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LehontiLehonti Ramos
Lehonti
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Lehonti Ramos
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File-scoped namespaces in files under Prediction (Microsoft.ML.Core) (#6792)
Co-authored-by: Lehonti Ramos <john@doe>
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‎src/Microsoft.ML.Core/Prediction/IPredictor.cs‎

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Original file line numberDiff line numberDiff line change
@@ -2,62 +2,61 @@
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// The .NET Foundation licenses this file to you under the MIT license.
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// See the LICENSE file in the project root for more information.
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namespace Microsoft.ML
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namespace Microsoft.ML;
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/// <summary>
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/// Type of prediction task. Note that this is a legacy structure and usage of this should generally be
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/// discouraged in future projects. Its presence suggests that there are privileged and supported
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/// tasks, and anything outside of this is unsupported. This runs rather contrary to the idea of this
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/// being an expandable framework, and it is inappropriately limiting. For legacy pipelines based on
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/// <see cref="ITrainer"/> and <see cref="IPredictor"/> it is still useful, but for things based on
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/// the <see cref="IEstimator{TTransformer}"/> idiom, it is inappropriate.
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/// </summary>
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[BestFriend]
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internal enum PredictionKind
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{
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/// <summary>
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/// Type of prediction task. Note that this is a legacy structure and usage of this should generally be
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/// discouraged in future projects. Its presence suggests that there are privileged and supported
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/// tasks, and anything outside of this is unsupported. This runs rather contrary to the idea of this
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/// being an expandable framework, and it is inappropriately limiting. For legacy pipelines based on
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/// <see cref="ITrainer"/> and <see cref="IPredictor"/> it is still useful, but for things based on
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/// the <see cref="IEstimator{TTransformer}"/> idiom, it is inappropriate.
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/// </summary>
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[BestFriend]
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internal enum PredictionKind
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{
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Unknown = 0,
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Custom = 1,
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Unknown = 0,
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Custom = 1,
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BinaryClassification = 2,
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MulticlassClassification = 3,
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Regression = 4,
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MultiOutputRegression = 5,
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Ranking = 6,
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Recommendation = 7,
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AnomalyDetection = 8,
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Clustering = 9,
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SequenceClassification = 10,
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BinaryClassification = 2,
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MulticlassClassification = 3,
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Regression = 4,
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MultiOutputRegression = 5,
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Ranking = 6,
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Recommendation = 7,
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AnomalyDetection = 8,
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Clustering = 9,
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SequenceClassification = 10,
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// More to be added later.
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}
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// More to be added later.
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}
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/// <summary>
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/// Weakly typed version of IPredictor.
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/// </summary>
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[BestFriend]
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internal interface IPredictor
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{
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/// <summary>
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/// Weakly typed version of IPredictor.
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/// Return the type of prediction task.
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/// </summary>
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[BestFriend]
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internal interface IPredictor
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{
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/// <summary>
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/// Return the type of prediction task.
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/// </summary>
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PredictionKind PredictionKind { get; }
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}
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PredictionKind PredictionKind { get; }
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}
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/// <summary>
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/// A predictor the produces values of the indicated type.
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/// REVIEW: Determine whether this is just a temporary shim or long term solution.
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/// </summary>
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[BestFriend]
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internal interface IPredictorProducing<out TResult> : IPredictor
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{
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}
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/// <summary>
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/// A predictor the produces values of the indicated type.
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/// REVIEW: Determine whether this is just a temporary shim or long term solution.
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/// </summary>
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[BestFriend]
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internal interface IPredictorProducing<out TResult> : IPredictor
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{
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}
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/// <summary>
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/// A predictor that produces values and distributions of the indicated types.
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/// Note that from a public API perspective this is bad.
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/// </summary>
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[BestFriend]
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internal interface IDistPredictorProducing<out TResult, out TResultDistribution> : IPredictorProducing<TResult>
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{
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}
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/// <summary>
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/// A predictor that produces values and distributions of the indicated types.
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/// Note that from a public API perspective this is bad.
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/// </summary>
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[BestFriend]
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internal interface IDistPredictorProducing<out TResult, out TResultDistribution> : IPredictorProducing<TResult>
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{
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}

‎src/Microsoft.ML.Core/Prediction/ITrainer.cs‎

Lines changed: 87 additions & 88 deletions
Original file line numberDiff line numberDiff line change
@@ -4,104 +4,103 @@
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using Microsoft.ML.Data;
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7-
namespace Microsoft.ML
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{
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// REVIEW: Would be nice if the registration under SignatureTrainer were automatic
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// given registration for one of the "sub-class" signatures.
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namespace Microsoft.ML;
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12-
/// <summary>
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/// Loadable class signatures for trainers. Typically each trainer should register with
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/// both SignatureTrainer and SignatureXxxTrainer where Xxx is the prediction kind.
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/// </summary>
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[BestFriend]
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internal delegate void SignatureTrainer();
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// REVIEW: Would be nice if the registration under SignatureTrainer were automatic
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// given registration for one of the "sub-class" signatures.
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[BestFriend]
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internal delegate void SignatureBinaryClassifierTrainer();
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[BestFriend]
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internal delegate void SignatureMulticlassClassifierTrainer();
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[BestFriend]
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internal delegate void SignatureRegressorTrainer();
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[BestFriend]
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internal delegate void SignatureMultiOutputRegressorTrainer();
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[BestFriend]
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internal delegate void SignatureRankerTrainer();
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[BestFriend]
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internal delegate void SignatureAnomalyDetectorTrainer();
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[BestFriend]
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internal delegate void SignatureClusteringTrainer();
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[BestFriend]
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internal delegate void SignatureSequenceTrainer();
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[BestFriend]
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internal delegate void SignatureMatrixRecommendingTrainer();
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/// <summary>
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/// Loadable class signatures for trainers. Typically each trainer should register with
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/// both SignatureTrainer and SignatureXxxTrainer where Xxx is the prediction kind.
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/// </summary>
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[BestFriend]
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internal delegate void SignatureTrainer();
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[BestFriend]
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internal delegate void SignatureBinaryClassifierTrainer();
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[BestFriend]
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internal delegate void SignatureMulticlassClassifierTrainer();
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[BestFriend]
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internal delegate void SignatureRegressorTrainer();
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[BestFriend]
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internal delegate void SignatureMultiOutputRegressorTrainer();
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[BestFriend]
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internal delegate void SignatureRankerTrainer();
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[BestFriend]
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internal delegate void SignatureAnomalyDetectorTrainer();
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[BestFriend]
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internal delegate void SignatureClusteringTrainer();
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[BestFriend]
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internal delegate void SignatureSequenceTrainer();
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[BestFriend]
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internal delegate void SignatureMatrixRecommendingTrainer();
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/// <summary>
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/// The base interface for a trainers. Implementors should not implement this interface directly,
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/// but rather implement the more specific <see cref="ITrainer{TPredictor}"/>.
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/// </summary>
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[BestFriend]
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internal interface ITrainer
44+
{
3845
/// <summary>
39-
/// The base interface for a trainers. Implementors should not implement this interface directly,
40-
/// but rather implement the more specific <see cref="ITrainer{TPredictor}"/>.
46+
/// Auxiliary information about the trainer in terms of its capabilities
47+
/// and requirements.
4148
/// </summary>
42-
[BestFriend]
43-
internal interface ITrainer
44-
{
45-
/// <summary>
46-
/// Auxiliary information about the trainer in terms of its capabilities
47-
/// and requirements.
48-
/// </summary>
49-
TrainerInfo Info { get; }
49+
TrainerInfo Info { get; }
5050

51-
/// <summary>
52-
/// Return the type of prediction task for the produced predictor.
53-
/// </summary>
54-
PredictionKind PredictionKind { get; }
51+
/// <summary>
52+
/// Return the type of prediction task for the produced predictor.
53+
/// </summary>
54+
PredictionKind PredictionKind { get; }
5555

56-
/// <summary>
57-
/// Trains a predictor.
58-
/// </summary>
59-
/// <param name="context">A context containing at least the training data</param>
60-
/// <returns>The trained predictor</returns>
61-
/// <seealso cref="ITrainer{TPredictor}.Train(TrainContext)"/>
62-
IPredictor Train(TrainContext context);
63-
}
56+
/// <summary>
57+
/// Trains a predictor.
58+
/// </summary>
59+
/// <param name="context">A context containing at least the training data</param>
60+
/// <returns>The trained predictor</returns>
61+
/// <seealso cref="ITrainer{TPredictor}.Train(TrainContext)"/>
62+
IPredictor Train(TrainContext context);
63+
}
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65+
/// <summary>
66+
/// Strongly typed generic interface for a trainer. A trainer object takes training data
67+
/// and produces a predictor.
68+
/// </summary>
69+
/// <typeparam name="TPredictor"> Type of predictor produced</typeparam>
70+
[BestFriend]
71+
internal interface ITrainer<out TPredictor> : ITrainer
72+
where TPredictor : IPredictor
73+
{
6574
/// <summary>
66-
/// Strongly typed generic interface for a trainer. A trainer object takes training data
67-
/// and produces a predictor.
75+
/// Trains a predictor.
6876
/// </summary>
69-
/// <typeparam name="TPredictor"> Type of predictor produced</typeparam>
70-
[BestFriend]
71-
internal interface ITrainer<out TPredictor> : ITrainer
72-
where TPredictor : IPredictor
73-
{
74-
/// <summary>
75-
/// Trains a predictor.
76-
/// </summary>
77-
/// <param name="context">A context containing at least the training data</param>
78-
/// <returns>The trained predictor</returns>
79-
new TPredictor Train(TrainContext context);
80-
}
77+
/// <param name="context">A context containing at least the training data</param>
78+
/// <returns>The trained predictor</returns>
79+
new TPredictor Train(TrainContext context);
80+
}
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82-
[BestFriend]
83-
internal static class TrainerExtensions
84-
{
85-
/// <summary>
86-
/// Convenience train extension for the case where one has only a training set with no auxiliary information.
87-
/// Equivalent to calling <see cref="ITrainer.Train(TrainContext)"/>
88-
/// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
89-
/// </summary>
90-
/// <param name="trainer">The trainer</param>
91-
/// <param name="trainData">The training data.</param>
92-
/// <returns>The trained predictor</returns>
93-
public static IPredictor Train(this ITrainer trainer, RoleMappedData trainData)
94-
=> trainer.Train(new TrainContext(trainData));
82+
[BestFriend]
83+
internal static class TrainerExtensions
84+
{
85+
/// <summary>
86+
/// Convenience train extension for the case where one has only a training set with no auxiliary information.
87+
/// Equivalent to calling <see cref="ITrainer.Train(TrainContext)"/>
88+
/// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
89+
/// </summary>
90+
/// <param name="trainer">The trainer</param>
91+
/// <param name="trainData">The training data.</param>
92+
/// <returns>The trained predictor</returns>
93+
public static IPredictor Train(this ITrainer trainer, RoleMappedData trainData)
94+
=> trainer.Train(new TrainContext(trainData));
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96-
/// <summary>
97-
/// Convenience train extension for the case where one has only a training set with no auxiliary information.
98-
/// Equivalent to calling <see cref="ITrainer{TPredictor}.Train(TrainContext)"/>
99-
/// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
100-
/// </summary>
101-
/// <param name="trainer">The trainer</param>
102-
/// <param name="trainData">The training data.</param>
103-
/// <returns>The trained predictor</returns>
104-
public static TPredictor Train<TPredictor>(this ITrainer<TPredictor> trainer, RoleMappedData trainData) where TPredictor : IPredictor
105-
=> trainer.Train(new TrainContext(trainData));
106-
}
96+
/// <summary>
97+
/// Convenience train extension for the case where one has only a training set with no auxiliary information.
98+
/// Equivalent to calling <see cref="ITrainer{TPredictor}.Train(TrainContext)"/>
99+
/// on a <see cref="TrainContext"/> constructed with <paramref name="trainData"/>.
100+
/// </summary>
101+
/// <param name="trainer">The trainer</param>
102+
/// <param name="trainData">The training data.</param>
103+
/// <returns>The trained predictor</returns>
104+
public static TPredictor Train<TPredictor>(this ITrainer<TPredictor> trainer, RoleMappedData trainData) where TPredictor : IPredictor
105+
=> trainer.Train(new TrainContext(trainData));
107106
}

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