From 15d5382c7b7be5fc329ba21c76fcb9de3f708a1a Mon Sep 17 00:00:00 2001 From: Senja Filipi Date: Wed, 6 Feb 2019 11:46:07 -0800 Subject: [PATCH 1/3] removing the Microsoft.ML.Learners and the Microsoft.ML.Trainers.SymSGD namespaces. --- .../PermutationFeatureImportance/PFIHelper.cs | 3 ++- .../PfiBinaryClassificationExample.cs | 2 +- .../Static/SDCARegression.cs | 2 +- .../Trainer/Binary/EnsembleTrainer.cs | 2 +- .../MulticlassDataPartitionEnsembleTrainer.cs | 2 +- .../Regression/RegressionEnsembleTrainer.cs | 3 +-- .../ComputeLRTrainingStdThroughHal.cs | 2 +- .../HalLearnersCatalog.cs | 2 -- .../OlsLinearRegression.cs | 1 - .../SymSgdClassificationTrainer.cs | 5 ++--- .../Standard/LinearModelParameters.cs | 4 ++-- .../Standard/LinearPredictorUtils.cs | 2 +- .../LogisticRegression/LbfgsPredictorBase.cs | 2 +- .../LogisticRegression/LogisticRegression.cs | 4 ++-- .../MulticlassLogisticRegression.cs | 3 +-- .../Standard/ModelStatistics.cs | 4 ++-- .../MultiClass/MetaMulticlassTrainer.cs | 2 +- .../Standard/MultiClass/Ova.cs | 1 - .../Standard/MultiClass/Pkpd.cs | 1 - .../Standard/Online/AveragedLinear.cs | 1 - .../Standard/Online/AveragedPerceptron.cs | 1 - .../Standard/Online/LinearSvm.cs | 1 - .../Standard/Online/OnlineGradientDescent.cs | 1 - .../Standard/Online/OnlineLinear.cs | 1 - .../PoissonRegression/PoissonRegression.cs | 1 - .../Standard/SdcaBinary.cs | 1 - .../Standard/SdcaMultiClass.cs | 1 - .../Standard/SdcaRegression.cs | 1 - .../Standard/StochasticTrainerBase.cs | 2 +- .../StandardLearnersCatalog.cs | 19 +++++++++---------- src/Microsoft.ML.StaticPipe/LbfgsStatic.cs | 19 +++++++++---------- .../OnlineLearnerStatic.cs | 2 +- .../SdcaStaticExtensions.cs | 1 - .../KMeansAndLogisticRegressionBench.cs | 2 +- ...sticDualCoordinateAscentClassifierBench.cs | 1 - .../UnitTests/TestEntryPoints.cs | 3 +-- .../TestPredictors.cs | 5 ++--- .../Training.cs | 2 +- .../EnvironmentExtensions.cs | 2 +- test/Microsoft.ML.Tests/OnnxConversionTest.cs | 2 +- .../PermutationFeatureImportanceTests.cs | 2 +- .../Api/CookbookSamples/CookbookSamples.cs | 1 - .../CookbookSamplesDynamicApi.cs | 2 +- .../Api/Estimators/SimpleTrainAndPredict.cs | 2 +- test/Microsoft.ML.Tests/Scenarios/OvaTest.cs | 2 -- .../TrainerEstimators/CalibratorEstimators.cs | 3 +-- .../TrainerEstimators/LbfgsTests.cs | 2 -- .../SymSgdClassificationTests.cs | 3 +-- 48 files changed, 52 insertions(+), 81 deletions(-) diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/PermutationFeatureImportance/PFIHelper.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/PermutationFeatureImportance/PFIHelper.cs index 79052c2314..73471a0c52 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/PermutationFeatureImportance/PFIHelper.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/PermutationFeatureImportance/PFIHelper.cs @@ -1,7 +1,8 @@ using System; using System.Linq; using Microsoft.Data.DataView; -using Microsoft.ML.Learners; +using Microsoft.ML.Data; +using Microsoft.ML.Trainers; using Microsoft.ML.SamplesUtils; using Microsoft.ML.Trainers.HalLearners; diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/PermutationFeatureImportance/PfiBinaryClassificationExample.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/PermutationFeatureImportance/PfiBinaryClassificationExample.cs index 205f7cc4ce..77e2e63d27 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/PermutationFeatureImportance/PfiBinaryClassificationExample.cs +++ b/docs/samples/Microsoft.ML.Samples/Dynamic/PermutationFeatureImportance/PfiBinaryClassificationExample.cs @@ -1,6 +1,6 @@ using System; using System.Linq; -using Microsoft.ML.Learners; +using Microsoft.ML.Trainers; namespace Microsoft.ML.Samples.Dynamic.PermutationFeatureImportance { diff --git a/docs/samples/Microsoft.ML.Samples/Static/SDCARegression.cs b/docs/samples/Microsoft.ML.Samples/Static/SDCARegression.cs index 50d5b8c6aa..914788eae8 100644 --- a/docs/samples/Microsoft.ML.Samples/Static/SDCARegression.cs +++ b/docs/samples/Microsoft.ML.Samples/Static/SDCARegression.cs @@ -1,7 +1,7 @@ using System; using Microsoft.ML.Data; -using Microsoft.ML.Learners; using Microsoft.ML.StaticPipe; +using Microsoft.ML.Trainers; namespace Microsoft.ML.Samples.Static { diff --git a/src/Microsoft.ML.Ensemble/Trainer/Binary/EnsembleTrainer.cs b/src/Microsoft.ML.Ensemble/Trainer/Binary/EnsembleTrainer.cs index 83637c333f..959a5b20ed 100644 --- a/src/Microsoft.ML.Ensemble/Trainer/Binary/EnsembleTrainer.cs +++ b/src/Microsoft.ML.Ensemble/Trainer/Binary/EnsembleTrainer.cs @@ -12,7 +12,7 @@ using Microsoft.ML.Ensemble.OutputCombiners; using Microsoft.ML.Ensemble.Selector; using Microsoft.ML.Internal.Internallearn; -using Microsoft.ML.Learners; +using Microsoft.ML.Trainers; using Microsoft.ML.Trainers.Online; using Microsoft.ML.Training; diff --git a/src/Microsoft.ML.Ensemble/Trainer/Multiclass/MulticlassDataPartitionEnsembleTrainer.cs b/src/Microsoft.ML.Ensemble/Trainer/Multiclass/MulticlassDataPartitionEnsembleTrainer.cs index d194dfc947..d15b9a2596 100644 --- a/src/Microsoft.ML.Ensemble/Trainer/Multiclass/MulticlassDataPartitionEnsembleTrainer.cs +++ b/src/Microsoft.ML.Ensemble/Trainer/Multiclass/MulticlassDataPartitionEnsembleTrainer.cs @@ -13,7 +13,7 @@ using Microsoft.ML.Ensemble.OutputCombiners; using Microsoft.ML.Ensemble.Selector; using Microsoft.ML.Internal.Internallearn; -using Microsoft.ML.Learners; +using Microsoft.ML.Trainers; using Microsoft.ML.Training; [assembly: LoadableClass(MulticlassDataPartitionEnsembleTrainer.Summary, typeof(MulticlassDataPartitionEnsembleTrainer), diff --git a/src/Microsoft.ML.Ensemble/Trainer/Regression/RegressionEnsembleTrainer.cs b/src/Microsoft.ML.Ensemble/Trainer/Regression/RegressionEnsembleTrainer.cs index 569d4cd829..172ed62fc4 100644 --- a/src/Microsoft.ML.Ensemble/Trainer/Regression/RegressionEnsembleTrainer.cs +++ b/src/Microsoft.ML.Ensemble/Trainer/Regression/RegressionEnsembleTrainer.cs @@ -7,13 +7,12 @@ using System.Linq; using Microsoft.ML; using Microsoft.ML.CommandLine; -using Microsoft.ML.Data; using Microsoft.ML.Ensemble; using Microsoft.ML.Ensemble.EntryPoints; using Microsoft.ML.Ensemble.OutputCombiners; using Microsoft.ML.Ensemble.Selector; using Microsoft.ML.Internal.Internallearn; -using Microsoft.ML.Learners; +using Microsoft.ML.Trainers; using Microsoft.ML.Trainers.Online; using Microsoft.ML.Training; diff --git a/src/Microsoft.ML.HalLearners/ComputeLRTrainingStdThroughHal.cs b/src/Microsoft.ML.HalLearners/ComputeLRTrainingStdThroughHal.cs index bc30deabfc..ce3bad8b99 100644 --- a/src/Microsoft.ML.HalLearners/ComputeLRTrainingStdThroughHal.cs +++ b/src/Microsoft.ML.HalLearners/ComputeLRTrainingStdThroughHal.cs @@ -7,7 +7,7 @@ using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Trainers.HalLearners; -namespace Microsoft.ML.Learners +namespace Microsoft.ML.Trainers { using Mkl = OlsLinearRegressionTrainer.Mkl; diff --git a/src/Microsoft.ML.HalLearners/HalLearnersCatalog.cs b/src/Microsoft.ML.HalLearners/HalLearnersCatalog.cs index 1b635d49fc..564a5df3c6 100644 --- a/src/Microsoft.ML.HalLearners/HalLearnersCatalog.cs +++ b/src/Microsoft.ML.HalLearners/HalLearnersCatalog.cs @@ -2,11 +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 Microsoft.ML.Data; using Microsoft.ML.EntryPoints; using Microsoft.ML.Trainers.HalLearners; -using Microsoft.ML.Trainers.SymSgd; using Microsoft.ML.Transforms.Projections; namespace Microsoft.ML diff --git a/src/Microsoft.ML.HalLearners/OlsLinearRegression.cs b/src/Microsoft.ML.HalLearners/OlsLinearRegression.cs index 18a5d97b97..31c01b6324 100644 --- a/src/Microsoft.ML.HalLearners/OlsLinearRegression.cs +++ b/src/Microsoft.ML.HalLearners/OlsLinearRegression.cs @@ -15,7 +15,6 @@ 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.Trainers.HalLearners; using Microsoft.ML.Training; diff --git a/src/Microsoft.ML.HalLearners/SymSgdClassificationTrainer.cs b/src/Microsoft.ML.HalLearners/SymSgdClassificationTrainer.cs index 8b7377bbe1..e23619e81c 100644 --- a/src/Microsoft.ML.HalLearners/SymSgdClassificationTrainer.cs +++ b/src/Microsoft.ML.HalLearners/SymSgdClassificationTrainer.cs @@ -16,8 +16,7 @@ using Microsoft.ML.Internal.Calibration; using Microsoft.ML.Internal.Internallearn; using Microsoft.ML.Internal.Utilities; -using Microsoft.ML.Learners; -using Microsoft.ML.Trainers.SymSgd; +using Microsoft.ML.Trainers.HalLearners; using Microsoft.ML.Training; using Microsoft.ML.Transforms; @@ -29,7 +28,7 @@ [assembly: LoadableClass(typeof(void), typeof(SymSgdClassificationTrainer), null, typeof(SignatureEntryPointModule), SymSgdClassificationTrainer.LoadNameValue)] -namespace Microsoft.ML.Trainers.SymSgd +namespace Microsoft.ML.Trainers.HalLearners { using TPredictor = CalibratedModelParametersBase; diff --git a/src/Microsoft.ML.StandardLearners/Standard/LinearModelParameters.cs b/src/Microsoft.ML.StandardLearners/Standard/LinearModelParameters.cs index 3a88c62128..df52e48433 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/LinearModelParameters.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/LinearModelParameters.cs @@ -14,11 +14,11 @@ 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 Microsoft.ML.Trainers; using Newtonsoft.Json.Linq; // This is for deserialization from a model repository. @@ -36,7 +36,7 @@ "Poisson Regression Executor", PoissonRegressionModelParameters.LoaderSignature)] -namespace Microsoft.ML.Learners +namespace Microsoft.ML.Trainers { 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 f9f64f3689..b61f443e02 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/LinearPredictorUtils.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/LinearPredictorUtils.cs @@ -13,7 +13,7 @@ using Microsoft.ML.Internal.Utilities; using Float = System.Single; -namespace Microsoft.ML.Learners +namespace Microsoft.ML.Trainers { /// /// 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 c6c6602c52..ca335e033f 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LbfgsPredictorBase.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LbfgsPredictorBase.cs @@ -14,7 +14,7 @@ using Microsoft.ML.Numeric; using Microsoft.ML.Training; -namespace Microsoft.ML.Learners +namespace Microsoft.ML.Trainers { public abstract class LbfgsTrainerBase : TrainerEstimatorBase where TTransformer : ISingleFeaturePredictionTransformer diff --git a/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LogisticRegression.cs b/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LogisticRegression.cs index 3cdb24c7df..d5fe66bdd7 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LogisticRegression.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LogisticRegression.cs @@ -13,8 +13,8 @@ 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.Trainers; using Microsoft.ML.Training; [assembly: LoadableClass(LogisticRegression.Summary, typeof(LogisticRegression), typeof(LogisticRegression.Options), @@ -26,7 +26,7 @@ [assembly: LoadableClass(typeof(void), typeof(LogisticRegression), null, typeof(SignatureEntryPointModule), LogisticRegression.LoadNameValue)] -namespace Microsoft.ML.Learners +namespace Microsoft.ML.Trainers { /// diff --git a/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/MulticlassLogisticRegression.cs b/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/MulticlassLogisticRegression.cs index 0ed3f008da..9d809dd3fa 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/MulticlassLogisticRegression.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/MulticlassLogisticRegression.cs @@ -14,7 +14,6 @@ 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; @@ -35,7 +34,7 @@ "Multiclass LR Executor", MulticlassLogisticRegressionModelParameters.LoaderSignature)] -namespace Microsoft.ML.Learners +namespace Microsoft.ML.Trainers { /// /// diff --git a/src/Microsoft.ML.StandardLearners/Standard/ModelStatistics.cs b/src/Microsoft.ML.StandardLearners/Standard/ModelStatistics.cs index b5cb2813af..e5c2854da7 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/ModelStatistics.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/ModelStatistics.cs @@ -12,15 +12,15 @@ using Microsoft.ML.Internal.CpuMath; using Microsoft.ML.Internal.Internallearn; using Microsoft.ML.Internal.Utilities; -using Microsoft.ML.Learners; using Microsoft.ML.Model; +using Microsoft.ML.Trainers; // This is for deserialization from a model repository. [assembly: LoadableClass(typeof(LinearModelStatistics), null, typeof(SignatureLoadModel), "Linear Model Statistics", LinearModelStatistics.LoaderSignature)] -namespace Microsoft.ML.Learners +namespace Microsoft.ML.Trainers { /// /// 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 fdd32f2f20..448a078a8b 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/MultiClass/MetaMulticlassTrainer.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/MultiClass/MetaMulticlassTrainer.cs @@ -14,7 +14,7 @@ using Microsoft.ML.Trainers.Online; using Microsoft.ML.Training; -namespace Microsoft.ML.Learners +namespace Microsoft.ML.Trainers { using TScalarTrainer = ITrainerEstimator>, IPredictorProducing>; diff --git a/src/Microsoft.ML.StandardLearners/Standard/MultiClass/Ova.cs b/src/Microsoft.ML.StandardLearners/Standard/MultiClass/Ova.cs index cf7a083985..53f0f35fca 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/MultiClass/Ova.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/MultiClass/Ova.cs @@ -16,7 +16,6 @@ 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.Trainers; diff --git a/src/Microsoft.ML.StandardLearners/Standard/MultiClass/Pkpd.cs b/src/Microsoft.ML.StandardLearners/Standard/MultiClass/Pkpd.cs index 5e3dd33f8b..344f9e5f6a 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/MultiClass/Pkpd.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/MultiClass/Pkpd.cs @@ -11,7 +11,6 @@ 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.Trainers; using Microsoft.ML.Training; diff --git a/src/Microsoft.ML.StandardLearners/Standard/Online/AveragedLinear.cs b/src/Microsoft.ML.StandardLearners/Standard/Online/AveragedLinear.cs index bf7a88d27d..85da68d1f9 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/Online/AveragedLinear.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/Online/AveragedLinear.cs @@ -9,7 +9,6 @@ using Microsoft.ML.EntryPoints; using Microsoft.ML.Internal.Internallearn; using Microsoft.ML.Internal.Utilities; -using Microsoft.ML.Learners; using Microsoft.ML.Numeric; // 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 b3659974fa..c3610c7dd1 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/Online/AveragedPerceptron.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/Online/AveragedPerceptron.cs @@ -11,7 +11,6 @@ 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.Trainers.Online; using Microsoft.ML.Training; diff --git a/src/Microsoft.ML.StandardLearners/Standard/Online/LinearSvm.cs b/src/Microsoft.ML.StandardLearners/Standard/Online/LinearSvm.cs index 184a6554aa..e1382b3038 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/Online/LinearSvm.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/Online/LinearSvm.cs @@ -12,7 +12,6 @@ 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.Trainers.Online; using Microsoft.ML.Training; diff --git a/src/Microsoft.ML.StandardLearners/Standard/Online/OnlineGradientDescent.cs b/src/Microsoft.ML.StandardLearners/Standard/Online/OnlineGradientDescent.cs index 39ed31a6ec..8982127170 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/Online/OnlineGradientDescent.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/Online/OnlineGradientDescent.cs @@ -10,7 +10,6 @@ using Microsoft.ML.Data; using Microsoft.ML.EntryPoints; using Microsoft.ML.Internal.Internallearn; -using Microsoft.ML.Learners; using Microsoft.ML.Numeric; using Microsoft.ML.Trainers.Online; using Microsoft.ML.Training; diff --git a/src/Microsoft.ML.StandardLearners/Standard/Online/OnlineLinear.cs b/src/Microsoft.ML.StandardLearners/Standard/Online/OnlineLinear.cs index 662afe9a01..b41890a5fa 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/Online/OnlineLinear.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/Online/OnlineLinear.cs @@ -11,7 +11,6 @@ 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; diff --git a/src/Microsoft.ML.StandardLearners/Standard/PoissonRegression/PoissonRegression.cs b/src/Microsoft.ML.StandardLearners/Standard/PoissonRegression/PoissonRegression.cs index caf4a37166..b389fc6034 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/PoissonRegression/PoissonRegression.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/PoissonRegression/PoissonRegression.cs @@ -10,7 +10,6 @@ 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.Trainers; using Microsoft.ML.Training; diff --git a/src/Microsoft.ML.StandardLearners/Standard/SdcaBinary.cs b/src/Microsoft.ML.StandardLearners/Standard/SdcaBinary.cs index 191c906b78..ca07f7fbe5 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/SdcaBinary.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/SdcaBinary.cs @@ -18,7 +18,6 @@ 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.Trainers; using Microsoft.ML.Training; diff --git a/src/Microsoft.ML.StandardLearners/Standard/SdcaMultiClass.cs b/src/Microsoft.ML.StandardLearners/Standard/SdcaMultiClass.cs index aceabb7b82..ff49788028 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/SdcaMultiClass.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/SdcaMultiClass.cs @@ -14,7 +14,6 @@ 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.Trainers; using Microsoft.ML.Training; diff --git a/src/Microsoft.ML.StandardLearners/Standard/SdcaRegression.cs b/src/Microsoft.ML.StandardLearners/Standard/SdcaRegression.cs index 49b65abe89..9524c48365 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/SdcaRegression.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/SdcaRegression.cs @@ -12,7 +12,6 @@ using Microsoft.ML.EntryPoints; using Microsoft.ML.Internal.Internallearn; using Microsoft.ML.Internal.Utilities; -using Microsoft.ML.Learners; using Microsoft.ML.Trainers; using Microsoft.ML.Training; diff --git a/src/Microsoft.ML.StandardLearners/Standard/StochasticTrainerBase.cs b/src/Microsoft.ML.StandardLearners/Standard/StochasticTrainerBase.cs index 10fa3b75c8..d9265513f8 100644 --- a/src/Microsoft.ML.StandardLearners/Standard/StochasticTrainerBase.cs +++ b/src/Microsoft.ML.StandardLearners/Standard/StochasticTrainerBase.cs @@ -10,7 +10,7 @@ using Microsoft.ML.Training; using Microsoft.ML.Transforms; -namespace Microsoft.ML.Learners +namespace Microsoft.ML.Trainers { 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 6442e4eb01..ae03b46bc8 100644 --- a/src/Microsoft.ML.StandardLearners/StandardLearnersCatalog.cs +++ b/src/Microsoft.ML.StandardLearners/StandardLearnersCatalog.cs @@ -5,7 +5,6 @@ using System; using Microsoft.ML.Data; using Microsoft.ML.Internal.Calibration; -using Microsoft.ML.Learners; using Microsoft.ML.Trainers; using Microsoft.ML.Trainers.Online; using Microsoft.ML.Training; @@ -293,7 +292,7 @@ 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 catalog trainer object. /// The label column name, or dependent variable. @@ -302,7 +301,7 @@ 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. /// /// @@ -327,7 +326,7 @@ public static LogisticRegression LogisticRegression(this BinaryClassificationCat } /// - /// 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 catalog trainer object. /// Advanced arguments to the algorithm. @@ -341,7 +340,7 @@ public static LogisticRegression LogisticRegression(this BinaryClassificationCat } /// - /// 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 catalog trainer object. /// The labelColumn, or dependent variable. @@ -350,7 +349,7 @@ public static LogisticRegression LogisticRegression(this BinaryClassificationCat /// 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. public static PoissonRegression PoissonRegression(this RegressionCatalog.RegressionTrainers catalog, string labelColumn = DefaultColumnNames.Label, @@ -368,7 +367,7 @@ public static PoissonRegression PoissonRegression(this RegressionCatalog.Regress } /// - /// 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 catalog trainer object. /// Advanced arguments to the algorithm. @@ -382,7 +381,7 @@ public static PoissonRegression PoissonRegression(this RegressionCatalog.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. @@ -391,7 +390,7 @@ public static PoissonRegression PoissonRegression(this RegressionCatalog.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. public static MulticlassLogisticRegression LogisticRegression(this MulticlassClassificationCatalog.MulticlassClassificationTrainers catalog, string labelColumn = DefaultColumnNames.Label, @@ -409,7 +408,7 @@ public static MulticlassLogisticRegression LogisticRegression(this MulticlassCla } /// - /// 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 . /// Advanced arguments to the algorithm. diff --git a/src/Microsoft.ML.StaticPipe/LbfgsStatic.cs b/src/Microsoft.ML.StaticPipe/LbfgsStatic.cs index 5de22b6e89..7e2ed821c7 100644 --- a/src/Microsoft.ML.StaticPipe/LbfgsStatic.cs +++ b/src/Microsoft.ML.StaticPipe/LbfgsStatic.cs @@ -6,7 +6,6 @@ using Microsoft.ML.Data; using Microsoft.ML.EntryPoints; using Microsoft.ML.Internal.Calibration; -using Microsoft.ML.Learners; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Trainers; @@ -20,7 +19,7 @@ namespace Microsoft.ML.StaticPipe public static class LbfgsBinaryClassificationStaticExtensions { /// - /// 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 catalog trainer object. /// The label, or dependent variable. @@ -29,7 +28,7 @@ public static class LbfgsBinaryClassificationStaticExtensions /// 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 @@ -66,7 +65,7 @@ public static (Scalar score, Scalar probability, Scalar pred } /// - /// 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 catalog trainer object. /// The label, or dependent variable. @@ -116,7 +115,7 @@ public static (Scalar score, Scalar probability, Scalar pred 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 catalog trainer object. /// The label, or dependent variable. @@ -125,7 +124,7 @@ 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 that is called every time the /// method is called on the @@ -162,7 +161,7 @@ public static Scalar PoissonRegression(this RegressionCatalog.RegressionT } /// - /// 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 catalog trainer object. /// The label, or dependent variable. @@ -212,7 +211,7 @@ public static Scalar PoissonRegression(this RegressionCatalog.RegressionT 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 catalog trainer object. /// The label, or dependent variable. @@ -221,7 +220,7 @@ 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 that is called every time the /// method is called on the @@ -258,7 +257,7 @@ public static (Vector score, Key predictedLabel) } /// - /// 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 catalog trainer object. /// The label, or dependent variable. diff --git a/src/Microsoft.ML.StaticPipe/OnlineLearnerStatic.cs b/src/Microsoft.ML.StaticPipe/OnlineLearnerStatic.cs index fea4867428..38165451a6 100644 --- a/src/Microsoft.ML.StaticPipe/OnlineLearnerStatic.cs +++ b/src/Microsoft.ML.StaticPipe/OnlineLearnerStatic.cs @@ -3,8 +3,8 @@ // See the LICENSE file in the project root for more information. using System; -using Microsoft.ML.Learners; using Microsoft.ML.StaticPipe.Runtime; +using Microsoft.ML.Trainers; using Microsoft.ML.Trainers.Online; namespace Microsoft.ML.StaticPipe diff --git a/src/Microsoft.ML.StaticPipe/SdcaStaticExtensions.cs b/src/Microsoft.ML.StaticPipe/SdcaStaticExtensions.cs index 444a9fd7bc..62bc7f5e48 100644 --- a/src/Microsoft.ML.StaticPipe/SdcaStaticExtensions.cs +++ b/src/Microsoft.ML.StaticPipe/SdcaStaticExtensions.cs @@ -4,7 +4,6 @@ using System; using Microsoft.ML.Internal.Calibration; -using Microsoft.ML.Learners; using Microsoft.ML.StaticPipe.Runtime; using Microsoft.ML.Trainers; diff --git a/test/Microsoft.ML.Benchmarks/KMeansAndLogisticRegressionBench.cs b/test/Microsoft.ML.Benchmarks/KMeansAndLogisticRegressionBench.cs index 3c92045b31..870480ebbc 100644 --- a/test/Microsoft.ML.Benchmarks/KMeansAndLogisticRegressionBench.cs +++ b/test/Microsoft.ML.Benchmarks/KMeansAndLogisticRegressionBench.cs @@ -6,8 +6,8 @@ using Microsoft.ML.Benchmarks.Harness; using Microsoft.ML.Data; using Microsoft.ML.Internal.Calibration; -using Microsoft.ML.Learners; using Microsoft.ML.TestFramework; +using Microsoft.ML.Trainers; namespace Microsoft.ML.Benchmarks { diff --git a/test/Microsoft.ML.Benchmarks/StochasticDualCoordinateAscentClassifierBench.cs b/test/Microsoft.ML.Benchmarks/StochasticDualCoordinateAscentClassifierBench.cs index 7c67d13ac4..c08118bee6 100644 --- a/test/Microsoft.ML.Benchmarks/StochasticDualCoordinateAscentClassifierBench.cs +++ b/test/Microsoft.ML.Benchmarks/StochasticDualCoordinateAscentClassifierBench.cs @@ -9,7 +9,6 @@ using Microsoft.Data.DataView; using Microsoft.ML.Benchmarks.Harness; using Microsoft.ML.Data; -using Microsoft.ML.Learners; using Microsoft.ML.TestFramework; using Microsoft.ML.Trainers; using Microsoft.ML.Transforms; diff --git a/test/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs b/test/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs index 8fcb00842e..b159d2b659 100644 --- a/test/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs +++ b/test/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs @@ -20,14 +20,13 @@ 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.HalLearners; using Microsoft.ML.Trainers.PCA; -using Microsoft.ML.Trainers.SymSgd; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Categorical; using Microsoft.ML.Transforms.Conversions; diff --git a/test/Microsoft.ML.Predictor.Tests/TestPredictors.cs b/test/Microsoft.ML.Predictor.Tests/TestPredictors.cs index 339bede3e5..17b3971741 100644 --- a/test/Microsoft.ML.Predictor.Tests/TestPredictors.cs +++ b/test/Microsoft.ML.Predictor.Tests/TestPredictors.cs @@ -17,14 +17,13 @@ namespace Microsoft.ML.RunTests using Microsoft.ML.Ensemble; using Microsoft.ML.EntryPoints; using Microsoft.ML.Internal.Utilities; - using Microsoft.ML.Learners; using Microsoft.ML.LightGBM; using Microsoft.ML.TestFramework; + using Microsoft.ML.Trainers; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Trainers.FastTree.Internal; + using Microsoft.ML.Trainers.HalLearners; using Microsoft.ML.Trainers.Online; - using Microsoft.ML.Trainers.SymSgd; - using Microsoft.ML.Transforms.Categorical; using Xunit; using Xunit.Abstractions; using TestLearners = TestLearnersBase; diff --git a/test/Microsoft.ML.StaticPipelineTesting/Training.cs b/test/Microsoft.ML.StaticPipelineTesting/Training.cs index 1fdb3bae66..a1f81dfe25 100644 --- a/test/Microsoft.ML.StaticPipelineTesting/Training.cs +++ b/test/Microsoft.ML.StaticPipelineTesting/Training.cs @@ -8,9 +8,9 @@ using Microsoft.ML; using Microsoft.ML.Data; using Microsoft.ML.FactorizationMachine; +using Microsoft.ML.HalLearners; using Microsoft.ML.Internal.Calibration; using Microsoft.ML.Internal.Internallearn; -using Microsoft.ML.Learners; using Microsoft.ML.LightGBM; using Microsoft.ML.LightGBM.StaticPipe; using Microsoft.ML.RunTests; diff --git a/test/Microsoft.ML.TestFramework/EnvironmentExtensions.cs b/test/Microsoft.ML.TestFramework/EnvironmentExtensions.cs index 1b8cbdcb60..36fccc7980 100644 --- a/test/Microsoft.ML.TestFramework/EnvironmentExtensions.cs +++ b/test/Microsoft.ML.TestFramework/EnvironmentExtensions.cs @@ -5,7 +5,7 @@ using Microsoft.ML.Data; using Microsoft.ML.Ensemble; using Microsoft.ML.EntryPoints; -using Microsoft.ML.Learners; +using Microsoft.ML.Trainers; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Trainers.KMeans; using Microsoft.ML.Trainers.PCA; diff --git a/test/Microsoft.ML.Tests/OnnxConversionTest.cs b/test/Microsoft.ML.Tests/OnnxConversionTest.cs index f5b062c31a..00b7435d91 100644 --- a/test/Microsoft.ML.Tests/OnnxConversionTest.cs +++ b/test/Microsoft.ML.Tests/OnnxConversionTest.cs @@ -11,10 +11,10 @@ using Google.Protobuf; using Microsoft.Data.DataView; using Microsoft.ML.Data; -using Microsoft.ML.Learners; using Microsoft.ML.Model.Onnx; using Microsoft.ML.RunTests; using Microsoft.ML.Tools; +using Microsoft.ML.Trainers; using Microsoft.ML.Transforms; using Microsoft.ML.UniversalModelFormat.Onnx; using Newtonsoft.Json; diff --git a/test/Microsoft.ML.Tests/PermutationFeatureImportanceTests.cs b/test/Microsoft.ML.Tests/PermutationFeatureImportanceTests.cs index e6fa53c584..6be9b0adfe 100644 --- a/test/Microsoft.ML.Tests/PermutationFeatureImportanceTests.cs +++ b/test/Microsoft.ML.Tests/PermutationFeatureImportanceTests.cs @@ -8,8 +8,8 @@ using Microsoft.Data.DataView; using Microsoft.ML.Data; using Microsoft.ML.Internal.Utilities; -using Microsoft.ML.Learners; using Microsoft.ML.RunTests; +using Microsoft.ML.Trainers; 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 01501677be..eab7d56fdb 100644 --- a/test/Microsoft.ML.Tests/Scenarios/Api/CookbookSamples/CookbookSamples.cs +++ b/test/Microsoft.ML.Tests/Scenarios/Api/CookbookSamples/CookbookSamples.cs @@ -10,7 +10,6 @@ using Microsoft.ML; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Learners; using Microsoft.ML.RunTests; using Microsoft.ML.StaticPipe; using Microsoft.ML.TestFramework; diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/CookbookSamples/CookbookSamplesDynamicApi.cs b/test/Microsoft.ML.Tests/Scenarios/Api/CookbookSamples/CookbookSamplesDynamicApi.cs index 39957cc031..a0ef508417 100644 --- a/test/Microsoft.ML.Tests/Scenarios/Api/CookbookSamples/CookbookSamplesDynamicApi.cs +++ b/test/Microsoft.ML.Tests/Scenarios/Api/CookbookSamples/CookbookSamplesDynamicApi.cs @@ -11,9 +11,9 @@ using Microsoft.Data.DataView; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Learners; using Microsoft.ML.RunTests; using Microsoft.ML.TestFramework; +using Microsoft.ML.Trainers; using Microsoft.ML.Transforms.Categorical; using Microsoft.ML.Transforms.Normalizers; using Microsoft.ML.Transforms.Text; diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/SimpleTrainAndPredict.cs b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/SimpleTrainAndPredict.cs index 6d70b43d61..7a328c73d6 100644 --- a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/SimpleTrainAndPredict.cs +++ b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/SimpleTrainAndPredict.cs @@ -6,7 +6,7 @@ using Microsoft.ML.Data; using Microsoft.ML.RunTests; using Microsoft.ML.Trainers; -using Microsoft.ML.Trainers.SymSgd; +using Microsoft.ML.Trainers.HalLearners; using Xunit; namespace Microsoft.ML.Tests.Scenarios.Api diff --git a/test/Microsoft.ML.Tests/Scenarios/OvaTest.cs b/test/Microsoft.ML.Tests/Scenarios/OvaTest.cs index ecea5411a6..1ef0cda99c 100644 --- a/test/Microsoft.ML.Tests/Scenarios/OvaTest.cs +++ b/test/Microsoft.ML.Tests/Scenarios/OvaTest.cs @@ -3,8 +3,6 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Learners; -using Microsoft.ML.Trainers; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Trainers.Online; using Xunit; diff --git a/test/Microsoft.ML.Tests/TrainerEstimators/CalibratorEstimators.cs b/test/Microsoft.ML.Tests/TrainerEstimators/CalibratorEstimators.cs index b3f4207de4..3de1a3125a 100644 --- a/test/Microsoft.ML.Tests/TrainerEstimators/CalibratorEstimators.cs +++ b/test/Microsoft.ML.Tests/TrainerEstimators/CalibratorEstimators.cs @@ -6,8 +6,7 @@ using Microsoft.ML.Calibrator; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -using Microsoft.ML.Learners; -using Microsoft.ML.Trainers.Online; +using Microsoft.ML.Trainers; using Xunit; namespace Microsoft.ML.Tests.TrainerEstimators diff --git a/test/Microsoft.ML.Tests/TrainerEstimators/LbfgsTests.cs b/test/Microsoft.ML.Tests/TrainerEstimators/LbfgsTests.cs index 134b52f96e..4e61c3480b 100644 --- a/test/Microsoft.ML.Tests/TrainerEstimators/LbfgsTests.cs +++ b/test/Microsoft.ML.Tests/TrainerEstimators/LbfgsTests.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.Linq; using Microsoft.Data.DataView; using Microsoft.ML.Core.Data; using Microsoft.ML.Data; using Microsoft.ML.Internal.Calibration; -using Microsoft.ML.Learners; 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 5b1a698e95..1b4dbf86e2 100644 --- a/test/Microsoft.ML.Tests/TrainerEstimators/SymSgdClassificationTests.cs +++ b/test/Microsoft.ML.Tests/TrainerEstimators/SymSgdClassificationTests.cs @@ -4,10 +4,9 @@ using System.Linq; using Microsoft.ML.Data; +using Microsoft.ML.Trainers.HalLearners; using Microsoft.ML.Internal.Calibration; -using Microsoft.ML.Learners; using Microsoft.ML.Trainers; -using Microsoft.ML.Trainers.SymSgd; using Xunit; namespace Microsoft.ML.Tests.TrainerEstimators From 2b60c6de14eb0d5403c518a2ccecfdd6d34de903 Mon Sep 17 00:00:00 2001 From: Senja Filipi Date: Wed, 6 Feb 2019 13:38:08 -0800 Subject: [PATCH 2/3] removing the Microsoft.ML.Internal.Internallearn.ResultProcessor and the Microsoft.ML.Trainers.FastTree.Internal namespaces. --- .../EntryPoints/CreateEnsemble.cs | 3 +-- .../EntryPoints/DiversityMeasure.cs | 4 ++-- src/Microsoft.ML.Ensemble/EntryPoints/Ensemble.cs | 4 ++-- .../EntryPoints/FeatureSelector.cs | 4 ++-- .../EntryPoints/OutputCombiner.cs | 4 ++-- .../EntryPoints/PipelineEnsemble.cs | 4 ++-- .../EntryPoints/SubModelSelector.cs | 4 ++-- .../SubModelSelector/BestDiverseSelectorBinary.cs | 3 --- .../SubModelSelector/BestDiverseSelectorMultiClass.cs | 3 --- .../SubModelSelector/BestDiverseSelectorRegression.cs | 3 --- .../Selector/SubsetSelector/BaseSubsetSelector.cs | 1 - .../Trainer/Binary/EnsembleTrainer.cs | 1 - .../MulticlassDataPartitionEnsembleTrainer.cs | 1 - .../Trainer/Regression/RegressionEnsembleTrainer.cs | 1 - src/Microsoft.ML.FastTree/BinFile/BinFinder.cs | 2 +- .../BinFile/IniFileParserInterface.cs | 2 +- src/Microsoft.ML.FastTree/BoostingFastTree.cs | 1 - src/Microsoft.ML.FastTree/Dataset/Dataset.cs | 2 +- src/Microsoft.ML.FastTree/Dataset/DatasetUtils.cs | 2 +- src/Microsoft.ML.FastTree/Dataset/DenseIntArray.cs | 2 +- src/Microsoft.ML.FastTree/Dataset/Feature.cs | 2 +- src/Microsoft.ML.FastTree/Dataset/FeatureFlock.cs | 2 +- src/Microsoft.ML.FastTree/Dataset/FeatureHistogram.cs | 2 +- src/Microsoft.ML.FastTree/Dataset/FileObjectStore.cs | 2 +- src/Microsoft.ML.FastTree/Dataset/IntArray.cs | 2 +- src/Microsoft.ML.FastTree/Dataset/NHotFeatureFlock.cs | 2 +- .../Dataset/OneHotFeatureFlock.cs | 2 +- src/Microsoft.ML.FastTree/Dataset/RepeatIntArray.cs | 2 +- src/Microsoft.ML.FastTree/Dataset/SegmentIntArray.cs | 2 +- .../Dataset/SingletonFeatureFlock.cs | 2 +- src/Microsoft.ML.FastTree/Dataset/SparseIntArray.cs | 2 +- src/Microsoft.ML.FastTree/FastTree.cs | 1 - src/Microsoft.ML.FastTree/FastTreeClassification.cs | 1 - src/Microsoft.ML.FastTree/FastTreeRanking.cs | 1 - src/Microsoft.ML.FastTree/FastTreeRegression.cs | 2 -- src/Microsoft.ML.FastTree/FastTreeTweedie.cs | 1 - src/Microsoft.ML.FastTree/GamClassification.cs | 1 - src/Microsoft.ML.FastTree/GamModelParameters.cs | 1 - src/Microsoft.ML.FastTree/GamRegression.cs | 2 -- src/Microsoft.ML.FastTree/GamTrainer.cs | 3 --- src/Microsoft.ML.FastTree/RandomForest.cs | 2 -- .../RandomForestClassification.cs | 1 - src/Microsoft.ML.FastTree/RandomForestRegression.cs | 1 - src/Microsoft.ML.FastTree/RegressionTree.cs | 2 +- src/Microsoft.ML.FastTree/SumupPerformanceCommand.cs | 3 +-- .../Training/Applications/GradientWrappers.cs | 2 +- .../Training/Applications/ObjectiveFunction.cs | 2 +- src/Microsoft.ML.FastTree/Training/BaggingProvider.cs | 2 +- src/Microsoft.ML.FastTree/Training/DcgCalculator.cs | 2 +- .../Training/DcgPermutationComparer.cs | 2 +- .../Training/DocumentPartitioning.cs | 2 +- .../EnsembleCompression/IEnsembleCompressor.cs | 2 +- .../LassoBasedEnsembleCompressor.cs | 2 +- .../Training/EnsembleCompression/LassoFit.cs | 2 +- .../AcceleratedGradientDescent.cs | 2 +- .../ConjugateGradientDescent.cs | 2 +- .../OptimizationAlgorithms/GradientDescent.cs | 2 +- .../OptimizationAlgorithms/NoOptimizationAlgorithm.cs | 2 +- .../OptimizationAlgorithms/OptimizationAlgorithm.cs | 2 +- .../Training/Parallel/IParallelTraining.cs | 1 - .../Training/Parallel/SingleTrainer.cs | 5 ++--- .../Training/RegressionTreeNodeDocuments.cs | 2 +- src/Microsoft.ML.FastTree/Training/ScoreTracker.cs | 2 +- src/Microsoft.ML.FastTree/Training/StepSearch.cs | 2 +- src/Microsoft.ML.FastTree/Training/Test.cs | 2 +- .../TreeLearners/FastForestLeastSquaresTreeLearner.cs | 2 +- .../TreeLearners/LeastSquaresRegressionTreeLearner.cs | 2 +- .../Training/TreeLearners/TreeLearner.cs | 2 +- .../Training/WinLossCalculator.cs | 2 +- .../TreeEnsemble/InternalQuantileRegressionTree.cs | 2 +- .../TreeEnsemble/InternalRegressionTree.cs | 2 +- .../TreeEnsemble/InternalTreeEnsemble.cs | 2 +- .../TreeEnsemble/TreeEnsembleCombiner.cs | 5 ++--- src/Microsoft.ML.FastTree/Utils/Algorithms.cs | 2 +- src/Microsoft.ML.FastTree/Utils/BlockingThreadPool.cs | 2 +- src/Microsoft.ML.FastTree/Utils/BufferPoolManager.cs | 2 +- src/Microsoft.ML.FastTree/Utils/CompressUtils.cs | 2 +- .../Utils/FastTreeIniFileUtils.cs | 2 +- src/Microsoft.ML.FastTree/Utils/LinqExtensions.cs | 2 +- src/Microsoft.ML.FastTree/Utils/MD5Hasher.cs | 2 +- src/Microsoft.ML.FastTree/Utils/MappedObjectPool.cs | 2 +- .../Utils/PseudorandomFunction.cs | 2 +- src/Microsoft.ML.FastTree/Utils/StreamExtensions.cs | 2 +- src/Microsoft.ML.FastTree/Utils/ThreadTaskManager.cs | 2 +- src/Microsoft.ML.FastTree/Utils/Timer.cs | 2 +- .../Utils/ToByteArrayExtensions.cs | 2 +- src/Microsoft.ML.FastTree/Utils/VectorUtils.cs | 2 +- src/Microsoft.ML.LightGBM/LightGbmBinaryTrainer.cs | 1 - .../LightGbmMulticlassTrainer.cs | 2 +- src/Microsoft.ML.LightGBM/LightGbmRankingTrainer.cs | 1 - .../LightGbmRegressionTrainer.cs | 1 - src/Microsoft.ML.LightGBM/LightGbmTrainerBase.cs | 2 +- src/Microsoft.ML.LightGBM/WrappedLightGbmBooster.cs | 2 +- src/Microsoft.ML.ResultProcessor/ResultProcessor.cs | 3 ++- src/Microsoft.ML.Sweeper/Algorithms/KdoSweeper.cs | 2 +- src/Microsoft.ML.Sweeper/Algorithms/SmacSweeper.cs | 1 - src/Microsoft.ML.Sweeper/ConfigRunner.cs | 2 +- src/Microsoft.ML.Sweeper/SweepResultEvaluator.cs | 2 +- .../UnitTests/TestEntryPoints.cs | 2 +- .../UnitTests/TestUtilities.cs | 1 - .../TestParallelFasttreeInterface.cs | 2 +- test/Microsoft.ML.Predictor.Tests/TestPredictors.cs | 1 - test/Microsoft.ML.StaticPipelineTesting/Training.cs | 8 +++----- .../BaseTestPredictorsMaml.cs | 2 +- .../Scenarios/Api/Estimators/IntrospectiveTraining.cs | 2 +- .../TrainerEstimators/TreeEnsembleFeaturizerTest.cs | 11 +++++------ .../TrainerEstimators/TreeEstimators.cs | 2 +- 107 files changed, 95 insertions(+), 139 deletions(-) diff --git a/src/Microsoft.ML.Ensemble/EntryPoints/CreateEnsemble.cs b/src/Microsoft.ML.Ensemble/EntryPoints/CreateEnsemble.cs index cf88c501b8..baad8e2ca9 100644 --- a/src/Microsoft.ML.Ensemble/EntryPoints/CreateEnsemble.cs +++ b/src/Microsoft.ML.Ensemble/EntryPoints/CreateEnsemble.cs @@ -11,14 +11,13 @@ using Microsoft.ML.CommandLine; using Microsoft.ML.Data; using Microsoft.ML.Ensemble; -using Microsoft.ML.Ensemble.EntryPoints; 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.EntryPoints +namespace Microsoft.ML.Ensemble { /// /// 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 83d8fd0a96..069cce2556 100644 --- a/src/Microsoft.ML.Ensemble/EntryPoints/DiversityMeasure.cs +++ b/src/Microsoft.ML.Ensemble/EntryPoints/DiversityMeasure.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.Ensemble.EntryPoints; +using Microsoft.ML.Ensemble; using Microsoft.ML.Ensemble.Selector; using Microsoft.ML.Ensemble.Selector.DiversityMeasure; using Microsoft.ML.EntryPoints; @@ -11,7 +11,7 @@ [assembly: EntryPointModule(typeof(RegressionDisagreementDiversityFactory))] [assembly: EntryPointModule(typeof(MultiDisagreementDiversityFactory))] -namespace Microsoft.ML.Ensemble.EntryPoints +namespace Microsoft.ML.Ensemble { [TlcModule.Component(Name = DisagreementDiversityMeasure.LoadName, FriendlyName = DisagreementDiversityMeasure.UserName)] internal sealed class DisagreementDiversityFactory : ISupportBinaryDiversityMeasureFactory diff --git a/src/Microsoft.ML.Ensemble/EntryPoints/Ensemble.cs b/src/Microsoft.ML.Ensemble/EntryPoints/Ensemble.cs index 6cf8b418bc..4aa0ab10ce 100644 --- a/src/Microsoft.ML.Ensemble/EntryPoints/Ensemble.cs +++ b/src/Microsoft.ML.Ensemble/EntryPoints/Ensemble.cs @@ -3,12 +3,12 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML; -using Microsoft.ML.Ensemble.EntryPoints; +using Microsoft.ML.Ensemble; using Microsoft.ML.EntryPoints; [assembly: LoadableClass(typeof(void), typeof(Ensemble), null, typeof(SignatureEntryPointModule), "TrainEnsemble")] -namespace Microsoft.ML.Ensemble.EntryPoints +namespace Microsoft.ML.Ensemble { internal static class Ensemble { diff --git a/src/Microsoft.ML.Ensemble/EntryPoints/FeatureSelector.cs b/src/Microsoft.ML.Ensemble/EntryPoints/FeatureSelector.cs index c2d7862a31..66ae78ecb5 100644 --- a/src/Microsoft.ML.Ensemble/EntryPoints/FeatureSelector.cs +++ b/src/Microsoft.ML.Ensemble/EntryPoints/FeatureSelector.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.Ensemble.EntryPoints; +using Microsoft.ML.Ensemble; using Microsoft.ML.Ensemble.Selector; using Microsoft.ML.Ensemble.Selector.FeatureSelector; using Microsoft.ML.EntryPoints; @@ -10,7 +10,7 @@ [assembly: EntryPointModule(typeof(AllFeatureSelectorFactory))] [assembly: EntryPointModule(typeof(RandomFeatureSelector))] -namespace Microsoft.ML.Ensemble.EntryPoints +namespace Microsoft.ML.Ensemble { [TlcModule.Component(Name = AllFeatureSelector.LoadName, FriendlyName = AllFeatureSelector.UserName)] public sealed class AllFeatureSelectorFactory : ISupportFeatureSelectorFactory diff --git a/src/Microsoft.ML.Ensemble/EntryPoints/OutputCombiner.cs b/src/Microsoft.ML.Ensemble/EntryPoints/OutputCombiner.cs index 7583d72cfb..da10f30de4 100644 --- a/src/Microsoft.ML.Ensemble/EntryPoints/OutputCombiner.cs +++ b/src/Microsoft.ML.Ensemble/EntryPoints/OutputCombiner.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.Ensemble.EntryPoints; +using Microsoft.ML.Ensemble; using Microsoft.ML.Ensemble.OutputCombiners; using Microsoft.ML.EntryPoints; @@ -18,7 +18,7 @@ [assembly: EntryPointModule(typeof(VotingFactory))] [assembly: EntryPointModule(typeof(WeightedAverage))] -namespace Microsoft.ML.Ensemble.EntryPoints +namespace Microsoft.ML.Ensemble { [TlcModule.Component(Name = Average.LoadName, FriendlyName = Average.UserName)] public sealed class AverageFactory : ISupportBinaryOutputCombinerFactory, ISupportRegressionOutputCombinerFactory diff --git a/src/Microsoft.ML.Ensemble/EntryPoints/PipelineEnsemble.cs b/src/Microsoft.ML.Ensemble/EntryPoints/PipelineEnsemble.cs index c80dba1738..9452a9d064 100644 --- a/src/Microsoft.ML.Ensemble/EntryPoints/PipelineEnsemble.cs +++ b/src/Microsoft.ML.Ensemble/EntryPoints/PipelineEnsemble.cs @@ -4,13 +4,13 @@ using Microsoft.Data.DataView; using Microsoft.ML.Data; -using Microsoft.ML.Ensemble.EntryPoints; +using Microsoft.ML.Ensemble; using Microsoft.ML.EntryPoints; using Microsoft.ML.Internal.Calibration; [assembly: EntryPointModule(typeof(PipelineEnsemble))] -namespace Microsoft.ML.Ensemble.EntryPoints +namespace Microsoft.ML.Ensemble { internal static class PipelineEnsemble { diff --git a/src/Microsoft.ML.Ensemble/EntryPoints/SubModelSelector.cs b/src/Microsoft.ML.Ensemble/EntryPoints/SubModelSelector.cs index 10b1551c62..b749501f76 100644 --- a/src/Microsoft.ML.Ensemble/EntryPoints/SubModelSelector.cs +++ b/src/Microsoft.ML.Ensemble/EntryPoints/SubModelSelector.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.Ensemble.EntryPoints; +using Microsoft.ML.Ensemble; using Microsoft.ML.Ensemble.Selector; using Microsoft.ML.Ensemble.Selector.SubModelSelector; using Microsoft.ML.EntryPoints; @@ -16,7 +16,7 @@ [assembly: EntryPointModule(typeof(BestPerformanceSelector))] [assembly: EntryPointModule(typeof(BestPerformanceSelectorMultiClass))] -namespace Microsoft.ML.Ensemble.EntryPoints +namespace Microsoft.ML.Ensemble { [TlcModule.Component(Name = AllSelector.LoadName, FriendlyName = AllSelector.UserName)] public sealed class AllSelectorFactory : ISupportBinarySubModelSelectorFactory, ISupportRegressionSubModelSelectorFactory diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorBinary.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorBinary.cs index e2a0147f01..3b2204af4a 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorBinary.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorBinary.cs @@ -7,7 +7,6 @@ using System.Collections.Generic; using Microsoft.ML; using Microsoft.ML.CommandLine; -using Microsoft.ML.Ensemble.EntryPoints; using Microsoft.ML.Ensemble.Selector; using Microsoft.ML.Ensemble.Selector.DiversityMeasure; using Microsoft.ML.Ensemble.Selector.SubModelSelector; @@ -19,8 +18,6 @@ namespace Microsoft.ML.Ensemble.Selector.SubModelSelector { - using TScalarPredictor = IPredictorProducing; - internal sealed class BestDiverseSelectorBinary : BaseDiverseSelector, IBinarySubModelSelector { public const string UserName = "Best Diverse Selector"; diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorMultiClass.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorMultiClass.cs index a25fe4d8d1..8bae59d1f5 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorMultiClass.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorMultiClass.cs @@ -8,7 +8,6 @@ using Microsoft.ML; using Microsoft.ML.CommandLine; using Microsoft.ML.Data; -using Microsoft.ML.Ensemble.EntryPoints; using Microsoft.ML.Ensemble.Selector; using Microsoft.ML.Ensemble.Selector.DiversityMeasure; using Microsoft.ML.Ensemble.Selector.SubModelSelector; @@ -20,8 +19,6 @@ namespace Microsoft.ML.Ensemble.Selector.SubModelSelector { - using TVectorPredictor = IPredictorProducing>; - internal sealed class BestDiverseSelectorMultiClass : BaseDiverseSelector, IDiversityMeasure>>, IMulticlassSubModelSelector { public const string UserName = "Best Diverse Selector"; diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorRegression.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorRegression.cs index ef310eab7e..132f691034 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorRegression.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorRegression.cs @@ -7,7 +7,6 @@ using System.Collections.Generic; using Microsoft.ML; using Microsoft.ML.CommandLine; -using Microsoft.ML.Ensemble.EntryPoints; using Microsoft.ML.Ensemble.Selector; using Microsoft.ML.Ensemble.Selector.DiversityMeasure; using Microsoft.ML.Ensemble.Selector.SubModelSelector; @@ -19,8 +18,6 @@ namespace Microsoft.ML.Ensemble.Selector.SubModelSelector { - using TScalarPredictor = IPredictorProducing; - internal sealed class BestDiverseSelectorRegression : BaseDiverseSelector, IRegressionSubModelSelector { public const string UserName = "Best Diverse Selector"; diff --git a/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/BaseSubsetSelector.cs b/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/BaseSubsetSelector.cs index a17ea20d88..8504525012 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/BaseSubsetSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/BaseSubsetSelector.cs @@ -6,7 +6,6 @@ using System.Collections.Generic; using Microsoft.ML.CommandLine; using Microsoft.ML.Data; -using Microsoft.ML.Ensemble.EntryPoints; using Microsoft.ML.Transforms; namespace Microsoft.ML.Ensemble.Selector.SubsetSelector diff --git a/src/Microsoft.ML.Ensemble/Trainer/Binary/EnsembleTrainer.cs b/src/Microsoft.ML.Ensemble/Trainer/Binary/EnsembleTrainer.cs index 959a5b20ed..d63a183f2c 100644 --- a/src/Microsoft.ML.Ensemble/Trainer/Binary/EnsembleTrainer.cs +++ b/src/Microsoft.ML.Ensemble/Trainer/Binary/EnsembleTrainer.cs @@ -8,7 +8,6 @@ using Microsoft.ML; using Microsoft.ML.CommandLine; using Microsoft.ML.Ensemble; -using Microsoft.ML.Ensemble.EntryPoints; using Microsoft.ML.Ensemble.OutputCombiners; using Microsoft.ML.Ensemble.Selector; using Microsoft.ML.Internal.Internallearn; diff --git a/src/Microsoft.ML.Ensemble/Trainer/Multiclass/MulticlassDataPartitionEnsembleTrainer.cs b/src/Microsoft.ML.Ensemble/Trainer/Multiclass/MulticlassDataPartitionEnsembleTrainer.cs index d15b9a2596..9f5446d327 100644 --- a/src/Microsoft.ML.Ensemble/Trainer/Multiclass/MulticlassDataPartitionEnsembleTrainer.cs +++ b/src/Microsoft.ML.Ensemble/Trainer/Multiclass/MulticlassDataPartitionEnsembleTrainer.cs @@ -9,7 +9,6 @@ using Microsoft.ML.CommandLine; using Microsoft.ML.Data; using Microsoft.ML.Ensemble; -using Microsoft.ML.Ensemble.EntryPoints; using Microsoft.ML.Ensemble.OutputCombiners; using Microsoft.ML.Ensemble.Selector; using Microsoft.ML.Internal.Internallearn; diff --git a/src/Microsoft.ML.Ensemble/Trainer/Regression/RegressionEnsembleTrainer.cs b/src/Microsoft.ML.Ensemble/Trainer/Regression/RegressionEnsembleTrainer.cs index 172ed62fc4..a4075c9c94 100644 --- a/src/Microsoft.ML.Ensemble/Trainer/Regression/RegressionEnsembleTrainer.cs +++ b/src/Microsoft.ML.Ensemble/Trainer/Regression/RegressionEnsembleTrainer.cs @@ -8,7 +8,6 @@ using Microsoft.ML; using Microsoft.ML.CommandLine; using Microsoft.ML.Ensemble; -using Microsoft.ML.Ensemble.EntryPoints; using Microsoft.ML.Ensemble.OutputCombiners; using Microsoft.ML.Ensemble.Selector; using Microsoft.ML.Internal.Internallearn; diff --git a/src/Microsoft.ML.FastTree/BinFile/BinFinder.cs b/src/Microsoft.ML.FastTree/BinFile/BinFinder.cs index 7725cb7aeb..7df57005b7 100644 --- a/src/Microsoft.ML.FastTree/BinFile/BinFinder.cs +++ b/src/Microsoft.ML.FastTree/BinFile/BinFinder.cs @@ -7,7 +7,7 @@ using Microsoft.ML.Data; using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { /// /// A class that bins vectors of doubles into a specified number of equal mass bins. diff --git a/src/Microsoft.ML.FastTree/BinFile/IniFileParserInterface.cs b/src/Microsoft.ML.FastTree/BinFile/IniFileParserInterface.cs index 9b28df134c..257b9e83b5 100644 --- a/src/Microsoft.ML.FastTree/BinFile/IniFileParserInterface.cs +++ b/src/Microsoft.ML.FastTree/BinFile/IniFileParserInterface.cs @@ -7,7 +7,7 @@ using System.Runtime.InteropServices; using System.Text; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { internal sealed class IniFileParserInterface { diff --git a/src/Microsoft.ML.FastTree/BoostingFastTree.cs b/src/Microsoft.ML.FastTree/BoostingFastTree.cs index e84ec0117b..072ee2e20f 100644 --- a/src/Microsoft.ML.FastTree/BoostingFastTree.cs +++ b/src/Microsoft.ML.FastTree/BoostingFastTree.cs @@ -6,7 +6,6 @@ using System.Linq; using Microsoft.ML.Core.Data; using Microsoft.ML.Internal.Internallearn; -using Microsoft.ML.Trainers.FastTree.Internal; using Float = System.Single; namespace Microsoft.ML.Trainers.FastTree diff --git a/src/Microsoft.ML.FastTree/Dataset/Dataset.cs b/src/Microsoft.ML.FastTree/Dataset/Dataset.cs index 330ef028ca..1e5de9b229 100644 --- a/src/Microsoft.ML.FastTree/Dataset/Dataset.cs +++ b/src/Microsoft.ML.FastTree/Dataset/Dataset.cs @@ -8,7 +8,7 @@ using System.Threading.Tasks; using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { /// /// A dataset of features. diff --git a/src/Microsoft.ML.FastTree/Dataset/DatasetUtils.cs b/src/Microsoft.ML.FastTree/Dataset/DatasetUtils.cs index 542b097381..617e6559e0 100644 --- a/src/Microsoft.ML.FastTree/Dataset/DatasetUtils.cs +++ b/src/Microsoft.ML.FastTree/Dataset/DatasetUtils.cs @@ -5,7 +5,7 @@ using System.Collections.Generic; using System.Linq; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { /// /// Loads training/validation/test sets from file diff --git a/src/Microsoft.ML.FastTree/Dataset/DenseIntArray.cs b/src/Microsoft.ML.FastTree/Dataset/DenseIntArray.cs index c6f10843d8..68c33a0d2d 100644 --- a/src/Microsoft.ML.FastTree/Dataset/DenseIntArray.cs +++ b/src/Microsoft.ML.FastTree/Dataset/DenseIntArray.cs @@ -8,7 +8,7 @@ using System.Runtime.InteropServices; using System.Security; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { #if USE_SINGLE_PRECISION using FloatType = System.Single; diff --git a/src/Microsoft.ML.FastTree/Dataset/Feature.cs b/src/Microsoft.ML.FastTree/Dataset/Feature.cs index c74ef5baf4..3013b536cf 100644 --- a/src/Microsoft.ML.FastTree/Dataset/Feature.cs +++ b/src/Microsoft.ML.FastTree/Dataset/Feature.cs @@ -4,7 +4,7 @@ using System.Linq; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { /// diff --git a/src/Microsoft.ML.FastTree/Dataset/FeatureFlock.cs b/src/Microsoft.ML.FastTree/Dataset/FeatureFlock.cs index 73c6b646bf..2d370499a4 100644 --- a/src/Microsoft.ML.FastTree/Dataset/FeatureFlock.cs +++ b/src/Microsoft.ML.FastTree/Dataset/FeatureFlock.cs @@ -15,7 +15,7 @@ using Microsoft.ML.Internal.CpuMath; using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { /// /// Holds statistics per bin value for a feature. These are yielded by diff --git a/src/Microsoft.ML.FastTree/Dataset/FeatureHistogram.cs b/src/Microsoft.ML.FastTree/Dataset/FeatureHistogram.cs index 2294525a9f..4968ad6a58 100644 --- a/src/Microsoft.ML.FastTree/Dataset/FeatureHistogram.cs +++ b/src/Microsoft.ML.FastTree/Dataset/FeatureHistogram.cs @@ -5,7 +5,7 @@ using System; using System.Linq; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { #if USE_SINGLE_PRECISION using FloatType = System.Single; diff --git a/src/Microsoft.ML.FastTree/Dataset/FileObjectStore.cs b/src/Microsoft.ML.FastTree/Dataset/FileObjectStore.cs index 9f7623d0ad..ff6e990dca 100644 --- a/src/Microsoft.ML.FastTree/Dataset/FileObjectStore.cs +++ b/src/Microsoft.ML.FastTree/Dataset/FileObjectStore.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.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { #if !NO_STORE /// diff --git a/src/Microsoft.ML.FastTree/Dataset/IntArray.cs b/src/Microsoft.ML.FastTree/Dataset/IntArray.cs index e2c8de872b..05ed42c957 100644 --- a/src/Microsoft.ML.FastTree/Dataset/IntArray.cs +++ b/src/Microsoft.ML.FastTree/Dataset/IntArray.cs @@ -6,7 +6,7 @@ using System.Collections.Generic; using System.Linq; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { #if USE_SINGLE_PRECISION using FloatType = System.Single; diff --git a/src/Microsoft.ML.FastTree/Dataset/NHotFeatureFlock.cs b/src/Microsoft.ML.FastTree/Dataset/NHotFeatureFlock.cs index fcfa6c938a..43eacf22f0 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. -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { /// /// This is a feature flock that misuses a property of diff --git a/src/Microsoft.ML.FastTree/Dataset/OneHotFeatureFlock.cs b/src/Microsoft.ML.FastTree/Dataset/OneHotFeatureFlock.cs index da8592fc14..605d912328 100644 --- a/src/Microsoft.ML.FastTree/Dataset/OneHotFeatureFlock.cs +++ b/src/Microsoft.ML.FastTree/Dataset/OneHotFeatureFlock.cs @@ -4,7 +4,7 @@ using System.Linq; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { /// /// A feature flock for a set of features where per example at most one of the features has a diff --git a/src/Microsoft.ML.FastTree/Dataset/RepeatIntArray.cs b/src/Microsoft.ML.FastTree/Dataset/RepeatIntArray.cs index 3b9502a8db..ac176c20ec 100644 --- a/src/Microsoft.ML.FastTree/Dataset/RepeatIntArray.cs +++ b/src/Microsoft.ML.FastTree/Dataset/RepeatIntArray.cs @@ -6,7 +6,7 @@ using System.Collections.Generic; using System.Linq; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { #if USE_SINGLE_PRECISION using FloatType = Single; diff --git a/src/Microsoft.ML.FastTree/Dataset/SegmentIntArray.cs b/src/Microsoft.ML.FastTree/Dataset/SegmentIntArray.cs index 156f5e227c..bfeb19f2f2 100644 --- a/src/Microsoft.ML.FastTree/Dataset/SegmentIntArray.cs +++ b/src/Microsoft.ML.FastTree/Dataset/SegmentIntArray.cs @@ -7,7 +7,7 @@ using System.Runtime.InteropServices; using System.Security; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { #if USE_SINGLE_PRECISION using FloatType = System.Single; diff --git a/src/Microsoft.ML.FastTree/Dataset/SingletonFeatureFlock.cs b/src/Microsoft.ML.FastTree/Dataset/SingletonFeatureFlock.cs index c1cf5fe4d4..30f609faa4 100644 --- a/src/Microsoft.ML.FastTree/Dataset/SingletonFeatureFlock.cs +++ b/src/Microsoft.ML.FastTree/Dataset/SingletonFeatureFlock.cs @@ -5,7 +5,7 @@ using System.Linq; using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { /// /// The singleton feature flock is the simplest possible sort of flock, that is, a flock diff --git a/src/Microsoft.ML.FastTree/Dataset/SparseIntArray.cs b/src/Microsoft.ML.FastTree/Dataset/SparseIntArray.cs index b3dc61b07a..b9e5cc0f28 100644 --- a/src/Microsoft.ML.FastTree/Dataset/SparseIntArray.cs +++ b/src/Microsoft.ML.FastTree/Dataset/SparseIntArray.cs @@ -7,7 +7,7 @@ using System.Runtime.InteropServices; using System.Security; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { #if USE_SINGLE_PRECISION using FloatType = System.Single; diff --git a/src/Microsoft.ML.FastTree/FastTree.cs b/src/Microsoft.ML.FastTree/FastTree.cs index fc94e6099c..c2a90c4f3e 100644 --- a/src/Microsoft.ML.FastTree/FastTree.cs +++ b/src/Microsoft.ML.FastTree/FastTree.cs @@ -23,7 +23,6 @@ using Microsoft.ML.Model; using Microsoft.ML.Model.Onnx; using Microsoft.ML.Model.Pfa; -using Microsoft.ML.Trainers.FastTree.Internal; using Microsoft.ML.Training; using Microsoft.ML.Transforms; using Microsoft.ML.Transforms.Conversions; diff --git a/src/Microsoft.ML.FastTree/FastTreeClassification.cs b/src/Microsoft.ML.FastTree/FastTreeClassification.cs index ff47449238..4ae7ab7555 100644 --- a/src/Microsoft.ML.FastTree/FastTreeClassification.cs +++ b/src/Microsoft.ML.FastTree/FastTreeClassification.cs @@ -15,7 +15,6 @@ using Microsoft.ML.Internal.Internallearn; using Microsoft.ML.Model; using Microsoft.ML.Trainers.FastTree; -using Microsoft.ML.Trainers.FastTree.Internal; using Microsoft.ML.Training; [assembly: LoadableClass(FastTreeBinaryClassificationTrainer.Summary, typeof(FastTreeBinaryClassificationTrainer), typeof(FastTreeBinaryClassificationTrainer.Options), diff --git a/src/Microsoft.ML.FastTree/FastTreeRanking.cs b/src/Microsoft.ML.FastTree/FastTreeRanking.cs index 485a7639ca..059cd8ab93 100644 --- a/src/Microsoft.ML.FastTree/FastTreeRanking.cs +++ b/src/Microsoft.ML.FastTree/FastTreeRanking.cs @@ -17,7 +17,6 @@ using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Model; using Microsoft.ML.Trainers.FastTree; -using Microsoft.ML.Trainers.FastTree.Internal; using Microsoft.ML.Training; // REVIEW: Do we really need all these names? diff --git a/src/Microsoft.ML.FastTree/FastTreeRegression.cs b/src/Microsoft.ML.FastTree/FastTreeRegression.cs index e26ce00e82..1399b8bebe 100644 --- a/src/Microsoft.ML.FastTree/FastTreeRegression.cs +++ b/src/Microsoft.ML.FastTree/FastTreeRegression.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 System; using System.Linq; using System.Text; using Microsoft.Data.DataView; @@ -13,7 +12,6 @@ using Microsoft.ML.Internal.Internallearn; using Microsoft.ML.Model; using Microsoft.ML.Trainers.FastTree; -using Microsoft.ML.Trainers.FastTree.Internal; using Microsoft.ML.Training; [assembly: LoadableClass(FastTreeRegressionTrainer.Summary, typeof(FastTreeRegressionTrainer), typeof(FastTreeRegressionTrainer.Options), diff --git a/src/Microsoft.ML.FastTree/FastTreeTweedie.cs b/src/Microsoft.ML.FastTree/FastTreeTweedie.cs index b8ea0ce030..547d48f7ca 100644 --- a/src/Microsoft.ML.FastTree/FastTreeTweedie.cs +++ b/src/Microsoft.ML.FastTree/FastTreeTweedie.cs @@ -14,7 +14,6 @@ using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Model; using Microsoft.ML.Trainers.FastTree; -using Microsoft.ML.Trainers.FastTree.Internal; using Microsoft.ML.Training; [assembly: LoadableClass(FastTreeTweedieTrainer.Summary, typeof(FastTreeTweedieTrainer), typeof(FastTreeTweedieTrainer.Options), diff --git a/src/Microsoft.ML.FastTree/GamClassification.cs b/src/Microsoft.ML.FastTree/GamClassification.cs index 635862e178..79f8265dbb 100644 --- a/src/Microsoft.ML.FastTree/GamClassification.cs +++ b/src/Microsoft.ML.FastTree/GamClassification.cs @@ -14,7 +14,6 @@ using Microsoft.ML.Internal.Internallearn; using Microsoft.ML.Model; using Microsoft.ML.Trainers.FastTree; -using Microsoft.ML.Trainers.FastTree.Internal; using Microsoft.ML.Training; [assembly: LoadableClass(BinaryClassificationGamTrainer.Summary, diff --git a/src/Microsoft.ML.FastTree/GamModelParameters.cs b/src/Microsoft.ML.FastTree/GamModelParameters.cs index 38c931f03f..a726edd1bc 100644 --- a/src/Microsoft.ML.FastTree/GamModelParameters.cs +++ b/src/Microsoft.ML.FastTree/GamModelParameters.cs @@ -18,7 +18,6 @@ using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Model; using Microsoft.ML.Trainers.FastTree; -using Microsoft.ML.Trainers.FastTree.Internal; using Microsoft.ML.Training; [assembly: LoadableClass(typeof(GamModelParametersBase.VisualizationCommand), typeof(GamModelParametersBase.VisualizationCommand.Arguments), typeof(SignatureCommand), diff --git a/src/Microsoft.ML.FastTree/GamRegression.cs b/src/Microsoft.ML.FastTree/GamRegression.cs index 100cc6b61a..4c3fbe021b 100644 --- a/src/Microsoft.ML.FastTree/GamRegression.cs +++ b/src/Microsoft.ML.FastTree/GamRegression.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 System; using Microsoft.Data.DataView; using Microsoft.ML; using Microsoft.ML.CommandLine; @@ -11,7 +10,6 @@ using Microsoft.ML.Internal.Internallearn; using Microsoft.ML.Model; using Microsoft.ML.Trainers.FastTree; -using Microsoft.ML.Trainers.FastTree.Internal; using Microsoft.ML.Training; [assembly: LoadableClass(RegressionGamTrainer.Summary, diff --git a/src/Microsoft.ML.FastTree/GamTrainer.cs b/src/Microsoft.ML.FastTree/GamTrainer.cs index 87bcc370ba..11953bbe36 100644 --- a/src/Microsoft.ML.FastTree/GamTrainer.cs +++ b/src/Microsoft.ML.FastTree/GamTrainer.cs @@ -14,15 +14,12 @@ using Microsoft.ML.Internal.CpuMath; using Microsoft.ML.Internal.Internallearn; using Microsoft.ML.Trainers.FastTree; -using Microsoft.ML.Trainers.FastTree.Internal; using Microsoft.ML.Training; -using Timer = Microsoft.ML.Trainers.FastTree.Internal.Timer; [assembly: LoadableClass(typeof(void), typeof(Gam), null, typeof(SignatureEntryPointModule), "GAM")] namespace Microsoft.ML.Trainers.FastTree { - using AutoResetEvent = System.Threading.AutoResetEvent; using SplitInfo = LeastSquaresRegressionTreeLearner.SplitInfo; /// diff --git a/src/Microsoft.ML.FastTree/RandomForest.cs b/src/Microsoft.ML.FastTree/RandomForest.cs index 943b10f621..aea3a991bf 100644 --- a/src/Microsoft.ML.FastTree/RandomForest.cs +++ b/src/Microsoft.ML.FastTree/RandomForest.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; using Microsoft.ML.Core.Data; -using Microsoft.ML.Trainers.FastTree.Internal; namespace Microsoft.ML.Trainers.FastTree { diff --git a/src/Microsoft.ML.FastTree/RandomForestClassification.cs b/src/Microsoft.ML.FastTree/RandomForestClassification.cs index d6a31ec6a0..13d2261ea9 100644 --- a/src/Microsoft.ML.FastTree/RandomForestClassification.cs +++ b/src/Microsoft.ML.FastTree/RandomForestClassification.cs @@ -15,7 +15,6 @@ using Microsoft.ML.Internal.Internallearn; using Microsoft.ML.Model; using Microsoft.ML.Trainers.FastTree; -using Microsoft.ML.Trainers.FastTree.Internal; using Microsoft.ML.Training; [assembly: LoadableClass(FastForestClassification.Summary, typeof(FastForestClassification), typeof(FastForestClassification.Options), diff --git a/src/Microsoft.ML.FastTree/RandomForestRegression.cs b/src/Microsoft.ML.FastTree/RandomForestRegression.cs index de83cabeca..daed4b26c1 100644 --- a/src/Microsoft.ML.FastTree/RandomForestRegression.cs +++ b/src/Microsoft.ML.FastTree/RandomForestRegression.cs @@ -13,7 +13,6 @@ using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Model; using Microsoft.ML.Trainers.FastTree; -using Microsoft.ML.Trainers.FastTree.Internal; using Microsoft.ML.Training; [assembly: LoadableClass(FastForestRegression.Summary, typeof(FastForestRegression), typeof(FastForestRegression.Options), diff --git a/src/Microsoft.ML.FastTree/RegressionTree.cs b/src/Microsoft.ML.FastTree/RegressionTree.cs index 867d6015ef..96a0784602 100644 --- a/src/Microsoft.ML.FastTree/RegressionTree.cs +++ b/src/Microsoft.ML.FastTree/RegressionTree.cs @@ -4,7 +4,7 @@ using System.Collections.Generic; using System.Collections.Immutable; -using Microsoft.ML.Trainers.FastTree.Internal; +using Microsoft.ML.Trainers.FastTree; namespace Microsoft.ML.FastTree { diff --git a/src/Microsoft.ML.FastTree/SumupPerformanceCommand.cs b/src/Microsoft.ML.FastTree/SumupPerformanceCommand.cs index a25b370586..7816dc993b 100644 --- a/src/Microsoft.ML.FastTree/SumupPerformanceCommand.cs +++ b/src/Microsoft.ML.FastTree/SumupPerformanceCommand.cs @@ -17,14 +17,13 @@ using Microsoft.ML.CommandLine; using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Trainers.FastTree; -using Microsoft.ML.Trainers.FastTree.Internal; [assembly: LoadableClass(typeof(SumupPerformanceCommand), typeof(SumupPerformanceCommand.Arguments), typeof(SignatureCommand), "", "FastTreeSumupPerformance", "ftsumup")] namespace Microsoft.ML.Trainers.FastTree { -using Stopwatch = System.Diagnostics.Stopwatch; + using Stopwatch = System.Diagnostics.Stopwatch; /// /// This is an internal utility command to measure the performance of the IntArray sumup operation. diff --git a/src/Microsoft.ML.FastTree/Training/Applications/GradientWrappers.cs b/src/Microsoft.ML.FastTree/Training/Applications/GradientWrappers.cs index a1e65a455b..b360b9ea4a 100644 --- a/src/Microsoft.ML.FastTree/Training/Applications/GradientWrappers.cs +++ b/src/Microsoft.ML.FastTree/Training/Applications/GradientWrappers.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.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { /// /// Trivial weights wrapper. Creates proxy class holding the targets. diff --git a/src/Microsoft.ML.FastTree/Training/Applications/ObjectiveFunction.cs b/src/Microsoft.ML.FastTree/Training/Applications/ObjectiveFunction.cs index 2808e24cb7..644add5903 100644 --- a/src/Microsoft.ML.FastTree/Training/Applications/ObjectiveFunction.cs +++ b/src/Microsoft.ML.FastTree/Training/Applications/ObjectiveFunction.cs @@ -7,7 +7,7 @@ using System.Linq; using System.Threading.Tasks; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { public abstract class ObjectiveFunctionBase { diff --git a/src/Microsoft.ML.FastTree/Training/BaggingProvider.cs b/src/Microsoft.ML.FastTree/Training/BaggingProvider.cs index 3fd5125620..0dc50ce83b 100644 --- a/src/Microsoft.ML.FastTree/Training/BaggingProvider.cs +++ b/src/Microsoft.ML.FastTree/Training/BaggingProvider.cs @@ -4,7 +4,7 @@ using System; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { public class BaggingProvider { diff --git a/src/Microsoft.ML.FastTree/Training/DcgCalculator.cs b/src/Microsoft.ML.FastTree/Training/DcgCalculator.cs index e9284a6a5e..7fd960a190 100644 --- a/src/Microsoft.ML.FastTree/Training/DcgCalculator.cs +++ b/src/Microsoft.ML.FastTree/Training/DcgCalculator.cs @@ -7,7 +7,7 @@ using System.Threading.Tasks; using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { public sealed class DcgCalculator { diff --git a/src/Microsoft.ML.FastTree/Training/DcgPermutationComparer.cs b/src/Microsoft.ML.FastTree/Training/DcgPermutationComparer.cs index 05e2955ec9..e0fb3ff926 100644 --- a/src/Microsoft.ML.FastTree/Training/DcgPermutationComparer.cs +++ b/src/Microsoft.ML.FastTree/Training/DcgPermutationComparer.cs @@ -4,7 +4,7 @@ using System.Collections.Generic; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { public abstract class DcgPermutationComparer : IComparer { diff --git a/src/Microsoft.ML.FastTree/Training/DocumentPartitioning.cs b/src/Microsoft.ML.FastTree/Training/DocumentPartitioning.cs index 3a52acdebf..6e06480014 100644 --- a/src/Microsoft.ML.FastTree/Training/DocumentPartitioning.cs +++ b/src/Microsoft.ML.FastTree/Training/DocumentPartitioning.cs @@ -7,7 +7,7 @@ using System.Linq; using System.Threading.Tasks; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { #if USE_SINGLE_PRECISION using FloatType = System.Single; diff --git a/src/Microsoft.ML.FastTree/Training/EnsembleCompression/IEnsembleCompressor.cs b/src/Microsoft.ML.FastTree/Training/EnsembleCompression/IEnsembleCompressor.cs index 7f3c687819..fb87ab95f2 100644 --- a/src/Microsoft.ML.FastTree/Training/EnsembleCompression/IEnsembleCompressor.cs +++ b/src/Microsoft.ML.FastTree/Training/EnsembleCompression/IEnsembleCompressor.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.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { internal interface IEnsembleCompressor { diff --git a/src/Microsoft.ML.FastTree/Training/EnsembleCompression/LassoBasedEnsembleCompressor.cs b/src/Microsoft.ML.FastTree/Training/EnsembleCompression/LassoBasedEnsembleCompressor.cs index eba82d0cfe..69b2acd798 100644 --- a/src/Microsoft.ML.FastTree/Training/EnsembleCompression/LassoBasedEnsembleCompressor.cs +++ b/src/Microsoft.ML.FastTree/Training/EnsembleCompression/LassoBasedEnsembleCompressor.cs @@ -6,7 +6,7 @@ using System.Collections.Generic; using System.Diagnostics; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { /// /// This implementation is based on: diff --git a/src/Microsoft.ML.FastTree/Training/EnsembleCompression/LassoFit.cs b/src/Microsoft.ML.FastTree/Training/EnsembleCompression/LassoFit.cs index 7a1e7ac321..a29752f612 100644 --- a/src/Microsoft.ML.FastTree/Training/EnsembleCompression/LassoFit.cs +++ b/src/Microsoft.ML.FastTree/Training/EnsembleCompression/LassoFit.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.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { public sealed class LassoFit { diff --git a/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/AcceleratedGradientDescent.cs b/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/AcceleratedGradientDescent.cs index 0678eb4060..72cf5af52c 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. -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { //Accelerated gradient descent score tracker internal class AcceleratedGradientDescent : GradientDescent diff --git a/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/ConjugateGradientDescent.cs b/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/ConjugateGradientDescent.cs index 044ef7bcf3..bde9917c53 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. -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { // Conjugate gradient descent internal class ConjugateGradientDescent : GradientDescent diff --git a/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/GradientDescent.cs b/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/GradientDescent.cs index b2cf4f584b..5543763351 100644 --- a/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/GradientDescent.cs +++ b/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/GradientDescent.cs @@ -6,7 +6,7 @@ using System.Collections.Generic; using System.Linq; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { internal class GradientDescent : OptimizationAlgorithm { diff --git a/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/NoOptimizationAlgorithm.cs b/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/NoOptimizationAlgorithm.cs index 1925272122..9e53353316 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. -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { /// /// This is dummy optimizer. As Random forest does not have any boosting based optimization, this is place holder to be consistent diff --git a/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/OptimizationAlgorithm.cs b/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/OptimizationAlgorithm.cs index 299d13a300..986a9c13f7 100644 --- a/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/OptimizationAlgorithm.cs +++ b/src/Microsoft.ML.FastTree/Training/OptimizationAlgorithms/OptimizationAlgorithm.cs @@ -5,7 +5,7 @@ using System; using System.Collections.Generic; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { //An interface that can be implemnted on public interface IFastTrainingScoresUpdate diff --git a/src/Microsoft.ML.FastTree/Training/Parallel/IParallelTraining.cs b/src/Microsoft.ML.FastTree/Training/Parallel/IParallelTraining.cs index fccb0673eb..965026556c 100644 --- a/src/Microsoft.ML.FastTree/Training/Parallel/IParallelTraining.cs +++ b/src/Microsoft.ML.FastTree/Training/Parallel/IParallelTraining.cs @@ -4,7 +4,6 @@ using System; using Microsoft.ML.EntryPoints; -using Microsoft.ML.Trainers.FastTree.Internal; namespace Microsoft.ML.Trainers.FastTree { diff --git a/src/Microsoft.ML.FastTree/Training/Parallel/SingleTrainer.cs b/src/Microsoft.ML.FastTree/Training/Parallel/SingleTrainer.cs index 734cda69d9..52adef9a50 100644 --- a/src/Microsoft.ML.FastTree/Training/Parallel/SingleTrainer.cs +++ b/src/Microsoft.ML.FastTree/Training/Parallel/SingleTrainer.cs @@ -15,9 +15,8 @@ namespace Microsoft.ML.Trainers.FastTree { - using Microsoft.ML.Trainers.FastTree.Internal; - using LeafSplitCandidates = Internal.LeastSquaresRegressionTreeLearner.LeafSplitCandidates; - using SplitInfo = Internal.LeastSquaresRegressionTreeLearner.SplitInfo; + using LeafSplitCandidates = LeastSquaresRegressionTreeLearner.LeafSplitCandidates; + using SplitInfo = LeastSquaresRegressionTreeLearner.SplitInfo; internal sealed class SingleTrainer : IParallelTraining { diff --git a/src/Microsoft.ML.FastTree/Training/RegressionTreeNodeDocuments.cs b/src/Microsoft.ML.FastTree/Training/RegressionTreeNodeDocuments.cs index 75fe766cc6..8849aaa53e 100644 --- a/src/Microsoft.ML.FastTree/Training/RegressionTreeNodeDocuments.cs +++ b/src/Microsoft.ML.FastTree/Training/RegressionTreeNodeDocuments.cs @@ -5,7 +5,7 @@ using System.Collections.Generic; using System.Linq; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { // RegressionTreeNodeDocuments represents an association between a node in a regression // tree and documents belonging to that node. diff --git a/src/Microsoft.ML.FastTree/Training/ScoreTracker.cs b/src/Microsoft.ML.FastTree/Training/ScoreTracker.cs index 297aa06e29..882fa4a2d6 100644 --- a/src/Microsoft.ML.FastTree/Training/ScoreTracker.cs +++ b/src/Microsoft.ML.FastTree/Training/ScoreTracker.cs @@ -6,7 +6,7 @@ using System.Collections.Generic; using System.Threading.Tasks; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { public class ScoreTracker { diff --git a/src/Microsoft.ML.FastTree/Training/StepSearch.cs b/src/Microsoft.ML.FastTree/Training/StepSearch.cs index bffa5213ca..ca767a22ed 100644 --- a/src/Microsoft.ML.FastTree/Training/StepSearch.cs +++ b/src/Microsoft.ML.FastTree/Training/StepSearch.cs @@ -5,7 +5,7 @@ using System; using System.Linq; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { internal interface IStepSearch { diff --git a/src/Microsoft.ML.FastTree/Training/Test.cs b/src/Microsoft.ML.FastTree/Training/Test.cs index c76903d522..88f985f67a 100644 --- a/src/Microsoft.ML.FastTree/Training/Test.cs +++ b/src/Microsoft.ML.FastTree/Training/Test.cs @@ -8,7 +8,7 @@ using System.Threading; using System.Threading.Tasks; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { public sealed class TestResult : IComparable { diff --git a/src/Microsoft.ML.FastTree/Training/TreeLearners/FastForestLeastSquaresTreeLearner.cs b/src/Microsoft.ML.FastTree/Training/TreeLearners/FastForestLeastSquaresTreeLearner.cs index 3009bd500a..ae7f2a3b2f 100644 --- a/src/Microsoft.ML.FastTree/Training/TreeLearners/FastForestLeastSquaresTreeLearner.cs +++ b/src/Microsoft.ML.FastTree/Training/TreeLearners/FastForestLeastSquaresTreeLearner.cs @@ -4,7 +4,7 @@ using System; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { internal class RandomForestLeastSquaresTreeLearner : LeastSquaresRegressionTreeLearner { diff --git a/src/Microsoft.ML.FastTree/Training/TreeLearners/LeastSquaresRegressionTreeLearner.cs b/src/Microsoft.ML.FastTree/Training/TreeLearners/LeastSquaresRegressionTreeLearner.cs index 823942f824..2cf8f44a75 100644 --- a/src/Microsoft.ML.FastTree/Training/TreeLearners/LeastSquaresRegressionTreeLearner.cs +++ b/src/Microsoft.ML.FastTree/Training/TreeLearners/LeastSquaresRegressionTreeLearner.cs @@ -9,7 +9,7 @@ using Microsoft.ML.Internal.CpuMath; using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { #if USE_SINGLE_PRECISION using FloatType = System.Single; diff --git a/src/Microsoft.ML.FastTree/Training/TreeLearners/TreeLearner.cs b/src/Microsoft.ML.FastTree/Training/TreeLearners/TreeLearner.cs index e5f633b9c9..93dd45ca60 100644 --- a/src/Microsoft.ML.FastTree/Training/TreeLearners/TreeLearner.cs +++ b/src/Microsoft.ML.FastTree/Training/TreeLearners/TreeLearner.cs @@ -4,7 +4,7 @@ using System; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { internal abstract class TreeLearner { diff --git a/src/Microsoft.ML.FastTree/Training/WinLossCalculator.cs b/src/Microsoft.ML.FastTree/Training/WinLossCalculator.cs index 0320a23ded..a183ddc9f6 100644 --- a/src/Microsoft.ML.FastTree/Training/WinLossCalculator.cs +++ b/src/Microsoft.ML.FastTree/Training/WinLossCalculator.cs @@ -8,7 +8,7 @@ using System.Threading.Tasks; using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { public sealed class WinLossCalculator { diff --git a/src/Microsoft.ML.FastTree/TreeEnsemble/InternalQuantileRegressionTree.cs b/src/Microsoft.ML.FastTree/TreeEnsemble/InternalQuantileRegressionTree.cs index 453a223449..7a8d5dcf23 100644 --- a/src/Microsoft.ML.FastTree/TreeEnsemble/InternalQuantileRegressionTree.cs +++ b/src/Microsoft.ML.FastTree/TreeEnsemble/InternalQuantileRegressionTree.cs @@ -7,7 +7,7 @@ using Microsoft.ML.Model; using Float = System.Single; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { internal class InternalQuantileRegressionTree : InternalRegressionTree { diff --git a/src/Microsoft.ML.FastTree/TreeEnsemble/InternalRegressionTree.cs b/src/Microsoft.ML.FastTree/TreeEnsemble/InternalRegressionTree.cs index 8feb116f1d..31f65ae92e 100644 --- a/src/Microsoft.ML.FastTree/TreeEnsemble/InternalRegressionTree.cs +++ b/src/Microsoft.ML.FastTree/TreeEnsemble/InternalRegressionTree.cs @@ -15,7 +15,7 @@ using Microsoft.ML.Model.Pfa; using Newtonsoft.Json.Linq; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { /// Note that is shared between FastTree and LightGBM assemblies, /// so has . diff --git a/src/Microsoft.ML.FastTree/TreeEnsemble/InternalTreeEnsemble.cs b/src/Microsoft.ML.FastTree/TreeEnsemble/InternalTreeEnsemble.cs index 3a7a49573f..62fd670fc8 100644 --- a/src/Microsoft.ML.FastTree/TreeEnsemble/InternalTreeEnsemble.cs +++ b/src/Microsoft.ML.FastTree/TreeEnsemble/InternalTreeEnsemble.cs @@ -14,7 +14,7 @@ using Microsoft.ML.Model.Pfa; using Newtonsoft.Json.Linq; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { [BestFriend] internal class InternalTreeEnsemble diff --git a/src/Microsoft.ML.FastTree/TreeEnsemble/TreeEnsembleCombiner.cs b/src/Microsoft.ML.FastTree/TreeEnsemble/TreeEnsembleCombiner.cs index f215dec82a..48819147ef 100644 --- a/src/Microsoft.ML.FastTree/TreeEnsemble/TreeEnsembleCombiner.cs +++ b/src/Microsoft.ML.FastTree/TreeEnsemble/TreeEnsembleCombiner.cs @@ -8,12 +8,11 @@ using Microsoft.ML.Data; using Microsoft.ML.Ensemble; using Microsoft.ML.Internal.Calibration; -using Microsoft.ML.Internal.Internallearn; -using Microsoft.ML.Trainers.FastTree.Internal; +using Microsoft.ML.Trainers.FastTree; [assembly: LoadableClass(typeof(TreeEnsembleCombiner), null, typeof(SignatureModelCombiner), "Fast Tree Model Combiner", "FastTreeCombiner")] -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { public sealed class TreeEnsembleCombiner : IModelCombiner { diff --git a/src/Microsoft.ML.FastTree/Utils/Algorithms.cs b/src/Microsoft.ML.FastTree/Utils/Algorithms.cs index 9ad94b359a..553e0e7553 100644 --- a/src/Microsoft.ML.FastTree/Utils/Algorithms.cs +++ b/src/Microsoft.ML.FastTree/Utils/Algorithms.cs @@ -5,7 +5,7 @@ using System; using System.Linq; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { public static class Algorithms { diff --git a/src/Microsoft.ML.FastTree/Utils/BlockingThreadPool.cs b/src/Microsoft.ML.FastTree/Utils/BlockingThreadPool.cs index 76d623a850..e096de7005 100644 --- a/src/Microsoft.ML.FastTree/Utils/BlockingThreadPool.cs +++ b/src/Microsoft.ML.FastTree/Utils/BlockingThreadPool.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.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { /// /// This class wraps the standard .NET ThreadPool and adds the following functionality: diff --git a/src/Microsoft.ML.FastTree/Utils/BufferPoolManager.cs b/src/Microsoft.ML.FastTree/Utils/BufferPoolManager.cs index cd0d03cfc8..526fddba09 100644 --- a/src/Microsoft.ML.FastTree/Utils/BufferPoolManager.cs +++ b/src/Microsoft.ML.FastTree/Utils/BufferPoolManager.cs @@ -10,7 +10,7 @@ using System.Linq; using System.Runtime.InteropServices; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { /// /// This class enables basic buffer pooling. diff --git a/src/Microsoft.ML.FastTree/Utils/CompressUtils.cs b/src/Microsoft.ML.FastTree/Utils/CompressUtils.cs index 0588e386ae..4c87a666a9 100644 --- a/src/Microsoft.ML.FastTree/Utils/CompressUtils.cs +++ b/src/Microsoft.ML.FastTree/Utils/CompressUtils.cs @@ -7,7 +7,7 @@ using System.IO; using System.IO.Compression; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { internal struct BufferBlock { diff --git a/src/Microsoft.ML.FastTree/Utils/FastTreeIniFileUtils.cs b/src/Microsoft.ML.FastTree/Utils/FastTreeIniFileUtils.cs index 939306cbaa..a9400739dd 100644 --- a/src/Microsoft.ML.FastTree/Utils/FastTreeIniFileUtils.cs +++ b/src/Microsoft.ML.FastTree/Utils/FastTreeIniFileUtils.cs @@ -8,7 +8,7 @@ using Microsoft.ML.Internal.Calibration; using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { internal static class FastTreeIniFileUtils { diff --git a/src/Microsoft.ML.FastTree/Utils/LinqExtensions.cs b/src/Microsoft.ML.FastTree/Utils/LinqExtensions.cs index 88d8825205..0b912e58bc 100644 --- a/src/Microsoft.ML.FastTree/Utils/LinqExtensions.cs +++ b/src/Microsoft.ML.FastTree/Utils/LinqExtensions.cs @@ -6,7 +6,7 @@ using System.Collections.Generic; using System.Linq; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { public static class LinqExtensions { diff --git a/src/Microsoft.ML.FastTree/Utils/MD5Hasher.cs b/src/Microsoft.ML.FastTree/Utils/MD5Hasher.cs index fc31ec097e..8a5fda81ea 100644 --- a/src/Microsoft.ML.FastTree/Utils/MD5Hasher.cs +++ b/src/Microsoft.ML.FastTree/Utils/MD5Hasher.cs @@ -7,7 +7,7 @@ using System.Security.Cryptography; using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { public struct MD5Hash { diff --git a/src/Microsoft.ML.FastTree/Utils/MappedObjectPool.cs b/src/Microsoft.ML.FastTree/Utils/MappedObjectPool.cs index bcfb68e210..ad9b54e6cd 100644 --- a/src/Microsoft.ML.FastTree/Utils/MappedObjectPool.cs +++ b/src/Microsoft.ML.FastTree/Utils/MappedObjectPool.cs @@ -5,7 +5,7 @@ using System; using System.Linq; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { /// /// Implements a paging mechanism on indexed objects. diff --git a/src/Microsoft.ML.FastTree/Utils/PseudorandomFunction.cs b/src/Microsoft.ML.FastTree/Utils/PseudorandomFunction.cs index 59adf3a453..9a7800d5ac 100644 --- a/src/Microsoft.ML.FastTree/Utils/PseudorandomFunction.cs +++ b/src/Microsoft.ML.FastTree/Utils/PseudorandomFunction.cs @@ -5,7 +5,7 @@ using System; using System.Linq; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { /// /// This class defines a psuedorandom function, mapping a number to diff --git a/src/Microsoft.ML.FastTree/Utils/StreamExtensions.cs b/src/Microsoft.ML.FastTree/Utils/StreamExtensions.cs index c12ba5d066..125b49fecb 100644 --- a/src/Microsoft.ML.FastTree/Utils/StreamExtensions.cs +++ b/src/Microsoft.ML.FastTree/Utils/StreamExtensions.cs @@ -5,7 +5,7 @@ using System.IO; using System.IO.Compression; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { public static class StreamExtensions { diff --git a/src/Microsoft.ML.FastTree/Utils/ThreadTaskManager.cs b/src/Microsoft.ML.FastTree/Utils/ThreadTaskManager.cs index d479c2c53b..aa0e06ffc0 100644 --- a/src/Microsoft.ML.FastTree/Utils/ThreadTaskManager.cs +++ b/src/Microsoft.ML.FastTree/Utils/ThreadTaskManager.cs @@ -7,7 +7,7 @@ using System.Linq; using System.Threading.Tasks; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { internal static class ThreadTaskManager { diff --git a/src/Microsoft.ML.FastTree/Utils/Timer.cs b/src/Microsoft.ML.FastTree/Utils/Timer.cs index 35770a5e50..feb8d631cc 100644 --- a/src/Microsoft.ML.FastTree/Utils/Timer.cs +++ b/src/Microsoft.ML.FastTree/Utils/Timer.cs @@ -6,7 +6,7 @@ using System.Text; using System.Threading; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { using Stopwatch = System.Diagnostics.Stopwatch; diff --git a/src/Microsoft.ML.FastTree/Utils/ToByteArrayExtensions.cs b/src/Microsoft.ML.FastTree/Utils/ToByteArrayExtensions.cs index 108aeeac87..1452a3bbba 100644 --- a/src/Microsoft.ML.FastTree/Utils/ToByteArrayExtensions.cs +++ b/src/Microsoft.ML.FastTree/Utils/ToByteArrayExtensions.cs @@ -7,7 +7,7 @@ using System.Text; using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { /// /// This class contains extension methods that support binary serialization of some base C# types diff --git a/src/Microsoft.ML.FastTree/Utils/VectorUtils.cs b/src/Microsoft.ML.FastTree/Utils/VectorUtils.cs index 8941d50da0..3b54b1a33b 100644 --- a/src/Microsoft.ML.FastTree/Utils/VectorUtils.cs +++ b/src/Microsoft.ML.FastTree/Utils/VectorUtils.cs @@ -5,7 +5,7 @@ using System; using System.Text; -namespace Microsoft.ML.Trainers.FastTree.Internal +namespace Microsoft.ML.Trainers.FastTree { public class VectorUtils { diff --git a/src/Microsoft.ML.LightGBM/LightGbmBinaryTrainer.cs b/src/Microsoft.ML.LightGBM/LightGbmBinaryTrainer.cs index e73bf4acb9..bf01aecbfd 100644 --- a/src/Microsoft.ML.LightGBM/LightGbmBinaryTrainer.cs +++ b/src/Microsoft.ML.LightGBM/LightGbmBinaryTrainer.cs @@ -13,7 +13,6 @@ using Microsoft.ML.LightGBM; using Microsoft.ML.Model; using Microsoft.ML.Trainers.FastTree; -using Microsoft.ML.Trainers.FastTree.Internal; using Microsoft.ML.Training; [assembly: LoadableClass(LightGbmBinaryTrainer.Summary, typeof(LightGbmBinaryTrainer), typeof(Options), diff --git a/src/Microsoft.ML.LightGBM/LightGbmMulticlassTrainer.cs b/src/Microsoft.ML.LightGBM/LightGbmMulticlassTrainer.cs index a3ec3ffef5..3b2a1b56af 100644 --- a/src/Microsoft.ML.LightGBM/LightGbmMulticlassTrainer.cs +++ b/src/Microsoft.ML.LightGBM/LightGbmMulticlassTrainer.cs @@ -12,7 +12,7 @@ using Microsoft.ML.Internal.Calibration; using Microsoft.ML.LightGBM; using Microsoft.ML.Trainers; -using Microsoft.ML.Trainers.FastTree.Internal; +using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Training; [assembly: LoadableClass(LightGbmMulticlassTrainer.Summary, typeof(LightGbmMulticlassTrainer), typeof(Options), diff --git a/src/Microsoft.ML.LightGBM/LightGbmRankingTrainer.cs b/src/Microsoft.ML.LightGBM/LightGbmRankingTrainer.cs index 04e78e7a4d..559ed6b5e1 100644 --- a/src/Microsoft.ML.LightGBM/LightGbmRankingTrainer.cs +++ b/src/Microsoft.ML.LightGBM/LightGbmRankingTrainer.cs @@ -11,7 +11,6 @@ using Microsoft.ML.LightGBM; using Microsoft.ML.Model; using Microsoft.ML.Trainers.FastTree; -using Microsoft.ML.Trainers.FastTree.Internal; using Microsoft.ML.Training; [assembly: LoadableClass(LightGbmRankingTrainer.UserName, typeof(LightGbmRankingTrainer), typeof(Options), diff --git a/src/Microsoft.ML.LightGBM/LightGbmRegressionTrainer.cs b/src/Microsoft.ML.LightGBM/LightGbmRegressionTrainer.cs index 676627aa84..2068746cea 100644 --- a/src/Microsoft.ML.LightGBM/LightGbmRegressionTrainer.cs +++ b/src/Microsoft.ML.LightGBM/LightGbmRegressionTrainer.cs @@ -10,7 +10,6 @@ using Microsoft.ML.LightGBM; using Microsoft.ML.Model; using Microsoft.ML.Trainers.FastTree; -using Microsoft.ML.Trainers.FastTree.Internal; using Microsoft.ML.Training; [assembly: LoadableClass(LightGbmRegressorTrainer.Summary, typeof(LightGbmRegressorTrainer), typeof(Options), diff --git a/src/Microsoft.ML.LightGBM/LightGbmTrainerBase.cs b/src/Microsoft.ML.LightGBM/LightGbmTrainerBase.cs index 1ce9b0ccf4..695157f91b 100644 --- a/src/Microsoft.ML.LightGBM/LightGbmTrainerBase.cs +++ b/src/Microsoft.ML.LightGBM/LightGbmTrainerBase.cs @@ -8,7 +8,7 @@ using Microsoft.ML.Data; using Microsoft.ML.EntryPoints; using Microsoft.ML.Internal.Utilities; -using Microsoft.ML.Trainers.FastTree.Internal; +using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Training; namespace Microsoft.ML.LightGBM diff --git a/src/Microsoft.ML.LightGBM/WrappedLightGbmBooster.cs b/src/Microsoft.ML.LightGBM/WrappedLightGbmBooster.cs index 04dc9f9f62..cf8b9e4c8e 100644 --- a/src/Microsoft.ML.LightGBM/WrappedLightGbmBooster.cs +++ b/src/Microsoft.ML.LightGBM/WrappedLightGbmBooster.cs @@ -6,7 +6,7 @@ using System.Collections.Generic; using System.Globalization; using System.Linq; -using Microsoft.ML.Trainers.FastTree.Internal; +using Microsoft.ML.Trainers.FastTree; namespace Microsoft.ML.LightGBM { diff --git a/src/Microsoft.ML.ResultProcessor/ResultProcessor.cs b/src/Microsoft.ML.ResultProcessor/ResultProcessor.cs index 2ce8ae224f..ba7f0b2fce 100644 --- a/src/Microsoft.ML.ResultProcessor/ResultProcessor.cs +++ b/src/Microsoft.ML.ResultProcessor/ResultProcessor.cs @@ -12,6 +12,7 @@ using Microsoft.ML.Command; using Microsoft.ML.CommandLine; using Microsoft.ML.Data; +using Microsoft.ML.Internal.Internallearn; using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Model; using Microsoft.ML.Tools; @@ -20,7 +21,7 @@ using Microsoft.ML.ExperimentVisualization; #endif -namespace Microsoft.ML.Internal.Internallearn.ResultProcessor +namespace Microsoft.ML.ResultProcessor { using Float = System.Single; /// diff --git a/src/Microsoft.ML.Sweeper/Algorithms/KdoSweeper.cs b/src/Microsoft.ML.Sweeper/Algorithms/KdoSweeper.cs index 7e0ca2c035..469988ec7c 100644 --- a/src/Microsoft.ML.Sweeper/Algorithms/KdoSweeper.cs +++ b/src/Microsoft.ML.Sweeper/Algorithms/KdoSweeper.cs @@ -9,7 +9,7 @@ using Microsoft.ML.CommandLine; using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Sweeper.Algorithms; -using Microsoft.ML.Trainers.FastTree.Internal; +using Microsoft.ML.Trainers.FastTree; using Float = System.Single; [assembly: LoadableClass(typeof(KdoSweeper), typeof(KdoSweeper.Arguments), typeof(SignatureSweeper), diff --git a/src/Microsoft.ML.Sweeper/Algorithms/SmacSweeper.cs b/src/Microsoft.ML.Sweeper/Algorithms/SmacSweeper.cs index 6c1738b297..8a81844eb0 100644 --- a/src/Microsoft.ML.Sweeper/Algorithms/SmacSweeper.cs +++ b/src/Microsoft.ML.Sweeper/Algorithms/SmacSweeper.cs @@ -13,7 +13,6 @@ using Microsoft.ML.Sweeper; using Microsoft.ML.Sweeper.Algorithms; using Microsoft.ML.Trainers.FastTree; -using Microsoft.ML.Trainers.FastTree.Internal; using Float = System.Single; [assembly: LoadableClass(typeof(SmacSweeper), typeof(SmacSweeper.Arguments), typeof(SignatureSweeper), diff --git a/src/Microsoft.ML.Sweeper/ConfigRunner.cs b/src/Microsoft.ML.Sweeper/ConfigRunner.cs index 082a3fb4c9..cbe2a99900 100644 --- a/src/Microsoft.ML.Sweeper/ConfigRunner.cs +++ b/src/Microsoft.ML.Sweeper/ConfigRunner.cs @@ -12,7 +12,7 @@ using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Sweeper; -using ResultProcessorInternal = Microsoft.ML.Internal.Internallearn.ResultProcessor; +using ResultProcessorInternal = Microsoft.ML.ResultProcessor; [assembly: LoadableClass(typeof(LocalExeConfigRunner), typeof(LocalExeConfigRunner.Arguments), typeof(SignatureConfigRunner), "Local Sweep Config Runner", "Local")] diff --git a/src/Microsoft.ML.Sweeper/SweepResultEvaluator.cs b/src/Microsoft.ML.Sweeper/SweepResultEvaluator.cs index 8b03b89cb9..a55f8d4647 100644 --- a/src/Microsoft.ML.Sweeper/SweepResultEvaluator.cs +++ b/src/Microsoft.ML.Sweeper/SweepResultEvaluator.cs @@ -8,7 +8,7 @@ using Microsoft.ML.CommandLine; using Microsoft.ML.Data; using Microsoft.ML.Sweeper; -using ResultProcessor = Microsoft.ML.Internal.Internallearn.ResultProcessor; +using ResultProcessor = Microsoft.ML.ResultProcessor; [assembly: LoadableClass(typeof(InternalSweepResultEvaluator), typeof(InternalSweepResultEvaluator.Arguments), typeof(SignatureSweepResultEvaluator), "TLC Sweep Result Evaluator", "TlcEvaluator", "Tlc")] diff --git a/test/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs b/test/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs index b159d2b659..c9ae3f9da3 100644 --- a/test/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs +++ b/test/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs @@ -12,7 +12,7 @@ using Microsoft.ML.Core.Tests.UnitTests; using Microsoft.ML.Data; using Microsoft.ML.Data.IO; -using Microsoft.ML.Ensemble.EntryPoints; +using Microsoft.ML.Ensemble; using Microsoft.ML.Ensemble.OutputCombiners; using Microsoft.ML.EntryPoints; using Microsoft.ML.EntryPoints.JsonUtils; diff --git a/test/Microsoft.ML.Core.Tests/UnitTests/TestUtilities.cs b/test/Microsoft.ML.Core.Tests/UnitTests/TestUtilities.cs index 9c0bd79e8e..e94de49320 100644 --- a/test/Microsoft.ML.Core.Tests/UnitTests/TestUtilities.cs +++ b/test/Microsoft.ML.Core.Tests/UnitTests/TestUtilities.cs @@ -7,7 +7,6 @@ using System.Linq; using Microsoft.ML.Internal.Utilities; using Microsoft.ML.RunTests; -using Microsoft.ML.Trainers.FastTree.Internal; using Xunit; using Xunit.Abstractions; diff --git a/test/Microsoft.ML.Predictor.Tests/TestParallelFasttreeInterface.cs b/test/Microsoft.ML.Predictor.Tests/TestParallelFasttreeInterface.cs index 6c246fa4a0..776431faba 100644 --- a/test/Microsoft.ML.Predictor.Tests/TestParallelFasttreeInterface.cs +++ b/test/Microsoft.ML.Predictor.Tests/TestParallelFasttreeInterface.cs @@ -6,7 +6,7 @@ using Microsoft.ML; using Microsoft.ML.Internal.Utilities; using Microsoft.ML.RunTests; -using Microsoft.ML.Trainers.FastTree.Internal; +using Microsoft.ML.Trainers.FastTree; using Xunit; using Xunit.Abstractions; diff --git a/test/Microsoft.ML.Predictor.Tests/TestPredictors.cs b/test/Microsoft.ML.Predictor.Tests/TestPredictors.cs index 17b3971741..4ecd744c36 100644 --- a/test/Microsoft.ML.Predictor.Tests/TestPredictors.cs +++ b/test/Microsoft.ML.Predictor.Tests/TestPredictors.cs @@ -21,7 +21,6 @@ namespace Microsoft.ML.RunTests using Microsoft.ML.TestFramework; using Microsoft.ML.Trainers; using Microsoft.ML.Trainers.FastTree; - using Microsoft.ML.Trainers.FastTree.Internal; using Microsoft.ML.Trainers.HalLearners; using Microsoft.ML.Trainers.Online; using Xunit; diff --git a/test/Microsoft.ML.StaticPipelineTesting/Training.cs b/test/Microsoft.ML.StaticPipelineTesting/Training.cs index a1f81dfe25..c14b5071d2 100644 --- a/test/Microsoft.ML.StaticPipelineTesting/Training.cs +++ b/test/Microsoft.ML.StaticPipelineTesting/Training.cs @@ -8,13 +8,11 @@ using Microsoft.ML; using Microsoft.ML.Data; using Microsoft.ML.FactorizationMachine; -using Microsoft.ML.HalLearners; using Microsoft.ML.Internal.Calibration; using Microsoft.ML.Internal.Internallearn; using Microsoft.ML.LightGBM; using Microsoft.ML.LightGBM.StaticPipe; using Microsoft.ML.RunTests; -using Microsoft.ML.SamplesUtils; using Microsoft.ML.StaticPipe; using Microsoft.ML.Trainers; using Microsoft.ML.Trainers.FastTree; @@ -1027,7 +1025,7 @@ public void MultiClassLightGbmStaticPipelineWithInMemoryData() var mlContext = new MLContext(seed: 1, conc: 1); // Create in-memory examples as C# native class. - var examples = DatasetUtils.GenerateRandomMulticlassClassificationExamples(1000); + var examples = SamplesUtils.DatasetUtils.GenerateRandomMulticlassClassificationExamples(1000); // Convert native C# class to IDataView, a consumble format to ML.NET functions. var dataView = mlContext.Data.ReadFromEnumerable(examples); @@ -1079,7 +1077,7 @@ public void MultiClassLightGbmStaticPipelineWithInMemoryData() Assert.Equal(0.86309523809523814, metrics.AccuracyMicro, 6); // Convert prediction in ML.NET format to native C# class. - var nativePredictions = mlContext.CreateEnumerable(prediction.AsDynamic, false).ToList(); + var nativePredictions = mlContext.CreateEnumerable(prediction.AsDynamic, false).ToList(); // Get schema object of the prediction. It contains metadata such as the mapping from predicted label index // (e.g., 1) to its actual label (e.g., "AA"). @@ -1087,7 +1085,7 @@ public void MultiClassLightGbmStaticPipelineWithInMemoryData() // Retrieve the mapping from labels to label indexes. var labelBuffer = new VBuffer>(); - schema[nameof(DatasetUtils.MulticlassClassificationExample.PredictedLabelIndex)].Metadata.GetValue("KeyValues", ref labelBuffer); + schema[nameof(SamplesUtils.DatasetUtils.MulticlassClassificationExample.PredictedLabelIndex)].Metadata.GetValue("KeyValues", ref labelBuffer); var nativeLabels = labelBuffer.DenseValues().ToList(); // nativeLabels[nativePrediction.PredictedLabelIndex-1] is the original label indexed by nativePrediction.PredictedLabelIndex. // Show prediction result for the 3rd example. diff --git a/test/Microsoft.ML.TestFramework/BaseTestPredictorsMaml.cs b/test/Microsoft.ML.TestFramework/BaseTestPredictorsMaml.cs index 57b2983f44..16e2ef0325 100644 --- a/test/Microsoft.ML.TestFramework/BaseTestPredictorsMaml.cs +++ b/test/Microsoft.ML.TestFramework/BaseTestPredictorsMaml.cs @@ -9,7 +9,7 @@ namespace Microsoft.ML.RunTests { - using ResultProcessor = Microsoft.ML.Internal.Internallearn.ResultProcessor.ResultProcessor; + using ResultProcessor = ResultProcessor.ResultProcessor; /// /// This is a base test class designed to support running trainings and related diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/IntrospectiveTraining.cs b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/IntrospectiveTraining.cs index fd61f0eb77..5223cc0e38 100644 --- a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/IntrospectiveTraining.cs +++ b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/IntrospectiveTraining.cs @@ -94,7 +94,7 @@ public void FastTreeClassificationIntrospectiveTraining() public void FastForestRegressionIntrospectiveTraining() { var ml = new MLContext(seed: 1, conc: 1); - var data = DatasetUtils.GenerateFloatLabelFloatFeatureVectorSamples(1000); + var data = SamplesUtils.DatasetUtils.GenerateFloatLabelFloatFeatureVectorSamples(1000); var dataView = ml.Data.ReadFromEnumerable(data); RegressionPredictionTransformer pred = null; diff --git a/test/Microsoft.ML.Tests/TrainerEstimators/TreeEnsembleFeaturizerTest.cs b/test/Microsoft.ML.Tests/TrainerEstimators/TreeEnsembleFeaturizerTest.cs index 2cde2c918e..e6ced83d4d 100644 --- a/test/Microsoft.ML.Tests/TrainerEstimators/TreeEnsembleFeaturizerTest.cs +++ b/test/Microsoft.ML.Tests/TrainerEstimators/TreeEnsembleFeaturizerTest.cs @@ -2,12 +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; +using System.Linq; using Microsoft.Data.DataView; using Microsoft.ML.Data; -using Microsoft.ML.SamplesUtils; using Microsoft.ML.Trainers.FastTree; -using System; -using System.Linq; using Xunit; namespace Microsoft.ML.Tests.TrainerEstimators @@ -18,7 +17,7 @@ public partial class TrainerEstimators public void TreeEnsembleFeaturizerOutputSchemaTest() { // Create data set - var data = DatasetUtils.GenerateBinaryLabelFloatFeatureVectorSamples(1000).ToList(); + var data = SamplesUtils.DatasetUtils.GenerateBinaryLabelFloatFeatureVectorSamples(1000).ToList(); var dataView = ML.Data.ReadFromEnumerable(data); // Define a tree model whose trees will be extracted to construct a tree featurizer. @@ -38,8 +37,8 @@ public void TreeEnsembleFeaturizerOutputSchemaTest() // To get output schema, we need to create RoleMappedSchema for calling Bind(...). var roleMappedSchema = new RoleMappedSchema(dataView.Schema, - label: nameof(DatasetUtils.BinaryLabelFloatFeatureVectorSample.Label), - feature: nameof(DatasetUtils.BinaryLabelFloatFeatureVectorSample.Features)); + label: nameof(SamplesUtils.DatasetUtils.BinaryLabelFloatFeatureVectorSample.Label), + feature: nameof(SamplesUtils.DatasetUtils.BinaryLabelFloatFeatureVectorSample.Features)); // Retrieve output schema. var boundMapper = (treeFeaturizer as ISchemaBindableMapper).Bind(Env, roleMappedSchema); diff --git a/test/Microsoft.ML.Tests/TrainerEstimators/TreeEstimators.cs b/test/Microsoft.ML.Tests/TrainerEstimators/TreeEstimators.cs index ddaf368dd8..9f3dfe20ee 100644 --- a/test/Microsoft.ML.Tests/TrainerEstimators/TreeEstimators.cs +++ b/test/Microsoft.ML.Tests/TrainerEstimators/TreeEstimators.cs @@ -331,7 +331,7 @@ private void LightGbmHelper(bool useSoftmax, out string modelString, out List Date: Sat, 9 Feb 2019 22:46:47 -0800 Subject: [PATCH 3/3] regenerating the catalog --- .../Common/EntryPoints/core_ep-list.tsv | 26 +++++++++---------- 1 file changed, 13 insertions(+), 13 deletions(-) diff --git a/test/BaselineOutput/Common/EntryPoints/core_ep-list.tsv b/test/BaselineOutput/Common/EntryPoints/core_ep-list.tsv index 356268709c..256d946834 100644 --- a/test/BaselineOutput/Common/EntryPoints/core_ep-list.tsv +++ b/test/BaselineOutput/Common/EntryPoints/core_ep-list.tsv @@ -4,19 +4,19 @@ Data.IDataViewArrayConverter Create an array variable of IDataView Microsoft.ML. 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.EntryPoints.ImportTextData TextLoader Microsoft.ML.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.AnomalyPipelineEnsemble Combine anomaly detection models into an ensemble Microsoft.ML.Ensemble.EnsembleCreator CreateAnomalyPipelineEnsemble Microsoft.ML.Ensemble.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.BinaryEnsemble Combine binary classifiers into an ensemble Microsoft.ML.Ensemble.EnsembleCreator CreateBinaryEnsemble Microsoft.ML.Ensemble.EnsembleCreator+ClassifierInput Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput +Models.BinaryPipelineEnsemble Combine binary classification models into an ensemble Microsoft.ML.Ensemble.EnsembleCreator CreateBinaryPipelineEnsemble Microsoft.ML.Ensemble.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.EnsembleSummary Summarize a pipeline ensemble predictor. Microsoft.ML.Ensemble.PipelineEnsemble Summarize Microsoft.ML.EntryPoints.SummarizePredictor+Input Microsoft.ML.Ensemble.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.MultiClassPipelineEnsemble Combine multiclass classifiers into an ensemble Microsoft.ML.Ensemble.EnsembleCreator CreateMultiClassPipelineEnsemble Microsoft.ML.Ensemble.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] @@ -26,9 +26,9 @@ Models.PAVCalibrator Apply a PAV calibrator to an input model Microsoft.ML.Inter 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.RegressionEnsemble Combine regression models into an ensemble Microsoft.ML.Ensemble.EnsembleCreator CreateRegressionEnsemble Microsoft.ML.Ensemble.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.RegressionPipelineEnsemble Combine regression models into an ensemble Microsoft.ML.Ensemble.EnsembleCreator CreateRegressionPipelineEnsemble Microsoft.ML.Ensemble.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 @@ -40,9 +40,9 @@ TimeSeriesProcessingEntryPoints.SlidingWindowTransform Returns the last values f 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+Options 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.EnsembleBinaryClassifier Train binary ensemble. Microsoft.ML.Ensemble.Ensemble CreateBinaryEnsemble Microsoft.ML.Ensemble.EnsembleTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput +Trainers.EnsembleClassification Train multiclass ensemble. Microsoft.ML.Ensemble.Ensemble CreateMultiClassEnsemble Microsoft.ML.Ensemble.MulticlassDataPartitionEnsembleTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+MulticlassClassificationOutput +Trainers.EnsembleRegression Train regression ensemble. Microsoft.ML.Ensemble.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+Options 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+Options 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+Options Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput @@ -58,8 +58,8 @@ Trainers.LightGbmClassifier Train a LightGBM multi class model. Microsoft.ML.Lig Trainers.LightGbmRanker Train a LightGBM ranking model. Microsoft.ML.LightGBM.LightGbm TrainRanking Microsoft.ML.LightGBM.Options Microsoft.ML.EntryPoints.CommonOutputs+RankingOutput Trainers.LightGbmRegressor LightGBM Regression Microsoft.ML.LightGBM.LightGbm TrainRegression Microsoft.ML.LightGBM.Options Microsoft.ML.EntryPoints.CommonOutputs+RegressionOutput Trainers.LinearSvmBinaryClassifier Train a linear SVM. Microsoft.ML.Trainers.Online.LinearSvmTrainer TrainLinearSvm Microsoft.ML.Trainers.Online.LinearSvmTrainer+Options 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+Options 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+Options Microsoft.ML.EntryPoints.CommonOutputs+MulticlassClassificationOutput +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.Trainers.LogisticRegression TrainBinary Microsoft.ML.Trainers.LogisticRegression+Options 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.Trainers.LogisticRegression TrainMultiClass Microsoft.ML.Trainers.MulticlassLogisticRegression+Options 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+Options Microsoft.ML.EntryPoints.CommonOutputs+RegressionOutput Trainers.OrdinaryLeastSquaresRegressor Train an OLS regression model. Microsoft.ML.Trainers.HalLearners.OlsLinearRegressionTrainer TrainRegression Microsoft.ML.Trainers.HalLearners.OlsLinearRegressionTrainer+Options Microsoft.ML.EntryPoints.CommonOutputs+RegressionOutput @@ -69,7 +69,7 @@ Trainers.StochasticDualCoordinateAscentBinaryClassifier Train an SDCA binary mod Trainers.StochasticDualCoordinateAscentClassifier The SDCA linear multi-class classification trainer. Microsoft.ML.Trainers.Sdca TrainMultiClass Microsoft.ML.Trainers.SdcaMultiClassTrainer+Options Microsoft.ML.EntryPoints.CommonOutputs+MulticlassClassificationOutput Trainers.StochasticDualCoordinateAscentRegressor The SDCA linear regression trainer. Microsoft.ML.Trainers.Sdca TrainRegression Microsoft.ML.Trainers.SdcaRegressionTrainer+Options Microsoft.ML.EntryPoints.CommonOutputs+RegressionOutput Trainers.StochasticGradientDescentBinaryClassifier Train an Hogwild SGD binary model. Microsoft.ML.Trainers.StochasticGradientDescentClassificationTrainer TrainBinary Microsoft.ML.Trainers.StochasticGradientDescentClassificationTrainer+Options Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput -Trainers.SymSgdBinaryClassifier Train a symbolic SGD. Microsoft.ML.Trainers.SymSgd.SymSgdClassificationTrainer TrainSymSgd Microsoft.ML.Trainers.SymSgd.SymSgdClassificationTrainer+Options Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput +Trainers.SymSgdBinaryClassifier Train a symbolic SGD. Microsoft.ML.Trainers.HalLearners.SymSgdClassificationTrainer TrainSymSgd Microsoft.ML.Trainers.HalLearners.SymSgdClassificationTrainer+Options Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput Transforms.ApproximateBootstrapSampler Approximate bootstrap sampling. Microsoft.ML.Transforms.BootstrapSample GetSample Microsoft.ML.Transforms.BootstrapSamplingTransformer+Options 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