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use super::sealed::Sealed;
use crate::simd::{
intrinsics, LaneCount, Mask, Simd, SimdElement, SimdPartialOrd, SupportedLaneCount,
};
/// 对有符号整数的 SIMD vectors 的操作。
pub trait SimdInt: Copy + Sealed {
/// 用于操作此 SIMD vector 类型的掩码类型。
type Mask;
/// 此 SIMD vector 类型包含的标量类型。
type Scalar;
/// Lanewise 饱和加法。
///
/// # Examples
/// ```
/// # #![feature(portable_simd)]
/// # #[cfg(feature = "as_crate")] use core_simd::simd;
/// # #[cfg(not(feature = "as_crate"))] use core::simd;
/// # use simd::{Simd, SimdInt};
/// use core::i32::{MIN, MAX};
/// let x = Simd::from_array([MIN, 0, 1, MAX]);
/// let max = Simd::splat(MAX);
/// let unsat = x + max;
/// let sat = x.saturating_add(max);
/// assert_eq!(unsat, Simd::from_array([-1, MAX, MIN, -2]));
/// assert_eq!(sat, Simd::from_array([-1, MAX, MAX, MAX]));
/// ```
fn saturating_add(self, second: Self) -> Self;
/// Lanewise 饱和减法。
///
/// # Examples
/// ```
/// # #![feature(portable_simd)]
/// # #[cfg(feature = "as_crate")] use core_simd::simd;
/// # #[cfg(not(feature = "as_crate"))] use core::simd;
/// # use simd::{Simd, SimdInt};
/// use core::i32::{MIN, MAX};
/// let x = Simd::from_array([MIN, -2, -1, MAX]);
/// let max = Simd::splat(MAX);
/// let unsat = x - max;
/// let sat = x.saturating_sub(max);
/// assert_eq!(unsat, Simd::from_array([1, MAX, MIN, 0]));
/// assert_eq!(sat, Simd::from_array([MIN, MIN, MIN, 0]));
fn saturating_sub(self, second: Self) -> Self;
/// Lanewise 绝对值,在 Rust 中实现。
/// 每个 lane 都成为它的绝对值。
///
/// # Examples
/// ```
/// # #![feature(portable_simd)]
/// # #[cfg(feature = "as_crate")] use core_simd::simd;
/// # #[cfg(not(feature = "as_crate"))] use core::simd;
/// # use simd::{Simd, SimdInt};
/// use core::i32::{MIN, MAX};
/// let xs = Simd::from_array([MIN, MIN +1, -5, 0]);
/// assert_eq!(xs.abs(), Simd::from_array([MIN, MAX, 5, 0]));
/// ```
fn abs(self) -> Self;
/// Lanewise 饱和绝对值,在 Rust 中实现。
/// 作为 abs(),除了 MIN 值变为 MAX 而不是它本身。
///
/// # Examples
/// ```
/// # #![feature(portable_simd)]
/// # #[cfg(feature = "as_crate")] use core_simd::simd;
/// # #[cfg(not(feature = "as_crate"))] use core::simd;
/// # use simd::{Simd, SimdInt};
/// use core::i32::{MIN, MAX};
/// let xs = Simd::from_array([MIN, -2, 0, 3]);
/// let unsat = xs.abs();
/// let sat = xs.saturating_abs();
/// assert_eq!(unsat, Simd::from_array([MIN, 2, 0, 3]));
/// assert_eq!(sat, Simd::from_array([MAX, 2, 0, 3]));
/// ```
fn saturating_abs(self) -> Self;
/// Lanewise 饱和否定,在 Rust 中实现。
/// 作为 neg(),除了 MIN 值变为 MAX 而不是它本身。
///
/// # Examples
/// ```
/// # #![feature(portable_simd)]
/// # #[cfg(feature = "as_crate")] use core_simd::simd;
/// # #[cfg(not(feature = "as_crate"))] use core::simd;
/// # use simd::{Simd, SimdInt};
/// use core::i32::{MIN, MAX};
/// let x = Simd::from_array([MIN, -2, 3, MAX]);
/// let unsat = -x;
/// let sat = x.saturating_neg();
/// assert_eq!(unsat, Simd::from_array([MIN, 2, -3, MIN + 1]));
/// assert_eq!(sat, Simd::from_array([MAX, 2, -3, MIN + 1]));
/// ```
fn saturating_neg(self) -> Self;
/// 对于每个正 lane 返回真,如果为零或负则返回假。
fn is_positive(self) -> Self::Mask;
/// 对于每个负 lane 返回 true,如果为零或正则返回 false。
fn is_negative(self) -> Self::Mask;
/// 返回代表每个 lane 符号的数字。
/// * `0` 如果数字为零
/// * `1` 如果数字是正数
/// * `-1` 如果数字是负数
fn signum(self) -> Self;
/// 返回 vector 的 lane 总和,带包装加法。
///
/// # Examples
///
/// ```
/// # #![feature(portable_simd)]
/// # #[cfg(feature = "as_crate")] use core_simd::simd;
/// # #[cfg(not(feature = "as_crate"))] use core::simd;
/// # use simd::{i32x4, SimdInt};
/// let v = i32x4::from_array([1, 2, 3, 4]);
/// assert_eq!(v.reduce_sum(), 10);
///
/// // SIMD 整数加法总是换行
/// let v = i32x4::from_array([i32::MAX, 1, 0, 0]);
/// assert_eq!(v.reduce_sum(), i32::MIN);
/// ```
fn reduce_sum(self) -> Self::Scalar;
/// 返回 vector 的 lane 的乘积,带包装乘法。
///
/// # Examples
///
/// ```
/// # #![feature(portable_simd)]
/// # #[cfg(feature = "as_crate")] use core_simd::simd;
/// # #[cfg(not(feature = "as_crate"))] use core::simd;
/// # use simd::{i32x4, SimdInt};
/// let v = i32x4::from_array([1, 2, 3, 4]);
/// assert_eq!(v.reduce_product(), 24);
///
/// // SIMD 整数乘法总是换行
/// let v = i32x4::from_array([i32::MAX, 2, 1, 1]);
/// assert!(v.reduce_product() < i32::MAX);
/// ```
fn reduce_product(self) -> Self::Scalar;
/// 返回 vector 中的最大 lane。
///
/// # Examples
///
/// ```
/// # #![feature(portable_simd)]
/// # #[cfg(feature = "as_crate")] use core_simd::simd;
/// # #[cfg(not(feature = "as_crate"))] use core::simd;
/// # use simd::{i32x4, SimdInt};
/// let v = i32x4::from_array([1, 2, 3, 4]);
/// assert_eq!(v.reduce_max(), 4);
/// ```
fn reduce_max(self) -> Self::Scalar;
/// 返回 vector 中的最小 lane。
///
/// # Examples
///
/// ```
/// # #![feature(portable_simd)]
/// # #[cfg(feature = "as_crate")] use core_simd::simd;
/// # #[cfg(not(feature = "as_crate"))] use core::simd;
/// # use simd::{i32x4, SimdInt};
/// let v = i32x4::from_array([1, 2, 3, 4]);
/// assert_eq!(v.reduce_min(), 1);
/// ```
fn reduce_min(self) -> Self::Scalar;
/// 返回跨 vector lane 的累积按位与。
fn reduce_and(self) -> Self::Scalar;
/// 返回跨 vector lane 的累积按位或。
fn reduce_or(self) -> Self::Scalar;
/// 返回跨 vector lane 的累积按位异或。
fn reduce_xor(self) -> Self::Scalar;
}
macro_rules! impl_trait {
{ $($ty:ty),* } => {
$(
impl<const LANES: usize> Sealed for Simd<$ty, LANES>
where
LaneCount<LANES>: SupportedLaneCount,
{
}
impl<const LANES: usize> SimdInt for Simd<$ty, LANES>
where
LaneCount<LANES>: SupportedLaneCount,
{
type Mask = Mask<<$ty as SimdElement>::Mask, LANES>;
type Scalar = $ty;
#[inline]
fn saturating_add(self, second: Self) -> Self {
// 安全性: `self` 是 vector
unsafe { intrinsics::simd_saturating_add(self, second) }
}
#[inline]
fn saturating_sub(self, second: Self) -> Self {
// 安全性: `self` 是 vector
unsafe { intrinsics::simd_saturating_sub(self, second) }
}
#[inline]
fn abs(self) -> Self {
const SHR: $ty = <$ty>::BITS as $ty - 1;
let m = self >> Simd::splat(SHR);
(self^m) - m
}
#[inline]
fn saturating_abs(self) -> Self {
// 基于符号位的 -1 或 0 掩码的算术移位,给出 2s 补码
const SHR: $ty = <$ty>::BITS as $ty - 1;
let m = self >> Simd::splat(SHR);
(self^m).saturating_sub(m)
}
#[inline]
fn saturating_neg(self) -> Self {
Self::splat(0).saturating_sub(self)
}
#[inline]
fn is_positive(self) -> Self::Mask {
self.simd_gt(Self::splat(0))
}
#[inline]
fn is_negative(self) -> Self::Mask {
self.simd_lt(Self::splat(0))
}
#[inline]
fn signum(self) -> Self {
self.is_positive().select(
Self::splat(1),
self.is_negative().select(Self::splat(-1), Self::splat(0))
)
}
#[inline]
fn reduce_sum(self) -> Self::Scalar {
// 安全性: `self` 是整数 vector
unsafe { intrinsics::simd_reduce_add_ordered(self, 0) }
}
#[inline]
fn reduce_product(self) -> Self::Scalar {
// 安全性: `self` 是整数 vector
unsafe { intrinsics::simd_reduce_mul_ordered(self, 1) }
}
#[inline]
fn reduce_max(self) -> Self::Scalar {
// 安全性: `self` 是整数 vector
unsafe { intrinsics::simd_reduce_max(self) }
}
#[inline]
fn reduce_min(self) -> Self::Scalar {
// 安全性: `self` 是整数 vector
unsafe { intrinsics::simd_reduce_min(self) }
}
#[inline]
fn reduce_and(self) -> Self::Scalar {
// 安全性: `self` 是整数 vector
unsafe { intrinsics::simd_reduce_and(self) }
}
#[inline]
fn reduce_or(self) -> Self::Scalar {
// 安全性: `self` 是整数 vector
unsafe { intrinsics::simd_reduce_or(self) }
}
#[inline]
fn reduce_xor(self) -> Self::Scalar {
// 安全性: `self` 是整数 vector
unsafe { intrinsics::simd_reduce_xor(self) }
}
}
)*
}
}
impl_trait! { i8, i16, i32, i64, isize }