mirror of https://github.com/SixLabors/ImageSharp
James Jackson-South
3 weeks ago
13 changed files with 2886 additions and 532 deletions
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Subproject commit 7ac5703452348d9295db31fc0912c2bd9e419dc9 |
Subproject commit 74b7f32b8e41fdf8fe2f3eda54fd5a82ebbedfbc |
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File diff suppressed because it is too large
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// Copyright (c) Six Labors.
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// Licensed under the Six Labors Split License.
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using BenchmarkDotNet.Attributes; |
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using SixLabors.ImageSharp.Common.Helpers; |
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namespace SixLabors.ImageSharp.Benchmarks.General.BasicMath; |
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public class AddSpan |
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{ |
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private byte[] scalarValues = null!; |
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private byte[] tensorValues = null!; |
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private byte[] addends = null!; |
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/// <summary>
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/// Gets or sets the number of values to add.
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/// </summary>
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[Params(32, 257, 2048)] |
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public int Length { get; set; } |
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/// <summary>
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/// Creates equivalent deterministic inputs for both implementations.
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/// </summary>
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[GlobalSetup] |
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public void Setup() |
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{ |
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this.scalarValues = new byte[this.Length]; |
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this.tensorValues = new byte[this.Length]; |
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this.addends = new byte[this.Length]; |
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for (int i = 0; i < this.Length; i++) |
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{ |
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byte value = (byte)((i * 17) + 31); |
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this.scalarValues[i] = value; |
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this.tensorValues[i] = value; |
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this.addends[i] = (byte)((i * 29) + 7); |
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} |
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} |
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/// <summary>
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/// Adds the values with a scalar loop.
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/// </summary>
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/// <returns>The first result, which keeps the mutated data observable to the benchmark harness.</returns>
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[Benchmark(Baseline = true)] |
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public byte Scalar() |
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{ |
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for (int i = 0; i < this.scalarValues.Length; i++) |
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{ |
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this.scalarValues[i] += this.addends[i]; |
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} |
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return this.scalarValues[0]; |
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} |
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/// <summary>
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/// Adds the values with the tensor compatibility pipeline.
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/// </summary>
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/// <returns>The first result, which keeps the mutated data observable to the benchmark harness.</returns>
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[Benchmark] |
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public byte TensorPipeline() |
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{ |
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TensorPrimitives_.Add<byte>(this.tensorValues, this.addends, this.tensorValues); |
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return this.tensorValues[0]; |
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} |
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} |
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// Copyright (c) Six Labors.
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// Licensed under the Six Labors Split License.
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using BenchmarkDotNet.Attributes; |
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namespace SixLabors.ImageSharp.Benchmarks.General.BasicMath; |
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public class NormalizeSpan |
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{ |
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private float[] scalarValues = null!; |
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private float[] tensorValues = null!; |
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/// <summary>
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/// Gets or sets the number of values to normalize.
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/// </summary>
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[Params(7, 32, 257, 2048)] |
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public int Length { get; set; } |
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/// <summary>
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/// Creates equivalent deterministic inputs for both implementations.
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/// </summary>
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[GlobalSetup] |
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public void Setup() |
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{ |
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this.scalarValues = new float[this.Length]; |
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this.tensorValues = new float[this.Length]; |
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for (int i = 0; i < this.scalarValues.Length; i++) |
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{ |
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float value = ((i * 17) % 251) + 1; |
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this.scalarValues[i] = value; |
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this.tensorValues[i] = value; |
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} |
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} |
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/// <summary>
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/// Normalizes the values with a scalar loop.
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/// </summary>
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/// <returns>The first result, which keeps the mutated data observable to the benchmark harness.</returns>
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[Benchmark(Baseline = true)] |
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public float Scalar() |
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{ |
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for (int i = 0; i < this.scalarValues.Length; i++) |
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{ |
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this.scalarValues[i] /= 4096F; |
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} |
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return this.scalarValues[0]; |
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} |
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/// <summary>
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/// Normalizes the values with the tensor compatibility pipeline.
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/// </summary>
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/// <returns>The first result, which keeps the mutated data observable to the benchmark harness.</returns>
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[Benchmark] |
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public float TensorPipeline() |
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{ |
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Numerics.Normalize(this.tensorValues, 4096F); |
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return this.tensorValues[0]; |
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} |
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} |
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// Copyright (c) Six Labors.
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// Licensed under the Six Labors Split License.
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using System.Numerics; |
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using System.Runtime.CompilerServices; |
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using System.Runtime.InteropServices; |
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using System.Runtime.Intrinsics; |
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using System.Runtime.Intrinsics.X86; |
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using BenchmarkDotNet.Attributes; |
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using SixLabors.ImageSharp.Common.Helpers; |
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namespace SixLabors.ImageSharp.Benchmarks.General.BasicMath; |
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#pragma warning disable SA1649 // File name should match first type name
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public class TensorPrimitivesJpegMultiplyAssemblyComparison |
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#pragma warning restore SA1649 // File name should match first type name
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{ |
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private readonly float multiplier = -1F; |
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private float[] legacyValues = null!; |
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private float[] tensorValues = null!; |
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/// <summary>
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/// Creates equivalent stable inputs for both implementations.
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/// </summary>
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[GlobalSetup] |
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public void Setup() |
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{ |
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this.legacyValues = new float[256]; |
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this.tensorValues = new float[256]; |
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for (int i = 0; i < this.legacyValues.Length; i++) |
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{ |
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float value = ((i * 17) % 251) + 1; |
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this.legacyValues[i] = value; |
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this.tensorValues[i] = value; |
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} |
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} |
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/// <summary>
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/// Multiplies the row with the retired JPEG AVX pipeline.
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/// </summary>
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/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
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[Benchmark(Baseline = true)] |
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public float Legacy() |
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{ |
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LegacyMultiply(this.legacyValues, this.multiplier); |
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return this.legacyValues[0]; |
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} |
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/// <summary>
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/// Multiplies the row with the tensor compatibility pipeline.
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/// </summary>
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/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
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[Benchmark] |
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public float Tensor() |
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{ |
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TensorPrimitives_.Multiply(this.tensorValues, this.multiplier, this.tensorValues); |
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return this.tensorValues[0]; |
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} |
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/// <summary>
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/// Reproduces the retired JPEG multiplication loop for assembly comparison.
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/// </summary>
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/// <param name="target">The row to multiply.</param>
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/// <param name="multiplier">The scalar multiplier.</param>
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[MethodImpl(MethodImplOptions.AggressiveInlining)] |
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private static void LegacyMultiply(Span<float> target, float multiplier) |
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{ |
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ref Vector256<float> targetVector = ref Unsafe.As<float, Vector256<float>>(ref MemoryMarshal.GetReference(target)); |
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nuint count = (uint)target.Length / (uint)Vector256<float>.Count; |
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Vector256<float> multiplierVector = Vector256.Create(multiplier); |
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for (nuint i = 0; i < count; i++) |
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{ |
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Unsafe.Add(ref targetVector, i) = Avx.Multiply(Unsafe.Add(ref targetVector, i), multiplierVector); |
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} |
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} |
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} |
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public class TensorPrimitivesNormalizeAssemblyComparison |
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{ |
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private readonly float divisor = -1F; |
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private float[] legacyValues = null!; |
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private float[] tensorValues = null!; |
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/// <summary>
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/// Creates equivalent stable inputs for both implementations.
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/// </summary>
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[GlobalSetup] |
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public void Setup() |
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{ |
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this.legacyValues = new float[7]; |
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this.tensorValues = new float[7]; |
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for (int i = 0; i < this.legacyValues.Length; i++) |
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{ |
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float value = ((i * 17) % 251) + 1; |
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this.legacyValues[i] = value; |
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this.tensorValues[i] = value; |
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} |
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} |
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/// <summary>
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/// Normalizes the values with the retired fixed-width pipeline.
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/// </summary>
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/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
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[Benchmark(Baseline = true)] |
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public float Legacy() |
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{ |
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LegacyNormalize(this.legacyValues, this.divisor); |
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return this.legacyValues[0]; |
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} |
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/// <summary>
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/// Normalizes the values with the tensor compatibility pipeline.
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/// </summary>
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/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
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[Benchmark] |
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public float Tensor() |
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{ |
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Numerics.Normalize(this.tensorValues, this.divisor); |
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return this.tensorValues[0]; |
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} |
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/// <summary>
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/// Reproduces the retired normalization loop for assembly comparison.
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/// </summary>
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/// <param name="span">The values to normalize.</param>
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/// <param name="sum">The scalar divisor.</param>
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[MethodImpl(MethodImplOptions.AggressiveInlining)] |
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private static void LegacyNormalize(Span<float> span, float sum) |
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{ |
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ref float start = ref MemoryMarshal.GetReference(span); |
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ref float vectorEnd = ref Unsafe.Add(ref start, span.Length & ~7); |
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Vector256<float> sum256 = Vector256.Create(sum); |
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while (Unsafe.IsAddressLessThan(ref start, ref vectorEnd)) |
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{ |
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Unsafe.As<float, Vector256<float>>(ref start) /= sum256; |
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start = ref Unsafe.Add(ref start, (nuint)8); |
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} |
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if ((span.Length & 7) >= 4) |
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{ |
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Unsafe.As<float, Vector128<float>>(ref start) /= sum256.GetLower(); |
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start = ref Unsafe.Add(ref start, (nuint)4); |
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} |
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ref float end = ref Unsafe.Add(ref start, span.Length & 3); |
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while (Unsafe.IsAddressLessThan(ref start, ref end)) |
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{ |
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start /= sum; |
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start = ref Unsafe.Add(ref start, (nuint)1); |
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} |
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} |
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} |
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public class TensorPrimitivesUInt32AssemblyComparison |
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{ |
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private uint[] x = null!; |
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private uint[] y = null!; |
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private uint[] legacyDestination = null!; |
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private uint[] tensorDestination = null!; |
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/// <summary>
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/// Creates deterministic histogram inputs and independent destinations.
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/// </summary>
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[GlobalSetup] |
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public void Setup() |
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{ |
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this.x = new uint[2048]; |
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this.y = new uint[2048]; |
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this.legacyDestination = new uint[2048]; |
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this.tensorDestination = new uint[2048]; |
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for (int i = 0; i < this.x.Length; i++) |
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{ |
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this.x[i] = (uint)((i * 17) + 31); |
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this.y[i] = (uint)((i * 29) + 7); |
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} |
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} |
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/// <summary>
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/// Adds histogram bins with the retired four-vector AVX2 pipeline.
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/// </summary>
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/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
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[Benchmark(Baseline = true)] |
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public uint Legacy() |
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{ |
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LegacyAdd(this.x, this.y, this.legacyDestination); |
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return this.legacyDestination[0]; |
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} |
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/// <summary>
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/// Adds histogram bins with the tensor compatibility pipeline.
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/// </summary>
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/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
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[Benchmark] |
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public uint Tensor() |
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{ |
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TensorPrimitives_.Add<uint>(this.x, this.y, this.tensorDestination); |
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return this.tensorDestination[0]; |
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} |
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/// <summary>
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/// Reproduces the retired WebP histogram addition loop for assembly comparison.
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/// </summary>
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/// <param name="x">The first histogram.</param>
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/// <param name="y">The second histogram.</param>
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/// <param name="destination">The destination receiving the sums.</param>
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[MethodImpl(MethodImplOptions.AggressiveInlining)] |
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private static void LegacyAdd(ReadOnlySpan<uint> x, ReadOnlySpan<uint> y, Span<uint> destination) |
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{ |
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ref uint xRef = ref MemoryMarshal.GetReference(x); |
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ref uint yRef = ref MemoryMarshal.GetReference(y); |
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ref uint destinationRef = ref MemoryMarshal.GetReference(destination); |
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nuint index = 0; |
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do |
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{ |
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Vector256<uint> x0 = Unsafe.As<uint, Vector256<uint>>(ref Unsafe.Add(ref xRef, index)); |
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Vector256<uint> x1 = Unsafe.As<uint, Vector256<uint>>(ref Unsafe.Add(ref xRef, index + 8)); |
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Vector256<uint> x2 = Unsafe.As<uint, Vector256<uint>>(ref Unsafe.Add(ref xRef, index + 16)); |
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Vector256<uint> x3 = Unsafe.As<uint, Vector256<uint>>(ref Unsafe.Add(ref xRef, index + 24)); |
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Vector256<uint> y0 = Unsafe.As<uint, Vector256<uint>>(ref Unsafe.Add(ref yRef, index)); |
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Vector256<uint> y1 = Unsafe.As<uint, Vector256<uint>>(ref Unsafe.Add(ref yRef, index + 8)); |
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Vector256<uint> y2 = Unsafe.As<uint, Vector256<uint>>(ref Unsafe.Add(ref yRef, index + 16)); |
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Vector256<uint> y3 = Unsafe.As<uint, Vector256<uint>>(ref Unsafe.Add(ref yRef, index + 24)); |
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Unsafe.As<uint, Vector256<uint>>(ref Unsafe.Add(ref destinationRef, index)) = Avx2.Add(x0, y0); |
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Unsafe.As<uint, Vector256<uint>>(ref Unsafe.Add(ref destinationRef, index + 8)) = Avx2.Add(x1, y1); |
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Unsafe.As<uint, Vector256<uint>>(ref Unsafe.Add(ref destinationRef, index + 16)) = Avx2.Add(x2, y2); |
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Unsafe.As<uint, Vector256<uint>>(ref Unsafe.Add(ref destinationRef, index + 24)) = Avx2.Add(x3, y3); |
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index += 32; |
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} |
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while (index <= (uint)x.Length - 32); |
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for (int i = (int)index; i < x.Length; i++) |
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{ |
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destination[i] = x[i] + y[i]; |
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} |
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} |
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} |
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public class TensorPrimitivesByteAssemblyComparison |
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{ |
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private byte[] x = null!; |
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private byte[] y = null!; |
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private byte[] legacyDestination = null!; |
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private byte[] tensorDestination = null!; |
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/// <summary>
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/// Creates deterministic byte inputs and independent destinations.
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/// </summary>
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[GlobalSetup] |
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public void Setup() |
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{ |
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this.x = new byte[2048]; |
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this.y = new byte[2048]; |
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this.legacyDestination = new byte[2048]; |
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this.tensorDestination = new byte[2048]; |
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for (int i = 0; i < this.x.Length; i++) |
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{ |
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this.x[i] = (byte)((i * 17) + 31); |
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this.y[i] = (byte)((i * 29) + 7); |
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} |
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} |
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/// <summary>
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/// Adds bytes with the retired WebP AVX2 pipeline.
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/// </summary>
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/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
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[Benchmark(Baseline = true)] |
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public byte Legacy() |
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{ |
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LegacyAdd(this.x, this.y, this.legacyDestination); |
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return this.legacyDestination[0]; |
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} |
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/// <summary>
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/// Adds bytes with the tensor compatibility pipeline.
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/// </summary>
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/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
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[Benchmark] |
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public byte Tensor() |
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{ |
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TensorPrimitives_.Add<byte>(this.x, this.y, this.tensorDestination); |
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return this.tensorDestination[0]; |
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} |
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/// <summary>
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/// Reproduces the retired WebP byte addition loop for assembly comparison.
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/// </summary>
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/// <param name="x">The first input.</param>
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/// <param name="y">The second input.</param>
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/// <param name="destination">The destination receiving modulo-256 sums.</param>
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[MethodImpl(MethodImplOptions.AggressiveInlining)] |
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private static void LegacyAdd(ReadOnlySpan<byte> x, ReadOnlySpan<byte> y, Span<byte> destination) |
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|
{ |
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ref byte xRef = ref MemoryMarshal.GetReference(x); |
||||
|
ref byte yRef = ref MemoryMarshal.GetReference(y); |
||||
|
ref byte destinationRef = ref MemoryMarshal.GetReference(destination); |
||||
|
|
||||
|
nuint i; |
||||
|
int maxPosition = x.Length & ~31; |
||||
|
|
||||
|
for (i = 0; i < (uint)maxPosition; i += 32) |
||||
|
{ |
||||
|
Vector256<int> x0 = Unsafe.As<byte, Vector256<int>>(ref Unsafe.Add(ref xRef, i)); |
||||
|
Vector256<int> y0 = Unsafe.As<byte, Vector256<int>>(ref Unsafe.Add(ref yRef, i)); |
||||
|
Vector256<byte> result = x0.AsByte() + y0.AsByte(); |
||||
|
Unsafe.As<byte, Vector256<byte>>(ref Unsafe.Add(ref destinationRef, i)) = result; |
||||
|
} |
||||
|
|
||||
|
for (; i < (uint)x.Length; i++) |
||||
|
{ |
||||
|
Unsafe.Add(ref destinationRef, i) = (byte)(Unsafe.Add(ref xRef, i) + Unsafe.Add(ref yRef, i)); |
||||
|
} |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
public class TensorPrimitivesSingleAddAssemblyComparison |
||||
|
{ |
||||
|
private float[] legacyTarget = null!; |
||||
|
private float[] tensorTarget = null!; |
||||
|
private float[] source = null!; |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Creates deterministic JPEG row inputs.
|
||||
|
/// </summary>
|
||||
|
[GlobalSetup] |
||||
|
public void Setup() |
||||
|
{ |
||||
|
this.legacyTarget = new float[2048]; |
||||
|
this.tensorTarget = new float[2048]; |
||||
|
this.source = new float[2048]; |
||||
|
|
||||
|
for (int i = 0; i < this.source.Length; i++) |
||||
|
{ |
||||
|
float value = ((i * 17) % 251) + 1; |
||||
|
this.legacyTarget[i] = value; |
||||
|
this.tensorTarget[i] = value; |
||||
|
this.source[i] = ((i * 29) % 31) - 15; |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Adds JPEG row values with the retired AVX pipeline.
|
||||
|
/// </summary>
|
||||
|
/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
|
||||
|
[Benchmark(Baseline = true)] |
||||
|
public float Legacy() |
||||
|
{ |
||||
|
LegacyAdd(this.legacyTarget, this.source); |
||||
|
return this.legacyTarget[0]; |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Adds JPEG row values with the tensor compatibility pipeline.
|
||||
|
/// </summary>
|
||||
|
/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
|
||||
|
[Benchmark] |
||||
|
public float Tensor() |
||||
|
{ |
||||
|
TensorPrimitives_.Add<float>(this.tensorTarget, this.source, this.tensorTarget); |
||||
|
return this.tensorTarget[0]; |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Reproduces the retired JPEG row addition loop for assembly comparison.
|
||||
|
/// </summary>
|
||||
|
/// <param name="target">The destination row.</param>
|
||||
|
/// <param name="source">The row added to the destination.</param>
|
||||
|
[MethodImpl(MethodImplOptions.AggressiveInlining)] |
||||
|
private static void LegacyAdd(Span<float> target, ReadOnlySpan<float> source) |
||||
|
{ |
||||
|
ref Vector256<float> targetVector = ref Unsafe.As<float, Vector256<float>>(ref MemoryMarshal.GetReference(target)); |
||||
|
ref Vector256<float> sourceVector = ref Unsafe.As<float, Vector256<float>>(ref MemoryMarshal.GetReference(source)); |
||||
|
nuint count = (uint)source.Length / (uint)Vector256<float>.Count; |
||||
|
|
||||
|
for (nuint i = 0; i < count; i++) |
||||
|
{ |
||||
|
Unsafe.Add(ref targetVector, i) = Avx.Add(Unsafe.Add(ref targetVector, i), Unsafe.Add(ref sourceVector, i)); |
||||
|
} |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
[GenericTypeArguments(typeof(byte))] |
||||
|
[GenericTypeArguments(typeof(uint))] |
||||
|
[GenericTypeArguments(typeof(int))] |
||||
|
[GenericTypeArguments(typeof(float))] |
||||
|
[GenericTypeArguments(typeof(double))] |
||||
|
public class TensorPrimitivesClampAssemblyComparison<T> |
||||
|
where T : unmanaged, INumber<T> |
||||
|
{ |
||||
|
private T[] legacyValues = null!; |
||||
|
private T[] tensorValues = null!; |
||||
|
private T min; |
||||
|
private T max; |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Creates deterministic clamp inputs for the current element type.
|
||||
|
/// </summary>
|
||||
|
[GlobalSetup] |
||||
|
public void Setup() |
||||
|
{ |
||||
|
this.legacyValues = new T[2048]; |
||||
|
this.tensorValues = new T[2048]; |
||||
|
this.min = T.CreateTruncating(64); |
||||
|
this.max = T.CreateTruncating(128); |
||||
|
|
||||
|
for (int i = 0; i < this.legacyValues.Length; i++) |
||||
|
{ |
||||
|
T value = T.CreateTruncating((i * 31) % 257); |
||||
|
this.legacyValues[i] = value; |
||||
|
this.tensorValues[i] = value; |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Clamps values with the retired <see cref="Vector{T}"/> pipeline.
|
||||
|
/// </summary>
|
||||
|
/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
|
||||
|
[Benchmark(Baseline = true)] |
||||
|
public T Legacy() |
||||
|
{ |
||||
|
LegacyClamp(this.legacyValues, this.min, this.max); |
||||
|
return this.legacyValues[0]; |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Clamps values with the tensor compatibility pipeline.
|
||||
|
/// </summary>
|
||||
|
/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
|
||||
|
[Benchmark] |
||||
|
public T Tensor() |
||||
|
{ |
||||
|
TensorPrimitives_.Clamp(this.tensorValues, this.min, this.max, this.tensorValues); |
||||
|
return this.tensorValues[0]; |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Reproduces the retired clamp pipeline for assembly comparison.
|
||||
|
/// </summary>
|
||||
|
/// <param name="span">The values to clamp.</param>
|
||||
|
/// <param name="min">The inclusive lower bound.</param>
|
||||
|
/// <param name="max">The inclusive upper bound.</param>
|
||||
|
[MethodImpl(MethodImplOptions.AggressiveInlining)] |
||||
|
private static void LegacyClamp(Span<T> span, T min, T max) |
||||
|
{ |
||||
|
int remainder = Numerics.ModuloP2(span.Length, Vector<T>.Count); |
||||
|
int adjustedCount = span.Length - remainder; |
||||
|
|
||||
|
if (adjustedCount > 0) |
||||
|
{ |
||||
|
Vector<T> vectorMin = new(min); |
||||
|
Vector<T> vectorMax = new(max); |
||||
|
nint vectorCount = (nint)(uint)adjustedCount / Vector<T>.Count; |
||||
|
nint remainingVectors = Numerics.Modulo4(vectorCount); |
||||
|
nint unrolledVectors = vectorCount - remainingVectors; |
||||
|
|
||||
|
ref Vector<T> current0 = ref Unsafe.As<T, Vector<T>>(ref MemoryMarshal.GetReference(span)); |
||||
|
ref Vector<T> current1 = ref Unsafe.Add(ref current0, 1); |
||||
|
ref Vector<T> current2 = ref Unsafe.Add(ref current0, 2); |
||||
|
ref Vector<T> current3 = ref Unsafe.Add(ref current0, 3); |
||||
|
ref Vector<T> end = ref Unsafe.Add(ref current0, unrolledVectors); |
||||
|
|
||||
|
while (Unsafe.IsAddressLessThan(ref current0, ref end)) |
||||
|
{ |
||||
|
current0 = Vector.Min(Vector.Max(vectorMin, current0), vectorMax); |
||||
|
current1 = Vector.Min(Vector.Max(vectorMin, current1), vectorMax); |
||||
|
current2 = Vector.Min(Vector.Max(vectorMin, current2), vectorMax); |
||||
|
current3 = Vector.Min(Vector.Max(vectorMin, current3), vectorMax); |
||||
|
|
||||
|
current0 = ref Unsafe.Add(ref current0, 4); |
||||
|
current1 = ref Unsafe.Add(ref current1, 4); |
||||
|
current2 = ref Unsafe.Add(ref current2, 4); |
||||
|
current3 = ref Unsafe.Add(ref current3, 4); |
||||
|
} |
||||
|
|
||||
|
if (remainingVectors > 0) |
||||
|
{ |
||||
|
current0 = ref end; |
||||
|
end = ref Unsafe.Add(ref end, remainingVectors); |
||||
|
|
||||
|
while (Unsafe.IsAddressLessThan(ref current0, ref end)) |
||||
|
{ |
||||
|
current0 = Vector.Min(Vector.Max(vectorMin, current0), vectorMax); |
||||
|
current0 = ref Unsafe.Add(ref current0, 1); |
||||
|
} |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
for (int i = adjustedCount; i < span.Length; i++) |
||||
|
{ |
||||
|
T value = span[i]; |
||||
|
span[i] = value > max ? max : value < min ? min : value; |
||||
|
} |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
public class TensorPrimitivesIccMaxAssemblyComparison |
||||
|
{ |
||||
|
private Vector4[] legacyValues = null!; |
||||
|
private Vector4[] tensorValues = null!; |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Creates deterministic ICC values containing positive and negative channels.
|
||||
|
/// </summary>
|
||||
|
[GlobalSetup] |
||||
|
public void Setup() |
||||
|
{ |
||||
|
this.legacyValues = new Vector4[512]; |
||||
|
this.tensorValues = new Vector4[512]; |
||||
|
|
||||
|
for (int i = 0; i < this.legacyValues.Length; i++) |
||||
|
{ |
||||
|
float value = ((i * 17) % 251) - 125; |
||||
|
Vector4 vector = new(value, value + 1, value - 1, value + 2); |
||||
|
this.legacyValues[i] = vector; |
||||
|
this.tensorValues[i] = vector; |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Clips negative channels with the retired ICC pipeline.
|
||||
|
/// </summary>
|
||||
|
/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
|
||||
|
[Benchmark(Baseline = true)] |
||||
|
public float Legacy() |
||||
|
{ |
||||
|
for (int i = 0; i < this.legacyValues.Length; i++) |
||||
|
{ |
||||
|
this.legacyValues[i] = Vector4.Max(this.legacyValues[i], Vector4.Zero); |
||||
|
} |
||||
|
|
||||
|
return this.legacyValues[0].X; |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Clips negative channels with the tensor compatibility pipeline.
|
||||
|
/// </summary>
|
||||
|
/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
|
||||
|
[Benchmark] |
||||
|
public float Tensor() |
||||
|
{ |
||||
|
Span<float> values = MemoryMarshal.Cast<Vector4, float>(this.tensorValues.AsSpan()); |
||||
|
TensorPrimitives_.Max(values, 0F, values); |
||||
|
return values[0]; |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
public class TensorPrimitivesIccMultiplyAssemblyComparison |
||||
|
{ |
||||
|
private readonly float multiplier = 65280F / 65535F; |
||||
|
private Vector4[] source = null!; |
||||
|
private Vector4[] legacyDestination = null!; |
||||
|
private Vector4[] tensorDestination = null!; |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Creates deterministic ICC inputs and independent destinations.
|
||||
|
/// </summary>
|
||||
|
[GlobalSetup] |
||||
|
public void Setup() |
||||
|
{ |
||||
|
this.source = new Vector4[512]; |
||||
|
this.legacyDestination = new Vector4[512]; |
||||
|
this.tensorDestination = new Vector4[512]; |
||||
|
|
||||
|
for (int i = 0; i < this.source.Length; i++) |
||||
|
{ |
||||
|
float value = ((i * 17) % 251) + 1; |
||||
|
this.source[i] = new Vector4(value, value + 1, value + 2, value + 3); |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Multiplies ICC channels with the retired <see cref="Vector{T}"/> pipeline.
|
||||
|
/// </summary>
|
||||
|
/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
|
||||
|
[Benchmark(Baseline = true)] |
||||
|
public float Legacy() |
||||
|
{ |
||||
|
Span<float> source = MemoryMarshal.Cast<Vector4, float>(this.source.AsSpan()); |
||||
|
Span<float> destination = MemoryMarshal.Cast<Vector4, float>(this.legacyDestination.AsSpan()); |
||||
|
ref Vector<float> sourceVector = ref Unsafe.As<float, Vector<float>>(ref MemoryMarshal.GetReference(source)); |
||||
|
ref Vector<float> destinationVector = ref Unsafe.As<float, Vector<float>>(ref MemoryMarshal.GetReference(destination)); |
||||
|
Vector<float> scale = new(this.multiplier); |
||||
|
nuint count = (uint)source.Length / (uint)Vector<float>.Count; |
||||
|
|
||||
|
for (nuint i = 0; i < count; i++) |
||||
|
{ |
||||
|
Unsafe.Add(ref destinationVector, i) = Unsafe.Add(ref sourceVector, i) * scale; |
||||
|
} |
||||
|
|
||||
|
return destination[0]; |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Multiplies ICC channels with the tensor compatibility pipeline.
|
||||
|
/// </summary>
|
||||
|
/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
|
||||
|
[Benchmark] |
||||
|
public float Tensor() |
||||
|
{ |
||||
|
Span<float> source = MemoryMarshal.Cast<Vector4, float>(this.source.AsSpan()); |
||||
|
Span<float> destination = MemoryMarshal.Cast<Vector4, float>(this.tensorDestination.AsSpan()); |
||||
|
TensorPrimitives_.Multiply(source, this.multiplier, destination); |
||||
|
return destination[0]; |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
#if NET10_0_OR_GREATER
|
||||
|
[GenericTypeArguments(typeof(byte))] |
||||
|
[GenericTypeArguments(typeof(uint))] |
||||
|
[GenericTypeArguments(typeof(float))] |
||||
|
public class TensorPrimitivesRuntimeAddAssemblyComparison<T> |
||||
|
where T : unmanaged, INumber<T> |
||||
|
{ |
||||
|
private T[] x = null!; |
||||
|
private T[] y = null!; |
||||
|
private T[] compatibilityDestination = null!; |
||||
|
private T[] runtimeDestination = null!; |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Creates deterministic inputs and independent destinations.
|
||||
|
/// </summary>
|
||||
|
[GlobalSetup] |
||||
|
public void Setup() |
||||
|
{ |
||||
|
this.x = new T[2048]; |
||||
|
this.y = new T[2048]; |
||||
|
this.compatibilityDestination = new T[2048]; |
||||
|
this.runtimeDestination = new T[2048]; |
||||
|
|
||||
|
for (int i = 0; i < this.x.Length; i++) |
||||
|
{ |
||||
|
this.x[i] = T.CreateTruncating((i * 17) + 31); |
||||
|
this.y[i] = T.CreateTruncating((i * 29) + 7); |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Adds values with the compatibility implementation.
|
||||
|
/// </summary>
|
||||
|
/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
|
||||
|
[Benchmark(Baseline = true)] |
||||
|
public T Compatibility() |
||||
|
{ |
||||
|
TensorPrimitives_.Add<T>(this.x, this.y, this.compatibilityDestination); |
||||
|
return this.compatibilityDestination[0]; |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Adds values with the .NET runtime implementation.
|
||||
|
/// </summary>
|
||||
|
/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
|
||||
|
[Benchmark] |
||||
|
public T Runtime() |
||||
|
{ |
||||
|
System.Numerics.Tensors.TensorPrimitives.Add<T>(this.x, this.y, this.runtimeDestination); |
||||
|
return this.runtimeDestination[0]; |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
[GenericTypeArguments(typeof(byte))] |
||||
|
[GenericTypeArguments(typeof(uint))] |
||||
|
[GenericTypeArguments(typeof(int))] |
||||
|
[GenericTypeArguments(typeof(float))] |
||||
|
[GenericTypeArguments(typeof(double))] |
||||
|
public class TensorPrimitivesRuntimeClampAssemblyComparison<T> |
||||
|
where T : unmanaged, INumber<T> |
||||
|
{ |
||||
|
private T[] compatibilityValues = null!; |
||||
|
private T[] runtimeValues = null!; |
||||
|
private T min; |
||||
|
private T max; |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Creates deterministic inputs for both implementations.
|
||||
|
/// </summary>
|
||||
|
[GlobalSetup] |
||||
|
public void Setup() |
||||
|
{ |
||||
|
this.compatibilityValues = new T[2048]; |
||||
|
this.runtimeValues = new T[2048]; |
||||
|
this.min = T.CreateTruncating(64); |
||||
|
this.max = T.CreateTruncating(128); |
||||
|
|
||||
|
for (int i = 0; i < this.compatibilityValues.Length; i++) |
||||
|
{ |
||||
|
T value = T.CreateTruncating((i * 31) % 257); |
||||
|
this.compatibilityValues[i] = value; |
||||
|
this.runtimeValues[i] = value; |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Clamps values with the compatibility implementation.
|
||||
|
/// </summary>
|
||||
|
/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
|
||||
|
[Benchmark(Baseline = true)] |
||||
|
public T Compatibility() |
||||
|
{ |
||||
|
TensorPrimitives_.Clamp(this.compatibilityValues, this.min, this.max, this.compatibilityValues); |
||||
|
return this.compatibilityValues[0]; |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Clamps values with the .NET runtime implementation.
|
||||
|
/// </summary>
|
||||
|
/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
|
||||
|
[Benchmark] |
||||
|
public T Runtime() |
||||
|
{ |
||||
|
System.Numerics.Tensors.TensorPrimitives.Clamp(this.runtimeValues, this.min, this.max, this.runtimeValues); |
||||
|
return this.runtimeValues[0]; |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
public class TensorPrimitivesRuntimeSingleScalarAssemblyComparison |
||||
|
{ |
||||
|
private readonly float scalar = -1F; |
||||
|
private float[] compatibilityValues = null!; |
||||
|
private float[] runtimeValues = null!; |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Creates equivalent stable inputs for both implementations.
|
||||
|
/// </summary>
|
||||
|
[GlobalSetup] |
||||
|
public void Setup() |
||||
|
{ |
||||
|
this.compatibilityValues = new float[2048]; |
||||
|
this.runtimeValues = new float[2048]; |
||||
|
|
||||
|
for (int i = 0; i < this.compatibilityValues.Length; i++) |
||||
|
{ |
||||
|
float value = ((i * 17) % 251) + 1; |
||||
|
this.compatibilityValues[i] = value; |
||||
|
this.runtimeValues[i] = value; |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Divides values with the compatibility implementation.
|
||||
|
/// </summary>
|
||||
|
/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
|
||||
|
[Benchmark] |
||||
|
public float CompatibilityDivide() |
||||
|
{ |
||||
|
TensorPrimitives_.Divide(this.compatibilityValues, this.scalar, this.compatibilityValues); |
||||
|
return this.compatibilityValues[0]; |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Divides values with the .NET runtime implementation.
|
||||
|
/// </summary>
|
||||
|
/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
|
||||
|
[Benchmark] |
||||
|
public float RuntimeDivide() |
||||
|
{ |
||||
|
System.Numerics.Tensors.TensorPrimitives.Divide(this.runtimeValues, this.scalar, this.runtimeValues); |
||||
|
return this.runtimeValues[0]; |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Computes maximum values with the compatibility implementation.
|
||||
|
/// </summary>
|
||||
|
/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
|
||||
|
[Benchmark] |
||||
|
public float CompatibilityMax() |
||||
|
{ |
||||
|
TensorPrimitives_.Max(this.compatibilityValues, 0F, this.compatibilityValues); |
||||
|
return this.compatibilityValues[0]; |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Computes maximum values with the .NET runtime implementation.
|
||||
|
/// </summary>
|
||||
|
/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
|
||||
|
[Benchmark] |
||||
|
public float RuntimeMax() |
||||
|
{ |
||||
|
System.Numerics.Tensors.TensorPrimitives.Max(this.runtimeValues, 0F, this.runtimeValues); |
||||
|
return this.runtimeValues[0]; |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Multiplies values with the compatibility implementation.
|
||||
|
/// </summary>
|
||||
|
/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
|
||||
|
[Benchmark] |
||||
|
public float CompatibilityMultiply() |
||||
|
{ |
||||
|
TensorPrimitives_.Multiply(this.compatibilityValues, this.scalar, this.compatibilityValues); |
||||
|
return this.compatibilityValues[0]; |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Multiplies values with the .NET runtime implementation.
|
||||
|
/// </summary>
|
||||
|
/// <returns>The first result, which keeps the writes observable to the benchmark harness.</returns>
|
||||
|
[Benchmark] |
||||
|
public float RuntimeMultiply() |
||||
|
{ |
||||
|
System.Numerics.Tensors.TensorPrimitives.Multiply(this.runtimeValues, this.scalar, this.runtimeValues); |
||||
|
return this.runtimeValues[0]; |
||||
|
} |
||||
|
} |
||||
|
#endif
|
||||
@ -0,0 +1,356 @@ |
|||||
|
// Copyright (c) Six Labors.
|
||||
|
// Licensed under the Six Labors Split License.
|
||||
|
|
||||
|
using SixLabors.ImageSharp.Common.Helpers; |
||||
|
|
||||
|
namespace SixLabors.ImageSharp.Tests.Common; |
||||
|
|
||||
|
public class TensorPrimitivesTests |
||||
|
{ |
||||
|
/// <summary>
|
||||
|
/// Gets lengths that exercise scalar execution, every SIMD width, overlapping tails, and the unrolled loop.
|
||||
|
/// </summary>
|
||||
|
public static TheoryData<int> SpanLengths => new() |
||||
|
{ |
||||
|
0, |
||||
|
1, |
||||
|
3, |
||||
|
4, |
||||
|
5, |
||||
|
7, |
||||
|
8, |
||||
|
9, |
||||
|
15, |
||||
|
16, |
||||
|
17, |
||||
|
31, |
||||
|
32, |
||||
|
33, |
||||
|
63, |
||||
|
64, |
||||
|
65, |
||||
|
127, |
||||
|
128, |
||||
|
129, |
||||
|
2048 |
||||
|
}; |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Verifies that byte addition wraps modulo 256 and supports either input as the in-place destination.
|
||||
|
/// </summary>
|
||||
|
/// <param name="length">The input length.</param>
|
||||
|
[Theory] |
||||
|
[MemberData(nameof(SpanLengths))] |
||||
|
public void AddByteMatchesScalarFormula(int length) |
||||
|
{ |
||||
|
byte[] x = new byte[length]; |
||||
|
byte[] y = new byte[length]; |
||||
|
byte[] expected = new byte[length]; |
||||
|
|
||||
|
for (int i = 0; i < length; i++) |
||||
|
{ |
||||
|
x[i] = (byte)((i * 23) + 197); |
||||
|
y[i] = (byte)((i * 41) + 113); |
||||
|
expected[i] = unchecked((byte)(x[i] + y[i])); |
||||
|
} |
||||
|
|
||||
|
byte[] destination = new byte[length]; |
||||
|
TensorPrimitives_.Add<byte>(x, y, destination); |
||||
|
Assert.Equal(expected, destination); |
||||
|
|
||||
|
byte[] xInPlace = (byte[])x.Clone(); |
||||
|
TensorPrimitives_.Add<byte>(xInPlace, y, xInPlace); |
||||
|
Assert.Equal(expected, xInPlace); |
||||
|
|
||||
|
byte[] yInPlace = (byte[])y.Clone(); |
||||
|
TensorPrimitives_.Add<byte>(x, yInPlace, yInPlace); |
||||
|
Assert.Equal(expected, yInPlace); |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Verifies that unsigned integer addition preserves unchecked histogram accumulation semantics.
|
||||
|
/// </summary>
|
||||
|
/// <param name="length">The input length.</param>
|
||||
|
[Theory] |
||||
|
[MemberData(nameof(SpanLengths))] |
||||
|
public void AddUInt32MatchesScalarFormula(int length) |
||||
|
{ |
||||
|
uint[] x = new uint[length]; |
||||
|
uint[] y = new uint[length]; |
||||
|
uint[] expected = new uint[length]; |
||||
|
|
||||
|
for (int i = 0; i < length; i++) |
||||
|
{ |
||||
|
x[i] = ((uint)i * 1_234_567U) + 0xF0000000U; |
||||
|
y[i] = ((uint)i * 7_654_321U) + 0x30000000U; |
||||
|
expected[i] = unchecked(x[i] + y[i]); |
||||
|
} |
||||
|
|
||||
|
TensorPrimitives_.Add<uint>(x, y, x); |
||||
|
Assert.Equal(expected, x); |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Verifies that integer clamping produces identical results for separate and in-place destinations.
|
||||
|
/// </summary>
|
||||
|
/// <param name="length">The input length.</param>
|
||||
|
[Theory] |
||||
|
[MemberData(nameof(SpanLengths))] |
||||
|
public void ClampInt32MatchesScalarFormula(int length) |
||||
|
{ |
||||
|
int[] source = new int[length]; |
||||
|
int[] expected = new int[length]; |
||||
|
|
||||
|
for (int i = 0; i < source.Length; i++) |
||||
|
{ |
||||
|
source[i] = ((i * 37) % 401) - 200; |
||||
|
expected[i] = Math.Clamp(source[i], -73, 91); |
||||
|
} |
||||
|
|
||||
|
int[] destination = new int[length]; |
||||
|
TensorPrimitives_.Clamp<int>(source, -73, 91, destination); |
||||
|
Assert.Equal(expected, destination); |
||||
|
|
||||
|
int[] inPlace = (int[])source.Clone(); |
||||
|
TensorPrimitives_.Clamp<int>(inPlace, -73, 91, inPlace); |
||||
|
Assert.Equal(expected, inPlace); |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Verifies that floating-point clamping matches the runtime tensor formula for special values and unordered bounds.
|
||||
|
/// </summary>
|
||||
|
/// <param name="length">The input length.</param>
|
||||
|
[Theory] |
||||
|
[MemberData(nameof(SpanLengths))] |
||||
|
public void ClampSingleMatchesRuntimeFormula(int length) |
||||
|
{ |
||||
|
float[] values = |
||||
|
{ |
||||
|
float.NaN, |
||||
|
-0F, |
||||
|
0F, |
||||
|
-1F, |
||||
|
1F, |
||||
|
float.NegativeInfinity, |
||||
|
float.PositiveInfinity |
||||
|
}; |
||||
|
|
||||
|
float[] source = new float[length]; |
||||
|
float[] expected = new float[length]; |
||||
|
|
||||
|
for (int i = 0; i < source.Length; i++) |
||||
|
{ |
||||
|
source[i] = values[i % values.Length]; |
||||
|
|
||||
|
// Runtime main follows Min(Max(x, min), max) for vectorizable types, including unordered bounds.
|
||||
|
expected[i] = float.Min(float.Max(source[i], 2F), -2F); |
||||
|
} |
||||
|
|
||||
|
TensorPrimitives_.Clamp<float>(source, 2F, -2F, source); |
||||
|
AssertSingleBitsEqual(expected, source); |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Verifies that single-precision clamping preserves the runtime's signed-zero and NaN behavior.
|
||||
|
/// </summary>
|
||||
|
[Fact] |
||||
|
public void ClampSinglePreservesRuntimeSpecialValueSemantics() |
||||
|
{ |
||||
|
float[] values = |
||||
|
{ |
||||
|
float.NaN, |
||||
|
float.NegativeInfinity, |
||||
|
-0F, |
||||
|
0F, |
||||
|
float.PositiveInfinity |
||||
|
}; |
||||
|
|
||||
|
float[] actual = new float[129]; |
||||
|
float[] expected = new float[actual.Length]; |
||||
|
|
||||
|
for (int i = 0; i < actual.Length; i++) |
||||
|
{ |
||||
|
actual[i] = values[i % values.Length]; |
||||
|
expected[i] = float.Min(float.Max(actual[i], -0F), 0F); |
||||
|
} |
||||
|
|
||||
|
TensorPrimitives_.Clamp<float>(actual, -0F, 0F, actual); |
||||
|
AssertSingleBitsEqual(expected, actual); |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Verifies that double-precision clamping preserves the runtime's signed-zero and NaN behavior.
|
||||
|
/// </summary>
|
||||
|
[Fact] |
||||
|
public void ClampDoublePreservesRuntimeSpecialValueSemantics() |
||||
|
{ |
||||
|
double[] values = |
||||
|
{ |
||||
|
double.NaN, |
||||
|
double.NegativeInfinity, |
||||
|
-0D, |
||||
|
0D, |
||||
|
double.PositiveInfinity |
||||
|
}; |
||||
|
|
||||
|
double[] actual = new double[65]; |
||||
|
double[] expected = new double[actual.Length]; |
||||
|
|
||||
|
for (int i = 0; i < actual.Length; i++) |
||||
|
{ |
||||
|
actual[i] = values[i % values.Length]; |
||||
|
expected[i] = double.Min(double.Max(actual[i], -0D), 0D); |
||||
|
} |
||||
|
|
||||
|
TensorPrimitives_.Clamp<double>(actual, -0D, 0D, actual); |
||||
|
AssertDoubleBitsEqual(expected, actual); |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Verifies that division produces identical results for separate and in-place destinations.
|
||||
|
/// </summary>
|
||||
|
/// <param name="length">The input length.</param>
|
||||
|
[Theory] |
||||
|
[MemberData(nameof(SpanLengths))] |
||||
|
public void DivideSingleMatchesScalarFormula(int length) |
||||
|
{ |
||||
|
float[] source = new float[length]; |
||||
|
float[] expected = new float[length]; |
||||
|
|
||||
|
for (int i = 0; i < source.Length; i++) |
||||
|
{ |
||||
|
source[i] = (i - 65.25F) * 1.75F; |
||||
|
expected[i] = source[i] / 3.25F; |
||||
|
} |
||||
|
|
||||
|
float[] destination = new float[length]; |
||||
|
TensorPrimitives_.Divide<float>(source, 3.25F, destination); |
||||
|
AssertSingleBitsEqual(expected, destination); |
||||
|
|
||||
|
float[] inPlace = (float[])source.Clone(); |
||||
|
TensorPrimitives_.Divide<float>(inPlace, 3.25F, inPlace); |
||||
|
AssertSingleBitsEqual(expected, inPlace); |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Verifies that maximum selection preserves the runtime's NaN and signed-zero semantics.
|
||||
|
/// </summary>
|
||||
|
/// <param name="length">The input length.</param>
|
||||
|
[Theory] |
||||
|
[MemberData(nameof(SpanLengths))] |
||||
|
public void MaxSingleMatchesRuntimeFormula(int length) |
||||
|
{ |
||||
|
float[] values = |
||||
|
{ |
||||
|
float.NaN, |
||||
|
float.NegativeInfinity, |
||||
|
-1F, |
||||
|
-0F, |
||||
|
0F, |
||||
|
1F, |
||||
|
float.PositiveInfinity |
||||
|
}; |
||||
|
|
||||
|
float[] actual = new float[length]; |
||||
|
float[] expected = new float[length]; |
||||
|
|
||||
|
for (int i = 0; i < length; i++) |
||||
|
{ |
||||
|
actual[i] = values[i % values.Length]; |
||||
|
expected[i] = float.Max(actual[i], -0F); |
||||
|
} |
||||
|
|
||||
|
TensorPrimitives_.Max<float>(actual, -0F, actual); |
||||
|
AssertSingleBitsEqual(expected, actual); |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Verifies that multiplication produces identical results for separate and in-place destinations.
|
||||
|
/// </summary>
|
||||
|
/// <param name="length">The input length.</param>
|
||||
|
[Theory] |
||||
|
[MemberData(nameof(SpanLengths))] |
||||
|
public void MultiplySingleMatchesScalarFormula(int length) |
||||
|
{ |
||||
|
float[] source = new float[length]; |
||||
|
float[] expected = new float[length]; |
||||
|
|
||||
|
for (int i = 0; i < source.Length; i++) |
||||
|
{ |
||||
|
source[i] = (i - 65.25F) * 1.75F; |
||||
|
expected[i] = source[i] * 0.375F; |
||||
|
} |
||||
|
|
||||
|
float[] destination = new float[length]; |
||||
|
TensorPrimitives_.Multiply<float>(source, 0.375F, destination); |
||||
|
AssertSingleBitsEqual(expected, destination); |
||||
|
|
||||
|
TensorPrimitives_.Multiply<float>(source, 0.375F, source); |
||||
|
AssertSingleBitsEqual(expected, source); |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Verifies that the normalization compatibility call preserves its element-wise division contract.
|
||||
|
/// </summary>
|
||||
|
/// <param name="length">The input length.</param>
|
||||
|
[Theory] |
||||
|
[MemberData(nameof(SpanLengths))] |
||||
|
public void NormalizeMatchesScalarFormula(int length) |
||||
|
{ |
||||
|
float[] actual = new float[length]; |
||||
|
float[] expected = new float[length]; |
||||
|
|
||||
|
for (int i = 0; i < actual.Length; i++) |
||||
|
{ |
||||
|
actual[i] = (i + 1) * 0.125F; |
||||
|
expected[i] = actual[i] / 7.5F; |
||||
|
} |
||||
|
|
||||
|
Numerics.Normalize(actual, 7.5F); |
||||
|
AssertSingleBitsEqual(expected, actual); |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Compares floating-point results while preserving signed-zero behavior.
|
||||
|
/// </summary>
|
||||
|
/// <param name="expected">The expected values.</param>
|
||||
|
/// <param name="actual">The actual values.</param>
|
||||
|
private static void AssertSingleBitsEqual(ReadOnlySpan<float> expected, ReadOnlySpan<float> actual) |
||||
|
{ |
||||
|
Assert.Equal(expected.Length, actual.Length); |
||||
|
|
||||
|
for (int i = 0; i < expected.Length; i++) |
||||
|
{ |
||||
|
if (float.IsNaN(expected[i])) |
||||
|
{ |
||||
|
Assert.True(float.IsNaN(actual[i])); |
||||
|
} |
||||
|
else |
||||
|
{ |
||||
|
Assert.Equal(BitConverter.SingleToInt32Bits(expected[i]), BitConverter.SingleToInt32Bits(actual[i])); |
||||
|
} |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Compares double-precision results while preserving signed-zero behavior.
|
||||
|
/// </summary>
|
||||
|
/// <param name="expected">The expected values.</param>
|
||||
|
/// <param name="actual">The actual values.</param>
|
||||
|
private static void AssertDoubleBitsEqual(ReadOnlySpan<double> expected, ReadOnlySpan<double> actual) |
||||
|
{ |
||||
|
Assert.Equal(expected.Length, actual.Length); |
||||
|
|
||||
|
for (int i = 0; i < expected.Length; i++) |
||||
|
{ |
||||
|
if (double.IsNaN(expected[i])) |
||||
|
{ |
||||
|
Assert.True(double.IsNaN(actual[i])); |
||||
|
} |
||||
|
else |
||||
|
{ |
||||
|
Assert.Equal(BitConverter.DoubleToInt64Bits(expected[i]), BitConverter.DoubleToInt64Bits(actual[i])); |
||||
|
} |
||||
|
} |
||||
|
} |
||||
|
} |
||||
Loading…
Reference in new issue