Moved WhiteningTransform to HalLearners

docs/samples/Microsoft.ML.Samples/Microsoft.ML.Samples.csproj

@@ -6,6 +6,7 @@
   </PropertyGroup>
 
   <ItemGroup>
+    <ProjectReference Include="..\..\..\src\Microsoft.ML.HalLearners\Microsoft.ML.HalLearners.csproj" />
     <ProjectReference Include="..\..\..\src\Microsoft.ML.StandardLearners\Microsoft.ML.StandardLearners.csproj" />
     <ProjectReference Include="..\..\..\src\Microsoft.ML.SamplesUtils\Microsoft.ML.SamplesUtils.csproj" />
     <ProjectReference Include="..\..\..\src\Microsoft.ML.FastTree\Microsoft.ML.FastTree.csproj" />

src/Microsoft.ML.HalLearners/ProjectionCatalog.cs

@@ -0,0 +1,47 @@
+// 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.Transforms.Projections;
+
+namespace Microsoft.ML
+{
+    public static class ProjectionCatalog
+    {
+        /// <summary>
+        /// Takes column filled with a vector of random variables with a known covariance matrix into a set of new variables whose covariance is the identity matrix,
+        /// meaning that they are uncorrelated and each have variance 1.
+        /// </summary>
+        /// <param name="catalog">The transform's catalog.</param>
+        /// <param name="inputColumn">Name of the input column.</param>
+        /// <param name="outputColumn">Name of the column resulting from the transformation of <paramref name="inputColumn"/>. Null means <paramref name="inputColumn"/> is replaced. </param>
+        /// <param name="kind">Whitening kind (PCA/ZCA).</param>
+        /// <param name="eps">Whitening constant, prevents division by zero.</param>
+        /// <param name="maxRows">Maximum number of rows used to train the transform.</param>
+        /// <param name="pcaNum">In case of PCA whitening, indicates the number of components to retain.</param>
+        /// <example>
+        /// <format type="text/markdown">
+        /// <![CDATA[
+        /// [!code-csharp[VectorWhiten](~/../docs/samples/docs/samples/Microsoft.ML.Samples/Dynamic/ProjectionTransforms.cs?range=5-11,16-115)]
+        /// ]]>
+        /// </format>
+        /// </example>
+        public static VectorWhiteningEstimator VectorWhiten(this TransformsCatalog.ProjectionTransforms catalog, string inputColumn, string outputColumn = null,
+        WhiteningKind kind = VectorWhiteningTransformer.Defaults.Kind,
+        float eps = VectorWhiteningTransformer.Defaults.Eps,
+        int maxRows = VectorWhiteningTransformer.Defaults.MaxRows,
+        int pcaNum = VectorWhiteningTransformer.Defaults.PcaNum)
+        => new VectorWhiteningEstimator(CatalogUtils.GetEnvironment(catalog), inputColumn, outputColumn, kind, eps, maxRows, pcaNum);
+
+        /// <summary>
+        /// Takes columns filled with a vector of random variables with a known covariance matrix into a set of new variables whose covariance is the identity matrix,
+        /// meaning that they are uncorrelated and each have variance 1.
+        /// </summary>
+        /// <param name="catalog">The transform's catalog.</param>
+        /// <param name="columns">Describes the parameters of the whitening process for each column pair.</param>
+        public static VectorWhiteningEstimator VectorWhiten(this TransformsCatalog.ProjectionTransforms catalog, params VectorWhiteningTransformer.ColumnInfo[] columns)
+            => new VectorWhiteningEstimator(CatalogUtils.GetEnvironment(catalog), columns);
+    }
+}

src/Microsoft.ML.HalLearners/TransformsStatic.cs

@@ -0,0 +1,80 @@
+// 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.Core.Data;
+using Microsoft.ML.Runtime;
+using Microsoft.ML.StaticPipe.Runtime;
+using Microsoft.ML.Transforms.Projections;
+using System.Collections.Generic;
+
+namespace Microsoft.ML.StaticPipe
+{
+    /// <summary>
+    /// Extensions for statically typed Whitening estimator.
+    /// </summary>
+    public static class VectorWhiteningExtensions
+    {
+        private sealed class OutPipelineColumn : Vector<float>
+        {
+            public readonly Vector<float> Input;
+
+            public OutPipelineColumn(Vector<float> input, WhiteningKind kind, float eps, int maxRows, int pcaNum)
+                : base(new Reconciler(kind, eps, maxRows, pcaNum), input)
+            {
+                Input = input;
+            }
+        }
+
+        private sealed class Reconciler : EstimatorReconciler
+        {
+            private readonly WhiteningKind _kind;
+            private readonly float _eps;
+            private readonly int _maxRows;
+            private readonly int _pcaNum;
+
+            public Reconciler(WhiteningKind kind, float eps, int maxRows, int pcaNum)
+            {
+                _kind = kind;
+                _eps = eps;
+                _maxRows = maxRows;
+                _pcaNum = pcaNum;
+            }
+
+            public override IEstimator<ITransformer> Reconcile(IHostEnvironment env,
+                PipelineColumn[] toOutput,
+                IReadOnlyDictionary<PipelineColumn, string> inputNames,
+                IReadOnlyDictionary<PipelineColumn, string> outputNames,
+                IReadOnlyCollection<string> usedNames)
+            {
+                Contracts.Assert(toOutput.Length == 1);
+
+                var infos = new VectorWhiteningTransformer.ColumnInfo[toOutput.Length];
+                for (int i = 0; i < toOutput.Length; i++)
+                    infos[i] = new VectorWhiteningTransformer.ColumnInfo(inputNames[((OutPipelineColumn)toOutput[i]).Input], outputNames[toOutput[i]], _kind, _eps, _maxRows, _pcaNum);
+
+                return new VectorWhiteningEstimator(env, infos);
+            }
+        }
+
+        /// <include file='doc.xml' path='doc/members/member[@name="Whitening"]/*'/>
+        /// <param name="input">The column to which the transform will be applied.</param>
+        /// <param name="eps">Whitening constant, prevents division by zero when scaling the data by inverse of eigenvalues.</param>
+        /// <param name="maxRows">Maximum number of rows used to train the transform.</param>
+        /// <param name="pcaNum">In case of PCA whitening, indicates the number of components to retain.</param>
+        public static Vector<float> PcaWhitening(this Vector<float> input,
+            float eps = VectorWhiteningTransformer.Defaults.Eps,
+            int maxRows = VectorWhiteningTransformer.Defaults.MaxRows,
+            int pcaNum = VectorWhiteningTransformer.Defaults.PcaNum)
+            => new OutPipelineColumn(input, WhiteningKind.Pca, eps, maxRows, pcaNum);
+
+        /// <include file='doc.xml' path='doc/members/member[@name="Whitening"]/*'/>
+        /// <param name="input">The column to which the transform will be applied.</param>
+        /// <param name="eps">Whitening constant, prevents division by zero.</param>
+        /// <param name="maxRows">Maximum number of rows used to train the transform.</param>
+        public static Vector<float> ZcaWhitening(this Vector<float> input,
+            float eps = VectorWhiteningTransformer.Defaults.Eps,
+            int maxRows = VectorWhiteningTransformer.Defaults.MaxRows)
+            => new OutPipelineColumn(input, WhiteningKind.Zca, eps, maxRows, VectorWhiteningTransformer.Defaults.PcaNum);
+    }
+}

src/Microsoft.ML.Transforms/VectorWhitening.cs → src/Microsoft.ML.HalLearners/VectorWhitening.cs

@@ -380,7 +380,7 @@ private static void GetColTypesAndIndex(IHostEnvironment env, IDataView inputDat
 
             for (int i = 0; i < columns.Length; i++)
             {
-                if(!inputSchema.TryGetColumnIndex(columns[i].Input, out cols[i]))
+                if (!inputSchema.TryGetColumnIndex(columns[i].Input, out cols[i]))
                     throw env.ExceptSchemaMismatch(nameof(inputSchema), "input", columns[i].Input);
                 srcTypes[i] = inputSchema.GetColumnType(cols[i]);
                 var reason = TestColumn(srcTypes[i]);

src/Microsoft.ML.Transforms/ProjectionCatalog.cs

@@ -40,40 +40,6 @@ public static RandomFourierFeaturizingEstimator CreateRandomFourierFeatures(this
         public static RandomFourierFeaturizingEstimator CreateRandomFourierFeatures(this TransformsCatalog.ProjectionTransforms catalog, params RandomFourierFeaturizingTransformer.ColumnInfo[] columns)
             => new RandomFourierFeaturizingEstimator(CatalogUtils.GetEnvironment(catalog), columns);
 
-        /// <summary>
-        /// Takes column filled with a vector of random variables with a known covariance matrix into a set of new variables whose covariance is the identity matrix,
-        /// meaning that they are uncorrelated and each have variance 1.
-        /// </summary>
-        /// <param name="catalog">The transform's catalog.</param>
-        /// <param name="inputColumn">Name of the input column.</param>
-        /// <param name="outputColumn">Name of the column resulting from the transformation of <paramref name="inputColumn"/>. Null means <paramref name="inputColumn"/> is replaced. </param>
-        /// <param name="kind">Whitening kind (PCA/ZCA).</param>
-        /// <param name="eps">Whitening constant, prevents division by zero.</param>
-        /// <param name="maxRows">Maximum number of rows used to train the transform.</param>
-        /// <param name="pcaNum">In case of PCA whitening, indicates the number of components to retain.</param>
-        /// <example>
-        /// <format type="text/markdown">
-        /// <![CDATA[
-        /// [!code-csharp[VectorWhiten](~/../docs/samples/docs/samples/Microsoft.ML.Samples/Dynamic/ProjectionTransforms.cs?range=5-11,16-115)]
-        /// ]]>
-        /// </format>
-        /// </example>
-        public static VectorWhiteningEstimator VectorWhiten(this TransformsCatalog.ProjectionTransforms catalog, string inputColumn, string outputColumn = null,
-            WhiteningKind kind = VectorWhiteningTransformer.Defaults.Kind,
-            float eps = VectorWhiteningTransformer.Defaults.Eps,
-            int maxRows = VectorWhiteningTransformer.Defaults.MaxRows,
-            int pcaNum = VectorWhiteningTransformer.Defaults.PcaNum)
-            => new VectorWhiteningEstimator(CatalogUtils.GetEnvironment(catalog), inputColumn, outputColumn, kind, eps, maxRows, pcaNum);
-
-        /// <summary>
-        /// Takes columns filled with a vector of random variables with a known covariance matrix into a set of new variables whose covariance is the identity matrix,
-        /// meaning that they are uncorrelated and each have variance 1.
-        /// </summary>
-        /// <param name="catalog">The transform's catalog.</param>
-        /// <param name="columns"> Describes the parameters of the whitening process for each column pair.</param>
-        public static VectorWhiteningEstimator VectorWhiten(this TransformsCatalog.ProjectionTransforms catalog, params VectorWhiteningTransformer.ColumnInfo[] columns)
-            => new VectorWhiteningEstimator(CatalogUtils.GetEnvironment(catalog), columns);
-
         /// <summary>
         /// Takes column filled with a vector of floats and computes L-p norm of it.
         /// </summary>

src/Microsoft.ML.Transforms/TransformsStatic.cs

@@ -10,74 +10,6 @@
 
 namespace Microsoft.ML.StaticPipe
 {
-    /// <summary>
-    /// Extensions for statically typed Whitening estimator.
-    /// </summary>
-    public static class VectorWhiteningExtensions
-    {
-        private sealed class OutPipelineColumn : Vector<float>
-        {
-            public readonly Vector<float> Input;
-
-            public OutPipelineColumn(Vector<float> input, WhiteningKind kind, float eps, int maxRows, int pcaNum)
-                : base(new Reconciler(kind, eps, maxRows, pcaNum), input)
-            {
-                Input = input;
-            }
-        }
-
-        private sealed class Reconciler : EstimatorReconciler
-        {
-            private readonly WhiteningKind _kind;
-            private readonly float _eps;
-            private readonly int _maxRows;
-            private readonly int _pcaNum;
-
-            public Reconciler(WhiteningKind kind, float eps, int maxRows, int pcaNum)
-            {
-                _kind = kind;
-                _eps = eps;
-                _maxRows = maxRows;
-                _pcaNum = pcaNum;
-            }
-
-            public override IEstimator<ITransformer> Reconcile(IHostEnvironment env,
-                PipelineColumn[] toOutput,
-                IReadOnlyDictionary<PipelineColumn, string> inputNames,
-                IReadOnlyDictionary<PipelineColumn, string> outputNames,
-                IReadOnlyCollection<string> usedNames)
-            {
-                Contracts.Assert(toOutput.Length == 1);
-
-                var infos = new VectorWhiteningTransformer.ColumnInfo[toOutput.Length];
-                for (int i = 0; i < toOutput.Length; i++)
-                    infos[i] = new VectorWhiteningTransformer.ColumnInfo(inputNames[((OutPipelineColumn)toOutput[i]).Input], outputNames[toOutput[i]], _kind, _eps, _maxRows, _pcaNum);
-
-                return new VectorWhiteningEstimator(env, infos);
-            }
-        }
-
-        /// <include file='doc.xml' path='doc/members/member[@name="Whitening"]/*'/>
-        /// <param name="input">The column to which the transform will be applied.</param>
-        /// <param name="eps">Whitening constant, prevents division by zero when scaling the data by inverse of eigenvalues.</param>
-        /// <param name="maxRows">Maximum number of rows used to train the transform.</param>
-        /// <param name="pcaNum">In case of PCA whitening, indicates the number of components to retain.</param>
-        public static Vector<float> PcaWhitening(this Vector<float> input,
-            float eps = VectorWhiteningTransformer.Defaults.Eps,
-            int maxRows = VectorWhiteningTransformer.Defaults.MaxRows,
-            int pcaNum = VectorWhiteningTransformer.Defaults.PcaNum)
-            => new OutPipelineColumn(input, WhiteningKind.Pca, eps, maxRows, pcaNum);
-
-        /// <include file='doc.xml' path='doc/members/member[@name="Whitening"]/*'/>
-        /// <param name="input">The column to which the transform will be applied.</param>
-        /// <param name="eps">Whitening constant, prevents division by zero.</param>
-        /// <param name="maxRows">Maximum number of rows used to train the transform.</param>
-        public static Vector<float> ZcaWhitening(this Vector<float> input,
-            float eps = VectorWhiteningTransformer.Defaults.Eps,
-            int maxRows = VectorWhiteningTransformer.Defaults.MaxRows)
-            => new OutPipelineColumn(input, WhiteningKind.Zca, eps, maxRows, VectorWhiteningTransformer.Defaults.PcaNum);
-    }
-
     /// <summary>
     /// Extensions for statically typed <see cref="LpNormalizingEstimator"/>.
     /// </summary>