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

* [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

1 files changed, 39 insertions, 0 deletions

diff --git a/var/spack/repos/builtin/packages/py-torch-cluster/package.py b/var/spack/repos/builtin/packages/py-torch-cluster/package.py
new file mode 100644
index 0000000000..4d59fce476
--- /dev/null
+++ b/var/spack/repos/builtin/packages/py-torch-cluster/package.py
@@ -0,0 +1,39 @@
+# 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')