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//! Index interface and native implementations.
//!
//! This module hosts the vital [`Index`] trait, through which index building
//! and searching is made. It also contains [`index_factory`], a generic
//! function through which the user can retrieve most of the available index
//! implementations. A very typical usage scenario of this crate is to create
//! the index through this function, but some statically verified index types
//! are available as well.
//!
//! [`Index`]: trait.Index.html
//! [`index_factory`]: fn.index_factory.html
use crate::error::{Error, Result};
use crate::faiss_try;
use crate::metric::MetricType;
use crate::selector::IdSelector;
use std::ffi::CString;
use std::fmt::{self, Display, Formatter, Write};
use std::os::raw::c_uint;
use std::{mem, ptr};
use faiss_sys::*;
pub mod autotune;
pub mod flat;
pub mod id_map;
pub mod io;
pub mod io_flags;
pub mod ivf_flat;
pub mod lsh;
pub mod pretransform;
pub mod refine_flat;
pub mod scalar_quantizer;
#[cfg(feature = "gpu")]
pub mod gpu;
/// Primitive data type for identifying a vector in an index (or lack thereof).
///
/// Depending on the kind of index, it may be possible for vectors to share the
/// same ID.
#[repr(transparent)]
#[derive(Debug, Copy, Clone)]
pub struct Idx(idx_t);
impl Display for Idx {
fn fmt(&self, f: &mut Formatter) -> fmt::Result {
match self.get() {
None => f.write_char('x'),
Some(i) => i.fmt(f),
}
}
}
impl From<idx_t> for Idx {
fn from(x: idx_t) -> Self {
Idx(x)
}
}
impl Idx {
/// Create a vector identifier.
///
/// # Panic
///
/// Panics if the ID is too large (`>= 2^63`)
#[inline]
pub fn new(idx: u64) -> Self {
assert!(
idx < 0x8000_0000_0000_0000,
"too large index value provided to Idx::new"
);
let idx = idx as idx_t;
Idx(idx)
}
/// Create an identifier referring to no vector.
#[inline]
pub fn none() -> Self {
Idx(-1)
}
/// Check whether the vector identifier does not point to anything.
#[inline]
pub fn is_none(self) -> bool {
self.0 == -1
}
/// Check whether the vector identifier is not "none".
#[inline]
pub fn is_some(self) -> bool {
self.0 != -1
}
/// Retrieve the vector identifier as a primitive unsigned integer.
pub fn get(self) -> Option<u64> {
match self.0 {
-1 => None,
x => Some(x as u64),
}
}
/// Convert the vector identifier into a native `idx_t` value.
pub fn to_native(self) -> idx_t {
self.0
}
}
/// This comparison is not entirely reflexive: it returns always `false` if at
/// least one of the values is a `none`.
impl PartialEq<Idx> for Idx {
fn eq(&self, idx: &Idx) -> bool {
self.0 != -1 && idx.0 != -1 && self.0 == idx.0
}
}
/// This comparison is not entirely reflexive: it returns always `None` if at
/// least one of the values is a `none`.
impl PartialOrd<Idx> for Idx {
fn partial_cmp(&self, idx: &Idx) -> Option<std::cmp::Ordering> {
match (self.get(), idx.get()) {
(None, _) => None,
(_, None) => None,
(Some(a), Some(b)) => Some(a.cmp(&b)),
}
}
}
/// Interface for a Faiss index. Most methods in this trait match the ones in
/// the native library, whereas some others serve as getters to the index'
/// parameters.
///
/// Although all methods appear to be available for all index implementations,
/// some methods may not be supported. For instance, a [`FlatIndex`] stores
/// vectors sequentially, and so does not support `add_with_ids` nor
/// `remove_ids`. Users are advised to read the Faiss wiki pages in order
/// to understand which index algorithms support which operations.
///
/// [`FlatIndex`]: flat/struct.FlatIndex.html
pub trait Index {
/// Whether the Index does not require training, or if training is done already
fn is_trained(&self) -> bool;
/// The total number of vectors indexed
fn ntotal(&self) -> u64;
/// The dimensionality of the indexed vectors
fn d(&self) -> u32;
/// The metric type assumed by the index
fn metric_type(&self) -> MetricType;
/// Add new data vectors to the index.
/// This assumes a C-contiguous memory slice of vectors, where the total
/// number of vectors is `x.len() / d`.
fn add(&mut self, x: &[f32]) -> Result<()>;
/// Add new data vectors to the index with IDs.
/// This assumes a C-contiguous memory slice of vectors, where the total
/// number of vectors is `x.len() / d`.
/// Not all index types may support this operation.
fn add_with_ids(&mut self, x: &[f32], xids: &[Idx]) -> Result<()>;
/// Train the underlying index with the given data.
fn train(&mut self, x: &[f32]) -> Result<()>;
/// Similar to `search`, but only provides the labels.
fn assign(&mut self, q: &[f32], k: usize) -> Result<AssignSearchResult>;
/// Perform a search for the `k` closest vectors to the given query vectors.
fn search(&mut self, q: &[f32], k: usize) -> Result<SearchResult>;
/// Perform a ranged search for the vectors closest to the given query vectors
/// by the given radius.
fn range_search(&mut self, q: &[f32], radius: f32) -> Result<RangeSearchResult>;
/// Clear the entire index.
fn reset(&mut self) -> Result<()>;
/// Remove data vectors represented by IDs.
fn remove_ids(&mut self, sel: &IdSelector) -> Result<usize>;
/// Index verbosity level
fn verbose(&self) -> bool;
/// Set Index verbosity level
fn set_verbose(&mut self, value: bool);
}
impl<I> Index for Box<I>
where
I: Index,
{
fn is_trained(&self) -> bool {
(**self).is_trained()
}
fn ntotal(&self) -> u64 {
(**self).ntotal()
}
fn d(&self) -> u32 {
(**self).d()
}
fn metric_type(&self) -> MetricType {
(**self).metric_type()
}
fn add(&mut self, x: &[f32]) -> Result<()> {
(**self).add(x)
}
fn add_with_ids(&mut self, x: &[f32], xids: &[Idx]) -> Result<()> {
(**self).add_with_ids(x, xids)
}
fn train(&mut self, x: &[f32]) -> Result<()> {
(**self).train(x)
}
fn assign(&mut self, q: &[f32], k: usize) -> Result<AssignSearchResult> {
(**self).assign(q, k)
}
fn search(&mut self, q: &[f32], k: usize) -> Result<SearchResult> {
(**self).search(q, k)
}
fn range_search(&mut self, q: &[f32], radius: f32) -> Result<RangeSearchResult> {
(**self).range_search(q, radius)
}
fn reset(&mut self) -> Result<()> {
(**self).reset()
}
fn remove_ids(&mut self, sel: &IdSelector) -> Result<usize> {
(**self).remove_ids(sel)
}
fn verbose(&self) -> bool {
(**self).verbose()
}
fn set_verbose(&mut self, value: bool) {
(**self).set_verbose(value)
}
}
/// Sub-trait for native implementations of a Faiss index.
pub trait NativeIndex: Index {
/// Retrieve a pointer to the native index object.
fn inner_ptr(&self) -> *mut FaissIndex;
}
impl<NI: NativeIndex> NativeIndex for Box<NI> {
fn inner_ptr(&self) -> *mut FaissIndex {
(**self).inner_ptr()
}
}
/// Trait for a Faiss index that can be safely searched over multiple threads.
/// Operations which do not modify the index are given a method taking an
/// immutable reference. This is not the default for every index type because
/// some implementations (such as the ones running on the GPU) do not allow
/// concurrent searches.
///
/// Users of these methods should still note that batched querying is
/// considerably faster than running queries one by one, even in parallel.
pub trait ConcurrentIndex: Index {
/// Similar to `search`, but only provides the labels.
fn assign(&self, q: &[f32], k: usize) -> Result<AssignSearchResult>;
/// Perform a search for the `k` closest vectors to the given query vectors.
fn search(&self, q: &[f32], k: usize) -> Result<SearchResult>;
/// Perform a ranged search for the vectors closest to the given query vectors
/// by the given radius.
fn range_search(&self, q: &[f32], radius: f32) -> Result<RangeSearchResult>;
}
impl<CI: ConcurrentIndex> ConcurrentIndex for Box<CI> {
fn assign(&self, q: &[f32], k: usize) -> Result<AssignSearchResult> {
(**self).assign(q, k)
}
fn search(&self, q: &[f32], k: usize) -> Result<SearchResult> {
(**self).search(q, k)
}
fn range_search(&self, q: &[f32], radius: f32) -> Result<RangeSearchResult> {
(**self).range_search(q, radius)
}
}
/// Trait for Faiss index types known to be running on the CPU.
pub trait CpuIndex: Index {}
impl<CI: CpuIndex> CpuIndex for Box<CI> {}
/// Trait for Faiss index types which can be built from a pointer
/// to a native implementation.
pub trait FromInnerPtr: NativeIndex {
/// Create an index using the given pointer to a native object.
///
/// # Safety
///
/// `inner_ptr` must point to a valid, non-freed CPU index, and cannot be
/// shared across multiple instances. The inner index must also be
/// compatible with the target `NativeIndex` type according to the native
/// class hierarchy. For example, creating an `IndexImpl` out of a pointer
/// to `FaissIndexFlatL2` is valid, but creating a `FlatIndex` out of a
/// plain `FaissIndex` can cause undefined behavior.
unsafe fn from_inner_ptr(inner_ptr: *mut FaissIndex) -> Self;
}
/// Trait for Faiss index types which can be built from a pointer
/// to a native implementation.
pub trait TryFromInnerPtr: NativeIndex {
/// Create an index using the given pointer to a native object,
/// checking that the index behind the given pointer
/// is compatible with the target index type.
/// If the inner index is not compatible with the intended target type
/// (e.g. creating a `FlatIndex` out of a `FaissIndexLSH`),
/// an error is returned.
///
/// # Safety
///
/// This function is unable to check that
/// `inner_ptr` points to a valid, non-freed CPU index.
/// Moreover, `inner_ptr` must not be shared across multiple instances.
unsafe fn try_from_inner_ptr(inner_ptr: *mut FaissIndex) -> Result<Self>
where
Self: Sized;
}
/// A trait which provides a Clone implementation to native index types.
pub trait TryClone {
/// Create an independent clone of this index.
///
/// # Errors
///
/// May result in a native error if the clone operation is not
/// supported for the internal type of index.
fn try_clone(&self) -> Result<Self>
where
Self: Sized;
}
pub fn try_clone_from_inner_ptr<T>(val: &T) -> Result<T>
where
T: FromInnerPtr,
{
unsafe {
let mut new_index_ptr = ::std::ptr::null_mut();
faiss_try(faiss_clone_index(val.inner_ptr(), &mut new_index_ptr))?;
Ok(crate::index::FromInnerPtr::from_inner_ptr(new_index_ptr))
}
}
/// The outcome of an index assign operation.
#[derive(Debug, Clone, PartialEq)]
pub struct AssignSearchResult {
pub labels: Vec<Idx>,
}
/// The outcome of an index search operation.
#[derive(Debug, Clone, PartialEq)]
pub struct SearchResult {
pub distances: Vec<f32>,
pub labels: Vec<Idx>,
}
/// The outcome of an index range search operation.
#[derive(Debug, Clone, PartialEq)]
pub struct RangeSearchResult {
inner: *mut FaissRangeSearchResult,
}
impl RangeSearchResult {
pub fn nq(&self) -> usize {
unsafe { faiss_RangeSearchResult_nq(self.inner) }
}
pub fn lims(&self) -> &[usize] {
unsafe {
let mut lims_ptr = ptr::null_mut();
faiss_RangeSearchResult_lims(self.inner, &mut lims_ptr);
::std::slice::from_raw_parts(lims_ptr, self.nq() + 1)
}
}
/// getter for labels and respective distances (not sorted):
/// result for query `i` is `labels[lims[i] .. lims[i+1]]`
pub fn distance_and_labels(&self) -> (&[f32], &[Idx]) {
let lims = self.lims();
let full_len = lims.last().cloned().unwrap_or(0);
unsafe {
let mut distances_ptr = ptr::null_mut();
let mut labels_ptr = ptr::null_mut();
faiss_RangeSearchResult_labels(self.inner, &mut labels_ptr, &mut distances_ptr);
let distances = ::std::slice::from_raw_parts(distances_ptr, full_len);
let labels = ::std::slice::from_raw_parts(labels_ptr as *const Idx, full_len);
(distances, labels)
}
}
/// getter for labels and respective distances (not sorted):
/// result for query `i` is `labels[lims[i] .. lims[i+1]]`
pub fn distance_and_labels_mut(&self) -> (&mut [f32], &mut [Idx]) {
unsafe {
let buf_size = faiss_RangeSearchResult_buffer_size(self.inner);
let mut distances_ptr = ptr::null_mut();
let mut labels_ptr = ptr::null_mut();
faiss_RangeSearchResult_labels(self.inner, &mut labels_ptr, &mut distances_ptr);
let distances = ::std::slice::from_raw_parts_mut(distances_ptr, buf_size);
let labels = ::std::slice::from_raw_parts_mut(labels_ptr as *mut Idx, buf_size);
(distances, labels)
}
}
/// getter for distances (not sorted):
/// result for query `i` is `distances[lims[i] .. lims[i+1]]`
pub fn distances(&self) -> &[f32] {
self.distance_and_labels().0
}
/// getter for distances (not sorted):
/// result for query `i` is `distances[lims[i] .. lims[i+1]]`
pub fn distances_mut(&mut self) -> &mut [f32] {
self.distance_and_labels_mut().0
}
/// getter for labels (not sorted):
/// result for query `i` is `labels[lims[i] .. lims[i+1]]`
pub fn labels(&self) -> &[Idx] {
self.distance_and_labels().1
}
/// getter for labels (not sorted):
/// result for query `i` is `labels[lims[i] .. lims[i+1]]`
pub fn labels_mut(&mut self) -> &mut [Idx] {
self.distance_and_labels_mut().1
}
}
impl Drop for RangeSearchResult {
fn drop(&mut self) {
unsafe {
faiss_RangeSearchResult_free(self.inner);
}
}
}
/// Native implementation of a Faiss Index
/// running on the CPU.
#[derive(Debug)]
pub struct IndexImpl {
inner: *mut FaissIndex,
}
unsafe impl Send for IndexImpl {}
unsafe impl Sync for IndexImpl {}
impl CpuIndex for IndexImpl {}
impl Drop for IndexImpl {
fn drop(&mut self) {
unsafe {
faiss_Index_free(self.inner);
}
}
}
impl IndexImpl {
pub fn inner_ptr(&self) -> *mut FaissIndex {
self.inner
}
}
impl NativeIndex for IndexImpl {
fn inner_ptr(&self) -> *mut FaissIndex {
self.inner
}
}
impl FromInnerPtr for IndexImpl {
unsafe fn from_inner_ptr(inner_ptr: *mut FaissIndex) -> Self {
IndexImpl { inner: inner_ptr }
}
}
impl TryFromInnerPtr for IndexImpl {
unsafe fn try_from_inner_ptr(inner_ptr: *mut FaissIndex) -> Result<Self>
where
Self: Sized,
{
if inner_ptr.is_null() {
Err(Error::BadCast)
} else {
Ok(IndexImpl { inner: inner_ptr })
}
}
}
/// Index upcast trait.
///
/// If you need to store several different types of indexes in one collection,
/// you can cast all indexes to the common type `IndexImpl`.
/// # Examples
///
/// ```
/// # use faiss::{index::{IndexImpl, UpcastIndex}, FlatIndex, index_factory, MetricType};
/// let f1 = FlatIndex::new_l2(128).unwrap();
/// let f2 = index_factory(128, "Flat", MetricType::L2).unwrap();
/// let v: Vec<IndexImpl> = vec![
/// f1.upcast(),
/// f2,
/// ];
/// ```
///
pub trait UpcastIndex: NativeIndex {
/// Convert an index to the base `IndexImpl` type
fn upcast(self) -> IndexImpl;
}
impl<NI: NativeIndex> UpcastIndex for NI {
fn upcast(self) -> IndexImpl {
let inner_ptr = self.inner_ptr();
mem::forget(self);
unsafe { IndexImpl::from_inner_ptr(inner_ptr) }
}
}
impl_native_index!(IndexImpl);
impl TryClone for IndexImpl {
fn try_clone(&self) -> Result<Self>
where
Self: Sized,
{
try_clone_from_inner_ptr(self)
}
}
/// Use the index factory to create a native instance of a Faiss index, for `d`-dimensional
/// vectors. `description` should follow the exact guidelines as the native Faiss interface
/// (see the [Faiss wiki](https://github.com/facebookresearch/faiss/wiki/Faiss-indexes) for examples).
///
/// # Error
///
/// This function returns an error if the description contains any byte with the value `\0` (since
/// it cannot be converted to a C string), or if the internal index factory operation fails.
pub fn index_factory<D>(d: u32, description: D, metric: MetricType) -> Result<IndexImpl>
where
D: AsRef<str>,
{
unsafe {
let metric = metric as c_uint;
let description =
CString::new(description.as_ref()).map_err(|_| Error::IndexDescription)?;
let mut index_ptr = ::std::ptr::null_mut();
faiss_try(faiss_index_factory(
&mut index_ptr,
(d & 0x7FFF_FFFF) as i32,
description.as_ptr(),
metric,
))?;
Ok(IndexImpl { inner: index_ptr })
}
}
#[cfg(test)]
mod tests {
use super::{index_factory, Idx, Index, TryClone};
use crate::metric::MetricType;
#[test]
fn index_factory_flat() {
let index = index_factory(64, "Flat", MetricType::L2).unwrap();
assert_eq!(index.is_trained(), true); // Flat index does not need training
assert_eq!(index.ntotal(), 0);
}
#[test]
fn index_factory_flat_boxed() {
let index = index_factory(64, "Flat", MetricType::L2).unwrap();
let boxed = Box::new(index);
assert_eq!(boxed.is_trained(), true); // Flat index does not need training
assert_eq!(boxed.ntotal(), 0);
}
#[test]
fn index_factory_ivf_flat() {
let index = index_factory(64, "IVF8,Flat", MetricType::L2).unwrap();
assert_eq!(index.is_trained(), false);
assert_eq!(index.ntotal(), 0);
}
#[test]
fn index_factory_sq() {
let index = index_factory(64, "SQ8", MetricType::L2).unwrap();
assert_eq!(index.is_trained(), false);
assert_eq!(index.ntotal(), 0);
}
#[test]
fn index_factory_pq() {
let index = index_factory(64, "PQ8", MetricType::L2).unwrap();
assert_eq!(index.is_trained(), false);
assert_eq!(index.ntotal(), 0);
}
#[test]
fn index_factory_ivf_sq() {
let index = index_factory(64, "IVF8,SQ4", MetricType::L2).unwrap();
assert_eq!(index.is_trained(), false);
assert_eq!(index.ntotal(), 0);
let index = index_factory(64, "IVF8,SQ8", MetricType::L2).unwrap();
assert_eq!(index.is_trained(), false);
assert_eq!(index.ntotal(), 0);
}
#[test]
fn index_factory_hnsw() {
let index = index_factory(64, "HNSW8", MetricType::L2).unwrap();
assert_eq!(index.is_trained(), true); // training is not required
assert_eq!(index.ntotal(), 0);
}
#[test]
fn bad_index_factory_description() {
let r = index_factory(64, "fdnoyq", MetricType::L2);
assert!(r.is_err());
let r = index_factory(64, "Flat\0Flat", MetricType::L2);
assert!(r.is_err());
}
#[test]
fn index_clone() {
let mut index = index_factory(4, "Flat", MetricType::L2).unwrap();
let some_data = &[
7.5_f32, -7.5, 7.5, -7.5, 7.5, 7.5, 7.5, 7.5, -1., 1., 1., 1., 1., 1., 1., -1., 0., 0.,
0., 1., 1., 0., 0., -1.,
];
index.add(some_data).unwrap();
assert_eq!(index.ntotal(), 6);
let mut index2 = index.try_clone().unwrap();
assert_eq!(index2.ntotal(), 6);
let some_more_data = &[
100., 100., 100., 100., -100., 100., 100., 100., 120., 100., 100., 105., -100., 100.,
100., 105.,
];
index2.add(some_more_data).unwrap();
assert_eq!(index.ntotal(), 6);
assert_eq!(index2.ntotal(), 10);
}
#[test]
fn flat_index_search() {
let mut index = index_factory(8, "Flat", MetricType::L2).unwrap();
let some_data = &[
7.5_f32, -7.5, 7.5, -7.5, 7.5, 7.5, 7.5, 7.5, -1., 1., 1., 1., 1., 1., 1., -1., 0., 0.,
0., 1., 1., 0., 0., -1., 100., 100., 100., 100., -100., 100., 100., 100., 120., 100.,
100., 105., -100., 100., 100., 105.,
];
index.add(some_data).unwrap();
assert_eq!(index.ntotal(), 5);
let my_query = [0.; 8];
let result = index.search(&my_query, 5).unwrap();
assert_eq!(result.labels, vec![Idx(2), Idx(1), Idx(0), Idx(3), Idx(4)]);
assert!(result.distances.iter().all(|x| *x > 0.));
let my_query = [100.; 8];
let result = index.search(&my_query, 5).unwrap();
assert_eq!(result.labels, vec![Idx(3), Idx(4), Idx(0), Idx(1), Idx(2)]);
assert!(result.distances.iter().all(|x| *x > 0.));
let my_query = vec![
0., 0., 0., 0., 0., 0., 0., 0., 100., 100., 100., 100., 100., 100., 100., 100.,
];
let result = index.search(&my_query, 5).unwrap();
assert_eq!(
result.labels,
vec![
Idx(2),
Idx(1),
Idx(0),
Idx(3),
Idx(4),
Idx(3),
Idx(4),
Idx(0),
Idx(1),
Idx(2)
]
);
assert!(result.distances.iter().all(|x| *x > 0.));
}
#[test]
fn flat_index_assign() {
let mut index = index_factory(8, "Flat", MetricType::L2).unwrap();
assert_eq!(index.d(), 8);
assert_eq!(index.ntotal(), 0);
let some_data = &[
7.5_f32, -7.5, 7.5, -7.5, 7.5, 7.5, 7.5, 7.5, -1., 1., 1., 1., 1., 1., 1., -1., 0., 0.,
0., 1., 1., 0., 0., -1., 100., 100., 100., 100., -100., 100., 100., 100., 120., 100.,
100., 105., -100., 100., 100., 105.,
];
index.add(some_data).unwrap();
assert_eq!(index.ntotal(), 5);
let my_query = [0.; 8];
let result = index.assign(&my_query, 5).unwrap();
assert_eq!(result.labels, vec![Idx(2), Idx(1), Idx(0), Idx(3), Idx(4)]);
let my_query = [0.; 32];
let result = index.assign(&my_query, 5).unwrap();
assert_eq!(
result.labels,
vec![2, 1, 0, 3, 4, 2, 1, 0, 3, 4, 2, 1, 0, 3, 4, 2, 1, 0, 3, 4]
.into_iter()
.map(Idx)
.collect::<Vec<_>>()
);
let my_query = [100.; 8];
let result = index.assign(&my_query, 5).unwrap();
assert_eq!(
result.labels,
vec![3, 4, 0, 1, 2].into_iter().map(Idx).collect::<Vec<_>>()
);
let my_query = vec![
0., 0., 0., 0., 0., 0., 0., 0., 100., 100., 100., 100., 100., 100., 100., 100.,
];
let result = index.assign(&my_query, 5).unwrap();
assert_eq!(
result.labels,
vec![2, 1, 0, 3, 4, 3, 4, 0, 1, 2]
.into_iter()
.map(Idx)
.collect::<Vec<_>>()
);
index.reset().unwrap();
assert_eq!(index.ntotal(), 0);
}
#[test]
fn flat_index_range_search() {
let mut index = index_factory(8, "Flat", MetricType::L2).unwrap();
let some_data = &[
7.5_f32, -7.5, 7.5, -7.5, 7.5, 7.5, 7.5, 7.5, -1., 1., 1., 1., 1., 1., 1., -1., 0., 0.,
0., 1., 1., 0., 0., -1., 100., 100., 100., 100., -100., 100., 100., 100., 120., 100.,
100., 105., -100., 100., 100., 105.,
];
index.add(some_data).unwrap();
assert_eq!(index.ntotal(), 5);
let my_query = [0.; 8];
let result = index.range_search(&my_query, 8.125).unwrap();
let (distances, labels) = result.distance_and_labels();
assert!(labels == &[Idx(1), Idx(2)] || labels == &[Idx(2), Idx(1)]);
assert!(distances.iter().all(|x| *x > 0.));
}
}