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| # Adapted from https://github.com/NVIDIA/apex/blob/master/setup.py | |
| import sys | |
| import warnings | |
| import os | |
| from packaging.version import parse, Version | |
| import torch | |
| from torch.utils.cpp_extension import BuildExtension, CppExtension, CUDAExtension, CUDA_HOME | |
| from setuptools import setup, find_packages | |
| import subprocess | |
| # ninja build does not work unless include_dirs are abs path | |
| this_dir = os.path.dirname(os.path.abspath(__file__)) | |
| 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 | |
| bare_metal_version = parse(output[release_idx].split(",")[0]) | |
| return raw_output, bare_metal_version | |
| def check_cuda_torch_binary_vs_bare_metal(cuda_dir): | |
| raw_output, bare_metal_version = get_cuda_bare_metal_version(cuda_dir) | |
| torch_binary_version = parse(torch.version.cuda) | |
| print("\nCompiling cuda extensions with") | |
| print(raw_output + "from " + cuda_dir + "/bin\n") | |
| if (bare_metal_version != torch_binary_version): | |
| raise RuntimeError( | |
| "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. " | |
| "You can try commenting out this check (at your own risk)." | |
| ) | |
| def raise_if_cuda_home_none(global_option: str) -> None: | |
| if CUDA_HOME is not None: | |
| return | |
| raise RuntimeError( | |
| f"{global_option} was requested, but nvcc was not found. Are you sure your environment has nvcc available? " | |
| "If you're installing within a container from https://hub.docker.com/r/pytorch/pytorch, " | |
| "only images whose names contain 'devel' will provide nvcc." | |
| ) | |
| def append_nvcc_threads(nvcc_extra_args): | |
| _, bare_metal_version = get_cuda_bare_metal_version(CUDA_HOME) | |
| if bare_metal_version >= Version("11.2"): | |
| nvcc_threads = os.getenv("NVCC_THREADS") or "4" | |
| return nvcc_extra_args + ["--threads", nvcc_threads] | |
| return nvcc_extra_args | |
| 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, Apex 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 and CUDA_HOME is not None: | |
| _, bare_metal_version = get_cuda_bare_metal_version(CUDA_HOME) | |
| if bare_metal_version >= Version("11.8"): | |
| os.environ["TORCH_CUDA_ARCH_LIST"] = "6.0;6.1;6.2;7.0;7.5;8.0;8.6;9.0" | |
| elif bare_metal_version >= Version("11.1"): | |
| os.environ["TORCH_CUDA_ARCH_LIST"] = "6.0;6.1;6.2;7.0;7.5;8.0;8.6" | |
| elif bare_metal_version == Version("11.0"): | |
| 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" | |
| print("\n\ntorch.__version__ = {}\n\n".format(torch.__version__)) | |
| TORCH_MAJOR = int(torch.__version__.split(".")[0]) | |
| TORCH_MINOR = int(torch.__version__.split(".")[1]) | |
| cmdclass = {} | |
| ext_modules = [] | |
| raise_if_cuda_home_none("rotary_emb") | |
| # Check, if CUDA11 is installed for compute capability 8.0 | |
| cc_flag = [] | |
| _, bare_metal_version = get_cuda_bare_metal_version(CUDA_HOME) | |
| if bare_metal_version < Version("11.0"): | |
| raise RuntimeError("rotary_emb is only supported on CUDA 11 and above") | |
| cc_flag.append("-gencode") | |
| cc_flag.append("arch=compute_70,code=sm_70") | |
| cc_flag.append("-gencode") | |
| cc_flag.append("arch=compute_80,code=sm_80") | |
| if bare_metal_version >= Version("11.8"): | |
| cc_flag.append("-gencode") | |
| cc_flag.append("arch=compute_90,code=sm_90") | |
| ext_modules.append( | |
| CUDAExtension( | |
| 'rotary_emb', [ | |
| 'rotary.cpp', | |
| 'rotary_cuda.cu', | |
| ], | |
| extra_compile_args={'cxx': ['-g', '-march=native', '-funroll-loops'], | |
| 'nvcc': append_nvcc_threads([ | |
| '-O3', '--use_fast_math', '--expt-extended-lambda' | |
| ] + cc_flag) | |
| } | |
| ) | |
| ) | |
| setup( | |
| name="rotary_emb", | |
| version="0.1", | |
| ext_modules=ext_modules, | |
| cmdclass={"build_ext": BuildExtension} if ext_modules else {}, | |
| ) | |