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Format: 3.0 (quilt)
Source: faiss
Binary: libfaiss-dev, python3-faiss
Architecture: any
Version: 1.10.0-1
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: 4.7.0
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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 f7656b88c0c493c15108a97e959f4f7fcef8c3ab 8104 faiss_1.10.0-1.debian.tar.xz
Checksums-Sha256:
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Files:
 f31edf2492808b27cc963d0ab316a205 1110709 faiss_1.10.0.orig.tar.gz
 a8ff347c1d20f55aeafd5289db8d6e7b 8104 faiss_1.10.0-1.debian.tar.xz

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