Renaming ColumnInfo to ColumnOptions (#2709)

Author: artidoro

docs/code/MlNetCookBook.md

@@ -629,9 +629,9 @@ var trainData = mlContext.Data.ReadFromTextFile<IrisInputAllFeatures>(dataPath,
 // Apply all kinds of standard ML.NET normalization to the raw features.
 var pipeline =
     mlContext.Transforms.Normalize(
-        new NormalizingEstimator.MinMaxColumn("MinMaxNormalized", "Features", fixZero: true),
-        new NormalizingEstimator.MeanVarColumn("MeanVarNormalized", "Features", fixZero: true),
-        new NormalizingEstimator.BinningColumn("BinNormalized", "Features", numBins: 256));
+        new NormalizingEstimator.MinMaxColumnOptions("MinMaxNormalized", "Features", fixZero: true),
+        new NormalizingEstimator.MeanVarColumnOptions("MeanVarNormalized", "Features", fixZero: true),
+        new NormalizingEstimator.BinningColumnOptions("BinNormalized", "Features", numBins: 256));
 
 // Let's train our pipeline of normalizers, and then apply it to the same data.
 var normalizedData = pipeline.Fit(trainData).Transform(trainData);

docs/samples/Microsoft.ML.Samples/Dynamic/Normalizer.cs

@@ -66,7 +66,7 @@ public static void Example()
 
             // Composing a different pipeline if we wanted to normalize more than one column at a time. 
             // Using log scale as the normalization mode. 
-            var multiColPipeline = ml.Transforms.Normalize(NormalizingEstimator.NormalizerMode.LogMeanVariance, new SimpleColumnInfo[] { ("LogInduced", "Induced"), ("LogSpontaneous", "Spontaneous") });
+            var multiColPipeline = ml.Transforms.Normalize(NormalizingEstimator.NormalizerMode.LogMeanVariance, new ColumnOptions[] { ("LogInduced", "Induced"), ("LogSpontaneous", "Spontaneous") });
             // The transformed data.
             var multiColtransformer = multiColPipeline.Fit(trainData);
             var multiColtransformedData = multiColtransformer.Transform(trainData);

docs/samples/Microsoft.ML.Samples/Dynamic/TensorFlow/TextClassification.cs

@@ -70,7 +70,7 @@ public static void Example()
             };
 
             var engine = mlContext.Transforms.Text.TokenizeWords("TokenizedWords", "Sentiment_Text")
-                .Append(mlContext.Transforms.Conversion.ValueMap(lookupMap, "Words", "Ids", new SimpleColumnInfo[] { ("VariableLenghtFeatures", "TokenizedWords") }))
+                .Append(mlContext.Transforms.Conversion.ValueMap(lookupMap, "Words", "Ids", new ColumnOptions[] { ("VariableLenghtFeatures", "TokenizedWords") }))
                 .Append(mlContext.Transforms.CustomMapping(ResizeFeaturesAction, "Resize"))
                 .Append(mlContext.Transforms.ScoreTensorFlowModel(modelInfo, new[] { "Prediction/Softmax" }, new[] { "Features" }))
                 .Append(mlContext.Transforms.CopyColumns(("Prediction", "Prediction/Softmax")))

docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/Projection/VectorWhitenWithColumnInfo.cs renamed to docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/Projection/VectorWhitenWithColumnOptions.cs

@@ -5,7 +5,7 @@
 
 namespace Microsoft.ML.Samples.Dynamic
 {
-    public sealed class VectorWhitenWithColumnInfo
+    public sealed class VectorWhitenWithColumnOptions
     {
         /// This example requires installation of additional nuget package <a href="https://www.nuget.org/packages/Microsoft.ML.HalLearners/">Microsoft.ML.HalLearners</a>.
         public static void Example()
@@ -39,7 +39,7 @@ public static void Example()
 
 
             // A pipeline to project Features column into white noise vector.
-            var whiteningPipeline = ml.Transforms.Projection.VectorWhiten(new Transforms.Projections.VectorWhiteningEstimator.ColumnInfo(
+            var whiteningPipeline = ml.Transforms.Projection.VectorWhiten(new Transforms.Projections.VectorWhiteningEstimator.ColumnOptions(
                 nameof(SamplesUtils.DatasetUtils.SampleVectorOfNumbersData.Features), kind: Transforms.Projections.WhiteningKind.Pca, pcaNum: 4));
             // The transformed (projected) data.
             var transformedData = whiteningPipeline.Fit(trainData).Transform(trainData);

src/Microsoft.ML.Data/TrainCatalog.cs

@@ -226,12 +226,12 @@ private void EnsureGroupPreservationColumn(ref IDataView data, ref string sampli
                     // Generate a new column with the hashed samplingKeyColumn.
                     while (data.Schema.TryGetColumnIndex(samplingKeyColumn, out tmp))
                         samplingKeyColumn = string.Format("{0}_{1:000}", origStratCol, ++inc);
-                    HashingEstimator.ColumnInfo columnInfo;
+                    HashingEstimator.ColumnOptions columnOptions;
                     if (seed.HasValue)
-                        columnInfo = new HashingEstimator.ColumnInfo(samplingKeyColumn, origStratCol, 30, seed.Value);
+                        columnOptions = new HashingEstimator.ColumnOptions(samplingKeyColumn, origStratCol, 30, seed.Value);
                     else
-                        columnInfo = new HashingEstimator.ColumnInfo(samplingKeyColumn, origStratCol, 30);
-                    data = new HashingEstimator(Environment, columnInfo).Fit(data).Transform(data);
+                        columnOptions = new HashingEstimator.ColumnOptions(samplingKeyColumn, origStratCol, 30);
+                    data = new HashingEstimator(Environment, columnOptions).Fit(data).Transform(data);
                 }
             }
         }

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

@@ -134,7 +134,7 @@ internal sealed class TaggedOptions
         }
 
         [BestFriend]
-        internal sealed class ColumnInfo
+        internal sealed class ColumnOptions
         {
             public readonly string Name;
             private readonly (string name, string alias)[] _sources;
@@ -143,7 +143,7 @@ internal sealed class ColumnInfo
             /// <summary>
             /// This denotes a concatenation of all <paramref name="inputColumnNames"/> into column called <paramref name="name"/>.
             /// </summary>
-            public ColumnInfo(string name, params string[] inputColumnNames)
+            public ColumnOptions(string name, params string[] inputColumnNames)
                 : this(name, GetPairs(inputColumnNames))
             {
             }
@@ -159,7 +159,7 @@ public ColumnInfo(string name, params string[] inputColumnNames)
             /// For each input column, an 'alias' can be specified, to be used in constructing the resulting slot names.
             /// If the alias is not specified, it defaults to be column name.
             /// </summary>
-            public ColumnInfo(string name, IEnumerable<(string name, string alias)> inputColumnNames)
+            public ColumnOptions(string name, IEnumerable<(string name, string alias)> inputColumnNames)
             {
                 Contracts.CheckNonEmpty(name, nameof(name));
                 Contracts.CheckValue(inputColumnNames, nameof(inputColumnNames));
@@ -195,7 +195,7 @@ public void Save(ModelSaveContext ctx)
                 }
             }
 
-            internal ColumnInfo(ModelLoadContext ctx)
+            internal ColumnOptions(ModelLoadContext ctx)
             {
                 Contracts.AssertValue(ctx);
                 // *** Binary format ***
@@ -218,7 +218,7 @@ internal ColumnInfo(ModelLoadContext ctx)
             }
         }
 
-        private readonly ColumnInfo[] _columns;
+        private readonly ColumnOptions[] _columns;
 
         /// <summary>
         /// The names of the output and input column pairs for the transformation.
@@ -232,14 +232,14 @@ internal ColumnInfo(ModelLoadContext ctx)
         /// The column types must match, and the output column type is always a vector.
         /// </summary>
         internal ColumnConcatenatingTransformer(IHostEnvironment env, string outputColumnName, params string[] inputColumnNames)
-            : this(env, new ColumnInfo(outputColumnName, inputColumnNames))
+            : this(env, new ColumnOptions(outputColumnName, inputColumnNames))
         {
         }
 
         /// <summary>
         /// Concatenates multiple groups of columns, each group is denoted by one of <paramref name="columns"/>.
         /// </summary>
-        internal ColumnConcatenatingTransformer(IHostEnvironment env, params ColumnInfo[] columns) :
+        internal ColumnConcatenatingTransformer(IHostEnvironment env, params ColumnOptions[] columns) :
             base(Contracts.CheckRef(env, nameof(env)).Register(nameof(ColumnConcatenatingTransformer)))
         {
             Contracts.CheckValue(columns, nameof(columns));
@@ -272,7 +272,7 @@ private protected override void SaveModel(ModelSaveContext ctx)
             // *** Binary format ***
             // int: number of columns
             // for each column:
-            //    columnInfo
+            //    columnOptions
 
             Contracts.Assert(_columns.Length > 0);
             ctx.Writer.Write(_columns.Length);
@@ -293,18 +293,18 @@ private ColumnConcatenatingTransformer(IHostEnvironment env, ModelLoadContext ct
                 // *** Binary format ***
                 // int: number of columns
                 // for each column:
-                //    columnInfo
+                //    columnOptions
                 int n = ctx.Reader.ReadInt32();
                 Contracts.CheckDecode(n > 0);
-                _columns = new ColumnInfo[n];
+                _columns = new ColumnOptions[n];
                 for (int i = 0; i < n; i++)
-                    _columns[i] = new ColumnInfo(ctx);
+                    _columns[i] = new ColumnOptions(ctx);
             }
             else
                 _columns = LoadLegacy(ctx);
         }
 
-        private ColumnInfo[] LoadLegacy(ModelLoadContext ctx)
+        private ColumnOptions[] LoadLegacy(ModelLoadContext ctx)
         {
             // *** Legacy binary format ***
             // int: sizeof(Float).
@@ -359,9 +359,9 @@ private ColumnInfo[] LoadLegacy(ModelLoadContext ctx)
                 }
             }
 
-            var result = new ColumnInfo[n];
+            var result = new ColumnOptions[n];
             for (int i = 0; i < n; i++)
-                result[i] = new ColumnInfo(names[i],
+                result[i] = new ColumnOptions(names[i],
                     inputs[i].Zip(aliases[i], (name, alias) => (name, alias)));
             return result;
         }
@@ -380,7 +380,7 @@ internal static IDataTransform Create(IHostEnvironment env, Options options, IDa
                 env.CheckUserArg(Utils.Size(options.Columns[i].Source) > 0, nameof(options.Columns));
 
             var cols = options.Columns
-                .Select(c => new ColumnInfo(c.Name, c.Source))
+                .Select(c => new ColumnOptions(c.Name, c.Source))
                 .ToArray();
             var transformer = new ColumnConcatenatingTransformer(env, cols);
             return transformer.MakeDataTransform(input);
@@ -400,7 +400,7 @@ internal static IDataTransform Create(IHostEnvironment env, TaggedOptions option
                 env.CheckUserArg(Utils.Size(options.Columns[i].Source) > 0, nameof(options.Columns));
 
             var cols = options.Columns
-                .Select(c => new ColumnInfo(c.Name, c.Source.Select(kvp => (kvp.Value, kvp.Key != "" ? kvp.Key : null))))
+                .Select(c => new ColumnOptions(c.Name, c.Source.Select(kvp => (kvp.Value, kvp.Key != "" ? kvp.Key : null))))
                 .ToArray();
             var transformer = new ColumnConcatenatingTransformer(env, cols);
             return transformer.MakeDataTransform(input);
@@ -526,7 +526,7 @@ private sealed class BoundColumn
             {
                 public readonly int[] SrcIndices;
 
-                private readonly ColumnInfo _columnInfo;
+                private readonly ColumnOptions _columnOptions;
                 private readonly DataViewType[] _srcTypes;
 
                 public readonly VectorType OutputType;
@@ -542,10 +542,10 @@ private sealed class BoundColumn
 
                 private readonly DataViewSchema _inputSchema;
 
-                public BoundColumn(DataViewSchema inputSchema, ColumnInfo columnInfo, int[] sources, VectorType outputType,
+                public BoundColumn(DataViewSchema inputSchema, ColumnOptions columnOptions, int[] sources, VectorType outputType,
                     bool isNormalized, bool hasSlotNames, bool hasCategoricals, int slotCount, int catCount)
                 {
-                    _columnInfo = columnInfo;
+                    _columnOptions = columnOptions;
                     SrcIndices = sources;
                     _srcTypes = sources.Select(c => inputSchema[c].Type).ToArray();
 
@@ -570,7 +570,7 @@ public DataViewSchema.DetachedColumn MakeSchemaColumn()
                     if (_isIdentity)
                     {
                         var inputCol = _inputSchema[SrcIndices[0]];
-                        return new DataViewSchema.DetachedColumn(_columnInfo.Name, inputCol.Type, inputCol.Annotations);
+                        return new DataViewSchema.DetachedColumn(_columnOptions.Name, inputCol.Type, inputCol.Annotations);
                     }
 
                     var metadata = new DataViewSchema.Annotations.Builder();
@@ -581,7 +581,7 @@ public DataViewSchema.DetachedColumn MakeSchemaColumn()
                     if (_hasCategoricals)
                         metadata.Add(AnnotationUtils.Kinds.CategoricalSlotRanges, _categoricalRangeType, (ValueGetter<VBuffer<int>>)GetCategoricalSlotRanges);
 
-                    return new DataViewSchema.DetachedColumn(_columnInfo.Name, OutputType, metadata.ToAnnotations());
+                    return new DataViewSchema.DetachedColumn(_columnOptions.Name, OutputType, metadata.ToAnnotations());
                 }
 
                 private void GetIsNormalized(ref bool value) => value = _isNormalized;
@@ -630,9 +630,9 @@ private void GetSlotNames(ref VBuffer<ReadOnlyMemory<char>> dst)
                     {
                         int colSrc = SrcIndices[i];
                         var typeSrc = _srcTypes[i];
-                        Contracts.Assert(_columnInfo.Sources[i].alias != "");
+                        Contracts.Assert(_columnOptions.Sources[i].alias != "");
                         var colName = _inputSchema[colSrc].Name;
-                        var nameSrc = _columnInfo.Sources[i].alias ?? colName;
+                        var nameSrc = _columnOptions.Sources[i].alias ?? colName;
                         if (!(typeSrc is VectorType vectorTypeSrc))
                         {
                             bldr.AddFeature(slot++, nameSrc.AsMemory());
@@ -650,7 +650,7 @@ private void GetSlotNames(ref VBuffer<ReadOnlyMemory<char>> dst)
                         {
                             inputMetadata.GetValue(AnnotationUtils.Kinds.SlotNames, ref names);
                             sb.Clear();
-                            if (_columnInfo.Sources[i].alias != colName)
+                            if (_columnOptions.Sources[i].alias != colName)
                                 sb.Append(nameSrc).Append(".");
                             int len = sb.Length;
                             foreach (var kvp in names.Items())
@@ -801,15 +801,15 @@ private Delegate MakeGetter<T>(DataViewRow input)
                 public KeyValuePair<string, JToken> SavePfaInfo(BoundPfaContext ctx)
                 {
                     Contracts.AssertValue(ctx);
-                    string outName = _columnInfo.Name;
+                    string outName = _columnOptions.Name;
                     if (!OutputType.IsKnownSize) // Do not attempt variable length.
                         return new KeyValuePair<string, JToken>(outName, null);
 
                     string[] srcTokens = new string[SrcIndices.Length];
                     bool[] srcPrimitive = new bool[SrcIndices.Length];
                     for (int i = 0; i < SrcIndices.Length; ++i)
                     {
-                        var srcName = _columnInfo.Sources[i].name;
+                        var srcName = _columnOptions.Sources[i].name;
                         if ((srcTokens[i] = ctx.TokenOrNullForName(srcName)) == null)
                             return new KeyValuePair<string, JToken>(outName, null);
                         srcPrimitive[i] = _srcTypes[i] is PrimitiveDataViewType;