From 9942fd5bfa5a15f7d72a6ea00704588af8772cc6 Mon Sep 17 00:00:00 2001 From: ver217 Date: Mon, 15 Nov 2021 16:43:28 +0800 Subject: [PATCH] remove redundancy func in setup (#19) (#20) --- setup.py | 116 ++++++++++++++++++------------------------------------- 1 file changed, 38 insertions(+), 78 deletions(-) diff --git a/setup.py b/setup.py index e68430a21..d71876bb9 100644 --- a/setup.py +++ b/setup.py @@ -1,7 +1,6 @@ import os import subprocess import sys -import warnings import torch from setuptools import setup, find_packages @@ -11,71 +10,6 @@ from torch.utils.cpp_extension import BuildExtension, CUDAExtension, CUDA_HOME 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 - 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 - - -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: - _, bare_metal_major, _ = get_cuda_bare_metal_version(CUDA_HOME) - 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" - -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 == 0 and TORCH_MINOR < 4: - raise RuntimeError("Apex requires Pytorch 0.4 or newer.\n" + - "The latest stable release can be obtained from https://pytorch.org/") - -cmdclass = {} -ext_modules = [] - -extras = {} -if "--pyprof" in sys.argv: - string = "\n\nPyprof has been moved to its own dedicated repository and will " + \ - "soon be removed from Apex. Please visit\n" + \ - "https://github.com/NVIDIA/PyProf\n" + \ - "for the latest version." - warnings.warn(string, DeprecationWarning) - with open('requirements.txt') as f: - required_packages = f.read().splitlines() - extras['pyprof'] = required_packages - try: - sys.argv.remove("--pyprof") - except: - pass -else: - warnings.warn( - "Option --pyprof not specified. Not installing PyProf dependencies!") - -if "--cuda_ext" in sys.argv: - if TORCH_MAJOR == 0: - raise RuntimeError("--cuda_ext requires Pytorch 1.0 or later, " - "found torch.__version__ = {}".format(torch.__version__)) - - def get_cuda_bare_metal_version(cuda_dir): raw_output = subprocess.check_output( [cuda_dir + "/bin/nvcc", "-V"], universal_newlines=True) @@ -106,6 +40,40 @@ def check_cuda_torch_binary_vs_bare_metal(cuda_dir): "You can try commenting out this check (at your own risk).") +def fetch_requirements(path): + with open(path, 'r') as fd: + return [r.strip() for r in fd.readlines()] + + +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_HOME) + 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" + +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 == 0 and TORCH_MINOR < 4: + raise RuntimeError("Colossal-AI requires Pytorch 0.4 or newer.\n" + + "The latest stable release can be obtained from https://pytorch.org/") + +cmdclass = {} +ext_modules = [] + # Set up macros for forward/backward compatibility hack around # https://github.com/pytorch/pytorch/commit/4404762d7dd955383acee92e6f06b48144a0742e # and @@ -123,6 +91,10 @@ if (TORCH_MAJOR > 1) or (TORCH_MAJOR == 1 and TORCH_MINOR > 4): version_dependent_macros = version_ge_1_1 + version_ge_1_3 + version_ge_1_5 if "--cuda_ext" in sys.argv: + if TORCH_MAJOR == 0: + raise RuntimeError("--cuda_ext requires Pytorch 1.0 or later, " + "found torch.__version__ = {}".format(torch.__version__)) + sys.argv.remove("--cuda_ext") if CUDA_HOME is None: @@ -145,17 +117,6 @@ if "--cuda_ext" in sys.argv: # '--resource-usage', '--use_fast_math'] + version_dependent_macros})) -# Check, if ATen/CUDAGenerator.h is found, otherwise use the new ATen/CUDAGeneratorImpl.h, due to breaking change in https://github.com/pytorch/pytorch/pull/36026 -generator_flag = [] -torch_dir = torch.__path__[0] -if os.path.exists(os.path.join(torch_dir, 'include', 'ATen', 'CUDAGenerator.h')): - generator_flag = ['-DOLD_GENERATOR'] - - -def fetch_requirements(path): - with open(path, 'r') as fd: - return [r.strip() for r in fd.readlines()] - install_requires = fetch_requirements('requirements/requirements.txt') @@ -170,6 +131,5 @@ setup( description='An integrated large-scale model training system with efficient parallelization techniques', ext_modules=ext_modules, cmdclass={'build_ext': BuildExtension} if ext_modules else {}, - extras_require=extras, install_requires=install_requires, )