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// Licensed to the .NET Foundation under one or more agreements.
// The .NET Foundation licenses this file to you under the MIT license.
using System.Diagnostics;
using System.Runtime.Intrinsics;
namespace System.Numerics.Tensors
{
public static partial class TensorPrimitives
{
/// <summary>Computes the element-wise linear interpolation between two values based on the given weight in the specified tensors of numbers.</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="amount">The third 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" /> and length of <paramref name="amount" />.</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>
/// <exception cref="ArgumentException"><paramref name="amount"/> 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] = T.Lerp(<paramref name="x" />[i], <paramref name="y" />[i], <paramref name="amount" />[i])</c>.
/// </para>
/// <para>
/// If either of the element-wise input values is equal to <see cref="IFloatingPointIeee754{TSelf}.NaN"/>, the resulting element-wise value is also NaN.
/// </para>
/// </remarks>
public static void Lerp<T>(ReadOnlySpan<T> x, ReadOnlySpan<T> y, ReadOnlySpan<T> amount, Span<T> destination)
where T : IFloatingPointIeee754<T> =>
InvokeSpanSpanSpanIntoSpan<T, LerpOperator<T>>(x, y, amount, destination);
/// <summary>Computes the element-wise linear interpolation between two values based on the given weight in the specified tensors of numbers.</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="amount">The third tensor, represented as a scalar.</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] = T.Lerp(<paramref name="x" />[i], <paramref name="y" />[i], <paramref name="amount" />)</c>.
/// </para>
/// <para>
/// If either of the element-wise input values is equal to <see cref="IFloatingPointIeee754{TSelf}.NaN"/>, the resulting element-wise value is also NaN.
/// </para>
/// </remarks>
public static void Lerp<T>(ReadOnlySpan<T> x, ReadOnlySpan<T> y, T amount, Span<T> destination)
where T : IFloatingPointIeee754<T> =>
InvokeSpanSpanScalarIntoSpan<T, LerpOperator<T>>(x, y, amount, destination);
/// <summary>Computes the element-wise linear interpolation between two values based on the given weight in the specified tensors of numbers.</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="amount">The third 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="amount" />.</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="amount"/> 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] = T.Lerp(<paramref name="x" />[i], <paramref name="y" />, <paramref name="amount" />[i])</c>.
/// </para>
/// <para>
/// If either of the element-wise input values is equal to <see cref="IFloatingPointIeee754{TSelf}.NaN"/>, the resulting element-wise value is also NaN.
/// </para>
/// </remarks>
public static void Lerp<T>(ReadOnlySpan<T> x, T y, ReadOnlySpan<T> amount, Span<T> destination)
where T : IFloatingPointIeee754<T> =>
InvokeSpanScalarSpanIntoSpan<T, LerpOperator<T>>(x, y, amount, destination);
/// <summary>(x * (1 - z)) + (y * z)</summary>
private readonly struct LerpOperator<T> : ITernaryOperator<T> where T : IFloatingPointIeee754<T>
{
public static T Invoke(T x, T y, T amount) => T.Lerp(x, y, amount);
public static Vector128<T> Invoke(Vector128<T> x, Vector128<T> y, Vector128<T> amount)
{
#if NET9_0_OR_GREATER
if (typeof(T) == typeof(double))
{
return Vector128.Lerp(x.AsDouble(), y.AsDouble(), amount.AsDouble()).As<double, T>();
}
else
{
Debug.Assert(typeof(T) == typeof(float));
return Vector128.Lerp(x.AsSingle(), y.AsSingle(), amount.AsSingle()).As<float, T>();
}
#else
return MultiplyAddEstimateOperator<T>.Invoke(x, Vector128<T>.One - amount, y * amount);
#endif
}
public static Vector256<T> Invoke(Vector256<T> x, Vector256<T> y, Vector256<T> amount)
{
#if NET9_0_OR_GREATER
if (typeof(T) == typeof(double))
{
return Vector256.Lerp(x.AsDouble(), y.AsDouble(), amount.AsDouble()).As<double, T>();
}
else
{
Debug.Assert(typeof(T) == typeof(float));
return Vector256.Lerp(x.AsSingle(), y.AsSingle(), amount.AsSingle()).As<float, T>();
}
#else
return MultiplyAddEstimateOperator<T>.Invoke(x, Vector256<T>.One - amount, y * amount);
#endif
}
public static Vector512<T> Invoke(Vector512<T> x, Vector512<T> y, Vector512<T> amount)
{
#if NET9_0_OR_GREATER
if (typeof(T) == typeof(double))
{
return Vector512.Lerp(x.AsDouble(), y.AsDouble(), amount.AsDouble()).As<double, T>();
}
else
{
Debug.Assert(typeof(T) == typeof(float));
return Vector512.Lerp(x.AsSingle(), y.AsSingle(), amount.AsSingle()).As<float, T>();
}
#else
return MultiplyAddEstimateOperator<T>.Invoke(x, Vector512<T>.One - amount, y * amount);
#endif
}
}
}
}
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