a996a4a052
Summary: Pull Request resolved: https://github.com/facebookresearch/faiss/pull/2582 A few more or less cosmetic improvements * Index::idx_t was in the Index object, which does not make much sense, this diff moves it to faiss::idx_t * replace multiprocessing.dummy with multiprocessing.pool * add Alexandr as a core contributor of Faiss in the README ;-) ``` for i in $( find . -name \*.cu -o -name \*.cuh -o -name \*.h -o -name \*.cpp ) ; do sed -i s/Index::idx_t/idx_t/ $i done ``` For the fbcode deps: ``` for i in $( fbgs Index::idx_t --exclude fbcode/faiss -l ) ; do sed -i s/Index::idx_t/idx_t/ $i done ``` Reviewed By: algoriddle Differential Revision: D41437507 fbshipit-source-id: 8300f2a3ae97cace6172f3f14a9be3a83999fb89 |
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| .. | ||
| CMakeLists.txt | ||
| README.md | ||
| demo_auto_tune.py | ||
| demo_client_server_ivf.py | ||
| demo_imi_flat.cpp | ||
| demo_imi_pq.cpp | ||
| demo_ivfpq_indexing.cpp | ||
| demo_nndescent.cpp | ||
| demo_ondisk_ivf.py | ||
| demo_residual_quantizer.cpp | ||
| demo_sift1M.cpp | ||
| demo_weighted_kmeans.cpp | ||
README.md
Demos for a few Faiss functionalities
demo_auto_tune.py
Demonstrates the auto-tuning functionality of Faiss
demo_ondisk_ivf.py
Shows how to construct a Faiss index that stores the inverted file data on disk, eg. when it does not fit in RAM. The script works on a small dataset (sift1M) for demonstration and proceeds in stages:
0: train on the dataset
1-4: build 4 indexes, each containing 1/4 of the dataset. This can be done in parallel on several machines
5: merge the 4 indexes into one that is written directly to disk (needs not to fit in RAM)
6: load and test the index