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| <Project Sdk="Microsoft.NET.Sdk"> | ||
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| <PropertyGroup> | ||
| <TargetFrameworks>netstandard2.0;netcoreapp2.2;netcoreapp3.0</TargetFrameworks> | ||
| </PropertyGroup> | ||
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| <ItemGroup> | ||
| <PackageReference Include="Microsoft.Extensions.Logging.Console" /> | ||
| <PackageReference Include="Microsoft.Extensions.Logging.Debug" /> | ||
| <PackageReference Include="Microsoft.Extensions.ObjectPool" /> | ||
| <PackageReference Include="Microsoft.ML" /> | ||
| </ItemGroup> | ||
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| </Project> |
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| using Microsoft.ML; | ||
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| namespace Bet.Extensions.ML.Engine | ||
| { | ||
| public interface IMLModelEngine<TData, TPrediction> where TData : class where TPrediction : class | ||
| { | ||
| /// <summary> | ||
| /// The transformer is a component that transforms data. It also supports 'schema | ||
| /// propagation' to answer the question of 'how will the data with this schema look, | ||
| /// after you transform it?'. | ||
| /// </summary> | ||
| ITransformer MLModel { get; } | ||
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| /// <summary> | ||
| /// Predict based on <see cref="MLModel"/> that was loaded. | ||
| /// </summary> | ||
| /// <param name="dataSample">The data sample to be predicted on.</param> | ||
| /// <returns></returns> | ||
| TPrediction Predict(TData dataSample); | ||
| } | ||
| } |
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| using System; | ||
| using System.IO; | ||
| using Microsoft.Extensions.Logging; | ||
| using Microsoft.Extensions.ObjectPool; | ||
| using Microsoft.ML; | ||
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| namespace Bet.Extensions.ML.Engine | ||
| { | ||
| public class MLModelEngineObjectPool<TData, TPrediction> | ||
| : IMLModelEngine<TData, TPrediction> | ||
| where TData : class | ||
| where TPrediction : class, new() | ||
| { | ||
| private readonly MLContext _mlContext; | ||
| private readonly ILogger<PredictionEnginePooledObjectPolicy<TData, TPrediction>> _logger; | ||
| private readonly int _maximumObjectsRetained; | ||
| private readonly ObjectPool<PredictionEngine<TData, TPrediction>> _predictionEnginePool; | ||
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| public ITransformer MLModel { get; private set; } | ||
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| public MLModelEngineObjectPool( | ||
| string modelFilePathName, | ||
| ILogger<PredictionEnginePooledObjectPolicy<TData, TPrediction>> logger, | ||
| int maximumObjectsRetained = -1) | ||
| { | ||
| //Create the MLContext object to use under the scope of this class | ||
| _mlContext = new MLContext(); | ||
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| _logger = logger; | ||
| //Load the ProductSalesForecast model from the .ZIP file | ||
| using (var fileStream = File.OpenRead(modelFilePathName)) | ||
| { | ||
| MLModel = _mlContext.Model.Load(fileStream); | ||
| } | ||
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| _maximumObjectsRetained = maximumObjectsRetained; | ||
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| // create PredictionEngine Object Pool | ||
| _predictionEnginePool = CreatePredictionEngineObjectPool(); | ||
| } | ||
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| public TPrediction Predict(TData dataSample) | ||
| { | ||
| // get instance of PredictionEngine from the object pool | ||
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| var predictionEngine = _predictionEnginePool.Get(); | ||
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| try | ||
| { | ||
| return predictionEngine.Predict(dataSample); | ||
| } | ||
| catch (Exception ex) | ||
| { | ||
| _logger.LogError("PredictionEngine failed: {ex}", ex.ToString()); | ||
| } | ||
| finally | ||
| { | ||
| // release used PredictionEngine object into the Object pool. | ||
| _predictionEnginePool.Return(predictionEngine); | ||
| } | ||
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| // all other cases return null prediction. | ||
| return null; | ||
| } | ||
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| private ObjectPool<PredictionEngine<TData,TPrediction>> CreatePredictionEngineObjectPool() | ||
| { | ||
| var pooledObjectPolicy = new PredictionEnginePooledObjectPolicy<TData, TPrediction>(_mlContext, MLModel, _logger); | ||
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| DefaultObjectPool<PredictionEngine<TData, TPrediction>> pool; | ||
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| if (_maximumObjectsRetained != -1) | ||
| { | ||
| pool = new DefaultObjectPool<PredictionEngine<TData, TPrediction>>(pooledObjectPolicy, _maximumObjectsRetained); | ||
| } | ||
| else | ||
| { | ||
| //default maximumRetained is Environment.ProcessorCount * 2, if not explicitly provided | ||
| pool = new DefaultObjectPool<PredictionEngine<TData, TPrediction>>(pooledObjectPolicy); | ||
| } | ||
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| return pool; | ||
| } | ||
| } | ||
| } |
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src/Bet.Extensions.ML/Engine/PredictionEnginePooledObjectPolicy.cs
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| using Microsoft.Extensions.Logging; | ||
| using Microsoft.Extensions.ObjectPool; | ||
| using Microsoft.ML; | ||
| using System; | ||
| using System.Diagnostics; | ||
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| namespace Bet.Extensions.ML.Engine | ||
| { | ||
| /// <summary> | ||
| /// Creates instance of the <see cref="PredictionEngine{TSrc, TDst}"/> for the dataset. | ||
| /// </summary> | ||
| /// <typeparam name="TData"></typeparam> | ||
| /// <typeparam name="TPrediction"></typeparam> | ||
| public class PredictionEnginePooledObjectPolicy<TData, TPrediction> | ||
| : IPooledObjectPolicy<PredictionEngine<TData, TPrediction>> | ||
| where TData : class | ||
| where TPrediction : class, new() | ||
| { | ||
| private readonly MLContext _mlContext; | ||
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| private readonly ITransformer _model; | ||
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| private readonly ILogger<PredictionEnginePooledObjectPolicy<TData,TPrediction>> _logger; | ||
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| public PredictionEnginePooledObjectPolicy( | ||
| MLContext mlContext, | ||
| ITransformer model, | ||
| ILogger<PredictionEnginePooledObjectPolicy<TData,TPrediction>> logger) | ||
| { | ||
| _mlContext = mlContext ?? throw new ArgumentNullException(nameof(mlContext)); | ||
| _model = model ?? throw new ArgumentNullException(nameof(model)); | ||
| _logger = logger; | ||
| } | ||
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| public PredictionEngine<TData, TPrediction> Create() | ||
| { | ||
| var watch = Stopwatch.StartNew(); | ||
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| var predictionEngine = _model.CreatePredictionEngine<TData, TPrediction>(_mlContext); | ||
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| watch.Stop(); | ||
| _logger.LogDebug("Time took to create the prediction engine: {elapsed}", watch.ElapsedMilliseconds); | ||
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| return predictionEngine; | ||
| } | ||
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| public bool Return(PredictionEngine<TData, TPrediction> obj) | ||
| { | ||
| if(obj == null) | ||
| { | ||
| return false; | ||
| } | ||
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| return true; | ||
| } | ||
| } | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,43 @@ | ||
| using Bet.Extensions.ML.Engine; | ||
| using Microsoft.Extensions.DependencyInjection.Extensions; | ||
| using Microsoft.Extensions.Logging; | ||
| using Microsoft.Extensions.ObjectPool; | ||
| using System; | ||
| using System.IO; | ||
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| namespace Microsoft.Extensions.DependencyInjection | ||
| { | ||
| public static class ServiceCollectionExtensions | ||
| { | ||
| /// <summary> | ||
| /// Add <see cref="IMLModelEngine{TData, TPrediction}"/> prediction engine with specified model. | ||
| /// </summary> | ||
| /// <typeparam name="TData"></typeparam> | ||
| /// <typeparam name="TPrediction"></typeparam> | ||
| /// <param name="services"></param> | ||
| /// <param name="modelFilePath"></param> | ||
| /// <param name="maximumObjectRetained"></param> | ||
| /// <returns></returns> | ||
| public static IServiceCollection AddMLModelEngine<TData, TPrediction>( | ||
| this IServiceCollection services, | ||
| string modelFilePath, | ||
| int maximumObjectRetained = -1) where TData : class where TPrediction : class, new() | ||
| { | ||
| services.TryAddSingleton<ObjectPoolProvider, DefaultObjectPoolProvider>(); | ||
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| services.AddSingleton<IMLModelEngine<TData, TPrediction>>(sp => | ||
| { | ||
| if (!File.Exists(modelFilePath)) | ||
| { | ||
| throw new ArgumentException($"File: {modelFilePath} doesn't exist"); | ||
| } | ||
| var logger = sp.GetRequiredService<ILogger<PredictionEnginePooledObjectPolicy<TData, TPrediction>>>(); | ||
| return new MLModelEngineObjectPool<TData, TPrediction>(modelFilePath,logger,maximumObjectRetained); | ||
| }); | ||
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| return services; | ||
| } | ||
| } | ||
| } |