New package: py-torch-sparse (#18270)

* [py-torch-sparse] created template

* [py-torch-sparse] added dependencies

* [py-torch-sparse] extends py-torch-scatter

* [py-torch-sparse] added variant cuda and setting env vars

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

* [py-torch-sparse] flake8

* [py-torch-sparse] added variant description

* [py-torch-sparse] extends -> depends on

* [py-torch-sparse] added dependencies of py-setuptools and py-pytest-runner

1 files changed, 38 insertions, 0 deletions

diff --git a/var/spack/repos/builtin/packages/py-torch-sparse/package.py b/var/spack/repos/builtin/packages/py-torch-sparse/package.py
new file mode 100644
index 0000000000..4c16b1d8a7
--- /dev/null
+++ b/var/spack/repos/builtin/packages/py-torch-sparse/package.py
@@ -0,0 +1,38 @@
+# 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 PyTorchSparse(PythonPackage):
+    """This package consists of a small extension library of
+    optimized sparse matrix operations with autograd support."""
+
+    homepage = "https://github.com/rusty1s/pytorch_sparse/"
+    url      = "https://github.com/rusty1s/pytorch_sparse/archive/0.6.7.tar.gz"
+
+    version('0.6.7', sha256='0d038a1502548692972a085cd0496460b5d2050bb7328427add990f081d6c44d')
+
+    variant('cuda', default=False, description="Enable 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-scatter+cuda', when='+cuda')
+    depends_on('py-torch-scatter~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')