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| -rw-r--r-- | var/spack/repos/builtin/packages/py-dgl/package.py | 94 |
1 files changed, 94 insertions, 0 deletions
diff --git a/var/spack/repos/builtin/packages/py-dgl/package.py b/var/spack/repos/builtin/packages/py-dgl/package.py new file mode 100644 index 0000000000..336d69edf2 --- /dev/null +++ b/var/spack/repos/builtin/packages/py-dgl/package.py @@ -0,0 +1,94 @@ +# 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) + + +class PyDgl(CMakePackage): + """Deep Graph Library (DGL). + + DGL is an easy-to-use, high performance and scalable Python package for + deep learning on graphs. DGL is framework agnostic, meaning if a deep graph + model is a component of an end-to-end application, the rest of the logics + can be implemented in any major frameworks, such as PyTorch, Apache MXNet + or TensorFlow.""" + + homepage = "https://www.dgl.ai/" + git = "https://github.com/dmlc/dgl.git" + + maintainers = ['adamjstewart'] + + version('master', branch='master', submodules=True) + version('0.4.2', tag='0.4.2', submodules=True) + + variant('cuda', default=True, description='Build with CUDA') + variant('openmp', default=True, description='Build with OpenMP') + variant('backend', default='pytorch', description='Default backend', + values=['pytorch', 'mxnet', 'tensorflow'], multi=False) + + depends_on('cmake@3.5:', type='build') + depends_on('cuda', when='+cuda') + depends_on('llvm-openmp', when='%clang platform=darwin +openmp') + + # Python dependencies + extends('python') + depends_on('python@3.5:', type=('build', 'run')) + depends_on('py-setuptools', type='build') + depends_on('py-cython', type='build') + depends_on('py-numpy@1.14.0:', type=('build', 'run')) + depends_on('py-scipy@1.1.0:', type=('build', 'run')) + depends_on('py-networkx@2.1:', type=('build', 'run')) + + # Backends + depends_on('py-torch@0.4.1:', when='backend=pytorch', type='run') + depends_on('mxnet@1.5:', when='backend=mxnet', type='run') + depends_on('py-tensorflow@2.0:', when='backend=tensorflow', type='run') + depends_on('py-tfdlpack', when='backend=tensorflow', type='run') + + build_directory = 'build' + + def cmake_args(self): + args = [] + + if '+cuda' in self.spec: + args.append('-DUSE_CUDA=ON') + else: + args.append('-DUSE_CUDA=OFF') + + if '+openmp' in self.spec: + args.append('-DUSE_OPENMP=ON') + + if self.spec.satisfies('%clang platform=darwin'): + args.extend([ + '-DOpenMP_CXX_FLAGS=' + + self.spec['llvm-openmp'].headers.include_flags, + '-DOpenMP_CXX_LIB_NAMES=' + + self.spec['llvm-openmp'].libs.names[0], + '-DOpenMP_C_FLAGS=' + + self.spec['llvm-openmp'].headers.include_flags, + '-DOpenMP_C_LIB_NAMES=' + + self.spec['llvm-openmp'].libs.names[0], + '-DOpenMP_omp_LIBRARY=' + + self.spec['llvm-openmp'].libs[0], + ]) + else: + args.append('-DUSE_OPENMP=OFF') + + if self.run_tests: + args.append('-DBUILD_CPP_TEST=ON') + else: + args.append('-DBUILD_CPP_TEST=OFF') + + return args + + def install(self, spec, prefix): + with working_dir('python'): + import os + print('Current dir:', os.getcwd()) + setup_py('install', '--prefix=' + prefix, + '--single-version-externally-managed', '--root=/') + + def setup_run_environment(self, env): + # https://docs.dgl.ai/install/backend.html + backend = self.spec.variants['backend'].value + env.set('DGLBACKEND', backend) |