Adding extensions for Hal learners. More namespace re-ogr. (#1370)

* Adding extensions for Hal learners. More namespace re-org.

Author: sfilipi

src/Microsoft.ML.Ensemble/Trainer/Binary/EnsembleTrainer.cs

@@ -13,7 +13,7 @@
 using Microsoft.ML.Runtime.Ensemble.Selector;
 using Microsoft.ML.Runtime.EntryPoints;
 using Microsoft.ML.Runtime.Internal.Internallearn;
-using Microsoft.ML.Runtime.Learners;
+using Microsoft.ML.Trainers.Online;
 
 [assembly: LoadableClass(EnsembleTrainer.Summary, typeof(EnsembleTrainer), typeof(EnsembleTrainer.Arguments),
     new[] { typeof(SignatureBinaryClassifierTrainer), typeof(SignatureTrainer) },

src/Microsoft.ML.Ensemble/Trainer/Regression/RegressionEnsembleTrainer.cs

@@ -13,7 +13,7 @@
 using Microsoft.ML.Runtime.Ensemble.OutputCombiners;
 using Microsoft.ML.Runtime.Ensemble.Selector;
 using Microsoft.ML.Runtime.Internal.Internallearn;
-using Microsoft.ML.Runtime.Learners;
+using Microsoft.ML.Trainers.Online;
 
 [assembly: LoadableClass(typeof(RegressionEnsembleTrainer), typeof(RegressionEnsembleTrainer.Arguments),
     new[] { typeof(SignatureRegressorTrainer), typeof(SignatureTrainer) },

src/Microsoft.ML.FastTree/FastTreeCatalog.cs

@@ -19,7 +19,7 @@ public static class FastTreeRegressionExtensions
         /// </summary>
         /// <param name="ctx">The <see cref="RegressionContext"/>.</param>
         /// <param name="label">The label column.</param>
-        /// <param name="features">The features colum.</param>
+        /// <param name="features">The features column.</param>
         /// <param name="weights">The optional weights column.</param>
         /// <param name="numTrees">Total number of decision trees to create in the ensemble.</param>
         /// <param name="numLeaves">The maximum number of leaves per decision tree.</param>
@@ -50,7 +50,7 @@ public static class FastTreeBinaryClassificationExtensions
         /// </summary>
         /// <param name="ctx">The <see cref="BinaryClassificationContext"/>.</param>
         /// <param name="label">The label column.</param>
-        /// <param name="features">The features colum.</param>
+        /// <param name="features">The features column.</param>
         /// <param name="weights">The optional weights column.</param>
         /// <param name="numTrees">Total number of decision trees to create in the ensemble.</param>
         /// <param name="numLeaves">The maximum number of leaves per decision tree.</param>
@@ -81,7 +81,7 @@ public static class FastTreeRankingExtensions
         /// </summary>
         /// <param name="ctx">The <see cref="RegressionContext"/>.</param>
         /// <param name="label">The label column.</param>
-        /// <param name="features">The features colum.</param>
+        /// <param name="features">The features column.</param>
         /// <param name="groupId">The groupId column.</param>
         /// <param name="weights">The optional weights column.</param>
         /// <param name="advancedSettings">Algorithm advanced settings.</param>

src/Microsoft.ML.FastTree/FastTreeStatic.cs

@@ -22,7 +22,7 @@ public static class FastTreeRegressionExtensions
         /// </summary>
         /// <param name="ctx">The <see cref="RegressionContext"/>.</param>
         /// <param name="label">The label column.</param>
-        /// <param name="features">The features colum.</param>
+        /// <param name="features">The features column.</param>
         /// <param name="weights">The optional weights column.</param>
         /// <param name="numTrees">Total number of decision trees to create in the ensemble.</param>
         /// <param name="numLeaves">The maximum number of leaves per decision tree.</param>
@@ -75,7 +75,7 @@ public static class FastTreeBinaryClassificationExtensions
         /// </summary>
         /// <param name="ctx">The <see cref="BinaryClassificationContext"/>.</param>
         /// <param name="label">The label column.</param>
-        /// <param name="features">The features colum.</param>
+        /// <param name="features">The features column.</param>
         /// <param name="weights">The optional weights column.</param>
         /// <param name="numTrees">Total number of decision trees to create in the ensemble.</param>
         /// <param name="numLeaves">The maximum number of leaves per decision tree.</param>
@@ -125,7 +125,7 @@ public static class FastTreeRankingExtensions
         /// </summary>
         /// <param name="ctx">The <see cref="RegressionContext"/>.</param>
         /// <param name="label">The label column.</param>
-        /// <param name="features">The features colum.</param>
+        /// <param name="features">The features column.</param>
         /// <param name="groupId">The groupId column.</param>
         /// <param name="weights">The optional weights column.</param>
         /// <param name="numTrees">Total number of decision trees to create in the ensemble.</param>

src/Microsoft.ML.HalLearners/HalLearnersCatalog.cs

@@ -0,0 +1,54 @@
+// 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.ML.Runtime;
+using Microsoft.ML.Runtime.Data;
+using Microsoft.ML.Trainers.HalLearners;
+using Microsoft.ML.Trainers.SymSgd;
+using System;
+
+namespace Microsoft.ML
+{
+    /// <summary>
+    /// The trainer context extensions for the <see cref="OlsLinearRegressionTrainer"/> and <see cref="SymSgdClassificationTrainer"/>.
+    /// </summary>
+    public static class HalLearnersCatalog
+    {
+        /// <summary>
+        /// Predict a target using a linear regression model trained with the <see cref="OlsLinearRegressionTrainer"/>.
+        /// </summary>
+        /// <param name="ctx">The <see cref="RegressionContext"/>.</param>
+        /// <param name="label">The label column.</param>
+        /// <param name="features">The features column.</param>
+        /// <param name="weights">The weights column.</param>
+        /// <param name="advancedSettings">Algorithm advanced settings.</param>
+        public static OlsLinearRegressionTrainer OrdinaryLeastSquares(this RegressionContext.RegressionTrainers ctx,
+            string label,
+            string features,
+            string weights = null,
+            Action<OlsLinearRegressionTrainer.Arguments> advancedSettings = null)
+        {
+            Contracts.CheckValue(ctx, nameof(ctx));
+            var env = CatalogUtils.GetEnvironment(ctx);
+            return new OlsLinearRegressionTrainer(env, label, features, weights, advancedSettings);
+        }
+
+        /// <summary>
+        /// Predict a target using a linear regression model trained with the <see cref="SymSgdClassificationTrainer"/>.
+        /// </summary>
+        /// <param name="ctx">The <see cref="RegressionContext"/>.</param>
+        /// <param name="label">The label column.</param>
+        /// <param name="features">The features column.</param>
+        /// <param name="advancedSettings">Algorithm advanced settings.</param>
+        public static SymSgdClassificationTrainer SymbolicStochasticGradientDescent(this RegressionContext.RegressionTrainers ctx,
+            string label,
+            string features,
+            Action<SymSgdClassificationTrainer.Arguments> advancedSettings = null)
+        {
+            Contracts.CheckValue(ctx, nameof(ctx));
+            var env = CatalogUtils.GetEnvironment(ctx);
+            return new SymSgdClassificationTrainer(env, label, features, advancedSettings);
+        }
+    }
+}

src/Microsoft.ML.HalLearners/OlsLinearRegression.cs

@@ -7,7 +7,7 @@
 using System.IO;
 using Microsoft.ML.Core.Data;
 using Microsoft.ML.Runtime;
-using Microsoft.ML.Runtime.HalLearners;
+using Microsoft.ML.Trainers.HalLearners;
 using Microsoft.ML.Runtime.Internal.Internallearn;
 using Microsoft.ML.Runtime.Internal.Utilities;
 using Microsoft.ML.Runtime.CommandLine;
@@ -30,7 +30,7 @@
 
 [assembly: LoadableClass(typeof(void), typeof(OlsLinearRegressionTrainer), null, typeof(SignatureEntryPointModule), OlsLinearRegressionTrainer.LoadNameValue)]
 
-namespace Microsoft.ML.Runtime.HalLearners
+namespace Microsoft.ML.Trainers.HalLearners
 {
     /// <include file='doc.xml' path='doc/members/member[@name="OLS"]/*' />
     public sealed class OlsLinearRegressionTrainer : TrainerEstimatorBase<RegressionPredictionTransformer<OlsLinearRegressionPredictor>, OlsLinearRegressionPredictor>

src/Microsoft.ML.HalLearners/SymSgdClassificationTrainer.cs

@@ -16,7 +16,7 @@
 using Microsoft.ML.Runtime.Internal.Internallearn;
 using Microsoft.ML.Runtime.Internal.Utilities;
 using Microsoft.ML.Runtime.Learners;
-using Microsoft.ML.Runtime.SymSgd;
+using Microsoft.ML.Trainers.SymSgd;
 using Microsoft.ML.Runtime.Training;
 
 [assembly: LoadableClass(typeof(SymSgdClassificationTrainer), typeof(SymSgdClassificationTrainer.Arguments),
@@ -27,7 +27,7 @@
 
 [assembly: LoadableClass(typeof(void), typeof(SymSgdClassificationTrainer), null, typeof(SignatureEntryPointModule), SymSgdClassificationTrainer.LoadNameValue)]
 
-namespace Microsoft.ML.Runtime.SymSgd
+namespace Microsoft.ML.Trainers.SymSgd
 {
     using TPredictor = IPredictorWithFeatureWeights<float>;
 

src/Microsoft.ML.KMeansClustering/KMeansCatalog.cs

@@ -4,7 +4,7 @@
 
 using Microsoft.ML.Runtime;
 using Microsoft.ML.Runtime.Data;
-using Microsoft.ML.Runtime.KMeans;
+using Microsoft.ML.Trainers.KMeans;
 using System;
 
 namespace Microsoft.ML

src/Microsoft.ML.KMeansClustering/KMeansPlusPlusTrainer.cs

@@ -10,7 +10,7 @@
 using Microsoft.ML.Runtime.Internal.CpuMath;
 using Microsoft.ML.Runtime.Internal.Internallearn;
 using Microsoft.ML.Runtime.Internal.Utilities;
-using Microsoft.ML.Runtime.KMeans;
+using Microsoft.ML.Trainers.KMeans;
 using Microsoft.ML.Runtime.Numeric;
 using Microsoft.ML.Runtime.Training;
 using System;
@@ -25,7 +25,7 @@
 
 [assembly: LoadableClass(typeof(void), typeof(KMeansPlusPlusTrainer), null, typeof(SignatureEntryPointModule), "KMeans")]
 
-namespace Microsoft.ML.Runtime.KMeans
+namespace Microsoft.ML.Trainers.KMeans
 {
     /// <include file='./doc.xml' path='doc/members/member[@name="KMeans++"]/*' />
     public class KMeansPlusPlusTrainer : TrainerEstimatorBase<ClusteringPredictionTransformer<KMeansPredictor>, KMeansPredictor>

src/Microsoft.ML.KMeansClustering/KMeansPredictor.cs

@@ -10,7 +10,7 @@
 using Microsoft.ML.Runtime.Internal.Utilities;
 using Microsoft.ML.Runtime;
 using Microsoft.ML.Runtime.Data;
-using Microsoft.ML.Runtime.KMeans;
+using Microsoft.ML.Trainers.KMeans;
 using Microsoft.ML.Runtime.Model;
 using Microsoft.ML.Runtime.Model.Onnx;
 using Microsoft.ML.Runtime.Internal.Internallearn;
@@ -19,7 +19,7 @@
 [assembly: LoadableClass(typeof(KMeansPredictor), null, typeof(SignatureLoadModel),
     "KMeans predictor", KMeansPredictor.LoaderSignature)]
 
-namespace Microsoft.ML.Runtime.KMeans
+namespace Microsoft.ML.Trainers.KMeans
 {
     public sealed class KMeansPredictor :
         PredictorBase<VBuffer<Float>>,