diff --git a/test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.ConsoleAppProgramCSFileContentTest.approved.txt b/test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.ConsoleAppProgramCSFileContentTest.approved.txt
index 2156b23bb7..3ed75ad9e5 100644
--- a/test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.ConsoleAppProgramCSFileContentTest.approved.txt
+++ b/test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.ConsoleAppProgramCSFileContentTest.approved.txt
@@ -42,7 +42,7 @@ namespace TestNamespace.ConsoleApp
         private static ModelInput CreateSingleDataSample(string dataFilePath)
         {
             // Create MLContext
-            MLContext mlContext = new MLContext(1);
+            MLContext mlContext = new MLContext();
 
             // Load dataset
             IDataView dataView = mlContext.Data.LoadFromTextFile<ModelInput>(
diff --git a/test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.ConsumeModelContentTest.approved.txt b/test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.ConsumeModelContentTest.approved.txt
index 22f82a1c97..cc84f0f161 100644
--- a/test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.ConsumeModelContentTest.approved.txt
+++ b/test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.ConsumeModelContentTest.approved.txt
@@ -21,7 +21,7 @@ namespace TestNamespace.Model
         {
 
             // Create new MLContext
-            MLContext mlContext = new MLContext(1);
+            MLContext mlContext = new MLContext();
 
             // Load model & create prediction engine
             string modelPath = AppDomain.CurrentDomain.BaseDirectory + "MLModel.zip";
diff --git a/test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.PredictionProgramCSFileContentTest.approved.txt b/test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.PredictionProgramCSFileContentTest.approved.txt
index 2156b23bb7..3ed75ad9e5 100644
--- a/test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.PredictionProgramCSFileContentTest.approved.txt
+++ b/test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.PredictionProgramCSFileContentTest.approved.txt
@@ -42,7 +42,7 @@ namespace TestNamespace.ConsoleApp
         private static ModelInput CreateSingleDataSample(string dataFilePath)
         {
             // Create MLContext
-            MLContext mlContext = new MLContext(1);
+            MLContext mlContext = new MLContext();
 
             // Load dataset
             IDataView dataView = mlContext.Data.LoadFromTextFile<ModelInput>(
diff --git a/test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.Recommendation_GenerateConsoleAppProjectContents_VerifyPredictProgram.approved.txt b/test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.Recommendation_GenerateConsoleAppProjectContents_VerifyPredictProgram.approved.txt
index c367470b79..abc02fa615 100644
--- a/test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.Recommendation_GenerateConsoleAppProjectContents_VerifyPredictProgram.approved.txt
+++ b/test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.Recommendation_GenerateConsoleAppProjectContents_VerifyPredictProgram.approved.txt
@@ -39,7 +39,7 @@ namespace TestNamespace.ConsoleApp
         private static ModelInput CreateSingleDataSample(string dataFilePath)
         {
             // Create MLContext
-            MLContext mlContext = new MLContext(1);
+            MLContext mlContext = new MLContext();
 
             // Load dataset
             IDataView dataView = mlContext.Data.LoadFromTextFile<ModelInput>(
diff --git a/test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.Recommendation_GenerateModelProjectContents_VerifyConsumeModel.approved.txt b/test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.Recommendation_GenerateModelProjectContents_VerifyConsumeModel.approved.txt
index 22f82a1c97..cc84f0f161 100644
--- a/test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.Recommendation_GenerateModelProjectContents_VerifyConsumeModel.approved.txt
+++ b/test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.Recommendation_GenerateModelProjectContents_VerifyConsumeModel.approved.txt
@@ -21,7 +21,7 @@ namespace TestNamespace.Model
         {
 
             // Create new MLContext
-            MLContext mlContext = new MLContext(1);
+            MLContext mlContext = new MLContext();
 
             // Load model & create prediction engine
             string modelPath = AppDomain.CurrentDomain.BaseDirectory + "MLModel.zip";
diff --git a/test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.cs b/test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.cs
index 17b23291b0..5a31997876 100644
--- a/test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.cs
+++ b/test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.cs
@@ -294,7 +294,7 @@ private CodeGenerator PrepareForRecommendationTask()
         {
             if (mockedPipeline == null)
             {
-                MLContext context = new MLContext(1);
+                MLContext context = new MLContext();
 
                 var trainer1 = new SuggestedTrainer(context, new MatrixFactorizationExtension(), new ColumnInformation() {
                     LabelColumnName = "Label",
@@ -335,7 +335,7 @@ private CodeGenerator PrepareForRecommendationTask()
         {
             if (mockedPipeline == null)
             {
-                MLContext context = new MLContext(1);
+                MLContext context = new MLContext();
                 // same learners with different hyperparams
                 var hyperparams1 = new Microsoft.ML.AutoML.ParameterSet(new List<Microsoft.ML.AutoML.IParameterValue>() { new LongParameterValue("NumLeaves", 2) });
                 var trainer1 = new SuggestedTrainer(context, new LightGbmBinaryExtension(), new ColumnInformation(), hyperparams1);
@@ -372,7 +372,7 @@ private CodeGenerator PrepareForRecommendationTask()
         {
             if (mockedPipeline == null)
             {
-                MLContext context = new MLContext(1);
+                MLContext context = new MLContext();
                 // same learners with different hyperparams
                 var hyperparams1 = new Microsoft.ML.AutoML.ParameterSet(new List<Microsoft.ML.AutoML.IParameterValue>() { new LongParameterValue("NumLeaves", 2) });
                 var trainer1 = new SuggestedTrainer(context, new LightGbmRegressionExtension(), new ColumnInformation(), hyperparams1);
@@ -409,7 +409,7 @@ private CodeGenerator PrepareForRecommendationTask()
         {
             if (mockedOvaPipeline == null)
             {
-                MLContext context = new MLContext(1);
+                MLContext context = new MLContext();
                 // same learners with different hyperparams
                 var hyperparams1 = new Microsoft.ML.AutoML.ParameterSet(new List<Microsoft.ML.AutoML.IParameterValue>() { new LongParameterValue("NumLeaves", 2) });
                 var trainer1 = new SuggestedTrainer(context, new FastForestOvaExtension(), new ColumnInformation(), hyperparams1);
diff --git a/test/Microsoft.ML.CodeGenerator.Tests/CodeGenTests.cs b/test/Microsoft.ML.CodeGenerator.Tests/CodeGenTests.cs
index f2ee5eb501..816b08da68 100644
--- a/test/Microsoft.ML.CodeGenerator.Tests/CodeGenTests.cs
+++ b/test/Microsoft.ML.CodeGenerator.Tests/CodeGenTests.cs
@@ -17,7 +17,7 @@ public class CodeGeneratorTests
         [Fact]
         public void TrainerGeneratorBasicNamedParameterTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>()
             {
@@ -37,7 +37,7 @@ public void TrainerGeneratorBasicNamedParameterTest()
         [Fact]
         public void TrainerGeneratorBasicAdvancedParameterTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>()
             {
@@ -58,7 +58,7 @@ public void TrainerGeneratorBasicAdvancedParameterTest()
         [Fact]
         public void TransformGeneratorBasicTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("Normalizing", PipelineNodeType.Transform, new string[] { "Label" }, new string[] { "Label" }, elementProperties);
             Pipeline pipeline = new Pipeline(new PipelineNode[] { node });
@@ -72,7 +72,7 @@ public void TransformGeneratorBasicTest()
         [Fact]
         public void TransformGeneratorUsingTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("OneHotEncoding", PipelineNodeType.Transform, new string[] { "Label" }, new string[] { "Label" }, elementProperties);
             Pipeline pipeline = new Pipeline(new PipelineNode[] { node });
@@ -117,7 +117,7 @@ public void ClassLabelGenerationBasicTest()
         [Fact]
         public void TrainerComplexParameterTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>()
             {
diff --git a/test/Microsoft.ML.CodeGenerator.Tests/TrainerGeneratorTests.cs b/test/Microsoft.ML.CodeGenerator.Tests/TrainerGeneratorTests.cs
index ebe1e4c43b..0145d6e7f2 100644
--- a/test/Microsoft.ML.CodeGenerator.Tests/TrainerGeneratorTests.cs
+++ b/test/Microsoft.ML.CodeGenerator.Tests/TrainerGeneratorTests.cs
@@ -18,7 +18,7 @@ public class TrainerGeneratorTests
         public void CultureInvariantTest()
         {
 
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>()
             {
@@ -46,7 +46,7 @@ public void CultureInvariantTest()
         public void LightGbmBinaryBasicTest()
         {
 
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>()
             {
@@ -67,7 +67,7 @@ public void LightGbmBinaryBasicTest()
         public void LightGbmBinaryAdvancedParameterTest()
         {
 
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>()
             {
@@ -90,7 +90,7 @@ public void LightGbmBinaryAdvancedParameterTest()
         public void SymbolicSgdLogisticRegressionBinaryBasicTest()
         {
 
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("SymbolicSgdLogisticRegressionBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties);
@@ -107,7 +107,7 @@ public void SymbolicSgdLogisticRegressionBinaryBasicTest()
         public void SymbolicSgdLogisticRegressionBinaryAdvancedParameterTest()
         {
 
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>()
             {
@@ -127,7 +127,7 @@ public void SymbolicSgdLogisticRegressionBinaryAdvancedParameterTest()
         [Fact]
         public void SgdCalibratedBinaryBasicTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("SgdCalibratedBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties);
@@ -144,7 +144,7 @@ public void SgdCalibratedBinaryBasicTest()
         public void SgdCalibratedBinaryAdvancedParameterTest()
         {
 
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>()
             {
@@ -164,7 +164,7 @@ public void SgdCalibratedBinaryAdvancedParameterTest()
         [Fact]
         public void SdcaLogisticRegressionBinaryBasicTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("SdcaLogisticRegressionBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties);
@@ -181,7 +181,7 @@ public void SdcaLogisticRegressionBinaryBasicTest()
         public void SdcaLogisticRegressionBinaryAdvancedParameterTest()
         {
 
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>()
             {
@@ -201,7 +201,7 @@ public void SdcaLogisticRegressionBinaryAdvancedParameterTest()
         [Fact]
         public void SdcaMaximumEntropyMultiBasicTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("SdcaMaximumEntropyMulti", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties);
@@ -218,7 +218,7 @@ public void SdcaMaximumEntropyMultiBasicTest()
         public void SdcaMaximumEntropyMultiAdvancedParameterTest()
         {
 
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>()
             {
@@ -238,7 +238,7 @@ public void SdcaMaximumEntropyMultiAdvancedParameterTest()
         [Fact]
         public void SdcaRegressionBasicTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("SdcaRegression", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties);
@@ -255,7 +255,7 @@ public void SdcaRegressionBasicTest()
         public void SdcaRegressionAdvancedParameterTest()
         {
 
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>()
             {
@@ -275,7 +275,7 @@ public void SdcaRegressionAdvancedParameterTest()
         [Fact]
         public void MatrixFactorizationBasicTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("MatrixFactorization", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties);
             Pipeline pipeline = new Pipeline(new PipelineNode[] { node });
@@ -289,7 +289,7 @@ public void MatrixFactorizationBasicTest()
         [Fact]
         public void MatrixFactorizationAdvancedTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
             var elementProperties = new Dictionary<string, object>()
             {
                 {"MatrixColumnIndexColumnName","userId" },
@@ -308,7 +308,7 @@ public void MatrixFactorizationAdvancedTest()
         [Fact]
         public void LbfgsPoissonRegressionBasicTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("LbfgsPoissonRegression", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties);
@@ -325,7 +325,7 @@ public void LbfgsPoissonRegressionBasicTest()
         public void LbfgsPoissonRegressionAdvancedParameterTest()
         {
 
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>()
             {
@@ -345,7 +345,7 @@ public void LbfgsPoissonRegressionAdvancedParameterTest()
         [Fact]
         public void OlsRegressionBasicTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("OlsRegression", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties);
@@ -362,7 +362,7 @@ public void OlsRegressionBasicTest()
         public void OlsRegressionAdvancedParameterTest()
         {
 
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>()
             {
@@ -382,7 +382,7 @@ public void OlsRegressionAdvancedParameterTest()
         [Fact]
         public void OnlineGradientDescentRegressionBasicTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("OnlineGradientDescentRegression", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties);
@@ -399,7 +399,7 @@ public void OnlineGradientDescentRegressionBasicTest()
         public void OnlineGradientDescentRegressionAdvancedParameterTest()
         {
 
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>()
             {
@@ -419,7 +419,7 @@ public void OnlineGradientDescentRegressionAdvancedParameterTest()
         [Fact]
         public void LbfgsLogisticRegressionBinaryBasicTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("LbfgsLogisticRegressionBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties);
@@ -436,7 +436,7 @@ public void LbfgsLogisticRegressionBinaryBasicTest()
         public void LbfgsLogisticRegressionBinaryAdvancedParameterTest()
         {
 
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>()
             {
@@ -456,7 +456,7 @@ public void LbfgsLogisticRegressionBinaryAdvancedParameterTest()
         [Fact]
         public void LbfgsMaximumEntropyMultiMultiBasicTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("LbfgsMaximumEntropyMulti", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties);
@@ -473,7 +473,7 @@ public void LbfgsMaximumEntropyMultiMultiBasicTest()
         public void LbfgsMaximumEntropyMultiAdvancedParameterTest()
         {
 
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>()
             {
@@ -493,7 +493,7 @@ public void LbfgsMaximumEntropyMultiAdvancedParameterTest()
         [Fact]
         public void LinearSvmBinaryBasicTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("LinearSvmBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties);
@@ -510,7 +510,7 @@ public void LinearSvmBinaryBasicTest()
         public void LinearSvmBinaryParameterTest()
         {
 
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>()
             {
@@ -531,7 +531,7 @@ public void LinearSvmBinaryParameterTest()
         [Fact]
         public void FastTreeTweedieRegressionBasicTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("FastTreeTweedieRegression", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties);
@@ -548,7 +548,7 @@ public void FastTreeTweedieRegressionBasicTest()
         public void FastTreeTweedieRegressionAdvancedParameterTest()
         {
 
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>()
             {
@@ -569,7 +569,7 @@ public void FastTreeTweedieRegressionAdvancedParameterTest()
         [Fact]
         public void FastTreeRegressionBasicTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("FastTreeRegression", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties);
@@ -586,7 +586,7 @@ public void FastTreeRegressionBasicTest()
         public void FastTreeRegressionAdvancedParameterTest()
         {
 
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>()
             {
@@ -607,7 +607,7 @@ public void FastTreeRegressionAdvancedParameterTest()
         [Fact]
         public void FastTreeBinaryBasicTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("FastTreeBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties);
@@ -624,7 +624,7 @@ public void FastTreeBinaryBasicTest()
         public void FastTreeBinaryAdvancedParameterTest()
         {
 
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>()
             {
@@ -645,7 +645,7 @@ public void FastTreeBinaryAdvancedParameterTest()
         [Fact]
         public void FastForestRegressionBasicTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("FastForestRegression", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties);
@@ -661,7 +661,7 @@ public void FastForestRegressionBasicTest()
         [Fact]
         public void FastForestRegressionAdvancedParameterTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>()
             {
@@ -682,7 +682,7 @@ public void FastForestRegressionAdvancedParameterTest()
         [Fact]
         public void FastForestBinaryBasicTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("FastForestBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties);
@@ -699,7 +699,7 @@ public void FastForestBinaryBasicTest()
         public void FastForestBinaryAdvancedParameterTest()
         {
 
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>()
             {
@@ -720,7 +720,7 @@ public void FastForestBinaryAdvancedParameterTest()
         [Fact]
         public void AveragedPerceptronBinaryBasicTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("AveragedPerceptronBinary", PipelineNodeType.Trainer, default(string[]), default(string), elementProperties);
@@ -737,7 +737,7 @@ public void AveragedPerceptronBinaryBasicTest()
         public void AveragedPerceptronBinaryAdvancedParameterTest()
         {
 
-            var context = new MLContext(1);
+            var context = new MLContext();
 
             var elementProperties = new Dictionary<string, object>()
             {
diff --git a/test/Microsoft.ML.CodeGenerator.Tests/TransformGeneratorTests.cs b/test/Microsoft.ML.CodeGenerator.Tests/TransformGeneratorTests.cs
index d4ad99f60b..875b93f84e 100644
--- a/test/Microsoft.ML.CodeGenerator.Tests/TransformGeneratorTests.cs
+++ b/test/Microsoft.ML.CodeGenerator.Tests/TransformGeneratorTests.cs
@@ -15,7 +15,7 @@ public class TransformGeneratorTests
         [Fact]
         public void MissingValueReplacingTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
             var elementProperties = new Dictionary<string, object>();//categorical
             PipelineNode node = new PipelineNode("MissingValueReplacing", PipelineNodeType.Transform, new string[] { "categorical_column_1" }, new string[] { "categorical_column_1" }, elementProperties);
             Pipeline pipeline = new Pipeline(new PipelineNode[] { node });
@@ -29,7 +29,7 @@ public void MissingValueReplacingTest()
         [Fact]
         public void OneHotEncodingTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
             var elementProperties = new Dictionary<string, object>();//categorical
             PipelineNode node = new PipelineNode("OneHotEncoding", PipelineNodeType.Transform, new string[] { "categorical_column_1" }, new string[] { "categorical_column_1" }, elementProperties);
             Pipeline pipeline = new Pipeline(new PipelineNode[] { node });
@@ -43,7 +43,7 @@ public void OneHotEncodingTest()
         [Fact]
         public void NormalizingTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("Normalizing", PipelineNodeType.Transform, new string[] { "numeric_column_1" }, new string[] { "numeric_column_1_copy" }, elementProperties);
             Pipeline pipeline = new Pipeline(new PipelineNode[] { node });
@@ -57,7 +57,7 @@ public void NormalizingTest()
         [Fact]
         public void ColumnConcatenatingTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("ColumnConcatenating", PipelineNodeType.Transform, new string[] { "numeric_column_1", "numeric_column_2" }, new string[] { "Features" }, elementProperties);
             Pipeline pipeline = new Pipeline(new PipelineNode[] { node });
@@ -71,7 +71,7 @@ public void ColumnConcatenatingTest()
         [Fact]
         public void ColumnCopyingTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
             var elementProperties = new Dictionary<string, object>();//nume to num feature 2
             PipelineNode node = new PipelineNode("ColumnCopying", PipelineNodeType.Transform, new string[] { "numeric_column_1" }, new string[] { "numeric_column_2" }, elementProperties);
             Pipeline pipeline = new Pipeline(new PipelineNode[] { node });
@@ -85,7 +85,7 @@ public void ColumnCopyingTest()
         [Fact]
         public void KeyToValueMappingTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("KeyToValueMapping", PipelineNodeType.Transform, new string[] { "Label" }, new string[] { "Label" }, elementProperties);
             Pipeline pipeline = new Pipeline(new PipelineNode[] { node });
@@ -99,7 +99,7 @@ public void KeyToValueMappingTest()
         [Fact]
         public void MissingValueIndicatingTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
             var elementProperties = new Dictionary<string, object>();//numeric feature
             PipelineNode node = new PipelineNode("MissingValueIndicating", PipelineNodeType.Transform, new string[] { "numeric_column_1" }, new string[] { "numeric_column_1" }, elementProperties);
             Pipeline pipeline = new Pipeline(new PipelineNode[] { node });
@@ -113,7 +113,7 @@ public void MissingValueIndicatingTest()
         [Fact]
         public void OneHotHashEncodingTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("OneHotHashEncoding", PipelineNodeType.Transform, new string[] { "Categorical_column_1" }, new string[] { "Categorical_column_1" }, elementProperties);
             Pipeline pipeline = new Pipeline(new PipelineNode[] { node });
@@ -127,7 +127,7 @@ public void OneHotHashEncodingTest()
         [Fact]
         public void TextFeaturizingTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("TextFeaturizing", PipelineNodeType.Transform, new string[] { "Text_column_1" }, new string[] { "Text_column_1" }, elementProperties);
             Pipeline pipeline = new Pipeline(new PipelineNode[] { node });
@@ -141,7 +141,7 @@ public void TextFeaturizingTest()
         [Fact]
         public void TypeConvertingTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("TypeConverting", PipelineNodeType.Transform, new string[] { "I4_column_1" }, new string[] { "R4_column_1" }, elementProperties);
             Pipeline pipeline = new Pipeline(new PipelineNode[] { node });
@@ -155,7 +155,7 @@ public void TypeConvertingTest()
         [Fact]
         public void ValueToKeyMappingTest()
         {
-            var context = new MLContext(1);
+            var context = new MLContext();
             var elementProperties = new Dictionary<string, object>();
             PipelineNode node = new PipelineNode("ValueToKeyMapping", PipelineNodeType.Transform, new string[] { "Label" }, new string[] { "Label" }, elementProperties);
             Pipeline pipeline = new Pipeline(new PipelineNode[] { node });