File-scoped namespaces in files under Prediction (Microsoft.ML.Core)#6792

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Merged
michaelgsharp merged 3 commits into from
Sep 1, 2023
Merged

File-scoped namespaces in files under Prediction (Microsoft.ML.Core) #6792

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File-scoped namespaces in files under `Prediction` (`Microsoft.ML.Core`)
Aug 10, 2023
609936c
Merge branch 'dotnet:main' into improvement6
Lehonti Aug 26, 2023
547d22c
Merge branch 'dotnet:main' into improvement6
Lehonti Aug 31, 2023
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99 changes: 49 additions & 50 deletions src/Microsoft.ML.Core/Prediction/IPredictor.cs
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Original file line numberDiff line numberDiff line change
Expand Up@@ -2,62 +2,61 @@
// 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
namespace Microsoft.ML;

/// <summary>
/// Type of prediction task. Note that this is a legacy structure and usage of this should generally be
/// discouraged in future projects. Its presence suggests that there are privileged and supported
/// tasks, and anything outside of this is unsupported. This runs rather contrary to the idea of this
/// being an expandable framework, and it is inappropriately limiting. For legacy pipelines based on
/// <see cref="ITrainer"/> and <see cref="IPredictor"/> it is still useful, but for things based on
/// the <see cref="IEstimator{TTransformer}"/> idiom, it is inappropriate.
/// </summary>
[BestFriend]
internal enum PredictionKind
{
/// <summary>
/// Type of prediction task. Note that this is a legacy structure and usage of this should generally be
/// discouraged in future projects. Its presence suggests that there are privileged and supported
/// tasks, and anything outside of this is unsupported. This runs rather contrary to the idea of this
/// being an expandable framework, and it is inappropriately limiting. For legacy pipelines based on
/// <see cref="ITrainer"/> and <see cref="IPredictor"/> it is still useful, but for things based on
/// the <see cref="IEstimator{TTransformer}"/> idiom, it is inappropriate.
/// </summary>
[BestFriend]
internal enum PredictionKind
{
Unknown = 0,
Custom = 1,
Unknown = 0,
Custom = 1,

BinaryClassification = 2,
MulticlassClassification = 3,
Regression = 4,
MultiOutputRegression = 5,
Ranking = 6,
Recommendation = 7,
AnomalyDetection = 8,
Clustering = 9,
SequenceClassification = 10,
BinaryClassification = 2,
MulticlassClassification = 3,
Regression = 4,
MultiOutputRegression = 5,
Ranking = 6,
Recommendation = 7,
AnomalyDetection = 8,
Clustering = 9,
SequenceClassification = 10,

// More to be added later.
}
// More to be added later.
}

/// <summary>
/// Weakly typed version of IPredictor.
/// </summary>
[BestFriend]
internal interface IPredictor
{
/// <summary>
/// Weakly typed version of IPredictor.
/// Return the type of prediction task.
/// </summary>
[BestFriend]
internal interface IPredictor
{
/// <summary>
/// Return the type of prediction task.
/// </summary>
PredictionKind PredictionKind { get; }
}
PredictionKind PredictionKind { get; }
}

/// <summary>
/// A predictor the produces values of the indicated type.
/// REVIEW: Determine whether this is just a temporary shim or long term solution.
/// </summary>
[BestFriend]
internal interface IPredictorProducing<out TResult> : IPredictor
{
}
/// <summary>
/// A predictor the produces values of the indicated type.
/// REVIEW: Determine whether this is just a temporary shim or long term solution.
/// </summary>
[BestFriend]
internal interface IPredictorProducing<out TResult> : IPredictor
{
}

/// <summary>
/// A predictor that produces values and distributions of the indicated types.
/// Note that from a public API perspective this is bad.
/// </summary>
[BestFriend]
internal interface IDistPredictorProducing<out TResult, out TResultDistribution> : IPredictorProducing<TResult>
{
}
/// <summary>
/// A predictor that produces values and distributions of the indicated types.
/// Note that from a public API perspective this is bad.
/// </summary>
[BestFriend]
internal interface IDistPredictorProducing<out TResult, out TResultDistribution> : IPredictorProducing<TResult>
{
}
175 changes: 87 additions & 88 deletions src/Microsoft.ML.Core/Prediction/ITrainer.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -4,104 +4,103 @@

using Microsoft.ML.Data;

namespace Microsoft.ML
{
// REVIEW: Would be nice if the registration under SignatureTrainer were automatic
// given registration for one of the "sub-class" signatures.
namespace Microsoft.ML;

/// <summary>
/// Loadable class signatures for trainers. Typically each trainer should register with
/// both SignatureTrainer and SignatureXxxTrainer where Xxx is the prediction kind.
/// </summary>
[BestFriend]
internal delegate void SignatureTrainer();
// REVIEW: Would be nice if the registration under SignatureTrainer were automatic
// given registration for one of the "sub-class" signatures.

[BestFriend]
internal delegate void SignatureBinaryClassifierTrainer();
[BestFriend]
internal delegate void SignatureMulticlassClassifierTrainer();
[BestFriend]
internal delegate void SignatureRegressorTrainer();
[BestFriend]
internal delegate void SignatureMultiOutputRegressorTrainer();
[BestFriend]
internal delegate void SignatureRankerTrainer();
[BestFriend]
internal delegate void SignatureAnomalyDetectorTrainer();
[BestFriend]
internal delegate void SignatureClusteringTrainer();
[BestFriend]
internal delegate void SignatureSequenceTrainer();
[BestFriend]
internal delegate void SignatureMatrixRecommendingTrainer();
/// <summary>
/// Loadable class signatures for trainers. Typically each trainer should register with
/// both SignatureTrainer and SignatureXxxTrainer where Xxx is the prediction kind.
/// </summary>
[BestFriend]
internal delegate void SignatureTrainer();

[BestFriend]
internal delegate void SignatureBinaryClassifierTrainer();
[BestFriend]
internal delegate void SignatureMulticlassClassifierTrainer();
[BestFriend]
internal delegate void SignatureRegressorTrainer();
[BestFriend]
internal delegate void SignatureMultiOutputRegressorTrainer();
[BestFriend]
internal delegate void SignatureRankerTrainer();
[BestFriend]
internal delegate void SignatureAnomalyDetectorTrainer();
[BestFriend]
internal delegate void SignatureClusteringTrainer();
[BestFriend]
internal delegate void SignatureSequenceTrainer();
[BestFriend]
internal delegate void SignatureMatrixRecommendingTrainer();

/// <summary>
/// The base interface for a trainers. Implementors should not implement this interface directly,
/// but rather implement the more specific <see cref="ITrainer{TPredictor}"/>.
/// </summary>
[BestFriend]
internal interface ITrainer
{
/// <summary>
/// The base interface for a trainers. Implementors should not implement this interface directly,
/// but rather implement the more specific <see cref="ITrainer{TPredictor}"/>.
/// Auxiliary information about the trainer in terms of its capabilities
/// and requirements.
/// </summary>
[BestFriend]
internal interface ITrainer
{
/// <summary>
/// Auxiliary information about the trainer in terms of its capabilities
/// and requirements.
/// </summary>
TrainerInfo Info { get; }
TrainerInfo Info { get; }

/// <summary>
/// Return the type of prediction task for the produced predictor.
/// </summary>
PredictionKind PredictionKind { get; }
/// <summary>
/// Return the type of prediction task for the produced predictor.
/// </summary>
PredictionKind PredictionKind { get; }

/// <summary>
/// Trains a predictor.
/// </summary>
/// <param name="context">A context containing at least the training data</param>
/// <returns>The trained predictor</returns>
/// <seealso cref="ITrainer{TPredictor}.Train(TrainContext)"/>
IPredictor Train(TrainContext context);
}
/// <summary>
/// Trains a predictor.
/// </summary>
/// <param name="context">A context containing at least the training data</param>
/// <returns>The trained predictor</returns>
/// <seealso cref="ITrainer{TPredictor}.Train(TrainContext)"/>
IPredictor Train(TrainContext context);
}

/// <summary>
/// Strongly typed generic interface for a trainer. A trainer object takes training data
/// and produces a predictor.
/// </summary>
/// <typeparam name="TPredictor"> Type of predictor produced</typeparam>
[BestFriend]
internal interface ITrainer<out TPredictor> : ITrainer
where TPredictor : IPredictor
{
/// <summary>
/// Strongly typed generic interface for a trainer. A trainer object takes training data
/// and produces a predictor.
/// Trains a predictor.
/// </summary>
/// <typeparam name="TPredictor"> Type of predictor produced</typeparam>
[BestFriend]
internal interface ITrainer<out TPredictor> : ITrainer
where TPredictor : IPredictor
{
/// <summary>
/// Trains a predictor.
/// </summary>
/// <param name="context">A context containing at least the training data</param>
/// <returns>The trained predictor</returns>
new TPredictor Train(TrainContext context);
}
/// <param name="context">A context containing at least the training data</param>
/// <returns>The trained predictor</returns>
new TPredictor Train(TrainContext context);
}

[BestFriend]
internal static class TrainerExtensions
{
/// <summary>
/// Convenience train extension for the case where one has only a training set with no auxiliary information.
/// Equivalent to calling <see cref="ITrainer.Train(TrainContext)"/>
/// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
/// </summary>
/// <param name="trainer">The trainer</param>
/// <param name="trainData">The training data.</param>
/// <returns>The trained predictor</returns>
public static IPredictor Train(this ITrainer trainer, RoleMappedData trainData)
=> trainer.Train(new TrainContext(trainData));
[BestFriend]
internal static class TrainerExtensions
{
/// <summary>
/// Convenience train extension for the case where one has only a training set with no auxiliary information.
/// Equivalent to calling <see cref="ITrainer.Train(TrainContext)"/>
/// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
/// </summary>
/// <param name="trainer">The trainer</param>
/// <param name="trainData">The training data.</param>
/// <returns>The trained predictor</returns>
public static IPredictor Train(this ITrainer trainer, RoleMappedData trainData)
=> trainer.Train(new TrainContext(trainData));

/// <summary>
/// Convenience train extension for the case where one has only a training set with no auxiliary information.
/// Equivalent to calling <see cref="ITrainer{TPredictor}.Train(TrainContext)"/>
/// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
/// </summary>
/// <param name="trainer">The trainer</param>
/// <param name="trainData">The training data.</param>
/// <returns>The trained predictor</returns>
public static TPredictor Train<TPredictor>(this ITrainer<TPredictor> trainer, RoleMappedData trainData) where TPredictor : IPredictor
=> trainer.Train(new TrainContext(trainData));
}
/// <summary>
/// Convenience train extension for the case where one has only a training set with no auxiliary information.
/// Equivalent to calling <see cref="ITrainer{TPredictor}.Train(TrainContext)"/>
/// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
/// </summary>
/// <param name="trainer">The trainer</param>
/// <param name="trainData">The training data.</param>
/// <returns>The trained predictor</returns>
public static TPredictor Train<TPredictor>(this ITrainer<TPredictor> trainer, RoleMappedData trainData) where TPredictor : IPredictor
=> trainer.Train(new TrainContext(trainData));
}
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var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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File-scoped namespaces in files under Prediction (Microsoft.ML.Core)#6792

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 Merged

michaelgsharp
merged 3 commits into

from

Sep 1, 2023
 Merged


File-scoped namespaces in files under Prediction (Microsoft.ML.Core)
#6792
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6ec9418

File-scoped namespaces in files under `Prediction` (`Microsoft.ML.Core`)

Aug 10, 2023
609936c

Merge branch 'dotnet:main' into improvement6


Lehonti Aug 26, 2023
547d22c

Merge branch 'dotnet:main' into improvement6


Lehonti Aug 31, 2023

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99 changes: 49 additions & 50 deletions
src/Microsoft.ML.Core/Prediction/IPredictor.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -2,62 +2,61 @@
// 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
namespace Microsoft.ML;

/// <summary>
/// Type of prediction task. Note that this is a legacy structure and usage of this should generally be
/// discouraged in future projects. Its presence suggests that there are privileged and supported
/// tasks, and anything outside of this is unsupported. This runs rather contrary to the idea of this
/// being an expandable framework, and it is inappropriately limiting. For legacy pipelines based on
/// <see cref="ITrainer"/> and <see cref="IPredictor"/> it is still useful, but for things based on
/// the <see cref="IEstimator{TTransformer}"/> idiom, it is inappropriate.
/// </summary>
[BestFriend]
internal enum PredictionKind
{
 /// <summary>
 /// Type of prediction task. Note that this is a legacy structure and usage of this should generally be
 /// discouraged in future projects. Its presence suggests that there are privileged and supported
 /// tasks, and anything outside of this is unsupported. This runs rather contrary to the idea of this
 /// being an expandable framework, and it is inappropriately limiting. For legacy pipelines based on
 /// <see cref="ITrainer"/> and <see cref="IPredictor"/> it is still useful, but for things based on
 /// the <see cref="IEstimator{TTransformer}"/> idiom, it is inappropriate.
 /// </summary>
 [BestFriend]
 internal enum PredictionKind
 {
 Unknown = 0,
 Custom = 1,
 Unknown = 0,
 Custom = 1,

BinaryClassification = 2,
MulticlassClassification = 3,
Regression = 4,
MultiOutputRegression = 5,
Ranking = 6,
Recommendation = 7,
AnomalyDetection = 8,
Clustering = 9,
SequenceClassification = 10,
 BinaryClassification = 2,
 MulticlassClassification = 3,
 Regression = 4,
 MultiOutputRegression = 5,
 Ranking = 6,
 Recommendation = 7,
 AnomalyDetection = 8,
 Clustering = 9,
 SequenceClassification = 10,

// More to be added later.
}
 // More to be added later.
}

/// <summary>
/// Weakly typed version of IPredictor.
/// </summary>
[BestFriend]
internal interface IPredictor
{
 /// <summary>
 /// Weakly typed version of IPredictor.
 /// Return the type of prediction task.
 /// </summary>
 [BestFriend]
 internal interface IPredictor
 {
 /// <summary>
 /// Return the type of prediction task.
 /// </summary>
 PredictionKind PredictionKind { get; }
 }
 PredictionKind PredictionKind { get; }
}

/// <summary>
/// A predictor the produces values of the indicated type.
/// REVIEW: Determine whether this is just a temporary shim or long term solution.
/// </summary>
[BestFriend]
internal interface IPredictorProducing<out TResult> : IPredictor
{
}
/// <summary>
/// A predictor the produces values of the indicated type.
/// REVIEW: Determine whether this is just a temporary shim or long term solution.
/// </summary>
[BestFriend]
internal interface IPredictorProducing<out TResult> : IPredictor
{
}

 /// <summary>
 /// A predictor that produces values and distributions of the indicated types.
 /// Note that from a public API perspective this is bad.
 /// </summary>
 [BestFriend]
 internal interface IDistPredictorProducing<out TResult, out TResultDistribution> : IPredictorProducing<TResult>
 {
 }
/// <summary>
/// A predictor that produces values and distributions of the indicated types.
/// Note that from a public API perspective this is bad.
/// </summary>
[BestFriend]
internal interface IDistPredictorProducing<out TResult, out TResultDistribution> : IPredictorProducing<TResult>
{
}

175 changes: 87 additions & 88 deletions
src/Microsoft.ML.Core/Prediction/ITrainer.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -4,104 +4,103 @@

using Microsoft.ML.Data;

namespace Microsoft.ML
{
 // REVIEW: Would be nice if the registration under SignatureTrainer were automatic
 // given registration for one of the "sub-class" signatures.
namespace Microsoft.ML;

 /// <summary>
 /// Loadable class signatures for trainers. Typically each trainer should register with
 /// both SignatureTrainer and SignatureXxxTrainer where Xxx is the prediction kind.
 /// </summary>
 [BestFriend]
 internal delegate void SignatureTrainer();
// REVIEW: Would be nice if the registration under SignatureTrainer were automatic
// given registration for one of the "sub-class" signatures.

 [BestFriend]
 internal delegate void SignatureBinaryClassifierTrainer();
 [BestFriend]
 internal delegate void SignatureMulticlassClassifierTrainer();
 [BestFriend]
 internal delegate void SignatureRegressorTrainer();
 [BestFriend]
 internal delegate void SignatureMultiOutputRegressorTrainer();
 [BestFriend]
 internal delegate void SignatureRankerTrainer();
 [BestFriend]
 internal delegate void SignatureAnomalyDetectorTrainer();
 [BestFriend]
 internal delegate void SignatureClusteringTrainer();
 [BestFriend]
 internal delegate void SignatureSequenceTrainer();
 [BestFriend]
 internal delegate void SignatureMatrixRecommendingTrainer();
/// <summary>
/// Loadable class signatures for trainers. Typically each trainer should register with
/// both SignatureTrainer and SignatureXxxTrainer where Xxx is the prediction kind.
/// </summary>
[BestFriend]
internal delegate void SignatureTrainer();

[BestFriend]
internal delegate void SignatureBinaryClassifierTrainer();
[BestFriend]
internal delegate void SignatureMulticlassClassifierTrainer();
[BestFriend]
internal delegate void SignatureRegressorTrainer();
[BestFriend]
internal delegate void SignatureMultiOutputRegressorTrainer();
[BestFriend]
internal delegate void SignatureRankerTrainer();
[BestFriend]
internal delegate void SignatureAnomalyDetectorTrainer();
[BestFriend]
internal delegate void SignatureClusteringTrainer();
[BestFriend]
internal delegate void SignatureSequenceTrainer();
[BestFriend]
internal delegate void SignatureMatrixRecommendingTrainer();

/// <summary>
/// The base interface for a trainers. Implementors should not implement this interface directly,
/// but rather implement the more specific <see cref="ITrainer{TPredictor}"/>.
/// </summary>
[BestFriend]
internal interface ITrainer
{
 /// <summary>
 /// The base interface for a trainers. Implementors should not implement this interface directly,
 /// but rather implement the more specific <see cref="ITrainer{TPredictor}"/>.
 /// Auxiliary information about the trainer in terms of its capabilities
 /// and requirements.
 /// </summary>
 [BestFriend]
 internal interface ITrainer
 {
 /// <summary>
 /// Auxiliary information about the trainer in terms of its capabilities
 /// and requirements.
 /// </summary>
 TrainerInfo Info { get; }
 TrainerInfo Info { get; }

/// <summary>
/// Return the type of prediction task for the produced predictor.
/// </summary>
PredictionKind PredictionKind { get; }
 /// <summary>
 /// Return the type of prediction task for the produced predictor.
 /// </summary>
 PredictionKind PredictionKind { get; }

/// <summary>
/// Trains a predictor.
/// </summary>
/// <param name="context">A context containing at least the training data</param>
/// <returns>The trained predictor</returns>
/// <seealso cref="ITrainer{TPredictor}.Train(TrainContext)"/>
IPredictor Train(TrainContext context);
}
 /// <summary>
 /// Trains a predictor.
 /// </summary>
 /// <param name="context">A context containing at least the training data</param>
 /// <returns>The trained predictor</returns>
 /// <seealso cref="ITrainer{TPredictor}.Train(TrainContext)"/>
 IPredictor Train(TrainContext context);
}

/// <summary>
/// Strongly typed generic interface for a trainer. A trainer object takes training data
/// and produces a predictor.
/// </summary>
/// <typeparam name="TPredictor"> Type of predictor produced</typeparam>
[BestFriend]
internal interface ITrainer<out TPredictor> : ITrainer
 where TPredictor : IPredictor
{
 /// <summary>
 /// Strongly typed generic interface for a trainer. A trainer object takes training data
 /// and produces a predictor.
 /// Trains a predictor.
 /// </summary>
 /// <typeparam name="TPredictor"> Type of predictor produced</typeparam>
 [BestFriend]
 internal interface ITrainer<out TPredictor> : ITrainer
 where TPredictor : IPredictor
 {
 /// <summary>
 /// Trains a predictor.
 /// </summary>
 /// <param name="context">A context containing at least the training data</param>
 /// <returns>The trained predictor</returns>
 new TPredictor Train(TrainContext context);
 }
 /// <param name="context">A context containing at least the training data</param>
 /// <returns>The trained predictor</returns>
 new TPredictor Train(TrainContext context);
}

[BestFriend]
internal static class TrainerExtensions
{
/// <summary>
/// Convenience train extension for the case where one has only a training set with no auxiliary information.
/// Equivalent to calling <see cref="ITrainer.Train(TrainContext)"/>
/// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
/// </summary>
/// <param name="trainer">The trainer</param>
/// <param name="trainData">The training data.</param>
/// <returns>The trained predictor</returns>
public static IPredictor Train(this ITrainer trainer, RoleMappedData trainData)
=> trainer.Train(new TrainContext(trainData));
[BestFriend]
internal static class TrainerExtensions
{
 /// <summary>
 /// Convenience train extension for the case where one has only a training set with no auxiliary information.
 /// Equivalent to calling <see cref="ITrainer.Train(TrainContext)"/>
 /// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
 /// </summary>
 /// <param name="trainer">The trainer</param>
 /// <param name="trainData">The training data.</param>
 /// <returns>The trained predictor</returns>
 public static IPredictor Train(this ITrainer trainer, RoleMappedData trainData)
 => trainer.Train(new TrainContext(trainData));

 /// <summary>
 /// Convenience train extension for the case where one has only a training set with no auxiliary information.
 /// Equivalent to calling <see cref="ITrainer{TPredictor}.Train(TrainContext)"/>
 /// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
 /// </summary>
 /// <param name="trainer">The trainer</param>
 /// <param name="trainData">The training data.</param>
 /// <returns>The trained predictor</returns>
 public static TPredictor Train<TPredictor>(this ITrainer<TPredictor> trainer, RoleMappedData trainData) where TPredictor : IPredictor
 => trainer.Train(new TrainContext(trainData));
 }
 /// <summary>
 /// Convenience train extension for the case where one has only a training set with no auxiliary information.
 /// Equivalent to calling <see cref="ITrainer{TPredictor}.Train(TrainContext)"/>
 /// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
 /// </summary>
 /// <param name="trainer">The trainer</param>
 /// <param name="trainData">The training data.</param>
 /// <returns>The trained predictor</returns>
 public static TPredictor Train<TPredictor>(this ITrainer<TPredictor> trainer, RoleMappedData trainData) where TPredictor : IPredictor
 => trainer.Train(new TrainContext(trainData));
}
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try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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File-scoped namespaces in files under Prediction (Microsoft.ML.Core)#6792

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privacy statement. We’ll occasionally send you account related emails.

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 Merged

michaelgsharp
merged 3 commits into

from

Sep 1, 2023
 Merged


File-scoped namespaces in files under Prediction (Microsoft.ML.Core)
#6792
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6ec9418

File-scoped namespaces in files under `Prediction` (`Microsoft.ML.Core`)

Aug 10, 2023
609936c

Merge branch 'dotnet:main' into improvement6


Lehonti Aug 26, 2023
547d22c

Merge branch 'dotnet:main' into improvement6


Lehonti Aug 31, 2023

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99 changes: 49 additions & 50 deletions
src/Microsoft.ML.Core/Prediction/IPredictor.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -2,62 +2,61 @@
// 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
namespace Microsoft.ML;

/// <summary>
/// Type of prediction task. Note that this is a legacy structure and usage of this should generally be
/// discouraged in future projects. Its presence suggests that there are privileged and supported
/// tasks, and anything outside of this is unsupported. This runs rather contrary to the idea of this
/// being an expandable framework, and it is inappropriately limiting. For legacy pipelines based on
/// <see cref="ITrainer"/> and <see cref="IPredictor"/> it is still useful, but for things based on
/// the <see cref="IEstimator{TTransformer}"/> idiom, it is inappropriate.
/// </summary>
[BestFriend]
internal enum PredictionKind
{
 /// <summary>
 /// Type of prediction task. Note that this is a legacy structure and usage of this should generally be
 /// discouraged in future projects. Its presence suggests that there are privileged and supported
 /// tasks, and anything outside of this is unsupported. This runs rather contrary to the idea of this
 /// being an expandable framework, and it is inappropriately limiting. For legacy pipelines based on
 /// <see cref="ITrainer"/> and <see cref="IPredictor"/> it is still useful, but for things based on
 /// the <see cref="IEstimator{TTransformer}"/> idiom, it is inappropriate.
 /// </summary>
 [BestFriend]
 internal enum PredictionKind
 {
 Unknown = 0,
 Custom = 1,
 Unknown = 0,
 Custom = 1,

BinaryClassification = 2,
MulticlassClassification = 3,
Regression = 4,
MultiOutputRegression = 5,
Ranking = 6,
Recommendation = 7,
AnomalyDetection = 8,
Clustering = 9,
SequenceClassification = 10,
 BinaryClassification = 2,
 MulticlassClassification = 3,
 Regression = 4,
 MultiOutputRegression = 5,
 Ranking = 6,
 Recommendation = 7,
 AnomalyDetection = 8,
 Clustering = 9,
 SequenceClassification = 10,

// More to be added later.
}
 // More to be added later.
}

/// <summary>
/// Weakly typed version of IPredictor.
/// </summary>
[BestFriend]
internal interface IPredictor
{
 /// <summary>
 /// Weakly typed version of IPredictor.
 /// Return the type of prediction task.
 /// </summary>
 [BestFriend]
 internal interface IPredictor
 {
 /// <summary>
 /// Return the type of prediction task.
 /// </summary>
 PredictionKind PredictionKind { get; }
 }
 PredictionKind PredictionKind { get; }
}

/// <summary>
/// A predictor the produces values of the indicated type.
/// REVIEW: Determine whether this is just a temporary shim or long term solution.
/// </summary>
[BestFriend]
internal interface IPredictorProducing<out TResult> : IPredictor
{
}
/// <summary>
/// A predictor the produces values of the indicated type.
/// REVIEW: Determine whether this is just a temporary shim or long term solution.
/// </summary>
[BestFriend]
internal interface IPredictorProducing<out TResult> : IPredictor
{
}

 /// <summary>
 /// A predictor that produces values and distributions of the indicated types.
 /// Note that from a public API perspective this is bad.
 /// </summary>
 [BestFriend]
 internal interface IDistPredictorProducing<out TResult, out TResultDistribution> : IPredictorProducing<TResult>
 {
 }
/// <summary>
/// A predictor that produces values and distributions of the indicated types.
/// Note that from a public API perspective this is bad.
/// </summary>
[BestFriend]
internal interface IDistPredictorProducing<out TResult, out TResultDistribution> : IPredictorProducing<TResult>
{
}

175 changes: 87 additions & 88 deletions
src/Microsoft.ML.Core/Prediction/ITrainer.cs

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -4,104 +4,103 @@

using Microsoft.ML.Data;

namespace Microsoft.ML
{
 // REVIEW: Would be nice if the registration under SignatureTrainer were automatic
 // given registration for one of the "sub-class" signatures.
namespace Microsoft.ML;

 /// <summary>
 /// Loadable class signatures for trainers. Typically each trainer should register with
 /// both SignatureTrainer and SignatureXxxTrainer where Xxx is the prediction kind.
 /// </summary>
 [BestFriend]
 internal delegate void SignatureTrainer();
// REVIEW: Would be nice if the registration under SignatureTrainer were automatic
// given registration for one of the "sub-class" signatures.

 [BestFriend]
 internal delegate void SignatureBinaryClassifierTrainer();
 [BestFriend]
 internal delegate void SignatureMulticlassClassifierTrainer();
 [BestFriend]
 internal delegate void SignatureRegressorTrainer();
 [BestFriend]
 internal delegate void SignatureMultiOutputRegressorTrainer();
 [BestFriend]
 internal delegate void SignatureRankerTrainer();
 [BestFriend]
 internal delegate void SignatureAnomalyDetectorTrainer();
 [BestFriend]
 internal delegate void SignatureClusteringTrainer();
 [BestFriend]
 internal delegate void SignatureSequenceTrainer();
 [BestFriend]
 internal delegate void SignatureMatrixRecommendingTrainer();
/// <summary>
/// Loadable class signatures for trainers. Typically each trainer should register with
/// both SignatureTrainer and SignatureXxxTrainer where Xxx is the prediction kind.
/// </summary>
[BestFriend]
internal delegate void SignatureTrainer();

[BestFriend]
internal delegate void SignatureBinaryClassifierTrainer();
[BestFriend]
internal delegate void SignatureMulticlassClassifierTrainer();
[BestFriend]
internal delegate void SignatureRegressorTrainer();
[BestFriend]
internal delegate void SignatureMultiOutputRegressorTrainer();
[BestFriend]
internal delegate void SignatureRankerTrainer();
[BestFriend]
internal delegate void SignatureAnomalyDetectorTrainer();
[BestFriend]
internal delegate void SignatureClusteringTrainer();
[BestFriend]
internal delegate void SignatureSequenceTrainer();
[BestFriend]
internal delegate void SignatureMatrixRecommendingTrainer();

/// <summary>
/// The base interface for a trainers. Implementors should not implement this interface directly,
/// but rather implement the more specific <see cref="ITrainer{TPredictor}"/>.
/// </summary>
[BestFriend]
internal interface ITrainer
{
 /// <summary>
 /// The base interface for a trainers. Implementors should not implement this interface directly,
 /// but rather implement the more specific <see cref="ITrainer{TPredictor}"/>.
 /// Auxiliary information about the trainer in terms of its capabilities
 /// and requirements.
 /// </summary>
 [BestFriend]
 internal interface ITrainer
 {
 /// <summary>
 /// Auxiliary information about the trainer in terms of its capabilities
 /// and requirements.
 /// </summary>
 TrainerInfo Info { get; }
 TrainerInfo Info { get; }

/// <summary>
/// Return the type of prediction task for the produced predictor.
/// </summary>
PredictionKind PredictionKind { get; }
 /// <summary>
 /// Return the type of prediction task for the produced predictor.
 /// </summary>
 PredictionKind PredictionKind { get; }

/// <summary>
/// Trains a predictor.
/// </summary>
/// <param name="context">A context containing at least the training data</param>
/// <returns>The trained predictor</returns>
/// <seealso cref="ITrainer{TPredictor}.Train(TrainContext)"/>
IPredictor Train(TrainContext context);
}
 /// <summary>
 /// Trains a predictor.
 /// </summary>
 /// <param name="context">A context containing at least the training data</param>
 /// <returns>The trained predictor</returns>
 /// <seealso cref="ITrainer{TPredictor}.Train(TrainContext)"/>
 IPredictor Train(TrainContext context);
}

/// <summary>
/// Strongly typed generic interface for a trainer. A trainer object takes training data
/// and produces a predictor.
/// </summary>
/// <typeparam name="TPredictor"> Type of predictor produced</typeparam>
[BestFriend]
internal interface ITrainer<out TPredictor> : ITrainer
 where TPredictor : IPredictor
{
 /// <summary>
 /// Strongly typed generic interface for a trainer. A trainer object takes training data
 /// and produces a predictor.
 /// Trains a predictor.
 /// </summary>
 /// <typeparam name="TPredictor"> Type of predictor produced</typeparam>
 [BestFriend]
 internal interface ITrainer<out TPredictor> : ITrainer
 where TPredictor : IPredictor
 {
 /// <summary>
 /// Trains a predictor.
 /// </summary>
 /// <param name="context">A context containing at least the training data</param>
 /// <returns>The trained predictor</returns>
 new TPredictor Train(TrainContext context);
 }
 /// <param name="context">A context containing at least the training data</param>
 /// <returns>The trained predictor</returns>
 new TPredictor Train(TrainContext context);
}

[BestFriend]
internal static class TrainerExtensions
{
/// <summary>
/// Convenience train extension for the case where one has only a training set with no auxiliary information.
/// Equivalent to calling <see cref="ITrainer.Train(TrainContext)"/>
/// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
/// </summary>
/// <param name="trainer">The trainer</param>
/// <param name="trainData">The training data.</param>
/// <returns>The trained predictor</returns>
public static IPredictor Train(this ITrainer trainer, RoleMappedData trainData)
=> trainer.Train(new TrainContext(trainData));
[BestFriend]
internal static class TrainerExtensions
{
 /// <summary>
 /// Convenience train extension for the case where one has only a training set with no auxiliary information.
 /// Equivalent to calling <see cref="ITrainer.Train(TrainContext)"/>
 /// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
 /// </summary>
 /// <param name="trainer">The trainer</param>
 /// <param name="trainData">The training data.</param>
 /// <returns>The trained predictor</returns>
 public static IPredictor Train(this ITrainer trainer, RoleMappedData trainData)
 => trainer.Train(new TrainContext(trainData));

 /// <summary>
 /// Convenience train extension for the case where one has only a training set with no auxiliary information.
 /// Equivalent to calling <see cref="ITrainer{TPredictor}.Train(TrainContext)"/>
 /// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
 /// </summary>
 /// <param name="trainer">The trainer</param>
 /// <param name="trainData">The training data.</param>
 /// <returns>The trained predictor</returns>
 public static TPredictor Train<TPredictor>(this ITrainer<TPredictor> trainer, RoleMappedData trainData) where TPredictor : IPredictor
 => trainer.Train(new TrainContext(trainData));
 }
 /// <summary>
 /// Convenience train extension for the case where one has only a training set with no auxiliary information.
 /// Equivalent to calling <see cref="ITrainer{TPredictor}.Train(TrainContext)"/>
 /// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
 /// </summary>
 /// <param name="trainer">The trainer</param>
 /// <param name="trainData">The training data.</param>
 /// <returns>The trained predictor</returns>
 public static TPredictor Train<TPredictor>(this ITrainer<TPredictor> trainer, RoleMappedData trainData) where TPredictor : IPredictor
 => trainer.Train(new TrainContext(trainData));
}
Loading

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
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})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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 Merged

michaelgsharp
merged 3 commits into

from

Sep 1, 2023
 Merged


File-scoped namespaces in files under Prediction (Microsoft.ML.Core)
#6792
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6ec9418

File-scoped namespaces in files under `Prediction` (`Microsoft.ML.Core`)

Aug 10, 2023
609936c

Merge branch 'dotnet:main' into improvement6


Lehonti Aug 26, 2023
547d22c

Merge branch 'dotnet:main' into improvement6


Lehonti Aug 31, 2023

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99 changes: 49 additions & 50 deletions
src/Microsoft.ML.Core/Prediction/IPredictor.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -2,62 +2,61 @@
// 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
namespace Microsoft.ML;

/// <summary>
/// Type of prediction task. Note that this is a legacy structure and usage of this should generally be
/// discouraged in future projects. Its presence suggests that there are privileged and supported
/// tasks, and anything outside of this is unsupported. This runs rather contrary to the idea of this
/// being an expandable framework, and it is inappropriately limiting. For legacy pipelines based on
/// <see cref="ITrainer"/> and <see cref="IPredictor"/> it is still useful, but for things based on
/// the <see cref="IEstimator{TTransformer}"/> idiom, it is inappropriate.
/// </summary>
[BestFriend]
internal enum PredictionKind
{
 /// <summary>
 /// Type of prediction task. Note that this is a legacy structure and usage of this should generally be
 /// discouraged in future projects. Its presence suggests that there are privileged and supported
 /// tasks, and anything outside of this is unsupported. This runs rather contrary to the idea of this
 /// being an expandable framework, and it is inappropriately limiting. For legacy pipelines based on
 /// <see cref="ITrainer"/> and <see cref="IPredictor"/> it is still useful, but for things based on
 /// the <see cref="IEstimator{TTransformer}"/> idiom, it is inappropriate.
 /// </summary>
 [BestFriend]
 internal enum PredictionKind
 {
 Unknown = 0,
 Custom = 1,
 Unknown = 0,
 Custom = 1,

BinaryClassification = 2,
MulticlassClassification = 3,
Regression = 4,
MultiOutputRegression = 5,
Ranking = 6,
Recommendation = 7,
AnomalyDetection = 8,
Clustering = 9,
SequenceClassification = 10,
 BinaryClassification = 2,
 MulticlassClassification = 3,
 Regression = 4,
 MultiOutputRegression = 5,
 Ranking = 6,
 Recommendation = 7,
 AnomalyDetection = 8,
 Clustering = 9,
 SequenceClassification = 10,

// More to be added later.
}
 // More to be added later.
}

/// <summary>
/// Weakly typed version of IPredictor.
/// </summary>
[BestFriend]
internal interface IPredictor
{
 /// <summary>
 /// Weakly typed version of IPredictor.
 /// Return the type of prediction task.
 /// </summary>
 [BestFriend]
 internal interface IPredictor
 {
 /// <summary>
 /// Return the type of prediction task.
 /// </summary>
 PredictionKind PredictionKind { get; }
 }
 PredictionKind PredictionKind { get; }
}

/// <summary>
/// A predictor the produces values of the indicated type.
/// REVIEW: Determine whether this is just a temporary shim or long term solution.
/// </summary>
[BestFriend]
internal interface IPredictorProducing<out TResult> : IPredictor
{
}
/// <summary>
/// A predictor the produces values of the indicated type.
/// REVIEW: Determine whether this is just a temporary shim or long term solution.
/// </summary>
[BestFriend]
internal interface IPredictorProducing<out TResult> : IPredictor
{
}

 /// <summary>
 /// A predictor that produces values and distributions of the indicated types.
 /// Note that from a public API perspective this is bad.
 /// </summary>
 [BestFriend]
 internal interface IDistPredictorProducing<out TResult, out TResultDistribution> : IPredictorProducing<TResult>
 {
 }
/// <summary>
/// A predictor that produces values and distributions of the indicated types.
/// Note that from a public API perspective this is bad.
/// </summary>
[BestFriend]
internal interface IDistPredictorProducing<out TResult, out TResultDistribution> : IPredictorProducing<TResult>
{
}

175 changes: 87 additions & 88 deletions
src/Microsoft.ML.Core/Prediction/ITrainer.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -4,104 +4,103 @@

using Microsoft.ML.Data;

namespace Microsoft.ML
{
 // REVIEW: Would be nice if the registration under SignatureTrainer were automatic
 // given registration for one of the "sub-class" signatures.
namespace Microsoft.ML;

 /// <summary>
 /// Loadable class signatures for trainers. Typically each trainer should register with
 /// both SignatureTrainer and SignatureXxxTrainer where Xxx is the prediction kind.
 /// </summary>
 [BestFriend]
 internal delegate void SignatureTrainer();
// REVIEW: Would be nice if the registration under SignatureTrainer were automatic
// given registration for one of the "sub-class" signatures.

 [BestFriend]
 internal delegate void SignatureBinaryClassifierTrainer();
 [BestFriend]
 internal delegate void SignatureMulticlassClassifierTrainer();
 [BestFriend]
 internal delegate void SignatureRegressorTrainer();
 [BestFriend]
 internal delegate void SignatureMultiOutputRegressorTrainer();
 [BestFriend]
 internal delegate void SignatureRankerTrainer();
 [BestFriend]
 internal delegate void SignatureAnomalyDetectorTrainer();
 [BestFriend]
 internal delegate void SignatureClusteringTrainer();
 [BestFriend]
 internal delegate void SignatureSequenceTrainer();
 [BestFriend]
 internal delegate void SignatureMatrixRecommendingTrainer();
/// <summary>
/// Loadable class signatures for trainers. Typically each trainer should register with
/// both SignatureTrainer and SignatureXxxTrainer where Xxx is the prediction kind.
/// </summary>
[BestFriend]
internal delegate void SignatureTrainer();

[BestFriend]
internal delegate void SignatureBinaryClassifierTrainer();
[BestFriend]
internal delegate void SignatureMulticlassClassifierTrainer();
[BestFriend]
internal delegate void SignatureRegressorTrainer();
[BestFriend]
internal delegate void SignatureMultiOutputRegressorTrainer();
[BestFriend]
internal delegate void SignatureRankerTrainer();
[BestFriend]
internal delegate void SignatureAnomalyDetectorTrainer();
[BestFriend]
internal delegate void SignatureClusteringTrainer();
[BestFriend]
internal delegate void SignatureSequenceTrainer();
[BestFriend]
internal delegate void SignatureMatrixRecommendingTrainer();

/// <summary>
/// The base interface for a trainers. Implementors should not implement this interface directly,
/// but rather implement the more specific <see cref="ITrainer{TPredictor}"/>.
/// </summary>
[BestFriend]
internal interface ITrainer
{
 /// <summary>
 /// The base interface for a trainers. Implementors should not implement this interface directly,
 /// but rather implement the more specific <see cref="ITrainer{TPredictor}"/>.
 /// Auxiliary information about the trainer in terms of its capabilities
 /// and requirements.
 /// </summary>
 [BestFriend]
 internal interface ITrainer
 {
 /// <summary>
 /// Auxiliary information about the trainer in terms of its capabilities
 /// and requirements.
 /// </summary>
 TrainerInfo Info { get; }
 TrainerInfo Info { get; }

/// <summary>
/// Return the type of prediction task for the produced predictor.
/// </summary>
PredictionKind PredictionKind { get; }
 /// <summary>
 /// Return the type of prediction task for the produced predictor.
 /// </summary>
 PredictionKind PredictionKind { get; }

/// <summary>
/// Trains a predictor.
/// </summary>
/// <param name="context">A context containing at least the training data</param>
/// <returns>The trained predictor</returns>
/// <seealso cref="ITrainer{TPredictor}.Train(TrainContext)"/>
IPredictor Train(TrainContext context);
}
 /// <summary>
 /// Trains a predictor.
 /// </summary>
 /// <param name="context">A context containing at least the training data</param>
 /// <returns>The trained predictor</returns>
 /// <seealso cref="ITrainer{TPredictor}.Train(TrainContext)"/>
 IPredictor Train(TrainContext context);
}

/// <summary>
/// Strongly typed generic interface for a trainer. A trainer object takes training data
/// and produces a predictor.
/// </summary>
/// <typeparam name="TPredictor"> Type of predictor produced</typeparam>
[BestFriend]
internal interface ITrainer<out TPredictor> : ITrainer
 where TPredictor : IPredictor
{
 /// <summary>
 /// Strongly typed generic interface for a trainer. A trainer object takes training data
 /// and produces a predictor.
 /// Trains a predictor.
 /// </summary>
 /// <typeparam name="TPredictor"> Type of predictor produced</typeparam>
 [BestFriend]
 internal interface ITrainer<out TPredictor> : ITrainer
 where TPredictor : IPredictor
 {
 /// <summary>
 /// Trains a predictor.
 /// </summary>
 /// <param name="context">A context containing at least the training data</param>
 /// <returns>The trained predictor</returns>
 new TPredictor Train(TrainContext context);
 }
 /// <param name="context">A context containing at least the training data</param>
 /// <returns>The trained predictor</returns>
 new TPredictor Train(TrainContext context);
}

[BestFriend]
internal static class TrainerExtensions
{
/// <summary>
/// Convenience train extension for the case where one has only a training set with no auxiliary information.
/// Equivalent to calling <see cref="ITrainer.Train(TrainContext)"/>
/// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
/// </summary>
/// <param name="trainer">The trainer</param>
/// <param name="trainData">The training data.</param>
/// <returns>The trained predictor</returns>
public static IPredictor Train(this ITrainer trainer, RoleMappedData trainData)
=> trainer.Train(new TrainContext(trainData));
[BestFriend]
internal static class TrainerExtensions
{
 /// <summary>
 /// Convenience train extension for the case where one has only a training set with no auxiliary information.
 /// Equivalent to calling <see cref="ITrainer.Train(TrainContext)"/>
 /// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
 /// </summary>
 /// <param name="trainer">The trainer</param>
 /// <param name="trainData">The training data.</param>
 /// <returns>The trained predictor</returns>
 public static IPredictor Train(this ITrainer trainer, RoleMappedData trainData)
 => trainer.Train(new TrainContext(trainData));

 /// <summary>
 /// Convenience train extension for the case where one has only a training set with no auxiliary information.
 /// Equivalent to calling <see cref="ITrainer{TPredictor}.Train(TrainContext)"/>
 /// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
 /// </summary>
 /// <param name="trainer">The trainer</param>
 /// <param name="trainData">The training data.</param>
 /// <returns>The trained predictor</returns>
 public static TPredictor Train<TPredictor>(this ITrainer<TPredictor> trainer, RoleMappedData trainData) where TPredictor : IPredictor
 => trainer.Train(new TrainContext(trainData));
 }
 /// <summary>
 /// Convenience train extension for the case where one has only a training set with no auxiliary information.
 /// Equivalent to calling <see cref="ITrainer{TPredictor}.Train(TrainContext)"/>
 /// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
 /// </summary>
 /// <param name="trainer">The trainer</param>
 /// <param name="trainData">The training data.</param>
 /// <returns>The trained predictor</returns>
 public static TPredictor Train<TPredictor>(this ITrainer<TPredictor> trainer, RoleMappedData trainData) where TPredictor : IPredictor
 => trainer.Train(new TrainContext(trainData));
}
Loading

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})();
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try {
var __m = "youtube.com";
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michaelgsharp
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Sep 1, 2023
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File-scoped namespaces in files under Prediction (Microsoft.ML.Core)
#6792
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6ec9418

File-scoped namespaces in files under `Prediction` (`Microsoft.ML.Core`)

Aug 10, 2023
609936c

Merge branch 'dotnet:main' into improvement6


Lehonti Aug 26, 2023
547d22c

Merge branch 'dotnet:main' into improvement6


Lehonti Aug 31, 2023

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99 changes: 49 additions & 50 deletions
src/Microsoft.ML.Core/Prediction/IPredictor.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -2,62 +2,61 @@
// 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
namespace Microsoft.ML;

/// <summary>
/// Type of prediction task. Note that this is a legacy structure and usage of this should generally be
/// discouraged in future projects. Its presence suggests that there are privileged and supported
/// tasks, and anything outside of this is unsupported. This runs rather contrary to the idea of this
/// being an expandable framework, and it is inappropriately limiting. For legacy pipelines based on
/// <see cref="ITrainer"/> and <see cref="IPredictor"/> it is still useful, but for things based on
/// the <see cref="IEstimator{TTransformer}"/> idiom, it is inappropriate.
/// </summary>
[BestFriend]
internal enum PredictionKind
{
 /// <summary>
 /// Type of prediction task. Note that this is a legacy structure and usage of this should generally be
 /// discouraged in future projects. Its presence suggests that there are privileged and supported
 /// tasks, and anything outside of this is unsupported. This runs rather contrary to the idea of this
 /// being an expandable framework, and it is inappropriately limiting. For legacy pipelines based on
 /// <see cref="ITrainer"/> and <see cref="IPredictor"/> it is still useful, but for things based on
 /// the <see cref="IEstimator{TTransformer}"/> idiom, it is inappropriate.
 /// </summary>
 [BestFriend]
 internal enum PredictionKind
 {
 Unknown = 0,
 Custom = 1,
 Unknown = 0,
 Custom = 1,

BinaryClassification = 2,
MulticlassClassification = 3,
Regression = 4,
MultiOutputRegression = 5,
Ranking = 6,
Recommendation = 7,
AnomalyDetection = 8,
Clustering = 9,
SequenceClassification = 10,
 BinaryClassification = 2,
 MulticlassClassification = 3,
 Regression = 4,
 MultiOutputRegression = 5,
 Ranking = 6,
 Recommendation = 7,
 AnomalyDetection = 8,
 Clustering = 9,
 SequenceClassification = 10,

// More to be added later.
}
 // More to be added later.
}

/// <summary>
/// Weakly typed version of IPredictor.
/// </summary>
[BestFriend]
internal interface IPredictor
{
 /// <summary>
 /// Weakly typed version of IPredictor.
 /// Return the type of prediction task.
 /// </summary>
 [BestFriend]
 internal interface IPredictor
 {
 /// <summary>
 /// Return the type of prediction task.
 /// </summary>
 PredictionKind PredictionKind { get; }
 }
 PredictionKind PredictionKind { get; }
}

/// <summary>
/// A predictor the produces values of the indicated type.
/// REVIEW: Determine whether this is just a temporary shim or long term solution.
/// </summary>
[BestFriend]
internal interface IPredictorProducing<out TResult> : IPredictor
{
}
/// <summary>
/// A predictor the produces values of the indicated type.
/// REVIEW: Determine whether this is just a temporary shim or long term solution.
/// </summary>
[BestFriend]
internal interface IPredictorProducing<out TResult> : IPredictor
{
}

 /// <summary>
 /// A predictor that produces values and distributions of the indicated types.
 /// Note that from a public API perspective this is bad.
 /// </summary>
 [BestFriend]
 internal interface IDistPredictorProducing<out TResult, out TResultDistribution> : IPredictorProducing<TResult>
 {
 }
/// <summary>
/// A predictor that produces values and distributions of the indicated types.
/// Note that from a public API perspective this is bad.
/// </summary>
[BestFriend]
internal interface IDistPredictorProducing<out TResult, out TResultDistribution> : IPredictorProducing<TResult>
{
}

175 changes: 87 additions & 88 deletions
src/Microsoft.ML.Core/Prediction/ITrainer.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -4,104 +4,103 @@

using Microsoft.ML.Data;

namespace Microsoft.ML
{
 // REVIEW: Would be nice if the registration under SignatureTrainer were automatic
 // given registration for one of the "sub-class" signatures.
namespace Microsoft.ML;

 /// <summary>
 /// Loadable class signatures for trainers. Typically each trainer should register with
 /// both SignatureTrainer and SignatureXxxTrainer where Xxx is the prediction kind.
 /// </summary>
 [BestFriend]
 internal delegate void SignatureTrainer();
// REVIEW: Would be nice if the registration under SignatureTrainer were automatic
// given registration for one of the "sub-class" signatures.

 [BestFriend]
 internal delegate void SignatureBinaryClassifierTrainer();
 [BestFriend]
 internal delegate void SignatureMulticlassClassifierTrainer();
 [BestFriend]
 internal delegate void SignatureRegressorTrainer();
 [BestFriend]
 internal delegate void SignatureMultiOutputRegressorTrainer();
 [BestFriend]
 internal delegate void SignatureRankerTrainer();
 [BestFriend]
 internal delegate void SignatureAnomalyDetectorTrainer();
 [BestFriend]
 internal delegate void SignatureClusteringTrainer();
 [BestFriend]
 internal delegate void SignatureSequenceTrainer();
 [BestFriend]
 internal delegate void SignatureMatrixRecommendingTrainer();
/// <summary>
/// Loadable class signatures for trainers. Typically each trainer should register with
/// both SignatureTrainer and SignatureXxxTrainer where Xxx is the prediction kind.
/// </summary>
[BestFriend]
internal delegate void SignatureTrainer();

[BestFriend]
internal delegate void SignatureBinaryClassifierTrainer();
[BestFriend]
internal delegate void SignatureMulticlassClassifierTrainer();
[BestFriend]
internal delegate void SignatureRegressorTrainer();
[BestFriend]
internal delegate void SignatureMultiOutputRegressorTrainer();
[BestFriend]
internal delegate void SignatureRankerTrainer();
[BestFriend]
internal delegate void SignatureAnomalyDetectorTrainer();
[BestFriend]
internal delegate void SignatureClusteringTrainer();
[BestFriend]
internal delegate void SignatureSequenceTrainer();
[BestFriend]
internal delegate void SignatureMatrixRecommendingTrainer();

/// <summary>
/// The base interface for a trainers. Implementors should not implement this interface directly,
/// but rather implement the more specific <see cref="ITrainer{TPredictor}"/>.
/// </summary>
[BestFriend]
internal interface ITrainer
{
 /// <summary>
 /// The base interface for a trainers. Implementors should not implement this interface directly,
 /// but rather implement the more specific <see cref="ITrainer{TPredictor}"/>.
 /// Auxiliary information about the trainer in terms of its capabilities
 /// and requirements.
 /// </summary>
 [BestFriend]
 internal interface ITrainer
 {
 /// <summary>
 /// Auxiliary information about the trainer in terms of its capabilities
 /// and requirements.
 /// </summary>
 TrainerInfo Info { get; }
 TrainerInfo Info { get; }

/// <summary>
/// Return the type of prediction task for the produced predictor.
/// </summary>
PredictionKind PredictionKind { get; }
 /// <summary>
 /// Return the type of prediction task for the produced predictor.
 /// </summary>
 PredictionKind PredictionKind { get; }

/// <summary>
/// Trains a predictor.
/// </summary>
/// <param name="context">A context containing at least the training data</param>
/// <returns>The trained predictor</returns>
/// <seealso cref="ITrainer{TPredictor}.Train(TrainContext)"/>
IPredictor Train(TrainContext context);
}
 /// <summary>
 /// Trains a predictor.
 /// </summary>
 /// <param name="context">A context containing at least the training data</param>
 /// <returns>The trained predictor</returns>
 /// <seealso cref="ITrainer{TPredictor}.Train(TrainContext)"/>
 IPredictor Train(TrainContext context);
}

/// <summary>
/// Strongly typed generic interface for a trainer. A trainer object takes training data
/// and produces a predictor.
/// </summary>
/// <typeparam name="TPredictor"> Type of predictor produced</typeparam>
[BestFriend]
internal interface ITrainer<out TPredictor> : ITrainer
 where TPredictor : IPredictor
{
 /// <summary>
 /// Strongly typed generic interface for a trainer. A trainer object takes training data
 /// and produces a predictor.
 /// Trains a predictor.
 /// </summary>
 /// <typeparam name="TPredictor"> Type of predictor produced</typeparam>
 [BestFriend]
 internal interface ITrainer<out TPredictor> : ITrainer
 where TPredictor : IPredictor
 {
 /// <summary>
 /// Trains a predictor.
 /// </summary>
 /// <param name="context">A context containing at least the training data</param>
 /// <returns>The trained predictor</returns>
 new TPredictor Train(TrainContext context);
 }
 /// <param name="context">A context containing at least the training data</param>
 /// <returns>The trained predictor</returns>
 new TPredictor Train(TrainContext context);
}

[BestFriend]
internal static class TrainerExtensions
{
/// <summary>
/// Convenience train extension for the case where one has only a training set with no auxiliary information.
/// Equivalent to calling <see cref="ITrainer.Train(TrainContext)"/>
/// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
/// </summary>
/// <param name="trainer">The trainer</param>
/// <param name="trainData">The training data.</param>
/// <returns>The trained predictor</returns>
public static IPredictor Train(this ITrainer trainer, RoleMappedData trainData)
=> trainer.Train(new TrainContext(trainData));
[BestFriend]
internal static class TrainerExtensions
{
 /// <summary>
 /// Convenience train extension for the case where one has only a training set with no auxiliary information.
 /// Equivalent to calling <see cref="ITrainer.Train(TrainContext)"/>
 /// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
 /// </summary>
 /// <param name="trainer">The trainer</param>
 /// <param name="trainData">The training data.</param>
 /// <returns>The trained predictor</returns>
 public static IPredictor Train(this ITrainer trainer, RoleMappedData trainData)
 => trainer.Train(new TrainContext(trainData));

 /// <summary>
 /// Convenience train extension for the case where one has only a training set with no auxiliary information.
 /// Equivalent to calling <see cref="ITrainer{TPredictor}.Train(TrainContext)"/>
 /// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
 /// </summary>
 /// <param name="trainer">The trainer</param>
 /// <param name="trainData">The training data.</param>
 /// <returns>The trained predictor</returns>
 public static TPredictor Train<TPredictor>(this ITrainer<TPredictor> trainer, RoleMappedData trainData) where TPredictor : IPredictor
 => trainer.Train(new TrainContext(trainData));
 }
 /// <summary>
 /// Convenience train extension for the case where one has only a training set with no auxiliary information.
 /// Equivalent to calling <see cref="ITrainer{TPredictor}.Train(TrainContext)"/>
 /// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
 /// </summary>
 /// <param name="trainer">The trainer</param>
 /// <param name="trainData">The training data.</param>
 /// <returns>The trained predictor</returns>
 public static TPredictor Train<TPredictor>(this ITrainer<TPredictor> trainer, RoleMappedData trainData) where TPredictor : IPredictor
 => trainer.Train(new TrainContext(trainData));
}
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injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
File-scoped namespaces in files under Prediction (Microsoft.ML.Core)#6792

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 Merged

michaelgsharp
merged 3 commits into

from

Sep 1, 2023
 Merged


File-scoped namespaces in files under Prediction (Microsoft.ML.Core)
#6792
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6ec9418

File-scoped namespaces in files under `Prediction` (`Microsoft.ML.Core`)

Aug 10, 2023
609936c

Merge branch 'dotnet:main' into improvement6


Lehonti Aug 26, 2023
547d22c

Merge branch 'dotnet:main' into improvement6


Lehonti Aug 31, 2023

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99 changes: 49 additions & 50 deletions
src/Microsoft.ML.Core/Prediction/IPredictor.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -2,62 +2,61 @@
// 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
namespace Microsoft.ML;

/// <summary>
/// Type of prediction task. Note that this is a legacy structure and usage of this should generally be
/// discouraged in future projects. Its presence suggests that there are privileged and supported
/// tasks, and anything outside of this is unsupported. This runs rather contrary to the idea of this
/// being an expandable framework, and it is inappropriately limiting. For legacy pipelines based on
/// <see cref="ITrainer"/> and <see cref="IPredictor"/> it is still useful, but for things based on
/// the <see cref="IEstimator{TTransformer}"/> idiom, it is inappropriate.
/// </summary>
[BestFriend]
internal enum PredictionKind
{
 /// <summary>
 /// Type of prediction task. Note that this is a legacy structure and usage of this should generally be
 /// discouraged in future projects. Its presence suggests that there are privileged and supported
 /// tasks, and anything outside of this is unsupported. This runs rather contrary to the idea of this
 /// being an expandable framework, and it is inappropriately limiting. For legacy pipelines based on
 /// <see cref="ITrainer"/> and <see cref="IPredictor"/> it is still useful, but for things based on
 /// the <see cref="IEstimator{TTransformer}"/> idiom, it is inappropriate.
 /// </summary>
 [BestFriend]
 internal enum PredictionKind
 {
 Unknown = 0,
 Custom = 1,
 Unknown = 0,
 Custom = 1,

BinaryClassification = 2,
MulticlassClassification = 3,
Regression = 4,
MultiOutputRegression = 5,
Ranking = 6,
Recommendation = 7,
AnomalyDetection = 8,
Clustering = 9,
SequenceClassification = 10,
 BinaryClassification = 2,
 MulticlassClassification = 3,
 Regression = 4,
 MultiOutputRegression = 5,
 Ranking = 6,
 Recommendation = 7,
 AnomalyDetection = 8,
 Clustering = 9,
 SequenceClassification = 10,

// More to be added later.
}
 // More to be added later.
}

/// <summary>
/// Weakly typed version of IPredictor.
/// </summary>
[BestFriend]
internal interface IPredictor
{
 /// <summary>
 /// Weakly typed version of IPredictor.
 /// Return the type of prediction task.
 /// </summary>
 [BestFriend]
 internal interface IPredictor
 {
 /// <summary>
 /// Return the type of prediction task.
 /// </summary>
 PredictionKind PredictionKind { get; }
 }
 PredictionKind PredictionKind { get; }
}

/// <summary>
/// A predictor the produces values of the indicated type.
/// REVIEW: Determine whether this is just a temporary shim or long term solution.
/// </summary>
[BestFriend]
internal interface IPredictorProducing<out TResult> : IPredictor
{
}
/// <summary>
/// A predictor the produces values of the indicated type.
/// REVIEW: Determine whether this is just a temporary shim or long term solution.
/// </summary>
[BestFriend]
internal interface IPredictorProducing<out TResult> : IPredictor
{
}

 /// <summary>
 /// A predictor that produces values and distributions of the indicated types.
 /// Note that from a public API perspective this is bad.
 /// </summary>
 [BestFriend]
 internal interface IDistPredictorProducing<out TResult, out TResultDistribution> : IPredictorProducing<TResult>
 {
 }
/// <summary>
/// A predictor that produces values and distributions of the indicated types.
/// Note that from a public API perspective this is bad.
/// </summary>
[BestFriend]
internal interface IDistPredictorProducing<out TResult, out TResultDistribution> : IPredictorProducing<TResult>
{
}

175 changes: 87 additions & 88 deletions
src/Microsoft.ML.Core/Prediction/ITrainer.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -4,104 +4,103 @@

using Microsoft.ML.Data;

namespace Microsoft.ML
{
 // REVIEW: Would be nice if the registration under SignatureTrainer were automatic
 // given registration for one of the "sub-class" signatures.
namespace Microsoft.ML;

 /// <summary>
 /// Loadable class signatures for trainers. Typically each trainer should register with
 /// both SignatureTrainer and SignatureXxxTrainer where Xxx is the prediction kind.
 /// </summary>
 [BestFriend]
 internal delegate void SignatureTrainer();
// REVIEW: Would be nice if the registration under SignatureTrainer were automatic
// given registration for one of the "sub-class" signatures.

 [BestFriend]
 internal delegate void SignatureBinaryClassifierTrainer();
 [BestFriend]
 internal delegate void SignatureMulticlassClassifierTrainer();
 [BestFriend]
 internal delegate void SignatureRegressorTrainer();
 [BestFriend]
 internal delegate void SignatureMultiOutputRegressorTrainer();
 [BestFriend]
 internal delegate void SignatureRankerTrainer();
 [BestFriend]
 internal delegate void SignatureAnomalyDetectorTrainer();
 [BestFriend]
 internal delegate void SignatureClusteringTrainer();
 [BestFriend]
 internal delegate void SignatureSequenceTrainer();
 [BestFriend]
 internal delegate void SignatureMatrixRecommendingTrainer();
/// <summary>
/// Loadable class signatures for trainers. Typically each trainer should register with
/// both SignatureTrainer and SignatureXxxTrainer where Xxx is the prediction kind.
/// </summary>
[BestFriend]
internal delegate void SignatureTrainer();

[BestFriend]
internal delegate void SignatureBinaryClassifierTrainer();
[BestFriend]
internal delegate void SignatureMulticlassClassifierTrainer();
[BestFriend]
internal delegate void SignatureRegressorTrainer();
[BestFriend]
internal delegate void SignatureMultiOutputRegressorTrainer();
[BestFriend]
internal delegate void SignatureRankerTrainer();
[BestFriend]
internal delegate void SignatureAnomalyDetectorTrainer();
[BestFriend]
internal delegate void SignatureClusteringTrainer();
[BestFriend]
internal delegate void SignatureSequenceTrainer();
[BestFriend]
internal delegate void SignatureMatrixRecommendingTrainer();

/// <summary>
/// The base interface for a trainers. Implementors should not implement this interface directly,
/// but rather implement the more specific <see cref="ITrainer{TPredictor}"/>.
/// </summary>
[BestFriend]
internal interface ITrainer
{
 /// <summary>
 /// The base interface for a trainers. Implementors should not implement this interface directly,
 /// but rather implement the more specific <see cref="ITrainer{TPredictor}"/>.
 /// Auxiliary information about the trainer in terms of its capabilities
 /// and requirements.
 /// </summary>
 [BestFriend]
 internal interface ITrainer
 {
 /// <summary>
 /// Auxiliary information about the trainer in terms of its capabilities
 /// and requirements.
 /// </summary>
 TrainerInfo Info { get; }
 TrainerInfo Info { get; }

/// <summary>
/// Return the type of prediction task for the produced predictor.
/// </summary>
PredictionKind PredictionKind { get; }
 /// <summary>
 /// Return the type of prediction task for the produced predictor.
 /// </summary>
 PredictionKind PredictionKind { get; }

/// <summary>
/// Trains a predictor.
/// </summary>
/// <param name="context">A context containing at least the training data</param>
/// <returns>The trained predictor</returns>
/// <seealso cref="ITrainer{TPredictor}.Train(TrainContext)"/>
IPredictor Train(TrainContext context);
}
 /// <summary>
 /// Trains a predictor.
 /// </summary>
 /// <param name="context">A context containing at least the training data</param>
 /// <returns>The trained predictor</returns>
 /// <seealso cref="ITrainer{TPredictor}.Train(TrainContext)"/>
 IPredictor Train(TrainContext context);
}

/// <summary>
/// Strongly typed generic interface for a trainer. A trainer object takes training data
/// and produces a predictor.
/// </summary>
/// <typeparam name="TPredictor"> Type of predictor produced</typeparam>
[BestFriend]
internal interface ITrainer<out TPredictor> : ITrainer
 where TPredictor : IPredictor
{
 /// <summary>
 /// Strongly typed generic interface for a trainer. A trainer object takes training data
 /// and produces a predictor.
 /// Trains a predictor.
 /// </summary>
 /// <typeparam name="TPredictor"> Type of predictor produced</typeparam>
 [BestFriend]
 internal interface ITrainer<out TPredictor> : ITrainer
 where TPredictor : IPredictor
 {
 /// <summary>
 /// Trains a predictor.
 /// </summary>
 /// <param name="context">A context containing at least the training data</param>
 /// <returns>The trained predictor</returns>
 new TPredictor Train(TrainContext context);
 }
 /// <param name="context">A context containing at least the training data</param>
 /// <returns>The trained predictor</returns>
 new TPredictor Train(TrainContext context);
}

[BestFriend]
internal static class TrainerExtensions
{
/// <summary>
/// Convenience train extension for the case where one has only a training set with no auxiliary information.
/// Equivalent to calling <see cref="ITrainer.Train(TrainContext)"/>
/// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
/// </summary>
/// <param name="trainer">The trainer</param>
/// <param name="trainData">The training data.</param>
/// <returns>The trained predictor</returns>
public static IPredictor Train(this ITrainer trainer, RoleMappedData trainData)
=> trainer.Train(new TrainContext(trainData));
[BestFriend]
internal static class TrainerExtensions
{
 /// <summary>
 /// Convenience train extension for the case where one has only a training set with no auxiliary information.
 /// Equivalent to calling <see cref="ITrainer.Train(TrainContext)"/>
 /// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
 /// </summary>
 /// <param name="trainer">The trainer</param>
 /// <param name="trainData">The training data.</param>
 /// <returns>The trained predictor</returns>
 public static IPredictor Train(this ITrainer trainer, RoleMappedData trainData)
 => trainer.Train(new TrainContext(trainData));

 /// <summary>
 /// Convenience train extension for the case where one has only a training set with no auxiliary information.
 /// Equivalent to calling <see cref="ITrainer{TPredictor}.Train(TrainContext)"/>
 /// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
 /// </summary>
 /// <param name="trainer">The trainer</param>
 /// <param name="trainData">The training data.</param>
 /// <returns>The trained predictor</returns>
 public static TPredictor Train<TPredictor>(this ITrainer<TPredictor> trainer, RoleMappedData trainData) where TPredictor : IPredictor
 => trainer.Train(new TrainContext(trainData));
 }
 /// <summary>
 /// Convenience train extension for the case where one has only a training set with no auxiliary information.
 /// Equivalent to calling <see cref="ITrainer{TPredictor}.Train(TrainContext)"/>
 /// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
 /// </summary>
 /// <param name="trainer">The trainer</param>
 /// <param name="trainData">The training data.</param>
 /// <returns>The trained predictor</returns>
 public static TPredictor Train<TPredictor>(this ITrainer<TPredictor> trainer, RoleMappedData trainData) where TPredictor : IPredictor
 => trainer.Train(new TrainContext(trainData));
}
Loading

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
File-scoped namespaces in files under Prediction (Microsoft.ML.Core)#6792

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privacy statement. We’ll occasionally send you account related emails.

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 Merged

michaelgsharp
merged 3 commits into

from

Sep 1, 2023
 Merged


File-scoped namespaces in files under Prediction (Microsoft.ML.Core)
#6792
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6ec9418

File-scoped namespaces in files under `Prediction` (`Microsoft.ML.Core`)

Aug 10, 2023
609936c

Merge branch 'dotnet:main' into improvement6


Lehonti Aug 26, 2023
547d22c

Merge branch 'dotnet:main' into improvement6


Lehonti Aug 31, 2023

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99 changes: 49 additions & 50 deletions
src/Microsoft.ML.Core/Prediction/IPredictor.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -2,62 +2,61 @@
// 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
namespace Microsoft.ML;

/// <summary>
/// Type of prediction task. Note that this is a legacy structure and usage of this should generally be
/// discouraged in future projects. Its presence suggests that there are privileged and supported
/// tasks, and anything outside of this is unsupported. This runs rather contrary to the idea of this
/// being an expandable framework, and it is inappropriately limiting. For legacy pipelines based on
/// <see cref="ITrainer"/> and <see cref="IPredictor"/> it is still useful, but for things based on
/// the <see cref="IEstimator{TTransformer}"/> idiom, it is inappropriate.
/// </summary>
[BestFriend]
internal enum PredictionKind
{
 /// <summary>
 /// Type of prediction task. Note that this is a legacy structure and usage of this should generally be
 /// discouraged in future projects. Its presence suggests that there are privileged and supported
 /// tasks, and anything outside of this is unsupported. This runs rather contrary to the idea of this
 /// being an expandable framework, and it is inappropriately limiting. For legacy pipelines based on
 /// <see cref="ITrainer"/> and <see cref="IPredictor"/> it is still useful, but for things based on
 /// the <see cref="IEstimator{TTransformer}"/> idiom, it is inappropriate.
 /// </summary>
 [BestFriend]
 internal enum PredictionKind
 {
 Unknown = 0,
 Custom = 1,
 Unknown = 0,
 Custom = 1,

BinaryClassification = 2,
MulticlassClassification = 3,
Regression = 4,
MultiOutputRegression = 5,
Ranking = 6,
Recommendation = 7,
AnomalyDetection = 8,
Clustering = 9,
SequenceClassification = 10,
 BinaryClassification = 2,
 MulticlassClassification = 3,
 Regression = 4,
 MultiOutputRegression = 5,
 Ranking = 6,
 Recommendation = 7,
 AnomalyDetection = 8,
 Clustering = 9,
 SequenceClassification = 10,

// More to be added later.
}
 // More to be added later.
}

/// <summary>
/// Weakly typed version of IPredictor.
/// </summary>
[BestFriend]
internal interface IPredictor
{
 /// <summary>
 /// Weakly typed version of IPredictor.
 /// Return the type of prediction task.
 /// </summary>
 [BestFriend]
 internal interface IPredictor
 {
 /// <summary>
 /// Return the type of prediction task.
 /// </summary>
 PredictionKind PredictionKind { get; }
 }
 PredictionKind PredictionKind { get; }
}

/// <summary>
/// A predictor the produces values of the indicated type.
/// REVIEW: Determine whether this is just a temporary shim or long term solution.
/// </summary>
[BestFriend]
internal interface IPredictorProducing<out TResult> : IPredictor
{
}
/// <summary>
/// A predictor the produces values of the indicated type.
/// REVIEW: Determine whether this is just a temporary shim or long term solution.
/// </summary>
[BestFriend]
internal interface IPredictorProducing<out TResult> : IPredictor
{
}

 /// <summary>
 /// A predictor that produces values and distributions of the indicated types.
 /// Note that from a public API perspective this is bad.
 /// </summary>
 [BestFriend]
 internal interface IDistPredictorProducing<out TResult, out TResultDistribution> : IPredictorProducing<TResult>
 {
 }
/// <summary>
/// A predictor that produces values and distributions of the indicated types.
/// Note that from a public API perspective this is bad.
/// </summary>
[BestFriend]
internal interface IDistPredictorProducing<out TResult, out TResultDistribution> : IPredictorProducing<TResult>
{
}

175 changes: 87 additions & 88 deletions
src/Microsoft.ML.Core/Prediction/ITrainer.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -4,104 +4,103 @@

using Microsoft.ML.Data;

namespace Microsoft.ML
{
 // REVIEW: Would be nice if the registration under SignatureTrainer were automatic
 // given registration for one of the "sub-class" signatures.
namespace Microsoft.ML;

 /// <summary>
 /// Loadable class signatures for trainers. Typically each trainer should register with
 /// both SignatureTrainer and SignatureXxxTrainer where Xxx is the prediction kind.
 /// </summary>
 [BestFriend]
 internal delegate void SignatureTrainer();
// REVIEW: Would be nice if the registration under SignatureTrainer were automatic
// given registration for one of the "sub-class" signatures.

 [BestFriend]
 internal delegate void SignatureBinaryClassifierTrainer();
 [BestFriend]
 internal delegate void SignatureMulticlassClassifierTrainer();
 [BestFriend]
 internal delegate void SignatureRegressorTrainer();
 [BestFriend]
 internal delegate void SignatureMultiOutputRegressorTrainer();
 [BestFriend]
 internal delegate void SignatureRankerTrainer();
 [BestFriend]
 internal delegate void SignatureAnomalyDetectorTrainer();
 [BestFriend]
 internal delegate void SignatureClusteringTrainer();
 [BestFriend]
 internal delegate void SignatureSequenceTrainer();
 [BestFriend]
 internal delegate void SignatureMatrixRecommendingTrainer();
/// <summary>
/// Loadable class signatures for trainers. Typically each trainer should register with
/// both SignatureTrainer and SignatureXxxTrainer where Xxx is the prediction kind.
/// </summary>
[BestFriend]
internal delegate void SignatureTrainer();

[BestFriend]
internal delegate void SignatureBinaryClassifierTrainer();
[BestFriend]
internal delegate void SignatureMulticlassClassifierTrainer();
[BestFriend]
internal delegate void SignatureRegressorTrainer();
[BestFriend]
internal delegate void SignatureMultiOutputRegressorTrainer();
[BestFriend]
internal delegate void SignatureRankerTrainer();
[BestFriend]
internal delegate void SignatureAnomalyDetectorTrainer();
[BestFriend]
internal delegate void SignatureClusteringTrainer();
[BestFriend]
internal delegate void SignatureSequenceTrainer();
[BestFriend]
internal delegate void SignatureMatrixRecommendingTrainer();

/// <summary>
/// The base interface for a trainers. Implementors should not implement this interface directly,
/// but rather implement the more specific <see cref="ITrainer{TPredictor}"/>.
/// </summary>
[BestFriend]
internal interface ITrainer
{
 /// <summary>
 /// The base interface for a trainers. Implementors should not implement this interface directly,
 /// but rather implement the more specific <see cref="ITrainer{TPredictor}"/>.
 /// Auxiliary information about the trainer in terms of its capabilities
 /// and requirements.
 /// </summary>
 [BestFriend]
 internal interface ITrainer
 {
 /// <summary>
 /// Auxiliary information about the trainer in terms of its capabilities
 /// and requirements.
 /// </summary>
 TrainerInfo Info { get; }
 TrainerInfo Info { get; }

/// <summary>
/// Return the type of prediction task for the produced predictor.
/// </summary>
PredictionKind PredictionKind { get; }
 /// <summary>
 /// Return the type of prediction task for the produced predictor.
 /// </summary>
 PredictionKind PredictionKind { get; }

/// <summary>
/// Trains a predictor.
/// </summary>
/// <param name="context">A context containing at least the training data</param>
/// <returns>The trained predictor</returns>
/// <seealso cref="ITrainer{TPredictor}.Train(TrainContext)"/>
IPredictor Train(TrainContext context);
}
 /// <summary>
 /// Trains a predictor.
 /// </summary>
 /// <param name="context">A context containing at least the training data</param>
 /// <returns>The trained predictor</returns>
 /// <seealso cref="ITrainer{TPredictor}.Train(TrainContext)"/>
 IPredictor Train(TrainContext context);
}

/// <summary>
/// Strongly typed generic interface for a trainer. A trainer object takes training data
/// and produces a predictor.
/// </summary>
/// <typeparam name="TPredictor"> Type of predictor produced</typeparam>
[BestFriend]
internal interface ITrainer<out TPredictor> : ITrainer
 where TPredictor : IPredictor
{
 /// <summary>
 /// Strongly typed generic interface for a trainer. A trainer object takes training data
 /// and produces a predictor.
 /// Trains a predictor.
 /// </summary>
 /// <typeparam name="TPredictor"> Type of predictor produced</typeparam>
 [BestFriend]
 internal interface ITrainer<out TPredictor> : ITrainer
 where TPredictor : IPredictor
 {
 /// <summary>
 /// Trains a predictor.
 /// </summary>
 /// <param name="context">A context containing at least the training data</param>
 /// <returns>The trained predictor</returns>
 new TPredictor Train(TrainContext context);
 }
 /// <param name="context">A context containing at least the training data</param>
 /// <returns>The trained predictor</returns>
 new TPredictor Train(TrainContext context);
}

[BestFriend]
internal static class TrainerExtensions
{
/// <summary>
/// Convenience train extension for the case where one has only a training set with no auxiliary information.
/// Equivalent to calling <see cref="ITrainer.Train(TrainContext)"/>
/// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
/// </summary>
/// <param name="trainer">The trainer</param>
/// <param name="trainData">The training data.</param>
/// <returns>The trained predictor</returns>
public static IPredictor Train(this ITrainer trainer, RoleMappedData trainData)
=> trainer.Train(new TrainContext(trainData));
[BestFriend]
internal static class TrainerExtensions
{
 /// <summary>
 /// Convenience train extension for the case where one has only a training set with no auxiliary information.
 /// Equivalent to calling <see cref="ITrainer.Train(TrainContext)"/>
 /// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
 /// </summary>
 /// <param name="trainer">The trainer</param>
 /// <param name="trainData">The training data.</param>
 /// <returns>The trained predictor</returns>
 public static IPredictor Train(this ITrainer trainer, RoleMappedData trainData)
 => trainer.Train(new TrainContext(trainData));

 /// <summary>
 /// Convenience train extension for the case where one has only a training set with no auxiliary information.
 /// Equivalent to calling <see cref="ITrainer{TPredictor}.Train(TrainContext)"/>
 /// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
 /// </summary>
 /// <param name="trainer">The trainer</param>
 /// <param name="trainData">The training data.</param>
 /// <returns>The trained predictor</returns>
 public static TPredictor Train<TPredictor>(this ITrainer<TPredictor> trainer, RoleMappedData trainData) where TPredictor : IPredictor
 => trainer.Train(new TrainContext(trainData));
 }
 /// <summary>
 /// Convenience train extension for the case where one has only a training set with no auxiliary information.
 /// Equivalent to calling <see cref="ITrainer{TPredictor}.Train(TrainContext)"/>
 /// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
 /// </summary>
 /// <param name="trainer">The trainer</param>
 /// <param name="trainData">The training data.</param>
 /// <returns>The trained predictor</returns>
 public static TPredictor Train<TPredictor>(this ITrainer<TPredictor> trainer, RoleMappedData trainData) where TPredictor : IPredictor
 => trainer.Train(new TrainContext(trainData));
}
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} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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 Merged

michaelgsharp
merged 3 commits into

from

Sep 1, 2023
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File-scoped namespaces in files under Prediction (Microsoft.ML.Core)
#6792
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6ec9418

File-scoped namespaces in files under `Prediction` (`Microsoft.ML.Core`)

Aug 10, 2023
609936c

Merge branch 'dotnet:main' into improvement6


Lehonti Aug 26, 2023
547d22c

Merge branch 'dotnet:main' into improvement6


Lehonti Aug 31, 2023

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99 changes: 49 additions & 50 deletions
src/Microsoft.ML.Core/Prediction/IPredictor.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -2,62 +2,61 @@
// 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
namespace Microsoft.ML;

/// <summary>
/// Type of prediction task. Note that this is a legacy structure and usage of this should generally be
/// discouraged in future projects. Its presence suggests that there are privileged and supported
/// tasks, and anything outside of this is unsupported. This runs rather contrary to the idea of this
/// being an expandable framework, and it is inappropriately limiting. For legacy pipelines based on
/// <see cref="ITrainer"/> and <see cref="IPredictor"/> it is still useful, but for things based on
/// the <see cref="IEstimator{TTransformer}"/> idiom, it is inappropriate.
/// </summary>
[BestFriend]
internal enum PredictionKind
{
 /// <summary>
 /// Type of prediction task. Note that this is a legacy structure and usage of this should generally be
 /// discouraged in future projects. Its presence suggests that there are privileged and supported
 /// tasks, and anything outside of this is unsupported. This runs rather contrary to the idea of this
 /// being an expandable framework, and it is inappropriately limiting. For legacy pipelines based on
 /// <see cref="ITrainer"/> and <see cref="IPredictor"/> it is still useful, but for things based on
 /// the <see cref="IEstimator{TTransformer}"/> idiom, it is inappropriate.
 /// </summary>
 [BestFriend]
 internal enum PredictionKind
 {
 Unknown = 0,
 Custom = 1,
 Unknown = 0,
 Custom = 1,

BinaryClassification = 2,
MulticlassClassification = 3,
Regression = 4,
MultiOutputRegression = 5,
Ranking = 6,
Recommendation = 7,
AnomalyDetection = 8,
Clustering = 9,
SequenceClassification = 10,
 BinaryClassification = 2,
 MulticlassClassification = 3,
 Regression = 4,
 MultiOutputRegression = 5,
 Ranking = 6,
 Recommendation = 7,
 AnomalyDetection = 8,
 Clustering = 9,
 SequenceClassification = 10,

// More to be added later.
}
 // More to be added later.
}

/// <summary>
/// Weakly typed version of IPredictor.
/// </summary>
[BestFriend]
internal interface IPredictor
{
 /// <summary>
 /// Weakly typed version of IPredictor.
 /// Return the type of prediction task.
 /// </summary>
 [BestFriend]
 internal interface IPredictor
 {
 /// <summary>
 /// Return the type of prediction task.
 /// </summary>
 PredictionKind PredictionKind { get; }
 }
 PredictionKind PredictionKind { get; }
}

/// <summary>
/// A predictor the produces values of the indicated type.
/// REVIEW: Determine whether this is just a temporary shim or long term solution.
/// </summary>
[BestFriend]
internal interface IPredictorProducing<out TResult> : IPredictor
{
}
/// <summary>
/// A predictor the produces values of the indicated type.
/// REVIEW: Determine whether this is just a temporary shim or long term solution.
/// </summary>
[BestFriend]
internal interface IPredictorProducing<out TResult> : IPredictor
{
}

 /// <summary>
 /// A predictor that produces values and distributions of the indicated types.
 /// Note that from a public API perspective this is bad.
 /// </summary>
 [BestFriend]
 internal interface IDistPredictorProducing<out TResult, out TResultDistribution> : IPredictorProducing<TResult>
 {
 }
/// <summary>
/// A predictor that produces values and distributions of the indicated types.
/// Note that from a public API perspective this is bad.
/// </summary>
[BestFriend]
internal interface IDistPredictorProducing<out TResult, out TResultDistribution> : IPredictorProducing<TResult>
{
}

175 changes: 87 additions & 88 deletions
src/Microsoft.ML.Core/Prediction/ITrainer.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -4,104 +4,103 @@

using Microsoft.ML.Data;

namespace Microsoft.ML
{
 // REVIEW: Would be nice if the registration under SignatureTrainer were automatic
 // given registration for one of the "sub-class" signatures.
namespace Microsoft.ML;

 /// <summary>
 /// Loadable class signatures for trainers. Typically each trainer should register with
 /// both SignatureTrainer and SignatureXxxTrainer where Xxx is the prediction kind.
 /// </summary>
 [BestFriend]
 internal delegate void SignatureTrainer();
// REVIEW: Would be nice if the registration under SignatureTrainer were automatic
// given registration for one of the "sub-class" signatures.

 [BestFriend]
 internal delegate void SignatureBinaryClassifierTrainer();
 [BestFriend]
 internal delegate void SignatureMulticlassClassifierTrainer();
 [BestFriend]
 internal delegate void SignatureRegressorTrainer();
 [BestFriend]
 internal delegate void SignatureMultiOutputRegressorTrainer();
 [BestFriend]
 internal delegate void SignatureRankerTrainer();
 [BestFriend]
 internal delegate void SignatureAnomalyDetectorTrainer();
 [BestFriend]
 internal delegate void SignatureClusteringTrainer();
 [BestFriend]
 internal delegate void SignatureSequenceTrainer();
 [BestFriend]
 internal delegate void SignatureMatrixRecommendingTrainer();
/// <summary>
/// Loadable class signatures for trainers. Typically each trainer should register with
/// both SignatureTrainer and SignatureXxxTrainer where Xxx is the prediction kind.
/// </summary>
[BestFriend]
internal delegate void SignatureTrainer();

[BestFriend]
internal delegate void SignatureBinaryClassifierTrainer();
[BestFriend]
internal delegate void SignatureMulticlassClassifierTrainer();
[BestFriend]
internal delegate void SignatureRegressorTrainer();
[BestFriend]
internal delegate void SignatureMultiOutputRegressorTrainer();
[BestFriend]
internal delegate void SignatureRankerTrainer();
[BestFriend]
internal delegate void SignatureAnomalyDetectorTrainer();
[BestFriend]
internal delegate void SignatureClusteringTrainer();
[BestFriend]
internal delegate void SignatureSequenceTrainer();
[BestFriend]
internal delegate void SignatureMatrixRecommendingTrainer();

/// <summary>
/// The base interface for a trainers. Implementors should not implement this interface directly,
/// but rather implement the more specific <see cref="ITrainer{TPredictor}"/>.
/// </summary>
[BestFriend]
internal interface ITrainer
{
 /// <summary>
 /// The base interface for a trainers. Implementors should not implement this interface directly,
 /// but rather implement the more specific <see cref="ITrainer{TPredictor}"/>.
 /// Auxiliary information about the trainer in terms of its capabilities
 /// and requirements.
 /// </summary>
 [BestFriend]
 internal interface ITrainer
 {
 /// <summary>
 /// Auxiliary information about the trainer in terms of its capabilities
 /// and requirements.
 /// </summary>
 TrainerInfo Info { get; }
 TrainerInfo Info { get; }

/// <summary>
/// Return the type of prediction task for the produced predictor.
/// </summary>
PredictionKind PredictionKind { get; }
 /// <summary>
 /// Return the type of prediction task for the produced predictor.
 /// </summary>
 PredictionKind PredictionKind { get; }

/// <summary>
/// Trains a predictor.
/// </summary>
/// <param name="context">A context containing at least the training data</param>
/// <returns>The trained predictor</returns>
/// <seealso cref="ITrainer{TPredictor}.Train(TrainContext)"/>
IPredictor Train(TrainContext context);
}
 /// <summary>
 /// Trains a predictor.
 /// </summary>
 /// <param name="context">A context containing at least the training data</param>
 /// <returns>The trained predictor</returns>
 /// <seealso cref="ITrainer{TPredictor}.Train(TrainContext)"/>
 IPredictor Train(TrainContext context);
}

/// <summary>
/// Strongly typed generic interface for a trainer. A trainer object takes training data
/// and produces a predictor.
/// </summary>
/// <typeparam name="TPredictor"> Type of predictor produced</typeparam>
[BestFriend]
internal interface ITrainer<out TPredictor> : ITrainer
 where TPredictor : IPredictor
{
 /// <summary>
 /// Strongly typed generic interface for a trainer. A trainer object takes training data
 /// and produces a predictor.
 /// Trains a predictor.
 /// </summary>
 /// <typeparam name="TPredictor"> Type of predictor produced</typeparam>
 [BestFriend]
 internal interface ITrainer<out TPredictor> : ITrainer
 where TPredictor : IPredictor
 {
 /// <summary>
 /// Trains a predictor.
 /// </summary>
 /// <param name="context">A context containing at least the training data</param>
 /// <returns>The trained predictor</returns>
 new TPredictor Train(TrainContext context);
 }
 /// <param name="context">A context containing at least the training data</param>
 /// <returns>The trained predictor</returns>
 new TPredictor Train(TrainContext context);
}

[BestFriend]
internal static class TrainerExtensions
{
/// <summary>
/// Convenience train extension for the case where one has only a training set with no auxiliary information.
/// Equivalent to calling <see cref="ITrainer.Train(TrainContext)"/>
/// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
/// </summary>
/// <param name="trainer">The trainer</param>
/// <param name="trainData">The training data.</param>
/// <returns>The trained predictor</returns>
public static IPredictor Train(this ITrainer trainer, RoleMappedData trainData)
=> trainer.Train(new TrainContext(trainData));
[BestFriend]
internal static class TrainerExtensions
{
 /// <summary>
 /// Convenience train extension for the case where one has only a training set with no auxiliary information.
 /// Equivalent to calling <see cref="ITrainer.Train(TrainContext)"/>
 /// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
 /// </summary>
 /// <param name="trainer">The trainer</param>
 /// <param name="trainData">The training data.</param>
 /// <returns>The trained predictor</returns>
 public static IPredictor Train(this ITrainer trainer, RoleMappedData trainData)
 => trainer.Train(new TrainContext(trainData));

 /// <summary>
 /// Convenience train extension for the case where one has only a training set with no auxiliary information.
 /// Equivalent to calling <see cref="ITrainer{TPredictor}.Train(TrainContext)"/>
 /// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
 /// </summary>
 /// <param name="trainer">The trainer</param>
 /// <param name="trainData">The training data.</param>
 /// <returns>The trained predictor</returns>
 public static TPredictor Train<TPredictor>(this ITrainer<TPredictor> trainer, RoleMappedData trainData) where TPredictor : IPredictor
 => trainer.Train(new TrainContext(trainData));
 }
 /// <summary>
 /// Convenience train extension for the case where one has only a training set with no auxiliary information.
 /// Equivalent to calling <see cref="ITrainer{TPredictor}.Train(TrainContext)"/>
 /// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
 /// </summary>
 /// <param name="trainer">The trainer</param>
 /// <param name="trainData">The training data.</param>
 /// <returns>The trained predictor</returns>
 public static TPredictor Train<TPredictor>(this ITrainer<TPredictor> trainer, RoleMappedData trainData) where TPredictor : IPredictor
 => trainer.Train(new TrainContext(trainData));
}
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