Move Learner* input base and Transform* input base out of Entrypoints…

docs/samples/Microsoft.ML.Samples/Dynamic/Trainers/BinaryClassification/FieldAwareFactorizationMachinewWithOptions.cs

@@ -32,8 +32,8 @@ public static void Example()
                     FieldAwareFactorizationMachine(
                         new FieldAwareFactorizationMachineBinaryClassificationTrainer.Options
                         {
-                            FeatureColumn = "Features",
-                            LabelColumn = "Sentiment",
+                            FeatureColumnName = "Features",
+                            LabelColumnName = "Sentiment",
                             LearningRate = 0.1f,
                             NumberOfIterations = 10
                         }));

docs/samples/Microsoft.ML.Samples/Dynamic/Trainers/BinaryClassification/SDCALogisticRegression.cs

@@ -62,8 +62,8 @@ public static void Example()
             var advancedPipeline = mlContext.Transforms.Text.FeaturizeText("SentimentText", "Features")
                                   .Append(mlContext.BinaryClassification.Trainers.StochasticDualCoordinateAscent(
                                       new SdcaBinaryTrainer.Options { 
-                                        LabelColumn = "Sentiment",
-                                        FeatureColumn = "Features",
+                                        LabelColumnName = "Sentiment",
+                                        FeatureColumnName = "Features",
                                         ConvergenceTolerance = 0.01f,  // The learning rate for adjusting bias from being regularized
                                         NumThreads = 2, // Degree of lock-free parallelism 
                                       }));

docs/samples/Microsoft.ML.Samples/Dynamic/Trainers/MulticlassClassification/LightGbmWithOptions.cs

@@ -35,8 +35,8 @@ public static void Example()
             var pipeline = mlContext.Transforms.Conversion.MapValueToKey("LabelIndex", "Label")
                         .Append(mlContext.MulticlassClassification.Trainers.LightGbm(new Options
                         {
-                            LabelColumn = "LabelIndex",
-                            FeatureColumn = "Features",
+                            LabelColumnName = "LabelIndex",
+                            FeatureColumnName = "Features",
                             Booster = new DartBooster.Options
                             {
                                 DropRate = 0.15,

docs/samples/Microsoft.ML.Samples/Dynamic/Trainers/Regression/LightGbmWithOptions.cs

@@ -38,7 +38,7 @@ public static void Example()
             var pipeline = mlContext.Transforms.Concatenate("Features", featureNames)
                            .Append(mlContext.Regression.Trainers.LightGbm(new Options
                            {
-                               LabelColumn = labelName,
+                               LabelColumnName = labelName,
                                NumLeaves = 4,
                                MinDataPerLeaf = 6,
                                LearningRate = 0.001,

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

@@ -9,6 +9,7 @@
 using Microsoft.ML.Data;
 using Microsoft.ML.Data.IO;
 using Microsoft.ML.EntryPoints;
+using Microsoft.ML.Transforms;
 
 [assembly: LoadableClass(typeof(void), typeof(Cache), null, typeof(SignatureEntryPointModule), "Cache")]
 namespace Microsoft.ML.EntryPoints

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

@@ -509,9 +509,9 @@ private EntryPointNode(IHostEnvironment env, IChannel ch, RunContext context,
                 throw _host.Except($"The following required inputs were not provided: {String.Join(", ", missing)}");
 
             var inputInstance = _inputBuilder.GetInstance();
-            SetColumnArgument(ch, inputInstance, "LabelColumn", label, "label", typeof(CommonInputs.ITrainerInputWithLabel));
-            SetColumnArgument(ch, inputInstance, "GroupIdColumn", group, "group Id", typeof(CommonInputs.ITrainerInputWithGroupId));
-            SetColumnArgument(ch, inputInstance, "WeightColumn", weight, "weight", typeof(CommonInputs.ITrainerInputWithWeight), typeof(CommonInputs.IUnsupervisedTrainerWithWeight));
+            SetColumnArgument(ch, inputInstance, "LabelColumnName", label, "label", typeof(CommonInputs.ITrainerInputWithLabel));
+            SetColumnArgument(ch, inputInstance, "RowGroupColumnName", group, "group Id", typeof(CommonInputs.ITrainerInputWithGroupId));
+            SetColumnArgument(ch, inputInstance, "ExampleWeightColumnName", weight, "weight", typeof(CommonInputs.ITrainerInputWithWeight), typeof(CommonInputs.IUnsupervisedTrainerWithWeight));
             SetColumnArgument(ch, inputInstance, "NameColumn", name, "name");
 
             // Validate outputs.

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

@@ -9,24 +9,10 @@
 using Microsoft.ML.CommandLine;
 using Microsoft.ML.Data;
 using Microsoft.ML.Data.IO;
+using Microsoft.ML.Trainers;
 
 namespace Microsoft.ML.EntryPoints
 {
-    /// <summary>
-    /// The base class for all transform inputs.
-    /// </summary>
-    [TlcModule.EntryPointKind(typeof(CommonInputs.ITransformInput))]
-    public abstract class TransformInputBase
-    {
-        /// <summary>
-        /// The input dataset. Used only in entry-point methods, since the normal API mechanism for feeding in a dataset to
-        /// create an <see cref="ITransformer"/> is to use the <see cref="IEstimator{TTransformer}.Fit(IDataView)"/> method.
-        /// </summary>
-        [BestFriend]
-        [Argument(ArgumentType.Required, HelpText = "Input dataset", Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly, SortOrder = 1)]
-        internal IDataView Data;
-    }
-
     [BestFriend]
     internal enum CachingOptions
     {
@@ -36,89 +22,12 @@ internal enum CachingOptions
         None
     }
 
-    /// <summary>
-    /// The base class for all learner inputs.
-    /// </summary>
-    [TlcModule.EntryPointKind(typeof(CommonInputs.ITrainerInput))]
-    public abstract class LearnerInputBase
-    {
-        /// <summary>
-        /// The data to be used for training. Used only in entry-points, since in the API the expected mechanism is
-        /// that the user will use the <see cref="IEstimator{TTransformer}.Fit(IDataView)"/> or some other train
-        /// method.
-        /// </summary>
-        [BestFriend]
-        [Argument(ArgumentType.Required, ShortName = "data", HelpText = "The data to be used for training", SortOrder = 1, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)]
-        internal IDataView TrainingData;
-
-        /// <summary>
-        /// Column to use for features.
-        /// </summary>
-        [Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for features", ShortName = "feat", SortOrder = 2, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)]
-        public string FeatureColumn = DefaultColumnNames.Features;
-
-        /// <summary>
-        /// Normalize option for the feature column. Used only in entry-points, since in the API the user is expected to do this themselves.
-        /// </summary>
-        [BestFriend]
-        [Argument(ArgumentType.AtMostOnce, HelpText = "Normalize option for the feature column", ShortName = "norm", SortOrder = 5, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)]
-        internal NormalizeOption NormalizeFeatures = NormalizeOption.Auto;
-
-        /// <summary>
-        /// Whether learner should cache input training data. Used only in entry-points, since the intended API mechanism
-        /// is that the user will use the <see cref="DataOperationsCatalog.Cache(IDataView, string[])"/> or other method
-        /// like <see cref="EstimatorChain{TLastTransformer}.AppendCacheCheckpoint(IHostEnvironment)"/>.
-        /// </summary>
-        [BestFriend]
-        [Argument(ArgumentType.LastOccurenceWins, HelpText = "Whether learner should cache input training data", ShortName = "cache", SortOrder = 6, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)]
-        internal CachingOptions Caching = CachingOptions.Auto;
-    }
-
-    /// <summary>
-    /// The base class for all learner inputs that support a Label column.
-    /// </summary>
-    [TlcModule.EntryPointKind(typeof(CommonInputs.ITrainerInputWithLabel))]
-    public abstract class LearnerInputBaseWithLabel : LearnerInputBase
-    {
-        /// <summary>
-        /// Column to use for labels.
-        /// </summary>
-        [Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for labels", ShortName = "lab", SortOrder = 3, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)]
-        public string LabelColumn = DefaultColumnNames.Label;
-    }
-
-    // REVIEW: This is a known antipattern, but the solution involves the decorator pattern which can't be used in this case.
-    /// <summary>
-    /// The base class for all learner inputs that support a weight column.
-    /// </summary>
-    [TlcModule.EntryPointKind(typeof(CommonInputs.ITrainerInputWithWeight))]
-    public abstract class LearnerInputBaseWithWeight : LearnerInputBaseWithLabel
-    {
-        /// <summary>
-        /// The name of the example weight column.
-        /// </summary>
-        [Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for example weight", ShortName = "weight", SortOrder = 4, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)]
-        public string WeightColumn = null;
-    }
-
-    /// <summary>
-    /// The base class for all unsupervised learner inputs that support a weight column.
-    /// </summary>
-    [TlcModule.EntryPointKind(typeof(CommonInputs.IUnsupervisedTrainerWithWeight))]
-    public abstract class UnsupervisedLearnerInputBaseWithWeight : LearnerInputBase
-    {
-        /// <summary>
-        /// 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 string WeightColumn = null;
-    }
-
     /// <summary>
     /// The base class for all evaluators inputs.
     /// </summary>
     [TlcModule.EntryPointKind(typeof(CommonInputs.IEvaluatorInput))]
-    public abstract class EvaluateInputBase
+    [BestFriend]
+    internal abstract class EvaluateInputBase
     {
         [Argument(ArgumentType.Required, ShortName = "data", HelpText = "The data to be used for evaluation.", SortOrder = 1, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)]
         public IDataView Data;
@@ -127,18 +36,8 @@ public abstract class EvaluateInputBase
         public string NameColumn = DefaultColumnNames.Name;
     }
 
-    [TlcModule.EntryPointKind(typeof(CommonInputs.ITrainerInputWithGroupId))]
-    public abstract class LearnerInputBaseWithGroupId : LearnerInputBaseWithWeight
-    {
-        /// <summary>
-        /// Column to use for example groupId.
-        /// </summary>
-        [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]
-    internal static class LearnerEntryPointsUtils
+    internal static class TrainerEntryPointsUtils
     {
         public static string FindColumn(IExceptionContext ectx, DataViewSchema schema, Optional<string> value)
         {
@@ -166,13 +65,13 @@ public static TOut Train<TArg, TOut>(IHost host, TArg input,
             Func<IEnumerable<KeyValuePair<RoleMappedSchema.ColumnRole, string>>> getCustom = null,
             ICalibratorTrainerFactory calibrator = null,
             int maxCalibrationExamples = 0)
-            where TArg : LearnerInputBase
+            where TArg : TrainerInputBase
             where TOut : CommonOutputs.TrainerOutput, new()
         {
             using (var ch = host.Start("Training"))
             {
                 var schema = input.TrainingData.Schema;
-                var feature = FindColumn(ch, schema, input.FeatureColumn);
+                var feature = FindColumn(ch, schema, input.FeatureColumnName);
                 var label = getLabel?.Invoke();
                 var weight = getWeight?.Invoke();
                 var group = getGroup?.Invoke();

src/Microsoft.ML.Data/Prediction/Calibrator.cs

@@ -19,6 +19,7 @@
 using Microsoft.ML.Model;
 using Microsoft.ML.Model.OnnxConverter;
 using Microsoft.ML.Model.Pfa;
+using Microsoft.ML.Transforms;
 using Newtonsoft.Json.Linq;
 
 [assembly: LoadableClass(PlattCalibratorTrainer.Summary, typeof(PlattCalibratorTrainer), null, typeof(SignatureCalibrator),

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

@@ -0,0 +1,113 @@
+// Licensed to the .NET Foundation under one or more agreements.
+// The .NET Foundation licenses this file to you under the MIT license.
+// See the LICENSE file in the project root for more information.
+
+using System;
+using System.Collections.Generic;
+using Microsoft.Data.DataView;
+using Microsoft.ML.Calibrators;
+using Microsoft.ML.CommandLine;
+using Microsoft.ML.Data;
+using Microsoft.ML.Data.IO;
+using Microsoft.ML.EntryPoints;
+
+namespace Microsoft.ML.Trainers
+{
+    /// <summary>
+    /// The base class for all trainer inputs.
+    /// </summary>
+    [TlcModule.EntryPointKind(typeof(CommonInputs.ITrainerInput))]
+    public abstract class TrainerInputBase
+    {
+        private protected TrainerInputBase() { }
+
+        /// <summary>
+        /// The data to be used for training. Used only in entry-points, since in the API the expected mechanism is
+        /// that the user will use the <see cref="IEstimator{TTransformer}.Fit(IDataView)"/> or some other train
+        /// method.
+        /// </summary>
+        [BestFriend]
+        [Argument(ArgumentType.Required, ShortName = "data", HelpText = "The data to be used for training", SortOrder = 1, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)]
+        internal IDataView TrainingData;
+
+        /// <summary>
+        /// Column to use for features.
+        /// </summary>
+        [Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for features", ShortName = "feat", SortOrder = 2, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)]
+        public string FeatureColumnName = DefaultColumnNames.Features;
+
+        /// <summary>
+        /// Normalize option for the feature column. Used only in entry-points, since in the API the user is expected to do this themselves.
+        /// </summary>
+        [BestFriend]
+        [Argument(ArgumentType.AtMostOnce, HelpText = "Normalize option for the feature column", ShortName = "norm", SortOrder = 5, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)]
+        internal NormalizeOption NormalizeFeatures = NormalizeOption.Auto;
+
+        /// <summary>
+        /// Whether learner should cache input training data. Used only in entry-points, since the intended API mechanism
+        /// is that the user will use the <see cref="DataOperationsCatalog.Cache(IDataView, string[])"/> or other method
+        /// like <see cref="EstimatorChain{TLastTransformer}.AppendCacheCheckpoint(IHostEnvironment)"/>.
+        /// </summary>
+        [BestFriend]
+        [Argument(ArgumentType.LastOccurenceWins, HelpText = "Whether learner should cache input training data", ShortName = "cache", SortOrder = 6, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)]
+        internal CachingOptions Caching = CachingOptions.Auto;
+    }
+
+    /// <summary>
+    /// The base class for all learner inputs that support a Label column.
+    /// </summary>
+    [TlcModule.EntryPointKind(typeof(CommonInputs.ITrainerInputWithLabel))]
+    public abstract class TrainerInputBaseWithLabel : TrainerInputBase
+    {
+        private protected TrainerInputBaseWithLabel() { }
+
+        /// <summary>
+        /// Column to use for labels.
+        /// </summary>
+        [Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for labels", ShortName = "lab", SortOrder = 3, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)]
+        public string LabelColumnName = DefaultColumnNames.Label;
+    }
+
+    // REVIEW: This is a known antipattern, but the solution involves the decorator pattern which can't be used in this case.
+    /// <summary>
+    /// The base class for all learner inputs that support a weight column.
+    /// </summary>
+    [TlcModule.EntryPointKind(typeof(CommonInputs.ITrainerInputWithWeight))]
+    public abstract class TrainerInputBaseWithWeight : TrainerInputBaseWithLabel
+    {
+        private protected TrainerInputBaseWithWeight() { }
+
+        /// <summary>
+        /// 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 string ExampleWeightColumnName = null;
+    }
+
+    /// <summary>
+    /// The base class for all unsupervised learner inputs that support a weight column.
+    /// </summary>
+    [TlcModule.EntryPointKind(typeof(CommonInputs.IUnsupervisedTrainerWithWeight))]
+    public abstract class UnsupervisedTrainerInputBaseWithWeight : TrainerInputBase
+    {
+        private protected UnsupervisedTrainerInputBaseWithWeight() { }
+
+        /// <summary>
+        /// 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 string ExampleWeightColumnName = null;
+    }
+
+    [TlcModule.EntryPointKind(typeof(CommonInputs.ITrainerInputWithGroupId))]
+    public abstract class TrainerInputBaseWithGroupId : TrainerInputBaseWithWeight
+    {
+        private protected TrainerInputBaseWithGroupId() { }
+
+        /// <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 string RowGroupColumnName = null;
+    }
+}

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

@@ -13,6 +13,7 @@
 using Microsoft.ML.Internal.Internallearn;
 using Microsoft.ML.Internal.Utilities;
 using Microsoft.ML.Model;
+using Microsoft.ML.Transforms;
 
 [assembly: LoadableClass(FeatureContributionCalculatingTransformer.Summary, typeof(FeatureContributionCalculatingTransformer), null, typeof(SignatureLoadModel),
     FeatureContributionCalculatingTransformer.FriendlyName, FeatureContributionCalculatingTransformer.LoaderSignature)]

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

@@ -9,6 +9,7 @@
 using Microsoft.ML.Data;
 using Microsoft.ML.EntryPoints;
 using Microsoft.ML.Model;
+using Microsoft.ML.Transforms;
 
 [assembly: LoadableClass(NopTransform.Summary, typeof(NopTransform), null, typeof(SignatureLoadDataTransform),
     "", NopTransform.LoaderSignature)]

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

@@ -0,0 +1,27 @@
+// Licensed to the .NET Foundation under one or more agreements.
+// The .NET Foundation licenses this file to you under the MIT license.
+// See the LICENSE file in the project root for more information.
+
+using Microsoft.Data.DataView;
+using Microsoft.ML.CommandLine;
+using Microsoft.ML.EntryPoints;
+
+namespace Microsoft.ML.Transforms
+{
+    /// <summary>
+    /// The base class for all transform inputs.
+    /// </summary>
+    [TlcModule.EntryPointKind(typeof(CommonInputs.ITransformInput))]
+    public abstract class TransformInputBase
+    {
+        private protected TransformInputBase() { }
+
+        /// <summary>
+        /// The input dataset. Used only in entry-point methods, since the normal API mechanism for feeding in a dataset to
+        /// create an <see cref="ITransformer"/> is to use the <see cref="IEstimator{TTransformer}.Fit(IDataView)"/> method.
+        /// </summary>
+        [BestFriend]
+        [Argument(ArgumentType.Required, HelpText = "Input dataset", Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly, SortOrder = 1)]
+        internal IDataView Data;
+    }
+}