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Diffstat (limited to 'third_party/rust/rayon/src/slice/mod.rs')
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diff --git a/third_party/rust/rayon/src/slice/mod.rs b/third_party/rust/rayon/src/slice/mod.rs new file mode 100644 index 0000000000..dab56deb32 --- /dev/null +++ b/third_party/rust/rayon/src/slice/mod.rs @@ -0,0 +1,1041 @@ +//! Parallel iterator types for [slices][std::slice] +//! +//! You will rarely need to interact with this module directly unless you need +//! to name one of the iterator types. +//! +//! [std::slice]: https://doc.rust-lang.org/stable/std/slice/ + +mod chunks; +mod mergesort; +mod quicksort; +mod rchunks; + +mod test; + +use self::mergesort::par_mergesort; +use self::quicksort::par_quicksort; +use crate::iter::plumbing::*; +use crate::iter::*; +use crate::split_producer::*; +use std::cmp; +use std::cmp::Ordering; +use std::fmt::{self, Debug}; +use std::mem; + +pub use self::chunks::{Chunks, ChunksExact, ChunksExactMut, ChunksMut}; +pub use self::rchunks::{RChunks, RChunksExact, RChunksExactMut, RChunksMut}; + +/// Parallel extensions for slices. +pub trait ParallelSlice<T: Sync> { + /// Returns a plain slice, which is used to implement the rest of the + /// parallel methods. + fn as_parallel_slice(&self) -> &[T]; + + /// Returns a parallel iterator over subslices separated by elements that + /// match the separator. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// let smallest = [1, 2, 3, 0, 2, 4, 8, 0, 3, 6, 9] + /// .par_split(|i| *i == 0) + /// .map(|numbers| numbers.iter().min().unwrap()) + /// .min(); + /// assert_eq!(Some(&1), smallest); + /// ``` + fn par_split<P>(&self, separator: P) -> Split<'_, T, P> + where + P: Fn(&T) -> bool + Sync + Send, + { + Split { + slice: self.as_parallel_slice(), + separator, + } + } + + /// Returns a parallel iterator over all contiguous windows of length + /// `window_size`. The windows overlap. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// let windows: Vec<_> = [1, 2, 3].par_windows(2).collect(); + /// assert_eq!(vec![[1, 2], [2, 3]], windows); + /// ``` + fn par_windows(&self, window_size: usize) -> Windows<'_, T> { + Windows { + window_size, + slice: self.as_parallel_slice(), + } + } + + /// Returns a parallel iterator over at most `chunk_size` elements of + /// `self` at a time. The chunks do not overlap. + /// + /// If the number of elements in the iterator is not divisible by + /// `chunk_size`, the last chunk may be shorter than `chunk_size`. All + /// other chunks will have that exact length. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// let chunks: Vec<_> = [1, 2, 3, 4, 5].par_chunks(2).collect(); + /// assert_eq!(chunks, vec![&[1, 2][..], &[3, 4], &[5]]); + /// ``` + #[track_caller] + fn par_chunks(&self, chunk_size: usize) -> Chunks<'_, T> { + assert!(chunk_size != 0, "chunk_size must not be zero"); + Chunks::new(chunk_size, self.as_parallel_slice()) + } + + /// Returns a parallel iterator over `chunk_size` elements of + /// `self` at a time. The chunks do not overlap. + /// + /// If `chunk_size` does not divide the length of the slice, then the + /// last up to `chunk_size-1` elements will be omitted and can be + /// retrieved from the remainder function of the iterator. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// let chunks: Vec<_> = [1, 2, 3, 4, 5].par_chunks_exact(2).collect(); + /// assert_eq!(chunks, vec![&[1, 2][..], &[3, 4]]); + /// ``` + #[track_caller] + fn par_chunks_exact(&self, chunk_size: usize) -> ChunksExact<'_, T> { + assert!(chunk_size != 0, "chunk_size must not be zero"); + ChunksExact::new(chunk_size, self.as_parallel_slice()) + } + + /// Returns a parallel iterator over at most `chunk_size` elements of `self` at a time, + /// starting at the end. The chunks do not overlap. + /// + /// If the number of elements in the iterator is not divisible by + /// `chunk_size`, the last chunk may be shorter than `chunk_size`. All + /// other chunks will have that exact length. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// let chunks: Vec<_> = [1, 2, 3, 4, 5].par_rchunks(2).collect(); + /// assert_eq!(chunks, vec![&[4, 5][..], &[2, 3], &[1]]); + /// ``` + #[track_caller] + fn par_rchunks(&self, chunk_size: usize) -> RChunks<'_, T> { + assert!(chunk_size != 0, "chunk_size must not be zero"); + RChunks::new(chunk_size, self.as_parallel_slice()) + } + + /// Returns a parallel iterator over `chunk_size` elements of `self` at a time, + /// starting at the end. The chunks do not overlap. + /// + /// If `chunk_size` does not divide the length of the slice, then the + /// last up to `chunk_size-1` elements will be omitted and can be + /// retrieved from the remainder function of the iterator. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// let chunks: Vec<_> = [1, 2, 3, 4, 5].par_rchunks_exact(2).collect(); + /// assert_eq!(chunks, vec![&[4, 5][..], &[2, 3]]); + /// ``` + #[track_caller] + fn par_rchunks_exact(&self, chunk_size: usize) -> RChunksExact<'_, T> { + assert!(chunk_size != 0, "chunk_size must not be zero"); + RChunksExact::new(chunk_size, self.as_parallel_slice()) + } +} + +impl<T: Sync> ParallelSlice<T> for [T] { + #[inline] + fn as_parallel_slice(&self) -> &[T] { + self + } +} + +/// Parallel extensions for mutable slices. +pub trait ParallelSliceMut<T: Send> { + /// Returns a plain mutable slice, which is used to implement the rest of + /// the parallel methods. + fn as_parallel_slice_mut(&mut self) -> &mut [T]; + + /// Returns a parallel iterator over mutable subslices separated by + /// elements that match the separator. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// let mut array = [1, 2, 3, 0, 2, 4, 8, 0, 3, 6, 9]; + /// array.par_split_mut(|i| *i == 0) + /// .for_each(|slice| slice.reverse()); + /// assert_eq!(array, [3, 2, 1, 0, 8, 4, 2, 0, 9, 6, 3]); + /// ``` + fn par_split_mut<P>(&mut self, separator: P) -> SplitMut<'_, T, P> + where + P: Fn(&T) -> bool + Sync + Send, + { + SplitMut { + slice: self.as_parallel_slice_mut(), + separator, + } + } + + /// Returns a parallel iterator over at most `chunk_size` elements of + /// `self` at a time. The chunks are mutable and do not overlap. + /// + /// If the number of elements in the iterator is not divisible by + /// `chunk_size`, the last chunk may be shorter than `chunk_size`. All + /// other chunks will have that exact length. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// let mut array = [1, 2, 3, 4, 5]; + /// array.par_chunks_mut(2) + /// .for_each(|slice| slice.reverse()); + /// assert_eq!(array, [2, 1, 4, 3, 5]); + /// ``` + #[track_caller] + fn par_chunks_mut(&mut self, chunk_size: usize) -> ChunksMut<'_, T> { + assert!(chunk_size != 0, "chunk_size must not be zero"); + ChunksMut::new(chunk_size, self.as_parallel_slice_mut()) + } + + /// Returns a parallel iterator over `chunk_size` elements of + /// `self` at a time. The chunks are mutable and do not overlap. + /// + /// If `chunk_size` does not divide the length of the slice, then the + /// last up to `chunk_size-1` elements will be omitted and can be + /// retrieved from the remainder function of the iterator. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// let mut array = [1, 2, 3, 4, 5]; + /// array.par_chunks_exact_mut(3) + /// .for_each(|slice| slice.reverse()); + /// assert_eq!(array, [3, 2, 1, 4, 5]); + /// ``` + #[track_caller] + fn par_chunks_exact_mut(&mut self, chunk_size: usize) -> ChunksExactMut<'_, T> { + assert!(chunk_size != 0, "chunk_size must not be zero"); + ChunksExactMut::new(chunk_size, self.as_parallel_slice_mut()) + } + + /// Returns a parallel iterator over at most `chunk_size` elements of `self` at a time, + /// starting at the end. The chunks are mutable and do not overlap. + /// + /// If the number of elements in the iterator is not divisible by + /// `chunk_size`, the last chunk may be shorter than `chunk_size`. All + /// other chunks will have that exact length. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// let mut array = [1, 2, 3, 4, 5]; + /// array.par_rchunks_mut(2) + /// .for_each(|slice| slice.reverse()); + /// assert_eq!(array, [1, 3, 2, 5, 4]); + /// ``` + #[track_caller] + fn par_rchunks_mut(&mut self, chunk_size: usize) -> RChunksMut<'_, T> { + assert!(chunk_size != 0, "chunk_size must not be zero"); + RChunksMut::new(chunk_size, self.as_parallel_slice_mut()) + } + + /// Returns a parallel iterator over `chunk_size` elements of `self` at a time, + /// starting at the end. The chunks are mutable and do not overlap. + /// + /// If `chunk_size` does not divide the length of the slice, then the + /// last up to `chunk_size-1` elements will be omitted and can be + /// retrieved from the remainder function of the iterator. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// let mut array = [1, 2, 3, 4, 5]; + /// array.par_rchunks_exact_mut(3) + /// .for_each(|slice| slice.reverse()); + /// assert_eq!(array, [1, 2, 5, 4, 3]); + /// ``` + #[track_caller] + fn par_rchunks_exact_mut(&mut self, chunk_size: usize) -> RChunksExactMut<'_, T> { + assert!(chunk_size != 0, "chunk_size must not be zero"); + RChunksExactMut::new(chunk_size, self.as_parallel_slice_mut()) + } + + /// Sorts the slice in parallel. + /// + /// This sort is stable (i.e., does not reorder equal elements) and *O*(*n* \* log(*n*)) worst-case. + /// + /// When applicable, unstable sorting is preferred because it is generally faster than stable + /// sorting and it doesn't allocate auxiliary memory. + /// See [`par_sort_unstable`](#method.par_sort_unstable). + /// + /// # Current implementation + /// + /// The current algorithm is an adaptive merge sort inspired by + /// [timsort](https://en.wikipedia.org/wiki/Timsort). + /// It is designed to be very fast in cases where the slice is nearly sorted, or consists of + /// two or more sorted sequences concatenated one after another. + /// + /// Also, it allocates temporary storage the same size as `self`, but for very short slices a + /// non-allocating insertion sort is used instead. + /// + /// In order to sort the slice in parallel, the slice is first divided into smaller chunks and + /// all chunks are sorted in parallel. Then, adjacent chunks that together form non-descending + /// or descending runs are concatenated. Finally, the remaining chunks are merged together using + /// parallel subdivision of chunks and parallel merge operation. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let mut v = [-5, 4, 1, -3, 2]; + /// + /// v.par_sort(); + /// assert_eq!(v, [-5, -3, 1, 2, 4]); + /// ``` + fn par_sort(&mut self) + where + T: Ord, + { + par_mergesort(self.as_parallel_slice_mut(), T::lt); + } + + /// Sorts the slice in parallel with a comparator function. + /// + /// This sort is stable (i.e., does not reorder equal elements) and *O*(*n* \* log(*n*)) worst-case. + /// + /// The comparator function must define a total ordering for the elements in the slice. If + /// the ordering is not total, the order of the elements is unspecified. An order is a + /// total order if it is (for all `a`, `b` and `c`): + /// + /// * total and antisymmetric: exactly one of `a < b`, `a == b` or `a > b` is true, and + /// * transitive, `a < b` and `b < c` implies `a < c`. The same must hold for both `==` and `>`. + /// + /// For example, while [`f64`] doesn't implement [`Ord`] because `NaN != NaN`, we can use + /// `partial_cmp` as our sort function when we know the slice doesn't contain a `NaN`. + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let mut floats = [5f64, 4.0, 1.0, 3.0, 2.0]; + /// floats.par_sort_by(|a, b| a.partial_cmp(b).unwrap()); + /// assert_eq!(floats, [1.0, 2.0, 3.0, 4.0, 5.0]); + /// ``` + /// + /// When applicable, unstable sorting is preferred because it is generally faster than stable + /// sorting and it doesn't allocate auxiliary memory. + /// See [`par_sort_unstable_by`](#method.par_sort_unstable_by). + /// + /// # Current implementation + /// + /// The current algorithm is an adaptive merge sort inspired by + /// [timsort](https://en.wikipedia.org/wiki/Timsort). + /// It is designed to be very fast in cases where the slice is nearly sorted, or consists of + /// two or more sorted sequences concatenated one after another. + /// + /// Also, it allocates temporary storage the same size as `self`, but for very short slices a + /// non-allocating insertion sort is used instead. + /// + /// In order to sort the slice in parallel, the slice is first divided into smaller chunks and + /// all chunks are sorted in parallel. Then, adjacent chunks that together form non-descending + /// or descending runs are concatenated. Finally, the remaining chunks are merged together using + /// parallel subdivision of chunks and parallel merge operation. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let mut v = [5, 4, 1, 3, 2]; + /// v.par_sort_by(|a, b| a.cmp(b)); + /// assert_eq!(v, [1, 2, 3, 4, 5]); + /// + /// // reverse sorting + /// v.par_sort_by(|a, b| b.cmp(a)); + /// assert_eq!(v, [5, 4, 3, 2, 1]); + /// ``` + fn par_sort_by<F>(&mut self, compare: F) + where + F: Fn(&T, &T) -> Ordering + Sync, + { + par_mergesort(self.as_parallel_slice_mut(), |a, b| { + compare(a, b) == Ordering::Less + }); + } + + /// Sorts the slice in parallel with a key extraction function. + /// + /// This sort is stable (i.e., does not reorder equal elements) and *O*(*m* \* *n* \* log(*n*)) + /// worst-case, where the key function is *O*(*m*). + /// + /// For expensive key functions (e.g. functions that are not simple property accesses or + /// basic operations), [`par_sort_by_cached_key`](#method.par_sort_by_cached_key) is likely to + /// be significantly faster, as it does not recompute element keys. + /// + /// When applicable, unstable sorting is preferred because it is generally faster than stable + /// sorting and it doesn't allocate auxiliary memory. + /// See [`par_sort_unstable_by_key`](#method.par_sort_unstable_by_key). + /// + /// # Current implementation + /// + /// The current algorithm is an adaptive merge sort inspired by + /// [timsort](https://en.wikipedia.org/wiki/Timsort). + /// It is designed to be very fast in cases where the slice is nearly sorted, or consists of + /// two or more sorted sequences concatenated one after another. + /// + /// Also, it allocates temporary storage the same size as `self`, but for very short slices a + /// non-allocating insertion sort is used instead. + /// + /// In order to sort the slice in parallel, the slice is first divided into smaller chunks and + /// all chunks are sorted in parallel. Then, adjacent chunks that together form non-descending + /// or descending runs are concatenated. Finally, the remaining chunks are merged together using + /// parallel subdivision of chunks and parallel merge operation. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let mut v = [-5i32, 4, 1, -3, 2]; + /// + /// v.par_sort_by_key(|k| k.abs()); + /// assert_eq!(v, [1, 2, -3, 4, -5]); + /// ``` + fn par_sort_by_key<K, F>(&mut self, f: F) + where + K: Ord, + F: Fn(&T) -> K + Sync, + { + par_mergesort(self.as_parallel_slice_mut(), |a, b| f(a).lt(&f(b))); + } + + /// Sorts the slice in parallel with a key extraction function. + /// + /// During sorting, the key function is called at most once per element, by using + /// temporary storage to remember the results of key evaluation. + /// The key function is called in parallel, so the order of calls is completely unspecified. + /// + /// This sort is stable (i.e., does not reorder equal elements) and *O*(*m* \* *n* + *n* \* log(*n*)) + /// worst-case, where the key function is *O*(*m*). + /// + /// For simple key functions (e.g., functions that are property accesses or + /// basic operations), [`par_sort_by_key`](#method.par_sort_by_key) is likely to be + /// faster. + /// + /// # Current implementation + /// + /// The current algorithm is based on [pattern-defeating quicksort][pdqsort] by Orson Peters, + /// which combines the fast average case of randomized quicksort with the fast worst case of + /// heapsort, while achieving linear time on slices with certain patterns. It uses some + /// randomization to avoid degenerate cases, but with a fixed seed to always provide + /// deterministic behavior. + /// + /// In the worst case, the algorithm allocates temporary storage in a `Vec<(K, usize)>` the + /// length of the slice. + /// + /// All quicksorts work in two stages: partitioning into two halves followed by recursive + /// calls. The partitioning phase is sequential, but the two recursive calls are performed in + /// parallel. Finally, after sorting the cached keys, the item positions are updated sequentially. + /// + /// [pdqsort]: https://github.com/orlp/pdqsort + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let mut v = [-5i32, 4, 32, -3, 2]; + /// + /// v.par_sort_by_cached_key(|k| k.to_string()); + /// assert!(v == [-3, -5, 2, 32, 4]); + /// ``` + fn par_sort_by_cached_key<K, F>(&mut self, f: F) + where + F: Fn(&T) -> K + Sync, + K: Ord + Send, + { + let slice = self.as_parallel_slice_mut(); + let len = slice.len(); + if len < 2 { + return; + } + + // Helper macro for indexing our vector by the smallest possible type, to reduce allocation. + macro_rules! sort_by_key { + ($t:ty) => {{ + let mut indices: Vec<_> = slice + .par_iter_mut() + .enumerate() + .map(|(i, x)| (f(&*x), i as $t)) + .collect(); + // The elements of `indices` are unique, as they are indexed, so any sort will be + // stable with respect to the original slice. We use `sort_unstable` here because + // it requires less memory allocation. + indices.par_sort_unstable(); + for i in 0..len { + let mut index = indices[i].1; + while (index as usize) < i { + index = indices[index as usize].1; + } + indices[i].1 = index; + slice.swap(i, index as usize); + } + }}; + } + + let sz_u8 = mem::size_of::<(K, u8)>(); + let sz_u16 = mem::size_of::<(K, u16)>(); + let sz_u32 = mem::size_of::<(K, u32)>(); + let sz_usize = mem::size_of::<(K, usize)>(); + + if sz_u8 < sz_u16 && len <= (std::u8::MAX as usize) { + return sort_by_key!(u8); + } + if sz_u16 < sz_u32 && len <= (std::u16::MAX as usize) { + return sort_by_key!(u16); + } + if sz_u32 < sz_usize && len <= (std::u32::MAX as usize) { + return sort_by_key!(u32); + } + sort_by_key!(usize) + } + + /// Sorts the slice in parallel, but might not preserve the order of equal elements. + /// + /// This sort is unstable (i.e., may reorder equal elements), in-place + /// (i.e., does not allocate), and *O*(*n* \* log(*n*)) worst-case. + /// + /// # Current implementation + /// + /// The current algorithm is based on [pattern-defeating quicksort][pdqsort] by Orson Peters, + /// which combines the fast average case of randomized quicksort with the fast worst case of + /// heapsort, while achieving linear time on slices with certain patterns. It uses some + /// randomization to avoid degenerate cases, but with a fixed seed to always provide + /// deterministic behavior. + /// + /// It is typically faster than stable sorting, except in a few special cases, e.g., when the + /// slice consists of several concatenated sorted sequences. + /// + /// All quicksorts work in two stages: partitioning into two halves followed by recursive + /// calls. The partitioning phase is sequential, but the two recursive calls are performed in + /// parallel. + /// + /// [pdqsort]: https://github.com/orlp/pdqsort + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let mut v = [-5, 4, 1, -3, 2]; + /// + /// v.par_sort_unstable(); + /// assert_eq!(v, [-5, -3, 1, 2, 4]); + /// ``` + fn par_sort_unstable(&mut self) + where + T: Ord, + { + par_quicksort(self.as_parallel_slice_mut(), T::lt); + } + + /// Sorts the slice in parallel with a comparator function, but might not preserve the order of + /// equal elements. + /// + /// This sort is unstable (i.e., may reorder equal elements), in-place + /// (i.e., does not allocate), and *O*(*n* \* log(*n*)) worst-case. + /// + /// The comparator function must define a total ordering for the elements in the slice. If + /// the ordering is not total, the order of the elements is unspecified. An order is a + /// total order if it is (for all `a`, `b` and `c`): + /// + /// * total and antisymmetric: exactly one of `a < b`, `a == b` or `a > b` is true, and + /// * transitive, `a < b` and `b < c` implies `a < c`. The same must hold for both `==` and `>`. + /// + /// For example, while [`f64`] doesn't implement [`Ord`] because `NaN != NaN`, we can use + /// `partial_cmp` as our sort function when we know the slice doesn't contain a `NaN`. + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let mut floats = [5f64, 4.0, 1.0, 3.0, 2.0]; + /// floats.par_sort_unstable_by(|a, b| a.partial_cmp(b).unwrap()); + /// assert_eq!(floats, [1.0, 2.0, 3.0, 4.0, 5.0]); + /// ``` + /// + /// # Current implementation + /// + /// The current algorithm is based on [pattern-defeating quicksort][pdqsort] by Orson Peters, + /// which combines the fast average case of randomized quicksort with the fast worst case of + /// heapsort, while achieving linear time on slices with certain patterns. It uses some + /// randomization to avoid degenerate cases, but with a fixed seed to always provide + /// deterministic behavior. + /// + /// It is typically faster than stable sorting, except in a few special cases, e.g., when the + /// slice consists of several concatenated sorted sequences. + /// + /// All quicksorts work in two stages: partitioning into two halves followed by recursive + /// calls. The partitioning phase is sequential, but the two recursive calls are performed in + /// parallel. + /// + /// [pdqsort]: https://github.com/orlp/pdqsort + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let mut v = [5, 4, 1, 3, 2]; + /// v.par_sort_unstable_by(|a, b| a.cmp(b)); + /// assert_eq!(v, [1, 2, 3, 4, 5]); + /// + /// // reverse sorting + /// v.par_sort_unstable_by(|a, b| b.cmp(a)); + /// assert_eq!(v, [5, 4, 3, 2, 1]); + /// ``` + fn par_sort_unstable_by<F>(&mut self, compare: F) + where + F: Fn(&T, &T) -> Ordering + Sync, + { + par_quicksort(self.as_parallel_slice_mut(), |a, b| { + compare(a, b) == Ordering::Less + }); + } + + /// Sorts the slice in parallel with a key extraction function, but might not preserve the order + /// of equal elements. + /// + /// This sort is unstable (i.e., may reorder equal elements), in-place + /// (i.e., does not allocate), and *O*(m \* *n* \* log(*n*)) worst-case, + /// where the key function is *O*(*m*). + /// + /// # Current implementation + /// + /// The current algorithm is based on [pattern-defeating quicksort][pdqsort] by Orson Peters, + /// which combines the fast average case of randomized quicksort with the fast worst case of + /// heapsort, while achieving linear time on slices with certain patterns. It uses some + /// randomization to avoid degenerate cases, but with a fixed seed to always provide + /// deterministic behavior. + /// + /// Due to its key calling strategy, `par_sort_unstable_by_key` is likely to be slower than + /// [`par_sort_by_cached_key`](#method.par_sort_by_cached_key) in cases where the key function + /// is expensive. + /// + /// All quicksorts work in two stages: partitioning into two halves followed by recursive + /// calls. The partitioning phase is sequential, but the two recursive calls are performed in + /// parallel. + /// + /// [pdqsort]: https://github.com/orlp/pdqsort + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let mut v = [-5i32, 4, 1, -3, 2]; + /// + /// v.par_sort_unstable_by_key(|k| k.abs()); + /// assert_eq!(v, [1, 2, -3, 4, -5]); + /// ``` + fn par_sort_unstable_by_key<K, F>(&mut self, f: F) + where + K: Ord, + F: Fn(&T) -> K + Sync, + { + par_quicksort(self.as_parallel_slice_mut(), |a, b| f(a).lt(&f(b))); + } +} + +impl<T: Send> ParallelSliceMut<T> for [T] { + #[inline] + fn as_parallel_slice_mut(&mut self) -> &mut [T] { + self + } +} + +impl<'data, T: Sync + 'data> IntoParallelIterator for &'data [T] { + type Item = &'data T; + type Iter = Iter<'data, T>; + + fn into_par_iter(self) -> Self::Iter { + Iter { slice: self } + } +} + +impl<'data, T: Send + 'data> IntoParallelIterator for &'data mut [T] { + type Item = &'data mut T; + type Iter = IterMut<'data, T>; + + fn into_par_iter(self) -> Self::Iter { + IterMut { slice: self } + } +} + +/// Parallel iterator over immutable items in a slice +#[derive(Debug)] +pub struct Iter<'data, T: Sync> { + slice: &'data [T], +} + +impl<'data, T: Sync> Clone for Iter<'data, T> { + fn clone(&self) -> Self { + Iter { ..*self } + } +} + +impl<'data, T: Sync + 'data> ParallelIterator for Iter<'data, T> { + type Item = &'data T; + + fn drive_unindexed<C>(self, consumer: C) -> C::Result + where + C: UnindexedConsumer<Self::Item>, + { + bridge(self, consumer) + } + + fn opt_len(&self) -> Option<usize> { + Some(self.len()) + } +} + +impl<'data, T: Sync + 'data> IndexedParallelIterator for Iter<'data, T> { + fn drive<C>(self, consumer: C) -> C::Result + where + C: Consumer<Self::Item>, + { + bridge(self, consumer) + } + + fn len(&self) -> usize { + self.slice.len() + } + + fn with_producer<CB>(self, callback: CB) -> CB::Output + where + CB: ProducerCallback<Self::Item>, + { + callback.callback(IterProducer { slice: self.slice }) + } +} + +struct IterProducer<'data, T: Sync> { + slice: &'data [T], +} + +impl<'data, T: 'data + Sync> Producer for IterProducer<'data, T> { + type Item = &'data T; + type IntoIter = ::std::slice::Iter<'data, T>; + + fn into_iter(self) -> Self::IntoIter { + self.slice.iter() + } + + fn split_at(self, index: usize) -> (Self, Self) { + let (left, right) = self.slice.split_at(index); + (IterProducer { slice: left }, IterProducer { slice: right }) + } +} + +/// Parallel iterator over immutable overlapping windows of a slice +#[derive(Debug)] +pub struct Windows<'data, T: Sync> { + window_size: usize, + slice: &'data [T], +} + +impl<'data, T: Sync> Clone for Windows<'data, T> { + fn clone(&self) -> Self { + Windows { ..*self } + } +} + +impl<'data, T: Sync + 'data> ParallelIterator for Windows<'data, T> { + type Item = &'data [T]; + + fn drive_unindexed<C>(self, consumer: C) -> C::Result + where + C: UnindexedConsumer<Self::Item>, + { + bridge(self, consumer) + } + + fn opt_len(&self) -> Option<usize> { + Some(self.len()) + } +} + +impl<'data, T: Sync + 'data> IndexedParallelIterator for Windows<'data, T> { + fn drive<C>(self, consumer: C) -> C::Result + where + C: Consumer<Self::Item>, + { + bridge(self, consumer) + } + + fn len(&self) -> usize { + assert!(self.window_size >= 1); + self.slice.len().saturating_sub(self.window_size - 1) + } + + fn with_producer<CB>(self, callback: CB) -> CB::Output + where + CB: ProducerCallback<Self::Item>, + { + callback.callback(WindowsProducer { + window_size: self.window_size, + slice: self.slice, + }) + } +} + +struct WindowsProducer<'data, T: Sync> { + window_size: usize, + slice: &'data [T], +} + +impl<'data, T: 'data + Sync> Producer for WindowsProducer<'data, T> { + type Item = &'data [T]; + type IntoIter = ::std::slice::Windows<'data, T>; + + fn into_iter(self) -> Self::IntoIter { + self.slice.windows(self.window_size) + } + + fn split_at(self, index: usize) -> (Self, Self) { + let left_index = cmp::min(self.slice.len(), index + (self.window_size - 1)); + let left = &self.slice[..left_index]; + let right = &self.slice[index..]; + ( + WindowsProducer { + window_size: self.window_size, + slice: left, + }, + WindowsProducer { + window_size: self.window_size, + slice: right, + }, + ) + } +} + +/// Parallel iterator over mutable items in a slice +#[derive(Debug)] +pub struct IterMut<'data, T: Send> { + slice: &'data mut [T], +} + +impl<'data, T: Send + 'data> ParallelIterator for IterMut<'data, T> { + type Item = &'data mut T; + + fn drive_unindexed<C>(self, consumer: C) -> C::Result + where + C: UnindexedConsumer<Self::Item>, + { + bridge(self, consumer) + } + + fn opt_len(&self) -> Option<usize> { + Some(self.len()) + } +} + +impl<'data, T: Send + 'data> IndexedParallelIterator for IterMut<'data, T> { + fn drive<C>(self, consumer: C) -> C::Result + where + C: Consumer<Self::Item>, + { + bridge(self, consumer) + } + + fn len(&self) -> usize { + self.slice.len() + } + + fn with_producer<CB>(self, callback: CB) -> CB::Output + where + CB: ProducerCallback<Self::Item>, + { + callback.callback(IterMutProducer { slice: self.slice }) + } +} + +struct IterMutProducer<'data, T: Send> { + slice: &'data mut [T], +} + +impl<'data, T: 'data + Send> Producer for IterMutProducer<'data, T> { + type Item = &'data mut T; + type IntoIter = ::std::slice::IterMut<'data, T>; + + fn into_iter(self) -> Self::IntoIter { + self.slice.iter_mut() + } + + fn split_at(self, index: usize) -> (Self, Self) { + let (left, right) = self.slice.split_at_mut(index); + ( + IterMutProducer { slice: left }, + IterMutProducer { slice: right }, + ) + } +} + +/// Parallel iterator over slices separated by a predicate +pub struct Split<'data, T, P> { + slice: &'data [T], + separator: P, +} + +impl<'data, T, P: Clone> Clone for Split<'data, T, P> { + fn clone(&self) -> Self { + Split { + separator: self.separator.clone(), + ..*self + } + } +} + +impl<'data, T: Debug, P> Debug for Split<'data, T, P> { + fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result { + f.debug_struct("Split").field("slice", &self.slice).finish() + } +} + +impl<'data, T, P> ParallelIterator for Split<'data, T, P> +where + P: Fn(&T) -> bool + Sync + Send, + T: Sync, +{ + type Item = &'data [T]; + + fn drive_unindexed<C>(self, consumer: C) -> C::Result + where + C: UnindexedConsumer<Self::Item>, + { + let producer = SplitProducer::new(self.slice, &self.separator); + bridge_unindexed(producer, consumer) + } +} + +/// Implement support for `SplitProducer`. +impl<'data, T, P> Fissile<P> for &'data [T] +where + P: Fn(&T) -> bool, +{ + fn length(&self) -> usize { + self.len() + } + + fn midpoint(&self, end: usize) -> usize { + end / 2 + } + + fn find(&self, separator: &P, start: usize, end: usize) -> Option<usize> { + self[start..end].iter().position(separator) + } + + fn rfind(&self, separator: &P, end: usize) -> Option<usize> { + self[..end].iter().rposition(separator) + } + + fn split_once(self, index: usize) -> (Self, Self) { + let (left, right) = self.split_at(index); + (left, &right[1..]) // skip the separator + } + + fn fold_splits<F>(self, separator: &P, folder: F, skip_last: bool) -> F + where + F: Folder<Self>, + Self: Send, + { + let mut split = self.split(separator); + if skip_last { + split.next_back(); + } + folder.consume_iter(split) + } +} + +/// Parallel iterator over mutable slices separated by a predicate +pub struct SplitMut<'data, T, P> { + slice: &'data mut [T], + separator: P, +} + +impl<'data, T: Debug, P> Debug for SplitMut<'data, T, P> { + fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result { + f.debug_struct("SplitMut") + .field("slice", &self.slice) + .finish() + } +} + +impl<'data, T, P> ParallelIterator for SplitMut<'data, T, P> +where + P: Fn(&T) -> bool + Sync + Send, + T: Send, +{ + type Item = &'data mut [T]; + + fn drive_unindexed<C>(self, consumer: C) -> C::Result + where + C: UnindexedConsumer<Self::Item>, + { + let producer = SplitProducer::new(self.slice, &self.separator); + bridge_unindexed(producer, consumer) + } +} + +/// Implement support for `SplitProducer`. +impl<'data, T, P> Fissile<P> for &'data mut [T] +where + P: Fn(&T) -> bool, +{ + fn length(&self) -> usize { + self.len() + } + + fn midpoint(&self, end: usize) -> usize { + end / 2 + } + + fn find(&self, separator: &P, start: usize, end: usize) -> Option<usize> { + self[start..end].iter().position(separator) + } + + fn rfind(&self, separator: &P, end: usize) -> Option<usize> { + self[..end].iter().rposition(separator) + } + + fn split_once(self, index: usize) -> (Self, Self) { + let (left, right) = self.split_at_mut(index); + (left, &mut right[1..]) // skip the separator + } + + fn fold_splits<F>(self, separator: &P, folder: F, skip_last: bool) -> F + where + F: Folder<Self>, + Self: Send, + { + let mut split = self.split_mut(separator); + if skip_last { + split.next_back(); + } + folder.consume_iter(split) + } +} |