upgrade to mlnet 0.11 (dotnet#263)

srsaggam · daholste · commit c77b78a9e490 · 2019-03-05T16:43:14.000-08:00
diff --git a/src/Microsoft.ML.Auto/EstimatorExtensions/EstimatorExtensions.cs b/src/Microsoft.ML.Auto/EstimatorExtensions/EstimatorExtensions.cs
@@ -4,8 +4,6 @@
 
 using Microsoft.ML.Data;
 using Microsoft.ML.Transforms;
-using Microsoft.ML.Transforms.Categorical;
-using Microsoft.ML.Transforms.Conversions;
 
 namespace Microsoft.ML.Auto
 {
@@ -39,7 +37,7 @@ public IEstimator<ITransformer> CreateInstance(MLContext context, PipelineNode p
 
         public static SuggestedTransform CreateSuggestedTransform(MLContext context, string inColumn, string outColumn)
         {
-            var pipelineNode = new PipelineNode(EstimatorName.ColumnCopying.ToString(), 
+            var pipelineNode = new PipelineNode(EstimatorName.ColumnCopying.ToString(),
                 PipelineNodeType.Transform, inColumn, outColumn);
             var estimator = CreateInstance(context, inColumn, outColumn);
             return new SuggestedTransform(pipelineNode, estimator);
@@ -192,7 +190,7 @@ public IEstimator<ITransformer> CreateInstance(MLContext context, PipelineNode p
 
         public static SuggestedTransform CreateSuggestedTransform(MLContext context, string inColumn, string outColumn)
         {
-            var pipelineNode = new PipelineNode(EstimatorName.TextFeaturizing.ToString(), 
+            var pipelineNode = new PipelineNode(EstimatorName.TextFeaturizing.ToString(),
                 PipelineNodeType.Transform, inColumn, outColumn);
             var estimator = CreateInstance(context, inColumn, outColumn);
             return new SuggestedTransform(pipelineNode, estimator);
@@ -213,7 +211,7 @@ public IEstimator<ITransformer> CreateInstance(MLContext context, PipelineNode p
 
         public static SuggestedTransform CreateSuggestedTransform(MLContext context, string[] inColumns, string[] outColumns)
         {
-            var pipelineNode = new PipelineNode(EstimatorName.TypeConverting.ToString(), 
+            var pipelineNode = new PipelineNode(EstimatorName.TypeConverting.ToString(),
                 PipelineNodeType.Transform, inColumns, outColumns);
             var estimator = CreateInstance(context, inColumns, outColumns);
             return new SuggestedTransform(pipelineNode, estimator);
@@ -239,7 +237,7 @@ public IEstimator<ITransformer> CreateInstance(MLContext context, PipelineNode p
 
         public static SuggestedTransform CreateSuggestedTransform(MLContext context, string inColumn, string outColumn)
         {
-            var pipelineNode = new PipelineNode(EstimatorName.ValueToKeyMapping.ToString(), 
+            var pipelineNode = new PipelineNode(EstimatorName.ValueToKeyMapping.ToString(),
                 PipelineNodeType.Transform, inColumn, outColumn);
             var estimator = CreateInstance(context, inColumn, outColumn);
             return new SuggestedTransform(pipelineNode, estimator);
diff --git a/src/Microsoft.ML.Auto/Microsoft.ML.Auto.csproj b/src/Microsoft.ML.Auto/Microsoft.ML.Auto.csproj
@@ -1,14 +1,14 @@
-<Project Sdk="Microsoft.NET.Sdk">
+﻿<Project Sdk="Microsoft.NET.Sdk">
   <PropertyGroup>
     <TargetFramework>netstandard2.0</TargetFramework>
     <LangVersion>7.3</LangVersion>
     <RootNamespace>Microsoft.ML.Auto</RootNamespace>
   </PropertyGroup>
 
   <ItemGroup>
-    <PackageReference Include="Microsoft.ML" Version="0.11.0-preview-27428-4" />
-    <PackageReference Include="Microsoft.ML.HalLearners" Version="0.11.0-preview-27428-4" />
-    <PackageReference Include="Microsoft.ML.LightGBM" Version="0.11.0-preview-27428-4" />
+    <PackageReference Include="Microsoft.ML" Version="0.11.0" />
+    <PackageReference Include="Microsoft.ML.HalLearners" Version="0.11.0" />
+    <PackageReference Include="Microsoft.ML.LightGBM" Version="0.11.0" />
   </ItemGroup>
 
   <PropertyGroup>
diff --git a/src/Microsoft.ML.Auto/TrainerExtensions/BinaryTrainerExtensions.cs b/src/Microsoft.ML.Auto/TrainerExtensions/BinaryTrainerExtensions.cs
@@ -7,7 +7,6 @@
 using Microsoft.ML.Trainers;
 using Microsoft.ML.Trainers.FastTree;
 using Microsoft.ML.Trainers.HalLearners;
-using Microsoft.ML.Trainers.Online;
 
 namespace Microsoft.ML.Auto
 {
diff --git a/src/Microsoft.ML.Auto/TrainerExtensions/RegressionTrainerExtensions.cs b/src/Microsoft.ML.Auto/TrainerExtensions/RegressionTrainerExtensions.cs
@@ -6,7 +6,6 @@
 using Microsoft.ML.Trainers;
 using Microsoft.ML.Trainers.FastTree;
 using Microsoft.ML.Trainers.HalLearners;
-using Microsoft.ML.Trainers.Online;
 
 namespace Microsoft.ML.Auto
 {
diff --git a/src/mlnet.Test/ApprovalTests/ConsoleCodeGeneratorTests.GeneratedProjectCodeTest.approved.txt b/src/mlnet.Test/ApprovalTests/ConsoleCodeGeneratorTests.GeneratedProjectCodeTest.approved.txt
@@ -8,16 +8,15 @@
   <PropertyGroup>
     <RestoreSources>
       https://api.nuget.org/v3/index.json;
-      https://dotnet.myget.org/F/dotnet-core/api/v3/index.json;
     </RestoreSources>
   </PropertyGroup>
   <ItemGroup>
     <Compile Include="Program.cs" />
     <Compile Include="ConsoleHelper.cs" />
   </ItemGroup>
   <ItemGroup>
-    <PackageReference Include="Microsoft.ML" Version="0.11.0-preview-27428-4" />
-    <PackageReference Include="Microsoft.ML.HalLearners" Version="0.11.0-preview-27428-4" />
-    <PackageReference Include="Microsoft.ML.LightGBM" Version="0.11.0-preview-27428-4" /> 
+    <PackageReference Include="Microsoft.ML" Version="0.11.0" />
+    <PackageReference Include="Microsoft.ML.HalLearners" Version="0.11.0" />
+    <PackageReference Include="Microsoft.ML.LightGBM" Version="0.11.0" /> 
   </ItemGroup>
 </Project>
diff --git a/src/mlnet.Test/CodeGenTests.cs b/src/mlnet.Test/CodeGenTests.cs
@@ -78,7 +78,7 @@ public void TransformGeneratorUsingTest()
             CodeGenerator codeGenerator = new CodeGenerator(pipeline, null, null);
             var actual = codeGenerator.GenerateTransformsAndUsings();
             string expectedTransform = "Categorical.OneHotEncoding(new []{new OneHotEncodingEstimator.ColumnOptions(\"Label\",\"Label\")})";
-            var expectedUsings = "using Microsoft.ML.Transforms.Categorical;\r\n";
+            var expectedUsings = "using Microsoft.ML.Transforms;\r\n";
             Assert.AreEqual(expectedTransform, actual[0].Item1);
             Assert.AreEqual(expectedUsings, actual[0].Item2);
         }
diff --git a/src/mlnet.Test/TrainerGeneratorTests.cs b/src/mlnet.Test/TrainerGeneratorTests.cs
@@ -309,7 +309,7 @@ public void OnlineGradientDescentRegressionAdvancedParameterTest()
             Pipeline pipeline = new Pipeline(new PipelineNode[] { node });
             CodeGenerator codeGenerator = new CodeGenerator(pipeline, null, null);
             var actual = codeGenerator.GenerateTrainerAndUsings();
-            var expectedUsings = "using Microsoft.ML.Trainers.Online;\r\n";
+            var expectedUsings = "using Microsoft.ML.Trainers;\r\n";
             string expectedTrainerString = "OnlineGradientDescent(new OnlineGradientDescentTrainer.Options(){RecencyGainMulti=true,LabelColumn=\"Label\",FeatureColumn=\"Features\"})";
             Assert.AreEqual(expectedTrainerString, actual.Item1);
             Assert.AreEqual(expectedUsings, actual.Item2);
@@ -383,7 +383,7 @@ public void LinearSvmBinaryParameterTest()
             Pipeline pipeline = new Pipeline(new PipelineNode[] { node });
             CodeGenerator codeGenerator = new CodeGenerator(pipeline, null, null);
             var actual = codeGenerator.GenerateTrainerAndUsings();
-            var expectedUsings = "using Microsoft.ML.Trainers.Online;\r\n ";
+            var expectedUsings = "using Microsoft.ML.Trainers;\r\n ";
             string expectedTrainerString = "LinearSupportVectorMachines(new LinearSvmTrainer.Options(){NoBias=true,LabelColumn=\"Label\",FeatureColumn=\"Features\"})";
             Assert.AreEqual(expectedTrainerString, actual.Item1);
             Assert.AreEqual(expectedUsings, actual.Item2);
@@ -421,7 +421,7 @@ public void FastTreeTweedieRegressionAdvancedParameterTest()
             Pipeline pipeline = new Pipeline(new PipelineNode[] { node });
             CodeGenerator codeGenerator = new CodeGenerator(pipeline, null, null);
             var actual = codeGenerator.GenerateTrainerAndUsings();
-            var expectedUsings = "using Microsoft.ML.Trainers.Online;\r\n";
+            var expectedUsings = "using Microsoft.ML.Trainers;\r\n";
             string expectedTrainerString = "OnlineGradientDescent(new OnlineGradientDescentTrainer.Options(){Shrinkage=0.1f,LabelColumn=\"Label\",FeatureColumn=\"Features\"})";
             Assert.AreEqual(expectedTrainerString, actual.Item1);
             Assert.AreEqual(expectedUsings, actual.Item2);
@@ -610,7 +610,7 @@ public void AveragedPerceptronBinaryAdvancedParameterTest()
             Pipeline pipeline = new Pipeline(new PipelineNode[] { node });
             CodeGenerator codeGenerator = new CodeGenerator(pipeline, null, null);
             var actual = codeGenerator.GenerateTrainerAndUsings();
-            var expectedUsings = "using Microsoft.ML.Trainers.Online;\r\n ";
+            var expectedUsings = "using Microsoft.ML.Trainers;\r\n ";
             string expectedTrainerString = "AveragedPerceptron(new AveragedPerceptronTrainer.Options(){Shuffle=true,LabelColumn=\"Label\",FeatureColumn=\"Features\"})";
             Assert.AreEqual(expectedTrainerString, actual.Item1);
             Assert.AreEqual(expectedUsings, actual.Item2);
diff --git a/src/mlnet.Test/TransformGeneratorTests.cs b/src/mlnet.Test/TransformGeneratorTests.cs
@@ -34,7 +34,7 @@ public void OneHotEncodingTest()
             CodeGenerator codeGenerator = new CodeGenerator(pipeline, null, null);
             var actual = codeGenerator.GenerateTransformsAndUsings();
             string expectedTransform = "Categorical.OneHotEncoding(new []{new OneHotEncodingEstimator.ColumnOptions(\"categorical_column_1\",\"categorical_column_1\")})";
-            var expectedUsings = "using Microsoft.ML.Transforms.Categorical;\r\n";
+            var expectedUsings = "using Microsoft.ML.Transforms;\r\n";
             Assert.AreEqual(expectedTransform, actual[0].Item1);
             Assert.AreEqual(expectedUsings, actual[0].Item2);
         }
@@ -109,7 +109,7 @@ public void OneHotHashEncodingTest()
             CodeGenerator codeGenerator = new CodeGenerator(pipeline, null, null);
             var actual = codeGenerator.GenerateTransformsAndUsings();
             string expectedTransform = "Categorical.OneHotHashEncoding(new []{new OneHotHashEncodingEstimator.ColumnOptions(\"Categorical_column_1\",\"Categorical_column_1\")})";
-            var expectedUsings = "using Microsoft.ML.Transforms.Categorical;\r\n";
+            var expectedUsings = "using Microsoft.ML.Transforms;\r\n";
             Assert.AreEqual(expectedTransform, actual[0].Item1);
             Assert.AreEqual(expectedUsings, actual[0].Item2);
         }
@@ -139,7 +139,7 @@ public void TypeConvertingTest()
             CodeGenerator codeGenerator = new CodeGenerator(pipeline, null, null);
             var actual = codeGenerator.GenerateTransformsAndUsings();
             string expectedTransform = "Conversion.ConvertType(new []{new TypeConvertingEstimator.ColumnOptions(\"R4_column_1\",DataKind.Single,\"I4_column_1\")})";
-            string expectedUsings = "using Microsoft.ML.Transforms.Conversions;\r\n";
+            string expectedUsings = "using Microsoft.ML.Transforms;\r\n";
             Assert.AreEqual(expectedTransform, actual[0].Item1);
             Assert.AreEqual(expectedUsings, actual[0].Item2);
         }
@@ -154,7 +154,7 @@ public void ValueToKeyMappingTest()
             CodeGenerator codeGenerator = new CodeGenerator(pipeline, null, null);
             var actual = codeGenerator.GenerateTransformsAndUsings();
             string expectedTransform = "Conversion.MapValueToKey(\"Label\",\"Label\")";
-            var expectedUsings = "using Microsoft.ML.Transforms.Conversions;\r\n";
+            var expectedUsings = "using Microsoft.ML.Transforms;\r\n";
             Assert.AreEqual(expectedTransform, actual[0].Item1);
             Assert.AreEqual(expectedUsings, actual[0].Item2);
         }
diff --git a/src/mlnet/CodeGenerator/CSharp/TrainerGenerators.cs b/src/mlnet/CodeGenerator/CSharp/TrainerGenerators.cs
@@ -70,7 +70,7 @@ internal override IDictionary<string, string> NamedParameters
                 }
             }
 
-            internal override string Usings => "using Microsoft.ML.Trainers.Online;\r\n ";
+            internal override string Usings => "using Microsoft.ML.Trainers;\r\n ";
 
             public AveragedPerceptron(PipelineNode node) : base(node)
             {
@@ -196,7 +196,7 @@ internal override IDictionary<string, string> NamedParameters
                 }
             }
 
-            internal override string Usings => "using Microsoft.ML.Trainers.Online;\r\n ";
+            internal override string Usings => "using Microsoft.ML.Trainers;\r\n ";
 
             public LinearSvm(PipelineNode node) : base(node)
             {
@@ -266,7 +266,7 @@ internal override IDictionary<string, string> NamedParameters
                 }
             }
 
-            internal override string Usings => "using Microsoft.ML.Trainers.Online;\r\n";
+            internal override string Usings => "using Microsoft.ML.Trainers;\r\n";
 
             public OnlineGradientDescentRegression(PipelineNode node) : base(node)
             {
diff --git a/src/mlnet/CodeGenerator/CSharp/TransformGenerators.cs b/src/mlnet/CodeGenerator/CSharp/TransformGenerators.cs
@@ -42,7 +42,7 @@ public OneHotEncoding(PipelineNode node) : base(node)
 
         internal override string MethodName => "Categorical.OneHotEncoding";
 
-        internal override string Usings => "using Microsoft.ML.Transforms.Categorical;\r\n";
+        internal override string Usings => "using Microsoft.ML.Transforms;\r\n";
 
         private string ArgumentsName = "OneHotEncodingEstimator.ColumnOptions";
 
@@ -210,7 +210,7 @@ public OneHotHashEncoding(PipelineNode node) : base(node)
 
         internal override string MethodName => "Categorical.OneHotHashEncoding";
 
-        internal override string Usings => "using Microsoft.ML.Transforms.Categorical;\r\n";
+        internal override string Usings => "using Microsoft.ML.Transforms;\r\n";
 
         private string ArgumentsName = "OneHotHashEncodingEstimator.ColumnOptions";
 
@@ -272,7 +272,7 @@ public TypeConverting(PipelineNode node) : base(node)
 
         internal override string MethodName => "Conversion.ConvertType";
 
-        internal override string Usings => "using Microsoft.ML.Transforms.Conversions;\r\n";
+        internal override string Usings => "using Microsoft.ML.Transforms;\r\n";
 
         private string ArgumentsName = "TypeConvertingEstimator.ColumnOptions";
 
@@ -311,7 +311,7 @@ public ValueToKeyMapping(PipelineNode node) : base(node)
 
         internal override string MethodName => "Conversion.MapValueToKey";
 
-        internal override string Usings => "using Microsoft.ML.Transforms.Conversions;\r\n";
+        internal override string Usings => "using Microsoft.ML.Transforms;\r\n";
 
         public override string GenerateTransformer()
         {
diff --git a/src/mlnet/Templates/Console/MLProjectGen.cs b/src/mlnet/Templates/Console/MLProjectGen.cs
@@ -35,17 +35,16 @@ public virtual string TransformText()
   <PropertyGroup>
     <RestoreSources>
       https://api.nuget.org/v3/index.json;
-      https://dotnet.myget.org/F/dotnet-core/api/v3/index.json;
     </RestoreSources>
   </PropertyGroup>
   <ItemGroup>
     <Compile Include=""Program.cs"" />
     <Compile Include=""ConsoleHelper.cs"" />
   </ItemGroup>
   <ItemGroup>
-    <PackageReference Include=""Microsoft.ML"" Version=""0.11.0-preview-27428-4"" />
-    <PackageReference Include=""Microsoft.ML.HalLearners"" Version=""0.11.0-preview-27428-4"" />
-    <PackageReference Include=""Microsoft.ML.LightGBM"" Version=""0.11.0-preview-27428-4"" /> 
+    <PackageReference Include=""Microsoft.ML"" Version=""0.11.0"" />
+    <PackageReference Include=""Microsoft.ML.HalLearners"" Version=""0.11.0"" />
+    <PackageReference Include=""Microsoft.ML.LightGBM"" Version=""0.11.0"" /> 
   </ItemGroup>
 </Project>
 ");
diff --git a/src/mlnet/Templates/Console/MLProjectGen.tt b/src/mlnet/Templates/Console/MLProjectGen.tt
@@ -13,16 +13,15 @@
   <PropertyGroup>
     <RestoreSources>
       https://api.nuget.org/v3/index.json;
-      https://dotnet.myget.org/F/dotnet-core/api/v3/index.json;
     </RestoreSources>
   </PropertyGroup>
   <ItemGroup>
     <Compile Include="Program.cs" />
     <Compile Include="ConsoleHelper.cs" />
   </ItemGroup>
   <ItemGroup>
-    <PackageReference Include="Microsoft.ML" Version="0.11.0-preview-27428-4" />
-    <PackageReference Include="Microsoft.ML.HalLearners" Version="0.11.0-preview-27428-4" />
-    <PackageReference Include="Microsoft.ML.LightGBM" Version="0.11.0-preview-27428-4" /> 
+    <PackageReference Include="Microsoft.ML" Version="0.11.0" />
+    <PackageReference Include="Microsoft.ML.HalLearners" Version="0.11.0" />
+    <PackageReference Include="Microsoft.ML.LightGBM" Version="0.11.0" /> 
   </ItemGroup>
 </Project>
diff --git a/src/mlnet/Utilities/ConsolePrinter.cs b/src/mlnet/Utilities/ConsolePrinter.cs
@@ -12,28 +12,28 @@ internal class ConsolePrinter
         private static NLog.Logger logger = NLog.LogManager.GetCurrentClassLogger();
         internal static void PrintRegressionMetrics(int iteration, string trainerName, RegressionMetrics metrics)
         {
-            logger.Log(LogLevel.Info, $"{iteration,-3}{trainerName,-35}{metrics.RSquared,-10:0.###}{metrics.LossFn,-8:0.##}{metrics.L1,-15:#.##}{metrics.L2,-15:#.##}{metrics.Rms,-10:#.##}");
+            logger.Log(LogLevel.Info, $"{iteration,-4}{trainerName,-35}{metrics.RSquared,-10:F4}{metrics.LossFn,-8:F2}{metrics.L1,-15:F2}{metrics.L2,-15:F2}{metrics.Rms,-10:F2}");
         }
 
         internal static void PrintBinaryClassificationMetrics(int iteration, string trainerName, BinaryClassificationMetrics metrics)
         {
-            logger.Log(LogLevel.Info, $"{iteration,-3}{trainerName,-35}{metrics.Accuracy,-10:0.###}{metrics.Auc,-8:0.##}");
+            logger.Log(LogLevel.Info, $"{iteration,-4}{trainerName,-35}{metrics.Accuracy,-10:F4}{metrics.Auc,-8:F2}");
         }
 
         internal static void PrintBinaryClassificationMetricsHeader()
         {
             logger.Log(LogLevel.Info, $"*************************************************");
             logger.Log(LogLevel.Info, $"*       {Strings.MetricsForBinaryClassModels}     ");
             logger.Log(LogLevel.Info, $"*------------------------------------------------");
-            logger.Log(LogLevel.Info, $"{" ",-3}{"Trainer",-35}{"Accuracy",-10}{"Auc",-8}");
+            logger.Log(LogLevel.Info, $"{" ",-4}{"Trainer",-35}{"Accuracy",-10}{"Auc",-8}");
         }
 
         internal static void PrintRegressionMetricsHeader()
         {
             logger.Log(LogLevel.Info, $"*************************************************");
             logger.Log(LogLevel.Info, $"*       {Strings.MetricsForRegressionModels}     ");
             logger.Log(LogLevel.Info, $"*------------------------------------------------");
-            logger.Log(LogLevel.Info, $"{" ",-3}{"Trainer",-35}{"R2-Score",-10}{"LossFn",-8}{"Absolute-loss",-15}{"Squared-loss",-15}{"RMS-loss",-10}");
+            logger.Log(LogLevel.Info, $"{" ",-4}{"Trainer",-35}{"R2-Score",-10}{"LossFn",-8}{"Absolute-loss",-15}{"Squared-loss",-15}{"RMS-loss",-10}");
         }
 
         internal static void PrintBestPipelineHeader()

Original file line number	Diff line number	Diff line change
`@@ -7,7 +7,6 @@`
`7`	`7`	`using Microsoft.ML.Trainers;`
`8`	`8`	`using Microsoft.ML.Trainers.FastTree;`
`9`	`9`	`using Microsoft.ML.Trainers.HalLearners;`
`10`		`-using Microsoft.ML.Trainers.Online;`
`11`	`10`
`12`	`11`	`namespace Microsoft.ML.Auto`
`13`	`12`	`{`
Original file line number	Diff line number	Diff line change
`@@ -6,7 +6,6 @@`
`6`	`6`	`using Microsoft.ML.Trainers;`
`7`	`7`	`using Microsoft.ML.Trainers.FastTree;`
`8`	`8`	`using Microsoft.ML.Trainers.HalLearners;`
`9`		`-using Microsoft.ML.Trainers.Online;`
`10`	`9`
`11`	`10`	`namespace Microsoft.ML.Auto`
`12`	`11`	`{`
Original file line number	Diff line number	Diff line change
`@@ -78,7 +78,7 @@ public void TransformGeneratorUsingTest()`
`78`	`78`	`CodeGenerator codeGenerator = new CodeGenerator(pipeline, null, null);`
`79`	`79`	`var actual = codeGenerator.GenerateTransformsAndUsings();`
`80`	`80`	`string expectedTransform = "Categorical.OneHotEncoding(new []{new OneHotEncodingEstimator.ColumnOptions(\"Label\",\"Label\")})";`
`81`		`- var expectedUsings = "using Microsoft.ML.Transforms.Categorical;\r\n";`
	`81`	`+ var expectedUsings = "using Microsoft.ML.Transforms;\r\n";`
`82`	`82`	`Assert.AreEqual(expectedTransform, actual[0].Item1);`
`83`	`83`	`Assert.AreEqual(expectedUsings, actual[0].Item2);`
`84`	`84`	`}`
Original file line number	Diff line number	Diff line change
`@@ -70,7 +70,7 @@ internal override IDictionary<string, string> NamedParameters`
`70`	`70`	`}`
`71`	`71`	`}`
`72`	`72`
`73`		`- internal override string Usings => "using Microsoft.ML.Trainers.Online;\r\n ";`
	`73`	`+ internal override string Usings => "using Microsoft.ML.Trainers;\r\n ";`
`74`	`74`
`75`	`75`	`public AveragedPerceptron(PipelineNode node) : base(node)`
`76`	`76`	`{`
`@@ -196,7 +196,7 @@ internal override IDictionary<string, string> NamedParameters`
`196`	`196`	`}`
`197`	`197`	`}`
`198`	`198`
`199`		`- internal override string Usings => "using Microsoft.ML.Trainers.Online;\r\n ";`
	`199`	`+ internal override string Usings => "using Microsoft.ML.Trainers;\r\n ";`
`200`	`200`
`201`	`201`	`public LinearSvm(PipelineNode node) : base(node)`
`202`	`202`	`{`
`@@ -266,7 +266,7 @@ internal override IDictionary<string, string> NamedParameters`
`266`	`266`	`}`
`267`	`267`	`}`
`268`	`268`
`269`		`- internal override string Usings => "using Microsoft.ML.Trainers.Online;\r\n";`
	`269`	`+ internal override string Usings => "using Microsoft.ML.Trainers;\r\n";`
`270`	`270`
`271`	`271`	`public OnlineGradientDescentRegression(PipelineNode node) : base(node)`
`272`	`272`	`{`