Rearrangements, review comments.

Author: TomFinley

src/Microsoft.ML.Core/Prediction/ITrainer.cs

@@ -26,47 +26,6 @@ namespace Microsoft.ML.Runtime
     public delegate void SignatureSequenceTrainer();
     public delegate void SignatureMatrixRecommendingTrainer();
 
-    /// <summary>
-    /// Interface to provide extra information about a trainer.
-    /// </summary>
-    public interface ITrainerEx : ITrainer
-    {
-        // REVIEW: Ideally trainers should be able to communicate
-        // something about the type of data they are capable of being trained
-        // on, e.g., what ColumnKinds they want, how many of each, of what type,
-        // etc. This interface seems like the most natural conduit for that sort
-        // of extra information.
-
-        // REVIEW: Can we please have consistent naming here?
-        // 'Need' vs. 'Want' looks arbitrary to me, and it's grammatically more correct to
-        // be 'Needs' / 'Wants' anyway.
-
-        /// <summary>
-        /// Whether the trainer needs to see data in normalized form.
-        /// </summary>
-        bool NeedNormalization { get; }
-
-        /// <summary>
-        /// Whether the trainer needs calibration to produce probabilities.
-        /// </summary>
-        bool NeedCalibration { get; }
-
-        /// <summary>
-        /// Whether this trainer could benefit from a cached view of the data.
-        /// </summary>
-        bool WantCaching { get; }
-
-        bool SupportsValidation { get; }
-        bool SupportsIncrementalTraining { get; }
-    }
-
-    // The Trainer (of Factory) can optionally implement this.
-    public interface IModelCombiner<TModel, TPredictor>
-        where TPredictor : IPredictor
-    {
-        TPredictor CombineModels(IEnumerable<TModel> models);
-    }
-
     public delegate void SignatureModelCombiner(PredictionKind kind);
 
     /// <summary>
@@ -130,6 +89,58 @@ public static TPredictor Train<TPredictor>(this ITrainer<TPredictor> trainer, Ro
             => trainer.Train(new TrainContext(trainData));
     }
 
+    /// <summary>
+    /// Interface to provide extra information about a trainer.
+    /// </summary>
+    public interface ITrainerEx : ITrainer
+    {
+        // REVIEW: Ideally trainers should be able to communicate
+        // something about the type of data they are capable of being trained
+        // on, e.g., what ColumnKinds they want, how many of each, of what type,
+        // etc. This interface seems like the most natural conduit for that sort
+        // of extra information.
+
+        // REVIEW: Can we please have consistent naming here?
+        // 'Need' vs. 'Want' looks arbitrary to me, and it's grammatically more correct to
+        // be 'Needs' / 'Wants' anyway.
+
+        /// <summary>
+        /// Whether the trainer needs to see data in normalized form.
+        /// </summary>
+        bool NeedNormalization { get; }
+
+        /// <summary>
+        /// Whether the trainer needs calibration to produce probabilities.
+        /// </summary>
+        bool NeedCalibration { get; }
+
+        /// <summary>
+        /// Whether this trainer could benefit from a cached view of the data.
+        /// </summary>
+        bool WantCaching { get; }
+
+        /// <summary>
+        /// Whether the trainer supports validation sets via <see cref="TrainContext.ValidationSet"/>.
+        /// Not implementing this interface and returning <c>true</c> from this property is an indication
+        /// the trainer does not support that.
+        /// </summary>
+        bool SupportsValidation { get; }
+
+        /// <summary>
+        /// Whether the trainer can support incremental trainers via <see cref="TrainContext.InitialPredictor"/>.
+        /// Not implementing this interface and returning <c>true</c> from this property is an indication
+        /// the trainer does not support that.
+        /// </summary>
+        bool SupportsIncrementalTraining { get; }
+    }
+
+    // A trainer can optionally implement this to indicate it can combine multiple models into a single predictor.
+    public interface IModelCombiner<TModel, TPredictor>
+        where TPredictor : IPredictor
+    {
+        TPredictor CombineModels(IEnumerable<TModel> models);
+    }
+
     /// <summary>
     /// Interface implemented by the MetalinearLearners base class.
     /// Used to distinguish the MetaLinear Learners from the other learners