dotnet format/spellchecking (#5988)

.editorconfig

@@ -306,6 +306,10 @@ dotnet_diagnostic.IDE2004.severity = warning
 dotnet_diagnostic.CA1822.severity = suggestion
 
 [test/**/*.cs]
+# IDE0044: Don't force readonly for tests
+dotnet_diagnostic.IDE0044.severity = none
+dotnet_style_readonly_field = false
+
 # MSML_GeneralName: This name should be PascalCased
 dotnet_diagnostic.MSML_GeneralName.severity = none
 
@@ -322,4 +326,18 @@ dotnet_diagnostic.MSML_ExtendBaseTestClass.severity = none
 
 # The MSML_RelaxTestNaming suppressor for VSTHRD200 is not active for CodeAnalyzer.Tests, so we disable it altogether.
 # VSTHRD200: Use "Async" suffix for async methods
-dotnet_diagnostic.VSTHRD200.severity = none
+dotnet_diagnostic.VSTHRD200.severity = none
+
+[docs/**/*.cs]
+# IDE0073: Dont want license file header in samples
+dotnet_diagnostic.IDE0073.severity = none
+file_header_template = unset
+
+# IDE0044: Don't force readonly for samples
+dotnet_diagnostic.IDE0044.severity = none
+dotnet_style_readonly_field = false
+
+[test/Microsoft.ML.TestFrameworkCommon/Utility/*.cs]
+# IDE0073: Dont want license file header in code we are using from elsewhere
+dotnet_diagnostic.IDE0073.severity = none
+file_header_template = unset

Directory.Build.props

@@ -17,6 +17,7 @@
     <DebugType>portable</DebugType>
     <DebugSymbols>true</DebugSymbols>
     <LangVersion>latest</LangVersion>
+    <EnforceCodeStyleInBuild>true</EnforceCodeStyleInBuild>
   </PropertyGroup>
 
   <PropertyGroup>

docs/samples/Microsoft.ML.AutoML.Samples/RankingExperiment.cs

@@ -1,10 +1,10 @@
 using System;
 using System.Collections.Generic;
-using System.Text;
 using System.IO;
 using System.Linq;
-using Microsoft.ML.Data;
+using System.Text;
 using Microsoft.ML.AutoML.Samples.DataStructures;
+using Microsoft.ML.Data;
 
 namespace Microsoft.ML.AutoML.Samples
 {

docs/samples/Microsoft.ML.Samples/Dynamic/Trainers/MulticlassClassification/ImageClassification/ResnetV2101TransferLearningEarlyStopping.cs

@@ -2,15 +2,15 @@
 using System;
 using System.Collections.Generic;
 using System.IO;
+using System.IO.Compression;
+using System.Linq;
+using System.Net;
+using System.Threading;
 using System.Threading.Tasks;
 using Microsoft.ML;
-using static Microsoft.ML.DataOperationsCatalog;
-using System.Linq;
 using Microsoft.ML.Data;
-using System.IO.Compression;
-using System.Threading;
-using System.Net;
 using Microsoft.ML.Vision;
+using static Microsoft.ML.DataOperationsCatalog;
 
 namespace Samples.Dynamic
 {

docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/CustomMappingWithInMemoryCustomType.cs

@@ -18,7 +18,7 @@ namespace Samples.Dynamic
         // AlienBody members to produce a SuperAlienHero entity with a "Name" member of type
         // string and a single "Merged" member of type AlienBody, where the merger is just
         // the addition of the various members of AlienBody.
-        static public void Example()
+        public static void Example()
         {
             var mlContext = new MLContext();
             // Build in-memory data.

docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/ImageAnalytics/ConvertToGrayScaleInMemory.cs

@@ -7,7 +7,7 @@ namespace Samples.Dynamic
 {
     class ConvertToGrayScaleInMemory
     {
-        static public void Example()
+        public static void Example()
         {
             var mlContext = new MLContext();
             // Create an image list.

docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/TimeSeries/ForecastingWithConfidenceInterval.cs

@@ -1,8 +1,8 @@
 using System;
 using System.Collections.Generic;
+using System.IO;
 using Microsoft.ML;
 using Microsoft.ML.Transforms.TimeSeries;
-using System.IO;
 
 namespace Samples.Dynamic
 {

src/Microsoft.Data.Analysis/ArrowStringDataFrameColumn.cs

@@ -20,9 +20,9 @@ namespace Microsoft.Data.Analysis
     /// </summary>
     public partial class ArrowStringDataFrameColumn : DataFrameColumn, IEnumerable<string>
     {
-        private IList<ReadOnlyDataFrameBuffer<byte>> _dataBuffers;
-        private IList<ReadOnlyDataFrameBuffer<int>> _offsetsBuffers;
-        private IList<ReadOnlyDataFrameBuffer<byte>> _nullBitMapBuffers;
+        private readonly IList<ReadOnlyDataFrameBuffer<byte>> _dataBuffers;
+        private readonly IList<ReadOnlyDataFrameBuffer<int>> _offsetsBuffers;
+        private readonly IList<ReadOnlyDataFrameBuffer<byte>> _nullBitMapBuffers;
 
         /// <summary>
         /// Constructs an empty <see cref="ArrowStringDataFrameColumn"/> with the given <paramref name="name"/>.
@@ -40,7 +40,7 @@ namespace Microsoft.Data.Analysis
         /// </summary>
         /// <param name="name">The name of the column.</param>
         /// <param name="values">The Arrow formatted string values in this column.</param>
-        /// <param name="offsets">The Arrow formatted offets in this column.</param>
+        /// <param name="offsets">The Arrow formatted offsets in this column.</param>
         /// <param name="nullBits">The Arrow formatted null bits in this column.</param>
         /// <param name="length">The length of the column.</param>
         /// <param name="nullCount">The number of <see langword="null" /> values in this column.</param>

src/Microsoft.Data.Analysis/DataFrame.IO.cs

@@ -293,10 +293,10 @@ namespace Microsoft.Data.Analysis
 
         private class WrappedStreamReaderOrStringReader
         {
-            private Stream _stream;
-            private long _initialPosition;
-            private Encoding _encoding;
-            private string _csvString;
+            private readonly Stream _stream;
+            private readonly long _initialPosition;
+            private readonly Encoding _encoding;
+            private readonly string _csvString;
 
             public WrappedStreamReaderOrStringReader(Stream stream, Encoding encoding)
             {

src/Microsoft.Data.Analysis/DataFrame.Join.cs

@@ -142,7 +142,7 @@ namespace Microsoft.Data.Analysis
             return ret;
         }
 
-        private static bool IsAnyNullValueInColumns (IReadOnlyCollection<DataFrameColumn> columns, long index)
+        private static bool IsAnyNullValueInColumns(IReadOnlyCollection<DataFrameColumn> columns, long index)
         {
             foreach (var column in columns)
             {
@@ -176,19 +176,19 @@ namespace Microsoft.Data.Analysis
                 throw new ArgumentNullException(nameof(supplemetaryJoinColumnNames));
 
             if (retainedJoinColumnNames.Length != supplemetaryJoinColumnNames.Length)
-                throw new ArgumentException(Strings.MismatchedArrayLengths, nameof(retainedJoinColumnNames));  
-            
+                throw new ArgumentException(Strings.MismatchedArrayLengths, nameof(retainedJoinColumnNames));
+
 
             HashSet<long> intersection = calculateIntersection ? new HashSet<long>() : null;
 
             // Get occurrences of values in columns used for join in the retained and supplementary dataframes
             Dictionary<long, ICollection<long>> occurrences = null;
             Dictionary<long, long> retainedIndicesReverseMapping = null;
-            
+
             HashSet<long> supplementaryJoinColumnsNullIndices = new HashSet<long>();
 
-            
-            for (int colNameIndex =  0; colNameIndex < retainedJoinColumnNames.Length; colNameIndex++)
+
+            for (int colNameIndex = 0; colNameIndex < retainedJoinColumnNames.Length; colNameIndex++)
             {
                 DataFrameColumn shrinkedRetainedColumn = retainedDataFrame.Columns[retainedJoinColumnNames[colNameIndex]];
 
@@ -211,7 +211,7 @@ namespace Microsoft.Data.Analysis
                     retainedIndicesReverseMapping = newRetainedIndicesReverseMapping;
                     shrinkedRetainedColumn = shrinkedRetainedColumn.Clone(new Int64DataFrameColumn("Indices", shrinkedRetainedIndices));
                 }
-                
+
                 DataFrameColumn supplementaryColumn = supplementaryDataFrame.Columns[supplemetaryJoinColumnNames[colNameIndex]];
 
                 //Find occurrenses on current step (join column)
@@ -222,7 +222,7 @@ namespace Microsoft.Data.Analysis
                     newOccurrences = newOccurrences.ToDictionary(kvp => retainedIndicesReverseMapping[kvp.Key], kvp => kvp.Value);
 
                 supplementaryJoinColumnsNullIndices.UnionWith(supplementaryColumnNullIndices);
-                
+
                 // shrink join result on current column by previous join columns (if any)
                 // (we have to remove occurrences that doesn't exist in previous columns, because JOIN happens only if ALL left and right columns in JOIN are matched)
                 if (occurrences != null)
@@ -242,7 +242,7 @@ namespace Microsoft.Data.Analysis
 
                 occurrences = newOccurrences;
             }
-            
+
             retainedRowIndices = new Int64DataFrameColumn("RetainedIndices");
             supplementaryRowIndices = new Int64DataFrameColumn("SupplementaryIndices");
 
@@ -280,7 +280,7 @@ namespace Microsoft.Data.Analysis
                     }
                 }
                 else
-                {                    
+                {
                     foreach (long row in supplementaryJoinColumnsNullIndices)
                     {
                         retainedRowIndices.Append(i);
@@ -288,10 +288,10 @@ namespace Microsoft.Data.Analysis
                     }
                 }
             }
-                    
+
             return intersection;
         }
-                    
+
         public DataFrame Merge(DataFrame other, string[] leftJoinColumns, string[] rightJoinColumns, string leftSuffix = "_left", string rightSuffix = "_right", JoinAlgorithm joinAlgorithm = JoinAlgorithm.Left)
         {
             if (other == null)
@@ -335,7 +335,7 @@ namespace Microsoft.Data.Analysis
             else if (joinAlgorithm == JoinAlgorithm.FullOuter)
             {
                 //In full outer join we would like to retain data from both side, so we do it into 2 steps: one first we do LEFT JOIN and then add lost data from the RIGHT side
-                
+
                 //Step 1
                 //Do LEFT JOIN
                 isLeftDataFrameRetained = true;
@@ -347,7 +347,7 @@ namespace Microsoft.Data.Analysis
                 var retainedJoinColumns = isLeftDataFrameRetained ? leftJoinColumns : rightJoinColumns;
 
                 var intersection = Merge(retainedDataFrame, supplementaryDataFrame, retainedJoinColumns, supplementaryJoinColumns, out retainedRowIndices, out supplementaryRowIndices, calculateIntersection: true);
-                                
+
                 //Step 2
                 //Do RIGHT JOIN to retain all data from supplementary DataFrame too (take into account data intersection from the first step to avoid duplicates)
                 for (long i = 0; i < supplementaryDataFrame.Columns.RowCount; i++)
@@ -365,9 +365,9 @@ namespace Microsoft.Data.Analysis
             }
             else
                 throw new NotImplementedException(nameof(joinAlgorithm));
-                                    
+
             DataFrame ret = new DataFrame();
-                       
+
             //insert columns from left dataframe (this)
             for (int i = 0; i < this.Columns.Count; i++)
             {

src/Microsoft.Data.Analysis/DataFrameColumn.cs

@@ -244,7 +244,7 @@ namespace Microsoft.Data.Analysis
                     ret.Add(i, otherRowIndices);
                 }
             }
-            
+
             return ret;
         }
 

src/Microsoft.Data.Analysis/DataFrameColumnCollection.cs

@@ -13,11 +13,11 @@ namespace Microsoft.Data.Analysis
     /// </summary>
     public class DataFrameColumnCollection : Collection<DataFrameColumn>
     {
-        private Action ColumnsChanged;
+        private readonly Action ColumnsChanged;
 
-        private List<string> _columnNames = new List<string>();
+        private readonly List<string> _columnNames = new List<string>();
 
-        private Dictionary<string, int> _columnNameToIndexDictionary = new Dictionary<string, int>(StringComparer.Ordinal);
+        private readonly Dictionary<string, int> _columnNameToIndexDictionary = new Dictionary<string, int>(StringComparer.Ordinal);
 
         internal long RowCount { get; set; }
 

src/Microsoft.Data.Analysis/GroupBy.cs

@@ -101,9 +101,9 @@ namespace Microsoft.Data.Analysis
 
         #endregion
 
-        private int _groupByColumnIndex;
-        private IDictionary<TKey, ICollection<long>> _keyToRowIndicesMap;
-        private DataFrame _dataFrame;
+        private readonly int _groupByColumnIndex;
+        private readonly IDictionary<TKey, ICollection<long>> _keyToRowIndicesMap;
+        private readonly DataFrame _dataFrame;
 
         public GroupBy(DataFrame dataFrame, int groupByColumnIndex, IDictionary<TKey, ICollection<long>> keyToRowIndices)
         {

src/Microsoft.Data.Analysis/PrimitiveDataFrameColumn.cs

@@ -20,7 +20,7 @@ namespace Microsoft.Data.Analysis
     public partial class PrimitiveDataFrameColumn<T> : DataFrameColumn, IEnumerable<T?>
         where T : unmanaged
     {
-        private PrimitiveColumnContainer<T> _columnContainer;
+        private readonly PrimitiveColumnContainer<T> _columnContainer;
 
         internal PrimitiveColumnContainer<T> ColumnContainer => _columnContainer;
 

src/Microsoft.Data.Analysis/StringDataFrameColumn.cs

@@ -17,7 +17,7 @@ namespace Microsoft.Data.Analysis
     /// <remarks> Is NOT Arrow compatible </remarks>
     public partial class StringDataFrameColumn : DataFrameColumn, IEnumerable<string>
     {
-        private List<List<string>> _stringBuffers = new List<List<string>>(); // To store more than intMax number of strings
+        private readonly List<List<string>> _stringBuffers = new List<List<string>>(); // To store more than intMax number of strings
 
         public StringDataFrameColumn(string name, long length = 0) : base(name, length, typeof(string))
         {

src/Microsoft.Data.Analysis/TextFieldParser.cs

@@ -22,12 +22,12 @@ namespace Microsoft.Data.Analysis
 
     internal class QuoteDelimitedFieldBuilder
     {
-        private StringBuilder _field;
+        private readonly StringBuilder _field;
         private bool _fieldFinished;
         private int _index;
         private int _delimiterLength;
-        private Regex _delimiterRegex;
-        private string _spaceChars;
+        private readonly Regex _delimiterRegex;
+        private readonly string _spaceChars;
         private bool _malformedLine;
 
         public QuoteDelimitedFieldBuilder(Regex delimiterRegex, string spaceChars)
@@ -148,7 +148,7 @@ namespace Microsoft.Data.Analysis
 
         private Regex _delimiterWithEndCharsRegex;
 
-        private int[] _whitespaceCodes = new int[] { '\u0009', '\u000B', '\u000C', '\u0020', '\u0085', '\u00A0', '\u1680', '\u2000', '\u2001', '\u2002', '\u2003', '\u2004', '\u2005', '\u2006', '\u2007', '\u2008', '\u2009', '\u200A', '\u200B', '\u2028', '\u2029', '\u3000', '\uFEFF' };
+        private readonly int[] _whitespaceCodes = new int[] { '\u0009', '\u000B', '\u000C', '\u0020', '\u0085', '\u00A0', '\u1680', '\u2000', '\u2001', '\u2002', '\u2003', '\u2004', '\u2005', '\u2006', '\u2007', '\u2008', '\u2009', '\u200A', '\u200B', '\u2028', '\u2029', '\u3000', '\uFEFF' };
 
         private Regex _beginQuotesRegex;
 
@@ -172,13 +172,13 @@ namespace Microsoft.Data.Analysis
 
         private string _spaceChars;
 
-        private int _maxLineSize = 10000000;
+        private readonly int _maxLineSize = 10000000;
 
-        private int _maxBufferSize = 10000000;
+        private readonly int _maxBufferSize = 10000000;
 
-        private bool _leaveOpen;
+        private readonly bool _leaveOpen;
 
-        private char[] newLineChars = Environment.NewLine.ToCharArray();
+        private readonly char[] _newLineChars = Environment.NewLine.ToCharArray();
 
         public string[] CommentTokens
         {
@@ -419,7 +419,7 @@ namespace Microsoft.Data.Analysis
             }
 
             _lineNumber++;
-            return line.TrimEnd(newLineChars);
+            return line.TrimEnd(_newLineChars);
         }
 
         public string[] ReadFields()
@@ -470,7 +470,7 @@ namespace Microsoft.Data.Analysis
                 return null;
             }
 
-            line = line.TrimEnd(newLineChars);
+            line = line.TrimEnd(_newLineChars);
             if (line.Length < numberOfChars)
             {
                 return line;
@@ -799,7 +799,7 @@ namespace Microsoft.Data.Analysis
                     endHelper.BuildField(line, index);
                     if (endHelper.MalformedLine)
                     {
-                        _errorLine = line.TrimEnd(newLineChars);
+                        _errorLine = line.TrimEnd(_newLineChars);
                         _errorLineNumber = currentLineNumber;
                         throw new Exception(string.Format(Strings.CannotParseWithDelimiters, currentLineNumber));
                     }
@@ -817,13 +817,13 @@ namespace Microsoft.Data.Analysis
                             string newLine = ReadNextDataLine();
                             if (newLine == null)
                             {
-                                _errorLine = line.TrimEnd(newLineChars);
+                                _errorLine = line.TrimEnd(_newLineChars);
                                 _errorLineNumber = currentLineNumber;
                                 throw new Exception(string.Format(Strings.CannotParseWithDelimiters, currentLineNumber));
                             }
                             if (line.Length + newLine.Length > _maxLineSize)
                             {
-                                _errorLine = line.TrimEnd(newLineChars);
+                                _errorLine = line.TrimEnd(_newLineChars);
                                 _errorLineNumber = currentLineNumber;
                                 throw new Exception(string.Format(Strings.LineExceedsMaxLineSize, currentLineNumber));
                             }
@@ -832,7 +832,7 @@ namespace Microsoft.Data.Analysis
                             endHelper.BuildField(line, endOfLine);
                             if (endHelper.MalformedLine)
                             {
-                                _errorLine = line.TrimEnd(newLineChars);
+                                _errorLine = line.TrimEnd(_newLineChars);
                                 _errorLineNumber = currentLineNumber;
                                 throw new Exception(string.Format(Strings.CannotParseWithDelimiters, currentLineNumber));
                             }
@@ -862,7 +862,7 @@ namespace Microsoft.Data.Analysis
                     index = delimiterMatch.Index + delimiterMatch.Length;
                     continue;
                 }
-                field = line.Substring(index).TrimEnd(newLineChars);
+                field = line.Substring(index).TrimEnd(_newLineChars);
                 if (_trimWhiteSpace)
                 {
                     field = field.Trim();
@@ -881,7 +881,7 @@ namespace Microsoft.Data.Analysis
             {
                 return null;
             }
-            line = line.TrimEnd(newLineChars);
+            line = line.TrimEnd(_newLineChars);
             StringInfo lineInfo = new StringInfo(line);
             ValidateFixedWidthLine(lineInfo, _lineNumber - 1);
             int index = 0;
@@ -897,7 +897,7 @@ namespace Microsoft.Data.Analysis
 
         private string GetFixedWidthField(StringInfo line, int index, int fieldLength)
         {
-            string field = (fieldLength > 0) ? line.SubstringByTextElements(index, fieldLength) : ((index < line.LengthInTextElements) ? line.SubstringByTextElements(index).TrimEnd(newLineChars) : string.Empty);
+            string field = (fieldLength > 0) ? line.SubstringByTextElements(index, fieldLength) : ((index < line.LengthInTextElements) ? line.SubstringByTextElements(index).TrimEnd(_newLineChars) : string.Empty);
             if (_trimWhiteSpace)
             {
                 return field.Trim();
@@ -1062,7 +1062,7 @@ namespace Microsoft.Data.Analysis
                 {
                     throw new Exception(Strings.EmptyDelimiters);
                 }
-                if (delimiter.IndexOfAny(newLineChars) > -1)
+                if (delimiter.IndexOfAny(_newLineChars) > -1)
                 {
                     throw new Exception(Strings.DelimiterCannotBeNewlineChar);
                 }

src/Microsoft.Extensions.ML/Properties/AssemblyInfo.cs

@@ -1,3 +1,7 @@
-using System.Runtime.CompilerServices;
+// 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 System.Runtime.CompilerServices;
 
 [assembly: InternalsVisibleTo("Microsoft.Extensions.ML.Tests, PublicKey=00240000048000009400000006020000002400005253413100040000010001004b86c4cb78549b34bab61a3b1800e23bfeb5b3ec390074041536a7e3cbd97f5f04cf0f857155a8928eaa29ebfd11cfbbad3ba70efea7bda3226c6a8d370a4cd303f714486b6ebc225985a638471e6ef571cc92a4613c00b8fa65d61ccee0cbe5f36330c9a01f4183559f1bef24cc2917c6d913e3a541333a1d05d9bed22b38cb")]

src/Microsoft.ML.AutoML/API/AutoCatalog.cs

@@ -1,4 +1,4 @@
-// Foundation under one or more agreements.
+// 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.
 

src/Microsoft.ML.AutoML/API/BinaryClassificationExperiment.cs

@@ -1,4 +1,4 @@
-// Foundation under one or more agreements.
+// 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.
 

src/Microsoft.ML.AutoML/API/ColumnInference.cs

@@ -1,4 +1,4 @@
-// Foundation under one or more agreements.
+// 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.
 

src/Microsoft.ML.AutoML/API/ExperimentBase.cs

@@ -1,4 +1,4 @@
-// Foundation under one or more agreements.
+// 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.
 

src/Microsoft.ML.AutoML/API/ExperimentResults/CrossValidationExperimentResult.cs

@@ -1,4 +1,4 @@
-// Foundation under one or more agreements.
+// 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.
 

src/Microsoft.ML.AutoML/API/ExperimentResults/ExperimentResult.cs

@@ -1,4 +1,4 @@
-// Foundation under one or more agreements.
+// 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.
 

src/Microsoft.ML.AutoML/API/ExperimentSettings.cs

@@ -1,4 +1,4 @@
-// Foundation under one or more agreements.
+// 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.
 

src/Microsoft.ML.AutoML/API/MLContextExtension.cs

@@ -1,4 +1,4 @@
-// Foundation under one or more agreements.
+// 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.
 

src/Microsoft.ML.AutoML/API/MulticlassClassificationExperiment.cs

@@ -1,4 +1,4 @@
-// Foundation under one or more agreements.
+// 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.
 

src/Microsoft.ML.AutoML/API/RankingExperiment.cs

@@ -1,4 +1,4 @@
-// Foundation under one or more agreements.
+// 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.
 

src/Microsoft.ML.AutoML/API/RegressionExperiment.cs

@@ -1,4 +1,4 @@
-// Foundation under one or more agreements.
+// 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.
 

src/Microsoft.ML.AutoML/ColumnInference/ColumnInformationUtil.cs

@@ -1,4 +1,4 @@
-// Foundation under one or more agreements.
+// 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.
 

src/Microsoft.ML.AutoML/Experiment/OptimizingMetricInfo.cs

@@ -10,18 +10,18 @@ namespace Microsoft.ML.AutoML
     {
         public bool IsMaximizing { get; }
 
-        private static RegressionMetric[] _minimizingRegressionMetrics = new RegressionMetric[]
+        private static readonly RegressionMetric[] _minimizingRegressionMetrics = new RegressionMetric[]
         {
             RegressionMetric.MeanAbsoluteError,
             RegressionMetric.MeanSquaredError,
             RegressionMetric.RootMeanSquaredError
         };
 
-        private static BinaryClassificationMetric[] _minimizingBinaryMetrics = new BinaryClassificationMetric[]
+        private static readonly BinaryClassificationMetric[] _minimizingBinaryMetrics = new BinaryClassificationMetric[]
         {
         };
 
-        private static MulticlassClassificationMetric[] _minimizingMulticlassMetrics = new MulticlassClassificationMetric[]
+        private static readonly MulticlassClassificationMetric[] _minimizingMulticlassMetrics = new MulticlassClassificationMetric[]
         {
             MulticlassClassificationMetric.LogLoss,
         };

src/Microsoft.ML.AutoML/Sweepers/SmacSweeper.cs

@@ -344,8 +344,8 @@ namespace Microsoft.ML.AutoML
         // Todo: Remove the reflection below for TreeTreeEnsembleModelParameters methods GetLeaf and GetLeafValue.
         // Long-term, replace with tree featurizer once it becomes available
         // Tracking issue -- https://github.com/dotnet/machinelearning-automl/issues/342
-        private static MethodInfo _getLeafMethod = typeof(TreeEnsembleModelParameters).GetMethod("GetLeaf", BindingFlags.NonPublic | BindingFlags.Instance);
-        private static MethodInfo _getLeafValueMethod = typeof(TreeEnsembleModelParameters).GetMethod("GetLeafValue", BindingFlags.NonPublic | BindingFlags.Instance);
+        private static readonly MethodInfo _getLeafMethod = typeof(TreeEnsembleModelParameters).GetMethod("GetLeaf", BindingFlags.NonPublic | BindingFlags.Instance);
+        private static readonly MethodInfo _getLeafValueMethod = typeof(TreeEnsembleModelParameters).GetMethod("GetLeafValue", BindingFlags.NonPublic | BindingFlags.Instance);
 
         private static int GetLeaf(TreeEnsembleModelParameters model, int treeId, VBuffer<Float> features)
         {

src/Microsoft.ML.AutoML/TrainerExtensions/TrainerExtensionUtil.cs

@@ -75,7 +75,7 @@ namespace Microsoft.ML.AutoML
             return options;
         }
 
-        private static string[] _lightGbmBoosterParamNames = new[] { "L2Regularization", "L1Regularization" };
+        private static readonly string[] _lightGbmBoosterParamNames = new[] { "L2Regularization", "L1Regularization" };
         private const string LightGbmBoosterPropName = "Booster";
 
         public static TOptions CreateLightGbmOptions<TOptions, TOutput, TTransformer, TModel>(IEnumerable<SweepableParam> sweepParams, ColumnInformation columnInfo)

src/Microsoft.ML.AutoML/Utils/StringEditDistance.cs

@@ -1,4 +1,8 @@
-using System;
+// 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 System;
 
 namespace Microsoft.ML.AutoML.Utils
 {

src/Microsoft.ML.CodeGenerator/CodeGenerator/CSharp/AzureCodeGenerator/AzureAttachConsoleAppCodeGenerator.cs

@@ -76,7 +76,7 @@ namespace Microsoft.ML.CodeGenerator.CodeGenerator.CSharp
                     IncludeRecommenderPackage = false,
                     StablePackageVersion = _settings.StablePackageVersion,
                     UnstablePackageVersion = _settings.UnstablePackageVersion,
-                    OnnxRuntimePackageVersion = _settings.OnnxRuntimePacakgeVersion,
+                    OnnxRuntimePackageVersion = _settings.OnnxRuntimePackageVersion,
                 }.TransformText(),
                 Name = $"{_settings.OutputName}.ConsoleApp.csproj",
             };

src/Microsoft.ML.CodeGenerator/CodeGenerator/CSharp/AzureCodeGenerator/AzureAttachModelCodeGenerator.cs

@@ -92,7 +92,7 @@ namespace Microsoft.ML.CodeGenerator.CodeGenerator.CSharp.AzureCodeGenerator
                     IncludeRecommenderPackage = false,
                     StablePackageVersion = _settings.StablePackageVersion,
                     UnstablePackageVersion = _settings.UnstablePackageVersion,
-                    OnnxRuntimePackageVersion = _settings.OnnxRuntimePacakgeVersion,
+                    OnnxRuntimePackageVersion = _settings.OnnxRuntimePackageVersion,
                     Target = _settings.Target,
                 }.TransformText(),
                 Name = $"{ _settings.OutputName }.Model.csproj",

src/Microsoft.ML.CodeGenerator/CodeGenerator/CSharp/CodeGenerator.cs

@@ -285,7 +285,7 @@ namespace Microsoft.ML.CodeGenerator.CSharp
                 IncludeRecommenderPackage = includeRecommenderPackage,
                 StablePackageVersion = stablePackageVersion,
                 UnstablePackageVersion = unstablePackageVersion,
-                OnnxRuntimePackageVersion = _settings.OnnxRuntimePacakgeVersion,
+                OnnxRuntimePackageVersion = _settings.OnnxRuntimePackageVersion,
                 Target = target,
             };
 
@@ -336,7 +336,7 @@ namespace Microsoft.ML.CodeGenerator.CSharp
                 IncludeRecommenderPackage = includeRecommenderPackage,
                 StablePackageVersion = stablePackageVersion,
                 UnstablePackageVersion = unstablePackageVersion,
-                OnnxRuntimePackageVersion = _settings.OnnxRuntimePacakgeVersion,
+                OnnxRuntimePackageVersion = _settings.OnnxRuntimePackageVersion,
                 Target = target,
             };
             return predictProjectFileContent.TransformText();

src/Microsoft.ML.CodeGenerator/CodeGenerator/CSharp/CodeGeneratorSettings.cs

@@ -54,7 +54,7 @@ namespace Microsoft.ML.CodeGenerator.CSharp
 
         public string UnstablePackageVersion { get; set; }
 
-        public string OnnxRuntimePacakgeVersion { get; set; }
+        public string OnnxRuntimePackageVersion { get; set; }
 
         public bool IsAzureAttach { get; set; }
 

src/Microsoft.ML.CodeGenerator/CodeGenerator/CSharp/TrainerGenerators.cs

@@ -538,7 +538,7 @@ namespace Microsoft.ML.CodeGenerator.CSharp
 
         internal class OneVersusAll : TrainerGeneratorBase
         {
-            private PipelineNode _node;
+            private readonly PipelineNode _node;
             private string[] _binaryTrainerUsings;
 
             //ClassName of the trainer

src/Microsoft.ML.Core/CommandLine/CmdLexer.cs

@@ -10,7 +10,7 @@ namespace Microsoft.ML.CommandLine
     [BestFriend]
     internal sealed class CmdLexer
     {
-        private CharCursor _curs;
+        private readonly CharCursor _curs;
 
         // Whether \ has a special significance.
         private readonly bool _escapes;
@@ -307,7 +307,7 @@ namespace Microsoft.ML.CommandLine
     internal sealed class CmdQuoter
     {
         private readonly string _str;
-        private StringBuilder _sb;
+        private readonly StringBuilder _sb;
         private int _ich;
 
         private CmdQuoter(string str, StringBuilder sb)

src/Microsoft.ML.Core/Data/Repository.cs

@@ -79,7 +79,7 @@ namespace Microsoft.ML
         }
 
         // These are the open entries that may contain streams into our DirTemp.
-        private List<Entry> _open;
+        private readonly List<Entry> _open;
 
         private bool _disposed;
 
@@ -435,11 +435,11 @@ namespace Microsoft.ML
     [BestFriend]
     internal sealed class RepositoryReader : Repository
     {
-        private ZipArchive _archive;
+        private readonly ZipArchive _archive;
 
         // Maps from a normalized path to the entry in the _archive. This is needed since
         // a zip might use / or \ for directory separation.
-        private Dictionary<string, ZipArchiveEntry> _entries;
+        private readonly Dictionary<string, ZipArchiveEntry> _entries;
 
         public static RepositoryReader Open(Stream stream, IExceptionContext ectx = null, bool useFileSystem = true)
         {

src/Microsoft.ML.Core/Environment/ConsoleEnvironment.cs

@@ -352,7 +352,7 @@ namespace Microsoft.ML.Runtime
         private readonly MessageSensitivity _sensitivityFlags;
 
         // This object is used to write to the test log along with the console if the host process is a test environment
-        private TextWriter _testWriter;
+        private readonly TextWriter _testWriter;
 
         /// <summary>
         /// Create an ML.NET <see cref="IHostEnvironment"/> for local execution, with console feedback.

src/Microsoft.ML.Core/Utilities/BinFinder.cs

@@ -13,7 +13,7 @@ namespace Microsoft.ML.Internal.Utilities
     {
         private Single[] _valuesSng; // distinct values
         private Double[] _valuesDbl; // distinct values
-        private List<int> _counts; // counts for each value
+        private readonly List<int> _counts; // counts for each value
         private int[] _path; // current set of pegs
 
         protected int CountBins { get; private set; } // number of bins
@@ -314,8 +314,8 @@ namespace Microsoft.ML.Internal.Utilities
             }
         }
 
-        private Heap<Segment> _segmentHeap; // heap used for dropping initial peg placement
-        private HeapNode.Heap<Peg> _pegHeap; // heap used for selecting the largest energy decrease
+        private readonly Heap<Segment> _segmentHeap; // heap used for dropping initial peg placement
+        private readonly HeapNode.Heap<Peg> _pegHeap; // heap used for selecting the largest energy decrease
         private int[] _accum; // integral of counts
         private int[] _path; // current set of pegs
         private float _meanBinSize;

src/Microsoft.ML.Core/Utilities/DoubleParser.cs

@@ -732,7 +732,7 @@ LAfterDigits:
 
         // Map from base-10 exponent to 64-bit mantissa.
         // The approximation for 10^n is _mpe10man[n-1] * 2^(_mpe10e2[n-1]-64).
-        private static ulong[] _mpe10Man = new ulong[] {
+        private static readonly ulong[] _mpe10Man = new ulong[] {
             0xA000000000000000UL, 0xC800000000000000UL, 0xFA00000000000000UL, 0x9C40000000000000UL, 0xC350000000000000UL, /*005*/
             0xF424000000000000UL, 0x9896800000000000UL, 0xBEBC200000000000UL, 0xEE6B280000000000UL, 0x9502F90000000000UL, /*010*/
             0xBA43B74000000000UL, 0xE8D4A51000000000UL, 0x9184E72A00000000UL, 0xB5E620F480000000UL, 0xE35FA931A0000000UL, /*015*/
@@ -801,7 +801,7 @@ LAfterDigits:
 
         // Map from negative base-10 exponent to 64-bit mantissa. Note that the top bit of these is set.
         // The approximation for 10^-n is _mpne10man[n-1] * 2^(-_mpne10ne2[n-1]-64).
-        private static ulong[] _mpne10Man = new ulong[] {
+        private static readonly ulong[] _mpne10Man = new ulong[] {
             0xCCCCCCCCCCCCCCCDUL, 0xA3D70A3D70A3D70AUL, 0x83126E978D4FDF3BUL, 0xD1B71758E219652CUL, 0xA7C5AC471B478423UL, /*005*/
             0x8637BD05AF6C69B6UL, 0xD6BF94D5E57A42BCUL, 0xABCC77118461CEFDUL, 0x89705F4136B4A597UL, 0xDBE6FECEBDEDD5BFUL, /*010*/
             0xAFEBFF0BCB24AAFFUL, 0x8CBCCC096F5088CCUL, 0xE12E13424BB40E13UL, 0xB424DC35095CD80FUL, 0x901D7CF73AB0ACD9UL, /*015*/
@@ -878,7 +878,7 @@ LAfterDigits:
 
         // Map from base-10 exponent to base-2 exponent.
         // The approximation for 10^n is _mpe10man[n-1] * 2^(_mpe10e2[n-1]-64).
-        private static short[] _mpe10e2 = new short[] {
+        private static readonly short[] _mpe10e2 = new short[] {
                4,    7,   10,   14,   17,   20,   24,   27,   30,   34,   37,   40,   44,   47,   50,   54,   57,   60,   64,   67, /*020*/
               70,   74,   77,   80,   84,   87,   90,   94,   97,  100,  103,  107,  110,  113,  117,  120,  123,  127,  130,  133, /*040*/
              137,  140,  143,  147,  150,  153,  157,  160,  163,  167,  170,  173,  177,  180,  183,  187,  190,  193,  196,  200, /*060*/

src/Microsoft.ML.Core/Utilities/Stats.cs

@@ -42,7 +42,7 @@ namespace Microsoft.ML.Internal.Utilities
             return result;
         }
 
-        private static double _vScale = 2 * Math.Sqrt(2 / Math.E);
+        private static readonly double _vScale = 2 * Math.Sqrt(2 / Math.E);
 
         /// <summary>
         /// Returns a number sampled from a zero-mean, unit variance Gaussian
@@ -242,7 +242,7 @@ namespace Microsoft.ML.Internal.Utilities
             // n*p at which we switch algorithms
             private const int NPThresh = 10;
 
-            private static double[] _fctab = new double[] {
+            private static readonly double[] _fctab = new double[] {
                 0.08106146679532726, 0.04134069595540929, 0.02767792568499834,
                 0.02079067210376509, 0.01664469118982119, 0.01387612882307075,
                 0.01189670994589177, 0.01041126526197209, 0.009255462182712733,

src/Microsoft.ML.Core/Utilities/TextReaderStream.cs

@@ -28,7 +28,7 @@ namespace Microsoft.ML.Internal.Utilities
         private string _line;
         private int _lineCur;
 
-        private byte[] _buff;
+        private readonly byte[] _buff;
         private int _buffCur;
         private int _buffLim;
         private bool _eof;

src/Microsoft.ML.CpuMath/AlignedArray.cs

@@ -28,7 +28,7 @@ namespace Microsoft.ML.Internal.CpuMath
         private readonly int _cbAlign; // The alignment in bytes, a power of two, divisible by sizeof(Float).
         private int _base; // Where the values start in Items (changes to ensure alignment).
 
-        private object _lock; // Used to make sure only one thread can re-align the values.
+        private readonly object _lock; // Used to make sure only one thread can re-align the values.
 
         /// <summary>
         /// Allocate an aligned vector with the given alignment (in bytes).

src/Microsoft.ML.Data/Data/DataViewTypeManager.cs

@@ -23,7 +23,7 @@ namespace Microsoft.ML.Data
         /// For example, UInt32 and Key can be mapped to <see langword="uint"/>. This class enforces one-to-one mapping for all
         /// user-registered types.
         /// </summary>
-        private static HashSet<Type> _bannedRawTypes = new HashSet<Type>()
+        private static readonly HashSet<Type> _bannedRawTypes = new HashSet<Type>()
         {
             typeof(Boolean), typeof(SByte), typeof(Byte),
             typeof(Int16), typeof(UInt16), typeof(Int32), typeof(UInt32),
@@ -36,17 +36,17 @@ namespace Microsoft.ML.Data
         /// <summary>
         /// Mapping from a <see cref="Type"/> plus its <see cref="Attribute"/>s to a <see cref="DataViewType"/>.
         /// </summary>
-        private static Dictionary<TypeWithAttributes, DataViewType> _rawTypeToDataViewTypeMap = new Dictionary<TypeWithAttributes, DataViewType>();
+        private static readonly Dictionary<TypeWithAttributes, DataViewType> _rawTypeToDataViewTypeMap = new Dictionary<TypeWithAttributes, DataViewType>();
 
         /// <summary>
         /// Mapping from a <see cref="DataViewType"/> to a <see cref="Type"/> plus its <see cref="Attribute"/>s.
         /// </summary>
-        private static Dictionary<DataViewType, TypeWithAttributes> _dataViewTypeToRawTypeMap = new Dictionary<DataViewType, TypeWithAttributes>();
+        private static readonly Dictionary<DataViewType, TypeWithAttributes> _dataViewTypeToRawTypeMap = new Dictionary<DataViewType, TypeWithAttributes>();
 
         /// <summary>
         /// The lock that one should acquire if the state of <see cref="DataViewTypeManager"/> will be accessed or modified.
         /// </summary>
-        private static object _lock = new object();
+        private static readonly object _lock = new object();
 
         /// <summary>
         /// Returns the <see cref="DataViewType"/> registered for <paramref name="type"/> and its <paramref name="typeAttributes"/>.
@@ -228,7 +228,7 @@ namespace Microsoft.ML.Data
             /// a key when using <see cref="TypeWithAttributes"/> as the key type in <see cref="Dictionary{TKey, TValue}"/>. Note that the
             /// uniqueness is determined by <see cref="Equals(object)"/> and <see cref="GetHashCode"/> below.
             /// </summary>
-            private DataViewTypeAttribute _associatedAttribute;
+            private readonly DataViewTypeAttribute _associatedAttribute;
 
             public TypeWithAttributes(Type type, DataViewTypeAttribute attribute)
             {

src/Microsoft.ML.Data/DataLoadSave/Binary/BinarySaver.cs

@@ -107,8 +107,8 @@ namespace Microsoft.ML.Data.IO
 
         private sealed class WritePipe<T> : WritePipe
         {
-            private ValueGetter<T> _getter;
-            private IValueCodec<T> _codec;
+            private readonly ValueGetter<T> _getter;
+            private readonly IValueCodec<T> _codec;
             private IValueWriter<T> _writer;
             private MemoryStream _currentStream;
             private T _value;

src/Microsoft.ML.Data/DataLoadSave/Binary/Codecs.cs

@@ -313,7 +313,7 @@ namespace Microsoft.ML.Data.IO
             private sealed class Writer : ValueWriterBase<ReadOnlyMemory<char>>
             {
                 private StringBuilder _builder;
-                private List<int> _boundaries;
+                private readonly List<int> _boundaries;
 
                 public Writer(TextCodec codec, Stream stream)
                     : base(codec.Factory, stream)
@@ -353,7 +353,7 @@ namespace Microsoft.ML.Data.IO
                 private readonly int _entries;
                 private readonly int[] _boundaries;
                 private int _index;
-                private string _text;
+                private readonly string _text;
 
                 public Reader(TextCodec codec, Stream stream, int items)
                     : base(codec.Factory, stream)

src/Microsoft.ML.Data/DataLoadSave/Binary/UnsafeTypeOps.cs

@@ -25,7 +25,7 @@ namespace Microsoft.ML.Internal.Internallearn
 
     internal static class UnsafeTypeOpsFactory
     {
-        private static Dictionary<Type, object> _type2ops;
+        private static readonly Dictionary<Type, object> _type2ops;
 
         static UnsafeTypeOpsFactory()
         {

src/Microsoft.ML.Data/DataLoadSave/Text/TextLoaderParser.cs

@@ -249,7 +249,7 @@ namespace Microsoft.ML.Data
             private readonly TryParseMapper<TResult> _conv;
 
             // Has length Rows.Count, so indexed by irow.
-            private TResult[] _values;
+            private readonly TResult[] _values;
 
             public override bool HasNA { get; }
 
@@ -436,7 +436,7 @@ namespace Microsoft.ML.Data
             }
 
             // Has length Rows.Count, so indexed by irow.
-            private VectorValue[] _values;
+            private readonly VectorValue[] _values;
 
             public VectorPipe(RowSet rows, PrimitiveDataViewType type, TryParseMapper<TItem> conv)
                 : base(rows)

src/Microsoft.ML.Data/DataLoadSave/Text/TextSaver.cs

@@ -221,7 +221,7 @@ namespace Microsoft.ML.Data.IO
         {
             private readonly ValueGetter<T> _getSrc;
             private T _src;
-            private string _columnName;
+            private readonly string _columnName;
 
             public ValueWriter(DataViewRowCursor cursor, PrimitiveDataViewType type, int source, char sep)
                 : base(type, source, sep)
@@ -535,8 +535,8 @@ namespace Microsoft.ML.Data.IO
             private int _dstPrev;
 
             // Map from column to starting destination index and slot.
-            private int[] _mpcoldst;
-            private int[] _mpcolslot;
+            private readonly int[] _mpcoldst;
+            private readonly int[] _mpcolslot;
 
             // "slot" is an index into _mpslotdst and _mpslotichLim. _mpslotdst is the sequence of
             // destination indices. _mpslotichLim is the sequence of upper bounds on the characters

src/Microsoft.ML.Data/DataView/CompositeRowToRowMapper.cs

@@ -89,7 +89,7 @@ namespace Microsoft.ML.Data
         private sealed class SubsetActive : DataViewRow
         {
             private readonly DataViewRow _row;
-            private Func<int, bool> _pred;
+            private readonly Func<int, bool> _pred;
 
             public SubsetActive(DataViewRow row, Func<int, bool> pred)
             {

src/Microsoft.ML.Data/DataView/DataViewConstructionUtils.cs

@@ -686,7 +686,7 @@ namespace Microsoft.ML.Data
         internal sealed class StreamingDataView<TRow> : DataViewBase<TRow>
             where TRow : class
         {
-            private IEnumerable<TRow> _data;
+            private readonly IEnumerable<TRow> _data;
 
             public StreamingDataView(IHostEnvironment env, IEnumerable<TRow> data, InternalSchemaDefinition schemaDefn)
                 : base(env, "StreamingDataView", schemaDefn)
@@ -936,7 +936,7 @@ namespace Microsoft.ML.Data
             if (AnnotationType is VectorDataViewType annotationVectorType)
             {
                 // VBuffer<T> -> VBuffer<T>
-                // REVIEW: Do we care about accomodating VBuffer<string> -> VBuffer<ReadOnlyMemory<char>>?
+                // REVIEW: Do we care about accommodating VBuffer<string> -> VBuffer<ReadOnlyMemory<char>>?
 
                 Contracts.Assert(typeT.IsGenericType);
                 Contracts.Check(typeof(TDst).IsGenericType);

src/Microsoft.ML.Data/Dirty/PredictionUtils.cs

@@ -58,7 +58,7 @@ namespace Microsoft.ML.Internal.Internallearn
             return CmdParser.CombineSettings(settings) + " " + CmdParser.CombineSettings(SplitOnSemis(extraSettings));
         }
 
-        private static char[] _dontSplitChars = new char[] { ' ', '=', '{', '}', '\t' };
+        private static readonly char[] _dontSplitChars = new char[] { ' ', '=', '{', '}', '\t' };
 
         // REVIEW: Deprecate this!
         public static string[] SplitOnSemis(string[] args)

src/Microsoft.ML.Data/EntryPoints/EntryPointNode.cs

@@ -427,7 +427,7 @@ namespace Microsoft.ML.EntryPoints
 
         public TimeSpan RunTime { get; internal set; }
 
-        private static Regex _stageIdRegex = new Regex(@"[a-zA-Z0-9]*", RegexOptions.Compiled);
+        private static readonly Regex _stageIdRegex = new Regex(@"[a-zA-Z0-9]*", RegexOptions.Compiled);
         private string _stageId;
         /// <summary>
         /// An alphanumeric string indicating the stage of a node.
@@ -1060,7 +1060,7 @@ namespace Microsoft.ML.EntryPoints
         // An EntryPoint variable can be followed with an array or dictionary specifier, which begins
         // with '[', contains either an integer or alphanumeric string, optionally wrapped in single-quotes,
         // followed with ']'.
-        private static Regex _variableRegex = new Regex(
+        private static readonly Regex _variableRegex = new Regex(
             @"\$(?<Name>[a-zA-Z_][a-zA-Z0-9_]*)(\[(((?<NumericAccessor>[0-9]*))|(\'?(?<StringAccessor>[a-zA-Z0-9_]*)\'?))\])?",
             RegexOptions.Compiled);
 
@@ -1193,7 +1193,7 @@ namespace Microsoft.ML.EntryPoints
 
     /// <summary>
     /// Represents the l-value assignable destination of a <see cref="VariableBinding"/>.
-    /// Subclasses exist to express the needed bindinds for subslots
+    /// Subclasses exist to express the needed bindings for subslots
     /// of a yet-to-be-constructed array or dictionary EntryPoint input parameter
     /// (for example, "myVar": ["$var1", "$var2"] would yield two <see cref="ArrayIndexParameterBinding"/>: (myVar, 0), (myVar, 1))
     /// </summary>

src/Microsoft.ML.Data/Evaluators/QuantileRegressionEvaluator.cs

@@ -210,7 +210,7 @@ namespace Microsoft.ML.Data
             private readonly Counters _counters;
             private readonly Counters _weightedCounters;
 
-            private VBuffer<ReadOnlyMemory<char>> _slotNames;
+            private readonly VBuffer<ReadOnlyMemory<char>> _slotNames;
 
             public override CountersBase UnweightedCounters { get { return _counters; } }
 

src/Microsoft.ML.Data/Prediction/Calibrator.cs

@@ -1069,8 +1069,8 @@ namespace Microsoft.ML.Calibrators
     {
         private readonly IHost _host;
 
-        private List<float> _cMargins;
-        private List<float> _ncMargins;
+        private readonly List<float> _cMargins;
+        private readonly List<float> _ncMargins;
 
         public int NumBins;
         public float BinSize;
@@ -1846,7 +1846,7 @@ namespace Microsoft.ML.Calibrators
     [BestFriend]
     internal sealed class PavCalibratorTrainer : CalibratorTrainerBase
     {
-        // a piece of the piecwise function
+        // a piece of the piecewise function
         private readonly struct Piece
         {
             public readonly float MinX; // end of interval.

src/Microsoft.ML.Data/Prediction/CalibratorCatalog.cs

@@ -69,7 +69,7 @@ namespace Microsoft.ML.Calibrators
                 LabelColumn = TrainerUtils.MakeBoolScalarLabel(labelColumn);
             else
                 env.CheckParam(!calibratorTrainer.NeedsTraining, nameof(labelColumn), "For trained calibrators, " + nameof(labelColumn) + " must be specified.");
-            ScoreColumn = TrainerUtils.MakeR4ScalarColumn(scoreColumn); // Do we fanthom this being named anything else (renaming column)? Complete metadata?
+            ScoreColumn = TrainerUtils.MakeR4ScalarColumn(scoreColumn); // Do we fathom this being named anything else (renaming column)? Complete metadata?
 
             if (weightColumn != null)
                 WeightColumn = TrainerUtils.MakeR4ScalarWeightColumn(weightColumn);
@@ -239,10 +239,10 @@ namespace Microsoft.ML.Calibrators
         private sealed class Mapper<TCalibrator> : MapperBase, ISaveAsOnnx
             where TCalibrator : class, ICalibrator
         {
-            private TCalibrator _calibrator;
+            private readonly TCalibrator _calibrator;
             private readonly int _scoreColIndex;
-            private CalibratorTransformer<TCalibrator> _parent;
-            private string _scoreColumnName;
+            private readonly CalibratorTransformer<TCalibrator> _parent;
+            private readonly string _scoreColumnName;
 
             bool ICanSaveOnnx.CanSaveOnnx(OnnxContext ctx) => _calibrator is ICanSaveOnnx onnxMapper ? onnxMapper.CanSaveOnnx(ctx) : false;
 
@@ -294,7 +294,7 @@ namespace Microsoft.ML.Calibrators
                     builder.Add(setIdCol.Name, setIdType, annotation.GetGetter<uint>(setIdCol));
                     // Now, this next one I'm a little less sure about. It is entirely reasonable for someone to, say,
                     // try to calibrate the result of a regression or ranker training, or something else. But should we
-                    // just pass through this class just like that? Having throught through the alternatives I view this
+                    // just pass through this class just like that? Having thought through the alternatives I view this
                     // as the least harmful thing we could be doing, but it is something to consider I may be wrong
                     // about if it proves that it ever causes problems to, say, have something identified as a probability
                     // column but be marked as being a regression task, or what have you.
@@ -415,7 +415,7 @@ namespace Microsoft.ML.Calibrators
     }
 
     /// <summary>
-    /// The naive binning-based calbirator estimator.
+    /// The naive binning-based calibrator estimator.
     /// </summary>
     /// <remarks>
     /// It divides the range of the outputs into equally sized bins. In each bin,

src/Microsoft.ML.Data/Scorers/FeatureContributionCalculation.cs

@@ -299,7 +299,7 @@ namespace Microsoft.ML.Data
             private readonly BindableMapper _parent;
             private readonly DataViewSchema _outputSchema;
             private readonly DataViewSchema _outputGenericSchema;
-            private VBuffer<ReadOnlyMemory<char>> _slotNames;
+            private readonly VBuffer<ReadOnlyMemory<char>> _slotNames;
 
             public RoleMappedSchema InputRoleMappedSchema { get; }
 

src/Microsoft.ML.Data/Transforms/ColumnSelecting.cs

@@ -90,7 +90,7 @@ namespace Microsoft.ML.Transforms
         /// <param name="keepHidden">If true will keep hidden columns and false will remove hidden columns. The argument is
         /// ignored if the Estimator is in "drop mode".</param>
         /// <param name="ignoreMissing">If false will check for any columns given in <paramref name="keepColumns"/>
-        ///     or <paramref name="dropColumns"/> that are missing from the input. If a missing colums exists a
+        ///     or <paramref name="dropColumns"/> that are missing from the input. If a missing column exists a
         ///     SchemaMistmatch exception is thrown. If true, the check is not made.</param>
         internal ColumnSelectingEstimator(IHostEnvironment env, string[] keepColumns,
                                     string[] dropColumns, bool keepHidden = Defaults.KeepHidden,
@@ -160,7 +160,7 @@ namespace Microsoft.ML.Transforms
         internal const string ChooseLoaderSignatureOld = "ChooseColumnsFunction";
 
         private readonly IHost _host;
-        private string[] _selectedColumns;
+        private readonly string[] _selectedColumns;
 
         bool ITransformer.IsRowToRowMapper => true;
 
@@ -697,7 +697,7 @@ namespace Microsoft.ML.Transforms
                 var inputCols = ((IRowToRowMapper)this).GetDependencies(columnsNeeded);
                 var inputs = Source.GetRowCursorSet(inputCols, n, rand);
 
-                // Build out the acitve state for the output
+                // Build out the active state for the output
                 var active = Utils.BuildArray(_mapper.OutputSchema.Count, columnsNeeded);
                 _host.AssertNonEmpty(inputs);
 

src/Microsoft.ML.Data/Transforms/NormalizeColumnDbl.cs

@@ -1830,7 +1830,7 @@ namespace Microsoft.ML.Transforms
             {
                 private readonly bool _fix;
                 private readonly int _numBins;
-                private List<TFloat> _values;
+                private readonly List<TFloat> _values;
 
                 private BinOneColumnFunctionBuilder(IHost host, long lim, bool fix, int numBins, ValueGetter<TFloat> getSrc)
                     : base(host, lim, getSrc)
@@ -1874,7 +1874,7 @@ namespace Microsoft.ML.Transforms
             {
                 private readonly bool _fix;
                 private readonly int _numBins;
-                private List<TFloat>[] _values;
+                private readonly List<TFloat>[] _values;
 
                 private BinVecColumnFunctionBuilder(IHost host, int cv, long lim, bool fix, int numBins,
                     ValueGetter<VBuffer<TFloat>> getSrc)
@@ -2097,7 +2097,7 @@ namespace Microsoft.ML.Transforms
                     // The difference is how the min/max are used.
                     _minMaxAggregator = new MinMaxDblAggregator(vectorSize);
 
-                    // If we aren't centering data dont need the median.
+                    // If we aren't centering data don't need the median.
                     _medianAggregators = new MedianDblAggregator[vectorSize];
 
                     for (int i = 0; i < vectorSize; i++)

src/Microsoft.ML.Data/Transforms/NormalizeColumnSng.cs

@@ -1993,7 +1993,7 @@ namespace Microsoft.ML.Transforms
             {
                 private readonly bool _fix;
                 private readonly int _numBins;
-                private List<TFloat> _values;
+                private readonly List<TFloat> _values;
 
                 private BinOneColumnFunctionBuilder(IHost host, long lim, bool fix, int numBins, ValueGetter<TFloat> getSrc)
                     : base(host, lim, getSrc)
@@ -2037,7 +2037,7 @@ namespace Microsoft.ML.Transforms
             {
                 private readonly bool _fix;
                 private readonly int _numBins;
-                private List<TFloat>[] _values;
+                private readonly List<TFloat>[] _values;
 
                 private BinVecColumnFunctionBuilder(IHost host, int cv, long lim, bool fix, int numBins,
                     ValueGetter<VBuffer<TFloat>> getSrc)

src/Microsoft.ML.Data/Transforms/Normalizer.cs

@@ -714,7 +714,7 @@ namespace Microsoft.ML.Transforms
 
         private sealed class Mapper : OneToOneMapperBase, ISaveAsOnnx, ISaveAsPfa
         {
-            private NormalizingTransformer _parent;
+            private readonly NormalizingTransformer _parent;
 
             public bool CanSaveOnnx(OnnxContext ctx) => true;
             public bool CanSavePfa => true;

src/Microsoft.ML.Data/Transforms/ValueMapping.cs

@@ -186,7 +186,7 @@ namespace Microsoft.ML.Transforms
     internal class DataViewHelper
     {
         /// <summary>
-        /// Helper function to retrieve the Primitie type given a Type
+        /// Helper function to retrieve the Primitive type given a Type
         /// </summary>
         internal static PrimitiveDataViewType GetPrimitiveType(Type rawType, out bool isVectorType)
         {
@@ -359,7 +359,7 @@ namespace Microsoft.ML.Transforms
         private const string DefaultMapName = "DefaultMap.idv";
         internal static string DefaultKeyColumnName = "Key";
         internal static string DefaultValueColumnName = "Value";
-        private ValueMap _valueMap;
+        private readonly ValueMap _valueMap;
         private readonly byte[] _dataView;
 
         internal DataViewType ValueColumnType => _valueMap.ValueColumn.Type;
@@ -834,7 +834,7 @@ namespace Microsoft.ML.Transforms
             private static readonly FuncStaticMethodInfo1<TValue, TValue> _getValueMethodInfo
                 = new FuncStaticMethodInfo1<TValue, TValue>(GetValue<int>);
 
-            private Dictionary<TKey, TValue> _mapping;
+            private readonly Dictionary<TKey, TValue> _mapping;
             private TValue _missingValue;
 
             private Dictionary<TKey, TValue> CreateDictionary()

src/Microsoft.ML.Ensemble/OutputCombiners/WeightedAverage.cs

@@ -46,7 +46,7 @@ namespace Microsoft.ML.Trainers.Ensemble
             public IBinaryOutputCombiner CreateComponent(IHostEnvironment env) => new WeightedAverage(env, this);
         }
 
-        private WeightageKind _weightageKind;
+        private readonly WeightageKind _weightageKind;
 
         public string WeightageMetricName { get { return _weightageKind.ToString(); } }
 

src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BaseDiverseSelector.cs

@@ -19,7 +19,7 @@ namespace Microsoft.ML.Trainers.Ensemble
         }
 
         private readonly IComponentFactory<IDiversityMeasure<TOutput>> _diversityMetricType;
-        private ConcurrentDictionary<FeatureSubsetModel<TOutput>, TOutput[]> _predictions;
+        private readonly ConcurrentDictionary<FeatureSubsetModel<TOutput>, TOutput[]> _predictions;
 
         private protected BaseDiverseSelector(IHostEnvironment env, DiverseSelectorArguments args, string name,
             IComponentFactory<IDiversityMeasure<TOutput>> diversityMetricType)

src/Microsoft.ML.FastTree/Dataset/Dataset.cs

@@ -420,12 +420,12 @@ namespace Microsoft.ML.Trainers.FastTree
         /// </summary>
         public sealed class DatasetSkeleton
         {
-            private short[] _ratings;
+            private readonly short[] _ratings;
             public readonly int[] Boundaries;
             public readonly ulong[] QueryIds;
             public readonly ulong[] DocIds;
             public double[][] MaxDcg;
-            private int[] _docToQuery;
+            private readonly int[] _docToQuery;
 
             public Dictionary<string, DatasetSkeletonQueryDocData> AuxiliaryData { get; set; }
 

src/Microsoft.ML.FastTree/Dataset/DenseIntArray.cs

@@ -205,7 +205,7 @@ namespace Microsoft.ML.Trainers.FastTree
     {
         private const int _bits = 10;
         private const int _mask = (1 << _bits) - 1;
-        private uint[] _data;
+        private readonly uint[] _data;
 
         public override IntArrayBits BitsPerItem { get { return IntArrayBits.Bits10; } }
 
@@ -381,7 +381,7 @@ namespace Microsoft.ML.Trainers.FastTree
     /// 0-bit array only represents the value -1</remarks>
     internal sealed class Dense8BitIntArray : DenseDataCallbackIntArray
     {
-        private byte[] _data;
+        private readonly byte[] _data;
 
         public override IntArrayBits BitsPerItem { get { return IntArrayBits.Bits8; } }
 
@@ -468,7 +468,7 @@ namespace Microsoft.ML.Trainers.FastTree
         /// <summary>
         /// For a given byte, the high 4 bits is the first value, the low 4 bits is the next value.
         /// </summary>
-        private byte[] _data;
+        private readonly byte[] _data;
 
         public override IntArrayBits BitsPerItem { get { return IntArrayBits.Bits4; } }
 
@@ -588,7 +588,7 @@ namespace Microsoft.ML.Trainers.FastTree
     /// </summary>
     internal sealed class Dense16BitIntArray : DenseDataCallbackIntArray
     {
-        private ushort[] _data;
+        private readonly ushort[] _data;
 
         public override IntArrayBits BitsPerItem { get { return IntArrayBits.Bits16; } }
 
@@ -677,7 +677,7 @@ namespace Microsoft.ML.Trainers.FastTree
     /// </summary>
     internal sealed class Dense32BitIntArray : DenseDataCallbackIntArray
     {
-        private int[] _data;
+        private readonly int[] _data;
 
         public override IntArrayBits BitsPerItem { get { return IntArrayBits.Bits32; } }
 

src/Microsoft.ML.FastTree/Dataset/RepeatIntArray.cs

@@ -19,7 +19,7 @@ namespace Microsoft.ML.Trainers.FastTree
     {
         private readonly DenseIntArray _values;
         private readonly int _length;
-        private byte[] _deltas;
+        private readonly byte[] _deltas;
         private readonly int _deltasActualLength;
 
         public DeltaRepeatIntArray(int length, IntArrayBits bitsPerItem, IEnumerable<int> values)

src/Microsoft.ML.FastTree/FastTree.cs

@@ -2616,7 +2616,7 @@ namespace Microsoft.ML.Trainers.FastTree
 #if DEBUG
                 // Holds for each feature the row index that it was previously accessed on.
                 // Purely for validation purposes.
-                private int[] _lastRow;
+                private readonly int[] _lastRow;
 #endif
 
                 /// <summary>

src/Microsoft.ML.FastTree/FastTreeClassification.cs

@@ -140,7 +140,7 @@ namespace Microsoft.ML.Trainers.FastTree
         internal const string ShortName = "ftc";
 
         private bool[] _trainSetLabels;
-        private double _sigmoidParameter;
+        private readonly double _sigmoidParameter;
 
         /// <summary>
         /// Initializes a new instance of <see cref="FastTreeBinaryTrainer"/>
@@ -325,7 +325,7 @@ namespace Microsoft.ML.Trainers.FastTree
             private readonly bool _unbalancedSets; //Should we use balanced or unbalanced loss function
             private readonly long _npos;
             private readonly long _nneg;
-            private IParallelTraining _parallelTraining;
+            private readonly IParallelTraining _parallelTraining;
             private readonly double _sigmoidParameter; // Parameter for scaling the loss
 
             public ObjectiveImpl(

src/Microsoft.ML.FastTree/FastTreeRanking.cs

@@ -88,7 +88,7 @@ namespace Microsoft.ML.Trainers.FastTree
         /// <param name="labelColumnName">The name of the label column.</param>
         /// <param name="featureColumnName">The name of the feature column.</param>
         /// <param name="rowGroupColumnName">The name for the column containing the group ID. </param>
-        /// <param name="exampleWeightColumnName">The name for the column containing the examle weight.</param>
+        /// <param name="exampleWeightColumnName">The name for the column containing the example weight.</param>
         /// <param name="numberOfLeaves">The max number of leaves in each regression tree.</param>
         /// <param name="numberOfTrees">Total number of decision trees to create in the ensemble.</param>
         /// <param name="minimumExampleCountPerLeaf">The minimal number of examples allowed in a leaf of a regression tree, out of the subsampled data.</param>
@@ -266,7 +266,7 @@ namespace Microsoft.ML.Trainers.FastTree
             {
                 if (!FastTreeTrainerOptions.UseTolerantPruning)
                 {
-                    //use simple eraly stopping condition
+                    //use simple early stopping condition
                     PruningTest = new TestHistory(ValidTest, 0);
                 }
                 else
@@ -363,7 +363,7 @@ namespace Microsoft.ML.Trainers.FastTree
 
             // We only print non-zero train&valid graph if earlyStoppingTruncation!=0
             // In case /es is not set, we print 0 for train and valid graph NDCG
-            // Let's keeping this behaviour for backward compatibility with previous FR version
+            // Let's keeping this behavior for backward compatibility with previous FR version
             // Ideally /graphtv should enforce non-zero /es in the commandline validation
             if (_specialTrainSetTest != null)
             {
@@ -385,7 +385,7 @@ namespace Microsoft.ML.Trainers.FastTree
             base.Train(ch);
             // Print final last iteration.
             // Note that trainNDCG printed in graph will be from copy of a value from previous iteration
-            // and will diffre slightly from the proper final value computed by FullTest.
+            // and will differ slightly from the proper final value computed by FullTest.
             // We cannot compute the final NDCG here due to the fact we use FastNDCGTestForTrainSet computing NDCG based on label sort saved during gradient computation (and we don;t have gradients for n+1 iteration)
             // Keeping it in sync with original FR code
             PrintTestGraph(ch);
@@ -507,19 +507,19 @@ namespace Microsoft.ML.Trainers.FastTree
             private readonly double[] _discount;
             private readonly int[] _oneTwoThree;
 
-            private int[][] _labelCounts;
+            private readonly int[][] _labelCounts;
 
             // reusable memory, technical stuff
-            private int[][] _permutationBuffers;
-            private DcgPermutationComparer[] _comparers;
+            private readonly int[][] _permutationBuffers;
+            private readonly DcgPermutationComparer[] _comparers;
 
             //gains
-            private double[] _gain;
+            private readonly double[] _gain;
             private double[] _gainLabels;
 
             // parameters
-            private int _maxDcgTruncationLevel;
-            private bool _useDcg;
+            private readonly int _maxDcgTruncationLevel;
+            private readonly bool _useDcg;
             // A lookup table for the sigmoid used in the lambda calculation
             // Note: Is built for a specific sigmoid parameter, so assumes this will be constant throughout computation
             private double[] _sigmoidTable;
@@ -533,9 +533,9 @@ namespace Microsoft.ML.Trainers.FastTree
 
             // Secondary gains, currently not used in any way.
 #pragma warning disable 0649
-            private double _secondaryMetricShare;
-            private double[] _secondaryInverseMaxDcgt;
-            private double[] _secondaryGains;
+            private readonly double _secondaryMetricShare;
+            private readonly double[] _secondaryInverseMaxDcgt;
+            private readonly double[] _secondaryGains;
 #pragma warning restore 0649
 
             // Baseline risk.
@@ -546,19 +546,19 @@ namespace Microsoft.ML.Trainers.FastTree
             // 1. preprocessing the scores for continuous cost function
             // 2. shifted NDCG
             // 3. max DCG per query
-            private double[] _scoresCopy;
-            private short[] _labelsCopy;
-            private short[] _groupIdToTopLabel;
+            private readonly double[] _scoresCopy;
+            private readonly short[] _labelsCopy;
+            private readonly short[] _groupIdToTopLabel;
 
             // parameters
-            private double _sigmoidParam;
-            private char _costFunctionParam;
-            private bool _filterZeroLambdas;
+            private readonly double _sigmoidParam;
+            private readonly char _costFunctionParam;
+            private readonly bool _filterZeroLambdas;
 
-            private bool _distanceWeight2;
-            private bool _normalizeQueryLambdas;
-            private bool _useShiftedNdcg;
-            private IParallelTraining _parallelTraining;
+            private readonly bool _distanceWeight2;
+            private readonly bool _normalizeQueryLambdas;
+            private readonly bool _useShiftedNdcg;
+            private readonly IParallelTraining _parallelTraining;
 
             // Used for training NDCG calculation
             // Keeps track of labels of top 3 documents per query

src/Microsoft.ML.FastTree/GamTrainer.cs

@@ -204,7 +204,7 @@ namespace Microsoft.ML.Trainers.FastTree
             Host.CheckParam(options.NumberOfThreads == null || options.NumberOfThreads > 0, nameof(options.NumberOfThreads), "Must be positive.");
             Host.CheckParam(0 <= options.EntropyCoefficient && options.EntropyCoefficient <= 1, nameof(options.EntropyCoefficient), "Must be in [0, 1].");
             Host.CheckParam(0 <= options.GainConfidenceLevel && options.GainConfidenceLevel < 1, nameof(options.GainConfidenceLevel), "Must be in [0, 1).");
-            Host.CheckParam(0 < options.MaximumBinCountPerFeature, nameof(options.MaximumBinCountPerFeature), "Must be posittive.");
+            Host.CheckParam(0 < options.MaximumBinCountPerFeature, nameof(options.MaximumBinCountPerFeature), "Must be positive.");
             Host.CheckParam(0 < options.NumberOfIterations, nameof(options.NumberOfIterations), "Must be positive.");
             Host.CheckParam(0 < options.MinimumExampleCountPerLeaf, nameof(options.MinimumExampleCountPerLeaf), "Must be positive.");
 
@@ -608,7 +608,7 @@ namespace Microsoft.ML.Trainers.FastTree
 
         private class LeafSplitHelper : ILeafSplitStatisticsCalculator
         {
-            private bool _hasWeights;
+            private readonly bool _hasWeights;
 
             public LeafSplitHelper(bool hasWeights)
             {

src/Microsoft.ML.FastTree/Training/DcgCalculator.cs

@@ -18,15 +18,15 @@ namespace Microsoft.ML.Trainers.FastTree
         private readonly int[] _oneTwoThree;
 
         // reusable memory
-        private int[][] _permutationBuffers;
-        private double[][] _scoreBuffers;
-        private DcgPermutationComparer[] _comparers;
+        private readonly int[][] _permutationBuffers;
+        private readonly double[][] _scoreBuffers;
+        private readonly DcgPermutationComparer[] _comparers;
 
         /// <summary>
         /// Contains the instances for a second Level comparer, which gets applied after the initial rank
         /// based ordering has happened. The array stores one second level comparer per thread.
         /// </summary>
-        private DescendingStableIdealComparer[] _secondLevelcomparers;
+        private readonly DescendingStableIdealComparer[] _secondLevelcomparers;
 
         private double _result;
 

src/Microsoft.ML.FastTree/Training/DocumentPartitioning.cs

@@ -22,7 +22,7 @@ namespace Microsoft.ML.Trainers.FastTree
         private readonly int[] _leafCount;
         private readonly int[] _documents;
         private int[] _tempDocuments;
-        private int[] _initialDocuments;
+        private readonly int[] _initialDocuments;
 
         /// <summary>
         /// Constructor

src/Microsoft.ML.FastTree/Training/EnsembleCompression/LassoFit.cs

@@ -33,7 +33,7 @@ namespace Microsoft.ML.Trainers.FastTree
         // Total number of passes over data
         public int NumberOfPasses;
 
-        private int _numFeatures;
+        private readonly int _numFeatures;
 
         public LassoFit(int numberOfLambdas, int maxAllowedFeaturesAlongPath, int numFeatures)
         {

src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/GradientDescent.cs

@@ -11,14 +11,14 @@ namespace Microsoft.ML.Trainers.FastTree
 {
     internal class GradientDescent : OptimizationAlgorithm
     {
-        private IGradientAdjuster _gradientWrapper;
+        private readonly IGradientAdjuster _gradientWrapper;
 
         /// number of trees dropped in this iteration
         private int _numberOfDroppedTrees;
         // treeScores stores for every tree the predictions it makes on every training example. This is used
         // to eliminate the need for computing the scores when we drop trees. However, it causes a horrifying
         // memory drain.
-        private List<double[]> _treeScores;
+        private readonly List<double[]> _treeScores;
         private double[] _droppedScores;
         private double[] _scores;
 

src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/NoOptimizationAlgorithm.cs

@@ -11,8 +11,8 @@ namespace Microsoft.ML.Trainers.FastTree
     /// </summary>
     internal class RandomForestOptimizer : GradientDescent
     {
-        private IGradientAdjuster _gradientWrapper;
-        // REVIEW: When the FastTree appliation is decoupled with tree learner and boosting logic, this class should be removed.
+        private readonly IGradientAdjuster _gradientWrapper;
+        // REVIEW: When the FastTree application is decoupled with tree learner and boosting logic, this class should be removed.
         internal RandomForestOptimizer(InternalTreeEnsemble ensemble, Dataset trainData, double[] initTrainScores, IGradientAdjuster gradientWrapper)
             : base(ensemble, trainData, initTrainScores, gradientWrapper)
         {

src/Microsoft.ML.FastTree/Training/ScoreTracker.cs

@@ -135,13 +135,13 @@ namespace Microsoft.ML.Trainers.FastTree
             throw Contracts.ExceptNotSupp("This code should not be reachable");
         }
 
-        //Computes AGD specific mutiplier. Given that we have tree number t in ensemble (we count trees starting from 0)
+        //Computes AGD specific multiplier. Given that we have tree number t in ensemble (we count trees starting from 0)
         //And we have total k trees in ensemble, what should be the multiplier on the tree when sum the ensemble together based on AGD formula being
         //X[k+1] = Y[k] + Tree[k]
         //Y[k+1] = X[k+1] + C[k] * (X[k+1] – X[k])
         //C[k] = (k-1) / (k+2)
 
-        private static Dictionary<int, Dictionary<int, double>> _treeMultiplierMap = new Dictionary<int, Dictionary<int, double>>();
+        private static readonly Dictionary<int, Dictionary<int, double>> _treeMultiplierMap = new Dictionary<int, Dictionary<int, double>>();
         public static double TreeMultiplier(int t, int k)
         {
             if (_treeMultiplierMap.ContainsKey(t))

src/Microsoft.ML.FastTree/Training/StepSearch.cs

@@ -16,8 +16,8 @@ namespace Microsoft.ML.Trainers.FastTree
     internal sealed class LineSearch : IStepSearch, IFastTrainingScoresUpdate
     {
         private double _historicStepSize;
-        private int _numPostbracketSteps;
-        private double _minStepSize;
+        private readonly int _numPostbracketSteps;
+        private readonly double _minStepSize;
 
         public LineSearch(Test lossCalculator, int lossIndex, int numPostbracketSteps, double minStepSize)
             : this(lossCalculator, lossIndex) { _numPostbracketSteps = numPostbracketSteps; _minStepSize = minStepSize; }

src/Microsoft.ML.FastTree/Training/Test.cs

@@ -273,11 +273,11 @@ namespace Microsoft.ML.Trainers.FastTree
         private readonly int _windowSize;
         private readonly double _tolerance;
         // Queue for moving window
-        private LinkedList<double> _window;
+        private readonly LinkedList<double> _window;
 
         // This queue keeps track of the iterations which are within tolerance from the best iteration
         // The first element of the queue is the early stopping candidate
-        private LinkedList<ValueIterationPair> _toleratedQueue;
+        private readonly LinkedList<ValueIterationPair> _toleratedQueue;
 
         // Average validation for the current window
         private double _currentWindowSum;

src/Microsoft.ML.FastTree/Training/TreeLearners/FastForestLeastSquaresTreeLearner.cs

@@ -9,8 +9,8 @@ namespace Microsoft.ML.Trainers.FastTree
 {
     internal class RandomForestLeastSquaresTreeLearner : LeastSquaresRegressionTreeLearner
     {
-        private int _quantileSampleCount;
-        private bool _quantileEnabled;
+        private readonly int _quantileSampleCount;
+        private readonly bool _quantileEnabled;
 
         public RandomForestLeastSquaresTreeLearner(Dataset trainData, int numLeaves, int minDocsInLeaf, Double entropyCoefficient, Double featureFirstUsePenalty,
             Double featureReusePenalty, Double softmaxTemperature, int histogramPoolSize, int randomSeed, Double splitFraction, bool allowEmptyTrees,

src/Microsoft.ML.FastTree/Training/TreeLearners/LeastSquaresRegressionTreeLearner.cs

@@ -39,7 +39,7 @@ namespace Microsoft.ML.Trainers.FastTree
         public readonly double Bias;
 
         // Multithread task to find best threshold.
-        private IThreadTask _calculateLeafSplitCandidates;
+        private readonly IThreadTask _calculateLeafSplitCandidates;
 
         protected SplitInfo[] BestSplitInfoPerLeaf;
         protected HashSet<int> CategoricalThresholds;
@@ -74,7 +74,7 @@ namespace Microsoft.ML.Trainers.FastTree
         // size of reserved memory
         private readonly long _sizeOfReservedMemory;
 
-        private IParallelTraining _parallelTraining;
+        private readonly IParallelTraining _parallelTraining;
 
         public int MaxCategoricalGroupsPerNode { get; }
 
@@ -828,7 +828,7 @@ namespace Microsoft.ML.Trainers.FastTree
             private double _sumWeights;
             private double _sumSquaredTargets;
             private int[] _docIndices;
-            private int[] _docIndicesCopy;
+            private readonly int[] _docIndicesCopy;
             public readonly FloatType[] Targets;
             public readonly double[] Weights;
             public readonly SplitInfo[] FeatureSplitInfo;

src/Microsoft.ML.FastTree/TreeEnsemble/InternalRegressionTree.cs

@@ -23,12 +23,12 @@ namespace Microsoft.ML.Trainers.FastTree
     internal class InternalRegressionTree
     {
         private double _maxOutput;
-        private double[] _splitGain;
-        private double[] _gainPValue;
+        private readonly double[] _splitGain;
+        private readonly double[] _gainPValue;
         /// <summary>
         /// The value of this non-leaf node, prior to split when it was a leaf.
         /// </summary>
-        private double[] _previousLeafValue;
+        private readonly double[] _previousLeafValue;
 
         // for each non-leaf, we keep the following data
         public float[] DefaultValueForMissing;
@@ -820,7 +820,7 @@ namespace Microsoft.ML.Trainers.FastTree
 
         private float GetFeatureValue(float x, int node)
         {
-            // Not need to convert missing vaules.
+            // Not need to convert missing values.
             if (DefaultValueForMissing == null)
                 return x;
 

src/Microsoft.ML.FastTree/TreeEnsembleFeaturizationEstimator.cs

@@ -190,7 +190,7 @@ namespace Microsoft.ML.Trainers.FastTree
             public TreeEnsembleModelParameters ModelParameters;
         };
 
-        private TreeEnsembleModelParameters _modelParameters;
+        private readonly TreeEnsembleModelParameters _modelParameters;
 
         internal PretrainedTreeFeaturizationEstimator(IHostEnvironment env, Options options) : base(env, options)
         {

src/Microsoft.ML.FastTree/TreeEnsembleFeaturizer.cs

@@ -84,14 +84,14 @@ namespace Microsoft.ML.Data
             /// and the i-th vector element is the prediction value predicted by the i-th tree.
             /// If <see cref="_treesColumnName"/> is <see langword="null"/>, this output column may not be generated.
             /// </summary>
-            private string _treesColumnName;
+            private readonly string _treesColumnName;
 
             /// <summary>
             /// The 0-1 encoding of all leaf nodes' IDs. Its type is a vector of <see cref="System.Single"/>. If the given feature
             /// vector falls into the first leaf of the first tree, the first element in the 0-1 encoding would be 1.
             /// If <see cref="_leavesColumnName"/> is <see langword="null"/>, this output column may not be generated.
             /// </summary>
-            private string _leavesColumnName;
+            private readonly string _leavesColumnName;
 
             /// <summary>
             /// The 0-1 encoding of the paths to the leaves. If the path to the first tree's leaf is node 1 (2nd node in the first tree),
@@ -99,7 +99,7 @@ namespace Microsoft.ML.Data
             /// would be 1.
             /// If <see cref="_pathsColumnName"/> is <see langword="null"/>, this output column may not be generated.
             /// </summary>
-            private string _pathsColumnName;
+            private readonly string _pathsColumnName;
 
             public BoundMapper(IExceptionContext ectx, TreeEnsembleFeaturizerBindableMapper owner, RoleMappedSchema schema,
                 string treesColumnName, string leavesColumnName, string pathsColumnName)
@@ -230,7 +230,7 @@ namespace Microsoft.ML.Data
                 private readonly int _numLeaves;
 
                 private VBuffer<float> _src;
-                private ValueGetter<VBuffer<float>> _featureGetter;
+                private readonly ValueGetter<VBuffer<float>> _featureGetter;
                 private long _cachedPosition;
                 private readonly int[] _leafIds;
                 private readonly List<int>[] _pathIds;

src/Microsoft.ML.FastTree/Utils/BufferPoolManager.cs

@@ -27,7 +27,7 @@ namespace Microsoft.ML.Trainers.FastTree
         /// <summary>
         /// A dictionary containing all buffer pool types
         /// </summary>
-        private static ConcurrentDictionary<Type, SortedList<int, List<Array>>> _bufferPools = new ConcurrentDictionary<Type, SortedList<int, List<Array>>>();
+        private static readonly ConcurrentDictionary<Type, SortedList<int, List<Array>>> _bufferPools = new ConcurrentDictionary<Type, SortedList<int, List<Array>>>();
 
         /// <summary>
         /// Gets a buffer from the pool with at least the same size as passed as input parameter

src/Microsoft.ML.FastTree/Utils/MappedObjectPool.cs

@@ -12,10 +12,10 @@ namespace Microsoft.ML.Trainers.FastTree
     /// </summary>
     internal class MappedObjectPool<T> where T : class
     {
-        private T[] _pool;
-        private int[] _map;
-        private int[] _inverseMap;
-        private int[] _lastAccessTime;
+        private readonly T[] _pool;
+        private readonly int[] _map;
+        private readonly int[] _inverseMap;
+        private readonly int[] _lastAccessTime;
         private int _time;
 
         /// <summary>

src/Microsoft.ML.FastTree/Utils/ThreadTaskManager.cs

@@ -12,7 +12,7 @@ namespace Microsoft.ML.Trainers.FastTree
 {
     internal static class ThreadTaskManager
     {
-        private static object _lockObject = new object();
+        private static readonly object _lockObject = new object();
 
         // REVIEW: Should this bother with number of threads? What should it do?
         public static int NumThreads { get; private set; }

src/Microsoft.ML.Featurizers/Common.cs

@@ -1,4 +1,8 @@
-using System;
+// 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 System;
 using System.Collections.Generic;
 using System.Diagnostics;
 using System.Runtime.InteropServices;
@@ -117,7 +121,7 @@ namespace Microsoft.ML.Featurizers
     internal delegate bool DestroyTransformedDataNative(IntPtr output, out IntPtr errorHandle);
     internal class TransformedDataSafeHandle : SafeHandleZeroOrMinusOneIsInvalid
     {
-        private DestroyTransformedDataNative _destroySaveDataHandler;
+        private readonly DestroyTransformedDataNative _destroySaveDataHandler;
 
         public TransformedDataSafeHandle(IntPtr handle, DestroyTransformedDataNative destroyCppTransformerEstimator) : base(true)
         {
@@ -137,7 +141,7 @@ namespace Microsoft.ML.Featurizers
     internal delegate bool DestroyNativeTransformerEstimator(IntPtr estimator, out IntPtr errorHandle);
     internal class TransformerEstimatorSafeHandle : SafeHandleZeroOrMinusOneIsInvalid
     {
-        private DestroyNativeTransformerEstimator _destroyNativeTransformerEstimator;
+        private readonly DestroyNativeTransformerEstimator _destroyNativeTransformerEstimator;
         public TransformerEstimatorSafeHandle(IntPtr handle, DestroyNativeTransformerEstimator destroyNativeTransformerEstimator) : base(true)
         {
             SetHandle(handle);
@@ -169,7 +173,7 @@ namespace Microsoft.ML.Featurizers
 
         protected override bool ReleaseHandle()
         {
-            // Not sure what to do with error stuff here.  There shoudln't ever be one though.
+            // Not sure what to do with error stuff here.  There shouldn't ever be one though.
             return DestroyTransformerSaveDataNative(handle, _dataSize, out _);
         }
     }

src/Microsoft.ML.Featurizers/DateTimeTransformer.cs

@@ -245,8 +245,8 @@ namespace Microsoft.ML.Featurizers
         internal const string ShortName = "DateTimeTransform";
         internal const string LoadName = "DateTimeTransform";
         internal const string LoaderSignature = "DateTimeTransform";
-        private LongTypedColumn _column;
-        private DataViewSchema _schema;
+        private readonly LongTypedColumn _column;
+        private readonly DataViewSchema _schema;
 
         #endregion
 
@@ -554,7 +554,7 @@ namespace Microsoft.ML.Featurizers
 
             internal abstract void CreateTransformerFromEstimator(DateTimeEstimator.HolidayList country);
             private protected abstract unsafe void CreateTransformerFromSavedDataHelper(byte* rawData, IntPtr dataSize);
-            private protected unsafe abstract bool CreateEstimatorHelper(byte* countryName, byte* dataRootDir, out IntPtr estimator, out IntPtr errorHandle);
+            private protected abstract unsafe bool CreateEstimatorHelper(byte* countryName, byte* dataRootDir, out IntPtr estimator, out IntPtr errorHandle);
             private protected abstract bool CreateTransformerFromEstimatorHelper(TransformerEstimatorSafeHandle estimator, out IntPtr transformer, out IntPtr errorHandle);
             private protected abstract bool DestroyEstimatorHelper(IntPtr estimator, out IntPtr errorHandle);
             private protected abstract bool DestroyTransformerHelper(IntPtr transformer, out IntPtr errorHandle);
@@ -668,7 +668,7 @@ namespace Microsoft.ML.Featurizers
             }
 
             [DllImport("Featurizers", EntryPoint = "DateTimeFeaturizer_CreateEstimator"), SuppressUnmanagedCodeSecurity]
-            private static unsafe extern bool CreateEstimatorNative(byte* countryName, byte* dataRootDir, out IntPtr estimator, out IntPtr errorHandle);
+            private static extern unsafe bool CreateEstimatorNative(byte* countryName, byte* dataRootDir, out IntPtr estimator, out IntPtr errorHandle);
 
             [DllImport("Featurizers", EntryPoint = "DateTimeFeaturizer_DestroyEstimator"), SuppressUnmanagedCodeSecurity]
             private static extern bool DestroyEstimatorNative(IntPtr estimator, out IntPtr errorHandle); // Should ONLY be called by safe handle
@@ -683,7 +683,7 @@ namespace Microsoft.ML.Featurizers
             }
 
             [DllImport("Featurizers", EntryPoint = "DateTimeFeaturizer_CreateTransformerFromSavedDataWithDataRoot"), SuppressUnmanagedCodeSecurity]
-            private static unsafe extern bool CreateTransformerFromSavedDataNative(byte* rawData, IntPtr bufferSize, byte* dataRootDir, out IntPtr transformer, out IntPtr errorHandle);
+            private static extern unsafe bool CreateTransformerFromSavedDataNative(byte* rawData, IntPtr bufferSize, byte* dataRootDir, out IntPtr transformer, out IntPtr errorHandle);
             private protected override unsafe void CreateTransformerFromSavedDataHelper(byte* rawData, IntPtr dataSize)
             {
                 byte[] dataRoot;
@@ -748,7 +748,7 @@ namespace Microsoft.ML.Featurizers
                     _transformerHandler.Dispose();
             }
 
-            private protected unsafe override bool CreateEstimatorHelper(byte* countryName, byte* dataRootDir, out IntPtr estimator, out IntPtr errorHandle) =>
+            private protected override unsafe bool CreateEstimatorHelper(byte* countryName, byte* dataRootDir, out IntPtr estimator, out IntPtr errorHandle) =>
                 CreateEstimatorNative(countryName, dataRootDir, out estimator, out errorHandle);
 
             private protected override bool CreateTransformerFromEstimatorHelper(TransformerEstimatorSafeHandle estimator, out IntPtr transformer, out IntPtr errorHandle) =>

src/Microsoft.ML.Featurizers/TimeSeriesImputer.cs

@@ -1,4 +1,8 @@
-using System;
+// 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 System;
 using System.Collections.Generic;
 using System.Diagnostics;
 using System.IO;
@@ -84,7 +88,7 @@ namespace Microsoft.ML.Featurizers
     /// boolean value representing if the row was created as a result of this operation or not.
     ///
     /// The imputation strategies that are currently supported are ForwardFill, where the last good value is propagated forward, Backfill, where the next good value is propagated backwards,
-    /// and Median, where the mathmatical median is used to fill in missing values.
+    /// and Median, where the mathematical median is used to fill in missing values.
     ///
     /// NOTE: It is not recommended to chain this multiple times. If a column is filtered, the default value is placed when a row is imputed, and the
     /// default value is not null. Thus any other TimeSeriesImputers will not be able to replace those values anymore causing essentially a very
@@ -97,7 +101,7 @@ namespace Microsoft.ML.Featurizers
     /// <seealso cref="TimeSeriesImputerExtensionClass.ReplaceMissingTimeSeriesValues(TransformsCatalog, string, string[], string[], FilterMode, ImputationStrategy, bool)"/>
     public sealed class TimeSeriesImputerEstimator : IEstimator<TimeSeriesImputerTransformer>
     {
-        private Options _options;
+        private readonly Options _options;
         internal const string IsRowImputedColumnName = "IsRowImputed";
 
         private readonly IHost _host;
@@ -158,14 +162,14 @@ namespace Microsoft.ML.Featurizers
 
         /// <summary>
         /// Method by which columns are selected for imputing values.
-        /// NoFilter takes all of the columns so you dont have to specify anything.
+        /// NoFilter takes all of the columns so you don't have to specify anything.
         /// Include only does the specified ImputationStrategy on the columns you specify. The other columns will get a default value.
         /// Exclude is the exact opposite of Include, and does the ImputationStrategy on all columns but the ones you specify, which will get the default value.
         /// </summary>
         public enum FilterMode : byte
         {
             /// <summary>
-            /// Takes all of the columns so you dont have to specify anything.
+            /// Takes all of the columns so you don't have to specify anything.
             /// </summary>
             NoFilter = 1,
 
@@ -458,7 +462,7 @@ namespace Microsoft.ML.Featurizers
                 if (!success)
                     throw new Exception(GetErrorDetailsAndFreeNativeMemory(errorHandle));
 
-                // Manually dispose of the IEnumerator since we dont have a using statement;
+                // Manually dispose of the IEnumerator since we don't have a using statement;
                 cursor.Dispose();
 
                 return new TransformerEstimatorSafeHandle(transformer, DestroyTransformerNative);
@@ -577,7 +581,7 @@ namespace Microsoft.ML.Featurizers
         // TODO: Update entry points
 
         [DllImport("Featurizers", EntryPoint = "TimeSeriesImputerFeaturizer_BinaryArchive_CreateEstimator", CallingConvention = CallingConvention.Cdecl), SuppressUnmanagedCodeSecurity]
-        private static unsafe extern bool CreateEstimatorNative(TypeId* grainTypes, IntPtr grainTypesSize, TypeId* dataTypes, IntPtr dataTypesSize, TimeSeriesImputerEstimator.ImputationStrategy strategy, bool* suppressTypeErrors, out IntPtr estimator, out IntPtr errorHandle);
+        private static extern unsafe bool CreateEstimatorNative(TypeId* grainTypes, IntPtr grainTypesSize, TypeId* dataTypes, IntPtr dataTypesSize, TimeSeriesImputerEstimator.ImputationStrategy strategy, bool* suppressTypeErrors, out IntPtr estimator, out IntPtr errorHandle);
 
         [DllImport("Featurizers", EntryPoint = "TimeSeriesImputerFeaturizer_BinaryArchive_DestroyEstimator", CallingConvention = CallingConvention.Cdecl), SuppressUnmanagedCodeSecurity]
         private static extern bool DestroyEstimatorNative(IntPtr estimator, out IntPtr errorHandle); // Should ONLY be called by safe handle
@@ -589,7 +593,7 @@ namespace Microsoft.ML.Featurizers
         private static extern bool CompleteTrainingNative(TransformerEstimatorSafeHandle estimator, out IntPtr errorHandle);
 
         [DllImport("Featurizers", EntryPoint = "TimeSeriesImputerFeaturizer_BinaryArchive_Fit", CallingConvention = CallingConvention.Cdecl), SuppressUnmanagedCodeSecurity]
-        private static unsafe extern bool FitNative(TransformerEstimatorSafeHandle estimator, NativeBinaryArchiveData data, out FitResult fitResult, out IntPtr errorHandle);
+        private static extern unsafe bool FitNative(TransformerEstimatorSafeHandle estimator, NativeBinaryArchiveData data, out FitResult fitResult, out IntPtr errorHandle);
 
         [DllImport("Featurizers", EntryPoint = "TimeSeriesImputerFeaturizer_BinaryArchive_CreateTransformerFromEstimator", CallingConvention = CallingConvention.Cdecl), SuppressUnmanagedCodeSecurity]
         private static extern bool CreateTransformerFromEstimatorNative(TransformerEstimatorSafeHandle estimator, out IntPtr transformer, out IntPtr errorHandle);
@@ -601,13 +605,13 @@ namespace Microsoft.ML.Featurizers
         private static extern bool CreateOnnxSaveDataNative(TransformerEstimatorSafeHandle transformer, out IntPtr buffer, out IntPtr bufferSize, out IntPtr error);
 
         [DllImport("Featurizers", EntryPoint = "TimeSeriesImputerFeaturizer_BinaryArchive_CreateTransformerFromSavedData"), SuppressUnmanagedCodeSecurity]
-        private static unsafe extern bool CreateTransformerFromSavedDataNative(byte* rawData, IntPtr bufferSize, out IntPtr transformer, out IntPtr errorHandle);
+        private static extern unsafe bool CreateTransformerFromSavedDataNative(byte* rawData, IntPtr bufferSize, out IntPtr transformer, out IntPtr errorHandle);
 
         [DllImport("Featurizers", EntryPoint = "TimeSeriesImputerFeaturizer_BinaryArchive_OnDataCompleted"), SuppressUnmanagedCodeSecurity]
-        private static unsafe extern bool OnDataCompletedNative(TransformerEstimatorSafeHandle estimator, out IntPtr errorHandle);
+        private static extern unsafe bool OnDataCompletedNative(TransformerEstimatorSafeHandle estimator, out IntPtr errorHandle);
 
         [DllImport("Featurizers", EntryPoint = "TimeSeriesImputerFeaturizer_BinaryArchive_GetState"), SuppressUnmanagedCodeSecurity]
-        private static unsafe extern bool GetStateNative(TransformerEstimatorSafeHandle estimator, out TrainingState trainingState, out IntPtr errorHandle);
+        private static extern unsafe bool GetStateNative(TransformerEstimatorSafeHandle estimator, out TrainingState trainingState, out IntPtr errorHandle);
 
         #endregion
 

src/Microsoft.ML.Featurizers/TimeSeriesImputerDataView.cs

@@ -22,7 +22,7 @@ namespace Microsoft.ML.Transforms
     internal sealed class TimeSeriesImputerDataView : IDataTransform
     {
         #region Typed Columns
-        private TimeSeriesImputerTransformer _parent;
+        private readonly TimeSeriesImputerTransformer _parent;
         public class SharedColumnState
         {
             public SharedColumnState()
@@ -269,7 +269,7 @@ namespace Microsoft.ML.Transforms
                 return typeof(T).GetNativeTypeIdFromType();
             }
 
-            internal unsafe abstract T GetDataFromNativeBinaryArchiveData(byte* data, int offset);
+            internal abstract unsafe T GetDataFromNativeBinaryArchiveData(byte* data, int offset);
         }
 
         private abstract class NumericTypedColumn<T> : TypedColumn<T>
@@ -308,7 +308,7 @@ namespace Microsoft.ML.Transforms
             {
             }
 
-            internal unsafe override byte GetDataFromNativeBinaryArchiveData(byte* data, int offset)
+            internal override unsafe byte GetDataFromNativeBinaryArchiveData(byte* data, int offset)
             {
                 if (IsNullable)
                 {
@@ -329,7 +329,7 @@ namespace Microsoft.ML.Transforms
             {
             }
 
-            internal unsafe override sbyte GetDataFromNativeBinaryArchiveData(byte* data, int offset)
+            internal override unsafe sbyte GetDataFromNativeBinaryArchiveData(byte* data, int offset)
             {
                 if (IsNullable)
                 {
@@ -350,7 +350,7 @@ namespace Microsoft.ML.Transforms
             {
             }
 
-            internal unsafe override short GetDataFromNativeBinaryArchiveData(byte* data, int offset)
+            internal override unsafe short GetDataFromNativeBinaryArchiveData(byte* data, int offset)
             {
                 if (IsNullable)
                 {
@@ -371,7 +371,7 @@ namespace Microsoft.ML.Transforms
             {
             }
 
-            internal unsafe override ushort GetDataFromNativeBinaryArchiveData(byte* data, int offset)
+            internal override unsafe ushort GetDataFromNativeBinaryArchiveData(byte* data, int offset)
             {
                 if (IsNullable)
                 {
@@ -392,7 +392,7 @@ namespace Microsoft.ML.Transforms
             {
             }
 
-            internal unsafe override int GetDataFromNativeBinaryArchiveData(byte* data, int offset)
+            internal override unsafe int GetDataFromNativeBinaryArchiveData(byte* data, int offset)
             {
                 if (IsNullable)
                 {
@@ -413,7 +413,7 @@ namespace Microsoft.ML.Transforms
             {
             }
 
-            internal unsafe override uint GetDataFromNativeBinaryArchiveData(byte* data, int offset)
+            internal override unsafe uint GetDataFromNativeBinaryArchiveData(byte* data, int offset)
             {
                 if (IsNullable)
                 {
@@ -434,7 +434,7 @@ namespace Microsoft.ML.Transforms
             {
             }
 
-            internal unsafe override long GetDataFromNativeBinaryArchiveData(byte* data, int offset)
+            internal override unsafe long GetDataFromNativeBinaryArchiveData(byte* data, int offset)
             {
                 if (IsNullable)
                 {
@@ -455,7 +455,7 @@ namespace Microsoft.ML.Transforms
             {
             }
 
-            internal unsafe override ulong GetDataFromNativeBinaryArchiveData(byte* data, int offset)
+            internal override unsafe ulong GetDataFromNativeBinaryArchiveData(byte* data, int offset)
             {
                 if (IsNullable)
                 {
@@ -476,7 +476,7 @@ namespace Microsoft.ML.Transforms
             {
             }
 
-            internal unsafe override float GetDataFromNativeBinaryArchiveData(byte* data, int offset)
+            internal override unsafe float GetDataFromNativeBinaryArchiveData(byte* data, int offset)
             {
                 var bytes = new byte[sizeof(float)];
                 Marshal.Copy((IntPtr)(data + offset), bytes, 0, sizeof(float));
@@ -491,7 +491,7 @@ namespace Microsoft.ML.Transforms
             {
             }
 
-            internal unsafe override double GetDataFromNativeBinaryArchiveData(byte* data, int offset)
+            internal override unsafe double GetDataFromNativeBinaryArchiveData(byte* data, int offset)
             {
                 var bytes = new byte[sizeof(double)];
                 Marshal.Copy((IntPtr)(data + offset), bytes, 0, sizeof(double));
@@ -506,7 +506,7 @@ namespace Microsoft.ML.Transforms
             {
             }
 
-            internal unsafe override bool GetDataFromNativeBinaryArchiveData(byte* data, int offset)
+            internal override unsafe bool GetDataFromNativeBinaryArchiveData(byte* data, int offset)
             {
                 if (IsNullable)
                 {
@@ -552,7 +552,7 @@ namespace Microsoft.ML.Transforms
                 binaryWriter.Write(stringBytes);
             }
 
-            internal unsafe override ReadOnlyMemory<char> GetDataFromNativeBinaryArchiveData(byte* data, int offset)
+            internal override unsafe ReadOnlyMemory<char> GetDataFromNativeBinaryArchiveData(byte* data, int offset)
             {
                 if (_isNullable)
                 {
@@ -608,7 +608,7 @@ namespace Microsoft.ML.Transforms
                 binaryWriter.Write(value);
             }
 
-            internal unsafe override DateTime GetDataFromNativeBinaryArchiveData(byte* data, int offset)
+            internal override unsafe DateTime GetDataFromNativeBinaryArchiveData(byte* data, int offset)
             {
                 long value;
                 if (_isNullable)
@@ -656,7 +656,7 @@ namespace Microsoft.ML.Transforms
 
         internal class TransformedDataSafeHandle : SafeHandleZeroOrMinusOneIsInvalid
         {
-            private IntPtr _size;
+            private readonly IntPtr _size;
             public TransformedDataSafeHandle(IntPtr handle, IntPtr size) : base(true)
             {
                 SetHandle(handle);
@@ -728,7 +728,7 @@ namespace Microsoft.ML.Transforms
         private sealed class Cursor : DataViewRowCursor
         {
             private readonly IChannelProvider _ch;
-            private DataViewRowCursor _input;
+            private readonly DataViewRowCursor _input;
             private long _position;
             private bool _isGood;
             private readonly Dictionary<string, TypedColumn> _allColumns;

src/Microsoft.ML.ImageAnalytics/ImageGrayscale.cs

@@ -160,7 +160,7 @@ namespace Microsoft.ML.Transforms.Image
 
         private sealed class Mapper : OneToOneMapperBase
         {
-            private ImageGrayscalingTransformer _parent;
+            private readonly ImageGrayscalingTransformer _parent;
 
             public Mapper(ImageGrayscalingTransformer parent, DataViewSchema inputSchema)
                 : base(parent.Host.Register(nameof(Mapper)), parent, inputSchema)

src/Microsoft.ML.OnnxTransformer/OnnxMapType.cs

@@ -49,8 +49,8 @@ namespace Microsoft.ML.Transforms.Onnx
     /// </summary>
     public sealed class OnnxMapTypeAttribute : DataViewTypeAttribute
     {
-        private Type _keyType;
-        private Type _valueType;
+        private readonly Type _keyType;
+        private readonly Type _valueType;
 
         /// <summary>
         /// Create a map (aka dictionary) type.

src/Microsoft.ML.OnnxTransformer/OnnxSequenceType.cs

@@ -55,7 +55,7 @@ namespace Microsoft.ML.Transforms.Onnx
     /// </summary>
     public sealed class OnnxSequenceTypeAttribute : DataViewTypeAttribute
     {
-        private Type _elemType;
+        private readonly Type _elemType;
 
         // Make default constructor obsolete.
         // Use default constructor will left the _elemType field empty and cause exception in methods using _elemType.

src/Microsoft.ML.OnnxTransformer/OnnxUtils.cs

@@ -91,7 +91,7 @@ namespace Microsoft.ML.Transforms.Onnx
             {
                 var index = OutputNames.IndexOf(name);
                 if (index < 0)
-                    throw Contracts.ExceptParamValue(name, nameof(name), $"Onput tensor, {name}, does not exist in the ONNX model. " +
+                    throw Contracts.ExceptParamValue(name, nameof(name), $"Ouput tensor, {name}, does not exist in the ONNX model. " +
                         $"Available output names are [{string.Join(",", OutputNames)}].");
                 return OutputsInfo[index];
             }
@@ -423,7 +423,7 @@ namespace Microsoft.ML.Transforms.Onnx
 
     internal sealed class OnnxUtils
     {
-        private static HashSet<Type> _onnxTypeMap =
+        private static readonly HashSet<Type> _onnxTypeMap =
             new HashSet<Type>
                 {
                      typeof(Double),
@@ -439,7 +439,7 @@ namespace Microsoft.ML.Transforms.Onnx
                      typeof(SByte),
                      typeof(Byte)
                 };
-        private static Dictionary<Type, InternalDataKind> _typeToKindMap =
+        private static readonly Dictionary<Type, InternalDataKind> _typeToKindMap =
             new Dictionary<Type, InternalDataKind>
                 {
                     { typeof(Single) , InternalDataKind.R4},

src/Microsoft.ML.Parquet/ParquetLoader.cs

@@ -441,7 +441,7 @@ namespace Microsoft.ML.Data
             private readonly ReaderOptions _readerOptions;
             private int _curDataSetRow;
             private IEnumerator<int> _dataSetEnumerator;
-            private IEnumerator<int> _blockEnumerator;
+            private readonly IEnumerator<int> _blockEnumerator;
             private readonly IList[] _columnValues;
             private readonly Random _rand;
 

src/Microsoft.ML.Parquet/PartitionedFileLoader.cs

@@ -370,20 +370,20 @@ namespace Microsoft.ML.Data
             private static readonly FuncInstanceMethodInfo1<Cursor, int, DataViewType, Delegate> _createGetterDelegateCoreMethodInfo
                 = FuncInstanceMethodInfo1<Cursor, int, DataViewType, Delegate>.Create(target => target.CreateGetterDelegateCore<int>);
 
-            private PartitionedFileLoader _parent;
+            private readonly PartitionedFileLoader _parent;
 
             private readonly bool[] _active;
             private readonly bool[] _subActive; // Active columns of the sub-cursor.
-            private Delegate[] _getters;
-            private Delegate[] _subGetters; // Cached getters of the sub-cursor.
+            private readonly Delegate[] _getters;
+            private readonly Delegate[] _subGetters; // Cached getters of the sub-cursor.
 
             private readonly IEnumerable<DataViewSchema.Column> _columnsNeeded;
             private readonly IEnumerable<DataViewSchema.Column> _subActivecolumnsNeeded;
 
-            private ReadOnlyMemory<char>[] _colValues; // Column values cached from the file path.
+            private readonly ReadOnlyMemory<char>[] _colValues; // Column values cached from the file path.
             private DataViewRowCursor _subCursor; // Sub cursor of the current file.
 
-            private IEnumerator<int> _fileOrder;
+            private readonly IEnumerator<int> _fileOrder;
 
             public Cursor(IChannelProvider provider, PartitionedFileLoader parent, IMultiStreamSource files, IEnumerable<DataViewSchema.Column> columnsNeeded, Random rand)
                 : base(provider)
@@ -744,7 +744,7 @@ namespace Microsoft.ML.Data
         /// </summary>
         /// <param name="basepath">A base path.</param>
         /// <param name="files">A list of files under the base path.</param>
-        /// <returns>A realtive file path.</returns>
+        /// <returns>A relative file path.</returns>
         private string GetRelativePath(string basepath, IMultiStreamSource files)
         {
             Contracts.CheckNonEmpty(basepath, nameof(basepath));