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New packages: py-torch-cluster (#18262)

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* [py-torch-cluster] created template

* [py-torch-cluster] added dependencies

* [py-torch-cluster] setting TORCH_CUDA_ARCH_LIST

* [py-torch-cluster] limited extends

* [py-torch-cluster] depends on scipy

* [py-torch-cluster] added variant cuda and set env vars

* [py-torch-cluster] added homepage and description. removed fixmes

* [py-torch-cluster] flake8

* [py-torch-cluster] switched to depends_on from extends.

* [py-torch-cluster] added variant description

* [py-torch-cluster] added py-setuptools and py-pytest-runner as dependencies
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Jen Herting 2020-08-31 11:11:53 -04:00 committed by GitHub
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commit 122a4719ca
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var/spack/repos/builtin/packages/py-torch-cluster/package.py Normal file
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# Copyright 2013-2020 Lawrence Livermore National Security, LLC and other
# Spack Project Developers. See the top-level COPYRIGHT file for details.
#
# SPDX-License-Identifier: (Apache-2.0 OR MIT)
from spack import *
class PyTorchCluster(PythonPackage):
"""This package consists of a small extension library of
highly optimized graph cluster algorithms for the use in
PyTorch."""
homepage = "https://github.com/rusty1s/pytorch_cluster"
url = "https://github.com/rusty1s/pytorch_cluster/archive/1.5.7.tar.gz"
version('1.5.7', sha256='71701d2f7f3e458ebe5904c982951349fdb60e6f1654e19c7e102a226e2de72e')
variant('cuda', default=False, description='Enables CUDA support')
depends_on('python@3.6:', type=('build', 'run'))
depends_on('py-setuptools', type='build')
depends_on('py-pytest-runner', type='build')
depends_on('py-scipy', type=('build', 'run'))
depends_on('py-torch+cuda', when='+cuda')
depends_on('py-torch~cuda', when='~cuda')
def setup_build_environment(self, env):
if '+cuda' in self.spec:
cuda_arches = list(
self.spec['py-torch'].variants['cuda_arch'].value)
for i, x in enumerate(cuda_arches):
cuda_arches[i] = '{0}.{1}'.format(x[0:-1], x[-1])
env.set('TORCH_CUDA_ARCH_LIST', str.join(' ', cuda_arches))
env.set('FORCE_CUDA', '1')
env.set('CUDA_HOME', self.spec['cuda'].prefix)
else:
env.set('FORCE_CUDA', '0')