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remove redundancy func in setup (#19) (#20)

pull/28/head
ver217 2021-11-15 16:43:28 +08:00 committed by GitHub
parent 0aa07e600c
commit 9942fd5bfa
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1 changed files with 38 additions and 78 deletions
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116
setup.py
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@ -1,7 +1,6 @@
import os import os
import subprocess import subprocess
import sys import sys
import warnings
import torch import torch
from setuptools import setup, find_packages 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__)) 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): def get_cuda_bare_metal_version(cuda_dir):
raw_output = subprocess.check_output( raw_output = subprocess.check_output(
[cuda_dir + "/bin/nvcc", "-V"], universal_newlines=True) [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).") "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 # Set up macros for forward/backward compatibility hack around
# https://github.com/pytorch/pytorch/commit/4404762d7dd955383acee92e6f06b48144a0742e # https://github.com/pytorch/pytorch/commit/4404762d7dd955383acee92e6f06b48144a0742e
# and # 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 version_dependent_macros = version_ge_1_1 + version_ge_1_3 + version_ge_1_5
if "--cuda_ext" in sys.argv: 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") sys.argv.remove("--cuda_ext")
if CUDA_HOME is None: if CUDA_HOME is None:
@ -145,17 +117,6 @@ if "--cuda_ext" in sys.argv:
# '--resource-usage', # '--resource-usage',
'--use_fast_math'] + version_dependent_macros})) '--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') install_requires = fetch_requirements('requirements/requirements.txt')
@ -170,6 +131,5 @@ setup(
description='An integrated large-scale model training system with efficient parallelization techniques', description='An integrated large-scale model training system with efficient parallelization techniques',
ext_modules=ext_modules, ext_modules=ext_modules,
cmdclass={'build_ext': BuildExtension} if ext_modules else {}, cmdclass={'build_ext': BuildExtension} if ext_modules else {},
extras_require=extras,
install_requires=install_requires, install_requires=install_requires,
) )