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Added new PSO-based optimization tests.
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‎Src/ILGPU.Algorithms.Tests/Configurations.txt

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11
ArrayExtensionTests
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GroupExtensionTests
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HistogramTests
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HistogramTests
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InitializeTests
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OptimizationTests
56
RadixSortExtensionTests
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RandomTests
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ReductionExtensionTests

‎Src/ILGPU.Algorithms.Tests/OptimizationTests.cs

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// ---------------------------------------------------------------------------------------
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// ILGPU Algorithms
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// Copyright (c) 2023 ILGPU Project
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// www.ilgpu.net
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//
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// File: OptimizationTests.cs
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//
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// This file is part of ILGPU and is distributed under the University of Illinois Open
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// Source License. See LICENSE.txt for details.
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// ---------------------------------------------------------------------------------------
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#if NET7_0_OR_GREATER
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using ILGPU.Algorithms.Optimization;
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using ILGPU.Algorithms.Optimization.Optimizers;
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using ILGPU.Algorithms.Random;
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using ILGPU.Algorithms.Vectors;
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#endif
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using ILGPU.Runtime;
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using ILGPU.Tests;
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using System.Linq;
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using System.Numerics;
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using Xunit;
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using Xunit.Abstractions;
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#pragma warning disable CA1034
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#pragma warning disable CA1819
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#pragma warning disable xUnit1026
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namespace ILGPU.Algorithms.Tests
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{
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public abstract partial class OptimizationTests : TestBase
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{
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protected OptimizationTests(ITestOutputHelper output, TestContext testContext)
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: base(output, testContext)
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{ }
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#if NET7_0_OR_GREATER
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#region Objectives
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public readonly record struct DistanceF32x2(float Constant) :
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IOptimizationFunction<Float32x2, float, float>
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{
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public float Evaluate(
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LongIndex1D index,
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Index1D dimension,
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SingleVectorView<Float32x2> positionView)
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{
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float result = 0;
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for (Index1D i = 0; i < dimension; ++i)
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{
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var vec = positionView[i];
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var dist = vec - Float32x2.FromScalar(Constant);
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result += dist.X * dist.X + dist.Y * dist.Y;
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}
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return result / dimension;
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}
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public bool CurrentIsBetter(float current, float proposed) =>
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current <= proposed;
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}
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#endregion
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#region MemberData
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public record OptimizerConfig<TElementType>(
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int NumIterations,
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int NumParticles,
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int NumDimensions,
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TElementType[] BestPositions,
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TElementType[] Parameters);
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public static TheoryData<
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object,
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object,
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object,
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object,
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object,
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object,
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object,
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object,
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object> TestData =>
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new TheoryData<
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object,
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object,
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object,
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object,
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object,
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object,
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object,
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object,
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object>
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{
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{
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new OptimizerConfig<float>(
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32,
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64,
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4,
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new float[] { 0.0f, 0.0f, 0.0f, 0.0f},
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new float[] { PSO.Omega, PSO.PhiG, PSO.PhiP }),
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new DistanceF32x2(1.3f),
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0.0f,
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2.0f,
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float.MaxValue,
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4e-4f,
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0.0001f,
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default(Float32x2),
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default(XorShift64Star)
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},
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{
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new OptimizerConfig<float>(
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512,
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2048,
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6,
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new float[] { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f},
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new float[] { PSO.Omega, PSO.PhiG, PSO.PhiP }),
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new DistanceF32x2(4.7f),
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0.0f,
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20.0f,
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float.MaxValue,
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1e-5f,
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1e-6f,
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default(Float32x2),
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default(XorShift128Plus)
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},
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};
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#endregion
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[SkippableTheory()]
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[MemberData(nameof(TestData))]
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public void ParticleSwarmOptimization<
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TFunc,
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TNumericType,
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TElementType,
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TEvalType,
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TRandom>(
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OptimizerConfig<TElementType> optimizerConfig,
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TFunc function,
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TElementType lower,
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TElementType upper,
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TEvalType best,
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TEvalType expected,
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TEvalType delta,
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TNumericType _,
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TRandom __)
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where TNumericType : unmanaged, IVectorType<TNumericType, TElementType>
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where TElementType : unmanaged, INumber<TElementType>
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where TEvalType : unmanaged, INumber<TEvalType>
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where TRandom : unmanaged, IRandomProvider<TRandom>
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where TFunc : struct,
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IOptimizationFunction<TNumericType, TElementType, TEvalType>
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{
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// Skip larger problems on the CPU
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Skip.If(
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Accelerator.AcceleratorType == AcceleratorType.CPU &&
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optimizerConfig.NumIterations * optimizerConfig.NumParticles > 2048);
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const int Seed = 24404699;
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using var pso = new PSO<
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TNumericType,
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TElementType,
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TEvalType,
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TRandom>(
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Accelerator,
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optimizerConfig.NumParticles,
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optimizerConfig.NumDimensions);
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using var stream = Accelerator.CreateStream();
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var random = new System.Random(Seed);
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using var optimizer = pso.CreateOptimizer(stream, random, function);
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// Load config
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var lowerRange = Enumerable.Repeat(lower, pso.Dimension).ToArray();
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var upperRange = Enumerable.Repeat(upper, pso.Dimension).ToArray();
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pso.LoadBounds(stream, lowerRange, upperRange);
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pso.LoadParameters(stream, optimizerConfig.Parameters);
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// Optimize and wait for results
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var result = optimizer.OptimizeToCPUAsync(
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stream,
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optimizerConfig.BestPositions,
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best,
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optimizerConfig.NumIterations);
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stream.Synchronize();
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// Check result
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Assert.True(
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result.Result - delta <= expected,
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"Invalid result");
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}
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#endif
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}
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}
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#pragma warning restore xUnit1026
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#pragma warning restore CA1034
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#pragma warning restore CA1819
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