Make test methods public

test/Microsoft.ML.Functional.Tests/DataTransformation.cs

@@ -23,7 +23,7 @@ public DataTransformation(ITestOutputHelper output) : base(output)
         /// Extensibility: Add a new column that is a function of other columns.
         /// </summary>
         [Fact]
-        void ExtensibilityAddAColumnAsAFunctionOfMultipleColumns()
+        public void ExtensibilityAddAColumnAsAFunctionOfMultipleColumns()
         {
             // Concurrency must be 1 to assure that the mapping is done sequentially.
             var mlContext = new MLContext(seed: 1);
@@ -76,7 +76,7 @@ float angiospermCosine(float petalWidth, float petalLength, float sepalWidth, fl
         /// Extensibility: Add multiple new columns.
         /// </summary>
         [Fact]
-        void ExtensibilityAddingTwoColumns()
+        public void ExtensibilityAddingTwoColumns()
         {
             // Concurrency must be 1 to assure that the mapping is done sequentially.
             var mlContext = new MLContext(seed: 1);
@@ -124,7 +124,7 @@ void ExtensibilityAddingTwoColumns()
         /// Extensibility: Featurize text using custom word-grams, char-grams, and normalization.
         /// </summary>
         [Fact]
-        void ExtensibilityModifyTextFeaturization()
+        public void ExtensibilityModifyTextFeaturization()
         {
             // Concurrency must be 1 to assure that the mapping is done sequentially.
             var mlContext = new MLContext(seed: 1);
@@ -160,7 +160,7 @@ void ExtensibilityModifyTextFeaturization()
         /// Extensibility: Apply a normalizer to columns in the dataset.
         /// </summary>
         [Fact]
-        void ExtensibilityNormalizeColumns()
+        public void ExtensibilityNormalizeColumns()
         {
             // Concurrency must be 1 to assure that the mapping is done sequentially.
             var mlContext = new MLContext(seed: 1);

test/Microsoft.ML.Functional.Tests/Debugging.cs

@@ -32,7 +32,7 @@ public Debugging(ITestOutputHelper output) : base(output)
         /// float vector {3:1, 25:1, 203:1, 511:1}, etc. etc.
         /// </remarks>
         [Fact]
-        void InspectIntermediatePipelineSteps()
+        public void InspectIntermediatePipelineSteps()
         {
             var mlContext = new MLContext(seed: 1);
 

test/Microsoft.ML.Functional.Tests/IntrospectiveTraining.cs

@@ -128,7 +128,7 @@ public void InspectFastTreeModelParameters()
         /// Introspective Training: GAM Shape Functions are easily accessed.
         /// </summary>
         [Fact]
-        void IntrospectGamShapeFunctions()
+        public void IntrospectGamShapeFunctions()
         {
             // Concurrency must be 1 to assure that the mapping is done sequentially.
             var mlContext = new MLContext(seed: 1);
@@ -240,7 +240,7 @@ public void InpsectLinearModelParameters()
         /// Introspectable Training: Parameters of a trained Normalizer are easily accessed.
         /// </summary>
         [Fact]
-        void IntrospectNormalization()
+        public void IntrospectNormalization()
         {
             // Concurrency must be 1 to assure that the mapping is done sequentially.
             var mlContext = new MLContext(seed: 1);

test/Microsoft.ML.Functional.Tests/Validation.cs

@@ -26,7 +26,7 @@ public Validation(ITestOutputHelper output) : base(output)
         /// metrics, trained pipelines, and scored test data for each fold.
         /// </summary>
         [Fact]
-        void CrossValidation()
+        public void CrossValidation()
         {
             var mlContext = new MLContext(seed: 1);
 

test/Microsoft.ML.OnnxTransformerTest/DnnImageFeaturizerTest.cs

@@ -54,7 +54,7 @@ public DnnImageFeaturizerTests(ITestOutputHelper helper) : base(helper)
         }
 
         [OnnxFact]
-        void TestDnnImageFeaturizer()
+        public void TestDnnImageFeaturizer()
         {
             var samplevector = GetSampleArrayData();
 

test/Microsoft.ML.OnnxTransformerTest/OnnxTransformTests.cs

@@ -104,7 +104,7 @@ public OnnxTransformTests(ITestOutputHelper output) : base(output)
         }
 
         [OnnxFact]
-        void TestSimpleCase()
+        public void TestSimpleCase()
         {
             var modelFile = "squeezenet/00000001/model.onnx";
             var samplevector = GetSampleArrayData();
@@ -144,7 +144,7 @@ void TestSimpleCase()
         [OnnxTheory]
         [InlineData(null, false)]
         [InlineData(null, true)]
-        void TestOldSavingAndLoading(int? gpuDeviceId, bool fallbackToCpu)
+        public void TestOldSavingAndLoading(int? gpuDeviceId, bool fallbackToCpu)
         {
             var modelFile = "squeezenet/00000001/model.onnx";
             var samplevector = GetSampleArrayData();
@@ -240,14 +240,14 @@ public void OnnxWorkout()
         }
 
         [OnnxFact]
-        void TestCommandLine()
+        public void TestCommandLine()
         {
             var x = Maml.Main(new[] { @"showschema loader=Text{col=data_0:R4:0-150527} xf=Onnx{InputColumns={data_0} OutputColumns={softmaxout_1} model={squeezenet/00000001/model.onnx}}" });
             Assert.Equal(0, x);
         }
 
         [OnnxFact]
-        void TestCommandLineWithCustomShape()
+        public void TestCommandLineWithCustomShape()
         {
             var x = Maml.Main(new[] { @"showschema loader=Text{col=data_0:R4:0-150527} xf=Onnx{customShapeInfos={Name=data_0 Shape=1 Shape=3 Shape=224 Shape=224} InputColumns={data_0} OutputColumns={softmaxout_1} model={squeezenet/00000001/model.onnx}}" });
             Assert.Equal(0, x);

test/Microsoft.ML.Tests/FakeSchemaTest.cs

@@ -18,7 +18,7 @@ public FakeSchemaTest(ITestOutputHelper output)
         }
 
         [Fact]
-        void SimpleTest()
+        public void SimpleTest()
         {
             var metadataBuilder = new DataViewSchema.Annotations.Builder();
             metadataBuilder.Add("M", NumberDataViewType.Single, (ref float v) => v = 484f);

test/Microsoft.ML.Tests/OnnxConversionTest.cs

@@ -313,7 +313,7 @@ private class DataPoint
         }
 
         [Fact]
-        void LpNormOnnxConversionTest()
+        public void LpNormOnnxConversionTest()
         {
             var mlContext = new MLContext(seed: 1);
 
@@ -369,7 +369,7 @@ void LpNormOnnxConversionTest()
         }
 
         [Fact]
-        void CommandLineOnnxConversionTest()
+        public void CommandLineOnnxConversionTest()
         {
             string dataPath = GetDataPath("breast-cancer.txt");
             string modelPath = GetOutputPath("ModelWithLessIO.zip");
@@ -918,7 +918,7 @@ public bool Equals(TransformedDataPoint other)
         }
 
         [Fact]
-        void IndicateMissingValuesOnnxConversionTest()
+        public void IndicateMissingValuesOnnxConversionTest()
         {
             var mlContext = new MLContext(seed: 1);
 
@@ -968,7 +968,7 @@ void IndicateMissingValuesOnnxConversionTest()
         }
 
         [Fact]
-        void ValueToKeyMappingOnnxConversionTest()
+        public void ValueToKeyMappingOnnxConversionTest()
         {
             var mlContext = new MLContext(seed: 1);
             string filePath = GetDataPath("type-conversion.txt");
@@ -1018,7 +1018,7 @@ private class TextData
         }
 
         [Fact]
-        void WordTokenizerOnnxConversionTest()
+        public void WordTokenizerOnnxConversionTest()
         {
             var mlContext = new MLContext(seed: 1);
 
@@ -1055,7 +1055,7 @@ void WordTokenizerOnnxConversionTest()
         }
 
         [Fact]
-        void NgramOnnxConnversionTest()
+        public void NgramOnnxConnversionTest()
         {
             var mlContext = new MLContext(seed: 1);
 
@@ -1171,7 +1171,7 @@ public void OptionalColumnOnnxTest()
         }
 
         [Fact]
-        private void KeyToValueOnnxConversionTest()
+        public void KeyToValueOnnxConversionTest()
         {
             var mlContext = new MLContext(seed: 1);
 
@@ -1207,7 +1207,7 @@ private void KeyToValueOnnxConversionTest()
         }
 
         [Fact]
-        void MulticlassTrainersOnnxConversionTest()
+        public void MulticlassTrainersOnnxConversionTest()
         {
             var mlContext = new MLContext(seed: 1);
 
@@ -1262,7 +1262,7 @@ void MulticlassTrainersOnnxConversionTest()
         }
 
         [Fact]
-        void CopyColumnsOnnxTest()
+        public void CopyColumnsOnnxTest()
         {
             var mlContext = new MLContext(seed: 1);
 

test/Microsoft.ML.Tests/Scenarios/Api/Estimators/DecomposableTrainAndPredict.cs

@@ -23,7 +23,7 @@ public partial class ApiScenariosTests
         /// say, injecting a dummy label.
         /// </summary>
         [Fact]
-        void DecomposableTrainAndPredict()
+        public void DecomposableTrainAndPredict()
         {
             var dataPath = GetDataPath(TestDatasets.irisData.trainFilename);
             var ml = new MLContext();

test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Extensibility.cs

@@ -22,7 +22,7 @@ public partial class ApiScenariosTests
         /// usage of already established components), but should still be possible.
         /// </summary>
         [Fact]
-        void Extensibility()
+        public void Extensibility()
         {
             var dataPath = GetDataPath(TestDatasets.irisData.trainFilename);
 

test/Microsoft.ML.Tests/Scenarios/Api/Estimators/MultithreadedPrediction.cs

@@ -22,7 +22,7 @@ public partial class ApiScenariosTests
         /// and performant in the new API.
         /// </summary>
         [Fact]
-        void MultithreadedPrediction()
+        public void MultithreadedPrediction()
         {
             var ml = new MLContext(seed: 1);
             var data = ml.Data.LoadFromTextFile<SentimentData>(GetDataPath(TestDatasets.Sentiment.trainFilename), hasHeader: true);

test/Microsoft.ML.Tests/Scenarios/Api/Estimators/PredictAndMetadata.cs

@@ -21,7 +21,7 @@ public partial class ApiScenariosTests
         /// key value to original label value. This example also shows how to convert key value to original label.
         /// </summary>
         [Fact]
-        void PredictAndMetadata()
+        public void PredictAndMetadata()
         {
             var dataPath = GetDataPath(TestDatasets.irisData.trainFilename);
             var ml = new MLContext();
@@ -70,7 +70,7 @@ void PredictAndMetadata()
         }
 
         [Fact]
-        void MulticlassConfusionMatrixSlotNames()
+        public void MulticlassConfusionMatrixSlotNames()
         {
             var mlContext = new MLContext(seed: 1);
 

test/Microsoft.ML.Tests/TensorFlowEstimatorTests.cs

@@ -57,7 +57,7 @@ public TensorFlowEstimatorTests(ITestOutputHelper output) : base(output)
         }
 
         [TensorFlowFact]
-        void TestSimpleCase()
+        public void TestSimpleCase()
         {
             var modelFile = "model_matmul/frozen_saved_model.pb";
 
@@ -97,7 +97,7 @@ void TestSimpleCase()
         }
 
         [TensorFlowFact]
-        void TestOldSavingAndLoading()
+        public void TestOldSavingAndLoading()
         {
             var modelFile = "model_matmul/frozen_saved_model.pb";
 
@@ -133,7 +133,7 @@ void TestOldSavingAndLoading()
         }
 
         [TensorFlowFact]
-        void TestCommandLine()
+        public void TestCommandLine()
         {
             // typeof helps to load the TensorFlowTransformer type.
             Type type = typeof(TensorFlowTransformer);

test/Microsoft.ML.Tests/TermEstimatorTests.cs

@@ -49,7 +49,7 @@ class TestMetaClass
         }
 
         [Fact]
-        void TestDifferentTypes()
+        public void TestDifferentTypes()
         {
             string dataPath = GetDataPath("adult.tiny.with-schema.txt");
 
@@ -92,7 +92,7 @@ void TestDifferentTypes()
         }
 
         [Fact]
-        void TestSimpleCase()
+        public void TestSimpleCase()
         {
             var data = new[] { new TestClass() { A = 1, B = 2, C = 3, }, new TestClass() { A = 4, B = 5, C = 6 } };
 
@@ -110,7 +110,7 @@ void TestSimpleCase()
         }
 
         [Fact]
-        void TestOldSavingAndLoading()
+        public void TestOldSavingAndLoading()
         {
             var data = new[] { new TestClass() { A = 1, B = 2, C = 3, }, new TestClass() { A = 4, B = 5, C = 6 } };
             var dataView = ML.Data.LoadFromEnumerable(data);
@@ -132,7 +132,7 @@ void TestOldSavingAndLoading()
         }
 
         [Fact]
-        void TestMetadataCopy()
+        public void TestMetadataCopy()
         {
             var data = new[] { new TestMetaClass() { Term = "A", NotUsed = 1 }, new TestMetaClass() { Term = "B" }, new TestMetaClass() { Term = "C" } };
             var dataView = ML.Data.LoadFromEnumerable(data);
@@ -150,7 +150,7 @@ void TestMetadataCopy()
         }
 
         [Fact]
-        void TestCommandLine()
+        public void TestCommandLine()
         {
             Assert.Equal(0, Maml.Main(new[] { @"showschema loader=Text{col=A:R4:0} xf=Term{col=B:A} in=f:\2.txt" }));
         }

test/Microsoft.ML.Tests/Transformers/ConcatTests.cs

@@ -19,7 +19,7 @@ public ConcatTests(ITestOutputHelper output) : base(output)
         }
 
         [Fact]
-        void TestConcatNoInputColumns()
+        public void TestConcatNoInputColumns()
         {
             var thrown = false;
 
@@ -38,7 +38,7 @@ void TestConcatNoInputColumns()
         }
 
         [Fact]
-        void TestConcat()
+        public void TestConcat()
         {
             string dataPath = GetDataPath("adult.tiny.with-schema.txt");