* feat: live_reload for read-only quantized vectors
* Propagate live_reload params through quantized chunked storage
Thread fs, deleted_points, new_points and hw_counter through the full
quantized live_reload chain instead of synthesizing empty deltas and a
disposable hardware counter at the leaf storages.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* fix: use LiveReload trait in chunked mmap
* fix: use LiveReload trait
* fix: compiler errors
---------
Co-authored-by: generall <andrey@vasnetsov.com>
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* feat: add read-only QuantizedVectors generic over UniversalRead
Introduce `QuantizedVectorsRead<S>` / `QuantizedVectorStorageRead<S>`, a
read-only counterpart of `QuantizedVectors` organized like
`VectorStorageReadEnum`: generic over the `UniversalRead` backend `S`,
opened from existing on-disk data, with no create/upsert/builder path and
no disk writes.
Highlights:
- Keep both in-RAM (`*Ram`) and read-only mmap (`*Mmap`) variants; drop the
appendable `*ChunkedMmap` variants (the only mutable ones).
- All bulk reads go through `S`: add `QuantizedRamStorage::from_universal_read`
and `MultivectorOffsetsStorageRam::open`, and make
`MultivectorOffsetsStorageMmap` generic over `S` (default `MmapFile`).
- Share scorer construction between the read-write and read-only enums via a
`QuantizedScorerDispatch` trait, so only the per-variant match is duplicated
while the datatype/distance and per-query dispatch live once in the builder.
Tested: read-only vs read-write scorer parity (scalar/binary/product, single
and multivector, RAM and mmap), covering both `raw_scorer` and
`raw_internal_scorer`.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* refactor: route quantized RAM loading through UniversalRead
Follow-up to the read-only quantized work, removing direct-filesystem reads
and load-path duplication:
- `EncodedVectors{U8,PQ,Bin,TQ}::load` now take a `UniversalRead` filesystem
and read metadata via `read_json_via` instead of `fs::read_to_string` —
every read flows through universal IO. Single-vector `load` returns
`common::universal_io::Result`; `validate_storage_vector_size` stays
`std::io::Result`.
- Add `common::universal_io::OneshotFile<S>`: a thin RAII wrapper over any
`UniversalRead` handle that evicts the data from cache via `clear_ram_cache`
on drop (the universal-IO counterpart of `fs::OneshotFile`).
- Collapse `QuantizedRamStorage::{from_file, from_universal_read}` into one
`from_file<S: UniversalRead>`. It reads the whole file in a single access
(no separate `len()` round-trip — cheaper on S3-like backends) and loads via
the new `VolatileChunkedVectors::extend`, which inserts one chunk per
`copy_from_slice` instead of one vector at a time.
- RW callers pass the local `READ_FS` (mmap) backend; the read-only loader
passes its `S`.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* feat: load appendable (chunked) quantization format read-only
`storage_type` only selects the on-disk layout, so the read-only quantized
storage must be able to load both — the immutable flat format and the
appendable chunked format (produced only by Binary/TurboQuant). Previously the
read-only loader rejected the Mutable layout outright.
- Add `QuantizedChunkedStorageRead<S>` and `MultivectorOffsetsStorageChunkedRead<S>`,
read-only wrappers over the existing `ChunkedVectorsRead<_, S>` primitive
(mirrors the dense read-view's chunked read storage). Generic over the
`UniversalRead` backend, on-disk, no write path.
- Add `BinaryChunked`/`TQChunked` (+ multi) variants to `QuantizedVectorStorageRead`
and wire them through every accessor and the scorer dispatch.
- Route `storage_type == Mutable` to the chunked read variants in the loader and
drop the blanket rejection.
- Tests: parametrize the read-only/read-write parity tests over `storage_type`
and add chunked (Mutable) cases for binary/turbo, single and multivector.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* refactor: split quantized chunked & multivector storage into modules
`quantized_chunked_mmap_storage.rs` and `quantized_multivector_storage.rs` had
grown to hold several unrelated structures, making them hard to navigate.
Convert each into a module (pure code movement, no behavior change):
- quantized_chunked_mmap_storage/{read_write,read_only}.rs — the appendable
mmap storage + builder vs. the read-only chunked storage.
- quantized_multivector_storage/{mod,offsets}.rs — the core
`QuantizedMultivectorStorage` + offset traits stay in mod.rs; the four
`MultivectorOffsetsStorage*` backends move to offsets.rs.
Public paths are unchanged via re-exports.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* refactor: single source of truth for quantized vector size
The on-disk stride (bytes per quantized vector), including the binary
`u8`(multi)/`u128`(single) word-type choice, was independently re-derived in
every load/open site with no compile-time link — the kind of value-level
duplication that silently diverges (it already caused the binary multi
`u8`/`u128` bug).
Extract it into one place:
- `QuantizedVectors::quantized_vector_size(quantization_config, vector_parameters, is_multi)`
and the `QuantizedVectorsConfig::quantized_vector_size(is_multi)` convenience.
Route every reader through it:
- read-only `open_single`/`open_multi` and the read-write `{scalar,pq,binary,turbo}`
loaders now hoist `config.quantized_vector_size(is_multi)` once instead of
recomputing the per-method formula per branch.
The create (write) path keeps its own computation for now; it stays guarded by
`validate_storage_vector_size` and the read-only/read-write parity tests.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* refactor: flat-match quantized loaders on a shared QuantizedStorageKind
The loaders chose the concrete storage variant via a nested
`method × (storage_type / is_ram)` match, re-derived independently in the
read-only and read-write paths — hard to follow and easy to drift.
- Add `QuantizedStorageKind` + `QuantizedVectorsConfig::storage_kind(on_disk)`
(and `is_ram(on_disk)`): the single place the method × backend decision lives.
- Both loaders now compute the kind once and use a flat 10-arm match:
- read-only `open_single`/`open_multi`;
- read-write `load_single`/`load_multi` (consolidating the four per-method
`{scalar,pq,binary,turbo}/load.rs` files, which are removed).
Both matches are exhaustive over the same enum, so the read and read-write
variants can no longer fall out of sync without a compile error.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* refactor: genericize write-capable chunked quantized storages over Fs
Drop the hardcoded `MmapFile` specialization from `QuantizedChunkedStorage`,
`QuantizedChunkedStorageBuilder`, and `MultivectorOffsetsStorageChunked`. They
now expose the `Fs` backend (defaulting to `MmapFile`) and accept the fs handle
as a parameter, matching the read-only variants.
Introduce a single shared `ReadFile` type alias and `READ_FS` value handle in
the `quantized_vectors` module root, used by the create, load, and storage enum
paths so the local-file backend is named in one place.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* refactor: move is_in_ram_or_mmap match into UniversalKind
Deduplicate the identical kind-to-residency match in the read-only and
write-capable chunked quantized storages by adding
UniversalKind::is_in_ram_or_mmap.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* fix: adapt TurboVectorStorage to quantized rename + update_from move
Integration fix after rebasing onto dev's TurboQuant work:
- QuantizedChunkedMmapStorage -> QuantizedChunkedStorage<MmapFile>
- update_from moved off the VectorStorage trait onto an inherent method,
matching the per-kind sub-trait refactor; TurboVectorStorage implements
neither DenseVectorStorage<T> nor the other kind traits.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* Add `EncodedStorage::for_each_in_batch` method
* Implement `for_each_in_batch` method for `QuantizedChunkedMmapStorage`
* Add `EncodedVectors::for_each_in_batch` method
* Add `EncodedVectors::score` method
* Implement `score_stored_batch` for `QuantizedQueryScorer` and `Quanti…
* Remove `TElement` and `TMetric` type parameters from `QuantizedMultiQ…
* Use `QuantizedMultiQueryScorer` when building `raw_internal_scorer`...
* Add TQ+ ErrorCorrection on top of renorm
Per-coordinate shift+scale fits each rotated, length-rescaled coord onto
the codebook's N(0, 1) grid before quantization. EncodedVectorsTQ::encode
runs a first pass to fit the stats when TQMode::Plus.
Scoring stays correct under renorm's `scaling_factor` framework:
- Asymmetric: precompute_query scales `Q .* D'` and stashes `qm = ⟨Q, M⟩`
on EncodedQueryTQ; score_precomputed adds qm to raw_dot before applying
scaling_factor.
- Symmetric: scalar slow path computes `Σ X+_a X+_b D'_i² + xm_a + xm_b
− ⟨M, M⟩` (xm stored per vector in extras, mm_const cached on
ErrorCorrection). Result feeds the existing `* v1_scale * v2_scale` arms.
SIMD reuse for this path is a follow-up.
Storage layout: TQMode::Plus extras are 4 bytes longer (xm appended after
scaling_factor). Zero-vector inputs skip EC application so renorm's
existing zero-norm guard keeps producing score ≈ 0 within tolerance.
VectorStats refactor: streaming `VectorStatsBuilder` so the Plus first
pass can feed Welford with a reused buffer; `build` now takes `dim`
directly and is generic over `T: Into<f64>`.
Integration tests run on both Normal and Plus via rstest cases.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* Fix TQ+ recall regression on non-uniform per-coord variance data
Two compounding bugs in the renorm + TQ+ composition:
1. centroid_norm was measured on `X+` centroids, which have chi-squared
norm distribution across vectors (~10% spread for d=256). renorm
assumed `cn` should be deterministic `sqrt(d)` (just quantization
drift), so the per-vector correction ended up amplifying intrinsic
chi-squared noise into ranking error. Fix: revert EC per coord before
measuring (`c · D' + M`), matching llama-turbo-quant. The reverted
centroids approximate `rescaled` which has length `sqrt(d)` exactly
by construction. dequantize follows the same convention so the
stored `scaling_factor = l2/cn` round-trips back to the original l2.
2. Asymmetric query path pre-scaled `Q* = R_q · D'` before SIMD encoding.
The SIMD encoder normalizes by `max(|input|)`, so a query whose coords
span 5× magnitude (which `R_q · D'` does on real data) loses precision
on the small-D' coords. Fix: keep `rotated` unscaled, store it as a
side field on `EncodedQueryTQ`, and use a scalar decode-and-dot path
for TQ+ (`Σ R_q_i · c_i · D'_i + qm`). SIMD support for this is a
follow-up.
Catches both via `recall_skewed_data` test on data with 8 spike-variance
input coords. Without the fixes, Bits4 Plus dropped to 0.93 vs Normal
0.98; after the fixes, Plus tracks Normal within 2%.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* TQ+ asymmetric: skip the SIMD encoding entirely
The TQ+ asymmetric path doesn't use the SIMD-encoded query — it goes
through `score_precomputed_ec` with `rotated_query`. So building the
SIMD form was wasted work + memory. Make `data` an `Option` and only
populate it for the cases that actually use it (Normal mode any distance,
TQ+ L1 via dequantize fallback).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* Revert TQ+ to SIMD scoring path
The whole point of TQ+ is that scoring code-paths stay identical between
Normal and Plus modes — only the query precomputation changes. We
pre-scale `Q* = R_q · D'` so the existing SIMD raw_dot computes
`⟨Q · D', X+⟩` directly, then add `qm` and apply renorm's scaling_factor.
Drops `score_precomputed_ec` and `EncodedQueryTQ::rotated_query`. The
recall regression that motivated the scalar fallback was entirely from
the `compute_centroid_norm` bug (measuring `‖X+‖` instead of `‖rescaled‖`)
fixed in the prior commit; SIMD precision was a red herring.
`recall_skewed_data` confirms: Bits4 Normal=0.984 / Plus=0.978, Bits2
Normal=0.902 / Plus=0.908.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* TQ+ Bits1: widen query encoding to 12 bits
For 1-bit storage with TQ+, the per-coord `D' = 1/scale` pre-scaling on
the query can push some coords toward the small end of the SIMD encoder's
integer range (which normalizes by `max(|input|)`). At 8 bits those small
coords lose precision; at 12 bits the rounding error drops ~10× per the
existing `test_query_dotprod_matches_reference` parity test.
`Query1bitSimd` is already generic over BITS so this is just a new
`EncodedQueryTQData::Bits1Wide(Query1bitSimd<12>)` variant + a TQ+/Bits1
dispatch in `precompute_query`. Bits2/Bits4 don't need this — their
storage is fine-grained enough that query precision isn't the bottleneck,
and their SIMD encoders aren't generic over BITS today.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* are you happy fmt
* TQ+ Bits1Wide: bump to 16-bit query quantization (kernel max)
12 bits helped on real datasets but not enough — push to the kernel's
ceiling of 16. `Query1bitSimd<BITS>` asserts `BITS ∈ [2, 16]`, so this
is the most precision the existing SIMD path can give us before needing
a wider integer kernel.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* TQ+: shift by per-coord median, not mean
For 1-bit storage the codebook boundary sits at 0, so post-shift values
are quantized purely by sign. Median is the sign-balance point of the
distribution; mean isn't (skewed coords pull mean off the median).
On anisotropic embeddings — dbpedia-openai being the reference case —
mean-based shift produced a ~60/40 biased sign distribution per coord,
losing 1-bit's representational capacity. Median-based shift restores
50/50 and matches llama-turbo-quant's behavior. Higher bit-widths are
less sensitive but still benefit; the codebook boundaries still lie at
distribution-percentile-aware positions when the data is centered on
the median.
Median requires per-coord samples in memory, so cap the stats pass at
10K vectors. Estimates converge fast (~√N) — 10K is plenty even for
million-vector indexes. The encoding pass still processes every vector.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* TQ+ Bits1Wide: revert to 12-bit query quantization
The recall regression on anisotropic data was the mean-vs-median shift,
not query precision. 12 bits is enough headroom for the per-coord D'
pre-scaling and avoids the extra storage of the 16-bit form.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* TQ+ Bits1Wide: bump back to 16-bit query quantization
12 bits helped a bit but not enough on the real dataset. Bump to the
kernel's ceiling. If 16 still isn't enough, the next step is checking
whether the gap is real (re-measure llama branch) before widening the
SIMD integer kernel itself.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* are you happy clippy
* use mean
* 1bit error correction
* review remarks
* are you happy clippy
* review remarks
---------
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* Add mincore-based memory stats to MmapFile
Add `resident_bytes()`, `disk_bytes()`, and `probe_memory_stats()` methods
to `MmapFile` for measuring page cache residency via `mincore(2)`. This is
the foundation for per-collection memory usage reporting.
Also extract `page_size()` as a public function in `mmap::advice`, replacing
the internal `PAGE_SIZE_MASK` with a direct page size cache.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* [AI] introduce trait for reporting memory usage per component
* [AI] memory reporter implementation for vector storage
* [AI] implement MemoryReporter for QuantizedVectors
* [AI] implement MemoryReporter for VectorIndexEnum
* Implement MemoryReporter for IdTrackerEnum with RAM estimation
Add ram_usage_bytes() to all ID tracker types and their data structures:
- PointMappings, CompressedPointMappings, CompressedVersions,
CompressedInternalToExternal, CompressedExternalToInternal
- MutableIdTracker, ImmutableIdTracker, InMemoryIdTracker
All ID trackers load their data into RAM (none use mmap for working data).
Files are reported as OnDisk (persistence only), actual RAM footprint
is reported via extra_ram_bytes. Uses struct destructuring to ensure
new fields trigger compile errors if not accounted for.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* [AI] implement MemoryReporter for PayloadStorageEnum and adjust FileStorageIntent
* [AI] implement MemoryReporter for PayloadStorageEnum and adjust FileStorageIntent
* [AI] implement MemoryReporter for payload indexes: in-ram structures memory consumtion computation + caching
* [AI] implement MemoryReporter for payload indexes: in-ram structures memory consumtion computation + caching
* [AI] segment-level memory usage report
* [AI] Block 3: Aggregation Layer and Data Model + internal api for remote shard
* [AI] REST API handler
* fmt
* [AI] clippy fixes
* [AI] macos fix + proxy segment fix
* [AI] make text index estimation a bit more correct
* fix is_on_disk reporting for dense_vector_storage
* fix after rebase
* [AI] deep account for quantized vectors RAM usage + unify chunk size + shring volatile storage after load
* remove debug log
* cache in test
* make manual test easier to run
* rollback chunk size diff, but keep it for test only
* review fixes
* Use exhaustive match
* Use div_ceil on bits everywhere
It does not seem to be strictly necessary because the number of bits
should already be a multiple of the used container size bytes. Still
it's good practice to be careful with this calculation.
* Improve heap size bytes for encoded product quantization vectors
* Include vector stats for binary quantized vectors
* In volatile chunked vectors, include heap allocated vector
* Include rest of heap allocated structures for mutable map index
* In mutable geo index, the hash map is also heap allocated
* Update tests/manual/test_memory_reporting.py
Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
---------
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: timvisee <tim@visee.me>
Co-authored-by: Tim Visée <tim+github@visee.me>
Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
* Unify parking_lot/arc_lock feature
* Move lib/common/{io,memory}/* -> lib/common/common/*
- Mmap-related items are grouped into `common::mmap` sub-module:
- `memory/src/chunked_utils.rs` -> `common/src/mmap/chunked.rs`
- `memory/src/madvise.rs` -> `common/src/mmap/advice.rs`
- `memory/src/mmap_ops.rs` -> `common/src/mmap/ops.rs`
- `memory/src/mmap_type_readonly.rs` -> `common/src/mmap/mmap_readonly.rs`
- `memory/src/mmap_type.rs` -> `common/src/mmap/mmap_rw.rs`
- Filesystem-related items are grouped into `common::fs` sub-module:
- `common/src/fs.rs` -> `common/src/fs/sync.rs`
- `io/src/file_operations.rs` -> `common/src/fs/ops.rs`
- `io/src/move_files.rs` -> `common/src/fs/move.rs`
- `io/src/safe_delete.rs` -> `common/src/fs/safe_delete.rs`
- `memory/src/checkfs.rs` -> `common/src/fs/check.rs`
- `memory/src/fadvise.rs` -> `common/src/fs/fadvise.rs`
- Rest is moved straight into `common`:
- `io/src/storage_version.rs` -> `common/src/storage_version.rs`
The old `io` and `memory` are now hollow crates that re-export items
from `common`. These hollow crates will be removed in next commits.
* Replace uses of `io` and `memory` with new paths in `common`
Since `io` and `memory` are just re-exports of `common`, these
replacements are no-op.
* Remove `io` and `memory` crates
* Implement `Optional<T>` type
Define a type with the same presumed layout as `Option<T>`, but with defined behavior.
* Make `transmute_*` functions unsafe
The functions `memory::mmap_ops::transmute_*` are inherently unsafe, but
are not marked as are. Their usage is documented, but it is not always clear
if the code is correct.
* Add `CsrHeader` to resolve another unsoundness
Tuples have no defined layout.
* Create and load for an appendable quantization
remove feature flag
more todo
review remarks
review remarks
* fix after rebase
* Rename is_appendable to supports_appendable
---------
Co-authored-by: timvisee <tim@visee.me>
* Quantization storage builder for chunked mmap
* fix after rebase
* Update lib/segment/src/vector_storage/quantized/quantized_chunked_mmap_storage.rs
---------
Co-authored-by: Tim Visée <tim+github@visee.me>
* Add common::typelevel module
* Use common::typelevel for score_bytes
* Revert "Split FilteredScorer into FilteredScorer and FilteredQuantizedScorer"
This reverts commit ff3a93ee95.
* FilteredQuantizedScorer
* Extract `struct Filters` from `FilteredScorer` and `FilteredQuantizedScorer`
* Revert "QuantizedVectors::query_scorer_bytes"
This reverts commit 9dee824afd.
* Partial revert "Add QueryScorerBytes::score_bytes"
This reverts commit d80af4f698, but keeps
the QueryScorerBytes trait while removing implementations.
* Partial revert "Add EncodedVectorsBytes::score_point_vs_bytes"
This partially reverts commit c741e42f9a.
- trait `EncodedVectorsBytes` and its implementations: reverted/removed
- calls to `EncodedVectorsBytes::score_point_vs_bytes`: replaced with
calls to `EncodedVectors::score_bytes`
* Remove unused method FilteredScorer::new_from_raw
* use vector statistics for scalar bq query
* fix minor error
* remove test_binary_scalar_internal test
* do NOT use special file for storing vector stats
---------
Co-authored-by: generall <andrey@vasnetsov.com>
* # This is a combination of 7 commits.
* SameAsStorage default value
* fix coderabbit warnings
* neon for u8 bq
* sse for u8 bq
* fix windows build
* rename function
* add comments
* fmt
* fix arm build
* review remarks
* bq encodings
* are you happy clippy
* are you happy clippy
* are you happy clippy
* are you happy clippy
* gpu tests
* update models
* are you happy fmt
* move additional bits to the end
* fix tests
* Welford's Algorithm
* review remarks
* are you happy clippy
* remove debug println in test
* coderabit nitpicks
* remove unnecessary clone and partialeq
* Use f64 for Welford's Algorithm
* try fix ci
* revert cargo-nextest
* add debug assertions
* Make EncodedVectors::EncodedQuery associated type
* Make EncodedStorageBuilder::Storage associated type
* Make QueryScorer::TVector associated type
* Remove TVector from RawScorerImpl generic parameters
* Fix vector_io_read for multivector recommendation
* fix
* cleanup
* single disposable
* do not use disposable hardware counter for quantized multivectors
* wip: implement explicit populate and clear_cache functions for all components
* fmt
* implement clear and populate for vector storages
* fmt
* implement clear and populate for payload storage
* wip: implement explicit populate and clear_cache functions payload indexes
* implement explicit populate and clear_cache functions payload indexes
* fix clippy on CI
* only compile posix_fadvise on linux
* only compile posix_fadvise on linux
* implement explicit populate and clear_cache functions for quantized vectors
* fmt
* remove post-load prefault
* fix typo
* implement is-on-disk for payload indexes, implement clear on drop for segment, implement clear after segment build
* fmt
* also evict quantized vectors after optimization
* re-use and replace advise_dontneed
* Bump Rust edition to 2024
* gen is a reserved keyword now
* Remove ref mut on references
* Mark extern C as unsafe
* Wrap unsafe function bodies in unsafe block
* Geo hash implements Copy, don't reference but pass by value instead
* Replace secluded self import with parent
* Update execute_cluster_read_operation with new match semantics
* Fix lifetime issue
* Replace map_or with is_none_or
* set_var is unsafe now
* Reformat
* parent 33b2c176cb
author Ivan Pleshkov <pleshkov.ivan@gmail.com> 1729676438 +0200
committer Ivan Pleshkov <pleshkov.ivan@gmail.com> 1732012991 +0100
parent 33b2c176cb
author Ivan Pleshkov <pleshkov.ivan@gmail.com> 1729676438 +0200
committer Ivan Pleshkov <pleshkov.ivan@gmail.com> 1732012977 +0100
parent 33b2c176cb
author Ivan Pleshkov <pleshkov.ivan@gmail.com> 1729676438 +0200
committer Ivan Pleshkov <pleshkov.ivan@gmail.com> 1732012901 +0100
parent 33b2c176cb
author Ivan Pleshkov <pleshkov.ivan@gmail.com> 1729676438 +0200
committer Ivan Pleshkov <pleshkov.ivan@gmail.com> 1732012766 +0100
parent 33b2c176cb
author Ivan Pleshkov <pleshkov.ivan@gmail.com> 1729676438 +0200
committer Ivan Pleshkov <pleshkov.ivan@gmail.com> 1732012730 +0100
vulkan api wrapper crate
fmt
gpu is not a workspace member
exclude gpu from workspace
disable tests for gpu crate
ash version up
change collection for pipeline builder
gpu test
gpu is not optional
check device features
remove feature
make all fields private
more comments
are you happy fmt
qdrant team as authors
gpu vectors
move changes from magic branch
move storage updates
are you happy codespell
are you happy clippy
don't make storage_impl public
review remarks
are you happy clippy
are you happy fmt
* Update lib/segment/src/index/hnsw_index/gpu/gpu_vector_storage/tests.rs
Co-authored-by: Tim Visée <tim+github@visee.me>
* review remarks
---------
Co-authored-by: Tim Visée <tim+github@visee.me>
