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Format: 3.0 (quilt)
Source: faiss
Binary: libfaiss-dev, python3-faiss
Architecture: any
Version: 1.13.2-1build1
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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 97da3c9e862c069fc56cc7dd2d2d71e569755914 9144 faiss_1.13.2-1build1.debian.tar.xz
Checksums-Sha256:
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Files:
 980ac68e45ddae0efefcc7d2382c73cd 1279483 faiss_1.13.2.orig.tar.gz
 a715a87c28c40679072d2aab14c21c46 9144 faiss_1.13.2-1build1.debian.tar.xz

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