Pass objects as arguments instead of delegate

abgoswam · abgoswam · commit b255eb3e7b9b · 2019-01-07T02:34:57.000Z
diff --git a/src/Microsoft.ML.FastTree/BoostingFastTree.cs b/src/Microsoft.ML.FastTree/BoostingFastTree.cs
@@ -44,7 +44,7 @@ protected BoostingFastTreeTrainerBase(IHostEnvironment env,
             string featureColumn,
             string weightColumn,
             string groupIdColumn,
-            Action<TArgs> advancedSettings)
+            TArgs advancedSettings)
             : base(env, label, featureColumn, weightColumn, groupIdColumn, advancedSettings)
         {
         }
diff --git a/src/Microsoft.ML.FastTree/FastTree.cs b/src/Microsoft.ML.FastTree/FastTree.cs
@@ -155,13 +155,10 @@ private protected FastTreeTrainerBase(IHostEnvironment env,
             string featureColumn,
             string weightColumn,
             string groupIdColumn,
-            Action<TArgs> advancedSettings)
+            TArgs advancedSettings)
             : base(Contracts.CheckRef(env, nameof(env)).Register(RegisterName), TrainerUtils.MakeR4VecFeature(featureColumn), label, TrainerUtils.MakeR4ScalarWeightColumn(weightColumn), TrainerUtils.MakeU4ScalarColumn(groupIdColumn))
         {
-            Args = new TArgs();
-
-            //apply the advanced args, if the user supplied any
-            advancedSettings?.Invoke(Args);
+            Args = advancedSettings;
 
             Args.LabelColumn = label.Name;
             Args.FeatureColumn = featureColumn;
diff --git a/src/Microsoft.ML.FastTree/FastTreeClassification.cs b/src/Microsoft.ML.FastTree/FastTreeClassification.cs
@@ -148,12 +148,12 @@ public FastTreeBinaryClassificationTrainer(IHostEnvironment env,
         /// <param name="labelColumn">The name of the label column.</param>
         /// <param name="featureColumn">The name of the feature column.</param>
         /// <param name="weightColumn">The name for the column containing the initial weight.</param>
-        /// <param name="advancedSettings">A delegate to apply all the advanced arguments to the algorithm.</param>
+        /// <param name="advancedSettings">Advanced arguments to the algorithm.</param>
         public FastTreeBinaryClassificationTrainer(IHostEnvironment env,
             string labelColumn,
             string featureColumn,
             string weightColumn,
-            Action<Options> advancedSettings)
+            Options advancedSettings)
             : base(env, TrainerUtils.MakeBoolScalarLabel(labelColumn), featureColumn, weightColumn, null, advancedSettings)
         {
             // Set the sigmoid parameter to the 2 * learning rate, for traditional FastTreeClassification loss
diff --git a/src/Microsoft.ML.FastTree/FastTreeRanking.cs b/src/Microsoft.ML.FastTree/FastTreeRanking.cs
@@ -93,13 +93,13 @@ public FastTreeRankingTrainer(IHostEnvironment env,
         /// <param name="featureColumn">The name of the feature column.</param>
         /// <param name="groupIdColumn">The name for the column containing the group ID. </param>
         /// <param name="weightColumn">The name for the column containing the initial weight.</param>
-        /// <param name="advancedSettings">A delegate to apply all the advanced arguments to the algorithm.</param>
+        /// <param name="advancedSettings">Advanced arguments to the algorithm.</param>
         public FastTreeRankingTrainer(IHostEnvironment env,
             string labelColumn,
             string featureColumn,
             string groupIdColumn,
             string weightColumn,
-            Action<Options> advancedSettings = null)
+            Options advancedSettings)
             : base(env, TrainerUtils.MakeR4ScalarColumn(labelColumn), featureColumn, weightColumn, groupIdColumn, advancedSettings)
         {
             Host.CheckNonEmpty(groupIdColumn, nameof(groupIdColumn));
diff --git a/src/Microsoft.ML.FastTree/FastTreeRegression.cs b/src/Microsoft.ML.FastTree/FastTreeRegression.cs
@@ -81,12 +81,12 @@ public FastTreeRegressionTrainer(IHostEnvironment env,
         /// <param name="labelColumn">The name of the label column.</param>
         /// <param name="featureColumn">The name of the feature column.</param>
         /// <param name="weightColumn">The name for the column containing the initial weight.</param>
-        /// <param name="advancedSettings">A delegate to apply all the advanced arguments to the algorithm.</param>
+        /// <param name="advancedSettings">Advanced arguments to the algorithm.</param>
         public FastTreeRegressionTrainer(IHostEnvironment env,
             string labelColumn,
             string featureColumn,
             string weightColumn,
-            Action<Options> advancedSettings = null)
+            Options advancedSettings)
             : base(env, TrainerUtils.MakeR4ScalarColumn(labelColumn), featureColumn, weightColumn, null, advancedSettings)
         {
         }
diff --git a/src/Microsoft.ML.FastTree/FastTreeTweedie.cs b/src/Microsoft.ML.FastTree/FastTreeTweedie.cs
@@ -82,12 +82,12 @@ public FastTreeTweedieTrainer(IHostEnvironment env,
         /// <param name="labelColumn">The name of the label column.</param>
         /// <param name="featureColumn">The name of the feature column.</param>
         /// <param name="weightColumn">The name for the column containing the initial weight.</param>
-        /// <param name="advancedSettings">A delegate to apply all the advanced arguments to the algorithm.</param>
+        /// <param name="advancedSettings">Advanced arguments to the algorithm.</param>
         public FastTreeTweedieTrainer(IHostEnvironment env,
             string labelColumn,
             string featureColumn,
             string weightColumn,
-            Action<Options> advancedSettings)
+            Options advancedSettings)
             : base(env, TrainerUtils.MakeR4ScalarColumn(labelColumn), featureColumn, weightColumn, null, advancedSettings)
         {
             Host.CheckNonEmpty(labelColumn, nameof(labelColumn));
diff --git a/src/Microsoft.ML.FastTree/RandomForest.cs b/src/Microsoft.ML.FastTree/RandomForest.cs
@@ -50,7 +50,7 @@ protected RandomForestTrainerBase(IHostEnvironment env,
             string featureColumn,
             string weightColumn,
             string groupIdColumn,
-            Action<TArgs> advancedSettings,
+            TArgs advancedSettings,
             bool quantileEnabled = false)
             : base(env, label, featureColumn, weightColumn, null, advancedSettings)
         {
diff --git a/src/Microsoft.ML.FastTree/RandomForestClassification.cs b/src/Microsoft.ML.FastTree/RandomForestClassification.cs
@@ -166,12 +166,12 @@ public FastForestClassification(IHostEnvironment env,
         /// <param name="labelColumn">The name of the label column.</param>
         /// <param name="featureColumn">The name of the feature column.</param>
         /// <param name="weightColumn">The name for the column containing the initial weight.</param>
-        /// <param name="advancedSettings">A delegate to apply all the advanced arguments to the algorithm.</param>
+        /// <param name="advancedSettings">Advanced arguments to the algorithm.</param>
         public FastForestClassification(IHostEnvironment env,
             string labelColumn,
             string featureColumn,
             string weightColumn,
-            Action<Options> advancedSettings)
+            Options advancedSettings)
             : base(env, TrainerUtils.MakeBoolScalarLabel(labelColumn), featureColumn, weightColumn, null, advancedSettings)
         {
             Host.CheckNonEmpty(labelColumn, nameof(labelColumn));
diff --git a/src/Microsoft.ML.FastTree/RandomForestRegression.cs b/src/Microsoft.ML.FastTree/RandomForestRegression.cs
@@ -184,12 +184,12 @@ public FastForestRegression(IHostEnvironment env,
         /// <param name="labelColumn">The name of the label column.</param>
         /// <param name="featureColumn">The name of the feature column.</param>
         /// <param name="weightColumn">The optional name for the column containing the initial weight.</param>
-        /// <param name="advancedSettings">A delegate to apply all the advanced arguments to the algorithm.</param>
+        /// <param name="advancedSettings">Advanced arguments to the algorithm.</param>
         public FastForestRegression(IHostEnvironment env,
             string labelColumn,
             string featureColumn,
             string weightColumn,
-            Action<Options> advancedSettings)
+            Options advancedSettings)
             : base(env, TrainerUtils.MakeR4ScalarColumn(labelColumn), featureColumn, weightColumn, null, advancedSettings)
         {
             Host.CheckNonEmpty(labelColumn, nameof(labelColumn));
diff --git a/src/Microsoft.ML.FastTree/TreeTrainersCatalog.cs b/src/Microsoft.ML.FastTree/TreeTrainersCatalog.cs
@@ -50,7 +50,7 @@ public static FastTreeRegressionTrainer FastTree(this RegressionContext.Regressi
             string labelColumn,
             string featureColumn,
             string weights,
-            Action<FastTreeRegressionTrainer.Options> advancedSettings)
+            FastTreeRegressionTrainer.Options advancedSettings)
         {
             Contracts.CheckValue(ctx, nameof(ctx));
             var env = CatalogUtils.GetEnvironment(ctx);
@@ -94,7 +94,7 @@ public static FastTreeBinaryClassificationTrainer FastTree(this BinaryClassifica
             string labelColumn,
             string featureColumn,
             string weights,
-            Action<FastTreeBinaryClassificationTrainer.Options> advancedSettings)
+            FastTreeBinaryClassificationTrainer.Options advancedSettings)
         {
             Contracts.CheckValue(ctx, nameof(ctx));
             var env = CatalogUtils.GetEnvironment(ctx);
@@ -142,7 +142,7 @@ public static FastTreeRankingTrainer FastTree(this RankingContext.RankingTrainer
             string featureColumn,
             string groupId,
             string weights,
-            Action<FastTreeRankingTrainer.Options> advancedSettings)
+            FastTreeRankingTrainer.Options advancedSettings)
         {
             Contracts.CheckValue(ctx, nameof(ctx));
             var env = CatalogUtils.GetEnvironment(ctx);
@@ -236,7 +236,7 @@ public static FastTreeTweedieTrainer FastTreeTweedie(this RegressionContext.Regr
             string labelColumn,
             string featureColumn,
             string weights,
-            Action<FastTreeTweedieTrainer.Options> advancedSettings = null)
+            FastTreeTweedieTrainer.Options advancedSettings = null)
         {
             Contracts.CheckValue(ctx, nameof(ctx));
             var env = CatalogUtils.GetEnvironment(ctx);
@@ -280,7 +280,7 @@ public static FastForestRegression FastForest(this RegressionContext.RegressionT
             string labelColumn,
             string featureColumn,
             string weights,
-            Action<FastForestRegression.Options> advancedSettings = null)
+            FastForestRegression.Options advancedSettings = null)
         {
             Contracts.CheckValue(ctx, nameof(ctx));
             var env = CatalogUtils.GetEnvironment(ctx);
@@ -324,7 +324,7 @@ public static FastForestClassification FastForest(this BinaryClassificationConte
             string labelColumn,
             string featureColumn,
             string weights,
-            Action<FastForestClassification.Options> advancedSettings)
+            FastForestClassification.Options advancedSettings)
         {
             Contracts.CheckValue(ctx, nameof(ctx));
             var env = CatalogUtils.GetEnvironment(ctx);
diff --git a/src/Microsoft.ML.StaticPipe/TreeTrainersStatic.cs b/src/Microsoft.ML.StaticPipe/TreeTrainersStatic.cs
@@ -84,10 +84,11 @@ public static Scalar<float> FastTree(this RegressionContext.RegressionTrainers c
         /// </example>
         public static Scalar<float> FastTree(this RegressionContext.RegressionTrainers ctx,
             Scalar<float> label, Vector<float> features, Scalar<float> weights,
-            Action<FastTreeRegressionTrainer.Options> advancedSettings,
+            FastTreeRegressionTrainer.Options advancedSettings,
             Action<FastTreeRegressionModelParameters> onFit = null)
         {
-            CheckUserValues(label, features, weights, advancedSettings, onFit);
+            Contracts.CheckValueOrNull(advancedSettings);
+            CheckUserValues(label, features, weights, onFit);
 
             var rec = new TrainerEstimatorReconciler.Regression(
                (env, labelName, featuresName, weightsName) =>
@@ -175,10 +176,11 @@ public static (Scalar<float> score, Scalar<float> probability, Scalar<bool> pred
         /// </example>
         public static (Scalar<float> score, Scalar<float> probability, Scalar<bool> predictedLabel) FastTree(this BinaryClassificationContext.BinaryClassificationTrainers ctx,
             Scalar<bool> label, Vector<float> features, Scalar<float> weights,
-            Action<FastTreeBinaryClassificationTrainer.Options> advancedSettings,
+            FastTreeBinaryClassificationTrainer.Options advancedSettings,
             Action<IPredictorWithFeatureWeights<float>> onFit = null)
         {
-            CheckUserValues(label, features, weights, advancedSettings, onFit);
+            Contracts.CheckValueOrNull(advancedSettings);
+            CheckUserValues(label, features, weights, onFit);
 
             var rec = new TrainerEstimatorReconciler.BinaryClassifier(
                (env, labelName, featuresName, weightsName) =>
@@ -254,10 +256,11 @@ public static Scalar<float> FastTree<TVal>(this RankingContext.RankingTrainers c
         /// <returns>The Score output column indicating the predicted value.</returns>
         public static Scalar<float> FastTree<TVal>(this RankingContext.RankingTrainers ctx,
             Scalar<float> label, Vector<float> features, Key<uint, TVal> groupId, Scalar<float> weights,
-            Action<FastTreeRankingTrainer.Options> advancedSettings,
+            FastTreeRankingTrainer.Options advancedSettings,
             Action<FastTreeRankingModelParameters> onFit = null)
         {
-            CheckUserValues(label, features, weights, advancedSettings, onFit);
+            Contracts.CheckValueOrNull(advancedSettings);
+            CheckUserValues(label, features, weights, onFit);
 
             var rec = new TrainerEstimatorReconciler.Ranker<TVal>(
                (env, labelName, featuresName, groupIdName, weightsName) =>
@@ -289,13 +292,11 @@ internal static void CheckUserValues(PipelineColumn label, Vector<float> feature
         }
 
         internal static void CheckUserValues(PipelineColumn label, Vector<float> features, Scalar<float> weights,
-            Delegate advancedSettings,
             Delegate onFit)
         {
             Contracts.CheckValue(label, nameof(label));
             Contracts.CheckValue(features, nameof(features));
             Contracts.CheckValueOrNull(weights);
-            Contracts.CheckValueOrNull(advancedSettings);
             Contracts.CheckValueOrNull(onFit);
         }
     }
diff --git a/src/Microsoft.ML.Sweeper/Algorithms/SmacSweeper.cs b/src/Microsoft.ML.Sweeper/Algorithms/SmacSweeper.cs
@@ -136,11 +136,11 @@ private FastForestRegressionModelParameters FitModel(IEnumerable<IRunResult> pre
                 // Set relevant random forest arguments.
                 // Train random forest.
                 var trainer = new FastForestRegression(_host, DefaultColumnNames.Label, DefaultColumnNames.Features, null,
-                    advancedSettings: s =>
+                    new FastForestRegression.Options
                     {
-                        s.FeatureFraction = _args.SplitRatio;
-                        s.NumTrees = _args.NumOfTrees;
-                        s.MinDocumentsInLeafs = _args.NMinForSplit;
+                        FeatureFraction = _args.SplitRatio,
+                        NumTrees = _args.NumOfTrees,
+                        MinDocumentsInLeafs = _args.NMinForSplit,
                     });
                 var predictor = trainer.Train(data);
 
diff --git a/test/Microsoft.ML.Tests/Scenarios/OvaTest.cs b/test/Microsoft.ML.Tests/Scenarios/OvaTest.cs
@@ -105,7 +105,7 @@ public void OvaFastTree()
             var pipeline = new Ova(
                 mlContext,
                 new FastTreeBinaryClassificationTrainer(mlContext, DefaultColumnNames.Label, DefaultColumnNames.Features, null,
-                    advancedSettings: s => { s.NumThreads = 1; }),
+                    new FastTreeBinaryClassificationTrainer.Options { NumThreads = 1 }),
                 useProbabilities: false);
 
             var model = pipeline.Fit(data);
diff --git a/test/Microsoft.ML.Tests/TrainerEstimators/TreeEstimators.cs b/test/Microsoft.ML.Tests/TrainerEstimators/TreeEstimators.cs
@@ -25,10 +25,10 @@ public void FastTreeBinaryEstimator()
             var (pipe, dataView) = GetBinaryClassificationPipeline();
 
             var trainer = new FastTreeBinaryClassificationTrainer(Env, DefaultColumnNames.Label, DefaultColumnNames.Features, null,
-                advancedSettings: s =>  {
-                    s.NumThreads = 1;
-                    s.NumTrees = 10;
-                    s.NumLeaves = 5;
+                new FastTreeBinaryClassificationTrainer.Options { 
+                    NumThreads = 1,
+                    NumTrees = 10,
+                    NumLeaves = 5,
                 });
 
             var pipeWithTrainer = pipe.Append(trainer);
@@ -83,11 +83,12 @@ public void FastForestClassificationEstimator()
         {
             var (pipe, dataView) = GetBinaryClassificationPipeline();
 
-            var trainer = new FastForestClassification(Env, DefaultColumnNames.Label, DefaultColumnNames.Features, null, advancedSettings: s =>
-            {
-                s.NumLeaves = 10;
-                s.NumTrees = 20;
-            });
+            var trainer = new FastForestClassification(Env, DefaultColumnNames.Label, DefaultColumnNames.Features, null, 
+                new FastForestClassification.Options { 
+                    NumLeaves = 10,
+                    NumTrees = 20,
+                });
+
             var pipeWithTrainer = pipe.Append(trainer);
             TestEstimatorCore(pipeWithTrainer, dataView);
 
@@ -104,8 +105,7 @@ public void FastTreeRankerEstimator()
         {
             var (pipe, dataView) = GetRankingPipeline();
 
-            var trainer = new FastTreeRankingTrainer(Env, "Label0", "NumericFeatures", "Group", null,
-                                advancedSettings: s => { s.NumTrees = 10; });
+            var trainer = new FastTreeRankingTrainer(Env, "Label0", "NumericFeatures", "Group", null, new FastTreeRankingTrainer.Options { NumTrees = 10 });
             var pipeWithTrainer = pipe.Append(trainer);
             TestEstimatorCore(pipeWithTrainer, dataView);
 
@@ -139,12 +139,8 @@ public void LightGBMRankerEstimator()
         public void FastTreeRegressorEstimator()
         {
             var dataView = GetRegressionPipeline();
-            var trainer = new FastTreeRegressionTrainer(Env, DefaultColumnNames.Label, DefaultColumnNames.Features, null, advancedSettings: s =>
-            {
-                s.NumTrees = 10;
-                s.NumThreads = 1;
-                s.NumLeaves = 5;
-            });
+            var trainer = new FastTreeRegressionTrainer(Env, DefaultColumnNames.Label, DefaultColumnNames.Features, null,
+                new FastTreeRegressionTrainer.Options { NumTrees = 10, NumThreads = 1, NumLeaves = 5 });
 
             TestEstimatorCore(trainer, dataView);
             var model = trainer.Train(dataView, dataView);
@@ -196,11 +192,11 @@ public void GAMRegressorEstimator()
         public void TweedieRegressorEstimator()
         {
             var dataView = GetRegressionPipeline();
-            var trainer = new FastTreeTweedieTrainer(Env, "Label", "Features", null, advancedSettings: s =>
-            {
-                s.EntropyCoefficient = 0.3;
-                s.OptimizationAlgorithm = BoostedTreeArgs.OptimizationAlgorithmType.AcceleratedGradientDescent;
-            });
+            var trainer = new FastTreeTweedieTrainer(Env, "Label", "Features", null, 
+                new FastTreeTweedieTrainer.Options { 
+                    EntropyCoefficient = 0.3,
+                    OptimizationAlgorithm = BoostedTreeArgs.OptimizationAlgorithmType.AcceleratedGradientDescent,
+                });
 
             TestEstimatorCore(trainer, dataView);
             var model = trainer.Train(dataView, dataView);
@@ -214,11 +210,11 @@ public void TweedieRegressorEstimator()
         public void FastForestRegressorEstimator()
         {
             var dataView = GetRegressionPipeline();
-            var trainer = new FastForestRegression(Env, DefaultColumnNames.Label, DefaultColumnNames.Features, null, advancedSettings: s =>
-            {
-                s.BaggingSize = 2;
-                s.NumTrees = 10;
-            });
+            var trainer = new FastForestRegression(Env, DefaultColumnNames.Label, DefaultColumnNames.Features, null, 
+                new FastForestRegression.Options { 
+                    BaggingSize = 2,
+                    NumTrees = 10,
+                });
 
             TestEstimatorCore(trainer, dataView);
             var model = trainer.Train(dataView, dataView);

Original file line number	Diff line number	Diff line change
`@@ -44,7 +44,7 @@ protected BoostingFastTreeTrainerBase(IHostEnvironment env,`
`44`	`44`	`string featureColumn,`
`45`	`45`	`string weightColumn,`
`46`	`46`	`string groupIdColumn,`
`47`		`- Action<TArgs> advancedSettings)`
	`47`	`+ TArgs advancedSettings)`
`48`	`48`	`: base(env, label, featureColumn, weightColumn, groupIdColumn, advancedSettings)`
`49`	`49`	`{`
`50`	`50`	`}`
Original file line number	Diff line number	Diff line change
`@@ -50,7 +50,7 @@ protected RandomForestTrainerBase(IHostEnvironment env,`
`50`	`50`	`string featureColumn,`
`51`	`51`	`string weightColumn,`
`52`	`52`	`string groupIdColumn,`
`53`		`- Action<TArgs> advancedSettings,`
	`53`	`+ TArgs advancedSettings,`
`54`	`54`	`bool quantileEnabled = false)`
`55`	`55`	`: base(env, label, featureColumn, weightColumn, null, advancedSettings)`
`56`	`56`	`{`