Binary quantization

Cargo.toml

@@ -22,6 +22,7 @@ rayon = "1.10.0"
 roaring = "0.10.5"
 tempfile = "3.10.1"
 thiserror = "1.0.61"
+nohash = "0.2.0"
 
 [dev-dependencies]
 anyhow = "1.0.86"
@@ -30,6 +31,7 @@ clap = { version = "4.5.7", features = ["derive"] }
 env_logger = "0.11.3"
 insta = "1.39.0"
 instant-distance = "0.6.1"
+proptest = "1.5.0"
 rand = { version = "0.8.5", features = ["std_rng"] }
 tempfile = "3.10.1"
 

examples/compare_with_hnsw.rs

@@ -1,9 +1,8 @@
-use std::borrow::Cow;
 use std::num::NonZeroUsize;
 use std::time::Instant;
 
 use arroy::distances::Euclidean;
-use arroy::internals::{Leaf, UnalignedF32Slice};
+use arroy::internals::{Leaf, UnalignedVector};
 use arroy::{Database, Distance, ItemId, Reader, Result, Writer};
 use heed::{EnvOpenOptions, RwTxn};
 use instant_distance::{Builder, HnswMap, MapItem};
@@ -46,7 +45,8 @@ fn main() -> Result<()> {
     let search_k =
         if is_precise { NonZeroUsize::new(NUMBER_FETCHED * reader.n_trees() * 20) } else { None };
 
-    let arroy_results = reader.nns_by_item(&rtxn, 0, NUMBER_FETCHED, search_k, None)?.unwrap();
+    let arroy_results =
+        reader.nns_by_item(&rtxn, 0, NUMBER_FETCHED, search_k, None, None)?.unwrap();
     eprintln!("took {:.02?} to find into arroy", before.elapsed());
 
     let first = Point(reader.item_vector(&rtxn, 0)?.unwrap());
@@ -94,10 +94,10 @@ struct Point(Vec<f32>);
 
 impl instant_distance::Point for Point {
     fn distance(&self, other: &Self) -> f32 {
-        let this = UnalignedF32Slice::from_slice(&self.0);
-        let other = UnalignedF32Slice::from_slice(&other.0);
-        let p = Leaf { header: Euclidean::new_header(this), vector: Cow::Borrowed(this) };
-        let q = Leaf { header: Euclidean::new_header(other), vector: Cow::Borrowed(other) };
+        let this = UnalignedVector::from_slice(&self.0);
+        let other = UnalignedVector::from_slice(&other.0);
+        let p = Leaf { header: Euclidean::new_header(&this), vector: this };
+        let q = Leaf { header: Euclidean::new_header(&other), vector: other };
         arroy::distances::Euclidean::built_distance(&p, &q).sqrt()
     }
 }

examples/relevancy.rs

@@ -0,0 +1,209 @@
+use std::fmt;
+
+use rand::seq::SliceRandom;
+
+use arroy::distances::{
+    Angular, BinaryQuantizedAngular, BinaryQuantizedEuclidean, BinaryQuantizedManhattan,
+    DotProduct, Euclidean, Manhattan,
+};
+use arroy::internals::{self, Leaf, NodeCodec, UnalignedVector};
+use arroy::{Database, Distance, ItemId, Result, Writer};
+use heed::{EnvOpenOptions, RwTxn};
+use rand::rngs::StdRng;
+use rand::{Rng, SeedableRng};
+
+const TWENTY_HUNDRED_MIB: usize = 2 * 1024 * 1024 * 1024;
+const NUMBER_VECTORS: usize = 4_000;
+const OVERSAMPLING: usize = 3;
+
+fn main() {
+    let dimensions_tested = [256, 512, 1024, 1536, 3072];
+    let recall_tested = [1, 10, 50, 100];
+    let color: Vec<_> = (0..=100).step_by(10).map(|i| Recall(i as f32 / 100.0)).collect();
+
+    println!("Testing the following dimensions: {dimensions_tested:?}");
+    println!("Testing the following recall: @{recall_tested:?}");
+    println!("Oversampling of: x{OVERSAMPLING}");
+    println!("With color code: {color:?}");
+    println!("Starting...");
+    println!();
+
+    for (distance_name, func) in &[
+        (
+            BinaryQuantizedAngular::name(),
+            &measure_distance::<BinaryQuantizedAngular, Angular> as &dyn Fn(usize, usize) -> f32,
+        ),
+        (Angular::name(), &measure_distance::<Angular, Angular> as &dyn Fn(usize, usize) -> f32),
+        (
+            BinaryQuantizedManhattan::name(),
+            &measure_distance::<BinaryQuantizedManhattan, Manhattan>
+                as &dyn Fn(usize, usize) -> f32,
+        ),
+        (
+            Manhattan::name(),
+            &measure_distance::<Manhattan, Manhattan> as &dyn Fn(usize, usize) -> f32,
+        ),
+        (
+            BinaryQuantizedEuclidean::name(),
+            &measure_distance::<BinaryQuantizedEuclidean, Euclidean>
+                as &dyn Fn(usize, usize) -> f32,
+        ),
+        (
+            Euclidean::name(),
+            &measure_distance::<Euclidean, Euclidean> as &dyn Fn(usize, usize) -> f32,
+        ),
+        (
+            DotProduct::name(),
+            &measure_distance::<DotProduct, DotProduct> as &dyn Fn(usize, usize) -> f32,
+        ),
+    ] {
+        let now = std::time::Instant::now();
+        println!("{distance_name}");
+        // The openAI dimensions
+        for dimensions in [256, 512, 1024, 1536, 3072] {
+            let mut recall = Vec::new();
+            for number_fetched in recall_tested {
+                let rec = (func)(number_fetched, dimensions);
+                recall.push(Recall(rec));
+            }
+            println!("For {dimensions:4} dim, recall: {recall:3?}");
+        }
+        println!("Took {:?}", now.elapsed());
+        println!();
+    }
+}
+
+struct Recall(f32);
+
+impl fmt::Debug for Recall {
+    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
+        match self.0 {
+            // red
+            f32::NEG_INFINITY..=0.25 => write!(f, "\x1b[1;31m")?,
+            // yellow
+            0.25..=0.5 => write!(f, "\x1b[1;33m")?,
+            // green
+            0.5..=0.75 => write!(f, "\x1b[1;32m")?,
+            // blue
+            0.75..=0.90 => write!(f, "\x1b[1;34m")?,
+            // cyan
+            0.90..=0.999 => write!(f, "\x1b[1;36m")?,
+            // underlined cyan
+            0.999..=f32::INFINITY => write!(f, "\x1b[1;4;36m")?,
+            _ => (),
+        }
+        write!(f, "{:.2}\x1b[0m", self.0)
+    }
+}
+
+fn measure_distance<ArroyDistance: Distance, PerfectDistance: Distance>(
+    number_fetched: usize,
+    dimensions: usize,
+) -> f32 {
+    let dir = tempfile::tempdir().unwrap();
+    let env =
+        unsafe { EnvOpenOptions::new().map_size(TWENTY_HUNDRED_MIB).open(dir.path()) }.unwrap();
+
+    let mut rng = StdRng::seed_from_u64(13);
+    let points = generate_points(&mut rng, NUMBER_VECTORS, dimensions);
+    let mut wtxn = env.write_txn().unwrap();
+
+    let database = env
+        .create_database::<internals::KeyCodec, NodeCodec<ArroyDistance>>(&mut wtxn, None)
+        .unwrap();
+    load_into_arroy(&mut rng, &mut wtxn, database, dimensions, &points).unwrap();
+
+    let reader = arroy::Reader::open(&wtxn, 0, database).unwrap();
+
+    let mut correctly_retrieved = 0;
+    for _ in 0..100 {
+        let querying = points.choose(&mut rng).unwrap();
+
+        let relevant = partial_sort_by::<PerfectDistance>(
+            points.iter().map(|(i, v)| (*i, v.as_slice())),
+            &querying.1,
+            number_fetched,
+        );
+
+        let mut arroy = reader
+            .nns_by_item(&wtxn, querying.0, number_fetched * OVERSAMPLING, None, None, None)
+            .unwrap()
+            .unwrap();
+        arroy.truncate(number_fetched);
+
+        for ret in arroy {
+            if relevant.iter().any(|(id, _, _)| *id == ret.0) {
+                correctly_retrieved += 1;
+            }
+        }
+    }
+
+    // println!("recall@{number_fetched}: {}", correctly_retrieved as f32 / relevant.len() as f32);
+    correctly_retrieved as f32 / (number_fetched as f32 * 100.0)
+}
+
+fn partial_sort_by<'a, D: Distance>(
+    mut vectors: impl Iterator<Item = (ItemId, &'a [f32])>,
+    sort_by: &[f32],
+    elements: usize,
+) -> Vec<(ItemId, &'a [f32], f32)> {
+    let mut ret = Vec::with_capacity(elements);
+    ret.extend(vectors.by_ref().take(elements).map(|(i, v)| (i, v, distance::<D>(sort_by, v))));
+    ret.sort_by(|(_, _, left), (_, _, right)| left.total_cmp(right));
+
+    if ret.is_empty() {
+        return ret;
+    }
+
+    for (item_id, vector) in vectors {
+        let distance = distance::<D>(sort_by, vector);
+        if distance < ret.last().unwrap().2 {
+            match ret.binary_search_by(|(_, _, d)| d.total_cmp(&distance)) {
+                Ok(i) | Err(i) => {
+                    ret.pop();
+                    ret.insert(i, (item_id, vector, distance))
+                }
+            }
+        }
+    }
+
+    ret
+}
+
+fn distance<D: Distance>(left: &[f32], right: &[f32]) -> f32 {
+    let left = UnalignedVector::from_slice(left);
+    let left = Leaf { header: D::new_header(&left), vector: left };
+    let right = UnalignedVector::from_slice(right);
+    let right = Leaf { header: D::new_header(&right), vector: right };
+
+    D::built_distance(&left, &right)
+}
+
+fn load_into_arroy<D: Distance>(
+    rng: &mut StdRng,
+    wtxn: &mut RwTxn,
+    database: Database<D>,
+    dimensions: usize,
+    points: &[(ItemId, Vec<f32>)],
+) -> Result<()> {
+    let writer = Writer::<D>::new(database, 0, dimensions);
+    for (i, vector) in points.iter() {
+        writer.add_item(wtxn, *i, &vector[..])?;
+    }
+    writer.build(wtxn, rng, None)?;
+
+    Ok(())
+}
+
+fn generate_points<R: Rng>(mut rng: R, count: usize, dimensions: usize) -> Vec<(ItemId, Vec<f32>)> {
+    let mut points = Vec::with_capacity(count);
+    for item_id in 0..count {
+        let mut vector = vec![0.0; dimensions];
+        for scalar in &mut vector {
+            *scalar = rng.gen_range(-1.0..1.0);
+        }
+        // rng.try_fill(&mut vector[..]).unwrap();
+        points.push((item_id.try_into().unwrap(), vector));
+    }
+    points
+}

examples/search_movies.rs

@@ -27,7 +27,7 @@ fn main() {
     #[rustfmt::skip]
     let query: Vec<f32> = vec![-0.016822422, -0.021621706, 0.00019239318, 0.054372, 0.034900583, -0.011089119, 0.042128928, 0.02026509, 0.0019038923, -0.0014809829, -0.033832666, -0.029640282, -0.054234847, 0.018665258, -0.055895746, 0.0753006, 0.0061977296, 0.032228395, 0.022795584, -0.058140032, 0.026109613, -0.029421866, 0.04866331, 0.020661665, 0.017602501, 0.020653117, 0.046483666, 0.042843442, -0.045545023, -0.0017392042, 0.012052985, -0.0058927303, 0.032480225, 0.009872672, 0.024758337, -0.013354463, -0.044432696, -0.03226193, -0.059227727, 0.0078192735, 0.013650394, 0.0031477972, 0.005877705, 0.0068786396, 0.002517114, -0.011458909, 0.008640344, 0.044904687, -0.0047290456, -0.012748338, -0.048921518, 0.07827129, 0.005205742, -0.021857478, -0.02370976, 0.041743826, -0.016076453, -0.011403813, -0.025544455, -0.0046601044, -0.021723151, 0.007303265, -0.0136509575, 0.0073000537, -0.005085544, 0.04384241, -0.018964743, 0.03818674, -0.09198379, -0.032043297, -0.0067259674, 0.019887544, 0.005341308, 0.0050093965, 0.054900724, -0.020799952, 0.020495495, 0.01472667, 0.019677797, 0.037550557, -0.010920308, 0.03371257, 0.0020930816, 0.03709999, -0.036922902, -0.049608115, 0.0154750785, 0.007696657, -0.058294553, 0.045302838, -0.023393214, -0.060448237, -0.005798211, 0.053323198, 0.04070376, -0.0028753958, 0.051668108, -0.0069777397, 0.033418525, 0.016234992, -0.033323497, -0.0074829464, -0.008664235, -0.05547656, -0.11400871, -0.03518515, -0.0056998464, 0.01812429, -0.031799175, -0.0073341345, -0.06147767, -0.003742939, -0.004249079, -0.013904026, -0.00065635156, 0.09179383, 0.004267396, 0.00015509031, -0.049766053, 0.029881846, 0.10485467, -0.03120661, 0.014043553, 0.08671136, 0.059179407, 0.029454986, -0.0122302845, 0.06451508, 0.021481989, -0.06484224, 0.018707344, 0.022344032, -0.004790084, -0.04705671, 0.016396629, -0.03346155, 0.0064264126, -0.0053360737, 0.06672058, -0.0078784805, -0.016174054, 0.026566355, -0.046398066, 0.0025418145, 0.046905387, -0.020884424, -0.051193744, -0.031737294, -0.009927951, 0.023741305, -0.058117628, 0.051733956, -0.025581324, -0.030992776, 0.008804903, 0.04388304, 0.013213721, 0.004467152, -0.04988626, 0.0069321035, 0.039403677, 0.019677948, -0.066907056, 0.018572355, 0.013511877, -0.010518738, 0.010099771, -0.003633823, -0.0631501, -0.025649378, -0.043461364, 0.0016490245, 0.064196914, 0.033599235, -0.013222726, 0.015318823, 0.0771801, -0.0070276, -0.031138066, 0.0055310773, -0.09972089, 0.05066132, 0.047467627, -0.03498512, -0.03416252, -0.018362196, 0.040274452, -0.031371195, 0.030042851, 0.016328678, -0.05765591, -0.048823263, 0.054553114, -0.02033182, 0.046627544, 0.016558101, -0.0033715998, 0.0006232865, -0.0065704435, 0.008104579, 0.016307961, -0.041840676, 0.048135996, -0.018808063, -0.036892023, -0.0450471, 0.02718623, -0.036660295, -0.022694368, 0.005702901, -0.022678563, 0.0013453028, 0.07429447, -0.034700394, -0.032727163, 0.00596015, 0.034842487, -0.027818438, -0.00051779655, -0.014468772, 0.033954486, 0.04148899, -0.0829876, -0.015300944, 0.015376903, 0.09567573, 0.036652327, -0.049033575, -0.04484115, 0.041701544, -0.057027884, 0.0069984253, -0.0053272387, 0.025826871, 0.002177651, -0.030157669, 0.007895542, -0.014717798, 0.054724272, -0.05034077, -0.016694192, 0.038352106, -0.060709346, 0.08236629, -0.0096279215, 0.014632059, 0.025158316, -0.0009260515, -0.043707818, -0.01941624, -0.0118600605, -0.035666965, 0.037794825, 0.014687504, 0.038666032, -0.075831376, -0.038647566, -0.048394937, 0.031239703, 0.029136332, -0.00076040986, -0.015906896, 0.03718925, -0.0140040675, -0.037951406, -0.041062936, -0.06529122, 0.011906159, -0.011368897, 0.0060307034, 0.03684682, 0.031995844, -0.033985753, -0.018714348, -0.012443444, -0.007389346, 0.03257332, -0.04580996, -0.026579294, -0.024290696, -0.025647637, 0.022456668, -0.02420987, -0.065709755, -0.02623659, -0.028259972, 0.019707581, -0.022819564, -0.0409341, 0.026851093, 0.031858675, 0.048687093, -0.013439109, 0.011736404, 0.016420575, 0.03451187, -0.0059358296, 0.015338021, 0.04402986, 0.033739056, 0.033959225, 0.0068245684, -0.0143376645, -0.0007635987, -0.01949658, 0.016379116, 0.018640755, -0.06126936, -0.22691156, 0.015514225, -0.0010716971, 0.0044359663, 0.03258783, -0.0018310734, 0.010761778, -0.033404265, 0.005418415, 0.028870588, -0.0366465, 0.025508897, -0.003327967, -0.025249101, 0.041501254, -0.06906739, -0.03184493, -0.041302733, -0.03037772, 0.015740091, 0.008446552, -0.0459613, -0.022405358, -0.0036640046, 0.017842831, 0.003960712, -0.025942408, -0.038227286, -0.045894515, -0.01752483, 0.017444108, -0.051017836, 0.029609472, 0.008688325, 0.020816054, 0.008120903, 0.03892946, -0.033378396, 0.02176841, 0.027685048, -0.012064678, -0.079198286, -0.04271553, 0.005021753, 0.066962436, -0.03443632, -0.004004281, -0.050009515, -0.01630804, 0.06379373, 0.055116866, 0.027930314, 0.043325268, 0.02733439, -0.015951807, 0.059688378, -0.0075212875, 0.03786285, -0.04638327, -0.043671872, 0.043587692, 0.011264745, -0.059823193, 0.008415408, -0.040225852, -0.05263509, -0.0038932117, -0.047234535, 0.05749084, 0.029582193, -0.012869698, 0.027698075, -0.014221754, -0.05440618, 0.007839065, -0.028753158, -0.029088387, -0.00039888048, 0.012631819, 0.0038486738, -0.059913363, -0.0034661351, 0.011339918, 0.005836589, -0.018044928, -0.035229705, 0.0015524679, -0.035521194, -0.028409205, 0.0004174717, 0.060292065, -0.009710763, -0.04719587, 0.034226153, 0.04258676, 0.03754591, 0.056335006, -0.012293127, 0.03885916, -0.011872468, 0.026709288, -0.030494772, -0.0027441443, 0.01256448, 0.0070703924, 0.011282641, -0.03820788, -0.029001744, 0.0024300558, -0.0032799696, 0.037857816, 0.001686728, 0.056249045, -0.01862739, 0.04376537, -0.0019654054, 0.050269835, 0.035223164, 0.0059567657, 0.013870472, -0.001804614, 0.027300585, -0.03382222, -0.041098855, -0.060636565, 0.0047175046, 0.029142305, 0.06523361, 0.028681634, -0.023454288, -0.018000197, -0.030090509, -0.0046562785, -0.04519735, 0.047884777, -0.00059952086, -0.03280122, -0.08012555, 0.008639195, 0.01629006, 0.032155965, 0.034481294, 0.021274198, 0.010470909, 0.022913199, -0.035904404, 0.041294016, -0.00987633, -0.021613108, 0.012205929, 0.005322071, 0.025864823, 0.08942025, -0.08067831, -0.014871667, -0.034839284, 0.028048998, -0.0063091223, 0.037978478, -0.055790387, 0.0045954804, -0.042958327, 0.02137769, -0.008589233, -0.00062141696, 0.052822173, 0.034125473, -0.015106767, 0.0030919765, -0.0072712647, 0.0056287237, 0.019516133, -0.031278323, 0.025771588, 0.01701546, 0.019516064, 0.016180338, 0.01349268, 0.011978184, 0.011838524, -0.0050102035, -0.06970658, 0.022854539, -0.004192521, 0.0577575, -0.003954721, -0.054374386, -0.027609108, 0.0134023735, 0.010305641, -0.011130317, 0.052328475, 0.014928648, -0.013976018, -0.07100651, -0.06789901, -0.031873316, -0.011598853, 0.029284442, -0.04940027, 0.0100974385, -0.02187546, -0.062819175, 0.0069366414, 0.052176703, -0.06834835, 0.013463273, -0.0013379813, 0.005786334, 0.017775143, -0.01291353, -0.016923305, -0.049682386, -0.034103107, 0.010883184, -0.055132758, 0.025268175, -0.025599582, 0.015927013, -0.03237898, -0.027073668, -0.034358867, -0.027672807, 0.022677394, -0.03531693, 0.010573503, 0.00032215187, 0.0066956943, -0.051510572, -0.029456092, 0.05758612, -0.038166363, -0.00999853, 0.05758596, -0.006796505, 0.028503977, -0.024184246, 0.054051045, 0.0040905816, 0.099899694, 0.06076009, 0.011753628, -0.03253187, -0.0035343366, 0.02351163, 0.03206495, 0.004892613, -0.04530409, -0.0056237346, -0.006101407, 0.019704496, -0.010228795, 0.027814431, 0.020409154, 0.033115197, -0.07446951, -0.042142425, 0.03928483, -0.022784598, -0.003539396, -0.0074683367, 0.043651864, 0.007761874, 0.022063423, 0.05344986, 0.05065469, 0.029476669, -0.028968832, 0.023550583, -0.022291148, 0.055309687, -0.053843252, 0.020895477, -0.0148687605, 0.012166838, 0.0033556349, -0.07022937, -0.059401378, 0.013194393, -0.0419862, -0.0070434613, 0.030479655, -0.053955454, -0.031870224, 0.034511264, -0.047943473, 0.0069080396, 0.026099209, -0.012516935, 0.0003174421, -0.006716995, 0.07027558, 0.038463045, -0.016081728, 0.05018074, -0.062176052, 0.08961092, 0.03679902, 0.011107996, -0.0032339245, -0.0118898135, 0.013669906, 0.056221563, -0.049234938, 0.003090264, 0.01062722, -0.008937757, -0.08464787, -0.032616463, 0.055935893, 0.006192905, -0.014768529, 0.04930304, 0.053852808, -0.036349185, -0.037947245, 0.0076732435, -0.040889677, 0.022189876, 0.015142795, 0.005928425, -0.009679575, 0.039194115, 0.0041091475, 0.035120673, 0.016776932, -0.04100678, 0.041131947, 0.040904496, 0.047341976, 0.029321635, 0.030489001, -0.0135518275, 0.038717188, 0.0017859036, -0.044703316, -0.007397534, 0.029149175, -0.00021891313, 0.019795585, -0.054424375, 0.010228703, -0.0057461066, 0.05096695, 0.05683213, -0.018136851, -0.0030009004, -0.033427265, 0.010878728, 0.050759643, 0.040795874, 0.019920254, -0.026135486, -0.07642272, 0.035290312, 0.004655317, 0.0043676766, -0.010411962, -0.0076723946, 0.015248613, 0.008905208, -0.0002423048, 0.03892336, -0.025703456, -0.021123456, -0.00066909986, 0.04459856, 0.052217484, -0.017885901, -0.015303531, 0.0057848957, -0.036129624, -0.0736907, 0.035401847, -0.025658514, -0.0082354145, -0.0012491915, -0.040769547, -0.039205503, 0.05530217, -0.014954734, 0.0056790086, -0.04454665, -0.028425619, -0.034654, -0.057087515, -0.0224583, -0.005496095, -0.009889468, -0.05025576, -0.009459795, -0.00871503, 0.021968294, 0.0074964114, -0.032455806, -0.005696087, 0.005180231, 0.056079067, -0.03189999, 0.045113377, 0.061360348, 0.01839327, -0.053088665, 0.04942768, 0.014662789, 0.06641078, -0.008998172, -0.009717696, -0.079248, 0.047506567, 0.04778238, 0.025009798, -0.03899872, 0.009850679, -0.04399064, -0.053494785, 0.055456433, 0.026770461, -0.011158729, -0.073486604, -0.04088162, -0.023263954, -0.022185653, 0.03401001, -0.034742568, 0.043794204, 0.004035502, 0.011585448, -0.009235968, 0.031503983, 0.016500674, -0.012498497, -0.05733327, 0.0024852154, -0.02377962, -0.072548844, -0.008489325, 0.01825339, 0.032909963, -0.023669574, 0.0022601841, -0.008336443, 0.0041536367, 0.007989558, -0.035507284, -0.03951105, 0.0069870483, 0.04283141, -0.05102877, -0.025309727, 0.052937508, -0.014378752, -0.012047669, -0.024964543, -0.00071902486, 0.009493713, 0.024152702, 0.022622166, 0.06481285, 0.0022744837];
     let now = Instant::now();
-    let _ret = reader.nns_by_vector(&rtxn, &query, 20, None, None).unwrap();
+    let _ret = reader.nns_by_vector(&rtxn, &query, 20, None, None, None).unwrap();
     println!("Louis's query took {:?}", now.elapsed());
 
     let mut durations = Vec::new();
@@ -37,7 +37,7 @@ fn main() {
     println!("Starts querying all documents ...");
     for (id, _) in vectors.into_iter() {
         let now = Instant::now();
-        reader.nns_by_item(&rtxn, id, 20, None, None).unwrap().unwrap();
+        reader.nns_by_item(&rtxn, id, 20, None, None, None).unwrap().unwrap();
         // reader.nns_by_item(&rtxn, id, 20, None, Some(&filter)).unwrap().unwrap();
         durations.push(now.elapsed());
     }