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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 pkg_resources import DistributionNotFound, get_distribution, parse_version
from setuptools import find_packages, setup
EXT_TYPE = ''
try:
import torch
if torch.__version__ == 'parrots':
from parrots.utils.build_extension import BuildExtension
EXT_TYPE = 'parrots'
elif (hasattr(torch, 'is_mlu_available') and torch.is_mlu_available()) or \
os.getenv('FORCE_MLU', '0') == '1':
from torch_mlu.utils.cpp_extension import BuildExtension
EXT_TYPE = 'pytorch'
else:
from torch.utils.cpp_extension import BuildExtension
EXT_TYPE = 'pytorch'
cmd_class = {'build_ext': BuildExtension}
except ModuleNotFoundError:
cmd_class = {}
print('Skip building ext ops due to the absence of torch.')
def choose_requirement(primary, secondary):
"""If some version of primary requirement installed, return primary, else
return secondary."""
try:
name = re.split(r'[!<>=]', primary)[0]
get_distribution(name)
except DistributionNotFound:
return secondary
return str(primary)
def get_version():
version_file = 'mmcv/version.py'
with open(version_file, encoding='utf-8') as f:
exec(compile(f.read(), version_file, 'exec'))
return locals()['__version__']
def parse_requirements(fname='requirements/runtime.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) as f:
for line in f.readlines():
line = line.strip()
if line and not line.startswith('#'):
yield from parse_line(line)
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
install_requires = parse_requirements()
try:
# OpenCV installed via conda.
import cv2 # NOQA: F401
major, minor, *rest = cv2.__version__.split('.')
if int(major) < 3:
raise RuntimeError(
f'OpenCV >=3 is required but {cv2.__version__} is installed')
except ImportError:
# If first not installed install second package
CHOOSE_INSTALL_REQUIRES = [('opencv-python-headless>=3',
'opencv-python>=3')]
for main, secondary in CHOOSE_INSTALL_REQUIRES:
install_requires.append(choose_requirement(main, secondary))
def get_extensions():
extensions = []
if os.getenv('MMCV_WITH_OPS', '1') == '0':
return extensions
if EXT_TYPE == 'parrots':
ext_name = 'mmcv._ext'
from parrots.utils.build_extension import Extension
# new parrots op impl do not use MMCV_USE_PARROTS
# define_macros = [('MMCV_USE_PARROTS', None)]
define_macros = []
include_dirs = []
op_files = glob.glob('./mmcv/ops/csrc/pytorch/cuda/*.cu') +\
glob.glob('./mmcv/ops/csrc/pytorch/cpu/*.cpp') +\
glob.glob('./mmcv/ops/csrc/parrots/*.cpp')
include_dirs.append(os.path.abspath('./mmcv/ops/csrc/common'))
include_dirs.append(os.path.abspath('./mmcv/ops/csrc/common/cuda'))
op_files.remove('./mmcv/ops/csrc/pytorch/cuda/iou3d_cuda.cu')
op_files.remove('./mmcv/ops/csrc/pytorch/cpu/bbox_overlaps_cpu.cpp')
op_files.remove('./mmcv/ops/csrc/pytorch/cuda/bias_act_cuda.cu')
cuda_args = os.getenv('MMCV_CUDA_ARGS')
extra_compile_args = {
'nvcc': [cuda_args, '-std=c++14'] if cuda_args else ['-std=c++14'],
'cxx': ['-std=c++14'],
}
if torch.cuda.is_available() or os.getenv('FORCE_CUDA', '0') == '1':
define_macros += [('MMCV_WITH_CUDA', None)]
extra_compile_args['nvcc'] += [
'-D__CUDA_NO_HALF_OPERATORS__',
'-D__CUDA_NO_HALF_CONVERSIONS__',
'-D__CUDA_NO_HALF2_OPERATORS__',
]
ext_ops = Extension(
name=ext_name,
sources=op_files,
include_dirs=include_dirs,
define_macros=define_macros,
extra_compile_args=extra_compile_args,
cuda=True,
pytorch=True)
extensions.append(ext_ops)
elif EXT_TYPE == 'pytorch':
ext_name = 'mmcv._ext'
from torch.utils.cpp_extension import CppExtension, CUDAExtension
# 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 = []
# Before PyTorch1.8.0, when compiling CUDA code, `cxx` is a
# required key passed to PyTorch. Even if there is no flag passed
# to cxx, users also need to pass an empty list to PyTorch.
# Since PyTorch1.8.0, it has a default value so users do not need
# to pass an empty list anymore.
# More details at https://github.com/pytorch/pytorch/pull/45956
extra_compile_args = {'cxx': []}
if platform.system() != 'Windows':
extra_compile_args['cxx'] = ['-std=c++14']
else:
# TODO: In Windows, C++17 is chosen to compile extensions in
# PyTorch2.0 , but a compile error will be reported.
# As a temporary solution, force the use of C++14.
if parse_version(torch.__version__) >= parse_version('2.0.0'):
extra_compile_args['cxx'] = ['/std:c++14']
include_dirs = []
library_dirs = []
libraries = []
extra_objects = []
extra_link_args = []
is_rocm_pytorch = False
try:
from torch.utils.cpp_extension import ROCM_HOME
is_rocm_pytorch = True if ((torch.version.hip is not None) and
(ROCM_HOME is not None)) else False
except ImportError:
pass
if os.getenv('MMCV_WITH_DIOPI', '0') == '1':
import mmengine # NOQA: F401
from mmengine.utils.version_utils import digit_version
assert digit_version(mmengine.__version__) >= digit_version(
'0.7.4'), f'mmengine >= 0.7.4 is required \
but {mmengine.__version__} is installed'
print(f'Compiling {ext_name} with CPU and DIPU')
define_macros += [('MMCV_WITH_DIOPI', None)]
define_macros += [('DIOPI_ATTR_WEAK', None)]
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'))
dipu_root = os.getenv('DIPU_ROOT')
diopi_path = os.getenv('DIOPI_PATH')
dipu_path = os.getenv('DIPU_PATH')
vendor_include_dirs = os.getenv('VENDOR_INCLUDE_DIRS')
nccl_include_dirs = os.getenv('NCCL_INCLUDE_DIRS')
include_dirs.append(dipu_root)
include_dirs.append(diopi_path + '/include')
include_dirs.append(dipu_path + '/dist/include')
include_dirs.append(vendor_include_dirs)
if nccl_include_dirs:
include_dirs.append(nccl_include_dirs)
library_dirs += [dipu_root]
libraries += ['torch_dipu']
elif is_rocm_pytorch or torch.cuda.is_available() or os.getenv(
'FORCE_CUDA', '0') == '1':
if is_rocm_pytorch:
define_macros += [('MMCV_WITH_HIP', None)]
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/pytorch'))
include_dirs.append(os.path.abspath('./mmcv/ops/csrc/common'))
include_dirs.append(os.path.abspath('./mmcv/ops/csrc/common/cuda'))
elif (hasattr(torch, 'is_mlu_available') and
torch.is_mlu_available()) or \
os.getenv('FORCE_MLU', '0') == '1':
from torch_mlu.utils.cpp_extension import MLUExtension
def get_mluops_version(file_path):
with open(file_path) as f:
for line in f:
if re.search('MLUOP_MAJOR', line):
major = line.strip().split(' ')[2]
if re.search('MLUOP_MINOR', line):
minor = line.strip().split(' ')[2]
if re.search('MLUOP_PATCHLEVEL', line):
patchlevel = line.strip().split(' ')[2]
mluops_version = f'v{major}.{minor}.{patchlevel}'
return mluops_version
mmcv_mluops_version = get_mluops_version(
'./mmcv/ops/csrc/pytorch/mlu/mlu_common_helper.h')
mlu_ops_path = os.getenv('MMCV_MLU_OPS_PATH')
if mlu_ops_path:
exists_mluops_version = get_mluops_version(
mlu_ops_path + '/bangc-ops/mlu_op.h')
if exists_mluops_version != mmcv_mluops_version:
print('the version of mlu-ops provided is %s,'
' while %s is needed.' %
(exists_mluops_version, mmcv_mluops_version))
exit()
try:
if os.path.exists('mlu-ops'):
if os.path.islink('mlu-ops'):
os.remove('mlu-ops')
os.symlink(mlu_ops_path, 'mlu-ops')
elif os.path.abspath('mlu-ops') != mlu_ops_path:
os.symlink(mlu_ops_path, 'mlu-ops')
else:
os.symlink(mlu_ops_path, 'mlu-ops')
except Exception:
raise FileExistsError(
'mlu-ops already exists, please move it out,'
'or rename or remove it.')
else:
if not os.path.exists('mlu-ops'):
import requests
mluops_url = 'https://github.com/Cambricon/mlu-ops/' + \
'archive/refs/tags/' + mmcv_mluops_version + '.zip'
req = requests.get(mluops_url)
with open('./mlu-ops.zip', 'wb') as f:
try:
f.write(req.content)
except Exception:
raise ImportError('failed to download mlu-ops')
from zipfile import BadZipFile, ZipFile
with ZipFile('./mlu-ops.zip', 'r') as archive:
try:
archive.extractall()
dir_name = archive.namelist()[0].split('/')[0]
os.rename(dir_name, 'mlu-ops')
except BadZipFile:
print('invalid mlu-ops.zip file')
else:
exists_mluops_version = get_mluops_version(
'./mlu-ops/bangc-ops/mlu_op.h')
if exists_mluops_version != mmcv_mluops_version:
print('the version of provided mlu-ops is %s,'
' while %s is needed.' %
(exists_mluops_version, mmcv_mluops_version))
exit()
define_macros += [('MMCV_WITH_MLU', None)]
mlu_args = os.getenv('MMCV_MLU_ARGS', '-DNDEBUG ')
mluops_includes = []
mluops_includes.append('-I' +
os.path.abspath('./mlu-ops/bangc-ops'))
mluops_includes.append(
'-I' + os.path.abspath('./mlu-ops/bangc-ops/kernels'))
extra_compile_args['cncc'] = [mlu_args] + \
mluops_includes if mlu_args else mluops_includes
extra_compile_args['cxx'] += ['-fno-gnu-unique']
op_files = glob.glob('./mmcv/ops/csrc/pytorch/*.cpp') + \
glob.glob('./mmcv/ops/csrc/pytorch/cpu/*.cpp') + \
glob.glob('./mmcv/ops/csrc/pytorch/mlu/*.cpp') + \
glob.glob('./mmcv/ops/csrc/common/mlu/*.mlu') + \
glob.glob(
'./mlu-ops/bangc-ops/core/**/*.cpp', recursive=True) + \
glob.glob(
'./mlu-ops/bangc-ops/kernels/**/*.cpp', recursive=True) + \
glob.glob(
'./mlu-ops/bangc-ops/kernels/**/*.mlu', recursive=True)
extra_link_args = [
'-Wl,--whole-archive',
'./mlu-ops/bangc-ops/kernels/kernel_wrapper/lib/libextops.a',
'-Wl,--no-whole-archive'
]
extension = MLUExtension
include_dirs.append(os.path.abspath('./mmcv/ops/csrc/common'))
include_dirs.append(os.path.abspath('./mmcv/ops/csrc/common/mlu'))
include_dirs.append(os.path.abspath('./mlu-ops/bangc-ops'))
elif (hasattr(torch.backends, 'mps')
and torch.backends.mps.is_available()) or os.getenv(
'FORCE_MPS', '0') == '1':
# objc compiler support
from distutils.unixccompiler import UnixCCompiler
if '.mm' not in UnixCCompiler.src_extensions:
UnixCCompiler.src_extensions.append('.mm')
UnixCCompiler.language_map['.mm'] = 'objc'
define_macros += [('MMCV_WITH_MPS', None)]
extra_compile_args = {}
extra_compile_args['cxx'] = ['-Wall', '-std=c++17']
extra_compile_args['cxx'] += [
'-framework', 'Metal', '-framework', 'Foundation'
]
extra_compile_args['cxx'] += ['-ObjC++']
# src
op_files = glob.glob('./mmcv/ops/csrc/pytorch/*.cpp') + \
glob.glob('./mmcv/ops/csrc/pytorch/cpu/*.cpp') + \
glob.glob('./mmcv/ops/csrc/common/mps/*.mm') + \
glob.glob('./mmcv/ops/csrc/pytorch/mps/*.mm')
extension = CppExtension
include_dirs.append(os.path.abspath('./mmcv/ops/csrc/common'))
include_dirs.append(os.path.abspath('./mmcv/ops/csrc/common/mps'))
elif (os.getenv('FORCE_NPU', '0') == '1'):
print(f'Compiling {ext_name} only with CPU and NPU')
try:
from torch_npu.utils.cpp_extension import NpuExtension
define_macros += [('MMCV_WITH_NPU', None)]
extension = NpuExtension
except Exception:
raise ImportError('can not find any torch_npu')
# src
op_files = glob.glob('./mmcv/ops/csrc/pytorch/*.cpp') + \
glob.glob('./mmcv/ops/csrc/pytorch/cpu/*.cpp') + \
glob.glob('./mmcv/ops/csrc/common/npu/*.cpp') + \
glob.glob('./mmcv/ops/csrc/pytorch/npu/*.cpp')
include_dirs.append(os.path.abspath('./mmcv/ops/csrc/common'))
include_dirs.append(os.path.abspath('./mmcv/ops/csrc/common/npu'))
else:
print(f'Compiling {ext_name} only with CPU')
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'))
# Since the PR (https://github.com/open-mmlab/mmcv/pull/1463) uses
# c++14 features, the argument ['std=c++14'] must be added here.
# However, in the windows environment, some standard libraries
# will depend on c++17 or higher. In fact, for the windows
# environment, the compiler will choose the appropriate compiler
# to compile those cpp files, so there is no need to add the
# argument
if 'nvcc' in extra_compile_args and platform.system() != 'Windows':
extra_compile_args['nvcc'] += ['-std=c++14']
ext_ops = extension(
name=ext_name,
sources=op_files,
include_dirs=include_dirs,
define_macros=define_macros,
extra_objects=extra_objects,
extra_compile_args=extra_compile_args,
library_dirs=library_dirs,
libraries=libraries,
extra_link_args=extra_link_args)
extensions.append(ext_ops)
return extensions
setup(
name='mmcv' if os.getenv('MMCV_WITH_OPS', '1') == '1' else 'mmcv-lite',
version=get_version(),
description='OpenMMLab Computer Vision Foundation',
keywords='computer vision',
packages=find_packages(),
include_package_data=True,
classifiers=[
'Development Status :: 4 - Beta',
'License :: OSI Approved :: Apache Software License',
'Operating System :: OS Independent',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.7',
'Programming Language :: Python :: 3.8',
'Programming Language :: Python :: 3.9',
'Programming Language :: Python :: 3.10',
'Topic :: Utilities',
],
url='https://github.com/open-mmlab/mmcv',
author='MMCV Contributors',
author_email='[email protected]',
install_requires=install_requires,
extras_require={
'all': parse_requirements('requirements.txt'),
'tests': parse_requirements('requirements/test.txt'),
'build': parse_requirements('requirements/build.txt'),
'optional': parse_requirements('requirements/optional.txt'),
},
python_requires='>=3.7',
ext_modules=get_extensions(),
cmdclass=cmd_class,
zip_safe=False)