3 releases
0.1.2 | May 13, 2024 |
---|---|
0.1.1 | Apr 29, 2024 |
0.1.0 | Apr 29, 2024 |
#1336 in Algorithms
824 downloads per month
Used in 7 crates
(2 directly)
71KB
1.5K
SLoC
anndists
This crate provides distances computations used in some related crates hnsw_rs, annembed and coreset
All distances implement the trait Distance:
pub trait Distance<T: Send + Sync> {
fn eval(&self, va: &[T], vb: &[T]) -> f32;
}
Functionalities
The crate provides:
-
usual distances as L1, L2, Cosine, Jaccard, Hamming for vectors of standard numeric types, Levenshtein distance on u16.
-
Hellinger distance and Jeffreys divergence between probability distributions (f32 and f64). It must be noted that the Jeffreys divergence (a symetrized Kullback-Leibler divergence) do not satisfy the triangle inequality. (Neither Cosine distance !).
-
Jensen-Shannon distance between probability distributions (f32 and f64). It is defined as the square root of the Jensen-Shannon divergence and is a bounded metric. See Nielsen F. in Entropy 2019, 21(5), 485.
-
A Trait to enable the user to implement its own distances. It takes as data slices of types T satisfying T:Serialize+Clone+Send+Sync. It is also possible to use C extern functions or closures.
-
Simd implementation is provided for the most often used case.
Implementation
Simd support is provided with the simdeez crate on Intel and partial implementation with std::simd for general case.
Building
Simd
-
The simd provided by the simdeez crate is accessible with the feature "simdeez_f" for x86_64 processors. Compile with cargo build --release --features "simdeez_f" .... To compile this crate on a M1 chip just do not activate this feature.
-
It is nevertheless possible to experiment with std::simd. Compiling with the feature stdsimd (cargo build --release --features "stdsimd"), activates the portable_simd feature on rust nightly. This requires nightly compiler. Only the Hamming distance with the u32x16 and u64x8 types and DistL1,DistL2 and DistDot on f32*16 are provided for now.
Benchmarks and Examples
The speed is illustated in the hnsw_rs, annembed crates
Contributions
Petter Egesund added the DistLevenshtein distance.
License
Licensed under either of
- Apache License, Version 2.0, LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0
- MIT license LICENSE-MIT or http://opensource.org/licenses/MIT
at your option.
Dependencies
~4.5–6.5MB
~112K SLoC