Eric comments

TomFinley · TomFinley · commit fdb4d7c6f67f · 2018-11-16T12:52:37.000-08:00
diff --git a/src/Microsoft.ML.Api/TypedCursor.cs b/src/Microsoft.ML.Api/TypedCursor.cs
@@ -528,8 +528,6 @@ public ICursor GetRootCursor()
     /// </summary>
     public static class CursoringUtils
     {
-        private const string NeedEnvObsoleteMessage = "This method is obsolete. Please use the overload that takes an additional 'env' argument. An environment can be created via new LocalEnvironment().";
-
         /// <summary>
         /// Generate a strongly-typed cursorable wrapper of the <see cref="IDataView"/>.
         /// </summary>
@@ -550,24 +548,6 @@ public static ICursorable<TRow> AsCursorable<TRow>(this IDataView data, IHostEnv
             return TypedCursorable<TRow>.Create(env, data, ignoreMissingColumns, schemaDefinition);
         }
 
-        /// <summary>
-        /// Generate a strongly-typed cursorable wrapper of the <see cref="IDataView"/>.
-        /// </summary>
-        /// <typeparam name="TRow">The user-defined row type.</typeparam>
-        /// <param name="data">The underlying data view.</param>
-        /// <param name="ignoreMissingColumns">Whether to ignore the case when a requested column is not present in the data view.</param>
-        /// <param name="schemaDefinition">Optional user-provided schema definition. If it is not present, the schema is inferred from the definition of T.</param>
-        /// <returns>The cursorable wrapper of <paramref name="data"/>.</returns>
-        [Obsolete(NeedEnvObsoleteMessage)]
-        public static ICursorable<TRow> AsCursorable<TRow>(this IDataView data, bool ignoreMissingColumns = false,
-            SchemaDefinition schemaDefinition = null)
-            where TRow : class, new()
-        {
-            // REVIEW: Take this as a parameter, or else make it a method on the context itself.
-            var ml = new MLContext();
-            return data.AsCursorable<TRow>(ml, ignoreMissingColumns, schemaDefinition);
-        }
-
         /// <summary>
         /// Convert an <see cref="IDataView"/> into a strongly-typed <see cref="IEnumerable{TRow}"/>.
         /// </summary>
@@ -589,24 +569,5 @@ public static IEnumerable<TRow> AsEnumerable<TRow>(this IDataView data, IHostEnv
             var engine = new PipeEngine<TRow>(env, data, ignoreMissingColumns, schemaDefinition);
             return engine.RunPipe(reuseRowObject);
         }
-
-        /// <summary>
-        /// Convert an <see cref="IDataView"/> into a strongly-typed <see cref="IEnumerable{TRow}"/>.
-        /// </summary>
-        /// <typeparam name="TRow">The user-defined row type.</typeparam>
-        /// <param name="data">The underlying data view.</param>
-        /// <param name="reuseRowObject">Whether to return the same object on every row, or allocate a new one per row.</param>
-        /// <param name="ignoreMissingColumns">Whether to ignore the case when a requested column is not present in the data view.</param>
-        /// <param name="schemaDefinition">Optional user-provided schema definition. If it is not present, the schema is inferred from the definition of T.</param>
-        /// <returns>The <see cref="IEnumerable{TRow}"/> that holds the data in <paramref name="data"/>. It can be enumerated multiple times.</returns>
-        [Obsolete(NeedEnvObsoleteMessage)]
-        public static IEnumerable<TRow> AsEnumerable<TRow>(this IDataView data, bool reuseRowObject,
-            bool ignoreMissingColumns = false, SchemaDefinition schemaDefinition = null)
-            where TRow : class, new()
-        {
-            // REVIEW: Take this as a parameter, or else make it a method on the context itself.
-            var ml = new MLContext();
-            return data.AsEnumerable<TRow>(ml, reuseRowObject, ignoreMissingColumns, schemaDefinition);
-        }
     }
 }
diff --git a/src/Microsoft.ML.Core/ComponentModel/AssemblyLoadingUtils.cs b/src/Microsoft.ML.Core/ComponentModel/AssemblyLoadingUtils.cs
@@ -10,6 +10,8 @@
 
 namespace Microsoft.ML.Runtime
 {
+    [Obsolete("The usage for this is intended for the internal command line utilities and is not intended for anything related to the API. " +
+        "Please consider another way of doing whatever it is you're attempting to accomplish.")]
     [BestFriend]
     internal static class AssemblyLoadingUtils
     {
diff --git a/src/Microsoft.ML.Core/Properties/AssemblyInfo.cs b/src/Microsoft.ML.Core/Properties/AssemblyInfo.cs
@@ -12,7 +12,6 @@
 [assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.InferenceTesting" + PublicKey.TestValue)]
 [assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.StaticPipelineTesting" + PublicKey.TestValue)]
 [assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.OnnxTransformTest" + PublicKey.TestValue)]
-[assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.BenchMarks" + PublicKey.TestValue)]
 
 [assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.Legacy" + PublicKey.Value)]
 [assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.Maml" + PublicKey.Value)]
diff --git a/src/Microsoft.ML.Data/Properties/AssemblyInfo.cs b/src/Microsoft.ML.Data/Properties/AssemblyInfo.cs
@@ -9,7 +9,6 @@
 [assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.Tests" + PublicKey.TestValue)]
 [assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.InferenceTesting" + PublicKey.TestValue)]
 [assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.OnnxTransformTest" + PublicKey.TestValue)]
-[assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.BenchMarks" + PublicKey.TestValue)]
 
 [assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.Legacy" + PublicKey.Value)]
 [assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.Maml" + PublicKey.Value)]
diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/BaseScalarStacking.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/BaseScalarStacking.cs
@@ -9,7 +9,7 @@
 
 namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
 {
-    public abstract class BaseScalarStacking : BaseStacking<Single>
+    internal abstract class BaseScalarStacking : BaseStacking<Single>
     {
         internal BaseScalarStacking(IHostEnvironment env, string name, ArgumentsBase args)
             : base(env, name, args)
diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/BaseStacking.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/BaseStacking.cs
@@ -16,7 +16,7 @@
 namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners
 {
     using ColumnRole = RoleMappedSchema.ColumnRole;
-    public abstract class BaseStacking<TOutput> : IStackingTrainer<TOutput>
+    internal abstract class BaseStacking<TOutput> : IStackingTrainer<TOutput>
     {
         public abstract class ArgumentsBase
         {
diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/MultiStacking.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/MultiStacking.cs
@@ -41,7 +41,7 @@ private static VersionInfo GetVersionInfo()
         [TlcModule.Component(Name = LoadName, FriendlyName = Stacking.UserName)]
         public sealed class Arguments : ArgumentsBase, ISupportMulticlassOutputCombinerFactory
         {
-            // TODO: If we make this public again it should be an *estimator* of this type of predictor, rather than the (deprecated) ITrainer.
+            // REVIEW: If we make this public again it should be an *estimator* of this type of predictor, rather than the (deprecated) ITrainer.
             [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
                 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureMultiClassClassifierTrainer))]
             [TGUI(Label = "Base predictor")]
diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/RegressionStacking.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/RegressionStacking.cs
@@ -39,7 +39,7 @@ private static VersionInfo GetVersionInfo()
         [TlcModule.Component(Name = LoadName, FriendlyName = Stacking.UserName)]
         public sealed class Arguments : ArgumentsBase, ISupportRegressionOutputCombinerFactory
         {
-            // TODO: If we make this public again it should be an *estimator* of this type of predictor, rather than the (deprecated) ITrainer.
+            // REVIEW: If we make this public again it should be an *estimator* of this type of predictor, rather than the (deprecated) ITrainer.
             [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
                 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureRegressorTrainer))]
             [TGUI(Label = "Base predictor")]
diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/Stacking.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/Stacking.cs
@@ -37,7 +37,7 @@ private static VersionInfo GetVersionInfo()
         [TlcModule.Component(Name = LoadName, FriendlyName = UserName)]
         public sealed class Arguments : ArgumentsBase, ISupportBinaryOutputCombinerFactory
         {
-            // TODO: If we make this public again it should be an *estimator* of this type of predictor, rather than the (deprecated) ITrainer.
+            // REVIEW: If we make this public again it should be an *estimator* of this type of predictor, rather than the (deprecated) ITrainer.
             [Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
                 Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureBinaryClassifierTrainer))]
             [TGUI(Label = "Base predictor")]
diff --git a/src/Microsoft.ML.Ensemble/Trainer/Binary/EnsembleTrainer.cs b/src/Microsoft.ML.Ensemble/Trainer/Binary/EnsembleTrainer.cs
@@ -48,7 +48,7 @@ public sealed class Arguments : ArgumentsBase
             [TGUI(Label = "Output combiner", Description = "Output combiner type")]
             public ISupportBinaryOutputCombinerFactory OutputCombiner = new MedianFactory();
 
-            // TODO: If we make this public again it should be an *estimator* of this type of predictor, rather than the (deprecated) ITrainer.
+            // REVIEW: If we make this public again it should be an *estimator* of this type of predictor, rather than the (deprecated) ITrainer.
             [Argument(ArgumentType.Multiple, HelpText = "Base predictor type", ShortName = "bp,basePredictorTypes", SortOrder = 1, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureBinaryClassifierTrainer))]
             public IComponentFactory<ITrainer<TScalarPredictor>>[] BasePredictors;
 
diff --git a/src/Microsoft.ML.Ensemble/Trainer/Multiclass/MulticlassDataPartitionEnsembleTrainer.cs b/src/Microsoft.ML.Ensemble/Trainer/Multiclass/MulticlassDataPartitionEnsembleTrainer.cs
@@ -49,7 +49,7 @@ public sealed class Arguments : ArgumentsBase
             [TGUI(Label = "Output combiner", Description = "Output combiner type")]
             public ISupportMulticlassOutputCombinerFactory OutputCombiner = new MultiMedian.Arguments();
 
-            // TODO: If we make this public again it should be an *estimator* of this type of predictor, rather than the (deprecated) ITrainer.
+            // REVIEW: If we make this public again it should be an *estimator* of this type of predictor, rather than the (deprecated) ITrainer.
             [Argument(ArgumentType.Multiple, HelpText = "Base predictor type", ShortName = "bp,basePredictorTypes", SortOrder = 1, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureMultiClassClassifierTrainer))]
             public IComponentFactory<ITrainer<TVectorPredictor>>[] BasePredictors;
 
diff --git a/src/Microsoft.ML.Ensemble/Trainer/Regression/RegressionEnsembleTrainer.cs b/src/Microsoft.ML.Ensemble/Trainer/Regression/RegressionEnsembleTrainer.cs
@@ -43,7 +43,7 @@ public sealed class Arguments : ArgumentsBase
             [TGUI(Label = "Output combiner", Description = "Output combiner type")]
             public ISupportRegressionOutputCombinerFactory OutputCombiner = new MedianFactory();
 
-            // TODO: If we make this public again it should be an *estimator* of this type of predictor, rather than the (deprecated) ITrainer.
+            // REVIEW: If we make this public again it should be an *estimator* of this type of predictor, rather than the (deprecated) ITrainer.
             [Argument(ArgumentType.Multiple, HelpText = "Base predictor type", ShortName = "bp,basePredictorTypes", SortOrder = 1, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureRegressorTrainer))]
             public IComponentFactory<ITrainer<TScalarPredictor>>[] BasePredictors;
 
diff --git a/src/Microsoft.ML.Legacy/AssemblyRegistration.cs b/src/Microsoft.ML.Legacy/AssemblyRegistration.cs
@@ -28,7 +28,9 @@ public static void RegisterAssemblies(IHostEnvironment environment)
                 Contracts.Assert(_assemblyInitializer.Value);
             }
 
+#pragma warning disable CS0618 // The legacy API that internally uses dependency injection for all calls will be deleted anyway.
             AssemblyLoadingUtils.RegisterCurrentLoadedAssemblies(environment);
+#pragma warning restore CS0618
         }
 
         /// <summary>
diff --git a/src/Microsoft.ML.Maml/HelpCommand.cs b/src/Microsoft.ML.Maml/HelpCommand.cs
@@ -101,7 +101,9 @@ public void Run()
 
         public void Run(int? columns)
         {
+#pragma warning disable CS0618 // The help command should be entirely within the command line anyway.
             AssemblyLoadingUtils.LoadAndRegister(_env, _extraAssemblies);
+#pragma warning restore CCS0618
 
             using (var ch = _env.Start("Help"))
             using (var sw = new StringWriter(CultureInfo.InvariantCulture))
diff --git a/src/Microsoft.ML.Maml/MAML.cs b/src/Microsoft.ML.Maml/MAML.cs
@@ -58,7 +58,9 @@ private static int MainWithProgress(string args)
             string currentDirectory = Path.GetDirectoryName(typeof(Maml).Module.FullyQualifiedName);
 
             using (var env = CreateEnvironment())
+#pragma warning disable CS0618 // This is the command line project, so the usage here is OK.
             using (AssemblyLoadingUtils.CreateAssemblyRegistrar(env, currentDirectory))
+#pragma warning restore CS0618
             using (var progressCancel = new CancellationTokenSource())
             {
                 var progressTrackerTask = Task.Run(() => TrackProgress(env, progressCancel.Token));
diff --git a/src/Microsoft.ML.ResultProcessor/ResultProcessor.cs b/src/Microsoft.ML.ResultProcessor/ResultProcessor.cs
@@ -151,7 +151,9 @@ public void GetDefaultSettingValues(IHostEnvironment env, string predictorName,
         /// <param name="extraAssemblies"></param>
         private Dictionary<string, string> GetDefaultSettings(IHostEnvironment env, string predictorName, string[] extraAssemblies = null)
         {
+#pragma warning disable CS0618 // The result processor is an internal command line processing utility anyway, so this is, while not great, OK.
             AssemblyLoadingUtils.LoadAndRegister(env, extraAssemblies);
+#pragma warning restore CS0618
 
             var cls = env.ComponentCatalog.GetLoadableClassInfo<SignatureTrainer>(predictorName);
             if (cls == null)
@@ -1154,7 +1156,9 @@ public static int Main(string[] args)
         {
             string currentDirectory = Path.GetDirectoryName(typeof(ResultProcessor).Module.FullyQualifiedName);
             using (var env = new ConsoleEnvironment(42))
+#pragma warning disable CS0618 // The result processor is an internal command line processing utility anyway, so this is, while not great, OK.
             using (AssemblyLoadingUtils.CreateAssemblyRegistrar(env, currentDirectory))
+#pragma warning restore CS0618
                 return Main(env, args);
         }
 
@@ -1197,7 +1201,9 @@ protected static void Run(IHostEnvironment env, string[] args)
             if (cmd.IncludePerFoldResults)
                 cmd.PerFoldResultSeparator = "" + PredictionUtil.SepCharFromString(cmd.PerFoldResultSeparator);
 
+#pragma warning disable CS0618 // The result processor is an internal command line processing utility anyway, so this is, while not great, OK.
             AssemblyLoadingUtils.LoadAndRegister(env, cmd.ExtraAssemblies);
+#pragma warning restore CS0618
 
             if (cmd.Metrics.Length == 0)
                 cmd.Metrics = null;
diff --git a/src/Microsoft.ML.Sweeper/ConfigRunner.cs b/src/Microsoft.ML.Sweeper/ConfigRunner.cs
@@ -110,7 +110,9 @@ public virtual void Finish()
                 string currentDirectory = Path.GetDirectoryName(typeof(ExeConfigRunnerBase).Module.FullyQualifiedName);
 
                 using (var ch = Host.Start("Finish"))
+#pragma warning disable CS0618 // As this deals with invoking command lines, this may be OK, though this code has some other problems.
                 using (AssemblyLoadingUtils.CreateAssemblyRegistrar(Host, currentDirectory))
+#pragma warning restore CS0618
                 {
                     var runs = RunNums.ToArray();
                     var args = Utils.BuildArray(RunNums.Count + 2,
diff --git a/test/Microsoft.ML.Benchmarks/Helpers/EnvironmentFactory.cs b/test/Microsoft.ML.Benchmarks/Helpers/EnvironmentFactory.cs
@@ -5,6 +5,7 @@
 using Microsoft.ML.Core.Data;
 using Microsoft.ML.Runtime;
 using Microsoft.ML.Runtime.Data;
+using Microsoft.ML.Runtime.Training;
 using Microsoft.ML.Transforms;
 
 namespace Microsoft.ML.Benchmarks
@@ -14,7 +15,7 @@ internal static class EnvironmentFactory
         internal static MLContext CreateClassificationEnvironment<TLoader, TTransformer, TTrainer>()
            where TLoader : IDataReader<IMultiStreamSource>
            where TTransformer : ITransformer
-           where TTrainer : ITrainer
+           where TTrainer : ITrainerEstimator<ISingleFeaturePredictionTransformer<IPredictor>, IPredictor>
         {
             var ctx = new MLContext();
             IHostEnvironment environment = ctx;
@@ -30,7 +31,7 @@ internal static MLContext CreateRankingEnvironment<TEvaluator, TLoader, TTransfo
             where TEvaluator : IEvaluator
             where TLoader : IDataReader<IMultiStreamSource>
             where TTransformer : ITransformer
-            where TTrainer : ITrainer
+            where TTrainer : ITrainerEstimator<ISingleFeaturePredictionTransformer<IPredictor>, IPredictor>
         {
             var ctx = new MLContext();
             IHostEnvironment environment = ctx;
diff --git a/test/Microsoft.ML.Benchmarks/KMeansAndLogisticRegressionBench.cs b/test/Microsoft.ML.Benchmarks/KMeansAndLogisticRegressionBench.cs
@@ -3,14 +3,8 @@
 // See the LICENSE file in the project root for more information.
 
 using BenchmarkDotNet.Attributes;
-using Microsoft.ML.Runtime;
 using Microsoft.ML.Runtime.Data;
 using Microsoft.ML.Runtime.Internal.Calibration;
-using Microsoft.ML.Runtime.Learners;
-using Microsoft.ML.Trainers.KMeans;
-using Microsoft.ML.Transforms;
-using Microsoft.ML.Transforms.Categorical;
-using Microsoft.ML.Transforms.Normalizers;
 
 namespace Microsoft.ML.Benchmarks
 {
@@ -21,14 +15,10 @@ public class KMeansAndLogisticRegressionBench
         [Benchmark]
         public ParameterMixingCalibratedPredictor TrainKMeansAndLR()
         {
-            var env = new MLContext(seed: 1);
+            var ml = new MLContext(seed: 1);
             // Pipeline
-            var loader = TextLoader.ReadFile(env,
-                new TextLoader.Arguments()
-                {
-                    HasHeader = true,
-                    Separator = ",",
-                    Column = new[] {
+
+            var input = ml.Data.ReadFromTextFile(new[] {
                             new TextLoader.Column("Label", DataKind.R4, 14),
                             new TextLoader.Column("CatFeatures", DataKind.TX,
                                 new [] {
@@ -43,29 +33,23 @@ public ParameterMixingCalibratedPredictor TrainKMeansAndLR()
                                     new TextLoader.Range() { Min = 2, Max = 2 },
                                     new TextLoader.Range() { Min = 4, Max = 4 },
                                     new TextLoader.Range() { Min = 10, Max = 12 }
-                                })
-                    }
-                }, new MultiFileSource(_dataPath));
-
-            IDataView trans = new OneHotEncodingEstimator(env, "CatFeatures").Fit(loader).Transform(loader);
-
-            trans = NormalizeTransform.CreateMinMaxNormalizer(env, trans, "NumFeatures");
-            trans = new ColumnConcatenatingTransformer(env, "Features", "NumFeatures", "CatFeatures").Transform(trans);
-            trans = TrainAndScoreTransformer.Create(env, new TrainAndScoreTransformer.Arguments
+                                }),
+            }, _dataPath, s =>
             {
-                Trainer = ComponentFactoryUtils.CreateFromFunction(host =>
-                    new KMeansPlusPlusTrainer(host, "Features", advancedSettings: s=> 
-                    {
-                        s.K = 100;
-                    })),
-                FeatureColumn = "Features"
-            }, trans);
-            trans = new ColumnConcatenatingTransformer(env, "Features", "Features", "Score").Transform(trans);
+                s.HasHeader = true;
+                s.Separator = ",";
+            });
+
+            var estimatorPipeline = ml.Transforms.Categorical.OneHotEncoding("CatFeatures")
+                .Append(ml.Transforms.Normalize("NumFeatures"))
+                .Append(ml.Transforms.Concatenate("Features", "NumFeatures", "CatFeatures"))
+                .Append(ml.Clustering.Trainers.KMeans("Features"))
+                .Append(ml.Transforms.Concatenate("Features", "Features", "Score"))
+                .Append(ml.BinaryClassification.Trainers.LogisticRegression(advancedSettings: args => { args.EnforceNonNegativity = true; args.OptTol = 1e-3f; }));
 
-            // Train
-            var trainer = new LogisticRegression(env, "Label", "Features", advancedSettings: args => { args.EnforceNonNegativity = true; args.OptTol = 1e-3f; });
-            var trainRoles = new RoleMappedData(trans, label: "Label", feature: "Features");
-            return trainer.Train(trainRoles);
+            var model = estimatorPipeline.Fit(input);
+            // Return the last model in the chain.
+            return model.LastTransformer.Model;
         }
     }
 }
diff --git a/test/Microsoft.ML.Benchmarks/StochasticDualCoordinateAscentClassifierBench.cs b/test/Microsoft.ML.Benchmarks/StochasticDualCoordinateAscentClassifierBench.cs

Original file line number	Diff line number	Diff line change
`@@ -10,6 +10,8 @@`
`10`	`10`
`11`	`11`	`namespace Microsoft.ML.Runtime`
`12`	`12`	`{`
	`13`	`+ [Obsolete("The usage for this is intended for the internal command line utilities and is not intended for anything related to the API. " +`
	`14`	`+ "Please consider another way of doing whatever it is you're attempting to accomplish.")]`
`13`	`15`	`[BestFriend]`
`14`	`16`	`internal static class AssemblyLoadingUtils`
`15`	`17`	`{`
Original file line number	Diff line number	Diff line change
`@@ -9,7 +9,7 @@`
`9`	`9`
`10`	`10`	`namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners`
`11`	`11`	`{`
`12`		`- public abstract class BaseScalarStacking : BaseStacking<Single>`
	`12`	`+ internal abstract class BaseScalarStacking : BaseStacking<Single>`
`13`	`13`	`{`
`14`	`14`	`internal BaseScalarStacking(IHostEnvironment env, string name, ArgumentsBase args)`
`15`	`15`	`: base(env, name, args)`
Original file line number	Diff line number	Diff line change
`@@ -16,7 +16,7 @@`
`16`	`16`	`namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners`
`17`	`17`	`{`
`18`	`18`	`using ColumnRole = RoleMappedSchema.ColumnRole;`
`19`		`- public abstract class BaseStacking<TOutput> : IStackingTrainer<TOutput>`
	`19`	`+ internal abstract class BaseStacking<TOutput> : IStackingTrainer<TOutput>`
`20`	`20`	`{`
`21`	`21`	`public abstract class ArgumentsBase`
`22`	`22`	`{`
Original file line number	Diff line number	Diff line change
`@@ -41,7 +41,7 @@ private static VersionInfo GetVersionInfo()`
`41`	`41`	`[TlcModule.Component(Name = LoadName, FriendlyName = Stacking.UserName)]`
`42`	`42`	`public sealed class Arguments : ArgumentsBase, ISupportMulticlassOutputCombinerFactory`
`43`	`43`	`{`
`44`		`- // TODO: If we make this public again it should be an estimator of this type of predictor, rather than the (deprecated) ITrainer.`
	`44`	`+ // REVIEW: If we make this public again it should be an estimator of this type of predictor, rather than the (deprecated) ITrainer.`
`45`	`45`	`[Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,`
`46`	`46`	`Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureMultiClassClassifierTrainer))]`
`47`	`47`	`[TGUI(Label = "Base predictor")]`
Original file line number	Diff line number	Diff line change
`@@ -39,7 +39,7 @@ private static VersionInfo GetVersionInfo()`
`39`	`39`	`[TlcModule.Component(Name = LoadName, FriendlyName = Stacking.UserName)]`
`40`	`40`	`public sealed class Arguments : ArgumentsBase, ISupportRegressionOutputCombinerFactory`
`41`	`41`	`{`
`42`		`- // TODO: If we make this public again it should be an estimator of this type of predictor, rather than the (deprecated) ITrainer.`
	`42`	`+ // REVIEW: If we make this public again it should be an estimator of this type of predictor, rather than the (deprecated) ITrainer.`
`43`	`43`	`[Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,`
`44`	`44`	`Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureRegressorTrainer))]`
`45`	`45`	`[TGUI(Label = "Base predictor")]`
Original file line number	Diff line number	Diff line change
`@@ -37,7 +37,7 @@ private static VersionInfo GetVersionInfo()`
`37`	`37`	`[TlcModule.Component(Name = LoadName, FriendlyName = UserName)]`
`38`	`38`	`public sealed class Arguments : ArgumentsBase, ISupportBinaryOutputCombinerFactory`
`39`	`39`	`{`
`40`		`- // TODO: If we make this public again it should be an estimator of this type of predictor, rather than the (deprecated) ITrainer.`
	`40`	`+ // REVIEW: If we make this public again it should be an estimator of this type of predictor, rather than the (deprecated) ITrainer.`
`41`	`41`	`[Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,`
`42`	`42`	`Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureBinaryClassifierTrainer))]`
`43`	`43`	`[TGUI(Label = "Base predictor")]`