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Format: 3.0 (quilt)
Source: faiss
Binary: libfaiss-dev, python3-faiss
Architecture: any
Version: 1.10.0-2build1
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: 4.7.0
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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 3a678af6abb01e6fdc9877953532d038c9508848 9164 faiss_1.10.0-2build1.debian.tar.xz
Checksums-Sha256:
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Files:
 f31edf2492808b27cc963d0ab316a205 1110709 faiss_1.10.0.orig.tar.gz
 349be66cb4f24cd41f387366115945d4 9164 faiss_1.10.0-2build1.debian.tar.xz

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