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Add TensorPrimitives.Max/MinNumber (dotnet#101435)
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* Add TensorPrimitives.Max/MinNumber

* Address PR feedback plus some cleanup
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stephentoub authored and matouskozak committed Apr 30, 2024
1 parent 0f4afbc commit c6cb51f
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Showing 7 changed files with 340 additions and 90 deletions.
Original file line number Diff line number Diff line change
Expand Up @@ -89,12 +89,18 @@ public static partial class TensorPrimitives
public static T Max<T>(System.ReadOnlySpan<T> x) where T : System.Numerics.INumber<T> { throw null; }
public static void Max<T>(System.ReadOnlySpan<T> x, System.ReadOnlySpan<T> y, System.Span<T> destination) where T : System.Numerics.INumber<T> { }
public static void Max<T>(System.ReadOnlySpan<T> x, T y, System.Span<T> destination) where T : System.Numerics.INumber<T> { }
public static T MaxNumber<T>(System.ReadOnlySpan<T> x) where T : System.Numerics.INumber<T> { throw null; }
public static void MaxNumber<T>(System.ReadOnlySpan<T> x, System.ReadOnlySpan<T> y, System.Span<T> destination) where T : System.Numerics.INumber<T> { }
public static void MaxNumber<T>(System.ReadOnlySpan<T> x, T y, System.Span<T> destination) where T : System.Numerics.INumber<T> { }
public static T MinMagnitude<T>(System.ReadOnlySpan<T> x) where T : System.Numerics.INumberBase<T> { throw null; }
public static void MinMagnitude<T>(System.ReadOnlySpan<T> x, System.ReadOnlySpan<T> y, System.Span<T> destination) where T : System.Numerics.INumberBase<T> { }
public static void MinMagnitude<T>(System.ReadOnlySpan<T> x, T y, System.Span<T> destination) where T : System.Numerics.INumberBase<T> { }
public static T Min<T>(System.ReadOnlySpan<T> x) where T : System.Numerics.INumber<T> { throw null; }
public static void Min<T>(System.ReadOnlySpan<T> x, System.ReadOnlySpan<T> y, System.Span<T> destination) where T : System.Numerics.INumber<T> { }
public static void Min<T>(System.ReadOnlySpan<T> x, T y, System.Span<T> destination) where T : System.Numerics.INumber<T> { }
public static T MinNumber<T>(System.ReadOnlySpan<T> x) where T : System.Numerics.INumber<T> { throw null; }
public static void MinNumber<T>(System.ReadOnlySpan<T> x, System.ReadOnlySpan<T> y, System.Span<T> destination) where T : System.Numerics.INumber<T> { }
public static void MinNumber<T>(System.ReadOnlySpan<T> x, T y, System.Span<T> destination) where T : System.Numerics.INumber<T> { }
public static void MultiplyAdd<T>(System.ReadOnlySpan<T> x, System.ReadOnlySpan<T> y, System.ReadOnlySpan<T> addend, System.Span<T> destination) where T : System.Numerics.IAdditionOperators<T, T, T>, System.Numerics.IMultiplyOperators<T, T, T> { }
public static void MultiplyAdd<T>(System.ReadOnlySpan<T> x, System.ReadOnlySpan<T> y, T addend, System.Span<T> destination) where T : System.Numerics.IAdditionOperators<T, T, T>, System.Numerics.IMultiplyOperators<T, T, T> { }
public static void MultiplyAdd<T>(System.ReadOnlySpan<T> x, T y, System.ReadOnlySpan<T> addend, System.Span<T> destination) where T : System.Numerics.IAdditionOperators<T, T, T>, System.Numerics.IMultiplyOperators<T, T, T> { }
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
<Project Sdk="Microsoft.NET.Sdk">
<Project Sdk="Microsoft.NET.Sdk">

<PropertyGroup>
<TargetFrameworks>$(NetCoreAppCurrent);$(NetCoreAppPrevious);$(NetCoreAppMinimum);netstandard2.0;$(NetFrameworkMinimum)</TargetFrameworks>
Expand Down Expand Up @@ -82,8 +82,10 @@
<Compile Include="System\Numerics\Tensors\netcore\TensorPrimitives.LogP1.cs" />
<Compile Include="System\Numerics\Tensors\netcore\TensorPrimitives.Max.cs" />
<Compile Include="System\Numerics\Tensors\netcore\TensorPrimitives.MaxMagnitude.cs" />
<Compile Include="System\Numerics\Tensors\netcore\TensorPrimitives.MaxNumber.cs" />
<Compile Include="System\Numerics\Tensors\netcore\TensorPrimitives.Min.cs" />
<Compile Include="System\Numerics\Tensors\netcore\TensorPrimitives.MinMagnitude.cs" />
<Compile Include="System\Numerics\Tensors\netcore\TensorPrimitives.MinNumber.cs" />
<Compile Include="System\Numerics\Tensors\netcore\TensorPrimitives.Multiply.cs" />
<Compile Include="System\Numerics\Tensors\netcore\TensorPrimitives.MultiplyAdd.cs" />
<Compile Include="System\Numerics\Tensors\netcore\TensorPrimitives.MultiplyAddEstimate.cs" />
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Original file line number Diff line number Diff line change
Expand Up @@ -96,35 +96,21 @@ public static T Invoke(T x, T y)
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static Vector128<T> Invoke(Vector128<T> x, Vector128<T> y)
{
if (AdvSimd.IsSupported)
{
if (typeof(T) == typeof(byte)) return AdvSimd.Max(x.AsByte(), y.AsByte()).As<byte, T>();
if (typeof(T) == typeof(sbyte)) return AdvSimd.Max(x.AsSByte(), y.AsSByte()).As<sbyte, T>();
if (typeof(T) == typeof(short)) return AdvSimd.Max(x.AsInt16(), y.AsInt16()).As<short, T>();
if (typeof(T) == typeof(ushort)) return AdvSimd.Max(x.AsUInt16(), y.AsUInt16()).As<ushort, T>();
if (typeof(T) == typeof(int)) return AdvSimd.Max(x.AsInt32(), y.AsInt32()).As<int, T>();
if (typeof(T) == typeof(uint)) return AdvSimd.Max(x.AsUInt32(), y.AsUInt32()).As<uint, T>();
if (typeof(T) == typeof(float)) return AdvSimd.Max(x.AsSingle(), y.AsSingle()).As<float, T>();
}

if (AdvSimd.Arm64.IsSupported)
if (typeof(T) == typeof(float) || typeof(T) == typeof(double))
{
if (typeof(T) == typeof(double)) return AdvSimd.Arm64.Max(x.AsDouble(), y.AsDouble()).As<double, T>();
}
if (AdvSimd.IsSupported && typeof(T) == typeof(float))
{
return AdvSimd.Max(x.AsSingle(), y.AsSingle()).As<float, T>();
}

if (typeof(T) == typeof(float))
{
return
Vector128.ConditionalSelect(Vector128.Equals(x, y),
Vector128.ConditionalSelect(IsNegative(x.AsSingle()).As<float, T>(), y, x),
Vector128.Max(x, y));
}
if (AdvSimd.Arm64.IsSupported && typeof(T) == typeof(double))
{
return AdvSimd.Arm64.Max(x.AsDouble(), y.AsDouble()).As<double, T>();
}

if (typeof(T) == typeof(double))
{
return
Vector128.ConditionalSelect(Vector128.Equals(x, y),
Vector128.ConditionalSelect(IsNegative(x.AsDouble()).As<double, T>(), y, x),
Vector128.ConditionalSelect(IsNegative(x), y, x),
Vector128.Max(x, y));
}

Expand All @@ -134,19 +120,11 @@ public static Vector128<T> Invoke(Vector128<T> x, Vector128<T> y)
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static Vector256<T> Invoke(Vector256<T> x, Vector256<T> y)
{
if (typeof(T) == typeof(float))
{
return
Vector256.ConditionalSelect(Vector256.Equals(x, y),
Vector256.ConditionalSelect(IsNegative(x.AsSingle()).As<float, T>(), y, x),
Vector256.Max(x, y));
}

if (typeof(T) == typeof(double))
if (typeof(T) == typeof(float) || typeof(T) == typeof(double))
{
return
Vector256.ConditionalSelect(Vector256.Equals(x, y),
Vector256.ConditionalSelect(IsNegative(x.AsDouble()).As<double, T>(), y, x),
Vector256.ConditionalSelect(IsNegative(x), y, x),
Vector256.Max(x, y));
}

Expand All @@ -156,19 +134,11 @@ public static Vector256<T> Invoke(Vector256<T> x, Vector256<T> y)
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static Vector512<T> Invoke(Vector512<T> x, Vector512<T> y)
{
if (typeof(T) == typeof(float))
{
return
Vector512.ConditionalSelect(Vector512.Equals(x, y),
Vector512.ConditionalSelect(IsNegative(x.AsSingle()).As<float, T>(), y, x),
Vector512.Max(x, y));
}

if (typeof(T) == typeof(double))
if (typeof(T) == typeof(float) || typeof(T) == typeof(double))
{
return
Vector512.ConditionalSelect(Vector512.Equals(x, y),
Vector512.ConditionalSelect(IsNegative(x.AsDouble()).As<double, T>(), y, x),
Vector512.ConditionalSelect(IsNegative(x), y, x),
Vector512.Max(x, y));
}

Expand All @@ -192,24 +162,18 @@ public static Vector512<T> Invoke(Vector512<T> x, Vector512<T> y)
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static Vector128<T> Invoke(Vector128<T> x, Vector128<T> y)
{
if (AdvSimd.IsSupported)
if (typeof(T) == typeof(float) || typeof(T) == typeof(double))
{
if (typeof(T) == typeof(byte)) return AdvSimd.Max(x.AsByte(), y.AsByte()).As<byte, T>();
if (typeof(T) == typeof(sbyte)) return AdvSimd.Max(x.AsSByte(), y.AsSByte()).As<sbyte, T>();
if (typeof(T) == typeof(ushort)) return AdvSimd.Max(x.AsUInt16(), y.AsUInt16()).As<ushort, T>();
if (typeof(T) == typeof(short)) return AdvSimd.Max(x.AsInt16(), y.AsInt16()).As<short, T>();
if (typeof(T) == typeof(uint)) return AdvSimd.Max(x.AsUInt32(), y.AsUInt32()).As<uint, T>();
if (typeof(T) == typeof(int)) return AdvSimd.Max(x.AsInt32(), y.AsInt32()).As<int, T>();
if (typeof(T) == typeof(float)) return AdvSimd.Max(x.AsSingle(), y.AsSingle()).As<float, T>();
}
if (AdvSimd.IsSupported && typeof(T) == typeof(float))
{
return AdvSimd.Max(x.AsSingle(), y.AsSingle()).As<float, T>();
}

if (AdvSimd.Arm64.IsSupported)
{
if (typeof(T) == typeof(double)) return AdvSimd.Arm64.Max(x.AsDouble(), y.AsDouble()).As<double, T>();
}
if (AdvSimd.Arm64.IsSupported && typeof(T) == typeof(double))
{
return AdvSimd.Arm64.Max(x.AsDouble(), y.AsDouble()).As<double, T>();
}

if (typeof(T) == typeof(float) || typeof(T) == typeof(double))
{
return
Vector128.ConditionalSelect(Vector128.Equals(x, x),
Vector128.ConditionalSelect(Vector128.Equals(y, y),
Expand Down
Original file line number Diff line number Diff line change
@@ -0,0 +1,142 @@
// Licensed to the .NET Foundation under one or more agreements.
// The .NET Foundation licenses this file to you under the MIT license.

using System.Runtime.CompilerServices;
using System.Runtime.InteropServices;
using System.Runtime.Intrinsics;
using System.Runtime.Intrinsics.Arm;

namespace System.Numerics.Tensors
{
public static partial class TensorPrimitives
{
/// <summary>Searches for the largest number in the specified tensor.</summary>
/// <param name="x">The tensor, represented as a span.</param>
/// <returns>The maximum element in <paramref name="x"/>.</returns>
/// <exception cref="ArgumentException">Length of <paramref name="x" /> must be greater than zero.</exception>
/// <remarks>
/// <para>
/// The determination of the maximum element matches the IEEE 754:2019 `maximumNumber` function. Positive 0 is considered greater than negative 0.
/// </para>
/// <para>
/// This method may call into the underlying C runtime or employ instructions specific to the current architecture. Exact results may differ between different
/// operating systems or architectures.
/// </para>
/// </remarks>
public static T MaxNumber<T>(ReadOnlySpan<T> x)
where T : INumber<T> =>
MinMaxCore<T, MaxNumberOperator<T>>(x);

/// <summary>Computes the element-wise maximum of the numbers in the specified tensors.</summary>
/// <param name="x">The first tensor, represented as a span.</param>
/// <param name="y">The second tensor, represented as a span.</param>
/// <param name="destination">The destination tensor, represented as a span.</param>
/// <exception cref="ArgumentException">Length of <paramref name="x" /> must be same as length of <paramref name="y" />.</exception>
/// <exception cref="ArgumentException">Destination is too short.</exception>
/// <exception cref="ArgumentException"><paramref name="x"/> and <paramref name="destination"/> reference overlapping memory locations and do not begin at the same location.</exception>
/// <exception cref="ArgumentException"><paramref name="y"/> and <paramref name="destination"/> reference overlapping memory locations and do not begin at the same location.</exception>
/// <remarks>
/// <para>
/// This method effectively computes <c><paramref name="destination" />[i] = <typeparamref name="T"/>.MaxNumber(<paramref name="x" />[i], <paramref name="y" />[i])</c>.
/// </para>
/// <para>
/// The determination of the maximum element matches the IEEE 754:2019 `maximumNumber` function. If either value is <see cref="IFloatingPointIeee754{TSelf}.NaN"/>
/// the other is returned. Positive 0 is considered greater than negative 0.
/// </para>
/// <para>
/// This method may call into the underlying C runtime or employ instructions specific to the current architecture. Exact results may differ between different
/// operating systems or architectures.
/// </para>
/// </remarks>
public static void MaxNumber<T>(ReadOnlySpan<T> x, ReadOnlySpan<T> y, Span<T> destination)
where T : INumber<T> =>
InvokeSpanSpanIntoSpan<T, MaxNumberOperator<T>>(x, y, destination);

/// <summary>Computes the element-wise maximum of the numbers in the specified tensors.</summary>
/// <param name="x">The first tensor, represented as a span.</param>
/// <param name="y">The second tensor, represented as a scalar.</param>
/// <param name="destination">The destination tensor, represented as a span.</param>
/// <exception cref="ArgumentException">Destination is too short.</exception>
/// <exception cref="ArgumentException"><paramref name="x"/> and <paramref name="destination"/> reference overlapping memory locations and do not begin at the same location.</exception>
/// <remarks>
/// <para>
/// This method effectively computes <c><paramref name="destination" />[i] = <typeparamref name="T"/>.MaxNumber(<paramref name="x" />[i], <paramref name="y" />)</c>.
/// </para>
/// <para>
/// The determination of the maximum element matches the IEEE 754:2019 `maximumNumber` function. If either value is <see cref="IFloatingPointIeee754{TSelf}.NaN"/>
/// the other is returned. Positive 0 is considered greater than negative 0.
/// </para>
/// <para>
/// This method may call into the underlying C runtime or employ instructions specific to the current architecture. Exact results may differ between different
/// operating systems or architectures.
/// </para>
/// </remarks>
public static void MaxNumber<T>(ReadOnlySpan<T> x, T y, Span<T> destination)
where T : INumber<T> =>
InvokeSpanScalarIntoSpan<T, MaxNumberOperator<T>>(x, y, destination);

/// <summary>T.MaxNumber(x, y)</summary>
internal readonly struct MaxNumberOperator<T> : IAggregationOperator<T> where T : INumber<T>
{
public static bool Vectorizable => true;

public static T Invoke(T x, T y) => T.MaxNumber(x, y);

[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static Vector128<T> Invoke(Vector128<T> x, Vector128<T> y)
{
if (typeof(T) == typeof(float) || typeof(T) == typeof(double))
{
if (AdvSimd.IsSupported && typeof(T) == typeof(float))
{
return AdvSimd.MaxNumber(x.AsSingle(), y.AsSingle()).As<float, T>();
}

if (AdvSimd.Arm64.IsSupported && typeof(T) == typeof(double))
{
return AdvSimd.Arm64.MaxNumber(x.AsDouble(), y.AsDouble()).As<double, T>();
}

return
Vector128.ConditionalSelect(Vector128.Equals(x, y),
Vector128.ConditionalSelect(IsNegative(y), x, y),
Vector128.ConditionalSelect(Vector128.Equals(y, y), Vector128.Max(x, y), x));
}

return Vector128.Max(x, y);
}

[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static Vector256<T> Invoke(Vector256<T> x, Vector256<T> y)
{
if (typeof(T) == typeof(float) || typeof(T) == typeof(double))
{
return
Vector256.ConditionalSelect(Vector256.Equals(x, y),
Vector256.ConditionalSelect(IsNegative(y), x, y),
Vector256.ConditionalSelect(Vector256.Equals(y, y), Vector256.Max(x, y), x));
}

return Vector256.Max(x, y);
}

[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static Vector512<T> Invoke(Vector512<T> x, Vector512<T> y)
{
if (typeof(T) == typeof(float) || typeof(T) == typeof(double))
{
return
Vector512.ConditionalSelect(Vector512.Equals(x, y),
Vector512.ConditionalSelect(IsNegative(y), x, y),
Vector512.ConditionalSelect(Vector512.Equals(y, y), Vector512.Max(x, y), x));
}

return Vector512.Max(x, y);
}

public static T Invoke(Vector128<T> x) => HorizontalAggregate<T, MaxNumberOperator<T>>(x);
public static T Invoke(Vector256<T> x) => HorizontalAggregate<T, MaxNumberOperator<T>>(x);
public static T Invoke(Vector512<T> x) => HorizontalAggregate<T, MaxNumberOperator<T>>(x);
}
}
}
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