6 Commits

Author SHA1 Message Date
Matthijs Douze
b8fe92dfee contrib clustering module (#2217)
Summary:
Pull Request resolved: https://github.com/facebookresearch/faiss/pull/2217

This diff introduces a new Faiss contrib module that contains:
- generic k-means implemented in python (was in distributed_ondisk)
- the two-level clustering code, including a simple function that runs it on a Faiss IVF index.
- sparse clustering code (new)

The main idea is that that code is often re-used so better have it in contrib.

Reviewed By: beauby

Differential Revision: D34170932

fbshipit-source-id: cc297cc56d241b5ef421500ed410d8e2be0f1b77
2022-02-28 14:18:47 -08:00
Lucas Hosseini
ac74f576f7 fbshipit-source-id: 4f3cfa59471d548af93fe118d1b73d45bc648edf 2020-08-04 12:00:38 -07:00
Lucas Hosseini
cd38e82f0c
Facebook sync 2020-07-31 (#1308) 2020-08-03 22:15:02 +02:00
Lucas Hosseini
2ba6985f81 Facebook sync 20191129 (#1048)
Looks good!
2019-12-04 07:21:02 +01:00
Matthijs Douze
a9a475b003
Update distributed_kmeans.py 2019-08-29 15:34:14 +02:00
Matthijs Douze
8d08912453
Ondisk distributed index implementation (#930)
Adds the code for the distributed on-disk index
2019-08-29 13:44:08 +02:00