setup.py

import glob
import os
import os.path as osp
import platform
import sys
from itertools import product

import torch
from setuptools import find_packages, setup
from torch.__config__ import parallel_info
from torch.utils.cpp_extension import (CUDA_HOME, BuildExtension, CppExtension,
                                       CUDAExtension)

__version__ = '1.6.0'
URL = 'https://github.com/rusty1s/pytorch_cluster'

WITH_HIP = torch.cuda.is_available() and CUDA_HOME is not None
suffices = ['cpu', 'cuda'] if WITH_HIP else ['cpu']
if os.getenv('FORCE_CUDA', '0') == '1':
    suffices = ['cuda', 'cpu']
if os.getenv('FORCE_ONLY_HIP', '0') == '1':
    suffices = ['hip']
if os.getenv('FORCE_ONLY_CPU', '0') == '1':
    suffices = ['cpu']
ROCM_PATH = os.getenv('ROCM_PATH')
HIPLIB2 = osp.join(ROCM_PATH, 'hiprand', 'include')
HIPLIB1 = osp.join(ROCM_PATH, 'hipsparse', 'include')

BUILD_DOCS = os.getenv('BUILD_DOCS', '0') == '1'


def get_extensions():
    extensions = []

    extensions_dir = osp.join('csrc')
    main_files = glob.glob(osp.join(extensions_dir, '*.cpp'))

    for main, suffix in product(main_files, suffices):
        define_macros = []
        extra_compile_args = {'cxx': ['-O2']}
        if not os.name == 'nt':  # Not on Windows:
            extra_compile_args['cxx'] += ['-Wno-sign-compare']
        extra_link_args = ['-s']
        extra_link_args += ['-fopenmp','-lomp']

        info = parallel_info()
        if ('backend: OpenMP' in info and 'OpenMP not found' not in info
                and sys.platform != 'darwin'):
            extra_compile_args['cxx'] += ['-DAT_PARALLEL_OPENMP']
            if sys.platform == 'win32':
                extra_compile_args['cxx'] += ['/openmp']
            else:
                extra_compile_args['cxx'] += ['-fopenmp']
        else:
            print('Compiling without OpenMP...')

        # Compile for mac arm64
        if (sys.platform == 'darwin' and platform.machine() == 'arm64'):
            extra_compile_args['cxx'] += ['-arch', 'arm64']
            extra_link_args += ['-arch', 'arm64']

        if suffix == 'hip':
            define_macros += [('WITH_HIP', None)]
            hipcc_flags = os.getenv('HIPCC_FLAGS', '')
            hipcc_flags = [] if hipcc_flags == '' else hipcc_flags.split(' ')
            hipcc_flags += ['--expt-relaxed-constexpr', '-O2']
            extra_compile_args['hipcc'] = hipcc_flags

        name = main.split(os.sep)[-1][:-4]
        sources = [main]

        path = osp.join(extensions_dir, 'cpu', f'{name}_cpu.cpp')
        if osp.exists(path):
            sources += [path]

        path = osp.join(extensions_dir, 'hip', f'{name}_hip.hip')
        if suffix == 'hip' and osp.exists(path):
            sources += [path]

        Extension = CppExtension if suffix == 'cpu' else CUDAExtension
        define_macros += [('TORCH_HIP_VERSION', 10000), ('__HIP__', None), ('__HCC__', None)]
        extension = Extension(
            f'torch_cluster._{name}_{suffix}',
            sources,
            include_dirs=[extensions_dir, HIPLIB1, HIPLIB2],
            define_macros=define_macros,
            extra_compile_args=extra_compile_args,
            extra_link_args=extra_link_args,
        )
        extensions += [extension]

    return extensions


install_requires = []

test_requires = [
    'pytest',
    'pytest-cov',
    'scipy',
]

setup(
    name='torch_cluster',
    version=__version__,
    description=('PyTorch Extension Library of Optimized Graph Cluster '
                 'Algorithms'),
    author='Matthias Fey',
    author_email='matthias.fey@tu-dortmund.de',
    url=URL,
    download_url=f'{URL}/archive/{__version__}.tar.gz',
    keywords=[
        'pytorch',
        'geometric-deep-learning',
        'graph-neural-networks',
        'cluster-algorithms',
    ],
    python_requires='>=3.7',
    install_requires=install_requires,
    extras_require={
        'test': test_requires,
    },
    ext_modules=get_extensions() if not BUILD_DOCS else [],
    cmdclass={
        'build_ext':
        BuildExtension.with_options(no_python_abi_suffix=True, use_ninja=False)
    },
    packages=find_packages(),
    include_package_data=False,
)