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
Summary:
As discussed in https://github.com/facebookresearch/faiss/issues/685, I'm going to add an NSG index to faiss. This PR which adds an NNDescent index is the first step as I commented [here ](https://github.com/facebookresearch/faiss/issues/685#issuecomment-760608431).
**Changes:**
1. Add an `IndexNNDescent` and an `IndexNNDescentFlat` which allow users to construct a KNN graph on a million scale dataset using CPU and search NN on it. The implementation part is put under `faiss/impl`.
2. Add compilation entries to `CMakeLists.txt` for C++ and `swigfaiss.swig` for Python. `IndexNNDescentFlat` could be directly called by users in C++ and Python.
3. `VisitedTable` struct in `HNSW.h` is moved into `AuxIndexStructures.h`.
3. Add a demo `demo_nndescent.cpp` to demonstrate the effectiveness.
**TODO**
1. Support index factor.
2. Implement `IndexNNDescentPQ` and `IndexNNDescentSQ`
3. More comments in the code.
Pull Request resolved: https://github.com/facebookresearch/faiss/pull/1654
Test Plan:
buck test //faiss/tests/:test_index_accuracy -- TestNNDescent
buck test //faiss/tests/:test_build_blocks -- TestNNDescentKNNG
Reviewed By: wickedfoo
Differential Revision: D26309716
Pulled By: mdouze
fbshipit-source-id: 2abade9708d29023f8bccbf77143e8eea14f66c4