize the columns only if needed	Microsoft.ML.Data.Normalize	IfNeeded	Microsoft.ML.Transforms.Normalizers.NormalizeTransform+MinMaxArguments	Microsoft.ML.EntryPoints.CommonOutputs+MacroOutput`1[Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput]
 Transforms.DataCache	Caches using the specified cache option.	Microsoft.ML.EntryPoints.Cache	CacheData	Microsoft.ML.EntryPoints.Cache+CacheInput	Microsoft.ML.EntryPoints.Cache+CacheOutput
 Transforms.DatasetScorer	Score a dataset with a predictor model	Microsoft.ML.EntryPoints.ScoreModel	Score	Microsoft.ML.EntryPoints.ScoreModel+Input	Microsoft.ML.EntryPoints.ScoreModel+Output
@@ -98,7 +98,7 @@ Transforms.ImagePixelExtractor	Extract color plane(s) from an image. Options inc
 Transforms.ImageResizer	Scales an image to specified dimensions using one of the three scale types: isotropic with padding, isotropic with cropping or anisotropic. In case of isotropic padding, transparent color is used to pad resulting image.	Microsoft.ML.ImageAnalytics.EntryPoints.ImageAnalytics	ImageResizer	Microsoft.ML.ImageAnalytics.ImageResizingTransformer+Arguments	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
 Transforms.KeyToTextConverter	KeyToValueTransform utilizes KeyValues metadata to map key indices to the corresponding values in the KeyValues metadata.	Microsoft.ML.Transforms.Categorical.Categorical	KeyToText	Microsoft.ML.Transforms.Conversions.KeyToValueMappingTransformer+Options	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
 Transforms.LabelColumnKeyBooleanConverter	Transforms the label to either key or bool (if needed) to make it suitable for classification.	Microsoft.ML.EntryPoints.FeatureCombiner	PrepareClassificationLabel	Microsoft.ML.EntryPoints.FeatureCombiner+ClassificationLabelInput	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
-Transforms.LabelIndicator	Label remapper used by OVA	Microsoft.ML.Transforms.LabelIndicatorTransform	LabelIndicator	Microsoft.ML.Transforms.LabelIndicatorTransform+Arguments	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
+Transforms.LabelIndicator	Label remapper used by OVA	Microsoft.ML.Transforms.LabelIndicatorTransform	LabelIndicator	Microsoft.ML.Transforms.LabelIndicatorTransform+Options	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
 Transforms.LabelToFloatConverter	Transforms the label to float to make it suitable for regression.	Microsoft.ML.EntryPoints.FeatureCombiner	PrepareRegressionLabel	Microsoft.ML.EntryPoints.FeatureCombiner+RegressionLabelInput	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
 Transforms.LightLda	The LDA transform implements LightLDA, a state-of-the-art implementation of Latent Dirichlet Allocation.	Microsoft.ML.Transforms.Text.TextAnalytics	LightLda	Microsoft.ML.Transforms.Text.LatentDirichletAllocationTransformer+Options	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
 Transforms.LogMeanVarianceNormalizer	Normalizes the data based on the computed mean and variance of the logarithm of the data.	Microsoft.ML.Data.Normalize	LogMeanVar	Microsoft.ML.Transforms.Normalizers.NormalizeTransform+LogMeanVarArguments	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
@@ -117,14 +117,14 @@ Transforms.NoOperation	Does nothing.	Microsoft.ML.Data.NopTransform	Nop	Microsof
 Transforms.OptionalColumnCreator	If the source column does not exist after deserialization, create a column with the right type and default values.	Microsoft.ML.Transforms.OptionalColumnTransform	MakeOptional	Microsoft.ML.Transforms.OptionalColumnTransform+Arguments	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
 Transforms.PcaCalculator	PCA is a dimensionality-reduction transform which computes the projection of a numeric vector onto a low-rank subspace.	Microsoft.ML.Transforms.Projections.PrincipalComponentAnalysisTransformer	Calculate	Microsoft.ML.Transforms.Projections.PrincipalComponentAnalysisTransformer+Options	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
 Transforms.PredictedLabelColumnOriginalValueConverter	Transforms a predicted label column to its original values, unless it is of type bool.	Microsoft.ML.EntryPoints.FeatureCombiner	ConvertPredictedLabel	Microsoft.ML.EntryPoints.FeatureCombiner+PredictedLabelInput	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
-Transforms.RandomNumberGenerator	Adds a column with a generated number sequence.	Microsoft.ML.Transforms.RandomNumberGenerator	Generate	Microsoft.ML.Transforms.GenerateNumberTransform+Arguments	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
-Transforms.RowRangeFilter	Filters a dataview on a column of type Single, Double or Key (contiguous). Keeps the values that are in the specified min/max range. NaNs are always filtered out. If the input is a Key type, the min/max are considered percentages of the number of values.	Microsoft.ML.EntryPoints.SelectRows	FilterByRange	Microsoft.ML.Transforms.RangeFilter+Arguments	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
-Transforms.RowSkipAndTakeFilter	Allows limiting input to a subset of rows at an optional offset.  Can be used to implement data paging.	Microsoft.ML.EntryPoints.SelectRows	SkipAndTakeFilter	Microsoft.ML.Transforms.SkipTakeFilter+Arguments	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
-Transforms.RowSkipFilter	Allows limiting input to a subset of rows by skipping a number of rows.	Microsoft.ML.EntryPoints.SelectRows	SkipFilter	Microsoft.ML.Transforms.SkipTakeFilter+SkipArguments	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
-Transforms.RowTakeFilter	Allows limiting input to a subset of rows by taking N first rows.	Microsoft.ML.EntryPoints.SelectRows	TakeFilter	Microsoft.ML.Transforms.SkipTakeFilter+TakeArguments	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
+Transforms.RandomNumberGenerator	Adds a column with a generated number sequence.	Microsoft.ML.Transforms.RandomNumberGenerator	Generate	Microsoft.ML.Transforms.GenerateNumberTransform+Options	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
+Transforms.RowRangeFilter	Filters a dataview on a column of type Single, Double or Key (contiguous). Keeps the values that are in the specified min/max range. NaNs are always filtered out. If the input is a Key type, the min/max are considered percentages of the number of values.	Microsoft.ML.EntryPoints.SelectRows	FilterByRange	Microsoft.ML.Transforms.RangeFilter+Options	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
+Transforms.RowSkipAndTakeFilter	Allows limiting input to a subset of rows at an optional offset.  Can be used to implement data paging.	Microsoft.ML.EntryPoints.SelectRows	SkipAndTakeFilter	Microsoft.ML.Transforms.SkipTakeFilter+Options	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
+Transforms.RowSkipFilter	Allows limiting input to a subset of rows by skipping a number of rows.	Microsoft.ML.EntryPoints.SelectRows	SkipFilter	Microsoft.ML.Transforms.SkipTakeFilter+SkipOptions	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
+Transforms.RowTakeFilter	Allows limiting input to a subset of rows by taking N first rows.	Microsoft.ML.EntryPoints.SelectRows	TakeFilter	Microsoft.ML.Transforms.SkipTakeFilter+TakeOptions	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
 Transforms.ScoreColumnSelector	Selects only the last score columns and the extra columns specified in the arguments.	Microsoft.ML.EntryPoints.ScoreModel	SelectColumns	Microsoft.ML.EntryPoints.ScoreModel+ScoreColumnSelectorInput	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
 Transforms.Scorer	Turn the predictor model into a transform model	Microsoft.ML.EntryPoints.ScoreModel	MakeScoringTransform	Microsoft.ML.EntryPoints.ScoreModel+ModelInput	Microsoft.ML.EntryPoints.ScoreModel+Output
-Transforms.Segregator	Un-groups vector columns into sequences of rows, inverse of Group transform	Microsoft.ML.Transforms.GroupingOperations	Ungroup	Microsoft.ML.Transforms.UngroupTransform+Arguments	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
+Transforms.Segregator	Un-groups vector columns into sequences of rows, inverse of Group transform	Microsoft.ML.Transforms.GroupingOperations	Ungroup	Microsoft.ML.Transforms.UngroupTransform+Options	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
 Transforms.SentimentAnalyzer	Uses a pretrained sentiment model to score input strings	Microsoft.ML.Transforms.Text.TextAnalytics	AnalyzeSentiment	Microsoft.ML.Transforms.Text.SentimentAnalyzingTransformer+Arguments	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
 Transforms.TensorFlowScorer	Transforms the data using the TensorFlow model.	Microsoft.ML.Transforms.TensorFlowTransformer	TensorFlowScorer	Microsoft.ML.Transforms.TensorFlowTransformer+Options	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput
 Transforms.TextFeaturizer	A transform that turns a collection of text documents into numerical feature vectors. The feature vectors are normalized counts of (word and/or character) ngrams in a given tokenized text.	Microsoft.ML.Transforms.Text.TextAnalytics	TextTransform	Microsoft.ML.Transforms.Text.TextFeaturizingEstimator+Arguments	Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput

test/Microsoft.ML.StaticPipelineTesting/StaticPipeTests.cs

@@ -415,9 +415,9 @@ public void NormalizerWithOnFit()
             // Just for fun, let's also write out some of the lines of the data to the console.
             using (var stream = new MemoryStream())
             {
-                IDataView v = ML.Transforms.SelectColumns("r", "ncdf", "n", "b").Fit(tdata.AsDynamic).Transform(tdata.AsDynamic);
+                IDataView v = ml.Transforms.SelectColumns("r", "ncdf", "n", "b").Fit(tdata.AsDynamic).Transform(tdata.AsDynamic);
                 v = ml.Data.TakeRows(v, 10);
-                var saver = new TextSaver(env, new TextSaver.Arguments()
+                var saver = new TextSaver(ml, new TextSaver.Arguments()
                 {
                     Dense = true,
                     Separator = ",",

test/Microsoft.ML.Tests/Transformers/NormalizerTests.cs

@@ -283,7 +283,7 @@ public void LpGcNormAndWhiteningWorkout()
             using (var ch = Env.Start("save"))
             {
                 var saver = new TextSaver(ML, new TextSaver.Arguments { Silent = true, OutputHeader = false });
-                var savedData = ML.Data.TakeRows(est.Fit(data.AsDynamic)Transform(data.AsDynamic), 4);
+                var savedData = ML.Data.TakeRows(est.Fit(data.AsDynamic).Transform(data.AsDynamic), 4);
                 savedData = ML.Transforms.SelectColumns("lpnorm", "gcnorm", "whitened").Fit(savedData).Transform(savedData);
 
                 using (var fs = File.Create(outputPath))