-
Notifications
You must be signed in to change notification settings - Fork 49
/
Copy pathsetup.py
175 lines (153 loc) · 6.35 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
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
"""
Copyright (c) 2024 by SageAttention team.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
import os
import subprocess
from packaging.version import parse, Version
from typing import List, Set
import warnings
from setuptools import setup, find_packages
import torch
from torch.utils.cpp_extension import BuildExtension, CUDAExtension, CUDA_HOME
# Supported NVIDIA GPU architectures.
SUPPORTED_ARCHS = {"8.0", "8.6", "8.7", "8.9", "9.0"}
# Compiler flags.
CXX_FLAGS = ["-g", "-O3", "-fopenmp", "-lgomp", "-std=c++17", "-DENABLE_BF16"]
NVCC_FLAGS = [
"-O3",
"-std=c++17",
"-U__CUDA_NO_HALF_OPERATORS__",
"-U__CUDA_NO_HALF_CONVERSIONS__",
"--use_fast_math",
"--threads=8",
"-Xptxas=-v",
"-diag-suppress=174", # suppress the specific warning
]
ABI = 1 if torch._C._GLIBCXX_USE_CXX11_ABI else 0
CXX_FLAGS += [f"-D_GLIBCXX_USE_CXX11_ABI={ABI}"]
NVCC_FLAGS += [f"-D_GLIBCXX_USE_CXX11_ABI={ABI}"]
if CUDA_HOME is None:
raise RuntimeError(
"Cannot find CUDA_HOME. CUDA must be available to build the package.")
def get_nvcc_cuda_version(cuda_dir: str) -> Version:
"""Get the CUDA version from nvcc.
Adapted from https://github.com/NVIDIA/apex/blob/8b7a1ff183741dd8f9b87e7bafd04cfde99cea28/setup.py
"""
nvcc_output = subprocess.check_output([cuda_dir + "/bin/nvcc", "-V"],
universal_newlines=True)
output = nvcc_output.split()
release_idx = output.index("release") + 1
nvcc_cuda_version = parse(output[release_idx].split(",")[0])
return nvcc_cuda_version
def get_torch_arch_list() -> Set[str]:
# TORCH_CUDA_ARCH_LIST can have one or more architectures,
# e.g. "8.0" or "7.5,8.0,8.6+PTX". Here, the "8.6+PTX" option asks the
# compiler to additionally include PTX code that can be runtime-compiled
# and executed on the 8.6 or newer architectures. While the PTX code will
# not give the best performance on the newer architectures, it provides
# forward compatibility.
env_arch_list = os.environ.get("TORCH_CUDA_ARCH_LIST", None)
if env_arch_list is None:
return set()
# List are separated by ; or space.
torch_arch_list = set(env_arch_list.replace(" ", ";").split(";"))
if not torch_arch_list:
return set()
# Filter out the invalid architectures and print a warning.
valid_archs = SUPPORTED_ARCHS.union({s + "+PTX" for s in SUPPORTED_ARCHS})
arch_list = torch_arch_list.intersection(valid_archs)
# If none of the specified architectures are valid, raise an error.
if not arch_list:
raise RuntimeError(
"None of the CUDA architectures in `TORCH_CUDA_ARCH_LIST` env "
f"variable ({env_arch_list}) is supported. "
f"Supported CUDA architectures are: {valid_archs}.")
invalid_arch_list = torch_arch_list - valid_archs
if invalid_arch_list:
warnings.warn(
f"Unsupported CUDA architectures ({invalid_arch_list}) are "
"excluded from the `TORCH_CUDA_ARCH_LIST` env variable "
f"({env_arch_list}). Supported CUDA architectures are: "
f"{valid_archs}.")
return arch_list
# First, check the TORCH_CUDA_ARCH_LIST environment variable.
compute_capabilities = get_torch_arch_list()
if not compute_capabilities:
# If TORCH_CUDA_ARCH_LIST is not defined or empty, target all available
# GPUs on the current machine.
device_count = torch.cuda.device_count()
for i in range(device_count):
major, minor = torch.cuda.get_device_capability(i)
if major < 8:
raise RuntimeError(
"GPUs with compute capability below 8.0 are not supported.")
compute_capabilities.add(f"{major}.{minor}")
nvcc_cuda_version = get_nvcc_cuda_version(CUDA_HOME)
if not compute_capabilities:
raise RuntimeError("No GPUs found. Please specify the target GPU architectures or build on a machine with GPUs.")
# Validate the NVCC CUDA version.
if nvcc_cuda_version < Version("12.0"):
raise RuntimeError("CUDA 12.0 or higher is required to build the package.")
if nvcc_cuda_version < Version("12.4"):
if any(cc.startswith("8.9") for cc in compute_capabilities):
raise RuntimeError(
"CUDA 12.4 or higher is required for compute capability 8.9.")
if any(cc.startswith("9.0") for cc in compute_capabilities):
raise RuntimeError(
"CUDA 12.4 or higher is required for compute capability 9.0.")
# Add target compute capabilities to NVCC flags.
for capability in compute_capabilities:
num = capability[0] + capability[2]
NVCC_FLAGS += ["-gencode", f"arch=compute_{num},code=sm_{num}"]
if capability.endswith("+PTX"):
NVCC_FLAGS += ["-gencode", f"arch=compute_{num},code=compute_{num}"]
ext_modules = []
# Attention kernels.
qattn_extension = CUDAExtension(
name="sageattention._qattn",
sources=[
"csrc/qattn/pybind.cpp",
"csrc/qattn/qk_int_sv_f16_cuda.cu",
"csrc/qattn/qk_int_sv_f8_cuda.cu",
"csrc/qattn/qk_int_sv_f16_buffer_cuda.cu",
"csrc/qattn/qk_int_sv_f8_buffer_cuda.cu",
],
extra_compile_args={
"cxx": CXX_FLAGS,
"nvcc": NVCC_FLAGS,
},
)
ext_modules.append(qattn_extension)
# Fused kernels.
fused_extension = CUDAExtension(
name="sageattention._fused",
sources=["csrc/fused/pybind.cpp", "csrc/fused/fused.cu"],
extra_compile_args={
"cxx": CXX_FLAGS,
"nvcc": NVCC_FLAGS,
},
)
ext_modules.append(fused_extension)
setup(
name='sageattention',
version='2.0.1',
author='SageAttention team',
license='Apache 2.0 License',
description='Accurate and efficient plug-and-play low-bit attention.',
long_description=open('README.md').read(),
long_description_content_type='text/markdown',
url='https://github.com/thu-ml/SageAttention',
packages=find_packages(),
python_requires='>=3.9',
ext_modules=ext_modules,
cmdclass={"build_ext": BuildExtension},
)