Module hnsw_rs::prelude

source ·

Re-exports§

  • pub use crate::api::*;
  • pub use crate::hnsw::*;
  • pub use crate::filter::*;
  • pub use crate::hnswio::*;

Structs§

  • DistCFFI
    A structure to implement Distance Api for type DistCFnPtr<T>, i.e distance provided by a C function pointer.
    It must be noted that this can be used in Julia via the macro @cfunction to define interactiveley a distance function , compile it on the fly and sent it to Rust via the init_hnsw_{f32, i32, u16, u32, u8} function defined in libext
  • DistCosine
    Cosine distance : implemented for f32, f64, i64, i32 , u16
  • DistDot
    This is essentially the Cosine distance but we suppose all vectors (graph construction and request vectors have been l2 normalized to unity BEFORE INSERTING in HNSW!.
    No control is made, so it is the user responsability to send normalized vectors everywhere in inserting and searching.
  • DistFn
    This structure is to let user define their own distance with closures.
  • DistHamming
    Hamming distance. Implemented for u8, u16, u32, i32 and i16 The distance returned is normalized by length of slices, so it is between 0. and 1.
  • DistHellinger
    A structure to compute Hellinger distance between probalilities. Vector must be >= 0 and normalized to 1.
  • DistJaccard
    Jaccard distance. Implemented for u8, u16 , u32.
  • DistJeffreys
    A structure to compute Jeffreys divergence between probalilities. If p and q are 2 probability distributions the “distance” is computed as: sum (p[i] - q[i]) * ln(p[i]/q[i])
  • DistJensenShannon
    Jensen-Shannon distance.
    It is defined as the square root of the Jensen–Shannon divergence and is a metric. Vector must be >= 0 and normalized to 1! The distance computation does not check that.
  • DistL1
    L1 distance : implemented for i32, f64, i64, u32 , u16 , u8 and with Simd avx2 for f32
  • DistL2
    L2 distance : implemented for i32, f64, i64, u32 , u16 , u8 and with Simd avx2 for f32
  • DistLevenshtein
    Levenshtein distance. Implemented for u16
  • DistPtr
    This structure uses a Rust function pointer to define the distance. For commodity it can build upon a fonction returning a f64. Beware that if F is f64, the distance converted to f32 can overflow!
  • NoDist
    Special forbidden computation distance. It is associated to a unit NoData structure This is a special structure used when we want to only reload the graph from a previous computation possibly from an foreign language (and we do not have access to the original type of data from the foreign language).

Constants§

Traits§

  • Distance
    This is the basic Trait describing a distance. The structure Hnsw can be instantiated by anything satisfying this Trait. The crate provides implmentations for L1, L2 , Cosine, Jaccard, Hamming. For other distances implement the trait possibly with the newtype pattern

Functions§