Creation of components through MLContext and cleanup (Onnx, Tensorflow, SelectColumn, KeytoBinVec, ValueMap)

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

@@ -35,7 +35,7 @@ public static void OnnxTransformSample()
             var mlContext = new MLContext();
             var data = GetTensorData();
             var idv = mlContext.Data.ReadFromEnumerable(data);
-            var pipeline = new OnnxScoringEstimator(mlContext, new[] { outputInfo.Key }, new[] { inputInfo.Key }, modelPath);
+            var pipeline = mlContext.Transforms.ApplyOnnxModel(modelPath, new[] { outputInfo.Key }, new[] { inputInfo.Key });
 
             // Run the pipeline and get the transformed values
             var transformedValues = pipeline.Fit(idv).Transform(idv);

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

@@ -52,7 +52,7 @@ public static void Run()
             };
 
             // Constructs the ValueMappingEstimator making the ML.net pipeline
-            var pipeline = new ValueMappingEstimator<string, int>(mlContext, educationKeys, educationValues, ("EducationFeature", "Education"));
+            var pipeline = mlContext.Transforms.Conversion.ValueMap<string, int>(educationKeys, educationValues, ("EducationFeature", "Education"));
 
             // Fits the ValueMappingEstimator and transforms the data adding the EducationFeature column.
             IDataView transformedData = pipeline.Fit(trainData).Transform(trainData);

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

@@ -58,7 +58,7 @@ public static void Run()
             // Generate the ValueMappingEstimator that will output KeyTypes even though our values are strings.
             // The KeyToValueMappingEstimator is added to provide a reverse lookup of the KeyType, converting the KeyType value back
             // to the original value.
-            var pipeline = new ValueMappingEstimator<string, string>(mlContext, educationKeys, educationValues, true, ("EducationKeyType", "Education"))
+            var pipeline = mlContext.Transforms.Conversion.ValueMap<string, string>(educationKeys, educationValues, true, ("EducationKeyType", "Education"))
                               .Append(mlContext.Transforms.Conversion.MapKeyToValue(("EducationCategory", "EducationKeyType")));
 
             // Fits the ValueMappingEstimator and transforms the data adding the EducationKeyType column.

src/Microsoft.ML.Data/Commands/CrossValidationCommand.cs

@@ -168,7 +168,7 @@ private void RunCore(IChannel ch, string cmd)
                                 "", ComponentFactoryUtils.CreateFromFunction<IDataView, IDataTransform>(
                                     (env, input) =>
                                     {
-                                        var args = new GenerateNumberTransform.Arguments();
+                                        var args = new GenerateNumberTransform.Options();
                                         args.Columns = new[] { new GenerateNumberTransform.Column() { Name = DefaultColumnNames.Name }, };
                                         args.UseCounter = true;
                                         return new GenerateNumberTransform(env, args, input);
@@ -313,7 +313,7 @@ private string GetSplitColumn(IChannel ch, IDataView input, ref IDataView output
                 int inc = 0;
                 while (input.Schema.TryGetColumnIndex(stratificationColumn, out tmp))
                     stratificationColumn = string.Format("StratificationColumn_{0:000}", ++inc);
-                var keyGenArgs = new GenerateNumberTransform.Arguments();
+                var keyGenArgs = new GenerateNumberTransform.Options();
                 var col = new GenerateNumberTransform.Column();
                 col.Name = stratificationColumn;
                 keyGenArgs.Columns = new[] { col };
@@ -514,7 +514,7 @@ private FoldResult RunFold(int fold)
                     ITrainer trainer = _trainer.CreateComponent(host);
 
                     // Train pipe.
-                    var trainFilter = new RangeFilter.Arguments();
+                    var trainFilter = new RangeFilter.Options();
                     trainFilter.Column = _splitColumn;
                     trainFilter.Min = (Double)fold / _numFolds;
                     trainFilter.Max = (Double)(fold + 1) / _numFolds;
@@ -524,7 +524,7 @@ private FoldResult RunFold(int fold)
                     var trainData = _createExamples(host, ch, trainPipe, trainer);
 
                     // Test pipe.
-                    var testFilter = new RangeFilter.Arguments();
+                    var testFilter = new RangeFilter.Options();
                     testFilter.Column = trainFilter.Column;
                     testFilter.Min = trainFilter.Min;
                     testFilter.Max = trainFilter.Max;

src/Microsoft.ML.Data/Commands/SaveDataCommand.cs

@@ -158,7 +158,7 @@ private void RunCore(IChannel ch)
             // Send the first N lines to console.
             if (Args.Rows > 0)
             {
-                var args = new SkipTakeFilter.TakeArguments() { Count = Args.Rows };
+                var args = new SkipTakeFilter.TakeOptions() { Count = Args.Rows };
                 data = SkipTakeFilter.Create(Host, args, data);
             }
             var textSaver = saver as TextSaver;

src/Microsoft.ML.Data/DataLoadSave/DataOperationsCatalog.cs

@@ -242,7 +242,7 @@ public IDataView SkipRows(IDataView input, long count)
             Environment.CheckValue(input, nameof(input));
             Environment.CheckUserArg(count > 0, nameof(count), "Must be greater than zero.");
 
-            var options = new SkipTakeFilter.SkipArguments()
+            var options = new SkipTakeFilter.SkipOptions()
             {
                 Count = count
             };
@@ -270,7 +270,7 @@ public IDataView TakeRows(IDataView input, long count)
             Environment.CheckValue(input, nameof(input));
             Environment.CheckUserArg(count > 0, nameof(count), "Must be greater than zero.");
 
-            var options = new SkipTakeFilter.TakeArguments()
+            var options = new SkipTakeFilter.TakeOptions()
             {
                 Count = count
             };

src/Microsoft.ML.Data/DataLoadSave/Transpose/TransposeSaver.cs

@@ -142,10 +142,10 @@ private void SaveTransposedData(IChannel ch, Stream stream, ITransposeDataView d
 
             // First write out the no-row data, limited to these columns.
             IDataView subdata = new ChooseColumnsByIndexTransform(_host,
-                new ChooseColumnsByIndexTransform.Arguments() { Indices = cols }, data);
+                new ChooseColumnsByIndexTransform.Options() { Indices = cols }, data);
             // If we want the "dual mode" row-wise and slot-wise file, don't filter out anything.
             if (!_writeRowData)
-                subdata = SkipTakeFilter.Create(_host, new SkipTakeFilter.TakeArguments() { Count = 0 }, subdata);
+                subdata = SkipTakeFilter.Create(_host, new SkipTakeFilter.TakeOptions() { Count = 0 }, subdata);
 
             string msg = _writeRowData ? "row-wise data, schema, and metadata" : "schema and metadata";
             viewAction(msg, subdata);

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

@@ -165,7 +165,7 @@ private static IDataView SelectCachableColumns(IDataView data, IHostEnvironment
                 return data;
 
             // REVIEW: This can potentially cause hidden columns to become unhidden. See task 3739.
-            var args = new ChooseColumnsByIndexTransform.Arguments();
+            var args = new ChooseColumnsByIndexTransform.Options();
             args.Drop = true;
             args.Indices = columnsToDrop.ToArray();
             return new ChooseColumnsByIndexTransform(env, args, data);

src/Microsoft.ML.Data/DebuggerExtensions.cs

@@ -48,7 +48,7 @@ public static DataDebuggerPreview Preview(this IEstimator<ITransformer> estimato
 
             using (var env = new LocalEnvironment(conc: 1))
             {
-                var trainData = SkipTakeFilter.Create(env, new SkipTakeFilter.TakeArguments { Count = maxTrainingRows }, data);
+                var trainData = SkipTakeFilter.Create(env, new SkipTakeFilter.TakeOptions { Count = maxTrainingRows }, data);
                 return new DataDebuggerPreview(estimator.Fit(trainData).Transform(data), maxRows);
             }
         }

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

@@ -12,17 +12,18 @@
 using Microsoft.ML.Internal.Utilities;
 using Microsoft.ML.Model;
 
-[assembly: LoadableClass(typeof(ChooseColumnsByIndexTransform), typeof(ChooseColumnsByIndexTransform.Arguments), typeof(SignatureDataTransform),
+[assembly: LoadableClass(typeof(ChooseColumnsByIndexTransform), typeof(ChooseColumnsByIndexTransform.Options), typeof(SignatureDataTransform),
     "", "ChooseColumnsByIndexTransform", "ChooseColumnsByIndex")]
 
 [assembly: LoadableClass(typeof(ChooseColumnsByIndexTransform), null, typeof(SignatureLoadDataTransform),
     "", ChooseColumnsByIndexTransform.LoaderSignature, ChooseColumnsByIndexTransform.LoaderSignatureOld)]
 
 namespace Microsoft.ML.Data
 {
-    public sealed class ChooseColumnsByIndexTransform : RowToRowTransformBase
+    [BestFriend]
+    internal sealed class ChooseColumnsByIndexTransform : RowToRowTransformBase
     {
-        public sealed class Arguments
+        public sealed class Options
         {
             [Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Column indices to select", Name = "Index", ShortName = "ind")]
             public int[] Indices;
@@ -59,17 +60,17 @@ private sealed class Bindings
             // This transform's output schema.
             internal Schema OutputSchema { get; }
 
-            internal Bindings(Arguments args, Schema sourceSchema)
+            internal Bindings(Options options, Schema sourceSchema)
             {
-                Contracts.AssertValue(args);
+                Contracts.AssertValue(options);
                 Contracts.AssertValue(sourceSchema);
 
                 _sourceSchema = sourceSchema;
 
                 // Store user-specified arguments as the major state of this transform. Only the major states will
                 // be saved and all other attributes can be reconstructed from them.
-                _drop = args.Drop;
-                _selectedColumnIndexes = args.Indices;
+                _drop = options.Drop;
+                _selectedColumnIndexes = options.Indices;
 
                 // Compute actually used attributes in runtime from those major states.
                 ComputeSources(_drop, _selectedColumnIndexes, _sourceSchema, out _sources);
@@ -194,12 +195,12 @@ private static VersionInfo GetVersionInfo()
         /// <summary>
         /// Public constructor corresponding to SignatureDataTransform.
         /// </summary>
-        public ChooseColumnsByIndexTransform(IHostEnvironment env, Arguments args, IDataView input)
+        public ChooseColumnsByIndexTransform(IHostEnvironment env, Options options, IDataView input)
             : base(env, RegistrationName, input)
         {
-            Host.CheckValue(args, nameof(args));
+            Host.CheckValue(options, nameof(options));
 
-            _bindings = new Bindings(args, Source.Schema);
+            _bindings = new Bindings(options, Source.Schema);
         }
 
         private ChooseColumnsByIndexTransform(IHost host, ModelLoadContext ctx, IDataView input)

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

@@ -26,7 +26,7 @@ public static CommonOutputs.TransformOutput ConcatColumns(IHostEnvironment env,
         }
 
         [TlcModule.EntryPoint(Name = "Transforms.ColumnSelector", Desc = "Selects a set of columns, dropping all others", UserName = "Select Columns")]
-        public static CommonOutputs.TransformOutput SelectColumns(IHostEnvironment env, ColumnSelectingTransformer.Arguments input)
+        public static CommonOutputs.TransformOutput SelectColumns(IHostEnvironment env, ColumnSelectingTransformer.Options input)
         {
             Contracts.CheckValue(env, nameof(env));
             var host = env.Register("SelectColumns");

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

@@ -15,7 +15,7 @@ namespace Microsoft.ML.EntryPoints
     internal static class SelectRows
     {
         [TlcModule.EntryPoint(Name = "Transforms.RowRangeFilter", Desc = RangeFilter.Summary, UserName = RangeFilter.UserName, ShortName = RangeFilter.LoaderSignature)]
-        public static CommonOutputs.TransformOutput FilterByRange(IHostEnvironment env, RangeFilter.Arguments input)
+        public static CommonOutputs.TransformOutput FilterByRange(IHostEnvironment env, RangeFilter.Options input)
         {
             Contracts.CheckValue(env, nameof(env));
             var host = env.Register(RangeFilter.LoaderSignature);
@@ -28,7 +28,7 @@ public static CommonOutputs.TransformOutput FilterByRange(IHostEnvironment env,
 
         [TlcModule.EntryPoint(Name = "Transforms.RowSkipFilter", Desc = SkipTakeFilter.SkipFilterSummary, UserName = SkipTakeFilter.SkipFilterUserName,
             ShortName = SkipTakeFilter.SkipFilterShortName)]
-        public static CommonOutputs.TransformOutput SkipFilter(IHostEnvironment env, SkipTakeFilter.SkipArguments input)
+        public static CommonOutputs.TransformOutput SkipFilter(IHostEnvironment env, SkipTakeFilter.SkipOptions input)
         {
             Contracts.CheckValue(env, nameof(env));
             var host = env.Register("SkipFilter");
@@ -40,7 +40,7 @@ public static CommonOutputs.TransformOutput SkipFilter(IHostEnvironment env, Ski
 
         [TlcModule.EntryPoint(Name = "Transforms.RowTakeFilter", Desc = SkipTakeFilter.TakeFilterSummary, UserName = SkipTakeFilter.TakeFilterUserName,
             ShortName = SkipTakeFilter.TakeFilterShortName)]
-        public static CommonOutputs.TransformOutput TakeFilter(IHostEnvironment env, SkipTakeFilter.TakeArguments input)
+        public static CommonOutputs.TransformOutput TakeFilter(IHostEnvironment env, SkipTakeFilter.TakeOptions input)
         {
             Contracts.CheckValue(env, nameof(env));
             var host = env.Register("TakeFilter");
@@ -52,7 +52,7 @@ public static CommonOutputs.TransformOutput TakeFilter(IHostEnvironment env, Ski
 
         [TlcModule.EntryPoint(Name = "Transforms.RowSkipAndTakeFilter", Desc = SkipTakeFilter.SkipTakeFilterSummary,
             UserName = SkipTakeFilter.SkipTakeFilterUserName, ShortName = SkipTakeFilter.SkipTakeFilterShortName)]
-        public static CommonOutputs.TransformOutput SkipAndTakeFilter(IHostEnvironment env, SkipTakeFilter.Arguments input)
+        public static CommonOutputs.TransformOutput SkipAndTakeFilter(IHostEnvironment env, SkipTakeFilter.Options input)
         {
             Contracts.CheckValue(env, nameof(env));
             var host = env.Register("SkipTakeFilter");

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

@@ -880,7 +880,7 @@ private static IDataView AppendPerInstanceDataViews(IHostEnvironment env, string
                 var idv = dv;
                 if (hidden.Count > 0)
                 {
-                    var args = new ChooseColumnsByIndexTransform.Arguments();
+                    var args = new ChooseColumnsByIndexTransform.Options();
                     args.Drop = true;
                     args.Indices = hidden.ToArray();
                     idv = new ChooseColumnsByIndexTransform(env, args, idv);
@@ -910,12 +910,12 @@ private static IDataView AppendPerInstanceDataViews(IHostEnvironment env, string
 
                         idv = new KeyToValueMappingTransformer(env, keyCol).Transform(idv);
                         var hidden = FindHiddenColumns(idv.Schema, keyCol);
-                        idv = new ChooseColumnsByIndexTransform(env, new ChooseColumnsByIndexTransform.Arguments() { Drop = true, Indices = hidden.ToArray() }, idv);
+                        idv = new ChooseColumnsByIndexTransform(env, new ChooseColumnsByIndexTransform.Options() { Drop = true, Indices = hidden.ToArray() }, idv);
                     }
                     foreach (var keyCol in firstDvKeyNoNamesColumns)
                     {
                         var hidden = FindHiddenColumns(idv.Schema, keyCol.Key);
-                        idv = new ChooseColumnsByIndexTransform(env, new ChooseColumnsByIndexTransform.Arguments() { Drop = true, Indices = hidden.ToArray() }, idv);
+                        idv = new ChooseColumnsByIndexTransform(env, new ChooseColumnsByIndexTransform.Options() { Drop = true, Indices = hidden.ToArray() }, idv);
                     }
                     return idv;
                 };

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

@@ -246,7 +246,7 @@ private IDataView WrapPerInstance(RoleMappedData perInst)
             }
             else
             {
-                var args = new GenerateNumberTransform.Arguments();
+                var args = new GenerateNumberTransform.Options();
                 args.Columns = new[] { new GenerateNumberTransform.Column() { Name = "Instance" } };
                 args.UseCounter = true;
                 idv = new GenerateNumberTransform(Host, args, idv);

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

@@ -932,7 +932,7 @@ private protected override IDataView CombineOverallMetricsCore(IDataView[] metri
                             idv.Schema[col].Name.Equals(MultiClassClassifierEvaluator.PerClassLogLoss))
                         {
                             idv = new ChooseColumnsByIndexTransform(Host,
-                                new ChooseColumnsByIndexTransform.Arguments() { Drop = true, Indices = new[] { col } }, idv);
+                                new ChooseColumnsByIndexTransform.Options() { Drop = true, Indices = new[] { col } }, idv);
                             break;
                         }
                     }

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

@@ -522,7 +522,7 @@ private IDataView ExtractRelevantIndex(IDataView data)
                     output = LambdaColumnMapper.Create(Host, "Quantile Regression", output, name, name, type, NumberType.R8,
                         (in VBuffer<Double> src, ref Double dst) => dst = src.GetItemOrDefault(index));
                     output = new ChooseColumnsByIndexTransform(Host,
-                        new ChooseColumnsByIndexTransform.Arguments() { Drop = true, Indices = new[] { i } }, output);
+                        new ChooseColumnsByIndexTransform.Options() { Drop = true, Indices = new[] { i } }, output);
                 }
             }
             return output;

src/Microsoft.ML.Data/TrainCatalog.cs

@@ -46,14 +46,14 @@ public abstract class TrainCatalogBase
 
             EnsureStratificationColumn(ref data, ref stratificationColumn, seed);
 
-            var trainFilter = new RangeFilter(Host, new RangeFilter.Arguments()
+            var trainFilter = new RangeFilter(Host, new RangeFilter.Options()
             {
                 Column = stratificationColumn,
                 Min = 0,
                 Max = testFraction,
                 Complement = true
             }, data);
-            var testFilter = new RangeFilter(Host, new RangeFilter.Arguments()
+            var testFilter = new RangeFilter(Host, new RangeFilter.Options()
             {
                 Column = stratificationColumn,
                 Min = 0,
@@ -81,14 +81,14 @@ protected internal (IDataView scoredTestSet, ITransformer model)[] CrossValidate
             Func<int, (IDataView scores, ITransformer model)> foldFunction =
                 fold =>
                 {
-                    var trainFilter = new RangeFilter(Host, new RangeFilter.Arguments
+                    var trainFilter = new RangeFilter(Host, new RangeFilter.Options
                     {
                         Column = stratificationColumn,
                         Min = (double)fold / numFolds,
                         Max = (double)(fold + 1) / numFolds,
                         Complement = true
                     }, data);
-                    var testFilter = new RangeFilter(Host, new RangeFilter.Arguments
+                    var testFilter = new RangeFilter(Host, new RangeFilter.Options
                     {
                         Column = stratificationColumn,
                         Min = (double)fold / numFolds,