Internalize more stray members in the data assembly (#2936)

src/Microsoft.ML.Data/Commands/EvaluateCommand.cs

@@ -27,7 +27,8 @@ namespace Microsoft.ML.Data
     /// This class contains information about an overall metric, namely its name and whether it is a vector
     /// metric or not.
     /// </summary>
-    public sealed class MetricColumn
+    [BestFriend]
+    internal sealed class MetricColumn
     {
         /// <summary>
         /// An enum specifying whether the metric should be maximized or minimized while sweeping. 'Info' should be
@@ -186,7 +187,7 @@ public sealed class Arguments : DataCommand.ArgumentsBase
             public string NameColumn = DefaultColumnNames.Name;
 
             [Argument(ArgumentType.LastOccurenceWins, HelpText = "Columns with custom kinds declared through key assignments, for example, col[Kind]=Name to assign column named 'Name' kind 'Kind'",
-                Name ="CustomColumn", ShortName = "col", SortOrder = 10)]
+                Name = "CustomColumn", ShortName = "col", SortOrder = 10)]
             public KeyValuePair<string, string>[] CustomColumns;
 
             [Argument(ArgumentType.Multiple, HelpText = "Evaluator to use", ShortName = "eval", SignatureType = typeof(SignatureMamlEvaluator))]

src/Microsoft.ML.Data/Commands/TrainCommand.cs

@@ -25,7 +25,8 @@ namespace Microsoft.ML.Data
 {
     using ColumnRole = RoleMappedSchema.ColumnRole;
 
-    public enum NormalizeOption
+    [BestFriend]
+    internal enum NormalizeOption
     {
         No,
         Warn,

src/Microsoft.ML.Data/DataLoadSave/TrivialLoaderEstimator.cs

@@ -7,7 +7,7 @@ namespace Microsoft.ML.Data
     /// <summary>
     /// The trivial wrapper for a <see cref="IDataLoader{TSource}"/> that acts as an estimator and ignores the source.
     /// </summary>
-    public sealed class TrivialLoaderEstimator<TSource, TLoader> : IDataLoaderEstimator<TSource, TLoader>
+    internal sealed class TrivialLoaderEstimator<TSource, TLoader> : IDataLoaderEstimator<TSource, TLoader>
         where TLoader : IDataLoader<TSource>
     {
         public TLoader Loader { get; }

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

@@ -35,7 +35,8 @@ namespace Microsoft.ML.Transforms
     /// If all the slots are to be dropped, a vector valued column will be changed to a vector of length 1 (a scalar column will retain its type) and
     /// the value will be the default value.
     /// </summary>
-    public sealed class SlotsDroppingTransformer : OneToOneTransformerBase
+    [BestFriend]
+    internal sealed class SlotsDroppingTransformer : OneToOneTransformerBase
     {
         internal sealed class Options
         {

src/Microsoft.ML.StandardTrainers/Standard/MultiClass/OneVersusAllTrainer.cs

@@ -241,9 +241,10 @@ private static VersionInfo GetVersionInfo()
         /// <see cref="Softmax"/>: Generate probability by feeding raw outputs to softmax function. Output is [z_1, ..., z_n], where z_i is exp(y_i) / (exp(y_1) + ... + exp(y_n)).
         /// </para>
         /// </summary>
-        public enum OutputFormula { Raw = 0, ProbabilityNormalization = 1, Softmax = 2 };
-        private readonly DataViewType _outputType;
-        private DataViewType DistType => _outputType;
+        [BestFriend]
+        internal enum OutputFormula { Raw = 0, ProbabilityNormalization = 1, Softmax = 2 };
+
+        private DataViewType DistType { get; }
 
         bool ICanSavePfa.CanSavePfa => _impl.CanSavePfa;
 
@@ -313,7 +314,7 @@ private OneVersusAllModelParameters(IHostEnvironment env, ImplBase impl)
             Host.Assert(Utils.Size(impl.Predictors) > 0);
 
             _impl = impl;
-            _outputType = new VectorType(NumberDataViewType.Single, _impl.Predictors.Length);
+            DistType = new VectorType(NumberDataViewType.Single, _impl.Predictors.Length);
         }
 
         private OneVersusAllModelParameters(IHostEnvironment env, ModelLoadContext ctx)
@@ -339,7 +340,7 @@ private OneVersusAllModelParameters(IHostEnvironment env, ModelLoadContext ctx)
                 _impl = new ImplRaw(predictors);
             }
 
-            _outputType = new VectorType(NumberDataViewType.Single, _impl.Predictors.Length);
+            DistType = new VectorType(NumberDataViewType.Single, _impl.Predictors.Length);
         }
 
         private static OneVersusAllModelParameters Create(IHostEnvironment env, ModelLoadContext ctx)
@@ -389,7 +390,7 @@ DataViewType IValueMapper.InputType
 
         DataViewType IValueMapper.OutputType
         {
-            get { return _outputType; }
+            get { return DistType; }
         }
         ValueMapper<TIn, TOut> IValueMapper.GetMapper<TIn, TOut>()
         {