Mark EntryPoints classes and APIs as internal (#2674)

Author: ganik

src/Microsoft.ML.Core/EntryPoints/ModuleArgs.cs

@@ -650,7 +650,8 @@ public static bool IsNumericKind(DataKind kind)
     /// <summary>
     /// The untyped base class for 'maybe'.
     /// </summary>
-    public abstract class Optional
+    [BestFriend]
+    internal abstract class Optional
     {
         /// <summary>
         /// Whether the value was set 'explicitly', or 'implicitly'.
@@ -674,7 +675,8 @@ private protected Optional(bool isExplicit)
     /// the weight column to be 'Weight', we need to actually enforce the presence of the column.
     /// </summary>
     /// <typeparam name="T">The type of the value</typeparam>
-    public sealed class Optional<T> : Optional
+    [BestFriend]
+    internal sealed class Optional<T> : Optional
     {
         public readonly T Value;
 

src/Microsoft.ML.Core/EntryPoints/PredictorModel.cs

@@ -11,7 +11,8 @@ namespace Microsoft.ML.EntryPoints
     /// <summary>
     /// Base type for standard predictor model port type.
     /// </summary>
-    public abstract class PredictorModel
+    [BestFriend]
+    internal abstract class PredictorModel
     {
         [BestFriend]
         private protected PredictorModel()

src/Microsoft.ML.Core/EntryPoints/TransformModel.cs

@@ -11,7 +11,8 @@ namespace Microsoft.ML.EntryPoints
     /// <summary>
     /// Interface for standard transform model port type.
     /// </summary>
-    public abstract class TransformModel
+    [BestFriend]
+    internal abstract class TransformModel
     {
         [BestFriend]
         private protected TransformModel()

src/Microsoft.ML.Data/EntryPoints/EntryPointNode.cs

@@ -16,7 +16,7 @@
 
 namespace Microsoft.ML.EntryPoints
 {
-    public class VarSerializer : JsonConverter
+    internal class VarSerializer : JsonConverter
     {
         public override void WriteJson(JsonWriter writer, object value, JsonSerializer serializer)
         {
@@ -53,7 +53,8 @@ internal interface IVarSerializationHelper
     /// in an entry point graph.
     /// </summary>
     [JsonConverter(typeof(VarSerializer))]
-    public sealed class Var<T> : IVarSerializationHelper
+    [BestFriend]
+    internal sealed class Var<T> : IVarSerializationHelper
     {
         public string VarName { get; set; }
         bool IVarSerializationHelper.IsValue { get; }
@@ -90,7 +91,8 @@ public static bool CheckType(Type type)
     /// in an entry point graph.
     /// </summary>
     [JsonConverter(typeof(VarSerializer))]
-    public sealed class ArrayVar<T> : IVarSerializationHelper
+    [BestFriend]
+    internal sealed class ArrayVar<T> : IVarSerializationHelper
     {
         public string VarName { get; set; }
         private readonly bool _isValue;
@@ -127,7 +129,7 @@ public Var<T> this[int i]
     /// in an entry point graph.
     /// </summary>
     [JsonConverter(typeof(VarSerializer))]
-    public sealed class DictionaryVar<T> : IVarSerializationHelper
+    internal sealed class DictionaryVar<T> : IVarSerializationHelper
     {
         public string VarName { get; set; }
         bool IVarSerializationHelper.IsValue { get; }
@@ -153,7 +155,8 @@ public Var<T> this[string key]
     /// <summary>
     /// A descriptor of one 'variable' of the graph (input or output that is referenced as a $variable in the graph definition).
     /// </summary>
-    public sealed class EntryPointVariable
+    [BestFriend]
+    internal sealed class EntryPointVariable
     {
         private readonly IExceptionContext _ectx;
         public readonly string Name;
@@ -257,7 +260,8 @@ public EntryPointVariable Clone(string newName)
     /// This is populated by individual nodes when they parse their respective JSON definitions, and then the values are updated
     /// during the node execution.
     /// </summary>
-    public sealed class RunContext
+    [BestFriend]
+    internal sealed class RunContext
     {
         private readonly Dictionary<string, EntryPointVariable> _vars;
         private readonly IExceptionContext _ectx;
@@ -404,7 +408,8 @@ public EntryPointVariable CreateTempOutputVar<T>(string varPrefix)
     /// <summary>
     /// A representation of one graph node.
     /// </summary>
-    public sealed class EntryPointNode
+    [BestFriend]
+    internal sealed class EntryPointNode
     {
         // The unique node ID, generated at compilation.
         public readonly string Id;
@@ -983,7 +988,8 @@ public Tuple<Var<T>, VariableBinding> AddNewVariable<T>(string uniqueName, T val
         }
     }
 
-    public sealed class EntryPointGraph
+    [BestFriend]
+    internal sealed class EntryPointGraph
     {
         private const string RegistrationName = "EntryPointGraph";
         private readonly IHost _host;
@@ -1049,7 +1055,8 @@ public void AddNode(EntryPointNode node)
     /// or a array-indexed or dictionary-keyed value from the variable, assuming it is
     /// of an Array or Dictionary type.
     /// </summary>
-    public abstract class VariableBinding
+    [BestFriend]
+    internal abstract class VariableBinding
     {
         public string VariableName { get; private set; }
 
@@ -1124,7 +1131,8 @@ public void Rename(string newName)
         public override string ToString() => VariableName;
     }
 
-    public sealed class SimpleVariableBinding
+    [BestFriend]
+    internal sealed class SimpleVariableBinding
         : VariableBinding
     {
         public SimpleVariableBinding(string name)
@@ -1143,7 +1151,7 @@ public override string ToJson()
         }
     }
 
-    public sealed class DictionaryKeyVariableBinding
+    internal sealed class DictionaryKeyVariableBinding
         : VariableBinding
     {
         public readonly string Key;
@@ -1168,7 +1176,8 @@ public override string ToJson()
         }
     }
 
-    public sealed class ArrayIndexVariableBinding
+    [BestFriend]
+    internal sealed class ArrayIndexVariableBinding
         : VariableBinding
     {
         public readonly int Index;
@@ -1199,7 +1208,8 @@ public override string ToJson()
     /// of a yet-to-be-constructed array or dictionary EntryPoint input parameter
     /// (for example, "myVar": ["$var1", "$var2"] would yield two <see cref="ArrayIndexParameterBinding"/>: (myVar, 0), (myVar, 1))
     /// </summary>
-    public abstract class ParameterBinding
+    [BestFriend]
+    internal abstract class ParameterBinding
     {
         public readonly string ParameterName;
 
@@ -1212,7 +1222,8 @@ protected ParameterBinding(string name)
         public override string ToString() => ParameterName;
     }
 
-    public sealed class SimpleParameterBinding
+    [BestFriend]
+    internal sealed class SimpleParameterBinding
         : ParameterBinding
     {
         public SimpleParameterBinding(string name)
@@ -1233,7 +1244,7 @@ public override int GetHashCode()
         }
     }
 
-    public sealed class DictionaryKeyParameterBinding
+    internal sealed class DictionaryKeyParameterBinding
         : ParameterBinding
     {
         public readonly string Key;
@@ -1261,7 +1272,8 @@ public override int GetHashCode()
         }
     }
 
-    public sealed class ArrayIndexParameterBinding
+    [BestFriend]
+    internal sealed class ArrayIndexParameterBinding
         : ParameterBinding
     {
         public readonly int Index;

src/Microsoft.ML.Data/EntryPoints/InputBase.cs

@@ -98,7 +98,7 @@ public abstract class LearnerInputBaseWithWeight : LearnerInputBaseWithLabel
         /// Column to use for example weight.
         /// </summary>
         [Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for example weight", ShortName = "weight", SortOrder = 4, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)]
-        public Optional<string> WeightColumn = Optional<string>.Implicit(DefaultColumnNames.Weight);
+        public string WeightColumn = null;
     }
 
     /// <summary>
@@ -111,7 +111,7 @@ public abstract class UnsupervisedLearnerInputBaseWithWeight : LearnerInputBase
         /// Column to use for example weight.
         /// </summary>
         [Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for example weight", ShortName = "weight", SortOrder = 4, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)]
-        public Optional<string> WeightColumn = Optional<string>.Implicit(DefaultColumnNames.Weight);
+        public string WeightColumn = null;
     }
 
     /// <summary>
@@ -133,8 +133,8 @@ public abstract class LearnerInputBaseWithGroupId : LearnerInputBaseWithWeight
         /// <summary>
         /// Column to use for example groupId.
         /// </summary>
-        [Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for example groupId", ShortName = "groupId", SortOrder = 5, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)]
-        public Optional<string> GroupIdColumn = Optional<string>.Implicit(DefaultColumnNames.GroupId);
+        [Argument(ArgumentType.AtMostOnce, Name = "GroupIdColumn", HelpText = "Column to use for example groupId", ShortName = "groupId", SortOrder = 5, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)]
+        public string GroupIdColumn = null;
     }
 
     [BestFriend]
@@ -275,23 +275,23 @@ public interface ITrainerInputWithLabel : ITrainerInput
         /// </summary>
         public interface IUnsupervisedTrainerWithWeight : ITrainerInput
         {
-            Optional<string> WeightColumn { get; }
+            string WeightColumn { get; }
         }
 
         /// <summary>
         /// Interface that all API trainer input classes will implement.
         /// </summary>
         public interface ITrainerInputWithWeight : ITrainerInputWithLabel
         {
-            Optional<string> WeightColumn { get; }
+            string WeightColumn { get; }
         }
 
         /// <summary>
         /// Interface that all API trainer input classes will implement.
         /// </summary>
         public interface ITrainerInputWithGroupId : ITrainerInputWithWeight
         {
-            Optional<string> GroupIdColumn { get; }
+            string GroupIdColumn { get; }
         }
 
         /// <summary>

src/Microsoft.ML.Data/EntryPoints/InputBuilder.cs

@@ -18,7 +18,7 @@ namespace Microsoft.ML.EntryPoints.JsonUtils
     /// required values. The values can be set from their JSON representation (during the graph parsing stage), as well as directly
     /// (in the process of graph execution).
     /// </summary>
-    public sealed class InputBuilder
+    internal sealed class InputBuilder
     {
         private readonly struct Attributes
         {
@@ -646,7 +646,7 @@ public object GetInstance()
     /// This class wraps around the output object type, does not create an instance, and provides utility methods for field type checking
     /// and extracting values.
     /// </summary>
-    public sealed class OutputHelper
+    internal sealed class OutputHelper
     {
         private readonly IExceptionContext _ectx;
         private readonly Type _type;
@@ -736,7 +736,8 @@ public JObject GetJsonObject(Dictionary<string, string> outputMap)
     /// <summary>
     /// These are the common field names used in the JSON objects for defining the manifest.
     /// </summary>
-    public static class FieldNames
+    [BestFriend]
+    internal static class FieldNames
     {
         public const string Nodes = "Nodes";
         public const string Kind = "Kind";

src/Microsoft.ML.Data/Training/TrainerUtils.cs

@@ -389,17 +389,6 @@ public static SchemaShape.Column MakeR4ScalarWeightColumn(string weightColumn)
             return new SchemaShape.Column(weightColumn, SchemaShape.Column.VectorKind.Scalar, NumberDataViewType.Single, false);
         }
 
-        /// <summary>
-        /// The <see cref="SchemaShape.Column"/> for the weight column.
-        /// </summary>
-        /// <param name="weightColumn">name of the weight column</param>
-        public static SchemaShape.Column MakeR4ScalarWeightColumn(Optional<string> weightColumn)
-        {
-            if (weightColumn == null || weightColumn.Value == null || !weightColumn.IsExplicit)
-                return default;
-            return new SchemaShape.Column(weightColumn, SchemaShape.Column.VectorKind.Scalar, NumberDataViewType.Single, false);
-        }
-
         /// <summary>
         /// This is a shim class to translate the more contemporaneous <see cref="ITrainerEstimator{TTransformer, TPredictor}"/>
         /// style transformers into the older now disfavored <see cref="ITrainer{TPredictor}"/> idiom, for components that still

src/Microsoft.ML.FastTree/FastTree.cs

@@ -124,12 +124,8 @@ private protected FastTreeTrainerBase(IHostEnvironment env,
 
             FastTreeTrainerOptions.LabelColumn = label.Name;
             FastTreeTrainerOptions.FeatureColumn = featureColumn;
-
-            if (weightColumn != null)
-                FastTreeTrainerOptions.WeightColumn = Optional<string>.Explicit(weightColumn);
-
-            if (groupIdColumn != null)
-                FastTreeTrainerOptions.GroupIdColumn = Optional<string>.Explicit(groupIdColumn);
+            FastTreeTrainerOptions.WeightColumn = weightColumn;
+            FastTreeTrainerOptions.GroupIdColumn = groupIdColumn;
 
             // The discretization step renders this trainer non-parametric, and therefore it does not need normalization.
             // Also since it builds its own internal discretized columnar structures, it cannot benefit from caching.

src/Microsoft.ML.HalLearners/HalLearnersCatalog.cs

@@ -39,7 +39,7 @@ public static OlsLinearRegressionTrainer OrdinaryLeastSquares(this RegressionCat
             {
                 LabelColumn = labelColumnName,
                 FeatureColumn = featureColumnName,
-                WeightColumn = weightColumn != null ? Optional<string>.Explicit(weightColumn) : Optional<string>.Implicit(DefaultColumnNames.Weight)
+                WeightColumn = weightColumn
             };
 
             return new OlsLinearRegressionTrainer(env, options);

src/Microsoft.ML.KMeansClustering/KMeansCatalog.cs

@@ -38,7 +38,7 @@ public static KMeansPlusPlusTrainer KMeans(this ClusteringCatalog.ClusteringTrai
             var options = new KMeansPlusPlusTrainer.Options
             {
                 FeatureColumn = featureColumn,
-                WeightColumn = weights != null ? Optional<string>.Explicit(weights) : Optional<string>.Implicit(DefaultColumnNames.Weight),
+                WeightColumn = weights,
                 ClustersCount = clustersCount
             };
             return new KMeansPlusPlusTrainer(env, options);