Creation of components through MLContext and cleanup (GcnNorm, LpNorm, RandomFourier, CustomStopWords, VectorWhiten, PCA)

src/Microsoft.ML.Data/Transforms/BootstrapSamplingTransformer.cs

@@ -13,7 +13,7 @@
 using Microsoft.ML.Model;
 using Microsoft.ML.Transforms;
 
-[assembly: LoadableClass(BootstrapSamplingTransformer.Summary, typeof(BootstrapSamplingTransformer), typeof(BootstrapSamplingTransformer.Arguments), typeof(SignatureDataTransform),
+[assembly: LoadableClass(BootstrapSamplingTransformer.Summary, typeof(BootstrapSamplingTransformer), typeof(BootstrapSamplingTransformer.Options), typeof(SignatureDataTransform),
     BootstrapSamplingTransformer.UserName, "BootstrapSampleTransform", "BootstrapSample")]
 
 [assembly: LoadableClass(BootstrapSamplingTransformer.Summary, typeof(BootstrapSamplingTransformer), null, typeof(SignatureLoadDataTransform),
@@ -36,7 +36,7 @@ internal static class Defaults
             public const int PoolSize = 1000;
         }
 
-        public sealed class Arguments : TransformInputBase
+        public sealed class Options : TransformInputBase
         {
             [Argument(ArgumentType.AtMostOnce, HelpText = "Whether this is the out-of-bag sample, that is, all those rows that are not selected by the transform.",
                 ShortName = "comp")]
@@ -76,16 +76,16 @@ private static VersionInfo GetVersionInfo()
         private readonly bool _shuffleInput;
         private readonly int _poolSize;
 
-        public BootstrapSamplingTransformer(IHostEnvironment env, Arguments args, IDataView input)
+        public BootstrapSamplingTransformer(IHostEnvironment env, Options options, IDataView input)
             : base(env, RegistrationName, input)
         {
-            Host.CheckValue(args, nameof(args));
-            Host.CheckUserArg(args.PoolSize >= 0, nameof(args.PoolSize), "Cannot be negative");
+            Host.CheckValue(options, nameof(options));
+            Host.CheckUserArg(options.PoolSize >= 0, nameof(options.PoolSize), "Cannot be negative");
 
-            _complement = args.Complement;
-            _state = new TauswortheHybrid.State(args.Seed ?? (uint)Host.Rand.Next());
-            _shuffleInput = args.ShuffleInput;
-            _poolSize = args.PoolSize;
+            _complement = options.Complement;
+            _state = new TauswortheHybrid.State(options.Seed ?? (uint)Host.Rand.Next());
+            _shuffleInput = options.ShuffleInput;
+            _poolSize = options.PoolSize;
         }
 
         /// <summary>
@@ -103,7 +103,7 @@ public BootstrapSamplingTransformer(IHostEnvironment env,
             uint? seed = null,
             bool shuffleInput = Defaults.ShuffleInput,
             int poolSize = Defaults.PoolSize)
-            : this(env, new Arguments() { Complement = complement, Seed = seed, ShuffleInput = shuffleInput, PoolSize = poolSize }, input)
+            : this(env, new Options() { Complement = complement, Seed = seed, ShuffleInput = shuffleInput, PoolSize = poolSize }, input)
         {
         }
 
@@ -242,7 +242,7 @@ protected override bool MoveNextCore()
     internal static class BootstrapSample
     {
         [TlcModule.EntryPoint(Name = "Transforms.ApproximateBootstrapSampler", Desc = BootstrapSamplingTransformer.Summary, UserName = BootstrapSamplingTransformer.UserName, ShortName = BootstrapSamplingTransformer.RegistrationName)]
-        public static CommonOutputs.TransformOutput GetSample(IHostEnvironment env, BootstrapSamplingTransformer.Arguments input)
+        public static CommonOutputs.TransformOutput GetSample(IHostEnvironment env, BootstrapSamplingTransformer.Options input)
         {
             Contracts.CheckValue(env, nameof(env));
             env.CheckValue(input, nameof(input));

src/Microsoft.ML.Data/Transforms/RowShufflingTransformer.cs

@@ -15,7 +15,7 @@
 using Microsoft.ML.Model;
 using Microsoft.ML.Transforms;
 
-[assembly: LoadableClass(RowShufflingTransformer.Summary, typeof(RowShufflingTransformer), typeof(RowShufflingTransformer.Arguments), typeof(SignatureDataTransform),
+[assembly: LoadableClass(RowShufflingTransformer.Summary, typeof(RowShufflingTransformer), typeof(RowShufflingTransformer.Options), typeof(SignatureDataTransform),
     "Shuffle Transform", "ShuffleTransform", "Shuffle", "shuf")]
 
 [assembly: LoadableClass(RowShufflingTransformer.Summary, typeof(RowShufflingTransformer), null, typeof(SignatureLoadDataTransform),
@@ -30,7 +30,8 @@ namespace Microsoft.ML.Transforms
     /// rows in the input cursor, and then, successively, the output cursor will yield one
     /// of these rows and replace it with another row from the input.
     /// </summary>
-    public sealed class RowShufflingTransformer : RowToRowTransformBase
+    [BestFriend]
+    internal sealed class RowShufflingTransformer : RowToRowTransformBase
     {
         private static class Defaults
         {
@@ -39,7 +40,7 @@ private static class Defaults
             public const bool ForceShuffle = false;
         }
 
-        public sealed class Arguments
+        public sealed class Options
         {
             // REVIEW: A more intelligent heuristic, based on the expected size of the inputs, perhaps?
             [Argument(ArgumentType.LastOccurenceWins, HelpText = "The pool will have this many rows", ShortName = "rows")]
@@ -99,14 +100,14 @@ public RowShufflingTransformer(IHostEnvironment env,
             int poolRows = Defaults.PoolRows,
             bool poolOnly = Defaults.PoolOnly,
             bool forceShuffle = Defaults.ForceShuffle)
-            : this(env, new Arguments() { PoolRows = poolRows, PoolOnly = poolOnly, ForceShuffle = forceShuffle }, input)
+            : this(env, new Options() { PoolRows = poolRows, PoolOnly = poolOnly, ForceShuffle = forceShuffle }, input)
         {
         }
 
         /// <summary>
         /// Public constructor corresponding to SignatureDataTransform.
         /// </summary>
-        public RowShufflingTransformer(IHostEnvironment env, Arguments args, IDataView input)
+        public RowShufflingTransformer(IHostEnvironment env, Options args, IDataView input)
             : base(env, RegistrationName, input)
         {
             Host.CheckValue(args, nameof(args));

src/Microsoft.ML.Ensemble/Selector/SubsetSelector/BootstrapSelector.cs

@@ -47,7 +47,7 @@ public override IEnumerable<Subset> GetSubsets(Batch batch, Random rand)
             for (int i = 0; i < Size; i++)
             {
                 // REVIEW: Consider ways to reintroduce "balanced" samples.
-                var viewTrain = new BootstrapSamplingTransformer(Host, new BootstrapSamplingTransformer.Arguments(), Data.Data);
+                var viewTrain = new BootstrapSamplingTransformer(Host, new BootstrapSamplingTransformer.Options(), Data.Data);
                 var dataTrain = new RoleMappedData(viewTrain, Data.Schema.GetColumnRoleNames());
                 yield return FeatureSelector.SelectFeatures(dataTrain, rand);
             }

src/Microsoft.ML.HalLearners.StaticPipe/VectorWhiteningStaticExtensions.cs

@@ -49,9 +49,9 @@ public override IEstimator<ITransformer> Reconcile(IHostEnvironment env,
             {
                 Contracts.Assert(toOutput.Length == 1);
 
-                var infos = new VectorWhiteningTransformer.ColumnInfo[toOutput.Length];
+                var infos = new VectorWhiteningEstimator.ColumnInfo[toOutput.Length];
                 for (int i = 0; i < toOutput.Length; i++)
-                    infos[i] = new VectorWhiteningTransformer.ColumnInfo(outputNames[toOutput[i]], inputNames[((OutPipelineColumn)toOutput[i]).Input], _kind, _eps, _maxRows, _pcaNum);
+                    infos[i] = new VectorWhiteningEstimator.ColumnInfo(outputNames[toOutput[i]], inputNames[((OutPipelineColumn)toOutput[i]).Input], _kind, _eps, _maxRows, _pcaNum);
 
                 return new VectorWhiteningEstimator(env, infos);
             }
@@ -63,18 +63,18 @@ public override IEstimator<ITransformer> Reconcile(IHostEnvironment env,
         /// <param name="maxRows">Maximum number of rows used to train the transform.</param>
         /// <param name="pcaNum">In case of PCA whitening, indicates the number of components to retain.</param>
         public static Vector<float> PcaWhitening(this Vector<float> input,
-            float eps = VectorWhiteningTransformer.Defaults.Eps,
-            int maxRows = VectorWhiteningTransformer.Defaults.MaxRows,
-            int pcaNum = VectorWhiteningTransformer.Defaults.PcaNum)
+            float eps = VectorWhiteningEstimator.Defaults.Eps,
+            int maxRows = VectorWhiteningEstimator.Defaults.MaxRows,
+            int pcaNum = VectorWhiteningEstimator.Defaults.PcaNum)
             => new OutPipelineColumn(input, WhiteningKind.Pca, eps, maxRows, pcaNum);
 
         /// <include file='../Microsoft.ML.HalLearners/doc.xml' path='doc/members/member[@name="Whitening"]/*'/>
         /// <param name="input">The column to which the transform will be applied.</param>
         /// <param name="eps">Whitening constant, prevents division by zero.</param>
         /// <param name="maxRows">Maximum number of rows used to train the transform.</param>
         public static Vector<float> ZcaWhitening(this Vector<float> input,
-            float eps = VectorWhiteningTransformer.Defaults.Eps,
-            int maxRows = VectorWhiteningTransformer.Defaults.MaxRows)
-            => new OutPipelineColumn(input, WhiteningKind.Zca, eps, maxRows, VectorWhiteningTransformer.Defaults.PcaNum);
+            float eps = VectorWhiteningEstimator.Defaults.Eps,
+            int maxRows = VectorWhiteningEstimator.Defaults.MaxRows)
+            => new OutPipelineColumn(input, WhiteningKind.Zca, eps, maxRows, VectorWhiteningEstimator.Defaults.PcaNum);
     }
 }

src/Microsoft.ML.HalLearners/HalLearnersCatalog.cs

@@ -112,10 +112,10 @@ public static SymSgdClassificationTrainer SymbolicStochasticGradientDescent(
         /// </format>
         /// </example>
         public static VectorWhiteningEstimator VectorWhiten(this TransformsCatalog.ProjectionTransforms catalog, string outputColumnName, string inputColumnName = null,
-            WhiteningKind kind = VectorWhiteningTransformer.Defaults.Kind,
-            float eps = VectorWhiteningTransformer.Defaults.Eps,
-            int maxRows = VectorWhiteningTransformer.Defaults.MaxRows,
-            int pcaNum = VectorWhiteningTransformer.Defaults.PcaNum)
+            WhiteningKind kind = VectorWhiteningEstimator.Defaults.Kind,
+            float eps = VectorWhiteningEstimator.Defaults.Eps,
+            int maxRows = VectorWhiteningEstimator.Defaults.MaxRows,
+            int pcaNum = VectorWhiteningEstimator.Defaults.PcaNum)
                 => new VectorWhiteningEstimator(CatalogUtils.GetEnvironment(catalog), outputColumnName, inputColumnName, kind, eps, maxRows, pcaNum);
 
         /// <summary>
@@ -124,7 +124,7 @@ public static VectorWhiteningEstimator VectorWhiten(this TransformsCatalog.Proje
         /// </summary>
         /// <param name="catalog">The transform's catalog.</param>
         /// <param name="columns">Describes the parameters of the whitening process for each column pair.</param>
-        public static VectorWhiteningEstimator VectorWhiten(this TransformsCatalog.ProjectionTransforms catalog, params VectorWhiteningTransformer.ColumnInfo[] columns)
+        public static VectorWhiteningEstimator VectorWhiten(this TransformsCatalog.ProjectionTransforms catalog, params VectorWhiteningEstimator.ColumnInfo[] columns)
             => new VectorWhiteningEstimator(CatalogUtils.GetEnvironment(catalog), columns);
 
     }

src/Microsoft.ML.HalLearners/SymSgdClassificationTrainer.cs

@@ -141,7 +141,7 @@ private RoleMappedData PrepareDataFromTrainingExamples(IChannel ch, RoleMappedDa
                 idvToFeedTrain = idvToShuffle;
             else
             {
-                var shuffleArgs = new RowShufflingTransformer.Arguments
+                var shuffleArgs = new RowShufflingTransformer.Options
                 {
                     PoolOnly = false,
                     ForceShuffle = _options.Shuffle