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setup.py
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setup.py
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import glob
import os
import platform
import re
from packaging.version import parse as parse_version
from setuptools import find_packages, setup
import torch
from torch.utils.cpp_extension import BuildExtension, CppExtension, CUDAExtension
EXT_TYPE = 'pytorch'
cmd_class = {'build_ext': BuildExtension}
cur_path = os.path.dirname(os.path.abspath(__file__))
def make_cuda_ext(name,
module,
sources,
sources_cuda=[],
extra_args=[],
extra_include_path=[]):
define_macros = []
extra_compile_args = {'cxx': [] + extra_args}
if torch.cuda.is_available():
define_macros += [('WITH_CUDA', None)]
extension = CUDAExtension
extra_compile_args['nvcc'] = extra_args + [
'-D__CUDA_NO_HALF_OPERATORS__',
'-D__CUDA_NO_HALF_CONVERSIONS__',
'-D__CUDA_NO_HALF2_OPERATORS__',
]
sources += sources_cuda
else:
print('Compiling {} without CUDA'.format(name))
extension = CppExtension
return extension(
name='{}.{}'.format(module, name),
sources=[os.path.join(*module.split('.'), p) for p in sources],
include_dirs=extra_include_path,
define_macros=define_macros,
extra_compile_args=extra_compile_args)
def parse_requirements(fname='requirements.txt', with_version=True):
"""Parse the package dependencies listed in a requirements file but strips
specific versioning information.
Args:
fname (str): path to requirements file
with_version (bool, default=False): if True include version specs
Returns:
List[str]: list of requirements items
CommandLine:
python -c "import setup; print(setup.parse_requirements())"
"""
import sys
from os.path import exists
require_fpath = fname
def parse_line(line):
"""Parse information from a line in a requirements text file."""
if line.startswith('-r '):
# Allow specifying requirements in other files
target = line.split(' ')[1]
for info in parse_require_file(target):
yield info
else:
info = {'line': line}
if line.startswith('-e '):
info['package'] = line.split('#egg=')[1]
else:
# Remove versioning from the package
pat = '(' + '|'.join(['>=', '==', '>']) + ')'
parts = re.split(pat, line, maxsplit=1)
parts = [p.strip() for p in parts]
info['package'] = parts[0]
if len(parts) > 1:
op, rest = parts[1:]
if ';' in rest:
# Handle platform specific dependencies
# http://setuptools.readthedocs.io/en/latest/setuptools.html#declaring-platform-specific-dependencies
version, platform_deps = map(str.strip,
rest.split(';'))
info['platform_deps'] = platform_deps
else:
version = rest # NOQA
info['version'] = (op, version)
yield info
def parse_require_file(fpath):
with open(fpath, 'r') as f:
for line in f.readlines():
line = line.strip()
if line and not line.startswith('#'):
for info in parse_line(line):
yield info
def gen_packages_items():
if exists(require_fpath):
for info in parse_require_file(require_fpath):
parts = [info['package']]
if with_version and 'version' in info:
parts.extend(info['version'])
if not sys.version.startswith('3.4'):
# apparently package_deps are broken in 3.4
platform_deps = info.get('platform_deps')
if platform_deps is not None:
parts.append(';' + platform_deps)
item = ''.join(parts)
yield item
packages = list(gen_packages_items())
return packages
def get_extensions():
extensions = []
if EXT_TYPE == 'pytorch':
ext_name = 'mmcv._ext'
# prevent ninja from using too many resources
try:
import psutil
num_cpu = len(psutil.Process().cpu_affinity())
cpu_use = max(4, num_cpu - 1)
except (ModuleNotFoundError, AttributeError):
cpu_use = 4
os.environ.setdefault('MAX_JOBS', str(cpu_use))
define_macros = []
extra_compile_args = {'cxx': []}
if platform.system() != 'Windows':
if parse_version(torch.__version__) <= parse_version('1.12.1'):
extra_compile_args['cxx'] = ['-std=c++14']
else:
extra_compile_args['cxx'] = ['-std=c++17']
else:
if parse_version(torch.__version__) <= parse_version('1.12.1'):
extra_compile_args['cxx'] = ['/std:c++14']
else:
extra_compile_args['cxx'] = ['/std:c++17']
include_dirs = []
if torch.cuda.is_available():
define_macros += [('MMCV_WITH_CUDA', None)]
cuda_args = os.getenv('MMCV_CUDA_ARGS')
extra_compile_args['nvcc'] = [cuda_args] if cuda_args else []
op_files = glob.glob('./mmcv/ops/csrc/pytorch/*.cpp') + \
glob.glob('./mmcv/ops/csrc/pytorch/cpu/*.cpp') + \
glob.glob('./mmcv/ops/csrc/pytorch/cuda/*.cu') + \
glob.glob('./mmcv/ops/csrc/pytorch/cuda/*.cpp')
extension = CUDAExtension
include_dirs.append(os.path.abspath('./mmcv/ops/csrc/common'))
include_dirs.append(os.path.abspath('./mmcv/ops/csrc/common/cuda'))
else:
print(f'Compiling {ext_name} without CUDA')
op_files = glob.glob('./mmcv/ops/csrc/pytorch/*.cpp') + \
glob.glob('./mmcv/ops/csrc/pytorch/cpu/*.cpp')
extension = CppExtension
include_dirs.append(os.path.abspath('./mmcv/ops/csrc/common'))
if 'nvcc' in extra_compile_args and platform.system() != 'Windows':
if parse_version(torch.__version__) <= parse_version('1.12.1'):
extra_compile_args['nvcc'] += ['-std=c++14']
else:
extra_compile_args['nvcc'] += ['-std=c++17']
ext_ops = extension(
name=ext_name,
sources=op_files,
include_dirs=include_dirs,
define_macros=define_macros,
extra_compile_args=extra_compile_args)
extensions.append(ext_ops)
return extensions
setup(
name='mmcv',
version='0.0.1',
description='OpenMMLab Computer Vision Foundation',
keywords='computer vision',
packages=[
*find_packages(include=('mmcv', "mmcv.*")),
*find_packages(include=('adzoo', "adzoo.*")),
*find_packages(where=".mmcv", include=('nuscenes', "nuscenes.*"))
],
include_package_data=True,
classifiers=[
'Development Status :: 4 - Beta',
'License :: OSI Approved :: Apache Software License',
'Operating System :: OS Independent',
'Programming Language :: Python :: 3.8',
'Programming Language :: Python :: 3.9',
'Topic :: Utilities',
],
url='https://github.com/open-mmlab/mmcv',
author='MMCV Contributors',
author_email='[email protected]',
install_requires=parse_requirements(),
ext_modules= get_extensions() + [
make_cuda_ext(
name='iou3d_cuda',
module='mmcv.ops.iou3d_det',
sources=[
'src/iou3d.cpp',
'src/iou3d_kernel.cu',
]),
make_cuda_ext(
name='roiaware_pool3d_ext',
module='mmcv.ops.roiaware_pool3d',
sources=[
'src/roiaware_pool3d.cpp',
'src/points_in_boxes_cpu.cpp',
],
sources_cuda=[
'src/roiaware_pool3d_kernel.cu',
'src/points_in_boxes_cuda.cu',
]),
],
cmdclass=cmd_class,
zip_safe=False)