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cclauss efa1e3f64f Use print() function in both Python 2 and Python 3 (#1443) 
Summary:
Legacy __print__ statements are syntax errors in Python 3 but __print()__ function works as expected in both Python 2 and Python 3.

Pull Request resolved: https://github.com/facebookresearch/faiss/pull/1443

Reviewed By: LowikC

Differential Revision: D24157415

Pulled By: mdouze

fbshipit-source-id: 4ec637aa26b61272e5337d47b7796a330ce25bad
 		2020-10-08 00:27:29 -07:00
..
README.md Update README.md 2018-12-20 14:52:59 +01:00
bench_all_ivf.py fbshipit-source-id: 4f3cfa59471d548af93fe118d1b73d45bc648edf 2020-08-04 12:00:38 -07:00
bench_kmeans.py fbshipit-source-id: 4f3cfa59471d548af93fe118d1b73d45bc648edf 2020-08-04 12:00:38 -07:00
datasets.py fbshipit-source-id: 4f3cfa59471d548af93fe118d1b73d45bc648edf 2020-08-04 12:00:38 -07:00
parse_bench_all_ivf.py Use print() function in both Python 2 and Python 3 (#1443) 2020-10-08 00:27:29 -07:00
run_on_cluster_generic.bash Facebook sync (May 2019) + relicense (#838) 2019-05-28 16:17:22 +02:00

README.md

Benchmark of IVF variants

This is a benchmark of IVF index variants, looking at compression vs. speed vs. accuracy. The results are in this wiki chapter

The code is organized as:

  • datasets.py: code to access the datafiles, compute the ground-truth and report accuracies

  • bench_all_ivf.py: evaluate one type of inverted file

  • run_on_cluster_generic.bash: call bench_all_ivf.py for all tested types of indices. Since the number of experiments is quite large the script is structued so that the benchmark can be run on a cluster.

  • parse_bench_all_ivf.py: make nice tradeoff plots from all the results.

The code depends on Faiss and can use 1 to 8 GPUs to do the k-means clustering for large vocabularies.

It was run in October 2018 for the results in the wiki.