import os import subprocess import sys from setuptools import find_packages, setup # ninja build does not work unless include_dirs are abs path this_dir = os.path.dirname(os.path.abspath(__file__)) build_cuda_ext = True ext_modules = [] if '--no_cuda_ext' in sys.argv: sys.argv.remove('--no_cuda_ext') build_cuda_ext = False def get_cuda_bare_metal_version(cuda_dir): raw_output = subprocess.check_output([cuda_dir + "/bin/nvcc", "-V"], universal_newlines=True) output = raw_output.split() release_idx = output.index("release") + 1 release = output[release_idx].split(".") bare_metal_major = release[0] bare_metal_minor = release[1][0] return raw_output, bare_metal_major, bare_metal_minor def check_cuda_torch_binary_vs_bare_metal(cuda_dir): raw_output, bare_metal_major, bare_metal_minor = get_cuda_bare_metal_version(cuda_dir) torch_binary_major = torch.version.cuda.split(".")[0] torch_binary_minor = torch.version.cuda.split(".")[1] print("\nCompiling cuda extensions with") print(raw_output + "from " + cuda_dir + "/bin\n") if bare_metal_major != torch_binary_major: print( f'The detected CUDA version ({raw_output}) mismatches the version that was used to compile PyTorch ({torch.version.cuda}). CUDA extension will not be installed.') return False if bare_metal_minor != torch_binary_minor: print("\nWarning: Cuda extensions are being compiled with a version of Cuda that does " + "not match the version used to compile Pytorch binaries. " + "Pytorch binaries were compiled with Cuda {}.\n".format(torch.version.cuda) + "In some cases, a minor-version mismatch will not cause later errors: " + "https://github.com/NVIDIA/apex/pull/323#discussion_r287021798. ") return True def check_cuda_availability(cuda_dir): if not torch.cuda.is_available(): # https://github.com/NVIDIA/apex/issues/486 # Extension builds after https://github.com/pytorch/pytorch/pull/23408 attempt to query torch.cuda.get_device_capability(), # which will fail if you are compiling in an environment without visible GPUs (e.g. during an nvidia-docker build command). print('\nWarning: Torch did not find available GPUs on this system.\n', 'If your intention is to cross-compile, this is not an error.\n' 'By default, Colossal-AI will cross-compile for Pascal (compute capabilities 6.0, 6.1, 6.2),\n' 'Volta (compute capability 7.0), Turing (compute capability 7.5),\n' 'and, if the CUDA version is >= 11.0, Ampere (compute capability 8.0).\n' 'If you wish to cross-compile for a single specific architecture,\n' 'export TORCH_CUDA_ARCH_LIST="compute capability" before running setup.py.\n') if os.environ.get("TORCH_CUDA_ARCH_LIST", None) is None: _, bare_metal_major, _ = get_cuda_bare_metal_version(cuda_dir) if int(bare_metal_major) == 11: os.environ["TORCH_CUDA_ARCH_LIST"] = "6.0;6.1;6.2;7.0;7.5;8.0" else: os.environ["TORCH_CUDA_ARCH_LIST"] = "6.0;6.1;6.2;7.0;7.5" return False if cuda_dir is None: print( "nvcc was not found. CUDA extension will not be installed. If you're installing within a container from https://hub.docker.com/r/pytorch/pytorch, only images whose names contain 'devel' will provide nvcc.") return False return True def append_nvcc_threads(nvcc_extra_args): _, bare_metal_major, bare_metal_minor = get_cuda_bare_metal_version(CUDA_HOME) if int(bare_metal_major) >= 11 and int(bare_metal_minor) >= 2: return nvcc_extra_args + ["--threads", "4"] return nvcc_extra_args def fetch_requirements(path): with open(path, 'r') as fd: return [r.strip() for r in fd.readlines()] def fetch_readme(): with open('README.md', encoding='utf-8') as f: return f.read() def get_version(): with open('version.txt') as f: return f.read().strip() if build_cuda_ext: try: import torch from torch.utils.cpp_extension import (CUDA_HOME, BuildExtension, CUDAExtension) print("\n\ntorch.__version__ = {}\n\n".format(torch.__version__)) TORCH_MAJOR = int(torch.__version__.split('.')[0]) TORCH_MINOR = int(torch.__version__.split('.')[1]) if TORCH_MAJOR < 1 or (TORCH_MAJOR == 1 and TORCH_MINOR < 8): raise RuntimeError("Colossal-AI requires Pytorch 1.8 or newer.\n" + "The latest stable release can be obtained from https://pytorch.org/") except ImportError: print('torch is not found. CUDA extension will not be installed') build_cuda_ext = False if build_cuda_ext: build_cuda_ext = check_cuda_availability(CUDA_HOME) and check_cuda_torch_binary_vs_bare_metal(CUDA_HOME) if build_cuda_ext: # Set up macros for forward/backward compatibility hack around # https://github.com/pytorch/pytorch/commit/4404762d7dd955383acee92e6f06b48144a0742e # and # https://github.com/NVIDIA/apex/issues/456 # https://github.com/pytorch/pytorch/commit/eb7b39e02f7d75c26d8a795ea8c7fd911334da7e#diff-4632522f237f1e4e728cb824300403ac version_dependent_macros = ['-DVERSION_GE_1_1', '-DVERSION_GE_1_3', '-DVERSION_GE_1_5'] def cuda_ext_helper(name, sources, extra_cuda_flags, extra_cxx_flags=[]): return CUDAExtension(name=name, sources=[os.path.join('colossalai/kernel/cuda_native/csrc', path) for path in sources], include_dirs=[os.path.join( this_dir, 'colossalai/kernel/cuda_native/csrc/kernels/include')], extra_compile_args={'cxx': ['-O3'] + version_dependent_macros + extra_cxx_flags, 'nvcc': append_nvcc_threads(['-O3', '--use_fast_math'] + version_dependent_macros + extra_cuda_flags)}) ext_modules.append(cuda_ext_helper('colossal_C', ['colossal_C_frontend.cpp', 'multi_tensor_sgd_kernel.cu', 'multi_tensor_scale_kernel.cu', 'multi_tensor_adam.cu', 'multi_tensor_l2norm_kernel.cu', 'multi_tensor_lamb.cu'], ['-lineinfo'])) cc_flag = ['-gencode', 'arch=compute_70,code=sm_70'] _, bare_metal_major, _ = get_cuda_bare_metal_version(CUDA_HOME) if int(bare_metal_major) >= 11: cc_flag.append('-gencode') cc_flag.append('arch=compute_80,code=sm_80') extra_cuda_flags = ['-U__CUDA_NO_HALF_OPERATORS__', '-U__CUDA_NO_HALF_CONVERSIONS__', '--expt-relaxed-constexpr', '--expt-extended-lambda'] ext_modules.append(cuda_ext_helper('colossal_scaled_upper_triang_masked_softmax', ['scaled_upper_triang_masked_softmax.cpp', 'scaled_upper_triang_masked_softmax_cuda.cu'], extra_cuda_flags + cc_flag)) ext_modules.append(cuda_ext_helper('colossal_scaled_masked_softmax', ['scaled_masked_softmax.cpp', 'scaled_masked_softmax_cuda.cu'], extra_cuda_flags + cc_flag)) ext_modules.append(cuda_ext_helper('colossal_moe_cuda', ['moe_cuda.cpp', 'moe_cuda_kernel.cu'], extra_cuda_flags + cc_flag)) extra_cuda_flags = ['-maxrregcount=50'] ext_modules.append(cuda_ext_helper('colossal_layer_norm_cuda', ['layer_norm_cuda.cpp', 'layer_norm_cuda_kernel.cu'], extra_cuda_flags + cc_flag)) extra_cuda_flags = ['-std=c++14', '-U__CUDA_NO_HALF_OPERATORS__', '-U__CUDA_NO_HALF_CONVERSIONS__', '-U__CUDA_NO_HALF2_OPERATORS__', '-DTHRUST_IGNORE_CUB_VERSION_CHECK'] ext_modules.append(cuda_ext_helper('colossal_multihead_attention', ['multihead_attention_1d.cpp', 'kernels/cublas_wrappers.cu', 'kernels/transform_kernels.cu', 'kernels/dropout_kernels.cu', 'kernels/normalize_kernels.cu', 'kernels/softmax_kernels.cu', 'kernels/general_kernels.cu', 'kernels/cuda_util.cu'], extra_cuda_flags + cc_flag)) extra_cxx_flags = ['-std=c++14', '-lcudart', '-lcublas', '-g', '-Wno-reorder', '-fopenmp', '-march=native'] ext_modules.append(cuda_ext_helper('cpu_adam', ['cpu_adam.cpp'], extra_cuda_flags, extra_cxx_flags)) setup( name='colossalai', version=get_version(), packages=find_packages(exclude=('benchmark', 'docker', 'tests', 'docs', 'examples', 'tests', 'scripts', 'requirements', '*.egg-info',)), description='An integrated large-scale model training system with efficient parallelization techniques', long_description=fetch_readme(), long_description_content_type='text/markdown', url='https://www.colossalai.org', project_urls={ 'Forum': 'https://github.com/hpcaitech/ColossalAI/discussions', 'Bug Tracker': 'https://github.com/hpcaitech/ColossalAI/issues', 'Examples': 'https://github.com/hpcaitech/ColossalAI-Examples', 'Documentation': 'http://colossalai.readthedocs.io', 'Github': 'https://github.com/hpcaitech/ColossalAI', }, ext_modules=ext_modules, cmdclass={'build_ext': BuildExtension} if ext_modules else {}, install_requires=fetch_requirements('requirements/requirements.txt'), extras_require={ 'zero': fetch_requirements('requirements/requirements-zero.txt'), }, python_requires='>=3.7', classifiers=[ 'Programming Language :: Python :: 3', 'License :: OSI Approved :: Apache Software License', 'Environment :: GPU :: NVIDIA CUDA', 'Topic :: Scientific/Engineering :: Artificial Intelligence', 'Topic :: System :: Distributed Computing', ], )