Summary:
Pull Request resolved: https://github.com/facebookresearch/faiss/pull/1906
This PR implemented LSQ/LSQ++, a vector quantization technique described in the following two papers:
1. Revisiting additive quantization
2. LSQ++: Lower running time and higher recall in multi-codebook quantization
Here is a benchmark running on SIFT1M for 64 bits encoding:
```
===== lsq:
mean square error = 17335.390208
training time: 312.729779958725 s
encoding time: 244.6277096271515 s
===== pq:
mean square error = 23743.004672
training time: 1.1610801219940186 s
encoding time: 2.636141061782837 s
===== rq:
mean square error = 20999.737344
training time: 31.813055515289307 s
encoding time: 307.51959800720215 s
```
Changes:
1. Add LocalSearchQuantizer object
2. Fix an out of memory bug in ResidualQuantizer
3. Add a benchmark for evaluating quantizers
4. Add tests for LocalSearchQuantizer
Pull Request resolved: https://github.com/facebookresearch/faiss/pull/1862
Test Plan:
```
buck test //faiss/tests/:test_lsq
buck run mode/opt //faiss/benchs/:bench_quantizer -- lsq pq rq
```
Reviewed By: beauby
Differential Revision: D28376369
Pulled By: mdouze
fbshipit-source-id: 2a394d38bf75b9de0a1c2cd6faddf7dd362a6fa8
Summary:
This diff includes:
- progressive dimension k-means.
- the ResidualQuantizer object
- GpuProgressiveDimIndexFactory so that it can be trained on GPU
- corresponding tests
- reference Python implementation of the same in scripts/matthijs/LCC_encoding
Reviewed By: wickedfoo
Differential Revision: D27608029
fbshipit-source-id: 9a8cf3310c8439a93641961ca8b042941f0f4249
Summary:
After initial positive feedback to the idea in https://github.com/facebookresearch/faiss/issues/1741 from mdouze, here are the patches
I currently have as a basis for discussion.
Matthijs suggests to not bother with the deprecation warnings at all, which is fine for me
as well, though I would normally still advocate to provide users with _some_ advance notice
before removing parts of an interface.
Fixes https://github.com/facebookresearch/faiss/issues/1741
PS. The deprecation warning is only shown once per session (per class)
PPS. I have tested in https://github.com/conda-forge/faiss-split-feedstock/pull/32 that the respective
classes remain available both through `import faiss` and `from faiss import *`.
Pull Request resolved: https://github.com/facebookresearch/faiss/pull/1742
Reviewed By: mdouze
Differential Revision: D26978886
Pulled By: beauby
fbshipit-source-id: b52e2b5b5b0117af7cd95ef5df3128e9914633ad
Summary:
## Description:
This diff implemented Navigating Spreading-out Graph (NSG) which accepts a KNN graph as input.
Here is the interface of building an NSG graph:
``` c++
void IndexNSG::build(idx_t n, const float *x, idx_t *knn_graph, int GK);
```
where `GK` is the nb of neighbors per node and `knn_graph[i * GK + j]` is the j-th neighbor of node i.
The `add` method is not implemented yet.
The unit tests could be found in `tests/test_nsg.cpp`.
mdouze beauby Maybe I need some advice on how to design the interface and support python.
Pull Request resolved: https://github.com/facebookresearch/faiss/pull/1707
Test Plan: buck test //faiss/tests/:test_index -- TestNSG
Reviewed By: beauby
Differential Revision: D26748498
Pulled By: mdouze
fbshipit-source-id: 3280f705fb1b5f9c8cc5efeba63b904c3b832544
Summary: add getstate / setstate to serialize indexes. Seems to work properly with object ownership etc.
Reviewed By: wickedfoo
Differential Revision: D26521228
fbshipit-source-id: ebbe08cfe2c15af2aa5b7ea1fc1bf87546066c23
