diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/Calibrator.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/Calibrator.cs index 96339d44fa..865fba994f 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/Calibrator.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/Calibrator.cs @@ -1,6 +1,6 @@ using Microsoft.ML.Calibrator; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using System; using System.Linq; diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/ConcatTransform.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/ConcatTransform.cs index 9ac39e2cd4..8f1cd6e06e 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/ConcatTransform.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/ConcatTransform.cs @@ -1,5 +1,4 @@ using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; using Microsoft.ML.Transforms; using System; using System.Collections.Generic; diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/FastTreeRegression.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/FastTreeRegression.cs index 634513c6de..2fcd6f41f4 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/FastTreeRegression.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/FastTreeRegression.cs @@ -1,5 +1,4 @@ -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Data; +using Microsoft.ML.Data; using System; using System.Collections.Generic; diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/FeatureContributionCalculationTransform.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/FeatureContributionCalculationTransform.cs index 3daf76f856..c7ebf84504 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/FeatureContributionCalculationTransform.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/FeatureContributionCalculationTransform.cs @@ -1,5 +1,4 @@ using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; using System; namespace Microsoft.ML.Samples.Dynamic diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/FeatureSelectionTransform.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/FeatureSelectionTransform.cs index f0d0442d42..f7d922db30 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/FeatureSelectionTransform.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/FeatureSelectionTransform.cs @@ -1,5 +1,4 @@ using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; using System; using System.Collections.Generic; diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/FieldAwareFactorizationMachine.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/FieldAwareFactorizationMachine.cs index eeffd8214e..5b22c7d416 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/FieldAwareFactorizationMachine.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/FieldAwareFactorizationMachine.cs @@ -1,8 +1,5 @@ -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.FactorizationMachine; +using Microsoft.ML.Data; using System; -using System.Linq; - namespace Microsoft.ML.Samples.Dynamic { public class FFM_BinaryClassificationExample diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/GeneralizedAdditiveModels.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/GeneralizedAdditiveModels.cs index ae05e606d4..81f8d7a306 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/GeneralizedAdditiveModels.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/GeneralizedAdditiveModels.cs @@ -1,4 +1,4 @@ -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; using System; using System.Linq; diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/IidChangePointDetectorTransform.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/IidChangePointDetectorTransform.cs index 773410e542..8d1df4632e 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/IidChangePointDetectorTransform.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/IidChangePointDetectorTransform.cs @@ -1,13 +1,15 @@ +// 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.Linq; using System.Collections.Generic; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.TimeSeriesProcessing; +using Microsoft.ML.Data; +using Microsoft.ML.TimeSeriesProcessing; using Microsoft.ML.Core.Data; using Microsoft.ML.TimeSeries; using System.IO; -using Microsoft.ML.Data; namespace Microsoft.ML.Samples.Dynamic { diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/IidSpikeDetectorTransform.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/IidSpikeDetectorTransform.cs index 308c47932f..2d51bdba64 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/IidSpikeDetectorTransform.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/IidSpikeDetectorTransform.cs @@ -3,9 +3,7 @@ using System.Linq; using System.Collections.Generic; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.TimeSeriesProcessing; +using Microsoft.ML.TimeSeriesProcessing; using Microsoft.ML.Core.Data; using Microsoft.ML.TimeSeries; diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/KMeans.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/KMeans.cs index fc678ed24d..2dff3d5b3c 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/KMeans.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/KMeans.cs @@ -1,5 +1,4 @@ using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; using System; namespace Microsoft.ML.Samples.Dynamic diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/KeyToValue_Term.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/KeyToValue_Term.cs index 5ba169b38e..6acb34fc42 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/KeyToValue_Term.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/KeyToValue_Term.cs @@ -1,6 +1,4 @@ using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using Microsoft.ML.Transforms.Conversions; using Microsoft.ML.Transforms.Text; using System; diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/LdaTransform.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/LdaTransform.cs index 79c074e7b3..c0d9637bd1 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/LdaTransform.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/LdaTransform.cs @@ -1,6 +1,4 @@ using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using System; using System.Collections.Generic; diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/MatrixFactorization.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/MatrixFactorization.cs index f8603ea524..a6bfd4ce57 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/MatrixFactorization.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/MatrixFactorization.cs @@ -1,5 +1,4 @@ using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; using System; using System.Collections.Generic; diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/NgramExtraction.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/NgramExtraction.cs index 5d1567753e..f7438a8494 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/NgramExtraction.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/NgramExtraction.cs @@ -1,6 +1,4 @@ using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using System; using System.Collections.Generic; diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/Normalizer.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/Normalizer.cs index a8de69a04d..50fe5ccf44 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/Normalizer.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/Normalizer.cs @@ -1,5 +1,4 @@ using Microsoft.ML.Data; -using Microsoft.ML.Runtime; using Microsoft.ML.Transforms.Normalizers; using System; using System.Collections.Generic; diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/OnnxTransform.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/OnnxTransform.cs index bb7b9a70c8..be5b9bcec0 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/OnnxTransform.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/OnnxTransform.cs @@ -1,6 +1,5 @@ using Microsoft.ML.Data; using Microsoft.ML.OnnxRuntime; -using Microsoft.ML.Runtime.Data; using Microsoft.ML.Transforms; using System; using System.Linq; diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/PermutationFeatureImportance/PFIHelper.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/PermutationFeatureImportance/PFIHelper.cs index 268864a788..07a1ac2225 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/PermutationFeatureImportance/PFIHelper.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/PermutationFeatureImportance/PFIHelper.cs @@ -1,5 +1,5 @@ -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Learners; +using Microsoft.ML.Data; +using Microsoft.ML.Learners; using Microsoft.ML.Trainers.HalLearners; using System; using System.Linq; diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/PermutationFeatureImportance/PfiBinaryClassificationExample.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/PermutationFeatureImportance/PfiBinaryClassificationExample.cs index 250bbcd8d4..5c8c38649c 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/PermutationFeatureImportance/PfiBinaryClassificationExample.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/PermutationFeatureImportance/PfiBinaryClassificationExample.cs @@ -1,4 +1,4 @@ -using Microsoft.ML.Runtime.Learners; +using Microsoft.ML.Learners; using System; using System.Linq; diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/ProjectionTransforms.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/ProjectionTransforms.cs index b6246ab746..d16a5528e6 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/ProjectionTransforms.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/ProjectionTransforms.cs @@ -1,6 +1,4 @@ -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Data; +using Microsoft.ML.Data; using System; using System.Collections.Generic; using System.Linq; diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/SDCA.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/SDCA.cs index 09dea18ff1..499327c437 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/SDCA.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/SDCA.cs @@ -1,4 +1,4 @@ -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; using System; using System.Linq; diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/SsaChangePointDetectorTransform.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/SsaChangePointDetectorTransform.cs index d52fffb44a..aa94a0b49d 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/SsaChangePointDetectorTransform.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/SsaChangePointDetectorTransform.cs @@ -1,7 +1,6 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.TimeSeriesProcessing; +using Microsoft.ML.TimeSeriesProcessing; using Microsoft.ML.TimeSeries; using System; using System.Collections.Generic; diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/SsaSpikeDetectorTransform.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/SsaSpikeDetectorTransform.cs index bd6c81bb2a..090e680125 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/SsaSpikeDetectorTransform.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/SsaSpikeDetectorTransform.cs @@ -1,7 +1,6 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.TimeSeriesProcessing; +using Microsoft.ML.TimeSeriesProcessing; using Microsoft.ML.TimeSeries; using System; using System.Collections.Generic; diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/TensorFlowTransform.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/TensorFlowTransform.cs index 8c9fb477ba..46eb3f5242 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/TensorFlowTransform.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/TensorFlowTransform.cs @@ -1,5 +1,4 @@ using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; using System; using System.Linq; diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/TextTransform.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/TextTransform.cs index 23933a03a2..5d3ab034de 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/TextTransform.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/TextTransform.cs @@ -1,6 +1,4 @@ -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Data; +using Microsoft.ML.Data; using Microsoft.ML.Transforms.Text; using System; using System.Collections.Generic; diff --git a/docs/samples/Microsoft.ML.Samples/Static/AveragedPerceptronBinaryClassification.cs b/docs/samples/Microsoft.ML.Samples/Static/AveragedPerceptronBinaryClassification.cs index d2359526e9..68e4b35015 100644 --- a/docs/samples/Microsoft.ML.Samples/Static/AveragedPerceptronBinaryClassification.cs +++ b/docs/samples/Microsoft.ML.Samples/Static/AveragedPerceptronBinaryClassification.cs @@ -1,7 +1,6 @@ -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; using Microsoft.ML.StaticPipe; using Microsoft.ML.Transforms; -using Microsoft.ML.Transforms.Categorical; using System; namespace Microsoft.ML.Samples.Static diff --git a/docs/samples/Microsoft.ML.Samples/Static/FastTreeBinaryClassification.cs b/docs/samples/Microsoft.ML.Samples/Static/FastTreeBinaryClassification.cs index d28b7c79de..041d297645 100644 --- a/docs/samples/Microsoft.ML.Samples/Static/FastTreeBinaryClassification.cs +++ b/docs/samples/Microsoft.ML.Samples/Static/FastTreeBinaryClassification.cs @@ -1,8 +1,6 @@ -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; using Microsoft.ML.StaticPipe; using Microsoft.ML.Transforms; -using Microsoft.ML.Transforms.Categorical; -using Microsoft.ML.Transforms.FeatureSelection; using System; namespace Microsoft.ML.Samples.Static diff --git a/docs/samples/Microsoft.ML.Samples/Static/FastTreeRegression.cs b/docs/samples/Microsoft.ML.Samples/Static/FastTreeRegression.cs index ba271b25ce..990bad111a 100644 --- a/docs/samples/Microsoft.ML.Samples/Static/FastTreeRegression.cs +++ b/docs/samples/Microsoft.ML.Samples/Static/FastTreeRegression.cs @@ -1,4 +1,4 @@ -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.StaticPipe; using System; diff --git a/docs/samples/Microsoft.ML.Samples/Static/FeatureSelectionTransform.cs b/docs/samples/Microsoft.ML.Samples/Static/FeatureSelectionTransform.cs index d38f428eea..a621cbbb14 100644 --- a/docs/samples/Microsoft.ML.Samples/Static/FeatureSelectionTransform.cs +++ b/docs/samples/Microsoft.ML.Samples/Static/FeatureSelectionTransform.cs @@ -1,5 +1,4 @@ using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; using Microsoft.ML.StaticPipe; using System; using System.Collections.Generic; diff --git a/docs/samples/Microsoft.ML.Samples/Static/LightGBMBinaryClassification.cs b/docs/samples/Microsoft.ML.Samples/Static/LightGBMBinaryClassification.cs index ce02dc4864..48a374667c 100644 --- a/docs/samples/Microsoft.ML.Samples/Static/LightGBMBinaryClassification.cs +++ b/docs/samples/Microsoft.ML.Samples/Static/LightGBMBinaryClassification.cs @@ -1,6 +1,7 @@ -using Microsoft.ML.LightGBM.StaticPipe; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.LightGBM.StaticPipe; +using Microsoft.ML.Data; using Microsoft.ML.StaticPipe; +using Microsoft.ML.Transforms; using System; namespace Microsoft.ML.Samples.Static diff --git a/docs/samples/Microsoft.ML.Samples/Static/LightGBMRegression.cs b/docs/samples/Microsoft.ML.Samples/Static/LightGBMRegression.cs index 505663190b..7c0ac7c6c6 100644 --- a/docs/samples/Microsoft.ML.Samples/Static/LightGBMRegression.cs +++ b/docs/samples/Microsoft.ML.Samples/Static/LightGBMRegression.cs @@ -1,6 +1,7 @@ -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.LightGBM; using Microsoft.ML.LightGBM.StaticPipe; +using Microsoft.ML.Data; +using Microsoft.ML.LightGBM; +using Microsoft.ML.StaticPipe; using System; namespace Microsoft.ML.Samples.Static diff --git a/docs/samples/Microsoft.ML.Samples/Static/SDCABinaryClassification.cs b/docs/samples/Microsoft.ML.Samples/Static/SDCABinaryClassification.cs index 886342c416..474cec2b31 100644 --- a/docs/samples/Microsoft.ML.Samples/Static/SDCABinaryClassification.cs +++ b/docs/samples/Microsoft.ML.Samples/Static/SDCABinaryClassification.cs @@ -1,8 +1,6 @@ -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; using Microsoft.ML.StaticPipe; using Microsoft.ML.Transforms; -using Microsoft.ML.Transforms.Categorical; -using Microsoft.ML.Transforms.FeatureSelection; using System; namespace Microsoft.ML.Samples.Static diff --git a/docs/samples/Microsoft.ML.Samples/Static/SDCARegression.cs b/docs/samples/Microsoft.ML.Samples/Static/SDCARegression.cs index 1ebb4cf1db..6efb66008f 100644 --- a/docs/samples/Microsoft.ML.Samples/Static/SDCARegression.cs +++ b/docs/samples/Microsoft.ML.Samples/Static/SDCARegression.cs @@ -1,5 +1,5 @@ -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Learners; +using Microsoft.ML.Data; +using Microsoft.ML.Learners; using Microsoft.ML.StaticPipe; using System; diff --git a/src/Microsoft.ML.Console/Console.cs b/src/Microsoft.ML.Console/Console.cs index 152d65951a..549f222de7 100644 --- a/src/Microsoft.ML.Console/Console.cs +++ b/src/Microsoft.ML.Console/Console.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -namespace Microsoft.ML.Runtime.Tools.Console +namespace Microsoft.ML.Tools.Console { public static class Console { diff --git a/src/Microsoft.ML.Console/Microsoft.ML.Console.csproj b/src/Microsoft.ML.Console/Microsoft.ML.Console.csproj index f7c87c0abd..7fadb9ea75 100644 --- a/src/Microsoft.ML.Console/Microsoft.ML.Console.csproj +++ b/src/Microsoft.ML.Console/Microsoft.ML.Console.csproj @@ -4,7 +4,7 @@ netcoreapp2.1 Exe MML - Microsoft.ML.Runtime.Tools.Console.Console + Microsoft.ML.Tools.Console.Console diff --git a/src/Microsoft.ML.Core/BestFriendAttribute.cs b/src/Microsoft.ML.Core/BestFriendAttribute.cs index 1470f95c34..19c70922e7 100644 --- a/src/Microsoft.ML.Core/BestFriendAttribute.cs +++ b/src/Microsoft.ML.Core/BestFriendAttribute.cs @@ -6,7 +6,7 @@ #if CPUMATH_INFRASTRUCTURE // CpuMath has its own BestFriend and WantsToBeBestFriends attributes for making itself a standalone module -namespace Microsoft.ML.Runtime.Internal.CpuMath.Core +namespace Microsoft.ML.Internal.CpuMath.Core #else // This namespace contains the BestFriend and WantsToBeBestFriends attributes generally used in ML.NET project settings namespace Microsoft.ML diff --git a/src/Microsoft.ML.Core/CommandLine/ArgumentAttribute.cs b/src/Microsoft.ML.Core/CommandLine/ArgumentAttribute.cs index 70f9ec8d98..fdc296d7f8 100644 --- a/src/Microsoft.ML.Core/CommandLine/ArgumentAttribute.cs +++ b/src/Microsoft.ML.Core/CommandLine/ArgumentAttribute.cs @@ -5,7 +5,7 @@ using System; using System.Linq; -namespace Microsoft.ML.Runtime.CommandLine +namespace Microsoft.ML.CommandLine { /// /// Allows control of command line parsing. diff --git a/src/Microsoft.ML.Core/CommandLine/ArgumentType.cs b/src/Microsoft.ML.Core/CommandLine/ArgumentType.cs index 5840615fd5..d27acf9387 100644 --- a/src/Microsoft.ML.Core/CommandLine/ArgumentType.cs +++ b/src/Microsoft.ML.Core/CommandLine/ArgumentType.cs @@ -4,7 +4,7 @@ using System; -namespace Microsoft.ML.Runtime.CommandLine +namespace Microsoft.ML.CommandLine { /// /// Used to control parsing of command line arguments. diff --git a/src/Microsoft.ML.Core/CommandLine/CharCursor.cs b/src/Microsoft.ML.Core/CommandLine/CharCursor.cs index d8a591331c..85a60a7f36 100644 --- a/src/Microsoft.ML.Core/CommandLine/CharCursor.cs +++ b/src/Microsoft.ML.Core/CommandLine/CharCursor.cs @@ -2,9 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.CommandLine +namespace Microsoft.ML.CommandLine { internal sealed class CharCursor { diff --git a/src/Microsoft.ML.Core/CommandLine/CmdLexer.cs b/src/Microsoft.ML.Core/CommandLine/CmdLexer.cs index 7dc81ea8d2..ce4d6ef4d3 100644 --- a/src/Microsoft.ML.Core/CommandLine/CmdLexer.cs +++ b/src/Microsoft.ML.Core/CommandLine/CmdLexer.cs @@ -4,7 +4,7 @@ using System.Text; -namespace Microsoft.ML.Runtime.CommandLine +namespace Microsoft.ML.CommandLine { [BestFriend] internal sealed class CmdLexer diff --git a/src/Microsoft.ML.Core/CommandLine/CmdParser.cs b/src/Microsoft.ML.Core/CommandLine/CmdParser.cs index 30ad079c13..cecb73fb4b 100644 --- a/src/Microsoft.ML.Core/CommandLine/CmdParser.cs +++ b/src/Microsoft.ML.Core/CommandLine/CmdParser.cs @@ -9,12 +9,10 @@ using System.IO; using System.Linq; using System.Reflection; -using System.Runtime.InteropServices; using System.Text; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.CommandLine +namespace Microsoft.ML.CommandLine { /// diff --git a/src/Microsoft.ML.Core/CommandLine/DefaultArgumentAttribute.cs b/src/Microsoft.ML.Core/CommandLine/DefaultArgumentAttribute.cs index 2d676f1ece..12121df9ea 100644 --- a/src/Microsoft.ML.Core/CommandLine/DefaultArgumentAttribute.cs +++ b/src/Microsoft.ML.Core/CommandLine/DefaultArgumentAttribute.cs @@ -4,7 +4,7 @@ using System; -namespace Microsoft.ML.Runtime.CommandLine +namespace Microsoft.ML.CommandLine { /// /// Indicates that this argument is the default argument. diff --git a/src/Microsoft.ML.Core/CommandLine/EnumValueDisplayAttribute.cs b/src/Microsoft.ML.Core/CommandLine/EnumValueDisplayAttribute.cs index b6cf4254ca..9b3652d9b4 100644 --- a/src/Microsoft.ML.Core/CommandLine/EnumValueDisplayAttribute.cs +++ b/src/Microsoft.ML.Core/CommandLine/EnumValueDisplayAttribute.cs @@ -4,7 +4,7 @@ using System; -namespace Microsoft.ML.Runtime.CommandLine +namespace Microsoft.ML.CommandLine { /// /// On an enum value - specifies the display name. diff --git a/src/Microsoft.ML.Core/CommandLine/HideEnumValueAttribute.cs b/src/Microsoft.ML.Core/CommandLine/HideEnumValueAttribute.cs index 964a5cc3f3..078a8abfa8 100644 --- a/src/Microsoft.ML.Core/CommandLine/HideEnumValueAttribute.cs +++ b/src/Microsoft.ML.Core/CommandLine/HideEnumValueAttribute.cs @@ -4,7 +4,7 @@ using System; -namespace Microsoft.ML.Runtime.CommandLine +namespace Microsoft.ML.CommandLine { /// /// On an enum value - indicates that the value should not be shown in help or UI. diff --git a/src/Microsoft.ML.Core/CommandLine/SpecialPurpose.cs b/src/Microsoft.ML.Core/CommandLine/SpecialPurpose.cs index 46423d43d9..491ef4b21c 100644 --- a/src/Microsoft.ML.Core/CommandLine/SpecialPurpose.cs +++ b/src/Microsoft.ML.Core/CommandLine/SpecialPurpose.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -namespace Microsoft.ML.Runtime.CommandLine +namespace Microsoft.ML.CommandLine { [BestFriend] internal static class SpecialPurpose diff --git a/src/Microsoft.ML.Core/ComponentModel/AssemblyLoadingUtils.cs b/src/Microsoft.ML.Core/ComponentModel/AssemblyLoadingUtils.cs index e947776bc9..9358898ea6 100644 --- a/src/Microsoft.ML.Core/ComponentModel/AssemblyLoadingUtils.cs +++ b/src/Microsoft.ML.Core/ComponentModel/AssemblyLoadingUtils.cs @@ -2,13 +2,13 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; using System; using System.IO; using System.IO.Compression; using System.Reflection; -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { [Obsolete("The usage for this is intended for the internal command line utilities and is not intended for anything related to the API. " + "Please consider another way of doing whatever it is you're attempting to accomplish.")] @@ -159,7 +159,7 @@ private static bool ShouldSkipPath(string path) case "neuraltreeevaluator.dll": case "optimizationbuilderdotnet.dll": case "parallelcommunicator.dll": - case "microsoft.ml.runtime.runtests.dll": + case "Microsoft.ML.runtests.dll": case "scopecompiler.dll": case "symsgdnative.dll": case "tbb.dll": diff --git a/src/Microsoft.ML.Core/ComponentModel/ComponentCatalog.cs b/src/Microsoft.ML.Core/ComponentModel/ComponentCatalog.cs index d022a63eab..398e1e1e38 100644 --- a/src/Microsoft.ML.Core/ComponentModel/ComponentCatalog.cs +++ b/src/Microsoft.ML.Core/ComponentModel/ComponentCatalog.cs @@ -2,9 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; using System; using System.Collections.Generic; using System.Linq; @@ -12,7 +12,7 @@ using System.Text.RegularExpressions; // REVIEW: Determine ideal namespace. -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { /// /// This catalogs instantiatable components (aka, loadable classes). Components are registered via diff --git a/src/Microsoft.ML.Core/ComponentModel/ComponentFactory.cs b/src/Microsoft.ML.Core/ComponentModel/ComponentFactory.cs index 25165f62c9..93ebdf6397 100644 --- a/src/Microsoft.ML.Core/ComponentModel/ComponentFactory.cs +++ b/src/Microsoft.ML.Core/ComponentModel/ComponentFactory.cs @@ -4,7 +4,7 @@ using System; -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { /// /// This is a token interface that all component factories must implement. diff --git a/src/Microsoft.ML.Core/ComponentModel/LoadableClassAttribute.cs b/src/Microsoft.ML.Core/ComponentModel/LoadableClassAttribute.cs index bd0be7f84e..7e8ea83e73 100644 --- a/src/Microsoft.ML.Core/ComponentModel/LoadableClassAttribute.cs +++ b/src/Microsoft.ML.Core/ComponentModel/LoadableClassAttribute.cs @@ -5,9 +5,9 @@ using System; using System.Linq; using System.Reflection; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { /// /// Common signature type with no extra parameters. diff --git a/src/Microsoft.ML.Core/Data/ColumnType.cs b/src/Microsoft.ML.Core/Data/ColumnType.cs index 66bfbc6076..a75093ca0e 100644 --- a/src/Microsoft.ML.Core/Data/ColumnType.cs +++ b/src/Microsoft.ML.Core/Data/ColumnType.cs @@ -10,9 +10,9 @@ using System.Reflection; using System.Text; using System.Threading; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// This is the abstract base class for all types in the type system. diff --git a/src/Microsoft.ML.Core/Data/DataKind.cs b/src/Microsoft.ML.Core/Data/DataKind.cs index b52d5d7587..6844f17a05 100644 --- a/src/Microsoft.ML.Core/Data/DataKind.cs +++ b/src/Microsoft.ML.Core/Data/DataKind.cs @@ -5,7 +5,7 @@ using System; using System.Text; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Data type specifier. diff --git a/src/Microsoft.ML.Core/Data/ICommand.cs b/src/Microsoft.ML.Core/Data/ICommand.cs index 44d4c7340b..2e00b8b272 100644 --- a/src/Microsoft.ML.Core/Data/ICommand.cs +++ b/src/Microsoft.ML.Core/Data/ICommand.cs @@ -3,10 +3,10 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Data; -namespace Microsoft.ML.Runtime.Command +namespace Microsoft.ML.Command { /// /// The signature for commands. diff --git a/src/Microsoft.ML.Core/Data/IDataView.cs b/src/Microsoft.ML.Core/Data/IDataView.cs index 51f6400dc0..893b17a26a 100644 --- a/src/Microsoft.ML.Core/Data/IDataView.cs +++ b/src/Microsoft.ML.Core/Data/IDataView.cs @@ -2,11 +2,10 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Data; using System; using System.Collections.Generic; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Legacy interface for schema information. diff --git a/src/Microsoft.ML.Core/Data/IEstimator.cs b/src/Microsoft.ML.Core/Data/IEstimator.cs index 28bda75ff1..6fe0fe200b 100644 --- a/src/Microsoft.ML.Core/Data/IEstimator.cs +++ b/src/Microsoft.ML.Core/Data/IEstimator.cs @@ -3,8 +3,6 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using System.Collections; using System.Collections.Generic; using System.Collections.Immutable; diff --git a/src/Microsoft.ML.Core/Data/IFileHandle.cs b/src/Microsoft.ML.Core/Data/IFileHandle.cs index 37b871b7b6..b5b2ae8183 100644 --- a/src/Microsoft.ML.Core/Data/IFileHandle.cs +++ b/src/Microsoft.ML.Core/Data/IFileHandle.cs @@ -5,9 +5,9 @@ using System; using System.Collections.Generic; using System.IO; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { /// /// A file handle. diff --git a/src/Microsoft.ML.Core/Data/IHostEnvironment.cs b/src/Microsoft.ML.Core/Data/IHostEnvironment.cs index bfff2459ef..72639c6ac2 100644 --- a/src/Microsoft.ML.Core/Data/IHostEnvironment.cs +++ b/src/Microsoft.ML.Core/Data/IHostEnvironment.cs @@ -5,7 +5,7 @@ using System; using System.ComponentModel.Composition.Hosting; -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { /// /// A channel provider can create new channels and generic information pipes. diff --git a/src/Microsoft.ML.Core/Data/IProgressChannel.cs b/src/Microsoft.ML.Core/Data/IProgressChannel.cs index 924e7806f9..26dd7e1831 100644 --- a/src/Microsoft.ML.Core/Data/IProgressChannel.cs +++ b/src/Microsoft.ML.Core/Data/IProgressChannel.cs @@ -4,7 +4,7 @@ using System; -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { /// /// This is a factory interface for . diff --git a/src/Microsoft.ML.Core/Data/IRowToRowMapper.cs b/src/Microsoft.ML.Core/Data/IRowToRowMapper.cs index 29de619946..4f0a541363 100644 --- a/src/Microsoft.ML.Core/Data/IRowToRowMapper.cs +++ b/src/Microsoft.ML.Core/Data/IRowToRowMapper.cs @@ -5,7 +5,7 @@ using Microsoft.ML.Data; using System; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// This interface maps an input to an output . Typically, the output contains diff --git a/src/Microsoft.ML.Core/Data/ISchemaBindableMapper.cs b/src/Microsoft.ML.Core/Data/ISchemaBindableMapper.cs index ff005d157d..5ae835fe8c 100644 --- a/src/Microsoft.ML.Core/Data/ISchemaBindableMapper.cs +++ b/src/Microsoft.ML.Core/Data/ISchemaBindableMapper.cs @@ -5,7 +5,7 @@ using Microsoft.ML.Data; using System.Collections.Generic; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// A mapper that can be bound to a (which is an ISchema, with mappings from column kinds diff --git a/src/Microsoft.ML.Core/Data/IValueMapper.cs b/src/Microsoft.ML.Core/Data/IValueMapper.cs index f5e194cd80..dcdf6706c7 100644 --- a/src/Microsoft.ML.Core/Data/IValueMapper.cs +++ b/src/Microsoft.ML.Core/Data/IValueMapper.cs @@ -2,9 +2,7 @@ // 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.Runtime.Data +namespace Microsoft.ML.Data { /// /// Delegate type to map/convert a value. diff --git a/src/Microsoft.ML.Core/Data/InPredicate.cs b/src/Microsoft.ML.Core/Data/InPredicate.cs index 74d16e906d..3c35bf600a 100644 --- a/src/Microsoft.ML.Core/Data/InPredicate.cs +++ b/src/Microsoft.ML.Core/Data/InPredicate.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { public delegate bool InPredicate(in T value); } diff --git a/src/Microsoft.ML.Core/Data/LinkedRootCursorBase.cs b/src/Microsoft.ML.Core/Data/LinkedRootCursorBase.cs index 9025e27af4..efb785a835 100644 --- a/src/Microsoft.ML.Core/Data/LinkedRootCursorBase.cs +++ b/src/Microsoft.ML.Core/Data/LinkedRootCursorBase.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Base class for a cursor has an input cursor, but still needs to do work on diff --git a/src/Microsoft.ML.Core/Data/LinkedRowFilterCursorBase.cs b/src/Microsoft.ML.Core/Data/LinkedRowFilterCursorBase.cs index 67f66b2103..fa35240ad1 100644 --- a/src/Microsoft.ML.Core/Data/LinkedRowFilterCursorBase.cs +++ b/src/Microsoft.ML.Core/Data/LinkedRowFilterCursorBase.cs @@ -2,9 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Data; - -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Base class for creating a cursor of rows that filters out some input rows. diff --git a/src/Microsoft.ML.Core/Data/LinkedRowRootCursorBase.cs b/src/Microsoft.ML.Core/Data/LinkedRowRootCursorBase.cs index fb045ec6e4..1f427ddeb9 100644 --- a/src/Microsoft.ML.Core/Data/LinkedRowRootCursorBase.cs +++ b/src/Microsoft.ML.Core/Data/LinkedRowRootCursorBase.cs @@ -2,9 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Data; - -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// A base class for a that has an input cursor, but still needs diff --git a/src/Microsoft.ML.Core/Data/MetadataBuilder.cs b/src/Microsoft.ML.Core/Data/MetadataBuilder.cs index 06bf090567..54907bc137 100644 --- a/src/Microsoft.ML.Core/Data/MetadataBuilder.cs +++ b/src/Microsoft.ML.Core/Data/MetadataBuilder.cs @@ -2,9 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; using System; using System.Collections.Generic; using System.Linq; diff --git a/src/Microsoft.ML.Core/Data/MetadataUtils.cs b/src/Microsoft.ML.Core/Data/MetadataUtils.cs index cbb8d7bd2f..efa22d134a 100644 --- a/src/Microsoft.ML.Core/Data/MetadataUtils.cs +++ b/src/Microsoft.ML.Core/Data/MetadataUtils.cs @@ -9,9 +9,7 @@ using System.Linq; using System.Threading; using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; namespace Microsoft.ML.Data { diff --git a/src/Microsoft.ML.Core/Data/ProgressReporter.cs b/src/Microsoft.ML.Core/Data/ProgressReporter.cs index 191364e2a3..e49c559571 100644 --- a/src/Microsoft.ML.Core/Data/ProgressReporter.cs +++ b/src/Microsoft.ML.Core/Data/ProgressReporter.cs @@ -7,9 +7,9 @@ using System.Collections.Generic; using System.Linq; using System.Threading; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// The progress reporting classes used by descendants. diff --git a/src/Microsoft.ML.Core/Data/ReadOnlyMemoryUtils.cs b/src/Microsoft.ML.Core/Data/ReadOnlyMemoryUtils.cs index 20ebb85b04..8d20ebcd21 100644 --- a/src/Microsoft.ML.Core/Data/ReadOnlyMemoryUtils.cs +++ b/src/Microsoft.ML.Core/Data/ReadOnlyMemoryUtils.cs @@ -2,13 +2,13 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; using System; using System.Collections.Generic; using System.Runtime.InteropServices; using System.Text; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { [BestFriend] internal static class ReadOnlyMemoryUtils diff --git a/src/Microsoft.ML.Core/Data/RoleMappedSchema.cs b/src/Microsoft.ML.Core/Data/RoleMappedSchema.cs index 643136b6e0..8c4c7318c0 100644 --- a/src/Microsoft.ML.Core/Data/RoleMappedSchema.cs +++ b/src/Microsoft.ML.Core/Data/RoleMappedSchema.cs @@ -4,9 +4,9 @@ using System.Collections.Generic; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Encapsulates an plus column role mapping information. The purpose of role mappings is to diff --git a/src/Microsoft.ML.Core/Data/RootCursorBase.cs b/src/Microsoft.ML.Core/Data/RootCursorBase.cs index 15c0b501ff..dae6c32888 100644 --- a/src/Microsoft.ML.Core/Data/RootCursorBase.cs +++ b/src/Microsoft.ML.Core/Data/RootCursorBase.cs @@ -2,10 +2,7 @@ // 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 Microsoft.ML.Data; - -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { // REVIEW: Since each cursor will create a channel, it would be great that the RootCursorBase takes // ownership of the channel so the derived classes don't have to. diff --git a/src/Microsoft.ML.Core/Data/RowId.cs b/src/Microsoft.ML.Core/Data/RowId.cs index 09a5fa2d25..c5b7795a07 100644 --- a/src/Microsoft.ML.Core/Data/RowId.cs +++ b/src/Microsoft.ML.Core/Data/RowId.cs @@ -4,9 +4,9 @@ using System; using System.Runtime.CompilerServices; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// A structure serving as a sixteen-byte unsigned integer. It is used as the row id of . diff --git a/src/Microsoft.ML.Core/Data/Schema.cs b/src/Microsoft.ML.Core/Data/Schema.cs index 700cac4f3e..b2fb948f37 100644 --- a/src/Microsoft.ML.Core/Data/Schema.cs +++ b/src/Microsoft.ML.Core/Data/Schema.cs @@ -2,9 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; using System; using System.Collections; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Core/Data/SchemaBuilder.cs b/src/Microsoft.ML.Core/Data/SchemaBuilder.cs index 711360ac79..41f109530f 100644 --- a/src/Microsoft.ML.Core/Data/SchemaBuilder.cs +++ b/src/Microsoft.ML.Core/Data/SchemaBuilder.cs @@ -2,11 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using System; using System.Collections.Generic; -using System.Text; namespace Microsoft.ML.Data { diff --git a/src/Microsoft.ML.Core/Data/SchemaDebuggerProxy.cs b/src/Microsoft.ML.Core/Data/SchemaDebuggerProxy.cs index a6fe722741..0f0116af8f 100644 --- a/src/Microsoft.ML.Core/Data/SchemaDebuggerProxy.cs +++ b/src/Microsoft.ML.Core/Data/SchemaDebuggerProxy.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; using System.Collections.Generic; using System.Linq; diff --git a/src/Microsoft.ML.Core/Data/ServerChannel.cs b/src/Microsoft.ML.Core/Data/ServerChannel.cs index a9b33d1986..c66fcd3980 100644 --- a/src/Microsoft.ML.Core/Data/ServerChannel.cs +++ b/src/Microsoft.ML.Core/Data/ServerChannel.cs @@ -5,10 +5,10 @@ using System; using System.Collections.Generic; using System.Reflection; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { /// /// Instances of this class are used to set up a bundle of named delegates. These diff --git a/src/Microsoft.ML.Core/Data/SynchronizedCursorBase.cs b/src/Microsoft.ML.Core/Data/SynchronizedCursorBase.cs index 91549ab047..47ee841fb5 100644 --- a/src/Microsoft.ML.Core/Data/SynchronizedCursorBase.cs +++ b/src/Microsoft.ML.Core/Data/SynchronizedCursorBase.cs @@ -4,7 +4,7 @@ using Microsoft.ML.Data; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Base class for creating a cursor on top of another cursor that does not add or remove rows. diff --git a/src/Microsoft.ML.Core/Data/VBuffer.cs b/src/Microsoft.ML.Core/Data/VBuffer.cs index a86f0bdae4..949857bc2b 100644 --- a/src/Microsoft.ML.Core/Data/VBuffer.cs +++ b/src/Microsoft.ML.Core/Data/VBuffer.cs @@ -4,9 +4,9 @@ using System; using System.Collections.Generic; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// A buffer that supports both dense and sparse representations. This is the diff --git a/src/Microsoft.ML.Core/Data/VBufferEditor.cs b/src/Microsoft.ML.Core/Data/VBufferEditor.cs index 8da19b641f..1dafac0fa5 100644 --- a/src/Microsoft.ML.Core/Data/VBufferEditor.cs +++ b/src/Microsoft.ML.Core/Data/VBufferEditor.cs @@ -4,7 +4,7 @@ using System; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Various methods for creating instances. diff --git a/src/Microsoft.ML.Core/Data/WrappingRow.cs b/src/Microsoft.ML.Core/Data/WrappingRow.cs index 4022778945..f6568cf205 100644 --- a/src/Microsoft.ML.Core/Data/WrappingRow.cs +++ b/src/Microsoft.ML.Core/Data/WrappingRow.cs @@ -4,7 +4,7 @@ using System; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Convenient base class for implementors that wrap a single diff --git a/src/Microsoft.ML.Core/EntryPoints/EntryPointModuleAttribute.cs b/src/Microsoft.ML.Core/EntryPoints/EntryPointModuleAttribute.cs index 0163222fc1..175e7cb09a 100644 --- a/src/Microsoft.ML.Core/EntryPoints/EntryPointModuleAttribute.cs +++ b/src/Microsoft.ML.Core/EntryPoints/EntryPointModuleAttribute.cs @@ -4,7 +4,7 @@ using System; -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { /// /// This is a signature for classes that are 'holders' of entry points and components. diff --git a/src/Microsoft.ML.Core/EntryPoints/EntryPointUtils.cs b/src/Microsoft.ML.Core/EntryPoints/EntryPointUtils.cs index a7c3ddd298..f03048f8af 100644 --- a/src/Microsoft.ML.Core/EntryPoints/EntryPointUtils.cs +++ b/src/Microsoft.ML.Core/EntryPoints/EntryPointUtils.cs @@ -3,12 +3,12 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; using System; using System.Linq; -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { [BestFriend] internal static class EntryPointUtils diff --git a/src/Microsoft.ML.Core/EntryPoints/ModuleArgs.cs b/src/Microsoft.ML.Core/EntryPoints/ModuleArgs.cs index 3ed68ae056..1308008c6e 100644 --- a/src/Microsoft.ML.Core/EntryPoints/ModuleArgs.cs +++ b/src/Microsoft.ML.Core/EntryPoints/ModuleArgs.cs @@ -4,15 +4,11 @@ using System; using System.Collections.Generic; -using System.Diagnostics; using System.Linq; -using System.Net.Sockets; -using System.Reflection; using System.Text; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Data; -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { /// /// This class defines attributes to annotate module inputs, outputs, entry points etc. when defining diff --git a/src/Microsoft.ML.Core/EntryPoints/PredictorModel.cs b/src/Microsoft.ML.Core/EntryPoints/PredictorModel.cs index 8a9117c7b4..30872a5faa 100644 --- a/src/Microsoft.ML.Core/EntryPoints/PredictorModel.cs +++ b/src/Microsoft.ML.Core/EntryPoints/PredictorModel.cs @@ -2,11 +2,10 @@ // 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.IO; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { /// /// Base type for standard predictor model port type. diff --git a/src/Microsoft.ML.Core/EntryPoints/TransformModel.cs b/src/Microsoft.ML.Core/EntryPoints/TransformModel.cs index 2e025019ff..110c75c7aa 100644 --- a/src/Microsoft.ML.Core/EntryPoints/TransformModel.cs +++ b/src/Microsoft.ML.Core/EntryPoints/TransformModel.cs @@ -2,12 +2,10 @@ // 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.IO; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { /// /// Interface for standard transform model port type. diff --git a/src/Microsoft.ML.Core/Environment/ConsoleEnvironment.cs b/src/Microsoft.ML.Core/Environment/ConsoleEnvironment.cs index 4dfd92b11f..057969c81f 100644 --- a/src/Microsoft.ML.Core/Environment/ConsoleEnvironment.cs +++ b/src/Microsoft.ML.Core/Environment/ConsoleEnvironment.cs @@ -9,7 +9,7 @@ using System.Linq; using System.Threading; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { using Stopwatch = System.Diagnostics.Stopwatch; diff --git a/src/Microsoft.ML.Core/Environment/HostEnvironmentBase.cs b/src/Microsoft.ML.Core/Environment/HostEnvironmentBase.cs index 0641d28369..3f1da929bd 100644 --- a/src/Microsoft.ML.Core/Environment/HostEnvironmentBase.cs +++ b/src/Microsoft.ML.Core/Environment/HostEnvironmentBase.cs @@ -9,7 +9,7 @@ using System.ComponentModel.Composition.Hosting; using System.IO; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Base class for channel providers. This is a common base class for. diff --git a/src/Microsoft.ML.Core/Environment/TelemetryMessage.cs b/src/Microsoft.ML.Core/Environment/TelemetryMessage.cs index 72b08e2715..57762bfdf1 100644 --- a/src/Microsoft.ML.Core/Environment/TelemetryMessage.cs +++ b/src/Microsoft.ML.Core/Environment/TelemetryMessage.cs @@ -8,7 +8,7 @@ using System.Text; using System.Threading.Tasks; -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { /// /// A telemetry message. diff --git a/src/Microsoft.ML.Core/Prediction/IPredictor.cs b/src/Microsoft.ML.Core/Prediction/IPredictor.cs index 6bd1ac2056..682cec417d 100644 --- a/src/Microsoft.ML.Core/Prediction/IPredictor.cs +++ b/src/Microsoft.ML.Core/Prediction/IPredictor.cs @@ -2,9 +2,7 @@ // 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.Runtime +namespace Microsoft.ML { /// /// Type of prediction task diff --git a/src/Microsoft.ML.Core/Prediction/ITrainer.cs b/src/Microsoft.ML.Core/Prediction/ITrainer.cs index 5e796aa602..ad5a0b2539 100644 --- a/src/Microsoft.ML.Core/Prediction/ITrainer.cs +++ b/src/Microsoft.ML.Core/Prediction/ITrainer.cs @@ -2,10 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; -using System; +using Microsoft.ML.Data; -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { // REVIEW: Would be nice if the registration under SignatureTrainer were automatic // given registration for one of the "sub-class" signatures. diff --git a/src/Microsoft.ML.Core/Prediction/ITree.cs b/src/Microsoft.ML.Core/Prediction/ITree.cs index 67642ecfc5..9b07acdef7 100644 --- a/src/Microsoft.ML.Core/Prediction/ITree.cs +++ b/src/Microsoft.ML.Core/Prediction/ITree.cs @@ -2,10 +2,9 @@ // 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; -namespace Microsoft.ML.Runtime.TreePredictor +namespace Microsoft.ML.TreePredictor { // The interfaces contained herein are meant to allow tree visualizer to run without an explicit dependency // on FastTree, so as to allow it greater generality. These should probably be moved somewhere else, but where? diff --git a/src/Microsoft.ML.Core/Prediction/TrainContext.cs b/src/Microsoft.ML.Core/Prediction/TrainContext.cs index e5e4bbad1c..ff37caf598 100644 --- a/src/Microsoft.ML.Core/Prediction/TrainContext.cs +++ b/src/Microsoft.ML.Core/Prediction/TrainContext.cs @@ -2,9 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { /// /// Holds information relevant to trainers. Instances of this class are meant to be constructed and passed diff --git a/src/Microsoft.ML.Core/Prediction/TrainerInfo.cs b/src/Microsoft.ML.Core/Prediction/TrainerInfo.cs index 4f97c0c893..53398bc651 100644 --- a/src/Microsoft.ML.Core/Prediction/TrainerInfo.cs +++ b/src/Microsoft.ML.Core/Prediction/TrainerInfo.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { /// /// Instances of this class posses information about trainers, in terms of their requirements and capabilities. diff --git a/src/Microsoft.ML.Core/Properties/AssemblyInfo.cs b/src/Microsoft.ML.Core/Properties/AssemblyInfo.cs index 352ca8bb2f..58bda21829 100644 --- a/src/Microsoft.ML.Core/Properties/AssemblyInfo.cs +++ b/src/Microsoft.ML.Core/Properties/AssemblyInfo.cs @@ -33,7 +33,7 @@ [assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.PCA" + PublicKey.Value)] [assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.PipelineInference" + PublicKey.Value)] [assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.Recommender" + PublicKey.Value)] -[assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.Runtime.ImageAnalytics" + PublicKey.Value)] +[assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.ImageAnalytics" + PublicKey.Value)] [assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.Scoring" + PublicKey.Value)] [assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.StandardLearners" + PublicKey.Value)] [assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.Sweeper" + PublicKey.Value)] diff --git a/src/Microsoft.ML.Core/PublicKey.cs b/src/Microsoft.ML.Core/PublicKey.cs index 9a944c3d18..63718c3f8e 100644 --- a/src/Microsoft.ML.Core/PublicKey.cs +++ b/src/Microsoft.ML.Core/PublicKey.cs @@ -7,8 +7,8 @@ namespace Microsoft.ML #else // CpuMath module has its own PublicKey for isolating itself from Microsoft.ML.Core -// Note that CpuMath uses its own BestFriend defined in Microsoft.ML.Runtime.Internal.CpuMath.Core. -namespace Microsoft.ML.Runtime.Internal.CpuMath.Core +// Note that CpuMath uses its own BestFriend defined in Microsoft.ML.Internal.CpuMath.Core. +namespace Microsoft.ML.Internal.CpuMath.Core #endif { [BestFriend] diff --git a/src/Microsoft.ML.Core/Utilities/BigArray.cs b/src/Microsoft.ML.Core/Utilities/BigArray.cs index 3bfb4f688f..bda630cbc0 100644 --- a/src/Microsoft.ML.Core/Utilities/BigArray.cs +++ b/src/Microsoft.ML.Core/Utilities/BigArray.cs @@ -6,7 +6,7 @@ using System.Collections; using System.Collections.Generic; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { /// /// An array-like data structure that supports storing more than diff --git a/src/Microsoft.ML.Core/Utilities/BinFinder.cs b/src/Microsoft.ML.Core/Utilities/BinFinder.cs index cdfd0ad08b..642aeedd98 100644 --- a/src/Microsoft.ML.Core/Utilities/BinFinder.cs +++ b/src/Microsoft.ML.Core/Utilities/BinFinder.cs @@ -7,7 +7,7 @@ using System; using System.Collections.Generic; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { [BestFriend] internal abstract class BinFinderBase @@ -273,7 +273,7 @@ public static Double GetSplitValue(Double a, Double b) } } -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { // This needs to be large enough to represent a product of 2 ints without losing precision using EnergyType = System.Int64; @@ -525,7 +525,7 @@ private void UpdatePeg(Peg peg) } } -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { // Reasonable choices are Double and System.Int64. using EnergyType = System.Double; diff --git a/src/Microsoft.ML.Core/Utilities/BitUtils.cs b/src/Microsoft.ML.Core/Utilities/BitUtils.cs index 376b0ac8ef..bd42a8f0f3 100644 --- a/src/Microsoft.ML.Core/Utilities/BitUtils.cs +++ b/src/Microsoft.ML.Core/Utilities/BitUtils.cs @@ -5,7 +5,7 @@ using System; using System.Runtime.CompilerServices; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { internal static partial class Utils { diff --git a/src/Microsoft.ML.Core/Utilities/CharUtils.cs b/src/Microsoft.ML.Core/Utilities/CharUtils.cs index d88197c8e7..089239f1a7 100644 --- a/src/Microsoft.ML.Core/Utilities/CharUtils.cs +++ b/src/Microsoft.ML.Core/Utilities/CharUtils.cs @@ -8,7 +8,7 @@ using System.Runtime.CompilerServices; using System.Threading; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { [BestFriend] internal static class CharUtils diff --git a/src/Microsoft.ML.Core/Utilities/CmdIndenter.cs b/src/Microsoft.ML.Core/Utilities/CmdIndenter.cs index 6b4dbc48db..4866122f05 100644 --- a/src/Microsoft.ML.Core/Utilities/CmdIndenter.cs +++ b/src/Microsoft.ML.Core/Utilities/CmdIndenter.cs @@ -8,9 +8,9 @@ using System.Linq; using System.Text; using System.Threading.Tasks; -using Microsoft.ML.Runtime.CommandLine; +using Microsoft.ML.CommandLine; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { [BestFriend] internal static class CmdIndenter diff --git a/src/Microsoft.ML.Core/Utilities/Contracts.cs b/src/Microsoft.ML.Core/Utilities/Contracts.cs index cda7cbc539..6fc94f6304 100644 --- a/src/Microsoft.ML.Core/Utilities/Contracts.cs +++ b/src/Microsoft.ML.Core/Utilities/Contracts.cs @@ -17,9 +17,9 @@ using System.Threading; #if CPUMATH_INFRASTRUCTURE -namespace Microsoft.ML.Runtime.Internal.CpuMath.Core +namespace Microsoft.ML.Internal.CpuMath.Core #else -namespace Microsoft.ML.Runtime +namespace Microsoft.ML #endif { using Conditional = System.Diagnostics.ConditionalAttribute; diff --git a/src/Microsoft.ML.Core/Utilities/DoubleParser.cs b/src/Microsoft.ML.Core/Utilities/DoubleParser.cs index 4f2ef9ad80..ded68121d9 100644 --- a/src/Microsoft.ML.Core/Utilities/DoubleParser.cs +++ b/src/Microsoft.ML.Core/Utilities/DoubleParser.cs @@ -11,7 +11,7 @@ using System.Linq; using System.Text; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { [BestFriend] internal static class DoubleParser diff --git a/src/Microsoft.ML.Core/Utilities/FixedSizeQueue.cs b/src/Microsoft.ML.Core/Utilities/FixedSizeQueue.cs index 7263304046..ab2d938d22 100644 --- a/src/Microsoft.ML.Core/Utilities/FixedSizeQueue.cs +++ b/src/Microsoft.ML.Core/Utilities/FixedSizeQueue.cs @@ -2,9 +2,7 @@ // 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.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { using Conditional = System.Diagnostics.ConditionalAttribute; diff --git a/src/Microsoft.ML.Core/Utilities/FloatUtils.cs b/src/Microsoft.ML.Core/Utilities/FloatUtils.cs index 06d403da9a..b93541eb3e 100644 --- a/src/Microsoft.ML.Core/Utilities/FloatUtils.cs +++ b/src/Microsoft.ML.Core/Utilities/FloatUtils.cs @@ -6,7 +6,7 @@ using System.Globalization; using System.Runtime.InteropServices; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { [BestFriend] internal static class FloatUtils diff --git a/src/Microsoft.ML.Core/Utilities/HashArray.cs b/src/Microsoft.ML.Core/Utilities/HashArray.cs index 64dced9792..c9f31b5361 100644 --- a/src/Microsoft.ML.Core/Utilities/HashArray.cs +++ b/src/Microsoft.ML.Core/Utilities/HashArray.cs @@ -6,7 +6,7 @@ using System; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { // REVIEW: May want to add an IEnumerable>. diff --git a/src/Microsoft.ML.Core/Utilities/Hashing.cs b/src/Microsoft.ML.Core/Utilities/Hashing.cs index ae36fae95d..8345a319ac 100644 --- a/src/Microsoft.ML.Core/Utilities/Hashing.cs +++ b/src/Microsoft.ML.Core/Utilities/Hashing.cs @@ -3,11 +3,10 @@ // See the LICENSE file in the project root for more information. using System; -using System.Collections.Generic; using System.Runtime.CompilerServices; using System.Text; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { [BestFriend] internal static class Hashing diff --git a/src/Microsoft.ML.Core/Utilities/Heap.cs b/src/Microsoft.ML.Core/Utilities/Heap.cs index 7652163f10..fe1178abd3 100644 --- a/src/Microsoft.ML.Core/Utilities/Heap.cs +++ b/src/Microsoft.ML.Core/Utilities/Heap.cs @@ -5,7 +5,7 @@ using System; using System.Collections.Generic; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { using Conditional = System.Diagnostics.ConditionalAttribute; diff --git a/src/Microsoft.ML.Core/Utilities/HybridMemoryStream.cs b/src/Microsoft.ML.Core/Utilities/HybridMemoryStream.cs index 02f713dd6e..c1db619510 100644 --- a/src/Microsoft.ML.Core/Utilities/HybridMemoryStream.cs +++ b/src/Microsoft.ML.Core/Utilities/HybridMemoryStream.cs @@ -5,7 +5,7 @@ using System; using System.IO; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { using Conditional = System.Diagnostics.ConditionalAttribute; diff --git a/src/Microsoft.ML.Core/Utilities/IndentedTextWriterExtensions.cs b/src/Microsoft.ML.Core/Utilities/IndentedTextWriterExtensions.cs index fe8fd12e96..fd733dc60c 100644 --- a/src/Microsoft.ML.Core/Utilities/IndentedTextWriterExtensions.cs +++ b/src/Microsoft.ML.Core/Utilities/IndentedTextWriterExtensions.cs @@ -4,10 +4,8 @@ using System; using System.CodeDom.Compiler; -using System.IO; -using System.Text; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { [BestFriend] internal static class IndentedTextWriterExtensions diff --git a/src/Microsoft.ML.Core/Utilities/LineParser.cs b/src/Microsoft.ML.Core/Utilities/LineParser.cs index 73d9bb6158..bc8eabcdda 100644 --- a/src/Microsoft.ML.Core/Utilities/LineParser.cs +++ b/src/Microsoft.ML.Core/Utilities/LineParser.cs @@ -5,7 +5,7 @@ using System; using System.Runtime.CompilerServices; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { [BestFriend] internal static class LineParser diff --git a/src/Microsoft.ML.Core/Utilities/LruCache.cs b/src/Microsoft.ML.Core/Utilities/LruCache.cs index e041efde02..ad874b60c1 100644 --- a/src/Microsoft.ML.Core/Utilities/LruCache.cs +++ b/src/Microsoft.ML.Core/Utilities/LruCache.cs @@ -5,7 +5,7 @@ using System.Collections.Generic; using System.Linq; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { /// /// Implements a least recently used cache. diff --git a/src/Microsoft.ML.Core/Utilities/MathUtils.cs b/src/Microsoft.ML.Core/Utilities/MathUtils.cs index 296639d1b3..4517729f3b 100644 --- a/src/Microsoft.ML.Core/Utilities/MathUtils.cs +++ b/src/Microsoft.ML.Core/Utilities/MathUtils.cs @@ -8,7 +8,7 @@ using System.Collections.Generic; using System.Linq; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { /// /// Some useful math methods. diff --git a/src/Microsoft.ML.Core/Utilities/MatrixTransposeOps.cs b/src/Microsoft.ML.Core/Utilities/MatrixTransposeOps.cs index cb945e56a2..2e25599c1d 100644 --- a/src/Microsoft.ML.Core/Utilities/MatrixTransposeOps.cs +++ b/src/Microsoft.ML.Core/Utilities/MatrixTransposeOps.cs @@ -7,7 +7,7 @@ using System.Linq; using System.Threading.Tasks; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { [BestFriend] internal static class MatrixTransposeOps diff --git a/src/Microsoft.ML.Core/Utilities/MinWaiter.cs b/src/Microsoft.ML.Core/Utilities/MinWaiter.cs index fbaf8fb6d6..23af027bc1 100644 --- a/src/Microsoft.ML.Core/Utilities/MinWaiter.cs +++ b/src/Microsoft.ML.Core/Utilities/MinWaiter.cs @@ -5,7 +5,7 @@ using System; using System.Threading; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { /// /// A synchronization primitive meant to address situations where you have a set of diff --git a/src/Microsoft.ML.Core/Utilities/NormStr.cs b/src/Microsoft.ML.Core/Utilities/NormStr.cs index c79e2425d1..5849925ee8 100644 --- a/src/Microsoft.ML.Core/Utilities/NormStr.cs +++ b/src/Microsoft.ML.Core/Utilities/NormStr.cs @@ -8,9 +8,9 @@ using System.Linq; using System.Threading; using System.Text; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { using Conditional = System.Diagnostics.ConditionalAttribute; diff --git a/src/Microsoft.ML.Core/Utilities/ObjectPool.cs b/src/Microsoft.ML.Core/Utilities/ObjectPool.cs index a06202af76..a5a9591fae 100644 --- a/src/Microsoft.ML.Core/Utilities/ObjectPool.cs +++ b/src/Microsoft.ML.Core/Utilities/ObjectPool.cs @@ -6,7 +6,7 @@ using System.Collections.Concurrent; using System.Threading; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { [BestFriend] internal sealed class ObjectPool : ObjectPoolBase where T : class, new() diff --git a/src/Microsoft.ML.Core/Utilities/OrderedWaiter.cs b/src/Microsoft.ML.Core/Utilities/OrderedWaiter.cs index ca0ef23445..5a71c6205d 100644 --- a/src/Microsoft.ML.Core/Utilities/OrderedWaiter.cs +++ b/src/Microsoft.ML.Core/Utilities/OrderedWaiter.cs @@ -5,7 +5,7 @@ using System; using System.Threading; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { /// /// The primary use case for this structure is to impose ordering among diff --git a/src/Microsoft.ML.Core/Utilities/PathUtils.cs b/src/Microsoft.ML.Core/Utilities/PathUtils.cs index 98407e24a1..c10e36b1eb 100644 --- a/src/Microsoft.ML.Core/Utilities/PathUtils.cs +++ b/src/Microsoft.ML.Core/Utilities/PathUtils.cs @@ -6,7 +6,7 @@ using System.IO; using System.Threading; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { internal static partial class Utils { diff --git a/src/Microsoft.ML.Core/Utilities/PlatformUtils.cs b/src/Microsoft.ML.Core/Utilities/PlatformUtils.cs index 2bd8acab3e..16cadbdb5b 100644 --- a/src/Microsoft.ML.Core/Utilities/PlatformUtils.cs +++ b/src/Microsoft.ML.Core/Utilities/PlatformUtils.cs @@ -6,7 +6,7 @@ using System.Collections.ObjectModel; using System.Reflection; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { /// /// Contains extension methods that aid in building cross platform. diff --git a/src/Microsoft.ML.Core/Utilities/Random.cs b/src/Microsoft.ML.Core/Utilities/Random.cs index 50093698b6..c79a22426b 100644 --- a/src/Microsoft.ML.Core/Utilities/Random.cs +++ b/src/Microsoft.ML.Core/Utilities/Random.cs @@ -4,9 +4,9 @@ using System; using System.IO; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { [BestFriend] internal static class RandomUtils diff --git a/src/Microsoft.ML.Core/Utilities/ReservoirSampler.cs b/src/Microsoft.ML.Core/Utilities/ReservoirSampler.cs index 91fc4d3a62..f442fd8e59 100644 --- a/src/Microsoft.ML.Core/Utilities/ReservoirSampler.cs +++ b/src/Microsoft.ML.Core/Utilities/ReservoirSampler.cs @@ -5,9 +5,9 @@ using System; using System.Collections.Generic; using System.Linq; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { /// /// This is an interface for creating samples of a requested size from a stream of data of type . diff --git a/src/Microsoft.ML.Core/Utilities/ResourceManagerUtils.cs b/src/Microsoft.ML.Core/Utilities/ResourceManagerUtils.cs index 9e9c6f80bb..0813dac0fe 100644 --- a/src/Microsoft.ML.Core/Utilities/ResourceManagerUtils.cs +++ b/src/Microsoft.ML.Core/Utilities/ResourceManagerUtils.cs @@ -10,7 +10,7 @@ using System.Threading; using System.Threading.Tasks; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { /// /// This class takes care of downloading resources needed by ML.NET components. Resources are located in diff --git a/src/Microsoft.ML.Core/Utilities/Stats.cs b/src/Microsoft.ML.Core/Utilities/Stats.cs index 26c538084e..c1630158dd 100644 --- a/src/Microsoft.ML.Core/Utilities/Stats.cs +++ b/src/Microsoft.ML.Core/Utilities/Stats.cs @@ -6,7 +6,7 @@ using System; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { /// /// A class containing common statistical functions diff --git a/src/Microsoft.ML.Core/Utilities/Stream.cs b/src/Microsoft.ML.Core/Utilities/Stream.cs index 4fe21e7df7..633ee672f7 100644 --- a/src/Microsoft.ML.Core/Utilities/Stream.cs +++ b/src/Microsoft.ML.Core/Utilities/Stream.cs @@ -9,7 +9,7 @@ using System.Text; using System.Threading; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { internal static partial class Utils { diff --git a/src/Microsoft.ML.Core/Utilities/SubsetStream.cs b/src/Microsoft.ML.Core/Utilities/SubsetStream.cs index 3bf9ad2c9e..022ca28cb1 100644 --- a/src/Microsoft.ML.Core/Utilities/SubsetStream.cs +++ b/src/Microsoft.ML.Core/Utilities/SubsetStream.cs @@ -5,7 +5,7 @@ using System; using System.IO; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { /// /// Returns a "view" stream, which appears to be a possibly truncated diff --git a/src/Microsoft.ML.Core/Utilities/SummaryStatistics.cs b/src/Microsoft.ML.Core/Utilities/SummaryStatistics.cs index 3e36191564..3382885e9c 100644 --- a/src/Microsoft.ML.Core/Utilities/SummaryStatistics.cs +++ b/src/Microsoft.ML.Core/Utilities/SummaryStatistics.cs @@ -4,7 +4,7 @@ using System; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { internal abstract class SummaryStatisticsBase { diff --git a/src/Microsoft.ML.Core/Utilities/SupervisedBinFinder.cs b/src/Microsoft.ML.Core/Utilities/SupervisedBinFinder.cs index 63257823a2..d76a9e578d 100644 --- a/src/Microsoft.ML.Core/Utilities/SupervisedBinFinder.cs +++ b/src/Microsoft.ML.Core/Utilities/SupervisedBinFinder.cs @@ -8,7 +8,7 @@ using System.Collections.Generic; using System.Diagnostics; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { /// /// This class performs discretization of (value, label) pairs into bins in a way that minimizes diff --git a/src/Microsoft.ML.Core/Utilities/TextReaderStream.cs b/src/Microsoft.ML.Core/Utilities/TextReaderStream.cs index 682a0336cb..691876c0c7 100644 --- a/src/Microsoft.ML.Core/Utilities/TextReaderStream.cs +++ b/src/Microsoft.ML.Core/Utilities/TextReaderStream.cs @@ -6,7 +6,7 @@ using System.IO; using System.Text; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { /// /// A readable that is backed by a . diff --git a/src/Microsoft.ML.Core/Utilities/ThreadUtils.cs b/src/Microsoft.ML.Core/Utilities/ThreadUtils.cs index 46a82a4e7c..3585b36f23 100644 --- a/src/Microsoft.ML.Core/Utilities/ThreadUtils.cs +++ b/src/Microsoft.ML.Core/Utilities/ThreadUtils.cs @@ -8,7 +8,7 @@ using System.Threading; using System.Threading.Tasks; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { internal static partial class Utils { diff --git a/src/Microsoft.ML.Core/Utilities/Tree.cs b/src/Microsoft.ML.Core/Utilities/Tree.cs index 8d4c0f7585..cbec20fe8e 100644 --- a/src/Microsoft.ML.Core/Utilities/Tree.cs +++ b/src/Microsoft.ML.Core/Utilities/Tree.cs @@ -5,7 +5,7 @@ using System.Collections; using System.Collections.Generic; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { /// /// The tree structure is simultaneously a tree, and a node in a tree. The interface to diff --git a/src/Microsoft.ML.Core/Utilities/Utils.cs b/src/Microsoft.ML.Core/Utilities/Utils.cs index a84e1b31ee..f5234c69b3 100644 --- a/src/Microsoft.ML.Core/Utilities/Utils.cs +++ b/src/Microsoft.ML.Core/Utilities/Utils.cs @@ -13,7 +13,7 @@ using System.Text.RegularExpressions; using System.Threading; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { [BestFriend] diff --git a/src/Microsoft.ML.Core/Utilities/VBufferUtils.cs b/src/Microsoft.ML.Core/Utilities/VBufferUtils.cs index 974af42339..9120ccbedd 100644 --- a/src/Microsoft.ML.Core/Utilities/VBufferUtils.cs +++ b/src/Microsoft.ML.Core/Utilities/VBufferUtils.cs @@ -4,9 +4,9 @@ using System; using System.Collections.Generic; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { // REVIEW: Consider automatic densification in some of the operations, where appropriate. // REVIEW: Once we do the conversions from Vector/WritableVector, review names of methods, diff --git a/src/Microsoft.ML.CpuMath/AlignedArray.cs b/src/Microsoft.ML.CpuMath/AlignedArray.cs index a303b072e0..25f9457661 100644 --- a/src/Microsoft.ML.CpuMath/AlignedArray.cs +++ b/src/Microsoft.ML.CpuMath/AlignedArray.cs @@ -2,10 +2,10 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Internal.CpuMath.Core; +using Microsoft.ML.Internal.CpuMath.Core; using System; -namespace Microsoft.ML.Runtime.Internal.CpuMath +namespace Microsoft.ML.Internal.CpuMath { /// /// This implements a logical array of floats that is automatically aligned for SSE/AVX operations. diff --git a/src/Microsoft.ML.CpuMath/AlignedMatrix.cs b/src/Microsoft.ML.CpuMath/AlignedMatrix.cs index 6d550fc3fc..9e8c95ae51 100644 --- a/src/Microsoft.ML.CpuMath/AlignedMatrix.cs +++ b/src/Microsoft.ML.CpuMath/AlignedMatrix.cs @@ -4,12 +4,12 @@ using Float = System.Single; -using Microsoft.ML.Runtime.Internal.CpuMath.Core; +using Microsoft.ML.Internal.CpuMath.Core; using System; using System.Collections; using System.Collections.Generic; -namespace Microsoft.ML.Runtime.Internal.CpuMath +namespace Microsoft.ML.Internal.CpuMath { using Conditional = System.Diagnostics.ConditionalAttribute; diff --git a/src/Microsoft.ML.CpuMath/AssemblyInfo.cs b/src/Microsoft.ML.CpuMath/AssemblyInfo.cs index 7710703c29..52b73c15a8 100644 --- a/src/Microsoft.ML.CpuMath/AssemblyInfo.cs +++ b/src/Microsoft.ML.CpuMath/AssemblyInfo.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Internal.CpuMath.Core; +using Microsoft.ML.Internal.CpuMath.Core; using System.Runtime.CompilerServices; [assembly: InternalsVisibleTo("Microsoft.ML.CpuMath.UnitTests.netstandard" + PublicKey.TestValue)] diff --git a/src/Microsoft.ML.CpuMath/AvxIntrinsics.cs b/src/Microsoft.ML.CpuMath/AvxIntrinsics.cs index 1b19b46949..fc50acc90e 100644 --- a/src/Microsoft.ML.CpuMath/AvxIntrinsics.cs +++ b/src/Microsoft.ML.CpuMath/AvxIntrinsics.cs @@ -9,7 +9,7 @@ // * P suffix means sparse (unaligned) partial vector - the vector is only part of a larger sparse vector. // * Tran means the matrix is transposed. -using Microsoft.ML.Runtime.Internal.CpuMath.Core; +using Microsoft.ML.Internal.CpuMath.Core; using System; using System.Runtime.CompilerServices; using System.Runtime.InteropServices; @@ -17,7 +17,7 @@ using System.Runtime.Intrinsics.X86; using nuint = System.UInt64; -namespace Microsoft.ML.Runtime.Internal.CpuMath +namespace Microsoft.ML.Internal.CpuMath { internal static class AvxIntrinsics { diff --git a/src/Microsoft.ML.CpuMath/CpuAligenedMathUtils.cs b/src/Microsoft.ML.CpuMath/CpuAligenedMathUtils.cs index 33690055b2..c80cdec192 100644 --- a/src/Microsoft.ML.CpuMath/CpuAligenedMathUtils.cs +++ b/src/Microsoft.ML.CpuMath/CpuAligenedMathUtils.cs @@ -2,9 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Internal.CpuMath.Core; +using Microsoft.ML.Internal.CpuMath.Core; -namespace Microsoft.ML.Runtime.Internal.CpuMath +namespace Microsoft.ML.Internal.CpuMath { [BestFriend] internal static class CpuAligenedMathUtils diff --git a/src/Microsoft.ML.CpuMath/CpuMathUtils.netcoreapp.cs b/src/Microsoft.ML.CpuMath/CpuMathUtils.netcoreapp.cs index d895e590a9..2a4a8618d7 100644 --- a/src/Microsoft.ML.CpuMath/CpuMathUtils.netcoreapp.cs +++ b/src/Microsoft.ML.CpuMath/CpuMathUtils.netcoreapp.cs @@ -2,12 +2,12 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Internal.CpuMath.Core; +using Microsoft.ML.Internal.CpuMath.Core; using System.Runtime.CompilerServices; using System.Runtime.Intrinsics.X86; using System; -namespace Microsoft.ML.Runtime.Internal.CpuMath +namespace Microsoft.ML.Internal.CpuMath { internal static partial class CpuMathUtils { diff --git a/src/Microsoft.ML.CpuMath/CpuMathUtils.netstandard.cs b/src/Microsoft.ML.CpuMath/CpuMathUtils.netstandard.cs index a046bbba98..ff021697d6 100644 --- a/src/Microsoft.ML.CpuMath/CpuMathUtils.netstandard.cs +++ b/src/Microsoft.ML.CpuMath/CpuMathUtils.netstandard.cs @@ -2,12 +2,12 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Internal.CpuMath.Core; +using Microsoft.ML.Internal.CpuMath.Core; using System; using System.Runtime.CompilerServices; using System.Runtime.InteropServices; -namespace Microsoft.ML.Runtime.Internal.CpuMath +namespace Microsoft.ML.Internal.CpuMath { [BestFriend] internal static partial class CpuMathUtils diff --git a/src/Microsoft.ML.CpuMath/EigenUtils.cs b/src/Microsoft.ML.CpuMath/EigenUtils.cs index cff9d1b32d..af5bb33508 100644 --- a/src/Microsoft.ML.CpuMath/EigenUtils.cs +++ b/src/Microsoft.ML.CpuMath/EigenUtils.cs @@ -2,11 +2,11 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Internal.CpuMath.Core; +using Microsoft.ML.Internal.CpuMath.Core; using System; using Float = System.Single; -namespace Microsoft.ML.Runtime.Internal.CpuMath +namespace Microsoft.ML.Internal.CpuMath { [BestFriend] // REVIEW: improve perf with SSE and Multithreading diff --git a/src/Microsoft.ML.CpuMath/ICpuBuffer.cs b/src/Microsoft.ML.CpuMath/ICpuBuffer.cs index a121351cff..ffffc9aaa6 100644 --- a/src/Microsoft.ML.CpuMath/ICpuBuffer.cs +++ b/src/Microsoft.ML.CpuMath/ICpuBuffer.cs @@ -2,12 +2,12 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Internal.CpuMath.Core; +using Microsoft.ML.Internal.CpuMath.Core; using System; using System.Collections.Generic; using Float = System.Single; -namespace Microsoft.ML.Runtime.Internal.CpuMath +namespace Microsoft.ML.Internal.CpuMath { using Conditional = System.Diagnostics.ConditionalAttribute; diff --git a/src/Microsoft.ML.CpuMath/IntUtils.cs b/src/Microsoft.ML.CpuMath/IntUtils.cs index dbb07e31cb..9c57f66fad 100644 --- a/src/Microsoft.ML.CpuMath/IntUtils.cs +++ b/src/Microsoft.ML.CpuMath/IntUtils.cs @@ -2,12 +2,12 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Internal.CpuMath.Core; +using Microsoft.ML.Internal.CpuMath.Core; using System.Runtime.InteropServices; using System.Runtime.CompilerServices; using System.Security; -namespace Microsoft.ML.Runtime.Internal.CpuMath +namespace Microsoft.ML.Internal.CpuMath { [BestFriend] internal static class IntUtils diff --git a/src/Microsoft.ML.CpuMath/ProbabilityFunctions.cs b/src/Microsoft.ML.CpuMath/ProbabilityFunctions.cs index 64875bb8b6..c00d72ea85 100644 --- a/src/Microsoft.ML.CpuMath/ProbabilityFunctions.cs +++ b/src/Microsoft.ML.CpuMath/ProbabilityFunctions.cs @@ -2,10 +2,10 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Internal.CpuMath.Core; +using Microsoft.ML.Internal.CpuMath.Core; using System; -namespace Microsoft.ML.Runtime.Internal.CpuMath +namespace Microsoft.ML.Internal.CpuMath { /// /// Probability Functions. diff --git a/src/Microsoft.ML.CpuMath/SseIntrinsics.cs b/src/Microsoft.ML.CpuMath/SseIntrinsics.cs index 44bf8abcaa..c9334cc70e 100644 --- a/src/Microsoft.ML.CpuMath/SseIntrinsics.cs +++ b/src/Microsoft.ML.CpuMath/SseIntrinsics.cs @@ -13,7 +13,7 @@ // * D suffix means convolution matrix, with implicit source padding. // * Tran means the matrix is transposed. -using Microsoft.ML.Runtime.Internal.CpuMath.Core; +using Microsoft.ML.Internal.CpuMath.Core; using System; using System.Runtime.CompilerServices; using System.Runtime.InteropServices; @@ -21,7 +21,7 @@ using System.Runtime.Intrinsics.X86; using nuint = System.UInt64; -namespace Microsoft.ML.Runtime.Internal.CpuMath +namespace Microsoft.ML.Internal.CpuMath { internal static class SseIntrinsics { diff --git a/src/Microsoft.ML.CpuMath/Thunk.cs b/src/Microsoft.ML.CpuMath/Thunk.cs index 8ff725b54a..d3bbea60a9 100644 --- a/src/Microsoft.ML.CpuMath/Thunk.cs +++ b/src/Microsoft.ML.CpuMath/Thunk.cs @@ -2,11 +2,11 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Internal.CpuMath.Core; +using Microsoft.ML.Internal.CpuMath.Core; using System.Runtime.InteropServices; using System.Security; -namespace Microsoft.ML.Runtime.Internal.CpuMath +namespace Microsoft.ML.Internal.CpuMath { [BestFriend] internal static unsafe class Thunk diff --git a/src/Microsoft.ML.Data/Commands/CrossValidationCommand.cs b/src/Microsoft.ML.Data/Commands/CrossValidationCommand.cs index 7a53d2651b..cc1865660e 100644 --- a/src/Microsoft.ML.Data/Commands/CrossValidationCommand.cs +++ b/src/Microsoft.ML.Data/Commands/CrossValidationCommand.cs @@ -3,12 +3,11 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Command; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Command; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Conversions; using System; @@ -20,7 +19,7 @@ [assembly: LoadableClass(typeof(CrossValidationCommand), typeof(CrossValidationCommand.Arguments), typeof(SignatureCommand), "Cross Validation", CrossValidationCommand.LoadName)] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { [BestFriend] internal sealed class CrossValidationCommand : DataCommand.ImplBase diff --git a/src/Microsoft.ML.Data/Commands/DataCommand.cs b/src/Microsoft.ML.Data/Commands/DataCommand.cs index 493a47b639..d74cd2cd03 100644 --- a/src/Microsoft.ML.Data/Commands/DataCommand.cs +++ b/src/Microsoft.ML.Data/Commands/DataCommand.cs @@ -6,13 +6,13 @@ using System.Collections.Generic; using System.IO; using System.Linq; -using Microsoft.ML.Runtime.Command; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.Command; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// This holds useful base classes for commands that ingest a primary dataset and deal with associated model files. diff --git a/src/Microsoft.ML.Data/Commands/DefaultColumnNames.cs b/src/Microsoft.ML.Data/Commands/DefaultColumnNames.cs index 85b6b0f1a5..d66e4d518b 100644 --- a/src/Microsoft.ML.Data/Commands/DefaultColumnNames.cs +++ b/src/Microsoft.ML.Data/Commands/DefaultColumnNames.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { public static class DefaultColumnNames { diff --git a/src/Microsoft.ML.Data/Commands/EvaluateCommand.cs b/src/Microsoft.ML.Data/Commands/EvaluateCommand.cs index 315b6d7fbe..06f81f4306 100644 --- a/src/Microsoft.ML.Data/Commands/EvaluateCommand.cs +++ b/src/Microsoft.ML.Data/Commands/EvaluateCommand.cs @@ -5,11 +5,11 @@ using System; using System.Collections.Generic; using System.Text.RegularExpressions; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Command; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Command; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; [assembly: LoadableClass(EvaluateTransform.Summary, typeof(IDataTransform), typeof(EvaluateTransform), typeof(EvaluateTransform.Arguments), typeof(SignatureDataTransform), "Evaluate Predictor", "Evaluate")] @@ -17,7 +17,7 @@ [assembly: LoadableClass(EvaluateCommand.Summary, typeof(EvaluateCommand), typeof(EvaluateCommand.Arguments), typeof(SignatureCommand), "Evaluate Predictor", "Evaluate")] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { // REVIEW: For simplicity (since this is currently the case), // we assume that all metrics are either numeric, or numeric vectors. diff --git a/src/Microsoft.ML.Data/Commands/SaveDataCommand.cs b/src/Microsoft.ML.Data/Commands/SaveDataCommand.cs index 6d8d668b81..403bdba3bd 100644 --- a/src/Microsoft.ML.Data/Commands/SaveDataCommand.cs +++ b/src/Microsoft.ML.Data/Commands/SaveDataCommand.cs @@ -2,12 +2,12 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Command; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Command; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Transforms; using System; using System.Collections.Generic; @@ -20,7 +20,7 @@ [assembly: LoadableClass(ShowDataCommand.Summary, typeof(ShowDataCommand), typeof(ShowDataCommand.Arguments), typeof(SignatureCommand), "Show Data", "ShowData", "show")] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { internal sealed class SaveDataCommand : DataCommand.ImplBase { diff --git a/src/Microsoft.ML.Data/Commands/SavePredictorCommand.cs b/src/Microsoft.ML.Data/Commands/SavePredictorCommand.cs index c537cbd3ab..898cd67ef0 100644 --- a/src/Microsoft.ML.Data/Commands/SavePredictorCommand.cs +++ b/src/Microsoft.ML.Data/Commands/SavePredictorCommand.cs @@ -4,21 +4,21 @@ using System.IO; using System.Text; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Command; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML; +using Microsoft.ML.Command; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Tools; // REVIEW: Fix these namespaces. -using Microsoft.ML.Runtime.Internal.Internallearn; +using Microsoft.ML.Internal.Internallearn; [assembly: LoadableClass(SavePredictorCommand.Summary, typeof(SavePredictorCommand), typeof(SavePredictorCommand.Arguments), typeof(SignatureCommand), "Save Predictor As", "SavePredictorAs", "SavePredictor", "SaveAs", "SaveModel")] -namespace Microsoft.ML.Runtime.Tools +namespace Microsoft.ML.Tools { internal sealed class SavePredictorCommand : ICommand { diff --git a/src/Microsoft.ML.Data/Commands/ScoreCommand.cs b/src/Microsoft.ML.Data/Commands/ScoreCommand.cs index fe289fa4f7..3f5db72df0 100644 --- a/src/Microsoft.ML.Data/Commands/ScoreCommand.cs +++ b/src/Microsoft.ML.Data/Commands/ScoreCommand.cs @@ -8,17 +8,16 @@ using System.Collections.Generic; using System.IO; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Command; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Command; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Utilities; [assembly: LoadableClass(ScoreCommand.Summary, typeof(ScoreCommand), typeof(ScoreCommand.Arguments), typeof(SignatureCommand), "Score Predictor", "Score")] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { using TScorerFactory = IComponentFactory; diff --git a/src/Microsoft.ML.Data/Commands/ShowSchemaCommand.cs b/src/Microsoft.ML.Data/Commands/ShowSchemaCommand.cs index 48c28a377f..5a7e180abc 100644 --- a/src/Microsoft.ML.Data/Commands/ShowSchemaCommand.cs +++ b/src/Microsoft.ML.Data/Commands/ShowSchemaCommand.cs @@ -10,17 +10,16 @@ using System.Reflection; using System.Text; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Command; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.Conversion; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Command; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data.Conversion; +using Microsoft.ML.Internal.Utilities; [assembly: LoadableClass(ShowSchemaCommand.Summary, typeof(ShowSchemaCommand), typeof(ShowSchemaCommand.Arguments), typeof(SignatureCommand), "Show Schema", ShowSchemaCommand.LoadName, "schema")] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { internal sealed class ShowSchemaCommand : DataCommand.ImplBase { diff --git a/src/Microsoft.ML.Data/Commands/TestCommand.cs b/src/Microsoft.ML.Data/Commands/TestCommand.cs index eb7d689b61..c27e95aa29 100644 --- a/src/Microsoft.ML.Data/Commands/TestCommand.cs +++ b/src/Microsoft.ML.Data/Commands/TestCommand.cs @@ -3,16 +3,16 @@ // See the LICENSE file in the project root for more information. using System.Collections.Generic; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Command; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Command; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; [assembly: LoadableClass(TestCommand.Summary, typeof(TestCommand), typeof(TestCommand.Arguments), typeof(SignatureCommand), "Test Predictor", "Test")] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// This command is essentially chaining together and diff --git a/src/Microsoft.ML.Data/Commands/TrainCommand.cs b/src/Microsoft.ML.Data/Commands/TrainCommand.cs index 7a1bec133a..a9b9671177 100644 --- a/src/Microsoft.ML.Data/Commands/TrainCommand.cs +++ b/src/Microsoft.ML.Data/Commands/TrainCommand.cs @@ -3,14 +3,13 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Command; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.Command; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms.Normalizers; using System; using System.Collections.Generic; @@ -20,7 +19,7 @@ [assembly: LoadableClass(TrainCommand.Summary, typeof(TrainCommand), typeof(TrainCommand.Arguments), typeof(SignatureCommand), "Train Predictor", "Train")] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { using ColumnRole = RoleMappedSchema.ColumnRole; diff --git a/src/Microsoft.ML.Data/Commands/TrainTestCommand.cs b/src/Microsoft.ML.Data/Commands/TrainTestCommand.cs index 466c759f10..40bac35c7b 100644 --- a/src/Microsoft.ML.Data/Commands/TrainTestCommand.cs +++ b/src/Microsoft.ML.Data/Commands/TrainTestCommand.cs @@ -4,18 +4,18 @@ using System.Collections.Generic; using System.IO; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Command; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.Command; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; [assembly: LoadableClass(TrainTestCommand.Summary, typeof(TrainTestCommand), typeof(TrainTestCommand.Arguments), typeof(SignatureCommand), "Train Test", TrainTestCommand.LoadName)] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { [BestFriend] internal sealed class TrainTestCommand : DataCommand.ImplBase diff --git a/src/Microsoft.ML.Data/Commands/TypeInfoCommand.cs b/src/Microsoft.ML.Data/Commands/TypeInfoCommand.cs index e9db784f1f..1e3fc16e5d 100644 --- a/src/Microsoft.ML.Data/Commands/TypeInfoCommand.cs +++ b/src/Microsoft.ML.Data/Commands/TypeInfoCommand.cs @@ -6,11 +6,11 @@ using System.Collections.Generic; using System.Linq; using Microsoft.ML.Data.Commands; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Command; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.Conversion; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Command; +using Microsoft.ML.Data; +using Microsoft.ML.Data.Conversion; +using Microsoft.ML.Internal.Utilities; [assembly: LoadableClass(typeof(TypeInfoCommand), typeof(TypeInfoCommand.Arguments), typeof(SignatureCommand), "", TypeInfoCommand.LoadName)] diff --git a/src/Microsoft.ML.Data/Data/BufferBuilder.cs b/src/Microsoft.ML.Data/Data/BufferBuilder.cs index 2f37f4ea81..3527c50096 100644 --- a/src/Microsoft.ML.Data/Data/BufferBuilder.cs +++ b/src/Microsoft.ML.Data/Data/BufferBuilder.cs @@ -3,9 +3,9 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { using Conditional = System.Diagnostics.ConditionalAttribute; diff --git a/src/Microsoft.ML.Data/Data/Combiner.cs b/src/Microsoft.ML.Data/Data/Combiner.cs index 6335620b8b..834dd7a4ee 100644 --- a/src/Microsoft.ML.Data/Data/Combiner.cs +++ b/src/Microsoft.ML.Data/Data/Combiner.cs @@ -9,7 +9,7 @@ using System; using System.Threading; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { // REVIEW: Need better names for these and possibly a distinct namespace. These are too // specialized to have such prominent fully qualified names. diff --git a/src/Microsoft.ML.Data/Data/Conversion.cs b/src/Microsoft.ML.Data/Data/Conversion.cs index cf4379e74d..ccb681b925 100644 --- a/src/Microsoft.ML.Data/Data/Conversion.cs +++ b/src/Microsoft.ML.Data/Data/Conversion.cs @@ -10,9 +10,9 @@ using System.Reflection; using System.Text; using System.Threading; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Data.Conversion +namespace Microsoft.ML.Data.Conversion { using BL = Boolean; using DT = DateTime; diff --git a/src/Microsoft.ML.Data/Data/DataViewUtils.cs b/src/Microsoft.ML.Data/Data/DataViewUtils.cs index 01f6960cce..1ee926378c 100644 --- a/src/Microsoft.ML.Data/Data/DataViewUtils.cs +++ b/src/Microsoft.ML.Data/Data/DataViewUtils.cs @@ -9,11 +9,10 @@ using System.Reflection; using System.Text; using System.Threading; -using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data.Conversion; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Data.Conversion; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { public static class DataViewUtils { diff --git a/src/Microsoft.ML.Data/Data/IDataLoader.cs b/src/Microsoft.ML.Data/Data/IDataLoader.cs index 8aecbb70df..fcd09a628f 100644 --- a/src/Microsoft.ML.Data/Data/IDataLoader.cs +++ b/src/Microsoft.ML.Data/Data/IDataLoader.cs @@ -4,9 +4,9 @@ using System; using System.IO; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.Model; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// An interface for exposing some number of items that can be opened for reading. diff --git a/src/Microsoft.ML.Data/Data/IRowSeekable.cs b/src/Microsoft.ML.Data/Data/IRowSeekable.cs index d1ae1ebb7e..b29a49343c 100644 --- a/src/Microsoft.ML.Data/Data/IRowSeekable.cs +++ b/src/Microsoft.ML.Data/Data/IRowSeekable.cs @@ -2,10 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Data; using System; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { // REVIEW: Would it be a better apporach to add something akin to CanSeek, // as we have a CanShuffle? The idea is trying to make IRowSeekable propagate along certain transforms. diff --git a/src/Microsoft.ML.Data/Data/ITransposeDataView.cs b/src/Microsoft.ML.Data/Data/ITransposeDataView.cs index 88116431ec..a608a28712 100644 --- a/src/Microsoft.ML.Data/Data/ITransposeDataView.cs +++ b/src/Microsoft.ML.Data/Data/ITransposeDataView.cs @@ -2,9 +2,7 @@ // 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.Runtime.Data +namespace Microsoft.ML.Data { // REVIEW: There are a couple problems. Firstly, what to do about cases where // the number of rows exceeds int.MaxValue? Right now we just fail. Practically this makes diff --git a/src/Microsoft.ML.Data/Data/RowCursorUtils.cs b/src/Microsoft.ML.Data/Data/RowCursorUtils.cs index 0e5e226b39..7f6aeff35e 100644 --- a/src/Microsoft.ML.Data/Data/RowCursorUtils.cs +++ b/src/Microsoft.ML.Data/Data/RowCursorUtils.cs @@ -7,11 +7,10 @@ using System.Linq; using System.Reflection; using System.Text; -using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data.Conversion; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Data.Conversion; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { public static class RowCursorUtils { @@ -473,7 +472,7 @@ public static T Fetch(IExceptionContext ectx, Row row, string name) /// /// Given a row, returns a one-row data view. This is useful for cases where you have a row, and you /// wish to use some facility normally only exposed to dataviews. (For example, you have an - /// but want to save it somewhere using a .) + /// but want to save it somewhere using a .) /// Note that it is not possible for this method to ensure that the input does not /// change, so users of this convenience must take care of what they do with the input row or the data /// source it came from, while the returned dataview is potentially being used. diff --git a/src/Microsoft.ML.Data/Data/SchemaDefinition.cs b/src/Microsoft.ML.Data/Data/SchemaDefinition.cs index 437d37d071..b06d04301b 100644 --- a/src/Microsoft.ML.Data/Data/SchemaDefinition.cs +++ b/src/Microsoft.ML.Data/Data/SchemaDefinition.cs @@ -6,9 +6,9 @@ using System.Collections.Generic; using System.Linq; using System.Reflection; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; namespace Microsoft.ML.Data { diff --git a/src/Microsoft.ML.Data/Data/SlotCursor.cs b/src/Microsoft.ML.Data/Data/SlotCursor.cs index 7e151254e0..1b043a9273 100644 --- a/src/Microsoft.ML.Data/Data/SlotCursor.cs +++ b/src/Microsoft.ML.Data/Data/SlotCursor.cs @@ -4,7 +4,7 @@ using System; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// A cursor that allows slot-by-slot access of data. This is to diff --git a/src/Microsoft.ML.Data/DataDebuggerPreview.cs b/src/Microsoft.ML.Data/DataDebuggerPreview.cs index 5c09e17049..c07bfcc287 100644 --- a/src/Microsoft.ML.Data/DataDebuggerPreview.cs +++ b/src/Microsoft.ML.Data/DataDebuggerPreview.cs @@ -2,9 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; using System; using System.Collections.Generic; using System.Collections.Immutable; diff --git a/src/Microsoft.ML.Data/DataLoadSave/Binary/BinaryLoader.cs b/src/Microsoft.ML.Data/DataLoadSave/Binary/BinaryLoader.cs index ddaf747b3a..8a39549de9 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/Binary/BinaryLoader.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/Binary/BinaryLoader.cs @@ -3,13 +3,12 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Command; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.Command; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms; using System; using System.Collections.Concurrent; @@ -34,7 +33,7 @@ [assembly: LoadableClass(typeof(BinaryLoader.InfoCommand), typeof(BinaryLoader.InfoCommand.Arguments), typeof(SignatureCommand), "", BinaryLoader.InfoCommand.LoadName, "idv")] -namespace Microsoft.ML.Runtime.Data.IO +namespace Microsoft.ML.Data.IO { public sealed class BinaryLoader : IDataLoader, IDisposable { diff --git a/src/Microsoft.ML.Data/DataLoadSave/Binary/BinaryLoaderSaverCatalog.cs b/src/Microsoft.ML.Data/DataLoadSave/Binary/BinaryLoaderSaverCatalog.cs index d697112719..f1e1350358 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/Binary/BinaryLoaderSaverCatalog.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/Binary/BinaryLoaderSaverCatalog.cs @@ -3,9 +3,9 @@ // See the LICENSE file in the project root for more information. using System.IO; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Data.IO; namespace Microsoft.ML { diff --git a/src/Microsoft.ML.Data/DataLoadSave/Binary/BinarySaver.cs b/src/Microsoft.ML.Data/DataLoadSave/Binary/BinarySaver.cs index 11be283690..58e56bcd4a 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/Binary/BinarySaver.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/Binary/BinarySaver.cs @@ -13,16 +13,15 @@ using System.Threading; using System.Threading.Tasks; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Utilities; [assembly: LoadableClass(BinarySaver.Summary, typeof(BinarySaver), typeof(BinarySaver.Arguments), typeof(SignatureDataSaver), "Binary Saver", "BinarySaver", "Binary")] -namespace Microsoft.ML.Runtime.Data.IO +namespace Microsoft.ML.Data.IO { using Stopwatch = System.Diagnostics.Stopwatch; diff --git a/src/Microsoft.ML.Data/DataLoadSave/Binary/BlockLookup.cs b/src/Microsoft.ML.Data/DataLoadSave/Binary/BlockLookup.cs index c5b1571f5a..ff5edd2014 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/Binary/BlockLookup.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/Binary/BlockLookup.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -namespace Microsoft.ML.Runtime.Data.IO +namespace Microsoft.ML.Data.IO { /// /// This structure is utilized by both the binary loader and binary saver to hold diff --git a/src/Microsoft.ML.Data/DataLoadSave/Binary/CodecFactory.cs b/src/Microsoft.ML.Data/DataLoadSave/Binary/CodecFactory.cs index 735ea8730b..66a3ceacc1 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/Binary/CodecFactory.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/Binary/CodecFactory.cs @@ -6,9 +6,9 @@ using System.Collections.Generic; using System.IO; using System.Text; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Data.IO +namespace Microsoft.ML.Data.IO { internal sealed partial class CodecFactory { diff --git a/src/Microsoft.ML.Data/DataLoadSave/Binary/Codecs.cs b/src/Microsoft.ML.Data/DataLoadSave/Binary/Codecs.cs index 11963c3700..10ab84dd11 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/Binary/Codecs.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/Binary/Codecs.cs @@ -8,10 +8,10 @@ using System.Linq; using System.Runtime.InteropServices; using System.Text; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Internal.Internallearn; -namespace Microsoft.ML.Runtime.Data.IO +namespace Microsoft.ML.Data.IO { internal sealed partial class CodecFactory { diff --git a/src/Microsoft.ML.Data/DataLoadSave/Binary/CompressionKind.cs b/src/Microsoft.ML.Data/DataLoadSave/Binary/CompressionKind.cs index 438177807a..4c22a9b31f 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/Binary/CompressionKind.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/Binary/CompressionKind.cs @@ -5,13 +5,13 @@ using System; using System.IO; using System.IO.Compression; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Data.IO.Zlib; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Data.IO.Zlib; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Data.IO +namespace Microsoft.ML.Data.IO { /// /// A code indicating the kind of compression. It is supposed that each kind of compression is totally diff --git a/src/Microsoft.ML.Data/DataLoadSave/Binary/Header.cs b/src/Microsoft.ML.Data/DataLoadSave/Binary/Header.cs index b552ab6523..0395094700 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/Binary/Header.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/Binary/Header.cs @@ -4,7 +4,7 @@ using System.Runtime.InteropServices; -namespace Microsoft.ML.Runtime.Data.IO +namespace Microsoft.ML.Data.IO { [StructLayout(LayoutKind.Explicit, Size = HeaderSize)] public struct Header diff --git a/src/Microsoft.ML.Data/DataLoadSave/Binary/IValueCodec.cs b/src/Microsoft.ML.Data/DataLoadSave/Binary/IValueCodec.cs index 2f81e90056..5419e67ab8 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/Binary/IValueCodec.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/Binary/IValueCodec.cs @@ -5,7 +5,7 @@ using System; using System.IO; -namespace Microsoft.ML.Runtime.Data.IO +namespace Microsoft.ML.Data.IO { /// /// A value codec encapsulates implementations capable of writing and reading data of some diff --git a/src/Microsoft.ML.Data/DataLoadSave/Binary/MemoryStreamPool.cs b/src/Microsoft.ML.Data/DataLoadSave/Binary/MemoryStreamPool.cs index 105b0cf8a0..5fbb5c1318 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/Binary/MemoryStreamPool.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/Binary/MemoryStreamPool.cs @@ -5,9 +5,9 @@ using System; using System.IO; using System.Threading; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Data.IO +namespace Microsoft.ML.Data.IO { internal sealed class MemoryStreamPool { diff --git a/src/Microsoft.ML.Data/DataLoadSave/Binary/UnsafeTypeOps.cs b/src/Microsoft.ML.Data/DataLoadSave/Binary/UnsafeTypeOps.cs index 49d3919e43..5fc7215a20 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/Binary/UnsafeTypeOps.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/Binary/UnsafeTypeOps.cs @@ -7,11 +7,11 @@ using System; using System.Collections.Generic; using System.IO; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using System.Runtime.InteropServices; -namespace Microsoft.ML.Runtime.Internal.Internallearn +namespace Microsoft.ML.Internal.Internallearn { /// /// Represents some common global operations over a type diff --git a/src/Microsoft.ML.Data/DataLoadSave/Binary/Zlib/Constants.cs b/src/Microsoft.ML.Data/DataLoadSave/Binary/Zlib/Constants.cs index 51f3869ee8..5599a2909d 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/Binary/Zlib/Constants.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/Binary/Zlib/Constants.cs @@ -8,7 +8,7 @@ using System.Text; using System.Threading.Tasks; -namespace Microsoft.ML.Runtime.Data.IO.Zlib +namespace Microsoft.ML.Data.IO.Zlib { /// /// See zlib.h diff --git a/src/Microsoft.ML.Data/DataLoadSave/Binary/Zlib/ZDeflateStream.cs b/src/Microsoft.ML.Data/DataLoadSave/Binary/Zlib/ZDeflateStream.cs index 9b46743ab5..b7d2a98ac9 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/Binary/Zlib/ZDeflateStream.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/Binary/Zlib/ZDeflateStream.cs @@ -5,7 +5,7 @@ using System; using System.IO; -namespace Microsoft.ML.Runtime.Data.IO.Zlib +namespace Microsoft.ML.Data.IO.Zlib { public sealed class ZDeflateStream : Stream { diff --git a/src/Microsoft.ML.Data/DataLoadSave/Binary/Zlib/ZInflateStream.cs b/src/Microsoft.ML.Data/DataLoadSave/Binary/Zlib/ZInflateStream.cs index cb8bef5360..57b6e55aaf 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/Binary/Zlib/ZInflateStream.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/Binary/Zlib/ZInflateStream.cs @@ -4,9 +4,9 @@ using System; using System.IO; -using Microsoft.ML.Runtime; +using Microsoft.ML; -namespace Microsoft.ML.Runtime.Data.IO.Zlib +namespace Microsoft.ML.Data.IO.Zlib { public sealed class ZInflateStream : Stream { diff --git a/src/Microsoft.ML.Data/DataLoadSave/Binary/Zlib/Zlib.cs b/src/Microsoft.ML.Data/DataLoadSave/Binary/Zlib/Zlib.cs index 7b2ae812a8..879394acfe 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/Binary/Zlib/Zlib.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/Binary/Zlib/Zlib.cs @@ -6,7 +6,7 @@ using System.Runtime.InteropServices; using System.Security; -namespace Microsoft.ML.Runtime.Data.IO.Zlib +namespace Microsoft.ML.Data.IO.Zlib { internal static class Zlib { diff --git a/src/Microsoft.ML.Data/DataLoadSave/CompositeDataLoader.cs b/src/Microsoft.ML.Data/DataLoadSave/CompositeDataLoader.cs index 1395ec833d..93636ea701 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/CompositeDataLoader.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/CompositeDataLoader.cs @@ -3,11 +3,10 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using System; using System.Collections.Generic; using System.IO; @@ -20,7 +19,7 @@ [assembly: LoadableClass(typeof(IDataLoader), typeof(CompositeDataLoader), null, typeof(SignatureLoadDataLoader), "Pipe DataL Loader", CompositeDataLoader.LoaderSignature)] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// A data loader that wraps an underlying loader plus a sequence of transforms. diff --git a/src/Microsoft.ML.Data/DataLoadSave/CompositeDataReader.cs b/src/Microsoft.ML.Data/DataLoadSave/CompositeDataReader.cs index 830684ae0d..2e9a61e76c 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/CompositeDataReader.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/CompositeDataReader.cs @@ -3,9 +3,9 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Model; using System.IO; namespace Microsoft.ML.Data diff --git a/src/Microsoft.ML.Data/DataLoadSave/CompositeReaderEstimator.cs b/src/Microsoft.ML.Data/DataLoadSave/CompositeReaderEstimator.cs index 61f1246563..2b24ed77c7 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/CompositeReaderEstimator.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/CompositeReaderEstimator.cs @@ -5,7 +5,7 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// An estimator class for composite data reader. diff --git a/src/Microsoft.ML.Data/DataLoadSave/DataOperations.cs b/src/Microsoft.ML.Data/DataLoadSave/DataOperations.cs index cc0998da03..c07bd3b4de 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/DataOperations.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/DataOperations.cs @@ -3,11 +3,10 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Transforms; -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { /// /// A catalog of operations over data that are not transformers or estimators. diff --git a/src/Microsoft.ML.Data/DataLoadSave/EstimatorChain.cs b/src/Microsoft.ML.Data/DataLoadSave/EstimatorChain.cs index 7d20d22761..946b86d145 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/EstimatorChain.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/EstimatorChain.cs @@ -4,10 +4,10 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; using System.Linq; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Represents a chain (potentially empty) of estimators that end with a . diff --git a/src/Microsoft.ML.Data/DataLoadSave/EstimatorExtensions.cs b/src/Microsoft.ML.Data/DataLoadSave/EstimatorExtensions.cs index f64ecb4ef2..3fa87d3183 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/EstimatorExtensions.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/EstimatorExtensions.cs @@ -4,9 +4,8 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Internal.Utilities; using System; namespace Microsoft.ML diff --git a/src/Microsoft.ML.Data/DataLoadSave/FakeSchema.cs b/src/Microsoft.ML.Data/DataLoadSave/FakeSchema.cs index 296dc69a1d..62919d4149 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/FakeSchema.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/FakeSchema.cs @@ -3,8 +3,8 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; using System; namespace Microsoft.ML.Data.DataLoadSave diff --git a/src/Microsoft.ML.Data/DataLoadSave/MultiFileSource.cs b/src/Microsoft.ML.Data/DataLoadSave/MultiFileSource.cs index 74fe0cb544..7cc97fcc0b 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/MultiFileSource.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/MultiFileSource.cs @@ -4,9 +4,9 @@ using System; using System.IO; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Wraps a potentially compound path as an IMultiStreamSource. diff --git a/src/Microsoft.ML.Data/DataLoadSave/PartitionedFileLoader.cs b/src/Microsoft.ML.Data/DataLoadSave/PartitionedFileLoader.cs index 7b97cce6d6..63a73b89ea 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/PartitionedFileLoader.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/PartitionedFileLoader.cs @@ -8,14 +8,13 @@ using System.Linq; using System.Text; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.Conversion; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Data.Utilities; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data.Conversion; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Data.Utilities; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; [assembly: LoadableClass(PartitionedFileLoader.Summary, typeof(PartitionedFileLoader), typeof(PartitionedFileLoader.Arguments), typeof(SignatureDataLoader), PartitionedFileLoader.UserName, PartitionedFileLoader.LoadName, PartitionedFileLoader.ShortName)] @@ -23,7 +22,7 @@ [assembly: LoadableClass(PartitionedFileLoader.Summary, typeof(PartitionedFileLoader), null, typeof(SignatureLoadDataLoader), PartitionedFileLoader.UserName, PartitionedFileLoader.LoadName, PartitionedFileLoader.ShortName)] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Loads a set of directory partitioned files into an IDataView. diff --git a/src/Microsoft.ML.Data/DataLoadSave/PartitionedPathParser.cs b/src/Microsoft.ML.Data/DataLoadSave/PartitionedPathParser.cs index 33f0a5b5f4..5b7f3db452 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/PartitionedPathParser.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/PartitionedPathParser.cs @@ -7,12 +7,12 @@ using System.Linq; using System.Text; using System.Web; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.Utilities; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Data.Utilities; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Model; [assembly: LoadableClass(SimplePartitionedPathParser.Summary, typeof(SimplePartitionedPathParser), typeof(SimplePartitionedPathParser.Arguments), typeof(PartitionedPathParser), SimplePartitionedPathParser.UserName, SimplePartitionedPathParser.LoadName, SimplePartitionedPathParser.ShortName)] @@ -28,7 +28,7 @@ [assembly: EntryPointModule(typeof(SimplePartitionedPathParser.Arguments))] [assembly: EntryPointModule(typeof(ParquetPartitionedPathParserFactory))] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Delegate signature for a partitioned path parser. diff --git a/src/Microsoft.ML.Data/DataLoadSave/Text/LoadColumnAttribute.cs b/src/Microsoft.ML.Data/DataLoadSave/Text/LoadColumnAttribute.cs index fcf0cbae3f..5789146ac4 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/Text/LoadColumnAttribute.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/Text/LoadColumnAttribute.cs @@ -2,7 +2,6 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Data/DataLoadSave/Text/TextLoader.cs b/src/Microsoft.ML.Data/DataLoadSave/Text/TextLoader.cs index ef85702173..92e9ac78e6 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/Text/TextLoader.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/Text/TextLoader.cs @@ -4,11 +4,10 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using System; using System.Collections.Generic; using System.Linq; @@ -22,7 +21,7 @@ [assembly: LoadableClass(TextLoader.Summary, typeof(IDataLoader), typeof(TextLoader), null, typeof(SignatureLoadDataLoader), "Text Loader", TextLoader.LoaderSignature)] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Loads a text file into an IDataView. Supports basic mapping from input columns to IDataView columns. diff --git a/src/Microsoft.ML.Data/DataLoadSave/Text/TextLoaderCursor.cs b/src/Microsoft.ML.Data/DataLoadSave/Text/TextLoaderCursor.cs index ac879cdac8..98e4b446c5 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/Text/TextLoaderCursor.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/Text/TextLoaderCursor.cs @@ -3,14 +3,14 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; using System; using System.Collections.Concurrent; using System.Collections.Generic; using System.Text; using System.Threading; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { public sealed partial class TextLoader { diff --git a/src/Microsoft.ML.Data/DataLoadSave/Text/TextLoaderParser.cs b/src/Microsoft.ML.Data/DataLoadSave/Text/TextLoaderParser.cs index f9d6cd2b09..cd05a05021 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/Text/TextLoaderParser.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/Text/TextLoaderParser.cs @@ -13,10 +13,10 @@ using System.Runtime.CompilerServices; using System.Text; using System.Threading; -using Microsoft.ML.Runtime.Data.Conversion; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Data.Conversion; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { using Conditional = System.Diagnostics.ConditionalAttribute; diff --git a/src/Microsoft.ML.Data/DataLoadSave/Text/TextLoaderSaverCatalog.cs b/src/Microsoft.ML.Data/DataLoadSave/Text/TextLoaderSaverCatalog.cs index 0c8fc1b574..7636dd1f16 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/Text/TextLoaderSaverCatalog.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/Text/TextLoaderSaverCatalog.cs @@ -1,11 +1,13 @@ -// Licensed to the .NET 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. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Data.IO; +using System; using System.IO; +using static Microsoft.ML.Data.TextLoader; namespace Microsoft.ML { diff --git a/src/Microsoft.ML.Data/DataLoadSave/Text/TextLoaderStatic.cs b/src/Microsoft.ML.Data/DataLoadSave/Text/TextLoaderStatic.cs index c70a1158d9..708cd30647 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/Text/TextLoaderStatic.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/Text/TextLoaderStatic.cs @@ -8,7 +8,7 @@ using Microsoft.ML.StaticPipe; using Microsoft.ML.StaticPipe.Runtime; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { public sealed partial class TextLoader { diff --git a/src/Microsoft.ML.Data/DataLoadSave/Text/TextSaver.cs b/src/Microsoft.ML.Data/DataLoadSave/Text/TextSaver.cs index b368e8dbc1..e03816c715 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/Text/TextSaver.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/Text/TextSaver.cs @@ -5,19 +5,17 @@ using System; using System.IO; using System.Text; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.Conversion; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Internal.Internallearn; +using Microsoft.ML; +using Microsoft.ML.CommandLine; using Microsoft.ML.Data; +using Microsoft.ML.Data.Conversion; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Utilities; [assembly: LoadableClass(TextSaver.Summary, typeof(TextSaver), typeof(TextSaver.Arguments), typeof(SignatureDataSaver), "Text Saver", "TextSaver", "Text", DocName = "saver/TextSaver.md")] -namespace Microsoft.ML.Runtime.Data.IO +namespace Microsoft.ML.Data.IO { public sealed class TextSaver : IDataSaver { diff --git a/src/Microsoft.ML.Data/DataLoadSave/TransformWrapper.cs b/src/Microsoft.ML.Data/DataLoadSave/TransformWrapper.cs index 82ffcaa81c..7d9c79b39a 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/TransformWrapper.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/TransformWrapper.cs @@ -5,16 +5,15 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data.DataLoadSave; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Model; using System.Collections.Generic; [assembly: LoadableClass(typeof(TransformWrapper), null, typeof(SignatureLoadModel), "Transform wrapper", TransformWrapper.LoaderSignature)] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { // REVIEW: this class is public, as long as the Wrappers.cs in tests still rely on it. // It needs to become internal. diff --git a/src/Microsoft.ML.Data/DataLoadSave/TransformerChain.cs b/src/Microsoft.ML.Data/DataLoadSave/TransformerChain.cs index f1a7ca5308..9f4a00c0e8 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/TransformerChain.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/TransformerChain.cs @@ -4,10 +4,9 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using System; using System.Collections; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Data/DataLoadSave/Transpose/TransposeLoader.cs b/src/Microsoft.ML.Data/DataLoadSave/Transpose/TransposeLoader.cs index 7566d156a5..18d5aeac8e 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/Transpose/TransposeLoader.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/Transpose/TransposeLoader.cs @@ -10,12 +10,11 @@ using System.Runtime.InteropServices; using System.Threading; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; [assembly: LoadableClass(TransposeLoader.Summary, typeof(TransposeLoader), typeof(TransposeLoader.Arguments), typeof(SignatureDataLoader), "Transpose Loader", TransposeLoader.LoadName, "Transpose", "trans")] @@ -23,7 +22,7 @@ [assembly: LoadableClass(TransposeLoader.Summary, typeof(TransposeLoader), null, typeof(SignatureLoadDataLoader), "Transpose Data View Loader", TransposeLoader.LoadName)] -namespace Microsoft.ML.Runtime.Data.IO +namespace Microsoft.ML.Data.IO { /// /// The transposed loader reads the transposed binary format. This binary format, at a high level, is nothing more diff --git a/src/Microsoft.ML.Data/DataLoadSave/Transpose/TransposeSaver.cs b/src/Microsoft.ML.Data/DataLoadSave/Transpose/TransposeSaver.cs index bd351d1e58..ed5ec37a62 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/Transpose/TransposeSaver.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/Transpose/TransposeSaver.cs @@ -2,11 +2,11 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Transforms; using System; using System.Collections.Generic; @@ -17,7 +17,7 @@ [assembly: LoadableClass(TransposeSaver.Summary, typeof(TransposeSaver), typeof(TransposeSaver.Arguments), typeof(SignatureDataSaver), "Transpose Saver", TransposeSaver.LoadName, "TransposedSaver", "Transpose", "Transposed", "trans")] -namespace Microsoft.ML.Runtime.Data.IO +namespace Microsoft.ML.Data.IO { /// /// Saver for a format that can be loaded using the . diff --git a/src/Microsoft.ML.Data/DataLoadSave/TrivialEstimator.cs b/src/Microsoft.ML.Data/DataLoadSave/TrivialEstimator.cs index 34eb0874c6..e1ac2a2936 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/TrivialEstimator.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/TrivialEstimator.cs @@ -4,7 +4,7 @@ using Microsoft.ML.Core.Data; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// The trivial implementation of that already has diff --git a/src/Microsoft.ML.Data/DataLoadSave/TrivialReaderEstimator.cs b/src/Microsoft.ML.Data/DataLoadSave/TrivialReaderEstimator.cs index 506ea8cf73..957a20ee55 100644 --- a/src/Microsoft.ML.Data/DataLoadSave/TrivialReaderEstimator.cs +++ b/src/Microsoft.ML.Data/DataLoadSave/TrivialReaderEstimator.cs @@ -4,7 +4,7 @@ using Microsoft.ML.Core.Data; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// The trivial wrapper for a that acts as an estimator and ignores the source. diff --git a/src/Microsoft.ML.Data/DataView/AppendRowsDataView.cs b/src/Microsoft.ML.Data/DataView/AppendRowsDataView.cs index a499ce2e61..1b32f35cc5 100644 --- a/src/Microsoft.ML.Data/DataView/AppendRowsDataView.cs +++ b/src/Microsoft.ML.Data/DataView/AppendRowsDataView.cs @@ -3,14 +3,11 @@ // See the LICENSE file in the project root for more information. using System; -using System.Collections.Generic; using System.Linq; using System.Reflection; -using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { // REVIEW: Currently, to enable shuffling, we require the row counts of the sources to be known. // We can think of the shuffling in AppendRowsDataView as a two-stage process: diff --git a/src/Microsoft.ML.Data/DataView/ArrayDataViewBuilder.cs b/src/Microsoft.ML.Data/DataView/ArrayDataViewBuilder.cs index 882b7e33cb..12bad5d794 100644 --- a/src/Microsoft.ML.Data/DataView/ArrayDataViewBuilder.cs +++ b/src/Microsoft.ML.Data/DataView/ArrayDataViewBuilder.cs @@ -3,11 +3,11 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; using System; using System.Collections.Generic; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { using BitArray = System.Collections.BitArray; diff --git a/src/Microsoft.ML.Data/DataView/CacheDataView.cs b/src/Microsoft.ML.Data/DataView/CacheDataView.cs index 04368994a8..0e49d7deb5 100644 --- a/src/Microsoft.ML.Data/DataView/CacheDataView.cs +++ b/src/Microsoft.ML.Data/DataView/CacheDataView.cs @@ -4,9 +4,9 @@ #pragma warning disable 420 // volatile with Interlocked.CompareExchange -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; using System; using System.Collections.Concurrent; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Data/DataView/CompositeRowToRowMapper.cs b/src/Microsoft.ML.Data/DataView/CompositeRowToRowMapper.cs index f3ca9290c7..cfdbef628b 100644 --- a/src/Microsoft.ML.Data/DataView/CompositeRowToRowMapper.cs +++ b/src/Microsoft.ML.Data/DataView/CompositeRowToRowMapper.cs @@ -4,9 +4,9 @@ using System; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// A row-to-row mapper that is the result of a chained application of multiple mappers. diff --git a/src/Microsoft.ML.Data/DataView/CompositeSchema.cs b/src/Microsoft.ML.Data/DataView/CompositeSchema.cs index cbdee62cbb..57bc36bf58 100644 --- a/src/Microsoft.ML.Data/DataView/CompositeSchema.cs +++ b/src/Microsoft.ML.Data/DataView/CompositeSchema.cs @@ -6,9 +6,9 @@ using System.Collections.Generic; using System.Linq; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// A convenience class for concatenating several schemas together. diff --git a/src/Microsoft.ML.Data/DataView/DataViewConstructionUtils.cs b/src/Microsoft.ML.Data/DataView/DataViewConstructionUtils.cs index 46304599fe..88b23ea32b 100644 --- a/src/Microsoft.ML.Data/DataView/DataViewConstructionUtils.cs +++ b/src/Microsoft.ML.Data/DataView/DataViewConstructionUtils.cs @@ -2,17 +2,15 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using System; using System.Collections.Generic; using System.IO; using System.Linq; using System.Reflection; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// A helper class to create data views based on the user-provided types. diff --git a/src/Microsoft.ML.Data/DataView/EmptyDataView.cs b/src/Microsoft.ML.Data/DataView/EmptyDataView.cs index 45560794ba..8a59ef9510 100644 --- a/src/Microsoft.ML.Data/DataView/EmptyDataView.cs +++ b/src/Microsoft.ML.Data/DataView/EmptyDataView.cs @@ -4,9 +4,9 @@ using System; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// This implements a data view that has a schema, but no rows. diff --git a/src/Microsoft.ML.Data/DataView/InternalSchemaDefinition.cs b/src/Microsoft.ML.Data/DataView/InternalSchemaDefinition.cs index a33ac4b949..1e44e6c6ba 100644 --- a/src/Microsoft.ML.Data/DataView/InternalSchemaDefinition.cs +++ b/src/Microsoft.ML.Data/DataView/InternalSchemaDefinition.cs @@ -8,7 +8,7 @@ using System.Linq; using System.Reflection; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { using Conditional = System.Diagnostics.ConditionalAttribute; /// diff --git a/src/Microsoft.ML.Data/DataView/LambdaColumnMapper.cs b/src/Microsoft.ML.Data/DataView/LambdaColumnMapper.cs index ab0a1fa0df..d5815fc528 100644 --- a/src/Microsoft.ML.Data/DataView/LambdaColumnMapper.cs +++ b/src/Microsoft.ML.Data/DataView/LambdaColumnMapper.cs @@ -5,10 +5,10 @@ using System; using System.Reflection; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data.Conversion; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.Data.Conversion; +using Microsoft.ML.Model; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// This applies the user provided ValueMapper to a column to produce a new column. It automatically diff --git a/src/Microsoft.ML.Data/DataView/LambdaFilter.cs b/src/Microsoft.ML.Data/DataView/LambdaFilter.cs index bb1753d7e0..848a650fa9 100644 --- a/src/Microsoft.ML.Data/DataView/LambdaFilter.cs +++ b/src/Microsoft.ML.Data/DataView/LambdaFilter.cs @@ -4,10 +4,10 @@ using System; using System.Reflection; -using Microsoft.ML.Runtime.Data.Conversion; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.Data.Conversion; +using Microsoft.ML.Model; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// This applies the user provided RefPredicate to a column and drops rows that map to false. It automatically diff --git a/src/Microsoft.ML.Data/DataView/OpaqueDataView.cs b/src/Microsoft.ML.Data/DataView/OpaqueDataView.cs index 835ca035fe..ab7ff7b39f 100644 --- a/src/Microsoft.ML.Data/DataView/OpaqueDataView.cs +++ b/src/Microsoft.ML.Data/DataView/OpaqueDataView.cs @@ -5,7 +5,7 @@ using Microsoft.ML.Data; using System; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Opaque IDataView implementation to provide a barrier for data pipe optimizations. diff --git a/src/Microsoft.ML.Data/DataView/RowToRowMapperTransform.cs b/src/Microsoft.ML.Data/DataView/RowToRowMapperTransform.cs index 2e4a8d6446..5990381ed0 100644 --- a/src/Microsoft.ML.Data/DataView/RowToRowMapperTransform.cs +++ b/src/Microsoft.ML.Data/DataView/RowToRowMapperTransform.cs @@ -3,22 +3,19 @@ // See the LICENSE file in the project root for more information. using System; -using System.Collections.Generic; using System.IO; using System.Linq; -using System.Reflection; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Onnx; -using Microsoft.ML.Runtime.Model.Pfa; +using Microsoft.ML; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Onnx; +using Microsoft.ML.Model.Pfa; [assembly: LoadableClass(typeof(RowToRowMapperTransform), null, typeof(SignatureLoadDataTransform), "", RowToRowMapperTransform.LoaderSignature)] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// This interface is used to create a . diff --git a/src/Microsoft.ML.Data/DataView/SimpleRow.cs b/src/Microsoft.ML.Data/DataView/SimpleRow.cs index 01a2b719b6..ed9d0fba20 100644 --- a/src/Microsoft.ML.Data/DataView/SimpleRow.cs +++ b/src/Microsoft.ML.Data/DataView/SimpleRow.cs @@ -6,9 +6,9 @@ using System.Collections.Generic; using System.Linq; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// An implementation of that gets its , , diff --git a/src/Microsoft.ML.Data/DataView/Transposer.cs b/src/Microsoft.ML.Data/DataView/Transposer.cs index 96cc366397..38cf12d97e 100644 --- a/src/Microsoft.ML.Data/DataView/Transposer.cs +++ b/src/Microsoft.ML.Data/DataView/Transposer.cs @@ -8,10 +8,11 @@ using System.Linq; using System.Reflection; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// This provides a scalable method of getting a "transposed" view of a subset of columns from an diff --git a/src/Microsoft.ML.Data/DataView/TypedCursor.cs b/src/Microsoft.ML.Data/DataView/TypedCursor.cs index 034ba371a4..23f3aaebb6 100644 --- a/src/Microsoft.ML.Data/DataView/TypedCursor.cs +++ b/src/Microsoft.ML.Data/DataView/TypedCursor.cs @@ -2,9 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; using System; using System.Collections.Generic; using System.Linq; diff --git a/src/Microsoft.ML.Data/DataView/ZipDataView.cs b/src/Microsoft.ML.Data/DataView/ZipDataView.cs index 714412595e..5d85bcd73d 100644 --- a/src/Microsoft.ML.Data/DataView/ZipDataView.cs +++ b/src/Microsoft.ML.Data/DataView/ZipDataView.cs @@ -6,9 +6,9 @@ using System.Collections.Generic; using System.Linq; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// This is a data view that is a 'zip' of several data views. diff --git a/src/Microsoft.ML.Data/DebuggerExtensions.cs b/src/Microsoft.ML.Data/DebuggerExtensions.cs index 1a7c6e4920..0f479b83b1 100644 --- a/src/Microsoft.ML.Data/DebuggerExtensions.cs +++ b/src/Microsoft.ML.Data/DebuggerExtensions.cs @@ -4,8 +4,6 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using Microsoft.ML.Transforms; namespace Microsoft.ML diff --git a/src/Microsoft.ML.Data/Depricated/Instances/HeaderSchema.cs b/src/Microsoft.ML.Data/Depricated/Instances/HeaderSchema.cs index 38867fe005..e1730b01d2 100644 --- a/src/Microsoft.ML.Data/Depricated/Instances/HeaderSchema.cs +++ b/src/Microsoft.ML.Data/Depricated/Instances/HeaderSchema.cs @@ -5,16 +5,15 @@ #pragma warning disable 420 // volatile with Interlocked.CompareExchange using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using System; using System.Collections; using System.Collections.Generic; using System.Linq; using System.Threading; -namespace Microsoft.ML.Runtime.Internal.Internallearn +namespace Microsoft.ML.Internal.Internallearn { [BestFriend] internal abstract class FeatureNameCollection : IEnumerable diff --git a/src/Microsoft.ML.Data/Depricated/TGUIAttribute.cs b/src/Microsoft.ML.Data/Depricated/TGUIAttribute.cs index 5f09c604bb..0fe3d34a9a 100644 --- a/src/Microsoft.ML.Data/Depricated/TGUIAttribute.cs +++ b/src/Microsoft.ML.Data/Depricated/TGUIAttribute.cs @@ -3,9 +3,9 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; +using Microsoft.ML; -namespace Microsoft.ML.Runtime.Internal.Internallearn +namespace Microsoft.ML.Internal.Internallearn { #pragma warning disable MSML_GeneralName // This structure should be deprecated anyway. // REVIEW: Get rid of this. Everything should be in the ArgumentAttribute (or a class diff --git a/src/Microsoft.ML.Data/Depricated/Vector/GenericSpanSortHelper.cs b/src/Microsoft.ML.Data/Depricated/Vector/GenericSpanSortHelper.cs index 3f90ddca23..f11fbce53b 100644 --- a/src/Microsoft.ML.Data/Depricated/Vector/GenericSpanSortHelper.cs +++ b/src/Microsoft.ML.Data/Depricated/Vector/GenericSpanSortHelper.cs @@ -20,7 +20,7 @@ using System; -namespace Microsoft.ML.Runtime.Numeric +namespace Microsoft.ML.Numeric { internal static class IntrospectiveSortUtilities { diff --git a/src/Microsoft.ML.Data/Depricated/Vector/VBufferMathUtils.cs b/src/Microsoft.ML.Data/Depricated/Vector/VBufferMathUtils.cs index 4fcf0b40ac..89336aa064 100644 --- a/src/Microsoft.ML.Data/Depricated/Vector/VBufferMathUtils.cs +++ b/src/Microsoft.ML.Data/Depricated/Vector/VBufferMathUtils.cs @@ -3,11 +3,11 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.CpuMath; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.CpuMath; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Numeric +namespace Microsoft.ML.Numeric { // REVIEW: Once we do the conversions from Vector/WritableVector, review names of methods, // parameters, parameter order, etc. diff --git a/src/Microsoft.ML.Data/Depricated/Vector/VectorUtils.cs b/src/Microsoft.ML.Data/Depricated/Vector/VectorUtils.cs index b0c810633d..8871893334 100644 --- a/src/Microsoft.ML.Data/Depricated/Vector/VectorUtils.cs +++ b/src/Microsoft.ML.Data/Depricated/Vector/VectorUtils.cs @@ -5,12 +5,12 @@ using System; using System.Collections.Generic; using System.Linq; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.CpuMath; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.CpuMath; +using Microsoft.ML.Internal.Utilities; using Float = System.Single; -namespace Microsoft.ML.Runtime.Numeric +namespace Microsoft.ML.Numeric { /// /// A series of vector utility functions, generally operating over arrays or diff --git a/src/Microsoft.ML.Data/Dirty/ChooseColumnsByIndexTransform.cs b/src/Microsoft.ML.Data/Dirty/ChooseColumnsByIndexTransform.cs index 769a3100a1..3346fc0abe 100644 --- a/src/Microsoft.ML.Data/Dirty/ChooseColumnsByIndexTransform.cs +++ b/src/Microsoft.ML.Data/Dirty/ChooseColumnsByIndexTransform.cs @@ -3,11 +3,10 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using System; using System.Linq; @@ -17,7 +16,7 @@ [assembly: LoadableClass(typeof(ChooseColumnsByIndexTransform), null, typeof(SignatureLoadDataTransform), "", ChooseColumnsByIndexTransform.LoaderSignature, ChooseColumnsByIndexTransform.LoaderSignatureOld)] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { public sealed class ChooseColumnsByIndexTransform : RowToRowTransformBase { diff --git a/src/Microsoft.ML.Data/Dirty/ILoss.cs b/src/Microsoft.ML.Data/Dirty/ILoss.cs index 69c394c76e..b889eca456 100644 --- a/src/Microsoft.ML.Data/Dirty/ILoss.cs +++ b/src/Microsoft.ML.Data/Dirty/ILoss.cs @@ -5,9 +5,9 @@ using Float = System.Single; using System; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML.EntryPoints; -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { public interface ILossFunction { diff --git a/src/Microsoft.ML.Data/Dirty/IniFileUtils.cs b/src/Microsoft.ML.Data/Dirty/IniFileUtils.cs index 542048825f..f704aca7a0 100644 --- a/src/Microsoft.ML.Data/Dirty/IniFileUtils.cs +++ b/src/Microsoft.ML.Data/Dirty/IniFileUtils.cs @@ -4,9 +4,9 @@ using System.Text; using System.Text.RegularExpressions; -using Microsoft.ML.Runtime.Internal.Calibration; +using Microsoft.ML.Internal.Calibration; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { [BestFriend] internal static class IniFileUtils diff --git a/src/Microsoft.ML.Data/Dirty/ModelParametersBase.cs b/src/Microsoft.ML.Data/Dirty/ModelParametersBase.cs index 5a0f47c5a0..bc9eddf5df 100644 --- a/src/Microsoft.ML.Data/Dirty/ModelParametersBase.cs +++ b/src/Microsoft.ML.Data/Dirty/ModelParametersBase.cs @@ -3,9 +3,10 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.Model; -namespace Microsoft.ML.Runtime.Internal.Internallearn +namespace Microsoft.ML.Internal.Internallearn { /// /// A base class for predictors producing . diff --git a/src/Microsoft.ML.Data/Dirty/PredictionUtils.cs b/src/Microsoft.ML.Data/Dirty/PredictionUtils.cs index 9a78defd82..fc79e88fd7 100644 --- a/src/Microsoft.ML.Data/Dirty/PredictionUtils.cs +++ b/src/Microsoft.ML.Data/Dirty/PredictionUtils.cs @@ -6,11 +6,11 @@ using System.Collections.Generic; using System.Linq; using System.Text; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Internal.Internallearn +namespace Microsoft.ML.Internal.Internallearn { using Float = System.Single; diff --git a/src/Microsoft.ML.Data/Dirty/PredictorInterfaces.cs b/src/Microsoft.ML.Data/Dirty/PredictorInterfaces.cs index 6bae4b8f30..6a2e872033 100644 --- a/src/Microsoft.ML.Data/Dirty/PredictorInterfaces.cs +++ b/src/Microsoft.ML.Data/Dirty/PredictorInterfaces.cs @@ -5,10 +5,10 @@ using System; using System.Collections.Generic; using System.IO; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; using Microsoft.ML.Calibrator; -namespace Microsoft.ML.Runtime.Internal.Internallearn +namespace Microsoft.ML.Internal.Internallearn { /// diff --git a/src/Microsoft.ML.Data/Dirty/PredictorUtils.cs b/src/Microsoft.ML.Data/Dirty/PredictorUtils.cs index 46e6a859f5..0efe9b6fb3 100644 --- a/src/Microsoft.ML.Data/Dirty/PredictorUtils.cs +++ b/src/Microsoft.ML.Data/Dirty/PredictorUtils.cs @@ -3,11 +3,11 @@ // See the LICENSE file in the project root for more information. using System.IO; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Model; -namespace Microsoft.ML.Runtime.Internal.Internallearn +namespace Microsoft.ML.Internal.Internallearn { [BestFriend] internal static class PredictorUtils diff --git a/src/Microsoft.ML.Data/EntryPoints/Cache.cs b/src/Microsoft.ML.Data/EntryPoints/Cache.cs index fc9bb6c1c0..0c376f5dcc 100644 --- a/src/Microsoft.ML.Data/EntryPoints/Cache.cs +++ b/src/Microsoft.ML.Data/EntryPoints/Cache.cs @@ -7,14 +7,13 @@ using System.IO; using System.Linq; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data.IO; +using Microsoft.ML.EntryPoints; [assembly: LoadableClass(typeof(void), typeof(Cache), null, typeof(SignatureEntryPointModule), "Cache")] -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { public static class Cache { diff --git a/src/Microsoft.ML.Data/EntryPoints/CommonOutputs.cs b/src/Microsoft.ML.Data/EntryPoints/CommonOutputs.cs index c4647c6ae8..552c27ac77 100644 --- a/src/Microsoft.ML.Data/EntryPoints/CommonOutputs.cs +++ b/src/Microsoft.ML.Data/EntryPoints/CommonOutputs.cs @@ -4,9 +4,9 @@ using System; using System.Collections.Generic; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { /// /// Common output classes for trainers and transforms. diff --git a/src/Microsoft.ML.Data/EntryPoints/EntryPointNode.cs b/src/Microsoft.ML.Data/EntryPoints/EntryPointNode.cs index 999b8d0495..ac1da11a49 100644 --- a/src/Microsoft.ML.Data/EntryPoints/EntryPointNode.cs +++ b/src/Microsoft.ML.Data/EntryPoints/EntryPointNode.cs @@ -7,13 +7,13 @@ using System.Diagnostics; using System.Linq; using System.Text.RegularExpressions; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints.JsonUtils; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints.JsonUtils; +using Microsoft.ML.Internal.Utilities; using Newtonsoft.Json; using Newtonsoft.Json.Linq; -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { public class VarSerializer : JsonConverter { diff --git a/src/Microsoft.ML.Data/EntryPoints/InputBase.cs b/src/Microsoft.ML.Data/EntryPoints/InputBase.cs index 2eae61e079..7a45ba5379 100644 --- a/src/Microsoft.ML.Data/EntryPoints/InputBase.cs +++ b/src/Microsoft.ML.Data/EntryPoints/InputBase.cs @@ -5,12 +5,11 @@ using System; using System.Collections.Generic; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Calibration; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Calibration; -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { /// /// The base class for all transform inputs. diff --git a/src/Microsoft.ML.Data/EntryPoints/InputBuilder.cs b/src/Microsoft.ML.Data/EntryPoints/InputBuilder.cs index 0c8dae6438..40a9e2a5b5 100644 --- a/src/Microsoft.ML.Data/EntryPoints/InputBuilder.cs +++ b/src/Microsoft.ML.Data/EntryPoints/InputBuilder.cs @@ -6,12 +6,12 @@ using System.Collections.Generic; using System.Linq; using System.Reflection; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; using Newtonsoft.Json.Linq; -namespace Microsoft.ML.Runtime.EntryPoints.JsonUtils +namespace Microsoft.ML.EntryPoints.JsonUtils { /// /// The class that creates and wraps around an instance of an input object and gradually populates all fields, keeping track of missing diff --git a/src/Microsoft.ML.Data/EntryPoints/PredictorModelImpl.cs b/src/Microsoft.ML.Data/EntryPoints/PredictorModelImpl.cs index 49802efb39..80ecd4a62d 100644 --- a/src/Microsoft.ML.Data/EntryPoints/PredictorModelImpl.cs +++ b/src/Microsoft.ML.Data/EntryPoints/PredictorModelImpl.cs @@ -7,12 +7,11 @@ using System.IO; using System.Linq; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Model; -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { /// /// This class encapsulates the predictor and a preceding transform model, as the concrete and hidden diff --git a/src/Microsoft.ML.Data/EntryPoints/SchemaManipulation.cs b/src/Microsoft.ML.Data/EntryPoints/SchemaManipulation.cs index 40302bdc9d..d062fcac46 100644 --- a/src/Microsoft.ML.Data/EntryPoints/SchemaManipulation.cs +++ b/src/Microsoft.ML.Data/EntryPoints/SchemaManipulation.cs @@ -2,14 +2,14 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; using Microsoft.ML.Transforms; [assembly: LoadableClass(typeof(void), typeof(SchemaManipulation), null, typeof(SignatureEntryPointModule), "SchemaManipulation")] -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { public static class SchemaManipulation { diff --git a/src/Microsoft.ML.Data/EntryPoints/ScoreColumnSelector.cs b/src/Microsoft.ML.Data/EntryPoints/ScoreColumnSelector.cs index 6ea0d84289..c1bc095465 100644 --- a/src/Microsoft.ML.Data/EntryPoints/ScoreColumnSelector.cs +++ b/src/Microsoft.ML.Data/EntryPoints/ScoreColumnSelector.cs @@ -3,14 +3,13 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.CommandLine; using Microsoft.ML.Transforms; using System; using System.Collections.Generic; using System.Linq; -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { public static partial class ScoreModel { diff --git a/src/Microsoft.ML.Data/EntryPoints/ScoreModel.cs b/src/Microsoft.ML.Data/EntryPoints/ScoreModel.cs index 1792303468..39982369fc 100644 --- a/src/Microsoft.ML.Data/EntryPoints/ScoreModel.cs +++ b/src/Microsoft.ML.Data/EntryPoints/ScoreModel.cs @@ -3,14 +3,14 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; [assembly: LoadableClass(typeof(void), typeof(ScoreModel), null, typeof(SignatureEntryPointModule), "ScoreModel")] -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { /// /// This module handles scoring a against a new dataset. diff --git a/src/Microsoft.ML.Data/EntryPoints/SelectRows.cs b/src/Microsoft.ML.Data/EntryPoints/SelectRows.cs index eaabf248dc..ddee42fa1f 100644 --- a/src/Microsoft.ML.Data/EntryPoints/SelectRows.cs +++ b/src/Microsoft.ML.Data/EntryPoints/SelectRows.cs @@ -2,12 +2,12 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML.EntryPoints; using Microsoft.ML.Transforms; [assembly: EntryPointModule(typeof(SelectRows))] -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { public static class SelectRows { diff --git a/src/Microsoft.ML.Data/EntryPoints/SummarizePredictor.cs b/src/Microsoft.ML.Data/EntryPoints/SummarizePredictor.cs index 12cee16b3b..80919b5024 100644 --- a/src/Microsoft.ML.Data/EntryPoints/SummarizePredictor.cs +++ b/src/Microsoft.ML.Data/EntryPoints/SummarizePredictor.cs @@ -4,15 +4,15 @@ using System.IO; using System.Text; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Internallearn; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Internallearn; [assembly: EntryPointModule(typeof(SummarizePredictor))] -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { public static class SummarizePredictor { diff --git a/src/Microsoft.ML.Data/EntryPoints/TransformModelImpl.cs b/src/Microsoft.ML.Data/EntryPoints/TransformModelImpl.cs index e3213151fc..091d3d6d6f 100644 --- a/src/Microsoft.ML.Data/EntryPoints/TransformModelImpl.cs +++ b/src/Microsoft.ML.Data/EntryPoints/TransformModelImpl.cs @@ -6,12 +6,11 @@ using System.Collections.Generic; using System.IO; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { /// /// This encapsulates zero or more transform models. It does this by recording diff --git a/src/Microsoft.ML.Data/Evaluators/AnomalyDetectionEvaluator.cs b/src/Microsoft.ML.Data/Evaluators/AnomalyDetectionEvaluator.cs index fff79ebf75..dd6d04cd62 100644 --- a/src/Microsoft.ML.Data/Evaluators/AnomalyDetectionEvaluator.cs +++ b/src/Microsoft.ML.Data/Evaluators/AnomalyDetectionEvaluator.cs @@ -3,11 +3,10 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Transforms; using System; using System.Collections.Generic; @@ -20,7 +19,7 @@ [assembly: LoadableClass(typeof(AnomalyDetectionMamlEvaluator), typeof(AnomalyDetectionMamlEvaluator), typeof(AnomalyDetectionMamlEvaluator.Arguments), typeof(SignatureMamlEvaluator), "Anomaly Detection Evaluator", AnomalyDetectionEvaluator.LoadName, "AnomalyDetection", "Anomaly")] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { public sealed class AnomalyDetectionEvaluator : EvaluatorBase { diff --git a/src/Microsoft.ML.Data/Evaluators/AucAggregator.cs b/src/Microsoft.ML.Data/Evaluators/AucAggregator.cs index f2fbe9d238..73c64070d0 100644 --- a/src/Microsoft.ML.Data/Evaluators/AucAggregator.cs +++ b/src/Microsoft.ML.Data/Evaluators/AucAggregator.cs @@ -5,9 +5,9 @@ using System; using System.Collections.Generic; using System.Linq; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { public abstract partial class EvaluatorBase { diff --git a/src/Microsoft.ML.Data/Evaluators/BinaryClassifierEvaluator.cs b/src/Microsoft.ML.Data/Evaluators/BinaryClassifierEvaluator.cs index 7fed38a710..ff3515d444 100644 --- a/src/Microsoft.ML.Data/Evaluators/BinaryClassifierEvaluator.cs +++ b/src/Microsoft.ML.Data/Evaluators/BinaryClassifierEvaluator.cs @@ -3,12 +3,11 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms; using System; using System.Collections.Generic; @@ -26,7 +25,7 @@ [assembly: LoadableClass(typeof(void), typeof(Evaluate), null, typeof(SignatureEntryPointModule), "Evaluators")] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { public sealed class BinaryClassifierEvaluator : RowToRowEvaluatorBase { diff --git a/src/Microsoft.ML.Data/Evaluators/ClusteringEvaluator.cs b/src/Microsoft.ML.Data/Evaluators/ClusteringEvaluator.cs index 79d8ed42b7..d703890480 100644 --- a/src/Microsoft.ML.Data/Evaluators/ClusteringEvaluator.cs +++ b/src/Microsoft.ML.Data/Evaluators/ClusteringEvaluator.cs @@ -3,13 +3,12 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Numeric; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Numeric; using Microsoft.ML.Transforms.FeatureSelection; using System; using System.Collections.Generic; @@ -25,7 +24,7 @@ [assembly: LoadableClass(typeof(ClusteringPerInstanceEvaluator), null, typeof(SignatureLoadRowMapper), "", ClusteringPerInstanceEvaluator.LoaderSignature)] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { using Conditional = System.Diagnostics.ConditionalAttribute; diff --git a/src/Microsoft.ML.Data/Evaluators/EvaluatorBase.cs b/src/Microsoft.ML.Data/Evaluators/EvaluatorBase.cs index 5a897a8793..58cc19579a 100644 --- a/src/Microsoft.ML.Data/Evaluators/EvaluatorBase.cs +++ b/src/Microsoft.ML.Data/Evaluators/EvaluatorBase.cs @@ -7,10 +7,10 @@ using System.Linq; using System.Reflection; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// This is a base class for TLC evaluators. It implements both of the methods: and diff --git a/src/Microsoft.ML.Data/Evaluators/EvaluatorStaticExtensions.cs b/src/Microsoft.ML.Data/Evaluators/EvaluatorStaticExtensions.cs index 46972dc75d..55f360d879 100644 --- a/src/Microsoft.ML.Data/Evaluators/EvaluatorStaticExtensions.cs +++ b/src/Microsoft.ML.Data/Evaluators/EvaluatorStaticExtensions.cs @@ -4,11 +4,11 @@ using System; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML.Training; using Microsoft.ML.StaticPipe; using Microsoft.ML.StaticPipe.Runtime; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Extension methods for evaluation. diff --git a/src/Microsoft.ML.Data/Evaluators/EvaluatorUtils.cs b/src/Microsoft.ML.Data/Evaluators/EvaluatorUtils.cs index 095ad1bb5c..e85444921f 100644 --- a/src/Microsoft.ML.Data/Evaluators/EvaluatorUtils.cs +++ b/src/Microsoft.ML.Data/Evaluators/EvaluatorUtils.cs @@ -4,8 +4,8 @@ #pragma warning disable 420 // volatile with Interlocked.CompareExchange using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Conversions; using System; @@ -15,7 +15,7 @@ using System.Text; using System.Threading; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { [BestFriend] internal static class EvaluateUtils diff --git a/src/Microsoft.ML.Data/Evaluators/MamlEvaluator.cs b/src/Microsoft.ML.Data/Evaluators/MamlEvaluator.cs index 3c8e3d9c82..e67d468119 100644 --- a/src/Microsoft.ML.Data/Evaluators/MamlEvaluator.cs +++ b/src/Microsoft.ML.Data/Evaluators/MamlEvaluator.cs @@ -3,13 +3,13 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; using Microsoft.ML.Transforms; using System.Collections.Generic; using System.Linq; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// This interface is used by Maml components (the , the diff --git a/src/Microsoft.ML.Data/Evaluators/Metrics/BinaryClassificationMetrics.cs b/src/Microsoft.ML.Data/Evaluators/Metrics/BinaryClassificationMetrics.cs index 59a0c2c700..74f81d4719 100644 --- a/src/Microsoft.ML.Data/Evaluators/Metrics/BinaryClassificationMetrics.cs +++ b/src/Microsoft.ML.Data/Evaluators/Metrics/BinaryClassificationMetrics.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; namespace Microsoft.ML.Data { diff --git a/src/Microsoft.ML.Data/Evaluators/Metrics/CalibratedBinaryClassificationMetrics.cs b/src/Microsoft.ML.Data/Evaluators/Metrics/CalibratedBinaryClassificationMetrics.cs index 7a8787eeff..bfc65d5c95 100644 --- a/src/Microsoft.ML.Data/Evaluators/Metrics/CalibratedBinaryClassificationMetrics.cs +++ b/src/Microsoft.ML.Data/Evaluators/Metrics/CalibratedBinaryClassificationMetrics.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; namespace Microsoft.ML.Data { diff --git a/src/Microsoft.ML.Data/Evaluators/Metrics/ClusteringMetrics.cs b/src/Microsoft.ML.Data/Evaluators/Metrics/ClusteringMetrics.cs index 7537fc9c3a..a0e3c2becc 100644 --- a/src/Microsoft.ML.Data/Evaluators/Metrics/ClusteringMetrics.cs +++ b/src/Microsoft.ML.Data/Evaluators/Metrics/ClusteringMetrics.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; namespace Microsoft.ML.Data { diff --git a/src/Microsoft.ML.Data/Evaluators/Metrics/MultiClassClassifierMetrics.cs b/src/Microsoft.ML.Data/Evaluators/Metrics/MultiClassClassifierMetrics.cs index a89502a33c..8bff650c50 100644 --- a/src/Microsoft.ML.Data/Evaluators/Metrics/MultiClassClassifierMetrics.cs +++ b/src/Microsoft.ML.Data/Evaluators/Metrics/MultiClassClassifierMetrics.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; namespace Microsoft.ML.Data { diff --git a/src/Microsoft.ML.Data/Evaluators/Metrics/RankerMetrics.cs b/src/Microsoft.ML.Data/Evaluators/Metrics/RankerMetrics.cs index 2eb5aaee13..7f593dedb0 100644 --- a/src/Microsoft.ML.Data/Evaluators/Metrics/RankerMetrics.cs +++ b/src/Microsoft.ML.Data/Evaluators/Metrics/RankerMetrics.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; namespace Microsoft.ML.Data { diff --git a/src/Microsoft.ML.Data/Evaluators/Metrics/RegressionMetrics.cs b/src/Microsoft.ML.Data/Evaluators/Metrics/RegressionMetrics.cs index 8bda753e21..9cca21517e 100644 --- a/src/Microsoft.ML.Data/Evaluators/Metrics/RegressionMetrics.cs +++ b/src/Microsoft.ML.Data/Evaluators/Metrics/RegressionMetrics.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; namespace Microsoft.ML.Data { diff --git a/src/Microsoft.ML.Data/Evaluators/MultiClassClassifierEvaluator.cs b/src/Microsoft.ML.Data/Evaluators/MultiClassClassifierEvaluator.cs index 8c47d9a790..06d8c210ca 100644 --- a/src/Microsoft.ML.Data/Evaluators/MultiClassClassifierEvaluator.cs +++ b/src/Microsoft.ML.Data/Evaluators/MultiClassClassifierEvaluator.cs @@ -3,12 +3,11 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.FeatureSelection; using System; @@ -26,7 +25,7 @@ [assembly: LoadableClass(typeof(MultiClassPerInstanceEvaluator), null, typeof(SignatureLoadRowMapper), "", MultiClassPerInstanceEvaluator.LoaderSignature)] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { public sealed class MultiClassClassifierEvaluator : RowToRowEvaluatorBase { diff --git a/src/Microsoft.ML.Data/Evaluators/MultiOutputRegressionEvaluator.cs b/src/Microsoft.ML.Data/Evaluators/MultiOutputRegressionEvaluator.cs index 0b383e8c61..c5823bb99c 100644 --- a/src/Microsoft.ML.Data/Evaluators/MultiOutputRegressionEvaluator.cs +++ b/src/Microsoft.ML.Data/Evaluators/MultiOutputRegressionEvaluator.cs @@ -3,13 +3,12 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Numeric; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Numeric; using System; using System.Collections.Generic; using System.Text; @@ -26,7 +25,7 @@ [assembly: LoadableClass(typeof(MultiOutputRegressionPerInstanceEvaluator), null, typeof(SignatureLoadRowMapper), "", MultiOutputRegressionPerInstanceEvaluator.LoaderSignature)] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { public sealed class MultiOutputRegressionEvaluator : RegressionLossEvaluatorBase { diff --git a/src/Microsoft.ML.Data/Evaluators/QuantileRegressionEvaluator.cs b/src/Microsoft.ML.Data/Evaluators/QuantileRegressionEvaluator.cs index bfeb0e5ebf..15b7ee6992 100644 --- a/src/Microsoft.ML.Data/Evaluators/QuantileRegressionEvaluator.cs +++ b/src/Microsoft.ML.Data/Evaluators/QuantileRegressionEvaluator.cs @@ -3,12 +3,11 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using System; using System.Collections.Generic; using Float = System.Single; @@ -23,7 +22,7 @@ [assembly: LoadableClass(typeof(QuantileRegressionPerInstanceEvaluator), null, typeof(SignatureLoadRowMapper), "", QuantileRegressionPerInstanceEvaluator.LoaderSignature)] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { public sealed class QuantileRegressionEvaluator : RegressionEvaluatorBase, VBuffer> diff --git a/src/Microsoft.ML.Data/Evaluators/RankerEvaluator.cs b/src/Microsoft.ML.Data/Evaluators/RankerEvaluator.cs index b9cec5d2d6..8d72e6eaa2 100644 --- a/src/Microsoft.ML.Data/Evaluators/RankerEvaluator.cs +++ b/src/Microsoft.ML.Data/Evaluators/RankerEvaluator.cs @@ -10,12 +10,11 @@ using System.Text.RegularExpressions; using System.Threading; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; [assembly: LoadableClass(typeof(RankerEvaluator), typeof(RankerEvaluator), typeof(RankerEvaluator.Arguments), typeof(SignatureEvaluator), "Ranking Evaluator", RankerEvaluator.LoadName, "Ranking", "rank")] @@ -26,7 +25,7 @@ [assembly: LoadableClass(typeof(RankerPerInstanceTransform), null, typeof(SignatureLoadDataTransform), "", RankerPerInstanceTransform.LoaderSignature)] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { public sealed class RankerEvaluator : EvaluatorBase { diff --git a/src/Microsoft.ML.Data/Evaluators/RegressionEvaluator.cs b/src/Microsoft.ML.Data/Evaluators/RegressionEvaluator.cs index e5af2e8bad..f31a22ea06 100644 --- a/src/Microsoft.ML.Data/Evaluators/RegressionEvaluator.cs +++ b/src/Microsoft.ML.Data/Evaluators/RegressionEvaluator.cs @@ -4,11 +4,10 @@ using Float = System.Single; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Model; +using Microsoft.ML; using System.Collections.Generic; using System; @@ -22,7 +21,7 @@ [assembly: LoadableClass(typeof(RegressionPerInstanceEvaluator), null, typeof(SignatureLoadRowMapper), "", RegressionPerInstanceEvaluator.LoaderSignature)] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { public sealed class RegressionEvaluator : RegressionEvaluatorBase diff --git a/src/Microsoft.ML.Data/Evaluators/RegressionEvaluatorBase.cs b/src/Microsoft.ML.Data/Evaluators/RegressionEvaluatorBase.cs index 9a5634de80..0dcb516339 100644 --- a/src/Microsoft.ML.Data/Evaluators/RegressionEvaluatorBase.cs +++ b/src/Microsoft.ML.Data/Evaluators/RegressionEvaluatorBase.cs @@ -5,10 +5,10 @@ using System; using System.Collections.Generic; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { public abstract class RegressionLossEvaluatorBase : RowToRowEvaluatorBase where TAgg : EvaluatorBase.AggregatorBase diff --git a/src/Microsoft.ML.Data/MLContext.cs b/src/Microsoft.ML.Data/MLContext.cs index 326562a978..6eef3d51bf 100644 --- a/src/Microsoft.ML.Data/MLContext.cs +++ b/src/Microsoft.ML.Data/MLContext.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using System; using System.ComponentModel.Composition; using System.ComponentModel.Composition.Hosting; diff --git a/src/Microsoft.ML.Data/Model/ModelHeader.cs b/src/Microsoft.ML.Data/Model/ModelHeader.cs index b74d0fdca6..84bf57f23a 100644 --- a/src/Microsoft.ML.Data/Model/ModelHeader.cs +++ b/src/Microsoft.ML.Data/Model/ModelHeader.cs @@ -7,9 +7,9 @@ using System.Reflection; using System.Runtime.InteropServices; using System.Text; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Model +namespace Microsoft.ML.Model { [StructLayout(LayoutKind.Explicit, Size = ModelHeader.Size)] internal struct ModelHeader diff --git a/src/Microsoft.ML.Data/Model/ModelLoadContext.cs b/src/Microsoft.ML.Data/Model/ModelLoadContext.cs index 749a226012..8838b031de 100644 --- a/src/Microsoft.ML.Data/Model/ModelLoadContext.cs +++ b/src/Microsoft.ML.Data/Model/ModelLoadContext.cs @@ -5,9 +5,9 @@ using System; using System.IO; using System.Text; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Model +namespace Microsoft.ML.Model { /// /// This is a convenience context object for loading models from a repository, for diff --git a/src/Microsoft.ML.Data/Model/ModelLoading.cs b/src/Microsoft.ML.Data/Model/ModelLoading.cs index 981da9e797..06ebc0bf06 100644 --- a/src/Microsoft.ML.Data/Model/ModelLoading.cs +++ b/src/Microsoft.ML.Data/Model/ModelLoading.cs @@ -6,9 +6,9 @@ using System.IO; using System.Reflection; using System.Text; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Model +namespace Microsoft.ML.Model { public sealed partial class ModelLoadContext : IDisposable { diff --git a/src/Microsoft.ML.Data/Model/ModelOperationsCatalog.cs b/src/Microsoft.ML.Data/Model/ModelOperationsCatalog.cs index 63fcd75779..c91225c4b9 100644 --- a/src/Microsoft.ML.Data/Model/ModelOperationsCatalog.cs +++ b/src/Microsoft.ML.Data/Model/ModelOperationsCatalog.cs @@ -4,10 +4,9 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; using System.IO; -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { /// /// An object serving as a 'catalog' of available model operations. diff --git a/src/Microsoft.ML.Data/Model/ModelSaveContext.cs b/src/Microsoft.ML.Data/Model/ModelSaveContext.cs index eee8d23df7..d8da3f4edb 100644 --- a/src/Microsoft.ML.Data/Model/ModelSaveContext.cs +++ b/src/Microsoft.ML.Data/Model/ModelSaveContext.cs @@ -5,9 +5,9 @@ using System; using System.IO; using System.Text; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Model +namespace Microsoft.ML.Model { /// /// This is a convenience context object for saving models to a repository, for diff --git a/src/Microsoft.ML.Data/Model/ModelSaving.cs b/src/Microsoft.ML.Data/Model/ModelSaving.cs index da15986d9d..a73e631bbe 100644 --- a/src/Microsoft.ML.Data/Model/ModelSaving.cs +++ b/src/Microsoft.ML.Data/Model/ModelSaving.cs @@ -6,7 +6,7 @@ using System.IO; using System.Text; -namespace Microsoft.ML.Runtime.Model +namespace Microsoft.ML.Model { public sealed partial class ModelSaveContext : IDisposable { diff --git a/src/Microsoft.ML.Data/Model/Onnx/ICanSaveOnnx.cs b/src/Microsoft.ML.Data/Model/Onnx/ICanSaveOnnx.cs index 5e3dce06be..33c9f628e5 100644 --- a/src/Microsoft.ML.Data/Model/Onnx/ICanSaveOnnx.cs +++ b/src/Microsoft.ML.Data/Model/Onnx/ICanSaveOnnx.cs @@ -2,10 +2,10 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; using Microsoft.ML.Calibrator; -namespace Microsoft.ML.Runtime.Model.Onnx +namespace Microsoft.ML.Model.Onnx { [BestFriend] internal interface ICanSaveOnnx diff --git a/src/Microsoft.ML.Data/Model/Onnx/OnnxContext.cs b/src/Microsoft.ML.Data/Model/Onnx/OnnxContext.cs index 38d9f77915..d8685af52c 100644 --- a/src/Microsoft.ML.Data/Model/Onnx/OnnxContext.cs +++ b/src/Microsoft.ML.Data/Model/Onnx/OnnxContext.cs @@ -3,9 +3,9 @@ // See the LICENSE file in the project root for more information. using System.Collections.Generic; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; -namespace Microsoft.ML.Runtime.Model.Onnx +namespace Microsoft.ML.Model.Onnx { [BestFriend] internal enum OnnxVersion { Stable = 0, Experimental = 1 } diff --git a/src/Microsoft.ML.Data/Model/Onnx/OnnxNode.cs b/src/Microsoft.ML.Data/Model/Onnx/OnnxNode.cs index 79df068b9b..45f86e2647 100644 --- a/src/Microsoft.ML.Data/Model/Onnx/OnnxNode.cs +++ b/src/Microsoft.ML.Data/Model/Onnx/OnnxNode.cs @@ -4,9 +4,9 @@ using System; using System.Collections.Generic; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; -namespace Microsoft.ML.Runtime.Model.Onnx +namespace Microsoft.ML.Model.Onnx { /// /// An abstraction for an ONNX node as created by diff --git a/src/Microsoft.ML.Data/Model/Pfa/BoundPfaContext.cs b/src/Microsoft.ML.Data/Model/Pfa/BoundPfaContext.cs index 959a7df2c1..997b4d0dc8 100644 --- a/src/Microsoft.ML.Data/Model/Pfa/BoundPfaContext.cs +++ b/src/Microsoft.ML.Data/Model/Pfa/BoundPfaContext.cs @@ -5,10 +5,9 @@ using System.Collections.Generic; using System.Linq; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; using Newtonsoft.Json.Linq; -namespace Microsoft.ML.Runtime.Model.Pfa +namespace Microsoft.ML.Model.Pfa { using T = PfaUtils.Type; diff --git a/src/Microsoft.ML.Data/Model/Pfa/ICanSavePfa.cs b/src/Microsoft.ML.Data/Model/Pfa/ICanSavePfa.cs index e442960b40..cc07e75a3c 100644 --- a/src/Microsoft.ML.Data/Model/Pfa/ICanSavePfa.cs +++ b/src/Microsoft.ML.Data/Model/Pfa/ICanSavePfa.cs @@ -3,10 +3,10 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Calibrator; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; using Newtonsoft.Json.Linq; -namespace Microsoft.ML.Runtime.Model.Pfa +namespace Microsoft.ML.Model.Pfa { [BestFriend] internal interface ICanSavePfa diff --git a/src/Microsoft.ML.Data/Model/Pfa/ModelUtils.cs b/src/Microsoft.ML.Data/Model/Pfa/ModelUtils.cs index 110296e1d0..e33a9ae4a6 100644 --- a/src/Microsoft.ML.Data/Model/Pfa/ModelUtils.cs +++ b/src/Microsoft.ML.Data/Model/Pfa/ModelUtils.cs @@ -4,7 +4,7 @@ using System; -namespace Microsoft.ML.Runtime.Model +namespace Microsoft.ML.Model { internal static class ModelUtils { diff --git a/src/Microsoft.ML.Data/Model/Pfa/PfaContext.cs b/src/Microsoft.ML.Data/Model/Pfa/PfaContext.cs index 2d89916028..9619e195ca 100644 --- a/src/Microsoft.ML.Data/Model/Pfa/PfaContext.cs +++ b/src/Microsoft.ML.Data/Model/Pfa/PfaContext.cs @@ -6,7 +6,7 @@ using System.Linq; using Newtonsoft.Json.Linq; -namespace Microsoft.ML.Runtime.Model.Pfa +namespace Microsoft.ML.Model.Pfa { /// /// A context for defining a restricted sort of PFA output. diff --git a/src/Microsoft.ML.Data/Model/Pfa/PfaUtils.cs b/src/Microsoft.ML.Data/Model/Pfa/PfaUtils.cs index 9b4f6bcf3f..9215e233e0 100644 --- a/src/Microsoft.ML.Data/Model/Pfa/PfaUtils.cs +++ b/src/Microsoft.ML.Data/Model/Pfa/PfaUtils.cs @@ -2,11 +2,11 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; using Newtonsoft.Json.Linq; -namespace Microsoft.ML.Runtime.Model.Pfa +namespace Microsoft.ML.Model.Pfa { [BestFriend] internal static class PfaUtils diff --git a/src/Microsoft.ML.Data/Model/Pfa/SavePfaCommand.cs b/src/Microsoft.ML.Data/Model/Pfa/SavePfaCommand.cs index c2890a5bbf..685fdacab2 100644 --- a/src/Microsoft.ML.Data/Model/Pfa/SavePfaCommand.cs +++ b/src/Microsoft.ML.Data/Model/Pfa/SavePfaCommand.cs @@ -5,19 +5,19 @@ using System; using System.Collections.Generic; using System.IO; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Command; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model.Pfa; +using Microsoft.ML; +using Microsoft.ML.Command; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model.Pfa; using Newtonsoft.Json; using Newtonsoft.Json.Linq; [assembly: LoadableClass(SavePfaCommand.Summary, typeof(SavePfaCommand), typeof(SavePfaCommand.Arguments), typeof(SignatureCommand), "Save PFA", "SavePfa", DocName = "command/SavePfa.md")] -namespace Microsoft.ML.Runtime.Model.Pfa +namespace Microsoft.ML.Model.Pfa { internal sealed class SavePfaCommand : DataCommand.ImplBase { diff --git a/src/Microsoft.ML.Data/Model/PredictionEngineExtensions.cs b/src/Microsoft.ML.Data/Model/PredictionEngineExtensions.cs index 59b473fe4a..bc288ef864 100644 --- a/src/Microsoft.ML.Data/Model/PredictionEngineExtensions.cs +++ b/src/Microsoft.ML.Data/Model/PredictionEngineExtensions.cs @@ -2,12 +2,8 @@ // 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.Text; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; namespace Microsoft.ML { diff --git a/src/Microsoft.ML.Data/Model/Repository.cs b/src/Microsoft.ML.Data/Model/Repository.cs index c93e6d00b6..4e3b8d89c1 100644 --- a/src/Microsoft.ML.Data/Model/Repository.cs +++ b/src/Microsoft.ML.Data/Model/Repository.cs @@ -6,9 +6,9 @@ using System.Collections.Generic; using System.IO; using System.IO.Compression; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Model +namespace Microsoft.ML.Model { /// /// Signature for a repository based model loader. This is the dual of ICanSaveModel. diff --git a/src/Microsoft.ML.Data/Prediction/Calibrator.cs b/src/Microsoft.ML.Data/Prediction/Calibrator.cs index a894617ce0..f4a73b8aef 100644 --- a/src/Microsoft.ML.Data/Prediction/Calibrator.cs +++ b/src/Microsoft.ML.Data/Prediction/Calibrator.cs @@ -4,16 +4,15 @@ using Microsoft.ML.Calibrator; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Onnx; -using Microsoft.ML.Runtime.Model.Pfa; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Onnx; +using Microsoft.ML.Model.Pfa; using Newtonsoft.Json.Linq; using System; using System.Collections; @@ -80,7 +79,7 @@ [assembly: EntryPointModule(typeof(PavCalibratorTrainerFactory))] [assembly: EntryPointModule(typeof(PlattCalibratorTrainerFactory))] -namespace Microsoft.ML.Runtime.Internal.Calibration +namespace Microsoft.ML.Internal.Calibration { /// /// Signature for the loaders of calibrators. diff --git a/src/Microsoft.ML.Data/Prediction/CalibratorCatalog.cs b/src/Microsoft.ML.Data/Prediction/CalibratorCatalog.cs index 08460a27c5..788debbd58 100644 --- a/src/Microsoft.ML.Data/Prediction/CalibratorCatalog.cs +++ b/src/Microsoft.ML.Data/Prediction/CalibratorCatalog.cs @@ -5,11 +5,10 @@ using Microsoft.ML.Calibrator; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Model; +using Microsoft.ML.Training; using System; using System.Collections.Generic; using System.Linq; diff --git a/src/Microsoft.ML.Data/Prediction/IPredictionTransformer.cs b/src/Microsoft.ML.Data/Prediction/IPredictionTransformer.cs index d3f1e9ddf2..9292edbe9b 100644 --- a/src/Microsoft.ML.Data/Prediction/IPredictionTransformer.cs +++ b/src/Microsoft.ML.Data/Prediction/IPredictionTransformer.cs @@ -4,9 +4,9 @@ using Microsoft.ML.Calibrator; using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { /// /// An interface for all the transformer that can transform data based on the field. diff --git a/src/Microsoft.ML.Data/Prediction/PredictionEngine.cs b/src/Microsoft.ML.Data/Prediction/PredictionEngine.cs index 385343b571..eebcd56ead 100644 --- a/src/Microsoft.ML.Data/Prediction/PredictionEngine.cs +++ b/src/Microsoft.ML.Data/Prediction/PredictionEngine.cs @@ -4,12 +4,11 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; using System; using System.Collections.Generic; using System.IO; -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { // REVIEW: Temporarly moving here since it is used by the Legacy project. Remove when removing the legacy project. /// diff --git a/src/Microsoft.ML.Data/Properties/AssemblyInfo.cs b/src/Microsoft.ML.Data/Properties/AssemblyInfo.cs index 9d001f1a7f..43587d4544 100644 --- a/src/Microsoft.ML.Data/Properties/AssemblyInfo.cs +++ b/src/Microsoft.ML.Data/Properties/AssemblyInfo.cs @@ -30,7 +30,7 @@ [assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.PCA" + PublicKey.Value)] [assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.PipelineInference" + PublicKey.Value)] [assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.Recommender" + PublicKey.Value)] -[assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.Runtime.ImageAnalytics" + PublicKey.Value)] +[assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.ImageAnalytics" + PublicKey.Value)] [assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.Scoring" + PublicKey.Value)] [assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.StandardLearners" + PublicKey.Value)] [assembly: InternalsVisibleTo(assemblyName: "Microsoft.ML.Sweeper" + PublicKey.Value)] diff --git a/src/Microsoft.ML.Data/Scorers/BinaryClassifierScorer.cs b/src/Microsoft.ML.Data/Scorers/BinaryClassifierScorer.cs index 46a8f29e6e..270f0ec3a6 100644 --- a/src/Microsoft.ML.Data/Scorers/BinaryClassifierScorer.cs +++ b/src/Microsoft.ML.Data/Scorers/BinaryClassifierScorer.cs @@ -3,12 +3,11 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Onnx; -using Microsoft.ML.Runtime.Model.Pfa; +using Microsoft.ML; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Onnx; +using Microsoft.ML.Model.Pfa; using Newtonsoft.Json.Linq; using System; @@ -21,7 +20,7 @@ [assembly: LoadableClass(typeof(BinaryClassifierScorer), null, typeof(SignatureLoadDataTransform), "Binary Classifier Scorer", BinaryClassifierScorer.LoaderSignature)] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { public sealed class BinaryClassifierScorer : PredictedLabelScorerBase, ITransformCanSaveOnnx { diff --git a/src/Microsoft.ML.Data/Scorers/ClusteringScorer.cs b/src/Microsoft.ML.Data/Scorers/ClusteringScorer.cs index 1b5aa01c05..15d940d298 100644 --- a/src/Microsoft.ML.Data/Scorers/ClusteringScorer.cs +++ b/src/Microsoft.ML.Data/Scorers/ClusteringScorer.cs @@ -6,12 +6,11 @@ using System; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Pfa; -using Microsoft.ML.Runtime.Numeric; +using Microsoft.ML; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Pfa; +using Microsoft.ML.Numeric; using Newtonsoft.Json.Linq; [assembly: LoadableClass(typeof(ClusteringScorer), typeof(ClusteringScorer.Arguments), typeof(SignatureDataScorer), @@ -20,7 +19,7 @@ [assembly: LoadableClass(typeof(ClusteringScorer), null, typeof(SignatureLoadDataTransform), "Clustering Scorer", ClusteringScorer.LoaderSignature)] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { public sealed class ClusteringScorer : PredictedLabelScorerBase { diff --git a/src/Microsoft.ML.Data/Scorers/FeatureContributionCalculation.cs b/src/Microsoft.ML.Data/Scorers/FeatureContributionCalculation.cs index f4357bb246..b7a23752da 100644 --- a/src/Microsoft.ML.Data/Scorers/FeatureContributionCalculation.cs +++ b/src/Microsoft.ML.Data/Scorers/FeatureContributionCalculation.cs @@ -7,13 +7,12 @@ using System.Reflection; using System.Text; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Numeric; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Numeric; [assembly: LoadableClass(typeof(IDataScorerTransform), typeof(FeatureContributionScorer), typeof(FeatureContributionScorer.Arguments), typeof(SignatureDataScorer), "Feature Contribution Scorer", "fcc", "wtf", "fct", "FeatureContributionCalculationScorer", MetadataUtils.Const.ScoreColumnKind.FeatureContribution)] @@ -24,7 +23,7 @@ [assembly: LoadableClass(typeof(ISchemaBindableMapper), typeof(FeatureContributionScorer), null, typeof(SignatureLoadModel), "Feature Contribution Mapper", FeatureContributionScorer.MapperLoaderSignature)] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Used only by the command line API for scoring and calculation of feature contribution. diff --git a/src/Microsoft.ML.Data/Scorers/GenericScorer.cs b/src/Microsoft.ML.Data/Scorers/GenericScorer.cs index e7e060cd98..db55bd0cef 100644 --- a/src/Microsoft.ML.Data/Scorers/GenericScorer.cs +++ b/src/Microsoft.ML.Data/Scorers/GenericScorer.cs @@ -5,11 +5,10 @@ using System; using System.Collections.Generic; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Onnx; -using Microsoft.ML.Runtime.Model.Pfa; +using Microsoft.ML; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Onnx; +using Microsoft.ML.Model.Pfa; [assembly: LoadableClass(typeof(GenericScorer), typeof(GenericScorer.Arguments), typeof(SignatureDataScorer), "Generic Scorer", GenericScorer.LoadName, "Generic")] @@ -17,7 +16,7 @@ [assembly: LoadableClass(typeof(GenericScorer), null, typeof(SignatureLoadDataTransform), "Generic Scorer", GenericScorer.LoaderSignature)] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// This class is a scorer that passes through all the ISchemaBound columns without adding any "derived columns". diff --git a/src/Microsoft.ML.Data/Scorers/MultiClassClassifierScorer.cs b/src/Microsoft.ML.Data/Scorers/MultiClassClassifierScorer.cs index e052a55870..fc198369ac 100644 --- a/src/Microsoft.ML.Data/Scorers/MultiClassClassifierScorer.cs +++ b/src/Microsoft.ML.Data/Scorers/MultiClassClassifierScorer.cs @@ -3,14 +3,13 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Onnx; -using Microsoft.ML.Runtime.Model.Pfa; -using Microsoft.ML.Runtime.Numeric; +using Microsoft.ML; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Onnx; +using Microsoft.ML.Model.Pfa; +using Microsoft.ML.Numeric; using Newtonsoft.Json.Linq; using System; using System.Collections.Generic; @@ -28,7 +27,7 @@ [assembly: LoadableClass(typeof(ISchemaBindableMapper), typeof(MultiClassClassifierScorer.LabelNameBindableMapper), null, typeof(SignatureLoadModel), "Multi-Class Label-Name Mapper", MultiClassClassifierScorer.LabelNameBindableMapper.LoaderSignature)] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { public sealed class MultiClassClassifierScorer : PredictedLabelScorerBase { diff --git a/src/Microsoft.ML.Data/Scorers/PredictedLabelScorerBase.cs b/src/Microsoft.ML.Data/Scorers/PredictedLabelScorerBase.cs index a30c88ab8b..b2e7390649 100644 --- a/src/Microsoft.ML.Data/Scorers/PredictedLabelScorerBase.cs +++ b/src/Microsoft.ML.Data/Scorers/PredictedLabelScorerBase.cs @@ -3,17 +3,17 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Onnx; -using Microsoft.ML.Runtime.Model.Pfa; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Onnx; +using Microsoft.ML.Model.Pfa; using Newtonsoft.Json.Linq; using System; using System.Collections.Generic; using Float = System.Single; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Class for scorers that compute on additional "PredictedLabel" column from the score column. diff --git a/src/Microsoft.ML.Data/Scorers/PredictionTransformer.cs b/src/Microsoft.ML.Data/Scorers/PredictionTransformer.cs index 08bf96af22..1a36823bce 100644 --- a/src/Microsoft.ML.Data/Scorers/PredictionTransformer.cs +++ b/src/Microsoft.ML.Data/Scorers/PredictionTransformer.cs @@ -4,10 +4,9 @@ using System.IO; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Model; [assembly: LoadableClass(typeof(BinaryPredictionTransformer>), typeof(BinaryPredictionTransformer), null, typeof(SignatureLoadModel), "", BinaryPredictionTransformer.LoaderSignature)] @@ -27,7 +26,7 @@ [assembly: LoadableClass(typeof(ClusteringPredictionTransformer>>), typeof(ClusteringPredictionTransformer), null, typeof(SignatureLoadModel), "", ClusteringPredictionTransformer.LoaderSignature)] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// diff --git a/src/Microsoft.ML.Data/Scorers/QuantileRegressionScorer.cs b/src/Microsoft.ML.Data/Scorers/QuantileRegressionScorer.cs index 2dec3a0e4a..ba7a00d3bf 100644 --- a/src/Microsoft.ML.Data/Scorers/QuantileRegressionScorer.cs +++ b/src/Microsoft.ML.Data/Scorers/QuantileRegressionScorer.cs @@ -5,10 +5,9 @@ using System; using System.Linq; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Internallearn; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Internallearn; [assembly: LoadableClass(typeof(IDataScorerTransform), typeof(QuantileRegressionScorerTransform), typeof(QuantileRegressionScorerTransform.Arguments), typeof(SignatureDataScorer), "Quantile Regression Scorer", "QuantileRegressionScorer", MetadataUtils.Const.ScoreColumnKind.QuantileRegression)] @@ -16,7 +15,7 @@ [assembly: LoadableClass(typeof(ISchemaBindableMapper), typeof(QuantileRegressionScorerTransform), typeof(QuantileRegressionScorerTransform.Arguments), typeof(SignatureBindableMapper), "Quantile Regression Mapper", "QuantileRegressionScorer", MetadataUtils.Const.ScoreColumnKind.QuantileRegression)] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { internal static class QuantileRegressionScorerTransform { diff --git a/src/Microsoft.ML.Data/Scorers/RowToRowScorerBase.cs b/src/Microsoft.ML.Data/Scorers/RowToRowScorerBase.cs index 4b0afe59c1..dba5c4289a 100644 --- a/src/Microsoft.ML.Data/Scorers/RowToRowScorerBase.cs +++ b/src/Microsoft.ML.Data/Scorers/RowToRowScorerBase.cs @@ -7,10 +7,10 @@ using System.Linq; using System.Reflection; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Model; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Base class for scoring rows independently. This assumes that all columns produced by the diff --git a/src/Microsoft.ML.Data/Scorers/SchemaBindablePredictorWrapper.cs b/src/Microsoft.ML.Data/Scorers/SchemaBindablePredictorWrapper.cs index c14893f1da..aade6d061a 100644 --- a/src/Microsoft.ML.Data/Scorers/SchemaBindablePredictorWrapper.cs +++ b/src/Microsoft.ML.Data/Scorers/SchemaBindablePredictorWrapper.cs @@ -5,13 +5,12 @@ #pragma warning disable 420 // volatile with Interlocked.CompareExchange using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Onnx; -using Microsoft.ML.Runtime.Model.Pfa; +using Microsoft.ML; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Onnx; +using Microsoft.ML.Model.Pfa; using Newtonsoft.Json.Linq; using System; using System.Collections.Generic; @@ -28,7 +27,7 @@ [assembly: LoadableClass(typeof(SchemaBindableBinaryPredictorWrapper), null, typeof(SignatureLoadModel), "Binary Classification Bindable Mapper", SchemaBindableBinaryPredictorWrapper.LoaderSignature)] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { // REVIEW: Consider implementing ICanSaveAs(Code/Text/etc.) for these classes as well. /// diff --git a/src/Microsoft.ML.Data/Scorers/ScoreMapperSchema.cs b/src/Microsoft.ML.Data/Scorers/ScoreMapperSchema.cs index 1753d12fc8..fe0995a9c3 100644 --- a/src/Microsoft.ML.Data/Scorers/ScoreMapperSchema.cs +++ b/src/Microsoft.ML.Data/Scorers/ScoreMapperSchema.cs @@ -6,7 +6,7 @@ using System; using System.Collections.Generic; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// A base class for schemas for ISchemaBoundMappers. Takes care of all the metadata that has to do with diff --git a/src/Microsoft.ML.Data/StaticPipe/DataLoadSaveOperationsExtensions.cs b/src/Microsoft.ML.Data/StaticPipe/DataLoadSaveOperationsExtensions.cs index a5f0172935..a7ea5e910d 100644 --- a/src/Microsoft.ML.Data/StaticPipe/DataLoadSaveOperationsExtensions.cs +++ b/src/Microsoft.ML.Data/StaticPipe/DataLoadSaveOperationsExtensions.cs @@ -2,10 +2,10 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using System; -using static Microsoft.ML.Runtime.Data.TextLoader; +using static Microsoft.ML.Data.TextLoader; namespace Microsoft.ML.StaticPipe { diff --git a/src/Microsoft.ML.Data/StaticPipe/DataReader.cs b/src/Microsoft.ML.Data/StaticPipe/DataReader.cs index b17004c20d..f35e430eca 100644 --- a/src/Microsoft.ML.Data/StaticPipe/DataReader.cs +++ b/src/Microsoft.ML.Data/StaticPipe/DataReader.cs @@ -4,8 +4,6 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using Microsoft.ML.StaticPipe.Runtime; namespace Microsoft.ML.StaticPipe diff --git a/src/Microsoft.ML.Data/StaticPipe/DataReaderEstimator.cs b/src/Microsoft.ML.Data/StaticPipe/DataReaderEstimator.cs index 540389414d..8639e3e785 100644 --- a/src/Microsoft.ML.Data/StaticPipe/DataReaderEstimator.cs +++ b/src/Microsoft.ML.Data/StaticPipe/DataReaderEstimator.cs @@ -4,8 +4,6 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using Microsoft.ML.StaticPipe.Runtime; namespace Microsoft.ML.StaticPipe diff --git a/src/Microsoft.ML.Data/StaticPipe/DataView.cs b/src/Microsoft.ML.Data/StaticPipe/DataView.cs index 8d3bdd968b..1b6cc27122 100644 --- a/src/Microsoft.ML.Data/StaticPipe/DataView.cs +++ b/src/Microsoft.ML.Data/StaticPipe/DataView.cs @@ -3,8 +3,6 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using Microsoft.ML.StaticPipe.Runtime; using System.Collections.Generic; using System; diff --git a/src/Microsoft.ML.Data/StaticPipe/Estimator.cs b/src/Microsoft.ML.Data/StaticPipe/Estimator.cs index 3a7eda5fd0..4c8b81cff9 100644 --- a/src/Microsoft.ML.Data/StaticPipe/Estimator.cs +++ b/src/Microsoft.ML.Data/StaticPipe/Estimator.cs @@ -5,9 +5,6 @@ using System; using System.Collections.Generic; using Microsoft.ML.Core.Data; -using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using Microsoft.ML.StaticPipe.Runtime; namespace Microsoft.ML.StaticPipe diff --git a/src/Microsoft.ML.Data/StaticPipe/PipelineColumn.cs b/src/Microsoft.ML.Data/StaticPipe/PipelineColumn.cs index 3d12e10d1d..5aef9eb706 100644 --- a/src/Microsoft.ML.Data/StaticPipe/PipelineColumn.cs +++ b/src/Microsoft.ML.Data/StaticPipe/PipelineColumn.cs @@ -4,8 +4,7 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; using Microsoft.ML.StaticPipe.Runtime; namespace Microsoft.ML.StaticPipe diff --git a/src/Microsoft.ML.Data/StaticPipe/Reconciler.cs b/src/Microsoft.ML.Data/StaticPipe/Reconciler.cs index f60c4d5327..6f376b61e9 100644 --- a/src/Microsoft.ML.Data/StaticPipe/Reconciler.cs +++ b/src/Microsoft.ML.Data/StaticPipe/Reconciler.cs @@ -3,7 +3,7 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; +using Microsoft.ML; using Microsoft.ML.Transforms; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Data/StaticPipe/SchemaAssertionContext.cs b/src/Microsoft.ML.Data/StaticPipe/SchemaAssertionContext.cs index 2457a3852a..eab9600244 100644 --- a/src/Microsoft.ML.Data/StaticPipe/SchemaAssertionContext.cs +++ b/src/Microsoft.ML.Data/StaticPipe/SchemaAssertionContext.cs @@ -3,7 +3,6 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; namespace Microsoft.ML.StaticPipe.Runtime { diff --git a/src/Microsoft.ML.Data/StaticPipe/SchemaBearing.cs b/src/Microsoft.ML.Data/StaticPipe/SchemaBearing.cs index d4010dd28d..60cfdb2a59 100644 --- a/src/Microsoft.ML.Data/StaticPipe/SchemaBearing.cs +++ b/src/Microsoft.ML.Data/StaticPipe/SchemaBearing.cs @@ -3,8 +3,8 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.StaticPipe.Runtime; using System.Threading; diff --git a/src/Microsoft.ML.Data/StaticPipe/StaticPipeExtensions.cs b/src/Microsoft.ML.Data/StaticPipe/StaticPipeExtensions.cs index d0e57b93da..a0b9ded104 100644 --- a/src/Microsoft.ML.Data/StaticPipe/StaticPipeExtensions.cs +++ b/src/Microsoft.ML.Data/StaticPipe/StaticPipeExtensions.cs @@ -2,9 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; using System; -using Microsoft.ML.Runtime; +using Microsoft.ML; using Microsoft.ML.Core.Data; using Microsoft.ML.StaticPipe.Runtime; diff --git a/src/Microsoft.ML.Data/StaticPipe/StaticPipeInternalUtils.cs b/src/Microsoft.ML.Data/StaticPipe/StaticPipeInternalUtils.cs index b5a4fbecf1..0eae14d2f6 100644 --- a/src/Microsoft.ML.Data/StaticPipe/StaticPipeInternalUtils.cs +++ b/src/Microsoft.ML.Data/StaticPipe/StaticPipeInternalUtils.cs @@ -8,10 +8,7 @@ using System.Reflection; using System.Runtime.CompilerServices; using Microsoft.ML.Core.Data; -using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; namespace Microsoft.ML.StaticPipe.Runtime { diff --git a/src/Microsoft.ML.Data/StaticPipe/StaticPipeUtils.cs b/src/Microsoft.ML.Data/StaticPipe/StaticPipeUtils.cs index fa5cb7d477..29ca5d199a 100644 --- a/src/Microsoft.ML.Data/StaticPipe/StaticPipeUtils.cs +++ b/src/Microsoft.ML.Data/StaticPipe/StaticPipeUtils.cs @@ -7,9 +7,7 @@ using System.Collections.Immutable; using System.Linq; using Microsoft.ML.Core.Data; -using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; using Microsoft.ML.Transforms; namespace Microsoft.ML.StaticPipe.Runtime diff --git a/src/Microsoft.ML.Data/StaticPipe/StaticSchemaShape.cs b/src/Microsoft.ML.Data/StaticPipe/StaticSchemaShape.cs index 2b8b5856ce..f162693e1d 100644 --- a/src/Microsoft.ML.Data/StaticPipe/StaticSchemaShape.cs +++ b/src/Microsoft.ML.Data/StaticPipe/StaticSchemaShape.cs @@ -7,8 +7,6 @@ using System.Reflection; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; namespace Microsoft.ML.StaticPipe.Runtime { diff --git a/src/Microsoft.ML.Data/StaticPipe/TrainerEstimatorReconciler.cs b/src/Microsoft.ML.Data/StaticPipe/TrainerEstimatorReconciler.cs index 49e559e78c..48bcf00aa8 100644 --- a/src/Microsoft.ML.Data/StaticPipe/TrainerEstimatorReconciler.cs +++ b/src/Microsoft.ML.Data/StaticPipe/TrainerEstimatorReconciler.cs @@ -4,9 +4,7 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Transforms; using System.Collections.Generic; using System.Linq; diff --git a/src/Microsoft.ML.Data/StaticPipe/Transformer.cs b/src/Microsoft.ML.Data/StaticPipe/Transformer.cs index e3cbff72d2..92566cf3c9 100644 --- a/src/Microsoft.ML.Data/StaticPipe/Transformer.cs +++ b/src/Microsoft.ML.Data/StaticPipe/Transformer.cs @@ -4,7 +4,7 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; +using Microsoft.ML; using Microsoft.ML.StaticPipe.Runtime; namespace Microsoft.ML.StaticPipe diff --git a/src/Microsoft.ML.Data/TrainContext.cs b/src/Microsoft.ML.Data/TrainContext.cs index 970e160685..f79fef57ff 100644 --- a/src/Microsoft.ML.Data/TrainContext.cs +++ b/src/Microsoft.ML.Data/TrainContext.cs @@ -4,8 +4,6 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Conversions; using System; diff --git a/src/Microsoft.ML.Data/Training/EarlyStoppingCriteria.cs b/src/Microsoft.ML.Data/Training/EarlyStoppingCriteria.cs index 1da5a5562a..54874878db 100644 --- a/src/Microsoft.ML.Data/Training/EarlyStoppingCriteria.cs +++ b/src/Microsoft.ML.Data/Training/EarlyStoppingCriteria.cs @@ -6,10 +6,10 @@ using System; using System.Collections.Generic; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.EntryPoints; [assembly: LoadableClass(typeof(TolerantEarlyStoppingCriterion), typeof(TolerantEarlyStoppingCriterion.Arguments), typeof(SignatureEarlyStoppingCriterion), "Tolerant (TR)", "tr")] [assembly: LoadableClass(typeof(GLEarlyStoppingCriterion), typeof(GLEarlyStoppingCriterion.Arguments), typeof(SignatureEarlyStoppingCriterion), "Loss of Generality (GL)", "gl")] @@ -23,7 +23,7 @@ [assembly: EntryPointModule(typeof(PQEarlyStoppingCriterion))] [assembly: EntryPointModule(typeof(UPEarlyStoppingCriterion))] -namespace Microsoft.ML.Runtime.Internal.Internallearn +namespace Microsoft.ML.Internal.Internallearn { public delegate void SignatureEarlyStoppingCriterion(bool lowerIsBetter); diff --git a/src/Microsoft.ML.Data/Training/ITrainerEstimator.cs b/src/Microsoft.ML.Data/Training/ITrainerEstimator.cs index 1194abd9a1..0384203a9e 100644 --- a/src/Microsoft.ML.Data/Training/ITrainerEstimator.cs +++ b/src/Microsoft.ML.Data/Training/ITrainerEstimator.cs @@ -4,7 +4,7 @@ using Microsoft.ML.Core.Data; -namespace Microsoft.ML.Runtime.Training +namespace Microsoft.ML.Training { public interface ITrainerEstimator : IEstimator where TTransformer : ISingleFeaturePredictionTransformer diff --git a/src/Microsoft.ML.Data/Training/TrainerBase.cs b/src/Microsoft.ML.Data/Training/TrainerBase.cs index d82dfb7ba6..1a6a145514 100644 --- a/src/Microsoft.ML.Data/Training/TrainerBase.cs +++ b/src/Microsoft.ML.Data/Training/TrainerBase.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -namespace Microsoft.ML.Runtime.Training +namespace Microsoft.ML.Training { public abstract class TrainerBase : ITrainer where TPredictor : IPredictor diff --git a/src/Microsoft.ML.Data/Training/TrainerEstimatorBase.cs b/src/Microsoft.ML.Data/Training/TrainerEstimatorBase.cs index 583badaf62..23651b0510 100644 --- a/src/Microsoft.ML.Data/Training/TrainerEstimatorBase.cs +++ b/src/Microsoft.ML.Data/Training/TrainerEstimatorBase.cs @@ -2,13 +2,11 @@ // 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.Collections.Generic; using System.Linq; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -namespace Microsoft.ML.Runtime.Training +namespace Microsoft.ML.Training { /// /// This represents a basic class for 'simple trainer'. diff --git a/src/Microsoft.ML.Data/Training/TrainerUtils.cs b/src/Microsoft.ML.Data/Training/TrainerUtils.cs index 18e8850492..0678e373ee 100644 --- a/src/Microsoft.ML.Data/Training/TrainerUtils.cs +++ b/src/Microsoft.ML.Data/Training/TrainerUtils.cs @@ -4,13 +4,12 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; using System; using System.Collections.Generic; -namespace Microsoft.ML.Runtime.Training +namespace Microsoft.ML.Training { /// /// Options for creating a row cursor from a RoleMappedData with specified standard columns active. diff --git a/src/Microsoft.ML.Data/Training/TrainingStaticExtensions.cs b/src/Microsoft.ML.Data/Training/TrainingStaticExtensions.cs index a3ee486d43..cf887f19f3 100644 --- a/src/Microsoft.ML.Data/Training/TrainingStaticExtensions.cs +++ b/src/Microsoft.ML.Data/Training/TrainingStaticExtensions.cs @@ -4,7 +4,7 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; +using Microsoft.ML; using Microsoft.ML.StaticPipe; using Microsoft.ML.StaticPipe.Runtime; using System; diff --git a/src/Microsoft.ML.Data/Transforms/BindingsWrappedRowCursor.cs b/src/Microsoft.ML.Data/Transforms/BindingsWrappedRowCursor.cs index 114bbc4fdd..e266dc266d 100644 --- a/src/Microsoft.ML.Data/Transforms/BindingsWrappedRowCursor.cs +++ b/src/Microsoft.ML.Data/Transforms/BindingsWrappedRowCursor.cs @@ -4,7 +4,7 @@ using Microsoft.ML.Data; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// A class for mapping an input to an output cursor assuming no output columns diff --git a/src/Microsoft.ML.Data/Transforms/CatalogUtils.cs b/src/Microsoft.ML.Data/Transforms/CatalogUtils.cs index 011542d7e6..0d9137fb48 100644 --- a/src/Microsoft.ML.Data/Transforms/CatalogUtils.cs +++ b/src/Microsoft.ML.Data/Transforms/CatalogUtils.cs @@ -1,8 +1,12 @@ -// Licensed to the .NET 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. -namespace Microsoft.ML.Runtime.Data +using System; +using System.Collections.Generic; +using System.Text; + +namespace Microsoft.ML.Data { /// /// Set of extension methods to extract from various catalog classes. diff --git a/src/Microsoft.ML.Data/Transforms/ColumnBindingsBase.cs b/src/Microsoft.ML.Data/Transforms/ColumnBindingsBase.cs index 3d937d05f8..8c1c651c9a 100644 --- a/src/Microsoft.ML.Data/Transforms/ColumnBindingsBase.cs +++ b/src/Microsoft.ML.Data/Transforms/ColumnBindingsBase.cs @@ -3,9 +3,9 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms.Conversions; using System; using System.Collections.Generic; @@ -13,7 +13,7 @@ using System.Text; using System.Threading; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { public abstract class SourceNameColumnBase { diff --git a/src/Microsoft.ML.Data/Transforms/ColumnConcatenatingEstimator.cs b/src/Microsoft.ML.Data/Transforms/ColumnConcatenatingEstimator.cs index 0dad71cd36..fd659f7cc2 100644 --- a/src/Microsoft.ML.Data/Transforms/ColumnConcatenatingEstimator.cs +++ b/src/Microsoft.ML.Data/Transforms/ColumnConcatenatingEstimator.cs @@ -4,9 +4,8 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Internal.Utilities; using Microsoft.ML.StaticPipe; using Microsoft.ML.StaticPipe.Runtime; using System; diff --git a/src/Microsoft.ML.Data/Transforms/ColumnConcatenatingTransformer.cs b/src/Microsoft.ML.Data/Transforms/ColumnConcatenatingTransformer.cs index 010e5bdcc3..2c76dc3f4a 100644 --- a/src/Microsoft.ML.Data/Transforms/ColumnConcatenatingTransformer.cs +++ b/src/Microsoft.ML.Data/Transforms/ColumnConcatenatingTransformer.cs @@ -2,16 +2,14 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Onnx; -using Microsoft.ML.Runtime.Model.Pfa; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Onnx; +using Microsoft.ML.Model.Pfa; using Newtonsoft.Json.Linq; using System; using System.Collections.Generic; @@ -30,7 +28,7 @@ [assembly: LoadableClass(typeof(IRowMapper), typeof(ColumnConcatenatingTransformer), null, typeof(SignatureLoadRowMapper), ColumnConcatenatingTransformer.UserName, ColumnConcatenatingTransformer.LoaderSignature)] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { using PfaType = PfaUtils.Type; diff --git a/src/Microsoft.ML.Data/Transforms/ColumnCopying.cs b/src/Microsoft.ML.Data/Transforms/ColumnCopying.cs index 0f85276e9d..32008b5330 100644 --- a/src/Microsoft.ML.Data/Transforms/ColumnCopying.cs +++ b/src/Microsoft.ML.Data/Transforms/ColumnCopying.cs @@ -8,13 +8,12 @@ using System.Text; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Onnx; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Onnx; using Microsoft.ML.Transforms; [assembly: LoadableClass(ColumnCopyingTransformer.Summary, typeof(IDataTransform), typeof(ColumnCopyingTransformer), diff --git a/src/Microsoft.ML.Data/Transforms/ColumnSelecting.cs b/src/Microsoft.ML.Data/Transforms/ColumnSelecting.cs index 8fd08b3a35..898c5ef09c 100644 --- a/src/Microsoft.ML.Data/Transforms/ColumnSelecting.cs +++ b/src/Microsoft.ML.Data/Transforms/ColumnSelecting.cs @@ -4,12 +4,11 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Data/Transforms/ConversionsExtensionsCatalog.cs b/src/Microsoft.ML.Data/Transforms/ConversionsExtensionsCatalog.cs index db6dcd3d14..12d9e22a71 100644 --- a/src/Microsoft.ML.Data/Transforms/ConversionsExtensionsCatalog.cs +++ b/src/Microsoft.ML.Data/Transforms/ConversionsExtensionsCatalog.cs @@ -1,10 +1,10 @@ -// Licensed to the .NET 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. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using Microsoft.ML.Transforms; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.Transforms.Conversions; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Data/Transforms/DropSlotsTransform.cs b/src/Microsoft.ML.Data/Transforms/DropSlotsTransform.cs index d79cfcf52e..c88ce1bcc8 100644 --- a/src/Microsoft.ML.Data/Transforms/DropSlotsTransform.cs +++ b/src/Microsoft.ML.Data/Transforms/DropSlotsTransform.cs @@ -3,12 +3,11 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms.FeatureSelection; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Data/Transforms/ExplainabilityCatalog.cs b/src/Microsoft.ML.Data/Transforms/ExplainabilityCatalog.cs index f598472265..9baf2714ae 100644 --- a/src/Microsoft.ML.Data/Transforms/ExplainabilityCatalog.cs +++ b/src/Microsoft.ML.Data/Transforms/ExplainabilityCatalog.cs @@ -3,9 +3,7 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Internallearn; +using Microsoft.ML.Internal.Internallearn; namespace Microsoft.ML { diff --git a/src/Microsoft.ML.Data/Transforms/ExtensionsCatalog.cs b/src/Microsoft.ML.Data/Transforms/ExtensionsCatalog.cs index defe52ee65..e91962cd66 100644 --- a/src/Microsoft.ML.Data/Transforms/ExtensionsCatalog.cs +++ b/src/Microsoft.ML.Data/Transforms/ExtensionsCatalog.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.Transforms; namespace Microsoft.ML diff --git a/src/Microsoft.ML.Data/Transforms/FeatureContributionCalculationTransform.cs b/src/Microsoft.ML.Data/Transforms/FeatureContributionCalculationTransform.cs index 12b0513a17..18529ac043 100644 --- a/src/Microsoft.ML.Data/Transforms/FeatureContributionCalculationTransform.cs +++ b/src/Microsoft.ML.Data/Transforms/FeatureContributionCalculationTransform.cs @@ -8,13 +8,12 @@ using System.Reflection; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; [assembly: LoadableClass(FeatureContributionCalculatingTransformer.Summary, typeof(FeatureContributionCalculatingTransformer), null, typeof(SignatureLoadModel), FeatureContributionCalculatingTransformer.FriendlyName, FeatureContributionCalculatingTransformer.LoaderSignature)] @@ -24,7 +23,7 @@ [assembly: LoadableClass(typeof(void), typeof(FeatureContributionEntryPoint), null, typeof(SignatureEntryPointModule), FeatureContributionCalculatingTransformer.LoaderSignature)] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// The FeatureContributionCalculationTransformer computes model-specific contribution scores for each feature. diff --git a/src/Microsoft.ML.Data/Transforms/GenerateNumberTransform.cs b/src/Microsoft.ML.Data/Transforms/GenerateNumberTransform.cs index 86446b13cc..4dfe73744e 100644 --- a/src/Microsoft.ML.Data/Transforms/GenerateNumberTransform.cs +++ b/src/Microsoft.ML.Data/Transforms/GenerateNumberTransform.cs @@ -3,12 +3,11 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Data/Transforms/Hashing.cs b/src/Microsoft.ML.Data/Transforms/Hashing.cs index 91e32e870b..a770d6fb9a 100644 --- a/src/Microsoft.ML.Data/Transforms/Hashing.cs +++ b/src/Microsoft.ML.Data/Transforms/Hashing.cs @@ -4,11 +4,10 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms.Conversions; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Data/Transforms/InvertHashUtils.cs b/src/Microsoft.ML.Data/Transforms/InvertHashUtils.cs index 4c63d75ff7..8bf94ef57f 100644 --- a/src/Microsoft.ML.Data/Transforms/InvertHashUtils.cs +++ b/src/Microsoft.ML.Data/Transforms/InvertHashUtils.cs @@ -7,11 +7,11 @@ using System.IO; using System.Text; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { [BestFriend] internal static class InvertHashUtils diff --git a/src/Microsoft.ML.Data/Transforms/KeyToValue.cs b/src/Microsoft.ML.Data/Transforms/KeyToValue.cs index 4be64420ad..4df2548545 100644 --- a/src/Microsoft.ML.Data/Transforms/KeyToValue.cs +++ b/src/Microsoft.ML.Data/Transforms/KeyToValue.cs @@ -4,13 +4,12 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Pfa; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Pfa; using Microsoft.ML.StaticPipe; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Transforms.Conversions; @@ -318,16 +317,16 @@ public KeyToValueMap(Mapper parent, KeyType typeKey, PrimitiveType typeVal, VBuf _values = values; // REVIEW: May want to include more specific information about what the specific value is for the default. - _na = Runtime.Data.Conversion.Conversions.Instance.GetNAOrDefault(TypeOutput.ItemType, out _naMapsToDefault); + _na = Data.Conversion.Conversions.Instance.GetNAOrDefault(TypeOutput.ItemType, out _naMapsToDefault); if (_naMapsToDefault) { // Only initialize _isDefault if _defaultIsNA is true as this is the only case in which it is used. - _isDefault = Runtime.Data.Conversion.Conversions.Instance.GetIsDefaultPredicate(TypeOutput.ItemType); + _isDefault = Data.Conversion.Conversions.Instance.GetIsDefaultPredicate(TypeOutput.ItemType); } bool identity; - _convertToUInt = Runtime.Data.Conversion.Conversions.Instance.GetStandardConversion(typeKey, NumberType.U4, out identity); + _convertToUInt = Data.Conversion.Conversions.Instance.GetStandardConversion(typeKey, NumberType.U4, out identity); } private void MapKey(in TKey src, ref TValue dst) diff --git a/src/Microsoft.ML.Data/Transforms/KeyToVector.cs b/src/Microsoft.ML.Data/Transforms/KeyToVector.cs index f6001e1a89..9f6813adf1 100644 --- a/src/Microsoft.ML.Data/Transforms/KeyToVector.cs +++ b/src/Microsoft.ML.Data/Transforms/KeyToVector.cs @@ -4,13 +4,12 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Onnx; -using Microsoft.ML.Runtime.Model.Pfa; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Onnx; +using Microsoft.ML.Model.Pfa; using Microsoft.ML.Transforms.Conversions; using Newtonsoft.Json.Linq; using System; diff --git a/src/Microsoft.ML.Data/Transforms/LabelConvertTransform.cs b/src/Microsoft.ML.Data/Transforms/LabelConvertTransform.cs index 5af4089704..e1f20bc719 100644 --- a/src/Microsoft.ML.Data/Transforms/LabelConvertTransform.cs +++ b/src/Microsoft.ML.Data/Transforms/LabelConvertTransform.cs @@ -3,11 +3,10 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms; using System; using System.Text; diff --git a/src/Microsoft.ML.Data/Transforms/LabelIndicatorTransform.cs b/src/Microsoft.ML.Data/Transforms/LabelIndicatorTransform.cs index 799ff7eb80..f269a9eea5 100644 --- a/src/Microsoft.ML.Data/Transforms/LabelIndicatorTransform.cs +++ b/src/Microsoft.ML.Data/Transforms/LabelIndicatorTransform.cs @@ -2,12 +2,12 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms; using System; using System.Text; diff --git a/src/Microsoft.ML.Data/Transforms/MetadataDispatcher.cs b/src/Microsoft.ML.Data/Transforms/MetadataDispatcher.cs index 453c7b4fd4..8dc98752c1 100644 --- a/src/Microsoft.ML.Data/Transforms/MetadataDispatcher.cs +++ b/src/Microsoft.ML.Data/Transforms/MetadataDispatcher.cs @@ -7,11 +7,11 @@ using System.Linq; using System.Text; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Base class for handling the schema metadata API. diff --git a/src/Microsoft.ML.Data/Transforms/NAFilter.cs b/src/Microsoft.ML.Data/Transforms/NAFilter.cs index 8a5d324c36..4258d614d0 100644 --- a/src/Microsoft.ML.Data/Transforms/NAFilter.cs +++ b/src/Microsoft.ML.Data/Transforms/NAFilter.cs @@ -3,12 +3,12 @@ // See the LICENSE file in the project root for more information. // REVIEW: As soon as we stop writing sizeof(Float), or when we retire the double builds, we can remove this. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms; using System; using System.Collections.Generic; @@ -287,7 +287,7 @@ private static ValueOne CreateOne(Cursor cursor, ColInfo info) Contracts.Assert(info.Type.RawType == typeof(T)); var getSrc = cursor.Input.GetGetter(info.Index); - var hasBad = Runtime.Data.Conversion.Conversions.Instance.GetIsNAPredicate(info.Type); + var hasBad = Data.Conversion.Conversions.Instance.GetIsNAPredicate(info.Type); return new ValueOne(cursor, getSrc, hasBad); } @@ -299,7 +299,7 @@ private static ValueVec CreateVec(Cursor cursor, ColInfo info) Contracts.Assert(info.Type.RawType == typeof(VBuffer)); var getSrc = cursor.Input.GetGetter>(info.Index); - var hasBad = Runtime.Data.Conversion.Conversions.Instance.GetHasMissingPredicate((VectorType)info.Type); + var hasBad = Data.Conversion.Conversions.Instance.GetHasMissingPredicate((VectorType)info.Type); return new ValueVec(cursor, getSrc, hasBad); } diff --git a/src/Microsoft.ML.Data/Transforms/NopTransform.cs b/src/Microsoft.ML.Data/Transforms/NopTransform.cs index ad41595b68..e42e8055cb 100644 --- a/src/Microsoft.ML.Data/Transforms/NopTransform.cs +++ b/src/Microsoft.ML.Data/Transforms/NopTransform.cs @@ -4,17 +4,16 @@ using System; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Model; [assembly: LoadableClass(NopTransform.Summary, typeof(NopTransform), null, typeof(SignatureLoadDataTransform), "", NopTransform.LoaderSignature)] [assembly: LoadableClass(typeof(void), typeof(NopTransform), null, typeof(SignatureEntryPointModule), "NopTransform")] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// A transform that does nothing. diff --git a/src/Microsoft.ML.Data/Transforms/NormalizeColumn.cs b/src/Microsoft.ML.Data/Transforms/NormalizeColumn.cs index 549f8d6a55..16f3a53e15 100644 --- a/src/Microsoft.ML.Data/Transforms/NormalizeColumn.cs +++ b/src/Microsoft.ML.Data/Transforms/NormalizeColumn.cs @@ -3,14 +3,13 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Onnx; -using Microsoft.ML.Runtime.Model.Pfa; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Onnx; +using Microsoft.ML.Model.Pfa; using Microsoft.ML.Transforms.Normalizers; using Newtonsoft.Json.Linq; using System; diff --git a/src/Microsoft.ML.Data/Transforms/NormalizeColumnDbl.cs b/src/Microsoft.ML.Data/Transforms/NormalizeColumnDbl.cs index 44a9715c3e..827de6c851 100644 --- a/src/Microsoft.ML.Data/Transforms/NormalizeColumnDbl.cs +++ b/src/Microsoft.ML.Data/Transforms/NormalizeColumnDbl.cs @@ -2,12 +2,12 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Onnx; -using Microsoft.ML.Runtime.Model.Pfa; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Onnx; +using Microsoft.ML.Model.Pfa; using Newtonsoft.Json.Linq; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Data/Transforms/NormalizeColumnSng.cs b/src/Microsoft.ML.Data/Transforms/NormalizeColumnSng.cs index 28bca6c58f..eb630b2e5a 100644 --- a/src/Microsoft.ML.Data/Transforms/NormalizeColumnSng.cs +++ b/src/Microsoft.ML.Data/Transforms/NormalizeColumnSng.cs @@ -2,12 +2,12 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Onnx; -using Microsoft.ML.Runtime.Model.Pfa; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Onnx; +using Microsoft.ML.Model.Pfa; using Newtonsoft.Json.Linq; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Data/Transforms/NormalizeUtils.cs b/src/Microsoft.ML.Data/Transforms/NormalizeUtils.cs index e4ca0348f6..652cf534ad 100644 --- a/src/Microsoft.ML.Data/Transforms/NormalizeUtils.cs +++ b/src/Microsoft.ML.Data/Transforms/NormalizeUtils.cs @@ -3,12 +3,11 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Onnx; -using Microsoft.ML.Runtime.Model.Pfa; +using Microsoft.ML; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Onnx; +using Microsoft.ML.Model.Pfa; using Microsoft.ML.Transforms.Normalizers; using Newtonsoft.Json.Linq; using System; @@ -16,7 +15,7 @@ [assembly: LoadableClass(typeof(void), typeof(Normalize), null, typeof(SignatureEntryPointModule), "Normalize")] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Signature for a repository based loader of a IColumnFunction diff --git a/src/Microsoft.ML.Data/Transforms/Normalizer.cs b/src/Microsoft.ML.Data/Transforms/Normalizer.cs index 54958c2921..7a6e39d0ee 100644 --- a/src/Microsoft.ML.Data/Transforms/Normalizer.cs +++ b/src/Microsoft.ML.Data/Transforms/Normalizer.cs @@ -4,11 +4,10 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Onnx; -using Microsoft.ML.Runtime.Model.Pfa; +using Microsoft.ML; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Onnx; +using Microsoft.ML.Model.Pfa; using Microsoft.ML.Transforms.Normalizers; using Newtonsoft.Json.Linq; using System; diff --git a/src/Microsoft.ML.Data/Transforms/NormalizerCatalog.cs b/src/Microsoft.ML.Data/Transforms/NormalizerCatalog.cs index df9c435def..284e988bb7 100644 --- a/src/Microsoft.ML.Data/Transforms/NormalizerCatalog.cs +++ b/src/Microsoft.ML.Data/Transforms/NormalizerCatalog.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.Transforms.Normalizers; namespace Microsoft.ML diff --git a/src/Microsoft.ML.Data/Transforms/OneToOneTransformerBase.cs b/src/Microsoft.ML.Data/Transforms/OneToOneTransformerBase.cs index ad3e037f04..6c5e4f3452 100644 --- a/src/Microsoft.ML.Data/Transforms/OneToOneTransformerBase.cs +++ b/src/Microsoft.ML.Data/Transforms/OneToOneTransformerBase.cs @@ -3,11 +3,11 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.Model; using System; using System.Collections.Generic; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Base class for transformer which operates on pairs input and output columns. diff --git a/src/Microsoft.ML.Data/Transforms/PerGroupTransformBase.cs b/src/Microsoft.ML.Data/Transforms/PerGroupTransformBase.cs index a67dfa3652..7aaa182d76 100644 --- a/src/Microsoft.ML.Data/Transforms/PerGroupTransformBase.cs +++ b/src/Microsoft.ML.Data/Transforms/PerGroupTransformBase.cs @@ -4,9 +4,9 @@ using System; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.Model; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// This is a base implementation for a transform that in order to compute its output columns, needs to look diff --git a/src/Microsoft.ML.Data/Transforms/RangeFilter.cs b/src/Microsoft.ML.Data/Transforms/RangeFilter.cs index 0b8cdcce07..27019f17b6 100644 --- a/src/Microsoft.ML.Data/Transforms/RangeFilter.cs +++ b/src/Microsoft.ML.Data/Transforms/RangeFilter.cs @@ -2,12 +2,12 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms; using System; using System.Reflection; @@ -420,7 +420,7 @@ public KeyRowCursor(RangeFilter parent, RowCursor input, bool[] active) dst = _value; }; bool identity; - _conv = Runtime.Data.Conversion.Conversions.Instance.GetStandardConversion(Parent._type, NumberType.U8, out identity); + _conv = Data.Conversion.Conversions.Instance.GetStandardConversion(Parent._type, NumberType.U8, out identity); } protected override Delegate GetGetter() diff --git a/src/Microsoft.ML.Data/Transforms/RowShufflingTransformer.cs b/src/Microsoft.ML.Data/Transforms/RowShufflingTransformer.cs index f62aedc12d..ec96d610cd 100644 --- a/src/Microsoft.ML.Data/Transforms/RowShufflingTransformer.cs +++ b/src/Microsoft.ML.Data/Transforms/RowShufflingTransformer.cs @@ -5,11 +5,10 @@ #pragma warning disable 420 // volatile with Interlocked.CompareExchange using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Data/Transforms/RowToRowTransformerBase.cs b/src/Microsoft.ML.Data/Transforms/RowToRowTransformerBase.cs index 6796736da0..9d8b121a69 100644 --- a/src/Microsoft.ML.Data/Transforms/RowToRowTransformerBase.cs +++ b/src/Microsoft.ML.Data/Transforms/RowToRowTransformerBase.cs @@ -4,11 +4,11 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.Model; using System; using System.Linq; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Base class for transformer which produce new columns, but doesn't affect existing ones. diff --git a/src/Microsoft.ML.Data/Transforms/SkipTakeFilter.cs b/src/Microsoft.ML.Data/Transforms/SkipTakeFilter.cs index eae681db0b..294e8b023e 100644 --- a/src/Microsoft.ML.Data/Transforms/SkipTakeFilter.cs +++ b/src/Microsoft.ML.Data/Transforms/SkipTakeFilter.cs @@ -3,12 +3,11 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms; using System; diff --git a/src/Microsoft.ML.Data/Transforms/TrainAndScoreTransformer.cs b/src/Microsoft.ML.Data/Transforms/TrainAndScoreTransformer.cs index dbc4e4d685..1017dacff5 100644 --- a/src/Microsoft.ML.Data/Transforms/TrainAndScoreTransformer.cs +++ b/src/Microsoft.ML.Data/Transforms/TrainAndScoreTransformer.cs @@ -2,12 +2,12 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Model; using Microsoft.ML.Transforms; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Data/Transforms/TransformBase.cs b/src/Microsoft.ML.Data/Transforms/TransformBase.cs index fa6f887852..3534043044 100644 --- a/src/Microsoft.ML.Data/Transforms/TransformBase.cs +++ b/src/Microsoft.ML.Data/Transforms/TransformBase.cs @@ -7,13 +7,13 @@ using System.Linq; using System.Reflection; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Onnx; -using Microsoft.ML.Runtime.Model.Pfa; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Onnx; +using Microsoft.ML.Model.Pfa; using Newtonsoft.Json.Linq; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Base class for transforms. diff --git a/src/Microsoft.ML.Data/Transforms/TransformsCatalog.cs b/src/Microsoft.ML.Data/Transforms/TransformsCatalog.cs index 42f2031807..38033db8cf 100644 --- a/src/Microsoft.ML.Data/Transforms/TransformsCatalog.cs +++ b/src/Microsoft.ML.Data/Transforms/TransformsCatalog.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { /// /// Similar to training context, a transform context is an object serving as a 'catalog' of available transforms. diff --git a/src/Microsoft.ML.Data/Transforms/TypeConverting.cs b/src/Microsoft.ML.Data/Transforms/TypeConverting.cs index 87c0142f07..750bd334b8 100644 --- a/src/Microsoft.ML.Data/Transforms/TypeConverting.cs +++ b/src/Microsoft.ML.Data/Transforms/TypeConverting.cs @@ -6,13 +6,12 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Onnx; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Onnx; using Microsoft.ML.StaticPipe; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Transforms.Conversions; @@ -431,7 +430,7 @@ private static bool CanConvertToType(IExceptionContext ectx, ColumnType srcType, // Ensure that the conversion is legal. We don't actually cache the delegate here. It will get // re-fetched by the utils code when needed. - if (!Runtime.Data.Conversion.Conversions.Instance.TryGetStandardConversion(srcType.ItemType, itemType, out Delegate del, out bool identity)) + if (!Data.Conversion.Conversions.Instance.TryGetStandardConversion(srcType.ItemType, itemType, out Delegate del, out bool identity)) return false; typeDst = itemType; @@ -558,7 +557,7 @@ public override SchemaShape GetOutputSchema(SchemaShape inputSchema) throw Host.ExceptSchemaMismatch(nameof(inputSchema), "input", colInfo.Input); if (!TypeConvertingTransformer.GetNewType(Host, col.ItemType, colInfo.OutputKind, colInfo.OutputKeyRange, out PrimitiveType newType)) throw Host.ExceptParam(nameof(inputSchema), $"Can't convert {colInfo.Input} into {newType.ToString()}"); - if (!Runtime.Data.Conversion.Conversions.Instance.TryGetStandardConversion(col.ItemType, newType, out Delegate del, out bool identity)) + if (!Data.Conversion.Conversions.Instance.TryGetStandardConversion(col.ItemType, newType, out Delegate del, out bool identity)) throw Host.ExceptParam(nameof(inputSchema), $"Don't know how to convert {colInfo.Input} into {newType.ToString()}"); var metadata = new List(); if (col.ItemType.IsBool && newType.ItemType.IsNumber) diff --git a/src/Microsoft.ML.Data/Transforms/ValueMappingTransformer.cs b/src/Microsoft.ML.Data/Transforms/ValueMappingTransformer.cs index 15a0ccccfc..2c799a1d25 100644 --- a/src/Microsoft.ML.Data/Transforms/ValueMappingTransformer.cs +++ b/src/Microsoft.ML.Data/Transforms/ValueMappingTransformer.cs @@ -4,12 +4,11 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms.Conversions; using System; using System.Collections.Generic; @@ -439,7 +438,7 @@ private static TextLoader.Column GenerateValueColumn(IHostEnvironment env, // Try to parse the text as a key value between 1 and ulong.MaxValue. If this succeeds and res>0, // we update max and min accordingly. If res==0 it means the value is missing, in which case we ignore it for // computing max and min. - if (Microsoft.ML.Runtime.Data.Conversion.Conversions.Instance.TryParseKey(in value, 1, ulong.MaxValue, out res)) + if (Microsoft.ML.Data.Conversion.Conversions.Instance.TryParseKey(in value, 1, ulong.MaxValue, out res)) { if (res < keyMin && res != 0) keyMin = res; @@ -448,7 +447,7 @@ private static TextLoader.Column GenerateValueColumn(IHostEnvironment env, } // If parsing as key did not succeed, the value can still be 0, so we try parsing it as a ulong. If it succeeds, // then the value is 0, and we update min accordingly. - else if (Microsoft.ML.Runtime.Data.Conversion.Conversions.Instance.TryParse(in value, out res)) + else if (Microsoft.ML.Data.Conversion.Conversions.Instance.TryParse(in value, out res)) { keyMin = 0; } @@ -809,7 +808,7 @@ public override void Train(IHostEnvironment env, RowCursor cursor) // First check if there is a String->ValueType conversion method. If so, call the conversion method with an // empty string, the returned value will be the new missing value. // NOTE this will return NA for R4 and R8 types. - if (Microsoft.ML.Runtime.Data.Conversion.Conversions.Instance.TryGetStandardConversion, TValue>( + if (Microsoft.ML.Data.Conversion.Conversions.Instance.TryGetStandardConversion, TValue>( TextType.Instance, ValueType, out conv, diff --git a/src/Microsoft.ML.Data/Transforms/ValueToKeyMappingEstimator.cs b/src/Microsoft.ML.Data/Transforms/ValueToKeyMappingEstimator.cs index cc7d0559b7..0b46c9ef58 100644 --- a/src/Microsoft.ML.Data/Transforms/ValueToKeyMappingEstimator.cs +++ b/src/Microsoft.ML.Data/Transforms/ValueToKeyMappingEstimator.cs @@ -4,8 +4,7 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; using Microsoft.ML.StaticPipe; using Microsoft.ML.StaticPipe.Runtime; using System; diff --git a/src/Microsoft.ML.Data/Transforms/ValueToKeyMappingTransformer.cs b/src/Microsoft.ML.Data/Transforms/ValueToKeyMappingTransformer.cs index 33451cada6..df218750d5 100644 --- a/src/Microsoft.ML.Data/Transforms/ValueToKeyMappingTransformer.cs +++ b/src/Microsoft.ML.Data/Transforms/ValueToKeyMappingTransformer.cs @@ -3,15 +3,14 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Onnx; -using Microsoft.ML.Runtime.Model.Pfa; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data.IO; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Onnx; +using Microsoft.ML.Model.Pfa; using Microsoft.ML.Transforms.Conversions; using Newtonsoft.Json.Linq; using System; diff --git a/src/Microsoft.ML.Data/Transforms/ValueToKeyMappingTransformerImpl.cs b/src/Microsoft.ML.Data/Transforms/ValueToKeyMappingTransformerImpl.cs index 776e408194..f926be7261 100644 --- a/src/Microsoft.ML.Data/Transforms/ValueToKeyMappingTransformerImpl.cs +++ b/src/Microsoft.ML.Data/Transforms/ValueToKeyMappingTransformerImpl.cs @@ -3,11 +3,10 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using System; using System.IO; using System.Text; @@ -66,7 +65,7 @@ private static Builder CreateCore(PrimitiveType type, bool sorted) // of building our term dictionary. For the other types (practically, only the UX types), // we should ignore nothing. InPredicate mapsToMissing; - if (!Runtime.Data.Conversion.Conversions.Instance.TryGetIsNAPredicate(type, out mapsToMissing)) + if (!Data.Conversion.Conversions.Instance.TryGetIsNAPredicate(type, out mapsToMissing)) mapsToMissing = (in T val) => false; return new Impl(type, mapsToMissing, sorted); } @@ -206,7 +205,7 @@ protected Builder(PrimitiveType type) public override void ParseAddTermArg(ref ReadOnlyMemory terms, IChannel ch) { T val; - var tryParse = Runtime.Data.Conversion.Conversions.Instance.GetTryParseConversion(ItemType); + var tryParse = Data.Conversion.Conversions.Instance.GetTryParseConversion(ItemType); for (bool more = true; more;) { ReadOnlyMemory term; @@ -232,7 +231,7 @@ public override void ParseAddTermArg(ref ReadOnlyMemory terms, IChannel ch public override void ParseAddTermArg(string[] terms, IChannel ch) { T val; - var tryParse = Runtime.Data.Conversion.Conversions.Instance.GetTryParseConversion(ItemType); + var tryParse = Data.Conversion.Conversions.Instance.GetTryParseConversion(ItemType); foreach (var sterm in terms) { ReadOnlyMemory term = sterm.AsMemory(); @@ -747,7 +746,7 @@ internal override void WriteTextTerms(TextWriter writer) { writer.WriteLine("# Number of terms of type '{0}' = {1}", ItemType, Count); StringBuilder sb = null; - var stringMapper = Runtime.Data.Conversion.Conversions.Instance.GetStringConversion(ItemType); + var stringMapper = Data.Conversion.Conversions.Instance.GetStringConversion(ItemType); for (int i = 0; i < _values.Count; ++i) { T val = _values.GetItem(i); @@ -1045,7 +1044,7 @@ public override void AddMetadata(MetadataBuilder builder) return; if (IsTextMetadata && !TypedMap.ItemType.IsText) { - var conv = Runtime.Data.Conversion.Conversions.Instance; + var conv = Data.Conversion.Conversions.Instance; var stringMapper = conv.GetStringConversion(TypedMap.ItemType); ValueGetter>> getter = @@ -1105,7 +1104,7 @@ private bool AddMetadataCore(ColumnType srcMetaType, MetadataBuilder buil var srcType = TypedMap.ItemType as KeyType; _host.AssertValue(srcType); var dstType = new KeyType(DataKind.U4, srcType.Min, srcType.Count); - var convInst = Runtime.Data.Conversion.Conversions.Instance; + var convInst = Data.Conversion.Conversions.Instance; ValueMapper conv; bool identity; // If we can't convert this type to U4, don't try to pass along the metadata. @@ -1184,7 +1183,7 @@ private bool WriteTextTermsCore(PrimitiveType srcMetaType, TextWriter wri var srcType = TypedMap.ItemType as KeyType; _host.AssertValue(srcType); var dstType = new KeyType(DataKind.U4, srcType.Min, srcType.Count); - var convInst = Runtime.Data.Conversion.Conversions.Instance; + var convInst = Data.Conversion.Conversions.Instance; ValueMapper conv; bool identity; // If we can't convert this type to U4, don't try. diff --git a/src/Microsoft.ML.Data/Utilities/ApplyTransformUtils.cs b/src/Microsoft.ML.Data/Utilities/ApplyTransformUtils.cs index 7d0695083b..c8510c8413 100644 --- a/src/Microsoft.ML.Data/Utilities/ApplyTransformUtils.cs +++ b/src/Microsoft.ML.Data/Utilities/ApplyTransformUtils.cs @@ -4,9 +4,9 @@ using System.Collections.Generic; using System.IO; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.Model; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Utilities to rebind data transforms diff --git a/src/Microsoft.ML.Data/Utilities/ColumnCursor.cs b/src/Microsoft.ML.Data/Utilities/ColumnCursor.cs index 1ae2951628..b29f049f73 100644 --- a/src/Microsoft.ML.Data/Utilities/ColumnCursor.cs +++ b/src/Microsoft.ML.Data/Utilities/ColumnCursor.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Data/Utilities/ComponentCreation.cs b/src/Microsoft.ML.Data/Utilities/ComponentCreation.cs index 75aeac4a5b..7aa2ff9af7 100644 --- a/src/Microsoft.ML.Data/Utilities/ComponentCreation.cs +++ b/src/Microsoft.ML.Data/Utilities/ComponentCreation.cs @@ -3,10 +3,10 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Model; using System; using System.Collections.Generic; using System.IO; diff --git a/src/Microsoft.ML.Data/Utilities/LocalEnvironment.cs b/src/Microsoft.ML.Data/Utilities/LocalEnvironment.cs index 73e4c03e9f..a9e3a4a80e 100644 --- a/src/Microsoft.ML.Data/Utilities/LocalEnvironment.cs +++ b/src/Microsoft.ML.Data/Utilities/LocalEnvironment.cs @@ -5,7 +5,7 @@ using System; using System.ComponentModel.Composition.Hosting; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { using Stopwatch = System.Diagnostics.Stopwatch; diff --git a/src/Microsoft.ML.Data/Utilities/ModelFileUtils.cs b/src/Microsoft.ML.Data/Utilities/ModelFileUtils.cs index 0b962f435e..b06e8e32eb 100644 --- a/src/Microsoft.ML.Data/Utilities/ModelFileUtils.cs +++ b/src/Microsoft.ML.Data/Utilities/ModelFileUtils.cs @@ -6,13 +6,13 @@ using System.Collections.Generic; using System.IO; using System.Linq; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Internal.Internallearn; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Internal.Internallearn; -namespace Microsoft.ML.Runtime.Model +namespace Microsoft.ML.Model { using ColumnRole = RoleMappedSchema.ColumnRole; using Conditional = System.Diagnostics.ConditionalAttribute; diff --git a/src/Microsoft.ML.Data/Utilities/PartitionedPathUtils.cs b/src/Microsoft.ML.Data/Utilities/PartitionedPathUtils.cs index b13a0d5cee..88717c91c7 100644 --- a/src/Microsoft.ML.Data/Utilities/PartitionedPathUtils.cs +++ b/src/Microsoft.ML.Data/Utilities/PartitionedPathUtils.cs @@ -6,7 +6,7 @@ using System.Collections.Generic; using System.IO; -namespace Microsoft.ML.Runtime.Data.Utilities +namespace Microsoft.ML.Data.Utilities { internal static class PartitionedPathUtils { diff --git a/src/Microsoft.ML.Data/Utilities/SlotDropper.cs b/src/Microsoft.ML.Data/Utilities/SlotDropper.cs index d678302467..dacb5a83d5 100644 --- a/src/Microsoft.ML.Data/Utilities/SlotDropper.cs +++ b/src/Microsoft.ML.Data/Utilities/SlotDropper.cs @@ -3,11 +3,11 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Internal.Internallearn +namespace Microsoft.ML.Internal.Internallearn { /// /// Drops slots from a fixed or variable sized column based on slot ranges. diff --git a/src/Microsoft.ML.Data/Utilities/StreamUtils.cs b/src/Microsoft.ML.Data/Utilities/StreamUtils.cs index 5d52b45b3b..f157d09ea8 100644 --- a/src/Microsoft.ML.Data/Utilities/StreamUtils.cs +++ b/src/Microsoft.ML.Data/Utilities/StreamUtils.cs @@ -6,7 +6,7 @@ using System.IO; using System.Linq; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { // REVIEW: Implement properly on CoreCLR. [BestFriend] @@ -15,7 +15,7 @@ internal static class StreamUtils public static Stream OpenInStream(string fileName) { #if !CORECLR - return Microsoft.ML.Runtime.Internal.IO.ZStreamIn.Open(fileName); + return Microsoft.ML.Internal.IO.ZStreamIn.Open(fileName); #else return new FileStream(fileName, FileMode.Open, FileAccess.Read, FileShare.Read); #endif diff --git a/src/Microsoft.ML.Data/Utilities/TimerScope.cs b/src/Microsoft.ML.Data/Utilities/TimerScope.cs index c2a590ffe8..663ba669d5 100644 --- a/src/Microsoft.ML.Data/Utilities/TimerScope.cs +++ b/src/Microsoft.ML.Data/Utilities/TimerScope.cs @@ -4,7 +4,7 @@ using System; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { using Stopwatch = System.Diagnostics.Stopwatch; diff --git a/src/Microsoft.ML.Data/Utilities/TypeParsingUtils.cs b/src/Microsoft.ML.Data/Utilities/TypeParsingUtils.cs index a24d7d3883..f1363ad2f8 100644 --- a/src/Microsoft.ML.Data/Utilities/TypeParsingUtils.cs +++ b/src/Microsoft.ML.Data/Utilities/TypeParsingUtils.cs @@ -4,10 +4,10 @@ using System; using System.Text; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Utilities to parse command-line representations of types. diff --git a/src/Microsoft.ML.Data/Utilities/TypeUtils.cs b/src/Microsoft.ML.Data/Utilities/TypeUtils.cs index 8459a7d4cd..15120fcb2e 100644 --- a/src/Microsoft.ML.Data/Utilities/TypeUtils.cs +++ b/src/Microsoft.ML.Data/Utilities/TypeUtils.cs @@ -7,10 +7,10 @@ using System.Reflection; using System.Text; using System.Text.RegularExpressions; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Internal.Internallearn +namespace Microsoft.ML.Internal.Internallearn { public static class TypeUtils { diff --git a/src/Microsoft.ML.Data/Utils/ApiUtils.cs b/src/Microsoft.ML.Data/Utils/ApiUtils.cs index af738b219b..d1b14f2b94 100644 --- a/src/Microsoft.ML.Data/Utils/ApiUtils.cs +++ b/src/Microsoft.ML.Data/Utils/ApiUtils.cs @@ -5,9 +5,9 @@ using System; using System.Reflection; using System.Reflection.Emit; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { internal delegate void Peek(TRow row, long position, ref TValue value); diff --git a/src/Microsoft.ML.Data/Utils/LossFunctions.cs b/src/Microsoft.ML.Data/Utils/LossFunctions.cs index 1659b39387..77fdf503bd 100644 --- a/src/Microsoft.ML.Data/Utils/LossFunctions.cs +++ b/src/Microsoft.ML.Data/Utils/LossFunctions.cs @@ -5,10 +5,10 @@ using Float = System.Single; using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; [assembly: LoadableClass(LogLoss.Summary, typeof(LogLoss), null, typeof(SignatureClassificationLoss), "Log Loss", "LogLoss", "Logistic", "CrossEntropy")] @@ -39,7 +39,7 @@ [assembly: EntryPointModule(typeof(SquaredLossFactory))] [assembly: EntryPointModule(typeof(TweedieLoss.Arguments))] -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { /// /// The loss function may know the close-form solution to the optimal dual update diff --git a/src/Microsoft.ML.Data/Utils/SequencePool.cs b/src/Microsoft.ML.Data/Utils/SequencePool.cs index 6b9ebe01e3..989bbd195f 100644 --- a/src/Microsoft.ML.Data/Utils/SequencePool.cs +++ b/src/Microsoft.ML.Data/Utils/SequencePool.cs @@ -5,7 +5,7 @@ using System; using System.IO; -namespace Microsoft.ML.Runtime.Internal.Utilities +namespace Microsoft.ML.Internal.Utilities { using Conditional = System.Diagnostics.ConditionalAttribute; diff --git a/src/Microsoft.ML.DnnImageFeaturizer.AlexNet/AlexNetExtension.cs b/src/Microsoft.ML.DnnImageFeaturizer.AlexNet/AlexNetExtension.cs index 186d083679..3c8e868148 100644 --- a/src/Microsoft.ML.DnnImageFeaturizer.AlexNet/AlexNetExtension.cs +++ b/src/Microsoft.ML.DnnImageFeaturizer.AlexNet/AlexNetExtension.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using System.IO; using System.Reflection; diff --git a/src/Microsoft.ML.DnnImageFeaturizer.ResNet101/ResNet101Extension.cs b/src/Microsoft.ML.DnnImageFeaturizer.ResNet101/ResNet101Extension.cs index 0e5298211e..656e877c91 100644 --- a/src/Microsoft.ML.DnnImageFeaturizer.ResNet101/ResNet101Extension.cs +++ b/src/Microsoft.ML.DnnImageFeaturizer.ResNet101/ResNet101Extension.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using System.IO; using System.Reflection; diff --git a/src/Microsoft.ML.DnnImageFeaturizer.ResNet18/ResNet18Extension.cs b/src/Microsoft.ML.DnnImageFeaturizer.ResNet18/ResNet18Extension.cs index 8a0d0504b7..281e0f8ef6 100644 --- a/src/Microsoft.ML.DnnImageFeaturizer.ResNet18/ResNet18Extension.cs +++ b/src/Microsoft.ML.DnnImageFeaturizer.ResNet18/ResNet18Extension.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using System.IO; using System.Reflection; diff --git a/src/Microsoft.ML.DnnImageFeaturizer.ResNet50/ResNet50Extension.cs b/src/Microsoft.ML.DnnImageFeaturizer.ResNet50/ResNet50Extension.cs index b46d34f708..e1ed66463e 100644 --- a/src/Microsoft.ML.DnnImageFeaturizer.ResNet50/ResNet50Extension.cs +++ b/src/Microsoft.ML.DnnImageFeaturizer.ResNet50/ResNet50Extension.cs @@ -2,8 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; using System.IO; using System.Reflection; diff --git a/src/Microsoft.ML.Ensemble/Batch.cs b/src/Microsoft.ML.Ensemble/Batch.cs index 482456f83c..caaf6bf4f3 100644 --- a/src/Microsoft.ML.Ensemble/Batch.cs +++ b/src/Microsoft.ML.Ensemble/Batch.cs @@ -2,9 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; -namespace Microsoft.ML.Runtime.Ensemble +namespace Microsoft.ML.Ensemble { internal sealed class Batch { diff --git a/src/Microsoft.ML.Ensemble/EnsembleUtils.cs b/src/Microsoft.ML.Ensemble/EnsembleUtils.cs index 5515695bdf..0cb43ef7a4 100644 --- a/src/Microsoft.ML.Ensemble/EnsembleUtils.cs +++ b/src/Microsoft.ML.Ensemble/EnsembleUtils.cs @@ -4,10 +4,10 @@ using System; using System.Collections; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Ensemble +namespace Microsoft.ML.Ensemble { internal static class EnsembleUtils { diff --git a/src/Microsoft.ML.Ensemble/EntryPoints/CreateEnsemble.cs b/src/Microsoft.ML.Ensemble/EntryPoints/CreateEnsemble.cs index db8708d544..151b0d08b0 100644 --- a/src/Microsoft.ML.Ensemble/EntryPoints/CreateEnsemble.cs +++ b/src/Microsoft.ML.Ensemble/EntryPoints/CreateEnsemble.cs @@ -3,23 +3,21 @@ // See the LICENSE file in the project root for more information. using System; -using System.Collections.Generic; using System.IO; using System.IO.Compression; using System.Linq; using Microsoft.ML.Data; using Microsoft.ML.Ensemble.EntryPoints; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble; -using Microsoft.ML.Runtime.Ensemble.OutputCombiners; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Ensemble; +using Microsoft.ML.Ensemble.OutputCombiners; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; [assembly: LoadableClass(typeof(void), typeof(EnsembleCreator), null, typeof(SignatureEntryPointModule), "CreateEnsemble")] -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { /// /// A component to combine given models into an ensemble model. diff --git a/src/Microsoft.ML.Ensemble/EntryPoints/DiversityMeasure.cs b/src/Microsoft.ML.Ensemble/EntryPoints/DiversityMeasure.cs index b13cff3b35..de71c5d2f0 100644 --- a/src/Microsoft.ML.Ensemble/EntryPoints/DiversityMeasure.cs +++ b/src/Microsoft.ML.Ensemble/EntryPoints/DiversityMeasure.cs @@ -4,11 +4,11 @@ using System; using Microsoft.ML.Ensemble.EntryPoints; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble.Selector; -using Microsoft.ML.Runtime.Ensemble.Selector.DiversityMeasure; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble.Selector; +using Microsoft.ML.Ensemble.Selector.DiversityMeasure; +using Microsoft.ML.EntryPoints; [assembly: EntryPointModule(typeof(DisagreementDiversityFactory))] [assembly: EntryPointModule(typeof(RegressionDisagreementDiversityFactory))] diff --git a/src/Microsoft.ML.Ensemble/EntryPoints/Ensemble.cs b/src/Microsoft.ML.Ensemble/EntryPoints/Ensemble.cs index e5e9b79afc..0bfa15ba2c 100644 --- a/src/Microsoft.ML.Ensemble/EntryPoints/Ensemble.cs +++ b/src/Microsoft.ML.Ensemble/EntryPoints/Ensemble.cs @@ -3,9 +3,9 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Ensemble.EntryPoints; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Ensemble; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.Ensemble; +using Microsoft.ML.EntryPoints; [assembly: LoadableClass(typeof(void), typeof(Ensemble), null, typeof(SignatureEntryPointModule), "TrainEnsemble")] diff --git a/src/Microsoft.ML.Ensemble/EntryPoints/FeatureSelector.cs b/src/Microsoft.ML.Ensemble/EntryPoints/FeatureSelector.cs index 65ca5e9d06..f1d2593ef9 100644 --- a/src/Microsoft.ML.Ensemble/EntryPoints/FeatureSelector.cs +++ b/src/Microsoft.ML.Ensemble/EntryPoints/FeatureSelector.cs @@ -3,10 +3,10 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Ensemble.EntryPoints; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Ensemble.Selector; -using Microsoft.ML.Runtime.Ensemble.Selector.FeatureSelector; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.Ensemble.Selector; +using Microsoft.ML.Ensemble.Selector.FeatureSelector; +using Microsoft.ML.EntryPoints; [assembly: EntryPointModule(typeof(AllFeatureSelectorFactory))] [assembly: EntryPointModule(typeof(RandomFeatureSelector))] diff --git a/src/Microsoft.ML.Ensemble/EntryPoints/OutputCombiner.cs b/src/Microsoft.ML.Ensemble/EntryPoints/OutputCombiner.cs index 537b35f47b..143034cc21 100644 --- a/src/Microsoft.ML.Ensemble/EntryPoints/OutputCombiner.cs +++ b/src/Microsoft.ML.Ensemble/EntryPoints/OutputCombiner.cs @@ -3,9 +3,9 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Ensemble.EntryPoints; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Ensemble.OutputCombiners; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.Ensemble.OutputCombiners; +using Microsoft.ML.EntryPoints; [assembly: EntryPointModule(typeof(AverageFactory))] [assembly: EntryPointModule(typeof(MedianFactory))] diff --git a/src/Microsoft.ML.Ensemble/EntryPoints/PipelineEnsemble.cs b/src/Microsoft.ML.Ensemble/EntryPoints/PipelineEnsemble.cs index bcfaaefb89..66482b44a9 100644 --- a/src/Microsoft.ML.Ensemble/EntryPoints/PipelineEnsemble.cs +++ b/src/Microsoft.ML.Ensemble/EntryPoints/PipelineEnsemble.cs @@ -2,14 +2,14 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble.EntryPoints; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Calibration; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble.EntryPoints; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Calibration; [assembly: EntryPointModule(typeof(PipelineEnsemble))] -namespace Microsoft.ML.Runtime.Ensemble.EntryPoints +namespace Microsoft.ML.Ensemble.EntryPoints { public static class PipelineEnsemble { diff --git a/src/Microsoft.ML.Ensemble/EntryPoints/SubModelSelector.cs b/src/Microsoft.ML.Ensemble/EntryPoints/SubModelSelector.cs index 57001190ac..cb2ef60242 100644 --- a/src/Microsoft.ML.Ensemble/EntryPoints/SubModelSelector.cs +++ b/src/Microsoft.ML.Ensemble/EntryPoints/SubModelSelector.cs @@ -4,11 +4,11 @@ using System; using Microsoft.ML.Ensemble.EntryPoints; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble.Selector; -using Microsoft.ML.Runtime.Ensemble.Selector.SubModelSelector; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble.Selector; +using Microsoft.ML.Ensemble.Selector.SubModelSelector; +using Microsoft.ML.EntryPoints; [assembly: EntryPointModule(typeof(AllSelectorFactory))] [assembly: EntryPointModule(typeof(AllSelectorMultiClassFactory))] diff --git a/src/Microsoft.ML.Ensemble/FeatureSubsetModel.cs b/src/Microsoft.ML.Ensemble/FeatureSubsetModel.cs index 4518666d34..fadd096810 100644 --- a/src/Microsoft.ML.Ensemble/FeatureSubsetModel.cs +++ b/src/Microsoft.ML.Ensemble/FeatureSubsetModel.cs @@ -4,9 +4,9 @@ using System.Collections; using System.Collections.Generic; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Ensemble +namespace Microsoft.ML.Ensemble { public sealed class FeatureSubsetModel where TPredictor : IPredictor { diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/Average.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/Average.cs index de1e5ef505..05b85b37ec 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/Average.cs +++ b/src/Microsoft.ML.Ensemble/OutputCombiners/Average.cs @@ -3,14 +3,14 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Ensemble.OutputCombiners; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.Ensemble.OutputCombiners; +using Microsoft.ML.Model; [assembly: LoadableClass(typeof(Average), null, typeof(SignatureCombiner), Average.UserName)] [assembly: LoadableClass(typeof(Average), null, typeof(SignatureLoadModel), Average.UserName, Average.LoaderSignature)] -namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners +namespace Microsoft.ML.Ensemble.OutputCombiners { public sealed class Average : BaseAverager, ICanSaveModel, IRegressionOutputCombiner { diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/BaseAverager.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/BaseAverager.cs index 824300e594..1ffbe13ec1 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/BaseAverager.cs +++ b/src/Microsoft.ML.Ensemble/OutputCombiners/BaseAverager.cs @@ -3,9 +3,9 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.Model; -namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners +namespace Microsoft.ML.Ensemble.OutputCombiners { public abstract class BaseAverager : IBinaryOutputCombiner { diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/BaseMultiAverager.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/BaseMultiAverager.cs index e7a50c11c3..73e6f4ea7e 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/BaseMultiAverager.cs +++ b/src/Microsoft.ML.Ensemble/OutputCombiners/BaseMultiAverager.cs @@ -3,12 +3,12 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Numeric; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Numeric; -namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners +namespace Microsoft.ML.Ensemble.OutputCombiners { public abstract class BaseMultiAverager : BaseMultiCombiner { diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/BaseMultiCombiner.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/BaseMultiCombiner.cs index 350833aebb..5e8296862b 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/BaseMultiCombiner.cs +++ b/src/Microsoft.ML.Ensemble/OutputCombiners/BaseMultiCombiner.cs @@ -3,13 +3,13 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Numeric; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Numeric; -namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners +namespace Microsoft.ML.Ensemble.OutputCombiners { public abstract class BaseMultiCombiner : IMultiClassOutputCombiner { diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/BaseScalarStacking.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/BaseScalarStacking.cs index 257499cd13..ba75e05080 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/BaseScalarStacking.cs +++ b/src/Microsoft.ML.Ensemble/OutputCombiners/BaseScalarStacking.cs @@ -3,11 +3,11 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; -namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners +namespace Microsoft.ML.Ensemble.OutputCombiners { internal abstract class BaseScalarStacking : BaseStacking { diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/BaseStacking.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/BaseStacking.cs index d62650b7c2..769f95b4f9 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/BaseStacking.cs +++ b/src/Microsoft.ML.Ensemble/OutputCombiners/BaseStacking.cs @@ -5,15 +5,15 @@ using System; using System.Collections.Generic; using System.Threading.Tasks; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Training; - -namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Training; + +namespace Microsoft.ML.Ensemble.OutputCombiners { using ColumnRole = RoleMappedSchema.ColumnRole; internal abstract class BaseStacking : IStackingTrainer diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/IOutputCombiner.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/IOutputCombiner.cs index 6fcf55d5c8..53aec1f8d8 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/IOutputCombiner.cs +++ b/src/Microsoft.ML.Ensemble/OutputCombiners/IOutputCombiner.cs @@ -4,10 +4,10 @@ using System; using System.Collections.Generic; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; -namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners +namespace Microsoft.ML.Ensemble.OutputCombiners { /// /// Signature for combiners. diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/Median.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/Median.cs index 95bc0cc991..3b94196eb9 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/Median.cs +++ b/src/Microsoft.ML.Ensemble/OutputCombiners/Median.cs @@ -3,15 +3,15 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Ensemble.OutputCombiners; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.Ensemble.OutputCombiners; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; [assembly: LoadableClass(typeof(Median), null, typeof(SignatureCombiner), Median.UserName, Median.LoadName)] [assembly: LoadableClass(typeof(Median), null, typeof(SignatureLoadModel), Median.UserName, Median.LoaderSignature)] -namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners +namespace Microsoft.ML.Ensemble.OutputCombiners { /// /// Generic interface for combining outputs of multiple models diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/MultiAverage.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/MultiAverage.cs index fef6fa087e..1ba5cdf028 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/MultiAverage.cs +++ b/src/Microsoft.ML.Ensemble/OutputCombiners/MultiAverage.cs @@ -3,18 +3,18 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble.OutputCombiners; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble.OutputCombiners; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Model; [assembly: LoadableClass(typeof(MultiAverage), typeof(MultiAverage.Arguments), typeof(SignatureCombiner), Average.UserName, MultiAverage.LoadName)] [assembly: LoadableClass(typeof(MultiAverage), null, typeof(SignatureLoadModel), Average.UserName, MultiAverage.LoadName, MultiAverage.LoaderSignature)] -namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners +namespace Microsoft.ML.Ensemble.OutputCombiners { public sealed class MultiAverage : BaseMultiAverager, ICanSaveModel { diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/MultiMedian.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/MultiMedian.cs index 3b11146203..477a658355 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/MultiMedian.cs +++ b/src/Microsoft.ML.Ensemble/OutputCombiners/MultiMedian.cs @@ -3,18 +3,18 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble.OutputCombiners; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble.OutputCombiners; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; [assembly: LoadableClass(typeof(MultiMedian), typeof(MultiMedian.Arguments), typeof(SignatureCombiner), Median.UserName, MultiMedian.LoadName)] [assembly: LoadableClass(typeof(MultiMedian), null, typeof(SignatureLoadModel), Median.UserName, MultiMedian.LoaderSignature)] -namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners +namespace Microsoft.ML.Ensemble.OutputCombiners { /// /// Generic interface for combining outputs of multiple models diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/MultiStacking.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/MultiStacking.cs index f9e3b246f7..f87c532161 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/MultiStacking.cs +++ b/src/Microsoft.ML.Ensemble/OutputCombiners/MultiStacking.cs @@ -3,14 +3,14 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble.OutputCombiners; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble.OutputCombiners; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; [assembly: LoadableClass(typeof(MultiStacking), typeof(MultiStacking.Arguments), typeof(SignatureCombiner), Stacking.UserName, MultiStacking.LoadName)] @@ -18,7 +18,7 @@ [assembly: LoadableClass(typeof(MultiStacking), null, typeof(SignatureLoadModel), Stacking.UserName, MultiStacking.LoaderSignature)] -namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners +namespace Microsoft.ML.Ensemble.OutputCombiners { using TVectorPredictor = IPredictorProducing>; internal sealed class MultiStacking : BaseStacking>, ICanSaveModel, IMultiClassOutputCombiner diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/MultiVoting.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/MultiVoting.cs index ffa1b9c647..a8ba932926 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/MultiVoting.cs +++ b/src/Microsoft.ML.Ensemble/OutputCombiners/MultiVoting.cs @@ -3,17 +3,17 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble.OutputCombiners; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Numeric; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble.OutputCombiners; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Numeric; [assembly: LoadableClass(typeof(MultiVoting), null, typeof(SignatureCombiner), Voting.UserName, MultiVoting.LoadName)] [assembly: LoadableClass(typeof(MultiVoting), null, typeof(SignatureLoadModel), Voting.UserName, MultiVoting.LoaderSignature)] -namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners +namespace Microsoft.ML.Ensemble.OutputCombiners { // REVIEW: Why is MultiVoting based on BaseMultiCombiner? Normalizing the model outputs // is senseless, so the base adds no real functionality. diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/MultiWeightedAverage.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/MultiWeightedAverage.cs index a2f52b1451..deef23abcd 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/MultiWeightedAverage.cs +++ b/src/Microsoft.ML.Ensemble/OutputCombiners/MultiWeightedAverage.cs @@ -3,13 +3,13 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble.OutputCombiners; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble.OutputCombiners; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Model; [assembly: LoadableClass(typeof(MultiWeightedAverage), typeof(MultiWeightedAverage.Arguments), typeof(SignatureCombiner), MultiWeightedAverage.UserName, MultiWeightedAverage.LoadName)] @@ -17,7 +17,7 @@ [assembly: LoadableClass(typeof(MultiWeightedAverage), null, typeof(SignatureLoadModel), MultiWeightedAverage.UserName, MultiWeightedAverage.LoaderSignature)] -namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners +namespace Microsoft.ML.Ensemble.OutputCombiners { /// /// Generic interface for combining outputs of multiple models diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/RegressionStacking.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/RegressionStacking.cs index 8c984613db..ab57cfe9aa 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/RegressionStacking.cs +++ b/src/Microsoft.ML.Ensemble/OutputCombiners/RegressionStacking.cs @@ -2,12 +2,12 @@ // 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 Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Ensemble.OutputCombiners; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Ensemble.OutputCombiners; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Model; [assembly: LoadableClass(typeof(RegressionStacking), typeof(RegressionStacking.Arguments), typeof(SignatureCombiner), Stacking.UserName, RegressionStacking.LoadName)] @@ -15,7 +15,7 @@ [assembly: LoadableClass(typeof(RegressionStacking), null, typeof(SignatureLoadModel), Stacking.UserName, RegressionStacking.LoaderSignature)] -namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners +namespace Microsoft.ML.Ensemble.OutputCombiners { using TScalarPredictor = IPredictorProducing; diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/Stacking.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/Stacking.cs index f44f987b05..891963dbea 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/Stacking.cs +++ b/src/Microsoft.ML.Ensemble/OutputCombiners/Stacking.cs @@ -3,17 +3,17 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Ensemble.OutputCombiners; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Ensemble.OutputCombiners; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Model; [assembly: LoadableClass(typeof(Stacking), typeof(Stacking.Arguments), typeof(SignatureCombiner), Stacking.UserName, Stacking.LoadName)] [assembly: LoadableClass(typeof(Stacking), null, typeof(SignatureLoadModel), Stacking.UserName, Stacking.LoaderSignature)] -namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners +namespace Microsoft.ML.Ensemble.OutputCombiners { using TScalarPredictor = IPredictorProducing; internal sealed class Stacking : BaseScalarStacking, IBinaryOutputCombiner, ICanSaveModel diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/Voting.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/Voting.cs index d352439d55..b18de67b18 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/Voting.cs +++ b/src/Microsoft.ML.Ensemble/OutputCombiners/Voting.cs @@ -3,15 +3,15 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Ensemble.OutputCombiners; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.Ensemble.OutputCombiners; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; [assembly: LoadableClass(typeof(Voting), null, typeof(SignatureCombiner), Voting.UserName, Voting.LoadName)] [assembly: LoadableClass(typeof(Voting), null, typeof(SignatureLoadModel), Voting.UserName, Voting.LoaderSignature)] -namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners +namespace Microsoft.ML.Ensemble.OutputCombiners { public sealed class Voting : IBinaryOutputCombiner, ICanSaveModel { diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/WeightedAverage.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/WeightedAverage.cs index e11f0c9bb9..ec1d2dcd11 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/WeightedAverage.cs +++ b/src/Microsoft.ML.Ensemble/OutputCombiners/WeightedAverage.cs @@ -3,13 +3,13 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble.OutputCombiners; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble.OutputCombiners; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Model; [assembly: LoadableClass(typeof(WeightedAverage), typeof(WeightedAverage.Arguments), typeof(SignatureCombiner), WeightedAverage.UserName, WeightedAverage.LoadName)] @@ -17,7 +17,7 @@ [assembly: LoadableClass(typeof(WeightedAverage), null, typeof(SignatureLoadModel), WeightedAverage.UserName, WeightedAverage.LoaderSignature)] -namespace Microsoft.ML.Runtime.Ensemble.OutputCombiners +namespace Microsoft.ML.Ensemble.OutputCombiners { public sealed class WeightedAverage : BaseAverager, IWeightedAverager, ICanSaveModel { diff --git a/src/Microsoft.ML.Ensemble/PipelineEnsemble.cs b/src/Microsoft.ML.Ensemble/PipelineEnsemble.cs index 2becb019e0..ab88a83a65 100644 --- a/src/Microsoft.ML.Ensemble/PipelineEnsemble.cs +++ b/src/Microsoft.ML.Ensemble/PipelineEnsemble.cs @@ -8,20 +8,19 @@ using System.Linq; using System.Text; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble; -using Microsoft.ML.Runtime.Ensemble.OutputCombiners; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.Ensemble; +using Microsoft.ML.Ensemble.OutputCombiners; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; [assembly: LoadableClass(typeof(SchemaBindablePipelineEnsembleBase), null, typeof(SignatureLoadModel), SchemaBindablePipelineEnsembleBase.UserName, SchemaBindablePipelineEnsembleBase.LoaderSignature)] -namespace Microsoft.ML.Runtime.Ensemble +namespace Microsoft.ML.Ensemble { /// /// This class represents an ensemble predictor, where each predictor has its own featurization pipeline. It is diff --git a/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/BaseDisagreementDiversityMeasure.cs b/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/BaseDisagreementDiversityMeasure.cs index 52d5dd9a58..f6ac5da19e 100644 --- a/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/BaseDisagreementDiversityMeasure.cs +++ b/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/BaseDisagreementDiversityMeasure.cs @@ -6,7 +6,7 @@ using System.Collections.Concurrent; using System.Collections.Generic; -namespace Microsoft.ML.Runtime.Ensemble.Selector.DiversityMeasure +namespace Microsoft.ML.Ensemble.Selector.DiversityMeasure { public abstract class BaseDisagreementDiversityMeasure : IDiversityMeasure { diff --git a/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/DisagreementDiversityMeasure.cs b/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/DisagreementDiversityMeasure.cs index d36f00ea9d..c5af6268c3 100644 --- a/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/DisagreementDiversityMeasure.cs +++ b/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/DisagreementDiversityMeasure.cs @@ -3,14 +3,14 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Ensemble.Selector; -using Microsoft.ML.Runtime.Ensemble.Selector.DiversityMeasure; +using Microsoft.ML; +using Microsoft.ML.Ensemble.Selector; +using Microsoft.ML.Ensemble.Selector.DiversityMeasure; [assembly: LoadableClass(typeof(DisagreementDiversityMeasure), null, typeof(SignatureEnsembleDiversityMeasure), DisagreementDiversityMeasure.UserName, DisagreementDiversityMeasure.LoadName)] -namespace Microsoft.ML.Runtime.Ensemble.Selector.DiversityMeasure +namespace Microsoft.ML.Ensemble.Selector.DiversityMeasure { public class DisagreementDiversityMeasure : BaseDisagreementDiversityMeasure, IBinaryDiversityMeasure { diff --git a/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/ModelDiversityMetric.cs b/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/ModelDiversityMetric.cs index 1ee03a9489..621671c2f0 100644 --- a/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/ModelDiversityMetric.cs +++ b/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/ModelDiversityMetric.cs @@ -4,7 +4,7 @@ using System; -namespace Microsoft.ML.Runtime.Ensemble.Selector.DiversityMeasure +namespace Microsoft.ML.Ensemble.Selector.DiversityMeasure { public class ModelDiversityMetric { diff --git a/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/MultiDisagreementDiversityMeasure.cs b/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/MultiDisagreementDiversityMeasure.cs index 424e2a328d..1645ae9a8a 100644 --- a/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/MultiDisagreementDiversityMeasure.cs +++ b/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/MultiDisagreementDiversityMeasure.cs @@ -3,16 +3,16 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble.Selector; -using Microsoft.ML.Runtime.Ensemble.Selector.DiversityMeasure; -using Microsoft.ML.Runtime.Numeric; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble.Selector; +using Microsoft.ML.Ensemble.Selector.DiversityMeasure; +using Microsoft.ML.Numeric; [assembly: LoadableClass(typeof(MultiDisagreementDiversityMeasure), null, typeof(SignatureEnsembleDiversityMeasure), DisagreementDiversityMeasure.UserName, MultiDisagreementDiversityMeasure.LoadName)] -namespace Microsoft.ML.Runtime.Ensemble.Selector.DiversityMeasure +namespace Microsoft.ML.Ensemble.Selector.DiversityMeasure { public class MultiDisagreementDiversityMeasure : BaseDisagreementDiversityMeasure>, IMulticlassDiversityMeasure { diff --git a/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/RegressionDisagreementDiversityMeasure.cs b/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/RegressionDisagreementDiversityMeasure.cs index 68f882d19c..67b9eb0d21 100644 --- a/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/RegressionDisagreementDiversityMeasure.cs +++ b/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/RegressionDisagreementDiversityMeasure.cs @@ -3,14 +3,14 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Ensemble.Selector; -using Microsoft.ML.Runtime.Ensemble.Selector.DiversityMeasure; +using Microsoft.ML; +using Microsoft.ML.Ensemble.Selector; +using Microsoft.ML.Ensemble.Selector.DiversityMeasure; [assembly: LoadableClass(typeof(RegressionDisagreementDiversityMeasure), null, typeof(SignatureEnsembleDiversityMeasure), DisagreementDiversityMeasure.UserName, RegressionDisagreementDiversityMeasure.LoadName)] -namespace Microsoft.ML.Runtime.Ensemble.Selector.DiversityMeasure +namespace Microsoft.ML.Ensemble.Selector.DiversityMeasure { public class RegressionDisagreementDiversityMeasure : BaseDisagreementDiversityMeasure, IRegressionDiversityMeasure { diff --git a/src/Microsoft.ML.Ensemble/Selector/FeatureSelector/AllFeatureSelector.cs b/src/Microsoft.ML.Ensemble/Selector/FeatureSelector/AllFeatureSelector.cs index 3ce4cb1955..acfed82802 100644 --- a/src/Microsoft.ML.Ensemble/Selector/FeatureSelector/AllFeatureSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/FeatureSelector/AllFeatureSelector.cs @@ -2,16 +2,16 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble.Selector; -using Microsoft.ML.Runtime.Ensemble.Selector.FeatureSelector; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble.Selector; +using Microsoft.ML.Ensemble.Selector.FeatureSelector; using System; [assembly: LoadableClass(typeof(AllFeatureSelector), null, typeof(SignatureEnsembleFeatureSelector), AllFeatureSelector.UserName, AllFeatureSelector.LoadName)] -namespace Microsoft.ML.Runtime.Ensemble.Selector.FeatureSelector +namespace Microsoft.ML.Ensemble.Selector.FeatureSelector { internal sealed class AllFeatureSelector : IFeatureSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/FeatureSelector/RandomFeatureSelector.cs b/src/Microsoft.ML.Ensemble/Selector/FeatureSelector/RandomFeatureSelector.cs index c9b4890512..e28911c981 100644 --- a/src/Microsoft.ML.Ensemble/Selector/FeatureSelector/RandomFeatureSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/FeatureSelector/RandomFeatureSelector.cs @@ -4,18 +4,18 @@ using System; using System.Collections; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble.Selector; -using Microsoft.ML.Runtime.Ensemble.Selector.FeatureSelector; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble.Selector; +using Microsoft.ML.Ensemble.Selector.FeatureSelector; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Training; [assembly: LoadableClass(typeof(RandomFeatureSelector), typeof(RandomFeatureSelector.Arguments), typeof(SignatureEnsembleFeatureSelector), RandomFeatureSelector.UserName, RandomFeatureSelector.LoadName)] -namespace Microsoft.ML.Runtime.Ensemble.Selector.FeatureSelector +namespace Microsoft.ML.Ensemble.Selector.FeatureSelector { internal class RandomFeatureSelector : IFeatureSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/IDiversityMeasure.cs b/src/Microsoft.ML.Ensemble/Selector/IDiversityMeasure.cs index 01589c4714..4209761c94 100644 --- a/src/Microsoft.ML.Ensemble/Selector/IDiversityMeasure.cs +++ b/src/Microsoft.ML.Ensemble/Selector/IDiversityMeasure.cs @@ -5,11 +5,11 @@ using System; using System.Collections.Concurrent; using System.Collections.Generic; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble.Selector.DiversityMeasure; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble.Selector.DiversityMeasure; +using Microsoft.ML.EntryPoints; -namespace Microsoft.ML.Runtime.Ensemble.Selector +namespace Microsoft.ML.Ensemble.Selector { public interface IDiversityMeasure { diff --git a/src/Microsoft.ML.Ensemble/Selector/IFeatureSelector.cs b/src/Microsoft.ML.Ensemble/Selector/IFeatureSelector.cs index 90aa692391..3bbaa1cf86 100644 --- a/src/Microsoft.ML.Ensemble/Selector/IFeatureSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/IFeatureSelector.cs @@ -2,11 +2,11 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; using System; -namespace Microsoft.ML.Runtime.Ensemble.Selector +namespace Microsoft.ML.Ensemble.Selector { internal interface IFeatureSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/ISubModelSelector.cs b/src/Microsoft.ML.Ensemble/Selector/ISubModelSelector.cs index 33e5da6d7f..3454e37562 100644 --- a/src/Microsoft.ML.Ensemble/Selector/ISubModelSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/ISubModelSelector.cs @@ -2,12 +2,12 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; using System; using System.Collections.Generic; -namespace Microsoft.ML.Runtime.Ensemble.Selector +namespace Microsoft.ML.Ensemble.Selector { internal interface ISubModelSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/ISubsetSelector.cs b/src/Microsoft.ML.Ensemble/Selector/ISubsetSelector.cs index 983f094c34..6ba7002508 100644 --- a/src/Microsoft.ML.Ensemble/Selector/ISubsetSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/ISubsetSelector.cs @@ -4,10 +4,10 @@ using System; using System.Collections.Generic; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; -namespace Microsoft.ML.Runtime.Ensemble.Selector +namespace Microsoft.ML.Ensemble.Selector { internal interface ISubsetSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/AllSelector.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/AllSelector.cs index 9c6f9e6691..f88df3bfee 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/AllSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/AllSelector.cs @@ -3,13 +3,13 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Ensemble.Selector; -using Microsoft.ML.Runtime.Ensemble.Selector.SubModelSelector; +using Microsoft.ML; +using Microsoft.ML.Ensemble.Selector; +using Microsoft.ML.Ensemble.Selector.SubModelSelector; [assembly: LoadableClass(typeof(AllSelector), null, typeof(SignatureEnsembleSubModelSelector), AllSelector.UserName, AllSelector.LoadName)] -namespace Microsoft.ML.Runtime.Ensemble.Selector.SubModelSelector +namespace Microsoft.ML.Ensemble.Selector.SubModelSelector { internal sealed class AllSelector : BaseSubModelSelector, IBinarySubModelSelector, IRegressionSubModelSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/AllSelectorMultiClass.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/AllSelectorMultiClass.cs index 2c674b8842..2158b05733 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/AllSelectorMultiClass.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/AllSelectorMultiClass.cs @@ -3,15 +3,15 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble.Selector; -using Microsoft.ML.Runtime.Ensemble.Selector.SubModelSelector; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble.Selector; +using Microsoft.ML.Ensemble.Selector.SubModelSelector; [assembly: LoadableClass(typeof(AllSelectorMultiClass), null, typeof(SignatureEnsembleSubModelSelector), AllSelectorMultiClass.UserName, AllSelectorMultiClass.LoadName)] -namespace Microsoft.ML.Runtime.Ensemble.Selector.SubModelSelector +namespace Microsoft.ML.Ensemble.Selector.SubModelSelector { internal sealed class AllSelectorMultiClass : BaseSubModelSelector>, IMulticlassSubModelSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BaseBestPerformanceSelector.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BaseBestPerformanceSelector.cs index f4062787e2..cc6292e9b2 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BaseBestPerformanceSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BaseBestPerformanceSelector.cs @@ -6,9 +6,9 @@ using System.Collections.Generic; using System.Linq; using System.Reflection; -using Microsoft.ML.Runtime.CommandLine; +using Microsoft.ML.CommandLine; -namespace Microsoft.ML.Runtime.Ensemble.Selector.SubModelSelector +namespace Microsoft.ML.Ensemble.Selector.SubModelSelector { internal abstract class BaseBestPerformanceSelector : SubModelDataSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BaseDiverseSelector.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BaseDiverseSelector.cs index 0b72b16637..6d84c51bbc 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BaseDiverseSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BaseDiverseSelector.cs @@ -5,13 +5,13 @@ using System; using System.Collections.Concurrent; using System.Collections.Generic; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble.Selector.DiversityMeasure; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble.Selector.DiversityMeasure; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Training; -namespace Microsoft.ML.Runtime.Ensemble.Selector.SubModelSelector +namespace Microsoft.ML.Ensemble.Selector.SubModelSelector { internal abstract class BaseDiverseSelector : SubModelDataSelector where TDiversityMetric : class, IDiversityMeasure diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BaseSubModelSelector.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BaseSubModelSelector.cs index 32fe976551..e4df5351da 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BaseSubModelSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BaseSubModelSelector.cs @@ -6,10 +6,8 @@ using System.Collections.Generic; using System.Linq; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -namespace Microsoft.ML.Runtime.Ensemble.Selector.SubModelSelector +namespace Microsoft.ML.Ensemble.Selector.SubModelSelector { internal abstract class BaseSubModelSelector : ISubModelSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorBinary.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorBinary.cs index 9ef2861d33..178c08cb02 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorBinary.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorBinary.cs @@ -6,18 +6,18 @@ using System.Collections.Concurrent; using System.Collections.Generic; using Microsoft.ML.Ensemble.EntryPoints; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Ensemble.Selector; -using Microsoft.ML.Runtime.Ensemble.Selector.DiversityMeasure; -using Microsoft.ML.Runtime.Ensemble.Selector.SubModelSelector; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Ensemble.Selector; +using Microsoft.ML.Ensemble.Selector.DiversityMeasure; +using Microsoft.ML.Ensemble.Selector.SubModelSelector; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; [assembly: LoadableClass(typeof(BestDiverseSelectorBinary), typeof(BestDiverseSelectorBinary.Arguments), typeof(SignatureEnsembleSubModelSelector), BestDiverseSelectorBinary.UserName, BestDiverseSelectorBinary.LoadName)] -namespace Microsoft.ML.Runtime.Ensemble.Selector.SubModelSelector +namespace Microsoft.ML.Ensemble.Selector.SubModelSelector { using TScalarPredictor = IPredictorProducing; diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorMultiClass.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorMultiClass.cs index a5a0864338..ae5ea2101f 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorMultiClass.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorMultiClass.cs @@ -6,19 +6,19 @@ using System.Collections.Concurrent; using System.Collections.Generic; using Microsoft.ML.Ensemble.EntryPoints; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble.Selector; -using Microsoft.ML.Runtime.Ensemble.Selector.DiversityMeasure; -using Microsoft.ML.Runtime.Ensemble.Selector.SubModelSelector; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble.Selector; +using Microsoft.ML.Ensemble.Selector.DiversityMeasure; +using Microsoft.ML.Ensemble.Selector.SubModelSelector; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; [assembly: LoadableClass(typeof(BestDiverseSelectorMultiClass), typeof(BestDiverseSelectorMultiClass.Arguments), typeof(SignatureEnsembleSubModelSelector), BestDiverseSelectorMultiClass.UserName, BestDiverseSelectorMultiClass.LoadName)] -namespace Microsoft.ML.Runtime.Ensemble.Selector.SubModelSelector +namespace Microsoft.ML.Ensemble.Selector.SubModelSelector { using TVectorPredictor = IPredictorProducing>; diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorRegression.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorRegression.cs index f4e717d73c..8700133895 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorRegression.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorRegression.cs @@ -6,18 +6,18 @@ using System.Collections.Concurrent; using System.Collections.Generic; using Microsoft.ML.Ensemble.EntryPoints; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Ensemble.Selector; -using Microsoft.ML.Runtime.Ensemble.Selector.DiversityMeasure; -using Microsoft.ML.Runtime.Ensemble.Selector.SubModelSelector; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Ensemble.Selector; +using Microsoft.ML.Ensemble.Selector.DiversityMeasure; +using Microsoft.ML.Ensemble.Selector.SubModelSelector; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; [assembly: LoadableClass(typeof(BestDiverseSelectorRegression), typeof(BestDiverseSelectorRegression.Arguments), typeof(SignatureEnsembleSubModelSelector), BestDiverseSelectorRegression.UserName, BestDiverseSelectorRegression.LoadName)] -namespace Microsoft.ML.Runtime.Ensemble.Selector.SubModelSelector +namespace Microsoft.ML.Ensemble.Selector.SubModelSelector { using TScalarPredictor = IPredictorProducing; diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestPerformanceRegressionSelector.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestPerformanceRegressionSelector.cs index 0ad0e1024c..be7b7e8f35 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestPerformanceRegressionSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestPerformanceRegressionSelector.cs @@ -3,18 +3,18 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble.Selector; -using Microsoft.ML.Runtime.Ensemble.Selector.SubModelSelector; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble.Selector; +using Microsoft.ML.Ensemble.Selector.SubModelSelector; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; [assembly: LoadableClass(typeof(BestPerformanceRegressionSelector), typeof(BestPerformanceRegressionSelector.Arguments), typeof(SignatureEnsembleSubModelSelector), BestPerformanceRegressionSelector.UserName, BestPerformanceRegressionSelector.LoadName)] -namespace Microsoft.ML.Runtime.Ensemble.Selector.SubModelSelector +namespace Microsoft.ML.Ensemble.Selector.SubModelSelector { internal sealed class BestPerformanceRegressionSelector : BaseBestPerformanceSelector, IRegressionSubModelSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestPerformanceSelector.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestPerformanceSelector.cs index 84f00e0958..9b24798276 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestPerformanceSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestPerformanceSelector.cs @@ -3,18 +3,18 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble.Selector; -using Microsoft.ML.Runtime.Ensemble.Selector.SubModelSelector; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble.Selector; +using Microsoft.ML.Ensemble.Selector.SubModelSelector; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; [assembly: LoadableClass(typeof(BestPerformanceSelector), typeof(BestPerformanceSelector.Arguments), typeof(SignatureEnsembleSubModelSelector), BestPerformanceSelector.UserName, BestPerformanceSelector.LoadName)] -namespace Microsoft.ML.Runtime.Ensemble.Selector.SubModelSelector +namespace Microsoft.ML.Ensemble.Selector.SubModelSelector { internal sealed class BestPerformanceSelector : BaseBestPerformanceSelector, IBinarySubModelSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestPerformanceSelectorMultiClass.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestPerformanceSelectorMultiClass.cs index 6e3414d945..36f9635c87 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestPerformanceSelectorMultiClass.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestPerformanceSelectorMultiClass.cs @@ -3,18 +3,18 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble.Selector; -using Microsoft.ML.Runtime.Ensemble.Selector.SubModelSelector; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble.Selector; +using Microsoft.ML.Ensemble.Selector.SubModelSelector; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; [assembly: LoadableClass(typeof(BestPerformanceSelectorMultiClass), typeof(BestPerformanceSelectorMultiClass.Arguments), typeof(SignatureEnsembleSubModelSelector), BestPerformanceSelectorMultiClass.UserName, BestPerformanceSelectorMultiClass.LoadName)] -namespace Microsoft.ML.Runtime.Ensemble.Selector.SubModelSelector +namespace Microsoft.ML.Ensemble.Selector.SubModelSelector { internal sealed class BestPerformanceSelectorMultiClass : BaseBestPerformanceSelector>, IMulticlassSubModelSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/SubModelDataSelector.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/SubModelDataSelector.cs index 0bd623174f..0ba6497f25 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/SubModelDataSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/SubModelDataSelector.cs @@ -3,10 +3,10 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Internal.Internallearn; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Internallearn; -namespace Microsoft.ML.Runtime.Ensemble.Selector.SubModelSelector +namespace Microsoft.ML.Ensemble.Selector.SubModelSelector { internal abstract class SubModelDataSelector : BaseSubModelSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/AllInstanceSelector.cs b/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/AllInstanceSelector.cs index c56b6dc9e8..fa1d1b536e 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/AllInstanceSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/AllInstanceSelector.cs @@ -2,10 +2,10 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Ensemble.Selector; -using Microsoft.ML.Runtime.Ensemble.Selector.SubsetSelector; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.Ensemble.Selector; +using Microsoft.ML.Ensemble.Selector.SubsetSelector; +using Microsoft.ML.EntryPoints; using System; using System.Collections.Generic; @@ -14,7 +14,7 @@ [assembly: EntryPointModule(typeof(AllInstanceSelector))] -namespace Microsoft.ML.Runtime.Ensemble.Selector.SubsetSelector +namespace Microsoft.ML.Ensemble.Selector.SubsetSelector { internal sealed class AllInstanceSelector : BaseSubsetSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/BaseSubsetSelector.cs b/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/BaseSubsetSelector.cs index f3d26e646c..509770bfd3 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/BaseSubsetSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/BaseSubsetSelector.cs @@ -3,13 +3,13 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Ensemble.EntryPoints; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; using Microsoft.ML.Transforms; using System; using System.Collections.Generic; -namespace Microsoft.ML.Runtime.Ensemble.Selector.SubsetSelector +namespace Microsoft.ML.Ensemble.Selector.SubsetSelector { internal abstract class BaseSubsetSelector : ISubsetSelector where TArgs : BaseSubsetSelector.ArgumentsBase diff --git a/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/BootstrapSelector.cs b/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/BootstrapSelector.cs index c6020bbf8c..2bb1da56e6 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/BootstrapSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/BootstrapSelector.cs @@ -2,11 +2,11 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble.Selector; -using Microsoft.ML.Runtime.Ensemble.Selector.SubsetSelector; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble.Selector; +using Microsoft.ML.Ensemble.Selector.SubsetSelector; +using Microsoft.ML.EntryPoints; using Microsoft.ML.Transforms; using System; using System.Collections.Generic; @@ -16,7 +16,7 @@ [assembly: EntryPointModule(typeof(BootstrapSelector))] -namespace Microsoft.ML.Runtime.Ensemble.Selector.SubsetSelector +namespace Microsoft.ML.Ensemble.Selector.SubsetSelector { internal sealed class BootstrapSelector : BaseSubsetSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/RandomPartitionSelector.cs b/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/RandomPartitionSelector.cs index 81a8ec927f..453b6abf1d 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/RandomPartitionSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/RandomPartitionSelector.cs @@ -2,11 +2,11 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble.Selector; -using Microsoft.ML.Runtime.Ensemble.Selector.SubsetSelector; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble.Selector; +using Microsoft.ML.Ensemble.Selector.SubsetSelector; +using Microsoft.ML.EntryPoints; using Microsoft.ML.Transforms; using System; using System.Collections.Generic; @@ -16,7 +16,7 @@ [assembly: EntryPointModule(typeof(RandomPartitionSelector))] -namespace Microsoft.ML.Runtime.Ensemble.Selector.SubsetSelector +namespace Microsoft.ML.Ensemble.Selector.SubsetSelector { internal sealed class RandomPartitionSelector : BaseSubsetSelector { diff --git a/src/Microsoft.ML.Ensemble/Subset.cs b/src/Microsoft.ML.Ensemble/Subset.cs index b1baf8725c..743be33df6 100644 --- a/src/Microsoft.ML.Ensemble/Subset.cs +++ b/src/Microsoft.ML.Ensemble/Subset.cs @@ -3,9 +3,9 @@ // See the LICENSE file in the project root for more information. using System.Collections; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; -namespace Microsoft.ML.Runtime.Ensemble +namespace Microsoft.ML.Ensemble { internal sealed class Subset { diff --git a/src/Microsoft.ML.Ensemble/Trainer/Binary/EnsembleTrainer.cs b/src/Microsoft.ML.Ensemble/Trainer/Binary/EnsembleTrainer.cs index 003002b5ab..da0d8d69c0 100644 --- a/src/Microsoft.ML.Ensemble/Trainer/Binary/EnsembleTrainer.cs +++ b/src/Microsoft.ML.Ensemble/Trainer/Binary/EnsembleTrainer.cs @@ -6,13 +6,13 @@ using System.Collections.Generic; using System.Linq; using Microsoft.ML.Ensemble.EntryPoints; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Ensemble; -using Microsoft.ML.Runtime.Ensemble.OutputCombiners; -using Microsoft.ML.Runtime.Ensemble.Selector; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Ensemble; +using Microsoft.ML.Ensemble.OutputCombiners; +using Microsoft.ML.Ensemble.Selector; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; using Microsoft.ML.Trainers.Online; [assembly: LoadableClass(EnsembleTrainer.Summary, typeof(EnsembleTrainer), typeof(EnsembleTrainer.Arguments), @@ -22,7 +22,7 @@ [assembly: LoadableClass(typeof(EnsembleTrainer), typeof(EnsembleTrainer.Arguments), typeof(SignatureModelCombiner), "Binary Classification Ensemble Model Combiner", EnsembleTrainer.LoadNameValue, "pe", "ParallelEnsemble")] -namespace Microsoft.ML.Runtime.Ensemble +namespace Microsoft.ML.Ensemble { using TDistPredictor = IDistPredictorProducing; using TScalarPredictor = IPredictorProducing; diff --git a/src/Microsoft.ML.Ensemble/Trainer/EnsembleDistributionModelParameters.cs b/src/Microsoft.ML.Ensemble/Trainer/EnsembleDistributionModelParameters.cs index d7012951fd..f19e96fb47 100644 --- a/src/Microsoft.ML.Ensemble/Trainer/EnsembleDistributionModelParameters.cs +++ b/src/Microsoft.ML.Ensemble/Trainer/EnsembleDistributionModelParameters.cs @@ -6,18 +6,18 @@ using System.Collections.Generic; using System.Linq; using System.Threading.Tasks; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble; -using Microsoft.ML.Runtime.Ensemble.OutputCombiners; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble; +using Microsoft.ML.Ensemble.OutputCombiners; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; // These are for deserialization from a model repository. [assembly: LoadableClass(typeof(EnsembleDistributionModelParameters), null, typeof(SignatureLoadModel), EnsembleDistributionModelParameters.UserName, EnsembleDistributionModelParameters.LoaderSignature)] -namespace Microsoft.ML.Runtime.Ensemble +namespace Microsoft.ML.Ensemble { using TDistPredictor = IDistPredictorProducing; diff --git a/src/Microsoft.ML.Ensemble/Trainer/EnsembleModelParameters.cs b/src/Microsoft.ML.Ensemble/Trainer/EnsembleModelParameters.cs index cbddf77eea..5885752bef 100644 --- a/src/Microsoft.ML.Ensemble/Trainer/EnsembleModelParameters.cs +++ b/src/Microsoft.ML.Ensemble/Trainer/EnsembleModelParameters.cs @@ -4,19 +4,19 @@ using System; using System.Threading.Tasks; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Ensemble.OutputCombiners; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble; +using Microsoft.ML.Model; +using Microsoft.ML.Ensemble.OutputCombiners; +using Microsoft.ML.EntryPoints; [assembly: LoadableClass(typeof(EnsembleModelParameters), null, typeof(SignatureLoadModel), EnsembleModelParameters.UserName, EnsembleModelParameters.LoaderSignature)] [assembly: EntryPointModule(typeof(EnsembleModelParameters))] -namespace Microsoft.ML.Runtime.Ensemble +namespace Microsoft.ML.Ensemble { using TScalarPredictor = IPredictorProducing; diff --git a/src/Microsoft.ML.Ensemble/Trainer/EnsembleModelParametersBase.cs b/src/Microsoft.ML.Ensemble/Trainer/EnsembleModelParametersBase.cs index da9cc0f51b..f4a1d6d72d 100644 --- a/src/Microsoft.ML.Ensemble/Trainer/EnsembleModelParametersBase.cs +++ b/src/Microsoft.ML.Ensemble/Trainer/EnsembleModelParametersBase.cs @@ -5,13 +5,13 @@ using System; using System.Collections.Generic; using System.IO; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble.OutputCombiners; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble.OutputCombiners; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; -namespace Microsoft.ML.Runtime.Ensemble +namespace Microsoft.ML.Ensemble { public abstract class EnsembleModelParametersBase : ModelParametersBase, IPredictorProducing, ICanSaveInTextFormat, ICanSaveSummary diff --git a/src/Microsoft.ML.Ensemble/Trainer/EnsembleTrainerBase.cs b/src/Microsoft.ML.Ensemble/Trainer/EnsembleTrainerBase.cs index 7fffa89108..305e05c788 100644 --- a/src/Microsoft.ML.Ensemble/Trainer/EnsembleTrainerBase.cs +++ b/src/Microsoft.ML.Ensemble/Trainer/EnsembleTrainerBase.cs @@ -6,17 +6,17 @@ using System.Collections.Generic; using System.Linq; using System.Threading.Tasks; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble.OutputCombiners; -using Microsoft.ML.Runtime.Ensemble.Selector; -using Microsoft.ML.Runtime.Ensemble.Selector.SubsetSelector; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Training; - -namespace Microsoft.ML.Runtime.Ensemble +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble.OutputCombiners; +using Microsoft.ML.Ensemble.Selector; +using Microsoft.ML.Ensemble.Selector.SubsetSelector; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Training; + +namespace Microsoft.ML.Ensemble { using Stopwatch = System.Diagnostics.Stopwatch; diff --git a/src/Microsoft.ML.Ensemble/Trainer/IModelCombiner.cs b/src/Microsoft.ML.Ensemble/Trainer/IModelCombiner.cs index 196df4dc54..3a2d25b808 100644 --- a/src/Microsoft.ML.Ensemble/Trainer/IModelCombiner.cs +++ b/src/Microsoft.ML.Ensemble/Trainer/IModelCombiner.cs @@ -3,9 +3,9 @@ // See the LICENSE file in the project root for more information. using System.Collections.Generic; -using Microsoft.ML.Runtime; +using Microsoft.ML; -namespace Microsoft.ML.Runtime.Ensemble +namespace Microsoft.ML.Ensemble { public delegate void SignatureModelCombiner(PredictionKind kind); diff --git a/src/Microsoft.ML.Ensemble/Trainer/Multiclass/EnsembleMultiClassModelParameters.cs b/src/Microsoft.ML.Ensemble/Trainer/Multiclass/EnsembleMultiClassModelParameters.cs index 845ab8de90..ecf6ed0a57 100644 --- a/src/Microsoft.ML.Ensemble/Trainer/Multiclass/EnsembleMultiClassModelParameters.cs +++ b/src/Microsoft.ML.Ensemble/Trainer/Multiclass/EnsembleMultiClassModelParameters.cs @@ -4,16 +4,16 @@ using System; using System.Threading.Tasks; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble; -using Microsoft.ML.Runtime.Ensemble.OutputCombiners; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble; +using Microsoft.ML.Ensemble.OutputCombiners; +using Microsoft.ML.Model; [assembly: LoadableClass(typeof(EnsembleMultiClassModelParameters), null, typeof(SignatureLoadModel), EnsembleMultiClassModelParameters.UserName, EnsembleMultiClassModelParameters.LoaderSignature)] -namespace Microsoft.ML.Runtime.Ensemble +namespace Microsoft.ML.Ensemble { using TVectorPredictor = IPredictorProducing>; diff --git a/src/Microsoft.ML.Ensemble/Trainer/Multiclass/MulticlassDataPartitionEnsembleTrainer.cs b/src/Microsoft.ML.Ensemble/Trainer/Multiclass/MulticlassDataPartitionEnsembleTrainer.cs index a4b4844ded..d18803bff4 100644 --- a/src/Microsoft.ML.Ensemble/Trainer/Multiclass/MulticlassDataPartitionEnsembleTrainer.cs +++ b/src/Microsoft.ML.Ensemble/Trainer/Multiclass/MulticlassDataPartitionEnsembleTrainer.cs @@ -6,14 +6,14 @@ using System.Collections.Generic; using System.Linq; using Microsoft.ML.Ensemble.EntryPoints; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble; -using Microsoft.ML.Runtime.Ensemble.OutputCombiners; -using Microsoft.ML.Runtime.Ensemble.Selector; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Learners; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble; +using Microsoft.ML.Ensemble.OutputCombiners; +using Microsoft.ML.Ensemble.Selector; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Learners; [assembly: LoadableClass(MulticlassDataPartitionEnsembleTrainer.Summary, typeof(MulticlassDataPartitionEnsembleTrainer), typeof(MulticlassDataPartitionEnsembleTrainer.Arguments), @@ -24,7 +24,7 @@ [assembly: LoadableClass(typeof(MulticlassDataPartitionEnsembleTrainer), typeof(MulticlassDataPartitionEnsembleTrainer.Arguments), typeof(SignatureModelCombiner), "Multiclass Classification Ensemble Model Combiner", MulticlassDataPartitionEnsembleTrainer.LoadNameValue)] -namespace Microsoft.ML.Runtime.Ensemble +namespace Microsoft.ML.Ensemble { using TVectorPredictor = IPredictorProducing>; /// diff --git a/src/Microsoft.ML.Ensemble/Trainer/Regression/RegressionEnsembleTrainer.cs b/src/Microsoft.ML.Ensemble/Trainer/Regression/RegressionEnsembleTrainer.cs index 4799ae4863..2397736edd 100644 --- a/src/Microsoft.ML.Ensemble/Trainer/Regression/RegressionEnsembleTrainer.cs +++ b/src/Microsoft.ML.Ensemble/Trainer/Regression/RegressionEnsembleTrainer.cs @@ -6,13 +6,13 @@ using System.Collections.Generic; using System.Linq; using Microsoft.ML.Ensemble.EntryPoints; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble; -using Microsoft.ML.Runtime.Ensemble.OutputCombiners; -using Microsoft.ML.Runtime.Ensemble.Selector; -using Microsoft.ML.Runtime.Internal.Internallearn; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble; +using Microsoft.ML.Ensemble.OutputCombiners; +using Microsoft.ML.Ensemble.Selector; +using Microsoft.ML.Internal.Internallearn; using Microsoft.ML.Trainers.Online; [assembly: LoadableClass(typeof(RegressionEnsembleTrainer), typeof(RegressionEnsembleTrainer.Arguments), @@ -23,7 +23,7 @@ [assembly: LoadableClass(typeof(RegressionEnsembleTrainer), typeof(RegressionEnsembleTrainer.Arguments), typeof(SignatureModelCombiner), "Regression Ensemble Model Combiner", RegressionEnsembleTrainer.LoadNameValue)] -namespace Microsoft.ML.Runtime.Ensemble +namespace Microsoft.ML.Ensemble { using TScalarPredictor = IPredictorProducing; internal sealed class RegressionEnsembleTrainer : EnsembleTrainerBase /// The module that splits the input dataset into the specified number of cross-validation folds, and outputs the 'training' diff --git a/src/Microsoft.ML.EntryPoints/CrossValidationMacro.cs b/src/Microsoft.ML.EntryPoints/CrossValidationMacro.cs index 8e0c73fe44..ce64661b57 100644 --- a/src/Microsoft.ML.EntryPoints/CrossValidationMacro.cs +++ b/src/Microsoft.ML.EntryPoints/CrossValidationMacro.cs @@ -5,11 +5,11 @@ using System; using System.Collections.Generic; using System.Linq; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; using Newtonsoft.Json.Linq; [assembly: LoadableClass(typeof(void), typeof(CrossValidationMacro), null, typeof(SignatureEntryPointModule), "CrossValidationMacro")] @@ -17,7 +17,7 @@ // The warning #612 is disabled because the following code uses a lot of things in Legacy.Models and Legacy.Transforms while Legacy is marked as obsolete. // Because that dependency will be removed form ML.NET, one needs to rewrite all places where legacy APIs are used. #pragma warning disable 612 -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { /// diff --git a/src/Microsoft.ML.EntryPoints/DataViewReference.cs b/src/Microsoft.ML.EntryPoints/DataViewReference.cs index 19d51028ea..f799ed6cdf 100644 --- a/src/Microsoft.ML.EntryPoints/DataViewReference.cs +++ b/src/Microsoft.ML.EntryPoints/DataViewReference.cs @@ -2,14 +2,14 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; [assembly: LoadableClass(typeof(void), typeof(DataViewReference), null, typeof(SignatureEntryPointModule), "DataViewReference")] -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { public class DataViewReference { diff --git a/src/Microsoft.ML.EntryPoints/FeatureCombiner.cs b/src/Microsoft.ML.EntryPoints/FeatureCombiner.cs index 24de18e152..bf1faa4b9b 100644 --- a/src/Microsoft.ML.EntryPoints/FeatureCombiner.cs +++ b/src/Microsoft.ML.EntryPoints/FeatureCombiner.cs @@ -3,11 +3,10 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Transforms.Conversions; using System; using System.Collections.Generic; @@ -16,7 +15,7 @@ [assembly: LoadableClass(typeof(void), typeof(FeatureCombiner), null, typeof(SignatureEntryPointModule), "FeatureCombiner")] -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { public static class FeatureCombiner { diff --git a/src/Microsoft.ML.EntryPoints/ImportTextData.cs b/src/Microsoft.ML.EntryPoints/ImportTextData.cs index 483bad1ca1..249f416c4d 100644 --- a/src/Microsoft.ML.EntryPoints/ImportTextData.cs +++ b/src/Microsoft.ML.EntryPoints/ImportTextData.cs @@ -3,17 +3,17 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using System; [assembly: LoadableClass(typeof(void), typeof(ImportTextData), null, typeof(SignatureEntryPointModule), "ImportTextData")] // The warning #612 is disabled because the following code uses legacy TextLoader. // Because that dependency will be removed form ML.NET, one needs to rewrite all places where legacy APIs are used. #pragma warning disable 612 -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { /// /// A component for importing text files as . diff --git a/src/Microsoft.ML.EntryPoints/JsonUtils/ExecuteGraphCommand.cs b/src/Microsoft.ML.EntryPoints/JsonUtils/ExecuteGraphCommand.cs index faa3fbd0ff..75c7634b5a 100644 --- a/src/Microsoft.ML.EntryPoints/JsonUtils/ExecuteGraphCommand.cs +++ b/src/Microsoft.ML.EntryPoints/JsonUtils/ExecuteGraphCommand.cs @@ -6,20 +6,20 @@ using System.Collections.Generic; using System.IO; using System.Linq; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Command; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.EntryPoints.JsonUtils; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Command; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Data.IO; +using Microsoft.ML.EntryPoints.JsonUtils; +using Microsoft.ML.Internal.Utilities; using Newtonsoft.Json; using Newtonsoft.Json.Linq; [assembly: LoadableClass(typeof(ExecuteGraphCommand), typeof(ExecuteGraphCommand.Arguments), typeof(SignatureCommand), "", "ExecGraph")] -namespace Microsoft.ML.Runtime.EntryPoints.JsonUtils +namespace Microsoft.ML.EntryPoints.JsonUtils { internal sealed class ExecuteGraphCommand : ICommand { diff --git a/src/Microsoft.ML.EntryPoints/JsonUtils/GraphRunner.cs b/src/Microsoft.ML.EntryPoints/JsonUtils/GraphRunner.cs index 9cdee0946b..8cff9c0021 100644 --- a/src/Microsoft.ML.EntryPoints/JsonUtils/GraphRunner.cs +++ b/src/Microsoft.ML.EntryPoints/JsonUtils/GraphRunner.cs @@ -5,7 +5,7 @@ using System.Linq; using Newtonsoft.Json.Linq; -namespace Microsoft.ML.Runtime.EntryPoints.JsonUtils +namespace Microsoft.ML.EntryPoints.JsonUtils { /// /// This class runs a graph of entry points with the specified inputs, and produces the specified outputs. diff --git a/src/Microsoft.ML.EntryPoints/JsonUtils/JsonManifestUtils.cs b/src/Microsoft.ML.EntryPoints/JsonUtils/JsonManifestUtils.cs index 526683194a..4e6341dfd1 100644 --- a/src/Microsoft.ML.EntryPoints/JsonUtils/JsonManifestUtils.cs +++ b/src/Microsoft.ML.EntryPoints/JsonUtils/JsonManifestUtils.cs @@ -1,4 +1,4 @@ -// Licensed to the .NET 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. @@ -6,11 +6,11 @@ using System.Collections.Generic; using System.Linq; using System.Reflection; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; using Newtonsoft.Json.Linq; -namespace Microsoft.ML.Runtime.EntryPoints.JsonUtils +namespace Microsoft.ML.EntryPoints.JsonUtils { /// /// Utilities to generate JSON manifests for entry points and other components. @@ -305,7 +305,7 @@ private static JToken BuildTypeToken(IExceptionContext ectx, FieldInfo fieldInfo type == typeof(CommonOutputs.IEvaluatorOutput)) { var jo = new JObject(); - var typeString = $"{type}".Replace("Microsoft.ML.Runtime.EntryPoints.", ""); + var typeString = $"{type}".Replace("Microsoft.ML.EntryPoints.", ""); jo[FieldNames.Kind] = "EntryPoint"; jo[FieldNames.ItemType] = typeString; return jo; diff --git a/src/Microsoft.ML.EntryPoints/MacroUtils.cs b/src/Microsoft.ML.EntryPoints/MacroUtils.cs index 78250b673f..b482fae588 100644 --- a/src/Microsoft.ML.EntryPoints/MacroUtils.cs +++ b/src/Microsoft.ML.EntryPoints/MacroUtils.cs @@ -3,16 +3,17 @@ // See the LICENSE file in the project root for more information. using System.Collections.Generic; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using System.Linq; +using Microsoft.ML.Data; [assembly: EntryPointModule(typeof(MacroUtils))] // The warning #612 is disabled because the following code uses a lot of things in Legacy.Models while Legacy.Model is marked as obsolete. // Because that dependency will be removed form ML.NET, one needs to rewrite all places where legacy APIs are used. #pragma warning disable 612 -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { public static class MacroUtils { diff --git a/src/Microsoft.ML.EntryPoints/ModelOperations.cs b/src/Microsoft.ML.EntryPoints/ModelOperations.cs index 347dc9ef59..1c7cafe594 100644 --- a/src/Microsoft.ML.EntryPoints/ModelOperations.cs +++ b/src/Microsoft.ML.EntryPoints/ModelOperations.cs @@ -2,16 +2,17 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Learners; using Microsoft.ML.Trainers; using System.Linq; [assembly: LoadableClass(typeof(void), typeof(ModelOperations), null, typeof(SignatureEntryPointModule), "ModelOperations")] -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { public static class ModelOperations { diff --git a/src/Microsoft.ML.EntryPoints/OneVersusAllMacro.cs b/src/Microsoft.ML.EntryPoints/OneVersusAllMacro.cs index c39a40bcde..925ce6e342 100644 --- a/src/Microsoft.ML.EntryPoints/OneVersusAllMacro.cs +++ b/src/Microsoft.ML.EntryPoints/OneVersusAllMacro.cs @@ -4,12 +4,12 @@ using System; using System.Collections.Generic; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Training; using Microsoft.ML.Transforms; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Training; using Newtonsoft.Json.Linq; [assembly: LoadableClass(typeof(void), typeof(OneVersusAllMacro), null, typeof(SignatureEntryPointModule), "OneVersusAllMacro")] @@ -17,7 +17,7 @@ // The warning #612 is disabled because the following code uses Legacy.Models and Legacy.Transforms while Legacy is marked as obsolete. // Because that dependency will be removed form ML.NET, one needs to rewrite all places where legacy APIs are used. #pragma warning disable 612 -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { /// /// This macro entrypoint implements OVA. diff --git a/src/Microsoft.ML.EntryPoints/TrainTestMacro.cs b/src/Microsoft.ML.EntryPoints/TrainTestMacro.cs index 9669008446..25a2dd0790 100644 --- a/src/Microsoft.ML.EntryPoints/TrainTestMacro.cs +++ b/src/Microsoft.ML.EntryPoints/TrainTestMacro.cs @@ -2,10 +2,10 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; using Newtonsoft.Json.Linq; using System; using System.Collections.Generic; @@ -15,7 +15,7 @@ // The warning #612 is disabled because the following code uses a lot of things in Legacy.Models and Legacy.Transforms while Legacy is marked as obsolete. // Because that dependency will be removed form ML.NET, one needs to rewrite all places where legacy APIs are used. #pragma warning disable 612 -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { public static class TrainTestMacro { diff --git a/src/Microsoft.ML.EntryPoints/TrainTestSplit.cs b/src/Microsoft.ML.EntryPoints/TrainTestSplit.cs index 928e557e37..a4b8ec98a6 100644 --- a/src/Microsoft.ML.EntryPoints/TrainTestSplit.cs +++ b/src/Microsoft.ML.EntryPoints/TrainTestSplit.cs @@ -2,16 +2,16 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Conversions; [assembly: LoadableClass(typeof(void), typeof(TrainTestSplit), null, typeof(SignatureEntryPointModule), "TrainTestSplit")] -namespace Microsoft.ML.Runtime.EntryPoints +namespace Microsoft.ML.EntryPoints { public static class TrainTestSplit { diff --git a/src/Microsoft.ML.FastTree/Application/DominationLossApplication.cs b/src/Microsoft.ML.FastTree/Application/DominationLossApplication.cs index e9330adfe4..912163ff0e 100644 --- a/src/Microsoft.ML.FastTree/Application/DominationLossApplication.cs +++ b/src/Microsoft.ML.FastTree/Application/DominationLossApplication.cs @@ -3,7 +3,7 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime.CommandLine; +using Microsoft.ML.CommandLine; namespace Microsoft.ML.Trainers.FastTree.Internal { diff --git a/src/Microsoft.ML.FastTree/Application/LogLossApplication.cs b/src/Microsoft.ML.FastTree/Application/LogLossApplication.cs index 27fe732fc9..ff72ca0a87 100644 --- a/src/Microsoft.ML.FastTree/Application/LogLossApplication.cs +++ b/src/Microsoft.ML.FastTree/Application/LogLossApplication.cs @@ -6,7 +6,7 @@ using System.Collections.Generic; using System.Linq; using System.Text; -using Microsoft.ML.Runtime.CommandLine; +using Microsoft.ML.CommandLine; namespace Microsoft.ML.Trainers.FastTree.Internal { diff --git a/src/Microsoft.ML.FastTree/Application/SizeAdjustedLogLossApplication.cs b/src/Microsoft.ML.FastTree/Application/SizeAdjustedLogLossApplication.cs index 7ac4ce8dac..beaa529014 100644 --- a/src/Microsoft.ML.FastTree/Application/SizeAdjustedLogLossApplication.cs +++ b/src/Microsoft.ML.FastTree/Application/SizeAdjustedLogLossApplication.cs @@ -7,7 +7,7 @@ using System.Globalization; using System.IO; using System.Linq; -using Microsoft.ML.Runtime.CommandLine; +using Microsoft.ML.CommandLine; namespace Microsoft.ML.Trainers.FastTree.Internal { diff --git a/src/Microsoft.ML.FastTree/Application/WinLossSurplusApplication.cs b/src/Microsoft.ML.FastTree/Application/WinLossSurplusApplication.cs index 93618e2fa1..86d88a0e7a 100644 --- a/src/Microsoft.ML.FastTree/Application/WinLossSurplusApplication.cs +++ b/src/Microsoft.ML.FastTree/Application/WinLossSurplusApplication.cs @@ -5,7 +5,7 @@ using System; using System.Linq; using System.Runtime.InteropServices; -using Microsoft.ML.Runtime.CommandLine; +using Microsoft.ML.CommandLine; namespace Microsoft.ML.Trainers.FastTree.Internal { diff --git a/src/Microsoft.ML.FastTree/BinFile/BinFinder.cs b/src/Microsoft.ML.FastTree/BinFile/BinFinder.cs index eaae7d5448..3af21d4d1e 100644 --- a/src/Microsoft.ML.FastTree/BinFile/BinFinder.cs +++ b/src/Microsoft.ML.FastTree/BinFile/BinFinder.cs @@ -2,9 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; using System; using System.Threading; diff --git a/src/Microsoft.ML.FastTree/BinFile/IniFileParserInterface.cs b/src/Microsoft.ML.FastTree/BinFile/IniFileParserInterface.cs index 70d7899b90..9a56fcf601 100644 --- a/src/Microsoft.ML.FastTree/BinFile/IniFileParserInterface.cs +++ b/src/Microsoft.ML.FastTree/BinFile/IniFileParserInterface.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; using System; using System.Linq; using System.Runtime.InteropServices; diff --git a/src/Microsoft.ML.FastTree/BoostingFastTree.cs b/src/Microsoft.ML.FastTree/BoostingFastTree.cs index 4ae0bf16b6..386237b55c 100644 --- a/src/Microsoft.ML.FastTree/BoostingFastTree.cs +++ b/src/Microsoft.ML.FastTree/BoostingFastTree.cs @@ -3,8 +3,8 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Internal.Internallearn; +using Microsoft.ML; +using Microsoft.ML.Internal.Internallearn; using Microsoft.ML.Trainers.FastTree.Internal; using System; using System.Linq; diff --git a/src/Microsoft.ML.FastTree/Dataset/Dataset.cs b/src/Microsoft.ML.FastTree/Dataset/Dataset.cs index a1e70ab5b9..57a8f16417 100644 --- a/src/Microsoft.ML.FastTree/Dataset/Dataset.cs +++ b/src/Microsoft.ML.FastTree/Dataset/Dataset.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Internal.Utilities; using System; using System.Collections.Generic; using System.Linq; diff --git a/src/Microsoft.ML.FastTree/Dataset/DenseIntArray.cs b/src/Microsoft.ML.FastTree/Dataset/DenseIntArray.cs index bc28bf8e84..7d54e7ad59 100644 --- a/src/Microsoft.ML.FastTree/Dataset/DenseIntArray.cs +++ b/src/Microsoft.ML.FastTree/Dataset/DenseIntArray.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; using System; using System.Collections.Generic; using System.Linq; diff --git a/src/Microsoft.ML.FastTree/Dataset/Feature.cs b/src/Microsoft.ML.FastTree/Dataset/Feature.cs index 0b02f8e4f2..31f8b7d08a 100644 --- a/src/Microsoft.ML.FastTree/Dataset/Feature.cs +++ b/src/Microsoft.ML.FastTree/Dataset/Feature.cs @@ -3,7 +3,7 @@ // See the LICENSE file in the project root for more information. using System.Linq; -using Microsoft.ML.Runtime; +using Microsoft.ML; namespace Microsoft.ML.Trainers.FastTree.Internal { diff --git a/src/Microsoft.ML.FastTree/Dataset/FeatureFlock.cs b/src/Microsoft.ML.FastTree/Dataset/FeatureFlock.cs index cb3070d45b..b2cdec0ee8 100644 --- a/src/Microsoft.ML.FastTree/Dataset/FeatureFlock.cs +++ b/src/Microsoft.ML.FastTree/Dataset/FeatureFlock.cs @@ -12,9 +12,9 @@ using System.Collections.Generic; using System.Linq; using System.Runtime.CompilerServices; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Internal.CpuMath; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Internal.CpuMath; +using Microsoft.ML.Internal.Utilities; namespace Microsoft.ML.Trainers.FastTree.Internal { diff --git a/src/Microsoft.ML.FastTree/Dataset/FeatureHistogram.cs b/src/Microsoft.ML.FastTree/Dataset/FeatureHistogram.cs index 5ba2508374..5098517bcf 100644 --- a/src/Microsoft.ML.FastTree/Dataset/FeatureHistogram.cs +++ b/src/Microsoft.ML.FastTree/Dataset/FeatureHistogram.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; using System; using System.Linq; diff --git a/src/Microsoft.ML.FastTree/Dataset/IntArray.cs b/src/Microsoft.ML.FastTree/Dataset/IntArray.cs index dd17900733..eef09700a7 100644 --- a/src/Microsoft.ML.FastTree/Dataset/IntArray.cs +++ b/src/Microsoft.ML.FastTree/Dataset/IntArray.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; using System; using System.Collections.Generic; using System.Linq; diff --git a/src/Microsoft.ML.FastTree/Dataset/NHotFeatureFlock.cs b/src/Microsoft.ML.FastTree/Dataset/NHotFeatureFlock.cs index 272f9e6d92..7ced1e2d60 100644 --- a/src/Microsoft.ML.FastTree/Dataset/NHotFeatureFlock.cs +++ b/src/Microsoft.ML.FastTree/Dataset/NHotFeatureFlock.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; namespace Microsoft.ML.Trainers.FastTree.Internal { diff --git a/src/Microsoft.ML.FastTree/Dataset/OneHotFeatureFlock.cs b/src/Microsoft.ML.FastTree/Dataset/OneHotFeatureFlock.cs index 01a26e85d5..cb1b5c4722 100644 --- a/src/Microsoft.ML.FastTree/Dataset/OneHotFeatureFlock.cs +++ b/src/Microsoft.ML.FastTree/Dataset/OneHotFeatureFlock.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; using System.Linq; namespace Microsoft.ML.Trainers.FastTree.Internal diff --git a/src/Microsoft.ML.FastTree/Dataset/RepeatIntArray.cs b/src/Microsoft.ML.FastTree/Dataset/RepeatIntArray.cs index d5b9e2964e..64cdb6effe 100644 --- a/src/Microsoft.ML.FastTree/Dataset/RepeatIntArray.cs +++ b/src/Microsoft.ML.FastTree/Dataset/RepeatIntArray.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; using System; using System.Collections.Generic; using System.Linq; diff --git a/src/Microsoft.ML.FastTree/Dataset/SegmentIntArray.cs b/src/Microsoft.ML.FastTree/Dataset/SegmentIntArray.cs index 2ac14484bb..b8d862ee1b 100644 --- a/src/Microsoft.ML.FastTree/Dataset/SegmentIntArray.cs +++ b/src/Microsoft.ML.FastTree/Dataset/SegmentIntArray.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; using System.Collections.Generic; using System.Linq; using System.Runtime.InteropServices; diff --git a/src/Microsoft.ML.FastTree/Dataset/SingletonFeatureFlock.cs b/src/Microsoft.ML.FastTree/Dataset/SingletonFeatureFlock.cs index 91f74faa9a..d449a19d0a 100644 --- a/src/Microsoft.ML.FastTree/Dataset/SingletonFeatureFlock.cs +++ b/src/Microsoft.ML.FastTree/Dataset/SingletonFeatureFlock.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Internal.Utilities; using System.Linq; namespace Microsoft.ML.Trainers.FastTree.Internal diff --git a/src/Microsoft.ML.FastTree/Dataset/SparseIntArray.cs b/src/Microsoft.ML.FastTree/Dataset/SparseIntArray.cs index 8b030fc85a..3dcb7d341c 100644 --- a/src/Microsoft.ML.FastTree/Dataset/SparseIntArray.cs +++ b/src/Microsoft.ML.FastTree/Dataset/SparseIntArray.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; using System.Collections.Generic; using System.Linq; using System.Runtime.InteropServices; diff --git a/src/Microsoft.ML.FastTree/FastTree.cs b/src/Microsoft.ML.FastTree/FastTree.cs index 19835a99fa..d816d3ec59 100644 --- a/src/Microsoft.ML.FastTree/FastTree.cs +++ b/src/Microsoft.ML.FastTree/FastTree.cs @@ -5,19 +5,18 @@ using Microsoft.ML.Calibrator; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.Conversion; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Onnx; -using Microsoft.ML.Runtime.Model.Pfa; -using Microsoft.ML.Runtime.Training; -using Microsoft.ML.Runtime.TreePredictor; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data.Conversion; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Onnx; +using Microsoft.ML.Model.Pfa; +using Microsoft.ML.Training; +using Microsoft.ML.TreePredictor; using Microsoft.ML.Trainers.FastTree.Internal; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Conversions; @@ -2947,7 +2946,7 @@ ValueMapper> IFeatureContributionMapper.GetFeatureContribut (in VBuffer src, ref VBuffer dst) => { FeatureContributionMap(in src, ref dst, ref builder); - Runtime.Numeric.VectorUtils.SparsifyNormalize(ref dst, top, bottom, normalize); + Numeric.VectorUtils.SparsifyNormalize(ref dst, top, bottom, normalize); }; return (ValueMapper>)(Delegate)del; } diff --git a/src/Microsoft.ML.FastTree/FastTreeArguments.cs b/src/Microsoft.ML.FastTree/FastTreeArguments.cs index f68108d2e8..3a551d4359 100644 --- a/src/Microsoft.ML.FastTree/FastTreeArguments.cs +++ b/src/Microsoft.ML.FastTree/FastTreeArguments.cs @@ -2,10 +2,10 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; using Microsoft.ML.Trainers.FastTree; using System; diff --git a/src/Microsoft.ML.FastTree/FastTreeClassification.cs b/src/Microsoft.ML.FastTree/FastTreeClassification.cs index 533af9c511..090d6308cf 100644 --- a/src/Microsoft.ML.FastTree/FastTreeClassification.cs +++ b/src/Microsoft.ML.FastTree/FastTreeClassification.cs @@ -5,13 +5,12 @@ using Microsoft.ML.Calibrator; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Model; +using Microsoft.ML.Training; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Trainers.FastTree.Internal; using System; diff --git a/src/Microsoft.ML.FastTree/FastTreeRanking.cs b/src/Microsoft.ML.FastTree/FastTreeRanking.cs index 6fcb983311..054617841e 100644 --- a/src/Microsoft.ML.FastTree/FastTreeRanking.cs +++ b/src/Microsoft.ML.FastTree/FastTreeRanking.cs @@ -4,13 +4,12 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Training; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Trainers.FastTree.Internal; using System; diff --git a/src/Microsoft.ML.FastTree/FastTreeRegression.cs b/src/Microsoft.ML.FastTree/FastTreeRegression.cs index 9bccf98f9a..2649485545 100644 --- a/src/Microsoft.ML.FastTree/FastTreeRegression.cs +++ b/src/Microsoft.ML.FastTree/FastTreeRegression.cs @@ -4,12 +4,11 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Model; +using Microsoft.ML.Training; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Trainers.FastTree.Internal; using System; diff --git a/src/Microsoft.ML.FastTree/FastTreeTweedie.cs b/src/Microsoft.ML.FastTree/FastTreeTweedie.cs index 50f75c16d9..63bd90804a 100644 --- a/src/Microsoft.ML.FastTree/FastTreeTweedie.cs +++ b/src/Microsoft.ML.FastTree/FastTreeTweedie.cs @@ -4,13 +4,12 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Training; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Trainers.FastTree.Internal; using System; diff --git a/src/Microsoft.ML.FastTree/GamClassification.cs b/src/Microsoft.ML.FastTree/GamClassification.cs index 5bf850e547..6d96a709c8 100644 --- a/src/Microsoft.ML.FastTree/GamClassification.cs +++ b/src/Microsoft.ML.FastTree/GamClassification.cs @@ -5,13 +5,12 @@ using Microsoft.ML.Calibrator; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Model; +using Microsoft.ML.Training; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Trainers.FastTree.Internal; using System; diff --git a/src/Microsoft.ML.FastTree/GamRegression.cs b/src/Microsoft.ML.FastTree/GamRegression.cs index 6397c16711..287bd8428f 100644 --- a/src/Microsoft.ML.FastTree/GamRegression.cs +++ b/src/Microsoft.ML.FastTree/GamRegression.cs @@ -4,12 +4,11 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Model; +using Microsoft.ML.Training; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Trainers.FastTree.Internal; using System; diff --git a/src/Microsoft.ML.FastTree/GamTrainer.cs b/src/Microsoft.ML.FastTree/GamTrainer.cs index 8915b98305..cb5e50262b 100644 --- a/src/Microsoft.ML.FastTree/GamTrainer.cs +++ b/src/Microsoft.ML.FastTree/GamTrainer.cs @@ -4,17 +4,16 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Command; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.CpuMath; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.Command; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.CpuMath; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Training; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Trainers.FastTree.Internal; using System; @@ -1026,7 +1025,7 @@ private void GetFeatureContributions(in VBuffer features, ref VBuffer diff --git a/src/Microsoft.ML.FastTree/QuantileStatistics.cs b/src/Microsoft.ML.FastTree/QuantileStatistics.cs index ea8eb0eadd..d05407bf34 100644 --- a/src/Microsoft.ML.FastTree/QuantileStatistics.cs +++ b/src/Microsoft.ML.FastTree/QuantileStatistics.cs @@ -3,10 +3,10 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Internal.Internallearn; -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { public sealed class QuantileStatistics : IQuantileDistribution { diff --git a/src/Microsoft.ML.FastTree/RandomForest.cs b/src/Microsoft.ML.FastTree/RandomForest.cs index ab91a02e21..cb8cbf9cf6 100644 --- a/src/Microsoft.ML.FastTree/RandomForest.cs +++ b/src/Microsoft.ML.FastTree/RandomForest.cs @@ -3,7 +3,7 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; +using Microsoft.ML; using Microsoft.ML.Trainers.FastTree.Internal; using System; diff --git a/src/Microsoft.ML.FastTree/RandomForestClassification.cs b/src/Microsoft.ML.FastTree/RandomForestClassification.cs index e4710727cd..67438da189 100644 --- a/src/Microsoft.ML.FastTree/RandomForestClassification.cs +++ b/src/Microsoft.ML.FastTree/RandomForestClassification.cs @@ -5,14 +5,13 @@ using Microsoft.ML.Calibrator; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Model; +using Microsoft.ML.Training; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Trainers.FastTree.Internal; using System; diff --git a/src/Microsoft.ML.FastTree/RandomForestRegression.cs b/src/Microsoft.ML.FastTree/RandomForestRegression.cs index efd12235f5..bd20572ffd 100644 --- a/src/Microsoft.ML.FastTree/RandomForestRegression.cs +++ b/src/Microsoft.ML.FastTree/RandomForestRegression.cs @@ -4,14 +4,13 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Training; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Trainers.FastTree.Internal; using System; diff --git a/src/Microsoft.ML.FastTree/SumupPerformanceCommand.cs b/src/Microsoft.ML.FastTree/SumupPerformanceCommand.cs index fb48563dd6..19b44c4706 100644 --- a/src/Microsoft.ML.FastTree/SumupPerformanceCommand.cs +++ b/src/Microsoft.ML.FastTree/SumupPerformanceCommand.cs @@ -12,12 +12,12 @@ using System.Collections.Generic; using System.Linq; using System.Threading; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Command; -using Microsoft.ML.Runtime.CommandLine; +using Microsoft.ML; +using Microsoft.ML.Command; +using Microsoft.ML.CommandLine; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Trainers.FastTree.Internal; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; [assembly: LoadableClass(typeof(SumupPerformanceCommand), typeof(SumupPerformanceCommand.Arguments), typeof(SignatureCommand), "", "FastTreeSumupPerformance", "ftsumup")] diff --git a/src/Microsoft.ML.FastTree/Training/Applications/ObjectiveFunction.cs b/src/Microsoft.ML.FastTree/Training/Applications/ObjectiveFunction.cs index 775f15779b..4e6c978214 100644 --- a/src/Microsoft.ML.FastTree/Training/Applications/ObjectiveFunction.cs +++ b/src/Microsoft.ML.FastTree/Training/Applications/ObjectiveFunction.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; using System; using System.Collections.Concurrent; using System.Linq; diff --git a/src/Microsoft.ML.FastTree/Training/DcgCalculator.cs b/src/Microsoft.ML.FastTree/Training/DcgCalculator.cs index d81a93d6bc..0a0e293538 100644 --- a/src/Microsoft.ML.FastTree/Training/DcgCalculator.cs +++ b/src/Microsoft.ML.FastTree/Training/DcgCalculator.cs @@ -2,11 +2,11 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; using System; using System.Linq; using System.Threading.Tasks; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; namespace Microsoft.ML.Trainers.FastTree.Internal { diff --git a/src/Microsoft.ML.FastTree/Training/DcgPermutationComparer.cs b/src/Microsoft.ML.FastTree/Training/DcgPermutationComparer.cs index 6467c9d0eb..204d2f77d0 100644 --- a/src/Microsoft.ML.FastTree/Training/DcgPermutationComparer.cs +++ b/src/Microsoft.ML.FastTree/Training/DcgPermutationComparer.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; using System.Collections.Generic; namespace Microsoft.ML.Trainers.FastTree.Internal diff --git a/src/Microsoft.ML.FastTree/Training/DocumentPartitioning.cs b/src/Microsoft.ML.FastTree/Training/DocumentPartitioning.cs index 9b2947b556..7344331612 100644 --- a/src/Microsoft.ML.FastTree/Training/DocumentPartitioning.cs +++ b/src/Microsoft.ML.FastTree/Training/DocumentPartitioning.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; using System; using System.Collections.Generic; using System.Linq; diff --git a/src/Microsoft.ML.FastTree/Training/EnsembleCompression/IEnsembleCompressor.cs b/src/Microsoft.ML.FastTree/Training/EnsembleCompression/IEnsembleCompressor.cs index 47fca98092..e4ae77fb20 100644 --- a/src/Microsoft.ML.FastTree/Training/EnsembleCompression/IEnsembleCompressor.cs +++ b/src/Microsoft.ML.FastTree/Training/EnsembleCompression/IEnsembleCompressor.cs @@ -4,7 +4,7 @@ // // ----------------------------------------------------------------------- -using Microsoft.ML.Runtime; +using Microsoft.ML; namespace Microsoft.ML.Trainers.FastTree.Internal { diff --git a/src/Microsoft.ML.FastTree/Training/EnsembleCompression/LassoBasedEnsembleCompressor.cs b/src/Microsoft.ML.FastTree/Training/EnsembleCompression/LassoBasedEnsembleCompressor.cs index d005573d25..52e37f5761 100644 --- a/src/Microsoft.ML.FastTree/Training/EnsembleCompression/LassoBasedEnsembleCompressor.cs +++ b/src/Microsoft.ML.FastTree/Training/EnsembleCompression/LassoBasedEnsembleCompressor.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; using System; using System.Collections.Generic; using System.Diagnostics; diff --git a/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/AcceleratedGradientDescent.cs b/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/AcceleratedGradientDescent.cs index 110c40155e..a860389024 100644 --- a/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/AcceleratedGradientDescent.cs +++ b/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/AcceleratedGradientDescent.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; namespace Microsoft.ML.Trainers.FastTree.Internal { diff --git a/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/ConjugateGradientDescent.cs b/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/ConjugateGradientDescent.cs index 7eae8d90e9..5d4f979162 100644 --- a/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/ConjugateGradientDescent.cs +++ b/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/ConjugateGradientDescent.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; namespace Microsoft.ML.Trainers.FastTree.Internal { diff --git a/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/GradientDescent.cs b/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/GradientDescent.cs index 159e833b2d..d9b5b4ac08 100644 --- a/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/GradientDescent.cs +++ b/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/GradientDescent.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; using System; using System.Collections.Generic; using System.Linq; diff --git a/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/NoOptimizationAlgorithm.cs b/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/NoOptimizationAlgorithm.cs index 6822bdf4c2..bc8c3adfdc 100644 --- a/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/NoOptimizationAlgorithm.cs +++ b/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/NoOptimizationAlgorithm.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; namespace Microsoft.ML.Trainers.FastTree.Internal { diff --git a/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/OptimizationAlgorithm.cs b/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/OptimizationAlgorithm.cs index d18107e25d..e76d827a3e 100644 --- a/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/OptimizationAlgorithm.cs +++ b/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/OptimizationAlgorithm.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.FastTree/Training/Parallel/IParallelTraining.cs b/src/Microsoft.ML.FastTree/Training/Parallel/IParallelTraining.cs index 0b28e2157c..22fc393968 100644 --- a/src/Microsoft.ML.FastTree/Training/Parallel/IParallelTraining.cs +++ b/src/Microsoft.ML.FastTree/Training/Parallel/IParallelTraining.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.EntryPoints; using Microsoft.ML.Trainers.FastTree.Internal; using System; diff --git a/src/Microsoft.ML.FastTree/Training/Parallel/SingleTrainer.cs b/src/Microsoft.ML.FastTree/Training/Parallel/SingleTrainer.cs index c5859cd559..6ca4d6f18e 100644 --- a/src/Microsoft.ML.FastTree/Training/Parallel/SingleTrainer.cs +++ b/src/Microsoft.ML.FastTree/Training/Parallel/SingleTrainer.cs @@ -3,10 +3,10 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.EntryPoints; using Microsoft.ML.Trainers.FastTree; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; [assembly: LoadableClass(typeof(Microsoft.ML.Trainers.FastTree.SingleTrainer), null, typeof(Microsoft.ML.Trainers.FastTree.SignatureParallelTrainer), "single")] diff --git a/src/Microsoft.ML.FastTree/Training/ScoreTracker.cs b/src/Microsoft.ML.FastTree/Training/ScoreTracker.cs index c383681958..37fbfc84e5 100644 --- a/src/Microsoft.ML.FastTree/Training/ScoreTracker.cs +++ b/src/Microsoft.ML.FastTree/Training/ScoreTracker.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; using System; using System.Collections.Generic; using System.Threading.Tasks; diff --git a/src/Microsoft.ML.FastTree/Training/StepSearch.cs b/src/Microsoft.ML.FastTree/Training/StepSearch.cs index 13139f7e68..96a1b87b24 100644 --- a/src/Microsoft.ML.FastTree/Training/StepSearch.cs +++ b/src/Microsoft.ML.FastTree/Training/StepSearch.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; using System; using System.Linq; diff --git a/src/Microsoft.ML.FastTree/Training/Test.cs b/src/Microsoft.ML.FastTree/Training/Test.cs index 6792c84b81..5d60f32227 100644 --- a/src/Microsoft.ML.FastTree/Training/Test.cs +++ b/src/Microsoft.ML.FastTree/Training/Test.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; using System; using System.Collections.Generic; using System.Linq; diff --git a/src/Microsoft.ML.FastTree/Training/TreeLearners/FastForestLeastSquaresTreeLearner.cs b/src/Microsoft.ML.FastTree/Training/TreeLearners/FastForestLeastSquaresTreeLearner.cs index cd42672c74..69f218f958 100644 --- a/src/Microsoft.ML.FastTree/Training/TreeLearners/FastForestLeastSquaresTreeLearner.cs +++ b/src/Microsoft.ML.FastTree/Training/TreeLearners/FastForestLeastSquaresTreeLearner.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; using System; namespace Microsoft.ML.Trainers.FastTree.Internal diff --git a/src/Microsoft.ML.FastTree/Training/TreeLearners/LeastSquaresRegressionTreeLearner.cs b/src/Microsoft.ML.FastTree/Training/TreeLearners/LeastSquaresRegressionTreeLearner.cs index 7b1a5f8b7d..a932b2099a 100644 --- a/src/Microsoft.ML.FastTree/Training/TreeLearners/LeastSquaresRegressionTreeLearner.cs +++ b/src/Microsoft.ML.FastTree/Training/TreeLearners/LeastSquaresRegressionTreeLearner.cs @@ -2,9 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Internal.CpuMath; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Internal.CpuMath; +using Microsoft.ML.Internal.Utilities; using System; using System.Collections.Generic; using System.Linq; diff --git a/src/Microsoft.ML.FastTree/Training/TreeLearners/TreeLearner.cs b/src/Microsoft.ML.FastTree/Training/TreeLearners/TreeLearner.cs index 8d61f63e8b..51296d2f2b 100644 --- a/src/Microsoft.ML.FastTree/Training/TreeLearners/TreeLearner.cs +++ b/src/Microsoft.ML.FastTree/Training/TreeLearners/TreeLearner.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; using System; namespace Microsoft.ML.Trainers.FastTree.Internal diff --git a/src/Microsoft.ML.FastTree/Training/WinLossCalculator.cs b/src/Microsoft.ML.FastTree/Training/WinLossCalculator.cs index 0c3d89ed10..0320a23ded 100644 --- a/src/Microsoft.ML.FastTree/Training/WinLossCalculator.cs +++ b/src/Microsoft.ML.FastTree/Training/WinLossCalculator.cs @@ -6,7 +6,7 @@ using System.Collections.Concurrent; using System.Linq; using System.Threading.Tasks; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; namespace Microsoft.ML.Trainers.FastTree.Internal { diff --git a/src/Microsoft.ML.FastTree/TreeEnsemble/QuantileRegressionTree.cs b/src/Microsoft.ML.FastTree/TreeEnsemble/QuantileRegressionTree.cs index 6025160c20..f2d3bc9a3a 100644 --- a/src/Microsoft.ML.FastTree/TreeEnsemble/QuantileRegressionTree.cs +++ b/src/Microsoft.ML.FastTree/TreeEnsemble/QuantileRegressionTree.cs @@ -2,10 +2,10 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Float = System.Single; namespace Microsoft.ML.Trainers.FastTree.Internal diff --git a/src/Microsoft.ML.FastTree/TreeEnsemble/RegressionTree.cs b/src/Microsoft.ML.FastTree/TreeEnsemble/RegressionTree.cs index 7cd371ba91..ec170b5c35 100644 --- a/src/Microsoft.ML.FastTree/TreeEnsemble/RegressionTree.cs +++ b/src/Microsoft.ML.FastTree/TreeEnsemble/RegressionTree.cs @@ -2,12 +2,12 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Pfa; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Pfa; using Newtonsoft.Json.Linq; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.FastTree/TreeEnsemble/TreeEnsemble.cs b/src/Microsoft.ML.FastTree/TreeEnsemble/TreeEnsemble.cs index ab320319f1..3ce93dfb9a 100644 --- a/src/Microsoft.ML.FastTree/TreeEnsemble/TreeEnsemble.cs +++ b/src/Microsoft.ML.FastTree/TreeEnsemble/TreeEnsemble.cs @@ -3,11 +3,9 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Pfa; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Pfa; using Newtonsoft.Json.Linq; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.FastTree/TreeEnsemble/TreeEnsembleCombiner.cs b/src/Microsoft.ML.FastTree/TreeEnsemble/TreeEnsembleCombiner.cs index 21a8063218..405876bd04 100644 --- a/src/Microsoft.ML.FastTree/TreeEnsemble/TreeEnsembleCombiner.cs +++ b/src/Microsoft.ML.FastTree/TreeEnsemble/TreeEnsembleCombiner.cs @@ -2,9 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Ensemble; -using Microsoft.ML.Runtime.Internal.Calibration; +using Microsoft.ML; +using Microsoft.ML.Ensemble; +using Microsoft.ML.Internal.Calibration; using Microsoft.ML.Trainers.FastTree.Internal; using System.Collections.Generic; diff --git a/src/Microsoft.ML.FastTree/TreeEnsembleFeaturizer.cs b/src/Microsoft.ML.FastTree/TreeEnsembleFeaturizer.cs index 3e0fc0bb76..dfc55f931d 100644 --- a/src/Microsoft.ML.FastTree/TreeEnsembleFeaturizer.cs +++ b/src/Microsoft.ML.FastTree/TreeEnsembleFeaturizer.cs @@ -3,15 +3,14 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.Conversion; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.TreePredictor; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data.Conversion; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.TreePredictor; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Transforms; using System; @@ -33,7 +32,7 @@ [assembly: LoadableClass(typeof(void), typeof(TreeFeaturize), null, typeof(SignatureEntryPointModule), "TreeFeaturize")] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// A bindable mapper wrapper for tree ensembles, that creates a bound mapper with three outputs: diff --git a/src/Microsoft.ML.FastTree/TreeTrainersCatalog.cs b/src/Microsoft.ML.FastTree/TreeTrainersCatalog.cs index 584484de10..8a900adc64 100644 --- a/src/Microsoft.ML.FastTree/TreeTrainersCatalog.cs +++ b/src/Microsoft.ML.FastTree/TreeTrainersCatalog.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.Trainers.FastTree; using System; diff --git a/src/Microsoft.ML.FastTree/TreeTrainersStatic.cs b/src/Microsoft.ML.FastTree/TreeTrainersStatic.cs index 5893a06eda..375499ad44 100644 --- a/src/Microsoft.ML.FastTree/TreeTrainersStatic.cs +++ b/src/Microsoft.ML.FastTree/TreeTrainersStatic.cs @@ -2,10 +2,10 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.Trainers.FastTree; -using Microsoft.ML.Runtime.Internal.Internallearn; +using Microsoft.ML.Internal.Internallearn; using Microsoft.ML.StaticPipe.Runtime; using System; diff --git a/src/Microsoft.ML.FastTree/Utils/Algorithms.cs b/src/Microsoft.ML.FastTree/Utils/Algorithms.cs index 304e185c4f..0060ac5270 100644 --- a/src/Microsoft.ML.FastTree/Utils/Algorithms.cs +++ b/src/Microsoft.ML.FastTree/Utils/Algorithms.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; using System; using System.Linq; diff --git a/src/Microsoft.ML.FastTree/Utils/BufferPoolManager.cs b/src/Microsoft.ML.FastTree/Utils/BufferPoolManager.cs index 5197e7ed4c..112c130f21 100644 --- a/src/Microsoft.ML.FastTree/Utils/BufferPoolManager.cs +++ b/src/Microsoft.ML.FastTree/Utils/BufferPoolManager.cs @@ -4,7 +4,7 @@ // // ----------------------------------------------------------------------- -using Microsoft.ML.Runtime; +using Microsoft.ML; using System; using System.Collections.Concurrent; using System.Collections.Generic; diff --git a/src/Microsoft.ML.FastTree/Utils/MD5Hasher.cs b/src/Microsoft.ML.FastTree/Utils/MD5Hasher.cs index 4367d7940d..37792cd30b 100644 --- a/src/Microsoft.ML.FastTree/Utils/MD5Hasher.cs +++ b/src/Microsoft.ML.FastTree/Utils/MD5Hasher.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Internal.Utilities; using System; using System.IO; using System.Security.Cryptography; diff --git a/src/Microsoft.ML.FastTree/Utils/ThreadTaskManager.cs b/src/Microsoft.ML.FastTree/Utils/ThreadTaskManager.cs index e53bc7f0c6..7cece8ceea 100644 --- a/src/Microsoft.ML.FastTree/Utils/ThreadTaskManager.cs +++ b/src/Microsoft.ML.FastTree/Utils/ThreadTaskManager.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; using System; using System.Collections.Generic; using System.Linq; diff --git a/src/Microsoft.ML.FastTree/Utils/ToByteArrayExtensions.cs b/src/Microsoft.ML.FastTree/Utils/ToByteArrayExtensions.cs index dfecfc8f80..53d475df1e 100644 --- a/src/Microsoft.ML.FastTree/Utils/ToByteArrayExtensions.cs +++ b/src/Microsoft.ML.FastTree/Utils/ToByteArrayExtensions.cs @@ -5,7 +5,7 @@ using System; using System.Linq; using System.Text; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; namespace Microsoft.ML.Trainers.FastTree.Internal { diff --git a/src/Microsoft.ML.HalLearners.StaticPipe/VectorWhiteningStaticExtensions.cs b/src/Microsoft.ML.HalLearners.StaticPipe/VectorWhiteningStaticExtensions.cs index 2adaf92e13..d1f52bca9c 100644 --- a/src/Microsoft.ML.HalLearners.StaticPipe/VectorWhiteningStaticExtensions.cs +++ b/src/Microsoft.ML.HalLearners.StaticPipe/VectorWhiteningStaticExtensions.cs @@ -1,10 +1,10 @@ -// Licensed to the .NET 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. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; using Microsoft.ML.StaticPipe; +using Microsoft.ML; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Transforms.Projections; using System.Collections.Generic; diff --git a/src/Microsoft.ML.HalLearners/ComputeLRTrainingStdThroughHal.cs b/src/Microsoft.ML.HalLearners/ComputeLRTrainingStdThroughHal.cs index 0a387c1e03..a89de8e2aa 100644 --- a/src/Microsoft.ML.HalLearners/ComputeLRTrainingStdThroughHal.cs +++ b/src/Microsoft.ML.HalLearners/ComputeLRTrainingStdThroughHal.cs @@ -2,12 +2,12 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Trainers.HalLearners; using System; -namespace Microsoft.ML.Runtime.Learners +namespace Microsoft.ML.Learners { using Mkl = OlsLinearRegressionTrainer.Mkl; diff --git a/src/Microsoft.ML.HalLearners/HalLearnersCatalog.cs b/src/Microsoft.ML.HalLearners/HalLearnersCatalog.cs index 72d163e65a..42cc1ce797 100644 --- a/src/Microsoft.ML.HalLearners/HalLearnersCatalog.cs +++ b/src/Microsoft.ML.HalLearners/HalLearnersCatalog.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.Trainers.HalLearners; using Microsoft.ML.Trainers.SymSgd; using Microsoft.ML.Transforms.Projections; diff --git a/src/Microsoft.ML.HalLearners/OlsLinearRegression.cs b/src/Microsoft.ML.HalLearners/OlsLinearRegression.cs index d3af2258ca..e0b13c4555 100644 --- a/src/Microsoft.ML.HalLearners/OlsLinearRegression.cs +++ b/src/Microsoft.ML.HalLearners/OlsLinearRegression.cs @@ -4,15 +4,14 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Learners; +using Microsoft.ML.Model; +using Microsoft.ML.Training; using Microsoft.ML.Trainers.HalLearners; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.HalLearners/SymSgdClassificationTrainer.cs b/src/Microsoft.ML.HalLearners/SymSgdClassificationTrainer.cs index 1670e8a897..7eacb9a972 100644 --- a/src/Microsoft.ML.HalLearners/SymSgdClassificationTrainer.cs +++ b/src/Microsoft.ML.HalLearners/SymSgdClassificationTrainer.cs @@ -4,16 +4,15 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.Conversion; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data.Conversion; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Learners; +using Microsoft.ML.Training; using Microsoft.ML.Trainers.SymSgd; using Microsoft.ML.Transforms; using System; diff --git a/src/Microsoft.ML.HalLearners/VectorWhitening.cs b/src/Microsoft.ML.HalLearners/VectorWhitening.cs index f41a1e64e6..0a784065d6 100644 --- a/src/Microsoft.ML.HalLearners/VectorWhitening.cs +++ b/src/Microsoft.ML.HalLearners/VectorWhitening.cs @@ -4,13 +4,12 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.CpuMath; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.CpuMath; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms.Projections; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.ImageAnalytics/EntryPoints/ImageAnalytics.cs b/src/Microsoft.ML.ImageAnalytics/EntryPoints/ImageAnalytics.cs index dc63fa0f17..18e5cbc61f 100644 --- a/src/Microsoft.ML.ImageAnalytics/EntryPoints/ImageAnalytics.cs +++ b/src/Microsoft.ML.ImageAnalytics/EntryPoints/ImageAnalytics.cs @@ -2,12 +2,12 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.ImageAnalytics.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.ImageAnalytics.EntryPoints; [assembly: LoadableClass(typeof(void), typeof(ImageAnalytics), null, typeof(SignatureEntryPointModule), "ImageAnalytics")] -namespace Microsoft.ML.Runtime.ImageAnalytics.EntryPoints +namespace Microsoft.ML.ImageAnalytics.EntryPoints { public static class ImageAnalytics { diff --git a/src/Microsoft.ML.ImageAnalytics/ExtensionsCatalog.cs b/src/Microsoft.ML.ImageAnalytics/ExtensionsCatalog.cs index 0c76c08384..c39f0d33a9 100644 --- a/src/Microsoft.ML.ImageAnalytics/ExtensionsCatalog.cs +++ b/src/Microsoft.ML.ImageAnalytics/ExtensionsCatalog.cs @@ -2,9 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.ImageAnalytics; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.ImageAnalytics; namespace Microsoft.ML { diff --git a/src/Microsoft.ML.ImageAnalytics/ImageGrayscaleTransform.cs b/src/Microsoft.ML.ImageAnalytics/ImageGrayscaleTransform.cs index 7973efa037..4d14ddd9e8 100644 --- a/src/Microsoft.ML.ImageAnalytics/ImageGrayscaleTransform.cs +++ b/src/Microsoft.ML.ImageAnalytics/ImageGrayscaleTransform.cs @@ -4,13 +4,12 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.ImageAnalytics; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.ImageAnalytics; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.StaticPipe; using Microsoft.ML.StaticPipe.Runtime; using System; @@ -32,7 +31,7 @@ [assembly: LoadableClass(typeof(IRowMapper), typeof(ImageGrayscaleTransform), null, typeof(SignatureLoadRowMapper), ImageGrayscaleTransform.UserName, ImageGrayscaleTransform.LoaderSignature)] -namespace Microsoft.ML.Runtime.ImageAnalytics +namespace Microsoft.ML.ImageAnalytics { // REVIEW: Rewrite as LambdaTransform to simplify. // REVIEW: Should it be separate transform or part of ImageResizerTransform? diff --git a/src/Microsoft.ML.ImageAnalytics/ImageLoaderTransform.cs b/src/Microsoft.ML.ImageAnalytics/ImageLoaderTransform.cs index a5df8d315d..415024d153 100644 --- a/src/Microsoft.ML.ImageAnalytics/ImageLoaderTransform.cs +++ b/src/Microsoft.ML.ImageAnalytics/ImageLoaderTransform.cs @@ -4,13 +4,12 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.ImageAnalytics; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.ImageAnalytics; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.StaticPipe; using Microsoft.ML.StaticPipe.Runtime; using System; @@ -30,7 +29,7 @@ [assembly: LoadableClass(typeof(IRowMapper), typeof(ImageLoaderTransform), null, typeof(SignatureLoadRowMapper), "", ImageLoaderTransform.LoaderSignature)] -namespace Microsoft.ML.Runtime.ImageAnalytics +namespace Microsoft.ML.ImageAnalytics { /// /// Transform which takes one or many columns of type ReadOnlyMemory and loads them as diff --git a/src/Microsoft.ML.ImageAnalytics/ImagePixelExtractorTransform.cs b/src/Microsoft.ML.ImageAnalytics/ImagePixelExtractorTransform.cs index 8435715958..4d6cc8de22 100644 --- a/src/Microsoft.ML.ImageAnalytics/ImagePixelExtractorTransform.cs +++ b/src/Microsoft.ML.ImageAnalytics/ImagePixelExtractorTransform.cs @@ -10,13 +10,12 @@ using System.Text; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.ImageAnalytics; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.ImageAnalytics; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.StaticPipe; using Microsoft.ML.StaticPipe.Runtime; @@ -32,7 +31,7 @@ [assembly: LoadableClass(typeof(IRowMapper), typeof(ImagePixelExtractorTransform), null, typeof(SignatureLoadRowMapper), ImagePixelExtractorTransform.UserName, ImagePixelExtractorTransform.LoaderSignature)] -namespace Microsoft.ML.Runtime.ImageAnalytics +namespace Microsoft.ML.ImageAnalytics { /// /// Transform which takes one or many columns of and convert them into vector representation. diff --git a/src/Microsoft.ML.ImageAnalytics/ImageResizerTransform.cs b/src/Microsoft.ML.ImageAnalytics/ImageResizerTransform.cs index b0e9559f29..469cf69766 100644 --- a/src/Microsoft.ML.ImageAnalytics/ImageResizerTransform.cs +++ b/src/Microsoft.ML.ImageAnalytics/ImageResizerTransform.cs @@ -9,14 +9,13 @@ using System.Text; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.ImageAnalytics; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.ImageAnalytics; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.StaticPipe; using Microsoft.ML.StaticPipe.Runtime; @@ -32,7 +31,7 @@ [assembly: LoadableClass(typeof(IRowMapper), typeof(ImageResizerTransform), null, typeof(SignatureLoadRowMapper), ImageResizerTransform.UserName, ImageResizerTransform.LoaderSignature)] -namespace Microsoft.ML.Runtime.ImageAnalytics +namespace Microsoft.ML.ImageAnalytics { // REVIEW: Rewrite as LambdaTransform to simplify. /// diff --git a/src/Microsoft.ML.ImageAnalytics/ImageStaticPipe.cs b/src/Microsoft.ML.ImageAnalytics/ImageStaticPipe.cs index cf67103d86..aaf99431ee 100644 --- a/src/Microsoft.ML.ImageAnalytics/ImageStaticPipe.cs +++ b/src/Microsoft.ML.ImageAnalytics/ImageStaticPipe.cs @@ -6,7 +6,7 @@ using System.Drawing; using Microsoft.ML.StaticPipe; -namespace Microsoft.ML.Runtime.ImageAnalytics +namespace Microsoft.ML.ImageAnalytics { /// /// A type used in the generic argument to . We must simultaneously distinguish diff --git a/src/Microsoft.ML.ImageAnalytics/ImageType.cs b/src/Microsoft.ML.ImageAnalytics/ImageType.cs index fd31302808..4b6446e365 100644 --- a/src/Microsoft.ML.ImageAnalytics/ImageType.cs +++ b/src/Microsoft.ML.ImageAnalytics/ImageType.cs @@ -4,10 +4,10 @@ using System; using System.Drawing; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.ImageAnalytics +namespace Microsoft.ML.ImageAnalytics { public sealed class ImageType : StructuredType { diff --git a/src/Microsoft.ML.ImageAnalytics/Microsoft.ML.ImageAnalytics.csproj b/src/Microsoft.ML.ImageAnalytics/Microsoft.ML.ImageAnalytics.csproj index 9829bcf26f..0134a050fb 100644 --- a/src/Microsoft.ML.ImageAnalytics/Microsoft.ML.ImageAnalytics.csproj +++ b/src/Microsoft.ML.ImageAnalytics/Microsoft.ML.ImageAnalytics.csproj @@ -2,8 +2,8 @@ netstandard2.0 - Microsoft.ML.Runtime.ImageAnalytics - Microsoft.ML.Runtime.ImageAnalytics + Microsoft.ML.ImageAnalytics + Microsoft.ML.ImageAnalytics Microsoft.ML.ImageAnalytics diff --git a/src/Microsoft.ML.ImageAnalytics/VectorToImageTransform.cs b/src/Microsoft.ML.ImageAnalytics/VectorToImageTransform.cs index bee1383b14..0d2ccb53da 100644 --- a/src/Microsoft.ML.ImageAnalytics/VectorToImageTransform.cs +++ b/src/Microsoft.ML.ImageAnalytics/VectorToImageTransform.cs @@ -5,13 +5,13 @@ using System; using System.Drawing; using System.Text; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.ImageAnalytics; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.ImageAnalytics; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; [assembly: LoadableClass(VectorToImageTransform.Summary, typeof(VectorToImageTransform), typeof(VectorToImageTransform.Arguments), typeof(SignatureDataTransform), VectorToImageTransform.UserName, "VectorToImageTransform", "VectorToImage")] @@ -19,7 +19,7 @@ [assembly: LoadableClass(VectorToImageTransform.Summary, typeof(VectorToImageTransform), null, typeof(SignatureLoadDataTransform), VectorToImageTransform.UserName, VectorToImageTransform.LoaderSignature)] -namespace Microsoft.ML.Runtime.ImageAnalytics +namespace Microsoft.ML.ImageAnalytics { // REVIEW: Rewrite as LambdaTransform to simplify. diff --git a/src/Microsoft.ML.KMeansClustering/KMeansCatalog.cs b/src/Microsoft.ML.KMeansClustering/KMeansCatalog.cs index c096750ae0..2e121a61e6 100644 --- a/src/Microsoft.ML.KMeansClustering/KMeansCatalog.cs +++ b/src/Microsoft.ML.KMeansClustering/KMeansCatalog.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.Trainers.KMeans; using System; diff --git a/src/Microsoft.ML.KMeansClustering/KMeansModelParameters.cs b/src/Microsoft.ML.KMeansClustering/KMeansModelParameters.cs index baedf917d7..b70d6a0f65 100644 --- a/src/Microsoft.ML.KMeansClustering/KMeansModelParameters.cs +++ b/src/Microsoft.ML.KMeansClustering/KMeansModelParameters.cs @@ -4,13 +4,13 @@ using Float = System.Single; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Onnx; -using Microsoft.ML.Runtime.Numeric; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Onnx; +using Microsoft.ML.Numeric; using Microsoft.ML.Trainers.KMeans; using System; using System.IO; diff --git a/src/Microsoft.ML.KMeansClustering/KMeansPlusPlusTrainer.cs b/src/Microsoft.ML.KMeansClustering/KMeansPlusPlusTrainer.cs index 7d0ae0ab4b..eb249d29e3 100644 --- a/src/Microsoft.ML.KMeansClustering/KMeansPlusPlusTrainer.cs +++ b/src/Microsoft.ML.KMeansClustering/KMeansPlusPlusTrainer.cs @@ -4,15 +4,14 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.CpuMath; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Numeric; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.CpuMath; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Numeric; +using Microsoft.ML.Training; using Microsoft.ML.Trainers.KMeans; using System; using System.Linq; diff --git a/src/Microsoft.ML.KMeansClustering/KMeansStatic.cs b/src/Microsoft.ML.KMeansClustering/KMeansStatic.cs index 1fb94afc8e..7022cd8e6e 100644 --- a/src/Microsoft.ML.KMeansClustering/KMeansStatic.cs +++ b/src/Microsoft.ML.KMeansClustering/KMeansStatic.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Trainers.KMeans; using System; diff --git a/src/Microsoft.ML.Legacy/AssemblyRegistration.cs b/src/Microsoft.ML.Legacy/AssemblyRegistration.cs index e4d5d780e5..f8e6a855c3 100644 --- a/src/Microsoft.ML.Legacy/AssemblyRegistration.cs +++ b/src/Microsoft.ML.Legacy/AssemblyRegistration.cs @@ -2,10 +2,10 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble; -using Microsoft.ML.Runtime.Sweeper; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble; +using Microsoft.ML.Sweeper; +using Microsoft.ML.Tools; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Trainers.KMeans; using Microsoft.ML.Trainers.PCA; @@ -13,7 +13,7 @@ using System; using System.Reflection; -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { internal static class AssemblyRegistration { @@ -50,7 +50,7 @@ private static bool LoadStandardAssemblies() _ = typeof(OneHotEncodingTransformer).Assembly; // ML.Transforms // The following assemblies reference this assembly, so we can't directly reference them - //_ = typeof(Microsoft.ML.Runtime.Data.LinearPredictor).Assembly); // ML.StandardLearners + //_ = typeof(Microsoft.ML.Data.LinearPredictor).Assembly); // ML.StandardLearners _ = Assembly.Load(new AssemblyName() { Name = "Microsoft.ML.StandardLearners", diff --git a/src/Microsoft.ML.Legacy/CSharpApi.cs b/src/Microsoft.ML.Legacy/CSharpApi.cs index 98372c2339..b607908914 100644 --- a/src/Microsoft.ML.Legacy/CSharpApi.cs +++ b/src/Microsoft.ML.Legacy/CSharpApi.cs @@ -8,1939 +8,1936 @@ //------------------------------------------------------------------------------ #pragma warning disable using System.Collections.Generic; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; using Newtonsoft.Json; using System; using System.Linq; -using Microsoft.ML.Runtime.CommandLine; +using Microsoft.ML.CommandLine; namespace Microsoft.ML { - namespace Runtime + public sealed partial class Experiment { - public sealed partial class Experiment + [Obsolete] + public Microsoft.ML.Legacy.Data.CustomTextLoader.Output Add(Microsoft.ML.Legacy.Data.CustomTextLoader input) { - [Obsolete] - public Microsoft.ML.Legacy.Data.CustomTextLoader.Output Add(Microsoft.ML.Legacy.Data.CustomTextLoader input) - { - var output = new Microsoft.ML.Legacy.Data.CustomTextLoader.Output(); - Add(input, output); - return output; - } - - [Obsolete] - public void Add(Microsoft.ML.Legacy.Data.CustomTextLoader input, Microsoft.ML.Legacy.Data.CustomTextLoader.Output output) - { - _jsonNodes.Add(Serialize("Data.CustomTextLoader", input, output)); - } + var output = new Microsoft.ML.Legacy.Data.CustomTextLoader.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Data.DataViewReference.Output Add(Microsoft.ML.Legacy.Data.DataViewReference input) - { - var output = new Microsoft.ML.Legacy.Data.DataViewReference.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Data.CustomTextLoader input, Microsoft.ML.Legacy.Data.CustomTextLoader.Output output) + { + _jsonNodes.Add(Serialize("Data.CustomTextLoader", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Data.DataViewReference input, Microsoft.ML.Legacy.Data.DataViewReference.Output output) - { - _jsonNodes.Add(Serialize("Data.DataViewReference", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Data.DataViewReference.Output Add(Microsoft.ML.Legacy.Data.DataViewReference input) + { + var output = new Microsoft.ML.Legacy.Data.DataViewReference.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Data.IDataViewArrayConverter.Output Add(Microsoft.ML.Legacy.Data.IDataViewArrayConverter input) - { - var output = new Microsoft.ML.Legacy.Data.IDataViewArrayConverter.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Data.DataViewReference input, Microsoft.ML.Legacy.Data.DataViewReference.Output output) + { + _jsonNodes.Add(Serialize("Data.DataViewReference", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Data.IDataViewArrayConverter input, Microsoft.ML.Legacy.Data.IDataViewArrayConverter.Output output) - { - _jsonNodes.Add(Serialize("Data.IDataViewArrayConverter", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Data.IDataViewArrayConverter.Output Add(Microsoft.ML.Legacy.Data.IDataViewArrayConverter input) + { + var output = new Microsoft.ML.Legacy.Data.IDataViewArrayConverter.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Data.PredictorModelArrayConverter.Output Add(Microsoft.ML.Legacy.Data.PredictorModelArrayConverter input) - { - var output = new Microsoft.ML.Legacy.Data.PredictorModelArrayConverter.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Data.IDataViewArrayConverter input, Microsoft.ML.Legacy.Data.IDataViewArrayConverter.Output output) + { + _jsonNodes.Add(Serialize("Data.IDataViewArrayConverter", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Data.PredictorModelArrayConverter input, Microsoft.ML.Legacy.Data.PredictorModelArrayConverter.Output output) - { - _jsonNodes.Add(Serialize("Data.PredictorModelArrayConverter", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Data.PredictorModelArrayConverter.Output Add(Microsoft.ML.Legacy.Data.PredictorModelArrayConverter input) + { + var output = new Microsoft.ML.Legacy.Data.PredictorModelArrayConverter.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Data.TextLoader.Output Add(Microsoft.ML.Legacy.Data.TextLoader input) - { - var output = new Microsoft.ML.Legacy.Data.TextLoader.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Data.PredictorModelArrayConverter input, Microsoft.ML.Legacy.Data.PredictorModelArrayConverter.Output output) + { + _jsonNodes.Add(Serialize("Data.PredictorModelArrayConverter", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Data.TextLoader input, Microsoft.ML.Legacy.Data.TextLoader.Output output) - { - _jsonNodes.Add(Serialize("Data.TextLoader", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Data.TextLoader.Output Add(Microsoft.ML.Legacy.Data.TextLoader input) + { + var output = new Microsoft.ML.Legacy.Data.TextLoader.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Models.AnomalyDetectionEvaluator.Output Add(Microsoft.ML.Legacy.Models.AnomalyDetectionEvaluator input) - { - var output = new Microsoft.ML.Legacy.Models.AnomalyDetectionEvaluator.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Data.TextLoader input, Microsoft.ML.Legacy.Data.TextLoader.Output output) + { + _jsonNodes.Add(Serialize("Data.TextLoader", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.AnomalyDetectionEvaluator input, Microsoft.ML.Legacy.Models.AnomalyDetectionEvaluator.Output output) - { - _jsonNodes.Add(Serialize("Models.AnomalyDetectionEvaluator", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Models.AnomalyDetectionEvaluator.Output Add(Microsoft.ML.Legacy.Models.AnomalyDetectionEvaluator input) + { + var output = new Microsoft.ML.Legacy.Models.AnomalyDetectionEvaluator.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Models.AnomalyPipelineEnsemble.Output Add(Microsoft.ML.Legacy.Models.AnomalyPipelineEnsemble input) - { - var output = new Microsoft.ML.Legacy.Models.AnomalyPipelineEnsemble.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.AnomalyDetectionEvaluator input, Microsoft.ML.Legacy.Models.AnomalyDetectionEvaluator.Output output) + { + _jsonNodes.Add(Serialize("Models.AnomalyDetectionEvaluator", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.AnomalyPipelineEnsemble input, Microsoft.ML.Legacy.Models.AnomalyPipelineEnsemble.Output output) - { - _jsonNodes.Add(Serialize("Models.AnomalyPipelineEnsemble", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Models.AnomalyPipelineEnsemble.Output Add(Microsoft.ML.Legacy.Models.AnomalyPipelineEnsemble input) + { + var output = new Microsoft.ML.Legacy.Models.AnomalyPipelineEnsemble.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Models.BinaryClassificationEvaluator.Output Add(Microsoft.ML.Legacy.Models.BinaryClassificationEvaluator input) - { - var output = new Microsoft.ML.Legacy.Models.BinaryClassificationEvaluator.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.AnomalyPipelineEnsemble input, Microsoft.ML.Legacy.Models.AnomalyPipelineEnsemble.Output output) + { + _jsonNodes.Add(Serialize("Models.AnomalyPipelineEnsemble", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.BinaryClassificationEvaluator input, Microsoft.ML.Legacy.Models.BinaryClassificationEvaluator.Output output) - { - _jsonNodes.Add(Serialize("Models.BinaryClassificationEvaluator", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Models.BinaryClassificationEvaluator.Output Add(Microsoft.ML.Legacy.Models.BinaryClassificationEvaluator input) + { + var output = new Microsoft.ML.Legacy.Models.BinaryClassificationEvaluator.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Models.BinaryEnsemble.Output Add(Microsoft.ML.Legacy.Models.BinaryEnsemble input) - { - var output = new Microsoft.ML.Legacy.Models.BinaryEnsemble.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.BinaryClassificationEvaluator input, Microsoft.ML.Legacy.Models.BinaryClassificationEvaluator.Output output) + { + _jsonNodes.Add(Serialize("Models.BinaryClassificationEvaluator", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.BinaryEnsemble input, Microsoft.ML.Legacy.Models.BinaryEnsemble.Output output) - { - _jsonNodes.Add(Serialize("Models.BinaryEnsemble", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Models.BinaryEnsemble.Output Add(Microsoft.ML.Legacy.Models.BinaryEnsemble input) + { + var output = new Microsoft.ML.Legacy.Models.BinaryEnsemble.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Models.BinaryPipelineEnsemble.Output Add(Microsoft.ML.Legacy.Models.BinaryPipelineEnsemble input) - { - var output = new Microsoft.ML.Legacy.Models.BinaryPipelineEnsemble.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.BinaryEnsemble input, Microsoft.ML.Legacy.Models.BinaryEnsemble.Output output) + { + _jsonNodes.Add(Serialize("Models.BinaryEnsemble", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.BinaryPipelineEnsemble input, Microsoft.ML.Legacy.Models.BinaryPipelineEnsemble.Output output) - { - _jsonNodes.Add(Serialize("Models.BinaryPipelineEnsemble", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Models.BinaryPipelineEnsemble.Output Add(Microsoft.ML.Legacy.Models.BinaryPipelineEnsemble input) + { + var output = new Microsoft.ML.Legacy.Models.BinaryPipelineEnsemble.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Models.ClassificationEvaluator.Output Add(Microsoft.ML.Legacy.Models.ClassificationEvaluator input) - { - var output = new Microsoft.ML.Legacy.Models.ClassificationEvaluator.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.BinaryPipelineEnsemble input, Microsoft.ML.Legacy.Models.BinaryPipelineEnsemble.Output output) + { + _jsonNodes.Add(Serialize("Models.BinaryPipelineEnsemble", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.ClassificationEvaluator input, Microsoft.ML.Legacy.Models.ClassificationEvaluator.Output output) - { - _jsonNodes.Add(Serialize("Models.ClassificationEvaluator", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Models.ClassificationEvaluator.Output Add(Microsoft.ML.Legacy.Models.ClassificationEvaluator input) + { + var output = new Microsoft.ML.Legacy.Models.ClassificationEvaluator.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Models.ClusterEvaluator.Output Add(Microsoft.ML.Legacy.Models.ClusterEvaluator input) - { - var output = new Microsoft.ML.Legacy.Models.ClusterEvaluator.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.ClassificationEvaluator input, Microsoft.ML.Legacy.Models.ClassificationEvaluator.Output output) + { + _jsonNodes.Add(Serialize("Models.ClassificationEvaluator", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.ClusterEvaluator input, Microsoft.ML.Legacy.Models.ClusterEvaluator.Output output) - { - _jsonNodes.Add(Serialize("Models.ClusterEvaluator", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Models.ClusterEvaluator.Output Add(Microsoft.ML.Legacy.Models.ClusterEvaluator input) + { + var output = new Microsoft.ML.Legacy.Models.ClusterEvaluator.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Models.CrossValidationResultsCombiner.Output Add(Microsoft.ML.Legacy.Models.CrossValidationResultsCombiner input) - { - var output = new Microsoft.ML.Legacy.Models.CrossValidationResultsCombiner.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.ClusterEvaluator input, Microsoft.ML.Legacy.Models.ClusterEvaluator.Output output) + { + _jsonNodes.Add(Serialize("Models.ClusterEvaluator", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.CrossValidationResultsCombiner input, Microsoft.ML.Legacy.Models.CrossValidationResultsCombiner.Output output) - { - _jsonNodes.Add(Serialize("Models.CrossValidationResultsCombiner", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Models.CrossValidationResultsCombiner.Output Add(Microsoft.ML.Legacy.Models.CrossValidationResultsCombiner input) + { + var output = new Microsoft.ML.Legacy.Models.CrossValidationResultsCombiner.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Models.CrossValidator.Output Add(Microsoft.ML.Legacy.Models.CrossValidator input) - { - var output = new Microsoft.ML.Legacy.Models.CrossValidator.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.CrossValidationResultsCombiner input, Microsoft.ML.Legacy.Models.CrossValidationResultsCombiner.Output output) + { + _jsonNodes.Add(Serialize("Models.CrossValidationResultsCombiner", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.CrossValidator input, Microsoft.ML.Legacy.Models.CrossValidator.Output output) - { - _jsonNodes.Add(Serialize("Models.CrossValidator", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Models.CrossValidator.Output Add(Microsoft.ML.Legacy.Models.CrossValidator input) + { + var output = new Microsoft.ML.Legacy.Models.CrossValidator.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Models.CrossValidatorDatasetSplitter.Output Add(Microsoft.ML.Legacy.Models.CrossValidatorDatasetSplitter input) - { - var output = new Microsoft.ML.Legacy.Models.CrossValidatorDatasetSplitter.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.CrossValidator input, Microsoft.ML.Legacy.Models.CrossValidator.Output output) + { + _jsonNodes.Add(Serialize("Models.CrossValidator", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.CrossValidatorDatasetSplitter input, Microsoft.ML.Legacy.Models.CrossValidatorDatasetSplitter.Output output) - { - _jsonNodes.Add(Serialize("Models.CrossValidatorDatasetSplitter", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Models.CrossValidatorDatasetSplitter.Output Add(Microsoft.ML.Legacy.Models.CrossValidatorDatasetSplitter input) + { + var output = new Microsoft.ML.Legacy.Models.CrossValidatorDatasetSplitter.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Models.DatasetTransformer.Output Add(Microsoft.ML.Legacy.Models.DatasetTransformer input) - { - var output = new Microsoft.ML.Legacy.Models.DatasetTransformer.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.CrossValidatorDatasetSplitter input, Microsoft.ML.Legacy.Models.CrossValidatorDatasetSplitter.Output output) + { + _jsonNodes.Add(Serialize("Models.CrossValidatorDatasetSplitter", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.DatasetTransformer input, Microsoft.ML.Legacy.Models.DatasetTransformer.Output output) - { - _jsonNodes.Add(Serialize("Models.DatasetTransformer", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Models.DatasetTransformer.Output Add(Microsoft.ML.Legacy.Models.DatasetTransformer input) + { + var output = new Microsoft.ML.Legacy.Models.DatasetTransformer.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Models.EnsembleSummary.Output Add(Microsoft.ML.Legacy.Models.EnsembleSummary input) - { - var output = new Microsoft.ML.Legacy.Models.EnsembleSummary.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.DatasetTransformer input, Microsoft.ML.Legacy.Models.DatasetTransformer.Output output) + { + _jsonNodes.Add(Serialize("Models.DatasetTransformer", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.EnsembleSummary input, Microsoft.ML.Legacy.Models.EnsembleSummary.Output output) - { - _jsonNodes.Add(Serialize("Models.EnsembleSummary", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Models.EnsembleSummary.Output Add(Microsoft.ML.Legacy.Models.EnsembleSummary input) + { + var output = new Microsoft.ML.Legacy.Models.EnsembleSummary.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Models.FixedPlattCalibrator.Output Add(Microsoft.ML.Legacy.Models.FixedPlattCalibrator input) - { - var output = new Microsoft.ML.Legacy.Models.FixedPlattCalibrator.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.EnsembleSummary input, Microsoft.ML.Legacy.Models.EnsembleSummary.Output output) + { + _jsonNodes.Add(Serialize("Models.EnsembleSummary", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.FixedPlattCalibrator input, Microsoft.ML.Legacy.Models.FixedPlattCalibrator.Output output) - { - _jsonNodes.Add(Serialize("Models.FixedPlattCalibrator", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Models.FixedPlattCalibrator.Output Add(Microsoft.ML.Legacy.Models.FixedPlattCalibrator input) + { + var output = new Microsoft.ML.Legacy.Models.FixedPlattCalibrator.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Models.MultiClassPipelineEnsemble.Output Add(Microsoft.ML.Legacy.Models.MultiClassPipelineEnsemble input) - { - var output = new Microsoft.ML.Legacy.Models.MultiClassPipelineEnsemble.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.FixedPlattCalibrator input, Microsoft.ML.Legacy.Models.FixedPlattCalibrator.Output output) + { + _jsonNodes.Add(Serialize("Models.FixedPlattCalibrator", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.MultiClassPipelineEnsemble input, Microsoft.ML.Legacy.Models.MultiClassPipelineEnsemble.Output output) - { - _jsonNodes.Add(Serialize("Models.MultiClassPipelineEnsemble", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Models.MultiClassPipelineEnsemble.Output Add(Microsoft.ML.Legacy.Models.MultiClassPipelineEnsemble input) + { + var output = new Microsoft.ML.Legacy.Models.MultiClassPipelineEnsemble.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Models.MultiOutputRegressionEvaluator.Output Add(Microsoft.ML.Legacy.Models.MultiOutputRegressionEvaluator input) - { - var output = new Microsoft.ML.Legacy.Models.MultiOutputRegressionEvaluator.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.MultiClassPipelineEnsemble input, Microsoft.ML.Legacy.Models.MultiClassPipelineEnsemble.Output output) + { + _jsonNodes.Add(Serialize("Models.MultiClassPipelineEnsemble", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.MultiOutputRegressionEvaluator input, Microsoft.ML.Legacy.Models.MultiOutputRegressionEvaluator.Output output) - { - _jsonNodes.Add(Serialize("Models.MultiOutputRegressionEvaluator", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Models.MultiOutputRegressionEvaluator.Output Add(Microsoft.ML.Legacy.Models.MultiOutputRegressionEvaluator input) + { + var output = new Microsoft.ML.Legacy.Models.MultiOutputRegressionEvaluator.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Models.NaiveCalibrator.Output Add(Microsoft.ML.Legacy.Models.NaiveCalibrator input) - { - var output = new Microsoft.ML.Legacy.Models.NaiveCalibrator.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.MultiOutputRegressionEvaluator input, Microsoft.ML.Legacy.Models.MultiOutputRegressionEvaluator.Output output) + { + _jsonNodes.Add(Serialize("Models.MultiOutputRegressionEvaluator", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.NaiveCalibrator input, Microsoft.ML.Legacy.Models.NaiveCalibrator.Output output) - { - _jsonNodes.Add(Serialize("Models.NaiveCalibrator", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Models.NaiveCalibrator.Output Add(Microsoft.ML.Legacy.Models.NaiveCalibrator input) + { + var output = new Microsoft.ML.Legacy.Models.NaiveCalibrator.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Models.OneVersusAll.Output Add(Microsoft.ML.Legacy.Models.OneVersusAll input) - { - var output = new Microsoft.ML.Legacy.Models.OneVersusAll.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.NaiveCalibrator input, Microsoft.ML.Legacy.Models.NaiveCalibrator.Output output) + { + _jsonNodes.Add(Serialize("Models.NaiveCalibrator", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.OneVersusAll input, Microsoft.ML.Legacy.Models.OneVersusAll.Output output) - { - _jsonNodes.Add(Serialize("Models.OneVersusAll", input, output)); - } - - [Obsolete] - public Microsoft.ML.Legacy.Models.OnnxConverter.Output Add(Microsoft.ML.Legacy.Models.OnnxConverter input) - { - var output = new Microsoft.ML.Legacy.Models.OnnxConverter.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Models.OneVersusAll.Output Add(Microsoft.ML.Legacy.Models.OneVersusAll input) + { + var output = new Microsoft.ML.Legacy.Models.OneVersusAll.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.OnnxConverter input, Microsoft.ML.Legacy.Models.OnnxConverter.Output output) - { - _jsonNodes.Add(Serialize("Models.OnnxConverter", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.OneVersusAll input, Microsoft.ML.Legacy.Models.OneVersusAll.Output output) + { + _jsonNodes.Add(Serialize("Models.OneVersusAll", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Models.OvaModelCombiner.Output Add(Microsoft.ML.Legacy.Models.OvaModelCombiner input) - { - var output = new Microsoft.ML.Legacy.Models.OvaModelCombiner.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Models.OnnxConverter.Output Add(Microsoft.ML.Legacy.Models.OnnxConverter input) + { + var output = new Microsoft.ML.Legacy.Models.OnnxConverter.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.OvaModelCombiner input, Microsoft.ML.Legacy.Models.OvaModelCombiner.Output output) - { - _jsonNodes.Add(Serialize("Models.OvaModelCombiner", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.OnnxConverter input, Microsoft.ML.Legacy.Models.OnnxConverter.Output output) + { + _jsonNodes.Add(Serialize("Models.OnnxConverter", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Models.PAVCalibrator.Output Add(Microsoft.ML.Legacy.Models.PAVCalibrator input) - { - var output = new Microsoft.ML.Legacy.Models.PAVCalibrator.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Models.OvaModelCombiner.Output Add(Microsoft.ML.Legacy.Models.OvaModelCombiner input) + { + var output = new Microsoft.ML.Legacy.Models.OvaModelCombiner.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.PAVCalibrator input, Microsoft.ML.Legacy.Models.PAVCalibrator.Output output) - { - _jsonNodes.Add(Serialize("Models.PAVCalibrator", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.OvaModelCombiner input, Microsoft.ML.Legacy.Models.OvaModelCombiner.Output output) + { + _jsonNodes.Add(Serialize("Models.OvaModelCombiner", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Models.PlattCalibrator.Output Add(Microsoft.ML.Legacy.Models.PlattCalibrator input) - { - var output = new Microsoft.ML.Legacy.Models.PlattCalibrator.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Models.PAVCalibrator.Output Add(Microsoft.ML.Legacy.Models.PAVCalibrator input) + { + var output = new Microsoft.ML.Legacy.Models.PAVCalibrator.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.PlattCalibrator input, Microsoft.ML.Legacy.Models.PlattCalibrator.Output output) - { - _jsonNodes.Add(Serialize("Models.PlattCalibrator", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.PAVCalibrator input, Microsoft.ML.Legacy.Models.PAVCalibrator.Output output) + { + _jsonNodes.Add(Serialize("Models.PAVCalibrator", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Models.QuantileRegressionEvaluator.Output Add(Microsoft.ML.Legacy.Models.QuantileRegressionEvaluator input) - { - var output = new Microsoft.ML.Legacy.Models.QuantileRegressionEvaluator.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Models.PlattCalibrator.Output Add(Microsoft.ML.Legacy.Models.PlattCalibrator input) + { + var output = new Microsoft.ML.Legacy.Models.PlattCalibrator.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.QuantileRegressionEvaluator input, Microsoft.ML.Legacy.Models.QuantileRegressionEvaluator.Output output) - { - _jsonNodes.Add(Serialize("Models.QuantileRegressionEvaluator", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.PlattCalibrator input, Microsoft.ML.Legacy.Models.PlattCalibrator.Output output) + { + _jsonNodes.Add(Serialize("Models.PlattCalibrator", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Models.RankerEvaluator.Output Add(Microsoft.ML.Legacy.Models.RankerEvaluator input) - { - var output = new Microsoft.ML.Legacy.Models.RankerEvaluator.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Models.QuantileRegressionEvaluator.Output Add(Microsoft.ML.Legacy.Models.QuantileRegressionEvaluator input) + { + var output = new Microsoft.ML.Legacy.Models.QuantileRegressionEvaluator.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.RankerEvaluator input, Microsoft.ML.Legacy.Models.RankerEvaluator.Output output) - { - _jsonNodes.Add(Serialize("Models.RankerEvaluator", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.QuantileRegressionEvaluator input, Microsoft.ML.Legacy.Models.QuantileRegressionEvaluator.Output output) + { + _jsonNodes.Add(Serialize("Models.QuantileRegressionEvaluator", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Models.RegressionEnsemble.Output Add(Microsoft.ML.Legacy.Models.RegressionEnsemble input) - { - var output = new Microsoft.ML.Legacy.Models.RegressionEnsemble.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Models.RankerEvaluator.Output Add(Microsoft.ML.Legacy.Models.RankerEvaluator input) + { + var output = new Microsoft.ML.Legacy.Models.RankerEvaluator.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.RegressionEnsemble input, Microsoft.ML.Legacy.Models.RegressionEnsemble.Output output) - { - _jsonNodes.Add(Serialize("Models.RegressionEnsemble", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.RankerEvaluator input, Microsoft.ML.Legacy.Models.RankerEvaluator.Output output) + { + _jsonNodes.Add(Serialize("Models.RankerEvaluator", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Models.RegressionEvaluator.Output Add(Microsoft.ML.Legacy.Models.RegressionEvaluator input) - { - var output = new Microsoft.ML.Legacy.Models.RegressionEvaluator.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Models.RegressionEnsemble.Output Add(Microsoft.ML.Legacy.Models.RegressionEnsemble input) + { + var output = new Microsoft.ML.Legacy.Models.RegressionEnsemble.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.RegressionEvaluator input, Microsoft.ML.Legacy.Models.RegressionEvaluator.Output output) - { - _jsonNodes.Add(Serialize("Models.RegressionEvaluator", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.RegressionEnsemble input, Microsoft.ML.Legacy.Models.RegressionEnsemble.Output output) + { + _jsonNodes.Add(Serialize("Models.RegressionEnsemble", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Models.RegressionPipelineEnsemble.Output Add(Microsoft.ML.Legacy.Models.RegressionPipelineEnsemble input) - { - var output = new Microsoft.ML.Legacy.Models.RegressionPipelineEnsemble.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Models.RegressionEvaluator.Output Add(Microsoft.ML.Legacy.Models.RegressionEvaluator input) + { + var output = new Microsoft.ML.Legacy.Models.RegressionEvaluator.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.RegressionPipelineEnsemble input, Microsoft.ML.Legacy.Models.RegressionPipelineEnsemble.Output output) - { - _jsonNodes.Add(Serialize("Models.RegressionPipelineEnsemble", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.RegressionEvaluator input, Microsoft.ML.Legacy.Models.RegressionEvaluator.Output output) + { + _jsonNodes.Add(Serialize("Models.RegressionEvaluator", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Models.Summarizer.Output Add(Microsoft.ML.Legacy.Models.Summarizer input) - { - var output = new Microsoft.ML.Legacy.Models.Summarizer.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Models.RegressionPipelineEnsemble.Output Add(Microsoft.ML.Legacy.Models.RegressionPipelineEnsemble input) + { + var output = new Microsoft.ML.Legacy.Models.RegressionPipelineEnsemble.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.Summarizer input, Microsoft.ML.Legacy.Models.Summarizer.Output output) - { - _jsonNodes.Add(Serialize("Models.Summarizer", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.RegressionPipelineEnsemble input, Microsoft.ML.Legacy.Models.RegressionPipelineEnsemble.Output output) + { + _jsonNodes.Add(Serialize("Models.RegressionPipelineEnsemble", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Models.TrainTestEvaluator.Output Add(Microsoft.ML.Legacy.Models.TrainTestEvaluator input) - { - var output = new Microsoft.ML.Legacy.Models.TrainTestEvaluator.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Models.Summarizer.Output Add(Microsoft.ML.Legacy.Models.Summarizer input) + { + var output = new Microsoft.ML.Legacy.Models.Summarizer.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Models.TrainTestEvaluator input, Microsoft.ML.Legacy.Models.TrainTestEvaluator.Output output) - { - _jsonNodes.Add(Serialize("Models.TrainTestEvaluator", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.Summarizer input, Microsoft.ML.Legacy.Models.Summarizer.Output output) + { + _jsonNodes.Add(Serialize("Models.Summarizer", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.TimeSeriesProcessing.ExponentialAverage.Output Add(Microsoft.ML.Legacy.TimeSeriesProcessing.ExponentialAverage input) - { - var output = new Microsoft.ML.Legacy.TimeSeriesProcessing.ExponentialAverage.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Models.TrainTestEvaluator.Output Add(Microsoft.ML.Legacy.Models.TrainTestEvaluator input) + { + var output = new Microsoft.ML.Legacy.Models.TrainTestEvaluator.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.TimeSeriesProcessing.ExponentialAverage input, Microsoft.ML.Legacy.TimeSeriesProcessing.ExponentialAverage.Output output) - { - _jsonNodes.Add(Serialize("TimeSeriesProcessing.ExponentialAverage", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Models.TrainTestEvaluator input, Microsoft.ML.Legacy.Models.TrainTestEvaluator.Output output) + { + _jsonNodes.Add(Serialize("Models.TrainTestEvaluator", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.TimeSeriesProcessing.IidChangePointDetector.Output Add(Microsoft.ML.Legacy.TimeSeriesProcessing.IidChangePointDetector input) - { - var output = new Microsoft.ML.Legacy.TimeSeriesProcessing.IidChangePointDetector.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.ExponentialAverage.Output Add(Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.ExponentialAverage input) + { + var output = new Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.ExponentialAverage.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.TimeSeriesProcessing.IidChangePointDetector input, Microsoft.ML.Legacy.TimeSeriesProcessing.IidChangePointDetector.Output output) - { - _jsonNodes.Add(Serialize("TimeSeriesProcessing.IidChangePointDetector", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.ExponentialAverage input, Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.ExponentialAverage.Output output) + { + _jsonNodes.Add(Serialize("TimeSeriesProcessingEntryPoints.ExponentialAverage", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.TimeSeriesProcessing.IidSpikeDetector.Output Add(Microsoft.ML.Legacy.TimeSeriesProcessing.IidSpikeDetector input) - { - var output = new Microsoft.ML.Legacy.TimeSeriesProcessing.IidSpikeDetector.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.IidChangePointDetector.Output Add(Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.IidChangePointDetector input) + { + var output = new Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.IidChangePointDetector.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.TimeSeriesProcessing.IidSpikeDetector input, Microsoft.ML.Legacy.TimeSeriesProcessing.IidSpikeDetector.Output output) - { - _jsonNodes.Add(Serialize("TimeSeriesProcessing.IidSpikeDetector", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.IidChangePointDetector input, Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.IidChangePointDetector.Output output) + { + _jsonNodes.Add(Serialize("TimeSeriesProcessingEntryPoints.IidChangePointDetector", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.TimeSeriesProcessing.PercentileThresholdTransform.Output Add(Microsoft.ML.Legacy.TimeSeriesProcessing.PercentileThresholdTransform input) - { - var output = new Microsoft.ML.Legacy.TimeSeriesProcessing.PercentileThresholdTransform.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.IidSpikeDetector.Output Add(Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.IidSpikeDetector input) + { + var output = new Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.IidSpikeDetector.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.TimeSeriesProcessing.PercentileThresholdTransform input, Microsoft.ML.Legacy.TimeSeriesProcessing.PercentileThresholdTransform.Output output) - { - _jsonNodes.Add(Serialize("TimeSeriesProcessing.PercentileThresholdTransform", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.IidSpikeDetector input, Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.IidSpikeDetector.Output output) + { + _jsonNodes.Add(Serialize("TimeSeriesProcessingEntryPoints.IidSpikeDetector", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.TimeSeriesProcessing.PValueTransform.Output Add(Microsoft.ML.Legacy.TimeSeriesProcessing.PValueTransform input) - { - var output = new Microsoft.ML.Legacy.TimeSeriesProcessing.PValueTransform.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.PercentileThresholdTransform.Output Add(Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.PercentileThresholdTransform input) + { + var output = new Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.PercentileThresholdTransform.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.TimeSeriesProcessing.PValueTransform input, Microsoft.ML.Legacy.TimeSeriesProcessing.PValueTransform.Output output) - { - _jsonNodes.Add(Serialize("TimeSeriesProcessing.PValueTransform", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.PercentileThresholdTransform input, Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.PercentileThresholdTransform.Output output) + { + _jsonNodes.Add(Serialize("TimeSeriesProcessingEntryPoints.PercentileThresholdTransform", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.TimeSeriesProcessing.SlidingWindowTransform.Output Add(Microsoft.ML.Legacy.TimeSeriesProcessing.SlidingWindowTransform input) - { - var output = new Microsoft.ML.Legacy.TimeSeriesProcessing.SlidingWindowTransform.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.PValueTransform.Output Add(Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.PValueTransform input) + { + var output = new Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.PValueTransform.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.TimeSeriesProcessing.SlidingWindowTransform input, Microsoft.ML.Legacy.TimeSeriesProcessing.SlidingWindowTransform.Output output) - { - _jsonNodes.Add(Serialize("TimeSeriesProcessing.SlidingWindowTransform", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.PValueTransform input, Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.PValueTransform.Output output) + { + _jsonNodes.Add(Serialize("TimeSeriesProcessingEntryPoints.PValueTransform", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.TimeSeriesProcessing.SsaChangePointDetector.Output Add(Microsoft.ML.Legacy.TimeSeriesProcessing.SsaChangePointDetector input) - { - var output = new Microsoft.ML.Legacy.TimeSeriesProcessing.SsaChangePointDetector.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.SlidingWindowTransform.Output Add(Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.SlidingWindowTransform input) + { + var output = new Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.SlidingWindowTransform.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.TimeSeriesProcessing.SsaChangePointDetector input, Microsoft.ML.Legacy.TimeSeriesProcessing.SsaChangePointDetector.Output output) - { - _jsonNodes.Add(Serialize("TimeSeriesProcessing.SsaChangePointDetector", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.SlidingWindowTransform input, Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.SlidingWindowTransform.Output output) + { + _jsonNodes.Add(Serialize("TimeSeriesProcessingEntryPoints.SlidingWindowTransform", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.TimeSeriesProcessing.SsaSpikeDetector.Output Add(Microsoft.ML.Legacy.TimeSeriesProcessing.SsaSpikeDetector input) - { - var output = new Microsoft.ML.Legacy.TimeSeriesProcessing.SsaSpikeDetector.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.SsaChangePointDetector.Output Add(Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.SsaChangePointDetector input) + { + var output = new Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.SsaChangePointDetector.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.TimeSeriesProcessing.SsaSpikeDetector input, Microsoft.ML.Legacy.TimeSeriesProcessing.SsaSpikeDetector.Output output) - { - _jsonNodes.Add(Serialize("TimeSeriesProcessing.SsaSpikeDetector", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.SsaChangePointDetector input, Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.SsaChangePointDetector.Output output) + { + _jsonNodes.Add(Serialize("TimeSeriesProcessingEntryPoints.SsaChangePointDetector", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.AveragedPerceptronBinaryClassifier.Output Add(Microsoft.ML.Legacy.Trainers.AveragedPerceptronBinaryClassifier input) - { - var output = new Microsoft.ML.Legacy.Trainers.AveragedPerceptronBinaryClassifier.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.SsaSpikeDetector.Output Add(Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.SsaSpikeDetector input) + { + var output = new Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.SsaSpikeDetector.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.AveragedPerceptronBinaryClassifier input, Microsoft.ML.Legacy.Trainers.AveragedPerceptronBinaryClassifier.Output output) - { - _jsonNodes.Add(Serialize("Trainers.AveragedPerceptronBinaryClassifier", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.SsaSpikeDetector input, Microsoft.ML.Legacy.TimeSeriesProcessingEntryPoints.SsaSpikeDetector.Output output) + { + _jsonNodes.Add(Serialize("TimeSeriesProcessingEntryPoints.SsaSpikeDetector", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.EnsembleBinaryClassifier.Output Add(Microsoft.ML.Legacy.Trainers.EnsembleBinaryClassifier input) - { - var output = new Microsoft.ML.Legacy.Trainers.EnsembleBinaryClassifier.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.AveragedPerceptronBinaryClassifier.Output Add(Microsoft.ML.Legacy.Trainers.AveragedPerceptronBinaryClassifier input) + { + var output = new Microsoft.ML.Legacy.Trainers.AveragedPerceptronBinaryClassifier.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.EnsembleBinaryClassifier input, Microsoft.ML.Legacy.Trainers.EnsembleBinaryClassifier.Output output) - { - _jsonNodes.Add(Serialize("Trainers.EnsembleBinaryClassifier", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.AveragedPerceptronBinaryClassifier input, Microsoft.ML.Legacy.Trainers.AveragedPerceptronBinaryClassifier.Output output) + { + _jsonNodes.Add(Serialize("Trainers.AveragedPerceptronBinaryClassifier", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.EnsembleClassification.Output Add(Microsoft.ML.Legacy.Trainers.EnsembleClassification input) - { - var output = new Microsoft.ML.Legacy.Trainers.EnsembleClassification.Output(); - Add(input, output); - return output; - } - - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.EnsembleClassification input, Microsoft.ML.Legacy.Trainers.EnsembleClassification.Output output) - { - _jsonNodes.Add(Serialize("Trainers.EnsembleClassification", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.EnsembleBinaryClassifier.Output Add(Microsoft.ML.Legacy.Trainers.EnsembleBinaryClassifier input) + { + var output = new Microsoft.ML.Legacy.Trainers.EnsembleBinaryClassifier.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.EnsembleRegression.Output Add(Microsoft.ML.Legacy.Trainers.EnsembleRegression input) - { - var output = new Microsoft.ML.Legacy.Trainers.EnsembleRegression.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.EnsembleBinaryClassifier input, Microsoft.ML.Legacy.Trainers.EnsembleBinaryClassifier.Output output) + { + _jsonNodes.Add(Serialize("Trainers.EnsembleBinaryClassifier", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.EnsembleRegression input, Microsoft.ML.Legacy.Trainers.EnsembleRegression.Output output) - { - _jsonNodes.Add(Serialize("Trainers.EnsembleRegression", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.EnsembleClassification.Output Add(Microsoft.ML.Legacy.Trainers.EnsembleClassification input) + { + var output = new Microsoft.ML.Legacy.Trainers.EnsembleClassification.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.FastForestBinaryClassifier.Output Add(Microsoft.ML.Legacy.Trainers.FastForestBinaryClassifier input) - { - var output = new Microsoft.ML.Legacy.Trainers.FastForestBinaryClassifier.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.EnsembleClassification input, Microsoft.ML.Legacy.Trainers.EnsembleClassification.Output output) + { + _jsonNodes.Add(Serialize("Trainers.EnsembleClassification", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.FastForestBinaryClassifier input, Microsoft.ML.Legacy.Trainers.FastForestBinaryClassifier.Output output) - { - _jsonNodes.Add(Serialize("Trainers.FastForestBinaryClassifier", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.EnsembleRegression.Output Add(Microsoft.ML.Legacy.Trainers.EnsembleRegression input) + { + var output = new Microsoft.ML.Legacy.Trainers.EnsembleRegression.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.FastForestRegressor.Output Add(Microsoft.ML.Legacy.Trainers.FastForestRegressor input) - { - var output = new Microsoft.ML.Legacy.Trainers.FastForestRegressor.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.EnsembleRegression input, Microsoft.ML.Legacy.Trainers.EnsembleRegression.Output output) + { + _jsonNodes.Add(Serialize("Trainers.EnsembleRegression", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.FastForestRegressor input, Microsoft.ML.Legacy.Trainers.FastForestRegressor.Output output) - { - _jsonNodes.Add(Serialize("Trainers.FastForestRegressor", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.FastForestBinaryClassifier.Output Add(Microsoft.ML.Legacy.Trainers.FastForestBinaryClassifier input) + { + var output = new Microsoft.ML.Legacy.Trainers.FastForestBinaryClassifier.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.FastTreeBinaryClassifier.Output Add(Microsoft.ML.Legacy.Trainers.FastTreeBinaryClassifier input) - { - var output = new Microsoft.ML.Legacy.Trainers.FastTreeBinaryClassifier.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.FastForestBinaryClassifier input, Microsoft.ML.Legacy.Trainers.FastForestBinaryClassifier.Output output) + { + _jsonNodes.Add(Serialize("Trainers.FastForestBinaryClassifier", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.FastTreeBinaryClassifier input, Microsoft.ML.Legacy.Trainers.FastTreeBinaryClassifier.Output output) - { - _jsonNodes.Add(Serialize("Trainers.FastTreeBinaryClassifier", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.FastForestRegressor.Output Add(Microsoft.ML.Legacy.Trainers.FastForestRegressor input) + { + var output = new Microsoft.ML.Legacy.Trainers.FastForestRegressor.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.FastTreeRanker.Output Add(Microsoft.ML.Legacy.Trainers.FastTreeRanker input) - { - var output = new Microsoft.ML.Legacy.Trainers.FastTreeRanker.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.FastForestRegressor input, Microsoft.ML.Legacy.Trainers.FastForestRegressor.Output output) + { + _jsonNodes.Add(Serialize("Trainers.FastForestRegressor", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.FastTreeRanker input, Microsoft.ML.Legacy.Trainers.FastTreeRanker.Output output) - { - _jsonNodes.Add(Serialize("Trainers.FastTreeRanker", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.FastTreeBinaryClassifier.Output Add(Microsoft.ML.Legacy.Trainers.FastTreeBinaryClassifier input) + { + var output = new Microsoft.ML.Legacy.Trainers.FastTreeBinaryClassifier.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.FastTreeRegressor.Output Add(Microsoft.ML.Legacy.Trainers.FastTreeRegressor input) - { - var output = new Microsoft.ML.Legacy.Trainers.FastTreeRegressor.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.FastTreeBinaryClassifier input, Microsoft.ML.Legacy.Trainers.FastTreeBinaryClassifier.Output output) + { + _jsonNodes.Add(Serialize("Trainers.FastTreeBinaryClassifier", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.FastTreeRegressor input, Microsoft.ML.Legacy.Trainers.FastTreeRegressor.Output output) - { - _jsonNodes.Add(Serialize("Trainers.FastTreeRegressor", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.FastTreeRanker.Output Add(Microsoft.ML.Legacy.Trainers.FastTreeRanker input) + { + var output = new Microsoft.ML.Legacy.Trainers.FastTreeRanker.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.FastTreeTweedieRegressor.Output Add(Microsoft.ML.Legacy.Trainers.FastTreeTweedieRegressor input) - { - var output = new Microsoft.ML.Legacy.Trainers.FastTreeTweedieRegressor.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.FastTreeRanker input, Microsoft.ML.Legacy.Trainers.FastTreeRanker.Output output) + { + _jsonNodes.Add(Serialize("Trainers.FastTreeRanker", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.FastTreeTweedieRegressor input, Microsoft.ML.Legacy.Trainers.FastTreeTweedieRegressor.Output output) - { - _jsonNodes.Add(Serialize("Trainers.FastTreeTweedieRegressor", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.FastTreeRegressor.Output Add(Microsoft.ML.Legacy.Trainers.FastTreeRegressor input) + { + var output = new Microsoft.ML.Legacy.Trainers.FastTreeRegressor.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.FieldAwareFactorizationMachineBinaryClassifier.Output Add(Microsoft.ML.Legacy.Trainers.FieldAwareFactorizationMachineBinaryClassifier input) - { - var output = new Microsoft.ML.Legacy.Trainers.FieldAwareFactorizationMachineBinaryClassifier.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.FastTreeRegressor input, Microsoft.ML.Legacy.Trainers.FastTreeRegressor.Output output) + { + _jsonNodes.Add(Serialize("Trainers.FastTreeRegressor", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.FieldAwareFactorizationMachineBinaryClassifier input, Microsoft.ML.Legacy.Trainers.FieldAwareFactorizationMachineBinaryClassifier.Output output) - { - _jsonNodes.Add(Serialize("Trainers.FieldAwareFactorizationMachineBinaryClassifier", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.FastTreeTweedieRegressor.Output Add(Microsoft.ML.Legacy.Trainers.FastTreeTweedieRegressor input) + { + var output = new Microsoft.ML.Legacy.Trainers.FastTreeTweedieRegressor.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.GeneralizedAdditiveModelBinaryClassifier.Output Add(Microsoft.ML.Legacy.Trainers.GeneralizedAdditiveModelBinaryClassifier input) - { - var output = new Microsoft.ML.Legacy.Trainers.GeneralizedAdditiveModelBinaryClassifier.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.FastTreeTweedieRegressor input, Microsoft.ML.Legacy.Trainers.FastTreeTweedieRegressor.Output output) + { + _jsonNodes.Add(Serialize("Trainers.FastTreeTweedieRegressor", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.GeneralizedAdditiveModelBinaryClassifier input, Microsoft.ML.Legacy.Trainers.GeneralizedAdditiveModelBinaryClassifier.Output output) - { - _jsonNodes.Add(Serialize("Trainers.GeneralizedAdditiveModelBinaryClassifier", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.FieldAwareFactorizationMachineBinaryClassifier.Output Add(Microsoft.ML.Legacy.Trainers.FieldAwareFactorizationMachineBinaryClassifier input) + { + var output = new Microsoft.ML.Legacy.Trainers.FieldAwareFactorizationMachineBinaryClassifier.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.GeneralizedAdditiveModelRegressor.Output Add(Microsoft.ML.Legacy.Trainers.GeneralizedAdditiveModelRegressor input) - { - var output = new Microsoft.ML.Legacy.Trainers.GeneralizedAdditiveModelRegressor.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.FieldAwareFactorizationMachineBinaryClassifier input, Microsoft.ML.Legacy.Trainers.FieldAwareFactorizationMachineBinaryClassifier.Output output) + { + _jsonNodes.Add(Serialize("Trainers.FieldAwareFactorizationMachineBinaryClassifier", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.GeneralizedAdditiveModelRegressor input, Microsoft.ML.Legacy.Trainers.GeneralizedAdditiveModelRegressor.Output output) - { - _jsonNodes.Add(Serialize("Trainers.GeneralizedAdditiveModelRegressor", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.GeneralizedAdditiveModelBinaryClassifier.Output Add(Microsoft.ML.Legacy.Trainers.GeneralizedAdditiveModelBinaryClassifier input) + { + var output = new Microsoft.ML.Legacy.Trainers.GeneralizedAdditiveModelBinaryClassifier.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.KMeansPlusPlusClusterer.Output Add(Microsoft.ML.Legacy.Trainers.KMeansPlusPlusClusterer input) - { - var output = new Microsoft.ML.Legacy.Trainers.KMeansPlusPlusClusterer.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.GeneralizedAdditiveModelBinaryClassifier input, Microsoft.ML.Legacy.Trainers.GeneralizedAdditiveModelBinaryClassifier.Output output) + { + _jsonNodes.Add(Serialize("Trainers.GeneralizedAdditiveModelBinaryClassifier", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.KMeansPlusPlusClusterer input, Microsoft.ML.Legacy.Trainers.KMeansPlusPlusClusterer.Output output) - { - _jsonNodes.Add(Serialize("Trainers.KMeansPlusPlusClusterer", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.GeneralizedAdditiveModelRegressor.Output Add(Microsoft.ML.Legacy.Trainers.GeneralizedAdditiveModelRegressor input) + { + var output = new Microsoft.ML.Legacy.Trainers.GeneralizedAdditiveModelRegressor.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.LightGbmBinaryClassifier.Output Add(Microsoft.ML.Legacy.Trainers.LightGbmBinaryClassifier input) - { - var output = new Microsoft.ML.Legacy.Trainers.LightGbmBinaryClassifier.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.GeneralizedAdditiveModelRegressor input, Microsoft.ML.Legacy.Trainers.GeneralizedAdditiveModelRegressor.Output output) + { + _jsonNodes.Add(Serialize("Trainers.GeneralizedAdditiveModelRegressor", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.LightGbmBinaryClassifier input, Microsoft.ML.Legacy.Trainers.LightGbmBinaryClassifier.Output output) - { - _jsonNodes.Add(Serialize("Trainers.LightGbmBinaryClassifier", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.KMeansPlusPlusClusterer.Output Add(Microsoft.ML.Legacy.Trainers.KMeansPlusPlusClusterer input) + { + var output = new Microsoft.ML.Legacy.Trainers.KMeansPlusPlusClusterer.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.LightGbmClassifier.Output Add(Microsoft.ML.Legacy.Trainers.LightGbmClassifier input) - { - var output = new Microsoft.ML.Legacy.Trainers.LightGbmClassifier.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.KMeansPlusPlusClusterer input, Microsoft.ML.Legacy.Trainers.KMeansPlusPlusClusterer.Output output) + { + _jsonNodes.Add(Serialize("Trainers.KMeansPlusPlusClusterer", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.LightGbmClassifier input, Microsoft.ML.Legacy.Trainers.LightGbmClassifier.Output output) - { - _jsonNodes.Add(Serialize("Trainers.LightGbmClassifier", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.LightGbmBinaryClassifier.Output Add(Microsoft.ML.Legacy.Trainers.LightGbmBinaryClassifier input) + { + var output = new Microsoft.ML.Legacy.Trainers.LightGbmBinaryClassifier.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.LightGbmRanker.Output Add(Microsoft.ML.Legacy.Trainers.LightGbmRanker input) - { - var output = new Microsoft.ML.Legacy.Trainers.LightGbmRanker.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.LightGbmBinaryClassifier input, Microsoft.ML.Legacy.Trainers.LightGbmBinaryClassifier.Output output) + { + _jsonNodes.Add(Serialize("Trainers.LightGbmBinaryClassifier", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.LightGbmRanker input, Microsoft.ML.Legacy.Trainers.LightGbmRanker.Output output) - { - _jsonNodes.Add(Serialize("Trainers.LightGbmRanker", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.LightGbmClassifier.Output Add(Microsoft.ML.Legacy.Trainers.LightGbmClassifier input) + { + var output = new Microsoft.ML.Legacy.Trainers.LightGbmClassifier.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.LightGbmRegressor.Output Add(Microsoft.ML.Legacy.Trainers.LightGbmRegressor input) - { - var output = new Microsoft.ML.Legacy.Trainers.LightGbmRegressor.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.LightGbmClassifier input, Microsoft.ML.Legacy.Trainers.LightGbmClassifier.Output output) + { + _jsonNodes.Add(Serialize("Trainers.LightGbmClassifier", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.LightGbmRegressor input, Microsoft.ML.Legacy.Trainers.LightGbmRegressor.Output output) - { - _jsonNodes.Add(Serialize("Trainers.LightGbmRegressor", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.LightGbmRanker.Output Add(Microsoft.ML.Legacy.Trainers.LightGbmRanker input) + { + var output = new Microsoft.ML.Legacy.Trainers.LightGbmRanker.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.LinearSvmBinaryClassifier.Output Add(Microsoft.ML.Legacy.Trainers.LinearSvmBinaryClassifier input) - { - var output = new Microsoft.ML.Legacy.Trainers.LinearSvmBinaryClassifier.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.LightGbmRanker input, Microsoft.ML.Legacy.Trainers.LightGbmRanker.Output output) + { + _jsonNodes.Add(Serialize("Trainers.LightGbmRanker", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.LinearSvmBinaryClassifier input, Microsoft.ML.Legacy.Trainers.LinearSvmBinaryClassifier.Output output) - { - _jsonNodes.Add(Serialize("Trainers.LinearSvmBinaryClassifier", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.LightGbmRegressor.Output Add(Microsoft.ML.Legacy.Trainers.LightGbmRegressor input) + { + var output = new Microsoft.ML.Legacy.Trainers.LightGbmRegressor.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.LogisticRegressionBinaryClassifier.Output Add(Microsoft.ML.Legacy.Trainers.LogisticRegressionBinaryClassifier input) - { - var output = new Microsoft.ML.Legacy.Trainers.LogisticRegressionBinaryClassifier.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.LightGbmRegressor input, Microsoft.ML.Legacy.Trainers.LightGbmRegressor.Output output) + { + _jsonNodes.Add(Serialize("Trainers.LightGbmRegressor", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.LogisticRegressionBinaryClassifier input, Microsoft.ML.Legacy.Trainers.LogisticRegressionBinaryClassifier.Output output) - { - _jsonNodes.Add(Serialize("Trainers.LogisticRegressionBinaryClassifier", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.LinearSvmBinaryClassifier.Output Add(Microsoft.ML.Legacy.Trainers.LinearSvmBinaryClassifier input) + { + var output = new Microsoft.ML.Legacy.Trainers.LinearSvmBinaryClassifier.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.LogisticRegressionClassifier.Output Add(Microsoft.ML.Legacy.Trainers.LogisticRegressionClassifier input) - { - var output = new Microsoft.ML.Legacy.Trainers.LogisticRegressionClassifier.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.LinearSvmBinaryClassifier input, Microsoft.ML.Legacy.Trainers.LinearSvmBinaryClassifier.Output output) + { + _jsonNodes.Add(Serialize("Trainers.LinearSvmBinaryClassifier", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.LogisticRegressionClassifier input, Microsoft.ML.Legacy.Trainers.LogisticRegressionClassifier.Output output) - { - _jsonNodes.Add(Serialize("Trainers.LogisticRegressionClassifier", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.LogisticRegressionBinaryClassifier.Output Add(Microsoft.ML.Legacy.Trainers.LogisticRegressionBinaryClassifier input) + { + var output = new Microsoft.ML.Legacy.Trainers.LogisticRegressionBinaryClassifier.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.NaiveBayesClassifier.Output Add(Microsoft.ML.Legacy.Trainers.NaiveBayesClassifier input) - { - var output = new Microsoft.ML.Legacy.Trainers.NaiveBayesClassifier.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.LogisticRegressionBinaryClassifier input, Microsoft.ML.Legacy.Trainers.LogisticRegressionBinaryClassifier.Output output) + { + _jsonNodes.Add(Serialize("Trainers.LogisticRegressionBinaryClassifier", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.NaiveBayesClassifier input, Microsoft.ML.Legacy.Trainers.NaiveBayesClassifier.Output output) - { - _jsonNodes.Add(Serialize("Trainers.NaiveBayesClassifier", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.LogisticRegressionClassifier.Output Add(Microsoft.ML.Legacy.Trainers.LogisticRegressionClassifier input) + { + var output = new Microsoft.ML.Legacy.Trainers.LogisticRegressionClassifier.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.OnlineGradientDescentRegressor.Output Add(Microsoft.ML.Legacy.Trainers.OnlineGradientDescentRegressor input) - { - var output = new Microsoft.ML.Legacy.Trainers.OnlineGradientDescentRegressor.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.LogisticRegressionClassifier input, Microsoft.ML.Legacy.Trainers.LogisticRegressionClassifier.Output output) + { + _jsonNodes.Add(Serialize("Trainers.LogisticRegressionClassifier", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.OnlineGradientDescentRegressor input, Microsoft.ML.Legacy.Trainers.OnlineGradientDescentRegressor.Output output) - { - _jsonNodes.Add(Serialize("Trainers.OnlineGradientDescentRegressor", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.NaiveBayesClassifier.Output Add(Microsoft.ML.Legacy.Trainers.NaiveBayesClassifier input) + { + var output = new Microsoft.ML.Legacy.Trainers.NaiveBayesClassifier.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.OrdinaryLeastSquaresRegressor.Output Add(Microsoft.ML.Legacy.Trainers.OrdinaryLeastSquaresRegressor input) - { - var output = new Microsoft.ML.Legacy.Trainers.OrdinaryLeastSquaresRegressor.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.NaiveBayesClassifier input, Microsoft.ML.Legacy.Trainers.NaiveBayesClassifier.Output output) + { + _jsonNodes.Add(Serialize("Trainers.NaiveBayesClassifier", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.OrdinaryLeastSquaresRegressor input, Microsoft.ML.Legacy.Trainers.OrdinaryLeastSquaresRegressor.Output output) - { - _jsonNodes.Add(Serialize("Trainers.OrdinaryLeastSquaresRegressor", input, output)); - } - - [Obsolete] - public Microsoft.ML.Legacy.Trainers.PcaAnomalyDetector.Output Add(Microsoft.ML.Legacy.Trainers.PcaAnomalyDetector input) - { - var output = new Microsoft.ML.Legacy.Trainers.PcaAnomalyDetector.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.OnlineGradientDescentRegressor.Output Add(Microsoft.ML.Legacy.Trainers.OnlineGradientDescentRegressor input) + { + var output = new Microsoft.ML.Legacy.Trainers.OnlineGradientDescentRegressor.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.PcaAnomalyDetector input, Microsoft.ML.Legacy.Trainers.PcaAnomalyDetector.Output output) - { - _jsonNodes.Add(Serialize("Trainers.PcaAnomalyDetector", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.OnlineGradientDescentRegressor input, Microsoft.ML.Legacy.Trainers.OnlineGradientDescentRegressor.Output output) + { + _jsonNodes.Add(Serialize("Trainers.OnlineGradientDescentRegressor", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.PoissonRegressor.Output Add(Microsoft.ML.Legacy.Trainers.PoissonRegressor input) - { - var output = new Microsoft.ML.Legacy.Trainers.PoissonRegressor.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.OrdinaryLeastSquaresRegressor.Output Add(Microsoft.ML.Legacy.Trainers.OrdinaryLeastSquaresRegressor input) + { + var output = new Microsoft.ML.Legacy.Trainers.OrdinaryLeastSquaresRegressor.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.PoissonRegressor input, Microsoft.ML.Legacy.Trainers.PoissonRegressor.Output output) - { - _jsonNodes.Add(Serialize("Trainers.PoissonRegressor", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.OrdinaryLeastSquaresRegressor input, Microsoft.ML.Legacy.Trainers.OrdinaryLeastSquaresRegressor.Output output) + { + _jsonNodes.Add(Serialize("Trainers.OrdinaryLeastSquaresRegressor", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentBinaryClassifier.Output Add(Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentBinaryClassifier input) - { - var output = new Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentBinaryClassifier.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.PcaAnomalyDetector.Output Add(Microsoft.ML.Legacy.Trainers.PcaAnomalyDetector input) + { + var output = new Microsoft.ML.Legacy.Trainers.PcaAnomalyDetector.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentBinaryClassifier input, Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentBinaryClassifier.Output output) - { - _jsonNodes.Add(Serialize("Trainers.StochasticDualCoordinateAscentBinaryClassifier", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.PcaAnomalyDetector input, Microsoft.ML.Legacy.Trainers.PcaAnomalyDetector.Output output) + { + _jsonNodes.Add(Serialize("Trainers.PcaAnomalyDetector", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentClassifier.Output Add(Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentClassifier input) - { - var output = new Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentClassifier.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.PoissonRegressor.Output Add(Microsoft.ML.Legacy.Trainers.PoissonRegressor input) + { + var output = new Microsoft.ML.Legacy.Trainers.PoissonRegressor.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentClassifier input, Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentClassifier.Output output) - { - _jsonNodes.Add(Serialize("Trainers.StochasticDualCoordinateAscentClassifier", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.PoissonRegressor input, Microsoft.ML.Legacy.Trainers.PoissonRegressor.Output output) + { + _jsonNodes.Add(Serialize("Trainers.PoissonRegressor", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentRegressor.Output Add(Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentRegressor input) - { - var output = new Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentRegressor.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentBinaryClassifier.Output Add(Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentBinaryClassifier input) + { + var output = new Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentBinaryClassifier.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentRegressor input, Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentRegressor.Output output) - { - _jsonNodes.Add(Serialize("Trainers.StochasticDualCoordinateAscentRegressor", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentBinaryClassifier input, Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentBinaryClassifier.Output output) + { + _jsonNodes.Add(Serialize("Trainers.StochasticDualCoordinateAscentBinaryClassifier", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.StochasticGradientDescentBinaryClassifier.Output Add(Microsoft.ML.Legacy.Trainers.StochasticGradientDescentBinaryClassifier input) - { - var output = new Microsoft.ML.Legacy.Trainers.StochasticGradientDescentBinaryClassifier.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentClassifier.Output Add(Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentClassifier input) + { + var output = new Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentClassifier.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.StochasticGradientDescentBinaryClassifier input, Microsoft.ML.Legacy.Trainers.StochasticGradientDescentBinaryClassifier.Output output) - { - _jsonNodes.Add(Serialize("Trainers.StochasticGradientDescentBinaryClassifier", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentClassifier input, Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentClassifier.Output output) + { + _jsonNodes.Add(Serialize("Trainers.StochasticDualCoordinateAscentClassifier", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Trainers.SymSgdBinaryClassifier.Output Add(Microsoft.ML.Legacy.Trainers.SymSgdBinaryClassifier input) - { - var output = new Microsoft.ML.Legacy.Trainers.SymSgdBinaryClassifier.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentRegressor.Output Add(Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentRegressor input) + { + var output = new Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentRegressor.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Trainers.SymSgdBinaryClassifier input, Microsoft.ML.Legacy.Trainers.SymSgdBinaryClassifier.Output output) - { - _jsonNodes.Add(Serialize("Trainers.SymSgdBinaryClassifier", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentRegressor input, Microsoft.ML.Legacy.Trainers.StochasticDualCoordinateAscentRegressor.Output output) + { + _jsonNodes.Add(Serialize("Trainers.StochasticDualCoordinateAscentRegressor", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.ApproximateBootstrapSampler.Output Add(Microsoft.ML.Legacy.Transforms.ApproximateBootstrapSampler input) - { - var output = new Microsoft.ML.Legacy.Transforms.ApproximateBootstrapSampler.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.StochasticGradientDescentBinaryClassifier.Output Add(Microsoft.ML.Legacy.Trainers.StochasticGradientDescentBinaryClassifier input) + { + var output = new Microsoft.ML.Legacy.Trainers.StochasticGradientDescentBinaryClassifier.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.ApproximateBootstrapSampler input, Microsoft.ML.Legacy.Transforms.ApproximateBootstrapSampler.Output output) - { - _jsonNodes.Add(Serialize("Transforms.ApproximateBootstrapSampler", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.StochasticGradientDescentBinaryClassifier input, Microsoft.ML.Legacy.Trainers.StochasticGradientDescentBinaryClassifier.Output output) + { + _jsonNodes.Add(Serialize("Trainers.StochasticGradientDescentBinaryClassifier", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.BinaryPredictionScoreColumnsRenamer.Output Add(Microsoft.ML.Legacy.Transforms.BinaryPredictionScoreColumnsRenamer input) - { - var output = new Microsoft.ML.Legacy.Transforms.BinaryPredictionScoreColumnsRenamer.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Trainers.SymSgdBinaryClassifier.Output Add(Microsoft.ML.Legacy.Trainers.SymSgdBinaryClassifier input) + { + var output = new Microsoft.ML.Legacy.Trainers.SymSgdBinaryClassifier.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.BinaryPredictionScoreColumnsRenamer input, Microsoft.ML.Legacy.Transforms.BinaryPredictionScoreColumnsRenamer.Output output) - { - _jsonNodes.Add(Serialize("Transforms.BinaryPredictionScoreColumnsRenamer", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Trainers.SymSgdBinaryClassifier input, Microsoft.ML.Legacy.Trainers.SymSgdBinaryClassifier.Output output) + { + _jsonNodes.Add(Serialize("Trainers.SymSgdBinaryClassifier", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.BinNormalizer.Output Add(Microsoft.ML.Legacy.Transforms.BinNormalizer input) - { - var output = new Microsoft.ML.Legacy.Transforms.BinNormalizer.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.ApproximateBootstrapSampler.Output Add(Microsoft.ML.Legacy.Transforms.ApproximateBootstrapSampler input) + { + var output = new Microsoft.ML.Legacy.Transforms.ApproximateBootstrapSampler.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.BinNormalizer input, Microsoft.ML.Legacy.Transforms.BinNormalizer.Output output) - { - _jsonNodes.Add(Serialize("Transforms.BinNormalizer", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.ApproximateBootstrapSampler input, Microsoft.ML.Legacy.Transforms.ApproximateBootstrapSampler.Output output) + { + _jsonNodes.Add(Serialize("Transforms.ApproximateBootstrapSampler", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.CategoricalHashOneHotVectorizer.Output Add(Microsoft.ML.Legacy.Transforms.CategoricalHashOneHotVectorizer input) - { - var output = new Microsoft.ML.Legacy.Transforms.CategoricalHashOneHotVectorizer.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.BinaryPredictionScoreColumnsRenamer.Output Add(Microsoft.ML.Legacy.Transforms.BinaryPredictionScoreColumnsRenamer input) + { + var output = new Microsoft.ML.Legacy.Transforms.BinaryPredictionScoreColumnsRenamer.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.CategoricalHashOneHotVectorizer input, Microsoft.ML.Legacy.Transforms.CategoricalHashOneHotVectorizer.Output output) - { - _jsonNodes.Add(Serialize("Transforms.CategoricalHashOneHotVectorizer", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.BinaryPredictionScoreColumnsRenamer input, Microsoft.ML.Legacy.Transforms.BinaryPredictionScoreColumnsRenamer.Output output) + { + _jsonNodes.Add(Serialize("Transforms.BinaryPredictionScoreColumnsRenamer", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.CategoricalOneHotVectorizer.Output Add(Microsoft.ML.Legacy.Transforms.CategoricalOneHotVectorizer input) - { - var output = new Microsoft.ML.Legacy.Transforms.CategoricalOneHotVectorizer.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.BinNormalizer.Output Add(Microsoft.ML.Legacy.Transforms.BinNormalizer input) + { + var output = new Microsoft.ML.Legacy.Transforms.BinNormalizer.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.CategoricalOneHotVectorizer input, Microsoft.ML.Legacy.Transforms.CategoricalOneHotVectorizer.Output output) - { - _jsonNodes.Add(Serialize("Transforms.CategoricalOneHotVectorizer", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.BinNormalizer input, Microsoft.ML.Legacy.Transforms.BinNormalizer.Output output) + { + _jsonNodes.Add(Serialize("Transforms.BinNormalizer", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.CharacterTokenizer.Output Add(Microsoft.ML.Legacy.Transforms.CharacterTokenizer input) - { - var output = new Microsoft.ML.Legacy.Transforms.CharacterTokenizer.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.CategoricalHashOneHotVectorizer.Output Add(Microsoft.ML.Legacy.Transforms.CategoricalHashOneHotVectorizer input) + { + var output = new Microsoft.ML.Legacy.Transforms.CategoricalHashOneHotVectorizer.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.CharacterTokenizer input, Microsoft.ML.Legacy.Transforms.CharacterTokenizer.Output output) - { - _jsonNodes.Add(Serialize("Transforms.CharacterTokenizer", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.CategoricalHashOneHotVectorizer input, Microsoft.ML.Legacy.Transforms.CategoricalHashOneHotVectorizer.Output output) + { + _jsonNodes.Add(Serialize("Transforms.CategoricalHashOneHotVectorizer", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.ColumnConcatenator.Output Add(Microsoft.ML.Legacy.Transforms.ColumnConcatenator input) - { - var output = new Microsoft.ML.Legacy.Transforms.ColumnConcatenator.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.CategoricalOneHotVectorizer.Output Add(Microsoft.ML.Legacy.Transforms.CategoricalOneHotVectorizer input) + { + var output = new Microsoft.ML.Legacy.Transforms.CategoricalOneHotVectorizer.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.ColumnConcatenator input, Microsoft.ML.Legacy.Transforms.ColumnConcatenator.Output output) - { - _jsonNodes.Add(Serialize("Transforms.ColumnConcatenator", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.CategoricalOneHotVectorizer input, Microsoft.ML.Legacy.Transforms.CategoricalOneHotVectorizer.Output output) + { + _jsonNodes.Add(Serialize("Transforms.CategoricalOneHotVectorizer", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.ColumnCopier.Output Add(Microsoft.ML.Legacy.Transforms.ColumnCopier input) - { - var output = new Microsoft.ML.Legacy.Transforms.ColumnCopier.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.CharacterTokenizer.Output Add(Microsoft.ML.Legacy.Transforms.CharacterTokenizer input) + { + var output = new Microsoft.ML.Legacy.Transforms.CharacterTokenizer.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.ColumnCopier input, Microsoft.ML.Legacy.Transforms.ColumnCopier.Output output) - { - _jsonNodes.Add(Serialize("Transforms.ColumnCopier", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.CharacterTokenizer input, Microsoft.ML.Legacy.Transforms.CharacterTokenizer.Output output) + { + _jsonNodes.Add(Serialize("Transforms.CharacterTokenizer", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.ColumnSelector.Output Add(Microsoft.ML.Legacy.Transforms.ColumnSelector input) - { - var output = new Microsoft.ML.Legacy.Transforms.ColumnSelector.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.ColumnConcatenator.Output Add(Microsoft.ML.Legacy.Transforms.ColumnConcatenator input) + { + var output = new Microsoft.ML.Legacy.Transforms.ColumnConcatenator.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.ColumnSelector input, Microsoft.ML.Legacy.Transforms.ColumnSelector.Output output) - { - _jsonNodes.Add(Serialize("Transforms.ColumnSelector", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.ColumnConcatenator input, Microsoft.ML.Legacy.Transforms.ColumnConcatenator.Output output) + { + _jsonNodes.Add(Serialize("Transforms.ColumnConcatenator", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.ColumnTypeConverter.Output Add(Microsoft.ML.Legacy.Transforms.ColumnTypeConverter input) - { - var output = new Microsoft.ML.Legacy.Transforms.ColumnTypeConverter.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.ColumnCopier.Output Add(Microsoft.ML.Legacy.Transforms.ColumnCopier input) + { + var output = new Microsoft.ML.Legacy.Transforms.ColumnCopier.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.ColumnTypeConverter input, Microsoft.ML.Legacy.Transforms.ColumnTypeConverter.Output output) - { - _jsonNodes.Add(Serialize("Transforms.ColumnTypeConverter", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.ColumnCopier input, Microsoft.ML.Legacy.Transforms.ColumnCopier.Output output) + { + _jsonNodes.Add(Serialize("Transforms.ColumnCopier", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.CombinerByContiguousGroupId.Output Add(Microsoft.ML.Legacy.Transforms.CombinerByContiguousGroupId input) - { - var output = new Microsoft.ML.Legacy.Transforms.CombinerByContiguousGroupId.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.ColumnSelector.Output Add(Microsoft.ML.Legacy.Transforms.ColumnSelector input) + { + var output = new Microsoft.ML.Legacy.Transforms.ColumnSelector.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.CombinerByContiguousGroupId input, Microsoft.ML.Legacy.Transforms.CombinerByContiguousGroupId.Output output) - { - _jsonNodes.Add(Serialize("Transforms.CombinerByContiguousGroupId", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.ColumnSelector input, Microsoft.ML.Legacy.Transforms.ColumnSelector.Output output) + { + _jsonNodes.Add(Serialize("Transforms.ColumnSelector", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.ConditionalNormalizer.Output Add(Microsoft.ML.Legacy.Transforms.ConditionalNormalizer input) - { - var output = new Microsoft.ML.Legacy.Transforms.ConditionalNormalizer.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.ColumnTypeConverter.Output Add(Microsoft.ML.Legacy.Transforms.ColumnTypeConverter input) + { + var output = new Microsoft.ML.Legacy.Transforms.ColumnTypeConverter.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.ConditionalNormalizer input, Microsoft.ML.Legacy.Transforms.ConditionalNormalizer.Output output) - { - _jsonNodes.Add(Serialize("Transforms.ConditionalNormalizer", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.ColumnTypeConverter input, Microsoft.ML.Legacy.Transforms.ColumnTypeConverter.Output output) + { + _jsonNodes.Add(Serialize("Transforms.ColumnTypeConverter", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.DataCache.Output Add(Microsoft.ML.Legacy.Transforms.DataCache input) - { - var output = new Microsoft.ML.Legacy.Transforms.DataCache.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.CombinerByContiguousGroupId.Output Add(Microsoft.ML.Legacy.Transforms.CombinerByContiguousGroupId input) + { + var output = new Microsoft.ML.Legacy.Transforms.CombinerByContiguousGroupId.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.DataCache input, Microsoft.ML.Legacy.Transforms.DataCache.Output output) - { - _jsonNodes.Add(Serialize("Transforms.DataCache", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.CombinerByContiguousGroupId input, Microsoft.ML.Legacy.Transforms.CombinerByContiguousGroupId.Output output) + { + _jsonNodes.Add(Serialize("Transforms.CombinerByContiguousGroupId", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.DatasetScorer.Output Add(Microsoft.ML.Legacy.Transforms.DatasetScorer input) - { - var output = new Microsoft.ML.Legacy.Transforms.DatasetScorer.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.ConditionalNormalizer.Output Add(Microsoft.ML.Legacy.Transforms.ConditionalNormalizer input) + { + var output = new Microsoft.ML.Legacy.Transforms.ConditionalNormalizer.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.DatasetScorer input, Microsoft.ML.Legacy.Transforms.DatasetScorer.Output output) - { - _jsonNodes.Add(Serialize("Transforms.DatasetScorer", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.ConditionalNormalizer input, Microsoft.ML.Legacy.Transforms.ConditionalNormalizer.Output output) + { + _jsonNodes.Add(Serialize("Transforms.ConditionalNormalizer", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.DatasetTransformScorer.Output Add(Microsoft.ML.Legacy.Transforms.DatasetTransformScorer input) - { - var output = new Microsoft.ML.Legacy.Transforms.DatasetTransformScorer.Output(); - Add(input, output); - return output; - } - - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.DatasetTransformScorer input, Microsoft.ML.Legacy.Transforms.DatasetTransformScorer.Output output) - { - _jsonNodes.Add(Serialize("Transforms.DatasetTransformScorer", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.DataCache.Output Add(Microsoft.ML.Legacy.Transforms.DataCache input) + { + var output = new Microsoft.ML.Legacy.Transforms.DataCache.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.Dictionarizer.Output Add(Microsoft.ML.Legacy.Transforms.Dictionarizer input) - { - var output = new Microsoft.ML.Legacy.Transforms.Dictionarizer.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.DataCache input, Microsoft.ML.Legacy.Transforms.DataCache.Output output) + { + _jsonNodes.Add(Serialize("Transforms.DataCache", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.Dictionarizer input, Microsoft.ML.Legacy.Transforms.Dictionarizer.Output output) - { - _jsonNodes.Add(Serialize("Transforms.Dictionarizer", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.DatasetScorer.Output Add(Microsoft.ML.Legacy.Transforms.DatasetScorer input) + { + var output = new Microsoft.ML.Legacy.Transforms.DatasetScorer.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.FeatureCombiner.Output Add(Microsoft.ML.Legacy.Transforms.FeatureCombiner input) - { - var output = new Microsoft.ML.Legacy.Transforms.FeatureCombiner.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.DatasetScorer input, Microsoft.ML.Legacy.Transforms.DatasetScorer.Output output) + { + _jsonNodes.Add(Serialize("Transforms.DatasetScorer", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.FeatureCombiner input, Microsoft.ML.Legacy.Transforms.FeatureCombiner.Output output) - { - _jsonNodes.Add(Serialize("Transforms.FeatureCombiner", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.DatasetTransformScorer.Output Add(Microsoft.ML.Legacy.Transforms.DatasetTransformScorer input) + { + var output = new Microsoft.ML.Legacy.Transforms.DatasetTransformScorer.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.FeatureContributionCalculationTransformer.Output Add(Microsoft.ML.Legacy.Transforms.FeatureContributionCalculationTransformer input) - { - var output = new Microsoft.ML.Legacy.Transforms.FeatureContributionCalculationTransformer.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.DatasetTransformScorer input, Microsoft.ML.Legacy.Transforms.DatasetTransformScorer.Output output) + { + _jsonNodes.Add(Serialize("Transforms.DatasetTransformScorer", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.FeatureContributionCalculationTransformer input, Microsoft.ML.Legacy.Transforms.FeatureContributionCalculationTransformer.Output output) - { - _jsonNodes.Add(Serialize("Transforms.FeatureContributionCalculationTransformer", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.Dictionarizer.Output Add(Microsoft.ML.Legacy.Transforms.Dictionarizer input) + { + var output = new Microsoft.ML.Legacy.Transforms.Dictionarizer.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.FeatureSelectorByCount.Output Add(Microsoft.ML.Legacy.Transforms.FeatureSelectorByCount input) - { - var output = new Microsoft.ML.Legacy.Transforms.FeatureSelectorByCount.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.Dictionarizer input, Microsoft.ML.Legacy.Transforms.Dictionarizer.Output output) + { + _jsonNodes.Add(Serialize("Transforms.Dictionarizer", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.FeatureSelectorByCount input, Microsoft.ML.Legacy.Transforms.FeatureSelectorByCount.Output output) - { - _jsonNodes.Add(Serialize("Transforms.FeatureSelectorByCount", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.FeatureCombiner.Output Add(Microsoft.ML.Legacy.Transforms.FeatureCombiner input) + { + var output = new Microsoft.ML.Legacy.Transforms.FeatureCombiner.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.FeatureSelectorByMutualInformation.Output Add(Microsoft.ML.Legacy.Transforms.FeatureSelectorByMutualInformation input) - { - var output = new Microsoft.ML.Legacy.Transforms.FeatureSelectorByMutualInformation.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.FeatureCombiner input, Microsoft.ML.Legacy.Transforms.FeatureCombiner.Output output) + { + _jsonNodes.Add(Serialize("Transforms.FeatureCombiner", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.FeatureSelectorByMutualInformation input, Microsoft.ML.Legacy.Transforms.FeatureSelectorByMutualInformation.Output output) - { - _jsonNodes.Add(Serialize("Transforms.FeatureSelectorByMutualInformation", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.FeatureContributionCalculationTransformer.Output Add(Microsoft.ML.Legacy.Transforms.FeatureContributionCalculationTransformer input) + { + var output = new Microsoft.ML.Legacy.Transforms.FeatureContributionCalculationTransformer.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.GlobalContrastNormalizer.Output Add(Microsoft.ML.Legacy.Transforms.GlobalContrastNormalizer input) - { - var output = new Microsoft.ML.Legacy.Transforms.GlobalContrastNormalizer.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.FeatureContributionCalculationTransformer input, Microsoft.ML.Legacy.Transforms.FeatureContributionCalculationTransformer.Output output) + { + _jsonNodes.Add(Serialize("Transforms.FeatureContributionCalculationTransformer", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.GlobalContrastNormalizer input, Microsoft.ML.Legacy.Transforms.GlobalContrastNormalizer.Output output) - { - _jsonNodes.Add(Serialize("Transforms.GlobalContrastNormalizer", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.FeatureSelectorByCount.Output Add(Microsoft.ML.Legacy.Transforms.FeatureSelectorByCount input) + { + var output = new Microsoft.ML.Legacy.Transforms.FeatureSelectorByCount.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.HashConverter.Output Add(Microsoft.ML.Legacy.Transforms.HashConverter input) - { - var output = new Microsoft.ML.Legacy.Transforms.HashConverter.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.FeatureSelectorByCount input, Microsoft.ML.Legacy.Transforms.FeatureSelectorByCount.Output output) + { + _jsonNodes.Add(Serialize("Transforms.FeatureSelectorByCount", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.HashConverter input, Microsoft.ML.Legacy.Transforms.HashConverter.Output output) - { - _jsonNodes.Add(Serialize("Transforms.HashConverter", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.FeatureSelectorByMutualInformation.Output Add(Microsoft.ML.Legacy.Transforms.FeatureSelectorByMutualInformation input) + { + var output = new Microsoft.ML.Legacy.Transforms.FeatureSelectorByMutualInformation.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.ImageGrayscale.Output Add(Microsoft.ML.Legacy.Transforms.ImageGrayscale input) - { - var output = new Microsoft.ML.Legacy.Transforms.ImageGrayscale.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.FeatureSelectorByMutualInformation input, Microsoft.ML.Legacy.Transforms.FeatureSelectorByMutualInformation.Output output) + { + _jsonNodes.Add(Serialize("Transforms.FeatureSelectorByMutualInformation", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.ImageGrayscale input, Microsoft.ML.Legacy.Transforms.ImageGrayscale.Output output) - { - _jsonNodes.Add(Serialize("Transforms.ImageGrayscale", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.GlobalContrastNormalizer.Output Add(Microsoft.ML.Legacy.Transforms.GlobalContrastNormalizer input) + { + var output = new Microsoft.ML.Legacy.Transforms.GlobalContrastNormalizer.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.ImageLoader.Output Add(Microsoft.ML.Legacy.Transforms.ImageLoader input) - { - var output = new Microsoft.ML.Legacy.Transforms.ImageLoader.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.GlobalContrastNormalizer input, Microsoft.ML.Legacy.Transforms.GlobalContrastNormalizer.Output output) + { + _jsonNodes.Add(Serialize("Transforms.GlobalContrastNormalizer", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.ImageLoader input, Microsoft.ML.Legacy.Transforms.ImageLoader.Output output) - { - _jsonNodes.Add(Serialize("Transforms.ImageLoader", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.HashConverter.Output Add(Microsoft.ML.Legacy.Transforms.HashConverter input) + { + var output = new Microsoft.ML.Legacy.Transforms.HashConverter.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.ImagePixelExtractor.Output Add(Microsoft.ML.Legacy.Transforms.ImagePixelExtractor input) - { - var output = new Microsoft.ML.Legacy.Transforms.ImagePixelExtractor.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.HashConverter input, Microsoft.ML.Legacy.Transforms.HashConverter.Output output) + { + _jsonNodes.Add(Serialize("Transforms.HashConverter", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.ImagePixelExtractor input, Microsoft.ML.Legacy.Transforms.ImagePixelExtractor.Output output) - { - _jsonNodes.Add(Serialize("Transforms.ImagePixelExtractor", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.ImageGrayscale.Output Add(Microsoft.ML.Legacy.Transforms.ImageGrayscale input) + { + var output = new Microsoft.ML.Legacy.Transforms.ImageGrayscale.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.ImageResizer.Output Add(Microsoft.ML.Legacy.Transforms.ImageResizer input) - { - var output = new Microsoft.ML.Legacy.Transforms.ImageResizer.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.ImageGrayscale input, Microsoft.ML.Legacy.Transforms.ImageGrayscale.Output output) + { + _jsonNodes.Add(Serialize("Transforms.ImageGrayscale", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.ImageResizer input, Microsoft.ML.Legacy.Transforms.ImageResizer.Output output) - { - _jsonNodes.Add(Serialize("Transforms.ImageResizer", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.ImageLoader.Output Add(Microsoft.ML.Legacy.Transforms.ImageLoader input) + { + var output = new Microsoft.ML.Legacy.Transforms.ImageLoader.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.KeyToTextConverter.Output Add(Microsoft.ML.Legacy.Transforms.KeyToTextConverter input) - { - var output = new Microsoft.ML.Legacy.Transforms.KeyToTextConverter.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.ImageLoader input, Microsoft.ML.Legacy.Transforms.ImageLoader.Output output) + { + _jsonNodes.Add(Serialize("Transforms.ImageLoader", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.KeyToTextConverter input, Microsoft.ML.Legacy.Transforms.KeyToTextConverter.Output output) - { - _jsonNodes.Add(Serialize("Transforms.KeyToTextConverter", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.ImagePixelExtractor.Output Add(Microsoft.ML.Legacy.Transforms.ImagePixelExtractor input) + { + var output = new Microsoft.ML.Legacy.Transforms.ImagePixelExtractor.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.LabelColumnKeyBooleanConverter.Output Add(Microsoft.ML.Legacy.Transforms.LabelColumnKeyBooleanConverter input) - { - var output = new Microsoft.ML.Legacy.Transforms.LabelColumnKeyBooleanConverter.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.ImagePixelExtractor input, Microsoft.ML.Legacy.Transforms.ImagePixelExtractor.Output output) + { + _jsonNodes.Add(Serialize("Transforms.ImagePixelExtractor", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.LabelColumnKeyBooleanConverter input, Microsoft.ML.Legacy.Transforms.LabelColumnKeyBooleanConverter.Output output) - { - _jsonNodes.Add(Serialize("Transforms.LabelColumnKeyBooleanConverter", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.ImageResizer.Output Add(Microsoft.ML.Legacy.Transforms.ImageResizer input) + { + var output = new Microsoft.ML.Legacy.Transforms.ImageResizer.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.LabelIndicator.Output Add(Microsoft.ML.Legacy.Transforms.LabelIndicator input) - { - var output = new Microsoft.ML.Legacy.Transforms.LabelIndicator.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.ImageResizer input, Microsoft.ML.Legacy.Transforms.ImageResizer.Output output) + { + _jsonNodes.Add(Serialize("Transforms.ImageResizer", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.LabelIndicator input, Microsoft.ML.Legacy.Transforms.LabelIndicator.Output output) - { - _jsonNodes.Add(Serialize("Transforms.LabelIndicator", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.KeyToTextConverter.Output Add(Microsoft.ML.Legacy.Transforms.KeyToTextConverter input) + { + var output = new Microsoft.ML.Legacy.Transforms.KeyToTextConverter.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.LabelToFloatConverter.Output Add(Microsoft.ML.Legacy.Transforms.LabelToFloatConverter input) - { - var output = new Microsoft.ML.Legacy.Transforms.LabelToFloatConverter.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.KeyToTextConverter input, Microsoft.ML.Legacy.Transforms.KeyToTextConverter.Output output) + { + _jsonNodes.Add(Serialize("Transforms.KeyToTextConverter", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.LabelToFloatConverter input, Microsoft.ML.Legacy.Transforms.LabelToFloatConverter.Output output) - { - _jsonNodes.Add(Serialize("Transforms.LabelToFloatConverter", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.LabelColumnKeyBooleanConverter.Output Add(Microsoft.ML.Legacy.Transforms.LabelColumnKeyBooleanConverter input) + { + var output = new Microsoft.ML.Legacy.Transforms.LabelColumnKeyBooleanConverter.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.LightLda.Output Add(Microsoft.ML.Legacy.Transforms.LightLda input) - { - var output = new Microsoft.ML.Legacy.Transforms.LightLda.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.LabelColumnKeyBooleanConverter input, Microsoft.ML.Legacy.Transforms.LabelColumnKeyBooleanConverter.Output output) + { + _jsonNodes.Add(Serialize("Transforms.LabelColumnKeyBooleanConverter", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.LightLda input, Microsoft.ML.Legacy.Transforms.LightLda.Output output) - { - _jsonNodes.Add(Serialize("Transforms.LightLda", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.LabelIndicator.Output Add(Microsoft.ML.Legacy.Transforms.LabelIndicator input) + { + var output = new Microsoft.ML.Legacy.Transforms.LabelIndicator.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.LogMeanVarianceNormalizer.Output Add(Microsoft.ML.Legacy.Transforms.LogMeanVarianceNormalizer input) - { - var output = new Microsoft.ML.Legacy.Transforms.LogMeanVarianceNormalizer.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.LabelIndicator input, Microsoft.ML.Legacy.Transforms.LabelIndicator.Output output) + { + _jsonNodes.Add(Serialize("Transforms.LabelIndicator", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.LogMeanVarianceNormalizer input, Microsoft.ML.Legacy.Transforms.LogMeanVarianceNormalizer.Output output) - { - _jsonNodes.Add(Serialize("Transforms.LogMeanVarianceNormalizer", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.LabelToFloatConverter.Output Add(Microsoft.ML.Legacy.Transforms.LabelToFloatConverter input) + { + var output = new Microsoft.ML.Legacy.Transforms.LabelToFloatConverter.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.LpNormalizer.Output Add(Microsoft.ML.Legacy.Transforms.LpNormalizer input) - { - var output = new Microsoft.ML.Legacy.Transforms.LpNormalizer.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.LabelToFloatConverter input, Microsoft.ML.Legacy.Transforms.LabelToFloatConverter.Output output) + { + _jsonNodes.Add(Serialize("Transforms.LabelToFloatConverter", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.LpNormalizer input, Microsoft.ML.Legacy.Transforms.LpNormalizer.Output output) - { - _jsonNodes.Add(Serialize("Transforms.LpNormalizer", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.LightLda.Output Add(Microsoft.ML.Legacy.Transforms.LightLda input) + { + var output = new Microsoft.ML.Legacy.Transforms.LightLda.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.ManyHeterogeneousModelCombiner.Output Add(Microsoft.ML.Legacy.Transforms.ManyHeterogeneousModelCombiner input) - { - var output = new Microsoft.ML.Legacy.Transforms.ManyHeterogeneousModelCombiner.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.LightLda input, Microsoft.ML.Legacy.Transforms.LightLda.Output output) + { + _jsonNodes.Add(Serialize("Transforms.LightLda", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.ManyHeterogeneousModelCombiner input, Microsoft.ML.Legacy.Transforms.ManyHeterogeneousModelCombiner.Output output) - { - _jsonNodes.Add(Serialize("Transforms.ManyHeterogeneousModelCombiner", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.LogMeanVarianceNormalizer.Output Add(Microsoft.ML.Legacy.Transforms.LogMeanVarianceNormalizer input) + { + var output = new Microsoft.ML.Legacy.Transforms.LogMeanVarianceNormalizer.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.MeanVarianceNormalizer.Output Add(Microsoft.ML.Legacy.Transforms.MeanVarianceNormalizer input) - { - var output = new Microsoft.ML.Legacy.Transforms.MeanVarianceNormalizer.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.LogMeanVarianceNormalizer input, Microsoft.ML.Legacy.Transforms.LogMeanVarianceNormalizer.Output output) + { + _jsonNodes.Add(Serialize("Transforms.LogMeanVarianceNormalizer", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.MeanVarianceNormalizer input, Microsoft.ML.Legacy.Transforms.MeanVarianceNormalizer.Output output) - { - _jsonNodes.Add(Serialize("Transforms.MeanVarianceNormalizer", input, output)); - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.LpNormalizer.Output Add(Microsoft.ML.Legacy.Transforms.LpNormalizer input) + { + var output = new Microsoft.ML.Legacy.Transforms.LpNormalizer.Output(); + Add(input, output); + return output; + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.MinMaxNormalizer.Output Add(Microsoft.ML.Legacy.Transforms.MinMaxNormalizer input) - { - var output = new Microsoft.ML.Legacy.Transforms.MinMaxNormalizer.Output(); - Add(input, output); - return output; - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.LpNormalizer input, Microsoft.ML.Legacy.Transforms.LpNormalizer.Output output) + { + _jsonNodes.Add(Serialize("Transforms.LpNormalizer", input, output)); + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.MinMaxNormalizer input, Microsoft.ML.Legacy.Transforms.MinMaxNormalizer.Output output) - { - _jsonNodes.Add(Serialize("Transforms.MinMaxNormalizer", input, output)); - } - - [Obsolete] - public Microsoft.ML.Legacy.Transforms.MissingValueHandler.Output Add(Microsoft.ML.Legacy.Transforms.MissingValueHandler input) - { - var output = new Microsoft.ML.Legacy.Transforms.MissingValueHandler.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.ManyHeterogeneousModelCombiner.Output Add(Microsoft.ML.Legacy.Transforms.ManyHeterogeneousModelCombiner input) + { + var output = new Microsoft.ML.Legacy.Transforms.ManyHeterogeneousModelCombiner.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.MissingValueHandler input, Microsoft.ML.Legacy.Transforms.MissingValueHandler.Output output) - { - _jsonNodes.Add(Serialize("Transforms.MissingValueHandler", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.ManyHeterogeneousModelCombiner input, Microsoft.ML.Legacy.Transforms.ManyHeterogeneousModelCombiner.Output output) + { + _jsonNodes.Add(Serialize("Transforms.ManyHeterogeneousModelCombiner", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.MissingValueIndicator.Output Add(Microsoft.ML.Legacy.Transforms.MissingValueIndicator input) - { - var output = new Microsoft.ML.Legacy.Transforms.MissingValueIndicator.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.MeanVarianceNormalizer.Output Add(Microsoft.ML.Legacy.Transforms.MeanVarianceNormalizer input) + { + var output = new Microsoft.ML.Legacy.Transforms.MeanVarianceNormalizer.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.MissingValueIndicator input, Microsoft.ML.Legacy.Transforms.MissingValueIndicator.Output output) - { - _jsonNodes.Add(Serialize("Transforms.MissingValueIndicator", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.MeanVarianceNormalizer input, Microsoft.ML.Legacy.Transforms.MeanVarianceNormalizer.Output output) + { + _jsonNodes.Add(Serialize("Transforms.MeanVarianceNormalizer", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.MissingValuesDropper.Output Add(Microsoft.ML.Legacy.Transforms.MissingValuesDropper input) - { - var output = new Microsoft.ML.Legacy.Transforms.MissingValuesDropper.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.MinMaxNormalizer.Output Add(Microsoft.ML.Legacy.Transforms.MinMaxNormalizer input) + { + var output = new Microsoft.ML.Legacy.Transforms.MinMaxNormalizer.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.MissingValuesDropper input, Microsoft.ML.Legacy.Transforms.MissingValuesDropper.Output output) - { - _jsonNodes.Add(Serialize("Transforms.MissingValuesDropper", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.MinMaxNormalizer input, Microsoft.ML.Legacy.Transforms.MinMaxNormalizer.Output output) + { + _jsonNodes.Add(Serialize("Transforms.MinMaxNormalizer", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.MissingValuesRowDropper.Output Add(Microsoft.ML.Legacy.Transforms.MissingValuesRowDropper input) - { - var output = new Microsoft.ML.Legacy.Transforms.MissingValuesRowDropper.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.MissingValueHandler.Output Add(Microsoft.ML.Legacy.Transforms.MissingValueHandler input) + { + var output = new Microsoft.ML.Legacy.Transforms.MissingValueHandler.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.MissingValuesRowDropper input, Microsoft.ML.Legacy.Transforms.MissingValuesRowDropper.Output output) - { - _jsonNodes.Add(Serialize("Transforms.MissingValuesRowDropper", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.MissingValueHandler input, Microsoft.ML.Legacy.Transforms.MissingValueHandler.Output output) + { + _jsonNodes.Add(Serialize("Transforms.MissingValueHandler", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.MissingValueSubstitutor.Output Add(Microsoft.ML.Legacy.Transforms.MissingValueSubstitutor input) - { - var output = new Microsoft.ML.Legacy.Transforms.MissingValueSubstitutor.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.MissingValueIndicator.Output Add(Microsoft.ML.Legacy.Transforms.MissingValueIndicator input) + { + var output = new Microsoft.ML.Legacy.Transforms.MissingValueIndicator.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.MissingValueSubstitutor input, Microsoft.ML.Legacy.Transforms.MissingValueSubstitutor.Output output) - { - _jsonNodes.Add(Serialize("Transforms.MissingValueSubstitutor", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.MissingValueIndicator input, Microsoft.ML.Legacy.Transforms.MissingValueIndicator.Output output) + { + _jsonNodes.Add(Serialize("Transforms.MissingValueIndicator", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.ModelCombiner.Output Add(Microsoft.ML.Legacy.Transforms.ModelCombiner input) - { - var output = new Microsoft.ML.Legacy.Transforms.ModelCombiner.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.MissingValuesDropper.Output Add(Microsoft.ML.Legacy.Transforms.MissingValuesDropper input) + { + var output = new Microsoft.ML.Legacy.Transforms.MissingValuesDropper.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.ModelCombiner input, Microsoft.ML.Legacy.Transforms.ModelCombiner.Output output) - { - _jsonNodes.Add(Serialize("Transforms.ModelCombiner", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.MissingValuesDropper input, Microsoft.ML.Legacy.Transforms.MissingValuesDropper.Output output) + { + _jsonNodes.Add(Serialize("Transforms.MissingValuesDropper", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.NGramTranslator.Output Add(Microsoft.ML.Legacy.Transforms.NGramTranslator input) - { - var output = new Microsoft.ML.Legacy.Transforms.NGramTranslator.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.MissingValuesRowDropper.Output Add(Microsoft.ML.Legacy.Transforms.MissingValuesRowDropper input) + { + var output = new Microsoft.ML.Legacy.Transforms.MissingValuesRowDropper.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.NGramTranslator input, Microsoft.ML.Legacy.Transforms.NGramTranslator.Output output) - { - _jsonNodes.Add(Serialize("Transforms.NGramTranslator", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.MissingValuesRowDropper input, Microsoft.ML.Legacy.Transforms.MissingValuesRowDropper.Output output) + { + _jsonNodes.Add(Serialize("Transforms.MissingValuesRowDropper", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.NoOperation.Output Add(Microsoft.ML.Legacy.Transforms.NoOperation input) - { - var output = new Microsoft.ML.Legacy.Transforms.NoOperation.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.MissingValueSubstitutor.Output Add(Microsoft.ML.Legacy.Transforms.MissingValueSubstitutor input) + { + var output = new Microsoft.ML.Legacy.Transforms.MissingValueSubstitutor.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.NoOperation input, Microsoft.ML.Legacy.Transforms.NoOperation.Output output) - { - _jsonNodes.Add(Serialize("Transforms.NoOperation", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.MissingValueSubstitutor input, Microsoft.ML.Legacy.Transforms.MissingValueSubstitutor.Output output) + { + _jsonNodes.Add(Serialize("Transforms.MissingValueSubstitutor", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.OptionalColumnCreator.Output Add(Microsoft.ML.Legacy.Transforms.OptionalColumnCreator input) - { - var output = new Microsoft.ML.Legacy.Transforms.OptionalColumnCreator.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.ModelCombiner.Output Add(Microsoft.ML.Legacy.Transforms.ModelCombiner input) + { + var output = new Microsoft.ML.Legacy.Transforms.ModelCombiner.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.OptionalColumnCreator input, Microsoft.ML.Legacy.Transforms.OptionalColumnCreator.Output output) - { - _jsonNodes.Add(Serialize("Transforms.OptionalColumnCreator", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.ModelCombiner input, Microsoft.ML.Legacy.Transforms.ModelCombiner.Output output) + { + _jsonNodes.Add(Serialize("Transforms.ModelCombiner", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.PcaCalculator.Output Add(Microsoft.ML.Legacy.Transforms.PcaCalculator input) - { - var output = new Microsoft.ML.Legacy.Transforms.PcaCalculator.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.NGramTranslator.Output Add(Microsoft.ML.Legacy.Transforms.NGramTranslator input) + { + var output = new Microsoft.ML.Legacy.Transforms.NGramTranslator.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.PcaCalculator input, Microsoft.ML.Legacy.Transforms.PcaCalculator.Output output) - { - _jsonNodes.Add(Serialize("Transforms.PcaCalculator", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.NGramTranslator input, Microsoft.ML.Legacy.Transforms.NGramTranslator.Output output) + { + _jsonNodes.Add(Serialize("Transforms.NGramTranslator", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.PredictedLabelColumnOriginalValueConverter.Output Add(Microsoft.ML.Legacy.Transforms.PredictedLabelColumnOriginalValueConverter input) - { - var output = new Microsoft.ML.Legacy.Transforms.PredictedLabelColumnOriginalValueConverter.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.NoOperation.Output Add(Microsoft.ML.Legacy.Transforms.NoOperation input) + { + var output = new Microsoft.ML.Legacy.Transforms.NoOperation.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.PredictedLabelColumnOriginalValueConverter input, Microsoft.ML.Legacy.Transforms.PredictedLabelColumnOriginalValueConverter.Output output) - { - _jsonNodes.Add(Serialize("Transforms.PredictedLabelColumnOriginalValueConverter", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.NoOperation input, Microsoft.ML.Legacy.Transforms.NoOperation.Output output) + { + _jsonNodes.Add(Serialize("Transforms.NoOperation", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.RandomNumberGenerator.Output Add(Microsoft.ML.Legacy.Transforms.RandomNumberGenerator input) - { - var output = new Microsoft.ML.Legacy.Transforms.RandomNumberGenerator.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.OptionalColumnCreator.Output Add(Microsoft.ML.Legacy.Transforms.OptionalColumnCreator input) + { + var output = new Microsoft.ML.Legacy.Transforms.OptionalColumnCreator.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.RandomNumberGenerator input, Microsoft.ML.Legacy.Transforms.RandomNumberGenerator.Output output) - { - _jsonNodes.Add(Serialize("Transforms.RandomNumberGenerator", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.OptionalColumnCreator input, Microsoft.ML.Legacy.Transforms.OptionalColumnCreator.Output output) + { + _jsonNodes.Add(Serialize("Transforms.OptionalColumnCreator", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.RowRangeFilter.Output Add(Microsoft.ML.Legacy.Transforms.RowRangeFilter input) - { - var output = new Microsoft.ML.Legacy.Transforms.RowRangeFilter.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.PcaCalculator.Output Add(Microsoft.ML.Legacy.Transforms.PcaCalculator input) + { + var output = new Microsoft.ML.Legacy.Transforms.PcaCalculator.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.RowRangeFilter input, Microsoft.ML.Legacy.Transforms.RowRangeFilter.Output output) - { - _jsonNodes.Add(Serialize("Transforms.RowRangeFilter", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.PcaCalculator input, Microsoft.ML.Legacy.Transforms.PcaCalculator.Output output) + { + _jsonNodes.Add(Serialize("Transforms.PcaCalculator", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.RowSkipAndTakeFilter.Output Add(Microsoft.ML.Legacy.Transforms.RowSkipAndTakeFilter input) - { - var output = new Microsoft.ML.Legacy.Transforms.RowSkipAndTakeFilter.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.PredictedLabelColumnOriginalValueConverter.Output Add(Microsoft.ML.Legacy.Transforms.PredictedLabelColumnOriginalValueConverter input) + { + var output = new Microsoft.ML.Legacy.Transforms.PredictedLabelColumnOriginalValueConverter.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.RowSkipAndTakeFilter input, Microsoft.ML.Legacy.Transforms.RowSkipAndTakeFilter.Output output) - { - _jsonNodes.Add(Serialize("Transforms.RowSkipAndTakeFilter", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.PredictedLabelColumnOriginalValueConverter input, Microsoft.ML.Legacy.Transforms.PredictedLabelColumnOriginalValueConverter.Output output) + { + _jsonNodes.Add(Serialize("Transforms.PredictedLabelColumnOriginalValueConverter", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.RowSkipFilter.Output Add(Microsoft.ML.Legacy.Transforms.RowSkipFilter input) - { - var output = new Microsoft.ML.Legacy.Transforms.RowSkipFilter.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.RandomNumberGenerator.Output Add(Microsoft.ML.Legacy.Transforms.RandomNumberGenerator input) + { + var output = new Microsoft.ML.Legacy.Transforms.RandomNumberGenerator.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.RowSkipFilter input, Microsoft.ML.Legacy.Transforms.RowSkipFilter.Output output) - { - _jsonNodes.Add(Serialize("Transforms.RowSkipFilter", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.RandomNumberGenerator input, Microsoft.ML.Legacy.Transforms.RandomNumberGenerator.Output output) + { + _jsonNodes.Add(Serialize("Transforms.RandomNumberGenerator", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.RowTakeFilter.Output Add(Microsoft.ML.Legacy.Transforms.RowTakeFilter input) - { - var output = new Microsoft.ML.Legacy.Transforms.RowTakeFilter.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.RowRangeFilter.Output Add(Microsoft.ML.Legacy.Transforms.RowRangeFilter input) + { + var output = new Microsoft.ML.Legacy.Transforms.RowRangeFilter.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.RowTakeFilter input, Microsoft.ML.Legacy.Transforms.RowTakeFilter.Output output) - { - _jsonNodes.Add(Serialize("Transforms.RowTakeFilter", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.RowRangeFilter input, Microsoft.ML.Legacy.Transforms.RowRangeFilter.Output output) + { + _jsonNodes.Add(Serialize("Transforms.RowRangeFilter", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.ScoreColumnSelector.Output Add(Microsoft.ML.Legacy.Transforms.ScoreColumnSelector input) - { - var output = new Microsoft.ML.Legacy.Transforms.ScoreColumnSelector.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.RowSkipAndTakeFilter.Output Add(Microsoft.ML.Legacy.Transforms.RowSkipAndTakeFilter input) + { + var output = new Microsoft.ML.Legacy.Transforms.RowSkipAndTakeFilter.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.ScoreColumnSelector input, Microsoft.ML.Legacy.Transforms.ScoreColumnSelector.Output output) - { - _jsonNodes.Add(Serialize("Transforms.ScoreColumnSelector", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.RowSkipAndTakeFilter input, Microsoft.ML.Legacy.Transforms.RowSkipAndTakeFilter.Output output) + { + _jsonNodes.Add(Serialize("Transforms.RowSkipAndTakeFilter", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.Scorer.Output Add(Microsoft.ML.Legacy.Transforms.Scorer input) - { - var output = new Microsoft.ML.Legacy.Transforms.Scorer.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.RowSkipFilter.Output Add(Microsoft.ML.Legacy.Transforms.RowSkipFilter input) + { + var output = new Microsoft.ML.Legacy.Transforms.RowSkipFilter.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.Scorer input, Microsoft.ML.Legacy.Transforms.Scorer.Output output) - { - _jsonNodes.Add(Serialize("Transforms.Scorer", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.RowSkipFilter input, Microsoft.ML.Legacy.Transforms.RowSkipFilter.Output output) + { + _jsonNodes.Add(Serialize("Transforms.RowSkipFilter", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.Segregator.Output Add(Microsoft.ML.Legacy.Transforms.Segregator input) - { - var output = new Microsoft.ML.Legacy.Transforms.Segregator.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.RowTakeFilter.Output Add(Microsoft.ML.Legacy.Transforms.RowTakeFilter input) + { + var output = new Microsoft.ML.Legacy.Transforms.RowTakeFilter.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.Segregator input, Microsoft.ML.Legacy.Transforms.Segregator.Output output) - { - _jsonNodes.Add(Serialize("Transforms.Segregator", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.RowTakeFilter input, Microsoft.ML.Legacy.Transforms.RowTakeFilter.Output output) + { + _jsonNodes.Add(Serialize("Transforms.RowTakeFilter", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.SentimentAnalyzer.Output Add(Microsoft.ML.Legacy.Transforms.SentimentAnalyzer input) - { - var output = new Microsoft.ML.Legacy.Transforms.SentimentAnalyzer.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.ScoreColumnSelector.Output Add(Microsoft.ML.Legacy.Transforms.ScoreColumnSelector input) + { + var output = new Microsoft.ML.Legacy.Transforms.ScoreColumnSelector.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.SentimentAnalyzer input, Microsoft.ML.Legacy.Transforms.SentimentAnalyzer.Output output) - { - _jsonNodes.Add(Serialize("Transforms.SentimentAnalyzer", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.ScoreColumnSelector input, Microsoft.ML.Legacy.Transforms.ScoreColumnSelector.Output output) + { + _jsonNodes.Add(Serialize("Transforms.ScoreColumnSelector", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.TensorFlowScorer.Output Add(Microsoft.ML.Legacy.Transforms.TensorFlowScorer input) - { - var output = new Microsoft.ML.Legacy.Transforms.TensorFlowScorer.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.Scorer.Output Add(Microsoft.ML.Legacy.Transforms.Scorer input) + { + var output = new Microsoft.ML.Legacy.Transforms.Scorer.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.TensorFlowScorer input, Microsoft.ML.Legacy.Transforms.TensorFlowScorer.Output output) - { - _jsonNodes.Add(Serialize("Transforms.TensorFlowScorer", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.Scorer input, Microsoft.ML.Legacy.Transforms.Scorer.Output output) + { + _jsonNodes.Add(Serialize("Transforms.Scorer", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.TextFeaturizer.Output Add(Microsoft.ML.Legacy.Transforms.TextFeaturizer input) - { - var output = new Microsoft.ML.Legacy.Transforms.TextFeaturizer.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.Segregator.Output Add(Microsoft.ML.Legacy.Transforms.Segregator input) + { + var output = new Microsoft.ML.Legacy.Transforms.Segregator.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.TextFeaturizer input, Microsoft.ML.Legacy.Transforms.TextFeaturizer.Output output) - { - _jsonNodes.Add(Serialize("Transforms.TextFeaturizer", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.Segregator input, Microsoft.ML.Legacy.Transforms.Segregator.Output output) + { + _jsonNodes.Add(Serialize("Transforms.Segregator", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.TextToKeyConverter.Output Add(Microsoft.ML.Legacy.Transforms.TextToKeyConverter input) - { - var output = new Microsoft.ML.Legacy.Transforms.TextToKeyConverter.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.SentimentAnalyzer.Output Add(Microsoft.ML.Legacy.Transforms.SentimentAnalyzer input) + { + var output = new Microsoft.ML.Legacy.Transforms.SentimentAnalyzer.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.TextToKeyConverter input, Microsoft.ML.Legacy.Transforms.TextToKeyConverter.Output output) - { - _jsonNodes.Add(Serialize("Transforms.TextToKeyConverter", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.SentimentAnalyzer input, Microsoft.ML.Legacy.Transforms.SentimentAnalyzer.Output output) + { + _jsonNodes.Add(Serialize("Transforms.SentimentAnalyzer", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.TrainTestDatasetSplitter.Output Add(Microsoft.ML.Legacy.Transforms.TrainTestDatasetSplitter input) - { - var output = new Microsoft.ML.Legacy.Transforms.TrainTestDatasetSplitter.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.TensorFlowScorer.Output Add(Microsoft.ML.Legacy.Transforms.TensorFlowScorer input) + { + var output = new Microsoft.ML.Legacy.Transforms.TensorFlowScorer.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.TrainTestDatasetSplitter input, Microsoft.ML.Legacy.Transforms.TrainTestDatasetSplitter.Output output) - { - _jsonNodes.Add(Serialize("Transforms.TrainTestDatasetSplitter", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.TensorFlowScorer input, Microsoft.ML.Legacy.Transforms.TensorFlowScorer.Output output) + { + _jsonNodes.Add(Serialize("Transforms.TensorFlowScorer", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.TreeLeafFeaturizer.Output Add(Microsoft.ML.Legacy.Transforms.TreeLeafFeaturizer input) - { - var output = new Microsoft.ML.Legacy.Transforms.TreeLeafFeaturizer.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.TextFeaturizer.Output Add(Microsoft.ML.Legacy.Transforms.TextFeaturizer input) + { + var output = new Microsoft.ML.Legacy.Transforms.TextFeaturizer.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.TreeLeafFeaturizer input, Microsoft.ML.Legacy.Transforms.TreeLeafFeaturizer.Output output) - { - _jsonNodes.Add(Serialize("Transforms.TreeLeafFeaturizer", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.TextFeaturizer input, Microsoft.ML.Legacy.Transforms.TextFeaturizer.Output output) + { + _jsonNodes.Add(Serialize("Transforms.TextFeaturizer", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.TwoHeterogeneousModelCombiner.Output Add(Microsoft.ML.Legacy.Transforms.TwoHeterogeneousModelCombiner input) - { - var output = new Microsoft.ML.Legacy.Transforms.TwoHeterogeneousModelCombiner.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.TextToKeyConverter.Output Add(Microsoft.ML.Legacy.Transforms.TextToKeyConverter input) + { + var output = new Microsoft.ML.Legacy.Transforms.TextToKeyConverter.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.TwoHeterogeneousModelCombiner input, Microsoft.ML.Legacy.Transforms.TwoHeterogeneousModelCombiner.Output output) - { - _jsonNodes.Add(Serialize("Transforms.TwoHeterogeneousModelCombiner", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.TextToKeyConverter input, Microsoft.ML.Legacy.Transforms.TextToKeyConverter.Output output) + { + _jsonNodes.Add(Serialize("Transforms.TextToKeyConverter", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.VectorToImage.Output Add(Microsoft.ML.Legacy.Transforms.VectorToImage input) - { - var output = new Microsoft.ML.Legacy.Transforms.VectorToImage.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.TrainTestDatasetSplitter.Output Add(Microsoft.ML.Legacy.Transforms.TrainTestDatasetSplitter input) + { + var output = new Microsoft.ML.Legacy.Transforms.TrainTestDatasetSplitter.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.VectorToImage input, Microsoft.ML.Legacy.Transforms.VectorToImage.Output output) - { - _jsonNodes.Add(Serialize("Transforms.VectorToImage", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.TrainTestDatasetSplitter input, Microsoft.ML.Legacy.Transforms.TrainTestDatasetSplitter.Output output) + { + _jsonNodes.Add(Serialize("Transforms.TrainTestDatasetSplitter", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.WordEmbeddings.Output Add(Microsoft.ML.Legacy.Transforms.WordEmbeddings input) - { - var output = new Microsoft.ML.Legacy.Transforms.WordEmbeddings.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.TreeLeafFeaturizer.Output Add(Microsoft.ML.Legacy.Transforms.TreeLeafFeaturizer input) + { + var output = new Microsoft.ML.Legacy.Transforms.TreeLeafFeaturizer.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.WordEmbeddings input, Microsoft.ML.Legacy.Transforms.WordEmbeddings.Output output) - { - _jsonNodes.Add(Serialize("Transforms.WordEmbeddings", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.TreeLeafFeaturizer input, Microsoft.ML.Legacy.Transforms.TreeLeafFeaturizer.Output output) + { + _jsonNodes.Add(Serialize("Transforms.TreeLeafFeaturizer", input, output)); + } - [Obsolete] - public Microsoft.ML.Legacy.Transforms.WordTokenizer.Output Add(Microsoft.ML.Legacy.Transforms.WordTokenizer input) - { - var output = new Microsoft.ML.Legacy.Transforms.WordTokenizer.Output(); - Add(input, output); - return output; - } + [Obsolete] + public Microsoft.ML.Legacy.Transforms.TwoHeterogeneousModelCombiner.Output Add(Microsoft.ML.Legacy.Transforms.TwoHeterogeneousModelCombiner input) + { + var output = new Microsoft.ML.Legacy.Transforms.TwoHeterogeneousModelCombiner.Output(); + Add(input, output); + return output; + } - [Obsolete] - public void Add(Microsoft.ML.Legacy.Transforms.WordTokenizer input, Microsoft.ML.Legacy.Transforms.WordTokenizer.Output output) - { - _jsonNodes.Add(Serialize("Transforms.WordTokenizer", input, output)); - } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.TwoHeterogeneousModelCombiner input, Microsoft.ML.Legacy.Transforms.TwoHeterogeneousModelCombiner.Output output) + { + _jsonNodes.Add(Serialize("Transforms.TwoHeterogeneousModelCombiner", input, output)); + } + + [Obsolete] + public Microsoft.ML.Legacy.Transforms.VectorToImage.Output Add(Microsoft.ML.Legacy.Transforms.VectorToImage input) + { + var output = new Microsoft.ML.Legacy.Transforms.VectorToImage.Output(); + Add(input, output); + return output; + } + + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.VectorToImage input, Microsoft.ML.Legacy.Transforms.VectorToImage.Output output) + { + _jsonNodes.Add(Serialize("Transforms.VectorToImage", input, output)); + } + + [Obsolete] + public Microsoft.ML.Legacy.Transforms.WordEmbeddings.Output Add(Microsoft.ML.Legacy.Transforms.WordEmbeddings input) + { + var output = new Microsoft.ML.Legacy.Transforms.WordEmbeddings.Output(); + Add(input, output); + return output; + } + + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.WordEmbeddings input, Microsoft.ML.Legacy.Transforms.WordEmbeddings.Output output) + { + _jsonNodes.Add(Serialize("Transforms.WordEmbeddings", input, output)); + } + + [Obsolete] + public Microsoft.ML.Legacy.Transforms.WordTokenizer.Output Add(Microsoft.ML.Legacy.Transforms.WordTokenizer input) + { + var output = new Microsoft.ML.Legacy.Transforms.WordTokenizer.Output(); + Add(input, output); + return output; + } + [Obsolete] + public void Add(Microsoft.ML.Legacy.Transforms.WordTokenizer input, Microsoft.ML.Legacy.Transforms.WordTokenizer.Output output) + { + _jsonNodes.Add(Serialize("Transforms.WordTokenizer", input, output)); } + } namespace Legacy.Data { @@ -1957,7 +1954,7 @@ public sealed partial class CustomTextLoader /// Location of the input file /// [Obsolete] - public Var InputFile { get; set; } = new Var(); + public Var InputFile { get; set; } = new Var(); /// /// Custom schema to use for parsing @@ -1972,7 +1969,7 @@ public sealed class Output /// /// The resulting data view /// - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); } } @@ -1993,7 +1990,7 @@ public sealed partial class DataViewReference /// Pointer to IDataView in memory /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] @@ -2002,7 +1999,7 @@ public sealed class Output /// /// The resulting data view /// - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); } } @@ -2023,7 +2020,7 @@ public sealed partial class IDataViewArrayConverter /// The data sets /// [Obsolete] - public ArrayVar Data { get; set; } = new ArrayVar(); + public ArrayVar Data { get; set; } = new ArrayVar(); [Obsolete] @@ -2032,7 +2029,7 @@ public sealed class Output /// /// The data set array /// - public ArrayVar OutputData { get; set; } = new ArrayVar(); + public ArrayVar OutputData { get; set; } = new ArrayVar(); } } @@ -2053,7 +2050,7 @@ public sealed partial class PredictorModelArrayConverter /// The models /// [Obsolete] - public ArrayVar Model { get; set; } = new ArrayVar(); + public ArrayVar Model { get; set; } = new ArrayVar(); [Obsolete] @@ -2062,7 +2059,7 @@ public sealed class Output /// /// The model array /// - public ArrayVar OutputModel { get; set; } = new ArrayVar(); + public ArrayVar OutputModel { get; set; } = new ArrayVar(); } } @@ -2308,7 +2305,7 @@ public TextLoaderPipelineStep (Output output) /// Location of the input file /// [Obsolete] - public Var InputFile { get; set; } = new Var(); + public Var InputFile { get; set; } = new Var(); /// /// Arguments @@ -2323,7 +2320,7 @@ public sealed class Output /// /// The resulting data view /// - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); } } @@ -2336,7 +2333,7 @@ namespace Legacy.Models /// Evaluates an anomaly detection scored dataset. /// [Obsolete] - public sealed partial class AnomalyDetectionEvaluator : Microsoft.ML.Runtime.EntryPoints.CommonInputs.IEvaluatorInput + public sealed partial class AnomalyDetectionEvaluator : Microsoft.ML.EntryPoints.CommonInputs.IEvaluatorInput { @@ -2398,7 +2395,7 @@ public sealed partial class AnomalyDetectionEvaluator : Microsoft.ML.Runtime.Ent /// The data to be used for evaluation. /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); /// /// Name column name. @@ -2408,22 +2405,22 @@ public sealed partial class AnomalyDetectionEvaluator : Microsoft.ML.Runtime.Ent [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IEvaluatorOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IEvaluatorOutput { /// /// Warning dataset /// - public Var Warnings { get; set; } = new Var(); + public Var Warnings { get; set; } = new Var(); /// /// Overall metrics dataset /// - public Var OverallMetrics { get; set; } = new Var(); + public Var OverallMetrics { get; set; } = new Var(); /// /// Per instance metrics dataset /// - public Var PerInstanceMetrics { get; set; } = new Var(); + public Var PerInstanceMetrics { get; set; } = new Var(); } } @@ -2457,16 +2454,16 @@ public sealed partial class AnomalyPipelineEnsemble /// The models to combine into an ensemble /// [Obsolete] - public ArrayVar Models { get; set; } = new ArrayVar(); + public ArrayVar Models { get; set; } = new ArrayVar(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IAnomalyDetectionOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IAnomalyDetectionOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } } @@ -2479,7 +2476,7 @@ namespace Legacy.Models /// Evaluates a binary classification scored dataset. /// [Obsolete] - public sealed partial class BinaryClassificationEvaluator : Microsoft.ML.Runtime.EntryPoints.CommonInputs.IEvaluatorInput + public sealed partial class BinaryClassificationEvaluator : Microsoft.ML.EntryPoints.CommonInputs.IEvaluatorInput { @@ -2547,7 +2544,7 @@ public sealed partial class BinaryClassificationEvaluator : Microsoft.ML.Runtime /// The data to be used for evaluation. /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); /// /// Name column name. @@ -2557,27 +2554,27 @@ public sealed partial class BinaryClassificationEvaluator : Microsoft.ML.Runtime [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IClassificationEvaluatorOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IEvaluatorOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IClassificationEvaluatorOutput, Microsoft.ML.EntryPoints.CommonOutputs.IEvaluatorOutput { /// /// Confusion matrix dataset /// - public Var ConfusionMatrix { get; set; } = new Var(); + public Var ConfusionMatrix { get; set; } = new Var(); /// /// Warning dataset /// - public Var Warnings { get; set; } = new Var(); + public Var Warnings { get; set; } = new Var(); /// /// Overall metrics dataset /// - public Var OverallMetrics { get; set; } = new Var(); + public Var OverallMetrics { get; set; } = new Var(); /// /// Per instance metrics dataset /// - public Var PerInstanceMetrics { get; set; } = new Var(); + public Var PerInstanceMetrics { get; set; } = new Var(); } } @@ -2612,7 +2609,7 @@ public sealed partial class BinaryEnsemble /// The models to combine into an ensemble /// [Obsolete] - public ArrayVar Models { get; set; } = new ArrayVar(); + public ArrayVar Models { get; set; } = new ArrayVar(); /// /// Whether to validate that all the pipelines are identical @@ -2622,12 +2619,12 @@ public sealed partial class BinaryEnsemble [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } } @@ -2654,16 +2651,16 @@ public sealed partial class BinaryPipelineEnsemble /// The models to combine into an ensemble /// [Obsolete] - public ArrayVar Models { get; set; } = new ArrayVar(); + public ArrayVar Models { get; set; } = new ArrayVar(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } } @@ -2676,7 +2673,7 @@ namespace Legacy.Models /// Evaluates a multi class classification scored dataset. /// [Obsolete] - public sealed partial class ClassificationEvaluator : Microsoft.ML.Runtime.EntryPoints.CommonInputs.IEvaluatorInput + public sealed partial class ClassificationEvaluator : Microsoft.ML.EntryPoints.CommonInputs.IEvaluatorInput { @@ -2732,7 +2729,7 @@ public sealed partial class ClassificationEvaluator : Microsoft.ML.Runtime.Entry /// The data to be used for evaluation. /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); /// /// Name column name. @@ -2742,27 +2739,27 @@ public sealed partial class ClassificationEvaluator : Microsoft.ML.Runtime.Entry [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IClassificationEvaluatorOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IEvaluatorOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IClassificationEvaluatorOutput, Microsoft.ML.EntryPoints.CommonOutputs.IEvaluatorOutput { /// /// Confusion matrix dataset /// - public Var ConfusionMatrix { get; set; } = new Var(); + public Var ConfusionMatrix { get; set; } = new Var(); /// /// Warning dataset /// - public Var Warnings { get; set; } = new Var(); + public Var Warnings { get; set; } = new Var(); /// /// Overall metrics dataset /// - public Var OverallMetrics { get; set; } = new Var(); + public Var OverallMetrics { get; set; } = new Var(); /// /// Per instance metrics dataset /// - public Var PerInstanceMetrics { get; set; } = new Var(); + public Var PerInstanceMetrics { get; set; } = new Var(); } } @@ -2775,7 +2772,7 @@ namespace Legacy.Models /// Evaluates a clustering scored dataset. /// [Obsolete] - public sealed partial class ClusterEvaluator : Microsoft.ML.Runtime.EntryPoints.CommonInputs.IEvaluatorInput + public sealed partial class ClusterEvaluator : Microsoft.ML.EntryPoints.CommonInputs.IEvaluatorInput { @@ -2825,7 +2822,7 @@ public sealed partial class ClusterEvaluator : Microsoft.ML.Runtime.EntryPoints. /// The data to be used for evaluation. /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); /// /// Name column name. @@ -2835,22 +2832,22 @@ public sealed partial class ClusterEvaluator : Microsoft.ML.Runtime.EntryPoints. [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IEvaluatorOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IEvaluatorOutput { /// /// Warning dataset /// - public Var Warnings { get; set; } = new Var(); + public Var Warnings { get; set; } = new Var(); /// /// Overall metrics dataset /// - public Var OverallMetrics { get; set; } = new Var(); + public Var OverallMetrics { get; set; } = new Var(); /// /// Per instance metrics dataset /// - public Var PerInstanceMetrics { get; set; } = new Var(); + public Var PerInstanceMetrics { get; set; } = new Var(); } } @@ -2883,25 +2880,25 @@ public sealed partial class CrossValidationResultsCombiner /// Overall metrics datasets /// [Obsolete] - public ArrayVar OverallMetrics { get; set; } = new ArrayVar(); + public ArrayVar OverallMetrics { get; set; } = new ArrayVar(); /// /// Per instance metrics datasets /// [Obsolete] - public ArrayVar PerInstanceMetrics { get; set; } = new ArrayVar(); + public ArrayVar PerInstanceMetrics { get; set; } = new ArrayVar(); /// /// Confusion matrix datasets /// [Obsolete] - public ArrayVar ConfusionMatrix { get; set; } = new ArrayVar(); + public ArrayVar ConfusionMatrix { get; set; } = new ArrayVar(); /// /// Warning datasets /// [Obsolete] - public ArrayVar Warnings { get; set; } = new ArrayVar(); + public ArrayVar Warnings { get; set; } = new ArrayVar(); /// /// The label column name @@ -2913,19 +2910,19 @@ public sealed partial class CrossValidationResultsCombiner /// Column to use for example weight /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } /// /// Column to use for grouping /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional GroupColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional GroupColumn { get; set; } /// /// Name column name /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional NameColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional NameColumn { get; set; } /// /// Specifies the trainer kind, which determines the evaluator to be used. @@ -2940,22 +2937,22 @@ public sealed class Output /// /// Warning dataset /// - public Var Warnings { get; set; } = new Var(); + public Var Warnings { get; set; } = new Var(); /// /// Overall metrics dataset /// - public Var OverallMetrics { get; set; } = new Var(); + public Var OverallMetrics { get; set; } = new Var(); /// /// Per instance metrics dataset /// - public Var PerInstanceMetrics { get; set; } = new Var(); + public Var PerInstanceMetrics { get; set; } = new Var(); /// /// Confusion matrix dataset /// - public Var ConfusionMatrix { get; set; } = new Var(); + public Var ConfusionMatrix { get; set; } = new Var(); } } @@ -2971,7 +2968,7 @@ public sealed partial class CrossValidationMacroSubGraphInput /// The data to be used for training /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); } @@ -2982,7 +2979,7 @@ public sealed partial class CrossValidationMacroSubGraphOutput /// The predictor model /// [Obsolete] - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } @@ -2998,13 +2995,13 @@ public sealed partial class CrossValidator /// The data set /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); /// /// The transform model from the pipeline before this command. It gets included in the Output.PredictorModel. /// [Obsolete] - public Var TransformModel { get; set; } = new Var(); + public Var TransformModel { get; set; } = new Var(); /// /// The training subgraph @@ -3052,19 +3049,19 @@ public sealed partial class CrossValidator /// Column to use for example weight /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } /// /// Column to use for grouping /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional GroupColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional GroupColumn { get; set; } /// /// Name column name /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional NameColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional NameColumn { get; set; } [Obsolete] @@ -3073,27 +3070,27 @@ public sealed class Output /// /// The final model including the trained predictor model and the model from the transforms, provided as the Input.TransformModel. /// - public ArrayVar PredictorModel { get; set; } = new ArrayVar(); + public ArrayVar PredictorModel { get; set; } = new ArrayVar(); /// /// Warning dataset /// - public Var Warnings { get; set; } = new Var(); + public Var Warnings { get; set; } = new Var(); /// /// Overall metrics dataset /// - public Var OverallMetrics { get; set; } = new Var(); + public Var OverallMetrics { get; set; } = new Var(); /// /// Per instance metrics dataset /// - public Var PerInstanceMetrics { get; set; } = new Var(); + public Var PerInstanceMetrics { get; set; } = new Var(); /// /// Confusion matrix dataset /// - public Var ConfusionMatrix { get; set; } = new Var(); + public Var ConfusionMatrix { get; set; } = new Var(); } } @@ -3114,7 +3111,7 @@ public sealed partial class CrossValidatorDatasetSplitter /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); /// /// Number of folds to split into @@ -3135,12 +3132,12 @@ public sealed class Output /// /// Training data (one dataset per fold) /// - public ArrayVar TrainData { get; set; } = new ArrayVar(); + public ArrayVar TrainData { get; set; } = new ArrayVar(); /// /// Testing data (one dataset per fold) /// - public ArrayVar TestData { get; set; } = new ArrayVar(); + public ArrayVar TestData { get; set; } = new ArrayVar(); } } @@ -3153,7 +3150,7 @@ namespace Legacy.Models /// Applies a TransformModel to a dataset. /// [Obsolete] - public sealed partial class DatasetTransformer : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class DatasetTransformer : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -3161,13 +3158,13 @@ public sealed partial class DatasetTransformer : Microsoft.ML.Runtime.EntryPoint /// Transform model /// [Obsolete] - public Var TransformModel { get; set; } = new Var(); + public Var TransformModel { get; set; } = new Var(); /// /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] @@ -3176,7 +3173,7 @@ public sealed class Output /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); } [Obsolete] @@ -3230,7 +3227,7 @@ public sealed partial class EnsembleSummary /// The predictor to summarize /// [Obsolete] - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); [Obsolete] @@ -3239,12 +3236,12 @@ public sealed class Output /// /// The summaries of the individual predictors /// - public ArrayVar Summaries { get; set; } = new ArrayVar(); + public ArrayVar Summaries { get; set; } = new ArrayVar(); /// /// The model statistics of the individual predictors /// - public ArrayVar Stats { get; set; } = new ArrayVar(); + public ArrayVar Stats { get; set; } = new ArrayVar(); } } @@ -3257,7 +3254,7 @@ namespace Legacy.Models /// Apply a Platt calibrator with a fixed slope and offset to an input model /// [Obsolete] - public sealed partial class FixedPlattCalibrator : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ICalibratorInput, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class FixedPlattCalibrator : Microsoft.ML.EntryPoints.CommonInputs.ICalibratorInput, Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -3277,7 +3274,7 @@ public sealed partial class FixedPlattCalibrator : Microsoft.ML.Runtime.EntryPoi /// The predictor to calibrate /// [Obsolete] - public Var UncalibratedPredictorModel { get; set; } = new Var(); + public Var UncalibratedPredictorModel { get; set; } = new Var(); /// /// The maximum number of examples to train the calibrator on @@ -3290,16 +3287,16 @@ public sealed partial class FixedPlattCalibrator : Microsoft.ML.Runtime.EntryPoi /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ICalibratorOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ICalibratorOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -3357,16 +3354,16 @@ public sealed partial class MultiClassPipelineEnsemble /// The models to combine into an ensemble /// [Obsolete] - public ArrayVar Models { get; set; } = new ArrayVar(); + public ArrayVar Models { get; set; } = new ArrayVar(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IMulticlassClassificationOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IMulticlassClassificationOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } } @@ -3379,7 +3376,7 @@ namespace Legacy.Models /// Evaluates a multi output regression scored dataset. /// [Obsolete] - public sealed partial class MultiOutputRegressionEvaluator : Microsoft.ML.Runtime.EntryPoints.CommonInputs.IEvaluatorInput + public sealed partial class MultiOutputRegressionEvaluator : Microsoft.ML.EntryPoints.CommonInputs.IEvaluatorInput { @@ -3424,7 +3421,7 @@ public sealed partial class MultiOutputRegressionEvaluator : Microsoft.ML.Runtim /// The data to be used for evaluation. /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); /// /// Name column name. @@ -3434,22 +3431,22 @@ public sealed partial class MultiOutputRegressionEvaluator : Microsoft.ML.Runtim [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IEvaluatorOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IEvaluatorOutput { /// /// Warning dataset /// - public Var Warnings { get; set; } = new Var(); + public Var Warnings { get; set; } = new Var(); /// /// Overall metrics dataset /// - public Var OverallMetrics { get; set; } = new Var(); + public Var OverallMetrics { get; set; } = new Var(); /// /// Per instance metrics dataset /// - public Var PerInstanceMetrics { get; set; } = new Var(); + public Var PerInstanceMetrics { get; set; } = new Var(); } } @@ -3462,7 +3459,7 @@ namespace Legacy.Models /// Apply a Naive calibrator to an input model /// [Obsolete] - public sealed partial class NaiveCalibrator : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ICalibratorInput, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class NaiveCalibrator : Microsoft.ML.EntryPoints.CommonInputs.ICalibratorInput, Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -3470,7 +3467,7 @@ public sealed partial class NaiveCalibrator : Microsoft.ML.Runtime.EntryPoints.C /// The predictor to calibrate /// [Obsolete] - public Var UncalibratedPredictorModel { get; set; } = new Var(); + public Var UncalibratedPredictorModel { get; set; } = new Var(); /// /// The maximum number of examples to train the calibrator on @@ -3483,16 +3480,16 @@ public sealed partial class NaiveCalibrator : Microsoft.ML.Runtime.EntryPoints.C /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ICalibratorOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ICalibratorOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -3557,13 +3554,13 @@ public sealed partial class OneVersusAllMacroSubGraphOutput /// The predictor model for the subgraph exemplar. /// [Obsolete] - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } /// [Obsolete] - public sealed partial class OneVersusAll : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class OneVersusAll : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -3589,7 +3586,7 @@ public sealed partial class OneVersusAll : Microsoft.ML.Runtime.EntryPoints.Comm /// Column to use for example weight /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } /// /// Column to use for labels @@ -3601,7 +3598,7 @@ public sealed partial class OneVersusAll : Microsoft.ML.Runtime.EntryPoints.Comm /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -3628,7 +3625,7 @@ public sealed class Output /// /// The trained multiclass model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -3723,7 +3720,7 @@ public sealed partial class OnnxConverter /// Model that needs to be converted to ONNX format. /// [Obsolete] - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); /// /// The targeted ONNX version. It can be either "Stable" or "Experimental". If "Experimental" is used, produced model can contain components that is not officially supported in ONNX standard. @@ -3752,7 +3749,7 @@ namespace Legacy.Models /// Combines a sequence of PredictorModels into a single model /// [Obsolete] - public sealed partial class OvaModelCombiner : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class OvaModelCombiner : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -3760,7 +3757,7 @@ public sealed partial class OvaModelCombiner : Microsoft.ML.Runtime.EntryPoints. /// Input models /// [Obsolete] - public ArrayVar ModelArray { get; set; } = new ArrayVar(); + public ArrayVar ModelArray { get; set; } = new ArrayVar(); /// /// Use probabilities from learners instead of raw values. @@ -3772,7 +3769,7 @@ public sealed partial class OvaModelCombiner : Microsoft.ML.Runtime.EntryPoints. /// Column to use for example weight /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } /// /// Column to use for labels @@ -3784,7 +3781,7 @@ public sealed partial class OvaModelCombiner : Microsoft.ML.Runtime.EntryPoints. /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -3811,7 +3808,7 @@ public sealed class Output /// /// Predictor model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -3855,7 +3852,7 @@ namespace Legacy.Models /// Apply a PAV calibrator to an input model /// [Obsolete] - public sealed partial class PAVCalibrator : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ICalibratorInput, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class PAVCalibrator : Microsoft.ML.EntryPoints.CommonInputs.ICalibratorInput, Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -3863,7 +3860,7 @@ public sealed partial class PAVCalibrator : Microsoft.ML.Runtime.EntryPoints.Com /// The predictor to calibrate /// [Obsolete] - public Var UncalibratedPredictorModel { get; set; } = new Var(); + public Var UncalibratedPredictorModel { get; set; } = new Var(); /// /// The maximum number of examples to train the calibrator on @@ -3876,16 +3873,16 @@ public sealed partial class PAVCalibrator : Microsoft.ML.Runtime.EntryPoints.Com /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ICalibratorOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ICalibratorOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -3929,7 +3926,7 @@ namespace Legacy.Models /// Apply a Platt calibrator to an input model /// [Obsolete] - public sealed partial class PlattCalibrator : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ICalibratorInput, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class PlattCalibrator : Microsoft.ML.EntryPoints.CommonInputs.ICalibratorInput, Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -3937,7 +3934,7 @@ public sealed partial class PlattCalibrator : Microsoft.ML.Runtime.EntryPoints.C /// The predictor to calibrate /// [Obsolete] - public Var UncalibratedPredictorModel { get; set; } = new Var(); + public Var UncalibratedPredictorModel { get; set; } = new Var(); /// /// The maximum number of examples to train the calibrator on @@ -3950,16 +3947,16 @@ public sealed partial class PlattCalibrator : Microsoft.ML.Runtime.EntryPoints.C /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ICalibratorOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ICalibratorOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -4003,7 +4000,7 @@ namespace Legacy.Models /// Evaluates a quantile regression scored dataset. /// [Obsolete] - public sealed partial class QuantileRegressionEvaluator : Microsoft.ML.Runtime.EntryPoints.CommonInputs.IEvaluatorInput + public sealed partial class QuantileRegressionEvaluator : Microsoft.ML.EntryPoints.CommonInputs.IEvaluatorInput { @@ -4048,7 +4045,7 @@ public sealed partial class QuantileRegressionEvaluator : Microsoft.ML.Runtime.E /// The data to be used for evaluation. /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); /// /// Name column name. @@ -4058,22 +4055,22 @@ public sealed partial class QuantileRegressionEvaluator : Microsoft.ML.Runtime.E [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IEvaluatorOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IEvaluatorOutput { /// /// Warning dataset /// - public Var Warnings { get; set; } = new Var(); + public Var Warnings { get; set; } = new Var(); /// /// Overall metrics dataset /// - public Var OverallMetrics { get; set; } = new Var(); + public Var OverallMetrics { get; set; } = new Var(); /// /// Per instance metrics dataset /// - public Var PerInstanceMetrics { get; set; } = new Var(); + public Var PerInstanceMetrics { get; set; } = new Var(); } } @@ -4086,7 +4083,7 @@ namespace Legacy.Models /// Evaluates a ranking scored dataset. /// [Obsolete] - public sealed partial class RankerEvaluator : Microsoft.ML.Runtime.EntryPoints.CommonInputs.IEvaluatorInput + public sealed partial class RankerEvaluator : Microsoft.ML.EntryPoints.CommonInputs.IEvaluatorInput { @@ -4136,7 +4133,7 @@ public sealed partial class RankerEvaluator : Microsoft.ML.Runtime.EntryPoints.C /// The data to be used for evaluation. /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); /// /// Name column name. @@ -4146,22 +4143,22 @@ public sealed partial class RankerEvaluator : Microsoft.ML.Runtime.EntryPoints.C [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IEvaluatorOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IEvaluatorOutput { /// /// Warning dataset /// - public Var Warnings { get; set; } = new Var(); + public Var Warnings { get; set; } = new Var(); /// /// Overall metrics dataset /// - public Var OverallMetrics { get; set; } = new Var(); + public Var OverallMetrics { get; set; } = new Var(); /// /// Per instance metrics dataset /// - public Var PerInstanceMetrics { get; set; } = new Var(); + public Var PerInstanceMetrics { get; set; } = new Var(); } } @@ -4188,7 +4185,7 @@ public sealed partial class RegressionEnsemble /// The models to combine into an ensemble /// [Obsolete] - public ArrayVar Models { get; set; } = new ArrayVar(); + public ArrayVar Models { get; set; } = new ArrayVar(); /// /// Whether to validate that all the pipelines are identical @@ -4198,12 +4195,12 @@ public sealed partial class RegressionEnsemble [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IRegressionOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IRegressionOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } } @@ -4216,7 +4213,7 @@ namespace Legacy.Models /// Evaluates a regression scored dataset. /// [Obsolete] - public sealed partial class RegressionEvaluator : Microsoft.ML.Runtime.EntryPoints.CommonInputs.IEvaluatorInput + public sealed partial class RegressionEvaluator : Microsoft.ML.EntryPoints.CommonInputs.IEvaluatorInput { @@ -4255,7 +4252,7 @@ public sealed partial class RegressionEvaluator : Microsoft.ML.Runtime.EntryPoin /// The data to be used for evaluation. /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); /// /// Name column name. @@ -4265,22 +4262,22 @@ public sealed partial class RegressionEvaluator : Microsoft.ML.Runtime.EntryPoin [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IEvaluatorOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IEvaluatorOutput { /// /// Warning dataset /// - public Var Warnings { get; set; } = new Var(); + public Var Warnings { get; set; } = new Var(); /// /// Overall metrics dataset /// - public Var OverallMetrics { get; set; } = new Var(); + public Var OverallMetrics { get; set; } = new Var(); /// /// Per instance metrics dataset /// - public Var PerInstanceMetrics { get; set; } = new Var(); + public Var PerInstanceMetrics { get; set; } = new Var(); } } @@ -4307,16 +4304,16 @@ public sealed partial class RegressionPipelineEnsemble /// The models to combine into an ensemble /// [Obsolete] - public ArrayVar Models { get; set; } = new ArrayVar(); + public ArrayVar Models { get; set; } = new ArrayVar(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IRegressionOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IRegressionOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } } @@ -4337,7 +4334,7 @@ public sealed partial class Summarizer /// The predictor to summarize /// [Obsolete] - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); [Obsolete] @@ -4346,12 +4343,12 @@ public sealed class Output /// /// The summary of a predictor /// - public Var Summary { get; set; } = new Var(); + public Var Summary { get; set; } = new Var(); /// /// The training set statistics. Note that this output can be null. /// - public Var Stats { get; set; } = new Var(); + public Var Stats { get; set; } = new Var(); } } @@ -4367,7 +4364,7 @@ public sealed partial class TrainTestMacroSubGraphInput /// The data to be used for training /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); } @@ -4378,7 +4375,7 @@ public sealed partial class TrainTestMacroSubGraphOutput /// The predictor model /// [Obsolete] - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } @@ -4394,19 +4391,19 @@ public sealed partial class TrainTestEvaluator /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// The data to be used for testing /// [Obsolete] - public Var TestingData { get; set; } = new Var(); + public Var TestingData { get; set; } = new Var(); /// /// The aggregated transform model from the pipeline before this command, to apply to the test data, and also include in the final model, together with the predictor model. /// [Obsolete] - public Var TransformModel { get; set; } = new Var(); + public Var TransformModel { get; set; } = new Var(); /// /// The training subgraph @@ -4454,19 +4451,19 @@ public sealed partial class TrainTestEvaluator /// Column to use for example weight /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } /// /// Column to use for grouping /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional GroupColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional GroupColumn { get; set; } /// /// Name column name /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional NameColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional NameColumn { get; set; } [Obsolete] @@ -4475,60 +4472,60 @@ public sealed class Output /// /// The final model including the trained predictor model and the model from the transforms, provided as the Input.TransformModel. /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); /// /// Warning dataset /// - public Var Warnings { get; set; } = new Var(); + public Var Warnings { get; set; } = new Var(); /// /// Overall metrics dataset /// - public Var OverallMetrics { get; set; } = new Var(); + public Var OverallMetrics { get; set; } = new Var(); /// /// Per instance metrics dataset /// - public Var PerInstanceMetrics { get; set; } = new Var(); + public Var PerInstanceMetrics { get; set; } = new Var(); /// /// Confusion matrix dataset /// - public Var ConfusionMatrix { get; set; } = new Var(); + public Var ConfusionMatrix { get; set; } = new Var(); /// /// Warning dataset for training /// - public Var TrainingWarnings { get; set; } = new Var(); + public Var TrainingWarnings { get; set; } = new Var(); /// /// Overall metrics dataset for training /// - public Var TrainingOverallMetrics { get; set; } = new Var(); + public Var TrainingOverallMetrics { get; set; } = new Var(); /// /// Per instance metrics dataset for training /// - public Var TrainingPerInstanceMetrics { get; set; } = new Var(); + public Var TrainingPerInstanceMetrics { get; set; } = new Var(); /// /// Confusion matrix dataset for training /// - public Var TrainingConfusionMatrix { get; set; } = new Var(); + public Var TrainingConfusionMatrix { get; set; } = new Var(); } } } - namespace Legacy.TimeSeriesProcessing + namespace Legacy.TimeSeriesProcessingEntryPoints { /// /// Applies a Exponential average on a time series. /// [Obsolete] - public sealed partial class ExponentialAverage : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class ExponentialAverage : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -4554,21 +4551,21 @@ public sealed partial class ExponentialAverage : Microsoft.ML.Runtime.EntryPoint /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -4608,7 +4605,7 @@ public ExponentialAveragePipelineStep(Output output) } } - namespace Legacy.TimeSeriesProcessing + namespace Legacy.TimeSeriesProcessingEntryPoints { [Obsolete] public enum SequentialAnomalyDetectionTransformBaseSingleIidAnomalyDetectionBaseStateMartingaleType : byte @@ -4623,7 +4620,7 @@ public enum SequentialAnomalyDetectionTransformBaseSingleIidAnomalyDetectionBase /// This transform detects the change-points in an i.i.d. sequence using adaptive kernel density estimation and martingales. /// [Obsolete] - public sealed partial class IidChangePointDetector : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class IidChangePointDetector : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -4667,21 +4664,21 @@ public sealed partial class IidChangePointDetector : Microsoft.ML.Runtime.EntryP /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -4721,7 +4718,7 @@ public IidChangePointDetectorPipelineStep(Output output) } } - namespace Legacy.TimeSeriesProcessing + namespace Legacy.TimeSeriesProcessingEntryPoints { [Obsolete] public enum SequentialAnomalyDetectionTransformBaseSingleIidAnomalyDetectionBaseStateAnomalySide : byte @@ -4736,7 +4733,7 @@ public enum SequentialAnomalyDetectionTransformBaseSingleIidAnomalyDetectionBase /// This transform detects the spikes in a i.i.d. sequence using adaptive kernel density estimation. /// [Obsolete] - public sealed partial class IidSpikeDetector : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class IidSpikeDetector : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -4774,21 +4771,21 @@ public sealed partial class IidSpikeDetector : Microsoft.ML.Runtime.EntryPoints. /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -4828,14 +4825,14 @@ public IidSpikeDetectorPipelineStep(Output output) } } - namespace Legacy.TimeSeriesProcessing + namespace Legacy.TimeSeriesProcessingEntryPoints { /// /// Detects the values of time-series that are in the top percentile of the sliding window. /// [Obsolete] - public sealed partial class PercentileThresholdTransform : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class PercentileThresholdTransform : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -4867,21 +4864,21 @@ public sealed partial class PercentileThresholdTransform : Microsoft.ML.Runtime. /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -4921,14 +4918,14 @@ public PercentileThresholdTransformPipelineStep(Output output) } } - namespace Legacy.TimeSeriesProcessing + namespace Legacy.TimeSeriesProcessingEntryPoints { /// /// This P-Value transform calculates the p-value of the current input in the sequence with regard to the values in the sliding window. /// [Obsolete] - public sealed partial class PValueTransform : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class PValueTransform : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -4972,21 +4969,21 @@ public sealed partial class PValueTransform : Microsoft.ML.Runtime.EntryPoints.C /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -5026,7 +5023,7 @@ public PValueTransformPipelineStep(Output output) } } - namespace Legacy.TimeSeriesProcessing + namespace Legacy.TimeSeriesProcessingEntryPoints { [Obsolete] public enum SlidingWindowTransformBaseSingleBeginOptions : byte @@ -5040,7 +5037,7 @@ public enum SlidingWindowTransformBaseSingleBeginOptions : byte /// Returns the last values for a time series [y(t-d-l+1), y(t-d-l+2), ..., y(t-l-1), y(t-l)] where d is the size of the window, l the lag and y is a Float. /// [Obsolete] - public sealed partial class SlidingWindowTransform : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class SlidingWindowTransform : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -5078,21 +5075,21 @@ public sealed partial class SlidingWindowTransform : Microsoft.ML.Runtime.EntryP /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -5132,7 +5129,7 @@ public SlidingWindowTransformPipelineStep(Output output) } } - namespace Legacy.TimeSeriesProcessing + namespace Legacy.TimeSeriesProcessingEntryPoints { [Obsolete] public enum ErrorFunctionUtilsErrorFunction : byte @@ -5157,7 +5154,7 @@ public enum SequentialAnomalyDetectionTransformBaseSingleSsaAnomalyDetectionBase /// This transform detects the change-points in a seasonal time-series using Singular Spectrum Analysis (SSA). /// [Obsolete] - public sealed partial class SsaChangePointDetector : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class SsaChangePointDetector : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -5219,21 +5216,21 @@ public sealed partial class SsaChangePointDetector : Microsoft.ML.Runtime.EntryP /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -5273,7 +5270,7 @@ public SsaChangePointDetectorPipelineStep(Output output) } } - namespace Legacy.TimeSeriesProcessing + namespace Legacy.TimeSeriesProcessingEntryPoints { [Obsolete] public enum SequentialAnomalyDetectionTransformBaseSingleSsaAnomalyDetectionBaseStateAnomalySide : byte @@ -5288,7 +5285,7 @@ public enum SequentialAnomalyDetectionTransformBaseSingleSsaAnomalyDetectionBase /// This transform detects the spikes in a seasonal time-series using Singular Spectrum Analysis (SSA). /// [Obsolete] - public sealed partial class SsaSpikeDetector : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class SsaSpikeDetector : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -5344,21 +5341,21 @@ public sealed partial class SsaSpikeDetector : Microsoft.ML.Runtime.EntryPoints. /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -5404,7 +5401,7 @@ namespace Legacy.Trainers /// /// [Obsolete] - public sealed partial class AveragedPerceptronBinaryClassifier : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class AveragedPerceptronBinaryClassifier : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -5528,7 +5525,7 @@ public sealed partial class AveragedPerceptronBinaryClassifier : Microsoft.ML.Ru /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -5550,12 +5547,12 @@ public sealed partial class AveragedPerceptronBinaryClassifier : Microsoft.ML.Ru [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -5599,7 +5596,7 @@ namespace Legacy.Trainers /// Train binary ensemble. /// [Obsolete] - public sealed partial class EnsembleBinaryClassifier : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class EnsembleBinaryClassifier : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -5658,7 +5655,7 @@ public sealed partial class EnsembleBinaryClassifier : Microsoft.ML.Runtime.Entr /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -5680,12 +5677,12 @@ public sealed partial class EnsembleBinaryClassifier : Microsoft.ML.Runtime.Entr [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -5729,7 +5726,7 @@ namespace Legacy.Trainers /// Train multiclass ensemble. /// [Obsolete] - public sealed partial class EnsembleClassification : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class EnsembleClassification : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -5788,7 +5785,7 @@ public sealed partial class EnsembleClassification : Microsoft.ML.Runtime.EntryP /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -5810,12 +5807,12 @@ public sealed partial class EnsembleClassification : Microsoft.ML.Runtime.EntryP [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IMulticlassClassificationOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IMulticlassClassificationOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -5859,7 +5856,7 @@ namespace Legacy.Trainers /// Train regression ensemble. /// [Obsolete] - public sealed partial class EnsembleRegression : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class EnsembleRegression : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -5918,7 +5915,7 @@ public sealed partial class EnsembleRegression : Microsoft.ML.Runtime.EntryPoint /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -5940,12 +5937,12 @@ public sealed partial class EnsembleRegression : Microsoft.ML.Runtime.EntryPoint [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IRegressionOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IRegressionOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -5996,7 +5993,7 @@ public enum Bundle : byte /// /// [Obsolete] - public sealed partial class FastForestBinaryClassifier : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithGroupId, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class FastForestBinaryClassifier : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithGroupId, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -6255,13 +6252,13 @@ public sealed partial class FastForestBinaryClassifier : Microsoft.ML.Runtime.En /// Column to use for example groupId /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional GroupIdColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional GroupIdColumn { get; set; } /// /// Column to use for example weight /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } /// /// Column to use for labels @@ -6273,7 +6270,7 @@ public sealed partial class FastForestBinaryClassifier : Microsoft.ML.Runtime.En /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -6295,12 +6292,12 @@ public sealed partial class FastForestBinaryClassifier : Microsoft.ML.Runtime.En [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -6343,7 +6340,7 @@ namespace Legacy.Trainers /// /// [Obsolete] - public sealed partial class FastForestRegressor : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithGroupId, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class FastForestRegressor : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithGroupId, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -6589,13 +6586,13 @@ public sealed partial class FastForestRegressor : Microsoft.ML.Runtime.EntryPoin /// Column to use for example groupId /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional GroupIdColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional GroupIdColumn { get; set; } /// /// Column to use for example weight /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } /// /// Column to use for labels @@ -6607,7 +6604,7 @@ public sealed partial class FastForestRegressor : Microsoft.ML.Runtime.EntryPoin /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -6629,12 +6626,12 @@ public sealed partial class FastForestRegressor : Microsoft.ML.Runtime.EntryPoin [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IRegressionOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IRegressionOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -6685,7 +6682,7 @@ public enum BoostedTreeArgsOptimizationAlgorithmType /// /// [Obsolete] - public sealed partial class FastTreeBinaryClassifier : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithGroupId, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class FastTreeBinaryClassifier : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithGroupId, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -7061,13 +7058,13 @@ public sealed partial class FastTreeBinaryClassifier : Microsoft.ML.Runtime.Entr /// Column to use for example groupId /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional GroupIdColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional GroupIdColumn { get; set; } /// /// Column to use for example weight /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } /// /// Column to use for labels @@ -7079,7 +7076,7 @@ public sealed partial class FastTreeBinaryClassifier : Microsoft.ML.Runtime.Entr /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -7101,12 +7098,12 @@ public sealed partial class FastTreeBinaryClassifier : Microsoft.ML.Runtime.Entr [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -7149,7 +7146,7 @@ namespace Legacy.Trainers /// /// [Obsolete] - public sealed partial class FastTreeRanker : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithGroupId, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class FastTreeRanker : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithGroupId, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -7567,13 +7564,13 @@ public sealed partial class FastTreeRanker : Microsoft.ML.Runtime.EntryPoints.Co /// Column to use for example groupId /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional GroupIdColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional GroupIdColumn { get; set; } /// /// Column to use for example weight /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } /// /// Column to use for labels @@ -7585,7 +7582,7 @@ public sealed partial class FastTreeRanker : Microsoft.ML.Runtime.EntryPoints.Co /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -7607,12 +7604,12 @@ public sealed partial class FastTreeRanker : Microsoft.ML.Runtime.EntryPoints.Co [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IRankingOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IRankingOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -7655,7 +7652,7 @@ namespace Legacy.Trainers /// /// [Obsolete] - public sealed partial class FastTreeRegressor : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithGroupId, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class FastTreeRegressor : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithGroupId, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -8025,13 +8022,13 @@ public sealed partial class FastTreeRegressor : Microsoft.ML.Runtime.EntryPoints /// Column to use for example groupId /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional GroupIdColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional GroupIdColumn { get; set; } /// /// Column to use for example weight /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } /// /// Column to use for labels @@ -8043,7 +8040,7 @@ public sealed partial class FastTreeRegressor : Microsoft.ML.Runtime.EntryPoints /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -8065,12 +8062,12 @@ public sealed partial class FastTreeRegressor : Microsoft.ML.Runtime.EntryPoints [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IRegressionOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IRegressionOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -8112,7 +8109,7 @@ namespace Legacy.Trainers /// [Obsolete] - public sealed partial class FastTreeTweedieRegressor : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithGroupId, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class FastTreeTweedieRegressor : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithGroupId, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -8488,13 +8485,13 @@ public sealed partial class FastTreeTweedieRegressor : Microsoft.ML.Runtime.Entr /// Column to use for example groupId /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional GroupIdColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional GroupIdColumn { get; set; } /// /// Column to use for example weight /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } /// /// Column to use for labels @@ -8506,7 +8503,7 @@ public sealed partial class FastTreeTweedieRegressor : Microsoft.ML.Runtime.Entr /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -8528,12 +8525,12 @@ public sealed partial class FastTreeTweedieRegressor : Microsoft.ML.Runtime.Entr [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IRegressionOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IRegressionOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -8576,7 +8573,7 @@ namespace Legacy.Trainers /// /// [Obsolete] - public sealed partial class FieldAwareFactorizationMachineBinaryClassifier : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class FieldAwareFactorizationMachineBinaryClassifier : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -8650,7 +8647,7 @@ public sealed partial class FieldAwareFactorizationMachineBinaryClassifier : Mic /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -8672,12 +8669,12 @@ public sealed partial class FieldAwareFactorizationMachineBinaryClassifier : Mic [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -8721,7 +8718,7 @@ namespace Legacy.Trainers /// Trains a gradient boosted stump per feature, on all features simultaneously, to fit target values using least-squares. It mantains no interactions between features. /// [Obsolete] - public sealed partial class GeneralizedAdditiveModelBinaryClassifier : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class GeneralizedAdditiveModelBinaryClassifier : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -8816,7 +8813,7 @@ public sealed partial class GeneralizedAdditiveModelBinaryClassifier : Microsoft /// Column to use for example weight /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } /// /// Column to use for labels @@ -8828,7 +8825,7 @@ public sealed partial class GeneralizedAdditiveModelBinaryClassifier : Microsoft /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -8850,12 +8847,12 @@ public sealed partial class GeneralizedAdditiveModelBinaryClassifier : Microsoft [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -8899,7 +8896,7 @@ namespace Legacy.Trainers /// Trains a gradient boosted stump per feature, on all features simultaneously, to fit target values using least-squares. It mantains no interactions between features. /// [Obsolete] - public sealed partial class GeneralizedAdditiveModelRegressor : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class GeneralizedAdditiveModelRegressor : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -8994,7 +8991,7 @@ public sealed partial class GeneralizedAdditiveModelRegressor : Microsoft.ML.Run /// Column to use for example weight /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } /// /// Column to use for labels @@ -9006,7 +9003,7 @@ public sealed partial class GeneralizedAdditiveModelRegressor : Microsoft.ML.Run /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -9028,12 +9025,12 @@ public sealed partial class GeneralizedAdditiveModelRegressor : Microsoft.ML.Run [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IRegressionOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IRegressionOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -9084,7 +9081,7 @@ public enum KMeansPlusPlusTrainerInitAlgorithm /// /// [Obsolete] - public sealed partial class KMeansPlusPlusClusterer : Microsoft.ML.Runtime.EntryPoints.CommonInputs.IUnsupervisedTrainerWithWeight, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class KMeansPlusPlusClusterer : Microsoft.ML.EntryPoints.CommonInputs.IUnsupervisedTrainerWithWeight, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -9129,13 +9126,13 @@ public sealed partial class KMeansPlusPlusClusterer : Microsoft.ML.Runtime.Entry /// Column to use for example weight /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } /// /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -9157,12 +9154,12 @@ public sealed partial class KMeansPlusPlusClusterer : Microsoft.ML.Runtime.Entry [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IClusteringOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IClusteringOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -9220,7 +9217,7 @@ public enum LightGbmArgumentsEvalMetricType /// /// [Obsolete] - public sealed partial class LightGbmBinaryClassifier : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithGroupId, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class LightGbmBinaryClassifier : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithGroupId, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -9377,13 +9374,13 @@ public sealed partial class LightGbmBinaryClassifier : Microsoft.ML.Runtime.Entr /// Column to use for example groupId /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional GroupIdColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional GroupIdColumn { get; set; } /// /// Column to use for example weight /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } /// /// Column to use for labels @@ -9395,7 +9392,7 @@ public sealed partial class LightGbmBinaryClassifier : Microsoft.ML.Runtime.Entr /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -9417,12 +9414,12 @@ public sealed partial class LightGbmBinaryClassifier : Microsoft.ML.Runtime.Entr [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -9465,7 +9462,7 @@ namespace Legacy.Trainers /// /// [Obsolete] - public sealed partial class LightGbmClassifier : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithGroupId, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class LightGbmClassifier : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithGroupId, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -9622,13 +9619,13 @@ public sealed partial class LightGbmClassifier : Microsoft.ML.Runtime.EntryPoint /// Column to use for example groupId /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional GroupIdColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional GroupIdColumn { get; set; } /// /// Column to use for example weight /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } /// /// Column to use for labels @@ -9640,7 +9637,7 @@ public sealed partial class LightGbmClassifier : Microsoft.ML.Runtime.EntryPoint /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -9662,12 +9659,12 @@ public sealed partial class LightGbmClassifier : Microsoft.ML.Runtime.EntryPoint [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IMulticlassClassificationOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IMulticlassClassificationOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -9710,7 +9707,7 @@ namespace Legacy.Trainers /// /// [Obsolete] - public sealed partial class LightGbmRanker : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithGroupId, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class LightGbmRanker : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithGroupId, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -9867,13 +9864,13 @@ public sealed partial class LightGbmRanker : Microsoft.ML.Runtime.EntryPoints.Co /// Column to use for example groupId /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional GroupIdColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional GroupIdColumn { get; set; } /// /// Column to use for example weight /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } /// /// Column to use for labels @@ -9885,7 +9882,7 @@ public sealed partial class LightGbmRanker : Microsoft.ML.Runtime.EntryPoints.Co /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -9907,12 +9904,12 @@ public sealed partial class LightGbmRanker : Microsoft.ML.Runtime.EntryPoints.Co [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IRankingOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IRankingOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -9955,7 +9952,7 @@ namespace Legacy.Trainers /// /// [Obsolete] - public sealed partial class LightGbmRegressor : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithGroupId, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class LightGbmRegressor : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithGroupId, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -10112,13 +10109,13 @@ public sealed partial class LightGbmRegressor : Microsoft.ML.Runtime.EntryPoints /// Column to use for example groupId /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional GroupIdColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional GroupIdColumn { get; set; } /// /// Column to use for example weight /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } /// /// Column to use for labels @@ -10130,7 +10127,7 @@ public sealed partial class LightGbmRegressor : Microsoft.ML.Runtime.EntryPoints /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -10152,12 +10149,12 @@ public sealed partial class LightGbmRegressor : Microsoft.ML.Runtime.EntryPoints [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IRegressionOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IRegressionOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -10201,7 +10198,7 @@ namespace Legacy.Trainers /// Train a linear SVM. /// [Obsolete] - public sealed partial class LinearSvmBinaryClassifier : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class LinearSvmBinaryClassifier : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -10288,7 +10285,7 @@ public sealed partial class LinearSvmBinaryClassifier : Microsoft.ML.Runtime.Ent /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -10310,12 +10307,12 @@ public sealed partial class LinearSvmBinaryClassifier : Microsoft.ML.Runtime.Ent [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -10358,7 +10355,7 @@ namespace Legacy.Trainers /// /// [Obsolete] - public sealed partial class LogisticRegressionBinaryClassifier : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class LogisticRegressionBinaryClassifier : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -10451,7 +10448,7 @@ public sealed partial class LogisticRegressionBinaryClassifier : Microsoft.ML.Ru /// Column to use for example weight /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } /// /// Column to use for labels @@ -10463,7 +10460,7 @@ public sealed partial class LogisticRegressionBinaryClassifier : Microsoft.ML.Ru /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -10485,12 +10482,12 @@ public sealed partial class LogisticRegressionBinaryClassifier : Microsoft.ML.Ru [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -10533,7 +10530,7 @@ namespace Legacy.Trainers /// /// [Obsolete] - public sealed partial class LogisticRegressionClassifier : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class LogisticRegressionClassifier : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -10626,7 +10623,7 @@ public sealed partial class LogisticRegressionClassifier : Microsoft.ML.Runtime. /// Column to use for example weight /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } /// /// Column to use for labels @@ -10638,7 +10635,7 @@ public sealed partial class LogisticRegressionClassifier : Microsoft.ML.Runtime. /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -10660,12 +10657,12 @@ public sealed partial class LogisticRegressionClassifier : Microsoft.ML.Runtime. [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IMulticlassClassificationOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IMulticlassClassificationOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -10708,7 +10705,7 @@ namespace Legacy.Trainers /// /// [Obsolete] - public sealed partial class NaiveBayesClassifier : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class NaiveBayesClassifier : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -10722,7 +10719,7 @@ public sealed partial class NaiveBayesClassifier : Microsoft.ML.Runtime.EntryPoi /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -10744,12 +10741,12 @@ public sealed partial class NaiveBayesClassifier : Microsoft.ML.Runtime.EntryPoi [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IMulticlassClassificationOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IMulticlassClassificationOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -10792,7 +10789,7 @@ namespace Legacy.Trainers /// /// [Obsolete] - public sealed partial class OnlineGradientDescentRegressor : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class OnlineGradientDescentRegressor : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -10903,7 +10900,7 @@ public sealed partial class OnlineGradientDescentRegressor : Microsoft.ML.Runtim /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -10925,12 +10922,12 @@ public sealed partial class OnlineGradientDescentRegressor : Microsoft.ML.Runtim [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IRegressionOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IRegressionOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -10972,7 +10969,7 @@ namespace Legacy.Trainers /// [Obsolete] - public sealed partial class OrdinaryLeastSquaresRegressor : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class OrdinaryLeastSquaresRegressor : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -10993,7 +10990,7 @@ public sealed partial class OrdinaryLeastSquaresRegressor : Microsoft.ML.Runtime /// Column to use for example weight /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } /// /// Column to use for labels @@ -11005,7 +11002,7 @@ public sealed partial class OrdinaryLeastSquaresRegressor : Microsoft.ML.Runtime /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -11027,12 +11024,12 @@ public sealed partial class OrdinaryLeastSquaresRegressor : Microsoft.ML.Runtime [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IRegressionOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IRegressionOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -11075,7 +11072,7 @@ namespace Legacy.Trainers /// /// [Obsolete] - public sealed partial class PcaAnomalyDetector : Microsoft.ML.Runtime.EntryPoints.CommonInputs.IUnsupervisedTrainerWithWeight, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class PcaAnomalyDetector : Microsoft.ML.EntryPoints.CommonInputs.IUnsupervisedTrainerWithWeight, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -11110,13 +11107,13 @@ public sealed partial class PcaAnomalyDetector : Microsoft.ML.Runtime.EntryPoint /// Column to use for example weight /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } /// /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -11138,12 +11135,12 @@ public sealed partial class PcaAnomalyDetector : Microsoft.ML.Runtime.EntryPoint [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IAnomalyDetectionOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IAnomalyDetectionOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -11186,7 +11183,7 @@ namespace Legacy.Trainers /// /// [Obsolete] - public sealed partial class PoissonRegressor : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class PoissonRegressor : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -11273,7 +11270,7 @@ public sealed partial class PoissonRegressor : Microsoft.ML.Runtime.EntryPoints. /// Column to use for example weight /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } /// /// Column to use for labels @@ -11285,7 +11282,7 @@ public sealed partial class PoissonRegressor : Microsoft.ML.Runtime.EntryPoints. /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -11307,12 +11304,12 @@ public sealed partial class PoissonRegressor : Microsoft.ML.Runtime.EntryPoints. [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IRegressionOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IRegressionOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -11355,7 +11352,7 @@ namespace Legacy.Trainers /// /// [Obsolete] - public sealed partial class StochasticDualCoordinateAscentBinaryClassifier : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class StochasticDualCoordinateAscentBinaryClassifier : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -11449,7 +11446,7 @@ public sealed partial class StochasticDualCoordinateAscentBinaryClassifier : Mic /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -11471,12 +11468,12 @@ public sealed partial class StochasticDualCoordinateAscentBinaryClassifier : Mic [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -11519,7 +11516,7 @@ namespace Legacy.Trainers /// /// [Obsolete] - public sealed partial class StochasticDualCoordinateAscentClassifier : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class StochasticDualCoordinateAscentClassifier : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -11594,7 +11591,7 @@ public sealed partial class StochasticDualCoordinateAscentClassifier : Microsoft /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -11616,12 +11613,12 @@ public sealed partial class StochasticDualCoordinateAscentClassifier : Microsoft [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IMulticlassClassificationOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IMulticlassClassificationOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -11664,7 +11661,7 @@ namespace Legacy.Trainers /// /// [Obsolete] - public sealed partial class StochasticDualCoordinateAscentRegressor : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class StochasticDualCoordinateAscentRegressor : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -11739,7 +11736,7 @@ public sealed partial class StochasticDualCoordinateAscentRegressor : Microsoft. /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -11761,12 +11758,12 @@ public sealed partial class StochasticDualCoordinateAscentRegressor : Microsoft. [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IRegressionOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IRegressionOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -11810,7 +11807,7 @@ namespace Legacy.Trainers /// Train an Hogwild SGD binary model. /// [Obsolete] - public sealed partial class StochasticGradientDescentBinaryClassifier : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class StochasticGradientDescentBinaryClassifier : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithWeight, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -11890,7 +11887,7 @@ public sealed partial class StochasticGradientDescentBinaryClassifier : Microsof /// Column to use for example weight /// [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } /// /// Column to use for labels @@ -11902,7 +11899,7 @@ public sealed partial class StochasticGradientDescentBinaryClassifier : Microsof /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -11924,12 +11921,12 @@ public sealed partial class StochasticGradientDescentBinaryClassifier : Microsof [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -11971,7 +11968,7 @@ namespace Legacy.Trainers /// [Obsolete] - public sealed partial class SymSgdBinaryClassifier : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class SymSgdBinaryClassifier : Microsoft.ML.EntryPoints.CommonInputs.ITrainerInputWithLabel, Microsoft.ML.EntryPoints.CommonInputs.ITrainerInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -12043,7 +12040,7 @@ public sealed partial class SymSgdBinaryClassifier : Microsoft.ML.Runtime.EntryP /// The data to be used for training /// [Obsolete] - public Var TrainingData { get; set; } = new Var(); + public Var TrainingData { get; set; } = new Var(); /// /// Column to use for features @@ -12065,12 +12062,12 @@ public sealed partial class SymSgdBinaryClassifier : Microsoft.ML.Runtime.EntryP [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITrainerOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.IBinaryClassificationOutput, Microsoft.ML.EntryPoints.CommonOutputs.ITrainerOutput { /// /// The trained model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } [Obsolete] @@ -12114,7 +12111,7 @@ namespace Legacy.Transforms /// Approximate bootstrap sampling. /// [Obsolete] - public sealed partial class ApproximateBootstrapSampler : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class ApproximateBootstrapSampler : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -12146,21 +12143,21 @@ public sealed partial class ApproximateBootstrapSampler : Microsoft.ML.Runtime.E /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -12207,7 +12204,7 @@ namespace Legacy.Transforms /// For binary prediction, it renames the PredictedLabel and Score columns to include the name of the positive class. /// [Obsolete] - public sealed partial class BinaryPredictionScoreColumnsRenamer : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class BinaryPredictionScoreColumnsRenamer : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -12215,27 +12212,27 @@ public sealed partial class BinaryPredictionScoreColumnsRenamer : Microsoft.ML.R /// The predictor model used in scoring /// [Obsolete] - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); /// /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -12317,7 +12314,7 @@ public sealed partial class NormalizeTransformBinColumn : OneToOneColumn [Obsolete] - public sealed partial class BinNormalizer : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class BinNormalizer : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public BinNormalizer() @@ -12389,21 +12386,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -12505,7 +12502,7 @@ public sealed partial class OneHotHashEncodingColumn : OneToOneColumn /// [Obsolete] - public sealed partial class CategoricalHashOneHotVectorizer : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class CategoricalHashOneHotVectorizer : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public CategoricalHashOneHotVectorizer() @@ -12589,21 +12586,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -12703,7 +12700,7 @@ public sealed partial class OneHotEncodingTransformerColumn : OneToOneColumn /// [Obsolete] - public sealed partial class CategoricalOneHotVectorizer : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class CategoricalOneHotVectorizer : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public CategoricalOneHotVectorizer() @@ -12787,21 +12784,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -12863,7 +12860,7 @@ public sealed partial class TokenizingByCharactersTransformerColumn : OneToOneCo /// [Obsolete] - public sealed partial class CharacterTokenizer : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class CharacterTokenizer : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public CharacterTokenizer() @@ -12923,21 +12920,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -13001,7 +12998,7 @@ public sealed partial class ColumnConcatenatingTransformerColumn : ManyToOneColu /// Concatenates one or more columns of the same item type. /// [Obsolete] - public sealed partial class ColumnConcatenator : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class ColumnConcatenator : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public ColumnConcatenator() @@ -13031,21 +13028,21 @@ public void AddColumn(string name, params string[] source) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -13109,7 +13106,7 @@ public sealed partial class ColumnCopyingTransformerColumn : OneToOneColumn [Obsolete] - public sealed partial class ColumnCopier : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class ColumnCopier : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public ColumnCopier() @@ -13163,21 +13160,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -13224,7 +13221,7 @@ namespace Legacy.Transforms /// Selects a set of columns, dropping all others /// [Obsolete] - public sealed partial class ColumnSelector : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class ColumnSelector : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -13256,21 +13253,21 @@ public sealed partial class ColumnSelector : Microsoft.ML.Runtime.EntryPoints.Co /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -13346,7 +13343,7 @@ public sealed partial class TypeConvertingTransformerColumn : OneToOneColumn [Obsolete] - public sealed partial class ColumnTypeConverter : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class ColumnTypeConverter : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public ColumnTypeConverter() @@ -13412,21 +13409,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -13471,7 +13468,7 @@ namespace Legacy.Transforms /// [Obsolete] - public sealed partial class CombinerByContiguousGroupId : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class CombinerByContiguousGroupId : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -13491,21 +13488,21 @@ public sealed partial class CombinerByContiguousGroupId : Microsoft.ML.Runtime.E /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -13581,7 +13578,7 @@ public sealed partial class NormalizeTransformAffineColumn : OneToOneColumn [Obsolete] - public sealed partial class ConditionalNormalizer : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class ConditionalNormalizer : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public ConditionalNormalizer() @@ -13647,7 +13644,7 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] @@ -13656,12 +13653,12 @@ public sealed class Output /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -13715,7 +13712,7 @@ public enum CacheCachingType /// Caches using the specified cache option. /// [Obsolete] - public sealed partial class DataCache : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class DataCache : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -13729,7 +13726,7 @@ public sealed partial class DataCache : Microsoft.ML.Runtime.EntryPoints.CommonI /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] @@ -13738,7 +13735,7 @@ public sealed class Output /// /// Dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); } [Obsolete] @@ -13792,13 +13789,13 @@ public sealed partial class DatasetScorer /// The dataset to be scored /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); /// /// The predictor model to apply to data /// [Obsolete] - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); /// /// Suffix to append to the score columns @@ -13813,12 +13810,12 @@ public sealed class Output /// /// The scored dataset /// - public Var ScoredData { get; set; } = new Var(); + public Var ScoredData { get; set; } = new Var(); /// /// The scoring transform /// - public Var ScoringTransform { get; set; } = new Var(); + public Var ScoringTransform { get; set; } = new Var(); } } @@ -13839,13 +13836,13 @@ public sealed partial class DatasetTransformScorer /// The dataset to be scored /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); /// /// The transform model to apply to data /// [Obsolete] - public Var TransformModel { get; set; } = new Var(); + public Var TransformModel { get; set; } = new Var(); [Obsolete] @@ -13854,12 +13851,12 @@ public sealed class Output /// /// The scored dataset /// - public Var ScoredData { get; set; } = new Var(); + public Var ScoredData { get; set; } = new Var(); /// /// The scoring transform /// - public Var ScoringTransform { get; set; } = new Var(); + public Var ScoringTransform { get; set; } = new Var(); } } @@ -13913,7 +13910,7 @@ public sealed partial class ValueToKeyMappingTransformerColumn : OneToOneColumn< /// Converts input values (words, numbers, etc.) to index in a dictionary. /// [Obsolete] - public sealed partial class Dictionarizer : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class Dictionarizer : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public Dictionarizer() @@ -13991,21 +13988,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -14052,7 +14049,7 @@ namespace Legacy.Transforms /// Combines all the features into one feature column. /// [Obsolete] - public sealed partial class FeatureCombiner : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class FeatureCombiner : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -14066,21 +14063,21 @@ public sealed partial class FeatureCombiner : Microsoft.ML.Runtime.EntryPoints.C /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -14127,7 +14124,7 @@ namespace Legacy.Transforms /// For each data point, calculates the contribution of individual features to the model prediction. /// [Obsolete] - public sealed partial class FeatureContributionCalculationTransformer : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class FeatureContributionCalculationTransformer : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -14135,7 +14132,7 @@ public sealed partial class FeatureContributionCalculationTransformer : Microsof /// The predictor model to apply to data /// [Obsolete] - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); /// /// Name of feature column @@ -14165,21 +14162,21 @@ public sealed partial class FeatureContributionCalculationTransformer : Microsof /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -14225,7 +14222,7 @@ namespace Legacy.Transforms /// /// [Obsolete] - public sealed partial class FeatureSelectorByCount : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class FeatureSelectorByCount : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -14245,21 +14242,21 @@ public sealed partial class FeatureSelectorByCount : Microsoft.ML.Runtime.EntryP /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -14305,7 +14302,7 @@ namespace Legacy.Transforms /// /// [Obsolete] - public sealed partial class FeatureSelectorByMutualInformation : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class FeatureSelectorByMutualInformation : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -14337,21 +14334,21 @@ public sealed partial class FeatureSelectorByMutualInformation : Microsoft.ML.Ru /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -14431,7 +14428,7 @@ public sealed partial class LpNormalizingTransformerGcnColumn : OneToOneColumn [Obsolete] - public sealed partial class GlobalContrastNormalizer : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class GlobalContrastNormalizer : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public GlobalContrastNormalizer() @@ -14503,21 +14500,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -14610,7 +14607,7 @@ public sealed partial class HashJoiningTransformColumn : OneToOneColumn /// [Obsolete] - public sealed partial class HashConverter : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class HashConverter : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public HashConverter() @@ -14688,21 +14685,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -14766,7 +14763,7 @@ public sealed partial class ImageGrayscaleTransformColumn : OneToOneColumn [Obsolete] - public sealed partial class ImageGrayscale : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class ImageGrayscale : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public ImageGrayscale() @@ -14820,21 +14817,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -14898,7 +14895,7 @@ public sealed partial class ImageLoaderTransformColumn : OneToOneColumn [Obsolete] - public sealed partial class ImageLoader : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class ImageLoader : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public ImageLoader() @@ -14958,21 +14955,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -15084,7 +15081,7 @@ public sealed partial class ImagePixelExtractorTransformColumn : OneToOneColumn< /// Extract color plane(s) from an image. Options include scaling, offset and conversion to floating point. /// [Obsolete] - public sealed partial class ImagePixelExtractor : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class ImagePixelExtractor : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public ImagePixelExtractor() @@ -15186,21 +15183,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -15305,7 +15302,7 @@ public sealed partial class ImageResizerTransformColumn : OneToOneColumn [Obsolete] - public sealed partial class ImageResizer : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class ImageResizer : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public ImageResizer() @@ -15383,21 +15380,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -15459,7 +15456,7 @@ public sealed partial class KeyToValueMappingTransformerColumn : OneToOneColumn< /// [Obsolete] - public sealed partial class KeyToTextConverter : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class KeyToTextConverter : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public KeyToTextConverter() @@ -15513,21 +15510,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -15574,7 +15571,7 @@ namespace Legacy.Transforms /// Transforms the label to either key or bool (if needed) to make it suitable for classification. /// [Obsolete] - public sealed partial class LabelColumnKeyBooleanConverter : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class LabelColumnKeyBooleanConverter : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -15594,21 +15591,21 @@ public sealed partial class LabelColumnKeyBooleanConverter : Microsoft.ML.Runtim /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -15678,7 +15675,7 @@ public sealed partial class LabelIndicatorTransformColumn : OneToOneColumn [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -15799,7 +15796,7 @@ namespace Legacy.Transforms /// Transforms the label to float to make it suitable for regression. /// [Obsolete] - public sealed partial class LabelToFloatConverter : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class LabelToFloatConverter : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -15813,21 +15810,21 @@ public sealed partial class LabelToFloatConverter : Microsoft.ML.Runtime.EntryPo /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -15956,7 +15953,7 @@ public sealed partial class LatentDirichletAllocationTransformerColumn : OneToOn /// /// [Obsolete] - public sealed partial class LightLda : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class LightLda : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public LightLda() @@ -16088,21 +16085,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -16172,7 +16169,7 @@ public sealed partial class NormalizeTransformLogNormalColumn : OneToOneColumn [Obsolete] - public sealed partial class LogMeanVarianceNormalizer : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class LogMeanVarianceNormalizer : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public LogMeanVarianceNormalizer() @@ -16238,21 +16235,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -16335,7 +16332,7 @@ public sealed partial class LpNormalizingTransformerColumn : OneToOneColumn [Obsolete] - public sealed partial class LpNormalizer : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class LpNormalizer : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public LpNormalizer() @@ -16401,21 +16398,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -16470,13 +16467,13 @@ public sealed partial class ManyHeterogeneousModelCombiner /// Transform model /// [Obsolete] - public ArrayVar TransformModels { get; set; } = new ArrayVar(); + public ArrayVar TransformModels { get; set; } = new ArrayVar(); /// /// Predictor model /// [Obsolete] - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); [Obsolete] @@ -16485,7 +16482,7 @@ public sealed class Output /// /// Predictor model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } } @@ -16498,7 +16495,7 @@ namespace Legacy.Transforms /// Normalizes the data based on the computed mean and variance of the data. /// [Obsolete] - public sealed partial class MeanVarianceNormalizer : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class MeanVarianceNormalizer : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public MeanVarianceNormalizer() @@ -16570,21 +16567,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -16631,7 +16628,7 @@ namespace Legacy.Transforms /// Normalizes the data based on the observed minimum and maximum values of the data. /// [Obsolete] - public sealed partial class MinMaxNormalizer : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class MinMaxNormalizer : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public MinMaxNormalizer() @@ -16697,21 +16694,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -16801,7 +16798,7 @@ public sealed partial class MissingValueHandlingTransformerColumn : OneToOneColu /// /// [Obsolete] - public sealed partial class MissingValueHandler : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class MissingValueHandler : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public MissingValueHandler() @@ -16873,21 +16870,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -16950,7 +16947,7 @@ public sealed partial class MissingValueIndicatorTransformerColumn : OneToOneCol /// /// [Obsolete] - public sealed partial class MissingValueIndicator : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class MissingValueIndicator : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public MissingValueIndicator() @@ -17004,21 +17001,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -17081,7 +17078,7 @@ public sealed partial class MissingValueDroppingTransformerColumn : OneToOneColu /// /// [Obsolete] - public sealed partial class MissingValuesDropper : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class MissingValuesDropper : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public MissingValuesDropper() @@ -17135,21 +17132,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -17195,7 +17192,7 @@ namespace Legacy.Transforms /// /// [Obsolete] - public sealed partial class MissingValuesRowDropper : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class MissingValuesRowDropper : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -17215,21 +17212,21 @@ public sealed partial class MissingValuesRowDropper : Microsoft.ML.Runtime.Entry /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -17320,7 +17317,7 @@ public sealed partial class MissingValueReplacingTransformerColumn : OneToOneCol /// /// [Obsolete] - public sealed partial class MissingValueSubstitutor : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class MissingValueSubstitutor : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public MissingValueSubstitutor() @@ -17386,21 +17383,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -17455,7 +17452,7 @@ public sealed partial class ModelCombiner /// Input models /// [Obsolete] - public ArrayVar Models { get; set; } = new ArrayVar(); + public ArrayVar Models { get; set; } = new ArrayVar(); [Obsolete] @@ -17464,7 +17461,7 @@ public sealed class Output /// /// Combined model /// - public Var OutputModel { get; set; } = new Var(); + public Var OutputModel { get; set; } = new Var(); } } @@ -17530,7 +17527,7 @@ public sealed partial class NgramExtractingTransformerColumn : OneToOneColumn [Obsolete] - public sealed partial class NGramTranslator : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class NGramTranslator : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public NGramTranslator() @@ -17614,21 +17611,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -17675,7 +17672,7 @@ namespace Legacy.Transforms /// Does nothing. /// [Obsolete] - public sealed partial class NoOperation : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class NoOperation : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -17683,21 +17680,21 @@ public sealed partial class NoOperation : Microsoft.ML.Runtime.EntryPoints.Commo /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -17743,7 +17740,7 @@ namespace Legacy.Transforms /// /// [Obsolete] - public sealed partial class OptionalColumnCreator : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class OptionalColumnCreator : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -17757,21 +17754,21 @@ public sealed partial class OptionalColumnCreator : Microsoft.ML.Runtime.EntryPo /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -17864,7 +17861,7 @@ public sealed partial class PcaTransformColumn : OneToOneColumn /// [Obsolete] - public sealed partial class PcaCalculator : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class PcaCalculator : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public PcaCalculator() @@ -17948,21 +17945,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -18009,7 +18006,7 @@ namespace Legacy.Transforms /// Transforms a predicted label column to its original values, unless it is of type bool. /// [Obsolete] - public sealed partial class PredictedLabelColumnOriginalValueConverter : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class PredictedLabelColumnOriginalValueConverter : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -18023,21 +18020,21 @@ public sealed partial class PredictedLabelColumnOriginalValueConverter : Microso /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -18107,7 +18104,7 @@ public sealed partial class GenerateNumberTransformColumn /// Adds a column with a generated number sequence. /// [Obsolete] - public sealed partial class RandomNumberGenerator : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class RandomNumberGenerator : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -18133,21 +18130,21 @@ public sealed partial class RandomNumberGenerator : Microsoft.ML.Runtime.EntryPo /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -18194,7 +18191,7 @@ namespace Legacy.Transforms /// Filters a dataview on a column of type Single, Double or Key (contiguous). Keeps the values that are in the specified min/max range. NaNs are always filtered out. If the input is a Key type, the min/max are considered percentages of the number of values. /// [Obsolete] - public sealed partial class RowRangeFilter : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class RowRangeFilter : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -18238,21 +18235,21 @@ public sealed partial class RowRangeFilter : Microsoft.ML.Runtime.EntryPoints.Co /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -18299,7 +18296,7 @@ namespace Legacy.Transforms /// Allows limiting input to a subset of rows at an optional offset. Can be used to implement data paging. /// [Obsolete] - public sealed partial class RowSkipAndTakeFilter : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class RowSkipAndTakeFilter : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -18319,21 +18316,21 @@ public sealed partial class RowSkipAndTakeFilter : Microsoft.ML.Runtime.EntryPoi /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -18380,7 +18377,7 @@ namespace Legacy.Transforms /// Allows limiting input to a subset of rows by skipping a number of rows. /// [Obsolete] - public sealed partial class RowSkipFilter : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class RowSkipFilter : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -18394,21 +18391,21 @@ public sealed partial class RowSkipFilter : Microsoft.ML.Runtime.EntryPoints.Com /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -18455,7 +18452,7 @@ namespace Legacy.Transforms /// Allows limiting input to a subset of rows by taking N first rows. /// [Obsolete] - public sealed partial class RowTakeFilter : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class RowTakeFilter : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -18469,21 +18466,21 @@ public sealed partial class RowTakeFilter : Microsoft.ML.Runtime.EntryPoints.Com /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -18530,7 +18527,7 @@ namespace Legacy.Transforms /// Selects only the last score columns and the extra columns specified in the arguments. /// [Obsolete] - public sealed partial class ScoreColumnSelector : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class ScoreColumnSelector : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -18544,21 +18541,21 @@ public sealed partial class ScoreColumnSelector : Microsoft.ML.Runtime.EntryPoin /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -18613,7 +18610,7 @@ public sealed partial class Scorer /// The predictor model to turn into a transform /// [Obsolete] - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); [Obsolete] @@ -18622,12 +18619,12 @@ public sealed class Output /// /// The scored dataset /// - public Var ScoredData { get; set; } = new Var(); + public Var ScoredData { get; set; } = new Var(); /// /// The scoring transform /// - public Var ScoringTransform { get; set; } = new Var(); + public Var ScoringTransform { get; set; } = new Var(); } } @@ -18647,7 +18644,7 @@ public enum UngroupTransformUngroupMode /// /// [Obsolete] - public sealed partial class Segregator : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class Segregator : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -18667,21 +18664,21 @@ public sealed partial class Segregator : Microsoft.ML.Runtime.EntryPoints.Common /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -18727,7 +18724,7 @@ namespace Legacy.Transforms /// /// [Obsolete] - public sealed partial class SentimentAnalyzer : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class SentimentAnalyzer : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -18747,21 +18744,21 @@ public sealed partial class SentimentAnalyzer : Microsoft.ML.Runtime.EntryPoints /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -18807,7 +18804,7 @@ namespace Legacy.Transforms /// /// [Obsolete] - public sealed partial class TensorFlowScorer : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class TensorFlowScorer : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -18905,21 +18902,21 @@ public sealed partial class TensorFlowScorer : Microsoft.ML.Runtime.EntryPoints. /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -19034,7 +19031,7 @@ public sealed partial class TermLoaderArguments /// /// [Obsolete] - public sealed partial class TextFeaturizer : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class TextFeaturizer : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public TextFeaturizer() @@ -19130,21 +19127,21 @@ public void AddColumn(string name, params string[] source) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -19190,7 +19187,7 @@ namespace Legacy.Transforms /// /// [Obsolete] - public sealed partial class TextToKeyConverter : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class TextToKeyConverter : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public TextToKeyConverter() @@ -19268,21 +19265,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -19337,7 +19334,7 @@ public sealed partial class TrainTestDatasetSplitter /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); /// /// Fraction of training data @@ -19358,12 +19355,12 @@ public sealed class Output /// /// Training data /// - public Var TrainData { get; set; } = new Var(); + public Var TrainData { get; set; } = new Var(); /// /// Testing data /// - public Var TestData { get; set; } = new Var(); + public Var TestData { get; set; } = new Var(); } } @@ -19374,7 +19371,7 @@ namespace Legacy.Transforms /// [Obsolete] - public sealed partial class TreeLeafFeaturizer : Microsoft.ML.Runtime.EntryPoints.CommonInputs.IFeaturizerInput, Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class TreeLeafFeaturizer : Microsoft.ML.EntryPoints.CommonInputs.IFeaturizerInput, Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { @@ -19394,27 +19391,27 @@ public sealed partial class TreeLeafFeaturizer : Microsoft.ML.Runtime.EntryPoint /// Trainer to use /// [Obsolete] - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); /// /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -19469,13 +19466,13 @@ public sealed partial class TwoHeterogeneousModelCombiner /// Transform model /// [Obsolete] - public Var TransformModel { get; set; } = new Var(); + public Var TransformModel { get; set; } = new Var(); /// /// Predictor model /// [Obsolete] - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); [Obsolete] @@ -19484,7 +19481,7 @@ public sealed class Output /// /// Predictor model /// - public Var PredictorModel { get; set; } = new Var(); + public Var PredictorModel { get; set; } = new Var(); } } @@ -19568,7 +19565,7 @@ public sealed partial class VectorToImageTransformColumn : OneToOneColumn [Obsolete] - public sealed partial class VectorToImage : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class VectorToImage : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public VectorToImage() @@ -19676,21 +19673,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -19768,7 +19765,7 @@ public sealed partial class WordEmbeddingsExtractingTransformerColumn : OneToOne /// /// [Obsolete] - public sealed partial class WordEmbeddings : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class WordEmbeddings : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public WordEmbeddings() @@ -19834,21 +19831,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -19917,7 +19914,7 @@ public sealed partial class WordTokenizingTransformerColumn : OneToOneColumn /// [Obsolete] - public sealed partial class WordTokenizer : Microsoft.ML.Runtime.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem + public sealed partial class WordTokenizer : Microsoft.ML.EntryPoints.CommonInputs.ITransformInput, Microsoft.ML.Legacy.ILearningPipelineItem { public WordTokenizer() @@ -19977,21 +19974,21 @@ public void AddColumn(string outputColumn, string inputColumn) /// Input dataset /// [Obsolete] - public Var Data { get; set; } = new Var(); + public Var Data { get; set; } = new Var(); [Obsolete] - public sealed class Output : Microsoft.ML.Runtime.EntryPoints.CommonOutputs.ITransformOutput + public sealed class Output : Microsoft.ML.EntryPoints.CommonOutputs.ITransformOutput { /// /// Transformed dataset /// - public Var OutputData { get; set; } = new Var(); + public Var OutputData { get; set; } = new Var(); /// /// Transform model /// - public Var Model { get; set; } = new Var(); + public Var Model { get; set; } = new Var(); } [Obsolete] @@ -20031,3142 +20028,3139 @@ public WordTokenizerPipelineStep(Output output) } } - namespace Runtime + [Obsolete] + public abstract class BoosterParameterFunction : ComponentKind {} + + + + /// + /// Dropouts meet Multiple Additive Regresion Trees. See https://arxiv.org/abs/1505.01866 + /// + [Obsolete] + public sealed class DartBoosterParameterFunction : BoosterParameterFunction { + /// + /// Drop ratio for trees. Range:(0,1). + /// + [TlcModule.Range(Inf = 0d, Max = 1d)] [Obsolete] - public abstract class BoosterParameterFunction : ComponentKind {} + public double DropRate { get; set; } = 0.1d; + /// + /// Max number of dropped tree in a boosting round. + /// + [TlcModule.Range(Inf = 0, Max = 2147483647)] + [Obsolete] + public int MaxDrop { get; set; } = 1; + /// + /// Probability for not perform dropping in a boosting round. + /// + [TlcModule.Range(Inf = 0d, Max = 1d)] + [Obsolete] + public double SkipDrop { get; set; } = 0.5d; /// - /// Dropouts meet Multiple Additive Regresion Trees. See https://arxiv.org/abs/1505.01866 + /// True will enable xgboost dart mode. /// [Obsolete] - public sealed class DartBoosterParameterFunction : BoosterParameterFunction - { - /// - /// Drop ratio for trees. Range:(0,1). - /// - [TlcModule.Range(Inf = 0d, Max = 1d)] - [Obsolete] - public double DropRate { get; set; } = 0.1d; + public bool XgboostDartMode { get; set; } = false; - /// - /// Max number of dropped tree in a boosting round. - /// - [TlcModule.Range(Inf = 0, Max = 2147483647)] - [Obsolete] - public int MaxDrop { get; set; } = 1; + /// + /// True will enable uniform drop. + /// + [Obsolete] + public bool UniformDrop { get; set; } = false; - /// - /// Probability for not perform dropping in a boosting round. - /// - [TlcModule.Range(Inf = 0d, Max = 1d)] - [Obsolete] - public double SkipDrop { get; set; } = 0.5d; + /// + /// Use for binary classification when classes are not balanced. + /// + [Obsolete] + public bool UnbalancedSets { get; set; } = false; - /// - /// True will enable xgboost dart mode. - /// - [Obsolete] - public bool XgboostDartMode { get; set; } = false; + /// + /// Minimum loss reduction required to make a further partition on a leaf node of the tree. the larger, the more conservative the algorithm will be. + /// + [TlcModule.Range(Min = 0d)] + [Obsolete] + public double MinSplitGain { get; set; } - /// - /// True will enable uniform drop. - /// - [Obsolete] - public bool UniformDrop { get; set; } = false; + /// + /// Maximum depth of a tree. 0 means no limit. However, tree still grows by best-first. + /// + [TlcModule.Range(Min = 0, Max = 2147483647)] + [Obsolete] + public int MaxDepth { get; set; } - /// - /// Use for binary classification when classes are not balanced. - /// - [Obsolete] - public bool UnbalancedSets { get; set; } = false; + /// + /// Minimum sum of instance weight(hessian) needed in a child. If the tree partition step results in a leaf node with the sum of instance weight less than min_child_weight, then the building process will give up further partitioning. In linear regression mode, this simply corresponds to minimum number of instances needed to be in each node. The larger, the more conservative the algorithm will be. + /// + [TlcModule.Range(Min = 0d)] + [Obsolete] + public double MinChildWeight { get; set; } = 0.1d; - /// - /// Minimum loss reduction required to make a further partition on a leaf node of the tree. the larger, the more conservative the algorithm will be. - /// - [TlcModule.Range(Min = 0d)] - [Obsolete] - public double MinSplitGain { get; set; } + /// + /// Subsample frequency. 0 means no subsample. If subsampleFreq > 0, it will use a subset(ratio=subsample) to train. And the subset will be updated on every Subsample iteratinos. + /// + [TlcModule.Range(Min = 0, Max = 2147483647)] + [Obsolete] + public int SubsampleFreq { get; set; } - /// - /// Maximum depth of a tree. 0 means no limit. However, tree still grows by best-first. - /// - [TlcModule.Range(Min = 0, Max = 2147483647)] - [Obsolete] - public int MaxDepth { get; set; } + /// + /// Subsample ratio of the training instance. Setting it to 0.5 means that LightGBM randomly collected half of the data instances to grow trees and this will prevent overfitting. Range: (0,1]. + /// + [TlcModule.Range(Inf = 0d, Max = 1d)] + [Obsolete] + public double Subsample { get; set; } = 1d; - /// - /// Minimum sum of instance weight(hessian) needed in a child. If the tree partition step results in a leaf node with the sum of instance weight less than min_child_weight, then the building process will give up further partitioning. In linear regression mode, this simply corresponds to minimum number of instances needed to be in each node. The larger, the more conservative the algorithm will be. - /// - [TlcModule.Range(Min = 0d)] - [Obsolete] - public double MinChildWeight { get; set; } = 0.1d; + /// + /// Subsample ratio of columns when constructing each tree. Range: (0,1]. + /// + [TlcModule.Range(Inf = 0d, Max = 1d)] + [Obsolete] + public double FeatureFraction { get; set; } = 1d; - /// - /// Subsample frequency. 0 means no subsample. If subsampleFreq > 0, it will use a subset(ratio=subsample) to train. And the subset will be updated on every Subsample iteratinos. - /// - [TlcModule.Range(Min = 0, Max = 2147483647)] - [Obsolete] - public int SubsampleFreq { get; set; } + /// + /// L2 regularization term on weights, increasing this value will make model more conservative. + /// + [TlcModule.Range(Min = 0d)] + [TlcModule.SweepableDiscreteParamAttribute("RegLambda", new object[]{0f, 0.5f, 1f})] + [Obsolete] + public double RegLambda { get; set; } = 0.01d; - /// - /// Subsample ratio of the training instance. Setting it to 0.5 means that LightGBM randomly collected half of the data instances to grow trees and this will prevent overfitting. Range: (0,1]. - /// - [TlcModule.Range(Inf = 0d, Max = 1d)] - [Obsolete] - public double Subsample { get; set; } = 1d; + /// + /// L1 regularization term on weights, increase this value will make model more conservative. + /// + [TlcModule.Range(Min = 0d)] + [TlcModule.SweepableDiscreteParamAttribute("RegAlpha", new object[]{0f, 0.5f, 1f})] + [Obsolete] + public double RegAlpha { get; set; } - /// - /// Subsample ratio of columns when constructing each tree. Range: (0,1]. - /// - [TlcModule.Range(Inf = 0d, Max = 1d)] - [Obsolete] - public double FeatureFraction { get; set; } = 1d; + /// + /// Control the balance of positive and negative weights, useful for unbalanced classes. A typical value to consider: sum(negative cases) / sum(positive cases). + /// + [Obsolete] + public double ScalePosWeight { get; set; } = 1d; - /// - /// L2 regularization term on weights, increasing this value will make model more conservative. - /// - [TlcModule.Range(Min = 0d)] - [TlcModule.SweepableDiscreteParamAttribute("RegLambda", new object[]{0f, 0.5f, 1f})] - [Obsolete] - public double RegLambda { get; set; } = 0.01d; + [Obsolete] + internal override string ComponentName => "dart"; + } - /// - /// L1 regularization term on weights, increase this value will make model more conservative. - /// - [TlcModule.Range(Min = 0d)] - [TlcModule.SweepableDiscreteParamAttribute("RegAlpha", new object[]{0f, 0.5f, 1f})] - [Obsolete] - public double RegAlpha { get; set; } - /// - /// Control the balance of positive and negative weights, useful for unbalanced classes. A typical value to consider: sum(negative cases) / sum(positive cases). - /// - [Obsolete] - public double ScalePosWeight { get; set; } = 1d; - [Obsolete] - internal override string ComponentName => "dart"; - } + /// + /// Traditional Gradient Boosting Decision Tree. + /// + [Obsolete] + public sealed class GbdtBoosterParameterFunction : BoosterParameterFunction + { + /// + /// Use for binary classification when classes are not balanced. + /// + [Obsolete] + public bool UnbalancedSets { get; set; } = false; + /// + /// Minimum loss reduction required to make a further partition on a leaf node of the tree. the larger, the more conservative the algorithm will be. + /// + [TlcModule.Range(Min = 0d)] + [Obsolete] + public double MinSplitGain { get; set; } + /// + /// Maximum depth of a tree. 0 means no limit. However, tree still grows by best-first. + /// + [TlcModule.Range(Min = 0, Max = 2147483647)] + [Obsolete] + public int MaxDepth { get; set; } /// - /// Traditional Gradient Boosting Decision Tree. + /// Minimum sum of instance weight(hessian) needed in a child. If the tree partition step results in a leaf node with the sum of instance weight less than min_child_weight, then the building process will give up further partitioning. In linear regression mode, this simply corresponds to minimum number of instances needed to be in each node. The larger, the more conservative the algorithm will be. /// + [TlcModule.Range(Min = 0d)] [Obsolete] - public sealed class GbdtBoosterParameterFunction : BoosterParameterFunction - { - /// - /// Use for binary classification when classes are not balanced. - /// - [Obsolete] - public bool UnbalancedSets { get; set; } = false; + public double MinChildWeight { get; set; } = 0.1d; - /// - /// Minimum loss reduction required to make a further partition on a leaf node of the tree. the larger, the more conservative the algorithm will be. - /// - [TlcModule.Range(Min = 0d)] - [Obsolete] - public double MinSplitGain { get; set; } + /// + /// Subsample frequency. 0 means no subsample. If subsampleFreq > 0, it will use a subset(ratio=subsample) to train. And the subset will be updated on every Subsample iteratinos. + /// + [TlcModule.Range(Min = 0, Max = 2147483647)] + [Obsolete] + public int SubsampleFreq { get; set; } - /// - /// Maximum depth of a tree. 0 means no limit. However, tree still grows by best-first. - /// - [TlcModule.Range(Min = 0, Max = 2147483647)] - [Obsolete] - public int MaxDepth { get; set; } + /// + /// Subsample ratio of the training instance. Setting it to 0.5 means that LightGBM randomly collected half of the data instances to grow trees and this will prevent overfitting. Range: (0,1]. + /// + [TlcModule.Range(Inf = 0d, Max = 1d)] + [Obsolete] + public double Subsample { get; set; } = 1d; - /// - /// Minimum sum of instance weight(hessian) needed in a child. If the tree partition step results in a leaf node with the sum of instance weight less than min_child_weight, then the building process will give up further partitioning. In linear regression mode, this simply corresponds to minimum number of instances needed to be in each node. The larger, the more conservative the algorithm will be. - /// - [TlcModule.Range(Min = 0d)] - [Obsolete] - public double MinChildWeight { get; set; } = 0.1d; + /// + /// Subsample ratio of columns when constructing each tree. Range: (0,1]. + /// + [TlcModule.Range(Inf = 0d, Max = 1d)] + [Obsolete] + public double FeatureFraction { get; set; } = 1d; - /// - /// Subsample frequency. 0 means no subsample. If subsampleFreq > 0, it will use a subset(ratio=subsample) to train. And the subset will be updated on every Subsample iteratinos. - /// - [TlcModule.Range(Min = 0, Max = 2147483647)] - [Obsolete] - public int SubsampleFreq { get; set; } + /// + /// L2 regularization term on weights, increasing this value will make model more conservative. + /// + [TlcModule.Range(Min = 0d)] + [TlcModule.SweepableDiscreteParamAttribute("RegLambda", new object[]{0f, 0.5f, 1f})] + [Obsolete] + public double RegLambda { get; set; } = 0.01d; - /// - /// Subsample ratio of the training instance. Setting it to 0.5 means that LightGBM randomly collected half of the data instances to grow trees and this will prevent overfitting. Range: (0,1]. - /// - [TlcModule.Range(Inf = 0d, Max = 1d)] - [Obsolete] - public double Subsample { get; set; } = 1d; + /// + /// L1 regularization term on weights, increase this value will make model more conservative. + /// + [TlcModule.Range(Min = 0d)] + [TlcModule.SweepableDiscreteParamAttribute("RegAlpha", new object[]{0f, 0.5f, 1f})] + [Obsolete] + public double RegAlpha { get; set; } - /// - /// Subsample ratio of columns when constructing each tree. Range: (0,1]. - /// - [TlcModule.Range(Inf = 0d, Max = 1d)] - [Obsolete] - public double FeatureFraction { get; set; } = 1d; + /// + /// Control the balance of positive and negative weights, useful for unbalanced classes. A typical value to consider: sum(negative cases) / sum(positive cases). + /// + [Obsolete] + public double ScalePosWeight { get; set; } = 1d; - /// - /// L2 regularization term on weights, increasing this value will make model more conservative. - /// - [TlcModule.Range(Min = 0d)] - [TlcModule.SweepableDiscreteParamAttribute("RegLambda", new object[]{0f, 0.5f, 1f})] - [Obsolete] - public double RegLambda { get; set; } = 0.01d; + [Obsolete] + internal override string ComponentName => "gbdt"; + } - /// - /// L1 regularization term on weights, increase this value will make model more conservative. - /// - [TlcModule.Range(Min = 0d)] - [TlcModule.SweepableDiscreteParamAttribute("RegAlpha", new object[]{0f, 0.5f, 1f})] - [Obsolete] - public double RegAlpha { get; set; } - /// - /// Control the balance of positive and negative weights, useful for unbalanced classes. A typical value to consider: sum(negative cases) / sum(positive cases). - /// - [Obsolete] - public double ScalePosWeight { get; set; } = 1d; - [Obsolete] - internal override string ComponentName => "gbdt"; - } + /// + /// Gradient-based One-Side Sampling. + /// + [Obsolete] + public sealed class GossBoosterParameterFunction : BoosterParameterFunction + { + /// + /// Retain ratio for large gradient instances. + /// + [TlcModule.Range(Inf = 0d, Max = 1d)] + [Obsolete] + public double TopRate { get; set; } = 0.2d; + /// + /// Retain ratio for small gradient instances. + /// + [TlcModule.Range(Inf = 0d, Max = 1d)] + [Obsolete] + public double OtherRate { get; set; } = 0.1d; + /// + /// Use for binary classification when classes are not balanced. + /// + [Obsolete] + public bool UnbalancedSets { get; set; } = false; /// - /// Gradient-based One-Side Sampling. + /// Minimum loss reduction required to make a further partition on a leaf node of the tree. the larger, the more conservative the algorithm will be. /// + [TlcModule.Range(Min = 0d)] [Obsolete] - public sealed class GossBoosterParameterFunction : BoosterParameterFunction - { - /// - /// Retain ratio for large gradient instances. - /// - [TlcModule.Range(Inf = 0d, Max = 1d)] - [Obsolete] - public double TopRate { get; set; } = 0.2d; + public double MinSplitGain { get; set; } - /// - /// Retain ratio for small gradient instances. - /// - [TlcModule.Range(Inf = 0d, Max = 1d)] - [Obsolete] - public double OtherRate { get; set; } = 0.1d; + /// + /// Maximum depth of a tree. 0 means no limit. However, tree still grows by best-first. + /// + [TlcModule.Range(Min = 0, Max = 2147483647)] + [Obsolete] + public int MaxDepth { get; set; } - /// - /// Use for binary classification when classes are not balanced. - /// - [Obsolete] - public bool UnbalancedSets { get; set; } = false; + /// + /// Minimum sum of instance weight(hessian) needed in a child. If the tree partition step results in a leaf node with the sum of instance weight less than min_child_weight, then the building process will give up further partitioning. In linear regression mode, this simply corresponds to minimum number of instances needed to be in each node. The larger, the more conservative the algorithm will be. + /// + [TlcModule.Range(Min = 0d)] + [Obsolete] + public double MinChildWeight { get; set; } = 0.1d; - /// - /// Minimum loss reduction required to make a further partition on a leaf node of the tree. the larger, the more conservative the algorithm will be. - /// - [TlcModule.Range(Min = 0d)] - [Obsolete] - public double MinSplitGain { get; set; } + /// + /// Subsample frequency. 0 means no subsample. If subsampleFreq > 0, it will use a subset(ratio=subsample) to train. And the subset will be updated on every Subsample iteratinos. + /// + [TlcModule.Range(Min = 0, Max = 2147483647)] + [Obsolete] + public int SubsampleFreq { get; set; } - /// - /// Maximum depth of a tree. 0 means no limit. However, tree still grows by best-first. - /// - [TlcModule.Range(Min = 0, Max = 2147483647)] - [Obsolete] - public int MaxDepth { get; set; } + /// + /// Subsample ratio of the training instance. Setting it to 0.5 means that LightGBM randomly collected half of the data instances to grow trees and this will prevent overfitting. Range: (0,1]. + /// + [TlcModule.Range(Inf = 0d, Max = 1d)] + [Obsolete] + public double Subsample { get; set; } = 1d; - /// - /// Minimum sum of instance weight(hessian) needed in a child. If the tree partition step results in a leaf node with the sum of instance weight less than min_child_weight, then the building process will give up further partitioning. In linear regression mode, this simply corresponds to minimum number of instances needed to be in each node. The larger, the more conservative the algorithm will be. - /// - [TlcModule.Range(Min = 0d)] - [Obsolete] - public double MinChildWeight { get; set; } = 0.1d; + /// + /// Subsample ratio of columns when constructing each tree. Range: (0,1]. + /// + [TlcModule.Range(Inf = 0d, Max = 1d)] + [Obsolete] + public double FeatureFraction { get; set; } = 1d; - /// - /// Subsample frequency. 0 means no subsample. If subsampleFreq > 0, it will use a subset(ratio=subsample) to train. And the subset will be updated on every Subsample iteratinos. - /// - [TlcModule.Range(Min = 0, Max = 2147483647)] - [Obsolete] - public int SubsampleFreq { get; set; } + /// + /// L2 regularization term on weights, increasing this value will make model more conservative. + /// + [TlcModule.Range(Min = 0d)] + [TlcModule.SweepableDiscreteParamAttribute("RegLambda", new object[]{0f, 0.5f, 1f})] + [Obsolete] + public double RegLambda { get; set; } = 0.01d; - /// - /// Subsample ratio of the training instance. Setting it to 0.5 means that LightGBM randomly collected half of the data instances to grow trees and this will prevent overfitting. Range: (0,1]. - /// - [TlcModule.Range(Inf = 0d, Max = 1d)] - [Obsolete] - public double Subsample { get; set; } = 1d; + /// + /// L1 regularization term on weights, increase this value will make model more conservative. + /// + [TlcModule.Range(Min = 0d)] + [TlcModule.SweepableDiscreteParamAttribute("RegAlpha", new object[]{0f, 0.5f, 1f})] + [Obsolete] + public double RegAlpha { get; set; } - /// - /// Subsample ratio of columns when constructing each tree. Range: (0,1]. - /// - [TlcModule.Range(Inf = 0d, Max = 1d)] - [Obsolete] - public double FeatureFraction { get; set; } = 1d; + /// + /// Control the balance of positive and negative weights, useful for unbalanced classes. A typical value to consider: sum(negative cases) / sum(positive cases). + /// + [Obsolete] + public double ScalePosWeight { get; set; } = 1d; - /// - /// L2 regularization term on weights, increasing this value will make model more conservative. - /// - [TlcModule.Range(Min = 0d)] - [TlcModule.SweepableDiscreteParamAttribute("RegLambda", new object[]{0f, 0.5f, 1f})] - [Obsolete] - public double RegLambda { get; set; } = 0.01d; + [Obsolete] + internal override string ComponentName => "goss"; + } - /// - /// L1 regularization term on weights, increase this value will make model more conservative. - /// - [TlcModule.Range(Min = 0d)] - [TlcModule.SweepableDiscreteParamAttribute("RegAlpha", new object[]{0f, 0.5f, 1f})] - [Obsolete] - public double RegAlpha { get; set; } + [Obsolete] + public abstract class CalibratorTrainer : ComponentKind {} - /// - /// Control the balance of positive and negative weights, useful for unbalanced classes. A typical value to consider: sum(negative cases) / sum(positive cases). - /// - [Obsolete] - public double ScalePosWeight { get; set; } = 1d; - [Obsolete] - internal override string ComponentName => "goss"; - } + [Obsolete] + public sealed class FixedPlattCalibratorCalibratorTrainer : CalibratorTrainer + { + /// + /// The slope parameter of f(x) = 1 / (1 + exp(-slope * x + offset) + /// [Obsolete] - public abstract class CalibratorTrainer : ComponentKind {} - - + public double Slope { get; set; } = 1d; + /// + /// The offset parameter of f(x) = 1 / (1 + exp(-slope * x + offset) + /// [Obsolete] - public sealed class FixedPlattCalibratorCalibratorTrainer : CalibratorTrainer - { - /// - /// The slope parameter of f(x) = 1 / (1 + exp(-slope * x + offset) - /// - [Obsolete] - public double Slope { get; set; } = 1d; - - /// - /// The offset parameter of f(x) = 1 / (1 + exp(-slope * x + offset) - /// - [Obsolete] - public double Offset { get; set; } + public double Offset { get; set; } - [Obsolete] - internal override string ComponentName => "FixedPlattCalibrator"; - } + [Obsolete] + internal override string ComponentName => "FixedPlattCalibrator"; + } + [Obsolete] + public sealed class NaiveCalibratorCalibratorTrainer : CalibratorTrainer + { [Obsolete] - public sealed class NaiveCalibratorCalibratorTrainer : CalibratorTrainer - { - [Obsolete] - internal override string ComponentName => "NaiveCalibrator"; - } + internal override string ComponentName => "NaiveCalibrator"; + } + [Obsolete] + public sealed class PavCalibratorCalibratorTrainer : CalibratorTrainer + { [Obsolete] - public sealed class PavCalibratorCalibratorTrainer : CalibratorTrainer - { - [Obsolete] - internal override string ComponentName => "PavCalibrator"; - } + internal override string ComponentName => "PavCalibrator"; + } - /// - /// Platt calibration. - /// + /// + /// Platt calibration. + /// + [Obsolete] + public sealed class PlattCalibratorCalibratorTrainer : CalibratorTrainer + { [Obsolete] - public sealed class PlattCalibratorCalibratorTrainer : CalibratorTrainer - { - [Obsolete] - internal override string ComponentName => "PlattCalibrator"; - } + internal override string ComponentName => "PlattCalibrator"; + } - [Obsolete] - public abstract class ClassificationLossFunction : ComponentKind {} + [Obsolete] + public abstract class ClassificationLossFunction : ComponentKind {} + /// + /// Exponential loss. + /// + [Obsolete] + public sealed class ExpLossClassificationLossFunction : ClassificationLossFunction + { /// - /// Exponential loss. + /// Beta (dilation) /// [Obsolete] - public sealed class ExpLossClassificationLossFunction : ClassificationLossFunction - { - /// - /// Beta (dilation) - /// - [Obsolete] - public float Beta { get; set; } = 1f; + public float Beta { get; set; } = 1f; - [Obsolete] - internal override string ComponentName => "ExpLoss"; - } + [Obsolete] + internal override string ComponentName => "ExpLoss"; + } + /// + /// Hinge loss. + /// + [Obsolete] + public sealed class HingeLossClassificationLossFunction : ClassificationLossFunction + { /// - /// Hinge loss. + /// Margin value /// [Obsolete] - public sealed class HingeLossClassificationLossFunction : ClassificationLossFunction - { - /// - /// Margin value - /// - [Obsolete] - public float Margin { get; set; } = 1f; + public float Margin { get; set; } = 1f; - [Obsolete] - internal override string ComponentName => "HingeLoss"; - } + [Obsolete] + internal override string ComponentName => "HingeLoss"; + } - /// - /// Log loss. - /// + /// + /// Log loss. + /// + [Obsolete] + public sealed class LogLossClassificationLossFunction : ClassificationLossFunction + { [Obsolete] - public sealed class LogLossClassificationLossFunction : ClassificationLossFunction - { - [Obsolete] - internal override string ComponentName => "LogLoss"; - } + internal override string ComponentName => "LogLoss"; + } + /// + /// Smoothed Hinge loss. + /// + [Obsolete] + public sealed class SmoothedHingeLossClassificationLossFunction : ClassificationLossFunction + { /// - /// Smoothed Hinge loss. + /// Smoothing constant /// [Obsolete] - public sealed class SmoothedHingeLossClassificationLossFunction : ClassificationLossFunction - { - /// - /// Smoothing constant - /// - [Obsolete] - public float SmoothingConst { get; set; } = 1f; - - [Obsolete] - internal override string ComponentName => "SmoothedHingeLoss"; - } + public float SmoothingConst { get; set; } = 1f; [Obsolete] - public abstract class EarlyStoppingCriterion : ComponentKind {} + internal override string ComponentName => "SmoothedHingeLoss"; + } + [Obsolete] + public abstract class EarlyStoppingCriterion : ComponentKind {} + + /// + /// Stop in case of loss of generality. + /// + [Obsolete] + public sealed class GLEarlyStoppingCriterion : EarlyStoppingCriterion + { /// - /// Stop in case of loss of generality. + /// Threshold in range [0,1]. /// + [TlcModule.Range(Min = 0f, Max = 1f)] [Obsolete] - public sealed class GLEarlyStoppingCriterion : EarlyStoppingCriterion - { - /// - /// Threshold in range [0,1]. - /// - [TlcModule.Range(Min = 0f, Max = 1f)] - [Obsolete] - public float Threshold { get; set; } = 0.01f; + public float Threshold { get; set; } = 0.01f; - [Obsolete] - internal override string ComponentName => "GL"; - } + [Obsolete] + internal override string ComponentName => "GL"; + } + /// + /// Stops in case of low progress. + /// + [Obsolete] + public sealed class LPEarlyStoppingCriterion : EarlyStoppingCriterion + { /// - /// Stops in case of low progress. + /// Threshold in range [0,1]. /// + [TlcModule.Range(Min = 0f, Max = 1f)] [Obsolete] - public sealed class LPEarlyStoppingCriterion : EarlyStoppingCriterion - { - /// - /// Threshold in range [0,1]. - /// - [TlcModule.Range(Min = 0f, Max = 1f)] - [Obsolete] - public float Threshold { get; set; } = 0.01f; + public float Threshold { get; set; } = 0.01f; - /// - /// The window size. - /// - [TlcModule.Range(Inf = 0)] - [Obsolete] - public int WindowSize { get; set; } = 5; + /// + /// The window size. + /// + [TlcModule.Range(Inf = 0)] + [Obsolete] + public int WindowSize { get; set; } = 5; - [Obsolete] - internal override string ComponentName => "LP"; - } + [Obsolete] + internal override string ComponentName => "LP"; + } + /// + /// Stops in case of generality to progress ration exceeds threshold. + /// + [Obsolete] + public sealed class PQEarlyStoppingCriterion : EarlyStoppingCriterion + { /// - /// Stops in case of generality to progress ration exceeds threshold. + /// Threshold in range [0,1]. /// + [TlcModule.Range(Min = 0f, Max = 1f)] [Obsolete] - public sealed class PQEarlyStoppingCriterion : EarlyStoppingCriterion - { - /// - /// Threshold in range [0,1]. - /// - [TlcModule.Range(Min = 0f, Max = 1f)] - [Obsolete] - public float Threshold { get; set; } = 0.01f; + public float Threshold { get; set; } = 0.01f; - /// - /// The window size. - /// - [TlcModule.Range(Inf = 0)] - [Obsolete] - public int WindowSize { get; set; } = 5; + /// + /// The window size. + /// + [TlcModule.Range(Inf = 0)] + [Obsolete] + public int WindowSize { get; set; } = 5; - [Obsolete] - internal override string ComponentName => "PQ"; - } + [Obsolete] + internal override string ComponentName => "PQ"; + } + /// + /// Stop if validation score exceeds threshold value. + /// + [Obsolete] + public sealed class TREarlyStoppingCriterion : EarlyStoppingCriterion + { /// - /// Stop if validation score exceeds threshold value. + /// Tolerance threshold. (Non negative value) /// + [TlcModule.Range(Min = 0f)] [Obsolete] - public sealed class TREarlyStoppingCriterion : EarlyStoppingCriterion - { - /// - /// Tolerance threshold. (Non negative value) - /// - [TlcModule.Range(Min = 0f)] - [Obsolete] - public float Threshold { get; set; } = 0.01f; + public float Threshold { get; set; } = 0.01f; - [Obsolete] - internal override string ComponentName => "TR"; - } + [Obsolete] + internal override string ComponentName => "TR"; + } + /// + /// Stops in case of consecutive loss in generality. + /// + [Obsolete] + public sealed class UPEarlyStoppingCriterion : EarlyStoppingCriterion + { /// - /// Stops in case of consecutive loss in generality. + /// The window size. /// + [TlcModule.Range(Inf = 0)] [Obsolete] - public sealed class UPEarlyStoppingCriterion : EarlyStoppingCriterion - { - /// - /// The window size. - /// - [TlcModule.Range(Inf = 0)] - [Obsolete] - public int WindowSize { get; set; } = 5; - - [Obsolete] - internal override string ComponentName => "UP"; - } + public int WindowSize { get; set; } = 5; [Obsolete] - public abstract class EnsembleBinaryDiversityMeasure : ComponentKind {} + internal override string ComponentName => "UP"; + } + [Obsolete] + public abstract class EnsembleBinaryDiversityMeasure : ComponentKind {} - [Obsolete] - public sealed class DisagreementDiversityMeasureEnsembleBinaryDiversityMeasure : EnsembleBinaryDiversityMeasure - { - [Obsolete] - internal override string ComponentName => "DisagreementDiversityMeasure"; - } + [Obsolete] + public sealed class DisagreementDiversityMeasureEnsembleBinaryDiversityMeasure : EnsembleBinaryDiversityMeasure + { [Obsolete] - public abstract class EnsembleBinaryOutputCombiner : ComponentKind {} + internal override string ComponentName => "DisagreementDiversityMeasure"; + } + [Obsolete] + public abstract class EnsembleBinaryOutputCombiner : ComponentKind {} + + [Obsolete] + public sealed class AverageEnsembleBinaryOutputCombiner : EnsembleBinaryOutputCombiner + { [Obsolete] - public sealed class AverageEnsembleBinaryOutputCombiner : EnsembleBinaryOutputCombiner - { - [Obsolete] - internal override string ComponentName => "Average"; - } + internal override string ComponentName => "Average"; + } + [Obsolete] + public sealed class MedianEnsembleBinaryOutputCombiner : EnsembleBinaryOutputCombiner + { [Obsolete] - public sealed class MedianEnsembleBinaryOutputCombiner : EnsembleBinaryOutputCombiner - { - [Obsolete] - internal override string ComponentName => "Median"; - } + internal override string ComponentName => "Median"; + } + [Obsolete] + public sealed class StackingEnsembleBinaryOutputCombiner : EnsembleBinaryOutputCombiner + { + /// + /// The proportion of instances to be selected to test the individual base learner. If it is 0, it uses training set + /// [Obsolete] - public sealed class StackingEnsembleBinaryOutputCombiner : EnsembleBinaryOutputCombiner - { - /// - /// The proportion of instances to be selected to test the individual base learner. If it is 0, it uses training set - /// - [Obsolete] - public float ValidationDatasetProportion { get; set; } = 0.3f; + public float ValidationDatasetProportion { get; set; } = 0.3f; - [Obsolete] - internal override string ComponentName => "Stacking"; - } + [Obsolete] + internal override string ComponentName => "Stacking"; + } + [Obsolete] + public sealed class VotingEnsembleBinaryOutputCombiner : EnsembleBinaryOutputCombiner + { [Obsolete] - public sealed class VotingEnsembleBinaryOutputCombiner : EnsembleBinaryOutputCombiner - { - [Obsolete] - internal override string ComponentName => "Voting"; - } + internal override string ComponentName => "Voting"; + } - [Obsolete] - public enum WeightageKind - { - Accuracy = 0, - Auc = 1, - PosPrecision = 2, - PosRecall = 3, - NegPrecision = 4, - NegRecall = 5 - } + [Obsolete] + public enum WeightageKind + { + Accuracy = 0, + Auc = 1, + PosPrecision = 2, + PosRecall = 3, + NegPrecision = 4, + NegRecall = 5 + } + [Obsolete] + public sealed class WeightedAverageEnsembleBinaryOutputCombiner : EnsembleBinaryOutputCombiner + { + /// + /// The metric type to be used to find the weights for each model + /// [Obsolete] - public sealed class WeightedAverageEnsembleBinaryOutputCombiner : EnsembleBinaryOutputCombiner - { - /// - /// The metric type to be used to find the weights for each model - /// - [Obsolete] - public WeightageKind WeightageName { get; set; } = WeightageKind.Auc; + public WeightageKind WeightageName { get; set; } = WeightageKind.Auc; + + [Obsolete] + internal override string ComponentName => "WeightedAverage"; + } + + [Obsolete] + public abstract class EnsembleBinarySubModelSelector : ComponentKind {} + - [Obsolete] - internal override string ComponentName => "WeightedAverage"; - } + [Obsolete] + public sealed class AllSelectorEnsembleBinarySubModelSelector : EnsembleBinarySubModelSelector + { [Obsolete] - public abstract class EnsembleBinarySubModelSelector : ComponentKind {} + internal override string ComponentName => "AllSelector"; + } + [Obsolete] + public sealed class BestDiverseSelectorEnsembleBinarySubModelSelector : EnsembleBinarySubModelSelector + { + /// + /// The metric type to be used to find the diversity among base learners + /// + [JsonConverter(typeof(ComponentSerializer))] [Obsolete] - public sealed class AllSelectorEnsembleBinarySubModelSelector : EnsembleBinarySubModelSelector - { - [Obsolete] - internal override string ComponentName => "AllSelector"; - } + public EnsembleBinaryDiversityMeasure DiversityMetricType { get; set; } = new DisagreementDiversityMeasureEnsembleBinaryDiversityMeasure(); + /// + /// The proportion of best base learners to be selected. The range is 0.0-1.0 + /// + [Obsolete] + public float LearnersSelectionProportion { get; set; } = 0.5f; + /// + /// The proportion of instances to be selected to test the individual base learner. If it is 0, it uses training set + /// + [Obsolete] + public float ValidationDatasetProportion { get; set; } = 0.3f; [Obsolete] - public sealed class BestDiverseSelectorEnsembleBinarySubModelSelector : EnsembleBinarySubModelSelector - { - /// - /// The metric type to be used to find the diversity among base learners - /// - [JsonConverter(typeof(ComponentSerializer))] - [Obsolete] - public EnsembleBinaryDiversityMeasure DiversityMetricType { get; set; } = new DisagreementDiversityMeasureEnsembleBinaryDiversityMeasure(); + internal override string ComponentName => "BestDiverseSelector"; + } - /// - /// The proportion of best base learners to be selected. The range is 0.0-1.0 - /// - [Obsolete] - public float LearnersSelectionProportion { get; set; } = 0.5f; + [Obsolete] + public enum BinaryClassifierEvaluatorMetrics + { + Accuracy = 0, + PosPrecName = 1, + PosRecallName = 2, + NegPrecName = 3, + NegRecallName = 4, + Auc = 5, + LogLoss = 6, + LogLossReduction = 7, + F1 = 8, + AuPrc = 9 + } - /// - /// The proportion of instances to be selected to test the individual base learner. If it is 0, it uses training set - /// - [Obsolete] - public float ValidationDatasetProportion { get; set; } = 0.3f; - [Obsolete] - internal override string ComponentName => "BestDiverseSelector"; - } + [Obsolete] + public sealed class BestPerformanceSelectorEnsembleBinarySubModelSelector : EnsembleBinarySubModelSelector + { + /// + /// The metric type to be used to find the best performance + /// [Obsolete] - public enum BinaryClassifierEvaluatorMetrics - { - Accuracy = 0, - PosPrecName = 1, - PosRecallName = 2, - NegPrecName = 3, - NegRecallName = 4, - Auc = 5, - LogLoss = 6, - LogLossReduction = 7, - F1 = 8, - AuPrc = 9 - } + public BinaryClassifierEvaluatorMetrics MetricName { get; set; } = BinaryClassifierEvaluatorMetrics.Auc; + /// + /// The proportion of best base learners to be selected. The range is 0.0-1.0 + /// + [Obsolete] + public float LearnersSelectionProportion { get; set; } = 0.5f; + /// + /// The proportion of instances to be selected to test the individual base learner. If it is 0, it uses training set + /// + [Obsolete] + public float ValidationDatasetProportion { get; set; } = 0.3f; [Obsolete] - public sealed class BestPerformanceSelectorEnsembleBinarySubModelSelector : EnsembleBinarySubModelSelector - { - /// - /// The metric type to be used to find the best performance - /// - [Obsolete] - public BinaryClassifierEvaluatorMetrics MetricName { get; set; } = BinaryClassifierEvaluatorMetrics.Auc; + internal override string ComponentName => "BestPerformanceSelector"; + } - /// - /// The proportion of best base learners to be selected. The range is 0.0-1.0 - /// - [Obsolete] - public float LearnersSelectionProportion { get; set; } = 0.5f; + [Obsolete] + public abstract class EnsembleFeatureSelector : ComponentKind {} - /// - /// The proportion of instances to be selected to test the individual base learner. If it is 0, it uses training set - /// - [Obsolete] - public float ValidationDatasetProportion { get; set; } = 0.3f; - [Obsolete] - internal override string ComponentName => "BestPerformanceSelector"; - } + [Obsolete] + public sealed class AllFeatureSelectorEnsembleFeatureSelector : EnsembleFeatureSelector + { [Obsolete] - public abstract class EnsembleFeatureSelector : ComponentKind {} + internal override string ComponentName => "AllFeatureSelector"; + } + [Obsolete] + public sealed class RandomFeatureSelectorEnsembleFeatureSelector : EnsembleFeatureSelector + { + /// + /// The proportion of features to be selected. The range is 0.0-1.0 + /// [Obsolete] - public sealed class AllFeatureSelectorEnsembleFeatureSelector : EnsembleFeatureSelector - { - [Obsolete] - internal override string ComponentName => "AllFeatureSelector"; - } + public float FeaturesSelectionProportion { get; set; } = 0.8f; + [Obsolete] + internal override string ComponentName => "RandomFeatureSelector"; + } + [Obsolete] + public abstract class EnsembleMulticlassDiversityMeasure : ComponentKind {} - [Obsolete] - public sealed class RandomFeatureSelectorEnsembleFeatureSelector : EnsembleFeatureSelector - { - /// - /// The proportion of features to be selected. The range is 0.0-1.0 - /// - [Obsolete] - public float FeaturesSelectionProportion { get; set; } = 0.8f; - [Obsolete] - internal override string ComponentName => "RandomFeatureSelector"; - } + [Obsolete] + public sealed class MultiDisagreementDiversityMeasureEnsembleMulticlassDiversityMeasure : EnsembleMulticlassDiversityMeasure + { [Obsolete] - public abstract class EnsembleMulticlassDiversityMeasure : ComponentKind {} + internal override string ComponentName => "MultiDisagreementDiversityMeasure"; + } + + [Obsolete] + public abstract class EnsembleMulticlassOutputCombiner : ComponentKind {} + [Obsolete] + public sealed class MultiAverageEnsembleMulticlassOutputCombiner : EnsembleMulticlassOutputCombiner + { + /// + /// Whether to normalize the output of base models before combining them + /// [Obsolete] - public sealed class MultiDisagreementDiversityMeasureEnsembleMulticlassDiversityMeasure : EnsembleMulticlassDiversityMeasure - { - [Obsolete] - internal override string ComponentName => "MultiDisagreementDiversityMeasure"; - } + public bool Normalize { get; set; } = true; [Obsolete] - public abstract class EnsembleMulticlassOutputCombiner : ComponentKind {} + internal override string ComponentName => "MultiAverage"; + } + [Obsolete] + public sealed class MultiMedianEnsembleMulticlassOutputCombiner : EnsembleMulticlassOutputCombiner + { + /// + /// Whether to normalize the output of base models before combining them + /// [Obsolete] - public sealed class MultiAverageEnsembleMulticlassOutputCombiner : EnsembleMulticlassOutputCombiner - { - /// - /// Whether to normalize the output of base models before combining them - /// - [Obsolete] - public bool Normalize { get; set; } = true; + public bool Normalize { get; set; } = true; - [Obsolete] - internal override string ComponentName => "MultiAverage"; - } + [Obsolete] + internal override string ComponentName => "MultiMedian"; + } + [Obsolete] + public sealed class MultiStackingEnsembleMulticlassOutputCombiner : EnsembleMulticlassOutputCombiner + { + /// + /// The proportion of instances to be selected to test the individual base learner. If it is 0, it uses training set + /// [Obsolete] - public sealed class MultiMedianEnsembleMulticlassOutputCombiner : EnsembleMulticlassOutputCombiner - { - /// - /// Whether to normalize the output of base models before combining them - /// - [Obsolete] - public bool Normalize { get; set; } = true; + public float ValidationDatasetProportion { get; set; } = 0.3f; - [Obsolete] - internal override string ComponentName => "MultiMedian"; - } + [Obsolete] + internal override string ComponentName => "MultiStacking"; + } + [Obsolete] + public sealed class MultiVotingEnsembleMulticlassOutputCombiner : EnsembleMulticlassOutputCombiner + { [Obsolete] - public sealed class MultiStackingEnsembleMulticlassOutputCombiner : EnsembleMulticlassOutputCombiner - { - /// - /// The proportion of instances to be selected to test the individual base learner. If it is 0, it uses training set - /// - [Obsolete] - public float ValidationDatasetProportion { get; set; } = 0.3f; + internal override string ComponentName => "MultiVoting"; + } - [Obsolete] - internal override string ComponentName => "MultiStacking"; - } + [Obsolete] + public enum MultiWeightageKind + { + AccuracyMicroAvg = 0, + AccuracyMacroAvg = 1 + } + [Obsolete] + public sealed class MultiWeightedAverageEnsembleMulticlassOutputCombiner : EnsembleMulticlassOutputCombiner + { + /// + /// The metric type to be used to find the weights for each model + /// [Obsolete] - public sealed class MultiVotingEnsembleMulticlassOutputCombiner : EnsembleMulticlassOutputCombiner - { - [Obsolete] - internal override string ComponentName => "MultiVoting"; - } + public MultiWeightageKind WeightageName { get; set; } = MultiWeightageKind.AccuracyMicroAvg; + /// + /// Whether to normalize the output of base models before combining them + /// [Obsolete] - public enum MultiWeightageKind - { - AccuracyMicroAvg = 0, - AccuracyMacroAvg = 1 - } - - + public bool Normalize { get; set; } = true; [Obsolete] - public sealed class MultiWeightedAverageEnsembleMulticlassOutputCombiner : EnsembleMulticlassOutputCombiner - { - /// - /// The metric type to be used to find the weights for each model - /// - [Obsolete] - public MultiWeightageKind WeightageName { get; set; } = MultiWeightageKind.AccuracyMicroAvg; + internal override string ComponentName => "MultiWeightedAverage"; + } - /// - /// Whether to normalize the output of base models before combining them - /// - [Obsolete] - public bool Normalize { get; set; } = true; + [Obsolete] + public abstract class EnsembleMulticlassSubModelSelector : ComponentKind {} - [Obsolete] - internal override string ComponentName => "MultiWeightedAverage"; - } + + [Obsolete] + public sealed class AllSelectorMultiClassEnsembleMulticlassSubModelSelector : EnsembleMulticlassSubModelSelector + { [Obsolete] - public abstract class EnsembleMulticlassSubModelSelector : ComponentKind {} + internal override string ComponentName => "AllSelectorMultiClass"; + } + [Obsolete] + public sealed class BestDiverseSelectorMultiClassEnsembleMulticlassSubModelSelector : EnsembleMulticlassSubModelSelector + { + /// + /// The metric type to be used to find the diversity among base learners + /// + [JsonConverter(typeof(ComponentSerializer))] [Obsolete] - public sealed class AllSelectorMultiClassEnsembleMulticlassSubModelSelector : EnsembleMulticlassSubModelSelector - { - [Obsolete] - internal override string ComponentName => "AllSelectorMultiClass"; - } + public EnsembleMulticlassDiversityMeasure DiversityMetricType { get; set; } = new MultiDisagreementDiversityMeasureEnsembleMulticlassDiversityMeasure(); + /// + /// The proportion of best base learners to be selected. The range is 0.0-1.0 + /// + [Obsolete] + public float LearnersSelectionProportion { get; set; } = 0.5f; + /// + /// The proportion of instances to be selected to test the individual base learner. If it is 0, it uses training set + /// + [Obsolete] + public float ValidationDatasetProportion { get; set; } = 0.3f; [Obsolete] - public sealed class BestDiverseSelectorMultiClassEnsembleMulticlassSubModelSelector : EnsembleMulticlassSubModelSelector - { - /// - /// The metric type to be used to find the diversity among base learners - /// - [JsonConverter(typeof(ComponentSerializer))] - [Obsolete] - public EnsembleMulticlassDiversityMeasure DiversityMetricType { get; set; } = new MultiDisagreementDiversityMeasureEnsembleMulticlassDiversityMeasure(); + internal override string ComponentName => "BestDiverseSelectorMultiClass"; + } - /// - /// The proportion of best base learners to be selected. The range is 0.0-1.0 - /// - [Obsolete] - public float LearnersSelectionProportion { get; set; } = 0.5f; + [Obsolete] + public enum MultiClassClassifierEvaluatorMetrics + { + AccuracyMicro = 0, + AccuracyMacro = 1, + LogLoss = 2, + LogLossReduction = 3 + } - /// - /// The proportion of instances to be selected to test the individual base learner. If it is 0, it uses training set - /// - [Obsolete] - public float ValidationDatasetProportion { get; set; } = 0.3f; - [Obsolete] - internal override string ComponentName => "BestDiverseSelectorMultiClass"; - } + [Obsolete] + public sealed class BestPerformanceSelectorMultiClassEnsembleMulticlassSubModelSelector : EnsembleMulticlassSubModelSelector + { + /// + /// The metric type to be used to find the best performance + /// [Obsolete] - public enum MultiClassClassifierEvaluatorMetrics - { - AccuracyMicro = 0, - AccuracyMacro = 1, - LogLoss = 2, - LogLossReduction = 3 - } + public MultiClassClassifierEvaluatorMetrics MetricName { get; set; } = MultiClassClassifierEvaluatorMetrics.AccuracyMicro; + /// + /// The proportion of best base learners to be selected. The range is 0.0-1.0 + /// + [Obsolete] + public float LearnersSelectionProportion { get; set; } = 0.5f; + /// + /// The proportion of instances to be selected to test the individual base learner. If it is 0, it uses training set + /// + [Obsolete] + public float ValidationDatasetProportion { get; set; } = 0.3f; [Obsolete] - public sealed class BestPerformanceSelectorMultiClassEnsembleMulticlassSubModelSelector : EnsembleMulticlassSubModelSelector - { - /// - /// The metric type to be used to find the best performance - /// - [Obsolete] - public MultiClassClassifierEvaluatorMetrics MetricName { get; set; } = MultiClassClassifierEvaluatorMetrics.AccuracyMicro; + internal override string ComponentName => "BestPerformanceSelectorMultiClass"; + } - /// - /// The proportion of best base learners to be selected. The range is 0.0-1.0 - /// - [Obsolete] - public float LearnersSelectionProportion { get; set; } = 0.5f; + [Obsolete] + public abstract class EnsembleRegressionDiversityMeasure : ComponentKind {} - /// - /// The proportion of instances to be selected to test the individual base learner. If it is 0, it uses training set - /// - [Obsolete] - public float ValidationDatasetProportion { get; set; } = 0.3f; - [Obsolete] - internal override string ComponentName => "BestPerformanceSelectorMultiClass"; - } + [Obsolete] + public sealed class RegressionDisagreementDiversityMeasureEnsembleRegressionDiversityMeasure : EnsembleRegressionDiversityMeasure + { [Obsolete] - public abstract class EnsembleRegressionDiversityMeasure : ComponentKind {} + internal override string ComponentName => "RegressionDisagreementDiversityMeasure"; + } + [Obsolete] + public abstract class EnsembleRegressionOutputCombiner : ComponentKind {} - [Obsolete] - public sealed class RegressionDisagreementDiversityMeasureEnsembleRegressionDiversityMeasure : EnsembleRegressionDiversityMeasure - { - [Obsolete] - internal override string ComponentName => "RegressionDisagreementDiversityMeasure"; - } + [Obsolete] + public sealed class AverageEnsembleRegressionOutputCombiner : EnsembleRegressionOutputCombiner + { [Obsolete] - public abstract class EnsembleRegressionOutputCombiner : ComponentKind {} + internal override string ComponentName => "Average"; + } + [Obsolete] + public sealed class MedianEnsembleRegressionOutputCombiner : EnsembleRegressionOutputCombiner + { [Obsolete] - public sealed class AverageEnsembleRegressionOutputCombiner : EnsembleRegressionOutputCombiner - { - [Obsolete] - internal override string ComponentName => "Average"; - } + internal override string ComponentName => "Median"; + } + [Obsolete] + public sealed class RegressionStackingEnsembleRegressionOutputCombiner : EnsembleRegressionOutputCombiner + { + /// + /// The proportion of instances to be selected to test the individual base learner. If it is 0, it uses training set + /// [Obsolete] - public sealed class MedianEnsembleRegressionOutputCombiner : EnsembleRegressionOutputCombiner - { - [Obsolete] - internal override string ComponentName => "Median"; - } + public float ValidationDatasetProportion { get; set; } = 0.3f; + [Obsolete] + internal override string ComponentName => "RegressionStacking"; + } + [Obsolete] + public abstract class EnsembleRegressionSubModelSelector : ComponentKind {} - [Obsolete] - public sealed class RegressionStackingEnsembleRegressionOutputCombiner : EnsembleRegressionOutputCombiner - { - /// - /// The proportion of instances to be selected to test the individual base learner. If it is 0, it uses training set - /// - [Obsolete] - public float ValidationDatasetProportion { get; set; } = 0.3f; - [Obsolete] - internal override string ComponentName => "RegressionStacking"; - } + [Obsolete] + public sealed class AllSelectorEnsembleRegressionSubModelSelector : EnsembleRegressionSubModelSelector + { [Obsolete] - public abstract class EnsembleRegressionSubModelSelector : ComponentKind {} + internal override string ComponentName => "AllSelector"; + } + [Obsolete] + public sealed class BestDiverseSelectorRegressionEnsembleRegressionSubModelSelector : EnsembleRegressionSubModelSelector + { + /// + /// The metric type to be used to find the diversity among base learners + /// + [JsonConverter(typeof(ComponentSerializer))] [Obsolete] - public sealed class AllSelectorEnsembleRegressionSubModelSelector : EnsembleRegressionSubModelSelector - { - [Obsolete] - internal override string ComponentName => "AllSelector"; - } + public EnsembleRegressionDiversityMeasure DiversityMetricType { get; set; } = new RegressionDisagreementDiversityMeasureEnsembleRegressionDiversityMeasure(); + /// + /// The proportion of best base learners to be selected. The range is 0.0-1.0 + /// + [Obsolete] + public float LearnersSelectionProportion { get; set; } = 0.5f; + /// + /// The proportion of instances to be selected to test the individual base learner. If it is 0, it uses training set + /// + [Obsolete] + public float ValidationDatasetProportion { get; set; } = 0.3f; [Obsolete] - public sealed class BestDiverseSelectorRegressionEnsembleRegressionSubModelSelector : EnsembleRegressionSubModelSelector - { - /// - /// The metric type to be used to find the diversity among base learners - /// - [JsonConverter(typeof(ComponentSerializer))] - [Obsolete] - public EnsembleRegressionDiversityMeasure DiversityMetricType { get; set; } = new RegressionDisagreementDiversityMeasureEnsembleRegressionDiversityMeasure(); + internal override string ComponentName => "BestDiverseSelectorRegression"; + } - /// - /// The proportion of best base learners to be selected. The range is 0.0-1.0 - /// - [Obsolete] - public float LearnersSelectionProportion { get; set; } = 0.5f; + [Obsolete] + public enum RegressionEvaluatorMetrics + { + L1 = 0, + L2 = 1, + Rms = 2, + Loss = 3, + RSquared = 4 + } - /// - /// The proportion of instances to be selected to test the individual base learner. If it is 0, it uses training set - /// - [Obsolete] - public float ValidationDatasetProportion { get; set; } = 0.3f; - [Obsolete] - internal override string ComponentName => "BestDiverseSelectorRegression"; - } + [Obsolete] + public sealed class BestPerformanceRegressionSelectorEnsembleRegressionSubModelSelector : EnsembleRegressionSubModelSelector + { + /// + /// The metric type to be used to find the best performance + /// [Obsolete] - public enum RegressionEvaluatorMetrics - { - L1 = 0, - L2 = 1, - Rms = 2, - Loss = 3, - RSquared = 4 - } + public RegressionEvaluatorMetrics MetricName { get; set; } = RegressionEvaluatorMetrics.L1; + /// + /// The proportion of best base learners to be selected. The range is 0.0-1.0 + /// + [Obsolete] + public float LearnersSelectionProportion { get; set; } = 0.5f; + /// + /// The proportion of instances to be selected to test the individual base learner. If it is 0, it uses training set + /// + [Obsolete] + public float ValidationDatasetProportion { get; set; } = 0.3f; [Obsolete] - public sealed class BestPerformanceRegressionSelectorEnsembleRegressionSubModelSelector : EnsembleRegressionSubModelSelector - { - /// - /// The metric type to be used to find the best performance - /// - [Obsolete] - public RegressionEvaluatorMetrics MetricName { get; set; } = RegressionEvaluatorMetrics.L1; + internal override string ComponentName => "BestPerformanceRegressionSelector"; + } - /// - /// The proportion of best base learners to be selected. The range is 0.0-1.0 - /// - [Obsolete] - public float LearnersSelectionProportion { get; set; } = 0.5f; + [Obsolete] + public abstract class EnsembleSubsetSelector : ComponentKind {} - /// - /// The proportion of instances to be selected to test the individual base learner. If it is 0, it uses training set - /// - [Obsolete] - public float ValidationDatasetProportion { get; set; } = 0.3f; - [Obsolete] - internal override string ComponentName => "BestPerformanceRegressionSelector"; - } + + [Obsolete] + public sealed class AllInstanceSelectorEnsembleSubsetSelector : EnsembleSubsetSelector + { + /// + /// The Feature selector + /// + [JsonConverter(typeof(ComponentSerializer))] + [Obsolete] + public EnsembleFeatureSelector FeatureSelector { get; set; } = new AllFeatureSelectorEnsembleFeatureSelector(); [Obsolete] - public abstract class EnsembleSubsetSelector : ComponentKind {} + internal override string ComponentName => "AllInstanceSelector"; + } + [Obsolete] + public sealed class BootstrapSelectorEnsembleSubsetSelector : EnsembleSubsetSelector + { + /// + /// The Feature selector + /// + [JsonConverter(typeof(ComponentSerializer))] [Obsolete] - public sealed class AllInstanceSelectorEnsembleSubsetSelector : EnsembleSubsetSelector - { - /// - /// The Feature selector - /// - [JsonConverter(typeof(ComponentSerializer))] - [Obsolete] - public EnsembleFeatureSelector FeatureSelector { get; set; } = new AllFeatureSelectorEnsembleFeatureSelector(); + public EnsembleFeatureSelector FeatureSelector { get; set; } = new AllFeatureSelectorEnsembleFeatureSelector(); + + [Obsolete] + internal override string ComponentName => "BootstrapSelector"; + } - [Obsolete] - internal override string ComponentName => "AllInstanceSelector"; - } + [Obsolete] + public sealed class RandomPartitionSelectorEnsembleSubsetSelector : EnsembleSubsetSelector + { + /// + /// The Feature selector + /// + [JsonConverter(typeof(ComponentSerializer))] + [Obsolete] + public EnsembleFeatureSelector FeatureSelector { get; set; } = new AllFeatureSelectorEnsembleFeatureSelector(); [Obsolete] - public sealed class BootstrapSelectorEnsembleSubsetSelector : EnsembleSubsetSelector - { - /// - /// The Feature selector - /// - [JsonConverter(typeof(ComponentSerializer))] - [Obsolete] - public EnsembleFeatureSelector FeatureSelector { get; set; } = new AllFeatureSelectorEnsembleFeatureSelector(); + internal override string ComponentName => "RandomPartitionSelector"; + } - [Obsolete] - internal override string ComponentName => "BootstrapSelector"; - } + [Obsolete] + public abstract class FastTreeTrainer : ComponentKind {} + /// + /// Uses a logit-boost boosted tree learner to perform binary classification. + /// + [Obsolete] + public sealed class FastTreeBinaryClassificationFastTreeTrainer : FastTreeTrainer + { + /// + /// Should we use derivatives optimized for unbalanced sets + /// [Obsolete] - public sealed class RandomPartitionSelectorEnsembleSubsetSelector : EnsembleSubsetSelector - { - /// - /// The Feature selector - /// - [JsonConverter(typeof(ComponentSerializer))] - [Obsolete] - public EnsembleFeatureSelector FeatureSelector { get; set; } = new AllFeatureSelectorEnsembleFeatureSelector(); + public bool UnbalancedSets { get; set; } = false; - [Obsolete] - internal override string ComponentName => "RandomPartitionSelector"; - } + /// + /// Use best regression step trees? + /// + [Obsolete] + public bool BestStepRankingRegressionTrees { get; set; } = false; + /// + /// Should we use line search for a step size + /// [Obsolete] - public abstract class FastTreeTrainer : ComponentKind {} + public bool UseLineSearch { get; set; } = false; + /// + /// Number of post-bracket line search steps + /// + [Obsolete] + public int NumPostBracketSteps { get; set; } + /// + /// Minimum line search step size + /// + [Obsolete] + public double MinStepSize { get; set; } /// - /// Uses a logit-boost boosted tree learner to perform binary classification. + /// Optimization algorithm to be used (GradientDescent, AcceleratedGradientDescent) /// [Obsolete] - public sealed class FastTreeBinaryClassificationFastTreeTrainer : FastTreeTrainer - { - /// - /// Should we use derivatives optimized for unbalanced sets - /// - [Obsolete] - public bool UnbalancedSets { get; set; } = false; + public Microsoft.ML.Legacy.Trainers.BoostedTreeArgsOptimizationAlgorithmType OptimizationAlgorithm { get; set; } = Microsoft.ML.Legacy.Trainers.BoostedTreeArgsOptimizationAlgorithmType.GradientDescent; - /// - /// Use best regression step trees? - /// - [Obsolete] - public bool BestStepRankingRegressionTrees { get; set; } = false; + /// + /// Early stopping rule. (Validation set (/valid) is required.) + /// + [JsonConverter(typeof(ComponentSerializer))] + [Obsolete] + public EarlyStoppingCriterion EarlyStoppingRule { get; set; } - /// - /// Should we use line search for a step size - /// - [Obsolete] - public bool UseLineSearch { get; set; } = false; + /// + /// Early stopping metrics. (For regression, 1: L1, 2:L2; for ranking, 1:NDCG@1, 3:NDCG@3) + /// + [Obsolete] + public int EarlyStoppingMetrics { get; set; } - /// - /// Number of post-bracket line search steps - /// - [Obsolete] - public int NumPostBracketSteps { get; set; } + /// + /// Enable post-training pruning to avoid overfitting. (a validation set is required) + /// + [Obsolete] + public bool EnablePruning { get; set; } = false; - /// - /// Minimum line search step size - /// - [Obsolete] - public double MinStepSize { get; set; } + /// + /// Use window and tolerance for pruning + /// + [Obsolete] + public bool UseTolerantPruning { get; set; } = false; - /// - /// Optimization algorithm to be used (GradientDescent, AcceleratedGradientDescent) - /// - [Obsolete] - public Microsoft.ML.Legacy.Trainers.BoostedTreeArgsOptimizationAlgorithmType OptimizationAlgorithm { get; set; } = Microsoft.ML.Legacy.Trainers.BoostedTreeArgsOptimizationAlgorithmType.GradientDescent; + /// + /// The tolerance threshold for pruning + /// + [Obsolete] + public double PruningThreshold { get; set; } = 0.004d; - /// - /// Early stopping rule. (Validation set (/valid) is required.) - /// - [JsonConverter(typeof(ComponentSerializer))] - [Obsolete] - public EarlyStoppingCriterion EarlyStoppingRule { get; set; } + /// + /// The moving window size for pruning + /// + [Obsolete] + public int PruningWindowSize { get; set; } = 5; - /// - /// Early stopping metrics. (For regression, 1: L1, 2:L2; for ranking, 1:NDCG@1, 3:NDCG@3) - /// - [Obsolete] - public int EarlyStoppingMetrics { get; set; } + /// + /// The learning rate + /// + [TlcModule.SweepableFloatParamAttribute("LearningRates", 0.025f, 0.4f, isLogScale:true)] + [Obsolete] + public double LearningRates { get; set; } = 0.2d; - /// - /// Enable post-training pruning to avoid overfitting. (a validation set is required) - /// - [Obsolete] - public bool EnablePruning { get; set; } = false; + /// + /// Shrinkage + /// + [TlcModule.SweepableFloatParamAttribute("Shrinkage", 0.025f, 4f, isLogScale:true)] + [Obsolete] + public double Shrinkage { get; set; } = 1d; - /// - /// Use window and tolerance for pruning - /// - [Obsolete] - public bool UseTolerantPruning { get; set; } = false; + /// + /// Dropout rate for tree regularization + /// + [TlcModule.SweepableDiscreteParamAttribute("DropoutRate", new object[]{0f, 1E-09f, 0.05f, 0.1f, 0.2f})] + [Obsolete] + public double DropoutRate { get; set; } - /// - /// The tolerance threshold for pruning - /// - [Obsolete] - public double PruningThreshold { get; set; } = 0.004d; + /// + /// Sample each query 1 in k times in the GetDerivatives function + /// + [Obsolete] + public int GetDerivativesSampleRate { get; set; } = 1; - /// - /// The moving window size for pruning - /// - [Obsolete] - public int PruningWindowSize { get; set; } = 5; + /// + /// Write the last ensemble instead of the one determined by early stopping + /// + [Obsolete] + public bool WriteLastEnsemble { get; set; } = false; - /// - /// The learning rate - /// - [TlcModule.SweepableFloatParamAttribute("LearningRates", 0.025f, 0.4f, isLogScale:true)] - [Obsolete] - public double LearningRates { get; set; } = 0.2d; + /// + /// Upper bound on absolute value of single tree output + /// + [Obsolete] + public double MaxTreeOutput { get; set; } = 100d; - /// - /// Shrinkage - /// - [TlcModule.SweepableFloatParamAttribute("Shrinkage", 0.025f, 4f, isLogScale:true)] - [Obsolete] - public double Shrinkage { get; set; } = 1d; + /// + /// Training starts from random ordering (determined by /r1) + /// + [Obsolete] + public bool RandomStart { get; set; } = false; - /// - /// Dropout rate for tree regularization - /// - [TlcModule.SweepableDiscreteParamAttribute("DropoutRate", new object[]{0f, 1E-09f, 0.05f, 0.1f, 0.2f})] - [Obsolete] - public double DropoutRate { get; set; } + /// + /// Filter zero lambdas during training + /// + [Obsolete] + public bool FilterZeroLambdas { get; set; } = false; - /// - /// Sample each query 1 in k times in the GetDerivatives function - /// - [Obsolete] - public int GetDerivativesSampleRate { get; set; } = 1; + /// + /// Freeform defining the scores that should be used as the baseline ranker + /// + [Obsolete] + public string BaselineScoresFormula { get; set; } - /// - /// Write the last ensemble instead of the one determined by early stopping - /// - [Obsolete] - public bool WriteLastEnsemble { get; set; } = false; + /// + /// Baseline alpha for tradeoffs of risk (0 is normal training) + /// + [Obsolete] + public string BaselineAlphaRisk { get; set; } - /// - /// Upper bound on absolute value of single tree output - /// - [Obsolete] - public double MaxTreeOutput { get; set; } = 100d; + /// + /// The discount freeform which specifies the per position discounts of documents in a query (uses a single variable P for position where P=0 is first position) + /// + [Obsolete] + public string PositionDiscountFreeform { get; set; } - /// - /// Training starts from random ordering (determined by /r1) - /// - [Obsolete] - public bool RandomStart { get; set; } = false; - - /// - /// Filter zero lambdas during training - /// - [Obsolete] - public bool FilterZeroLambdas { get; set; } = false; - - /// - /// Freeform defining the scores that should be used as the baseline ranker - /// - [Obsolete] - public string BaselineScoresFormula { get; set; } - - /// - /// Baseline alpha for tradeoffs of risk (0 is normal training) - /// - [Obsolete] - public string BaselineAlphaRisk { get; set; } - - /// - /// The discount freeform which specifies the per position discounts of documents in a query (uses a single variable P for position where P=0 is first position) - /// - [Obsolete] - public string PositionDiscountFreeform { get; set; } - - /// - /// Allows to choose Parallel FastTree Learning Algorithm - /// - [JsonConverter(typeof(ComponentSerializer))] - [Obsolete] - public ParallelTraining ParallelTrainer { get; set; } = new SingleParallelTraining(); - - /// - /// The number of threads to use - /// - [Obsolete] - public int? NumThreads { get; set; } - - /// - /// The seed of the random number generator - /// - [Obsolete] - public int RngSeed { get; set; } = 123; - - /// - /// The seed of the active feature selection - /// - [Obsolete] - public int FeatureSelectSeed { get; set; } = 123; - - /// - /// The entropy (regularization) coefficient between 0 and 1 - /// - [Obsolete] - public double EntropyCoefficient { get; set; } - - /// - /// The number of histograms in the pool (between 2 and numLeaves) - /// - [Obsolete] - public int HistogramPoolSize { get; set; } = -1; - - /// - /// Whether to utilize the disk or the data's native transposition facilities (where applicable) when performing the transpose - /// - [Obsolete] - public bool? DiskTranspose { get; set; } - - /// - /// Whether to collectivize features during dataset preparation to speed up training - /// - [Obsolete] - public bool FeatureFlocks { get; set; } = true; - - /// - /// Whether to do split based on multiple categorical feature values. - /// - [Obsolete] - public bool CategoricalSplit { get; set; } = false; - - /// - /// Maximum categorical split groups to consider when splitting on a categorical feature. Split groups are a collection of split points. This is used to reduce overfitting when there many categorical features. - /// - [Obsolete] - public int MaxCategoricalGroupsPerNode { get; set; } = 64; - - /// - /// Maximum categorical split points to consider when splitting on a categorical feature. - /// - [Obsolete] - public int MaxCategoricalSplitPoints { get; set; } = 64; - - /// - /// Minimum categorical docs percentage in a bin to consider for a split. - /// - [Obsolete] - public double MinDocsPercentageForCategoricalSplit { get; set; } = 0.001d; - - /// - /// Minimum categorical doc count in a bin to consider for a split. - /// - [Obsolete] - public int MinDocsForCategoricalSplit { get; set; } = 100; - - /// - /// Bias for calculating gradient for each feature bin for a categorical feature. - /// - [Obsolete] - public double Bias { get; set; } - - /// - /// Bundle low population bins. Bundle.None(0): no bundling, Bundle.AggregateLowPopulation(1): Bundle low population, Bundle.Adjacent(2): Neighbor low population bundle. - /// - [Obsolete] - public Microsoft.ML.Legacy.Trainers.Bundle Bundling { get; set; } = Microsoft.ML.Legacy.Trainers.Bundle.None; - - /// - /// Maximum number of distinct values (bins) per feature - /// - [Obsolete] - public int MaxBins { get; set; } = 255; - - /// - /// Sparsity level needed to use sparse feature representation - /// - [Obsolete] - public double SparsifyThreshold { get; set; } = 0.7d; - - /// - /// The feature first use penalty coefficient - /// - [Obsolete] - public double FeatureFirstUsePenalty { get; set; } - - /// - /// The feature re-use penalty (regularization) coefficient - /// - [Obsolete] - public double FeatureReusePenalty { get; set; } - - /// - /// Tree fitting gain confidence requirement (should be in the range [0,1) ). - /// - [Obsolete] - public double GainConfidenceLevel { get; set; } + /// + /// Allows to choose Parallel FastTree Learning Algorithm + /// + [JsonConverter(typeof(ComponentSerializer))] + [Obsolete] + public ParallelTraining ParallelTrainer { get; set; } = new SingleParallelTraining(); - /// - /// The temperature of the randomized softmax distribution for choosing the feature - /// - [Obsolete] - public double SoftmaxTemperature { get; set; } + /// + /// The number of threads to use + /// + [Obsolete] + public int? NumThreads { get; set; } - /// - /// Print execution time breakdown to stdout - /// - [Obsolete] - public bool ExecutionTimes { get; set; } = false; + /// + /// The seed of the random number generator + /// + [Obsolete] + public int RngSeed { get; set; } = 123; - /// - /// The max number of leaves in each regression tree - /// - [TlcModule.SweepableLongParamAttribute("NumLeaves", 2, 128, stepSize:4, isLogScale:true)] - [Obsolete] - public int NumLeaves { get; set; } = 20; + /// + /// The seed of the active feature selection + /// + [Obsolete] + public int FeatureSelectSeed { get; set; } = 123; - /// - /// The minimal number of documents allowed in a leaf of a regression tree, out of the subsampled data - /// - [TlcModule.SweepableDiscreteParamAttribute("MinDocumentsInLeafs", new object[]{1, 10, 50})] - [Obsolete] - public int MinDocumentsInLeafs { get; set; } = 10; + /// + /// The entropy (regularization) coefficient between 0 and 1 + /// + [Obsolete] + public double EntropyCoefficient { get; set; } - /// - /// Total number of decision trees to create in the ensemble - /// - [TlcModule.SweepableDiscreteParamAttribute("NumTrees", new object[]{20, 100, 500})] - [Obsolete] - public int NumTrees { get; set; } = 100; + /// + /// The number of histograms in the pool (between 2 and numLeaves) + /// + [Obsolete] + public int HistogramPoolSize { get; set; } = -1; - /// - /// The fraction of features (chosen randomly) to use on each iteration - /// - [Obsolete] - public double FeatureFraction { get; set; } = 1d; + /// + /// Whether to utilize the disk or the data's native transposition facilities (where applicable) when performing the transpose + /// + [Obsolete] + public bool? DiskTranspose { get; set; } - /// - /// Number of trees in each bag (0 for disabling bagging) - /// - [Obsolete] - public int BaggingSize { get; set; } + /// + /// Whether to collectivize features during dataset preparation to speed up training + /// + [Obsolete] + public bool FeatureFlocks { get; set; } = true; - /// - /// Percentage of training examples used in each bag - /// - [Obsolete] - public double BaggingTrainFraction { get; set; } = 0.7d; + /// + /// Whether to do split based on multiple categorical feature values. + /// + [Obsolete] + public bool CategoricalSplit { get; set; } = false; - /// - /// The fraction of features (chosen randomly) to use on each split - /// - [Obsolete] - public double SplitFraction { get; set; } = 1d; + /// + /// Maximum categorical split groups to consider when splitting on a categorical feature. Split groups are a collection of split points. This is used to reduce overfitting when there many categorical features. + /// + [Obsolete] + public int MaxCategoricalGroupsPerNode { get; set; } = 64; - /// - /// Smoothing paramter for tree regularization - /// - [Obsolete] - public double Smoothing { get; set; } + /// + /// Maximum categorical split points to consider when splitting on a categorical feature. + /// + [Obsolete] + public int MaxCategoricalSplitPoints { get; set; } = 64; - /// - /// When a root split is impossible, allow training to proceed - /// - [Obsolete] - public bool AllowEmptyTrees { get; set; } = true; + /// + /// Minimum categorical docs percentage in a bin to consider for a split. + /// + [Obsolete] + public double MinDocsPercentageForCategoricalSplit { get; set; } = 0.001d; - /// - /// The level of feature compression to use - /// - [Obsolete] - public int FeatureCompressionLevel { get; set; } = 1; + /// + /// Minimum categorical doc count in a bin to consider for a split. + /// + [Obsolete] + public int MinDocsForCategoricalSplit { get; set; } = 100; - /// - /// Compress the tree Ensemble - /// - [Obsolete] - public bool CompressEnsemble { get; set; } = false; + /// + /// Bias for calculating gradient for each feature bin for a categorical feature. + /// + [Obsolete] + public double Bias { get; set; } - /// - /// Maximum Number of trees after compression - /// - [Obsolete] - public int MaxTreesAfterCompression { get; set; } = -1; + /// + /// Bundle low population bins. Bundle.None(0): no bundling, Bundle.AggregateLowPopulation(1): Bundle low population, Bundle.Adjacent(2): Neighbor low population bundle. + /// + [Obsolete] + public Microsoft.ML.Legacy.Trainers.Bundle Bundling { get; set; } = Microsoft.ML.Legacy.Trainers.Bundle.None; - /// - /// Print metrics graph for the first test set - /// - [Obsolete] - public bool PrintTestGraph { get; set; } = false; + /// + /// Maximum number of distinct values (bins) per feature + /// + [Obsolete] + public int MaxBins { get; set; } = 255; - /// - /// Print Train and Validation metrics in graph - /// - [Obsolete] - public bool PrintTrainValidGraph { get; set; } = false; + /// + /// Sparsity level needed to use sparse feature representation + /// + [Obsolete] + public double SparsifyThreshold { get; set; } = 0.7d; - /// - /// Calculate metric values for train/valid/test every k rounds - /// - [Obsolete] - public int TestFrequency { get; set; } = 2147483647; + /// + /// The feature first use penalty coefficient + /// + [Obsolete] + public double FeatureFirstUsePenalty { get; set; } - /// - /// Column to use for example groupId - /// - [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional GroupIdColumn { get; set; } + /// + /// The feature re-use penalty (regularization) coefficient + /// + [Obsolete] + public double FeatureReusePenalty { get; set; } - /// - /// Column to use for example weight - /// - [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + /// + /// Tree fitting gain confidence requirement (should be in the range [0,1) ). + /// + [Obsolete] + public double GainConfidenceLevel { get; set; } - /// - /// Column to use for labels - /// - [Obsolete] - public string LabelColumn { get; set; } = "Label"; + /// + /// The temperature of the randomized softmax distribution for choosing the feature + /// + [Obsolete] + public double SoftmaxTemperature { get; set; } - /// - /// The data to be used for training - /// - [Obsolete] - public Var TrainingData { get; set; } = new Var(); + /// + /// Print execution time breakdown to stdout + /// + [Obsolete] + public bool ExecutionTimes { get; set; } = false; - /// - /// Column to use for features - /// - [Obsolete] - public string FeatureColumn { get; set; } = "Features"; + /// + /// The max number of leaves in each regression tree + /// + [TlcModule.SweepableLongParamAttribute("NumLeaves", 2, 128, stepSize:4, isLogScale:true)] + [Obsolete] + public int NumLeaves { get; set; } = 20; - /// - /// Normalize option for the feature column - /// - [Obsolete] - public Microsoft.ML.Legacy.Models.NormalizeOption NormalizeFeatures { get; set; } = Microsoft.ML.Legacy.Models.NormalizeOption.Auto; + /// + /// The minimal number of documents allowed in a leaf of a regression tree, out of the subsampled data + /// + [TlcModule.SweepableDiscreteParamAttribute("MinDocumentsInLeafs", new object[]{1, 10, 50})] + [Obsolete] + public int MinDocumentsInLeafs { get; set; } = 10; - /// - /// Whether learner should cache input training data - /// - [Obsolete] - public Microsoft.ML.Legacy.Models.CachingOptions Caching { get; set; } = Microsoft.ML.Legacy.Models.CachingOptions.Auto; + /// + /// Total number of decision trees to create in the ensemble + /// + [TlcModule.SweepableDiscreteParamAttribute("NumTrees", new object[]{20, 100, 500})] + [Obsolete] + public int NumTrees { get; set; } = 100; - [Obsolete] - internal override string ComponentName => "FastTreeBinaryClassification"; - } + /// + /// The fraction of features (chosen randomly) to use on each iteration + /// + [Obsolete] + public double FeatureFraction { get; set; } = 1d; + /// + /// Number of trees in each bag (0 for disabling bagging) + /// + [Obsolete] + public int BaggingSize { get; set; } + /// + /// Percentage of training examples used in each bag + /// + [Obsolete] + public double BaggingTrainFraction { get; set; } = 0.7d; /// - /// Trains gradient boosted decision trees to the LambdaRank quasi-gradient. + /// The fraction of features (chosen randomly) to use on each split /// [Obsolete] - public sealed class FastTreeRankingFastTreeTrainer : FastTreeTrainer - { - /// - /// Comma seperated list of gains associated to each relevance label. - /// - [Obsolete] - public string CustomGains { get; set; } = "0,3,7,15,31"; + public double SplitFraction { get; set; } = 1d; - /// - /// Train DCG instead of NDCG - /// - [Obsolete] - public bool TrainDcg { get; set; } = false; + /// + /// Smoothing paramter for tree regularization + /// + [Obsolete] + public double Smoothing { get; set; } - /// - /// The sorting algorithm to use for DCG and LambdaMart calculations [DescendingStablePessimistic/DescendingStable/DescendingReverse/DescendingDotNet] - /// - [Obsolete] - public string SortingAlgorithm { get; set; } = "DescendingStablePessimistic"; + /// + /// When a root split is impossible, allow training to proceed + /// + [Obsolete] + public bool AllowEmptyTrees { get; set; } = true; - /// - /// max-NDCG truncation to use in the Lambda Mart algorithm - /// - [Obsolete] - public int LambdaMartMaxTruncation { get; set; } = 100; + /// + /// The level of feature compression to use + /// + [Obsolete] + public int FeatureCompressionLevel { get; set; } = 1; - /// - /// Use shifted NDCG - /// - [Obsolete] - public bool ShiftedNdcg { get; set; } = false; + /// + /// Compress the tree Ensemble + /// + [Obsolete] + public bool CompressEnsemble { get; set; } = false; - /// - /// Cost function parameter (w/c) - /// - [Obsolete] - public char CostFunctionParam { get; set; } = 'w'; + /// + /// Maximum Number of trees after compression + /// + [Obsolete] + public int MaxTreesAfterCompression { get; set; } = -1; - /// - /// Distance weight 2 adjustment to cost - /// - [Obsolete] - public bool DistanceWeight2 { get; set; } = false; + /// + /// Print metrics graph for the first test set + /// + [Obsolete] + public bool PrintTestGraph { get; set; } = false; - /// - /// Normalize query lambdas - /// - [Obsolete] - public bool NormalizeQueryLambdas { get; set; } = false; + /// + /// Print Train and Validation metrics in graph + /// + [Obsolete] + public bool PrintTrainValidGraph { get; set; } = false; - /// - /// Use best regression step trees? - /// - [Obsolete] - public bool BestStepRankingRegressionTrees { get; set; } = false; + /// + /// Calculate metric values for train/valid/test every k rounds + /// + [Obsolete] + public int TestFrequency { get; set; } = 2147483647; - /// - /// Should we use line search for a step size - /// - [Obsolete] - public bool UseLineSearch { get; set; } = false; + /// + /// Column to use for example groupId + /// + [Obsolete] + public Microsoft.ML.EntryPoints.Optional GroupIdColumn { get; set; } - /// - /// Number of post-bracket line search steps - /// - [Obsolete] - public int NumPostBracketSteps { get; set; } + /// + /// Column to use for example weight + /// + [Obsolete] + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } - /// - /// Minimum line search step size - /// - [Obsolete] - public double MinStepSize { get; set; } + /// + /// Column to use for labels + /// + [Obsolete] + public string LabelColumn { get; set; } = "Label"; - /// - /// Optimization algorithm to be used (GradientDescent, AcceleratedGradientDescent) - /// - [Obsolete] - public Microsoft.ML.Legacy.Trainers.BoostedTreeArgsOptimizationAlgorithmType OptimizationAlgorithm { get; set; } = Microsoft.ML.Legacy.Trainers.BoostedTreeArgsOptimizationAlgorithmType.GradientDescent; + /// + /// The data to be used for training + /// + [Obsolete] + public Var TrainingData { get; set; } = new Var(); - /// - /// Early stopping rule. (Validation set (/valid) is required.) - /// - [JsonConverter(typeof(ComponentSerializer))] - [Obsolete] - public EarlyStoppingCriterion EarlyStoppingRule { get; set; } + /// + /// Column to use for features + /// + [Obsolete] + public string FeatureColumn { get; set; } = "Features"; - /// - /// Early stopping metrics. (For regression, 1: L1, 2:L2; for ranking, 1:NDCG@1, 3:NDCG@3) - /// - [Obsolete] - public int EarlyStoppingMetrics { get; set; } = 1; + /// + /// Normalize option for the feature column + /// + [Obsolete] + public Microsoft.ML.Legacy.Models.NormalizeOption NormalizeFeatures { get; set; } = Microsoft.ML.Legacy.Models.NormalizeOption.Auto; - /// - /// Enable post-training pruning to avoid overfitting. (a validation set is required) - /// - [Obsolete] - public bool EnablePruning { get; set; } = false; + /// + /// Whether learner should cache input training data + /// + [Obsolete] + public Microsoft.ML.Legacy.Models.CachingOptions Caching { get; set; } = Microsoft.ML.Legacy.Models.CachingOptions.Auto; - /// - /// Use window and tolerance for pruning - /// - [Obsolete] - public bool UseTolerantPruning { get; set; } = false; + [Obsolete] + internal override string ComponentName => "FastTreeBinaryClassification"; + } - /// - /// The tolerance threshold for pruning - /// - [Obsolete] - public double PruningThreshold { get; set; } = 0.004d; - /// - /// The moving window size for pruning - /// - [Obsolete] - public int PruningWindowSize { get; set; } = 5; - /// - /// The learning rate - /// - [TlcModule.SweepableFloatParamAttribute("LearningRates", 0.025f, 0.4f, isLogScale:true)] - [Obsolete] - public double LearningRates { get; set; } = 0.2d; + /// + /// Trains gradient boosted decision trees to the LambdaRank quasi-gradient. + /// + [Obsolete] + public sealed class FastTreeRankingFastTreeTrainer : FastTreeTrainer + { + /// + /// Comma seperated list of gains associated to each relevance label. + /// + [Obsolete] + public string CustomGains { get; set; } = "0,3,7,15,31"; - /// - /// Shrinkage - /// - [TlcModule.SweepableFloatParamAttribute("Shrinkage", 0.025f, 4f, isLogScale:true)] - [Obsolete] - public double Shrinkage { get; set; } = 1d; + /// + /// Train DCG instead of NDCG + /// + [Obsolete] + public bool TrainDcg { get; set; } = false; - /// - /// Dropout rate for tree regularization - /// - [TlcModule.SweepableDiscreteParamAttribute("DropoutRate", new object[]{0f, 1E-09f, 0.05f, 0.1f, 0.2f})] - [Obsolete] - public double DropoutRate { get; set; } + /// + /// The sorting algorithm to use for DCG and LambdaMart calculations [DescendingStablePessimistic/DescendingStable/DescendingReverse/DescendingDotNet] + /// + [Obsolete] + public string SortingAlgorithm { get; set; } = "DescendingStablePessimistic"; - /// - /// Sample each query 1 in k times in the GetDerivatives function - /// - [Obsolete] - public int GetDerivativesSampleRate { get; set; } = 1; + /// + /// max-NDCG truncation to use in the Lambda Mart algorithm + /// + [Obsolete] + public int LambdaMartMaxTruncation { get; set; } = 100; - /// - /// Write the last ensemble instead of the one determined by early stopping - /// - [Obsolete] - public bool WriteLastEnsemble { get; set; } = false; + /// + /// Use shifted NDCG + /// + [Obsolete] + public bool ShiftedNdcg { get; set; } = false; - /// - /// Upper bound on absolute value of single tree output - /// - [Obsolete] - public double MaxTreeOutput { get; set; } = 100d; + /// + /// Cost function parameter (w/c) + /// + [Obsolete] + public char CostFunctionParam { get; set; } = 'w'; - /// - /// Training starts from random ordering (determined by /r1) - /// - [Obsolete] - public bool RandomStart { get; set; } = false; + /// + /// Distance weight 2 adjustment to cost + /// + [Obsolete] + public bool DistanceWeight2 { get; set; } = false; - /// - /// Filter zero lambdas during training - /// - [Obsolete] - public bool FilterZeroLambdas { get; set; } = false; + /// + /// Normalize query lambdas + /// + [Obsolete] + public bool NormalizeQueryLambdas { get; set; } = false; - /// - /// Freeform defining the scores that should be used as the baseline ranker - /// - [Obsolete] - public string BaselineScoresFormula { get; set; } + /// + /// Use best regression step trees? + /// + [Obsolete] + public bool BestStepRankingRegressionTrees { get; set; } = false; - /// - /// Baseline alpha for tradeoffs of risk (0 is normal training) - /// - [Obsolete] - public string BaselineAlphaRisk { get; set; } + /// + /// Should we use line search for a step size + /// + [Obsolete] + public bool UseLineSearch { get; set; } = false; - /// - /// The discount freeform which specifies the per position discounts of documents in a query (uses a single variable P for position where P=0 is first position) - /// - [Obsolete] - public string PositionDiscountFreeform { get; set; } + /// + /// Number of post-bracket line search steps + /// + [Obsolete] + public int NumPostBracketSteps { get; set; } - /// - /// Allows to choose Parallel FastTree Learning Algorithm - /// - [JsonConverter(typeof(ComponentSerializer))] - [Obsolete] - public ParallelTraining ParallelTrainer { get; set; } = new SingleParallelTraining(); + /// + /// Minimum line search step size + /// + [Obsolete] + public double MinStepSize { get; set; } - /// - /// The number of threads to use - /// - [Obsolete] - public int? NumThreads { get; set; } + /// + /// Optimization algorithm to be used (GradientDescent, AcceleratedGradientDescent) + /// + [Obsolete] + public Microsoft.ML.Legacy.Trainers.BoostedTreeArgsOptimizationAlgorithmType OptimizationAlgorithm { get; set; } = Microsoft.ML.Legacy.Trainers.BoostedTreeArgsOptimizationAlgorithmType.GradientDescent; - /// - /// The seed of the random number generator - /// - [Obsolete] - public int RngSeed { get; set; } = 123; + /// + /// Early stopping rule. (Validation set (/valid) is required.) + /// + [JsonConverter(typeof(ComponentSerializer))] + [Obsolete] + public EarlyStoppingCriterion EarlyStoppingRule { get; set; } - /// - /// The seed of the active feature selection - /// - [Obsolete] - public int FeatureSelectSeed { get; set; } = 123; + /// + /// Early stopping metrics. (For regression, 1: L1, 2:L2; for ranking, 1:NDCG@1, 3:NDCG@3) + /// + [Obsolete] + public int EarlyStoppingMetrics { get; set; } = 1; - /// - /// The entropy (regularization) coefficient between 0 and 1 - /// - [Obsolete] - public double EntropyCoefficient { get; set; } + /// + /// Enable post-training pruning to avoid overfitting. (a validation set is required) + /// + [Obsolete] + public bool EnablePruning { get; set; } = false; - /// - /// The number of histograms in the pool (between 2 and numLeaves) - /// - [Obsolete] - public int HistogramPoolSize { get; set; } = -1; + /// + /// Use window and tolerance for pruning + /// + [Obsolete] + public bool UseTolerantPruning { get; set; } = false; - /// - /// Whether to utilize the disk or the data's native transposition facilities (where applicable) when performing the transpose - /// - [Obsolete] - public bool? DiskTranspose { get; set; } + /// + /// The tolerance threshold for pruning + /// + [Obsolete] + public double PruningThreshold { get; set; } = 0.004d; - /// - /// Whether to collectivize features during dataset preparation to speed up training - /// - [Obsolete] - public bool FeatureFlocks { get; set; } = true; + /// + /// The moving window size for pruning + /// + [Obsolete] + public int PruningWindowSize { get; set; } = 5; - /// - /// Whether to do split based on multiple categorical feature values. - /// - [Obsolete] - public bool CategoricalSplit { get; set; } = false; + /// + /// The learning rate + /// + [TlcModule.SweepableFloatParamAttribute("LearningRates", 0.025f, 0.4f, isLogScale:true)] + [Obsolete] + public double LearningRates { get; set; } = 0.2d; - /// - /// Maximum categorical split groups to consider when splitting on a categorical feature. Split groups are a collection of split points. This is used to reduce overfitting when there many categorical features. - /// - [Obsolete] - public int MaxCategoricalGroupsPerNode { get; set; } = 64; + /// + /// Shrinkage + /// + [TlcModule.SweepableFloatParamAttribute("Shrinkage", 0.025f, 4f, isLogScale:true)] + [Obsolete] + public double Shrinkage { get; set; } = 1d; - /// - /// Maximum categorical split points to consider when splitting on a categorical feature. - /// - [Obsolete] - public int MaxCategoricalSplitPoints { get; set; } = 64; + /// + /// Dropout rate for tree regularization + /// + [TlcModule.SweepableDiscreteParamAttribute("DropoutRate", new object[]{0f, 1E-09f, 0.05f, 0.1f, 0.2f})] + [Obsolete] + public double DropoutRate { get; set; } - /// - /// Minimum categorical docs percentage in a bin to consider for a split. - /// - [Obsolete] - public double MinDocsPercentageForCategoricalSplit { get; set; } = 0.001d; + /// + /// Sample each query 1 in k times in the GetDerivatives function + /// + [Obsolete] + public int GetDerivativesSampleRate { get; set; } = 1; - /// - /// Minimum categorical doc count in a bin to consider for a split. - /// - [Obsolete] - public int MinDocsForCategoricalSplit { get; set; } = 100; + /// + /// Write the last ensemble instead of the one determined by early stopping + /// + [Obsolete] + public bool WriteLastEnsemble { get; set; } = false; - /// - /// Bias for calculating gradient for each feature bin for a categorical feature. - /// - [Obsolete] - public double Bias { get; set; } + /// + /// Upper bound on absolute value of single tree output + /// + [Obsolete] + public double MaxTreeOutput { get; set; } = 100d; - /// - /// Bundle low population bins. Bundle.None(0): no bundling, Bundle.AggregateLowPopulation(1): Bundle low population, Bundle.Adjacent(2): Neighbor low population bundle. - /// - [Obsolete] - public Microsoft.ML.Legacy.Trainers.Bundle Bundling { get; set; } = Microsoft.ML.Legacy.Trainers.Bundle.None; + /// + /// Training starts from random ordering (determined by /r1) + /// + [Obsolete] + public bool RandomStart { get; set; } = false; - /// - /// Maximum number of distinct values (bins) per feature - /// - [Obsolete] - public int MaxBins { get; set; } = 255; + /// + /// Filter zero lambdas during training + /// + [Obsolete] + public bool FilterZeroLambdas { get; set; } = false; - /// - /// Sparsity level needed to use sparse feature representation - /// - [Obsolete] - public double SparsifyThreshold { get; set; } = 0.7d; + /// + /// Freeform defining the scores that should be used as the baseline ranker + /// + [Obsolete] + public string BaselineScoresFormula { get; set; } - /// - /// The feature first use penalty coefficient - /// - [Obsolete] - public double FeatureFirstUsePenalty { get; set; } + /// + /// Baseline alpha for tradeoffs of risk (0 is normal training) + /// + [Obsolete] + public string BaselineAlphaRisk { get; set; } - /// - /// The feature re-use penalty (regularization) coefficient - /// - [Obsolete] - public double FeatureReusePenalty { get; set; } + /// + /// The discount freeform which specifies the per position discounts of documents in a query (uses a single variable P for position where P=0 is first position) + /// + [Obsolete] + public string PositionDiscountFreeform { get; set; } - /// - /// Tree fitting gain confidence requirement (should be in the range [0,1) ). - /// - [Obsolete] - public double GainConfidenceLevel { get; set; } + /// + /// Allows to choose Parallel FastTree Learning Algorithm + /// + [JsonConverter(typeof(ComponentSerializer))] + [Obsolete] + public ParallelTraining ParallelTrainer { get; set; } = new SingleParallelTraining(); - /// - /// The temperature of the randomized softmax distribution for choosing the feature - /// - [Obsolete] - public double SoftmaxTemperature { get; set; } + /// + /// The number of threads to use + /// + [Obsolete] + public int? NumThreads { get; set; } + + /// + /// The seed of the random number generator + /// + [Obsolete] + public int RngSeed { get; set; } = 123; - /// - /// Print execution time breakdown to stdout - /// - [Obsolete] - public bool ExecutionTimes { get; set; } = false; + /// + /// The seed of the active feature selection + /// + [Obsolete] + public int FeatureSelectSeed { get; set; } = 123; - /// - /// The max number of leaves in each regression tree - /// - [TlcModule.SweepableLongParamAttribute("NumLeaves", 2, 128, stepSize:4, isLogScale:true)] - [Obsolete] - public int NumLeaves { get; set; } = 20; + /// + /// The entropy (regularization) coefficient between 0 and 1 + /// + [Obsolete] + public double EntropyCoefficient { get; set; } - /// - /// The minimal number of documents allowed in a leaf of a regression tree, out of the subsampled data - /// - [TlcModule.SweepableDiscreteParamAttribute("MinDocumentsInLeafs", new object[]{1, 10, 50})] - [Obsolete] - public int MinDocumentsInLeafs { get; set; } = 10; + /// + /// The number of histograms in the pool (between 2 and numLeaves) + /// + [Obsolete] + public int HistogramPoolSize { get; set; } = -1; - /// - /// Total number of decision trees to create in the ensemble - /// - [TlcModule.SweepableDiscreteParamAttribute("NumTrees", new object[]{20, 100, 500})] - [Obsolete] - public int NumTrees { get; set; } = 100; + /// + /// Whether to utilize the disk or the data's native transposition facilities (where applicable) when performing the transpose + /// + [Obsolete] + public bool? DiskTranspose { get; set; } - /// - /// The fraction of features (chosen randomly) to use on each iteration - /// - [Obsolete] - public double FeatureFraction { get; set; } = 1d; + /// + /// Whether to collectivize features during dataset preparation to speed up training + /// + [Obsolete] + public bool FeatureFlocks { get; set; } = true; - /// - /// Number of trees in each bag (0 for disabling bagging) - /// - [Obsolete] - public int BaggingSize { get; set; } + /// + /// Whether to do split based on multiple categorical feature values. + /// + [Obsolete] + public bool CategoricalSplit { get; set; } = false; - /// - /// Percentage of training examples used in each bag - /// - [Obsolete] - public double BaggingTrainFraction { get; set; } = 0.7d; + /// + /// Maximum categorical split groups to consider when splitting on a categorical feature. Split groups are a collection of split points. This is used to reduce overfitting when there many categorical features. + /// + [Obsolete] + public int MaxCategoricalGroupsPerNode { get; set; } = 64; - /// - /// The fraction of features (chosen randomly) to use on each split - /// - [Obsolete] - public double SplitFraction { get; set; } = 1d; + /// + /// Maximum categorical split points to consider when splitting on a categorical feature. + /// + [Obsolete] + public int MaxCategoricalSplitPoints { get; set; } = 64; - /// - /// Smoothing paramter for tree regularization - /// - [Obsolete] - public double Smoothing { get; set; } + /// + /// Minimum categorical docs percentage in a bin to consider for a split. + /// + [Obsolete] + public double MinDocsPercentageForCategoricalSplit { get; set; } = 0.001d; - /// - /// When a root split is impossible, allow training to proceed - /// - [Obsolete] - public bool AllowEmptyTrees { get; set; } = true; + /// + /// Minimum categorical doc count in a bin to consider for a split. + /// + [Obsolete] + public int MinDocsForCategoricalSplit { get; set; } = 100; - /// - /// The level of feature compression to use - /// - [Obsolete] - public int FeatureCompressionLevel { get; set; } = 1; + /// + /// Bias for calculating gradient for each feature bin for a categorical feature. + /// + [Obsolete] + public double Bias { get; set; } - /// - /// Compress the tree Ensemble - /// - [Obsolete] - public bool CompressEnsemble { get; set; } = false; + /// + /// Bundle low population bins. Bundle.None(0): no bundling, Bundle.AggregateLowPopulation(1): Bundle low population, Bundle.Adjacent(2): Neighbor low population bundle. + /// + [Obsolete] + public Microsoft.ML.Legacy.Trainers.Bundle Bundling { get; set; } = Microsoft.ML.Legacy.Trainers.Bundle.None; - /// - /// Maximum Number of trees after compression - /// - [Obsolete] - public int MaxTreesAfterCompression { get; set; } = -1; + /// + /// Maximum number of distinct values (bins) per feature + /// + [Obsolete] + public int MaxBins { get; set; } = 255; - /// - /// Print metrics graph for the first test set - /// - [Obsolete] - public bool PrintTestGraph { get; set; } = false; + /// + /// Sparsity level needed to use sparse feature representation + /// + [Obsolete] + public double SparsifyThreshold { get; set; } = 0.7d; - /// - /// Print Train and Validation metrics in graph - /// - [Obsolete] - public bool PrintTrainValidGraph { get; set; } = false; + /// + /// The feature first use penalty coefficient + /// + [Obsolete] + public double FeatureFirstUsePenalty { get; set; } - /// - /// Calculate metric values for train/valid/test every k rounds - /// - [Obsolete] - public int TestFrequency { get; set; } = 2147483647; + /// + /// The feature re-use penalty (regularization) coefficient + /// + [Obsolete] + public double FeatureReusePenalty { get; set; } - /// - /// Column to use for example groupId - /// - [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional GroupIdColumn { get; set; } + /// + /// Tree fitting gain confidence requirement (should be in the range [0,1) ). + /// + [Obsolete] + public double GainConfidenceLevel { get; set; } - /// - /// Column to use for example weight - /// - [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + /// + /// The temperature of the randomized softmax distribution for choosing the feature + /// + [Obsolete] + public double SoftmaxTemperature { get; set; } - /// - /// Column to use for labels - /// - [Obsolete] - public string LabelColumn { get; set; } = "Label"; + /// + /// Print execution time breakdown to stdout + /// + [Obsolete] + public bool ExecutionTimes { get; set; } = false; - /// - /// The data to be used for training - /// - [Obsolete] - public Var TrainingData { get; set; } = new Var(); + /// + /// The max number of leaves in each regression tree + /// + [TlcModule.SweepableLongParamAttribute("NumLeaves", 2, 128, stepSize:4, isLogScale:true)] + [Obsolete] + public int NumLeaves { get; set; } = 20; - /// - /// Column to use for features - /// - [Obsolete] - public string FeatureColumn { get; set; } = "Features"; + /// + /// The minimal number of documents allowed in a leaf of a regression tree, out of the subsampled data + /// + [TlcModule.SweepableDiscreteParamAttribute("MinDocumentsInLeafs", new object[]{1, 10, 50})] + [Obsolete] + public int MinDocumentsInLeafs { get; set; } = 10; - /// - /// Normalize option for the feature column - /// - [Obsolete] - public Microsoft.ML.Legacy.Models.NormalizeOption NormalizeFeatures { get; set; } = Microsoft.ML.Legacy.Models.NormalizeOption.Auto; + /// + /// Total number of decision trees to create in the ensemble + /// + [TlcModule.SweepableDiscreteParamAttribute("NumTrees", new object[]{20, 100, 500})] + [Obsolete] + public int NumTrees { get; set; } = 100; - /// - /// Whether learner should cache input training data - /// - [Obsolete] - public Microsoft.ML.Legacy.Models.CachingOptions Caching { get; set; } = Microsoft.ML.Legacy.Models.CachingOptions.Auto; + /// + /// The fraction of features (chosen randomly) to use on each iteration + /// + [Obsolete] + public double FeatureFraction { get; set; } = 1d; - [Obsolete] - internal override string ComponentName => "FastTreeRanking"; - } + /// + /// Number of trees in each bag (0 for disabling bagging) + /// + [Obsolete] + public int BaggingSize { get; set; } + /// + /// Percentage of training examples used in each bag + /// + [Obsolete] + public double BaggingTrainFraction { get; set; } = 0.7d; + /// + /// The fraction of features (chosen randomly) to use on each split + /// + [Obsolete] + public double SplitFraction { get; set; } = 1d; /// - /// Trains gradient boosted decision trees to fit target values using least-squares. + /// Smoothing paramter for tree regularization /// [Obsolete] - public sealed class FastTreeRegressionFastTreeTrainer : FastTreeTrainer - { - /// - /// Use best regression step trees? - /// - [Obsolete] - public bool BestStepRankingRegressionTrees { get; set; } = false; + public double Smoothing { get; set; } - /// - /// Should we use line search for a step size - /// - [Obsolete] - public bool UseLineSearch { get; set; } = false; + /// + /// When a root split is impossible, allow training to proceed + /// + [Obsolete] + public bool AllowEmptyTrees { get; set; } = true; - /// - /// Number of post-bracket line search steps - /// - [Obsolete] - public int NumPostBracketSteps { get; set; } + /// + /// The level of feature compression to use + /// + [Obsolete] + public int FeatureCompressionLevel { get; set; } = 1; - /// - /// Minimum line search step size - /// - [Obsolete] - public double MinStepSize { get; set; } + /// + /// Compress the tree Ensemble + /// + [Obsolete] + public bool CompressEnsemble { get; set; } = false; - /// - /// Optimization algorithm to be used (GradientDescent, AcceleratedGradientDescent) - /// - [Obsolete] - public Microsoft.ML.Legacy.Trainers.BoostedTreeArgsOptimizationAlgorithmType OptimizationAlgorithm { get; set; } = Microsoft.ML.Legacy.Trainers.BoostedTreeArgsOptimizationAlgorithmType.GradientDescent; + /// + /// Maximum Number of trees after compression + /// + [Obsolete] + public int MaxTreesAfterCompression { get; set; } = -1; - /// - /// Early stopping rule. (Validation set (/valid) is required.) - /// - [JsonConverter(typeof(ComponentSerializer))] - [Obsolete] - public EarlyStoppingCriterion EarlyStoppingRule { get; set; } + /// + /// Print metrics graph for the first test set + /// + [Obsolete] + public bool PrintTestGraph { get; set; } = false; - /// - /// Early stopping metrics. (For regression, 1: L1, 2:L2; for ranking, 1:NDCG@1, 3:NDCG@3) - /// - [Obsolete] - public int EarlyStoppingMetrics { get; set; } = 1; + /// + /// Print Train and Validation metrics in graph + /// + [Obsolete] + public bool PrintTrainValidGraph { get; set; } = false; - /// - /// Enable post-training pruning to avoid overfitting. (a validation set is required) - /// - [Obsolete] - public bool EnablePruning { get; set; } = false; + /// + /// Calculate metric values for train/valid/test every k rounds + /// + [Obsolete] + public int TestFrequency { get; set; } = 2147483647; - /// - /// Use window and tolerance for pruning - /// - [Obsolete] - public bool UseTolerantPruning { get; set; } = false; + /// + /// Column to use for example groupId + /// + [Obsolete] + public Microsoft.ML.EntryPoints.Optional GroupIdColumn { get; set; } - /// - /// The tolerance threshold for pruning - /// - [Obsolete] - public double PruningThreshold { get; set; } = 0.004d; + /// + /// Column to use for example weight + /// + [Obsolete] + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } - /// - /// The moving window size for pruning - /// - [Obsolete] - public int PruningWindowSize { get; set; } = 5; + /// + /// Column to use for labels + /// + [Obsolete] + public string LabelColumn { get; set; } = "Label"; - /// - /// The learning rate - /// - [TlcModule.SweepableFloatParamAttribute("LearningRates", 0.025f, 0.4f, isLogScale:true)] - [Obsolete] - public double LearningRates { get; set; } = 0.2d; + /// + /// The data to be used for training + /// + [Obsolete] + public Var TrainingData { get; set; } = new Var(); - /// - /// Shrinkage - /// - [TlcModule.SweepableFloatParamAttribute("Shrinkage", 0.025f, 4f, isLogScale:true)] - [Obsolete] - public double Shrinkage { get; set; } = 1d; + /// + /// Column to use for features + /// + [Obsolete] + public string FeatureColumn { get; set; } = "Features"; - /// - /// Dropout rate for tree regularization - /// - [TlcModule.SweepableDiscreteParamAttribute("DropoutRate", new object[]{0f, 1E-09f, 0.05f, 0.1f, 0.2f})] - [Obsolete] - public double DropoutRate { get; set; } + /// + /// Normalize option for the feature column + /// + [Obsolete] + public Microsoft.ML.Legacy.Models.NormalizeOption NormalizeFeatures { get; set; } = Microsoft.ML.Legacy.Models.NormalizeOption.Auto; - /// - /// Sample each query 1 in k times in the GetDerivatives function - /// - [Obsolete] - public int GetDerivativesSampleRate { get; set; } = 1; + /// + /// Whether learner should cache input training data + /// + [Obsolete] + public Microsoft.ML.Legacy.Models.CachingOptions Caching { get; set; } = Microsoft.ML.Legacy.Models.CachingOptions.Auto; - /// - /// Write the last ensemble instead of the one determined by early stopping - /// - [Obsolete] - public bool WriteLastEnsemble { get; set; } = false; + [Obsolete] + internal override string ComponentName => "FastTreeRanking"; + } - /// - /// Upper bound on absolute value of single tree output - /// - [Obsolete] - public double MaxTreeOutput { get; set; } = 100d; - /// - /// Training starts from random ordering (determined by /r1) - /// - [Obsolete] - public bool RandomStart { get; set; } = false; - /// - /// Filter zero lambdas during training - /// - [Obsolete] - public bool FilterZeroLambdas { get; set; } = false; + /// + /// Trains gradient boosted decision trees to fit target values using least-squares. + /// + [Obsolete] + public sealed class FastTreeRegressionFastTreeTrainer : FastTreeTrainer + { + /// + /// Use best regression step trees? + /// + [Obsolete] + public bool BestStepRankingRegressionTrees { get; set; } = false; - /// - /// Freeform defining the scores that should be used as the baseline ranker - /// - [Obsolete] - public string BaselineScoresFormula { get; set; } + /// + /// Should we use line search for a step size + /// + [Obsolete] + public bool UseLineSearch { get; set; } = false; - /// - /// Baseline alpha for tradeoffs of risk (0 is normal training) - /// - [Obsolete] - public string BaselineAlphaRisk { get; set; } + /// + /// Number of post-bracket line search steps + /// + [Obsolete] + public int NumPostBracketSteps { get; set; } - /// - /// The discount freeform which specifies the per position discounts of documents in a query (uses a single variable P for position where P=0 is first position) - /// - [Obsolete] - public string PositionDiscountFreeform { get; set; } + /// + /// Minimum line search step size + /// + [Obsolete] + public double MinStepSize { get; set; } - /// - /// Allows to choose Parallel FastTree Learning Algorithm - /// - [JsonConverter(typeof(ComponentSerializer))] - [Obsolete] - public ParallelTraining ParallelTrainer { get; set; } = new SingleParallelTraining(); + /// + /// Optimization algorithm to be used (GradientDescent, AcceleratedGradientDescent) + /// + [Obsolete] + public Microsoft.ML.Legacy.Trainers.BoostedTreeArgsOptimizationAlgorithmType OptimizationAlgorithm { get; set; } = Microsoft.ML.Legacy.Trainers.BoostedTreeArgsOptimizationAlgorithmType.GradientDescent; - /// - /// The number of threads to use - /// - [Obsolete] - public int? NumThreads { get; set; } + /// + /// Early stopping rule. (Validation set (/valid) is required.) + /// + [JsonConverter(typeof(ComponentSerializer))] + [Obsolete] + public EarlyStoppingCriterion EarlyStoppingRule { get; set; } - /// - /// The seed of the random number generator - /// - [Obsolete] - public int RngSeed { get; set; } = 123; + /// + /// Early stopping metrics. (For regression, 1: L1, 2:L2; for ranking, 1:NDCG@1, 3:NDCG@3) + /// + [Obsolete] + public int EarlyStoppingMetrics { get; set; } = 1; - /// - /// The seed of the active feature selection - /// - [Obsolete] - public int FeatureSelectSeed { get; set; } = 123; + /// + /// Enable post-training pruning to avoid overfitting. (a validation set is required) + /// + [Obsolete] + public bool EnablePruning { get; set; } = false; - /// - /// The entropy (regularization) coefficient between 0 and 1 - /// - [Obsolete] - public double EntropyCoefficient { get; set; } + /// + /// Use window and tolerance for pruning + /// + [Obsolete] + public bool UseTolerantPruning { get; set; } = false; - /// - /// The number of histograms in the pool (between 2 and numLeaves) - /// - [Obsolete] - public int HistogramPoolSize { get; set; } = -1; + /// + /// The tolerance threshold for pruning + /// + [Obsolete] + public double PruningThreshold { get; set; } = 0.004d; - /// - /// Whether to utilize the disk or the data's native transposition facilities (where applicable) when performing the transpose - /// - [Obsolete] - public bool? DiskTranspose { get; set; } + /// + /// The moving window size for pruning + /// + [Obsolete] + public int PruningWindowSize { get; set; } = 5; - /// - /// Whether to collectivize features during dataset preparation to speed up training - /// - [Obsolete] - public bool FeatureFlocks { get; set; } = true; + /// + /// The learning rate + /// + [TlcModule.SweepableFloatParamAttribute("LearningRates", 0.025f, 0.4f, isLogScale:true)] + [Obsolete] + public double LearningRates { get; set; } = 0.2d; - /// - /// Whether to do split based on multiple categorical feature values. - /// - [Obsolete] - public bool CategoricalSplit { get; set; } = false; + /// + /// Shrinkage + /// + [TlcModule.SweepableFloatParamAttribute("Shrinkage", 0.025f, 4f, isLogScale:true)] + [Obsolete] + public double Shrinkage { get; set; } = 1d; - /// - /// Maximum categorical split groups to consider when splitting on a categorical feature. Split groups are a collection of split points. This is used to reduce overfitting when there many categorical features. - /// - [Obsolete] - public int MaxCategoricalGroupsPerNode { get; set; } = 64; + /// + /// Dropout rate for tree regularization + /// + [TlcModule.SweepableDiscreteParamAttribute("DropoutRate", new object[]{0f, 1E-09f, 0.05f, 0.1f, 0.2f})] + [Obsolete] + public double DropoutRate { get; set; } - /// - /// Maximum categorical split points to consider when splitting on a categorical feature. - /// - [Obsolete] - public int MaxCategoricalSplitPoints { get; set; } = 64; + /// + /// Sample each query 1 in k times in the GetDerivatives function + /// + [Obsolete] + public int GetDerivativesSampleRate { get; set; } = 1; - /// - /// Minimum categorical docs percentage in a bin to consider for a split. - /// - [Obsolete] - public double MinDocsPercentageForCategoricalSplit { get; set; } = 0.001d; + /// + /// Write the last ensemble instead of the one determined by early stopping + /// + [Obsolete] + public bool WriteLastEnsemble { get; set; } = false; - /// - /// Minimum categorical doc count in a bin to consider for a split. - /// - [Obsolete] - public int MinDocsForCategoricalSplit { get; set; } = 100; + /// + /// Upper bound on absolute value of single tree output + /// + [Obsolete] + public double MaxTreeOutput { get; set; } = 100d; - /// - /// Bias for calculating gradient for each feature bin for a categorical feature. - /// - [Obsolete] - public double Bias { get; set; } + /// + /// Training starts from random ordering (determined by /r1) + /// + [Obsolete] + public bool RandomStart { get; set; } = false; - /// - /// Bundle low population bins. Bundle.None(0): no bundling, Bundle.AggregateLowPopulation(1): Bundle low population, Bundle.Adjacent(2): Neighbor low population bundle. - /// - [Obsolete] - public Microsoft.ML.Legacy.Trainers.Bundle Bundling { get; set; } = Microsoft.ML.Legacy.Trainers.Bundle.None; + /// + /// Filter zero lambdas during training + /// + [Obsolete] + public bool FilterZeroLambdas { get; set; } = false; - /// - /// Maximum number of distinct values (bins) per feature - /// - [Obsolete] - public int MaxBins { get; set; } = 255; + /// + /// Freeform defining the scores that should be used as the baseline ranker + /// + [Obsolete] + public string BaselineScoresFormula { get; set; } - /// - /// Sparsity level needed to use sparse feature representation - /// - [Obsolete] - public double SparsifyThreshold { get; set; } = 0.7d; + /// + /// Baseline alpha for tradeoffs of risk (0 is normal training) + /// + [Obsolete] + public string BaselineAlphaRisk { get; set; } - /// - /// The feature first use penalty coefficient - /// - [Obsolete] - public double FeatureFirstUsePenalty { get; set; } + /// + /// The discount freeform which specifies the per position discounts of documents in a query (uses a single variable P for position where P=0 is first position) + /// + [Obsolete] + public string PositionDiscountFreeform { get; set; } + + /// + /// Allows to choose Parallel FastTree Learning Algorithm + /// + [JsonConverter(typeof(ComponentSerializer))] + [Obsolete] + public ParallelTraining ParallelTrainer { get; set; } = new SingleParallelTraining(); - /// - /// The feature re-use penalty (regularization) coefficient - /// - [Obsolete] - public double FeatureReusePenalty { get; set; } + /// + /// The number of threads to use + /// + [Obsolete] + public int? NumThreads { get; set; } - /// - /// Tree fitting gain confidence requirement (should be in the range [0,1) ). - /// - [Obsolete] - public double GainConfidenceLevel { get; set; } + /// + /// The seed of the random number generator + /// + [Obsolete] + public int RngSeed { get; set; } = 123; - /// - /// The temperature of the randomized softmax distribution for choosing the feature - /// - [Obsolete] - public double SoftmaxTemperature { get; set; } + /// + /// The seed of the active feature selection + /// + [Obsolete] + public int FeatureSelectSeed { get; set; } = 123; - /// - /// Print execution time breakdown to stdout - /// - [Obsolete] - public bool ExecutionTimes { get; set; } = false; + /// + /// The entropy (regularization) coefficient between 0 and 1 + /// + [Obsolete] + public double EntropyCoefficient { get; set; } - /// - /// The max number of leaves in each regression tree - /// - [TlcModule.SweepableLongParamAttribute("NumLeaves", 2, 128, stepSize:4, isLogScale:true)] - [Obsolete] - public int NumLeaves { get; set; } = 20; + /// + /// The number of histograms in the pool (between 2 and numLeaves) + /// + [Obsolete] + public int HistogramPoolSize { get; set; } = -1; - /// - /// The minimal number of documents allowed in a leaf of a regression tree, out of the subsampled data - /// - [TlcModule.SweepableDiscreteParamAttribute("MinDocumentsInLeafs", new object[]{1, 10, 50})] - [Obsolete] - public int MinDocumentsInLeafs { get; set; } = 10; + /// + /// Whether to utilize the disk or the data's native transposition facilities (where applicable) when performing the transpose + /// + [Obsolete] + public bool? DiskTranspose { get; set; } - /// - /// Total number of decision trees to create in the ensemble - /// - [TlcModule.SweepableDiscreteParamAttribute("NumTrees", new object[]{20, 100, 500})] - [Obsolete] - public int NumTrees { get; set; } = 100; + /// + /// Whether to collectivize features during dataset preparation to speed up training + /// + [Obsolete] + public bool FeatureFlocks { get; set; } = true; - /// - /// The fraction of features (chosen randomly) to use on each iteration - /// - [Obsolete] - public double FeatureFraction { get; set; } = 1d; + /// + /// Whether to do split based on multiple categorical feature values. + /// + [Obsolete] + public bool CategoricalSplit { get; set; } = false; - /// - /// Number of trees in each bag (0 for disabling bagging) - /// - [Obsolete] - public int BaggingSize { get; set; } + /// + /// Maximum categorical split groups to consider when splitting on a categorical feature. Split groups are a collection of split points. This is used to reduce overfitting when there many categorical features. + /// + [Obsolete] + public int MaxCategoricalGroupsPerNode { get; set; } = 64; - /// - /// Percentage of training examples used in each bag - /// - [Obsolete] - public double BaggingTrainFraction { get; set; } = 0.7d; + /// + /// Maximum categorical split points to consider when splitting on a categorical feature. + /// + [Obsolete] + public int MaxCategoricalSplitPoints { get; set; } = 64; - /// - /// The fraction of features (chosen randomly) to use on each split - /// - [Obsolete] - public double SplitFraction { get; set; } = 1d; + /// + /// Minimum categorical docs percentage in a bin to consider for a split. + /// + [Obsolete] + public double MinDocsPercentageForCategoricalSplit { get; set; } = 0.001d; - /// - /// Smoothing paramter for tree regularization - /// - [Obsolete] - public double Smoothing { get; set; } + /// + /// Minimum categorical doc count in a bin to consider for a split. + /// + [Obsolete] + public int MinDocsForCategoricalSplit { get; set; } = 100; - /// - /// When a root split is impossible, allow training to proceed - /// - [Obsolete] - public bool AllowEmptyTrees { get; set; } = true; + /// + /// Bias for calculating gradient for each feature bin for a categorical feature. + /// + [Obsolete] + public double Bias { get; set; } - /// - /// The level of feature compression to use - /// - [Obsolete] - public int FeatureCompressionLevel { get; set; } = 1; + /// + /// Bundle low population bins. Bundle.None(0): no bundling, Bundle.AggregateLowPopulation(1): Bundle low population, Bundle.Adjacent(2): Neighbor low population bundle. + /// + [Obsolete] + public Microsoft.ML.Legacy.Trainers.Bundle Bundling { get; set; } = Microsoft.ML.Legacy.Trainers.Bundle.None; - /// - /// Compress the tree Ensemble - /// - [Obsolete] - public bool CompressEnsemble { get; set; } = false; + /// + /// Maximum number of distinct values (bins) per feature + /// + [Obsolete] + public int MaxBins { get; set; } = 255; - /// - /// Maximum Number of trees after compression - /// - [Obsolete] - public int MaxTreesAfterCompression { get; set; } = -1; + /// + /// Sparsity level needed to use sparse feature representation + /// + [Obsolete] + public double SparsifyThreshold { get; set; } = 0.7d; - /// - /// Print metrics graph for the first test set - /// - [Obsolete] - public bool PrintTestGraph { get; set; } = false; + /// + /// The feature first use penalty coefficient + /// + [Obsolete] + public double FeatureFirstUsePenalty { get; set; } - /// - /// Print Train and Validation metrics in graph - /// - [Obsolete] - public bool PrintTrainValidGraph { get; set; } = false; + /// + /// The feature re-use penalty (regularization) coefficient + /// + [Obsolete] + public double FeatureReusePenalty { get; set; } - /// - /// Calculate metric values for train/valid/test every k rounds - /// - [Obsolete] - public int TestFrequency { get; set; } = 2147483647; + /// + /// Tree fitting gain confidence requirement (should be in the range [0,1) ). + /// + [Obsolete] + public double GainConfidenceLevel { get; set; } - /// - /// Column to use for example groupId - /// - [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional GroupIdColumn { get; set; } + /// + /// The temperature of the randomized softmax distribution for choosing the feature + /// + [Obsolete] + public double SoftmaxTemperature { get; set; } - /// - /// Column to use for example weight - /// - [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + /// + /// Print execution time breakdown to stdout + /// + [Obsolete] + public bool ExecutionTimes { get; set; } = false; - /// - /// Column to use for labels - /// - [Obsolete] - public string LabelColumn { get; set; } = "Label"; + /// + /// The max number of leaves in each regression tree + /// + [TlcModule.SweepableLongParamAttribute("NumLeaves", 2, 128, stepSize:4, isLogScale:true)] + [Obsolete] + public int NumLeaves { get; set; } = 20; - /// - /// The data to be used for training - /// - [Obsolete] - public Var TrainingData { get; set; } = new Var(); + /// + /// The minimal number of documents allowed in a leaf of a regression tree, out of the subsampled data + /// + [TlcModule.SweepableDiscreteParamAttribute("MinDocumentsInLeafs", new object[]{1, 10, 50})] + [Obsolete] + public int MinDocumentsInLeafs { get; set; } = 10; - /// - /// Column to use for features - /// - [Obsolete] - public string FeatureColumn { get; set; } = "Features"; + /// + /// Total number of decision trees to create in the ensemble + /// + [TlcModule.SweepableDiscreteParamAttribute("NumTrees", new object[]{20, 100, 500})] + [Obsolete] + public int NumTrees { get; set; } = 100; - /// - /// Normalize option for the feature column - /// - [Obsolete] - public Microsoft.ML.Legacy.Models.NormalizeOption NormalizeFeatures { get; set; } = Microsoft.ML.Legacy.Models.NormalizeOption.Auto; + /// + /// The fraction of features (chosen randomly) to use on each iteration + /// + [Obsolete] + public double FeatureFraction { get; set; } = 1d; - /// - /// Whether learner should cache input training data - /// - [Obsolete] - public Microsoft.ML.Legacy.Models.CachingOptions Caching { get; set; } = Microsoft.ML.Legacy.Models.CachingOptions.Auto; + /// + /// Number of trees in each bag (0 for disabling bagging) + /// + [Obsolete] + public int BaggingSize { get; set; } - [Obsolete] - internal override string ComponentName => "FastTreeRegression"; - } + /// + /// Percentage of training examples used in each bag + /// + [Obsolete] + public double BaggingTrainFraction { get; set; } = 0.7d; + /// + /// The fraction of features (chosen randomly) to use on each split + /// + [Obsolete] + public double SplitFraction { get; set; } = 1d; + /// + /// Smoothing paramter for tree regularization + /// + [Obsolete] + public double Smoothing { get; set; } /// - /// Trains gradient boosted decision trees to fit target values using a Tweedie loss function. This learner is a generalization of Poisson, compound Poisson, and gamma regression. + /// When a root split is impossible, allow training to proceed /// [Obsolete] - public sealed class FastTreeTweedieRegressionFastTreeTrainer : FastTreeTrainer - { - /// - /// Index parameter for the Tweedie distribution, in the range [1, 2]. 1 is Poisson loss, 2 is gamma loss, and intermediate values are compound Poisson loss. - /// - [Obsolete] - public double Index { get; set; } = 1.5d; + public bool AllowEmptyTrees { get; set; } = true; - /// - /// Use best regression step trees? - /// - [Obsolete] - public bool BestStepRankingRegressionTrees { get; set; } = false; + /// + /// The level of feature compression to use + /// + [Obsolete] + public int FeatureCompressionLevel { get; set; } = 1; - /// - /// Should we use line search for a step size - /// - [Obsolete] - public bool UseLineSearch { get; set; } = false; + /// + /// Compress the tree Ensemble + /// + [Obsolete] + public bool CompressEnsemble { get; set; } = false; - /// - /// Number of post-bracket line search steps - /// - [Obsolete] - public int NumPostBracketSteps { get; set; } + /// + /// Maximum Number of trees after compression + /// + [Obsolete] + public int MaxTreesAfterCompression { get; set; } = -1; + + /// + /// Print metrics graph for the first test set + /// + [Obsolete] + public bool PrintTestGraph { get; set; } = false; - /// - /// Minimum line search step size - /// - [Obsolete] - public double MinStepSize { get; set; } + /// + /// Print Train and Validation metrics in graph + /// + [Obsolete] + public bool PrintTrainValidGraph { get; set; } = false; - /// - /// Optimization algorithm to be used (GradientDescent, AcceleratedGradientDescent) - /// - [Obsolete] - public Microsoft.ML.Legacy.Trainers.BoostedTreeArgsOptimizationAlgorithmType OptimizationAlgorithm { get; set; } = Microsoft.ML.Legacy.Trainers.BoostedTreeArgsOptimizationAlgorithmType.GradientDescent; + /// + /// Calculate metric values for train/valid/test every k rounds + /// + [Obsolete] + public int TestFrequency { get; set; } = 2147483647; - /// - /// Early stopping rule. (Validation set (/valid) is required.) - /// - [JsonConverter(typeof(ComponentSerializer))] - [Obsolete] - public EarlyStoppingCriterion EarlyStoppingRule { get; set; } + /// + /// Column to use for example groupId + /// + [Obsolete] + public Microsoft.ML.EntryPoints.Optional GroupIdColumn { get; set; } - /// - /// Early stopping metrics. (For regression, 1: L1, 2:L2; for ranking, 1:NDCG@1, 3:NDCG@3) - /// - [Obsolete] - public int EarlyStoppingMetrics { get; set; } + /// + /// Column to use for example weight + /// + [Obsolete] + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } - /// - /// Enable post-training pruning to avoid overfitting. (a validation set is required) - /// - [Obsolete] - public bool EnablePruning { get; set; } = false; + /// + /// Column to use for labels + /// + [Obsolete] + public string LabelColumn { get; set; } = "Label"; - /// - /// Use window and tolerance for pruning - /// - [Obsolete] - public bool UseTolerantPruning { get; set; } = false; + /// + /// The data to be used for training + /// + [Obsolete] + public Var TrainingData { get; set; } = new Var(); - /// - /// The tolerance threshold for pruning - /// - [Obsolete] - public double PruningThreshold { get; set; } = 0.004d; + /// + /// Column to use for features + /// + [Obsolete] + public string FeatureColumn { get; set; } = "Features"; - /// - /// The moving window size for pruning - /// - [Obsolete] - public int PruningWindowSize { get; set; } = 5; + /// + /// Normalize option for the feature column + /// + [Obsolete] + public Microsoft.ML.Legacy.Models.NormalizeOption NormalizeFeatures { get; set; } = Microsoft.ML.Legacy.Models.NormalizeOption.Auto; - /// - /// The learning rate - /// - [TlcModule.SweepableFloatParamAttribute("LearningRates", 0.025f, 0.4f, isLogScale:true)] - [Obsolete] - public double LearningRates { get; set; } = 0.2d; + /// + /// Whether learner should cache input training data + /// + [Obsolete] + public Microsoft.ML.Legacy.Models.CachingOptions Caching { get; set; } = Microsoft.ML.Legacy.Models.CachingOptions.Auto; - /// - /// Shrinkage - /// - [TlcModule.SweepableFloatParamAttribute("Shrinkage", 0.025f, 4f, isLogScale:true)] - [Obsolete] - public double Shrinkage { get; set; } = 1d; + [Obsolete] + internal override string ComponentName => "FastTreeRegression"; + } - /// - /// Dropout rate for tree regularization - /// - [TlcModule.SweepableDiscreteParamAttribute("DropoutRate", new object[]{0f, 1E-09f, 0.05f, 0.1f, 0.2f})] - [Obsolete] - public double DropoutRate { get; set; } - /// - /// Sample each query 1 in k times in the GetDerivatives function - /// - [Obsolete] - public int GetDerivativesSampleRate { get; set; } = 1; - /// - /// Write the last ensemble instead of the one determined by early stopping - /// - [Obsolete] - public bool WriteLastEnsemble { get; set; } = false; + /// + /// Trains gradient boosted decision trees to fit target values using a Tweedie loss function. This learner is a generalization of Poisson, compound Poisson, and gamma regression. + /// + [Obsolete] + public sealed class FastTreeTweedieRegressionFastTreeTrainer : FastTreeTrainer + { + /// + /// Index parameter for the Tweedie distribution, in the range [1, 2]. 1 is Poisson loss, 2 is gamma loss, and intermediate values are compound Poisson loss. + /// + [Obsolete] + public double Index { get; set; } = 1.5d; - /// - /// Upper bound on absolute value of single tree output - /// - [Obsolete] - public double MaxTreeOutput { get; set; } = 100d; + /// + /// Use best regression step trees? + /// + [Obsolete] + public bool BestStepRankingRegressionTrees { get; set; } = false; - /// - /// Training starts from random ordering (determined by /r1) - /// - [Obsolete] - public bool RandomStart { get; set; } = false; + /// + /// Should we use line search for a step size + /// + [Obsolete] + public bool UseLineSearch { get; set; } = false; - /// - /// Filter zero lambdas during training - /// - [Obsolete] - public bool FilterZeroLambdas { get; set; } = false; + /// + /// Number of post-bracket line search steps + /// + [Obsolete] + public int NumPostBracketSteps { get; set; } - /// - /// Freeform defining the scores that should be used as the baseline ranker - /// - [Obsolete] - public string BaselineScoresFormula { get; set; } + /// + /// Minimum line search step size + /// + [Obsolete] + public double MinStepSize { get; set; } - /// - /// Baseline alpha for tradeoffs of risk (0 is normal training) - /// - [Obsolete] - public string BaselineAlphaRisk { get; set; } + /// + /// Optimization algorithm to be used (GradientDescent, AcceleratedGradientDescent) + /// + [Obsolete] + public Microsoft.ML.Legacy.Trainers.BoostedTreeArgsOptimizationAlgorithmType OptimizationAlgorithm { get; set; } = Microsoft.ML.Legacy.Trainers.BoostedTreeArgsOptimizationAlgorithmType.GradientDescent; - /// - /// The discount freeform which specifies the per position discounts of documents in a query (uses a single variable P for position where P=0 is first position) - /// - [Obsolete] - public string PositionDiscountFreeform { get; set; } + /// + /// Early stopping rule. (Validation set (/valid) is required.) + /// + [JsonConverter(typeof(ComponentSerializer))] + [Obsolete] + public EarlyStoppingCriterion EarlyStoppingRule { get; set; } - /// - /// Allows to choose Parallel FastTree Learning Algorithm - /// - [JsonConverter(typeof(ComponentSerializer))] - [Obsolete] - public ParallelTraining ParallelTrainer { get; set; } = new SingleParallelTraining(); + /// + /// Early stopping metrics. (For regression, 1: L1, 2:L2; for ranking, 1:NDCG@1, 3:NDCG@3) + /// + [Obsolete] + public int EarlyStoppingMetrics { get; set; } - /// - /// The number of threads to use - /// - [Obsolete] - public int? NumThreads { get; set; } + /// + /// Enable post-training pruning to avoid overfitting. (a validation set is required) + /// + [Obsolete] + public bool EnablePruning { get; set; } = false; - /// - /// The seed of the random number generator - /// - [Obsolete] - public int RngSeed { get; set; } = 123; + /// + /// Use window and tolerance for pruning + /// + [Obsolete] + public bool UseTolerantPruning { get; set; } = false; - /// - /// The seed of the active feature selection - /// - [Obsolete] - public int FeatureSelectSeed { get; set; } = 123; + /// + /// The tolerance threshold for pruning + /// + [Obsolete] + public double PruningThreshold { get; set; } = 0.004d; - /// - /// The entropy (regularization) coefficient between 0 and 1 - /// - [Obsolete] - public double EntropyCoefficient { get; set; } + /// + /// The moving window size for pruning + /// + [Obsolete] + public int PruningWindowSize { get; set; } = 5; - /// - /// The number of histograms in the pool (between 2 and numLeaves) - /// - [Obsolete] - public int HistogramPoolSize { get; set; } = -1; + /// + /// The learning rate + /// + [TlcModule.SweepableFloatParamAttribute("LearningRates", 0.025f, 0.4f, isLogScale:true)] + [Obsolete] + public double LearningRates { get; set; } = 0.2d; - /// - /// Whether to utilize the disk or the data's native transposition facilities (where applicable) when performing the transpose - /// - [Obsolete] - public bool? DiskTranspose { get; set; } + /// + /// Shrinkage + /// + [TlcModule.SweepableFloatParamAttribute("Shrinkage", 0.025f, 4f, isLogScale:true)] + [Obsolete] + public double Shrinkage { get; set; } = 1d; - /// - /// Whether to collectivize features during dataset preparation to speed up training - /// - [Obsolete] - public bool FeatureFlocks { get; set; } = true; + /// + /// Dropout rate for tree regularization + /// + [TlcModule.SweepableDiscreteParamAttribute("DropoutRate", new object[]{0f, 1E-09f, 0.05f, 0.1f, 0.2f})] + [Obsolete] + public double DropoutRate { get; set; } - /// - /// Whether to do split based on multiple categorical feature values. - /// - [Obsolete] - public bool CategoricalSplit { get; set; } = false; + /// + /// Sample each query 1 in k times in the GetDerivatives function + /// + [Obsolete] + public int GetDerivativesSampleRate { get; set; } = 1; - /// - /// Maximum categorical split groups to consider when splitting on a categorical feature. Split groups are a collection of split points. This is used to reduce overfitting when there many categorical features. - /// - [Obsolete] - public int MaxCategoricalGroupsPerNode { get; set; } = 64; + /// + /// Write the last ensemble instead of the one determined by early stopping + /// + [Obsolete] + public bool WriteLastEnsemble { get; set; } = false; - /// - /// Maximum categorical split points to consider when splitting on a categorical feature. - /// - [Obsolete] - public int MaxCategoricalSplitPoints { get; set; } = 64; + /// + /// Upper bound on absolute value of single tree output + /// + [Obsolete] + public double MaxTreeOutput { get; set; } = 100d; - /// - /// Minimum categorical docs percentage in a bin to consider for a split. - /// - [Obsolete] - public double MinDocsPercentageForCategoricalSplit { get; set; } = 0.001d; + /// + /// Training starts from random ordering (determined by /r1) + /// + [Obsolete] + public bool RandomStart { get; set; } = false; - /// - /// Minimum categorical doc count in a bin to consider for a split. - /// - [Obsolete] - public int MinDocsForCategoricalSplit { get; set; } = 100; + /// + /// Filter zero lambdas during training + /// + [Obsolete] + public bool FilterZeroLambdas { get; set; } = false; + + /// + /// Freeform defining the scores that should be used as the baseline ranker + /// + [Obsolete] + public string BaselineScoresFormula { get; set; } - /// - /// Bias for calculating gradient for each feature bin for a categorical feature. - /// - [Obsolete] - public double Bias { get; set; } + /// + /// Baseline alpha for tradeoffs of risk (0 is normal training) + /// + [Obsolete] + public string BaselineAlphaRisk { get; set; } - /// - /// Bundle low population bins. Bundle.None(0): no bundling, Bundle.AggregateLowPopulation(1): Bundle low population, Bundle.Adjacent(2): Neighbor low population bundle. - /// - [Obsolete] - public Microsoft.ML.Legacy.Trainers.Bundle Bundling { get; set; } = Microsoft.ML.Legacy.Trainers.Bundle.None; + /// + /// The discount freeform which specifies the per position discounts of documents in a query (uses a single variable P for position where P=0 is first position) + /// + [Obsolete] + public string PositionDiscountFreeform { get; set; } - /// - /// Maximum number of distinct values (bins) per feature - /// - [Obsolete] - public int MaxBins { get; set; } = 255; + /// + /// Allows to choose Parallel FastTree Learning Algorithm + /// + [JsonConverter(typeof(ComponentSerializer))] + [Obsolete] + public ParallelTraining ParallelTrainer { get; set; } = new SingleParallelTraining(); - /// - /// Sparsity level needed to use sparse feature representation - /// - [Obsolete] - public double SparsifyThreshold { get; set; } = 0.7d; + /// + /// The number of threads to use + /// + [Obsolete] + public int? NumThreads { get; set; } - /// - /// The feature first use penalty coefficient - /// - [Obsolete] - public double FeatureFirstUsePenalty { get; set; } + /// + /// The seed of the random number generator + /// + [Obsolete] + public int RngSeed { get; set; } = 123; - /// - /// The feature re-use penalty (regularization) coefficient - /// - [Obsolete] - public double FeatureReusePenalty { get; set; } + /// + /// The seed of the active feature selection + /// + [Obsolete] + public int FeatureSelectSeed { get; set; } = 123; - /// - /// Tree fitting gain confidence requirement (should be in the range [0,1) ). - /// - [Obsolete] - public double GainConfidenceLevel { get; set; } + /// + /// The entropy (regularization) coefficient between 0 and 1 + /// + [Obsolete] + public double EntropyCoefficient { get; set; } - /// - /// The temperature of the randomized softmax distribution for choosing the feature - /// - [Obsolete] - public double SoftmaxTemperature { get; set; } + /// + /// The number of histograms in the pool (between 2 and numLeaves) + /// + [Obsolete] + public int HistogramPoolSize { get; set; } = -1; - /// - /// Print execution time breakdown to stdout - /// - [Obsolete] - public bool ExecutionTimes { get; set; } = false; + /// + /// Whether to utilize the disk or the data's native transposition facilities (where applicable) when performing the transpose + /// + [Obsolete] + public bool? DiskTranspose { get; set; } - /// - /// The max number of leaves in each regression tree - /// - [TlcModule.SweepableLongParamAttribute("NumLeaves", 2, 128, stepSize:4, isLogScale:true)] - [Obsolete] - public int NumLeaves { get; set; } = 20; + /// + /// Whether to collectivize features during dataset preparation to speed up training + /// + [Obsolete] + public bool FeatureFlocks { get; set; } = true; - /// - /// The minimal number of documents allowed in a leaf of a regression tree, out of the subsampled data - /// - [TlcModule.SweepableDiscreteParamAttribute("MinDocumentsInLeafs", new object[]{1, 10, 50})] - [Obsolete] - public int MinDocumentsInLeafs { get; set; } = 10; + /// + /// Whether to do split based on multiple categorical feature values. + /// + [Obsolete] + public bool CategoricalSplit { get; set; } = false; - /// - /// Total number of decision trees to create in the ensemble - /// - [TlcModule.SweepableDiscreteParamAttribute("NumTrees", new object[]{20, 100, 500})] - [Obsolete] - public int NumTrees { get; set; } = 100; + /// + /// Maximum categorical split groups to consider when splitting on a categorical feature. Split groups are a collection of split points. This is used to reduce overfitting when there many categorical features. + /// + [Obsolete] + public int MaxCategoricalGroupsPerNode { get; set; } = 64; - /// - /// The fraction of features (chosen randomly) to use on each iteration - /// - [Obsolete] - public double FeatureFraction { get; set; } = 1d; + /// + /// Maximum categorical split points to consider when splitting on a categorical feature. + /// + [Obsolete] + public int MaxCategoricalSplitPoints { get; set; } = 64; - /// - /// Number of trees in each bag (0 for disabling bagging) - /// - [Obsolete] - public int BaggingSize { get; set; } + /// + /// Minimum categorical docs percentage in a bin to consider for a split. + /// + [Obsolete] + public double MinDocsPercentageForCategoricalSplit { get; set; } = 0.001d; - /// - /// Percentage of training examples used in each bag - /// - [Obsolete] - public double BaggingTrainFraction { get; set; } = 0.7d; + /// + /// Minimum categorical doc count in a bin to consider for a split. + /// + [Obsolete] + public int MinDocsForCategoricalSplit { get; set; } = 100; - /// - /// The fraction of features (chosen randomly) to use on each split - /// - [Obsolete] - public double SplitFraction { get; set; } = 1d; + /// + /// Bias for calculating gradient for each feature bin for a categorical feature. + /// + [Obsolete] + public double Bias { get; set; } - /// - /// Smoothing paramter for tree regularization - /// - [Obsolete] - public double Smoothing { get; set; } + /// + /// Bundle low population bins. Bundle.None(0): no bundling, Bundle.AggregateLowPopulation(1): Bundle low population, Bundle.Adjacent(2): Neighbor low population bundle. + /// + [Obsolete] + public Microsoft.ML.Legacy.Trainers.Bundle Bundling { get; set; } = Microsoft.ML.Legacy.Trainers.Bundle.None; - /// - /// When a root split is impossible, allow training to proceed - /// - [Obsolete] - public bool AllowEmptyTrees { get; set; } = true; + /// + /// Maximum number of distinct values (bins) per feature + /// + [Obsolete] + public int MaxBins { get; set; } = 255; - /// - /// The level of feature compression to use - /// - [Obsolete] - public int FeatureCompressionLevel { get; set; } = 1; + /// + /// Sparsity level needed to use sparse feature representation + /// + [Obsolete] + public double SparsifyThreshold { get; set; } = 0.7d; - /// - /// Compress the tree Ensemble - /// - [Obsolete] - public bool CompressEnsemble { get; set; } = false; + /// + /// The feature first use penalty coefficient + /// + [Obsolete] + public double FeatureFirstUsePenalty { get; set; } - /// - /// Maximum Number of trees after compression - /// - [Obsolete] - public int MaxTreesAfterCompression { get; set; } = -1; + /// + /// The feature re-use penalty (regularization) coefficient + /// + [Obsolete] + public double FeatureReusePenalty { get; set; } - /// - /// Print metrics graph for the first test set - /// - [Obsolete] - public bool PrintTestGraph { get; set; } = false; + /// + /// Tree fitting gain confidence requirement (should be in the range [0,1) ). + /// + [Obsolete] + public double GainConfidenceLevel { get; set; } - /// - /// Print Train and Validation metrics in graph - /// - [Obsolete] - public bool PrintTrainValidGraph { get; set; } = false; + /// + /// The temperature of the randomized softmax distribution for choosing the feature + /// + [Obsolete] + public double SoftmaxTemperature { get; set; } - /// - /// Calculate metric values for train/valid/test every k rounds - /// - [Obsolete] - public int TestFrequency { get; set; } = 2147483647; + /// + /// Print execution time breakdown to stdout + /// + [Obsolete] + public bool ExecutionTimes { get; set; } = false; - /// - /// Column to use for example groupId - /// - [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional GroupIdColumn { get; set; } + /// + /// The max number of leaves in each regression tree + /// + [TlcModule.SweepableLongParamAttribute("NumLeaves", 2, 128, stepSize:4, isLogScale:true)] + [Obsolete] + public int NumLeaves { get; set; } = 20; - /// - /// Column to use for example weight - /// - [Obsolete] - public Microsoft.ML.Runtime.EntryPoints.Optional WeightColumn { get; set; } + /// + /// The minimal number of documents allowed in a leaf of a regression tree, out of the subsampled data + /// + [TlcModule.SweepableDiscreteParamAttribute("MinDocumentsInLeafs", new object[]{1, 10, 50})] + [Obsolete] + public int MinDocumentsInLeafs { get; set; } = 10; - /// - /// Column to use for labels - /// - [Obsolete] - public string LabelColumn { get; set; } = "Label"; + /// + /// Total number of decision trees to create in the ensemble + /// + [TlcModule.SweepableDiscreteParamAttribute("NumTrees", new object[]{20, 100, 500})] + [Obsolete] + public int NumTrees { get; set; } = 100; - /// - /// The data to be used for training - /// - [Obsolete] - public Var TrainingData { get; set; } = new Var(); + /// + /// The fraction of features (chosen randomly) to use on each iteration + /// + [Obsolete] + public double FeatureFraction { get; set; } = 1d; - /// - /// Column to use for features - /// - [Obsolete] - public string FeatureColumn { get; set; } = "Features"; + /// + /// Number of trees in each bag (0 for disabling bagging) + /// + [Obsolete] + public int BaggingSize { get; set; } - /// - /// Normalize option for the feature column - /// - [Obsolete] - public Microsoft.ML.Legacy.Models.NormalizeOption NormalizeFeatures { get; set; } = Microsoft.ML.Legacy.Models.NormalizeOption.Auto; + /// + /// Percentage of training examples used in each bag + /// + [Obsolete] + public double BaggingTrainFraction { get; set; } = 0.7d; - /// - /// Whether learner should cache input training data - /// - [Obsolete] - public Microsoft.ML.Legacy.Models.CachingOptions Caching { get; set; } = Microsoft.ML.Legacy.Models.CachingOptions.Auto; + /// + /// The fraction of features (chosen randomly) to use on each split + /// + [Obsolete] + public double SplitFraction { get; set; } = 1d; - [Obsolete] - internal override string ComponentName => "FastTreeTweedieRegression"; - } + /// + /// Smoothing paramter for tree regularization + /// + [Obsolete] + public double Smoothing { get; set; } + /// + /// When a root split is impossible, allow training to proceed + /// [Obsolete] - public abstract class NgramExtractor : ComponentKind {} + public bool AllowEmptyTrees { get; set; } = true; + /// + /// The level of feature compression to use + /// + [Obsolete] + public int FeatureCompressionLevel { get; set; } = 1; + /// + /// Compress the tree Ensemble + /// + [Obsolete] + public bool CompressEnsemble { get; set; } = false; /// - /// Extracts NGrams from text and convert them to vector using dictionary. + /// Maximum Number of trees after compression /// [Obsolete] - public sealed class NGramNgramExtractor : NgramExtractor - { - /// - /// Ngram length - /// - [Obsolete] - public int NgramLength { get; set; } = 1; + public int MaxTreesAfterCompression { get; set; } = -1; - /// - /// Maximum number of tokens to skip when constructing an ngram - /// - [Obsolete] - public int SkipLength { get; set; } + /// + /// Print metrics graph for the first test set + /// + [Obsolete] + public bool PrintTestGraph { get; set; } = false; - /// - /// Whether to include all ngram lengths up to NgramLength or only NgramLength - /// - [Obsolete] - public bool AllLengths { get; set; } = true; + /// + /// Print Train and Validation metrics in graph + /// + [Obsolete] + public bool PrintTrainValidGraph { get; set; } = false; - /// - /// Maximum number of ngrams to store in the dictionary - /// - [Obsolete] - public int[] MaxNumTerms { get; set; } = { 10000000 }; + /// + /// Calculate metric values for train/valid/test every k rounds + /// + [Obsolete] + public int TestFrequency { get; set; } = 2147483647; - /// - /// The weighting criteria - /// - [Obsolete] - public Microsoft.ML.Legacy.Transforms.NgramExtractingEstimatorWeightingCriteria Weighting { get; set; } = Microsoft.ML.Legacy.Transforms.NgramExtractingEstimatorWeightingCriteria.Tf; + /// + /// Column to use for example groupId + /// + [Obsolete] + public Microsoft.ML.EntryPoints.Optional GroupIdColumn { get; set; } - [Obsolete] - internal override string ComponentName => "NGram"; - } + /// + /// Column to use for example weight + /// + [Obsolete] + public Microsoft.ML.EntryPoints.Optional WeightColumn { get; set; } + /// + /// Column to use for labels + /// + [Obsolete] + public string LabelColumn { get; set; } = "Label"; + /// + /// The data to be used for training + /// + [Obsolete] + public Var TrainingData { get; set; } = new Var(); /// - /// Extracts NGrams from text and convert them to vector using hashing trick. + /// Column to use for features /// [Obsolete] - public sealed class NGramHashNgramExtractor : NgramExtractor - { - /// - /// Ngram length - /// - [Obsolete] - public int NgramLength { get; set; } = 1; + public string FeatureColumn { get; set; } = "Features"; - /// - /// Maximum number of tokens to skip when constructing an ngram - /// - [Obsolete] - public int SkipLength { get; set; } + /// + /// Normalize option for the feature column + /// + [Obsolete] + public Microsoft.ML.Legacy.Models.NormalizeOption NormalizeFeatures { get; set; } = Microsoft.ML.Legacy.Models.NormalizeOption.Auto; - /// - /// Number of bits to hash into. Must be between 1 and 30, inclusive. - /// - [Obsolete] - public int HashBits { get; set; } = 16; + /// + /// Whether learner should cache input training data + /// + [Obsolete] + public Microsoft.ML.Legacy.Models.CachingOptions Caching { get; set; } = Microsoft.ML.Legacy.Models.CachingOptions.Auto; - /// - /// Hashing seed - /// - [Obsolete] - public uint Seed { get; set; } = 314489979; + [Obsolete] + internal override string ComponentName => "FastTreeTweedieRegression"; + } - /// - /// Whether the position of each source column should be included in the hash (when there are multiple source columns). - /// - [Obsolete] - public bool Ordered { get; set; } = true; + [Obsolete] + public abstract class NgramExtractor : ComponentKind {} - /// - /// Limit the number of keys used to generate the slot name to this many. 0 means no invert hashing, -1 means no limit. - /// - [Obsolete] - public int InvertHash { get; set; } - /// - /// Whether to include all ngram lengths up to ngramLength or only ngramLength - /// - [Obsolete] - public bool AllLengths { get; set; } = true; - [Obsolete] - internal override string ComponentName => "NGramHash"; - } + /// + /// Extracts NGrams from text and convert them to vector using dictionary. + /// + [Obsolete] + public sealed class NGramNgramExtractor : NgramExtractor + { + /// + /// Ngram length + /// + [Obsolete] + public int NgramLength { get; set; } = 1; + /// + /// Maximum number of tokens to skip when constructing an ngram + /// [Obsolete] - public abstract class ParallelLightGBM : ComponentKind {} + public int SkipLength { get; set; } + /// + /// Whether to include all ngram lengths up to NgramLength or only NgramLength + /// + [Obsolete] + public bool AllLengths { get; set; } = true; + /// + /// Maximum number of ngrams to store in the dictionary + /// + [Obsolete] + public int[] MaxNumTerms { get; set; } = { 10000000 }; /// - /// Single node machine learning process. + /// The weighting criteria /// [Obsolete] - public sealed class SingleParallelLightGBM : ParallelLightGBM - { - [Obsolete] - internal override string ComponentName => "Single"; - } + public Microsoft.ML.Legacy.Transforms.NgramExtractingEstimatorWeightingCriteria Weighting { get; set; } = Microsoft.ML.Legacy.Transforms.NgramExtractingEstimatorWeightingCriteria.Tf; [Obsolete] - public abstract class ParallelTraining : ComponentKind {} + internal override string ComponentName => "NGram"; + } + /// + /// Extracts NGrams from text and convert them to vector using hashing trick. + /// + [Obsolete] + public sealed class NGramHashNgramExtractor : NgramExtractor + { /// - /// Single node machine learning process. + /// Ngram length /// [Obsolete] - public sealed class SingleParallelTraining : ParallelTraining - { - [Obsolete] - internal override string ComponentName => "Single"; - } + public int NgramLength { get; set; } = 1; + /// + /// Maximum number of tokens to skip when constructing an ngram + /// [Obsolete] - public abstract class PartitionedPathParser : ComponentKind {} + public int SkipLength { get; set; } + /// + /// Number of bits to hash into. Must be between 1 and 30, inclusive. + /// + [Obsolete] + public int HashBits { get; set; } = 16; + /// + /// Hashing seed + /// + [Obsolete] + public uint Seed { get; set; } = 314489979; /// - /// Extract name/value pairs from Parquet formatted directory names. Example path: Year=2018/Month=12/data1.parquet + /// Whether the position of each source column should be included in the hash (when there are multiple source columns). /// [Obsolete] - public sealed class ParquetPathParserPartitionedPathParser : PartitionedPathParser - { - [Obsolete] - internal override string ComponentName => "ParquetPathParser"; - } + public bool Ordered { get; set; } = true; + /// + /// Limit the number of keys used to generate the slot name to this many. 0 means no invert hashing, -1 means no limit. + /// + [Obsolete] + public int InvertHash { get; set; } + /// + /// Whether to include all ngram lengths up to ngramLength or only ngramLength + /// [Obsolete] - public sealed partial class PartitionedFileLoaderColumn - { - /// - /// Name of the column. - /// - [Obsolete] - public string Name { get; set; } + public bool AllLengths { get; set; } = true; - /// - /// Data type of the column. - /// - [Obsolete] - public Microsoft.ML.Legacy.Data.DataKind? Type { get; set; } + [Obsolete] + internal override string ComponentName => "NGramHash"; + } - /// - /// Index of the directory representing this column. - /// - [Obsolete] - public int Source { get; set; } + [Obsolete] + public abstract class ParallelLightGBM : ComponentKind {} - } - /// - /// A simple parser that extracts directory names as column values. Column names are defined as arguments. - /// + /// + /// Single node machine learning process. + /// + [Obsolete] + public sealed class SingleParallelLightGBM : ParallelLightGBM + { [Obsolete] - public sealed class SimplePathParserPartitionedPathParser : PartitionedPathParser - { - /// - /// Column definitions used to override the Partitioned Path Parser. Expected with the format name:type:numeric-source, for example, col=MyFeature:R4:1 - /// - [Obsolete] - public PartitionedFileLoaderColumn[] Columns { get; set; } + internal override string ComponentName => "Single"; + } + + [Obsolete] + public abstract class ParallelTraining : ComponentKind {} - /// - /// Data type of each column. - /// - [Obsolete] - public Microsoft.ML.Legacy.Data.DataKind Type { get; set; } = Microsoft.ML.Legacy.Data.DataKind.TX; - [Obsolete] - internal override string ComponentName => "SimplePathParser"; - } + /// + /// Single node machine learning process. + /// + [Obsolete] + public sealed class SingleParallelTraining : ParallelTraining + { [Obsolete] - public abstract class RegressionLossFunction : ComponentKind {} + internal override string ComponentName => "Single"; + } + [Obsolete] + public abstract class PartitionedPathParser : ComponentKind {} + + /// + /// Extract name/value pairs from Parquet formatted directory names. Example path: Year=2018/Month=12/data1.parquet + /// + [Obsolete] + public sealed class ParquetPathParserPartitionedPathParser : PartitionedPathParser + { + [Obsolete] + internal override string ComponentName => "ParquetPathParser"; + } + + + [Obsolete] + public sealed partial class PartitionedFileLoaderColumn + { /// - /// Poisson loss. + /// Name of the column. /// [Obsolete] - public sealed class PoissonLossRegressionLossFunction : RegressionLossFunction - { - [Obsolete] - internal override string ComponentName => "PoissonLoss"; - } - + public string Name { get; set; } + /// + /// Data type of the column. + /// + [Obsolete] + public Microsoft.ML.Legacy.Data.DataKind? Type { get; set; } /// - /// Squared loss. + /// Index of the directory representing this column. /// [Obsolete] - public sealed class SquaredLossRegressionLossFunction : RegressionLossFunction - { - [Obsolete] - internal override string ComponentName => "SquaredLoss"; - } + public int Source { get; set; } + } + /// + /// A simple parser that extracts directory names as column values. Column names are defined as arguments. + /// + [Obsolete] + public sealed class SimplePathParserPartitionedPathParser : PartitionedPathParser + { /// - /// Tweedie loss. + /// Column definitions used to override the Partitioned Path Parser. Expected with the format name:type:numeric-source, for example, col=MyFeature:R4:1 /// [Obsolete] - public sealed class TweedieLossRegressionLossFunction : RegressionLossFunction - { - /// - /// Index parameter for the Tweedie distribution, in the range [1, 2]. 1 is Poisson loss, 2 is gamma loss, and intermediate values are compound Poisson loss. - /// - [Obsolete] - public double Index { get; set; } = 1.5d; + public PartitionedFileLoaderColumn[] Columns { get; set; } - [Obsolete] - internal override string ComponentName => "TweedieLoss"; - } + /// + /// Data type of each column. + /// + [Obsolete] + public Microsoft.ML.Legacy.Data.DataKind Type { get; set; } = Microsoft.ML.Legacy.Data.DataKind.TX; [Obsolete] - public abstract class SDCAClassificationLossFunction : ComponentKind {} + internal override string ComponentName => "SimplePathParser"; + } + [Obsolete] + public abstract class RegressionLossFunction : ComponentKind {} - /// - /// Hinge loss. - /// + + /// + /// Poisson loss. + /// + [Obsolete] + public sealed class PoissonLossRegressionLossFunction : RegressionLossFunction + { [Obsolete] - public sealed class HingeLossSDCAClassificationLossFunction : SDCAClassificationLossFunction - { - /// - /// Margin value - /// - [Obsolete] - public float Margin { get; set; } = 1f; + internal override string ComponentName => "PoissonLoss"; + } - [Obsolete] - internal override string ComponentName => "HingeLoss"; - } + + + /// + /// Squared loss. + /// + [Obsolete] + public sealed class SquaredLossRegressionLossFunction : RegressionLossFunction + { + [Obsolete] + internal override string ComponentName => "SquaredLoss"; + } + /// + /// Tweedie loss. + /// + [Obsolete] + public sealed class TweedieLossRegressionLossFunction : RegressionLossFunction + { /// - /// Log loss. + /// Index parameter for the Tweedie distribution, in the range [1, 2]. 1 is Poisson loss, 2 is gamma loss, and intermediate values are compound Poisson loss. /// [Obsolete] - public sealed class LogLossSDCAClassificationLossFunction : SDCAClassificationLossFunction - { - [Obsolete] - internal override string ComponentName => "LogLoss"; - } + public double Index { get; set; } = 1.5d; + + [Obsolete] + internal override string ComponentName => "TweedieLoss"; + } + [Obsolete] + public abstract class SDCAClassificationLossFunction : ComponentKind {} + + /// + /// Hinge loss. + /// + [Obsolete] + public sealed class HingeLossSDCAClassificationLossFunction : SDCAClassificationLossFunction + { /// - /// Smoothed Hinge loss. + /// Margin value /// [Obsolete] - public sealed class SmoothedHingeLossSDCAClassificationLossFunction : SDCAClassificationLossFunction - { - /// - /// Smoothing constant - /// - [Obsolete] - public float SmoothingConst { get; set; } = 1f; + public float Margin { get; set; } = 1f; - [Obsolete] - internal override string ComponentName => "SmoothedHingeLoss"; - } + [Obsolete] + internal override string ComponentName => "HingeLoss"; + } + + + /// + /// Log loss. + /// + [Obsolete] + public sealed class LogLossSDCAClassificationLossFunction : SDCAClassificationLossFunction + { [Obsolete] - public abstract class SDCARegressionLossFunction : ComponentKind {} + internal override string ComponentName => "LogLoss"; + } + /// + /// Smoothed Hinge loss. + /// + [Obsolete] + public sealed class SmoothedHingeLossSDCAClassificationLossFunction : SDCAClassificationLossFunction + { /// - /// Squared loss. + /// Smoothing constant /// [Obsolete] - public sealed class SquaredLossSDCARegressionLossFunction : SDCARegressionLossFunction - { - [Obsolete] - internal override string ComponentName => "SquaredLoss"; - } + public float SmoothingConst { get; set; } = 1f; [Obsolete] - public abstract class StopWordsRemover : ComponentKind {} + internal override string ComponentName => "SmoothedHingeLoss"; + } + [Obsolete] + public abstract class SDCARegressionLossFunction : ComponentKind {} - /// - /// Remover with list of stopwords specified by the user. - /// + + /// + /// Squared loss. + /// + [Obsolete] + public sealed class SquaredLossSDCARegressionLossFunction : SDCARegressionLossFunction + { [Obsolete] - public sealed class CustomStopWordsRemover : StopWordsRemover - { - /// - /// List of stopwords - /// - [Obsolete] - public string[] Stopword { get; set; } + internal override string ComponentName => "SquaredLoss"; + } - [Obsolete] - internal override string ComponentName => "Custom"; - } + [Obsolete] + public abstract class StopWordsRemover : ComponentKind {} + /// + /// Remover with list of stopwords specified by the user. + /// + [Obsolete] + public sealed class CustomStopWordsRemover : StopWordsRemover + { /// - /// Remover with predefined list of stop words. + /// List of stopwords /// [Obsolete] - public sealed class PredefinedStopWordsRemover : StopWordsRemover - { - [Obsolete] - internal override string ComponentName => "Predefined"; - } + public string[] Stopword { get; set; } + [Obsolete] + internal override string ComponentName => "Custom"; + } + + + + /// + /// Remover with predefined list of stop words. + /// + [Obsolete] + public sealed class PredefinedStopWordsRemover : StopWordsRemover + { + [Obsolete] + internal override string ComponentName => "Predefined"; } + } #pragma warning restore diff --git a/src/Microsoft.ML.Legacy/Data/CollectionDataSource.cs b/src/Microsoft.ML.Legacy/Data/CollectionDataSource.cs index ae0b7cf9ad..e95aa0cb56 100644 --- a/src/Microsoft.ML.Legacy/Data/CollectionDataSource.cs +++ b/src/Microsoft.ML.Legacy/Data/CollectionDataSource.cs @@ -3,10 +3,8 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Legacy/Data/TextLoader.cs b/src/Microsoft.ML.Legacy/Data/TextLoader.cs index 6e6dab405d..b4f2960e58 100644 --- a/src/Microsoft.ML.Legacy/Data/TextLoader.cs +++ b/src/Microsoft.ML.Legacy/Data/TextLoader.cs @@ -3,8 +3,6 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using System; using System.Collections.Generic; using System.Linq; @@ -13,74 +11,74 @@ namespace Microsoft.ML.Legacy.Data { - public sealed partial class TextLoaderRange - { - public TextLoaderRange() + public sealed partial class TextLoaderRange { - } + public TextLoaderRange() + { + } - /// - /// Convenience constructor for the scalar case, when a given column - /// in the schema spans only a single column in the dataset. - /// and are set to the single value . - /// - /// Column index in the dataset. - public TextLoaderRange(int ordinal) - { + /// + /// Convenience constructor for the scalar case, when a given column + /// in the schema spans only a single column in the dataset. + /// and are set to the single value . + /// + /// Column index in the dataset. + public TextLoaderRange(int ordinal) + { - Contracts.CheckParam(ordinal >= 0, nameof(ordinal), "Cannot be a negative number"); + Contracts.CheckParam(ordinal >= 0, nameof(ordinal), "Cannot be a negative number"); - Min = ordinal; - Max = ordinal; - } + Min = ordinal; + Max = ordinal; + } - /// - /// Convenience constructor for the vector case, when a given column - /// in the schema spans contiguous columns in the dataset. - /// - /// Starting column index in the dataset. - /// Ending column index in the dataset. - public TextLoaderRange(int min, int max) - { + /// + /// Convenience constructor for the vector case, when a given column + /// in the schema spans contiguous columns in the dataset. + /// + /// Starting column index in the dataset. + /// Ending column index in the dataset. + public TextLoaderRange(int min, int max) + { - Contracts.CheckParam(min >= 0, nameof(min), "Cannot be a negative number."); - Contracts.CheckParam(max >= min, nameof(max), "Cannot be less than " + nameof(min) +"."); + Contracts.CheckParam(min >= 0, nameof(min), "Cannot be a negative number."); + Contracts.CheckParam(max >= min, nameof(max), "Cannot be less than " + nameof(min) + "."); - Min = min; - Max = max; + Min = min; + Max = max; + } } - } - - public sealed partial class TextLoader - { - /// - /// Construct a TextLoader object by inferencing the dataset schema from a type. - /// - /// Does the file contains header? - /// Column separator character. Default is '\t' - /// Whether the input may include quoted values, - /// which can contain separator characters, colons, - /// and distinguish empty values from missing values. When true, consecutive separators - /// denote a missing value and an empty value is denoted by \"\". - /// When false, consecutive separators denote an empty value. - /// Whether the input may include sparse representations for example, - /// if one of the row contains "5 2:6 4:3" that's mean there are 5 columns all zero - /// except for 3rd and 5th columns which have values 6 and 3 - /// Remove trailing whitespace from lines - public TextLoader CreateFrom(bool useHeader = false, - char separator = '\t', bool allowQuotedStrings = true, - bool supportSparse = true, bool trimWhitespace = false) + + public sealed partial class TextLoader { - var userType = typeof(TInput); + /// + /// Construct a TextLoader object by inferencing the dataset schema from a type. + /// + /// Does the file contains header? + /// Column separator character. Default is '\t' + /// Whether the input may include quoted values, + /// which can contain separator characters, colons, + /// and distinguish empty values from missing values. When true, consecutive separators + /// denote a missing value and an empty value is denoted by \"\". + /// When false, consecutive separators denote an empty value. + /// Whether the input may include sparse representations for example, + /// if one of the row contains "5 2:6 4:3" that's mean there are 5 columns all zero + /// except for 3rd and 5th columns which have values 6 and 3 + /// Remove trailing whitespace from lines + public TextLoader CreateFrom(bool useHeader = false, + char separator = '\t', bool allowQuotedStrings = true, + bool supportSparse = true, bool trimWhitespace = false) + { + var userType = typeof(TInput); - var fieldInfos = userType.GetFields(BindingFlags.Public | BindingFlags.Instance); + var fieldInfos = userType.GetFields(BindingFlags.Public | BindingFlags.Instance); - var propertyInfos = - userType - .GetProperties(BindingFlags.Public | BindingFlags.Instance) - .Where(x => x.CanRead && x.CanWrite && x.GetGetMethod() != null && x.GetSetMethod() != null && x.GetIndexParameters().Length == 0); + var propertyInfos = + userType + .GetProperties(BindingFlags.Public | BindingFlags.Instance) + .Where(x => x.CanRead && x.CanWrite && x.GetGetMethod() != null && x.GetSetMethod() != null && x.GetIndexParameters().Length == 0); - var memberInfos = (fieldInfos as IEnumerable).Concat(propertyInfos).ToArray(); + var memberInfos = (fieldInfos as IEnumerable).Concat(propertyInfos).ToArray(); Arguments.Column = new TextLoaderColumn[memberInfos.Length]; for (int index = 0; index < memberInfos.Length; index++) @@ -97,108 +95,108 @@ public TextLoader CreateFrom(bool useHeader = false, var mappingNameAttr = memberInfo.GetCustomAttribute(); var name = mappingNameAttr?.Name ?? memberInfo.Name; - Runtime.Data.TextLoader.Range[] sources; - if (!Runtime.Data.TextLoader.Column.TryParseSourceEx(mappingAttr.Start, out sources)) + ML.Data.TextLoader.Range[] sources; + if (!ML.Data.TextLoader.Column.TryParseSourceEx(mappingAttr.Start, out sources)) throw Contracts.Except($"{mappingAttr.Start} could not be parsed."); #pragma warning restore 618 Contracts.Assert(sources != null); - TextLoaderColumn tlc = new TextLoaderColumn(); - tlc.Name = name; - tlc.Source = new TextLoaderRange[sources.Length]; - DataKind dk; - switch (memberInfo) - { - case FieldInfo field: - if (!TryGetDataKind(field.FieldType.IsArray ? field.FieldType.GetElementType() : field.FieldType, out dk)) - throw Contracts.Except($"Field {name} is of unsupported type."); + TextLoaderColumn tlc = new TextLoaderColumn(); + tlc.Name = name; + tlc.Source = new TextLoaderRange[sources.Length]; + DataKind dk; + switch (memberInfo) + { + case FieldInfo field: + if (!TryGetDataKind(field.FieldType.IsArray ? field.FieldType.GetElementType() : field.FieldType, out dk)) + throw Contracts.Except($"Field {name} is of unsupported type."); - break; + break; - case PropertyInfo property: - if (!TryGetDataKind(property.PropertyType.IsArray ? property.PropertyType.GetElementType() : property.PropertyType, out dk)) - throw Contracts.Except($"Property {name} is of unsupported type."); - break; + case PropertyInfo property: + if (!TryGetDataKind(property.PropertyType.IsArray ? property.PropertyType.GetElementType() : property.PropertyType, out dk)) + throw Contracts.Except($"Property {name} is of unsupported type."); + break; - default: - Contracts.Assert(false); - throw Contracts.ExceptNotSupp("Expected a FieldInfo or a PropertyInfo"); - } + default: + Contracts.Assert(false); + throw Contracts.ExceptNotSupp("Expected a FieldInfo or a PropertyInfo"); + } - tlc.Type = dk; + tlc.Type = dk; - for (int indexLocal = 0; indexLocal < tlc.Source.Length; indexLocal++) - { - tlc.Source[indexLocal] = new TextLoaderRange + for (int indexLocal = 0; indexLocal < tlc.Source.Length; indexLocal++) { - AllOther = sources[indexLocal].AllOther, - AutoEnd = sources[indexLocal].AutoEnd, - ForceVector = sources[indexLocal].ForceVector, - VariableEnd = sources[indexLocal].VariableEnd, - Max = sources[indexLocal].Max, - Min = sources[indexLocal].Min - }; + tlc.Source[indexLocal] = new TextLoaderRange + { + AllOther = sources[indexLocal].AllOther, + AutoEnd = sources[indexLocal].AutoEnd, + ForceVector = sources[indexLocal].ForceVector, + VariableEnd = sources[indexLocal].VariableEnd, + Max = sources[indexLocal].Max, + Min = sources[indexLocal].Min + }; + } + + Arguments.Column[index] = tlc; } - Arguments.Column[index] = tlc; - } - - Arguments.HasHeader = useHeader; - Arguments.Separator = new[] { separator }; - Arguments.AllowQuoting = allowQuotedStrings; - Arguments.AllowSparse = supportSparse; - Arguments.TrimWhitespace = trimWhitespace; + Arguments.HasHeader = useHeader; + Arguments.Separator = new[] { separator }; + Arguments.AllowQuoting = allowQuotedStrings; + Arguments.AllowSparse = supportSparse; + Arguments.TrimWhitespace = trimWhitespace; - return this; - } + return this; + } - /// - /// Try to map a System.Type to a corresponding DataKind value. - /// - private static bool TryGetDataKind(Type type, out DataKind kind) - { - Contracts.AssertValue(type); - - // REVIEW: Make this more efficient. Should we have a global dictionary? - if (type == typeof(sbyte)) - kind = DataKind.I1; - else if (type == typeof(byte) || type == typeof(char)) - kind = DataKind.U1; - else if (type == typeof(short)) - kind = DataKind.I2; - else if (type == typeof(ushort)) - kind = DataKind.U2; - else if ( type == typeof(int)) - kind = DataKind.I4; - else if (type == typeof(uint)) - kind = DataKind.U4; - else if (type == typeof(long)) - kind = DataKind.I8; - else if (type == typeof(ulong)) - kind = DataKind.U8; - else if (type == typeof(Single)) - kind = DataKind.R4; - else if (type == typeof(Double)) - kind = DataKind.R8; - else if (type == typeof(ReadOnlyMemory) || type == typeof(string)) - kind = DataKind.TX; - else if (type == typeof(bool)) - kind = DataKind.BL; - else if (type == typeof(TimeSpan)) - kind = DataKind.TS; - else if (type == typeof(DateTime)) - kind = DataKind.DT; - else if (type == typeof(DateTimeOffset)) - kind = DataKind.DZ; - else if (type == typeof(RowId)) - kind = DataKind.UG; - else + /// + /// Try to map a System.Type to a corresponding DataKind value. + /// + private static bool TryGetDataKind(Type type, out DataKind kind) { - kind = default(DataKind); - return false; - } + Contracts.AssertValue(type); + + // REVIEW: Make this more efficient. Should we have a global dictionary? + if (type == typeof(sbyte)) + kind = DataKind.I1; + else if (type == typeof(byte) || type == typeof(char)) + kind = DataKind.U1; + else if (type == typeof(short)) + kind = DataKind.I2; + else if (type == typeof(ushort)) + kind = DataKind.U2; + else if (type == typeof(int)) + kind = DataKind.I4; + else if (type == typeof(uint)) + kind = DataKind.U4; + else if (type == typeof(long)) + kind = DataKind.I8; + else if (type == typeof(ulong)) + kind = DataKind.U8; + else if (type == typeof(Single)) + kind = DataKind.R4; + else if (type == typeof(Double)) + kind = DataKind.R8; + else if (type == typeof(ReadOnlyMemory) || type == typeof(string)) + kind = DataKind.TX; + else if (type == typeof(bool)) + kind = DataKind.BL; + else if (type == typeof(TimeSpan)) + kind = DataKind.TS; + else if (type == typeof(DateTime)) + kind = DataKind.DT; + else if (type == typeof(DateTimeOffset)) + kind = DataKind.DZ; + else if (type == typeof(RowId)) + kind = DataKind.UG; + else + { + kind = default(DataKind); + return false; + } - return true; + return true; + } } - } } diff --git a/src/Microsoft.ML.Legacy/ILearningPipelineItem.cs b/src/Microsoft.ML.Legacy/ILearningPipelineItem.cs index f0b3019c87..4a7d452963 100644 --- a/src/Microsoft.ML.Legacy/ILearningPipelineItem.cs +++ b/src/Microsoft.ML.Legacy/ILearningPipelineItem.cs @@ -2,9 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; using System; namespace Microsoft.ML.Legacy diff --git a/src/Microsoft.ML.Legacy/LearningPipeline.cs b/src/Microsoft.ML.Legacy/LearningPipeline.cs index 944fe1b04c..701fa5721d 100644 --- a/src/Microsoft.ML.Legacy/LearningPipeline.cs +++ b/src/Microsoft.ML.Legacy/LearningPipeline.cs @@ -3,9 +3,7 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML.EntryPoints; using System; using System.Collections; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Legacy/LearningPipelineDebugProxy.cs b/src/Microsoft.ML.Legacy/LearningPipelineDebugProxy.cs index 4a3c4d46cb..da4cb8da1f 100644 --- a/src/Microsoft.ML.Legacy/LearningPipelineDebugProxy.cs +++ b/src/Microsoft.ML.Legacy/LearningPipelineDebugProxy.cs @@ -2,15 +2,13 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; using Microsoft.ML.Legacy.Transforms; using System; using System.Collections.Generic; using System.Diagnostics; using System.Linq; using System.Text; -using Microsoft.ML.Data; namespace Microsoft.ML.Legacy { diff --git a/src/Microsoft.ML.Legacy/Models/BinaryClassificationEvaluator.cs b/src/Microsoft.ML.Legacy/Models/BinaryClassificationEvaluator.cs index 4ef85f8d4e..9fecd9a73d 100644 --- a/src/Microsoft.ML.Legacy/Models/BinaryClassificationEvaluator.cs +++ b/src/Microsoft.ML.Legacy/Models/BinaryClassificationEvaluator.cs @@ -3,8 +3,8 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Legacy.Transforms; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; namespace Microsoft.ML.Legacy.Models { diff --git a/src/Microsoft.ML.Legacy/Models/BinaryClassificationMetrics.cs b/src/Microsoft.ML.Legacy/Models/BinaryClassificationMetrics.cs index 3668cca261..9dfc3f4083 100644 --- a/src/Microsoft.ML.Legacy/Models/BinaryClassificationMetrics.cs +++ b/src/Microsoft.ML.Legacy/Models/BinaryClassificationMetrics.cs @@ -3,11 +3,9 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using System; using System.Collections.Generic; -using static Microsoft.ML.Runtime.Data.MetricKinds; +using static Microsoft.ML.Data.MetricKinds; namespace Microsoft.ML.Legacy.Models { diff --git a/src/Microsoft.ML.Legacy/Models/ClassificationEvaluator.cs b/src/Microsoft.ML.Legacy/Models/ClassificationEvaluator.cs index 5d644baf32..77cbf0818e 100644 --- a/src/Microsoft.ML.Legacy/Models/ClassificationEvaluator.cs +++ b/src/Microsoft.ML.Legacy/Models/ClassificationEvaluator.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.Legacy.Transforms; namespace Microsoft.ML.Legacy.Models diff --git a/src/Microsoft.ML.Legacy/Models/ClassificationMetrics.cs b/src/Microsoft.ML.Legacy/Models/ClassificationMetrics.cs index 68d8620d97..88e765a363 100644 --- a/src/Microsoft.ML.Legacy/Models/ClassificationMetrics.cs +++ b/src/Microsoft.ML.Legacy/Models/ClassificationMetrics.cs @@ -3,11 +3,9 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using System; using System.Collections.Generic; -using static Microsoft.ML.Runtime.Data.MetricKinds; +using static Microsoft.ML.Data.MetricKinds; namespace Microsoft.ML.Legacy.Models { diff --git a/src/Microsoft.ML.Legacy/Models/ClusterEvaluator.cs b/src/Microsoft.ML.Legacy/Models/ClusterEvaluator.cs index 5d12ad85f9..0c41f78413 100644 --- a/src/Microsoft.ML.Legacy/Models/ClusterEvaluator.cs +++ b/src/Microsoft.ML.Legacy/Models/ClusterEvaluator.cs @@ -3,8 +3,8 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Legacy.Transforms; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; namespace Microsoft.ML.Legacy.Models { diff --git a/src/Microsoft.ML.Legacy/Models/ClusterMetrics.cs b/src/Microsoft.ML.Legacy/Models/ClusterMetrics.cs index dbb6640663..1a797342d3 100644 --- a/src/Microsoft.ML.Legacy/Models/ClusterMetrics.cs +++ b/src/Microsoft.ML.Legacy/Models/ClusterMetrics.cs @@ -3,11 +3,9 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using System; using System.Collections.Generic; -using static Microsoft.ML.Runtime.Data.MetricKinds; +using static Microsoft.ML.Data.MetricKinds; namespace Microsoft.ML.Legacy.Models { @@ -88,13 +86,13 @@ internal static List FromOverallMetrics(IHostEnvironment env, ID private sealed class SerializationClass { #pragma warning disable 649 // never assigned - [ColumnName(Runtime.Data.ClusteringEvaluator.Dbi)] + [ColumnName(ClusteringEvaluator.Dbi)] public Double Dbi; - [ColumnName(Runtime.Data.ClusteringEvaluator.Nmi)] + [ColumnName(ClusteringEvaluator.Nmi)] public Double Nmi; - [ColumnName(Runtime.Data.ClusteringEvaluator.AvgMinScore)] + [ColumnName(ClusteringEvaluator.AvgMinScore)] public Double AvgMinScore; [ColumnName(ColumnNames.FoldIndex)] diff --git a/src/Microsoft.ML.Legacy/Models/ConfusionMatrix.cs b/src/Microsoft.ML.Legacy/Models/ConfusionMatrix.cs index 9e7560729d..5197342c7b 100644 --- a/src/Microsoft.ML.Legacy/Models/ConfusionMatrix.cs +++ b/src/Microsoft.ML.Legacy/Models/ConfusionMatrix.cs @@ -3,11 +3,8 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using System; using System.Collections.Generic; -using System.Linq; namespace Microsoft.ML.Legacy.Models { diff --git a/src/Microsoft.ML.Legacy/Models/OneVersusAll.cs b/src/Microsoft.ML.Legacy/Models/OneVersusAll.cs index 82a58ab452..f5e0728a83 100644 --- a/src/Microsoft.ML.Legacy/Models/OneVersusAll.cs +++ b/src/Microsoft.ML.Legacy/Models/OneVersusAll.cs @@ -2,11 +2,11 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; using System; -using static Microsoft.ML.Runtime.EntryPoints.CommonInputs; +using static Microsoft.ML.EntryPoints.CommonInputs; namespace Microsoft.ML.Legacy.Models { diff --git a/src/Microsoft.ML.Legacy/Models/OnnxConverter.cs b/src/Microsoft.ML.Legacy/Models/OnnxConverter.cs index 00f077a8fc..499adc722e 100644 --- a/src/Microsoft.ML.Legacy/Models/OnnxConverter.cs +++ b/src/Microsoft.ML.Legacy/Models/OnnxConverter.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; +using Microsoft.ML; namespace Microsoft.ML.Legacy.Models { diff --git a/src/Microsoft.ML.Legacy/Models/RegressionEvaluator.cs b/src/Microsoft.ML.Legacy/Models/RegressionEvaluator.cs index ffee6108c6..89c8801f29 100644 --- a/src/Microsoft.ML.Legacy/Models/RegressionEvaluator.cs +++ b/src/Microsoft.ML.Legacy/Models/RegressionEvaluator.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.Legacy.Transforms; namespace Microsoft.ML.Legacy.Models diff --git a/src/Microsoft.ML.Legacy/Models/RegressionMetrics.cs b/src/Microsoft.ML.Legacy/Models/RegressionMetrics.cs index 2bc510a37b..9cbee20457 100644 --- a/src/Microsoft.ML.Legacy/Models/RegressionMetrics.cs +++ b/src/Microsoft.ML.Legacy/Models/RegressionMetrics.cs @@ -3,11 +3,9 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using System; using System.Collections.Generic; -using static Microsoft.ML.Runtime.Data.MetricKinds; +using static Microsoft.ML.Data.MetricKinds; namespace Microsoft.ML.Legacy.Models { @@ -105,19 +103,19 @@ internal static List FromOverallMetrics(IHostEnvironment env, private sealed class SerializationClass { #pragma warning disable 649 // never assigned - [ColumnName(Runtime.Data.RegressionEvaluator.L1)] + [ColumnName(ML.Data.RegressionEvaluator.L1)] public Double L1; - [ColumnName(Runtime.Data.RegressionEvaluator.L2)] + [ColumnName(ML.Data.RegressionEvaluator.L2)] public Double L2; - [ColumnName(Runtime.Data.RegressionEvaluator.Rms)] + [ColumnName(ML.Data.RegressionEvaluator.Rms)] public Double Rms; - [ColumnName(Runtime.Data.RegressionEvaluator.Loss)] + [ColumnName(ML.Data.RegressionEvaluator.Loss)] public Double LossFn; - [ColumnName(Runtime.Data.RegressionEvaluator.RSquared)] + [ColumnName(ML.Data.RegressionEvaluator.RSquared)] public Double RSquared; [ColumnName(ColumnNames.FoldIndex)] diff --git a/src/Microsoft.ML.Legacy/PredictionModel.cs b/src/Microsoft.ML.Legacy/PredictionModel.cs index e01c31c0ce..c00f648e94 100644 --- a/src/Microsoft.ML.Legacy/PredictionModel.cs +++ b/src/Microsoft.ML.Legacy/PredictionModel.cs @@ -3,9 +3,7 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML.EntryPoints; using System; using System.Collections.Generic; using System.IO; diff --git a/src/Microsoft.ML.Legacy/Runtime/EntryPoints/CodeGen/EntryPointGeneratorBase.cs b/src/Microsoft.ML.Legacy/Runtime/EntryPoints/CodeGen/EntryPointGeneratorBase.cs index 255529b5e3..4e22f089ac 100644 --- a/src/Microsoft.ML.Legacy/Runtime/EntryPoints/CodeGen/EntryPointGeneratorBase.cs +++ b/src/Microsoft.ML.Legacy/Runtime/EntryPoints/CodeGen/EntryPointGeneratorBase.cs @@ -4,10 +4,10 @@ using System; using System.CodeDom.Compiler; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.EntryPoints.CodeGen +namespace Microsoft.ML.EntryPoints.CodeGen { internal abstract class EntryPointGeneratorBase : GeneratorBase { @@ -128,10 +128,10 @@ protected override void GenerateUsings(IndentedTextWriter w) w.WriteLine("using System.Linq;"); w.WriteLine("using Microsoft.Analytics.MachineLearning;"); w.WriteLine("using Microsoft.Analytics.Modules;"); - w.WriteLine("using Microsoft.ML.Runtime;"); - w.WriteLine("using Microsoft.ML.Runtime.CommandLine;"); - w.WriteLine("using Microsoft.ML.Runtime.Data;"); - w.WriteLine("using Microsoft.ML.Runtime.Internal.Internallearn;"); + w.WriteLine("using Microsoft.ML;"); + w.WriteLine("using Microsoft.ML.CommandLine;"); + w.WriteLine("using Microsoft.ML.Data;"); + w.WriteLine("using Microsoft.ML.Internal.Internallearn;"); } } } \ No newline at end of file diff --git a/src/Microsoft.ML.Legacy/Runtime/EntryPoints/CodeGen/GeneratorBase.cs b/src/Microsoft.ML.Legacy/Runtime/EntryPoints/CodeGen/GeneratorBase.cs index 4bad797a57..abed47e26a 100644 --- a/src/Microsoft.ML.Legacy/Runtime/EntryPoints/CodeGen/GeneratorBase.cs +++ b/src/Microsoft.ML.Legacy/Runtime/EntryPoints/CodeGen/GeneratorBase.cs @@ -3,9 +3,9 @@ // See the LICENSE file in the project root for more information. using Microsoft.CSharp; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Transforms; using System; using System.CodeDom; @@ -13,7 +13,7 @@ using System.Collections.Generic; using System.Reflection; -namespace Microsoft.ML.Runtime.EntryPoints.CodeGen +namespace Microsoft.ML.EntryPoints.CodeGen { internal abstract class GeneratorBase { diff --git a/src/Microsoft.ML.Legacy/Runtime/EntryPoints/CodeGen/ImplGeneratorBase.cs b/src/Microsoft.ML.Legacy/Runtime/EntryPoints/CodeGen/ImplGeneratorBase.cs index 287481245f..6d427cb7a3 100644 --- a/src/Microsoft.ML.Legacy/Runtime/EntryPoints/CodeGen/ImplGeneratorBase.cs +++ b/src/Microsoft.ML.Legacy/Runtime/EntryPoints/CodeGen/ImplGeneratorBase.cs @@ -5,11 +5,11 @@ using System; using System.CodeDom.Compiler; using System.Linq; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.EntryPoints.CodeGen +namespace Microsoft.ML.EntryPoints.CodeGen { internal abstract class ImplGeneratorBase : GeneratorBase { @@ -97,10 +97,10 @@ protected override void GenerateUsings(IndentedTextWriter w) { w.WriteLine("using System;"); w.WriteLine("using System.Linq;"); - w.WriteLine("using Microsoft.ML.Runtime;"); - w.WriteLine("using Microsoft.ML.Runtime.CommandLine;"); - w.WriteLine("using Microsoft.ML.Runtime.Data;"); - w.WriteLine("using Microsoft.ML.Runtime.Internal.Internallearn;"); + w.WriteLine("using Microsoft.ML;"); + w.WriteLine("using Microsoft.ML.CommandLine;"); + w.WriteLine("using Microsoft.ML.Data;"); + w.WriteLine("using Microsoft.ML.Internal.Internallearn;"); } } } \ No newline at end of file diff --git a/src/Microsoft.ML.Legacy/Runtime/EntryPoints/CodeGen/LearnerGenerators.cs b/src/Microsoft.ML.Legacy/Runtime/EntryPoints/CodeGen/LearnerGenerators.cs index a047ce21ea..533a3fe8c4 100644 --- a/src/Microsoft.ML.Legacy/Runtime/EntryPoints/CodeGen/LearnerGenerators.cs +++ b/src/Microsoft.ML.Legacy/Runtime/EntryPoints/CodeGen/LearnerGenerators.cs @@ -6,10 +6,10 @@ using System.CodeDom.Compiler; using System.IO; using System.Linq; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.EntryPoints.CodeGen +namespace Microsoft.ML.EntryPoints.CodeGen { internal class LearnerImplGenerator : ImplGeneratorBase { diff --git a/src/Microsoft.ML.Legacy/Runtime/EntryPoints/CodeGen/ModuleGenerator.cs b/src/Microsoft.ML.Legacy/Runtime/EntryPoints/CodeGen/ModuleGenerator.cs index a8f2735870..4d571c2e40 100644 --- a/src/Microsoft.ML.Legacy/Runtime/EntryPoints/CodeGen/ModuleGenerator.cs +++ b/src/Microsoft.ML.Legacy/Runtime/EntryPoints/CodeGen/ModuleGenerator.cs @@ -10,17 +10,17 @@ using System.IO; using System.Linq; using System.Threading; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints.CodeGen; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints.CodeGen; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Tools; [assembly: LoadableClass(typeof(ModuleGenerator), typeof(ModuleGenerator.Arguments), typeof(SignatureModuleGenerator), "Module generator", "ModuleGenerator", "Module")] -namespace Microsoft.ML.Runtime.EntryPoints.CodeGen +namespace Microsoft.ML.EntryPoints.CodeGen { internal sealed class ModuleGenerator : IGenerator { diff --git a/src/Microsoft.ML.Legacy/Runtime/EntryPoints/CodeGen/TransformGenerators.cs b/src/Microsoft.ML.Legacy/Runtime/EntryPoints/CodeGen/TransformGenerators.cs index b43f94790f..e6bb58b14f 100644 --- a/src/Microsoft.ML.Legacy/Runtime/EntryPoints/CodeGen/TransformGenerators.cs +++ b/src/Microsoft.ML.Legacy/Runtime/EntryPoints/CodeGen/TransformGenerators.cs @@ -8,11 +8,11 @@ using System.IO; using System.Linq; using System.Text; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.EntryPoints.CodeGen +namespace Microsoft.ML.EntryPoints.CodeGen { internal sealed class TransformImplGenerator : ImplGeneratorBase { @@ -174,10 +174,10 @@ protected override void GenerateUsings(IndentedTextWriter w) allNamespaces.Add("System.Collections.Generic"); allNamespaces.Add("Microsoft.Analytics.Modules.Common"); allNamespaces.Add("Microsoft.Analytics.Platform.ML.Models"); - allNamespaces.Add("Microsoft.ML.Runtime.Data"); - allNamespaces.Add("Microsoft.ML.Runtime.Modules.Contracts"); - allNamespaces.Add("Microsoft.ML.Runtime.Modules.Contracts.Attributes"); - allNamespaces.Add("Microsoft.ML.Runtime.Modules.Contracts.Types"); + allNamespaces.Add("Microsoft.ML.Data"); + allNamespaces.Add("Microsoft.ML.Modules.Contracts"); + allNamespaces.Add("Microsoft.ML.Modules.Contracts.Attributes"); + allNamespaces.Add("Microsoft.ML.Modules.Contracts.Types"); var namespaces = allNamespaces.ToArray(); Array.Sort(namespaces, (a, b) => diff --git a/src/Microsoft.ML.Legacy/Runtime/EntryPoints/ImportTextData.cs b/src/Microsoft.ML.Legacy/Runtime/EntryPoints/ImportTextData.cs index 0c7e0e760f..fcd6272090 100644 --- a/src/Microsoft.ML.Legacy/Runtime/EntryPoints/ImportTextData.cs +++ b/src/Microsoft.ML.Legacy/Runtime/EntryPoints/ImportTextData.cs @@ -3,10 +3,8 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; [assembly: EntryPointModule(typeof(Microsoft.ML.Legacy.EntryPoints.ImportTextData))] @@ -31,14 +29,14 @@ public sealed class LoaderInput } [TlcModule.EntryPoint(Name = "Data.TextLoader", Desc = "Import a dataset from a text file")] - public static Runtime.EntryPoints.ImportTextData.Output TextLoader(IHostEnvironment env, LoaderInput input) + public static ML.EntryPoints.ImportTextData.Output TextLoader(IHostEnvironment env, LoaderInput input) { Contracts.CheckValue(env, nameof(env)); var host = env.Register("ImportTextData"); env.CheckValue(input, nameof(input)); EntryPointUtils.CheckInputArgs(host, input); var loader = host.CreateLoader(input.Arguments, new FileHandleSource(input.InputFile)); - return new Runtime.EntryPoints.ImportTextData.Output { Data = loader }; + return new ML.EntryPoints.ImportTextData.Output { Data = loader }; } } } diff --git a/src/Microsoft.ML.Legacy/Runtime/Experiment/Experiment.cs b/src/Microsoft.ML.Legacy/Runtime/Experiment/Experiment.cs index 1069c7194b..b83112cc9b 100644 --- a/src/Microsoft.ML.Legacy/Runtime/Experiment/Experiment.cs +++ b/src/Microsoft.ML.Legacy/Runtime/Experiment/Experiment.cs @@ -5,13 +5,13 @@ using System; using System.Collections.Generic; using System.IO; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.EntryPoints.JsonUtils; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.EntryPoints.JsonUtils; using Newtonsoft.Json; using Newtonsoft.Json.Converters; using Newtonsoft.Json.Linq; -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { /// /// This class represents an entry point graph. @@ -28,13 +28,13 @@ private sealed class SerializationHelper public object Outputs { get; set; } } - private readonly Runtime.IHostEnvironment _env; + private readonly IHostEnvironment _env; private readonly ComponentCatalog _catalog; private readonly List _jsonNodes; private readonly JsonSerializer _serializer; private readonly SerializationHelper _helper; private EntryPointGraph _graph; - public Experiment(Runtime.IHostEnvironment env) + public Experiment(IHostEnvironment env) { _env = env; AssemblyRegistration.RegisterAssemblies(_env); @@ -301,7 +301,7 @@ public sealed class EntryPointTransformOutput : CommonOutputs.ITransformOutput /// /// Transformed dataset /// - public Var OutputData { get; set; } + public Var OutputData { get; set; } /// /// Transform model @@ -310,7 +310,7 @@ public sealed class EntryPointTransformOutput : CommonOutputs.ITransformOutput public EntryPointTransformOutput() { - OutputData = new Var(); + OutputData = new Var(); Model = new Var(); } } diff --git a/src/Microsoft.ML.Legacy/Runtime/Internal/Tools/CSharpApiGenerator.cs b/src/Microsoft.ML.Legacy/Runtime/Internal/Tools/CSharpApiGenerator.cs index 997d19ae7b..91bdd46f21 100644 --- a/src/Microsoft.ML.Legacy/Runtime/Internal/Tools/CSharpApiGenerator.cs +++ b/src/Microsoft.ML.Legacy/Runtime/Internal/Tools/CSharpApiGenerator.cs @@ -8,21 +8,21 @@ using System.IO; using System.Linq; using System.Reflection; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Tools; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Tools; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Tools; using Newtonsoft.Json.Linq; -using static Microsoft.ML.Runtime.EntryPoints.CommonInputs; +using static Microsoft.ML.EntryPoints.CommonInputs; [assembly: LoadableClass(typeof(CSharpApiGenerator), typeof(CSharpApiGenerator.Arguments), typeof(SignatureModuleGenerator), "CSharp API generator", "CSGenerator", "CS")] #pragma warning disable 612 -namespace Microsoft.ML.Runtime.Internal.Tools +namespace Microsoft.ML.Internal.Tools { internal sealed class CSharpApiGenerator : IGenerator { @@ -78,7 +78,6 @@ public void Generate(IEnumerable infos) // Generate footer CSharpGeneratorUtils.GenerateFooter(writer); - CSharpGeneratorUtils.GenerateFooter(writer); foreach (var entryPointInfo in catalog.AllEntryPoints().Where(x => !_excludedSet.Contains(x.Name)).OrderBy(x => x.Name)) { @@ -86,10 +85,6 @@ public void Generate(IEnumerable infos) GenerateInputOutput(writer, entryPointInfo, catalog); } - writer.WriteLine("namespace Runtime"); - writer.WriteLine("{"); - writer.Indent(); - foreach (var kind in catalog.GetAllComponentKinds()) { // Generate kind base class @@ -102,7 +97,6 @@ public void Generate(IEnumerable infos) } } - CSharpGeneratorUtils.GenerateFooter(writer); CSharpGeneratorUtils.GenerateFooter(writer); writer.WriteLine("#pragma warning restore"); } @@ -604,16 +598,16 @@ private void GenerateComponentKind(IndentedTextWriter writer, string kind) private void GenerateComponent(IndentedTextWriter writer, ComponentCatalog.ComponentInfo component, ComponentCatalog catalog) { - GenerateEnums(writer, component.ArgumentType, "Runtime"); + GenerateEnums(writer, component.ArgumentType, ""); writer.WriteLineNoTabs(); - GenerateClasses(writer, component.ArgumentType, catalog, "Runtime"); + GenerateClasses(writer, component.ArgumentType, catalog, ""); writer.WriteLineNoTabs(); CSharpGeneratorUtils.GenerateSummary(writer, component.Description); writer.WriteLine("[Obsolete]"); writer.WriteLine($"public sealed class {CSharpGeneratorUtils.GetComponentName(component)} : {component.Kind}"); writer.WriteLine("{"); writer.Indent(); - GenerateInputFields(writer, component.ArgumentType, catalog, "Runtime"); + GenerateInputFields(writer, component.ArgumentType, catalog, ""); writer.WriteLine("[Obsolete]"); writer.WriteLine($"internal override string ComponentName => \"{component.Name}\";"); writer.Outdent(); diff --git a/src/Microsoft.ML.Legacy/Runtime/Internal/Tools/CSharpGeneratorUtils.cs b/src/Microsoft.ML.Legacy/Runtime/Internal/Tools/CSharpGeneratorUtils.cs index 58a496f2c7..e287aa6ae7 100644 --- a/src/Microsoft.ML.Legacy/Runtime/Internal/Tools/CSharpGeneratorUtils.cs +++ b/src/Microsoft.ML.Legacy/Runtime/Internal/Tools/CSharpGeneratorUtils.cs @@ -9,12 +9,12 @@ using System.Linq; using System.Reflection; using Microsoft.CSharp; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; using Newtonsoft.Json.Linq; -namespace Microsoft.ML.Runtime.Internal.Tools +namespace Microsoft.ML.Internal.Tools { internal static class CSharpGeneratorUtils { @@ -296,7 +296,7 @@ public static string GetValue(ComponentCatalog catalog, Type fieldType, object f if (generatedClasses.IsGenerated(fieldType.FullName)) return generatedClasses.GetApiName(fieldType, rootNameSpace) + "." + enumAsString; else - return generatedClasses.GetApiName(fieldType, "Runtime") + "." + enumAsString; + return generatedClasses.GetApiName(fieldType, "") + "." + enumAsString; case TlcModule.DataKind.Char: return $"'{GetCharAsString((char)fieldValue)}'"; case TlcModule.DataKind.Component: @@ -381,20 +381,17 @@ public static void GenerateHeader(IndentedTextWriter writer) writer.WriteLine("//------------------------------------------------------------------------------"); writer.WriteLine("#pragma warning disable"); writer.WriteLine("using System.Collections.Generic;"); - writer.WriteLine("using Microsoft.ML.Runtime;"); - writer.WriteLine("using Microsoft.ML.Runtime.Data;"); - writer.WriteLine("using Microsoft.ML.Runtime.EntryPoints;"); + writer.WriteLine("using Microsoft.ML;"); + writer.WriteLine("using Microsoft.ML.Data;"); + writer.WriteLine("using Microsoft.ML.EntryPoints;"); writer.WriteLine("using Newtonsoft.Json;"); writer.WriteLine("using System;"); writer.WriteLine("using System.Linq;"); - writer.WriteLine("using Microsoft.ML.Runtime.CommandLine;"); + writer.WriteLine("using Microsoft.ML.CommandLine;"); writer.WriteLineNoTabs(); writer.WriteLine("namespace Microsoft.ML"); writer.WriteLine("{"); writer.Indent(); - writer.WriteLine("namespace Runtime"); - writer.WriteLine("{"); - writer.Indent(); writer.WriteLine("public sealed partial class Experiment"); writer.WriteLine("{"); writer.Indent(); diff --git a/src/Microsoft.ML.Legacy/Runtime/Internal/Tools/GeneratedClasses.cs b/src/Microsoft.ML.Legacy/Runtime/Internal/Tools/GeneratedClasses.cs index fe8adf35fc..d8bccc1b68 100644 --- a/src/Microsoft.ML.Legacy/Runtime/Internal/Tools/GeneratedClasses.cs +++ b/src/Microsoft.ML.Legacy/Runtime/Internal/Tools/GeneratedClasses.cs @@ -6,7 +6,7 @@ using System.Collections.Generic; using System.Linq; -namespace Microsoft.ML.Runtime.Internal.Tools +namespace Microsoft.ML.Internal.Tools { internal sealed class GeneratedClasses { diff --git a/src/Microsoft.ML.LightGBM.StaticPipe/LightGbmStaticExtensions.cs b/src/Microsoft.ML.LightGBM.StaticPipe/LightGbmStaticExtensions.cs index 7e739f3d6b..89fe638c6b 100644 --- a/src/Microsoft.ML.LightGBM.StaticPipe/LightGbmStaticExtensions.cs +++ b/src/Microsoft.ML.LightGBM.StaticPipe/LightGbmStaticExtensions.cs @@ -1,11 +1,13 @@ -// Licensed to the .NET 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. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.LightGBM; using Microsoft.ML.StaticPipe; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Learners; +using Microsoft.ML.LightGBM; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Trainers; using System; diff --git a/src/Microsoft.ML.LightGBM/LightGbmArguments.cs b/src/Microsoft.ML.LightGBM/LightGbmArguments.cs index 044afe77ef..1f709d4639 100644 --- a/src/Microsoft.ML.LightGBM/LightGbmArguments.cs +++ b/src/Microsoft.ML.LightGBM/LightGbmArguments.cs @@ -5,11 +5,11 @@ using System.Collections.Generic; using System.Text; using System.Reflection; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.LightGBM; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.LightGBM; [assembly: LoadableClass(typeof(LightGbmArguments.TreeBooster), typeof(LightGbmArguments.TreeBooster.Arguments), typeof(SignatureLightGBMBooster), LightGbmArguments.TreeBooster.FriendlyName, LightGbmArguments.TreeBooster.Name)] @@ -22,7 +22,7 @@ [assembly: EntryPointModule(typeof(LightGbmArguments.DartBooster.Arguments))] [assembly: EntryPointModule(typeof(LightGbmArguments.GossBooster.Arguments))] -namespace Microsoft.ML.Runtime.LightGBM +namespace Microsoft.ML.LightGBM { public delegate void SignatureLightGBMBooster(); diff --git a/src/Microsoft.ML.LightGBM/LightGbmBinaryTrainer.cs b/src/Microsoft.ML.LightGBM/LightGbmBinaryTrainer.cs index 7361fe5bf3..9d70bd2c03 100644 --- a/src/Microsoft.ML.LightGBM/LightGbmBinaryTrainer.cs +++ b/src/Microsoft.ML.LightGBM/LightGbmBinaryTrainer.cs @@ -5,14 +5,13 @@ using Microsoft.ML.Calibrator; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.LightGBM; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.LightGBM; +using Microsoft.ML.Model; +using Microsoft.ML.Training; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Trainers.FastTree.Internal; using System; @@ -27,7 +26,7 @@ [assembly: LoadableClass(typeof(void), typeof(LightGbm), null, typeof(SignatureEntryPointModule), "LightGBM")] -namespace Microsoft.ML.Runtime.LightGBM +namespace Microsoft.ML.LightGBM { /// public sealed class LightGbmBinaryModelParameters : TreeEnsembleModelParameters diff --git a/src/Microsoft.ML.LightGBM/LightGbmCatalog.cs b/src/Microsoft.ML.LightGBM/LightGbmCatalog.cs index de4b84c3f1..d5d45cea0e 100644 --- a/src/Microsoft.ML.LightGBM/LightGbmCatalog.cs +++ b/src/Microsoft.ML.LightGBM/LightGbmCatalog.cs @@ -2,9 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.LightGBM; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.LightGBM; using System; namespace Microsoft.ML diff --git a/src/Microsoft.ML.LightGBM/LightGbmMulticlassTrainer.cs b/src/Microsoft.ML.LightGBM/LightGbmMulticlassTrainer.cs index d564314a14..5ebfe4a621 100644 --- a/src/Microsoft.ML.LightGBM/LightGbmMulticlassTrainer.cs +++ b/src/Microsoft.ML.LightGBM/LightGbmMulticlassTrainer.cs @@ -4,12 +4,11 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.LightGBM; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.LightGBM; +using Microsoft.ML.Training; using Microsoft.ML.Trainers; using Microsoft.ML.Trainers.FastTree.Internal; using System; @@ -19,7 +18,7 @@ new[] { typeof(SignatureMultiClassClassifierTrainer), typeof(SignatureTrainer) }, "LightGBM Multi-class Classifier", LightGbmMulticlassTrainer.LoadNameValue, LightGbmMulticlassTrainer.ShortName, DocName = "trainer/LightGBM.md")] -namespace Microsoft.ML.Runtime.LightGBM +namespace Microsoft.ML.LightGBM { /// diff --git a/src/Microsoft.ML.LightGBM/LightGbmRankingTrainer.cs b/src/Microsoft.ML.LightGBM/LightGbmRankingTrainer.cs index f815ed251a..5abc50bae2 100644 --- a/src/Microsoft.ML.LightGBM/LightGbmRankingTrainer.cs +++ b/src/Microsoft.ML.LightGBM/LightGbmRankingTrainer.cs @@ -4,12 +4,11 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.LightGBM; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.LightGBM; +using Microsoft.ML.Model; +using Microsoft.ML.Training; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Trainers.FastTree.Internal; using System; @@ -22,7 +21,7 @@ "LightGBM Ranking Executor", LightGbmRankingModelParameters.LoaderSignature)] -namespace Microsoft.ML.Runtime.LightGBM +namespace Microsoft.ML.LightGBM { public sealed class LightGbmRankingModelParameters : TreeEnsembleModelParameters diff --git a/src/Microsoft.ML.LightGBM/LightGbmRegressionTrainer.cs b/src/Microsoft.ML.LightGBM/LightGbmRegressionTrainer.cs index 36518d9dca..73ae3db649 100644 --- a/src/Microsoft.ML.LightGBM/LightGbmRegressionTrainer.cs +++ b/src/Microsoft.ML.LightGBM/LightGbmRegressionTrainer.cs @@ -4,12 +4,11 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.LightGBM; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.LightGBM; +using Microsoft.ML.Model; +using Microsoft.ML.Training; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Trainers.FastTree.Internal; using System; @@ -22,7 +21,7 @@ "LightGBM Regression Executor", LightGbmRegressionModelParameters.LoaderSignature)] -namespace Microsoft.ML.Runtime.LightGBM +namespace Microsoft.ML.LightGBM { /// public sealed class LightGbmRegressionModelParameters : TreeEnsembleModelParameters diff --git a/src/Microsoft.ML.LightGBM/LightGbmTrainerBase.cs b/src/Microsoft.ML.LightGBM/LightGbmTrainerBase.cs index e9a7de1a93..904a164b90 100644 --- a/src/Microsoft.ML.LightGBM/LightGbmTrainerBase.cs +++ b/src/Microsoft.ML.LightGBM/LightGbmTrainerBase.cs @@ -4,15 +4,14 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Training; using Microsoft.ML.Trainers.FastTree.Internal; using System; using System.Collections.Generic; -namespace Microsoft.ML.Runtime.LightGBM +namespace Microsoft.ML.LightGBM { /// /// Lock for LightGBM trainer. diff --git a/src/Microsoft.ML.LightGBM/Parallel/IParallel.cs b/src/Microsoft.ML.LightGBM/Parallel/IParallel.cs index 469beae930..8f3f005741 100644 --- a/src/Microsoft.ML.LightGBM/Parallel/IParallel.cs +++ b/src/Microsoft.ML.LightGBM/Parallel/IParallel.cs @@ -5,9 +5,9 @@ using System; using System.Collections.Generic; using System.Runtime.InteropServices; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML.EntryPoints; -namespace Microsoft.ML.Runtime.LightGBM +namespace Microsoft.ML.LightGBM { /// /// Signature of LightGBM IAllreduce diff --git a/src/Microsoft.ML.LightGBM/Parallel/SingleTrainer.cs b/src/Microsoft.ML.LightGBM/Parallel/SingleTrainer.cs index 4c61bd65c6..8041fb3d6f 100644 --- a/src/Microsoft.ML.LightGBM/Parallel/SingleTrainer.cs +++ b/src/Microsoft.ML.LightGBM/Parallel/SingleTrainer.cs @@ -3,15 +3,15 @@ // See the LICENSE file in the project root for more information. using System.Collections.Generic; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.EntryPoints; -[assembly: LoadableClass(typeof(Microsoft.ML.Runtime.LightGBM.SingleTrainer), - null, typeof(Microsoft.ML.Runtime.LightGBM.SignatureParallelTrainer), "single")] +[assembly: LoadableClass(typeof(Microsoft.ML.LightGBM.SingleTrainer), + null, typeof(Microsoft.ML.LightGBM.SignatureParallelTrainer), "single")] -[assembly: EntryPointModule(typeof(Microsoft.ML.Runtime.LightGBM.SingleTrainerFactory))] +[assembly: EntryPointModule(typeof(Microsoft.ML.LightGBM.SingleTrainerFactory))] -namespace Microsoft.ML.Runtime.LightGBM +namespace Microsoft.ML.LightGBM { public sealed class SingleTrainer : IParallel { diff --git a/src/Microsoft.ML.LightGBM/WrappedLightGbmBooster.cs b/src/Microsoft.ML.LightGBM/WrappedLightGbmBooster.cs index 7338bf30b3..152274740f 100644 --- a/src/Microsoft.ML.LightGBM/WrappedLightGbmBooster.cs +++ b/src/Microsoft.ML.LightGBM/WrappedLightGbmBooster.cs @@ -7,7 +7,7 @@ using System.Linq; using Microsoft.ML.Trainers.FastTree.Internal; -namespace Microsoft.ML.Runtime.LightGBM +namespace Microsoft.ML.LightGBM { /// /// Wrapper of Booster object of LightGBM. diff --git a/src/Microsoft.ML.LightGBM/WrappedLightGbmDataset.cs b/src/Microsoft.ML.LightGBM/WrappedLightGbmDataset.cs index 5dcf44a44d..c666d070e0 100644 --- a/src/Microsoft.ML.LightGBM/WrappedLightGbmDataset.cs +++ b/src/Microsoft.ML.LightGBM/WrappedLightGbmDataset.cs @@ -6,7 +6,7 @@ using System.Threading.Tasks; using System.Runtime.InteropServices; -namespace Microsoft.ML.Runtime.LightGBM +namespace Microsoft.ML.LightGBM { /// /// Wrapper of Dataset object of LightGBM. diff --git a/src/Microsoft.ML.LightGBM/WrappedLightGbmInterface.cs b/src/Microsoft.ML.LightGBM/WrappedLightGbmInterface.cs index 2a4fb24ca0..48128a84f8 100644 --- a/src/Microsoft.ML.LightGBM/WrappedLightGbmInterface.cs +++ b/src/Microsoft.ML.LightGBM/WrappedLightGbmInterface.cs @@ -7,7 +7,7 @@ using System.Globalization; using System.Runtime.InteropServices; -namespace Microsoft.ML.Runtime.LightGBM +namespace Microsoft.ML.LightGBM { /// /// Wrapper of the c interfaces of LightGBM. diff --git a/src/Microsoft.ML.LightGBM/WrappedLightGbmTraining.cs b/src/Microsoft.ML.LightGBM/WrappedLightGbmTraining.cs index 8b2036fb11..e7a726d6da 100644 --- a/src/Microsoft.ML.LightGBM/WrappedLightGbmTraining.cs +++ b/src/Microsoft.ML.LightGBM/WrappedLightGbmTraining.cs @@ -5,7 +5,7 @@ using System; using System.Collections.Generic; -namespace Microsoft.ML.Runtime.LightGBM +namespace Microsoft.ML.LightGBM { /// /// Helpers to train a booster with given parameters. diff --git a/src/Microsoft.ML.Maml/ChainCommand.cs b/src/Microsoft.ML.Maml/ChainCommand.cs index c51a78952b..80e9ef6359 100644 --- a/src/Microsoft.ML.Maml/ChainCommand.cs +++ b/src/Microsoft.ML.Maml/ChainCommand.cs @@ -3,15 +3,15 @@ // See the LICENSE file in the project root for more information. using System.Globalization; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Command; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML; +using Microsoft.ML.Command; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Tools; [assembly: LoadableClass(ChainCommand.Summary, typeof(ChainCommand), typeof(ChainCommand.Arguments), typeof(SignatureCommand), "Chain Command", "Chain")] -namespace Microsoft.ML.Runtime.Tools +namespace Microsoft.ML.Tools { using Stopwatch = System.Diagnostics.Stopwatch; diff --git a/src/Microsoft.ML.Maml/HelpCommand.cs b/src/Microsoft.ML.Maml/HelpCommand.cs index 65487fbfc3..b8d4833d80 100644 --- a/src/Microsoft.ML.Maml/HelpCommand.cs +++ b/src/Microsoft.ML.Maml/HelpCommand.cs @@ -10,11 +10,11 @@ using System.Linq; using System.Text; using System.Xml.Linq; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Command; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML; +using Microsoft.ML.Command; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Tools; [assembly: LoadableClass(HelpCommand.Summary, typeof(HelpCommand), typeof(HelpCommand.Arguments), typeof(SignatureCommand), "MAML Help Command", "Help", "?")] @@ -22,7 +22,7 @@ [assembly: LoadableClass(typeof(XmlGenerator), typeof(XmlGenerator.Arguments), typeof(SignatureModuleGenerator), "Xml generator", "XmlGenerator", "Xml")] -namespace Microsoft.ML.Runtime.Tools +namespace Microsoft.ML.Tools { [BestFriend] internal interface IGenerator diff --git a/src/Microsoft.ML.Maml/MAML.cs b/src/Microsoft.ML.Maml/MAML.cs index a4eaa43491..c71f16099e 100644 --- a/src/Microsoft.ML.Maml/MAML.cs +++ b/src/Microsoft.ML.Maml/MAML.cs @@ -9,19 +9,19 @@ using System.Text; using System.Threading; using System.Threading.Tasks; -using Microsoft.ML.Runtime.Command; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Command; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; #if CORECLR -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; #endif #if !CORECLR using System.Configuration; #endif -namespace Microsoft.ML.Runtime.Tools +namespace Microsoft.ML.Tools { public static class Maml { diff --git a/src/Microsoft.ML.Maml/VersionCommand.cs b/src/Microsoft.ML.Maml/VersionCommand.cs index 7e20db2260..292df51e42 100644 --- a/src/Microsoft.ML.Maml/VersionCommand.cs +++ b/src/Microsoft.ML.Maml/VersionCommand.cs @@ -3,14 +3,14 @@ // See the LICENSE file in the project root for more information. using System.Reflection; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Command; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML; +using Microsoft.ML.Command; +using Microsoft.ML.Tools; [assembly: LoadableClass(VersionCommand.Summary, typeof(VersionCommand), null, typeof(SignatureCommand), "Version Command", "Version")] -namespace Microsoft.ML.Runtime.Tools +namespace Microsoft.ML.Tools { internal sealed class VersionCommand : ICommand { diff --git a/src/Microsoft.ML.Onnx/Microsoft.ML.Onnx.csproj b/src/Microsoft.ML.Onnx/Microsoft.ML.Onnx.csproj index 145dd8be8c..bdfed3cb24 100644 --- a/src/Microsoft.ML.Onnx/Microsoft.ML.Onnx.csproj +++ b/src/Microsoft.ML.Onnx/Microsoft.ML.Onnx.csproj @@ -3,7 +3,7 @@ netstandard2.0 Microsoft.ML.Onnx - Microsoft.ML.Runtime.Model.Onnx + Microsoft.ML.Model.Onnx diff --git a/src/Microsoft.ML.Onnx/OnnxContextImpl.cs b/src/Microsoft.ML.Onnx/OnnxContextImpl.cs index 3f0e6f2fb7..e33896e811 100644 --- a/src/Microsoft.ML.Onnx/OnnxContextImpl.cs +++ b/src/Microsoft.ML.Onnx/OnnxContextImpl.cs @@ -5,10 +5,10 @@ using System; using System.Collections.Generic; using System.Linq; -using Microsoft.ML.Runtime.UniversalModelFormat.Onnx; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.UniversalModelFormat.Onnx; +using Microsoft.ML.Data; -namespace Microsoft.ML.Runtime.Model.Onnx +namespace Microsoft.ML.Model.Onnx { /// /// A context for defining a ONNX output. diff --git a/src/Microsoft.ML.Onnx/OnnxMl.cs b/src/Microsoft.ML.Onnx/OnnxMl.cs index 41dc5aaa4c..3f9f8171d4 100644 --- a/src/Microsoft.ML.Onnx/OnnxMl.cs +++ b/src/Microsoft.ML.Onnx/OnnxMl.cs @@ -9,7 +9,7 @@ using pbc = global::Google.Protobuf.Collections; using pbr = global::Google.Protobuf.Reflection; using scg = global::System.Collections.Generic; -namespace Microsoft.ML.Runtime.UniversalModelFormat.Onnx +namespace Microsoft.ML.UniversalModelFormat.Onnx { /// Holder for reflection information generated from onnx-ml.proto3 @@ -89,19 +89,19 @@ static OnnxMlReflection() "Lk1MLlJ1bnRpbWUuVW5pdmVyc2FsTW9kZWxGb3JtYXQuT25ueGIGcHJvdG8z")); descriptor = pbr::FileDescriptor.FromGeneratedCode(descriptorData, new pbr::FileDescriptor[] { }, - new pbr::GeneratedClrTypeInfo(new[] { typeof(global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.Version), }, new pbr::GeneratedClrTypeInfo[] { - new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.AttributeProto), global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.AttributeProto.Parser, new[]{ "Name", "RefAttrName", "DocString", "Type", "F", "I", "S", "T", "G", "Floats", "Ints", "Strings", "Tensors", "Graphs" }, null, new[]{ typeof(global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.AttributeProto.Types.AttributeType) }, null), - new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.ValueInfoProto), global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.ValueInfoProto.Parser, new[]{ "Name", "Type", "DocString" }, null, null, null), - new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.NodeProto), global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.NodeProto.Parser, new[]{ "Input", "Output", "Name", "OpType", "Domain", "Attribute", "DocString" }, null, null, null), - new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.ModelProto), global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.ModelProto.Parser, new[]{ "IrVersion", "OpsetImport", "ProducerName", "ProducerVersion", "Domain", "ModelVersion", "DocString", "Graph", "MetadataProps" }, null, null, null), - new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.StringStringEntryProto), global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.StringStringEntryProto.Parser, new[]{ "Key", "Value" }, null, null, null), - new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.GraphProto), global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.GraphProto.Parser, new[]{ "Node", "Name", "Initializer", "DocString", "Input", "Output", "ValueInfo" }, null, null, null), - new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorProto), global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorProto.Parser, new[]{ "Dims", "DataType", "Segment", "FloatData", "Int32Data", "StringData", "Int64Data", "Name", "DocString", "RawData", "DoubleData", "Uint64Data" }, null, new[]{ typeof(global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorProto.Types.DataType) }, new pbr::GeneratedClrTypeInfo[] { new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorProto.Types.Segment), global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorProto.Types.Segment.Parser, new[]{ "Begin", "End" }, null, null, null)}), - new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorShapeProto), global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorShapeProto.Parser, new[]{ "Dim" }, null, null, new pbr::GeneratedClrTypeInfo[] { new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorShapeProto.Types.Dimension), global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorShapeProto.Types.Dimension.Parser, new[]{ "DimValue", "DimParam", "Denotation" }, new[]{ "Value" }, null, null)}), - new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto), global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto.Parser, new[]{ "TensorType", "SequenceType", "MapType", "Denotation" }, new[]{ "Value" }, null, new pbr::GeneratedClrTypeInfo[] { new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto.Types.Tensor), global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto.Types.Tensor.Parser, new[]{ "ElemType", "Shape" }, null, null, null), - new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto.Types.Sequence), global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto.Types.Sequence.Parser, new[]{ "ElemType" }, null, null, null), - new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto.Types.Map), global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto.Types.Map.Parser, new[]{ "KeyType", "ValueType" }, null, null, null)}), - new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.OperatorSetIdProto), global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.OperatorSetIdProto.Parser, new[]{ "Domain", "Version" }, null, null, null) + new pbr::GeneratedClrTypeInfo(new[] { typeof(global::Microsoft.ML.UniversalModelFormat.Onnx.Version), }, new pbr::GeneratedClrTypeInfo[] { + new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.UniversalModelFormat.Onnx.AttributeProto), global::Microsoft.ML.UniversalModelFormat.Onnx.AttributeProto.Parser, new[]{ "Name", "RefAttrName", "DocString", "Type", "F", "I", "S", "T", "G", "Floats", "Ints", "Strings", "Tensors", "Graphs" }, null, new[]{ typeof(global::Microsoft.ML.UniversalModelFormat.Onnx.AttributeProto.Types.AttributeType) }, null), + new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.UniversalModelFormat.Onnx.ValueInfoProto), global::Microsoft.ML.UniversalModelFormat.Onnx.ValueInfoProto.Parser, new[]{ "Name", "Type", "DocString" }, null, null, null), + new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.UniversalModelFormat.Onnx.NodeProto), global::Microsoft.ML.UniversalModelFormat.Onnx.NodeProto.Parser, new[]{ "Input", "Output", "Name", "OpType", "Domain", "Attribute", "DocString" }, null, null, null), + new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.UniversalModelFormat.Onnx.ModelProto), global::Microsoft.ML.UniversalModelFormat.Onnx.ModelProto.Parser, new[]{ "IrVersion", "OpsetImport", "ProducerName", "ProducerVersion", "Domain", "ModelVersion", "DocString", "Graph", "MetadataProps" }, null, null, null), + new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.UniversalModelFormat.Onnx.StringStringEntryProto), global::Microsoft.ML.UniversalModelFormat.Onnx.StringStringEntryProto.Parser, new[]{ "Key", "Value" }, null, null, null), + new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.UniversalModelFormat.Onnx.GraphProto), global::Microsoft.ML.UniversalModelFormat.Onnx.GraphProto.Parser, new[]{ "Node", "Name", "Initializer", "DocString", "Input", "Output", "ValueInfo" }, null, null, null), + new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.UniversalModelFormat.Onnx.TensorProto), global::Microsoft.ML.UniversalModelFormat.Onnx.TensorProto.Parser, new[]{ "Dims", "DataType", "Segment", "FloatData", "Int32Data", "StringData", "Int64Data", "Name", "DocString", "RawData", "DoubleData", "Uint64Data" }, null, new[]{ typeof(global::Microsoft.ML.UniversalModelFormat.Onnx.TensorProto.Types.DataType) }, new pbr::GeneratedClrTypeInfo[] { new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.UniversalModelFormat.Onnx.TensorProto.Types.Segment), global::Microsoft.ML.UniversalModelFormat.Onnx.TensorProto.Types.Segment.Parser, new[]{ "Begin", "End" }, null, null, null)}), + new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.UniversalModelFormat.Onnx.TensorShapeProto), global::Microsoft.ML.UniversalModelFormat.Onnx.TensorShapeProto.Parser, new[]{ "Dim" }, null, null, new pbr::GeneratedClrTypeInfo[] { new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.UniversalModelFormat.Onnx.TensorShapeProto.Types.Dimension), global::Microsoft.ML.UniversalModelFormat.Onnx.TensorShapeProto.Types.Dimension.Parser, new[]{ "DimValue", "DimParam", "Denotation" }, new[]{ "Value" }, null, null)}), + new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto), global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto.Parser, new[]{ "TensorType", "SequenceType", "MapType", "Denotation" }, new[]{ "Value" }, null, new pbr::GeneratedClrTypeInfo[] { new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto.Types.Tensor), global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto.Types.Tensor.Parser, new[]{ "ElemType", "Shape" }, null, null, null), + new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto.Types.Sequence), global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto.Types.Sequence.Parser, new[]{ "ElemType" }, null, null, null), + new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto.Types.Map), global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto.Types.Map.Parser, new[]{ "KeyType", "ValueType" }, null, null, null)}), + new pbr::GeneratedClrTypeInfo(typeof(global::Microsoft.ML.UniversalModelFormat.Onnx.OperatorSetIdProto), global::Microsoft.ML.UniversalModelFormat.Onnx.OperatorSetIdProto.Parser, new[]{ "Domain", "Version" }, null, null, null) })); } #endregion @@ -167,7 +167,7 @@ public sealed partial class AttributeProto : pb::IMessage [global::System.Diagnostics.DebuggerNonUserCodeAttribute] public static pbr::MessageDescriptor Descriptor { - get { return global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.OnnxMlReflection.Descriptor.MessageTypes[0]; } + get { return global::Microsoft.ML.UniversalModelFormat.Onnx.OnnxMlReflection.Descriptor.MessageTypes[0]; } } [global::System.Diagnostics.DebuggerNonUserCodeAttribute] @@ -263,7 +263,7 @@ public string DocString /// Field number for the "type" field. public const int TypeFieldNumber = 20; - private global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.AttributeProto.Types.AttributeType type_ = 0; + private global::Microsoft.ML.UniversalModelFormat.Onnx.AttributeProto.Types.AttributeType type_ = 0; /// /// The type field MUST be present for this version of the IR. /// For 0.0.1 versions of the IR, this field was not defined, and @@ -273,7 +273,7 @@ public string DocString /// change was made to accomodate proto3 implementations. /// [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.AttributeProto.Types.AttributeType Type + public global::Microsoft.ML.UniversalModelFormat.Onnx.AttributeProto.Types.AttributeType Type { get { return type_; } set @@ -332,12 +332,12 @@ public long I /// Field number for the "t" field. public const int TFieldNumber = 5; - private global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorProto t_; + private global::Microsoft.ML.UniversalModelFormat.Onnx.TensorProto t_; /// /// tensor value /// [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorProto T + public global::Microsoft.ML.UniversalModelFormat.Onnx.TensorProto T { get { return t_; } set @@ -348,12 +348,12 @@ public long I /// Field number for the "g" field. public const int GFieldNumber = 6; - private global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.GraphProto g_; + private global::Microsoft.ML.UniversalModelFormat.Onnx.GraphProto g_; /// /// graph /// [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.GraphProto G + public global::Microsoft.ML.UniversalModelFormat.Onnx.GraphProto G { get { return g_; } set @@ -406,28 +406,28 @@ public long I /// Field number for the "tensors" field. public const int TensorsFieldNumber = 10; - private static readonly pb::FieldCodec _repeated_tensors_codec - = pb::FieldCodec.ForMessage(82, global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorProto.Parser); - private readonly pbc::RepeatedField tensors_ = new pbc::RepeatedField(); + private static readonly pb::FieldCodec _repeated_tensors_codec + = pb::FieldCodec.ForMessage(82, global::Microsoft.ML.UniversalModelFormat.Onnx.TensorProto.Parser); + private readonly pbc::RepeatedField tensors_ = new pbc::RepeatedField(); /// /// list of tensors /// [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public pbc::RepeatedField Tensors + public pbc::RepeatedField Tensors { get { return tensors_; } } /// Field number for the "graphs" field. public const int GraphsFieldNumber = 11; - private static readonly pb::FieldCodec _repeated_graphs_codec - = pb::FieldCodec.ForMessage(90, global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.GraphProto.Parser); - private readonly pbc::RepeatedField graphs_ = new pbc::RepeatedField(); + private static readonly pb::FieldCodec _repeated_graphs_codec + = pb::FieldCodec.ForMessage(90, global::Microsoft.ML.UniversalModelFormat.Onnx.GraphProto.Parser); + private readonly pbc::RepeatedField graphs_ = new pbc::RepeatedField(); /// /// list of graph /// [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public pbc::RepeatedField Graphs + public pbc::RepeatedField Graphs { get { return graphs_; } } @@ -647,7 +647,7 @@ public void MergeFrom(AttributeProto other) { if (t_ == null) { - t_ = new global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorProto(); + t_ = new global::Microsoft.ML.UniversalModelFormat.Onnx.TensorProto(); } T.MergeFrom(other.T); } @@ -655,7 +655,7 @@ public void MergeFrom(AttributeProto other) { if (g_ == null) { - g_ = new global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.GraphProto(); + g_ = new global::Microsoft.ML.UniversalModelFormat.Onnx.GraphProto(); } G.MergeFrom(other.G); } @@ -702,7 +702,7 @@ public void MergeFrom(pb::CodedInputStream input) { if (t_ == null) { - t_ = new global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorProto(); + t_ = new global::Microsoft.ML.UniversalModelFormat.Onnx.TensorProto(); } input.ReadMessage(t_); break; @@ -711,7 +711,7 @@ public void MergeFrom(pb::CodedInputStream input) { if (g_ == null) { - g_ = new global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.GraphProto(); + g_ = new global::Microsoft.ML.UniversalModelFormat.Onnx.GraphProto(); } input.ReadMessage(g_); break; @@ -750,7 +750,7 @@ public void MergeFrom(pb::CodedInputStream input) } case 160: { - type_ = (global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.AttributeProto.Types.AttributeType)input.ReadEnum(); + type_ = (global::Microsoft.ML.UniversalModelFormat.Onnx.AttributeProto.Types.AttributeType)input.ReadEnum(); break; } case 170: @@ -805,7 +805,7 @@ public sealed partial class ValueInfoProto : pb::IMessage [global::System.Diagnostics.DebuggerNonUserCodeAttribute] public static pbr::MessageDescriptor Descriptor { - get { return global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.OnnxMlReflection.Descriptor.MessageTypes[1]; } + get { return global::Microsoft.ML.UniversalModelFormat.Onnx.OnnxMlReflection.Descriptor.MessageTypes[1]; } } [global::System.Diagnostics.DebuggerNonUserCodeAttribute] @@ -855,12 +855,12 @@ public string Name /// Field number for the "type" field. public const int TypeFieldNumber = 2; - private global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto type_; + private global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto type_; /// /// This field MUST be present in this version of the IR. /// [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto Type + public global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto Type { get { return type_; } set @@ -990,7 +990,7 @@ public void MergeFrom(ValueInfoProto other) { if (type_ == null) { - type_ = new global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto(); + type_ = new global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto(); } Type.MergeFrom(other.Type); } @@ -1021,7 +1021,7 @@ public void MergeFrom(pb::CodedInputStream input) { if (type_ == null) { - type_ = new global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto(); + type_ = new global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto(); } input.ReadMessage(type_); break; @@ -1056,7 +1056,7 @@ public sealed partial class NodeProto : pb::IMessage [global::System.Diagnostics.DebuggerNonUserCodeAttribute] public static pbr::MessageDescriptor Descriptor { - get { return global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.OnnxMlReflection.Descriptor.MessageTypes[2]; } + get { return global::Microsoft.ML.UniversalModelFormat.Onnx.OnnxMlReflection.Descriptor.MessageTypes[2]; } } [global::System.Diagnostics.DebuggerNonUserCodeAttribute] @@ -1171,14 +1171,14 @@ public string Domain /// Field number for the "attribute" field. public const int AttributeFieldNumber = 5; - private static readonly pb::FieldCodec _repeated_attribute_codec - = pb::FieldCodec.ForMessage(42, global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.AttributeProto.Parser); - private readonly pbc::RepeatedField attribute_ = new pbc::RepeatedField(); + private static readonly pb::FieldCodec _repeated_attribute_codec + = pb::FieldCodec.ForMessage(42, global::Microsoft.ML.UniversalModelFormat.Onnx.AttributeProto.Parser); + private readonly pbc::RepeatedField attribute_ = new pbc::RepeatedField(); /// /// Additional named attributes. /// [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public pbc::RepeatedField Attribute + public pbc::RepeatedField Attribute { get { return attribute_; } } @@ -1411,7 +1411,7 @@ public sealed partial class ModelProto : pb::IMessage [global::System.Diagnostics.DebuggerNonUserCodeAttribute] public static pbr::MessageDescriptor Descriptor { - get { return global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.OnnxMlReflection.Descriptor.MessageTypes[3]; } + get { return global::Microsoft.ML.UniversalModelFormat.Onnx.OnnxMlReflection.Descriptor.MessageTypes[3]; } } [global::System.Diagnostics.DebuggerNonUserCodeAttribute] @@ -1468,9 +1468,9 @@ public long IrVersion /// Field number for the "opset_import" field. public const int OpsetImportFieldNumber = 8; - private static readonly pb::FieldCodec _repeated_opsetImport_codec - = pb::FieldCodec.ForMessage(66, global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.OperatorSetIdProto.Parser); - private readonly pbc::RepeatedField opsetImport_ = new pbc::RepeatedField(); + private static readonly pb::FieldCodec _repeated_opsetImport_codec + = pb::FieldCodec.ForMessage(66, global::Microsoft.ML.UniversalModelFormat.Onnx.OperatorSetIdProto.Parser); + private readonly pbc::RepeatedField opsetImport_ = new pbc::RepeatedField(); /// /// The OperatorSets this model relies on. /// All ModelProtos MUST have at least one entry that @@ -1482,7 +1482,7 @@ public long IrVersion /// in the referenced operator sets. /// [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public pbc::RepeatedField OpsetImport + public pbc::RepeatedField OpsetImport { get { return opsetImport_; } } @@ -1578,12 +1578,12 @@ public string DocString /// Field number for the "graph" field. public const int GraphFieldNumber = 7; - private global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.GraphProto graph_; + private global::Microsoft.ML.UniversalModelFormat.Onnx.GraphProto graph_; /// /// The parameterized graph that is evaluated to execute the model. /// [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.GraphProto Graph + public global::Microsoft.ML.UniversalModelFormat.Onnx.GraphProto Graph { get { return graph_; } set @@ -1594,14 +1594,14 @@ public string DocString /// Field number for the "metadata_props" field. public const int MetadataPropsFieldNumber = 14; - private static readonly pb::FieldCodec _repeated_metadataProps_codec - = pb::FieldCodec.ForMessage(114, global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.StringStringEntryProto.Parser); - private readonly pbc::RepeatedField metadataProps_ = new pbc::RepeatedField(); + private static readonly pb::FieldCodec _repeated_metadataProps_codec + = pb::FieldCodec.ForMessage(114, global::Microsoft.ML.UniversalModelFormat.Onnx.StringStringEntryProto.Parser); + private readonly pbc::RepeatedField metadataProps_ = new pbc::RepeatedField(); /// /// Named metadata values; keys should be distinct. /// [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public pbc::RepeatedField MetadataProps + public pbc::RepeatedField MetadataProps { get { return metadataProps_; } } @@ -1784,7 +1784,7 @@ public void MergeFrom(ModelProto other) { if (graph_ == null) { - graph_ = new global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.GraphProto(); + graph_ = new global::Microsoft.ML.UniversalModelFormat.Onnx.GraphProto(); } Graph.MergeFrom(other.Graph); } @@ -1837,7 +1837,7 @@ public void MergeFrom(pb::CodedInputStream input) { if (graph_ == null) { - graph_ = new global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.GraphProto(); + graph_ = new global::Microsoft.ML.UniversalModelFormat.Onnx.GraphProto(); } input.ReadMessage(graph_); break; @@ -1872,7 +1872,7 @@ public sealed partial class StringStringEntryProto : pb::IMessage [global::System.Diagnostics.DebuggerNonUserCodeAttribute] public static pbr::MessageDescriptor Descriptor { - get { return global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.OnnxMlReflection.Descriptor.MessageTypes[5]; } + get { return global::Microsoft.ML.UniversalModelFormat.Onnx.OnnxMlReflection.Descriptor.MessageTypes[5]; } } [global::System.Diagnostics.DebuggerNonUserCodeAttribute] @@ -2109,14 +2109,14 @@ public GraphProto Clone() /// Field number for the "node" field. public const int NodeFieldNumber = 1; - private static readonly pb::FieldCodec _repeated_node_codec - = pb::FieldCodec.ForMessage(10, global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.NodeProto.Parser); - private readonly pbc::RepeatedField node_ = new pbc::RepeatedField(); + private static readonly pb::FieldCodec _repeated_node_codec + = pb::FieldCodec.ForMessage(10, global::Microsoft.ML.UniversalModelFormat.Onnx.NodeProto.Parser); + private readonly pbc::RepeatedField node_ = new pbc::RepeatedField(); /// /// The nodes in the graph, sorted topologically. /// [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public pbc::RepeatedField Node + public pbc::RepeatedField Node { get { return node_; } } @@ -2139,16 +2139,16 @@ public string Name /// Field number for the "initializer" field. public const int InitializerFieldNumber = 5; - private static readonly pb::FieldCodec _repeated_initializer_codec - = pb::FieldCodec.ForMessage(42, global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorProto.Parser); - private readonly pbc::RepeatedField initializer_ = new pbc::RepeatedField(); + private static readonly pb::FieldCodec _repeated_initializer_codec + = pb::FieldCodec.ForMessage(42, global::Microsoft.ML.UniversalModelFormat.Onnx.TensorProto.Parser); + private readonly pbc::RepeatedField initializer_ = new pbc::RepeatedField(); /// /// A list of named tensor values, used to specify constant inputs of the graph. /// Each TensorProto entry must have a distinct name (within the list) that /// also appears in the input list. /// [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public pbc::RepeatedField Initializer + public pbc::RepeatedField Initializer { get { return initializer_; } } @@ -2171,40 +2171,40 @@ public string DocString /// Field number for the "input" field. public const int InputFieldNumber = 11; - private static readonly pb::FieldCodec _repeated_input_codec - = pb::FieldCodec.ForMessage(90, global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.ValueInfoProto.Parser); - private readonly pbc::RepeatedField input_ = new pbc::RepeatedField(); + private static readonly pb::FieldCodec _repeated_input_codec + = pb::FieldCodec.ForMessage(90, global::Microsoft.ML.UniversalModelFormat.Onnx.ValueInfoProto.Parser); + private readonly pbc::RepeatedField input_ = new pbc::RepeatedField(); /// /// The inputs and outputs of the graph. /// [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public pbc::RepeatedField Input + public pbc::RepeatedField Input { get { return input_; } } /// Field number for the "output" field. public const int OutputFieldNumber = 12; - private static readonly pb::FieldCodec _repeated_output_codec - = pb::FieldCodec.ForMessage(98, global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.ValueInfoProto.Parser); - private readonly pbc::RepeatedField output_ = new pbc::RepeatedField(); + private static readonly pb::FieldCodec _repeated_output_codec + = pb::FieldCodec.ForMessage(98, global::Microsoft.ML.UniversalModelFormat.Onnx.ValueInfoProto.Parser); + private readonly pbc::RepeatedField output_ = new pbc::RepeatedField(); [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public pbc::RepeatedField Output + public pbc::RepeatedField Output { get { return output_; } } /// Field number for the "value_info" field. public const int ValueInfoFieldNumber = 13; - private static readonly pb::FieldCodec _repeated_valueInfo_codec - = pb::FieldCodec.ForMessage(106, global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.ValueInfoProto.Parser); - private readonly pbc::RepeatedField valueInfo_ = new pbc::RepeatedField(); + private static readonly pb::FieldCodec _repeated_valueInfo_codec + = pb::FieldCodec.ForMessage(106, global::Microsoft.ML.UniversalModelFormat.Onnx.ValueInfoProto.Parser); + private readonly pbc::RepeatedField valueInfo_ = new pbc::RepeatedField(); /// /// Information for the values in the graph. The ValueInfoProto.name's /// must be distinct. It is optional for a value to appear in value_info list. /// [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public pbc::RepeatedField ValueInfo + public pbc::RepeatedField ValueInfo { get { return valueInfo_; } } @@ -2398,7 +2398,7 @@ public sealed partial class TensorProto : pb::IMessage [global::System.Diagnostics.DebuggerNonUserCodeAttribute] public static pbr::MessageDescriptor Descriptor { - get { return global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.OnnxMlReflection.Descriptor.MessageTypes[6]; } + get { return global::Microsoft.ML.UniversalModelFormat.Onnx.OnnxMlReflection.Descriptor.MessageTypes[6]; } } [global::System.Diagnostics.DebuggerNonUserCodeAttribute] @@ -2455,12 +2455,12 @@ public TensorProto Clone() /// Field number for the "data_type" field. public const int DataTypeFieldNumber = 2; - private global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorProto.Types.DataType dataType_ = 0; + private global::Microsoft.ML.UniversalModelFormat.Onnx.TensorProto.Types.DataType dataType_ = 0; /// /// The data type of the tensor. /// [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorProto.Types.DataType DataType + public global::Microsoft.ML.UniversalModelFormat.Onnx.TensorProto.Types.DataType DataType { get { return dataType_; } set @@ -2471,9 +2471,9 @@ public TensorProto Clone() /// Field number for the "segment" field. public const int SegmentFieldNumber = 3; - private global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorProto.Types.Segment segment_; + private global::Microsoft.ML.UniversalModelFormat.Onnx.TensorProto.Types.Segment segment_; [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorProto.Types.Segment Segment + public global::Microsoft.ML.UniversalModelFormat.Onnx.TensorProto.Types.Segment Segment { get { return segment_; } set @@ -2807,7 +2807,7 @@ public void MergeFrom(TensorProto other) { if (segment_ == null) { - segment_ = new global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorProto.Types.Segment(); + segment_ = new global::Microsoft.ML.UniversalModelFormat.Onnx.TensorProto.Types.Segment(); } Segment.MergeFrom(other.Segment); } @@ -2851,14 +2851,14 @@ public void MergeFrom(pb::CodedInputStream input) } case 16: { - dataType_ = (global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorProto.Types.DataType)input.ReadEnum(); + dataType_ = (global::Microsoft.ML.UniversalModelFormat.Onnx.TensorProto.Types.DataType)input.ReadEnum(); break; } case 26: { if (segment_ == null) { - segment_ = new global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorProto.Types.Segment(); + segment_ = new global::Microsoft.ML.UniversalModelFormat.Onnx.TensorProto.Types.Segment(); } input.ReadMessage(segment_); break; @@ -2993,7 +2993,7 @@ public sealed partial class Segment : pb::IMessage [global::System.Diagnostics.DebuggerNonUserCodeAttribute] public static pbr::MessageDescriptor Descriptor { - get { return global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorProto.Descriptor.NestedTypes[0]; } + get { return global::Microsoft.ML.UniversalModelFormat.Onnx.TensorProto.Descriptor.NestedTypes[0]; } } [global::System.Diagnostics.DebuggerNonUserCodeAttribute] @@ -3194,7 +3194,7 @@ public sealed partial class TensorShapeProto : pb::IMessage [global::System.Diagnostics.DebuggerNonUserCodeAttribute] public static pbr::MessageDescriptor Descriptor { - get { return global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.OnnxMlReflection.Descriptor.MessageTypes[7]; } + get { return global::Microsoft.ML.UniversalModelFormat.Onnx.OnnxMlReflection.Descriptor.MessageTypes[7]; } } [global::System.Diagnostics.DebuggerNonUserCodeAttribute] @@ -3226,11 +3226,11 @@ public TensorShapeProto Clone() /// Field number for the "dim" field. public const int DimFieldNumber = 1; - private static readonly pb::FieldCodec _repeated_dim_codec - = pb::FieldCodec.ForMessage(10, global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorShapeProto.Types.Dimension.Parser); - private readonly pbc::RepeatedField dim_ = new pbc::RepeatedField(); + private static readonly pb::FieldCodec _repeated_dim_codec + = pb::FieldCodec.ForMessage(10, global::Microsoft.ML.UniversalModelFormat.Onnx.TensorShapeProto.Types.Dimension.Parser); + private readonly pbc::RepeatedField dim_ = new pbc::RepeatedField(); [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public pbc::RepeatedField Dim + public pbc::RepeatedField Dim { get { return dim_; } } @@ -3342,7 +3342,7 @@ public sealed partial class Dimension : pb::IMessage [global::System.Diagnostics.DebuggerNonUserCodeAttribute] public static pbr::MessageDescriptor Descriptor { - get { return global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorShapeProto.Descriptor.NestedTypes[0]; } + get { return global::Microsoft.ML.UniversalModelFormat.Onnx.TensorShapeProto.Descriptor.NestedTypes[0]; } } [global::System.Diagnostics.DebuggerNonUserCodeAttribute] @@ -3621,7 +3621,7 @@ public sealed partial class TypeProto : pb::IMessage [global::System.Diagnostics.DebuggerNonUserCodeAttribute] public static pbr::MessageDescriptor Descriptor { - get { return global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.OnnxMlReflection.Descriptor.MessageTypes[8]; } + get { return global::Microsoft.ML.UniversalModelFormat.Onnx.OnnxMlReflection.Descriptor.MessageTypes[8]; } } [global::System.Diagnostics.DebuggerNonUserCodeAttribute] @@ -3670,9 +3670,9 @@ public TypeProto Clone() /// The type of a tensor. /// [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto.Types.Tensor TensorType + public global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto.Types.Tensor TensorType { - get { return valueCase_ == ValueOneofCase.TensorType ? (global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto.Types.Tensor)value_ : null; } + get { return valueCase_ == ValueOneofCase.TensorType ? (global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto.Types.Tensor)value_ : null; } set { value_ = value; @@ -3686,9 +3686,9 @@ public TypeProto Clone() /// The type of a sequence. /// [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto.Types.Sequence SequenceType + public global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto.Types.Sequence SequenceType { - get { return valueCase_ == ValueOneofCase.SequenceType ? (global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto.Types.Sequence)value_ : null; } + get { return valueCase_ == ValueOneofCase.SequenceType ? (global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto.Types.Sequence)value_ : null; } set { value_ = value; @@ -3702,9 +3702,9 @@ public TypeProto Clone() /// The type of a map. /// [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto.Types.Map MapType + public global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto.Types.Map MapType { - get { return valueCase_ == ValueOneofCase.MapType ? (global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto.Types.Map)value_ : null; } + get { return valueCase_ == ValueOneofCase.MapType ? (global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto.Types.Map)value_ : null; } set { value_ = value; @@ -3873,21 +3873,21 @@ public void MergeFrom(TypeProto other) case ValueOneofCase.TensorType: if (TensorType == null) { - TensorType = new global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto.Types.Tensor(); + TensorType = new global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto.Types.Tensor(); } TensorType.MergeFrom(other.TensorType); break; case ValueOneofCase.SequenceType: if (SequenceType == null) { - SequenceType = new global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto.Types.Sequence(); + SequenceType = new global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto.Types.Sequence(); } SequenceType.MergeFrom(other.SequenceType); break; case ValueOneofCase.MapType: if (MapType == null) { - MapType = new global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto.Types.Map(); + MapType = new global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto.Types.Map(); } MapType.MergeFrom(other.MapType); break; @@ -3909,7 +3909,7 @@ public void MergeFrom(pb::CodedInputStream input) break; case 10: { - global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto.Types.Tensor subBuilder = new global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto.Types.Tensor(); + global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto.Types.Tensor subBuilder = new global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto.Types.Tensor(); if (valueCase_ == ValueOneofCase.TensorType) { subBuilder.MergeFrom(TensorType); @@ -3920,7 +3920,7 @@ public void MergeFrom(pb::CodedInputStream input) } case 34: { - global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto.Types.Sequence subBuilder = new global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto.Types.Sequence(); + global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto.Types.Sequence subBuilder = new global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto.Types.Sequence(); if (valueCase_ == ValueOneofCase.SequenceType) { subBuilder.MergeFrom(SequenceType); @@ -3931,7 +3931,7 @@ public void MergeFrom(pb::CodedInputStream input) } case 42: { - global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto.Types.Map subBuilder = new global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto.Types.Map(); + global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto.Types.Map subBuilder = new global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto.Types.Map(); if (valueCase_ == ValueOneofCase.MapType) { subBuilder.MergeFrom(MapType); @@ -3964,7 +3964,7 @@ public sealed partial class Tensor : pb::IMessage [global::System.Diagnostics.DebuggerNonUserCodeAttribute] public static pbr::MessageDescriptor Descriptor { - get { return global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto.Descriptor.NestedTypes[0]; } + get { return global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto.Descriptor.NestedTypes[0]; } } [global::System.Diagnostics.DebuggerNonUserCodeAttribute] @@ -3997,13 +3997,13 @@ public Tensor Clone() /// Field number for the "elem_type" field. public const int ElemTypeFieldNumber = 1; - private global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorProto.Types.DataType elemType_ = 0; + private global::Microsoft.ML.UniversalModelFormat.Onnx.TensorProto.Types.DataType elemType_ = 0; /// /// This field MUST NOT have the value of UNDEFINED /// This field MUST be present for this version of the IR. /// [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorProto.Types.DataType ElemType + public global::Microsoft.ML.UniversalModelFormat.Onnx.TensorProto.Types.DataType ElemType { get { return elemType_; } set @@ -4014,9 +4014,9 @@ public Tensor Clone() /// Field number for the "shape" field. public const int ShapeFieldNumber = 2; - private global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorShapeProto shape_; + private global::Microsoft.ML.UniversalModelFormat.Onnx.TensorShapeProto shape_; [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorShapeProto Shape + public global::Microsoft.ML.UniversalModelFormat.Onnx.TensorShapeProto Shape { get { return shape_; } set @@ -4119,7 +4119,7 @@ public void MergeFrom(Tensor other) { if (shape_ == null) { - shape_ = new global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorShapeProto(); + shape_ = new global::Microsoft.ML.UniversalModelFormat.Onnx.TensorShapeProto(); } Shape.MergeFrom(other.Shape); } @@ -4139,14 +4139,14 @@ public void MergeFrom(pb::CodedInputStream input) break; case 8: { - elemType_ = (global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorProto.Types.DataType)input.ReadEnum(); + elemType_ = (global::Microsoft.ML.UniversalModelFormat.Onnx.TensorProto.Types.DataType)input.ReadEnum(); break; } case 18: { if (shape_ == null) { - shape_ = new global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorShapeProto(); + shape_ = new global::Microsoft.ML.UniversalModelFormat.Onnx.TensorShapeProto(); } input.ReadMessage(shape_); break; @@ -4170,7 +4170,7 @@ public sealed partial class Sequence : pb::IMessage [global::System.Diagnostics.DebuggerNonUserCodeAttribute] public static pbr::MessageDescriptor Descriptor { - get { return global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto.Descriptor.NestedTypes[1]; } + get { return global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto.Descriptor.NestedTypes[1]; } } [global::System.Diagnostics.DebuggerNonUserCodeAttribute] @@ -4202,13 +4202,13 @@ public Sequence Clone() /// Field number for the "elem_type" field. public const int ElemTypeFieldNumber = 1; - private global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto elemType_; + private global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto elemType_; /// /// The type and optional shape of each element of the sequence. /// This field MUST be present for this version of the IR. /// [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto ElemType + public global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto ElemType { get { return elemType_; } set @@ -4296,7 +4296,7 @@ public void MergeFrom(Sequence other) { if (elemType_ == null) { - elemType_ = new global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto(); + elemType_ = new global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto(); } ElemType.MergeFrom(other.ElemType); } @@ -4318,7 +4318,7 @@ public void MergeFrom(pb::CodedInputStream input) { if (elemType_ == null) { - elemType_ = new global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto(); + elemType_ = new global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto(); } input.ReadMessage(elemType_); break; @@ -4342,7 +4342,7 @@ public sealed partial class Map : pb::IMessage [global::System.Diagnostics.DebuggerNonUserCodeAttribute] public static pbr::MessageDescriptor Descriptor { - get { return global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto.Descriptor.NestedTypes[2]; } + get { return global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto.Descriptor.NestedTypes[2]; } } [global::System.Diagnostics.DebuggerNonUserCodeAttribute] @@ -4375,13 +4375,13 @@ public Map Clone() /// Field number for the "key_type" field. public const int KeyTypeFieldNumber = 1; - private global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorProto.Types.DataType keyType_ = 0; + private global::Microsoft.ML.UniversalModelFormat.Onnx.TensorProto.Types.DataType keyType_ = 0; /// /// This field MUST be present for this version of the IR. /// This field MUST refer to an integral type ([U]INT{8|16|32|64}) or STRING /// [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorProto.Types.DataType KeyType + public global::Microsoft.ML.UniversalModelFormat.Onnx.TensorProto.Types.DataType KeyType { get { return keyType_; } set @@ -4392,12 +4392,12 @@ public Map Clone() /// Field number for the "value_type" field. public const int ValueTypeFieldNumber = 2; - private global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto valueType_; + private global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto valueType_; /// /// This field MUST be present for this version of the IR. /// [global::System.Diagnostics.DebuggerNonUserCodeAttribute] - public global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto ValueType + public global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto ValueType { get { return valueType_; } set @@ -4500,7 +4500,7 @@ public void MergeFrom(Map other) { if (valueType_ == null) { - valueType_ = new global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto(); + valueType_ = new global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto(); } ValueType.MergeFrom(other.ValueType); } @@ -4520,14 +4520,14 @@ public void MergeFrom(pb::CodedInputStream input) break; case 8: { - keyType_ = (global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TensorProto.Types.DataType)input.ReadEnum(); + keyType_ = (global::Microsoft.ML.UniversalModelFormat.Onnx.TensorProto.Types.DataType)input.ReadEnum(); break; } case 18: { if (valueType_ == null) { - valueType_ = new global::Microsoft.ML.Runtime.UniversalModelFormat.Onnx.TypeProto(); + valueType_ = new global::Microsoft.ML.UniversalModelFormat.Onnx.TypeProto(); } input.ReadMessage(valueType_); break; @@ -4558,7 +4558,7 @@ public sealed partial class OperatorSetIdProto : pb::IMessage /// Contains methods to create ONNX models in protocol buffer. diff --git a/src/Microsoft.ML.Onnx/SaveOnnxCommand.cs b/src/Microsoft.ML.Onnx/SaveOnnxCommand.cs index 446fc4cc78..250969850f 100644 --- a/src/Microsoft.ML.Onnx/SaveOnnxCommand.cs +++ b/src/Microsoft.ML.Onnx/SaveOnnxCommand.cs @@ -5,13 +5,13 @@ using System.Collections.Generic; using System.IO; using Google.Protobuf; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Command; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model.Onnx; +using Microsoft.ML; +using Microsoft.ML.Command; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model.Onnx; using Newtonsoft.Json; [assembly: LoadableClass(SaveOnnxCommand.Summary, typeof(SaveOnnxCommand), typeof(SaveOnnxCommand.Arguments), typeof(SignatureCommand), @@ -19,7 +19,7 @@ [assembly: LoadableClass(typeof(void), typeof(SaveOnnxCommand), null, typeof(SignatureEntryPointModule), "SaveOnnx")] -namespace Microsoft.ML.Runtime.Model.Onnx +namespace Microsoft.ML.Model.Onnx { internal sealed class SaveOnnxCommand : DataCommand.ImplBase { diff --git a/src/Microsoft.ML.OnnxTransform.StaticPipe/DnnImageFeaturizerStaticExtensions.cs b/src/Microsoft.ML.OnnxTransform.StaticPipe/DnnImageFeaturizerStaticExtensions.cs index 2762a29084..5a524008d8 100644 --- a/src/Microsoft.ML.OnnxTransform.StaticPipe/DnnImageFeaturizerStaticExtensions.cs +++ b/src/Microsoft.ML.OnnxTransform.StaticPipe/DnnImageFeaturizerStaticExtensions.cs @@ -3,8 +3,7 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; using Microsoft.ML.StaticPipe; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Transforms; diff --git a/src/Microsoft.ML.OnnxTransform.StaticPipe/OnnxStaticExtensions.cs b/src/Microsoft.ML.OnnxTransform.StaticPipe/OnnxStaticExtensions.cs index fe1f245f79..656a25a915 100644 --- a/src/Microsoft.ML.OnnxTransform.StaticPipe/OnnxStaticExtensions.cs +++ b/src/Microsoft.ML.OnnxTransform.StaticPipe/OnnxStaticExtensions.cs @@ -3,7 +3,6 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; using Microsoft.ML.StaticPipe; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Transforms; diff --git a/src/Microsoft.ML.OnnxTransform/DnnImageFeaturizerTransform.cs b/src/Microsoft.ML.OnnxTransform/DnnImageFeaturizerTransform.cs index a18159d94e..fd146afef6 100644 --- a/src/Microsoft.ML.OnnxTransform/DnnImageFeaturizerTransform.cs +++ b/src/Microsoft.ML.OnnxTransform/DnnImageFeaturizerTransform.cs @@ -4,9 +4,6 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; using Microsoft.ML.StaticPipe; using Microsoft.ML.StaticPipe.Runtime; using System; diff --git a/src/Microsoft.ML.OnnxTransform/OnnxCatalog.cs b/src/Microsoft.ML.OnnxTransform/OnnxCatalog.cs index 4618c57ca1..45ec66fb3e 100644 --- a/src/Microsoft.ML.OnnxTransform/OnnxCatalog.cs +++ b/src/Microsoft.ML.OnnxTransform/OnnxCatalog.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.Transforms; namespace Microsoft.ML diff --git a/src/Microsoft.ML.OnnxTransform/OnnxTransform.cs b/src/Microsoft.ML.OnnxTransform/OnnxTransform.cs index b5e1e81387..0e3fd104c8 100644 --- a/src/Microsoft.ML.OnnxTransform/OnnxTransform.cs +++ b/src/Microsoft.ML.OnnxTransform/OnnxTransform.cs @@ -6,18 +6,17 @@ using System.Collections.Generic; using System.IO; using System.Linq; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.OnnxRuntime; using Microsoft.ML.Transforms; using Microsoft.ML.StaticPipe; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Core.Data; -using Microsoft.ML.Data; using OnnxShape = System.Collections.Generic.List; [assembly: LoadableClass(OnnxTransform.Summary, typeof(IDataTransform), typeof(OnnxTransform), diff --git a/src/Microsoft.ML.OnnxTransform/OnnxUtils.cs b/src/Microsoft.ML.OnnxTransform/OnnxUtils.cs index 001f2ce9d8..af9ae4f13a 100644 --- a/src/Microsoft.ML.OnnxTransform/OnnxUtils.cs +++ b/src/Microsoft.ML.OnnxTransform/OnnxUtils.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.OnnxRuntime; using System.Numerics.Tensors; using System; diff --git a/src/Microsoft.ML.PCA/PCACatalog.cs b/src/Microsoft.ML.PCA/PCACatalog.cs index 005638421f..4c5c02cd1f 100644 --- a/src/Microsoft.ML.PCA/PCACatalog.cs +++ b/src/Microsoft.ML.PCA/PCACatalog.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.Transforms.Projections; namespace Microsoft.ML diff --git a/src/Microsoft.ML.PCA/PcaTrainer.cs b/src/Microsoft.ML.PCA/PcaTrainer.cs index 29dc4be86d..21dab10a7a 100644 --- a/src/Microsoft.ML.PCA/PcaTrainer.cs +++ b/src/Microsoft.ML.PCA/PcaTrainer.cs @@ -4,16 +4,15 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.CpuMath; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Numeric; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.CpuMath; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Numeric; +using Microsoft.ML.Training; using Microsoft.ML.Trainers.PCA; using System; using System.IO; diff --git a/src/Microsoft.ML.PCA/PcaTransform.cs b/src/Microsoft.ML.PCA/PcaTransform.cs index 81d6bc7417..f3ed85f647 100644 --- a/src/Microsoft.ML.PCA/PcaTransform.cs +++ b/src/Microsoft.ML.PCA/PcaTransform.cs @@ -4,14 +4,13 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.CpuMath; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Numeric; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.CpuMath; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Numeric; using Microsoft.ML.StaticPipe; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Transforms.Projections; diff --git a/src/Microsoft.ML.Parquet/ParquetLoader.cs b/src/Microsoft.ML.Parquet/ParquetLoader.cs index 11d2c2d38e..1a34711da1 100644 --- a/src/Microsoft.ML.Parquet/ParquetLoader.cs +++ b/src/Microsoft.ML.Parquet/ParquetLoader.cs @@ -10,12 +10,11 @@ using System.Numerics; using System.Text; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Parquet; using Parquet.Data; using Parquet.File.Values.Primitives; @@ -26,7 +25,7 @@ [assembly: LoadableClass(ParquetLoader.Summary, typeof(ParquetLoader), null, typeof(SignatureLoadDataLoader), ParquetLoader.LoaderName, ParquetLoader.LoaderSignature)] -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// Loads a parquet file into an IDataView. Supports basic mapping from Parquet input column data types to framework data types. diff --git a/src/Microsoft.ML.Recommender/MatrixFactorizationPredictor.cs b/src/Microsoft.ML.Recommender/MatrixFactorizationPredictor.cs index fb78fdcd33..e4917ba0eb 100644 --- a/src/Microsoft.ML.Recommender/MatrixFactorizationPredictor.cs +++ b/src/Microsoft.ML.Recommender/MatrixFactorizationPredictor.cs @@ -6,14 +6,13 @@ using System.Collections.Generic; using System.IO; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Recommender; -using Microsoft.ML.Runtime.Recommender.Internal; +using Microsoft.ML; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Recommender; +using Microsoft.ML.Recommender.Internal; using Microsoft.ML.Trainers.Recommender; [assembly: LoadableClass(typeof(MatrixFactorizationPredictor), null, typeof(SignatureLoadModel), "Matrix Factorization Predictor Executor", MatrixFactorizationPredictor.LoaderSignature)] diff --git a/src/Microsoft.ML.Recommender/MatrixFactorizationStatic.cs b/src/Microsoft.ML.Recommender/MatrixFactorizationStatic.cs index fee3009a6e..c33af5f612 100644 --- a/src/Microsoft.ML.Recommender/MatrixFactorizationStatic.cs +++ b/src/Microsoft.ML.Recommender/MatrixFactorizationStatic.cs @@ -3,8 +3,8 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Trainers; using Microsoft.ML.Trainers.Recommender; diff --git a/src/Microsoft.ML.Recommender/MatrixFactorizationTrainer.cs b/src/Microsoft.ML.Recommender/MatrixFactorizationTrainer.cs index 2a4f5eb782..1bd4253e58 100644 --- a/src/Microsoft.ML.Recommender/MatrixFactorizationTrainer.cs +++ b/src/Microsoft.ML.Recommender/MatrixFactorizationTrainer.cs @@ -4,14 +4,13 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Recommender; -using Microsoft.ML.Runtime.Recommender.Internal; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Recommender; +using Microsoft.ML.Recommender.Internal; +using Microsoft.ML.Training; using Microsoft.ML.Trainers; using Microsoft.ML.Trainers.Recommender; using System; diff --git a/src/Microsoft.ML.Recommender/RecommenderCatalog.cs b/src/Microsoft.ML.Recommender/RecommenderCatalog.cs index a333df30f1..55bc159217 100644 --- a/src/Microsoft.ML.Recommender/RecommenderCatalog.cs +++ b/src/Microsoft.ML.Recommender/RecommenderCatalog.cs @@ -4,8 +4,6 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime; using Microsoft.ML.Trainers; using System.Linq; using System; diff --git a/src/Microsoft.ML.Recommender/RecommenderUtils.cs b/src/Microsoft.ML.Recommender/RecommenderUtils.cs index d683bad3ad..79a9bf2f54 100644 --- a/src/Microsoft.ML.Recommender/RecommenderUtils.cs +++ b/src/Microsoft.ML.Recommender/RecommenderUtils.cs @@ -1,12 +1,12 @@ -// Licensed to the .NET 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. +using System.Threading; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Recommender +namespace Microsoft.ML.Recommender { internal static class RecommenderUtils { diff --git a/src/Microsoft.ML.Recommender/SafeTrainingAndModelBuffer.cs b/src/Microsoft.ML.Recommender/SafeTrainingAndModelBuffer.cs index d2c918a55b..fd00ddb1f0 100644 --- a/src/Microsoft.ML.Recommender/SafeTrainingAndModelBuffer.cs +++ b/src/Microsoft.ML.Recommender/SafeTrainingAndModelBuffer.cs @@ -6,10 +6,10 @@ using System.Collections.Generic; using System.Runtime.InteropServices; using System.Security; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Recommender.Internal +namespace Microsoft.ML.Recommender.Internal { /// /// Contains mirrors of unmanaged struct import extern functions from mf.h / mf.cpp, which implements Matrix Factorization in native C++. diff --git a/src/Microsoft.ML.ResultProcessor/ResultProcessor.cs b/src/Microsoft.ML.ResultProcessor/ResultProcessor.cs index 987d63d237..3cccec12f8 100644 --- a/src/Microsoft.ML.ResultProcessor/ResultProcessor.cs +++ b/src/Microsoft.ML.ResultProcessor/ResultProcessor.cs @@ -9,18 +9,18 @@ using System.Linq; using System.Runtime.Serialization.Formatters.Binary; using System.Text.RegularExpressions; -using Microsoft.ML.Runtime.Command; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML.Command; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Tools; #if TLCFULLBUILD -using Microsoft.ML.Runtime.ExperimentVisualization; +using Microsoft.ML.ExperimentVisualization; #endif -namespace Microsoft.ML.Runtime.Internal.Internallearn.ResultProcessor +namespace Microsoft.ML.Internal.Internallearn.ResultProcessor { using Float = System.Single; /// diff --git a/src/Microsoft.ML.StandardLearners/FactorizationMachine/FactorizationMachineCatalog.cs b/src/Microsoft.ML.StandardLearners/FactorizationMachine/FactorizationMachineCatalog.cs index cc11b083dd..c5899db003 100644 --- a/src/Microsoft.ML.StandardLearners/FactorizationMachine/FactorizationMachineCatalog.cs +++ b/src/Microsoft.ML.StandardLearners/FactorizationMachine/FactorizationMachineCatalog.cs @@ -2,9 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.FactorizationMachine; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.FactorizationMachine; using System; namespace Microsoft.ML diff --git a/src/Microsoft.ML.StandardLearners/FactorizationMachine/FactorizationMachineInterface.cs b/src/Microsoft.ML.StandardLearners/FactorizationMachine/FactorizationMachineInterface.cs index f746c3bd89..cc99488891 100644 --- a/src/Microsoft.ML.StandardLearners/FactorizationMachine/FactorizationMachineInterface.cs +++ b/src/Microsoft.ML.StandardLearners/FactorizationMachine/FactorizationMachineInterface.cs @@ -2,12 +2,12 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Internal.CpuMath; +using Microsoft.ML.Internal.CpuMath; using System.Runtime.InteropServices; using System.Security; -namespace Microsoft.ML.Runtime.FactorizationMachine +namespace Microsoft.ML.FactorizationMachine { internal static unsafe class FieldAwareFactorizationMachineInterface { diff --git a/src/Microsoft.ML.StandardLearners/FactorizationMachine/FactorizationMachineStatic.cs b/src/Microsoft.ML.StandardLearners/FactorizationMachine/FactorizationMachineStatic.cs index 0d47813323..97a0a9f1f7 100644 --- a/src/Microsoft.ML.StandardLearners/FactorizationMachine/FactorizationMachineStatic.cs +++ b/src/Microsoft.ML.StandardLearners/FactorizationMachine/FactorizationMachineStatic.cs @@ -3,10 +3,9 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.FactorizationMachine; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Data; +using Microsoft.ML.FactorizationMachine; +using Microsoft.ML.Internal.Utilities; using Microsoft.ML.StaticPipe.Runtime; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.StandardLearners/FactorizationMachine/FactorizationMachineTrainer.cs b/src/Microsoft.ML.StandardLearners/FactorizationMachine/FactorizationMachineTrainer.cs index 07b49f1808..828614ac9c 100644 --- a/src/Microsoft.ML.StandardLearners/FactorizationMachine/FactorizationMachineTrainer.cs +++ b/src/Microsoft.ML.StandardLearners/FactorizationMachine/FactorizationMachineTrainer.cs @@ -4,14 +4,13 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.FactorizationMachine; -using Microsoft.ML.Runtime.Internal.CpuMath; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.FactorizationMachine; +using Microsoft.ML.Internal.CpuMath; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Training; using System; using System.Collections.Generic; using System.Linq; @@ -23,7 +22,7 @@ [assembly: LoadableClass(typeof(void), typeof(FieldAwareFactorizationMachineTrainer), null, typeof(SignatureEntryPointModule), FieldAwareFactorizationMachineTrainer.LoadName)] -namespace Microsoft.ML.Runtime.FactorizationMachine +namespace Microsoft.ML.FactorizationMachine { /* Train a field-aware factorization machine using ADAGRAD (an advanced stochastic gradient method). See references below diff --git a/src/Microsoft.ML.StandardLearners/FactorizationMachine/FieldAwareFactorizationMachineModelParameters.cs b/src/Microsoft.ML.StandardLearners/FactorizationMachine/FieldAwareFactorizationMachineModelParameters.cs index c6820a48db..69f156fc74 100644 --- a/src/Microsoft.ML.StandardLearners/FactorizationMachine/FieldAwareFactorizationMachineModelParameters.cs +++ b/src/Microsoft.ML.StandardLearners/FactorizationMachine/FieldAwareFactorizationMachineModelParameters.cs @@ -4,23 +4,21 @@ using System; using System.Collections.Generic; -using System.IO; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.FactorizationMachine; -using Microsoft.ML.Runtime.Internal.CpuMath; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.Data.IO; +using Microsoft.ML.FactorizationMachine; +using Microsoft.ML.Internal.CpuMath; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; [assembly: LoadableClass(typeof(FieldAwareFactorizationMachineModelParameters), null, typeof(SignatureLoadModel), "Field Aware Factorization Machine", FieldAwareFactorizationMachineModelParameters.LoaderSignature)] [assembly: LoadableClass(typeof(FieldAwareFactorizationMachinePredictionTransformer), typeof(FieldAwareFactorizationMachinePredictionTransformer), null, typeof(SignatureLoadModel), "", FieldAwareFactorizationMachinePredictionTransformer.LoaderSignature)] -namespace Microsoft.ML.Runtime.FactorizationMachine +namespace Microsoft.ML.FactorizationMachine { public sealed class FieldAwareFactorizationMachineModelParameters : ModelParametersBase, ISchemaBindableMapper { diff --git a/src/Microsoft.ML.StandardLearners/FactorizationMachine/FieldAwareFactorizationMachineUtils.cs b/src/Microsoft.ML.StandardLearners/FactorizationMachine/FieldAwareFactorizationMachineUtils.cs index 2bc1ce99b4..0696ac0516 100644 --- a/src/Microsoft.ML.StandardLearners/FactorizationMachine/FieldAwareFactorizationMachineUtils.cs +++ b/src/Microsoft.ML.StandardLearners/FactorizationMachine/FieldAwareFactorizationMachineUtils.cs @@ -6,11 +6,10 @@ using System.Collections.Generic; using System.Linq; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.CpuMath; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.CpuMath; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.FactorizationMachine +namespace Microsoft.ML.FactorizationMachine { internal sealed class FieldAwareFactorizationMachineUtils { diff --git a/src/Microsoft.ML.StandardLearners/Optimizer/DifferentiableFunction.cs b/src/Microsoft.ML.StandardLearners/Optimizer/DifferentiableFunction.cs index d54f6b8666..0f1552ba46 100644 --- a/src/Microsoft.ML.StandardLearners/Optimizer/DifferentiableFunction.cs +++ b/src/Microsoft.ML.StandardLearners/Optimizer/DifferentiableFunction.cs @@ -7,10 +7,10 @@ using System; using System.Collections.Generic; using System.Threading; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Numeric +namespace Microsoft.ML.Numeric { /// /// A delegate for functions with gradients. diff --git a/src/Microsoft.ML.StandardLearners/Optimizer/L1Optimizer.cs b/src/Microsoft.ML.StandardLearners/Optimizer/L1Optimizer.cs index 1f9174a601..84ef6e5b86 100644 --- a/src/Microsoft.ML.StandardLearners/Optimizer/L1Optimizer.cs +++ b/src/Microsoft.ML.StandardLearners/Optimizer/L1Optimizer.cs @@ -5,10 +5,10 @@ using Float = System.Single; using System; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Numeric +namespace Microsoft.ML.Numeric { /// /// Orthant-Wise Limited-memory Quasi-Newton algorithm diff --git a/src/Microsoft.ML.StandardLearners/Optimizer/LineSearch.cs b/src/Microsoft.ML.StandardLearners/Optimizer/LineSearch.cs index 6b905a8ef2..311a8007cd 100644 --- a/src/Microsoft.ML.StandardLearners/Optimizer/LineSearch.cs +++ b/src/Microsoft.ML.StandardLearners/Optimizer/LineSearch.cs @@ -5,10 +5,10 @@ using Float = System.Single; using System; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Numeric +namespace Microsoft.ML.Numeric { /// /// Line search that does not use derivatives diff --git a/src/Microsoft.ML.StandardLearners/Optimizer/OptimizationMonitor.cs b/src/Microsoft.ML.StandardLearners/Optimizer/OptimizationMonitor.cs index 705c9f8477..cf117ffc1d 100644 --- a/src/Microsoft.ML.StandardLearners/Optimizer/OptimizationMonitor.cs +++ b/src/Microsoft.ML.StandardLearners/Optimizer/OptimizationMonitor.cs @@ -6,10 +6,10 @@ using System; using System.Collections.Generic; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Numeric +namespace Microsoft.ML.Numeric { /// /// An object which is used to decide whether to stop optimization. diff --git a/src/Microsoft.ML.StandardLearners/Optimizer/Optimizer.cs b/src/Microsoft.ML.StandardLearners/Optimizer/Optimizer.cs index 914924d762..8d070670c3 100644 --- a/src/Microsoft.ML.StandardLearners/Optimizer/Optimizer.cs +++ b/src/Microsoft.ML.StandardLearners/Optimizer/Optimizer.cs @@ -6,10 +6,10 @@ using System; using System.Collections.Generic; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Numeric +namespace Microsoft.ML.Numeric { /// /// Limited-memory BFGS quasi-Newton optimization routine diff --git a/src/Microsoft.ML.StandardLearners/Optimizer/SgdOptimizer.cs b/src/Microsoft.ML.StandardLearners/Optimizer/SgdOptimizer.cs index c03c709e2a..53d5236bac 100644 --- a/src/Microsoft.ML.StandardLearners/Optimizer/SgdOptimizer.cs +++ b/src/Microsoft.ML.StandardLearners/Optimizer/SgdOptimizer.cs @@ -5,10 +5,10 @@ using Float = System.Single; using System; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Numeric +namespace Microsoft.ML.Numeric { /// /// Delegate for functions that determine whether to terminate search. Called after each update. diff --git a/src/Microsoft.ML.StandardLearners/Standard/LinearModelParameters.cs b/src/Microsoft.ML.StandardLearners/Standard/LinearModelParameters.cs index ef25970909..7eb4f5d980 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/LinearModelParameters.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/LinearModelParameters.cs @@ -4,16 +4,15 @@ using Microsoft.ML.Calibrator; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Onnx; -using Microsoft.ML.Runtime.Model.Pfa; -using Microsoft.ML.Runtime.Numeric; +using Microsoft.ML; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Learners; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Onnx; +using Microsoft.ML.Model.Pfa; +using Microsoft.ML.Numeric; using Newtonsoft.Json.Linq; using System; using System.Collections; @@ -36,7 +35,7 @@ "Poisson Regression Executor", PoissonRegressionModelParameters.LoaderSignature)] -namespace Microsoft.ML.Runtime.Learners +namespace Microsoft.ML.Learners { public abstract class LinearModelParameters : ModelParametersBase, IValueMapper, diff --git a/src/Microsoft.ML.StandardLearners/Standard/LinearPredictorUtils.cs b/src/Microsoft.ML.StandardLearners/Standard/LinearPredictorUtils.cs index 02aff9f02b..6d359eabed 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/LinearPredictorUtils.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/LinearPredictorUtils.cs @@ -11,11 +11,10 @@ using System.IO; using System.Text.RegularExpressions; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Learners +namespace Microsoft.ML.Learners { /// /// Helper methods for linear predictors diff --git a/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LbfgsPredictorBase.cs b/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LbfgsPredictorBase.cs index 490a3cca9f..4392896e17 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LbfgsPredictorBase.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LbfgsPredictorBase.cs @@ -6,15 +6,15 @@ using System.Collections.Generic; using System.Threading.Tasks; using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Numeric; -using Microsoft.ML.Runtime.Training; -using Microsoft.ML.Runtime.Internal.Internallearn; - -namespace Microsoft.ML.Runtime.Learners +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Numeric; +using Microsoft.ML.Training; +using Microsoft.ML.Internal.Internallearn; + +namespace Microsoft.ML.Learners { public abstract class LbfgsTrainerBase : TrainerEstimatorBase where TTransformer : ISingleFeaturePredictionTransformer diff --git a/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LbfgsStatic.cs b/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LbfgsStatic.cs index 8222c18f06..e192adeae4 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LbfgsStatic.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LbfgsStatic.cs @@ -2,10 +2,10 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Learners; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Learners; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Trainers; using System; @@ -20,7 +20,7 @@ namespace Microsoft.ML.StaticPipe public static class LbfgsBinaryClassificationExtensions { /// - /// Predict a target using a linear binary classification model trained with the trainer. + /// Predict a target using a linear binary classification model trained with the trainer. /// /// The binary classificaiton context trainer object. /// The label, or dependent variable. @@ -29,7 +29,7 @@ public static class LbfgsBinaryClassificationExtensions /// Enforce non-negative weights. /// Weight of L1 regularization term. /// Weight of L2 regularization term. - /// Memory size for . Low=faster, less accurate. + /// Memory size for . Low=faster, less accurate. /// Threshold for optimizer convergence. /// A delegate that is called every time the /// method is called on the @@ -75,7 +75,7 @@ public static class LbfgsRegressionExtensions { /// - /// Predict a target using a linear regression model trained with the trainer. + /// Predict a target using a linear regression model trained with the trainer. /// /// The regression context trainer object. /// The label, or dependent variable. @@ -84,7 +84,7 @@ public static class LbfgsRegressionExtensions /// Enforce non-negative weights. /// Weight of L1 regularization term. /// Weight of L2 regularization term. - /// Memory size for . Low=faster, less accurate. + /// Memory size for . Low=faster, less accurate. /// Threshold for optimizer convergence. /// A delegate to apply all the advanced arguments to the algorithm. /// A delegate that is called every time the @@ -130,7 +130,7 @@ public static class LbfgsMulticlassExtensions { /// - /// Predict a target using a linear multiclass classification model trained with the trainer. + /// Predict a target using a linear multiclass classification model trained with the trainer. /// /// The multiclass classification context trainer object. /// The label, or dependent variable. @@ -139,7 +139,7 @@ public static class LbfgsMulticlassExtensions /// Enforce non-negative weights. /// Weight of L1 regularization term. /// Weight of L2 regularization term. - /// Memory size for . Low=faster, less accurate. + /// Memory size for . Low=faster, less accurate. /// Threshold for optimizer convergence. /// A delegate to apply all the advanced arguments to the algorithm. /// A delegate that is called every time the diff --git a/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LogisticRegression.cs b/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LogisticRegression.cs index cbfc68dcea..22b5aba502 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LogisticRegression.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LogisticRegression.cs @@ -6,16 +6,15 @@ using System.Collections.Generic; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.Numeric; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Learners; +using Microsoft.ML.Numeric; +using Microsoft.ML.Training; [assembly: LoadableClass(LogisticRegression.Summary, typeof(LogisticRegression), typeof(LogisticRegression.Arguments), new[] { typeof(SignatureBinaryClassifierTrainer), typeof(SignatureTrainer), typeof(SignatureFeatureScorerTrainer) }, @@ -26,7 +25,7 @@ [assembly: LoadableClass(typeof(void), typeof(LogisticRegression), null, typeof(SignatureEntryPointModule), LogisticRegression.LoadNameValue)] -namespace Microsoft.ML.Runtime.Learners +namespace Microsoft.ML.Learners { /// diff --git a/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/MulticlassLogisticRegression.cs b/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/MulticlassLogisticRegression.cs index d9e0622211..f057c5b9ce 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/MulticlassLogisticRegression.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/MulticlassLogisticRegression.cs @@ -4,18 +4,17 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Onnx; -using Microsoft.ML.Runtime.Model.Pfa; -using Microsoft.ML.Runtime.Numeric; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Learners; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Onnx; +using Microsoft.ML.Model.Pfa; +using Microsoft.ML.Numeric; +using Microsoft.ML.Training; using Microsoft.ML.Trainers; using Newtonsoft.Json.Linq; using System; @@ -35,7 +34,7 @@ "Multiclass LR Executor", MulticlassLogisticRegressionModelParameters.LoaderSignature)] -namespace Microsoft.ML.Runtime.Learners +namespace Microsoft.ML.Learners { /// /// diff --git a/src/Microsoft.ML.StandardLearners/Standard/ModelStatistics.cs b/src/Microsoft.ML.StandardLearners/Standard/ModelStatistics.cs index 47c993dcfa..8a781561ee 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/ModelStatistics.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/ModelStatistics.cs @@ -3,13 +3,12 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.CpuMath; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML; +using Microsoft.ML.Internal.CpuMath; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Learners; +using Microsoft.ML.Model; using System; using System.Collections.Generic; using System.IO; @@ -20,7 +19,7 @@ "Linear Model Statistics", LinearModelStatistics.LoaderSignature)] -namespace Microsoft.ML.Runtime.Learners +namespace Microsoft.ML.Learners { /// /// Represents a coefficient statistics object. diff --git a/src/Microsoft.ML.StandardLearners/Standard/MultiClass/MetaMulticlassTrainer.cs b/src/Microsoft.ML.StandardLearners/Standard/MultiClass/MetaMulticlassTrainer.cs index 1f2905dc72..b02a33956b 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/MultiClass/MetaMulticlassTrainer.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/MultiClass/MetaMulticlassTrainer.cs @@ -4,17 +4,16 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.Conversion; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data.Conversion; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Training; using Microsoft.ML.Trainers.Online; using System.Collections.Generic; using System.Linq; -namespace Microsoft.ML.Runtime.Learners +namespace Microsoft.ML.Learners { using TScalarTrainer = ITrainerEstimator>, IPredictorProducing>; diff --git a/src/Microsoft.ML.StandardLearners/Standard/MultiClass/MultiClassNaiveBayesStatic.cs b/src/Microsoft.ML.StandardLearners/Standard/MultiClass/MultiClassNaiveBayesStatic.cs index 49d77a9d15..b32a6cbe9d 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/MultiClass/MultiClassNaiveBayesStatic.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/MultiClass/MultiClassNaiveBayesStatic.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.StaticPipe; using Microsoft.ML.StaticPipe.Runtime; using System; diff --git a/src/Microsoft.ML.StandardLearners/Standard/MultiClass/MultiClassNaiveBayesTrainer.cs b/src/Microsoft.ML.StandardLearners/Standard/MultiClass/MultiClassNaiveBayesTrainer.cs index ccac31db5a..77b9d82c53 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/MultiClass/MultiClassNaiveBayesTrainer.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/MultiClass/MultiClassNaiveBayesTrainer.cs @@ -4,13 +4,12 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Training; using Microsoft.ML.Trainers; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.StandardLearners/Standard/MultiClass/Ova.cs b/src/Microsoft.ML.StandardLearners/Standard/MultiClass/Ova.cs index d7173e6031..6fdf68d78d 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/MultiClass/Ova.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/MultiClass/Ova.cs @@ -2,17 +2,17 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Pfa; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Learners; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Pfa; +using Microsoft.ML.Training; using Microsoft.ML.Trainers; using Newtonsoft.Json.Linq; using System; diff --git a/src/Microsoft.ML.StandardLearners/Standard/MultiClass/Pkpd.cs b/src/Microsoft.ML.StandardLearners/Standard/MultiClass/Pkpd.cs index c645f0cc96..2ba6863aef 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/MultiClass/Pkpd.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/MultiClass/Pkpd.cs @@ -2,14 +2,14 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Learners; +using Microsoft.ML.Model; +using Microsoft.ML.Training; using Microsoft.ML.Trainers; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.StandardLearners/Standard/Online/AveragedLinear.cs b/src/Microsoft.ML.StandardLearners/Standard/Online/AveragedLinear.cs index 9e703db34d..78cb423301 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/Online/AveragedLinear.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/Online/AveragedLinear.cs @@ -6,14 +6,14 @@ using System; using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Numeric; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Numeric; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Learners; +using Microsoft.ML; // TODO: Check if it works properly if Averaged is set to false diff --git a/src/Microsoft.ML.StandardLearners/Standard/Online/AveragedPerceptron.cs b/src/Microsoft.ML.StandardLearners/Standard/Online/AveragedPerceptron.cs index c4789895f8..e77f1fa970 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/Online/AveragedPerceptron.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/Online/AveragedPerceptron.cs @@ -4,15 +4,14 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.Numeric; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Learners; +using Microsoft.ML.Numeric; +using Microsoft.ML.Training; using Microsoft.ML.Trainers.Online; using System; diff --git a/src/Microsoft.ML.StandardLearners/Standard/Online/LinearSvm.cs b/src/Microsoft.ML.StandardLearners/Standard/Online/LinearSvm.cs index ac804fde2a..6beeeccb6d 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/Online/LinearSvm.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/Online/LinearSvm.cs @@ -4,16 +4,15 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.Numeric; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Learners; +using Microsoft.ML.Numeric; +using Microsoft.ML.Training; using Microsoft.ML.Trainers.Online; using System; using Float = System.Single; diff --git a/src/Microsoft.ML.StandardLearners/Standard/Online/OnlineGradientDescent.cs b/src/Microsoft.ML.StandardLearners/Standard/Online/OnlineGradientDescent.cs index 5aa28ad584..eb599cc6d7 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/Online/OnlineGradientDescent.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/Online/OnlineGradientDescent.cs @@ -4,14 +4,13 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.Numeric; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Learners; +using Microsoft.ML.Numeric; +using Microsoft.ML.Training; using Microsoft.ML.Trainers.Online; using System; diff --git a/src/Microsoft.ML.StandardLearners/Standard/Online/OnlineLearnerStatic.cs b/src/Microsoft.ML.StandardLearners/Standard/Online/OnlineLearnerStatic.cs index c37aab67a5..8e4884eda3 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/Online/OnlineLearnerStatic.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/Online/OnlineLearnerStatic.cs @@ -2,9 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Learners; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Learners; using Microsoft.ML.Trainers.Online; using Microsoft.ML.StaticPipe.Runtime; using System; diff --git a/src/Microsoft.ML.StandardLearners/Standard/Online/OnlineLinear.cs b/src/Microsoft.ML.StandardLearners/Standard/Online/OnlineLinear.cs index 78341717d6..97047913fe 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/Online/OnlineLinear.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/Online/OnlineLinear.cs @@ -3,16 +3,16 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.Numeric; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Learners; +using Microsoft.ML.Numeric; +using Microsoft.ML.Training; using System; using System.Globalization; diff --git a/src/Microsoft.ML.StandardLearners/Standard/PoissonRegression/PoissonRegression.cs b/src/Microsoft.ML.StandardLearners/Standard/PoissonRegression/PoissonRegression.cs index eadb146e3a..e310d13336 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/PoissonRegression/PoissonRegression.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/PoissonRegression/PoissonRegression.cs @@ -4,14 +4,13 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.Numeric; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Learners; +using Microsoft.ML.Numeric; +using Microsoft.ML.Training; using Microsoft.ML.Trainers; using System; diff --git a/src/Microsoft.ML.StandardLearners/Standard/SdcaBinary.cs b/src/Microsoft.ML.StandardLearners/Standard/SdcaBinary.cs index fbb5bb5580..f86ec5d200 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/SdcaBinary.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/SdcaBinary.cs @@ -4,18 +4,17 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.Conversion; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.CpuMath; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.Numeric; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data.Conversion; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.CpuMath; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Learners; +using Microsoft.ML.Numeric; +using Microsoft.ML.Training; using Microsoft.ML.Trainers; using Microsoft.ML.Transforms; using System; @@ -1131,7 +1130,7 @@ protected Func GetIndexFromIdAndRowGetter(IdToIdxLookup idToI // This class can also be made to accommodate generic type, as long as the type implements a // good 64-bit hash function. /// - /// A hash table data structure to store Id of type , + /// A hash table data structure to store Id of type , /// and accommodates size larger than 2 billion. This class is an extension based on BCL. /// Two operations are supported: adding and retrieving an id with asymptotically constant complexity. /// The bucket size are prime numbers, starting from 3 and grows to the next prime larger than diff --git a/src/Microsoft.ML.StandardLearners/Standard/SdcaMultiClass.cs b/src/Microsoft.ML.StandardLearners/Standard/SdcaMultiClass.cs index bf5f342c5d..5bf8bfd715 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/SdcaMultiClass.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/SdcaMultiClass.cs @@ -4,16 +4,15 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.CpuMath; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.Numeric; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.CpuMath; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Learners; +using Microsoft.ML.Numeric; +using Microsoft.ML.Training; using Microsoft.ML.Trainers; using System; using System.Linq; diff --git a/src/Microsoft.ML.StandardLearners/Standard/SdcaRegression.cs b/src/Microsoft.ML.StandardLearners/Standard/SdcaRegression.cs index b8bd077840..cea366dbc6 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/SdcaRegression.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/SdcaRegression.cs @@ -4,15 +4,14 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.Conversion; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data.Conversion; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Learners; +using Microsoft.ML.Training; using Microsoft.ML.Trainers; using System; diff --git a/src/Microsoft.ML.StandardLearners/Standard/SgdStatic.cs b/src/Microsoft.ML.StandardLearners/Standard/SgdStatic.cs index 8bc0b510a1..c66138a596 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/SgdStatic.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/SgdStatic.cs @@ -2,9 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Internallearn; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Internallearn; using Microsoft.ML.Trainers; using Microsoft.ML.StaticPipe.Runtime; using System; diff --git a/src/Microsoft.ML.StandardLearners/Standard/Simple/SimpleTrainers.cs b/src/Microsoft.ML.StandardLearners/Standard/Simple/SimpleTrainers.cs index 7e66d8d9e5..796a82514a 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/Simple/SimpleTrainers.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/Simple/SimpleTrainers.cs @@ -4,12 +4,11 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Training; using Microsoft.ML.Trainers; using System; using System.Linq; diff --git a/src/Microsoft.ML.StandardLearners/Standard/StochasticTrainerBase.cs b/src/Microsoft.ML.StandardLearners/Standard/StochasticTrainerBase.cs index e4e00d5507..be9c00dbcb 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/StochasticTrainerBase.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/StochasticTrainerBase.cs @@ -3,13 +3,13 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Training; using Microsoft.ML.Transforms; using System; -namespace Microsoft.ML.Runtime.Learners +namespace Microsoft.ML.Learners { public abstract class StochasticTrainerBase : TrainerEstimatorBase where TTransformer : ISingleFeaturePredictionTransformer diff --git a/src/Microsoft.ML.StandardLearners/StandardLearnersCatalog.cs b/src/Microsoft.ML.StandardLearners/StandardLearnersCatalog.cs index be2f17ad9d..3337eaf7c7 100644 --- a/src/Microsoft.ML.StandardLearners/StandardLearnersCatalog.cs +++ b/src/Microsoft.ML.StandardLearners/StandardLearnersCatalog.cs @@ -2,11 +2,11 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Learners; +using Microsoft.ML.Training; using Microsoft.ML.Trainers; using Microsoft.ML.Trainers.Online; using System; @@ -227,7 +227,7 @@ public static OnlineGradientDescentTrainer OnlineGradientDescent(this Regression } /// - /// Predict a target using a linear binary classification model trained with the trainer. + /// Predict a target using a linear binary classification model trained with the trainer. /// /// The binary classificaiton context trainer object. /// The label column name, or dependent variable. @@ -236,7 +236,7 @@ public static OnlineGradientDescentTrainer OnlineGradientDescent(this Regression /// Enforce non-negative weights. /// Weight of L1 regularization term. /// Weight of L2 regularization term. - /// Memory size for . Low=faster, less accurate. + /// Memory size for . Low=faster, less accurate. /// Threshold for optimizer convergence. /// A delegate to apply all the advanced arguments to the algorithm. public static LogisticRegression LogisticRegression(this BinaryClassificationContext.BinaryClassificationTrainers ctx, @@ -256,7 +256,7 @@ public static LogisticRegression LogisticRegression(this BinaryClassificationCon } /// - /// Predict a target using a linear regression model trained with the trainer. + /// Predict a target using a linear regression model trained with the trainer. /// /// The regression context trainer object. /// The labelColumn, or dependent variable. @@ -265,7 +265,7 @@ public static LogisticRegression LogisticRegression(this BinaryClassificationCon /// Weight of L1 regularization term. /// Weight of L2 regularization term. /// Threshold for optimizer convergence. - /// Memory size for . Low=faster, less accurate. + /// Memory size for . Low=faster, less accurate. /// Enforce non-negative weights. /// A delegate to apply all the advanced arguments to the algorithm. public static PoissonRegression PoissonRegression(this RegressionContext.RegressionTrainers ctx, @@ -285,7 +285,7 @@ public static PoissonRegression PoissonRegression(this RegressionContext.Regress } /// - /// Predict a target using a linear multiclass classification model trained with the trainer. + /// Predict a target using a linear multiclass classification model trained with the trainer. /// /// The . /// The labelColumn, or dependent variable. @@ -294,7 +294,7 @@ public static PoissonRegression PoissonRegression(this RegressionContext.Regress /// Enforce non-negative weights. /// Weight of L1 regularization term. /// Weight of L2 regularization term. - /// Memory size for . Low=faster, less accurate. + /// Memory size for . Low=faster, less accurate. /// Threshold for optimizer convergence. /// A delegate to apply all the advanced arguments to the algorithm. public static MulticlassLogisticRegression LogisticRegression(this MulticlassClassificationContext.MulticlassClassificationTrainers ctx, diff --git a/src/Microsoft.ML.StaticPipe/CategoricalHashStaticExtensions.cs b/src/Microsoft.ML.StaticPipe/CategoricalHashStaticExtensions.cs index 07e45be1e7..a5da9fff76 100644 --- a/src/Microsoft.ML.StaticPipe/CategoricalHashStaticExtensions.cs +++ b/src/Microsoft.ML.StaticPipe/CategoricalHashStaticExtensions.cs @@ -3,7 +3,6 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Transforms.Categorical; using System.Collections.Generic; diff --git a/src/Microsoft.ML.StaticPipe/CategoricalStaticExtensions.cs b/src/Microsoft.ML.StaticPipe/CategoricalStaticExtensions.cs index 5e7327c9ca..17486a01a6 100644 --- a/src/Microsoft.ML.StaticPipe/CategoricalStaticExtensions.cs +++ b/src/Microsoft.ML.StaticPipe/CategoricalStaticExtensions.cs @@ -3,7 +3,6 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Transforms.Categorical; using Microsoft.ML.Transforms.Conversions; diff --git a/src/Microsoft.ML.StaticPipe/ConvertStaticExtensions.cs b/src/Microsoft.ML.StaticPipe/ConvertStaticExtensions.cs index 1389e60e55..a160e5ea7d 100644 --- a/src/Microsoft.ML.StaticPipe/ConvertStaticExtensions.cs +++ b/src/Microsoft.ML.StaticPipe/ConvertStaticExtensions.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.StaticPipe; namespace Microsoft.ML.StaticPipe diff --git a/src/Microsoft.ML.StaticPipe/ConvertStaticExtensions.tt b/src/Microsoft.ML.StaticPipe/ConvertStaticExtensions.tt index 993039eb78..ecc16c4672 100644 --- a/src/Microsoft.ML.StaticPipe/ConvertStaticExtensions.tt +++ b/src/Microsoft.ML.StaticPipe/ConvertStaticExtensions.tt @@ -8,8 +8,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.StaticPipe; namespace Microsoft.ML.StaticPipe diff --git a/src/Microsoft.ML.StaticPipe/LdaStaticExtensions.cs b/src/Microsoft.ML.StaticPipe/LdaStaticExtensions.cs index 6e40636a73..aedceb009b 100644 --- a/src/Microsoft.ML.StaticPipe/LdaStaticExtensions.cs +++ b/src/Microsoft.ML.StaticPipe/LdaStaticExtensions.cs @@ -1,9 +1,11 @@ -// Licensed to the .NET 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. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; + +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Transforms.Text; using System; diff --git a/src/Microsoft.ML.StaticPipe/LpNormalizerStaticExtensions.cs b/src/Microsoft.ML.StaticPipe/LpNormalizerStaticExtensions.cs index 44f733a571..a9ab5f2e5f 100644 --- a/src/Microsoft.ML.StaticPipe/LpNormalizerStaticExtensions.cs +++ b/src/Microsoft.ML.StaticPipe/LpNormalizerStaticExtensions.cs @@ -3,7 +3,6 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Transforms.Projections; using System.Collections.Generic; diff --git a/src/Microsoft.ML.StaticPipe/NormalizerStaticExtensions.cs b/src/Microsoft.ML.StaticPipe/NormalizerStaticExtensions.cs index 1493ba78f3..2c81fa0304 100644 --- a/src/Microsoft.ML.StaticPipe/NormalizerStaticExtensions.cs +++ b/src/Microsoft.ML.StaticPipe/NormalizerStaticExtensions.cs @@ -1,11 +1,11 @@ -// Licensed to the .NET 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. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Transforms.Normalizers; using System; diff --git a/src/Microsoft.ML.StaticPipe/SdcaStaticExtensions.cs b/src/Microsoft.ML.StaticPipe/SdcaStaticExtensions.cs index 4735a4ca0d..846d169b8f 100644 --- a/src/Microsoft.ML.StaticPipe/SdcaStaticExtensions.cs +++ b/src/Microsoft.ML.StaticPipe/SdcaStaticExtensions.cs @@ -1,10 +1,11 @@ -// Licensed to the .NET 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. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Learners; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Learners; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Trainers; using System; diff --git a/src/Microsoft.ML.StaticPipe/TermStaticExtensions.cs b/src/Microsoft.ML.StaticPipe/TermStaticExtensions.cs index 4016234300..11a8568898 100644 --- a/src/Microsoft.ML.StaticPipe/TermStaticExtensions.cs +++ b/src/Microsoft.ML.StaticPipe/TermStaticExtensions.cs @@ -1,11 +1,11 @@ -// Licensed to the .NET 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. using System; using Microsoft.ML.StaticPipe; -using Microsoft.ML.Runtime; using Microsoft.ML.Transforms.Conversions; +using Microsoft.ML; namespace Microsoft.ML.StaticPipe { diff --git a/src/Microsoft.ML.StaticPipe/TermStaticExtensions.tt b/src/Microsoft.ML.StaticPipe/TermStaticExtensions.tt index 6aaf5aa48f..a38b6087c4 100644 --- a/src/Microsoft.ML.StaticPipe/TermStaticExtensions.tt +++ b/src/Microsoft.ML.StaticPipe/TermStaticExtensions.tt @@ -1,4 +1,4 @@ -<#@ template debug="false" hostspecific="false" language="C#" #> +<#@ template debug="false" hostspecific="false" language="C#" #> <#@ assembly name="System.Core" #> <#@ import namespace="System.Linq" #> <#@ import namespace="System.Text" #> @@ -10,8 +10,8 @@ using System; using Microsoft.ML.StaticPipe; -using Microsoft.ML.Runtime; using Microsoft.ML.Transforms.Conversions; +using Microsoft.ML; namespace Microsoft.ML.StaticPipe { diff --git a/src/Microsoft.ML.StaticPipe/TextStaticExtensions.cs b/src/Microsoft.ML.StaticPipe/TextStaticExtensions.cs index 9a176bbfca..039fee4c00 100644 --- a/src/Microsoft.ML.StaticPipe/TextStaticExtensions.cs +++ b/src/Microsoft.ML.StaticPipe/TextStaticExtensions.cs @@ -3,7 +3,7 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; +using Microsoft.ML; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Transforms.Text; using System; diff --git a/src/Microsoft.ML.StaticPipe/TransformsStatic.cs b/src/Microsoft.ML.StaticPipe/TransformsStatic.cs index fed8bdbfdb..5ae35d788f 100644 --- a/src/Microsoft.ML.StaticPipe/TransformsStatic.cs +++ b/src/Microsoft.ML.StaticPipe/TransformsStatic.cs @@ -1,11 +1,11 @@ -// Licensed to the .NET 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. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Conversions; diff --git a/src/Microsoft.ML.StaticPipe/WordEmbeddingsStaticExtensions.cs b/src/Microsoft.ML.StaticPipe/WordEmbeddingsStaticExtensions.cs index 6438af5aca..74ff183bce 100644 --- a/src/Microsoft.ML.StaticPipe/WordEmbeddingsStaticExtensions.cs +++ b/src/Microsoft.ML.StaticPipe/WordEmbeddingsStaticExtensions.cs @@ -3,7 +3,6 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Transforms.Text; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Sweeper/Algorithms/Grid.cs b/src/Microsoft.ML.Sweeper/Algorithms/Grid.cs index cac83a5eed..a067db7cd7 100644 --- a/src/Microsoft.ML.Sweeper/Algorithms/Grid.cs +++ b/src/Microsoft.ML.Sweeper/Algorithms/Grid.cs @@ -4,18 +4,18 @@ using System.Collections.Generic; using System.Linq; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Sweeper; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Sweeper; [assembly: LoadableClass(typeof(RandomGridSweeper), typeof(RandomGridSweeper.Arguments), typeof(SignatureSweeper), "Random Grid Sweeper", "RandomGridSweeper", "RandomGrid")] [assembly: LoadableClass(typeof(RandomGridSweeper), typeof(RandomGridSweeper.Arguments), typeof(SignatureSweeperFromParameterList), "Random Grid Sweeper", "RandomGridSweeperParamList", "RandomGridpl")] -namespace Microsoft.ML.Runtime.Sweeper +namespace Microsoft.ML.Sweeper { /// /// Signature for the GUI loaders of sweepers. diff --git a/src/Microsoft.ML.Sweeper/Algorithms/KdoSweeper.cs b/src/Microsoft.ML.Sweeper/Algorithms/KdoSweeper.cs index f739dc2df2..dffca8ca3b 100644 --- a/src/Microsoft.ML.Sweeper/Algorithms/KdoSweeper.cs +++ b/src/Microsoft.ML.Sweeper/Algorithms/KdoSweeper.cs @@ -7,17 +7,17 @@ using System; using System.Collections.Generic; using System.Linq; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; using Microsoft.ML.Trainers.FastTree.Internal; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Sweeper.Algorithms; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Sweeper.Algorithms; [assembly: LoadableClass(typeof(KdoSweeper), typeof(KdoSweeper.Arguments), typeof(SignatureSweeper), "KDO Sweeper", "KDOSweeper", "KDO")] -namespace Microsoft.ML.Runtime.Sweeper.Algorithms +namespace Microsoft.ML.Sweeper.Algorithms { /// /// Kernel Density Optimization (KDO) is a sequential model-based optimization method originally developed by George D. Montanez (me). diff --git a/src/Microsoft.ML.Sweeper/Algorithms/NelderMead.cs b/src/Microsoft.ML.Sweeper/Algorithms/NelderMead.cs index 9e9700f38f..8b82be28d0 100644 --- a/src/Microsoft.ML.Sweeper/Algorithms/NelderMead.cs +++ b/src/Microsoft.ML.Sweeper/Algorithms/NelderMead.cs @@ -7,16 +7,16 @@ using System; using System.Collections.Generic; using System.Linq; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Numeric; -using Microsoft.ML.Runtime.Sweeper; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Numeric; +using Microsoft.ML.Sweeper; [assembly: LoadableClass(typeof(NelderMeadSweeper), typeof(NelderMeadSweeper.Arguments), typeof(SignatureSweeper), "Nelder Mead Sweeper", "NelderMeadSweeper", "NelderMead", "NM")] -namespace Microsoft.ML.Runtime.Sweeper +namespace Microsoft.ML.Sweeper { public sealed class NelderMeadSweeper : ISweeper { diff --git a/src/Microsoft.ML.Sweeper/Algorithms/Random.cs b/src/Microsoft.ML.Sweeper/Algorithms/Random.cs index fd40de3cda..6711696bf4 100644 --- a/src/Microsoft.ML.Sweeper/Algorithms/Random.cs +++ b/src/Microsoft.ML.Sweeper/Algorithms/Random.cs @@ -3,15 +3,15 @@ // See the LICENSE file in the project root for more information. using System.Linq; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Sweeper; +using Microsoft.ML; +using Microsoft.ML.Sweeper; [assembly: LoadableClass(typeof(UniformRandomSweeper), typeof(SweeperBase.ArgumentsBase), typeof(SignatureSweeper), "Uniform Random Sweeper", "UniformRandomSweeper", "UniformRandom")] [assembly: LoadableClass(typeof(UniformRandomSweeper), typeof(SweeperBase.ArgumentsBase), typeof(SignatureSweeperFromParameterList), "Uniform Random Sweeper", "UniformRandomSweeperParamList", "UniformRandompl")] -namespace Microsoft.ML.Runtime.Sweeper +namespace Microsoft.ML.Sweeper { /// /// Random sweeper, it generates random values for each of the parameters. diff --git a/src/Microsoft.ML.Sweeper/Algorithms/SmacSweeper.cs b/src/Microsoft.ML.Sweeper/Algorithms/SmacSweeper.cs index 9c7bf0199b..07aac5d94f 100644 --- a/src/Microsoft.ML.Sweeper/Algorithms/SmacSweeper.cs +++ b/src/Microsoft.ML.Sweeper/Algorithms/SmacSweeper.cs @@ -7,20 +7,20 @@ using System; using System.Collections.Generic; using System.Linq; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Sweeper; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Sweeper; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Trainers.FastTree.Internal; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Sweeper.Algorithms; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Sweeper.Algorithms; [assembly: LoadableClass(typeof(SmacSweeper), typeof(SmacSweeper.Arguments), typeof(SignatureSweeper), "SMAC Sweeper", "SMACSweeper", "SMAC")] -namespace Microsoft.ML.Runtime.Sweeper +namespace Microsoft.ML.Sweeper { //REVIEW: Figure out better way to do this. could introduce a base class for all smart sweepers, //encapsulating common functionality. This seems like a good plan to persue. diff --git a/src/Microsoft.ML.Sweeper/Algorithms/SweeperProbabilityUtils.cs b/src/Microsoft.ML.Sweeper/Algorithms/SweeperProbabilityUtils.cs index 503ffe75cc..09fc1ba847 100644 --- a/src/Microsoft.ML.Sweeper/Algorithms/SweeperProbabilityUtils.cs +++ b/src/Microsoft.ML.Sweeper/Algorithms/SweeperProbabilityUtils.cs @@ -4,9 +4,9 @@ using System; using System.Collections.Generic; -using Microsoft.ML.Runtime.Internal.CpuMath; +using Microsoft.ML.Internal.CpuMath; -namespace Microsoft.ML.Runtime.Sweeper.Algorithms +namespace Microsoft.ML.Sweeper.Algorithms { public sealed class SweeperProbabilityUtils { diff --git a/src/Microsoft.ML.Sweeper/AsyncSweeper.cs b/src/Microsoft.ML.Sweeper/AsyncSweeper.cs index 7f29dc2fa8..4713bb54dd 100644 --- a/src/Microsoft.ML.Sweeper/AsyncSweeper.cs +++ b/src/Microsoft.ML.Sweeper/AsyncSweeper.cs @@ -8,10 +8,10 @@ using System.Threading.Tasks; using System.Threading.Tasks.Dataflow; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Sweeper; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Sweeper; [assembly: LoadableClass(typeof(SimpleAsyncSweeper), typeof(SweeperBase.ArgumentsBase), typeof(SignatureAsyncSweeper), "Asynchronous Uniform Random Sweeper", "UniformRandomSweeper", "UniformRandom")] @@ -20,7 +20,7 @@ [assembly: LoadableClass(typeof(DeterministicSweeperAsync), typeof(DeterministicSweeperAsync.Arguments), typeof(SignatureAsyncSweeper), "Asynchronous and Deterministic Sweeper", "DeterministicSweeper", "Deterministic")] -namespace Microsoft.ML.Runtime.Sweeper +namespace Microsoft.ML.Sweeper { public delegate void SignatureAsyncSweeper(); diff --git a/src/Microsoft.ML.Sweeper/ConfigRunner.cs b/src/Microsoft.ML.Sweeper/ConfigRunner.cs index 504ba298a0..082a3fb4c9 100644 --- a/src/Microsoft.ML.Sweeper/ConfigRunner.cs +++ b/src/Microsoft.ML.Sweeper/ConfigRunner.cs @@ -7,17 +7,17 @@ using System.IO; using System.Linq; using System.Threading.Tasks; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Sweeper; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Sweeper; -using ResultProcessorInternal = Microsoft.ML.Runtime.Internal.Internallearn.ResultProcessor; +using ResultProcessorInternal = Microsoft.ML.Internal.Internallearn.ResultProcessor; [assembly: LoadableClass(typeof(LocalExeConfigRunner), typeof(LocalExeConfigRunner.Arguments), typeof(SignatureConfigRunner), "Local Sweep Config Runner", "Local")] -namespace Microsoft.ML.Runtime.Sweeper +namespace Microsoft.ML.Sweeper { public delegate void SignatureConfigRunner(); diff --git a/src/Microsoft.ML.Sweeper/ISweeper.cs b/src/Microsoft.ML.Sweeper/ISweeper.cs index 90832d66a1..ec51599ba6 100644 --- a/src/Microsoft.ML.Sweeper/ISweeper.cs +++ b/src/Microsoft.ML.Sweeper/ISweeper.cs @@ -8,9 +8,9 @@ using System.Collections; using System.Collections.Generic; using System.Linq; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { /// /// Signature for the loaders of sweepers. diff --git a/src/Microsoft.ML.Sweeper/Parameters.cs b/src/Microsoft.ML.Sweeper/Parameters.cs index 7e87d34c35..2a563858ac 100644 --- a/src/Microsoft.ML.Sweeper/Parameters.cs +++ b/src/Microsoft.ML.Sweeper/Parameters.cs @@ -9,10 +9,10 @@ using System.Globalization; using System.Linq; using System.Text.RegularExpressions; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Sweeper; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Sweeper; [assembly: LoadableClass(typeof(LongValueGenerator), typeof(LongParamArguments), typeof(SignatureSweeperParameter), "Long parameter", "lp")] @@ -21,7 +21,7 @@ [assembly: LoadableClass(typeof(DiscreteValueGenerator), typeof(DiscreteParamArguments), typeof(SignatureSweeperParameter), "Discrete parameter", "dp")] -namespace Microsoft.ML.Runtime.Sweeper +namespace Microsoft.ML.Sweeper { public delegate void SignatureSweeperParameter(); @@ -620,7 +620,7 @@ public bool TryParseParameter(string paramValue, Type paramType, string paramNam long max; if (!long.TryParse(minStr, out min) || !long.TryParse(maxStr, out max)) return false; - var generatorArgs = new Microsoft.ML.Runtime.Sweeper.LongParamArguments(); + var generatorArgs = new Microsoft.ML.Sweeper.LongParamArguments(); generatorArgs.Name = paramName; generatorArgs.Min = min; generatorArgs.Max = max; diff --git a/src/Microsoft.ML.Sweeper/SweepCommand.cs b/src/Microsoft.ML.Sweeper/SweepCommand.cs index fe61dc3c6e..eed99bdbbe 100644 --- a/src/Microsoft.ML.Sweeper/SweepCommand.cs +++ b/src/Microsoft.ML.Sweeper/SweepCommand.cs @@ -5,16 +5,16 @@ using System; using System.Collections.Generic; using System.IO; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Sweeper; -using Microsoft.ML.Runtime.Command; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Sweeper; +using Microsoft.ML.Command; [assembly: LoadableClass(SweepCommand.Summary, typeof(SweepCommand), typeof(SweepCommand.Arguments), typeof(SignatureCommand), SweepCommand.LoadName, SweepCommand.LoadName, DocName = "command/Sweep.md")] -namespace Microsoft.ML.Runtime.Sweeper +namespace Microsoft.ML.Sweeper { [BestFriend] internal sealed class SweepCommand : ICommand diff --git a/src/Microsoft.ML.Sweeper/SweepResultEvaluator.cs b/src/Microsoft.ML.Sweeper/SweepResultEvaluator.cs index 1bfd37ec70..dae1214b11 100644 --- a/src/Microsoft.ML.Sweeper/SweepResultEvaluator.cs +++ b/src/Microsoft.ML.Sweeper/SweepResultEvaluator.cs @@ -4,17 +4,17 @@ using System; using System.Text; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Sweeper; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Sweeper; -using ResultProcessor = Microsoft.ML.Runtime.Internal.Internallearn.ResultProcessor; +using ResultProcessor = Microsoft.ML.Internal.Internallearn.ResultProcessor; [assembly: LoadableClass(typeof(InternalSweepResultEvaluator), typeof(InternalSweepResultEvaluator.Arguments), typeof(SignatureSweepResultEvaluator), "TLC Sweep Result Evaluator", "TlcEvaluator", "Tlc")] -namespace Microsoft.ML.Runtime.Sweeper +namespace Microsoft.ML.Sweeper { public class InternalSweepResultEvaluator : ISweepResultEvaluator { diff --git a/src/Microsoft.ML.Sweeper/SynthConfigRunner.cs b/src/Microsoft.ML.Sweeper/SynthConfigRunner.cs index 27da71cc64..d112c0659e 100644 --- a/src/Microsoft.ML.Sweeper/SynthConfigRunner.cs +++ b/src/Microsoft.ML.Sweeper/SynthConfigRunner.cs @@ -7,14 +7,14 @@ using System.IO; using System.Threading.Tasks; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Sweeper; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Sweeper; [assembly: LoadableClass(typeof(SynthConfigRunner), typeof(SynthConfigRunner.Arguments), typeof(SignatureConfigRunner), "", "Synth")] -namespace Microsoft.ML.Runtime.Sweeper +namespace Microsoft.ML.Sweeper { /// /// This class gives a simple way of running optimization experiments on synthetic functions, rather than on actual learning problems. diff --git a/src/Microsoft.ML.TensorFlow.StaticPipe/TensorFlowStaticExtensions.cs b/src/Microsoft.ML.TensorFlow.StaticPipe/TensorFlowStaticExtensions.cs index c93dc72d99..a7e88930fc 100644 --- a/src/Microsoft.ML.TensorFlow.StaticPipe/TensorFlowStaticExtensions.cs +++ b/src/Microsoft.ML.TensorFlow.StaticPipe/TensorFlowStaticExtensions.cs @@ -1,5 +1,4 @@ using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; using Microsoft.ML.StaticPipe; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Transforms; diff --git a/src/Microsoft.ML.TensorFlow/TensorFlow/TensorflowUtils.cs b/src/Microsoft.ML.TensorFlow/TensorFlow/TensorflowUtils.cs index b8d5164b4f..72ef459492 100644 --- a/src/Microsoft.ML.TensorFlow/TensorFlow/TensorflowUtils.cs +++ b/src/Microsoft.ML.TensorFlow/TensorFlow/TensorflowUtils.cs @@ -3,9 +3,7 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; using System; using System.Collections.Generic; using System.IO; diff --git a/src/Microsoft.ML.TensorFlow/TensorFlowModelInfo.cs b/src/Microsoft.ML.TensorFlow/TensorFlowModelInfo.cs index d18a347ccc..fd43ea8bac 100644 --- a/src/Microsoft.ML.TensorFlow/TensorFlowModelInfo.cs +++ b/src/Microsoft.ML.TensorFlow/TensorFlowModelInfo.cs @@ -1,10 +1,9 @@ -// Licensed to the .NET 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. +using Microsoft.ML; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using Microsoft.ML.Transforms.TensorFlow; namespace Microsoft.ML.Transforms diff --git a/src/Microsoft.ML.TensorFlow/TensorflowCatalog.cs b/src/Microsoft.ML.TensorFlow/TensorflowCatalog.cs index 5d4c73664c..079458713d 100644 --- a/src/Microsoft.ML.TensorFlow/TensorflowCatalog.cs +++ b/src/Microsoft.ML.TensorFlow/TensorflowCatalog.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.Transforms; namespace Microsoft.ML diff --git a/src/Microsoft.ML.TensorFlow/TensorflowTransform.cs b/src/Microsoft.ML.TensorFlow/TensorflowTransform.cs index e2fa48bbc6..efc4f4fcf7 100644 --- a/src/Microsoft.ML.TensorFlow/TensorflowTransform.cs +++ b/src/Microsoft.ML.TensorFlow/TensorflowTransform.cs @@ -10,12 +10,11 @@ using System.Text; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.StaticPipe; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Transforms; diff --git a/src/Microsoft.ML.TimeSeries/AdaptiveSingularSpectrumSequenceModeler.cs b/src/Microsoft.ML.TimeSeries/AdaptiveSingularSpectrumSequenceModeler.cs index da22cb466e..8cac3bdc5e 100644 --- a/src/Microsoft.ML.TimeSeries/AdaptiveSingularSpectrumSequenceModeler.cs +++ b/src/Microsoft.ML.TimeSeries/AdaptiveSingularSpectrumSequenceModeler.cs @@ -5,19 +5,19 @@ using System; using System.Collections.Generic; using System.Numerics; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.CpuMath; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.TimeSeriesProcessing; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.CpuMath; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.TimeSeriesProcessing; using Microsoft.ML.TimeSeries; [assembly: LoadableClass(typeof(AdaptiveSingularSpectrumSequenceModeler), typeof(AdaptiveSingularSpectrumSequenceModeler), null, typeof(SignatureLoadModel), "SSA Sequence Modeler", AdaptiveSingularSpectrumSequenceModeler.LoaderSignature)] -namespace Microsoft.ML.Runtime.TimeSeriesProcessing +namespace Microsoft.ML.TimeSeriesProcessing { /// /// This class implements basic Singular Spectrum Analysis (SSA) model for modeling univariate time-series. diff --git a/src/Microsoft.ML.TimeSeries/EigenUtils.cs b/src/Microsoft.ML.TimeSeries/EigenUtils.cs index f54c237bb1..8d0b6794e5 100644 --- a/src/Microsoft.ML.TimeSeries/EigenUtils.cs +++ b/src/Microsoft.ML.TimeSeries/EigenUtils.cs @@ -5,10 +5,10 @@ using System; using System.Runtime.InteropServices; using System.Security; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; using Float = System.Single; -namespace Microsoft.ML.Runtime.TimeSeriesProcessing +namespace Microsoft.ML.TimeSeriesProcessing { //REVIEW: improve perf with SSE and Multithreading public static class EigenUtils diff --git a/src/Microsoft.ML.TimeSeries/ExponentialAverageTransform.cs b/src/Microsoft.ML.TimeSeries/ExponentialAverageTransform.cs index 8a1807a797..6d6a9ffd2a 100644 --- a/src/Microsoft.ML.TimeSeries/ExponentialAverageTransform.cs +++ b/src/Microsoft.ML.TimeSeries/ExponentialAverageTransform.cs @@ -4,20 +4,20 @@ using System; using System.Collections.Generic; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.TimeSeriesProcessing; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.TimeSeriesProcessing; [assembly: LoadableClass(ExponentialAverageTransform.Summary, typeof(ExponentialAverageTransform), typeof(ExponentialAverageTransform.Arguments), typeof(SignatureDataTransform), ExponentialAverageTransform.UserName, ExponentialAverageTransform.LoaderSignature, ExponentialAverageTransform.ShortName)] [assembly: LoadableClass(ExponentialAverageTransform.Summary, typeof(ExponentialAverageTransform), null, typeof(SignatureLoadDataTransform), ExponentialAverageTransform.UserName, ExponentialAverageTransform.LoaderSignature)] -namespace Microsoft.ML.Runtime.TimeSeriesProcessing +namespace Microsoft.ML.TimeSeriesProcessing { /// /// ExponentialAverageTransform is a weighted average of the values: ExpAvg(y_t) = a * y_t + (1-a) * ExpAvg(y_(t-1)). diff --git a/src/Microsoft.ML.TimeSeries/FftUtils.cs b/src/Microsoft.ML.TimeSeries/FftUtils.cs index 8b4414e423..2d657e8457 100644 --- a/src/Microsoft.ML.TimeSeries/FftUtils.cs +++ b/src/Microsoft.ML.TimeSeries/FftUtils.cs @@ -7,7 +7,7 @@ using System.Runtime.InteropServices; using System.Security; -namespace Microsoft.ML.Runtime.TimeSeriesProcessing +namespace Microsoft.ML.TimeSeriesProcessing { /// /// The utility functions that wrap the native Discrete Fast Fourier Transform functionality from Intel MKL. diff --git a/src/Microsoft.ML.TimeSeries/IidAnomalyDetectionBase.cs b/src/Microsoft.ML.TimeSeries/IidAnomalyDetectionBase.cs index 00158bc486..bbf61b5b42 100644 --- a/src/Microsoft.ML.TimeSeries/IidAnomalyDetectionBase.cs +++ b/src/Microsoft.ML.TimeSeries/IidAnomalyDetectionBase.cs @@ -5,12 +5,11 @@ using System; using System.IO; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.TimeSeries; -namespace Microsoft.ML.Runtime.TimeSeriesProcessing +namespace Microsoft.ML.TimeSeriesProcessing { /// /// This transform computes the p-values and martingale scores for a supposedly i.i.d input sequence of floats. In other words, it assumes diff --git a/src/Microsoft.ML.TimeSeries/IidChangePointDetector.cs b/src/Microsoft.ML.TimeSeries/IidChangePointDetector.cs index 33ef64f938..1fe419a5db 100644 --- a/src/Microsoft.ML.TimeSeries/IidChangePointDetector.cs +++ b/src/Microsoft.ML.TimeSeries/IidChangePointDetector.cs @@ -7,14 +7,13 @@ using System.Linq; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.TimeSeriesProcessing; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Model; +using Microsoft.ML.TimeSeriesProcessing; using Microsoft.ML.TimeSeries; -using static Microsoft.ML.Runtime.TimeSeriesProcessing.SequentialAnomalyDetectionTransformBase; +using static Microsoft.ML.TimeSeriesProcessing.SequentialAnomalyDetectionTransformBase; [assembly: LoadableClass(IidChangePointDetector.Summary, typeof(IDataTransform), typeof(IidChangePointDetector), typeof(IidChangePointDetector.Arguments), typeof(SignatureDataTransform), IidChangePointDetector.UserName, IidChangePointDetector.LoaderSignature, IidChangePointDetector.ShortName)] @@ -28,7 +27,7 @@ [assembly: LoadableClass(typeof(IRowMapper), typeof(IidChangePointDetector), null, typeof(SignatureLoadRowMapper), IidChangePointDetector.UserName, IidChangePointDetector.LoaderSignature)] -namespace Microsoft.ML.Runtime.TimeSeriesProcessing +namespace Microsoft.ML.TimeSeriesProcessing { /// /// This class implements the change point detector transform for an i.i.d. sequence based on adaptive kernel density estimation and martingales. diff --git a/src/Microsoft.ML.TimeSeries/IidSpikeDetector.cs b/src/Microsoft.ML.TimeSeries/IidSpikeDetector.cs index 5261827c87..46db68c459 100644 --- a/src/Microsoft.ML.TimeSeries/IidSpikeDetector.cs +++ b/src/Microsoft.ML.TimeSeries/IidSpikeDetector.cs @@ -6,14 +6,13 @@ using System.Linq; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.TimeSeriesProcessing; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Model; +using Microsoft.ML.TimeSeriesProcessing; using Microsoft.ML.TimeSeries; -using static Microsoft.ML.Runtime.TimeSeriesProcessing.SequentialAnomalyDetectionTransformBase; +using static Microsoft.ML.TimeSeriesProcessing.SequentialAnomalyDetectionTransformBase; [assembly: LoadableClass(IidSpikeDetector.Summary, typeof(IDataTransform), typeof(IidSpikeDetector), typeof(IidSpikeDetector.Arguments), typeof(SignatureDataTransform), IidSpikeDetector.UserName, IidSpikeDetector.LoaderSignature, IidSpikeDetector.ShortName)] @@ -27,7 +26,7 @@ [assembly: LoadableClass(typeof(IRowMapper), typeof(IidSpikeDetector), null, typeof(SignatureLoadRowMapper), IidSpikeDetector.UserName, IidSpikeDetector.LoaderSignature)] -namespace Microsoft.ML.Runtime.TimeSeriesProcessing +namespace Microsoft.ML.TimeSeriesProcessing { /// /// This class implements the spike detector transform for an i.i.d. sequence based on adaptive kernel density estimation. diff --git a/src/Microsoft.ML.TimeSeries/MovingAverageTransform.cs b/src/Microsoft.ML.TimeSeries/MovingAverageTransform.cs index da4094a125..37df2a7421 100644 --- a/src/Microsoft.ML.TimeSeries/MovingAverageTransform.cs +++ b/src/Microsoft.ML.TimeSeries/MovingAverageTransform.cs @@ -5,19 +5,19 @@ using System; using System.Linq; using System.Collections.Generic; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.TimeSeriesProcessing; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.TimeSeriesProcessing; [assembly: LoadableClass(MovingAverageTransform.Summary, typeof(MovingAverageTransform), typeof(MovingAverageTransform.Arguments), typeof(SignatureDataTransform), "Moving Average Transform", MovingAverageTransform.LoaderSignature, "MoAv")] [assembly: LoadableClass(MovingAverageTransform.Summary, typeof(MovingAverageTransform), null, typeof(SignatureLoadDataTransform), "Moving Average Transform", MovingAverageTransform.LoaderSignature)] -namespace Microsoft.ML.Runtime.TimeSeriesProcessing +namespace Microsoft.ML.TimeSeriesProcessing { /// /// MovingAverageTransform is a weighted average of the values in diff --git a/src/Microsoft.ML.TimeSeries/PValueTransform.cs b/src/Microsoft.ML.TimeSeries/PValueTransform.cs index 27f5911266..11cde270ca 100644 --- a/src/Microsoft.ML.TimeSeries/PValueTransform.cs +++ b/src/Microsoft.ML.TimeSeries/PValueTransform.cs @@ -3,20 +3,20 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.TimeSeriesProcessing; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.TimeSeriesProcessing; [assembly: LoadableClass(PValueTransform.Summary, typeof(PValueTransform), typeof(PValueTransform.Arguments), typeof(SignatureDataTransform), PValueTransform.UserName, PValueTransform.LoaderSignature, PValueTransform.ShortName)] [assembly: LoadableClass(PValueTransform.Summary, typeof(PValueTransform), null, typeof(SignatureLoadDataTransform), PValueTransform.UserName, PValueTransform.LoaderSignature)] -namespace Microsoft.ML.Runtime.TimeSeriesProcessing +namespace Microsoft.ML.TimeSeriesProcessing { /// /// PValueTransform is a sequential transform that computes the empirical p-value of the current value in the series based on the other values in diff --git a/src/Microsoft.ML.TimeSeries/PercentileThresholdTransform.cs b/src/Microsoft.ML.TimeSeries/PercentileThresholdTransform.cs index 571a1b1bc4..e83403fa3f 100644 --- a/src/Microsoft.ML.TimeSeries/PercentileThresholdTransform.cs +++ b/src/Microsoft.ML.TimeSeries/PercentileThresholdTransform.cs @@ -3,20 +3,20 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.TimeSeriesProcessing; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.TimeSeriesProcessing; [assembly: LoadableClass(PercentileThresholdTransform.Summary, typeof(PercentileThresholdTransform), typeof(PercentileThresholdTransform.Arguments), typeof(SignatureDataTransform), PercentileThresholdTransform.UserName, PercentileThresholdTransform.LoaderSignature, PercentileThresholdTransform.ShortName)] [assembly: LoadableClass(PercentileThresholdTransform.Summary, typeof(PercentileThresholdTransform), null, typeof(SignatureLoadDataTransform), PercentileThresholdTransform.UserName, PercentileThresholdTransform.LoaderSignature)] -namespace Microsoft.ML.Runtime.TimeSeriesProcessing +namespace Microsoft.ML.TimeSeriesProcessing { /// /// PercentileThresholdTransform is a sequential transform that decides whether the current value of the time-series belongs to the 'percentile' % of the top values in diff --git a/src/Microsoft.ML.TimeSeries/PolynomialUtils.cs b/src/Microsoft.ML.TimeSeries/PolynomialUtils.cs index 6c3f27907d..094984dcb2 100644 --- a/src/Microsoft.ML.TimeSeries/PolynomialUtils.cs +++ b/src/Microsoft.ML.TimeSeries/PolynomialUtils.cs @@ -6,9 +6,9 @@ using System.Collections.Generic; using System.Linq; using System.Numerics; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.TimeSeriesProcessing +namespace Microsoft.ML.TimeSeriesProcessing { public static class PolynomialUtils { diff --git a/src/Microsoft.ML.TimeSeries/PredictionFunction.cs b/src/Microsoft.ML.TimeSeries/PredictionFunction.cs index 44a34d3ad0..717665cfea 100644 --- a/src/Microsoft.ML.TimeSeries/PredictionFunction.cs +++ b/src/Microsoft.ML.TimeSeries/PredictionFunction.cs @@ -4,8 +4,6 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using System; using System.Collections.Generic; using System.IO; diff --git a/src/Microsoft.ML.TimeSeries/SequenceModelerBase.cs b/src/Microsoft.ML.TimeSeries/SequenceModelerBase.cs index 5b7b86d93f..d66b58c9f8 100644 --- a/src/Microsoft.ML.TimeSeries/SequenceModelerBase.cs +++ b/src/Microsoft.ML.TimeSeries/SequenceModelerBase.cs @@ -2,11 +2,11 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; -namespace Microsoft.ML.Runtime.TimeSeriesProcessing +namespace Microsoft.ML.TimeSeriesProcessing { /// /// The base container class for the forecast result on a sequence of type . diff --git a/src/Microsoft.ML.TimeSeries/SequentialAnomalyDetectionTransformBase.cs b/src/Microsoft.ML.TimeSeries/SequentialAnomalyDetectionTransformBase.cs index fde11e820a..25d2e66778 100644 --- a/src/Microsoft.ML.TimeSeries/SequentialAnomalyDetectionTransformBase.cs +++ b/src/Microsoft.ML.TimeSeries/SequentialAnomalyDetectionTransformBase.cs @@ -3,18 +3,16 @@ // See the LICENSE file in the project root for more information. using System; -using System.Collections.Generic; using System.IO; using System.Threading; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.CpuMath; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.CpuMath; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.TimeSeries; -namespace Microsoft.ML.Runtime.TimeSeriesProcessing +namespace Microsoft.ML.TimeSeriesProcessing { // REVIEW: This base class and its children classes generate one output column of type VBuffer to output 3 different anomaly scores as well as // the alert flag. Ideally these 4 output information should be put in four seaparate columns instead of one VBuffer<> column. However, this is not currently diff --git a/src/Microsoft.ML.TimeSeries/SequentialTransformBase.cs b/src/Microsoft.ML.TimeSeries/SequentialTransformBase.cs index d8565e486e..aab02b09fe 100644 --- a/src/Microsoft.ML.TimeSeries/SequentialTransformBase.cs +++ b/src/Microsoft.ML.TimeSeries/SequentialTransformBase.cs @@ -3,14 +3,13 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms; using System; -namespace Microsoft.ML.Runtime.TimeSeriesProcessing +namespace Microsoft.ML.TimeSeriesProcessing { /// /// The box class that is used to box the TInput and TOutput for the LambdaTransform. diff --git a/src/Microsoft.ML.TimeSeries/SequentialTransformerBase.cs b/src/Microsoft.ML.TimeSeries/SequentialTransformerBase.cs index f5424397e3..494714da56 100644 --- a/src/Microsoft.ML.TimeSeries/SequentialTransformerBase.cs +++ b/src/Microsoft.ML.TimeSeries/SequentialTransformerBase.cs @@ -3,19 +3,18 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Onnx; -using Microsoft.ML.Runtime.Model.Pfa; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Onnx; +using Microsoft.ML.Model.Pfa; using Microsoft.ML.TimeSeries; using Microsoft.ML.Transforms; using System; using System.IO; using System.Linq; -namespace Microsoft.ML.Runtime.TimeSeriesProcessing +namespace Microsoft.ML.TimeSeriesProcessing { /// /// The base class for sequential processing transforms. This class implements the basic sliding window buffering. The derived classes need to specify the transform logic, diff --git a/src/Microsoft.ML.TimeSeries/SlidingWindowTransform.cs b/src/Microsoft.ML.TimeSeries/SlidingWindowTransform.cs index ce3bbf0092..998de672c5 100644 --- a/src/Microsoft.ML.TimeSeries/SlidingWindowTransform.cs +++ b/src/Microsoft.ML.TimeSeries/SlidingWindowTransform.cs @@ -3,17 +3,17 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.TimeSeriesProcessing; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Model; +using Microsoft.ML.TimeSeriesProcessing; [assembly: LoadableClass(SlidingWindowTransform.Summary, typeof(SlidingWindowTransform), typeof(SlidingWindowTransform.Arguments), typeof(SignatureDataTransform), SlidingWindowTransform.UserName, SlidingWindowTransform.LoaderSignature, SlidingWindowTransform.ShortName)] [assembly: LoadableClass(SlidingWindowTransform.Summary, typeof(SlidingWindowTransform), null, typeof(SignatureLoadDataTransform), SlidingWindowTransform.UserName, SlidingWindowTransform.LoaderSignature)] -namespace Microsoft.ML.Runtime.TimeSeriesProcessing +namespace Microsoft.ML.TimeSeriesProcessing { /// /// Outputs a sliding window on a time series of type Single. diff --git a/src/Microsoft.ML.TimeSeries/SlidingWindowTransformBase.cs b/src/Microsoft.ML.TimeSeries/SlidingWindowTransformBase.cs index 38d038e1c3..92d0108e3d 100644 --- a/src/Microsoft.ML.TimeSeries/SlidingWindowTransformBase.cs +++ b/src/Microsoft.ML.TimeSeries/SlidingWindowTransformBase.cs @@ -2,16 +2,16 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.Conversion; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Data.Conversion; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms; using System; -namespace Microsoft.ML.Runtime.TimeSeriesProcessing +namespace Microsoft.ML.TimeSeriesProcessing { /// /// SlidingWindowTransformBase outputs a sliding window as a VBuffer from a series of any type. diff --git a/src/Microsoft.ML.TimeSeries/SsaAnomalyDetectionBase.cs b/src/Microsoft.ML.TimeSeries/SsaAnomalyDetectionBase.cs index 6568f3a2e1..4596fc3994 100644 --- a/src/Microsoft.ML.TimeSeries/SsaAnomalyDetectionBase.cs +++ b/src/Microsoft.ML.TimeSeries/SsaAnomalyDetectionBase.cs @@ -5,13 +5,12 @@ using System; using System.IO; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.TimeSeries; -namespace Microsoft.ML.Runtime.TimeSeriesProcessing +namespace Microsoft.ML.TimeSeriesProcessing { /// /// Provides the utility functions for different error functions for computing deviation. diff --git a/src/Microsoft.ML.TimeSeries/SsaChangePointDetector.cs b/src/Microsoft.ML.TimeSeries/SsaChangePointDetector.cs index f488740ac9..440c8fbba4 100644 --- a/src/Microsoft.ML.TimeSeries/SsaChangePointDetector.cs +++ b/src/Microsoft.ML.TimeSeries/SsaChangePointDetector.cs @@ -7,14 +7,13 @@ using System.Linq; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.TimeSeriesProcessing; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Model; +using Microsoft.ML.TimeSeriesProcessing; using Microsoft.ML.TimeSeries; -using static Microsoft.ML.Runtime.TimeSeriesProcessing.SequentialAnomalyDetectionTransformBase; +using static Microsoft.ML.TimeSeriesProcessing.SequentialAnomalyDetectionTransformBase; [assembly: LoadableClass(SsaChangePointDetector.Summary, typeof(IDataTransform), typeof(SsaChangePointDetector), typeof(SsaChangePointDetector.Arguments), typeof(SignatureDataTransform), SsaChangePointDetector.UserName, SsaChangePointDetector.LoaderSignature, SsaChangePointDetector.ShortName)] @@ -28,7 +27,7 @@ [assembly: LoadableClass(typeof(IRowMapper), typeof(SsaChangePointDetector), null, typeof(SignatureLoadRowMapper), SsaChangePointDetector.UserName, SsaChangePointDetector.LoaderSignature)] -namespace Microsoft.ML.Runtime.TimeSeriesProcessing +namespace Microsoft.ML.TimeSeriesProcessing { /// /// This class implements the change point detector transform based on Singular Spectrum modeling of the time-series. diff --git a/src/Microsoft.ML.TimeSeries/SsaSpikeDetector.cs b/src/Microsoft.ML.TimeSeries/SsaSpikeDetector.cs index 9cde0f6c72..d1176e85ac 100644 --- a/src/Microsoft.ML.TimeSeries/SsaSpikeDetector.cs +++ b/src/Microsoft.ML.TimeSeries/SsaSpikeDetector.cs @@ -6,14 +6,13 @@ using System.Linq; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.TimeSeriesProcessing; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Model; +using Microsoft.ML.TimeSeriesProcessing; using Microsoft.ML.TimeSeries; -using static Microsoft.ML.Runtime.TimeSeriesProcessing.SequentialAnomalyDetectionTransformBase; +using static Microsoft.ML.TimeSeriesProcessing.SequentialAnomalyDetectionTransformBase; [assembly: LoadableClass(SsaSpikeDetector.Summary, typeof(IDataTransform), typeof(SsaSpikeDetector), typeof(SsaSpikeDetector.Arguments), typeof(SignatureDataTransform), SsaSpikeDetector.UserName, SsaSpikeDetector.LoaderSignature, SsaSpikeDetector.ShortName)] @@ -27,7 +26,7 @@ [assembly: LoadableClass(typeof(IRowMapper), typeof(SsaSpikeDetector), null, typeof(SignatureLoadRowMapper), SsaSpikeDetector.UserName, SsaSpikeDetector.LoaderSignature)] -namespace Microsoft.ML.Runtime.TimeSeriesProcessing +namespace Microsoft.ML.TimeSeriesProcessing { /// /// This class implements the spike detector transform based on Singular Spectrum modeling of the time-series. diff --git a/src/Microsoft.ML.TimeSeries/TimeSeriesProcessing.cs b/src/Microsoft.ML.TimeSeries/TimeSeriesProcessing.cs index a03243857d..a08a720d1e 100644 --- a/src/Microsoft.ML.TimeSeries/TimeSeriesProcessing.cs +++ b/src/Microsoft.ML.TimeSeries/TimeSeriesProcessing.cs @@ -2,17 +2,17 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.TimeSeriesProcessing; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.TimeSeriesProcessing; -[assembly: EntryPointModule(typeof(TimeSeriesProcessing))] +[assembly: EntryPointModule(typeof(TimeSeriesProcessingEntryPoints))] -namespace Microsoft.ML.Runtime.TimeSeriesProcessing +namespace Microsoft.ML.TimeSeriesProcessing { /// /// Entry points for text anylytics transforms. /// - public static class TimeSeriesProcessing + public static class TimeSeriesProcessingEntryPoints { [TlcModule.EntryPoint(Desc = ExponentialAverageTransform.Summary, UserName = ExponentialAverageTransform.UserName, ShortName = ExponentialAverageTransform.ShortName)] public static CommonOutputs.TransformOutput ExponentialAverage(IHostEnvironment env, ExponentialAverageTransform.Arguments input) @@ -26,7 +26,7 @@ public static CommonOutputs.TransformOutput ExponentialAverage(IHostEnvironment }; } - [TlcModule.EntryPoint(Desc = Runtime.TimeSeriesProcessing.IidChangePointDetector.Summary, UserName = Runtime.TimeSeriesProcessing.IidChangePointDetector.UserName, ShortName = Runtime.TimeSeriesProcessing.IidChangePointDetector.ShortName)] + [TlcModule.EntryPoint(Desc = TimeSeriesProcessing.IidChangePointDetector.Summary, UserName = TimeSeriesProcessing.IidChangePointDetector.UserName, ShortName = TimeSeriesProcessing.IidChangePointDetector.ShortName)] public static CommonOutputs.TransformOutput IidChangePointDetector(IHostEnvironment env, IidChangePointDetector.Arguments input) { var h = EntryPointUtils.CheckArgsAndCreateHost(env, "IidChangePointDetector", input); @@ -38,7 +38,7 @@ public static CommonOutputs.TransformOutput IidChangePointDetector(IHostEnvironm }; } - [TlcModule.EntryPoint(Desc = Runtime.TimeSeriesProcessing.IidSpikeDetector.Summary, UserName = Runtime.TimeSeriesProcessing.IidSpikeDetector.UserName, ShortName = Runtime.TimeSeriesProcessing.IidSpikeDetector.ShortName)] + [TlcModule.EntryPoint(Desc = TimeSeriesProcessing.IidSpikeDetector.Summary, UserName = TimeSeriesProcessing.IidSpikeDetector.UserName, ShortName = TimeSeriesProcessing.IidSpikeDetector.ShortName)] public static CommonOutputs.TransformOutput IidSpikeDetector(IHostEnvironment env, IidSpikeDetector.Arguments input) { var h = EntryPointUtils.CheckArgsAndCreateHost(env, "IidSpikeDetector", input); @@ -50,7 +50,7 @@ public static CommonOutputs.TransformOutput IidSpikeDetector(IHostEnvironment en }; } - [TlcModule.EntryPoint(Desc = Runtime.TimeSeriesProcessing.PercentileThresholdTransform.Summary, UserName = Runtime.TimeSeriesProcessing.PercentileThresholdTransform.UserName, ShortName = Runtime.TimeSeriesProcessing.PercentileThresholdTransform.ShortName)] + [TlcModule.EntryPoint(Desc = TimeSeriesProcessing.PercentileThresholdTransform.Summary, UserName = TimeSeriesProcessing.PercentileThresholdTransform.UserName, ShortName = TimeSeriesProcessing.PercentileThresholdTransform.ShortName)] public static CommonOutputs.TransformOutput PercentileThresholdTransform(IHostEnvironment env, PercentileThresholdTransform.Arguments input) { var h = EntryPointUtils.CheckArgsAndCreateHost(env, "PercentileThresholdTransform", input); @@ -62,7 +62,7 @@ public static CommonOutputs.TransformOutput PercentileThresholdTransform(IHostEn }; } - [TlcModule.EntryPoint(Desc = Runtime.TimeSeriesProcessing.PValueTransform.Summary, UserName = Runtime.TimeSeriesProcessing.PValueTransform.UserName, ShortName = Runtime.TimeSeriesProcessing.PValueTransform.ShortName)] + [TlcModule.EntryPoint(Desc = TimeSeriesProcessing.PValueTransform.Summary, UserName = TimeSeriesProcessing.PValueTransform.UserName, ShortName = TimeSeriesProcessing.PValueTransform.ShortName)] public static CommonOutputs.TransformOutput PValueTransform(IHostEnvironment env, PValueTransform.Arguments input) { var h = EntryPointUtils.CheckArgsAndCreateHost(env, "PValueTransform", input); @@ -74,7 +74,7 @@ public static CommonOutputs.TransformOutput PValueTransform(IHostEnvironment env }; } - [TlcModule.EntryPoint(Desc = Runtime.TimeSeriesProcessing.SlidingWindowTransform.Summary, UserName = Runtime.TimeSeriesProcessing.SlidingWindowTransform.UserName, ShortName = Runtime.TimeSeriesProcessing.SlidingWindowTransform.ShortName)] + [TlcModule.EntryPoint(Desc = TimeSeriesProcessing.SlidingWindowTransform.Summary, UserName = TimeSeriesProcessing.SlidingWindowTransform.UserName, ShortName = TimeSeriesProcessing.SlidingWindowTransform.ShortName)] public static CommonOutputs.TransformOutput SlidingWindowTransform(IHostEnvironment env, SlidingWindowTransform.Arguments input) { var h = EntryPointUtils.CheckArgsAndCreateHost(env, "SlidingWindowTransform", input); @@ -86,7 +86,7 @@ public static CommonOutputs.TransformOutput SlidingWindowTransform(IHostEnvironm }; } - [TlcModule.EntryPoint(Desc = Runtime.TimeSeriesProcessing.SsaChangePointDetector.Summary, UserName = Runtime.TimeSeriesProcessing.SsaChangePointDetector.UserName, ShortName = Runtime.TimeSeriesProcessing.SsaChangePointDetector.ShortName)] + [TlcModule.EntryPoint(Desc = TimeSeriesProcessing.SsaChangePointDetector.Summary, UserName = TimeSeriesProcessing.SsaChangePointDetector.UserName, ShortName = TimeSeriesProcessing.SsaChangePointDetector.ShortName)] public static CommonOutputs.TransformOutput SsaChangePointDetector(IHostEnvironment env, SsaChangePointDetector.Arguments input) { var h = EntryPointUtils.CheckArgsAndCreateHost(env, "SsaChangePointDetector", input); @@ -98,7 +98,7 @@ public static CommonOutputs.TransformOutput SsaChangePointDetector(IHostEnvironm }; } - [TlcModule.EntryPoint(Desc = Runtime.TimeSeriesProcessing.SsaSpikeDetector.Summary, UserName = Runtime.TimeSeriesProcessing.SsaSpikeDetector.UserName, ShortName = Runtime.TimeSeriesProcessing.SsaSpikeDetector.ShortName)] + [TlcModule.EntryPoint(Desc = TimeSeriesProcessing.SsaSpikeDetector.Summary, UserName = TimeSeriesProcessing.SsaSpikeDetector.UserName, ShortName = TimeSeriesProcessing.SsaSpikeDetector.ShortName)] public static CommonOutputs.TransformOutput SsaSpikeDetector(IHostEnvironment env, SsaSpikeDetector.Arguments input) { var h = EntryPointUtils.CheckArgsAndCreateHost(env, "SsaSpikeDetector", input); diff --git a/src/Microsoft.ML.TimeSeries/TimeSeriesUtils.cs b/src/Microsoft.ML.TimeSeries/TimeSeriesUtils.cs index cb1c3c07b2..81baa8b687 100644 --- a/src/Microsoft.ML.TimeSeries/TimeSeriesUtils.cs +++ b/src/Microsoft.ML.TimeSeries/TimeSeriesUtils.cs @@ -1,5 +1,5 @@ -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Internal.Utilities; using System; using System.Collections.Generic; using System.IO; diff --git a/src/Microsoft.ML.TimeSeries/TrajectoryMatrix.cs b/src/Microsoft.ML.TimeSeries/TrajectoryMatrix.cs index 229e3e9a3e..537b0f7307 100644 --- a/src/Microsoft.ML.TimeSeries/TrajectoryMatrix.cs +++ b/src/Microsoft.ML.TimeSeries/TrajectoryMatrix.cs @@ -3,9 +3,9 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.TimeSeriesProcessing +namespace Microsoft.ML.TimeSeriesProcessing { /// /// This class encapsulates the trajectory matrix of a time-series used in Singular Spectrum Analysis (SSA). diff --git a/src/Microsoft.ML.Transforms/BootstrapSamplingTransformer.cs b/src/Microsoft.ML.Transforms/BootstrapSamplingTransformer.cs index d1783e873d..c3de29d2a6 100644 --- a/src/Microsoft.ML.Transforms/BootstrapSamplingTransformer.cs +++ b/src/Microsoft.ML.Transforms/BootstrapSamplingTransformer.cs @@ -3,12 +3,11 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms; using System; diff --git a/src/Microsoft.ML.Transforms/CategoricalCatalog.cs b/src/Microsoft.ML.Transforms/CategoricalCatalog.cs index 4cd908b41f..5d1cbfa9eb 100644 --- a/src/Microsoft.ML.Transforms/CategoricalCatalog.cs +++ b/src/Microsoft.ML.Transforms/CategoricalCatalog.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.Transforms.Categorical; namespace Microsoft.ML diff --git a/src/Microsoft.ML.Transforms/CompositeTransformer.cs b/src/Microsoft.ML.Transforms/CompositeTransformer.cs index fe1855c5fa..0b3d586011 100644 --- a/src/Microsoft.ML.Transforms/CompositeTransformer.cs +++ b/src/Microsoft.ML.Transforms/CompositeTransformer.cs @@ -2,9 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Model; using Microsoft.ML.Transforms; // REVIEW: This is a temporary hack code to allow loading old saved loader models. Delete it once it is no longer needed. diff --git a/src/Microsoft.ML.Transforms/ConversionsCatalog.cs b/src/Microsoft.ML.Transforms/ConversionsCatalog.cs index f02803b209..72fc05dadb 100644 --- a/src/Microsoft.ML.Transforms/ConversionsCatalog.cs +++ b/src/Microsoft.ML.Transforms/ConversionsCatalog.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.Transforms.Conversions; namespace Microsoft.ML diff --git a/src/Microsoft.ML.Transforms/CountFeatureSelection.cs b/src/Microsoft.ML.Transforms/CountFeatureSelection.cs index 74d89616f0..e3ab50f842 100644 --- a/src/Microsoft.ML.Transforms/CountFeatureSelection.cs +++ b/src/Microsoft.ML.Transforms/CountFeatureSelection.cs @@ -4,11 +4,10 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Transforms.FeatureSelection; using System; using System.Collections.Generic; @@ -336,8 +335,8 @@ public CountAggregator(ColumnType type, ValueGetter getter) getter(ref t); VBufferEditor.CreateFromBuffer(ref _buffer).Values[0] = t; }; - _isDefault = Runtime.Data.Conversion.Conversions.Instance.GetIsDefaultPredicate(type); - if (!Runtime.Data.Conversion.Conversions.Instance.TryGetIsNAPredicate(type, out _isMissing)) + _isDefault = Data.Conversion.Conversions.Instance.GetIsDefaultPredicate(type); + if (!Data.Conversion.Conversions.Instance.TryGetIsNAPredicate(type, out _isMissing)) _isMissing = (in T value) => false; } @@ -347,8 +346,8 @@ public CountAggregator(ColumnType type, ValueGetter> getter) var size = type.ValueCount; _count = new long[size]; _fillBuffer = () => getter(ref _buffer); - _isDefault = Runtime.Data.Conversion.Conversions.Instance.GetIsDefaultPredicate(type.ItemType); - if (!Runtime.Data.Conversion.Conversions.Instance.TryGetIsNAPredicate(type.ItemType, out _isMissing)) + _isDefault = Data.Conversion.Conversions.Instance.GetIsDefaultPredicate(type.ItemType); + if (!Data.Conversion.Conversions.Instance.TryGetIsNAPredicate(type.ItemType, out _isMissing)) _isMissing = (in T value) => false; } diff --git a/src/Microsoft.ML.Transforms/CustomMappingCatalog.cs b/src/Microsoft.ML.Transforms/CustomMappingCatalog.cs index 92e971a9bd..534558cf6f 100644 --- a/src/Microsoft.ML.Transforms/CustomMappingCatalog.cs +++ b/src/Microsoft.ML.Transforms/CustomMappingCatalog.cs @@ -3,8 +3,6 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using Microsoft.ML.Transforms; using System; diff --git a/src/Microsoft.ML.Transforms/CustomMappingTransformer.cs b/src/Microsoft.ML.Transforms/CustomMappingTransformer.cs index 3e35d214f3..655b53e9b7 100644 --- a/src/Microsoft.ML.Transforms/CustomMappingTransformer.cs +++ b/src/Microsoft.ML.Transforms/CustomMappingTransformer.cs @@ -4,10 +4,8 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using System; using System.Linq; diff --git a/src/Microsoft.ML.Transforms/EntryPoints/SelectFeatures.cs b/src/Microsoft.ML.Transforms/EntryPoints/SelectFeatures.cs index f7ccab8fc5..b8de0b3dc6 100644 --- a/src/Microsoft.ML.Transforms/EntryPoints/SelectFeatures.cs +++ b/src/Microsoft.ML.Transforms/EntryPoints/SelectFeatures.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.EntryPoints; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.FeatureSelection; diff --git a/src/Microsoft.ML.Transforms/EntryPoints/TextAnalytics.cs b/src/Microsoft.ML.Transforms/EntryPoints/TextAnalytics.cs index 4dac234ab9..c6009feb2c 100644 --- a/src/Microsoft.ML.Transforms/EntryPoints/TextAnalytics.cs +++ b/src/Microsoft.ML.Transforms/EntryPoints/TextAnalytics.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.EntryPoints; using Microsoft.ML.Transforms.Conversions; using Microsoft.ML.Transforms.Text; using System.Linq; diff --git a/src/Microsoft.ML.Transforms/ExtensionsCatalog.cs b/src/Microsoft.ML.Transforms/ExtensionsCatalog.cs index 66e57c3337..91e794b8b4 100644 --- a/src/Microsoft.ML.Transforms/ExtensionsCatalog.cs +++ b/src/Microsoft.ML.Transforms/ExtensionsCatalog.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.Transforms; namespace Microsoft.ML diff --git a/src/Microsoft.ML.Transforms/FeatureSelectionCatalog.cs b/src/Microsoft.ML.Transforms/FeatureSelectionCatalog.cs index 98ebe07fcb..0de5a41f5c 100644 --- a/src/Microsoft.ML.Transforms/FeatureSelectionCatalog.cs +++ b/src/Microsoft.ML.Transforms/FeatureSelectionCatalog.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.Transforms.FeatureSelection; namespace Microsoft.ML diff --git a/src/Microsoft.ML.Transforms/FourierDistributionSampler.cs b/src/Microsoft.ML.Transforms/FourierDistributionSampler.cs index 1cefd54c46..2d57aade4c 100644 --- a/src/Microsoft.ML.Transforms/FourierDistributionSampler.cs +++ b/src/Microsoft.ML.Transforms/FourierDistributionSampler.cs @@ -2,11 +2,11 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms; using System; diff --git a/src/Microsoft.ML.Transforms/GcnTransform.cs b/src/Microsoft.ML.Transforms/GcnTransform.cs index e67796272e..32e90ebe90 100644 --- a/src/Microsoft.ML.Transforms/GcnTransform.cs +++ b/src/Microsoft.ML.Transforms/GcnTransform.cs @@ -4,15 +4,12 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.CpuMath; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.StaticPipe; -using Microsoft.ML.StaticPipe.Runtime; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.CpuMath; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms.Projections; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Transforms/GroupTransform.cs b/src/Microsoft.ML.Transforms/GroupTransform.cs index 3511959015..7a4f429e91 100644 --- a/src/Microsoft.ML.Transforms/GroupTransform.cs +++ b/src/Microsoft.ML.Transforms/GroupTransform.cs @@ -7,12 +7,11 @@ using System.Linq; using System.Reflection; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms; [assembly: LoadableClass(GroupTransform.Summary, typeof(GroupTransform), typeof(GroupTransform.Arguments), typeof(SignatureDataTransform), diff --git a/src/Microsoft.ML.Transforms/HashJoiningTransform.cs b/src/Microsoft.ML.Transforms/HashJoiningTransform.cs index 030377e0b5..716cca24a7 100644 --- a/src/Microsoft.ML.Transforms/HashJoiningTransform.cs +++ b/src/Microsoft.ML.Transforms/HashJoiningTransform.cs @@ -3,12 +3,11 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms.Conversions; using System; using System.Linq; @@ -620,7 +619,7 @@ private HashDelegate ComposeHashDelegate() // Default case: convert to text and hash as a string. var sb = default(StringBuilder); - var conv = Runtime.Data.Conversion.Conversions.Instance.GetStringConversion(); + var conv = Data.Conversion.Conversions.Instance.GetStringConversion(); return (in TSrc value, uint seed) => { diff --git a/src/Microsoft.ML.Transforms/KeyToVectorMapping.cs b/src/Microsoft.ML.Transforms/KeyToVectorMapping.cs index 3158402b6f..c3a8f9db3b 100644 --- a/src/Microsoft.ML.Transforms/KeyToVectorMapping.cs +++ b/src/Microsoft.ML.Transforms/KeyToVectorMapping.cs @@ -4,11 +4,10 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms.Conversions; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Transforms/LambdaTransform.cs b/src/Microsoft.ML.Transforms/LambdaTransform.cs index 861907a089..3f5c55a74f 100644 --- a/src/Microsoft.ML.Transforms/LambdaTransform.cs +++ b/src/Microsoft.ML.Transforms/LambdaTransform.cs @@ -6,12 +6,11 @@ using System.IO; using System.Text; using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; +using Microsoft.ML; using Microsoft.ML.Transforms; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; [assembly: LoadableClass(typeof(ITransformer), typeof(LambdaTransform), null, typeof(SignatureLoadModel), "", LambdaTransform.LoaderSignature)] diff --git a/src/Microsoft.ML.Transforms/LearnerFeatureSelection.cs b/src/Microsoft.ML.Transforms/LearnerFeatureSelection.cs index 2224d6d69f..b87b6a3b30 100644 --- a/src/Microsoft.ML.Transforms/LearnerFeatureSelection.cs +++ b/src/Microsoft.ML.Transforms/LearnerFeatureSelection.cs @@ -2,11 +2,11 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.FeatureSelection; using System; diff --git a/src/Microsoft.ML.Transforms/LoadTransform.cs b/src/Microsoft.ML.Transforms/LoadTransform.cs index 55a8ebf359..023998f982 100644 --- a/src/Microsoft.ML.Transforms/LoadTransform.cs +++ b/src/Microsoft.ML.Transforms/LoadTransform.cs @@ -2,11 +2,11 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Transforms/MissingValueDroppingTransformer.cs b/src/Microsoft.ML.Transforms/MissingValueDroppingTransformer.cs index f74530e5d2..ddf89ca6fa 100644 --- a/src/Microsoft.ML.Transforms/MissingValueDroppingTransformer.cs +++ b/src/Microsoft.ML.Transforms/MissingValueDroppingTransformer.cs @@ -4,12 +4,11 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms; using System; using System.Collections.Generic; @@ -178,7 +177,7 @@ private Delegate GetIsNADelegate(ColumnType type) return Utils.MarshalInvoke(func, type.ItemType.RawType, type); } - private Delegate GetIsNADelegate(ColumnType type) => Runtime.Data.Conversion.Conversions.Instance.GetIsNAPredicate(type.ItemType); + private Delegate GetIsNADelegate(ColumnType type) => Data.Conversion.Conversions.Instance.GetIsNAPredicate(type.ItemType); protected override Schema.DetachedColumn[] GetOutputColumnsCore() { @@ -374,7 +373,7 @@ public override SchemaShape GetOutputSchema(SchemaShape inputSchema) var result = inputSchema.ToDictionary(x => x.Name); foreach (var colPair in Transformer.Columns) { - if (!inputSchema.TryFindColumn(colPair.input, out var col) || !Runtime.Data.Conversion.Conversions.Instance.TryGetIsNAPredicate(col.ItemType, out Delegate del)) + if (!inputSchema.TryFindColumn(colPair.input, out var col) || !Data.Conversion.Conversions.Instance.TryGetIsNAPredicate(col.ItemType, out Delegate del)) throw Host.ExceptSchemaMismatch(nameof(inputSchema), "input", colPair.input); if (!(col.Kind == SchemaShape.Column.VectorKind.Vector || col.Kind == SchemaShape.Column.VectorKind.VariableVector)) throw Host.ExceptSchemaMismatch(nameof(inputSchema), "input", colPair.input, "Vector", col.GetTypeString()); diff --git a/src/Microsoft.ML.Transforms/MissingValueHandlingTransformer.cs b/src/Microsoft.ML.Transforms/MissingValueHandlingTransformer.cs index 87703256c0..aaa7dfa284 100644 --- a/src/Microsoft.ML.Transforms/MissingValueHandlingTransformer.cs +++ b/src/Microsoft.ML.Transforms/MissingValueHandlingTransformer.cs @@ -2,11 +2,11 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Conversions; using System; @@ -159,7 +159,7 @@ public static IDataTransform Create(IHostEnvironment env, Arguments args, IDataV if (!input.Schema.TryGetColumnIndex(column.Source, out int inputCol)) throw h.Except("Column '{0}' does not exist", column.Source); var replaceType = input.Schema[inputCol].Type; - if (!Runtime.Data.Conversion.Conversions.Instance.TryGetStandardConversion(BoolType.Instance, replaceType.ItemType, out Delegate conv, out bool identity)) + if (!Data.Conversion.Conversions.Instance.TryGetStandardConversion(BoolType.Instance, replaceType.ItemType, out Delegate conv, out bool identity)) { throw h.Except("Cannot concatenate indicator column of type '{0}' to input column of type '{1}'", BoolType.Instance, replaceType.ItemType); diff --git a/src/Microsoft.ML.Transforms/MissingValueIndicatorTransform.cs b/src/Microsoft.ML.Transforms/MissingValueIndicatorTransform.cs index 1001b8fe9f..d53014f13b 100644 --- a/src/Microsoft.ML.Transforms/MissingValueIndicatorTransform.cs +++ b/src/Microsoft.ML.Transforms/MissingValueIndicatorTransform.cs @@ -7,11 +7,10 @@ using System; using System.Text; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms; [assembly: LoadableClass(typeof(MissingValueIndicatorTransform), typeof(MissingValueIndicatorTransform.Arguments), typeof(SignatureDataTransform), diff --git a/src/Microsoft.ML.Transforms/MissingValueIndicatorTransformer.cs b/src/Microsoft.ML.Transforms/MissingValueIndicatorTransformer.cs index a33ce6c99f..2d70d92cb9 100644 --- a/src/Microsoft.ML.Transforms/MissingValueIndicatorTransformer.cs +++ b/src/Microsoft.ML.Transforms/MissingValueIndicatorTransformer.cs @@ -8,13 +8,11 @@ using System.Text; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.Conversion; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.StaticPipe; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Transforms; @@ -221,7 +219,7 @@ private static Delegate GetIsNADelegate(ColumnType type) private static Delegate GetIsNADelegate(ColumnType type) { - return Runtime.Data.Conversion.Conversions.Instance.GetIsNAPredicate(type.ItemType); + return Data.Conversion.Conversions.Instance.GetIsNAPredicate(type.ItemType); } protected override Delegate MakeGetter(Row input, int iinfo, Func activeOutput, out Action disposer) @@ -463,7 +461,7 @@ public override SchemaShape GetOutputSchema(SchemaShape inputSchema) var result = inputSchema.ToDictionary(x => x.Name); foreach (var colPair in Transformer.Columns) { - if (!inputSchema.TryFindColumn(colPair.input, out var col) || !Runtime.Data.Conversion.Conversions.Instance.TryGetIsNAPredicate(col.ItemType, out Delegate del)) + if (!inputSchema.TryFindColumn(colPair.input, out var col) || !Data.Conversion.Conversions.Instance.TryGetIsNAPredicate(col.ItemType, out Delegate del)) throw Host.ExceptSchemaMismatch(nameof(inputSchema), "input", colPair.input); var metadata = new List(); if (col.Metadata.TryFindColumn(MetadataUtils.Kinds.SlotNames, out var slotMeta)) diff --git a/src/Microsoft.ML.Transforms/MissingValueReplacing.cs b/src/Microsoft.ML.Transforms/MissingValueReplacing.cs index 1b1ada8967..836085db91 100644 --- a/src/Microsoft.ML.Transforms/MissingValueReplacing.cs +++ b/src/Microsoft.ML.Transforms/MissingValueReplacing.cs @@ -4,14 +4,13 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Onnx; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data.IO; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Onnx; using Microsoft.ML.Transforms; using System; using System.Collections; @@ -158,7 +157,7 @@ internal static string TestType(ColumnType type) private static string TestType(ColumnType type) { Contracts.Assert(type.ItemType.RawType == typeof(T)); - if (!Runtime.Data.Conversion.Conversions.Instance.TryGetIsNAPredicate(type.ItemType, out InPredicate isNA)) + if (!Data.Conversion.Conversions.Instance.TryGetIsNAPredicate(type.ItemType, out InPredicate isNA)) { return string.Format("Type '{0}' is not supported by {1} since it doesn't have an NA value", type, LoadName); @@ -290,7 +289,7 @@ private T[] GetValuesArray(VBuffer src, ColumnType srcType, int iinfo) Host.Assert(srcType.IsVector); Host.Assert(srcType.VectorSize == src.Length); VBufferUtils.Densify(ref src); - InPredicate defaultPred = Runtime.Data.Conversion.Conversions.Instance.GetIsDefaultPredicate(srcType.ItemType); + InPredicate defaultPred = Data.Conversion.Conversions.Instance.GetIsDefaultPredicate(srcType.ItemType); _repIsDefault[iinfo] = new BitArray(srcType.VectorSize); var srcValues = src.GetValues(); for (int slot = 0; slot < srcValues.Length; slot++) @@ -404,7 +403,7 @@ private BitArray ComputeDefaultSlots(ColumnType type, T[] values) { Host.Assert(values.Length == type.VectorSize); BitArray defaultSlots = new BitArray(values.Length); - InPredicate defaultPred = Runtime.Data.Conversion.Conversions.Instance.GetIsDefaultPredicate(type.ItemType); + InPredicate defaultPred = Data.Conversion.Conversions.Instance.GetIsDefaultPredicate(type.ItemType); for (int slot = 0; slot < values.Length; slot++) { if (defaultPred(in values[slot])) @@ -435,7 +434,7 @@ private Delegate GetIsNADelegate(ColumnType type) } private Delegate GetIsNADelegate(ColumnType type) - => Runtime.Data.Conversion.Conversions.Instance.GetIsNAPredicate(type.ItemType); + => Data.Conversion.Conversions.Instance.GetIsNAPredicate(type.ItemType); /// /// Converts a string to its respective value in the corresponding type. @@ -454,7 +453,7 @@ private object GetSpecifiedValue(string srcStr, ColumnType dstType, InPredica { // Handles converting input strings to correct types. var srcTxt = srcStr.AsMemory(); - var strToT = Runtime.Data.Conversion.Conversions.Instance.GetStandardConversion, T>(TextType.Instance, dstType.ItemType, out bool identity); + var strToT = Data.Conversion.Conversions.Instance.GetStandardConversion, T>(TextType.Instance, dstType.ItemType, out bool identity); strToT(in srcTxt, ref val); // Make sure that the srcTxt can legitimately be converted to dstType, throw error otherwise. if (isNA(in val)) @@ -697,7 +696,7 @@ private Delegate ComposeGetterVec(Row input, int iinfo) { var getSrc = input.GetGetter>(ColMapNewToOld[iinfo]); var isNA = (InPredicate)_isNAs[iinfo]; - var isDefault = Runtime.Data.Conversion.Conversions.Instance.GetIsDefaultPredicate(_infos[iinfo].TypeSrc.ItemType); + var isDefault = Data.Conversion.Conversions.Instance.GetIsDefaultPredicate(_infos[iinfo].TypeSrc.ItemType); var src = default(VBuffer); ValueGetter> getter; diff --git a/src/Microsoft.ML.Transforms/MissingValueReplacingUtils.cs b/src/Microsoft.ML.Transforms/MissingValueReplacingUtils.cs index 1545350513..9e13762ec6 100644 --- a/src/Microsoft.ML.Transforms/MissingValueReplacingUtils.cs +++ b/src/Microsoft.ML.Transforms/MissingValueReplacingUtils.cs @@ -2,10 +2,10 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.CpuMath; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.CpuMath; +using Microsoft.ML.Internal.Utilities; using System; namespace Microsoft.ML.Transforms diff --git a/src/Microsoft.ML.Transforms/MutualInformationFeatureSelection.cs b/src/Microsoft.ML.Transforms/MutualInformationFeatureSelection.cs index 2a085be1e9..f1a7fd5795 100644 --- a/src/Microsoft.ML.Transforms/MutualInformationFeatureSelection.cs +++ b/src/Microsoft.ML.Transforms/MutualInformationFeatureSelection.cs @@ -6,11 +6,10 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Transforms.FeatureSelection; using System; using System.Collections.Generic; @@ -693,7 +692,7 @@ private void FillTable(in VBuffer features, int offset, int numFeatures) /// private static ValueMapper, VBuffer> BinKeys(ColumnType colType) { - var conv = Runtime.Data.Conversion.Conversions.Instance.GetStandardConversion(colType, NumberType.U4, out bool identity); + var conv = Data.Conversion.Conversions.Instance.GetStandardConversion(colType, NumberType.U4, out bool identity); ValueMapper mapper; if (identity) { diff --git a/src/Microsoft.ML.Transforms/NAHandling.cs b/src/Microsoft.ML.Transforms/NAHandling.cs index c2c234abb5..3d78ce45fc 100644 --- a/src/Microsoft.ML.Transforms/NAHandling.cs +++ b/src/Microsoft.ML.Transforms/NAHandling.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.EntryPoints; using Microsoft.ML.Transforms; [assembly: EntryPointModule(typeof(NAHandling))] diff --git a/src/Microsoft.ML.Transforms/OneHotEncoding.cs b/src/Microsoft.ML.Transforms/OneHotEncoding.cs index f15040eeff..a22de5809d 100644 --- a/src/Microsoft.ML.Transforms/OneHotEncoding.cs +++ b/src/Microsoft.ML.Transforms/OneHotEncoding.cs @@ -4,13 +4,12 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms.Categorical; using Microsoft.ML.Transforms.Conversions; using System; diff --git a/src/Microsoft.ML.Transforms/OneHotHashEncoding.cs b/src/Microsoft.ML.Transforms/OneHotHashEncoding.cs index aca4ee8802..779bf955b0 100644 --- a/src/Microsoft.ML.Transforms/OneHotHashEncoding.cs +++ b/src/Microsoft.ML.Transforms/OneHotHashEncoding.cs @@ -4,12 +4,11 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.StaticPipe; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Transforms.Categorical; diff --git a/src/Microsoft.ML.Transforms/OptionalColumnTransform.cs b/src/Microsoft.ML.Transforms/OptionalColumnTransform.cs index c24f7af467..5c83f4ecd3 100644 --- a/src/Microsoft.ML.Transforms/OptionalColumnTransform.cs +++ b/src/Microsoft.ML.Transforms/OptionalColumnTransform.cs @@ -6,15 +6,14 @@ using System.Collections.Generic; using System.IO; using System.Reflection; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Transforms; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; using Microsoft.ML.Data; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Transforms; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; [assembly: LoadableClass(OptionalColumnTransform.Summary, typeof(OptionalColumnTransform), typeof(OptionalColumnTransform.Arguments), typeof(SignatureDataTransform), diff --git a/src/Microsoft.ML.Transforms/PermutationFeatureImportance.cs b/src/Microsoft.ML.Transforms/PermutationFeatureImportance.cs index 2c24f343ed..538511cb2e 100644 --- a/src/Microsoft.ML.Transforms/PermutationFeatureImportance.cs +++ b/src/Microsoft.ML.Transforms/PermutationFeatureImportance.cs @@ -3,10 +3,8 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; using System; using System.Collections.Generic; using System.Collections.Immutable; diff --git a/src/Microsoft.ML.Transforms/PermutationFeatureImportanceExtensions.cs b/src/Microsoft.ML.Transforms/PermutationFeatureImportanceExtensions.cs index 80ce3c3b1c..025cfecaad 100644 --- a/src/Microsoft.ML.Transforms/PermutationFeatureImportanceExtensions.cs +++ b/src/Microsoft.ML.Transforms/PermutationFeatureImportanceExtensions.cs @@ -1,11 +1,10 @@ -// Licensed to the .NET 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. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Transforms; using System; using System.Collections.Immutable; diff --git a/src/Microsoft.ML.Transforms/ProduceIdTransform.cs b/src/Microsoft.ML.Transforms/ProduceIdTransform.cs index 7bcea11c9c..310c58a3ce 100644 --- a/src/Microsoft.ML.Transforms/ProduceIdTransform.cs +++ b/src/Microsoft.ML.Transforms/ProduceIdTransform.cs @@ -4,10 +4,9 @@ using System; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Model; using Microsoft.ML.Transforms; [assembly: LoadableClass(ProduceIdTransform.Summary, typeof(ProduceIdTransform), typeof(ProduceIdTransform.Arguments), typeof(SignatureDataTransform), diff --git a/src/Microsoft.ML.Transforms/ProjectionCatalog.cs b/src/Microsoft.ML.Transforms/ProjectionCatalog.cs index 1460613981..beefe3dede 100644 --- a/src/Microsoft.ML.Transforms/ProjectionCatalog.cs +++ b/src/Microsoft.ML.Transforms/ProjectionCatalog.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.Transforms.Projections; namespace Microsoft.ML diff --git a/src/Microsoft.ML.Transforms/RandomFourierFeaturizing.cs b/src/Microsoft.ML.Transforms/RandomFourierFeaturizing.cs index 54a147fb12..e668c681f7 100644 --- a/src/Microsoft.ML.Transforms/RandomFourierFeaturizing.cs +++ b/src/Microsoft.ML.Transforms/RandomFourierFeaturizing.cs @@ -4,13 +4,12 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.CpuMath; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Numeric; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.CpuMath; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Numeric; using Microsoft.ML.StaticPipe; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Transforms.Projections; diff --git a/src/Microsoft.ML.Transforms/SerializableLambdaTransform.cs b/src/Microsoft.ML.Transforms/SerializableLambdaTransform.cs index 9fa56b7eab..4ec70efb27 100644 --- a/src/Microsoft.ML.Transforms/SerializableLambdaTransform.cs +++ b/src/Microsoft.ML.Transforms/SerializableLambdaTransform.cs @@ -2,10 +2,10 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms; using System; using System.IO; diff --git a/src/Microsoft.ML.Transforms/StatefulFilterTransform.cs b/src/Microsoft.ML.Transforms/StatefulFilterTransform.cs index 949f02a564..6b36bcf5e4 100644 --- a/src/Microsoft.ML.Transforms/StatefulFilterTransform.cs +++ b/src/Microsoft.ML.Transforms/StatefulFilterTransform.cs @@ -3,8 +3,7 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; using System; using System.IO; diff --git a/src/Microsoft.ML.Transforms/Text/LdaSingleBox.cs b/src/Microsoft.ML.Transforms/Text/LdaSingleBox.cs index 4facdee991..50b3d6dad7 100644 --- a/src/Microsoft.ML.Transforms/Text/LdaSingleBox.cs +++ b/src/Microsoft.ML.Transforms/Text/LdaSingleBox.cs @@ -8,7 +8,7 @@ using System.Runtime.InteropServices; using System.Security; -namespace Microsoft.ML.Runtime.TextAnalytics +namespace Microsoft.ML.TextAnalytics { internal static class LdaInterface diff --git a/src/Microsoft.ML.Transforms/Text/LdaTransform.cs b/src/Microsoft.ML.Transforms/Text/LdaTransform.cs index 15ffe34d39..14a1f6e34a 100644 --- a/src/Microsoft.ML.Transforms/Text/LdaTransform.cs +++ b/src/Microsoft.ML.Transforms/Text/LdaTransform.cs @@ -4,14 +4,13 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.TextAnalytics; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.TextAnalytics; using Microsoft.ML.Transforms.Text; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Transforms/Text/NgramHashingTransformer.cs b/src/Microsoft.ML.Transforms/Text/NgramHashingTransformer.cs index 91c3ea5516..06ad0604e5 100644 --- a/src/Microsoft.ML.Transforms/Text/NgramHashingTransformer.cs +++ b/src/Microsoft.ML.Transforms/Text/NgramHashingTransformer.cs @@ -4,11 +4,10 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms.Text; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Transforms/Text/NgramTransform.cs b/src/Microsoft.ML.Transforms/Text/NgramTransform.cs index 7990d89469..a9956e2c77 100644 --- a/src/Microsoft.ML.Transforms/Text/NgramTransform.cs +++ b/src/Microsoft.ML.Transforms/Text/NgramTransform.cs @@ -4,12 +4,11 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms.Text; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Transforms/Text/NgramUtils.cs b/src/Microsoft.ML.Transforms/Text/NgramUtils.cs index 38bc6333e8..b272b0e368 100644 --- a/src/Microsoft.ML.Transforms/Text/NgramUtils.cs +++ b/src/Microsoft.ML.Transforms/Text/NgramUtils.cs @@ -5,9 +5,9 @@ using Float = System.Single; using System; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.Data +namespace Microsoft.ML.Data { /// /// This delegate represents a function that gets an ngram as input, and outputs the id of diff --git a/src/Microsoft.ML.Transforms/Text/SentimentAnalyzingTransform.cs b/src/Microsoft.ML.Transforms/Text/SentimentAnalyzingTransform.cs index 2dd0664aa4..8b25aff70d 100644 --- a/src/Microsoft.ML.Transforms/Text/SentimentAnalyzingTransform.cs +++ b/src/Microsoft.ML.Transforms/Text/SentimentAnalyzingTransform.cs @@ -2,12 +2,12 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms.Text; using System.Collections.Generic; using System.Linq; diff --git a/src/Microsoft.ML.Transforms/Text/StopWordsRemovingTransformer.cs b/src/Microsoft.ML.Transforms/Text/StopWordsRemovingTransformer.cs index d22fe93c61..583447628a 100644 --- a/src/Microsoft.ML.Transforms/Text/StopWordsRemovingTransformer.cs +++ b/src/Microsoft.ML.Transforms/Text/StopWordsRemovingTransformer.cs @@ -6,13 +6,12 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data.IO; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms.Text; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Transforms/Text/TextCatalog.cs b/src/Microsoft.ML.Transforms/Text/TextCatalog.cs index 0708771e4d..e2273a9767 100644 --- a/src/Microsoft.ML.Transforms/Text/TextCatalog.cs +++ b/src/Microsoft.ML.Transforms/Text/TextCatalog.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.Transforms.Text; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Transforms/Text/TextFeaturizingEstimator.cs b/src/Microsoft.ML.Transforms/Text/TextFeaturizingEstimator.cs index 7b7bf1f085..53bb1d67af 100644 --- a/src/Microsoft.ML.Transforms/Text/TextFeaturizingEstimator.cs +++ b/src/Microsoft.ML.Transforms/Text/TextFeaturizingEstimator.cs @@ -4,14 +4,13 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data.IO; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.StaticPipe; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Transforms.Projections; diff --git a/src/Microsoft.ML.Transforms/Text/TextNormalizing.cs b/src/Microsoft.ML.Transforms/Text/TextNormalizing.cs index 598f0399a2..198cf76099 100644 --- a/src/Microsoft.ML.Transforms/Text/TextNormalizing.cs +++ b/src/Microsoft.ML.Transforms/Text/TextNormalizing.cs @@ -6,11 +6,10 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms.Text; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Transforms/Text/TokenizingByCharacters.cs b/src/Microsoft.ML.Transforms/Text/TokenizingByCharacters.cs index 754a467cdf..486bd09f7e 100644 --- a/src/Microsoft.ML.Transforms/Text/TokenizingByCharacters.cs +++ b/src/Microsoft.ML.Transforms/Text/TokenizingByCharacters.cs @@ -6,12 +6,11 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms.Text; using System; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Transforms/Text/WordBagTransform.cs b/src/Microsoft.ML.Transforms/Text/WordBagTransform.cs index e89f60713c..ec36d67aef 100644 --- a/src/Microsoft.ML.Transforms/Text/WordBagTransform.cs +++ b/src/Microsoft.ML.Transforms/Text/WordBagTransform.cs @@ -3,11 +3,10 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Transforms.Conversions; using Microsoft.ML.Transforms.Text; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Transforms/Text/WordEmbeddingsExtractor.cs b/src/Microsoft.ML.Transforms/Text/WordEmbeddingsExtractor.cs index e1ccf982e0..5e4b20a07e 100644 --- a/src/Microsoft.ML.Transforms/Text/WordEmbeddingsExtractor.cs +++ b/src/Microsoft.ML.Transforms/Text/WordEmbeddingsExtractor.cs @@ -4,14 +4,13 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Onnx; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Onnx; using Microsoft.ML.StaticPipe; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Transforms.Text; diff --git a/src/Microsoft.ML.Transforms/Text/WordHashBagProducingTransform.cs b/src/Microsoft.ML.Transforms/Text/WordHashBagProducingTransform.cs index 268a98b872..11daf83b9a 100644 --- a/src/Microsoft.ML.Transforms/Text/WordHashBagProducingTransform.cs +++ b/src/Microsoft.ML.Transforms/Text/WordHashBagProducingTransform.cs @@ -2,11 +2,11 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Transforms.Conversions; using Microsoft.ML.Transforms.Text; using System.Collections.Generic; diff --git a/src/Microsoft.ML.Transforms/Text/WordTokenizing.cs b/src/Microsoft.ML.Transforms/Text/WordTokenizing.cs index e0149a27e9..6237a7fc49 100644 --- a/src/Microsoft.ML.Transforms/Text/WordTokenizing.cs +++ b/src/Microsoft.ML.Transforms/Text/WordTokenizing.cs @@ -4,14 +4,13 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Model.Pfa; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Model.Pfa; using Microsoft.ML.Transforms.Text; using Newtonsoft.Json.Linq; using System; diff --git a/src/Microsoft.ML.Transforms/Text/WrappedTextTransformers.cs b/src/Microsoft.ML.Transforms/Text/WrappedTextTransformers.cs index 0dd175f59d..1e997294ed 100644 --- a/src/Microsoft.ML.Transforms/Text/WrappedTextTransformers.cs +++ b/src/Microsoft.ML.Transforms/Text/WrappedTextTransformers.cs @@ -2,9 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; using System.Linq; namespace Microsoft.ML.Transforms.Text diff --git a/src/Microsoft.ML.Transforms/UngroupTransform.cs b/src/Microsoft.ML.Transforms/UngroupTransform.cs index 11008670d5..d912087bce 100644 --- a/src/Microsoft.ML.Transforms/UngroupTransform.cs +++ b/src/Microsoft.ML.Transforms/UngroupTransform.cs @@ -7,13 +7,11 @@ using System.Linq; using System.Reflection; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.Conversion; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.Transforms; [assembly: LoadableClass(UngroupTransform.Summary, typeof(UngroupTransform), typeof(UngroupTransform.Arguments), typeof(SignatureDataTransform), @@ -611,7 +609,7 @@ private ValueGetter MakeGetter(int col, PrimitiveType itemType) // cachedIndex == row.Count || _pivotColPosition <= row.Indices[cachedIndex]. int cachedIndex = 0; VBuffer row = default(VBuffer); - T naValue = Runtime.Data.Conversion.Conversions.Instance.GetNAOrDefault(itemType); + T naValue = Data.Conversion.Conversions.Instance.GetNAOrDefault(itemType); return (ref T value) => { diff --git a/test/BaselineOutput/Common/Command/codegen-out.cs b/test/BaselineOutput/Common/Command/codegen-out.cs index 052a079dad..12857cc945 100644 --- a/test/BaselineOutput/Common/Command/codegen-out.cs +++ b/test/BaselineOutput/Common/Command/codegen-out.cs @@ -1,7 +1,7 @@ using System; using System.Collections.Generic; using Microsoft.ML.Legacy; -using Microsoft.ML.Runtime.Api; +using Microsoft.ML.Api; namespace MLGeneratedCode { diff --git a/test/BaselineOutput/Common/EntryPoints/core_ep-list.tsv b/test/BaselineOutput/Common/EntryPoints/core_ep-list.tsv index e877d6d72d..165a3f923d 100644 --- a/test/BaselineOutput/Common/EntryPoints/core_ep-list.tsv +++ b/test/BaselineOutput/Common/EntryPoints/core_ep-list.tsv @@ -1,137 +1,137 @@ -Data.CustomTextLoader Import a dataset from a text file Microsoft.ML.Runtime.EntryPoints.ImportTextData ImportText Microsoft.ML.Runtime.EntryPoints.ImportTextData+Input Microsoft.ML.Runtime.EntryPoints.ImportTextData+Output -Data.DataViewReference Pass dataview from memory to experiment Microsoft.ML.Runtime.EntryPoints.DataViewReference ImportData Microsoft.ML.Runtime.EntryPoints.DataViewReference+Input Microsoft.ML.Runtime.EntryPoints.DataViewReference+Output -Data.IDataViewArrayConverter Create an array variable of IDataView Microsoft.ML.Runtime.EntryPoints.MacroUtils MakeArray Microsoft.ML.Runtime.EntryPoints.MacroUtils+ArrayIDataViewInput Microsoft.ML.Runtime.EntryPoints.MacroUtils+ArrayIDataViewOutput -Data.PredictorModelArrayConverter Create an array variable of PredictorModel Microsoft.ML.Runtime.EntryPoints.MacroUtils MakeArray Microsoft.ML.Runtime.EntryPoints.MacroUtils+ArrayIPredictorModelInput Microsoft.ML.Runtime.EntryPoints.MacroUtils+ArrayIPredictorModelOutput -Data.TextLoader Import a dataset from a text file Microsoft.ML.Legacy.EntryPoints.ImportTextData TextLoader Microsoft.ML.Legacy.EntryPoints.ImportTextData+LoaderInput Microsoft.ML.Runtime.EntryPoints.ImportTextData+Output -Models.AnomalyDetectionEvaluator Evaluates an anomaly detection scored dataset. Microsoft.ML.Runtime.Data.Evaluate AnomalyDetection Microsoft.ML.Runtime.Data.AnomalyDetectionMamlEvaluator+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+CommonEvaluateOutput -Models.AnomalyPipelineEnsemble Combine anomaly detection models into an ensemble Microsoft.ML.Runtime.EntryPoints.EnsembleCreator CreateAnomalyPipelineEnsemble Microsoft.ML.Runtime.EntryPoints.EnsembleCreator+PipelineAnomalyInput Microsoft.ML.Runtime.EntryPoints.CommonOutputs+AnomalyDetectionOutput -Models.BinaryClassificationEvaluator Evaluates a binary classification scored dataset. Microsoft.ML.Runtime.Data.Evaluate Binary Microsoft.ML.Runtime.Data.BinaryClassifierMamlEvaluator+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+ClassificationEvaluateOutput -Models.BinaryEnsemble Combine binary classifiers into an ensemble Microsoft.ML.Runtime.EntryPoints.EnsembleCreator CreateBinaryEnsemble Microsoft.ML.Runtime.EntryPoints.EnsembleCreator+ClassifierInput Microsoft.ML.Runtime.EntryPoints.CommonOutputs+BinaryClassificationOutput -Models.BinaryPipelineEnsemble Combine binary classification models into an ensemble Microsoft.ML.Runtime.EntryPoints.EnsembleCreator CreateBinaryPipelineEnsemble Microsoft.ML.Runtime.EntryPoints.EnsembleCreator+PipelineClassifierInput Microsoft.ML.Runtime.EntryPoints.CommonOutputs+BinaryClassificationOutput -Models.ClassificationEvaluator Evaluates a multi class classification scored dataset. Microsoft.ML.Runtime.Data.Evaluate MultiClass Microsoft.ML.Runtime.Data.MultiClassMamlEvaluator+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+ClassificationEvaluateOutput -Models.ClusterEvaluator Evaluates a clustering scored dataset. Microsoft.ML.Runtime.Data.Evaluate Clustering Microsoft.ML.Runtime.Data.ClusteringMamlEvaluator+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+CommonEvaluateOutput -Models.CrossValidationResultsCombiner Combine the metric data views returned from cross validation. Microsoft.ML.Runtime.EntryPoints.CrossValidationMacro CombineMetrics Microsoft.ML.Runtime.EntryPoints.CrossValidationMacro+CombineMetricsInput Microsoft.ML.Runtime.EntryPoints.CrossValidationMacro+CombinedOutput -Models.CrossValidator Cross validation for general learning Microsoft.ML.Runtime.EntryPoints.CrossValidationMacro CrossValidate Microsoft.ML.Runtime.EntryPoints.CrossValidationMacro+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+MacroOutput`1[Microsoft.ML.Runtime.EntryPoints.CrossValidationMacro+Output] -Models.CrossValidatorDatasetSplitter Split the dataset into the specified number of cross-validation folds (train and test sets) Microsoft.ML.Runtime.EntryPoints.CVSplit Split Microsoft.ML.Runtime.EntryPoints.CVSplit+Input Microsoft.ML.Runtime.EntryPoints.CVSplit+Output -Models.DatasetTransformer Applies a TransformModel to a dataset. Microsoft.ML.Runtime.EntryPoints.ModelOperations Apply Microsoft.ML.Runtime.EntryPoints.ModelOperations+ApplyTransformModelInput Microsoft.ML.Runtime.EntryPoints.ModelOperations+ApplyTransformModelOutput -Models.EnsembleSummary Summarize a pipeline ensemble predictor. Microsoft.ML.Runtime.Ensemble.EntryPoints.PipelineEnsemble Summarize Microsoft.ML.Runtime.EntryPoints.SummarizePredictor+Input Microsoft.ML.Runtime.Ensemble.EntryPoints.PipelineEnsemble+SummaryOutput -Models.FixedPlattCalibrator Apply a Platt calibrator with a fixed slope and offset to an input model Microsoft.ML.Runtime.Internal.Calibration.Calibrate FixedPlatt Microsoft.ML.Runtime.Internal.Calibration.Calibrate+FixedPlattInput Microsoft.ML.Runtime.EntryPoints.CommonOutputs+CalibratorOutput -Models.MultiClassPipelineEnsemble Combine multiclass classifiers into an ensemble Microsoft.ML.Runtime.EntryPoints.EnsembleCreator CreateMultiClassPipelineEnsemble Microsoft.ML.Runtime.EntryPoints.EnsembleCreator+PipelineClassifierInput Microsoft.ML.Runtime.EntryPoints.CommonOutputs+MulticlassClassificationOutput -Models.MultiOutputRegressionEvaluator Evaluates a multi output regression scored dataset. Microsoft.ML.Runtime.Data.Evaluate MultiOutputRegression Microsoft.ML.Runtime.Data.MultiOutputRegressionMamlEvaluator+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+CommonEvaluateOutput -Models.NaiveCalibrator Apply a Naive calibrator to an input model Microsoft.ML.Runtime.Internal.Calibration.Calibrate Naive Microsoft.ML.Runtime.Internal.Calibration.Calibrate+NoArgumentsInput Microsoft.ML.Runtime.EntryPoints.CommonOutputs+CalibratorOutput -Models.OneVersusAll One-vs-All macro (OVA) Microsoft.ML.Runtime.EntryPoints.OneVersusAllMacro OneVersusAll Microsoft.ML.Runtime.EntryPoints.OneVersusAllMacro+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+MacroOutput`1[Microsoft.ML.Runtime.EntryPoints.OneVersusAllMacro+Output] -Models.OnnxConverter Converts the model to ONNX format. Microsoft.ML.Runtime.Model.Onnx.SaveOnnxCommand Apply Microsoft.ML.Runtime.Model.Onnx.SaveOnnxCommand+Arguments Microsoft.ML.Runtime.Model.Onnx.SaveOnnxCommand+Output -Models.OvaModelCombiner Combines a sequence of PredictorModels into a single model Microsoft.ML.Runtime.EntryPoints.ModelOperations CombineOvaModels Microsoft.ML.Runtime.EntryPoints.ModelOperations+CombineOvaPredictorModelsInput Microsoft.ML.Runtime.EntryPoints.ModelOperations+PredictorModelOutput -Models.PAVCalibrator Apply a PAV calibrator to an input model Microsoft.ML.Runtime.Internal.Calibration.Calibrate Pav Microsoft.ML.Runtime.Internal.Calibration.Calibrate+NoArgumentsInput Microsoft.ML.Runtime.EntryPoints.CommonOutputs+CalibratorOutput -Models.PlattCalibrator Apply a Platt calibrator to an input model Microsoft.ML.Runtime.Internal.Calibration.Calibrate Platt Microsoft.ML.Runtime.Internal.Calibration.Calibrate+NoArgumentsInput Microsoft.ML.Runtime.EntryPoints.CommonOutputs+CalibratorOutput -Models.QuantileRegressionEvaluator Evaluates a quantile regression scored dataset. Microsoft.ML.Runtime.Data.Evaluate QuantileRegression Microsoft.ML.Runtime.Data.QuantileRegressionMamlEvaluator+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+CommonEvaluateOutput -Models.RankerEvaluator Evaluates a ranking scored dataset. Microsoft.ML.Runtime.Data.Evaluate Ranking Microsoft.ML.Runtime.Data.RankerMamlEvaluator+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+CommonEvaluateOutput -Models.RegressionEnsemble Combine regression models into an ensemble Microsoft.ML.Runtime.EntryPoints.EnsembleCreator CreateRegressionEnsemble Microsoft.ML.Runtime.EntryPoints.EnsembleCreator+RegressionInput Microsoft.ML.Runtime.EntryPoints.CommonOutputs+RegressionOutput -Models.RegressionEvaluator Evaluates a regression scored dataset. Microsoft.ML.Runtime.Data.Evaluate Regression Microsoft.ML.Runtime.Data.RegressionMamlEvaluator+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+CommonEvaluateOutput -Models.RegressionPipelineEnsemble Combine regression models into an ensemble Microsoft.ML.Runtime.EntryPoints.EnsembleCreator CreateRegressionPipelineEnsemble Microsoft.ML.Runtime.EntryPoints.EnsembleCreator+PipelineRegressionInput Microsoft.ML.Runtime.EntryPoints.CommonOutputs+RegressionOutput -Models.Summarizer Summarize a linear regression predictor. Microsoft.ML.Runtime.EntryPoints.SummarizePredictor Summarize Microsoft.ML.Runtime.EntryPoints.SummarizePredictor+Input Microsoft.ML.Runtime.EntryPoints.CommonOutputs+SummaryOutput -Models.TrainTestEvaluator General train test for any supported evaluator Microsoft.ML.Runtime.EntryPoints.TrainTestMacro TrainTest Microsoft.ML.Runtime.EntryPoints.TrainTestMacro+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+MacroOutput`1[Microsoft.ML.Runtime.EntryPoints.TrainTestMacro+Output] -TimeSeriesProcessing.ExponentialAverage Applies a Exponential average on a time series. Microsoft.ML.Runtime.TimeSeriesProcessing.TimeSeriesProcessing ExponentialAverage Microsoft.ML.Runtime.TimeSeriesProcessing.ExponentialAverageTransform+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -TimeSeriesProcessing.IidChangePointDetector This transform detects the change-points in an i.i.d. sequence using adaptive kernel density estimation and martingales. Microsoft.ML.Runtime.TimeSeriesProcessing.TimeSeriesProcessing IidChangePointDetector Microsoft.ML.Runtime.TimeSeriesProcessing.IidChangePointDetector+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -TimeSeriesProcessing.IidSpikeDetector This transform detects the spikes in a i.i.d. sequence using adaptive kernel density estimation. Microsoft.ML.Runtime.TimeSeriesProcessing.TimeSeriesProcessing IidSpikeDetector Microsoft.ML.Runtime.TimeSeriesProcessing.IidSpikeDetector+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -TimeSeriesProcessing.PercentileThresholdTransform Detects the values of time-series that are in the top percentile of the sliding window. Microsoft.ML.Runtime.TimeSeriesProcessing.TimeSeriesProcessing PercentileThresholdTransform Microsoft.ML.Runtime.TimeSeriesProcessing.PercentileThresholdTransform+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -TimeSeriesProcessing.PValueTransform This P-Value transform calculates the p-value of the current input in the sequence with regard to the values in the sliding window. Microsoft.ML.Runtime.TimeSeriesProcessing.TimeSeriesProcessing PValueTransform Microsoft.ML.Runtime.TimeSeriesProcessing.PValueTransform+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -TimeSeriesProcessing.SlidingWindowTransform Returns the last values for a time series [y(t-d-l+1), y(t-d-l+2), ..., y(t-l-1), y(t-l)] where d is the size of the window, l the lag and y is a Float. Microsoft.ML.Runtime.TimeSeriesProcessing.TimeSeriesProcessing SlidingWindowTransform Microsoft.ML.Runtime.TimeSeriesProcessing.SlidingWindowTransformBase`1+Arguments[System.Single] Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -TimeSeriesProcessing.SsaChangePointDetector This transform detects the change-points in a seasonal time-series using Singular Spectrum Analysis (SSA). Microsoft.ML.Runtime.TimeSeriesProcessing.TimeSeriesProcessing SsaChangePointDetector Microsoft.ML.Runtime.TimeSeriesProcessing.SsaChangePointDetector+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -TimeSeriesProcessing.SsaSpikeDetector This transform detects the spikes in a seasonal time-series using Singular Spectrum Analysis (SSA). Microsoft.ML.Runtime.TimeSeriesProcessing.TimeSeriesProcessing SsaSpikeDetector Microsoft.ML.Runtime.TimeSeriesProcessing.SsaSpikeDetector+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Trainers.AveragedPerceptronBinaryClassifier Averaged Perceptron Binary Classifier. Microsoft.ML.Trainers.Online.AveragedPerceptronTrainer TrainBinary Microsoft.ML.Trainers.Online.AveragedPerceptronTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+BinaryClassificationOutput -Trainers.EnsembleBinaryClassifier Train binary ensemble. Microsoft.ML.Ensemble.EntryPoints.Ensemble CreateBinaryEnsemble Microsoft.ML.Runtime.Ensemble.EnsembleTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+BinaryClassificationOutput -Trainers.EnsembleClassification Train multiclass ensemble. Microsoft.ML.Ensemble.EntryPoints.Ensemble CreateMultiClassEnsemble Microsoft.ML.Runtime.Ensemble.MulticlassDataPartitionEnsembleTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+MulticlassClassificationOutput -Trainers.EnsembleRegression Train regression ensemble. Microsoft.ML.Ensemble.EntryPoints.Ensemble CreateRegressionEnsemble Microsoft.ML.Runtime.Ensemble.RegressionEnsembleTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+RegressionOutput -Trainers.FastForestBinaryClassifier Uses a random forest learner to perform binary classification. Microsoft.ML.Trainers.FastTree.FastForest TrainBinary Microsoft.ML.Trainers.FastTree.FastForestClassification+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+BinaryClassificationOutput -Trainers.FastForestRegressor Trains a random forest to fit target values using least-squares. Microsoft.ML.Trainers.FastTree.FastForest TrainRegression Microsoft.ML.Trainers.FastTree.FastForestRegression+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+RegressionOutput -Trainers.FastTreeBinaryClassifier Uses a logit-boost boosted tree learner to perform binary classification. Microsoft.ML.Trainers.FastTree.FastTree TrainBinary Microsoft.ML.Trainers.FastTree.FastTreeBinaryClassificationTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+BinaryClassificationOutput -Trainers.FastTreeRanker Trains gradient boosted decision trees to the LambdaRank quasi-gradient. Microsoft.ML.Trainers.FastTree.FastTree TrainRanking Microsoft.ML.Trainers.FastTree.FastTreeRankingTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+RankingOutput -Trainers.FastTreeRegressor Trains gradient boosted decision trees to fit target values using least-squares. Microsoft.ML.Trainers.FastTree.FastTree TrainRegression Microsoft.ML.Trainers.FastTree.FastTreeRegressionTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+RegressionOutput -Trainers.FastTreeTweedieRegressor Trains gradient boosted decision trees to fit target values using a Tweedie loss function. This learner is a generalization of Poisson, compound Poisson, and gamma regression. Microsoft.ML.Trainers.FastTree.FastTree TrainTweedieRegression Microsoft.ML.Trainers.FastTree.FastTreeTweedieTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+RegressionOutput -Trainers.FieldAwareFactorizationMachineBinaryClassifier Train a field-aware factorization machine for binary classification Microsoft.ML.Runtime.FactorizationMachine.FieldAwareFactorizationMachineTrainer TrainBinary Microsoft.ML.Runtime.FactorizationMachine.FieldAwareFactorizationMachineTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+BinaryClassificationOutput -Trainers.GeneralizedAdditiveModelBinaryClassifier Trains a gradient boosted stump per feature, on all features simultaneously, to fit target values using least-squares. It mantains no interactions between features. Microsoft.ML.Trainers.FastTree.Gam TrainBinary Microsoft.ML.Trainers.FastTree.BinaryClassificationGamTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+BinaryClassificationOutput -Trainers.GeneralizedAdditiveModelRegressor Trains a gradient boosted stump per feature, on all features simultaneously, to fit target values using least-squares. It mantains no interactions between features. Microsoft.ML.Trainers.FastTree.Gam TrainRegression Microsoft.ML.Trainers.FastTree.RegressionGamTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+RegressionOutput -Trainers.KMeansPlusPlusClusterer K-means is a popular clustering algorithm. With K-means, the data is clustered into a specified number of clusters in order to minimize the within-cluster sum of squares. K-means++ improves upon K-means by using a better method for choosing the initial cluster centers. Microsoft.ML.Trainers.KMeans.KMeansPlusPlusTrainer TrainKMeans Microsoft.ML.Trainers.KMeans.KMeansPlusPlusTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+ClusteringOutput -Trainers.LightGbmBinaryClassifier Train a LightGBM binary classification model. Microsoft.ML.Runtime.LightGBM.LightGbm TrainBinary Microsoft.ML.Runtime.LightGBM.LightGbmArguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+BinaryClassificationOutput -Trainers.LightGbmClassifier Train a LightGBM multi class model. Microsoft.ML.Runtime.LightGBM.LightGbm TrainMultiClass Microsoft.ML.Runtime.LightGBM.LightGbmArguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+MulticlassClassificationOutput -Trainers.LightGbmRanker Train a LightGBM ranking model. Microsoft.ML.Runtime.LightGBM.LightGbm TrainRanking Microsoft.ML.Runtime.LightGBM.LightGbmArguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+RankingOutput -Trainers.LightGbmRegressor LightGBM Regression Microsoft.ML.Runtime.LightGBM.LightGbm TrainRegression Microsoft.ML.Runtime.LightGBM.LightGbmArguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+RegressionOutput -Trainers.LinearSvmBinaryClassifier Train a linear SVM. Microsoft.ML.Trainers.Online.LinearSvm TrainLinearSvm Microsoft.ML.Trainers.Online.LinearSvm+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+BinaryClassificationOutput -Trainers.LogisticRegressionBinaryClassifier Logistic Regression is a method in statistics used to predict the probability of occurrence of an event and can be used as a classification algorithm. The algorithm predicts the probability of occurrence of an event by fitting data to a logistical function. Microsoft.ML.Runtime.Learners.LogisticRegression TrainBinary Microsoft.ML.Runtime.Learners.LogisticRegression+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+BinaryClassificationOutput -Trainers.LogisticRegressionClassifier Logistic Regression is a method in statistics used to predict the probability of occurrence of an event and can be used as a classification algorithm. The algorithm predicts the probability of occurrence of an event by fitting data to a logistical function. Microsoft.ML.Runtime.Learners.LogisticRegression TrainMultiClass Microsoft.ML.Runtime.Learners.MulticlassLogisticRegression+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+MulticlassClassificationOutput -Trainers.NaiveBayesClassifier Train a MultiClassNaiveBayesTrainer. Microsoft.ML.Trainers.MultiClassNaiveBayesTrainer TrainMultiClassNaiveBayesTrainer Microsoft.ML.Trainers.MultiClassNaiveBayesTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+MulticlassClassificationOutput -Trainers.OnlineGradientDescentRegressor Train a Online gradient descent perceptron. Microsoft.ML.Trainers.Online.OnlineGradientDescentTrainer TrainRegression Microsoft.ML.Trainers.Online.OnlineGradientDescentTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+RegressionOutput -Trainers.OrdinaryLeastSquaresRegressor Train an OLS regression model. Microsoft.ML.Trainers.HalLearners.OlsLinearRegressionTrainer TrainRegression Microsoft.ML.Trainers.HalLearners.OlsLinearRegressionTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+RegressionOutput -Trainers.PcaAnomalyDetector Train an PCA Anomaly model. Microsoft.ML.Trainers.PCA.RandomizedPcaTrainer TrainPcaAnomaly Microsoft.ML.Trainers.PCA.RandomizedPcaTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+AnomalyDetectionOutput -Trainers.PoissonRegressor Train an Poisson regression model. Microsoft.ML.Trainers.PoissonRegression TrainRegression Microsoft.ML.Trainers.PoissonRegression+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+RegressionOutput -Trainers.StochasticDualCoordinateAscentBinaryClassifier Train an SDCA binary model. Microsoft.ML.Trainers.Sdca TrainBinary Microsoft.ML.Trainers.SdcaBinaryTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+BinaryClassificationOutput -Trainers.StochasticDualCoordinateAscentClassifier The SDCA linear multi-class classification trainer. Microsoft.ML.Trainers.Sdca TrainMultiClass Microsoft.ML.Trainers.SdcaMultiClassTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+MulticlassClassificationOutput -Trainers.StochasticDualCoordinateAscentRegressor The SDCA linear regression trainer. Microsoft.ML.Trainers.Sdca TrainRegression Microsoft.ML.Trainers.SdcaRegressionTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+RegressionOutput -Trainers.StochasticGradientDescentBinaryClassifier Train an Hogwild SGD binary model. Microsoft.ML.Trainers.StochasticGradientDescentClassificationTrainer TrainBinary Microsoft.ML.Trainers.StochasticGradientDescentClassificationTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+BinaryClassificationOutput -Trainers.SymSgdBinaryClassifier Train a symbolic SGD. Microsoft.ML.Trainers.SymSgd.SymSgdClassificationTrainer TrainSymSgd Microsoft.ML.Trainers.SymSgd.SymSgdClassificationTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+BinaryClassificationOutput -Transforms.ApproximateBootstrapSampler Approximate bootstrap sampling. Microsoft.ML.Transforms.BootstrapSample GetSample Microsoft.ML.Transforms.BootstrapSamplingTransformer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.BinaryPredictionScoreColumnsRenamer For binary prediction, it renames the PredictedLabel and Score columns to include the name of the positive class. Microsoft.ML.Runtime.EntryPoints.ScoreModel RenameBinaryPredictionScoreColumns Microsoft.ML.Runtime.EntryPoints.ScoreModel+RenameBinaryPredictionScoreColumnsInput Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.BinNormalizer The values are assigned into equidensity bins and a value is mapped to its bin_number/number_of_bins. Microsoft.ML.Runtime.Data.Normalize Bin Microsoft.ML.Transforms.Normalizers.NormalizeTransform+BinArguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.CategoricalHashOneHotVectorizer Converts the categorical value into an indicator array by hashing the value and using the hash as an index in the bag. If the input column is a vector, a single indicator bag is returned for it. Microsoft.ML.Transforms.Categorical.Categorical CatTransformHash Microsoft.ML.Transforms.Categorical.OneHotHashEncoding+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.CategoricalOneHotVectorizer Converts the categorical value into an indicator array by building a dictionary of categories based on the data and using the id in the dictionary as the index in the array. Microsoft.ML.Transforms.Categorical.Categorical CatTransformDict Microsoft.ML.Transforms.Categorical.OneHotEncodingTransformer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.CharacterTokenizer Character-oriented tokenizer where text is considered a sequence of characters. Microsoft.ML.Transforms.Text.TextAnalytics CharTokenize Microsoft.ML.Transforms.Text.TokenizingByCharactersTransformer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.ColumnConcatenator Concatenates one or more columns of the same item type. Microsoft.ML.Runtime.EntryPoints.SchemaManipulation ConcatColumns Microsoft.ML.Runtime.Data.ColumnConcatenatingTransformer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.ColumnCopier Duplicates columns from the dataset Microsoft.ML.Runtime.EntryPoints.SchemaManipulation CopyColumns Microsoft.ML.Transforms.ColumnCopyingTransformer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.ColumnSelector Selects a set of columns, dropping all others Microsoft.ML.Runtime.EntryPoints.SchemaManipulation SelectColumns Microsoft.ML.Transforms.ColumnSelectingTransformer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.ColumnTypeConverter Converts a column to a different type, using standard conversions. Microsoft.ML.Transforms.Conversions.TypeConversion Convert Microsoft.ML.Transforms.Conversions.TypeConvertingTransformer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.CombinerByContiguousGroupId Groups values of a scalar column into a vector, by a contiguous group ID Microsoft.ML.Transforms.GroupingOperations Group Microsoft.ML.Transforms.GroupTransform+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.ConditionalNormalizer Normalize the columns only if needed Microsoft.ML.Runtime.Data.Normalize IfNeeded Microsoft.ML.Transforms.Normalizers.NormalizeTransform+MinMaxArguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+MacroOutput`1[Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput] -Transforms.DataCache Caches using the specified cache option. Microsoft.ML.Runtime.EntryPoints.Cache CacheData Microsoft.ML.Runtime.EntryPoints.Cache+CacheInput Microsoft.ML.Runtime.EntryPoints.Cache+CacheOutput -Transforms.DatasetScorer Score a dataset with a predictor model Microsoft.ML.Runtime.EntryPoints.ScoreModel Score Microsoft.ML.Runtime.EntryPoints.ScoreModel+Input Microsoft.ML.Runtime.EntryPoints.ScoreModel+Output -Transforms.DatasetTransformScorer Score a dataset with a transform model Microsoft.ML.Runtime.EntryPoints.ScoreModel ScoreUsingTransform Microsoft.ML.Runtime.EntryPoints.ScoreModel+InputTransformScorer Microsoft.ML.Runtime.EntryPoints.ScoreModel+Output -Transforms.Dictionarizer Converts input values (words, numbers, etc.) to index in a dictionary. Microsoft.ML.Transforms.Text.TextAnalytics TermTransform Microsoft.ML.Transforms.Conversions.ValueToKeyMappingTransformer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.FeatureCombiner Combines all the features into one feature column. Microsoft.ML.Runtime.EntryPoints.FeatureCombiner PrepareFeatures Microsoft.ML.Runtime.EntryPoints.FeatureCombiner+FeatureCombinerInput Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.FeatureContributionCalculationTransformer For each data point, calculates the contribution of individual features to the model prediction. Microsoft.ML.Runtime.Data.FeatureContributionEntryPoint FeatureContributionCalculation Microsoft.ML.Runtime.Data.FeatureContributionCalculatingTransformer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.FeatureSelectorByCount Selects the slots for which the count of non-default values is greater than or equal to a threshold. Microsoft.ML.Transforms.SelectFeatures CountSelect Microsoft.ML.Transforms.FeatureSelection.CountFeatureSelectingEstimator+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.FeatureSelectorByMutualInformation Selects the top k slots across all specified columns ordered by their mutual information with the label column. Microsoft.ML.Transforms.SelectFeatures MutualInformationSelect Microsoft.ML.Transforms.FeatureSelection.MutualInformationFeatureSelectingEstimator+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.GlobalContrastNormalizer Performs a global contrast normalization on input values: Y = (s * X - M) / D, where s is a scale, M is mean and D is either L2 norm or standard deviation. Microsoft.ML.Transforms.Projections.LpNormalization GcNormalize Microsoft.ML.Transforms.Projections.LpNormalizingTransformer+GcnArguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.HashConverter Converts column values into hashes. This transform accepts both numeric and text inputs, both single and vector-valued columns. Microsoft.ML.Transforms.Conversions.HashJoin Apply Microsoft.ML.Transforms.Conversions.HashJoiningTransform+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.ImageGrayscale Convert image into grayscale. Microsoft.ML.Runtime.ImageAnalytics.EntryPoints.ImageAnalytics ImageGrayscale Microsoft.ML.Runtime.ImageAnalytics.ImageGrayscaleTransform+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.ImageLoader Load images from files. Microsoft.ML.Runtime.ImageAnalytics.EntryPoints.ImageAnalytics ImageLoader Microsoft.ML.Runtime.ImageAnalytics.ImageLoaderTransform+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.ImagePixelExtractor Extract color plane(s) from an image. Options include scaling, offset and conversion to floating point. Microsoft.ML.Runtime.ImageAnalytics.EntryPoints.ImageAnalytics ImagePixelExtractor Microsoft.ML.Runtime.ImageAnalytics.ImagePixelExtractorTransform+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.ImageResizer Scales an image to specified dimensions using one of the three scale types: isotropic with padding, isotropic with cropping or anisotropic. In case of isotropic padding, transparent color is used to pad resulting image. Microsoft.ML.Runtime.ImageAnalytics.EntryPoints.ImageAnalytics ImageResizer Microsoft.ML.Runtime.ImageAnalytics.ImageResizerTransform+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.KeyToTextConverter KeyToValueTransform utilizes KeyValues metadata to map key indices to the corresponding values in the KeyValues metadata. Microsoft.ML.Transforms.Categorical.Categorical KeyToText Microsoft.ML.Transforms.Conversions.KeyToValueMappingTransformer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.LabelColumnKeyBooleanConverter Transforms the label to either key or bool (if needed) to make it suitable for classification. Microsoft.ML.Runtime.EntryPoints.FeatureCombiner PrepareClassificationLabel Microsoft.ML.Runtime.EntryPoints.FeatureCombiner+ClassificationLabelInput Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.LabelIndicator Label remapper used by OVA Microsoft.ML.Transforms.LabelIndicatorTransform LabelIndicator Microsoft.ML.Transforms.LabelIndicatorTransform+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.LabelToFloatConverter Transforms the label to float to make it suitable for regression. Microsoft.ML.Runtime.EntryPoints.FeatureCombiner PrepareRegressionLabel Microsoft.ML.Runtime.EntryPoints.FeatureCombiner+RegressionLabelInput Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.LightLda The LDA transform implements LightLDA, a state-of-the-art implementation of Latent Dirichlet Allocation. Microsoft.ML.Transforms.Text.TextAnalytics LightLda Microsoft.ML.Transforms.Text.LatentDirichletAllocationTransformer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.LogMeanVarianceNormalizer Normalizes the data based on the computed mean and variance of the logarithm of the data. Microsoft.ML.Runtime.Data.Normalize LogMeanVar Microsoft.ML.Transforms.Normalizers.NormalizeTransform+LogMeanVarArguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.LpNormalizer Normalize vectors (rows) individually by rescaling them to unit norm (L2, L1 or LInf). Performs the following operation on a vector X: Y = (X - M) / D, where M is mean and D is either L2 norm, L1 norm or LInf norm. Microsoft.ML.Transforms.Projections.LpNormalization Normalize Microsoft.ML.Transforms.Projections.LpNormalizingTransformer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.ManyHeterogeneousModelCombiner Combines a sequence of TransformModels and a PredictorModel into a single PredictorModel. Microsoft.ML.Runtime.EntryPoints.ModelOperations CombineModels Microsoft.ML.Runtime.EntryPoints.ModelOperations+PredictorModelInput Microsoft.ML.Runtime.EntryPoints.ModelOperations+PredictorModelOutput -Transforms.MeanVarianceNormalizer Normalizes the data based on the computed mean and variance of the data. Microsoft.ML.Runtime.Data.Normalize MeanVar Microsoft.ML.Transforms.Normalizers.NormalizeTransform+MeanVarArguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.MinMaxNormalizer Normalizes the data based on the observed minimum and maximum values of the data. Microsoft.ML.Runtime.Data.Normalize MinMax Microsoft.ML.Transforms.Normalizers.NormalizeTransform+MinMaxArguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.MissingValueHandler Handle missing values by replacing them with either the default value or the mean/min/max value (for non-text columns only). An indicator column can optionally be concatenated, if theinput column type is numeric. Microsoft.ML.Transforms.NAHandling Handle Microsoft.ML.Transforms.MissingValueHandlingTransformer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.MissingValueIndicator Create a boolean output column with the same number of slots as the input column, where the output value is true if the value in the input column is missing. Microsoft.ML.Transforms.NAHandling Indicator Microsoft.ML.Transforms.MissingValueIndicatorTransformer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.MissingValuesDropper Removes NAs from vector columns. Microsoft.ML.Transforms.NAHandling Drop Microsoft.ML.Transforms.MissingValueDroppingTransformer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.MissingValuesRowDropper Filters out rows that contain missing values. Microsoft.ML.Transforms.NAHandling Filter Microsoft.ML.Transforms.NAFilter+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.MissingValueSubstitutor Create an output column of the same type and size of the input column, where missing values are replaced with either the default value or the mean/min/max value (for non-text columns only). Microsoft.ML.Transforms.NAHandling Replace Microsoft.ML.Transforms.MissingValueReplacingTransformer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.ModelCombiner Combines a sequence of TransformModels into a single model Microsoft.ML.Runtime.EntryPoints.ModelOperations CombineTransformModels Microsoft.ML.Runtime.EntryPoints.ModelOperations+CombineTransformModelsInput Microsoft.ML.Runtime.EntryPoints.ModelOperations+CombineTransformModelsOutput -Transforms.NGramTranslator Produces a bag of counts of ngrams (sequences of consecutive values of length 1-n) in a given vector of keys. It does so by building a dictionary of ngrams and using the id in the dictionary as the index in the bag. Microsoft.ML.Transforms.Text.TextAnalytics NGramTransform Microsoft.ML.Transforms.Text.NgramExtractingTransformer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.NoOperation Does nothing. Microsoft.ML.Runtime.Data.NopTransform Nop Microsoft.ML.Runtime.Data.NopTransform+NopInput Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.OptionalColumnCreator If the source column does not exist after deserialization, create a column with the right type and default values. Microsoft.ML.Transforms.OptionalColumnTransform MakeOptional Microsoft.ML.Transforms.OptionalColumnTransform+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.PcaCalculator PCA is a dimensionality-reduction transform which computes the projection of a numeric vector onto a low-rank subspace. Microsoft.ML.Transforms.Projections.PcaTransform Calculate Microsoft.ML.Transforms.Projections.PcaTransform+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.PredictedLabelColumnOriginalValueConverter Transforms a predicted label column to its original values, unless it is of type bool. Microsoft.ML.Runtime.EntryPoints.FeatureCombiner ConvertPredictedLabel Microsoft.ML.Runtime.EntryPoints.FeatureCombiner+PredictedLabelInput Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.RandomNumberGenerator Adds a column with a generated number sequence. Microsoft.ML.Transforms.RandomNumberGenerator Generate Microsoft.ML.Transforms.GenerateNumberTransform+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.RowRangeFilter Filters a dataview on a column of type Single, Double or Key (contiguous). Keeps the values that are in the specified min/max range. NaNs are always filtered out. If the input is a Key type, the min/max are considered percentages of the number of values. Microsoft.ML.Runtime.EntryPoints.SelectRows FilterByRange Microsoft.ML.Transforms.RangeFilter+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.RowSkipAndTakeFilter Allows limiting input to a subset of rows at an optional offset. Can be used to implement data paging. Microsoft.ML.Runtime.EntryPoints.SelectRows SkipAndTakeFilter Microsoft.ML.Transforms.SkipTakeFilter+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.RowSkipFilter Allows limiting input to a subset of rows by skipping a number of rows. Microsoft.ML.Runtime.EntryPoints.SelectRows SkipFilter Microsoft.ML.Transforms.SkipTakeFilter+SkipArguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.RowTakeFilter Allows limiting input to a subset of rows by taking N first rows. Microsoft.ML.Runtime.EntryPoints.SelectRows TakeFilter Microsoft.ML.Transforms.SkipTakeFilter+TakeArguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.ScoreColumnSelector Selects only the last score columns and the extra columns specified in the arguments. Microsoft.ML.Runtime.EntryPoints.ScoreModel SelectColumns Microsoft.ML.Runtime.EntryPoints.ScoreModel+ScoreColumnSelectorInput Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.Scorer Turn the predictor model into a transform model Microsoft.ML.Runtime.EntryPoints.ScoreModel MakeScoringTransform Microsoft.ML.Runtime.EntryPoints.ScoreModel+ModelInput Microsoft.ML.Runtime.EntryPoints.ScoreModel+Output -Transforms.Segregator Un-groups vector columns into sequences of rows, inverse of Group transform Microsoft.ML.Transforms.GroupingOperations Ungroup Microsoft.ML.Transforms.UngroupTransform+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.SentimentAnalyzer Uses a pretrained sentiment model to score input strings Microsoft.ML.Transforms.Text.TextAnalytics AnalyzeSentiment Microsoft.ML.Transforms.Text.SentimentAnalyzingTransformer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.TensorFlowScorer Transforms the data using the TensorFlow model. Microsoft.ML.Transforms.TensorFlowTransform TensorFlowScorer Microsoft.ML.Transforms.TensorFlowTransform+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.TextFeaturizer A transform that turns a collection of text documents into numerical feature vectors. The feature vectors are normalized counts of (word and/or character) ngrams in a given tokenized text. Microsoft.ML.Transforms.Text.TextAnalytics TextTransform Microsoft.ML.Transforms.Text.TextFeaturizingEstimator+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.TextToKeyConverter Converts input values (words, numbers, etc.) to index in a dictionary. Microsoft.ML.Transforms.Categorical.Categorical TextToKey Microsoft.ML.Transforms.Conversions.ValueToKeyMappingTransformer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.TrainTestDatasetSplitter Split the dataset into train and test sets Microsoft.ML.Runtime.EntryPoints.TrainTestSplit Split Microsoft.ML.Runtime.EntryPoints.TrainTestSplit+Input Microsoft.ML.Runtime.EntryPoints.TrainTestSplit+Output -Transforms.TreeLeafFeaturizer Trains a tree ensemble, or loads it from a file, then maps a numeric feature vector to three outputs: 1. A vector containing the individual tree outputs of the tree ensemble. 2. A vector indicating the leaves that the feature vector falls on in the tree ensemble. 3. A vector indicating the paths that the feature vector falls on in the tree ensemble. If a both a model file and a trainer are specified - will use the model file. If neither are specified, will train a default FastTree model. This can handle key labels by training a regression model towards their optionally permuted indices. Microsoft.ML.Runtime.Data.TreeFeaturize Featurizer Microsoft.ML.Runtime.Data.TreeEnsembleFeaturizerTransform+ArgumentsForEntryPoint Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.TwoHeterogeneousModelCombiner Combines a TransformModel and a PredictorModel into a single PredictorModel. Microsoft.ML.Runtime.EntryPoints.ModelOperations CombineTwoModels Microsoft.ML.Runtime.EntryPoints.ModelOperations+SimplePredictorModelInput Microsoft.ML.Runtime.EntryPoints.ModelOperations+PredictorModelOutput -Transforms.VectorToImage Converts vector array into image type. Microsoft.ML.Runtime.ImageAnalytics.EntryPoints.ImageAnalytics VectorToImage Microsoft.ML.Runtime.ImageAnalytics.VectorToImageTransform+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.WordEmbeddings Word Embeddings transform is a text featurizer which converts vectors of text tokens into sentence vectors using a pre-trained model Microsoft.ML.Transforms.Text.TextAnalytics WordEmbeddings Microsoft.ML.Transforms.Text.WordEmbeddingsExtractingTransformer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput -Transforms.WordTokenizer The input to this transform is text, and the output is a vector of text containing the words (tokens) in the original text. The separator is space, but can be specified as any other character (or multiple characters) if needed. Microsoft.ML.Transforms.Text.TextAnalytics DelimitedTokenizeTransform Microsoft.ML.Transforms.Text.WordTokenizingTransformer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+TransformOutput +Data.CustomTextLoader Import a dataset from a text file Microsoft.ML.EntryPoints.ImportTextData ImportText Microsoft.ML.EntryPoints.ImportTextData+Input Microsoft.ML.EntryPoints.ImportTextData+Output +Data.DataViewReference Pass dataview from memory to experiment Microsoft.ML.EntryPoints.DataViewReference ImportData Microsoft.ML.EntryPoints.DataViewReference+Input Microsoft.ML.EntryPoints.DataViewReference+Output +Data.IDataViewArrayConverter Create an array variable of IDataView Microsoft.ML.EntryPoints.MacroUtils MakeArray Microsoft.ML.EntryPoints.MacroUtils+ArrayIDataViewInput Microsoft.ML.EntryPoints.MacroUtils+ArrayIDataViewOutput +Data.PredictorModelArrayConverter Create an array variable of PredictorModel Microsoft.ML.EntryPoints.MacroUtils MakeArray Microsoft.ML.EntryPoints.MacroUtils+ArrayIPredictorModelInput Microsoft.ML.EntryPoints.MacroUtils+ArrayIPredictorModelOutput +Data.TextLoader Import a dataset from a text file Microsoft.ML.Legacy.EntryPoints.ImportTextData TextLoader Microsoft.ML.Legacy.EntryPoints.ImportTextData+LoaderInput Microsoft.ML.EntryPoints.ImportTextData+Output +Models.AnomalyDetectionEvaluator Evaluates an anomaly detection scored dataset. Microsoft.ML.Data.Evaluate AnomalyDetection Microsoft.ML.Data.AnomalyDetectionMamlEvaluator+Arguments Microsoft.ML.EntryPoints.CommonOutputs+CommonEvaluateOutput +Models.AnomalyPipelineEnsemble Combine anomaly detection models into an ensemble Microsoft.ML.EntryPoints.EnsembleCreator CreateAnomalyPipelineEnsemble Microsoft.ML.EntryPoints.EnsembleCreator+PipelineAnomalyInput Microsoft.ML.EntryPoints.CommonOutputs+AnomalyDetectionOutput +Models.BinaryClassificationEvaluator Evaluates a binary classification scored dataset. Microsoft.ML.Data.Evaluate Binary Microsoft.ML.Data.BinaryClassifierMamlEvaluator+Arguments Microsoft.ML.EntryPoints.CommonOutputs+ClassificationEvaluateOutput +Models.BinaryEnsemble Combine binary classifiers into an ensemble Microsoft.ML.EntryPoints.EnsembleCreator CreateBinaryEnsemble Microsoft.ML.EntryPoints.EnsembleCreator+ClassifierInput Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput +Models.BinaryPipelineEnsemble Combine binary classification models into an ensemble Microsoft.ML.EntryPoints.EnsembleCreator CreateBinaryPipelineEnsemble Microsoft.ML.EntryPoints.EnsembleCreator+PipelineClassifierInput Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput +Models.ClassificationEvaluator Evaluates a multi class classification scored dataset. Microsoft.ML.Data.Evaluate MultiClass Microsoft.ML.Data.MultiClassMamlEvaluator+Arguments Microsoft.ML.EntryPoints.CommonOutputs+ClassificationEvaluateOutput +Models.ClusterEvaluator Evaluates a clustering scored dataset. Microsoft.ML.Data.Evaluate Clustering Microsoft.ML.Data.ClusteringMamlEvaluator+Arguments Microsoft.ML.EntryPoints.CommonOutputs+CommonEvaluateOutput +Models.CrossValidationResultsCombiner Combine the metric data views returned from cross validation. Microsoft.ML.EntryPoints.CrossValidationMacro CombineMetrics Microsoft.ML.EntryPoints.CrossValidationMacro+CombineMetricsInput Microsoft.ML.EntryPoints.CrossValidationMacro+CombinedOutput +Models.CrossValidator Cross validation for general learning Microsoft.ML.EntryPoints.CrossValidationMacro CrossValidate Microsoft.ML.EntryPoints.CrossValidationMacro+Arguments Microsoft.ML.EntryPoints.CommonOutputs+MacroOutput`1[Microsoft.ML.EntryPoints.CrossValidationMacro+Output] +Models.CrossValidatorDatasetSplitter Split the dataset into the specified number of cross-validation folds (train and test sets) Microsoft.ML.EntryPoints.CVSplit Split Microsoft.ML.EntryPoints.CVSplit+Input Microsoft.ML.EntryPoints.CVSplit+Output +Models.DatasetTransformer Applies a TransformModel to a dataset. Microsoft.ML.EntryPoints.ModelOperations Apply Microsoft.ML.EntryPoints.ModelOperations+ApplyTransformModelInput Microsoft.ML.EntryPoints.ModelOperations+ApplyTransformModelOutput +Models.EnsembleSummary Summarize a pipeline ensemble predictor. Microsoft.ML.Ensemble.EntryPoints.PipelineEnsemble Summarize Microsoft.ML.EntryPoints.SummarizePredictor+Input Microsoft.ML.Ensemble.EntryPoints.PipelineEnsemble+SummaryOutput +Models.FixedPlattCalibrator Apply a Platt calibrator with a fixed slope and offset to an input model Microsoft.ML.Internal.Calibration.Calibrate FixedPlatt Microsoft.ML.Internal.Calibration.Calibrate+FixedPlattInput Microsoft.ML.EntryPoints.CommonOutputs+CalibratorOutput +Models.MultiClassPipelineEnsemble Combine multiclass classifiers into an ensemble Microsoft.ML.EntryPoints.EnsembleCreator CreateMultiClassPipelineEnsemble Microsoft.ML.EntryPoints.EnsembleCreator+PipelineClassifierInput Microsoft.ML.EntryPoints.CommonOutputs+MulticlassClassificationOutput +Models.MultiOutputRegressionEvaluator Evaluates a multi output regression scored dataset. Microsoft.ML.Data.Evaluate MultiOutputRegression Microsoft.ML.Data.MultiOutputRegressionMamlEvaluator+Arguments Microsoft.ML.EntryPoints.CommonOutputs+CommonEvaluateOutput +Models.NaiveCalibrator Apply a Naive calibrator to an input model Microsoft.ML.Internal.Calibration.Calibrate Naive Microsoft.ML.Internal.Calibration.Calibrate+NoArgumentsInput Microsoft.ML.EntryPoints.CommonOutputs+CalibratorOutput +Models.OneVersusAll One-vs-All macro (OVA) Microsoft.ML.EntryPoints.OneVersusAllMacro OneVersusAll Microsoft.ML.EntryPoints.OneVersusAllMacro+Arguments Microsoft.ML.EntryPoints.CommonOutputs+MacroOutput`1[Microsoft.ML.EntryPoints.OneVersusAllMacro+Output] +Models.OnnxConverter Converts the model to ONNX format. Microsoft.ML.Model.Onnx.SaveOnnxCommand Apply Microsoft.ML.Model.Onnx.SaveOnnxCommand+Arguments Microsoft.ML.Model.Onnx.SaveOnnxCommand+Output +Models.OvaModelCombiner Combines a sequence of PredictorModels into a single model Microsoft.ML.EntryPoints.ModelOperations CombineOvaModels Microsoft.ML.EntryPoints.ModelOperations+CombineOvaPredictorModelsInput Microsoft.ML.EntryPoints.ModelOperations+PredictorModelOutput +Models.PAVCalibrator Apply a PAV calibrator to an input model Microsoft.ML.Internal.Calibration.Calibrate Pav Microsoft.ML.Internal.Calibration.Calibrate+NoArgumentsInput Microsoft.ML.EntryPoints.CommonOutputs+CalibratorOutput +Models.PlattCalibrator Apply a Platt calibrator to an input model Microsoft.ML.Internal.Calibration.Calibrate Platt Microsoft.ML.Internal.Calibration.Calibrate+NoArgumentsInput Microsoft.ML.EntryPoints.CommonOutputs+CalibratorOutput +Models.QuantileRegressionEvaluator Evaluates a quantile regression scored dataset. Microsoft.ML.Data.Evaluate QuantileRegression Microsoft.ML.Data.QuantileRegressionMamlEvaluator+Arguments Microsoft.ML.EntryPoints.CommonOutputs+CommonEvaluateOutput +Models.RankerEvaluator Evaluates a ranking scored dataset. Microsoft.ML.Data.Evaluate Ranking Microsoft.ML.Data.RankerMamlEvaluator+Arguments Microsoft.ML.EntryPoints.CommonOutputs+CommonEvaluateOutput +Models.RegressionEnsemble Combine regression models into an ensemble Microsoft.ML.EntryPoints.EnsembleCreator CreateRegressionEnsemble Microsoft.ML.EntryPoints.EnsembleCreator+RegressionInput Microsoft.ML.EntryPoints.CommonOutputs+RegressionOutput +Models.RegressionEvaluator Evaluates a regression scored dataset. Microsoft.ML.Data.Evaluate Regression Microsoft.ML.Data.RegressionMamlEvaluator+Arguments Microsoft.ML.EntryPoints.CommonOutputs+CommonEvaluateOutput +Models.RegressionPipelineEnsemble Combine regression models into an ensemble Microsoft.ML.EntryPoints.EnsembleCreator CreateRegressionPipelineEnsemble Microsoft.ML.EntryPoints.EnsembleCreator+PipelineRegressionInput Microsoft.ML.EntryPoints.CommonOutputs+RegressionOutput +Models.Summarizer Summarize a linear regression predictor. Microsoft.ML.EntryPoints.SummarizePredictor Summarize Microsoft.ML.EntryPoints.SummarizePredictor+Input Microsoft.ML.EntryPoints.CommonOutputs+SummaryOutput +Models.TrainTestEvaluator General train test for any supported evaluator Microsoft.ML.EntryPoints.TrainTestMacro TrainTest Microsoft.ML.EntryPoints.TrainTestMacro+Arguments Microsoft.ML.EntryPoints.CommonOutputs+MacroOutput`1[Microsoft.ML.EntryPoints.TrainTestMacro+Output] +TimeSeriesProcessingEntryPoints.ExponentialAverage Applies a Exponential average on a time series. Microsoft.ML.TimeSeriesProcessing.TimeSeriesProcessingEntryPoints ExponentialAverage Microsoft.ML.TimeSeriesProcessing.ExponentialAverageTransform+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +TimeSeriesProcessingEntryPoints.IidChangePointDetector This transform detects the change-points in an i.i.d. sequence using adaptive kernel density estimation and martingales. Microsoft.ML.TimeSeriesProcessing.TimeSeriesProcessingEntryPoints IidChangePointDetector Microsoft.ML.TimeSeriesProcessing.IidChangePointDetector+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +TimeSeriesProcessingEntryPoints.IidSpikeDetector This transform detects the spikes in a i.i.d. sequence using adaptive kernel density estimation. Microsoft.ML.TimeSeriesProcessing.TimeSeriesProcessingEntryPoints IidSpikeDetector Microsoft.ML.TimeSeriesProcessing.IidSpikeDetector+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +TimeSeriesProcessingEntryPoints.PercentileThresholdTransform Detects the values of time-series that are in the top percentile of the sliding window. Microsoft.ML.TimeSeriesProcessing.TimeSeriesProcessingEntryPoints PercentileThresholdTransform Microsoft.ML.TimeSeriesProcessing.PercentileThresholdTransform+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +TimeSeriesProcessingEntryPoints.PValueTransform This P-Value transform calculates the p-value of the current input in the sequence with regard to the values in the sliding window. Microsoft.ML.TimeSeriesProcessing.TimeSeriesProcessingEntryPoints PValueTransform Microsoft.ML.TimeSeriesProcessing.PValueTransform+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +TimeSeriesProcessingEntryPoints.SlidingWindowTransform Returns the last values for a time series [y(t-d-l+1), y(t-d-l+2), ..., y(t-l-1), y(t-l)] where d is the size of the window, l the lag and y is a Float. Microsoft.ML.TimeSeriesProcessing.TimeSeriesProcessingEntryPoints SlidingWindowTransform Microsoft.ML.TimeSeriesProcessing.SlidingWindowTransformBase`1+Arguments[System.Single] Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +TimeSeriesProcessingEntryPoints.SsaChangePointDetector This transform detects the change-points in a seasonal time-series using Singular Spectrum Analysis (SSA). Microsoft.ML.TimeSeriesProcessing.TimeSeriesProcessingEntryPoints SsaChangePointDetector Microsoft.ML.TimeSeriesProcessing.SsaChangePointDetector+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +TimeSeriesProcessingEntryPoints.SsaSpikeDetector This transform detects the spikes in a seasonal time-series using Singular Spectrum Analysis (SSA). Microsoft.ML.TimeSeriesProcessing.TimeSeriesProcessingEntryPoints SsaSpikeDetector Microsoft.ML.TimeSeriesProcessing.SsaSpikeDetector+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Trainers.AveragedPerceptronBinaryClassifier Averaged Perceptron Binary Classifier. Microsoft.ML.Trainers.Online.AveragedPerceptronTrainer TrainBinary Microsoft.ML.Trainers.Online.AveragedPerceptronTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput +Trainers.EnsembleBinaryClassifier Train binary ensemble. Microsoft.ML.Ensemble.EntryPoints.Ensemble CreateBinaryEnsemble Microsoft.ML.Ensemble.EnsembleTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput +Trainers.EnsembleClassification Train multiclass ensemble. Microsoft.ML.Ensemble.EntryPoints.Ensemble CreateMultiClassEnsemble Microsoft.ML.Ensemble.MulticlassDataPartitionEnsembleTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+MulticlassClassificationOutput +Trainers.EnsembleRegression Train regression ensemble. Microsoft.ML.Ensemble.EntryPoints.Ensemble CreateRegressionEnsemble Microsoft.ML.Ensemble.RegressionEnsembleTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+RegressionOutput +Trainers.FastForestBinaryClassifier Uses a random forest learner to perform binary classification. Microsoft.ML.Trainers.FastTree.FastForest TrainBinary Microsoft.ML.Trainers.FastTree.FastForestClassification+Arguments Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput +Trainers.FastForestRegressor Trains a random forest to fit target values using least-squares. Microsoft.ML.Trainers.FastTree.FastForest TrainRegression Microsoft.ML.Trainers.FastTree.FastForestRegression+Arguments Microsoft.ML.EntryPoints.CommonOutputs+RegressionOutput +Trainers.FastTreeBinaryClassifier Uses a logit-boost boosted tree learner to perform binary classification. Microsoft.ML.Trainers.FastTree.FastTree TrainBinary Microsoft.ML.Trainers.FastTree.FastTreeBinaryClassificationTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput +Trainers.FastTreeRanker Trains gradient boosted decision trees to the LambdaRank quasi-gradient. Microsoft.ML.Trainers.FastTree.FastTree TrainRanking Microsoft.ML.Trainers.FastTree.FastTreeRankingTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+RankingOutput +Trainers.FastTreeRegressor Trains gradient boosted decision trees to fit target values using least-squares. Microsoft.ML.Trainers.FastTree.FastTree TrainRegression Microsoft.ML.Trainers.FastTree.FastTreeRegressionTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+RegressionOutput +Trainers.FastTreeTweedieRegressor Trains gradient boosted decision trees to fit target values using a Tweedie loss function. This learner is a generalization of Poisson, compound Poisson, and gamma regression. Microsoft.ML.Trainers.FastTree.FastTree TrainTweedieRegression Microsoft.ML.Trainers.FastTree.FastTreeTweedieTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+RegressionOutput +Trainers.FieldAwareFactorizationMachineBinaryClassifier Train a field-aware factorization machine for binary classification Microsoft.ML.FactorizationMachine.FieldAwareFactorizationMachineTrainer TrainBinary Microsoft.ML.FactorizationMachine.FieldAwareFactorizationMachineTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput +Trainers.GeneralizedAdditiveModelBinaryClassifier Trains a gradient boosted stump per feature, on all features simultaneously, to fit target values using least-squares. It mantains no interactions between features. Microsoft.ML.Trainers.FastTree.Gam TrainBinary Microsoft.ML.Trainers.FastTree.BinaryClassificationGamTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput +Trainers.GeneralizedAdditiveModelRegressor Trains a gradient boosted stump per feature, on all features simultaneously, to fit target values using least-squares. It mantains no interactions between features. Microsoft.ML.Trainers.FastTree.Gam TrainRegression Microsoft.ML.Trainers.FastTree.RegressionGamTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+RegressionOutput +Trainers.KMeansPlusPlusClusterer K-means is a popular clustering algorithm. With K-means, the data is clustered into a specified number of clusters in order to minimize the within-cluster sum of squares. K-means++ improves upon K-means by using a better method for choosing the initial cluster centers. Microsoft.ML.Trainers.KMeans.KMeansPlusPlusTrainer TrainKMeans Microsoft.ML.Trainers.KMeans.KMeansPlusPlusTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+ClusteringOutput +Trainers.LightGbmBinaryClassifier Train a LightGBM binary classification model. Microsoft.ML.LightGBM.LightGbm TrainBinary Microsoft.ML.LightGBM.LightGbmArguments Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput +Trainers.LightGbmClassifier Train a LightGBM multi class model. Microsoft.ML.LightGBM.LightGbm TrainMultiClass Microsoft.ML.LightGBM.LightGbmArguments Microsoft.ML.EntryPoints.CommonOutputs+MulticlassClassificationOutput +Trainers.LightGbmRanker Train a LightGBM ranking model. Microsoft.ML.LightGBM.LightGbm TrainRanking Microsoft.ML.LightGBM.LightGbmArguments Microsoft.ML.EntryPoints.CommonOutputs+RankingOutput +Trainers.LightGbmRegressor LightGBM Regression Microsoft.ML.LightGBM.LightGbm TrainRegression Microsoft.ML.LightGBM.LightGbmArguments Microsoft.ML.EntryPoints.CommonOutputs+RegressionOutput +Trainers.LinearSvmBinaryClassifier Train a linear SVM. Microsoft.ML.Trainers.Online.LinearSvm TrainLinearSvm Microsoft.ML.Trainers.Online.LinearSvm+Arguments Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput +Trainers.LogisticRegressionBinaryClassifier Logistic Regression is a method in statistics used to predict the probability of occurrence of an event and can be used as a classification algorithm. The algorithm predicts the probability of occurrence of an event by fitting data to a logistical function. Microsoft.ML.Learners.LogisticRegression TrainBinary Microsoft.ML.Learners.LogisticRegression+Arguments Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput +Trainers.LogisticRegressionClassifier Logistic Regression is a method in statistics used to predict the probability of occurrence of an event and can be used as a classification algorithm. The algorithm predicts the probability of occurrence of an event by fitting data to a logistical function. Microsoft.ML.Learners.LogisticRegression TrainMultiClass Microsoft.ML.Learners.MulticlassLogisticRegression+Arguments Microsoft.ML.EntryPoints.CommonOutputs+MulticlassClassificationOutput +Trainers.NaiveBayesClassifier Train a MultiClassNaiveBayesTrainer. Microsoft.ML.Trainers.MultiClassNaiveBayesTrainer TrainMultiClassNaiveBayesTrainer Microsoft.ML.Trainers.MultiClassNaiveBayesTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+MulticlassClassificationOutput +Trainers.OnlineGradientDescentRegressor Train a Online gradient descent perceptron. Microsoft.ML.Trainers.Online.OnlineGradientDescentTrainer TrainRegression Microsoft.ML.Trainers.Online.OnlineGradientDescentTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+RegressionOutput +Trainers.OrdinaryLeastSquaresRegressor Train an OLS regression model. Microsoft.ML.Trainers.HalLearners.OlsLinearRegressionTrainer TrainRegression Microsoft.ML.Trainers.HalLearners.OlsLinearRegressionTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+RegressionOutput +Trainers.PcaAnomalyDetector Train an PCA Anomaly model. Microsoft.ML.Trainers.PCA.RandomizedPcaTrainer TrainPcaAnomaly Microsoft.ML.Trainers.PCA.RandomizedPcaTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+AnomalyDetectionOutput +Trainers.PoissonRegressor Train an Poisson regression model. Microsoft.ML.Trainers.PoissonRegression TrainRegression Microsoft.ML.Trainers.PoissonRegression+Arguments Microsoft.ML.EntryPoints.CommonOutputs+RegressionOutput +Trainers.StochasticDualCoordinateAscentBinaryClassifier Train an SDCA binary model. Microsoft.ML.Trainers.Sdca TrainBinary Microsoft.ML.Trainers.SdcaBinaryTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput +Trainers.StochasticDualCoordinateAscentClassifier The SDCA linear multi-class classification trainer. Microsoft.ML.Trainers.Sdca TrainMultiClass Microsoft.ML.Trainers.SdcaMultiClassTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+MulticlassClassificationOutput +Trainers.StochasticDualCoordinateAscentRegressor The SDCA linear regression trainer. Microsoft.ML.Trainers.Sdca TrainRegression Microsoft.ML.Trainers.SdcaRegressionTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+RegressionOutput +Trainers.StochasticGradientDescentBinaryClassifier Train an Hogwild SGD binary model. Microsoft.ML.Trainers.StochasticGradientDescentClassificationTrainer TrainBinary Microsoft.ML.Trainers.StochasticGradientDescentClassificationTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput +Trainers.SymSgdBinaryClassifier Train a symbolic SGD. Microsoft.ML.Trainers.SymSgd.SymSgdClassificationTrainer TrainSymSgd Microsoft.ML.Trainers.SymSgd.SymSgdClassificationTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput +Transforms.ApproximateBootstrapSampler Approximate bootstrap sampling. Microsoft.ML.Transforms.BootstrapSample GetSample Microsoft.ML.Transforms.BootstrapSamplingTransformer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.BinaryPredictionScoreColumnsRenamer For binary prediction, it renames the PredictedLabel and Score columns to include the name of the positive class. Microsoft.ML.EntryPoints.ScoreModel RenameBinaryPredictionScoreColumns Microsoft.ML.EntryPoints.ScoreModel+RenameBinaryPredictionScoreColumnsInput Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.BinNormalizer The values are assigned into equidensity bins and a value is mapped to its bin_number/number_of_bins. Microsoft.ML.Data.Normalize Bin Microsoft.ML.Transforms.Normalizers.NormalizeTransform+BinArguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.CategoricalHashOneHotVectorizer Converts the categorical value into an indicator array by hashing the value and using the hash as an index in the bag. If the input column is a vector, a single indicator bag is returned for it. Microsoft.ML.Transforms.Categorical.Categorical CatTransformHash Microsoft.ML.Transforms.Categorical.OneHotHashEncoding+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.CategoricalOneHotVectorizer Converts the categorical value into an indicator array by building a dictionary of categories based on the data and using the id in the dictionary as the index in the array. Microsoft.ML.Transforms.Categorical.Categorical CatTransformDict Microsoft.ML.Transforms.Categorical.OneHotEncodingTransformer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.CharacterTokenizer Character-oriented tokenizer where text is considered a sequence of characters. Microsoft.ML.Transforms.Text.TextAnalytics CharTokenize Microsoft.ML.Transforms.Text.TokenizingByCharactersTransformer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.ColumnConcatenator Concatenates one or more columns of the same item type. Microsoft.ML.EntryPoints.SchemaManipulation ConcatColumns Microsoft.ML.Data.ColumnConcatenatingTransformer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.ColumnCopier Duplicates columns from the dataset Microsoft.ML.EntryPoints.SchemaManipulation CopyColumns Microsoft.ML.Transforms.ColumnCopyingTransformer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.ColumnSelector Selects a set of columns, dropping all others Microsoft.ML.EntryPoints.SchemaManipulation SelectColumns Microsoft.ML.Transforms.ColumnSelectingTransformer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.ColumnTypeConverter Converts a column to a different type, using standard conversions. Microsoft.ML.Transforms.Conversions.TypeConversion Convert Microsoft.ML.Transforms.Conversions.TypeConvertingTransformer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.CombinerByContiguousGroupId Groups values of a scalar column into a vector, by a contiguous group ID Microsoft.ML.Transforms.GroupingOperations Group Microsoft.ML.Transforms.GroupTransform+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.ConditionalNormalizer Normalize the columns only if needed Microsoft.ML.Data.Normalize IfNeeded Microsoft.ML.Transforms.Normalizers.NormalizeTransform+MinMaxArguments Microsoft.ML.EntryPoints.CommonOutputs+MacroOutput`1[Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput] +Transforms.DataCache Caches using the specified cache option. Microsoft.ML.EntryPoints.Cache CacheData Microsoft.ML.EntryPoints.Cache+CacheInput Microsoft.ML.EntryPoints.Cache+CacheOutput +Transforms.DatasetScorer Score a dataset with a predictor model Microsoft.ML.EntryPoints.ScoreModel Score Microsoft.ML.EntryPoints.ScoreModel+Input Microsoft.ML.EntryPoints.ScoreModel+Output +Transforms.DatasetTransformScorer Score a dataset with a transform model Microsoft.ML.EntryPoints.ScoreModel ScoreUsingTransform Microsoft.ML.EntryPoints.ScoreModel+InputTransformScorer Microsoft.ML.EntryPoints.ScoreModel+Output +Transforms.Dictionarizer Converts input values (words, numbers, etc.) to index in a dictionary. Microsoft.ML.Transforms.Text.TextAnalytics TermTransform Microsoft.ML.Transforms.Conversions.ValueToKeyMappingTransformer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.FeatureCombiner Combines all the features into one feature column. Microsoft.ML.EntryPoints.FeatureCombiner PrepareFeatures Microsoft.ML.EntryPoints.FeatureCombiner+FeatureCombinerInput Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.FeatureContributionCalculationTransformer For each data point, calculates the contribution of individual features to the model prediction. Microsoft.ML.Data.FeatureContributionEntryPoint FeatureContributionCalculation Microsoft.ML.Data.FeatureContributionCalculatingTransformer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.FeatureSelectorByCount Selects the slots for which the count of non-default values is greater than or equal to a threshold. Microsoft.ML.Transforms.SelectFeatures CountSelect Microsoft.ML.Transforms.FeatureSelection.CountFeatureSelectingEstimator+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.FeatureSelectorByMutualInformation Selects the top k slots across all specified columns ordered by their mutual information with the label column. Microsoft.ML.Transforms.SelectFeatures MutualInformationSelect Microsoft.ML.Transforms.FeatureSelection.MutualInformationFeatureSelectingEstimator+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.GlobalContrastNormalizer Performs a global contrast normalization on input values: Y = (s * X - M) / D, where s is a scale, M is mean and D is either L2 norm or standard deviation. Microsoft.ML.Transforms.Projections.LpNormalization GcNormalize Microsoft.ML.Transforms.Projections.LpNormalizingTransformer+GcnArguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.HashConverter Converts column values into hashes. This transform accepts both numeric and text inputs, both single and vector-valued columns. Microsoft.ML.Transforms.Conversions.HashJoin Apply Microsoft.ML.Transforms.Conversions.HashJoiningTransform+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.ImageGrayscale Convert image into grayscale. Microsoft.ML.ImageAnalytics.EntryPoints.ImageAnalytics ImageGrayscale Microsoft.ML.ImageAnalytics.ImageGrayscaleTransform+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.ImageLoader Load images from files. Microsoft.ML.ImageAnalytics.EntryPoints.ImageAnalytics ImageLoader Microsoft.ML.ImageAnalytics.ImageLoaderTransform+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.ImagePixelExtractor Extract color plane(s) from an image. Options include scaling, offset and conversion to floating point. Microsoft.ML.ImageAnalytics.EntryPoints.ImageAnalytics ImagePixelExtractor Microsoft.ML.ImageAnalytics.ImagePixelExtractorTransform+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.ImageResizer Scales an image to specified dimensions using one of the three scale types: isotropic with padding, isotropic with cropping or anisotropic. In case of isotropic padding, transparent color is used to pad resulting image. Microsoft.ML.ImageAnalytics.EntryPoints.ImageAnalytics ImageResizer Microsoft.ML.ImageAnalytics.ImageResizerTransform+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.KeyToTextConverter KeyToValueTransform utilizes KeyValues metadata to map key indices to the corresponding values in the KeyValues metadata. Microsoft.ML.Transforms.Categorical.Categorical KeyToText Microsoft.ML.Transforms.Conversions.KeyToValueMappingTransformer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.LabelColumnKeyBooleanConverter Transforms the label to either key or bool (if needed) to make it suitable for classification. Microsoft.ML.EntryPoints.FeatureCombiner PrepareClassificationLabel Microsoft.ML.EntryPoints.FeatureCombiner+ClassificationLabelInput Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.LabelIndicator Label remapper used by OVA Microsoft.ML.Transforms.LabelIndicatorTransform LabelIndicator Microsoft.ML.Transforms.LabelIndicatorTransform+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.LabelToFloatConverter Transforms the label to float to make it suitable for regression. Microsoft.ML.EntryPoints.FeatureCombiner PrepareRegressionLabel Microsoft.ML.EntryPoints.FeatureCombiner+RegressionLabelInput Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.LightLda The LDA transform implements LightLDA, a state-of-the-art implementation of Latent Dirichlet Allocation. Microsoft.ML.Transforms.Text.TextAnalytics LightLda Microsoft.ML.Transforms.Text.LatentDirichletAllocationTransformer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.LogMeanVarianceNormalizer Normalizes the data based on the computed mean and variance of the logarithm of the data. Microsoft.ML.Data.Normalize LogMeanVar Microsoft.ML.Transforms.Normalizers.NormalizeTransform+LogMeanVarArguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.LpNormalizer Normalize vectors (rows) individually by rescaling them to unit norm (L2, L1 or LInf). Performs the following operation on a vector X: Y = (X - M) / D, where M is mean and D is either L2 norm, L1 norm or LInf norm. Microsoft.ML.Transforms.Projections.LpNormalization Normalize Microsoft.ML.Transforms.Projections.LpNormalizingTransformer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.ManyHeterogeneousModelCombiner Combines a sequence of TransformModels and a PredictorModel into a single PredictorModel. Microsoft.ML.EntryPoints.ModelOperations CombineModels Microsoft.ML.EntryPoints.ModelOperations+PredictorModelInput Microsoft.ML.EntryPoints.ModelOperations+PredictorModelOutput +Transforms.MeanVarianceNormalizer Normalizes the data based on the computed mean and variance of the data. Microsoft.ML.Data.Normalize MeanVar Microsoft.ML.Transforms.Normalizers.NormalizeTransform+MeanVarArguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.MinMaxNormalizer Normalizes the data based on the observed minimum and maximum values of the data. Microsoft.ML.Data.Normalize MinMax Microsoft.ML.Transforms.Normalizers.NormalizeTransform+MinMaxArguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.MissingValueHandler Handle missing values by replacing them with either the default value or the mean/min/max value (for non-text columns only). An indicator column can optionally be concatenated, if theinput column type is numeric. Microsoft.ML.Transforms.NAHandling Handle Microsoft.ML.Transforms.MissingValueHandlingTransformer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.MissingValueIndicator Create a boolean output column with the same number of slots as the input column, where the output value is true if the value in the input column is missing. Microsoft.ML.Transforms.NAHandling Indicator Microsoft.ML.Transforms.MissingValueIndicatorTransformer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.MissingValuesDropper Removes NAs from vector columns. Microsoft.ML.Transforms.NAHandling Drop Microsoft.ML.Transforms.MissingValueDroppingTransformer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.MissingValuesRowDropper Filters out rows that contain missing values. Microsoft.ML.Transforms.NAHandling Filter Microsoft.ML.Transforms.NAFilter+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.MissingValueSubstitutor Create an output column of the same type and size of the input column, where missing values are replaced with either the default value or the mean/min/max value (for non-text columns only). Microsoft.ML.Transforms.NAHandling Replace Microsoft.ML.Transforms.MissingValueReplacingTransformer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.ModelCombiner Combines a sequence of TransformModels into a single model Microsoft.ML.EntryPoints.ModelOperations CombineTransformModels Microsoft.ML.EntryPoints.ModelOperations+CombineTransformModelsInput Microsoft.ML.EntryPoints.ModelOperations+CombineTransformModelsOutput +Transforms.NGramTranslator Produces a bag of counts of ngrams (sequences of consecutive values of length 1-n) in a given vector of keys. It does so by building a dictionary of ngrams and using the id in the dictionary as the index in the bag. Microsoft.ML.Transforms.Text.TextAnalytics NGramTransform Microsoft.ML.Transforms.Text.NgramExtractingTransformer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.NoOperation Does nothing. Microsoft.ML.Data.NopTransform Nop Microsoft.ML.Data.NopTransform+NopInput Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.OptionalColumnCreator If the source column does not exist after deserialization, create a column with the right type and default values. Microsoft.ML.Transforms.OptionalColumnTransform MakeOptional Microsoft.ML.Transforms.OptionalColumnTransform+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.PcaCalculator PCA is a dimensionality-reduction transform which computes the projection of a numeric vector onto a low-rank subspace. Microsoft.ML.Transforms.Projections.PcaTransform Calculate Microsoft.ML.Transforms.Projections.PcaTransform+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.PredictedLabelColumnOriginalValueConverter Transforms a predicted label column to its original values, unless it is of type bool. Microsoft.ML.EntryPoints.FeatureCombiner ConvertPredictedLabel Microsoft.ML.EntryPoints.FeatureCombiner+PredictedLabelInput Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.RandomNumberGenerator Adds a column with a generated number sequence. Microsoft.ML.Transforms.RandomNumberGenerator Generate Microsoft.ML.Transforms.GenerateNumberTransform+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.RowRangeFilter Filters a dataview on a column of type Single, Double or Key (contiguous). Keeps the values that are in the specified min/max range. NaNs are always filtered out. If the input is a Key type, the min/max are considered percentages of the number of values. Microsoft.ML.EntryPoints.SelectRows FilterByRange Microsoft.ML.Transforms.RangeFilter+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.RowSkipAndTakeFilter Allows limiting input to a subset of rows at an optional offset. Can be used to implement data paging. Microsoft.ML.EntryPoints.SelectRows SkipAndTakeFilter Microsoft.ML.Transforms.SkipTakeFilter+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.RowSkipFilter Allows limiting input to a subset of rows by skipping a number of rows. Microsoft.ML.EntryPoints.SelectRows SkipFilter Microsoft.ML.Transforms.SkipTakeFilter+SkipArguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.RowTakeFilter Allows limiting input to a subset of rows by taking N first rows. Microsoft.ML.EntryPoints.SelectRows TakeFilter Microsoft.ML.Transforms.SkipTakeFilter+TakeArguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.ScoreColumnSelector Selects only the last score columns and the extra columns specified in the arguments. Microsoft.ML.EntryPoints.ScoreModel SelectColumns Microsoft.ML.EntryPoints.ScoreModel+ScoreColumnSelectorInput Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.Scorer Turn the predictor model into a transform model Microsoft.ML.EntryPoints.ScoreModel MakeScoringTransform Microsoft.ML.EntryPoints.ScoreModel+ModelInput Microsoft.ML.EntryPoints.ScoreModel+Output +Transforms.Segregator Un-groups vector columns into sequences of rows, inverse of Group transform Microsoft.ML.Transforms.GroupingOperations Ungroup Microsoft.ML.Transforms.UngroupTransform+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.SentimentAnalyzer Uses a pretrained sentiment model to score input strings Microsoft.ML.Transforms.Text.TextAnalytics AnalyzeSentiment Microsoft.ML.Transforms.Text.SentimentAnalyzingTransformer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.TensorFlowScorer Transforms the data using the TensorFlow model. Microsoft.ML.Transforms.TensorFlowTransform TensorFlowScorer Microsoft.ML.Transforms.TensorFlowTransform+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.TextFeaturizer A transform that turns a collection of text documents into numerical feature vectors. The feature vectors are normalized counts of (word and/or character) ngrams in a given tokenized text. Microsoft.ML.Transforms.Text.TextAnalytics TextTransform Microsoft.ML.Transforms.Text.TextFeaturizingEstimator+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.TextToKeyConverter Converts input values (words, numbers, etc.) to index in a dictionary. Microsoft.ML.Transforms.Categorical.Categorical TextToKey Microsoft.ML.Transforms.Conversions.ValueToKeyMappingTransformer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.TrainTestDatasetSplitter Split the dataset into train and test sets Microsoft.ML.EntryPoints.TrainTestSplit Split Microsoft.ML.EntryPoints.TrainTestSplit+Input Microsoft.ML.EntryPoints.TrainTestSplit+Output +Transforms.TreeLeafFeaturizer Trains a tree ensemble, or loads it from a file, then maps a numeric feature vector to three outputs: 1. A vector containing the individual tree outputs of the tree ensemble. 2. A vector indicating the leaves that the feature vector falls on in the tree ensemble. 3. A vector indicating the paths that the feature vector falls on in the tree ensemble. If a both a model file and a trainer are specified - will use the model file. If neither are specified, will train a default FastTree model. This can handle key labels by training a regression model towards their optionally permuted indices. Microsoft.ML.Data.TreeFeaturize Featurizer Microsoft.ML.Data.TreeEnsembleFeaturizerTransform+ArgumentsForEntryPoint Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.TwoHeterogeneousModelCombiner Combines a TransformModel and a PredictorModel into a single PredictorModel. Microsoft.ML.EntryPoints.ModelOperations CombineTwoModels Microsoft.ML.EntryPoints.ModelOperations+SimplePredictorModelInput Microsoft.ML.EntryPoints.ModelOperations+PredictorModelOutput +Transforms.VectorToImage Converts vector array into image type. Microsoft.ML.ImageAnalytics.EntryPoints.ImageAnalytics VectorToImage Microsoft.ML.ImageAnalytics.VectorToImageTransform+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.WordEmbeddings Word Embeddings transform is a text featurizer which converts vectors of text tokens into sentence vectors using a pre-trained model Microsoft.ML.Transforms.Text.TextAnalytics WordEmbeddings Microsoft.ML.Transforms.Text.WordEmbeddingsExtractingTransformer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.WordTokenizer The input to this transform is text, and the output is a vector of text containing the words (tokens) in the original text. The separator is space, but can be specified as any other character (or multiple characters) if needed. Microsoft.ML.Transforms.Text.TextAnalytics DelimitedTokenizeTransform Microsoft.ML.Transforms.Text.WordTokenizingTransformer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput diff --git a/test/BaselineOutput/Common/EntryPoints/core_manifest.json b/test/BaselineOutput/Common/EntryPoints/core_manifest.json index 5296d7565c..3e95b0e09d 100644 --- a/test/BaselineOutput/Common/EntryPoints/core_manifest.json +++ b/test/BaselineOutput/Common/EntryPoints/core_manifest.json @@ -3330,7 +3330,7 @@ ] }, { - "Name": "TimeSeriesProcessing.ExponentialAverage", + "Name": "TimeSeriesProcessingEntryPoints.ExponentialAverage", "Desc": "Applies a Exponential average on a time series.", "FriendlyName": "Exponential Average Transform", "ShortName": "ExpAvg", @@ -3398,7 +3398,7 @@ ] }, { - "Name": "TimeSeriesProcessing.IidChangePointDetector", + "Name": "TimeSeriesProcessingEntryPoints.IidChangePointDetector", "Desc": "This transform detects the change-points in an i.i.d. sequence using adaptive kernel density estimation and martingales.", "FriendlyName": "IID Change Point Detection", "ShortName": "ichgpnt", @@ -3506,7 +3506,7 @@ ] }, { - "Name": "TimeSeriesProcessing.IidSpikeDetector", + "Name": "TimeSeriesProcessingEntryPoints.IidSpikeDetector", "Desc": "This transform detects the spikes in a i.i.d. sequence using adaptive kernel density estimation.", "FriendlyName": "IID Spike Detection", "ShortName": "ispike", @@ -3602,7 +3602,7 @@ ] }, { - "Name": "TimeSeriesProcessing.PercentileThresholdTransform", + "Name": "TimeSeriesProcessingEntryPoints.PercentileThresholdTransform", "Desc": "Detects the values of time-series that are in the top percentile of the sliding window.", "FriendlyName": "Percentile Threshold Transform", "ShortName": "TopPcnt", @@ -3682,7 +3682,7 @@ ] }, { - "Name": "TimeSeriesProcessing.PValueTransform", + "Name": "TimeSeriesProcessingEntryPoints.PValueTransform", "Desc": "This P-Value transform calculates the p-value of the current input in the sequence with regard to the values in the sliding window.", "FriendlyName": "p-Value Transform", "ShortName": "PVal", @@ -3786,7 +3786,7 @@ ] }, { - "Name": "TimeSeriesProcessing.SlidingWindowTransform", + "Name": "TimeSeriesProcessingEntryPoints.SlidingWindowTransform", "Desc": "Returns the last values for a time series [y(t-d-l+1), y(t-d-l+2), ..., y(t-l-1), y(t-l)] where d is the size of the window, l the lag and y is a Float.", "FriendlyName": "Sliding Window Transform", "ShortName": "SlideWin", @@ -3878,7 +3878,7 @@ ] }, { - "Name": "TimeSeriesProcessing.SsaChangePointDetector", + "Name": "TimeSeriesProcessingEntryPoints.SsaChangePointDetector", "Desc": "This transform detects the change-points in a seasonal time-series using Singular Spectrum Analysis (SSA).", "FriendlyName": "SSA Change Point Detection", "ShortName": "chgpnt", @@ -4031,7 +4031,7 @@ ] }, { - "Name": "TimeSeriesProcessing.SsaSpikeDetector", + "Name": "TimeSeriesProcessingEntryPoints.SsaSpikeDetector", "Desc": "This transform detects the spikes in a seasonal time-series using Singular Spectrum Analysis (SSA).", "FriendlyName": "SSA Spike Detection", "ShortName": "spike", diff --git a/test/Microsoft.ML.Benchmarks.Tests/BenchmarksTest.cs b/test/Microsoft.ML.Benchmarks.Tests/BenchmarksTest.cs index 96f4a6bd8f..2003969d76 100644 --- a/test/Microsoft.ML.Benchmarks.Tests/BenchmarksTest.cs +++ b/test/Microsoft.ML.Benchmarks.Tests/BenchmarksTest.cs @@ -7,7 +7,7 @@ using BenchmarkDotNet.Jobs; using BenchmarkDotNet.Loggers; using BenchmarkDotNet.Running; -using Microsoft.ML.Runtime.Internal.CpuMath; +using Microsoft.ML.Internal.CpuMath; using System; using System.Linq; using Xunit; diff --git a/test/Microsoft.ML.Benchmarks/CacheDataViewBench.cs b/test/Microsoft.ML.Benchmarks/CacheDataViewBench.cs index d01491f36f..1fbb452f10 100644 --- a/test/Microsoft.ML.Benchmarks/CacheDataViewBench.cs +++ b/test/Microsoft.ML.Benchmarks/CacheDataViewBench.cs @@ -3,7 +3,7 @@ // See the LICENSE file in the project root for more information. using BenchmarkDotNet.Attributes; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; using System; namespace Microsoft.ML.Benchmarks diff --git a/test/Microsoft.ML.Benchmarks/HashBench.cs b/test/Microsoft.ML.Benchmarks/HashBench.cs index d103188ecd..0973e5d430 100644 --- a/test/Microsoft.ML.Benchmarks/HashBench.cs +++ b/test/Microsoft.ML.Benchmarks/HashBench.cs @@ -4,8 +4,6 @@ using BenchmarkDotNet.Attributes; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using Microsoft.ML.Transforms.Conversions; using System; using System.Linq; diff --git a/test/Microsoft.ML.Benchmarks/Helpers/EnvironmentFactory.cs b/test/Microsoft.ML.Benchmarks/Helpers/EnvironmentFactory.cs index 20582c108d..505ab91252 100644 --- a/test/Microsoft.ML.Benchmarks/Helpers/EnvironmentFactory.cs +++ b/test/Microsoft.ML.Benchmarks/Helpers/EnvironmentFactory.cs @@ -3,9 +3,9 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Training; using Microsoft.ML.Transforms; namespace Microsoft.ML.Benchmarks diff --git a/test/Microsoft.ML.Benchmarks/KMeansAndLogisticRegressionBench.cs b/test/Microsoft.ML.Benchmarks/KMeansAndLogisticRegressionBench.cs index 04e735fb37..1861057bb9 100644 --- a/test/Microsoft.ML.Benchmarks/KMeansAndLogisticRegressionBench.cs +++ b/test/Microsoft.ML.Benchmarks/KMeansAndLogisticRegressionBench.cs @@ -3,8 +3,8 @@ // See the LICENSE file in the project root for more information. using BenchmarkDotNet.Attributes; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Calibration; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Calibration; namespace Microsoft.ML.Benchmarks { diff --git a/test/Microsoft.ML.Benchmarks/Numeric/Ranking.cs b/test/Microsoft.ML.Benchmarks/Numeric/Ranking.cs index adc1bccdce..19d66a87ed 100644 --- a/test/Microsoft.ML.Benchmarks/Numeric/Ranking.cs +++ b/test/Microsoft.ML.Benchmarks/Numeric/Ranking.cs @@ -3,11 +3,11 @@ // See the LICENSE file in the project root for more information. using BenchmarkDotNet.Attributes; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; using Microsoft.ML.Trainers.FastTree; -using Microsoft.ML.Runtime.LightGBM; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML.LightGBM; +using Microsoft.ML.RunTests; +using Microsoft.ML.Tools; using Microsoft.ML.Transforms.Conversions; using System.IO; diff --git a/test/Microsoft.ML.Benchmarks/PredictionEngineBench.cs b/test/Microsoft.ML.Benchmarks/PredictionEngineBench.cs index f38946e4e0..57a0c849fd 100644 --- a/test/Microsoft.ML.Benchmarks/PredictionEngineBench.cs +++ b/test/Microsoft.ML.Benchmarks/PredictionEngineBench.cs @@ -4,8 +4,6 @@ using BenchmarkDotNet.Attributes; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using Microsoft.ML.Trainers; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Text; diff --git a/test/Microsoft.ML.Benchmarks/RffTransform.cs b/test/Microsoft.ML.Benchmarks/RffTransform.cs index aee30ddea8..1d6861a338 100644 --- a/test/Microsoft.ML.Benchmarks/RffTransform.cs +++ b/test/Microsoft.ML.Benchmarks/RffTransform.cs @@ -3,8 +3,8 @@ // See the LICENSE file in the project root for more information. using BenchmarkDotNet.Attributes; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.Data; +using Microsoft.ML.RunTests; using Microsoft.ML.Transforms.Conversions; using System.IO; diff --git a/test/Microsoft.ML.Benchmarks/StochasticDualCoordinateAscentClassifierBench.cs b/test/Microsoft.ML.Benchmarks/StochasticDualCoordinateAscentClassifierBench.cs index 930c38af10..6395d8312d 100644 --- a/test/Microsoft.ML.Benchmarks/StochasticDualCoordinateAscentClassifierBench.cs +++ b/test/Microsoft.ML.Benchmarks/StochasticDualCoordinateAscentClassifierBench.cs @@ -8,7 +8,6 @@ using Microsoft.ML.Legacy.Models; using Microsoft.ML.Legacy.Trainers; using Microsoft.ML.Legacy.Transforms; -using Microsoft.ML.Runtime.Data; using Microsoft.ML.Trainers; using Microsoft.ML.Transforms.Text; using System.Collections.Generic; diff --git a/test/Microsoft.ML.Benchmarks/Text/MultiClassClassification.cs b/test/Microsoft.ML.Benchmarks/Text/MultiClassClassification.cs index d7705aaadb..63472b2864 100644 --- a/test/Microsoft.ML.Benchmarks/Text/MultiClassClassification.cs +++ b/test/Microsoft.ML.Benchmarks/Text/MultiClassClassification.cs @@ -3,10 +3,10 @@ // See the LICENSE file in the project root for more information. using BenchmarkDotNet.Attributes; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.LightGBM; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML.Data; +using Microsoft.ML.LightGBM; +using Microsoft.ML.RunTests; +using Microsoft.ML.Tools; using Microsoft.ML.Trainers.Online; using Microsoft.ML.Trainers; using Microsoft.ML.Transforms.Categorical; diff --git a/test/Microsoft.ML.CodeAnalyzer.Tests/Helpers/DiagnosticVerifier.cs b/test/Microsoft.ML.CodeAnalyzer.Tests/Helpers/DiagnosticVerifier.cs index 54262b6023..8d68cb98ff 100644 --- a/test/Microsoft.ML.CodeAnalyzer.Tests/Helpers/DiagnosticVerifier.cs +++ b/test/Microsoft.ML.CodeAnalyzer.Tests/Helpers/DiagnosticVerifier.cs @@ -262,8 +262,8 @@ private static string FormatDiagnostics(DiagnosticAnalyzer analyzer, params Diag private static readonly MetadataReference CSharpSymbolsReference = RefFromType(); private static readonly MetadataReference CodeAnalysisReference = RefFromType(); - private static readonly MetadataReference MLNetCoreReference = RefFromType(); - private static readonly MetadataReference MLNetDataReference = RefFromType(); + private static readonly MetadataReference MLNetCoreReference = RefFromType(); + private static readonly MetadataReference MLNetDataReference = RefFromType(); protected static MetadataReference RefFromType() => MetadataReference.CreateFromFile(typeof(TType).Assembly.Location); diff --git a/test/Microsoft.ML.CodeAnalyzer.Tests/Resources/ContractsCheckAfterFix.cs b/test/Microsoft.ML.CodeAnalyzer.Tests/Resources/ContractsCheckAfterFix.cs index c3e9ecfa31..1783bdf1bc 100644 --- a/test/Microsoft.ML.CodeAnalyzer.Tests/Resources/ContractsCheckAfterFix.cs +++ b/test/Microsoft.ML.CodeAnalyzer.Tests/Resources/ContractsCheckAfterFix.cs @@ -1,5 +1,5 @@ -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; +using Microsoft.ML; +using Microsoft.ML.CommandLine; using System; namespace Bubba { diff --git a/test/Microsoft.ML.CodeAnalyzer.Tests/Resources/ContractsCheckBeforeFix.cs b/test/Microsoft.ML.CodeAnalyzer.Tests/Resources/ContractsCheckBeforeFix.cs index 2835c06794..6c6cc61c47 100644 --- a/test/Microsoft.ML.CodeAnalyzer.Tests/Resources/ContractsCheckBeforeFix.cs +++ b/test/Microsoft.ML.CodeAnalyzer.Tests/Resources/ContractsCheckBeforeFix.cs @@ -1,5 +1,5 @@ -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; +using Microsoft.ML; +using Microsoft.ML.CommandLine; using System; namespace Bubba { diff --git a/test/Microsoft.ML.CodeAnalyzer.Tests/Resources/ContractsCheckResource.cs b/test/Microsoft.ML.CodeAnalyzer.Tests/Resources/ContractsCheckResource.cs index cd6690942f..3f6feb2212 100644 --- a/test/Microsoft.ML.CodeAnalyzer.Tests/Resources/ContractsCheckResource.cs +++ b/test/Microsoft.ML.CodeAnalyzer.Tests/Resources/ContractsCheckResource.cs @@ -4,8 +4,8 @@ // the corresponding code in ML.NET. using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.Model; namespace TestNamespace { @@ -59,7 +59,7 @@ public static class Messages } // Dummy declarations so that the independent compilation of contracts works as expected. -namespace Microsoft.ML.Runtime +namespace Microsoft.ML { [Flags] internal enum MessageSensitivity diff --git a/test/Microsoft.ML.CodeAnalyzer.Tests/Resources/TypeIsSchemaShapeClassResource.cs b/test/Microsoft.ML.CodeAnalyzer.Tests/Resources/TypeIsSchemaShapeClassResource.cs index d95d9d3140..855dc747df 100644 --- a/test/Microsoft.ML.CodeAnalyzer.Tests/Resources/TypeIsSchemaShapeClassResource.cs +++ b/test/Microsoft.ML.CodeAnalyzer.Tests/Resources/TypeIsSchemaShapeClassResource.cs @@ -1,6 +1,6 @@ using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.StaticPipe; namespace Bubba diff --git a/test/Microsoft.ML.CodeAnalyzer.Tests/Resources/TypeIsSchemaShapeResource.cs b/test/Microsoft.ML.CodeAnalyzer.Tests/Resources/TypeIsSchemaShapeResource.cs index 2aa2a6e990..cf1aefd9ac 100644 --- a/test/Microsoft.ML.CodeAnalyzer.Tests/Resources/TypeIsSchemaShapeResource.cs +++ b/test/Microsoft.ML.CodeAnalyzer.Tests/Resources/TypeIsSchemaShapeResource.cs @@ -1,7 +1,7 @@ using System; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; using Microsoft.ML.StaticPipe; namespace Bubba diff --git a/test/Microsoft.ML.CodeAnalyzer.Tests/Resources/TypeIsSchemaShapeResourceChained.cs b/test/Microsoft.ML.CodeAnalyzer.Tests/Resources/TypeIsSchemaShapeResourceChained.cs index 037e34a7e8..0c9f03eee0 100644 --- a/test/Microsoft.ML.CodeAnalyzer.Tests/Resources/TypeIsSchemaShapeResourceChained.cs +++ b/test/Microsoft.ML.CodeAnalyzer.Tests/Resources/TypeIsSchemaShapeResourceChained.cs @@ -1,8 +1,8 @@ using System; using System.Collections.Generic; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; using Microsoft.ML.StaticPipe; namespace Bubba diff --git a/test/Microsoft.ML.Core.Tests/UnitTests/ColumnTypes.cs b/test/Microsoft.ML.Core.Tests/UnitTests/ColumnTypes.cs index ac0bd8c187..6ecea0d219 100644 --- a/test/Microsoft.ML.Core.Tests/UnitTests/ColumnTypes.cs +++ b/test/Microsoft.ML.Core.Tests/UnitTests/ColumnTypes.cs @@ -4,11 +4,11 @@ using System; using System.Collections.Generic; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.ImageAnalytics; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.ImageAnalytics; using Xunit; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { public sealed class ColumnTypeTests { diff --git a/test/Microsoft.ML.Core.Tests/UnitTests/CoreBaseTestClass.cs b/test/Microsoft.ML.Core.Tests/UnitTests/CoreBaseTestClass.cs index 9e318a3b52..2d0ca7e602 100644 --- a/test/Microsoft.ML.Core.Tests/UnitTests/CoreBaseTestClass.cs +++ b/test/Microsoft.ML.Core.Tests/UnitTests/CoreBaseTestClass.cs @@ -2,15 +2,15 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.RunTests; using System; using System.Collections.Generic; using Xunit; using Xunit.Abstractions; -namespace Microsoft.ML.Runtime.Core.Tests.UnitTests +namespace Microsoft.ML.Core.Tests.UnitTests { public class CoreBaseTestClass : BaseTestBaseline { diff --git a/test/Microsoft.ML.Core.Tests/UnitTests/DataTypes.cs b/test/Microsoft.ML.Core.Tests/UnitTests/DataTypes.cs index 385e6cd527..21d616462c 100644 --- a/test/Microsoft.ML.Core.Tests/UnitTests/DataTypes.cs +++ b/test/Microsoft.ML.Core.Tests/UnitTests/DataTypes.cs @@ -2,12 +2,12 @@ using System.IO; using System.Linq; using System.Text; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.Conversion; +using Microsoft.ML.Data; +using Microsoft.ML.Data.Conversion; using Xunit; using Xunit.Abstractions; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { public class DataTypesTest : TestDataViewBase { diff --git a/test/Microsoft.ML.Core.Tests/UnitTests/FileSource.cs b/test/Microsoft.ML.Core.Tests/UnitTests/FileSource.cs index f46394bb7d..8a799738d9 100644 --- a/test/Microsoft.ML.Core.Tests/UnitTests/FileSource.cs +++ b/test/Microsoft.ML.Core.Tests/UnitTests/FileSource.cs @@ -2,12 +2,12 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; using System; using System.IO; using Xunit; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { public sealed class FileSource { diff --git a/test/Microsoft.ML.Core.Tests/UnitTests/TestCSharpApi.cs b/test/Microsoft.ML.Core.Tests/UnitTests/TestCSharpApi.cs index 6a04d7cf0a..0295b0f854 100644 --- a/test/Microsoft.ML.Core.Tests/UnitTests/TestCSharpApi.cs +++ b/test/Microsoft.ML.Core.Tests/UnitTests/TestCSharpApi.cs @@ -4,15 +4,14 @@ using Microsoft.ML.Data; using Microsoft.ML.Legacy.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML.EntryPoints; using Microsoft.ML.TestFramework; using System; using System.Collections.Generic; using Xunit; using Xunit.Abstractions; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { #pragma warning disable 612, 618 public class TestCSharpApi : BaseTestClass diff --git a/test/Microsoft.ML.Core.Tests/UnitTests/TestContracts.cs b/test/Microsoft.ML.Core.Tests/UnitTests/TestContracts.cs index ca1315b83b..3a539ce216 100644 --- a/test/Microsoft.ML.Core.Tests/UnitTests/TestContracts.cs +++ b/test/Microsoft.ML.Core.Tests/UnitTests/TestContracts.cs @@ -4,7 +4,7 @@ using System; using Xunit; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { public sealed class TestContracts { diff --git a/test/Microsoft.ML.Core.Tests/UnitTests/TestEarlyStoppingCriteria.cs b/test/Microsoft.ML.Core.Tests/UnitTests/TestEarlyStoppingCriteria.cs index 688287dda2..f4e8eef24b 100644 --- a/test/Microsoft.ML.Core.Tests/UnitTests/TestEarlyStoppingCriteria.cs +++ b/test/Microsoft.ML.Core.Tests/UnitTests/TestEarlyStoppingCriteria.cs @@ -2,12 +2,12 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Internallearn; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Internallearn; using Microsoft.ML.TestFramework; using Xunit; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { public sealed class TestEarlyStoppingCriteria { diff --git a/test/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs b/test/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs index b764eedd17..222ec6dc96 100644 --- a/test/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs +++ b/test/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs @@ -4,21 +4,20 @@ using Microsoft.ML.Data; using Microsoft.ML.Legacy.EntryPoints; -using Microsoft.ML.Runtime.Core.Tests.UnitTests; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Ensemble.EntryPoints; -using Microsoft.ML.Runtime.Ensemble.OutputCombiners; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.EntryPoints.JsonUtils; -using Microsoft.ML.Runtime.ImageAnalytics; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.LightGBM; -using Microsoft.ML.Runtime.Model.Onnx; -using Microsoft.ML.Runtime.TimeSeriesProcessing; +using Microsoft.ML.Core.Tests.UnitTests; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Ensemble.EntryPoints; +using Microsoft.ML.Ensemble.OutputCombiners; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.EntryPoints.JsonUtils; +using Microsoft.ML.ImageAnalytics; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Learners; +using Microsoft.ML.LightGBM; +using Microsoft.ML.Model.Onnx; +using Microsoft.ML.TimeSeriesProcessing; using Microsoft.ML.Trainers; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Trainers.PCA; @@ -39,7 +38,7 @@ using Xunit; using Xunit.Abstractions; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { #pragma warning disable 612 public partial class TestEntryPoints : CoreBaseTestClass @@ -353,7 +352,7 @@ public void EntryPointCatalogCheckDuplicateParams() Env.ComponentCatalog.RegisterAssembly(typeof(ImageLoaderTransform).Assembly); Env.ComponentCatalog.RegisterAssembly(typeof(SymSgdClassificationTrainer).Assembly); Env.ComponentCatalog.RegisterAssembly(typeof(SaveOnnxCommand).Assembly); - Env.ComponentCatalog.RegisterAssembly(typeof(TimeSeriesProcessing.TimeSeriesProcessing).Assembly); + Env.ComponentCatalog.RegisterAssembly(typeof(TimeSeriesProcessingEntryPoints).Assembly); var catalog = Env.ComponentCatalog; @@ -3695,8 +3694,8 @@ public void EntryPointSsaChangePoint() TestEntryPointPipelineRoutine(GetDataPath(Path.Combine("Timeseries", "A4Benchmark-TS1.csv")), "sep=, col=Features:R4:1 header=+", new[] { - "TimeSeriesProcessing.SsaChangePointDetector", - "TimeSeriesProcessing.SsaChangePointDetector", + "TimeSeriesProcessingEntryPoints.SsaChangePointDetector", + "TimeSeriesProcessingEntryPoints.SsaChangePointDetector", }, new[] { @@ -3724,8 +3723,8 @@ public void EntryPointIidSpikeDetector() TestEntryPointPipelineRoutine(GetDataPath(Path.Combine("Timeseries", "real_1.csv")), "sep=, col=Features:R4:1 header=+", new[] { - "TimeSeriesProcessing.IidSpikeDetector", - "TimeSeriesProcessing.IidSpikeDetector", + "TimeSeriesProcessingEntryPoints.IidSpikeDetector", + "TimeSeriesProcessingEntryPoints.IidSpikeDetector", }, new[] { @@ -3748,9 +3747,9 @@ public void EntryPointSsaSpikeDetector() TestEntryPointPipelineRoutine(GetDataPath(Path.Combine("Timeseries", "A4Benchmark-TS2.csv")), "sep=, col=Features:R4:1 header=+", new[] { - "TimeSeriesProcessing.SsaSpikeDetector", - "TimeSeriesProcessing.SsaSpikeDetector", - "TimeSeriesProcessing.SsaSpikeDetector", + "TimeSeriesProcessingEntryPoints.SsaSpikeDetector", + "TimeSeriesProcessingEntryPoints.SsaSpikeDetector", + "TimeSeriesProcessingEntryPoints.SsaSpikeDetector", }, new[] { @@ -3786,7 +3785,7 @@ public void EntryPointPercentileThreshold() TestEntryPointPipelineRoutine(GetDataPath("breast-cancer.txt"), "col=Input:R4:1", new[] { - "TimeSeriesProcessing.PercentileThresholdTransform" + "TimeSeriesProcessingEntryPoints.PercentileThresholdTransform" }, new[] { @@ -3803,7 +3802,7 @@ public void EntryPointPValue() TestEntryPointPipelineRoutine(GetDataPath("breast-cancer.txt"), "col=Input:R4:1", new[] { - "TimeSeriesProcessing.PValueTransform" + "TimeSeriesProcessingEntryPoints.PValueTransform" }, new[] { @@ -3819,10 +3818,10 @@ public void EntryPointSlidingWindow() TestEntryPointPipelineRoutine(GetDataPath("breast-cancer.txt"), "col=Input:R4:1", new[] { - "TimeSeriesProcessing.SlidingWindowTransform", - "TimeSeriesProcessing.SlidingWindowTransform", - "TimeSeriesProcessing.SlidingWindowTransform", - "TimeSeriesProcessing.SlidingWindowTransform", + "TimeSeriesProcessingEntryPoints.SlidingWindowTransform", + "TimeSeriesProcessingEntryPoints.SlidingWindowTransform", + "TimeSeriesProcessingEntryPoints.SlidingWindowTransform", + "TimeSeriesProcessingEntryPoints.SlidingWindowTransform", }, new[] { diff --git a/test/Microsoft.ML.Core.Tests/UnitTests/TestHosts.cs b/test/Microsoft.ML.Core.Tests/UnitTests/TestHosts.cs index 2f1df54285..c17e8e24c7 100644 --- a/test/Microsoft.ML.Core.Tests/UnitTests/TestHosts.cs +++ b/test/Microsoft.ML.Core.Tests/UnitTests/TestHosts.cs @@ -9,11 +9,11 @@ using System.Text; using System.Threading; using System.Threading.Tasks; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Xunit; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { public class TestHosts { diff --git a/test/Microsoft.ML.Core.Tests/UnitTests/TestLoss.cs b/test/Microsoft.ML.Core.Tests/UnitTests/TestLoss.cs index 41fd116b39..18dcfda3c9 100644 --- a/test/Microsoft.ML.Core.Tests/UnitTests/TestLoss.cs +++ b/test/Microsoft.ML.Core.Tests/UnitTests/TestLoss.cs @@ -5,9 +5,9 @@ using Float = System.Single; using System; -using Microsoft.ML.Runtime; +using Microsoft.ML; using Xunit; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { /// /// These are tests of the loss functions in the Learners assembly. diff --git a/test/Microsoft.ML.Core.Tests/UnitTests/TestLruCache.cs b/test/Microsoft.ML.Core.Tests/UnitTests/TestLruCache.cs index 8725e0b1bc..ea1a48d2e2 100644 --- a/test/Microsoft.ML.Core.Tests/UnitTests/TestLruCache.cs +++ b/test/Microsoft.ML.Core.Tests/UnitTests/TestLruCache.cs @@ -4,10 +4,10 @@ using System.Collections.Generic; using System.Linq; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; using Xunit; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { public class TestLruCache { diff --git a/test/Microsoft.ML.Core.Tests/UnitTests/TestModelLoad.cs b/test/Microsoft.ML.Core.Tests/UnitTests/TestModelLoad.cs index 8be5ce9628..30c64bdb13 100644 --- a/test/Microsoft.ML.Core.Tests/UnitTests/TestModelLoad.cs +++ b/test/Microsoft.ML.Core.Tests/UnitTests/TestModelLoad.cs @@ -2,13 +2,13 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.Data; +using Microsoft.ML.Model; using Microsoft.ML.TestFramework; using System.IO; using Xunit; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { public class TestModelLoad { diff --git a/test/Microsoft.ML.Core.Tests/UnitTests/TestVBuffer.cs b/test/Microsoft.ML.Core.Tests/UnitTests/TestVBuffer.cs index 2edbf0a7ff..4c44101d5b 100644 --- a/test/Microsoft.ML.Core.Tests/UnitTests/TestVBuffer.cs +++ b/test/Microsoft.ML.Core.Tests/UnitTests/TestVBuffer.cs @@ -5,12 +5,12 @@ using System; using System.Collections.Generic; using System.Linq; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Numeric; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Numeric; +using Microsoft.ML.RunTests; using Xunit; using Xunit.Abstractions; diff --git a/test/Microsoft.ML.CpuMath.PerformanceTests/AvxPerformanceTests.cs b/test/Microsoft.ML.CpuMath.PerformanceTests/AvxPerformanceTests.cs index 50a3b06fbe..af89929c71 100644 --- a/test/Microsoft.ML.CpuMath.PerformanceTests/AvxPerformanceTests.cs +++ b/test/Microsoft.ML.CpuMath.PerformanceTests/AvxPerformanceTests.cs @@ -5,7 +5,7 @@ using System; using BenchmarkDotNet.Attributes; using BenchmarkDotNet.Running; -using Microsoft.ML.Runtime.Internal.CpuMath; +using Microsoft.ML.Internal.CpuMath; namespace Microsoft.ML.CpuMath.PerformanceTests { diff --git a/test/Microsoft.ML.CpuMath.PerformanceTests/NativePerformanceTests.cs b/test/Microsoft.ML.CpuMath.PerformanceTests/NativePerformanceTests.cs index 92c0cc86db..1e3efb7ee1 100644 --- a/test/Microsoft.ML.CpuMath.PerformanceTests/NativePerformanceTests.cs +++ b/test/Microsoft.ML.CpuMath.PerformanceTests/NativePerformanceTests.cs @@ -5,8 +5,8 @@ using System; using BenchmarkDotNet.Attributes; using BenchmarkDotNet.Running; -using Microsoft.ML.Runtime.Internal.CpuMath; -using Microsoft.ML.Runtime.Internal.CpuMath.Core; +using Microsoft.ML.Internal.CpuMath; +using Microsoft.ML.Internal.CpuMath.Core; namespace Microsoft.ML.CpuMath.PerformanceTests { diff --git a/test/Microsoft.ML.CpuMath.PerformanceTests/PerformanceTests.cs b/test/Microsoft.ML.CpuMath.PerformanceTests/PerformanceTests.cs index d2dcf3cfff..a03e1cc95b 100644 --- a/test/Microsoft.ML.CpuMath.PerformanceTests/PerformanceTests.cs +++ b/test/Microsoft.ML.CpuMath.PerformanceTests/PerformanceTests.cs @@ -5,7 +5,7 @@ using System; using BenchmarkDotNet.Attributes; using BenchmarkDotNet.Running; -using Microsoft.ML.Runtime.Internal.CpuMath; +using Microsoft.ML.Internal.CpuMath; namespace Microsoft.ML.CpuMath.PerformanceTests { diff --git a/test/Microsoft.ML.CpuMath.PerformanceTests/SsePerformanceTests.cs b/test/Microsoft.ML.CpuMath.PerformanceTests/SsePerformanceTests.cs index e079e8bd7e..0c48ea04c6 100644 --- a/test/Microsoft.ML.CpuMath.PerformanceTests/SsePerformanceTests.cs +++ b/test/Microsoft.ML.CpuMath.PerformanceTests/SsePerformanceTests.cs @@ -5,7 +5,7 @@ using System; using BenchmarkDotNet.Attributes; using BenchmarkDotNet.Running; -using Microsoft.ML.Runtime.Internal.CpuMath; +using Microsoft.ML.Internal.CpuMath; namespace Microsoft.ML.CpuMath.PerformanceTests { diff --git a/test/Microsoft.ML.CpuMath.UnitTests.netcoreapp/UnitTests.cs b/test/Microsoft.ML.CpuMath.UnitTests.netcoreapp/UnitTests.cs index 7e2f1e5cc6..d8d7ebbcb2 100644 --- a/test/Microsoft.ML.CpuMath.UnitTests.netcoreapp/UnitTests.cs +++ b/test/Microsoft.ML.CpuMath.UnitTests.netcoreapp/UnitTests.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Internal.CpuMath; +using Microsoft.ML.Internal.CpuMath; using System; using System.Collections.Generic; using Xunit; diff --git a/test/Microsoft.ML.FSharp.Tests/SmokeTests.fs b/test/Microsoft.ML.FSharp.Tests/SmokeTests.fs index a5a6eb0ce7..b6060cfc9b 100644 --- a/test/Microsoft.ML.FSharp.Tests/SmokeTests.fs +++ b/test/Microsoft.ML.FSharp.Tests/SmokeTests.fs @@ -81,14 +81,14 @@ module SmokeTest1 = let _load = [ typeof; typeof; - typeof] // ML.EntryPoints + typeof] // ML.EntryPoints let testDataPath = __SOURCE_DIRECTORY__ + @"/../data/wikipedia-detox-250-line-data.tsv" let pipeline = Legacy.LearningPipeline() pipeline.Add( - TextLoader(testDataPath).CreateFrom( + Microsoft.ML.Legacy.Data.TextLoader(testDataPath).CreateFrom( Arguments = TextLoaderArguments( HasHeader = true, @@ -149,14 +149,14 @@ module SmokeTest2 = let _load = [ typeof; typeof; - typeof] // ML.EntryPoints + typeof] // ML.EntryPoints let testDataPath = __SOURCE_DIRECTORY__ + @"/../data/wikipedia-detox-250-line-data.tsv" let pipeline = Legacy.LearningPipeline() pipeline.Add( - TextLoader(testDataPath).CreateFrom( + Microsoft.ML.Legacy.Data.TextLoader(testDataPath).CreateFrom( Arguments = TextLoaderArguments( HasHeader = true, @@ -214,14 +214,14 @@ module SmokeTest3 = let _load = [ typeof; typeof; - typeof] // ML.EntryPoints + typeof] // ML.EntryPoints let testDataPath = __SOURCE_DIRECTORY__ + @"/../data/wikipedia-detox-250-line-data.tsv" let pipeline = Legacy.LearningPipeline() pipeline.Add( - TextLoader(testDataPath).CreateFrom( + Microsoft.ML.Legacy.Data.TextLoader(testDataPath).CreateFrom( Arguments = TextLoaderArguments( HasHeader = true, diff --git a/test/Microsoft.ML.OnnxTransformTest/DnnImageFeaturizerTest.cs b/test/Microsoft.ML.OnnxTransformTest/DnnImageFeaturizerTest.cs index 5b86c0bd85..e291ae35b5 100644 --- a/test/Microsoft.ML.OnnxTransformTest/DnnImageFeaturizerTest.cs +++ b/test/Microsoft.ML.OnnxTransformTest/DnnImageFeaturizerTest.cs @@ -1,15 +1,14 @@ -// Licensed to the .NET 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. using Microsoft.ML.Core.Data; using Microsoft.ML.Data; using Microsoft.ML.OnnxTransform.StaticPipe; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.ImageAnalytics; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML; +using Microsoft.ML.ImageAnalytics; +using Microsoft.ML.Model; +using Microsoft.ML.RunTests; using Microsoft.ML.Transforms; using System; using System.Collections.Generic; diff --git a/test/Microsoft.ML.OnnxTransformTest/OnnxTransformTests.cs b/test/Microsoft.ML.OnnxTransformTest/OnnxTransformTests.cs index 0542aee0b2..1cd7894a35 100644 --- a/test/Microsoft.ML.OnnxTransformTest/OnnxTransformTests.cs +++ b/test/Microsoft.ML.OnnxTransformTest/OnnxTransformTests.cs @@ -5,12 +5,11 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; using Microsoft.ML.OnnxTransform.StaticPipe; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.ImageAnalytics; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML; +using Microsoft.ML.ImageAnalytics; +using Microsoft.ML.Model; +using Microsoft.ML.RunTests; +using Microsoft.ML.Tools; using Microsoft.ML.Transforms; using System; using System.Collections.Generic; diff --git a/test/Microsoft.ML.Predictor.Tests/CmdLine/CmdIndenterTest.cs b/test/Microsoft.ML.Predictor.Tests/CmdLine/CmdIndenterTest.cs index 76fa11fa5f..f3be885813 100644 --- a/test/Microsoft.ML.Predictor.Tests/CmdLine/CmdIndenterTest.cs +++ b/test/Microsoft.ML.Predictor.Tests/CmdLine/CmdIndenterTest.cs @@ -2,14 +2,14 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; using System; using System.CodeDom.Compiler; using System.IO; using Xunit; using Xunit.Abstractions; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { public sealed partial class CmdIndenterTests : BaseTestBaseline { @@ -39,7 +39,7 @@ private string GetResText(string resName) internal void Run() { - string text = GetResText("Microsoft.ML.Runtime.RunTests.CmdLine.IndenterTestInput.txt"); + string text = GetResText("Microsoft.ML.RunTests.CmdLine.IndenterTestInput.txt"); string outName = "CmdIndenterOutput.txt"; string outPath = DeleteOutputPath("CmdLine", outName); diff --git a/test/Microsoft.ML.Predictor.Tests/CmdLine/CmdLine.cs b/test/Microsoft.ML.Predictor.Tests/CmdLine/CmdLine.cs index 0f11af8ae0..b591f49e56 100644 --- a/test/Microsoft.ML.Predictor.Tests/CmdLine/CmdLine.cs +++ b/test/Microsoft.ML.Predictor.Tests/CmdLine/CmdLine.cs @@ -10,18 +10,18 @@ using System.IO; using System.Linq; using System.Text; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; using Xunit; using Xunit.Abstractions; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { public sealed class CmdLine : BaseTestBaseline { - private const string ResourcePrefix = "Microsoft.ML.Runtime.RunTests.CmdLine."; + private const string ResourcePrefix = "Microsoft.ML.RunTests.CmdLine."; public CmdLine(ITestOutputHelper helper) : base(helper) diff --git a/test/Microsoft.ML.Predictor.Tests/CmdLine/CmdLineReverseTest.cs b/test/Microsoft.ML.Predictor.Tests/CmdLine/CmdLineReverseTest.cs index 51330648ee..2ae5ac834c 100644 --- a/test/Microsoft.ML.Predictor.Tests/CmdLine/CmdLineReverseTest.cs +++ b/test/Microsoft.ML.Predictor.Tests/CmdLine/CmdLineReverseTest.cs @@ -2,13 +2,13 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; using System.Reflection; using Xunit; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { public class CmdLineReverseTests { diff --git a/test/Microsoft.ML.Predictor.Tests/CompareBaselines.cs b/test/Microsoft.ML.Predictor.Tests/CompareBaselines.cs index f6f9eec83d..f40e7ecf5d 100644 --- a/test/Microsoft.ML.Predictor.Tests/CompareBaselines.cs +++ b/test/Microsoft.ML.Predictor.Tests/CompareBaselines.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; using System; using System.IO; using System.Linq; @@ -10,7 +10,7 @@ using Xunit; using Xunit.Abstractions; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { /// ///This is a test class for TestPredictorMainTest and is intended diff --git a/test/Microsoft.ML.Predictor.Tests/Global.cs b/test/Microsoft.ML.Predictor.Tests/Global.cs index af4292e6a9..1beecb62e1 100644 --- a/test/Microsoft.ML.Predictor.Tests/Global.cs +++ b/test/Microsoft.ML.Predictor.Tests/Global.cs @@ -2,10 +2,10 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Internal.Internallearn.Test; +using Microsoft.ML.Internal.Internallearn.Test; using Xunit; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { public sealed class Global { diff --git a/test/Microsoft.ML.Predictor.Tests/ResultProcessor/TestResultProcessor.cs b/test/Microsoft.ML.Predictor.Tests/ResultProcessor/TestResultProcessor.cs index 1b250b645c..40002c1caf 100644 --- a/test/Microsoft.ML.Predictor.Tests/ResultProcessor/TestResultProcessor.cs +++ b/test/Microsoft.ML.Predictor.Tests/ResultProcessor/TestResultProcessor.cs @@ -8,14 +8,14 @@ using Xunit.Abstractions; using Xunit; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { // REVIEW: The data files need to be ported. Are these tests even needed? public sealed class TestResultProcessor : BaseTestPredictors { public static StreamWriter OutFile; public const string SubDirectory = "ResultProcessor"; - private const string TestDataPrefix = "Microsoft.ML.Runtime.RunTests.ResultProcessor.TestData."; + private const string TestDataPrefix = "Microsoft.ML.RunTests.ResultProcessor.TestData."; private const string TestDataOutPath = @"ResultProcessor\TestData"; public TestResultProcessor(ITestOutputHelper helper) : base(helper) diff --git a/test/Microsoft.ML.Predictor.Tests/Test-API.cs b/test/Microsoft.ML.Predictor.Tests/Test-API.cs index f74a6558dc..776ef996bf 100644 --- a/test/Microsoft.ML.Predictor.Tests/Test-API.cs +++ b/test/Microsoft.ML.Predictor.Tests/Test-API.cs @@ -8,14 +8,14 @@ using System.Collections.Generic; using System.IO; using System.Threading; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.Model; - -namespace Microsoft.ML.Runtime.Internal.Internallearn.Test +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Learners; +using Microsoft.ML.Model; + +namespace Microsoft.ML.Internal.Internallearn.Test { #if OLD_TESTS // REVIEW: Should any of this be ported? using TestLearners = TestLearnersBase; diff --git a/test/Microsoft.ML.Predictor.Tests/TestConcurrency.cs b/test/Microsoft.ML.Predictor.Tests/TestConcurrency.cs index 8b62205f05..a2a428e308 100644 --- a/test/Microsoft.ML.Predictor.Tests/TestConcurrency.cs +++ b/test/Microsoft.ML.Predictor.Tests/TestConcurrency.cs @@ -2,11 +2,11 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; using Xunit; using Xunit.Abstractions; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { public sealed class TestConcurrency : BaseTestPredictors { diff --git a/test/Microsoft.ML.Predictor.Tests/TestCreateInstances.cs b/test/Microsoft.ML.Predictor.Tests/TestCreateInstances.cs index 8468c07d3b..90dfd3a417 100644 --- a/test/Microsoft.ML.Predictor.Tests/TestCreateInstances.cs +++ b/test/Microsoft.ML.Predictor.Tests/TestCreateInstances.cs @@ -5,11 +5,11 @@ using Float = System.Single; using System; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Trainers.PCA; -namespace Microsoft.ML.Runtime.Internal.Internallearn.Test +namespace Microsoft.ML.Internal.Internallearn.Test { #if OLD_TESTS // REVIEW: Does any of this need ported? public class CreateInstancesTests : BaseTestBaseline @@ -159,7 +159,7 @@ private void CompareInstances(TlcTextInstances instances1, TlcTextInstances inst [Fact, TestCategory("CreateInstances"), TestCategory("FeatureTransformer")] public void TestPcaTransform() { - // Force Microsoft.ML.Runtime.PCA assembly to be loaded into the AppDomain so + // Force Microsoft.ML.PCA assembly to be loaded into the AppDomain so // ReflectionUtils.FindClassCore does not return null when called by ReflectionUtils.CreateInstance Assert.AreEqual(typeof(PCAPredictor).Name, "PCAPredictor"); diff --git a/test/Microsoft.ML.Predictor.Tests/TestCrossValidation.cs b/test/Microsoft.ML.Predictor.Tests/TestCrossValidation.cs index e9f1a6adb6..4bf444725b 100644 --- a/test/Microsoft.ML.Predictor.Tests/TestCrossValidation.cs +++ b/test/Microsoft.ML.Predictor.Tests/TestCrossValidation.cs @@ -5,10 +5,10 @@ using Float = System.Single; using System; -using Microsoft.ML.Runtime.Numeric; -using Microsoft.ML.Runtime.CommandLine; +using Microsoft.ML.Numeric; +using Microsoft.ML.CommandLine; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { using TestLearners = TestLearnersBase; diff --git a/test/Microsoft.ML.Predictor.Tests/TestIniModels.cs b/test/Microsoft.ML.Predictor.Tests/TestIniModels.cs index 9f8b423de6..f2a2eb83c8 100644 --- a/test/Microsoft.ML.Predictor.Tests/TestIniModels.cs +++ b/test/Microsoft.ML.Predictor.Tests/TestIniModels.cs @@ -6,10 +6,10 @@ using System.Collections.Generic; using System.IO; using System.Threading; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { using TestLearners = TestLearnersBase; diff --git a/test/Microsoft.ML.Predictor.Tests/TestParallelFasttreeInterface.cs b/test/Microsoft.ML.Predictor.Tests/TestParallelFasttreeInterface.cs index ef45fd8bfa..7094aaacba 100644 --- a/test/Microsoft.ML.Predictor.Tests/TestParallelFasttreeInterface.cs +++ b/test/Microsoft.ML.Predictor.Tests/TestParallelFasttreeInterface.cs @@ -3,17 +3,17 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Runtime; +using Microsoft.ML; using Microsoft.ML.Trainers.FastTree.Internal; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.RunTests; using Xunit; using Xunit.Abstractions; [assembly: LoadableClass(typeof(FastTreeParallelInterfaceChecker), null, typeof(Microsoft.ML.Trainers.FastTree.SignatureParallelTrainer), "FastTreeParallelInterfaceChecker")] -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { using SplitInfo = Microsoft.ML.Trainers.FastTree.Internal.LeastSquaresRegressionTreeLearner.SplitInfo; using LeafSplitCandidates = Microsoft.ML.Trainers.FastTree.Internal.LeastSquaresRegressionTreeLearner.LeafSplitCandidates; diff --git a/test/Microsoft.ML.Predictor.Tests/TestPredictors.cs b/test/Microsoft.ML.Predictor.Tests/TestPredictors.cs index 35558a7e0a..efcc52f20c 100644 --- a/test/Microsoft.ML.Predictor.Tests/TestPredictors.cs +++ b/test/Microsoft.ML.Predictor.Tests/TestPredictors.cs @@ -7,15 +7,15 @@ using System.IO; using Float = System.Single; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { - using Microsoft.ML.Runtime; - using Microsoft.ML.Runtime.Data; - using Microsoft.ML.Runtime.EntryPoints; - using Microsoft.ML.Runtime.Ensemble; - using Microsoft.ML.Runtime.Internal.Utilities; - using Microsoft.ML.Runtime.Learners; - using Microsoft.ML.Runtime.LightGBM; + using Microsoft.ML; + using Microsoft.ML.Data; + using Microsoft.ML.EntryPoints; + using Microsoft.ML.Ensemble; + using Microsoft.ML.Internal.Utilities; + using Microsoft.ML.Learners; + using Microsoft.ML.LightGBM; using Microsoft.ML.TestFramework; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Trainers.FastTree.Internal; @@ -1422,8 +1422,8 @@ private OlsLinearRegressionPredictor WriteReloadOlsPredictor(OlsLinearRegression { PredictorUtils.Save(mem, pred, null, null, null, useFileSystem: true); mem.Seek(0, SeekOrigin.Begin); - Microsoft.ML.Runtime.Model.IDataModel model; - Microsoft.ML.Runtime.Model.IDataStats stats; + Microsoft.ML.Model.IDataModel model; + Microsoft.ML.Model.IDataStats stats; return (OlsLinearRegressionPredictor)PredictorUtils.LoadPredictor(out model, out stats, mem, false); } } diff --git a/test/Microsoft.ML.Predictor.Tests/TestTransposer.cs b/test/Microsoft.ML.Predictor.Tests/TestTransposer.cs index 4bf9001f3d..d80d6c136b 100644 --- a/test/Microsoft.ML.Predictor.Tests/TestTransposer.cs +++ b/test/Microsoft.ML.Predictor.Tests/TestTransposer.cs @@ -5,14 +5,14 @@ using System; using System.Collections.Generic; using System.IO; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Data; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Utilities; using Microsoft.ML.TestFramework; using Xunit; using Xunit.Abstractions; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { public sealed class TestTransposer : TestDataPipeBase { diff --git a/test/Microsoft.ML.Predictor.Tests/TestTrivialPredictors.cs b/test/Microsoft.ML.Predictor.Tests/TestTrivialPredictors.cs index 17cabac05c..0dc707e0ed 100644 --- a/test/Microsoft.ML.Predictor.Tests/TestTrivialPredictors.cs +++ b/test/Microsoft.ML.Predictor.Tests/TestTrivialPredictors.cs @@ -6,13 +6,13 @@ using System; using System.IO; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Internallearn.Test; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML; +using Microsoft.ML.Learners; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Internallearn.Test; +using Microsoft.ML.Model; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { #if OLD_TESTS // REVIEW: Port these tests. /// diff --git a/test/Microsoft.ML.StaticPipelineTesting/ImageAnalyticsTests.cs b/test/Microsoft.ML.StaticPipelineTesting/ImageAnalyticsTests.cs index 3d34a20584..cc2764d0f7 100644 --- a/test/Microsoft.ML.StaticPipelineTesting/ImageAnalyticsTests.cs +++ b/test/Microsoft.ML.StaticPipelineTesting/ImageAnalyticsTests.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.ImageAnalytics; +using Microsoft.ML.Data; +using Microsoft.ML.ImageAnalytics; using Xunit; using Xunit.Abstractions; diff --git a/test/Microsoft.ML.StaticPipelineTesting/StaticPipeFakes.cs b/test/Microsoft.ML.StaticPipelineTesting/StaticPipeFakes.cs index 552f4b6391..145ed514f4 100644 --- a/test/Microsoft.ML.StaticPipelineTesting/StaticPipeFakes.cs +++ b/test/Microsoft.ML.StaticPipelineTesting/StaticPipeFakes.cs @@ -1,6 +1,6 @@ using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.StaticPipe; using Microsoft.ML.StaticPipe.Runtime; using System; diff --git a/test/Microsoft.ML.StaticPipelineTesting/StaticPipeTests.cs b/test/Microsoft.ML.StaticPipelineTesting/StaticPipeTests.cs index 9bf5c86e77..90446f9150 100644 --- a/test/Microsoft.ML.StaticPipelineTesting/StaticPipeTests.cs +++ b/test/Microsoft.ML.StaticPipelineTesting/StaticPipeTests.cs @@ -4,10 +4,9 @@ using Microsoft.ML.Data; using Microsoft.ML.HalLearners.StaticPipe; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.RunTests; using Microsoft.ML.StaticPipe; using Microsoft.ML.TestFramework; using Microsoft.ML.Transforms; diff --git a/test/Microsoft.ML.StaticPipelineTesting/Training.cs b/test/Microsoft.ML.StaticPipelineTesting/Training.cs index efa48ed08e..56cc035241 100644 --- a/test/Microsoft.ML.StaticPipelineTesting/Training.cs +++ b/test/Microsoft.ML.StaticPipelineTesting/Training.cs @@ -1,16 +1,16 @@ -// Licensed to the .NET 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. using Microsoft.ML.LightGBM.StaticPipe; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.FactorizationMachine; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.LightGBM; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.FactorizationMachine; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Learners; +using Microsoft.ML.LightGBM; +using Microsoft.ML.RunTests; using Microsoft.ML.StaticPipe; using Microsoft.ML.Trainers; using Microsoft.ML.Trainers.FastTree; diff --git a/test/Microsoft.ML.Sweeper.Tests/SweeperTest.cs b/test/Microsoft.ML.Sweeper.Tests/SweeperTest.cs index 1cd0065703..28968fcabe 100644 --- a/test/Microsoft.ML.Sweeper.Tests/SweeperTest.cs +++ b/test/Microsoft.ML.Sweeper.Tests/SweeperTest.cs @@ -2,11 +2,11 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.Sweeper; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.RunTests; +using Microsoft.ML.Sweeper; using System; using System.IO; using Xunit; diff --git a/test/Microsoft.ML.Sweeper.Tests/TestSweeper.cs b/test/Microsoft.ML.Sweeper.Tests/TestSweeper.cs index 0718a7edde..1ea3a5cb3a 100644 --- a/test/Microsoft.ML.Sweeper.Tests/TestSweeper.cs +++ b/test/Microsoft.ML.Sweeper.Tests/TestSweeper.cs @@ -2,14 +2,14 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.Sweeper; -using Microsoft.ML.Runtime.Sweeper.Algorithms; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.RunTests; +using Microsoft.ML.Sweeper; +using Microsoft.ML.Sweeper.Algorithms; using System; using System.Collections.Generic; using System.Globalization; diff --git a/test/Microsoft.ML.TestFramework/BaseTestBaseline.cs b/test/Microsoft.ML.TestFramework/BaseTestBaseline.cs index c51a6c71f3..92ac41e1d9 100644 --- a/test/Microsoft.ML.TestFramework/BaseTestBaseline.cs +++ b/test/Microsoft.ML.TestFramework/BaseTestBaseline.cs @@ -2,9 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Tools; using Microsoft.ML.TestFramework; using System; using System.Collections.Generic; @@ -15,7 +15,7 @@ using Xunit; using Xunit.Abstractions; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { /// /// This is a base test class designed to support baseline comparison. diff --git a/test/Microsoft.ML.TestFramework/BaseTestClass.cs b/test/Microsoft.ML.TestFramework/BaseTestClass.cs index 034565592e..ec5dfdc67c 100644 --- a/test/Microsoft.ML.TestFramework/BaseTestClass.cs +++ b/test/Microsoft.ML.TestFramework/BaseTestClass.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Internal.Internallearn.Test; +using Microsoft.ML.Internal.Internallearn.Test; using System; using System.Globalization; using System.IO; diff --git a/test/Microsoft.ML.TestFramework/BaseTestPredictorsMaml.cs b/test/Microsoft.ML.TestFramework/BaseTestPredictorsMaml.cs index cf0303bc05..57b2983f44 100644 --- a/test/Microsoft.ML.TestFramework/BaseTestPredictorsMaml.cs +++ b/test/Microsoft.ML.TestFramework/BaseTestPredictorsMaml.cs @@ -7,9 +7,9 @@ using System.Linq; using System.Runtime.InteropServices; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { - using ResultProcessor = Microsoft.ML.Runtime.Internal.Internallearn.ResultProcessor.ResultProcessor; + using ResultProcessor = Microsoft.ML.Internal.Internallearn.ResultProcessor.ResultProcessor; /// /// This is a base test class designed to support running trainings and related diff --git a/test/Microsoft.ML.TestFramework/BytesStreamSource.cs b/test/Microsoft.ML.TestFramework/BytesStreamSource.cs index d77c99f848..4e63cc9402 100644 --- a/test/Microsoft.ML.TestFramework/BytesStreamSource.cs +++ b/test/Microsoft.ML.TestFramework/BytesStreamSource.cs @@ -4,8 +4,8 @@ using System.IO; using System.Text; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; namespace Microsoft.ML.TestFramework { diff --git a/test/Microsoft.ML.TestFramework/CopyAction.cs b/test/Microsoft.ML.TestFramework/CopyAction.cs index b7ec2327db..eb1dcf26ef 100644 --- a/test/Microsoft.ML.TestFramework/CopyAction.cs +++ b/test/Microsoft.ML.TestFramework/CopyAction.cs @@ -5,7 +5,7 @@ using System.IO; using System.Threading.Tasks; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { public class CopyAction { diff --git a/test/Microsoft.ML.TestFramework/DataPipe/Parquet.cs b/test/Microsoft.ML.TestFramework/DataPipe/Parquet.cs index eeebdaf6d7..e12dfe2c54 100644 --- a/test/Microsoft.ML.TestFramework/DataPipe/Parquet.cs +++ b/test/Microsoft.ML.TestFramework/DataPipe/Parquet.cs @@ -2,11 +2,11 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; using System; using Xunit; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { public sealed partial class TestParquet : TestDataPipeBase { diff --git a/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipe.cs b/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipe.cs index fe51159d25..ba616f146a 100644 --- a/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipe.cs +++ b/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipe.cs @@ -2,9 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Conversions; using Microsoft.ML.Transforms.Text; @@ -14,7 +14,7 @@ using Xunit; using Float = System.Single; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { public sealed partial class TestDataPipe : TestDataPipeBase { diff --git a/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipeBase.cs b/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipeBase.cs index f7d8170ad7..e9c870ef56 100644 --- a/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipeBase.cs +++ b/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipeBase.cs @@ -4,11 +4,10 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; using Microsoft.ML.TestFramework; using System; using System.Collections.Generic; @@ -17,7 +16,7 @@ using System.Reflection; using Xunit; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { public abstract partial class TestDataPipeBase : TestDataViewBase { diff --git a/test/Microsoft.ML.TestFramework/Datasets.cs b/test/Microsoft.ML.TestFramework/Datasets.cs index 3a1f5df3be..03b66f9788 100644 --- a/test/Microsoft.ML.TestFramework/Datasets.cs +++ b/test/Microsoft.ML.TestFramework/Datasets.cs @@ -2,10 +2,10 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; using System; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { public class TestDataset { diff --git a/test/Microsoft.ML.TestFramework/EnvironmentExtensions.cs b/test/Microsoft.ML.TestFramework/EnvironmentExtensions.cs index b25c376420..bb47e4a532 100644 --- a/test/Microsoft.ML.TestFramework/EnvironmentExtensions.cs +++ b/test/Microsoft.ML.TestFramework/EnvironmentExtensions.cs @@ -2,11 +2,11 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Ensemble; -using Microsoft.ML.Runtime.EntryPoints; -using Microsoft.ML.Runtime.Learners; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Ensemble; +using Microsoft.ML.EntryPoints; +using Microsoft.ML.Learners; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Trainers.KMeans; using Microsoft.ML.Trainers.PCA; diff --git a/test/Microsoft.ML.TestFramework/GlobalBase.cs b/test/Microsoft.ML.TestFramework/GlobalBase.cs index ecb185b625..701d6bd4e2 100644 --- a/test/Microsoft.ML.TestFramework/GlobalBase.cs +++ b/test/Microsoft.ML.TestFramework/GlobalBase.cs @@ -14,7 +14,7 @@ using System.Runtime.InteropServices; using Xunit; -namespace Microsoft.ML.Runtime.Internal.Internallearn.Test +namespace Microsoft.ML.Internal.Internallearn.Test { internal static class GlobalBase { diff --git a/test/Microsoft.ML.TestFramework/Learners.cs b/test/Microsoft.ML.TestFramework/Learners.cs index fd0e7d6aaa..863fbfa9d3 100644 --- a/test/Microsoft.ML.TestFramework/Learners.cs +++ b/test/Microsoft.ML.TestFramework/Learners.cs @@ -3,11 +3,11 @@ // See the LICENSE file in the project root for more information. using System.Text; -using Microsoft.ML.Runtime.CommandLine; +using Microsoft.ML.CommandLine; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.TestFramework; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { //=========================== Binary classifiers ==================== public class PredictorAndArgs diff --git a/test/Microsoft.ML.TestFramework/ModelHelper.cs b/test/Microsoft.ML.TestFramework/ModelHelper.cs index ff5e42f8a1..73370065c4 100644 --- a/test/Microsoft.ML.TestFramework/ModelHelper.cs +++ b/test/Microsoft.ML.TestFramework/ModelHelper.cs @@ -3,10 +3,10 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Legacy.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.EntryPoints; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Data; +using Microsoft.ML.EntryPoints; using System.IO; namespace Microsoft.ML.TestFramework @@ -44,27 +44,27 @@ public static IDataView GetKcHouseDataView(string dataPath) return s_environment.Data.ReadFromTextFile(dataPath, columns: new[] { - new Runtime.Data.TextLoader.Column("Id", Runtime.Data.DataKind.TX, 0), - new Runtime.Data.TextLoader.Column("Date", Runtime.Data.DataKind.TX, 1), - new Runtime.Data.TextLoader.Column("Label", Runtime.Data.DataKind.R4, 2), - new Runtime.Data.TextLoader.Column("BedRooms", Runtime.Data.DataKind.R4, 3), - new Runtime.Data.TextLoader.Column("BathRooms", Runtime.Data.DataKind.R4, 4), - new Runtime.Data.TextLoader.Column("SqftLiving", Runtime.Data.DataKind.R4, 5), - new Runtime.Data.TextLoader.Column("SqftLot", Runtime.Data.DataKind.R4, 6), - new Runtime.Data.TextLoader.Column("Floors", Runtime.Data.DataKind.R4, 7), - new Runtime.Data.TextLoader.Column("WaterFront", Runtime.Data.DataKind.R4, 8), - new Runtime.Data.TextLoader.Column("View", Runtime.Data.DataKind.R4, 9), - new Runtime.Data.TextLoader.Column("Condition", Runtime.Data.DataKind.R4, 10), - new Runtime.Data.TextLoader.Column("Grade", Runtime.Data.DataKind.R4, 11), - new Runtime.Data.TextLoader.Column("SqftAbove", Runtime.Data.DataKind.R4, 12), - new Runtime.Data.TextLoader.Column("SqftBasement", Runtime.Data.DataKind.R4, 13), - new Runtime.Data.TextLoader.Column("YearBuilt", Runtime.Data.DataKind.R4, 14), - new Runtime.Data.TextLoader.Column("YearRenovated", Runtime.Data.DataKind.R4, 15), - new Runtime.Data.TextLoader.Column("Zipcode", Runtime.Data.DataKind.R4, 16), - new Runtime.Data.TextLoader.Column("Lat", Runtime.Data.DataKind.R4, 17), - new Runtime.Data.TextLoader.Column("Long", Runtime.Data.DataKind.R4, 18), - new Runtime.Data.TextLoader.Column("SqftLiving15", Runtime.Data.DataKind.R4, 19), - new Runtime.Data.TextLoader.Column("SqftLot15", Runtime.Data.DataKind.R4, 20) + new Data.TextLoader.Column("Id", Data.DataKind.TX, 0), + new Data.TextLoader.Column("Date", Data.DataKind.TX, 1), + new Data.TextLoader.Column("Label", Data.DataKind.R4, 2), + new Data.TextLoader.Column("BedRooms", Data.DataKind.R4, 3), + new Data.TextLoader.Column("BathRooms", Data.DataKind.R4, 4), + new Data.TextLoader.Column("SqftLiving", Data.DataKind.R4, 5), + new Data.TextLoader.Column("SqftLot", Data.DataKind.R4, 6), + new Data.TextLoader.Column("Floors", Data.DataKind.R4, 7), + new Data.TextLoader.Column("WaterFront", Data.DataKind.R4, 8), + new Data.TextLoader.Column("View", Data.DataKind.R4, 9), + new Data.TextLoader.Column("Condition", Data.DataKind.R4, 10), + new Data.TextLoader.Column("Grade", Data.DataKind.R4, 11), + new Data.TextLoader.Column("SqftAbove", Data.DataKind.R4, 12), + new Data.TextLoader.Column("SqftBasement", Data.DataKind.R4, 13), + new Data.TextLoader.Column("YearBuilt", Data.DataKind.R4, 14), + new Data.TextLoader.Column("YearRenovated", Data.DataKind.R4, 15), + new Data.TextLoader.Column("Zipcode", Data.DataKind.R4, 16), + new Data.TextLoader.Column("Lat", Data.DataKind.R4, 17), + new Data.TextLoader.Column("Long", Data.DataKind.R4, 18), + new Data.TextLoader.Column("SqftLiving15", Data.DataKind.R4, 19), + new Data.TextLoader.Column("SqftLot15", Data.DataKind.R4, 20) }, hasHeader: true, separatorChar: ',' diff --git a/test/Microsoft.ML.TestFramework/SubComponent.cs b/test/Microsoft.ML.TestFramework/SubComponent.cs index 5a28502a36..5ef3a8d360 100644 --- a/test/Microsoft.ML.TestFramework/SubComponent.cs +++ b/test/Microsoft.ML.TestFramework/SubComponent.cs @@ -4,9 +4,9 @@ using System; using System.Text; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.CommandLine; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML; +using Microsoft.ML.CommandLine; +using Microsoft.ML.Internal.Utilities; namespace Microsoft.ML.TestFramework { diff --git a/test/Microsoft.ML.TestFramework/TestCommandBase.cs b/test/Microsoft.ML.TestFramework/TestCommandBase.cs index 8d995c8f33..4e253e2020 100644 --- a/test/Microsoft.ML.TestFramework/TestCommandBase.cs +++ b/test/Microsoft.ML.TestFramework/TestCommandBase.cs @@ -9,16 +9,16 @@ using System.Runtime.InteropServices; using System.Threading; using System.Threading.Tasks; -using Microsoft.ML.Runtime.Command; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML.Command; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.Tools; using Microsoft.ML.TestFramework; using Xunit; using Xunit.Abstractions; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { public abstract partial class TestCommandBase : TestDataViewBase { diff --git a/test/Microsoft.ML.TestFramework/TestInitialization.cs b/test/Microsoft.ML.TestFramework/TestInitialization.cs index ba501841f7..bfff800ef1 100644 --- a/test/Microsoft.ML.TestFramework/TestInitialization.cs +++ b/test/Microsoft.ML.TestFramework/TestInitialization.cs @@ -5,7 +5,7 @@ using Xunit; using Xunit.Abstractions; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { // The Xunit test framework requires the per-test initialization be implemented // as the test class constructor, and per-test clean-up be implemented in Dispose() @@ -241,7 +241,7 @@ public TestResultProcessor(ITestOutputHelper helper) } } -namespace Microsoft.ML.Runtime.RunTests.RServerScoring +namespace Microsoft.ML.RunTests.RServerScoring { public sealed partial class TestRServerScoringLibrary : TestDataViewBase diff --git a/test/Microsoft.ML.TestFramework/TestSparseDataView.cs b/test/Microsoft.ML.TestFramework/TestSparseDataView.cs index cb971e3be9..104907aa98 100644 --- a/test/Microsoft.ML.TestFramework/TestSparseDataView.cs +++ b/test/Microsoft.ML.TestFramework/TestSparseDataView.cs @@ -3,13 +3,11 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using System; using Xunit; using Xunit.Abstractions; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { public sealed class TestSparseDataView : TestDataViewBase { diff --git a/test/Microsoft.ML.Tests/CSharpCodeGen.cs b/test/Microsoft.ML.Tests/CSharpCodeGen.cs index a2f2fa7459..f656212d81 100644 --- a/test/Microsoft.ML.Tests/CSharpCodeGen.cs +++ b/test/Microsoft.ML.Tests/CSharpCodeGen.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.RunTests; using System.IO; using Xunit; using Xunit.Abstractions; @@ -19,14 +19,14 @@ public CSharpCodeGen(ITestOutputHelper output) : base(output) public void RegenerateCSharpApi() { var basePath = GetDataPath("../../src/Microsoft.ML.Legacy/CSharpApi.cs"); - Runtime.Tools.Maml.Main(new[] { $"? generator=cs{{csFilename={basePath}}}" }); + Tools.Maml.Main(new[] { $"? generator=cs{{csFilename={basePath}}}" }); } [ConditionalFact(typeof(BaseTestBaseline), nameof(LessThanNetCore30OrNotNetCore))] public void TestGeneratedCSharpAPI() { var dataPath = GetOutputPath("Api.cs"); - Runtime.Tools.Maml.Main(new[] { $"? generator=cs{{csFilename={dataPath}}}" }); + Tools.Maml.Main(new[] { $"? generator=cs{{csFilename={dataPath}}}" }); var basePath = GetDataPath("../../src/Microsoft.ML.Legacy/CSharpApi.cs"); using (StreamReader baseline = OpenReader(basePath)) diff --git a/test/Microsoft.ML.Tests/CachingTests.cs b/test/Microsoft.ML.Tests/CachingTests.cs index de9fc59e54..0493ec4a1b 100644 --- a/test/Microsoft.ML.Tests/CachingTests.cs +++ b/test/Microsoft.ML.Tests/CachingTests.cs @@ -3,8 +3,7 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.RunTests; using System.Linq; using System.Threading; using Xunit; diff --git a/test/Microsoft.ML.Tests/CollectionDataSourceTests.cs b/test/Microsoft.ML.Tests/CollectionDataSourceTests.cs index 17ba426483..5a7dbd4ca7 100644 --- a/test/Microsoft.ML.Tests/CollectionDataSourceTests.cs +++ b/test/Microsoft.ML.Tests/CollectionDataSourceTests.cs @@ -6,8 +6,6 @@ using Microsoft.ML.Legacy.Data; using Microsoft.ML.Legacy.Trainers; using Microsoft.ML.Legacy.Transforms; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using Microsoft.ML.TestFramework; using System; using System.Collections.Generic; diff --git a/test/Microsoft.ML.Tests/FeatureContributionTests.cs b/test/Microsoft.ML.Tests/FeatureContributionTests.cs index c27a2af296..4b6fd6b572 100644 --- a/test/Microsoft.ML.Tests/FeatureContributionTests.cs +++ b/test/Microsoft.ML.Tests/FeatureContributionTests.cs @@ -1,17 +1,16 @@ -// Licensed to the .NET 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. -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.Data; +using Microsoft.ML.RunTests; +using Microsoft.ML.Training; using System; using Xunit; using Xunit.Abstractions; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Training; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Transforms; using System.IO; diff --git a/test/Microsoft.ML.Tests/ImagesTests.cs b/test/Microsoft.ML.Tests/ImagesTests.cs index e145c3a7cb..7f4f861cf7 100644 --- a/test/Microsoft.ML.Tests/ImagesTests.cs +++ b/test/Microsoft.ML.Tests/ImagesTests.cs @@ -3,11 +3,9 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.ImageAnalytics; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.ImageAnalytics; +using Microsoft.ML.Model; +using Microsoft.ML.RunTests; using System; using System.Drawing; using System.IO; diff --git a/test/Microsoft.ML.Tests/LearningPipelineTests.cs b/test/Microsoft.ML.Tests/LearningPipelineTests.cs index 651d29a940..496f8598e2 100644 --- a/test/Microsoft.ML.Tests/LearningPipelineTests.cs +++ b/test/Microsoft.ML.Tests/LearningPipelineTests.cs @@ -6,7 +6,6 @@ using Microsoft.ML.Legacy.Data; using Microsoft.ML.Legacy.Trainers; using Microsoft.ML.Legacy.Transforms; -using Microsoft.ML.Runtime.Data; using Microsoft.ML.TestFramework; using System.Linq; using Xunit; diff --git a/test/Microsoft.ML.Tests/OnnxTests.cs b/test/Microsoft.ML.Tests/OnnxTests.cs index db6758b576..fd6a7a0735 100644 --- a/test/Microsoft.ML.Tests/OnnxTests.cs +++ b/test/Microsoft.ML.Tests/OnnxTests.cs @@ -7,9 +7,8 @@ using Microsoft.ML.Legacy.Models; using Microsoft.ML.Legacy.Trainers; using Microsoft.ML.Legacy.Transforms; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Model.Onnx; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.Model.Onnx; +using Microsoft.ML.RunTests; using System; using System.Collections.Generic; using System.IO; @@ -85,7 +84,7 @@ public void InitializerCreationTest() { var env = new MLContext(); // Create the actual implementation - var ctxImpl = new OnnxContextImpl(env, "model", "ML.NET", "0", 0, "com.test", Runtime.Model.Onnx.OnnxVersion.Stable); + var ctxImpl = new OnnxContextImpl(env, "model", "ML.NET", "0", 0, "com.test", Model.Onnx.OnnxVersion.Stable); // Use implementation as in the actual conversion code var ctx = ctxImpl as OnnxContext; diff --git a/test/Microsoft.ML.Tests/PartitionedFileLoaderTests.cs b/test/Microsoft.ML.Tests/PartitionedFileLoaderTests.cs index 4b5371a98b..b9088d0b0c 100644 --- a/test/Microsoft.ML.Tests/PartitionedFileLoaderTests.cs +++ b/test/Microsoft.ML.Tests/PartitionedFileLoaderTests.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.RunTests; using System.IO; using Xunit; using Xunit.Abstractions; diff --git a/test/Microsoft.ML.Tests/PermutationFeatureImportanceTests.cs b/test/Microsoft.ML.Tests/PermutationFeatureImportanceTests.cs index 85428e0888..88ef6af527 100644 --- a/test/Microsoft.ML.Tests/PermutationFeatureImportanceTests.cs +++ b/test/Microsoft.ML.Tests/PermutationFeatureImportanceTests.cs @@ -3,10 +3,10 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.RunTests; using System; using System.Collections.Immutable; using System.Linq; diff --git a/test/Microsoft.ML.Tests/RangeFilterTests.cs b/test/Microsoft.ML.Tests/RangeFilterTests.cs index 9619b635bf..e224cc6997 100644 --- a/test/Microsoft.ML.Tests/RangeFilterTests.cs +++ b/test/Microsoft.ML.Tests/RangeFilterTests.cs @@ -3,8 +3,7 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.RunTests; using System.Linq; using Xunit; using Xunit.Abstractions; diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/CookbookSamples/CookbookSamples.cs b/test/Microsoft.ML.Tests/Scenarios/Api/CookbookSamples/CookbookSamples.cs index dd1ca760f3..e5e3dd16b9 100644 --- a/test/Microsoft.ML.Tests/Scenarios/Api/CookbookSamples/CookbookSamples.cs +++ b/test/Microsoft.ML.Tests/Scenarios/Api/CookbookSamples/CookbookSamples.cs @@ -4,10 +4,9 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML; +using Microsoft.ML.Learners; +using Microsoft.ML.RunTests; using Microsoft.ML.StaticPipe; using Microsoft.ML.TestFramework; using Microsoft.ML.Trainers; diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/CookbookSamples/CookbookSamplesDynamicApi.cs b/test/Microsoft.ML.Tests/Scenarios/Api/CookbookSamples/CookbookSamplesDynamicApi.cs index b0075f9975..4ef4ec7e1d 100644 --- a/test/Microsoft.ML.Tests/Scenarios/Api/CookbookSamples/CookbookSamplesDynamicApi.cs +++ b/test/Microsoft.ML.Tests/Scenarios/Api/CookbookSamples/CookbookSamplesDynamicApi.cs @@ -2,12 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.RunTests; using Microsoft.ML.TestFramework; using Microsoft.ML.Transforms.Categorical; using Microsoft.ML.Transforms.Normalizers; diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/CrossValidation.cs b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/CrossValidation.cs index 057c9c3bf5..e1d8c831b0 100644 --- a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/CrossValidation.cs +++ b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/CrossValidation.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.Data; +using Microsoft.ML.RunTests; using Microsoft.ML.Transforms.Categorical; using Microsoft.ML.Transforms.Conversions; using Xunit; diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/DecomposableTrainAndPredict.cs b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/DecomposableTrainAndPredict.cs index 3fe1bf3db9..c74c9f196b 100644 --- a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/DecomposableTrainAndPredict.cs +++ b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/DecomposableTrainAndPredict.cs @@ -3,9 +3,7 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.RunTests; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Conversions; using System.Linq; diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Evaluation.cs b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Evaluation.cs index eb76f87158..2d26d1ddf0 100644 --- a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Evaluation.cs +++ b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Evaluation.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.Data; +using Microsoft.ML.RunTests; using Xunit; namespace Microsoft.ML.Tests.Scenarios.Api diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Extensibility.cs b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Extensibility.cs index dc74988675..0d2da98e63 100644 --- a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Extensibility.cs +++ b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Extensibility.cs @@ -3,9 +3,7 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.RunTests; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Conversions; using System; diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/FileBasedSavingOfData.cs b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/FileBasedSavingOfData.cs index 8408bd45c8..bbff52dcd6 100644 --- a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/FileBasedSavingOfData.cs +++ b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/FileBasedSavingOfData.cs @@ -2,11 +2,11 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Learners; +using Microsoft.ML.RunTests; using System.IO; using Xunit; diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/IntrospectiveTraining.cs b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/IntrospectiveTraining.cs index d0c40aaee4..ba01d98244 100644 --- a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/IntrospectiveTraining.cs +++ b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/IntrospectiveTraining.cs @@ -2,13 +2,13 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; using Microsoft.ML.Trainers.FastTree; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Internal.Internallearn; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.TextAnalytics; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Learners; +using Microsoft.ML.RunTests; +using Microsoft.ML.TextAnalytics; using System.Collections.Generic; using Xunit; diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Metacomponents.cs b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Metacomponents.cs index 410a26f6fa..1845bcf40c 100644 --- a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Metacomponents.cs +++ b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Metacomponents.cs @@ -3,14 +3,10 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.RunTests; using Microsoft.ML.Trainers; using Microsoft.ML.Transforms; -using Microsoft.ML.Transforms.Categorical; using Microsoft.ML.Transforms.Conversions; -using System.Linq; using Xunit; namespace Microsoft.ML.Tests.Scenarios.Api diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/MultithreadedPrediction.cs b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/MultithreadedPrediction.cs index bb7ae2bfbe..3968dc5e0b 100644 --- a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/MultithreadedPrediction.cs +++ b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/MultithreadedPrediction.cs @@ -3,9 +3,7 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.RunTests; using System.Threading.Tasks; using Xunit; diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/ReconfigurablePrediction.cs b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/ReconfigurablePrediction.cs index a3d0ef5223..7447433c2a 100644 --- a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/ReconfigurablePrediction.cs +++ b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/ReconfigurablePrediction.cs @@ -2,10 +2,10 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Learners; +using Microsoft.ML.RunTests; using Xunit; namespace Microsoft.ML.Tests.Scenarios.Api diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/SimpleTrainAndPredict.cs b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/SimpleTrainAndPredict.cs index 59e4aaefaf..5dbdde466b 100644 --- a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/SimpleTrainAndPredict.cs +++ b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/SimpleTrainAndPredict.cs @@ -3,8 +3,8 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML; +using Microsoft.ML.RunTests; using System.Linq; using Xunit; diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/TrainSaveModelAndPredict.cs b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/TrainSaveModelAndPredict.cs index 0d50865e4e..62821d264b 100644 --- a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/TrainSaveModelAndPredict.cs +++ b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/TrainSaveModelAndPredict.cs @@ -4,8 +4,8 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML; +using Microsoft.ML.RunTests; using System.IO; using System.Linq; using Xunit; diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/TrainWithInitialPredictor.cs b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/TrainWithInitialPredictor.cs index 6b10338782..6e2b798fa6 100644 --- a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/TrainWithInitialPredictor.cs +++ b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/TrainWithInitialPredictor.cs @@ -2,10 +2,10 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Learners; +using Microsoft.ML.RunTests; using Xunit; namespace Microsoft.ML.Tests.Scenarios.Api diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/TrainWithValidationSet.cs b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/TrainWithValidationSet.cs index b5550c2f73..1fa992d1d4 100644 --- a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/TrainWithValidationSet.cs +++ b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/TrainWithValidationSet.cs @@ -2,9 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.Data; +using Microsoft.ML.Learners; +using Microsoft.ML.RunTests; using Xunit; namespace Microsoft.ML.Tests.Scenarios.Api diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Visibility.cs b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Visibility.cs index 958c26f630..9c5668ccb1 100644 --- a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Visibility.cs +++ b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Visibility.cs @@ -2,12 +2,9 @@ // 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.Linq; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.RunTests; using Xunit; namespace Microsoft.ML.Tests.Scenarios.Api diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/TestApi.cs b/test/Microsoft.ML.Tests/Scenarios/Api/TestApi.cs index ea412e02ea..32265039d1 100644 --- a/test/Microsoft.ML.Tests/Scenarios/Api/TestApi.cs +++ b/test/Microsoft.ML.Tests/Scenarios/Api/TestApi.cs @@ -3,10 +3,8 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Internal.Utilities; using Microsoft.ML.TestFramework; using Microsoft.ML.Trainers.Online; using Microsoft.ML.Transforms; diff --git a/test/Microsoft.ML.Tests/Scenarios/ClusteringTests.cs b/test/Microsoft.ML.Tests/Scenarios/ClusteringTests.cs index 049ff574d1..007b173021 100644 --- a/test/Microsoft.ML.Tests/Scenarios/ClusteringTests.cs +++ b/test/Microsoft.ML.Tests/Scenarios/ClusteringTests.cs @@ -1,7 +1,5 @@ using Microsoft.ML.Data; using Microsoft.ML.Legacy.Transforms; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using System; using System.Collections.Generic; using Xunit; diff --git a/test/Microsoft.ML.Tests/Scenarios/GetColumnTests.cs b/test/Microsoft.ML.Tests/Scenarios/GetColumnTests.cs index 661933343c..0ed86701c0 100644 --- a/test/Microsoft.ML.Tests/Scenarios/GetColumnTests.cs +++ b/test/Microsoft.ML.Tests/Scenarios/GetColumnTests.cs @@ -4,9 +4,7 @@ using Microsoft.ML.Data; using Microsoft.ML.StaticPipe; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.RunTests; using Microsoft.ML.TestFramework; using System; using System.Linq; diff --git a/test/Microsoft.ML.Tests/Scenarios/IrisPlantClassificationTests.cs b/test/Microsoft.ML.Tests/Scenarios/IrisPlantClassificationTests.cs index 02921c9b8d..ad634680cc 100644 --- a/test/Microsoft.ML.Tests/Scenarios/IrisPlantClassificationTests.cs +++ b/test/Microsoft.ML.Tests/Scenarios/IrisPlantClassificationTests.cs @@ -6,7 +6,6 @@ using Microsoft.ML.Legacy.Models; using Microsoft.ML.Legacy.Trainers; using Microsoft.ML.Legacy.Transforms; -using Microsoft.ML.Runtime.Data; using Xunit; using TextLoader = Microsoft.ML.Legacy.Data.TextLoader; diff --git a/test/Microsoft.ML.Tests/Scenarios/OvaTest.cs b/test/Microsoft.ML.Tests/Scenarios/OvaTest.cs index 4fe2e95914..cb4d0a0af7 100644 --- a/test/Microsoft.ML.Tests/Scenarios/OvaTest.cs +++ b/test/Microsoft.ML.Tests/Scenarios/OvaTest.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Learners; +using Microsoft.ML.Data; +using Microsoft.ML.Learners; using Microsoft.ML.Trainers; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Trainers.Online; diff --git a/test/Microsoft.ML.Tests/Scenarios/PipelineApi/PipelineApiScenarioTests.cs b/test/Microsoft.ML.Tests/Scenarios/PipelineApi/PipelineApiScenarioTests.cs index 488827881c..3194370879 100644 --- a/test/Microsoft.ML.Tests/Scenarios/PipelineApi/PipelineApiScenarioTests.cs +++ b/test/Microsoft.ML.Tests/Scenarios/PipelineApi/PipelineApiScenarioTests.cs @@ -3,7 +3,6 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; using Microsoft.ML.TestFramework; using Xunit.Abstractions; diff --git a/test/Microsoft.ML.Tests/Scenarios/PipelineApi/SimpleTrainAndPredict.cs b/test/Microsoft.ML.Tests/Scenarios/PipelineApi/SimpleTrainAndPredict.cs index fb65f576e8..d04f3a4a1e 100644 --- a/test/Microsoft.ML.Tests/Scenarios/PipelineApi/SimpleTrainAndPredict.cs +++ b/test/Microsoft.ML.Tests/Scenarios/PipelineApi/SimpleTrainAndPredict.cs @@ -5,7 +5,7 @@ using Microsoft.ML.Legacy.Data; using Microsoft.ML.Legacy.Trainers; using Microsoft.ML.Legacy.Transforms; -using Microsoft.ML.Runtime; +using Microsoft.ML; using Xunit; namespace Microsoft.ML.Tests.Scenarios.PipelineApi diff --git a/test/Microsoft.ML.Tests/Scenarios/SentimentPredictionTests.cs b/test/Microsoft.ML.Tests/Scenarios/SentimentPredictionTests.cs index 5c7d898254..bab4403225 100644 --- a/test/Microsoft.ML.Tests/Scenarios/SentimentPredictionTests.cs +++ b/test/Microsoft.ML.Tests/Scenarios/SentimentPredictionTests.cs @@ -7,7 +7,7 @@ using Microsoft.ML.Legacy.Models; using Microsoft.ML.Legacy.Trainers; using Microsoft.ML.Legacy.Transforms; -using Microsoft.ML.Runtime; +using Microsoft.ML; using System; using System.Collections.Generic; using System.Linq; diff --git a/test/Microsoft.ML.Tests/Scenarios/TensorflowTests.cs b/test/Microsoft.ML.Tests/Scenarios/TensorflowTests.cs index c53c68d496..e72ebea3c4 100644 --- a/test/Microsoft.ML.Tests/Scenarios/TensorflowTests.cs +++ b/test/Microsoft.ML.Tests/Scenarios/TensorflowTests.cs @@ -3,9 +3,7 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.ImageAnalytics; +using Microsoft.ML.ImageAnalytics; using Microsoft.ML.Trainers; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Conversions; diff --git a/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/IrisPlantClassificationTests.cs b/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/IrisPlantClassificationTests.cs index f11de7fe58..d51585dba9 100644 --- a/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/IrisPlantClassificationTests.cs +++ b/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/IrisPlantClassificationTests.cs @@ -4,10 +4,8 @@ using Microsoft.ML.Data; using Microsoft.ML.Legacy.Models; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.Model; +using Microsoft.ML.RunTests; using System.IO; using Xunit; diff --git a/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/SentimentPredictionTests.cs b/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/SentimentPredictionTests.cs index dd796b0b59..091b9ad5e1 100644 --- a/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/SentimentPredictionTests.cs +++ b/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/SentimentPredictionTests.cs @@ -3,13 +3,11 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Transforms.Text; using System.Linq; using Xunit; -using Microsoft.ML.Runtime.Internal.Internallearn; +using Microsoft.ML.Internal.Internallearn; namespace Microsoft.ML.Scenarios { diff --git a/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/TensorflowTests.cs b/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/TensorflowTests.cs index bfa32178d6..05ea13c701 100644 --- a/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/TensorflowTests.cs +++ b/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/TensorflowTests.cs @@ -3,10 +3,8 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.ImageAnalytics; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.ImageAnalytics; +using Microsoft.ML.RunTests; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Normalizers; using Microsoft.ML.Transforms.TensorFlow; diff --git a/test/Microsoft.ML.Tests/TensorFlowEstimatorTests.cs b/test/Microsoft.ML.Tests/TensorFlowEstimatorTests.cs index c6738ffa7e..32566eb8f1 100644 --- a/test/Microsoft.ML.Tests/TensorFlowEstimatorTests.cs +++ b/test/Microsoft.ML.Tests/TensorFlowEstimatorTests.cs @@ -1,15 +1,14 @@ -// Licensed to the .NET 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. using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.ImageAnalytics; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.Tools; using Microsoft.ML.TensorFlow.StaticPipe; +using Microsoft.ML.ImageAnalytics; +using Microsoft.ML.Model; +using Microsoft.ML.RunTests; +using Microsoft.ML.Tools; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.TensorFlow; using System; diff --git a/test/Microsoft.ML.Tests/TermEstimatorTests.cs b/test/Microsoft.ML.Tests/TermEstimatorTests.cs index 296d1fd0ba..5e0e7a19b5 100644 --- a/test/Microsoft.ML.Tests/TermEstimatorTests.cs +++ b/test/Microsoft.ML.Tests/TermEstimatorTests.cs @@ -3,11 +3,10 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Model; +using Microsoft.ML.RunTests; +using Microsoft.ML.Tools; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Conversions; using System; diff --git a/test/Microsoft.ML.Tests/TextLoaderTests.cs b/test/Microsoft.ML.Tests/TextLoaderTests.cs index d425bd8bdf..2c1f7da782 100644 --- a/test/Microsoft.ML.Tests/TextLoaderTests.cs +++ b/test/Microsoft.ML.Tests/TextLoaderTests.cs @@ -3,9 +3,7 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.RunTests; using Microsoft.ML.TestFramework; using System; using System.Collections.Generic; diff --git a/test/Microsoft.ML.Tests/TrainerEstimators/CalibratorEstimators.cs b/test/Microsoft.ML.Tests/TrainerEstimators/CalibratorEstimators.cs index 63bfc8d960..2b278dee29 100644 --- a/test/Microsoft.ML.Tests/TrainerEstimators/CalibratorEstimators.cs +++ b/test/Microsoft.ML.Tests/TrainerEstimators/CalibratorEstimators.cs @@ -5,8 +5,7 @@ using Microsoft.ML.Calibrator; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Learners; +using Microsoft.ML.Learners; using Microsoft.ML.Trainers.Online; using Xunit; diff --git a/test/Microsoft.ML.Tests/TrainerEstimators/FAFMEstimator.cs b/test/Microsoft.ML.Tests/TrainerEstimators/FAFMEstimator.cs index c2bf22ec39..53a7fcb95c 100644 --- a/test/Microsoft.ML.Tests/TrainerEstimators/FAFMEstimator.cs +++ b/test/Microsoft.ML.Tests/TrainerEstimators/FAFMEstimator.cs @@ -3,10 +3,10 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.FactorizationMachine; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.Data; +using Microsoft.ML.FactorizationMachine; +using Microsoft.ML.Learners; +using Microsoft.ML.RunTests; using Xunit; using Xunit.Abstractions; diff --git a/test/Microsoft.ML.Tests/TrainerEstimators/LbfgsTests.cs b/test/Microsoft.ML.Tests/TrainerEstimators/LbfgsTests.cs index 2a7f440ca0..30cab6c409 100644 --- a/test/Microsoft.ML.Tests/TrainerEstimators/LbfgsTests.cs +++ b/test/Microsoft.ML.Tests/TrainerEstimators/LbfgsTests.cs @@ -4,9 +4,8 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.Learners; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.Learners; using Microsoft.ML.Trainers; using Xunit; diff --git a/test/Microsoft.ML.Tests/TrainerEstimators/MatrixFactorizationTests.cs b/test/Microsoft.ML.Tests/TrainerEstimators/MatrixFactorizationTests.cs index 132d2209f9..24c1ee7536 100644 --- a/test/Microsoft.ML.Tests/TrainerEstimators/MatrixFactorizationTests.cs +++ b/test/Microsoft.ML.Tests/TrainerEstimators/MatrixFactorizationTests.cs @@ -3,8 +3,7 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.RunTests; using Microsoft.ML.Trainers; using System; using System.Collections.Generic; diff --git a/test/Microsoft.ML.Tests/TrainerEstimators/MetalinearEstimators.cs b/test/Microsoft.ML.Tests/TrainerEstimators/MetalinearEstimators.cs index 2599df8bdd..8371e3e415 100644 --- a/test/Microsoft.ML.Tests/TrainerEstimators/MetalinearEstimators.cs +++ b/test/Microsoft.ML.Tests/TrainerEstimators/MetalinearEstimators.cs @@ -3,9 +3,8 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Calibration; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.Internal.Calibration; +using Microsoft.ML.RunTests; using Microsoft.ML.Trainers; using Microsoft.ML.Trainers.Online; using Microsoft.ML.Transforms; diff --git a/test/Microsoft.ML.Tests/TrainerEstimators/OnlineLinearTests.cs b/test/Microsoft.ML.Tests/TrainerEstimators/OnlineLinearTests.cs index cf708304d8..e134af0df1 100644 --- a/test/Microsoft.ML.Tests/TrainerEstimators/OnlineLinearTests.cs +++ b/test/Microsoft.ML.Tests/TrainerEstimators/OnlineLinearTests.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; +using Microsoft.ML; +using Microsoft.ML.Data; using Microsoft.ML.StaticPipe; using Microsoft.ML.Trainers.Online; using Xunit; diff --git a/test/Microsoft.ML.Tests/TrainerEstimators/PriorRandomTests.cs b/test/Microsoft.ML.Tests/TrainerEstimators/PriorRandomTests.cs index 2894c9ffa5..edafd5904f 100644 --- a/test/Microsoft.ML.Tests/TrainerEstimators/PriorRandomTests.cs +++ b/test/Microsoft.ML.Tests/TrainerEstimators/PriorRandomTests.cs @@ -2,10 +2,10 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Learners; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Learners; +using Microsoft.ML.RunTests; using Microsoft.ML.Trainers; using Xunit; diff --git a/test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs b/test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs index 691ea7447d..99efb5f82c 100644 --- a/test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs +++ b/test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; +using Microsoft.ML.Data; using Microsoft.ML.Trainers; using Xunit; diff --git a/test/Microsoft.ML.Tests/TrainerEstimators/SymSgdClassificationTests.cs b/test/Microsoft.ML.Tests/TrainerEstimators/SymSgdClassificationTests.cs index f6780cae26..49d7db7c4a 100644 --- a/test/Microsoft.ML.Tests/TrainerEstimators/SymSgdClassificationTests.cs +++ b/test/Microsoft.ML.Tests/TrainerEstimators/SymSgdClassificationTests.cs @@ -3,8 +3,6 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; using Microsoft.ML.Trainers; using Microsoft.ML.Trainers.SymSgd; using System.Linq; diff --git a/test/Microsoft.ML.Tests/TrainerEstimators/TrainerEstimators.cs b/test/Microsoft.ML.Tests/TrainerEstimators/TrainerEstimators.cs index e0d86ba784..85af744ac7 100644 --- a/test/Microsoft.ML.Tests/TrainerEstimators/TrainerEstimators.cs +++ b/test/Microsoft.ML.Tests/TrainerEstimators/TrainerEstimators.cs @@ -3,8 +3,8 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Core.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.Data; +using Microsoft.ML.RunTests; using Microsoft.ML.Trainers; using Microsoft.ML.Trainers.KMeans; using Microsoft.ML.Trainers.PCA; diff --git a/test/Microsoft.ML.Tests/TrainerEstimators/TreeEstimators.cs b/test/Microsoft.ML.Tests/TrainerEstimators/TreeEstimators.cs index 30b810c67a..1ca8ad3b87 100644 --- a/test/Microsoft.ML.Tests/TrainerEstimators/TreeEstimators.cs +++ b/test/Microsoft.ML.Tests/TrainerEstimators/TreeEstimators.cs @@ -1,13 +1,12 @@ -// Licensed to the .NET 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. +using Microsoft.ML; using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.LightGBM; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.LightGBM; +using Microsoft.ML.RunTests; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Transforms.Conversions; using System; diff --git a/test/Microsoft.ML.Tests/Transformers/CategoricalHashTests.cs b/test/Microsoft.ML.Tests/Transformers/CategoricalHashTests.cs index 14328c5c9b..c2208d05cc 100644 --- a/test/Microsoft.ML.Tests/Transformers/CategoricalHashTests.cs +++ b/test/Microsoft.ML.Tests/Transformers/CategoricalHashTests.cs @@ -3,11 +3,10 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Model; +using Microsoft.ML.RunTests; +using Microsoft.ML.Tools; using Microsoft.ML.StaticPipe; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Categorical; diff --git a/test/Microsoft.ML.Tests/Transformers/CategoricalTests.cs b/test/Microsoft.ML.Tests/Transformers/CategoricalTests.cs index 7c59744496..70854c6bce 100644 --- a/test/Microsoft.ML.Tests/Transformers/CategoricalTests.cs +++ b/test/Microsoft.ML.Tests/Transformers/CategoricalTests.cs @@ -3,11 +3,10 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Model; +using Microsoft.ML.RunTests; +using Microsoft.ML.Tools; using Microsoft.ML.StaticPipe; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Categorical; diff --git a/test/Microsoft.ML.Tests/Transformers/CharTokenizeTests.cs b/test/Microsoft.ML.Tests/Transformers/CharTokenizeTests.cs index 534d23180b..a1bddbc137 100644 --- a/test/Microsoft.ML.Tests/Transformers/CharTokenizeTests.cs +++ b/test/Microsoft.ML.Tests/Transformers/CharTokenizeTests.cs @@ -3,10 +3,9 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML.Model; +using Microsoft.ML.RunTests; +using Microsoft.ML.Tools; using Microsoft.ML.Transforms.Text; using System.IO; using Xunit; diff --git a/test/Microsoft.ML.Tests/Transformers/ConcatTests.cs b/test/Microsoft.ML.Tests/Transformers/ConcatTests.cs index 81eea9b625..84cb52211e 100644 --- a/test/Microsoft.ML.Tests/Transformers/ConcatTests.cs +++ b/test/Microsoft.ML.Tests/Transformers/ConcatTests.cs @@ -3,9 +3,8 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.Data.IO; +using Microsoft.ML.RunTests; using Microsoft.ML.Transforms; using System.IO; using Xunit; diff --git a/test/Microsoft.ML.Tests/Transformers/ConvertTests.cs b/test/Microsoft.ML.Tests/Transformers/ConvertTests.cs index a7a1245d49..14a72a362f 100644 --- a/test/Microsoft.ML.Tests/Transformers/ConvertTests.cs +++ b/test/Microsoft.ML.Tests/Transformers/ConvertTests.cs @@ -3,11 +3,10 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Model; +using Microsoft.ML.RunTests; +using Microsoft.ML.Tools; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Categorical; using Microsoft.ML.Transforms.Conversions; diff --git a/test/Microsoft.ML.Tests/Transformers/CopyColumnEstimatorTests.cs b/test/Microsoft.ML.Tests/Transformers/CopyColumnEstimatorTests.cs index b7b1d3a7a7..26a8ea510e 100644 --- a/test/Microsoft.ML.Tests/Transformers/CopyColumnEstimatorTests.cs +++ b/test/Microsoft.ML.Tests/Transformers/CopyColumnEstimatorTests.cs @@ -3,10 +3,8 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML.Model; +using Microsoft.ML.Tools; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Conversions; using System; diff --git a/test/Microsoft.ML.Tests/Transformers/CustomMappingTests.cs b/test/Microsoft.ML.Tests/Transformers/CustomMappingTests.cs index c26a749554..5470f45244 100644 --- a/test/Microsoft.ML.Tests/Transformers/CustomMappingTests.cs +++ b/test/Microsoft.ML.Tests/Transformers/CustomMappingTests.cs @@ -4,8 +4,7 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.RunTests; using Microsoft.ML.Transforms; using System; using System.ComponentModel.Composition; diff --git a/test/Microsoft.ML.Tests/Transformers/FeatureSelectionTests.cs b/test/Microsoft.ML.Tests/Transformers/FeatureSelectionTests.cs index ee2a20855d..a9ddf749a2 100644 --- a/test/Microsoft.ML.Tests/Transformers/FeatureSelectionTests.cs +++ b/test/Microsoft.ML.Tests/Transformers/FeatureSelectionTests.cs @@ -3,11 +3,10 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Model; +using Microsoft.ML.RunTests; +using Microsoft.ML.Tools; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.FeatureSelection; using Microsoft.ML.Transforms.Text; diff --git a/test/Microsoft.ML.Tests/Transformers/HashTests.cs b/test/Microsoft.ML.Tests/Transformers/HashTests.cs index 8e0faf8bb8..dc674c04af 100644 --- a/test/Microsoft.ML.Tests/Transformers/HashTests.cs +++ b/test/Microsoft.ML.Tests/Transformers/HashTests.cs @@ -3,11 +3,10 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Internal.Utilities; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Model; +using Microsoft.ML.RunTests; +using Microsoft.ML.Tools; using Microsoft.ML.Transforms.Conversions; using System; using System.IO; diff --git a/test/Microsoft.ML.Tests/Transformers/KeyToBinaryVectorEstimatorTest.cs b/test/Microsoft.ML.Tests/Transformers/KeyToBinaryVectorEstimatorTest.cs index b41fa4f28e..5549793721 100644 --- a/test/Microsoft.ML.Tests/Transformers/KeyToBinaryVectorEstimatorTest.cs +++ b/test/Microsoft.ML.Tests/Transformers/KeyToBinaryVectorEstimatorTest.cs @@ -3,10 +3,9 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML.Model; +using Microsoft.ML.RunTests; +using Microsoft.ML.Tools; using Microsoft.ML.StaticPipe; using Microsoft.ML.Transforms.Conversions; using System; diff --git a/test/Microsoft.ML.Tests/Transformers/KeyToValueTests.cs b/test/Microsoft.ML.Tests/Transformers/KeyToValueTests.cs index 73fdf8bd21..8a7e80c2b2 100644 --- a/test/Microsoft.ML.Tests/Transformers/KeyToValueTests.cs +++ b/test/Microsoft.ML.Tests/Transformers/KeyToValueTests.cs @@ -2,9 +2,9 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.Data; +using Microsoft.ML.Data.IO; +using Microsoft.ML.RunTests; using Microsoft.ML.StaticPipe; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Categorical; diff --git a/test/Microsoft.ML.Tests/Transformers/KeyToVectorEstimatorTests.cs b/test/Microsoft.ML.Tests/Transformers/KeyToVectorEstimatorTests.cs index 1b4d68728c..b90c302298 100644 --- a/test/Microsoft.ML.Tests/Transformers/KeyToVectorEstimatorTests.cs +++ b/test/Microsoft.ML.Tests/Transformers/KeyToVectorEstimatorTests.cs @@ -3,10 +3,9 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML.Model; +using Microsoft.ML.RunTests; +using Microsoft.ML.Tools; using Microsoft.ML.StaticPipe; using Microsoft.ML.Transforms.Conversions; using System; diff --git a/test/Microsoft.ML.Tests/Transformers/LineParserTests.cs b/test/Microsoft.ML.Tests/Transformers/LineParserTests.cs index 1beeaea68e..e51b5826ab 100644 --- a/test/Microsoft.ML.Tests/Transformers/LineParserTests.cs +++ b/test/Microsoft.ML.Tests/Transformers/LineParserTests.cs @@ -2,7 +2,7 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Internal.Utilities; +using Microsoft.ML.Internal.Utilities; using System.Collections.Generic; using Xunit; diff --git a/test/Microsoft.ML.Tests/Transformers/NAIndicatorTests.cs b/test/Microsoft.ML.Tests/Transformers/NAIndicatorTests.cs index 27e8759061..7817273e80 100644 --- a/test/Microsoft.ML.Tests/Transformers/NAIndicatorTests.cs +++ b/test/Microsoft.ML.Tests/Transformers/NAIndicatorTests.cs @@ -3,11 +3,10 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Model; +using Microsoft.ML.RunTests; +using Microsoft.ML.Tools; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Categorical; using System; diff --git a/test/Microsoft.ML.Tests/Transformers/NAReplaceTests.cs b/test/Microsoft.ML.Tests/Transformers/NAReplaceTests.cs index 0c4e4de6e1..40917beb34 100644 --- a/test/Microsoft.ML.Tests/Transformers/NAReplaceTests.cs +++ b/test/Microsoft.ML.Tests/Transformers/NAReplaceTests.cs @@ -3,11 +3,10 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Model; +using Microsoft.ML.RunTests; +using Microsoft.ML.Tools; using Microsoft.ML.StaticPipe; using Microsoft.ML.Transforms; using System.IO; diff --git a/test/Microsoft.ML.Tests/Transformers/NormalizerTests.cs b/test/Microsoft.ML.Tests/Transformers/NormalizerTests.cs index 478095fcf2..abfe1391a2 100644 --- a/test/Microsoft.ML.Tests/Transformers/NormalizerTests.cs +++ b/test/Microsoft.ML.Tests/Transformers/NormalizerTests.cs @@ -3,11 +3,10 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Model; +using Microsoft.ML.RunTests; +using Microsoft.ML.Tools; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Normalizers; using Microsoft.ML.Transforms.Projections; diff --git a/test/Microsoft.ML.Tests/Transformers/PcaTests.cs b/test/Microsoft.ML.Tests/Transformers/PcaTests.cs index 43ad1f7d70..b2d3079364 100644 --- a/test/Microsoft.ML.Tests/Transformers/PcaTests.cs +++ b/test/Microsoft.ML.Tests/Transformers/PcaTests.cs @@ -2,10 +2,10 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Data.IO; +using Microsoft.ML.RunTests; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Projections; using System.IO; diff --git a/test/Microsoft.ML.Tests/Transformers/RffTests.cs b/test/Microsoft.ML.Tests/Transformers/RffTests.cs index 4bfd6a2b84..201d3b8ab4 100644 --- a/test/Microsoft.ML.Tests/Transformers/RffTests.cs +++ b/test/Microsoft.ML.Tests/Transformers/RffTests.cs @@ -1,9 +1,8 @@ using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Model; +using Microsoft.ML.RunTests; +using Microsoft.ML.Tools; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Projections; using System; diff --git a/test/Microsoft.ML.Tests/Transformers/SelectColumnsTests.cs b/test/Microsoft.ML.Tests/Transformers/SelectColumnsTests.cs index d538ade380..e4086be339 100644 --- a/test/Microsoft.ML.Tests/Transformers/SelectColumnsTests.cs +++ b/test/Microsoft.ML.Tests/Transformers/SelectColumnsTests.cs @@ -3,9 +3,9 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML.Model; +using Microsoft.ML.RunTests; +using Microsoft.ML.Tools; using Microsoft.ML.Transforms; using System; using System.IO; diff --git a/test/Microsoft.ML.Tests/Transformers/TextFeaturizerTests.cs b/test/Microsoft.ML.Tests/Transformers/TextFeaturizerTests.cs index 950c6a30da..619fb7e9bc 100644 --- a/test/Microsoft.ML.Tests/Transformers/TextFeaturizerTests.cs +++ b/test/Microsoft.ML.Tests/Transformers/TextFeaturizerTests.cs @@ -1,13 +1,13 @@ -// Licensed to the .NET 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. -using Microsoft.ML.Runtime; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.Tools; using Microsoft.ML.StaticPipe; +using Microsoft.ML; +using Microsoft.ML.Data; +using Microsoft.ML.Data.IO; +using Microsoft.ML.RunTests; +using Microsoft.ML.Tools; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Categorical; using Microsoft.ML.Transforms.Conversions; diff --git a/test/Microsoft.ML.Tests/Transformers/TextNormalizer.cs b/test/Microsoft.ML.Tests/Transformers/TextNormalizer.cs index 8e777ee388..887634d363 100644 --- a/test/Microsoft.ML.Tests/Transformers/TextNormalizer.cs +++ b/test/Microsoft.ML.Tests/Transformers/TextNormalizer.cs @@ -3,11 +3,10 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Data.IO; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML.Data.IO; +using Microsoft.ML.Model; +using Microsoft.ML.RunTests; +using Microsoft.ML.Tools; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Text; using System.IO; diff --git a/test/Microsoft.ML.Tests/Transformers/ValueMappingTests.cs b/test/Microsoft.ML.Tests/Transformers/ValueMappingTests.cs index 99fcfa0020..b466d22ffd 100644 --- a/test/Microsoft.ML.Tests/Transformers/ValueMappingTests.cs +++ b/test/Microsoft.ML.Tests/Transformers/ValueMappingTests.cs @@ -4,10 +4,9 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML.Model; +using Microsoft.ML.RunTests; +using Microsoft.ML.Tools; using Microsoft.ML.Transforms.Conversions; using System; using System.Collections.Generic; diff --git a/test/Microsoft.ML.Tests/Transformers/WordEmbeddingsTests.cs b/test/Microsoft.ML.Tests/Transformers/WordEmbeddingsTests.cs index d8cdd26f37..56b3c9105a 100644 --- a/test/Microsoft.ML.Tests/Transformers/WordEmbeddingsTests.cs +++ b/test/Microsoft.ML.Tests/Transformers/WordEmbeddingsTests.cs @@ -2,8 +2,8 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.Data; +using Microsoft.ML.RunTests; using Microsoft.ML.Scenarios; using Microsoft.ML.StaticPipe; using Microsoft.ML.Transforms.Text; diff --git a/test/Microsoft.ML.Tests/Transformers/WordTokenizeTests.cs b/test/Microsoft.ML.Tests/Transformers/WordTokenizeTests.cs index fc01cfaf60..aca3c9de1b 100644 --- a/test/Microsoft.ML.Tests/Transformers/WordTokenizeTests.cs +++ b/test/Microsoft.ML.Tests/Transformers/WordTokenizeTests.cs @@ -3,10 +3,9 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.Model; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.Tools; +using Microsoft.ML.Model; +using Microsoft.ML.RunTests; +using Microsoft.ML.Tools; using Microsoft.ML.Transforms.Text; using System; using System.Collections.Generic; diff --git a/test/Microsoft.ML.TimeSeries.Tests/TimeSeries.cs b/test/Microsoft.ML.TimeSeries.Tests/TimeSeries.cs index f20de461f4..9a5f34eb1f 100644 --- a/test/Microsoft.ML.TimeSeries.Tests/TimeSeries.cs +++ b/test/Microsoft.ML.TimeSeries.Tests/TimeSeries.cs @@ -2,15 +2,15 @@ // The .NET Foundation licenses this file to you under the MIT license. // See the LICENSE file in the project root for more information. -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.TimeSeriesProcessing; +using Microsoft.ML.Data; +using Microsoft.ML.TimeSeriesProcessing; using System; using System.IO; using System.Linq; using Xunit; using Xunit.Abstractions; -namespace Microsoft.ML.Runtime.RunTests +namespace Microsoft.ML.RunTests { public sealed class TestTimeSeries : TestDataPipeBase { diff --git a/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesDirectApi.cs b/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesDirectApi.cs index 62441c611f..ac720e050c 100644 --- a/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesDirectApi.cs +++ b/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesDirectApi.cs @@ -4,9 +4,8 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.TimeSeriesProcessing; -using Microsoft.ML.Runtime.RunTests; +using Microsoft.ML.TimeSeriesProcessing; +using Microsoft.ML.RunTests; using Microsoft.ML.TimeSeries; using System.Collections.Generic; using System.IO; diff --git a/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesEstimatorTests.cs b/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesEstimatorTests.cs index 4630499fde..5d31ee2822 100644 --- a/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesEstimatorTests.cs +++ b/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesEstimatorTests.cs @@ -3,9 +3,8 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Runtime.Data; -using Microsoft.ML.Runtime.RunTests; -using Microsoft.ML.Runtime.TimeSeriesProcessing; +using Microsoft.ML.RunTests; +using Microsoft.ML.TimeSeriesProcessing; using System.Collections.Generic; using Xunit; using Xunit.Abstractions; diff --git a/tools-local/Microsoft.ML.InternalCodeAnalyzer/BestFriendAnalyzer.cs b/tools-local/Microsoft.ML.InternalCodeAnalyzer/BestFriendAnalyzer.cs index 98066222b3..87f0d7c148 100644 --- a/tools-local/Microsoft.ML.InternalCodeAnalyzer/BestFriendAnalyzer.cs +++ b/tools-local/Microsoft.ML.InternalCodeAnalyzer/BestFriendAnalyzer.cs @@ -111,7 +111,7 @@ private void AnalyzeCore(SemanticModelAnalysisContext context, string attributeN private void Analyze(SemanticModelAnalysisContext context) { AnalyzeCore(context, "Microsoft.ML.BestFriendAttribute", "Microsoft.ML.WantsToBeBestFriendsAttribute"); - AnalyzeCore(context, "Microsoft.ML.Runtime.Internal.CpuMath.Core.BestFriendAttribute", "Microsoft.ML.Runtime.Internal.CpuMath.Core.WantsToBeBestFriendsAttribute"); + AnalyzeCore(context, "Microsoft.ML.Internal.CpuMath.Core.BestFriendAttribute", "Microsoft.ML.Internal.CpuMath.Core.WantsToBeBestFriendsAttribute"); } } } diff --git a/tools-local/Microsoft.ML.InternalCodeAnalyzer/ContractsCheckAnalyzer.cs b/tools-local/Microsoft.ML.InternalCodeAnalyzer/ContractsCheckAnalyzer.cs index 6328a7cf5f..c5fa8f6b5d 100644 --- a/tools-local/Microsoft.ML.InternalCodeAnalyzer/ContractsCheckAnalyzer.cs +++ b/tools-local/Microsoft.ML.InternalCodeAnalyzer/ContractsCheckAnalyzer.cs @@ -196,10 +196,10 @@ private static void Analyze(SyntaxNodeAnalysisContext context) var containingSymbolName = methodSymbol.ContainingSymbol.ToString(); // The "internal" version is one used by some projects that want to benefit from Contracts, // but for some reason cannot reference MLCore. - // Contract functions defined Microsoft.ML.Runtime.Internal.CpuMath.Core are introduced for breaking the dependencies + // Contract functions defined Microsoft.ML.Internal.CpuMath.Core are introduced for breaking the dependencies // from CpuMath project to Microsoft.ML.Core. - if (containingSymbolName != "Microsoft.ML.Runtime.Contracts" && - containingSymbolName != "Microsoft.ML.Runtime.Internal.CpuMath.Core.Contracts") + if (containingSymbolName != "Microsoft.ML.Contracts" && + containingSymbolName != "Microsoft.ML.Internal.CpuMath.Core.Contracts") { return; }