import platform import os.path as osp from glob import glob from setuptools import setup, find_packages from sys import argv import torch from torch.utils.cpp_extension import CppExtension, CUDAExtension, CUDA_HOME cxx_extra_compile_args = [] nvcc_extra_compile_args = [] TORCH_MAJOR = int(torch.__version__.split('.')[0]) TORCH_MINOR = int(torch.__version__.split('.')[1]) extra_compile_args = [] if (TORCH_MAJOR > 1) or (TORCH_MAJOR == 1 and TORCH_MINOR > 2): cxx_extra_compile_args += ['-DVERSION_GE_1_3'] nvcc_extra_compile_args += ['-DVERSION_GE_1_3'] cmdclass = {'build_ext': torch.utils.cpp_extension.BuildExtension} ext_modules = [] exts = [e.split(osp.sep)[-1][:-4] for e in glob(osp.join('cpu', '*.cpp'))] ext_modules += [ CppExtension( f'torch_sparse.{ext}_cpu', [f'cpu/{ext}.cpp'], extra_compile_args=cxx_extra_compile_args) for ext in exts ] if CUDA_HOME is not None and '--cpu' not in argv: if platform.system() == 'Windows': extra_link_args = ['cusparse.lib'] else: extra_link_args = ['-lcusparse', '-l', 'cusparse'] exts = [e.split(osp.sep)[-1][:-4] for e in glob(osp.join('cuda', '*.cpp'))] ext_modules += [ CUDAExtension( f'torch_sparse.{ext}_cuda', [f'cuda/{ext}.cpp', f'cuda/{ext}_kernel.cu'], extra_compile_args={ 'cxx': cxx_extra_compile_args, 'nvcc': nvcc_extra_compile_args, }, extra_link_args=extra_link_args, ) for ext in exts ] __version__ = '0.4.3' url = 'https://github.com/rusty1s/pytorch_sparse' install_requires = ['scipy'] setup_requires = ['pytest-runner'] tests_require = ['pytest', 'pytest-cov'] setup( name='torch_sparse', version=__version__, description=('PyTorch Extension Library of Optimized Autograd Sparse ' 'Matrix Operations'), author='Matthias Fey', author_email='matthias.fey@tu-dortmund.de', url=url, download_url='{}/archive/{}.tar.gz'.format(url, __version__), keywords=['pytorch', 'sparse', 'sparse-matrices', 'autograd'], install_requires=install_requires, setup_requires=setup_requires, tests_require=tests_require, ext_modules=ext_modules, cmdclass=cmdclass, packages=find_packages(), )