forked from dotnet/machinelearning
-
Notifications
You must be signed in to change notification settings - Fork 0
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Added Microsoft.ML.Benchmarks Project (dotnet#62)
* Benchmark * Changed to .NET Core app * Added Accuracy Reporting * fixed build * Feedback from Gleb * Added batch prediction tests * Resolved conflicts the sln file * Renamed the new file to match type name * Removed duplicated method
- Loading branch information
1 parent
52ea962
commit 83f9bac
Showing
4 changed files
with
226 additions
and
0 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
23 changes: 23 additions & 0 deletions
23
test/Microsoft.ML.Benchmarks/Microsoft.ML.Benchmarks.csproj
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,23 @@ | ||
| <Project Sdk="Microsoft.NET.Sdk" ToolsVersion="15.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003"> | ||
| <PropertyGroup> | ||
| <OutputType>Exe</OutputType> | ||
| <LangVersion>7.2</LangVersion> | ||
| <StartupObject>Microsoft.ML.Benchmarks.Program</StartupObject> | ||
| <TargetFramework>netcoreapp2.0</TargetFramework> | ||
| </PropertyGroup> | ||
| <ItemGroup> | ||
| <Compile Remove="BenchmarkDotNet.Artifacts\**" /> | ||
| <EmbeddedResource Remove="BenchmarkDotNet.Artifacts\**" /> | ||
| <None Remove="BenchmarkDotNet.Artifacts\**" /> | ||
| </ItemGroup> | ||
| <ItemGroup> | ||
| <PackageReference Include="BenchmarkDotNet" Version="0.10.14" /> | ||
| </ItemGroup> | ||
| <ItemGroup> | ||
| <ProjectReference Include="..\..\src\Microsoft.ML.StandardLearners\Microsoft.ML.StandardLearners.csproj" /> | ||
| <ProjectReference Include="..\..\src\Microsoft.ML\Microsoft.ML.csproj" /> | ||
| </ItemGroup> | ||
| <ItemGroup> | ||
| <NativeAssemblyReference Include="CpuMathNative" /> | ||
| </ItemGroup> | ||
| </Project> |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,89 @@ | ||
| // Licensed to the .NET Foundation under one or more agreements. | ||
| // The .NET Foundation licenses this file to you under the MIT license. | ||
| // See the LICENSE file in the project root for more information. | ||
|
|
||
| using BenchmarkDotNet.Configs; | ||
| using BenchmarkDotNet.Diagnosers; | ||
| using BenchmarkDotNet.Jobs; | ||
| using BenchmarkDotNet.Running; | ||
| using BenchmarkDotNet.Columns; | ||
| using BenchmarkDotNet.Reports; | ||
| using BenchmarkDotNet.Toolchains.CsProj; | ||
| using BenchmarkDotNet.Toolchains.InProcess; | ||
| using System; | ||
| using System.IO; | ||
| using Microsoft.ML.Models; | ||
| using Microsoft.ML.Runtime.Api; | ||
| using Microsoft.ML.Trainers; | ||
| using Microsoft.ML.Transforms; | ||
| using Microsoft.ML.Benchmarks; | ||
|
|
||
| namespace Microsoft.ML.Benchmarks | ||
| { | ||
| class Program | ||
| { | ||
| /// <summary> | ||
| /// execute dotnet run -c Release and choose the benchmarks you want to run | ||
| /// </summary> | ||
| /// <param name="args"></param> | ||
| static void Main(string[] args) | ||
| { | ||
| BenchmarkSwitcher | ||
| .FromAssembly(typeof(Program).Assembly) | ||
| .Run(null, CreateClrVsCoreConfig()); | ||
| } | ||
|
|
||
| private static IConfig CreateClrVsCoreConfig() | ||
| { | ||
| var config = DefaultConfig.Instance.With( | ||
| Job.ShortRun. | ||
| With(InProcessToolchain.Instance)). | ||
| With(new ClassificationMetricsColumn("AccuracyMacro", "Macro-average accuracy of the model")). | ||
| With(MemoryDiagnoser.Default); | ||
| return config; | ||
| } | ||
|
|
||
| internal static string GetDataPath(string name) | ||
| => Path.GetFullPath(Path.Combine(_dataRoot, name)); | ||
|
|
||
| static readonly string _dataRoot; | ||
| static Program() | ||
| { | ||
| var currentAssemblyLocation = new FileInfo(typeof(Program).Assembly.Location); | ||
| var rootDir = currentAssemblyLocation.Directory.Parent.Parent.Parent.Parent.FullName; | ||
| _dataRoot = Path.Combine(rootDir, "test", "data"); | ||
| } | ||
| } | ||
|
|
||
| public class ClassificationMetricsColumn : IColumn | ||
| { | ||
| string _metricName; | ||
| string _legend; | ||
|
|
||
| public ClassificationMetricsColumn(string metricName, string legend) | ||
| { | ||
| _metricName = metricName; | ||
| _legend = legend; | ||
| } | ||
|
|
||
| public string ColumnName => _metricName; | ||
| public string Id => _metricName; | ||
| public string Legend => _legend; | ||
| public bool IsNumeric => true; | ||
| public bool IsDefault(Summary summary, Benchmark benchmark) => true; | ||
| public bool IsAvailable(Summary summary) => true; | ||
| public bool AlwaysShow => true; | ||
| public ColumnCategory Category => ColumnCategory.Custom; | ||
| public int PriorityInCategory => 1; | ||
| public UnitType UnitType => UnitType.Dimensionless; | ||
|
|
||
| public string GetValue(Summary summary, Benchmark benchmark, ISummaryStyle style) | ||
| { | ||
| var property = typeof(ClassificationMetrics).GetProperty(_metricName); | ||
| return property.GetValue(StochasticDualCoordinateAscentClassifierBench.s_metrics).ToString(); | ||
| } | ||
| public string GetValue(Summary summary, Benchmark benchmark) => GetValue(summary, benchmark, null); | ||
|
|
||
| public override string ToString() => ColumnName; | ||
| } | ||
| } |
107 changes: 107 additions & 0 deletions
107
test/Microsoft.ML.Benchmarks/StochasticDualCoordinateAscentClassifierBench.cs
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,107 @@ | ||
| // Licensed to the .NET Foundation under one or more agreements. | ||
| // The .NET Foundation licenses this file to you under the MIT license. | ||
| // See the LICENSE file in the project root for more information. | ||
|
|
||
| using BenchmarkDotNet.Attributes; | ||
| using BenchmarkDotNet.Running; | ||
| using Microsoft.ML.Models; | ||
| using Microsoft.ML.Runtime.Api; | ||
| using Microsoft.ML.Trainers; | ||
| using Microsoft.ML.Transforms; | ||
| using System; | ||
| using System.Collections.Generic; | ||
| using System.Linq; | ||
|
|
||
| namespace Microsoft.ML.Benchmarks | ||
| { | ||
| public class StochasticDualCoordinateAscentClassifierBench | ||
| { | ||
| internal static ClassificationMetrics s_metrics; | ||
| private static PredictionModel<IrisData, IrisPrediction> s_trainedModel; | ||
| private static string s_dataPath; | ||
| private static IrisData[][] s_batches; | ||
| private static readonly int[] s_batchSizes = new int[] { 1, 2, 5 }; | ||
| private readonly Random r = new Random(0); | ||
| private readonly static IrisData s_example = new IrisData() | ||
| { | ||
| SepalLength = 3.3f, | ||
| SepalWidth = 1.6f, | ||
| PetalLength = 0.2f, | ||
| PetalWidth = 5.1f, | ||
| }; | ||
|
|
||
| [Benchmark] | ||
| public PredictionModel<IrisData, IrisPrediction> TrainIris() => TrainCore(); | ||
|
|
||
| [Benchmark] | ||
| public float[] PredictIris() => s_trainedModel.Predict(s_example).PredictedLabels; | ||
|
|
||
| [Benchmark] | ||
| public IEnumerable<IrisPrediction> PredictIrisBatchOf1() => s_trainedModel.Predict(s_batches[0]); | ||
| [Benchmark] | ||
| public IEnumerable<IrisPrediction> PredictIrisBatchOf2() => s_trainedModel.Predict(s_batches[1]); | ||
| [Benchmark] | ||
| public IEnumerable<IrisPrediction> PredictIrisBatchOf5() => s_trainedModel.Predict(s_batches[2]); | ||
|
|
||
| [GlobalSetup] | ||
| public void Setup() | ||
| { | ||
| s_dataPath = Program.GetDataPath("iris.txt"); | ||
| s_trainedModel = TrainCore(); | ||
| IrisPrediction prediction = s_trainedModel.Predict(s_example); | ||
|
|
||
| var testData = new TextLoader<IrisData>(s_dataPath, useHeader: true, separator: "tab"); | ||
| var evaluator = new ClassificationEvaluator(); | ||
| s_metrics = evaluator.Evaluate(s_trainedModel, testData); | ||
|
|
||
| s_batches = new IrisData[s_batchSizes.Length][]; | ||
| for (int i = 0; i < s_batches.Length; i++) | ||
| { | ||
| var batch = new IrisData[s_batchSizes[i]]; | ||
| s_batches[i] = batch; | ||
| for (int bi = 0; bi < batch.Length; bi++) | ||
| { | ||
| batch[bi] = s_example; | ||
| } | ||
| } | ||
| } | ||
|
|
||
| private static PredictionModel<IrisData, IrisPrediction> TrainCore() | ||
| { | ||
| var pipeline = new LearningPipeline(); | ||
|
|
||
| pipeline.Add(new TextLoader<IrisData>(s_dataPath, useHeader: true, separator: "tab")); | ||
| pipeline.Add(new ColumnConcatenator(outputColumn: "Features", | ||
| "SepalLength", "SepalWidth", "PetalLength", "PetalWidth")); | ||
|
|
||
| pipeline.Add(new StochasticDualCoordinateAscentClassifier()); | ||
|
|
||
| PredictionModel<IrisData, IrisPrediction> model = pipeline.Train<IrisData, IrisPrediction>(); | ||
| return model; | ||
| } | ||
|
|
||
| public class IrisData | ||
| { | ||
| [Column("0")] | ||
| public float Label; | ||
|
|
||
| [Column("1")] | ||
| public float SepalLength; | ||
|
|
||
| [Column("2")] | ||
| public float SepalWidth; | ||
|
|
||
| [Column("3")] | ||
| public float PetalLength; | ||
|
|
||
| [Column("4")] | ||
| public float PetalWidth; | ||
| } | ||
|
|
||
| public class IrisPrediction | ||
| { | ||
| [ColumnName("Score")] | ||
| public float[] PredictedLabels; | ||
| } | ||
| } | ||
| } |