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Source: python-e3nn
#Testsuite: autopkgtest-pkg-python
Standards-Version: 4.7.3
Maintainer: Debian Deep Learning Team <debian-ai@lists.debian.org>
Uploaders:
Steffen Moeller <moeller@debian.org>,
Section: science
Priority: optional
Build-Depends:
debhelper-compat (= 13),
dh-sequence-python3,
python3-setuptools,
python3-all,
python3-opt-einsum-fx <!nocheck>,
pybuild-plugin-pyproject,
python3-pytest <!nocheck>,
python3-pytest-cov <!nocheck>,
python3-scipy <!nocheck>,
python3-time-machine <!nocheck>,
python3-torch <!nocheck>,
libtorch-dev <!nocheck>,
Vcs-Browser: https://salsa.debian.org/deeplearning-team/python-e3nn
Vcs-Git: https://salsa.debian.org/deeplearning-team/python-e3nn.git
Homepage: https://github.com/e3nn/e3nn
Package: python3-e3nn
Architecture: all
Section: python
Depends:
${python3:Depends},
${misc:Depends},
python3-sympy,
python3-scipy,
python3-torch,
python3-opt-einsum-fx,
Suggests:
libtorch-dev,
Description: provides 3D Euclidean neural networks
This library helps with the development of E(3) equivariant neural
networks. It contains fundamental mathematical operations such as
tensor products and spherical harmonics.
.
The technology supports the recognition of objects in 3D, at varying size
and rotation.
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