forked from NVIDIA/apex
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathsetup.py
133 lines (117 loc) · 6.09 KB
/
setup.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
import torch
from setuptools import setup, find_packages
import subprocess
from pip._internal import main as pipmain
import sys
import warnings
if not torch.cuda.is_available():
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")
print("torch.__version__ = ", 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 = []
if "--pyprof" in sys.argv:
with open('requirements.txt') as f:
required_packages = f.read().splitlines()
pipmain(["install"] + required_packages)
try:
sys.argv.remove("--pyprof")
except:
pass
else:
warnings.warn("Option --pyprof not specified. Not installing PyProf dependencies!")
if "--cpp_ext" in sys.argv or "--cuda_ext" in sys.argv:
if TORCH_MAJOR == 0:
raise RuntimeError("--cpp_ext requires Pytorch 1.0 or later, "
"found torch.__version__ = {}".format(torch.__version__))
from torch.utils.cpp_extension import BuildExtension
cmdclass['build_ext'] = BuildExtension
if "--cpp_ext" in sys.argv:
from torch.utils.cpp_extension import CppExtension
sys.argv.remove("--cpp_ext")
ext_modules.append(
CppExtension('apex_C',
['csrc/flatten_unflatten.cpp',]))
def check_cuda_torch_binary_vs_bare_metal(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]
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) or (bare_metal_minor != torch_binary_minor):
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).")
if "--cuda_ext" in sys.argv:
from torch.utils.cpp_extension import CUDAExtension
sys.argv.remove("--cuda_ext")
if torch.utils.cpp_extension.CUDA_HOME is None:
raise RuntimeError("--cuda_ext 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.")
else:
check_cuda_torch_binary_vs_bare_metal(torch.utils.cpp_extension.CUDA_HOME)
# Set up macros for forward/backward compatibility hack around
# https://github.com/pytorch/pytorch/commit/4404762d7dd955383acee92e6f06b48144a0742e
version_ge_1_1 = []
if (TORCH_MAJOR > 1) or (TORCH_MAJOR == 1 and TORCH_MINOR > 0):
version_ge_1_1 = ['-DVERSION_GE_1_1']
ext_modules.append(
CUDAExtension(name='amp_C',
sources=['csrc/amp_C_frontend.cpp',
'csrc/multi_tensor_scale_kernel.cu',
'csrc/multi_tensor_axpby_kernel.cu',
'csrc/multi_tensor_l2norm_kernel.cu',
'csrc/multi_tensor_lamb_stage_1.cu',
'csrc/multi_tensor_lamb_stage_2.cu'],
extra_compile_args={'cxx': ['-O3'],
'nvcc':['-lineinfo',
'-O3',
# '--resource-usage',
'--use_fast_math']}))
ext_modules.append(
CUDAExtension(name='fused_adam_cuda',
sources=['csrc/fused_adam_cuda.cpp',
'csrc/fused_adam_cuda_kernel.cu'],
extra_compile_args={'cxx': ['-O3',],
'nvcc':['-O3',
'--use_fast_math']}))
ext_modules.append(
CUDAExtension(name='syncbn',
sources=['csrc/syncbn.cpp',
'csrc/welford.cu']))
ext_modules.append(
CUDAExtension(name='fused_layer_norm_cuda',
sources=['csrc/layer_norm_cuda.cpp',
'csrc/layer_norm_cuda_kernel.cu'],
extra_compile_args={'cxx': ['-O3'] + version_ge_1_1,
'nvcc':['-maxrregcount=50',
'-O3',
'--use_fast_math'] + version_ge_1_1}))
setup(
name='apex',
version='0.1',
packages=find_packages(exclude=('build',
'csrc',
'include',
'tests',
'dist',
'docs',
'tests',
'examples',
'apex.egg-info',)),
description='PyTorch Extensions written by NVIDIA',
ext_modules=ext_modules,
cmdclass=cmdclass,
)