Enable MSML_ParameterLocalVarName for the full solution (#4833)

.editorconfig

@@ -24,9 +24,6 @@ dotnet_diagnostic.MSML_NoBestFriendInternal.severity = none
 # MSML_NoInstanceInitializers: No initializers on instance fields or properties
 dotnet_diagnostic.MSML_NoInstanceInitializers.severity = none
 
-# MSML_ParameterLocalVarName: Parameter or local variable name not standard
-dotnet_diagnostic.MSML_ParameterLocalVarName.severity = none
-
 [test/Microsoft.ML.CodeAnalyzer.Tests/**.cs]
 # BaseTestClass does not apply for analyzer testing.
 # MSML_ExtendBaseTestClass: Test classes should be derived from BaseTestClass

test/Microsoft.Extensions.ML.Tests/UriLoaderTests.cs

@@ -74,7 +74,7 @@ public void no_reload_no_change()
 
     class UriLoaderMock : UriModelLoader
     {
-        public Func<Uri, string, bool> ETagMatches { get; set; } = (_, __) => false;
+        public Func<Uri, string, bool> ETagMatches { get; set; } = delegate { return false; };
 
         public UriLoaderMock(IOptions<MLOptions> contextOptions,
                          ILogger<UriModelLoader> logger) : base(contextOptions, logger)

test/Microsoft.ML.AutoML.Tests/UserInputValidationTests.cs

@@ -188,16 +188,16 @@ public void ValidateFeaturesColInvalidType()
         [Fact]
         public void ValidateTextColumnNotText()
         {
-            const string TextPurposeColName = "TextColumn";
+            const string textPurposeColName = "TextColumn";
             var schemaBuilder = new DataViewSchema.Builder();
             schemaBuilder.AddColumn(DefaultColumnNames.Features, NumberDataViewType.Single);
             schemaBuilder.AddColumn(DefaultColumnNames.Label, NumberDataViewType.Single);
-            schemaBuilder.AddColumn(TextPurposeColName, NumberDataViewType.Single);
+            schemaBuilder.AddColumn(textPurposeColName, NumberDataViewType.Single);
             var schema = schemaBuilder.ToSchema();
             var dataView = DataViewTestFixture.BuildDummyDataView(schema);
 
             var columnInfo = new ColumnInformation();
-            columnInfo.TextColumnNames.Add(TextPurposeColName);
+            columnInfo.TextColumnNames.Add(textPurposeColName);
 
             foreach (var task in new[] { TaskKind.Recommendation, TaskKind.Regression })
             {

test/Microsoft.ML.Benchmarks/ImageClassificationBench.cs

@@ -205,10 +205,10 @@ public static void UnZip(String gzArchiveName, String destFolder)
 
         public static string GetAbsolutePath(string relativePath)
         {
-            FileInfo _dataRoot = new FileInfo(typeof(
+            FileInfo dataRoot = new FileInfo(typeof(
                 ImageClassificationBench).Assembly.Location);
 
-            string assemblyFolderPath = _dataRoot.Directory.FullName;
+            string assemblyFolderPath = dataRoot.Directory.FullName;
 
             string fullPath = Path.Combine(assemblyFolderPath, relativePath);
 

test/Microsoft.ML.Benchmarks/PredictionEngineBench.cs

@@ -34,7 +34,7 @@ public void SetupIrisPipeline()
                 PetalWidth = 5.1f,
             };
 
-            string _irisDataPath = BaseTestClass.GetDataPath("iris.txt");
+            string irisDataPath = BaseTestClass.GetDataPath("iris.txt");
 
             var env = new MLContext(seed: 1);
 
@@ -53,7 +53,7 @@ public void SetupIrisPipeline()
             };
             var loader = new TextLoader(env, options: options);
 
-            IDataView data = loader.Load(_irisDataPath);
+            IDataView data = loader.Load(irisDataPath);
 
             var pipeline = new ColumnConcatenatingEstimator(env, "Features", new[] { "SepalLength", "SepalWidth", "PetalLength", "PetalWidth" })
                 .Append(env.Transforms.Conversion.MapValueToKey("Label"))
@@ -73,7 +73,7 @@ public void SetupSentimentPipeline()
                 SentimentText = "Not a big fan of this."
             };
 
-            string _sentimentDataPath = BaseTestClass.GetDataPath("wikipedia-detox-250-line-data.tsv");
+            string sentimentDataPath = BaseTestClass.GetDataPath("wikipedia-detox-250-line-data.tsv");
 
             var mlContext = new MLContext(seed: 1);
 
@@ -89,7 +89,7 @@ public void SetupSentimentPipeline()
             };
             var loader = new TextLoader(mlContext, options: options);
 
-            IDataView data = loader.Load(_sentimentDataPath);
+            IDataView data = loader.Load(sentimentDataPath);
 
             var pipeline = mlContext.Transforms.Text.FeaturizeText("Features", "SentimentText")
                 .Append(mlContext.BinaryClassification.Trainers.SdcaNonCalibrated(
@@ -108,7 +108,7 @@ public void SetupBreastCancerPipeline()
                 Features = new[] { 5f, 1f, 1f, 1f, 2f, 1f, 3f, 1f, 1f }
             };
 
-            string _breastCancerDataPath = BaseTestClass.GetDataPath("breast-cancer.txt");
+            string breastCancerDataPath = BaseTestClass.GetDataPath("breast-cancer.txt");
 
             var env = new MLContext(seed: 1);
 
@@ -124,7 +124,7 @@ public void SetupBreastCancerPipeline()
             };
             var loader = new TextLoader(env, options: options);
 
-            IDataView data = loader.Load(_breastCancerDataPath);
+            IDataView data = loader.Load(breastCancerDataPath);
 
             var pipeline = env.BinaryClassification.Trainers.SdcaNonCalibrated(
                 new SdcaNonCalibratedBinaryTrainer.Options { NumberOfThreads = 1, ConvergenceTolerance = 1e-2f, });

test/Microsoft.ML.CpuMath.PerformanceTests/PerformanceTests.cs

@@ -48,13 +48,13 @@ private float NextFloat(Random rand, int expRange)
         private int GetSeed()
         {
             int seed = DefaultSeed;
-            string CPUMATH_SEED = Environment.GetEnvironmentVariable("CPUMATH_SEED");
+            string cpumathSeed = Environment.GetEnvironmentVariable("CPUMATH_SEED");
 
-            if (CPUMATH_SEED != null)
+            if (cpumathSeed != null)
             {
-                if (!int.TryParse(CPUMATH_SEED, out seed))
+                if (!int.TryParse(cpumathSeed, out seed))
                 {
-                    if (string.Equals(CPUMATH_SEED, "random", StringComparison.OrdinalIgnoreCase))
+                    if (string.Equals(cpumathSeed, "random", StringComparison.OrdinalIgnoreCase))
                     {
                         seed = new Random().Next();
                     }

test/Microsoft.ML.NugetPackageVersionUpdater/Program.cs

@@ -56,10 +56,10 @@ private static void UpdatePackageVersion(string projectFiles, IDictionary<string
 
             foreach (var projectFilePath in projectFilePaths)
             {
-                var CsprojDoc = new XmlDocument();
-                CsprojDoc.Load(projectFilePath);
+                var csprojDoc = new XmlDocument();
+                csprojDoc.Load(projectFilePath);
 
-                var packageReferenceNodes = CsprojDoc.DocumentElement.SelectNodes(packageReferencePath);
+                var packageReferenceNodes = csprojDoc.DocumentElement.SelectNodes(packageReferencePath);
 
                 for (int i = 0; i < packageReferenceNodes.Count; i++)
                 {
@@ -75,7 +75,7 @@ private static void UpdatePackageVersion(string projectFiles, IDictionary<string
                         Console.WriteLine($"Can't find newer version of Package {packageName} from NuGet source, don't need to update version.");
                 }
 
-                CsprojDoc.Save(projectFilePath);
+                csprojDoc.Save(projectFilePath);
             }
         }
     }

test/Microsoft.ML.Predictor.Tests/TestParallelFasttreeInterface.cs

@@ -24,7 +24,7 @@ internal sealed class FastTreeParallelInterfaceChecker : Trainers.FastTree.IPara
         private bool _isInitTreeLearner = false;
         private bool _isInitIteration = false;
         private bool _isCache = false;
-        public void CacheHistogram(bool isSmallerLeaf, int featureIdx, int subfeature, SufficientStatsBase sufficientStatsBase, bool HasWeights)
+        public void CacheHistogram(bool isSmallerLeaf, int featureIdx, int subfeature, SufficientStatsBase sufficientStatsBase, bool hasWeights)
         {
             Assert.True(_isInitEnv);
             Assert.True(_isInitTreeLearner);

test/Microsoft.ML.TestFramework/RemoteExecutor.cs

@@ -112,35 +112,35 @@ private static void RemoteInvoke(MethodInfo method, string[] args, RemoteInvokeO
             CheckProcess(Process.Start(psi), options);
         }
 
-        private static void CheckProcess(Process process, RemoteInvokeOptions Options)
+        private static void CheckProcess(Process process, RemoteInvokeOptions options)
         {
             if (process != null)
             {
                 // A bit unorthodox to do throwing operations in a Dispose, but by doing it here we avoid
                 // needing to do this in every derived test and keep each test much simpler.
                 try
                 {
-                    Assert.True(process.WaitForExit(Options.TimeOut),
-                        $"Timed out after {Options.TimeOut}ms waiting for remote process {process.Id}");
+                    Assert.True(process.WaitForExit(options.TimeOut),
+                        $"Timed out after {options.TimeOut}ms waiting for remote process {process.Id}");
 
-                    if (File.Exists(Options.ExceptionFile))
+                    if (File.Exists(options.ExceptionFile))
                     {
-                        throw new RemoteExecutionException(File.ReadAllText(Options.ExceptionFile));
+                        throw new RemoteExecutionException(File.ReadAllText(options.ExceptionFile));
                     }
 
-                    if (Options.CheckExitCode)
+                    if (options.CheckExitCode)
                     {
-                        int expected = RuntimeInformation.IsOSPlatform(OSPlatform.Windows) ? Options.ExpectedExitCode : unchecked((sbyte)Options.ExpectedExitCode);
+                        int expected = RuntimeInformation.IsOSPlatform(OSPlatform.Windows) ? options.ExpectedExitCode : unchecked((sbyte)options.ExpectedExitCode);
                         int actual = RuntimeInformation.IsOSPlatform(OSPlatform.Windows) ? process.ExitCode : unchecked((sbyte)process.ExitCode);
 
-                        Assert.True(expected == actual, $"Exit code was {process.ExitCode} but it should have been {Options.ExpectedExitCode}");
+                        Assert.True(expected == actual, $"Exit code was {process.ExitCode} but it should have been {options.ExpectedExitCode}");
                     }
                 }
                 finally
                 {
-                    if (File.Exists(Options.ExceptionFile))
+                    if (File.Exists(options.ExceptionFile))
                     {
-                        File.Delete(Options.ExceptionFile);
+                        File.Delete(options.ExceptionFile);
                     }
 
                     // Cleanup

test/Microsoft.ML.Tests/OnnxSequenceTypeWithAttributesTest.cs

@@ -56,12 +56,12 @@ public void OnnxSequenceTypeWithColumnNameAttributeTest()
 
             FloatInput input = new FloatInput() { Input = new float[] { 1.0f, 2.0f, 3.0f } };
             var output = predictor.Predict(input);
-            var onnx_out = output.Output.FirstOrDefault();
-            Assert.True(onnx_out.Count == 3, "Output missing data.");
-            var keys = new List<string>(onnx_out.Keys);
-            for(var i =0; i < onnx_out.Count; ++i)
+            var onnxOut = output.Output.FirstOrDefault();
+            Assert.True(onnxOut.Count == 3, "Output missing data.");
+            var keys = new List<string>(onnxOut.Keys);
+            for(var i =0; i < onnxOut.Count; ++i)
             {
-                Assert.Equal(onnx_out[keys[i]], input.Input[i]);
+                Assert.Equal(onnxOut[keys[i]], input.Input[i]);
             }
 
         }

test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/TensorflowTests.cs

@@ -108,7 +108,7 @@ public void TensorFlowTransforCifarEndToEndTest2()
         {
             var imageHeight = 32;
             var imageWidth = 32;
-            var model_location = "cifar_model/frozen_model.pb";
+            var modelLocation = "cifar_model/frozen_model.pb";
             var dataFile = GetDataPath("images/images.tsv");
             var imageFolder = Path.GetDirectoryName(dataFile);
 
@@ -125,7 +125,7 @@ public void TensorFlowTransforCifarEndToEndTest2()
             var pipeEstimator = new ImageLoadingEstimator(mlContext, imageFolder, ("ImageReal", "ImagePath"))
                     .Append(new ImageResizingEstimator(mlContext, "ImageCropped", imageHeight, imageWidth, "ImageReal"))
                     .Append(new ImagePixelExtractingEstimator(mlContext, "Input", "ImageCropped", interleavePixelColors: true))
-                    .Append(mlContext.Model.LoadTensorFlowModel(model_location).ScoreTensorFlowModel("Output", "Input"))
+                    .Append(mlContext.Model.LoadTensorFlowModel(modelLocation).ScoreTensorFlowModel("Output", "Input"))
                     .Append(new ColumnConcatenatingEstimator(mlContext, "Features", "Output"))
                     .Append(new ValueToKeyMappingEstimator(mlContext, "Label"))
                     .AppendCacheCheckpoint(mlContext)
@@ -345,7 +345,7 @@ private class TypesData
         public void TensorFlowTransformInputOutputTypesTest()
         {
             // This an identity model which returns the same output as input.
-            var model_location = "model_types_test";
+            var modelLocation = "model_types_test";
 
             //Data
             var data = new List<TypesData>(
@@ -382,7 +382,7 @@ public void TensorFlowTransformInputOutputTypesTest()
 
             var inputs = new string[] { "f64", "f32", "i64", "i32", "i16", "i8", "u64", "u32", "u16", "u8", "b" };
             var outputs = new string[] { "o_f64", "o_f32", "o_i64", "o_i32", "o_i16", "o_i8", "o_u64", "o_u32", "o_u16", "o_u8", "o_b" };
-            var trans = mlContext.Model.LoadTensorFlowModel(model_location).ScoreTensorFlowModel(outputs, inputs).Fit(loader).Transform(loader); ;
+            var trans = mlContext.Model.LoadTensorFlowModel(modelLocation).ScoreTensorFlowModel(outputs, inputs).Fit(loader).Transform(loader); ;
 
             using (var cursor = trans.GetRowCursorForAllColumns())
             {
@@ -546,8 +546,8 @@ public void TensorFlowTransformInceptionTest()
         public void TensorFlowInputsOutputsSchemaTest()
         {
             var mlContext = new MLContext(seed: 1);
-            var model_location = "mnist_model/frozen_saved_model.pb";
-            var schema = TensorFlowUtils.GetModelSchema(mlContext, model_location);
+            var modelLocation = "mnist_model/frozen_saved_model.pb";
+            var schema = TensorFlowUtils.GetModelSchema(mlContext, modelLocation);
             Assert.Equal(86, schema.Count);
             Assert.True(schema.TryGetColumnIndex("Placeholder", out int col));
             var type = (VectorDataViewType)schema[col].Type;
@@ -607,8 +607,8 @@ public void TensorFlowInputsOutputsSchemaTest()
             Assert.Equal(1, inputOps.Length);
             Assert.Equal("sequential/dense_1/BiasAdd", inputOps.GetValues()[0].ToString());
 
-            model_location = "model_matmul/frozen_saved_model.pb";
-            schema = TensorFlowUtils.GetModelSchema(mlContext, model_location);
+            modelLocation = "model_matmul/frozen_saved_model.pb";
+            schema = TensorFlowUtils.GetModelSchema(mlContext, modelLocation);
             char name = 'a';
             for (int i = 0; i < schema.Count; i++)
             {
@@ -663,7 +663,7 @@ public void TensorFlowTransformMNISTLRTrainingTest()
         {
             const double expectedMicroAccuracy = 0.72173913043478266;
             const double expectedMacroAccruacy = 0.67482993197278918;
-            var model_location = "mnist_lr_model";
+            var modelLocation = "mnist_lr_model";
             try
             {
                 var mlContext = new MLContext(seed: 1);
@@ -686,7 +686,7 @@ public void TensorFlowTransformMNISTLRTrainingTest()
                         labelColumnName: "OneHotLabel",
                         dnnLabel: "Label",
                         optimizationOperation: "SGDOptimizer",
-                        modelPath: model_location,
+                        modelPath: modelLocation,
                         lossOperation: "Loss",
                         epoch: 10,
                         learningRateOperation: "SGDOptimizer/learning_rate",
@@ -724,16 +724,16 @@ public void TensorFlowTransformMNISTLRTrainingTest()
             {
                 // This test changes the state of the model.
                 // Cleanup folder so that other test can also use the same model.
-                CleanUp(model_location);
+                CleanUp(modelLocation);
             }
         }
 
-        private void CleanUp(string model_location)
+        private void CleanUp(string modelLocation)
         {
-            var directories = Directory.GetDirectories(model_location, "variables-*");
+            var directories = Directory.GetDirectories(modelLocation, "variables-*");
             if (directories != null && directories.Length > 0)
             {
-                var varDir = Path.Combine(model_location, "variables");
+                var varDir = Path.Combine(modelLocation, "variables");
                 if (Directory.Exists(varDir))
                     Directory.Delete(varDir, true);
                 Directory.Move(directories[0], varDir);