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
Summary: Fixes 2 bugs spotted by ASAN in the demo.
Reviewed By: wenjieX
Differential Revision: D25897053
fbshipit-source-id: fd2bed13faded42426cefc5ebe9d027adec78015
Changelog:
- changed license: BSD+Patents -> MIT
- propagates exceptions raised in sub-indexes of IndexShards and IndexReplicas
- support for searching several inverted lists in parallel (parallel_mode != 0)
- better support for PQ codes where nbit != 8 or 16
- IVFSpectralHash implementation: spectral hash codes inside an IVF
- 6-bit per component scalar quantizer (4 and 8 bit were already supported)
- combinations of inverted lists: HStackInvertedLists and VStackInvertedLists
- configurable number of threads for OnDiskInvertedLists prefetching (including 0=no prefetch)
- more test and demo code compatible with Python 3 (print with parentheses)
- refactored benchmark code: data loading is now in a single file
+ Add conda packages metadata (now building Faiss using conda's toolchain);
+ add Dockerfile for building conda packages (for all CUDA versions);
+ add working Dockerfile building faiss on Centos7;
+ simplify GPU build;
+ avoid falling back to CPU-only version (python);
+ simplify TravisCI config;
+ update INSTALL.md;
+ add configure flag for specifying target architectures (--with-cuda-arch);
+ fix Makefile for gpu tests;
+ fix various Makefile issues;
+ remove stale file (gpu/utils/DeviceUtils.cpp).
* Refactors Makefiles and add configure script.
* Give MKL higher priority in configure script.
* Clean up Linux example makefile.inc.
* Cleanup makefile.inc examples.
* Fix python clean Makefile target.
* Regen swig wrappers.
* Remove useless CUDAFLAGS variable.
* Fix python linking flags.
* Separate compile and link phase in python makefile.
* Add macro to look for swig.
* Add CUDA check in configure script.
* Cleanup make depend targets.
* Cleanup CUDA flags.
* Fix linking flags.
* Fix python GPU linking.
* Remove useless flags from python gpu module linking.
* Add check for cuda libs.
* Cleanup GPU targets.
* Clean up test target.
* Add cpu/gpu targets to python makefile.
* Clean up tutorial Makefile.
* Remove stale OS var from example makefiles.
* Clean up cuda example flags.
Matthijs Douze
Check Deng
Lucas Hosseini
Lucas Hosseini
Minjoon Seo