# Copyright (c) Meta Platforms, Inc. and affiliates. # All rights reserved. # # This source code is licensed under the license found in the # LICENSE file in the root directory of this source tree. 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': 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 = [] 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 if parse_version(torch.__version__) <= parse_version('2.0.0'): define_macros += [('MMCV_WITH_XLA', None)] if parse_version(torch.__version__) > parse_version('2.0.0'): define_macros += [('MMCV_WITH_KPRIVATE', None)] 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': 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_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='sapiens_cv', version=get_version(), description='Sapiens: Foundation for Human Vision Models', 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='', author='Meta Reality Labs', author_email='', 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)