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Format: 3.0 (quilt)
Source: faiss
Binary: libfaiss-dev, python3-faiss
Architecture: any
Version: 1.11.0-1
Maintainer: Debian Deep Learning Team <debian-ai@lists.debian.org>
Uploaders: Mo Zhou <lumin@debian.org>, Shengqi Chen <harry@debian.org>
Homepage: https://github.com/facebookresearch/faiss
Description: efficient similarity search and clustering of dense vectors
 Faiss is a library for efficient similarity search and clustering of dense
 vectors. It contains algorithms that search in sets of vectors of any size, up
 to ones that possibly do not fit in RAM. It also contains supporting code for
 evaluation and parameter tuning. Faiss is written in C++ with complete wrappers
 for Python/numpy. Some of the most useful algorithms are implemented on the
 GPU. It is developed by Facebook AI Research.
Standards-Version: 4.7.2
Vcs-Browser: https://salsa.debian.org/deeplearning-team/faiss
Vcs-Git: https://salsa.debian.org/deeplearning-team/faiss.git
Testsuite: autopkgtest
Testsuite-Triggers: build-essential, c++-compiler, cmake, g++, libgtest-dev, ninja-build, python3-all
Build-Depends: cmake, debhelper-compat (= 13), dh-python, dh-sequence-numpy3, dh-sequence-python3, libblas-dev, libgtest-dev, liblapack-dev, libpython3-all-dev, python3-all-dev:any, python3-numpy, python3-setuptools, swig
Package-List:
 libfaiss-dev deb libdevel optional arch=any
 python3-faiss deb python optional arch=any
Checksums-Sha1:
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 6e5aed15f9fcf5229053becdde794c929c761d57 9212 faiss_1.11.0-1.debian.tar.xz
Checksums-Sha256:
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Files:
 7a162a1d29b33311f4ef29aefdf0f211 1138777 faiss_1.11.0.orig.tar.gz
 27497096053dd26e5240e6b7e534bafb 9212 faiss_1.11.0-1.debian.tar.xz

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