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setup.py
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setup.py
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# Copyright 2021 AlQuraishi Laboratory
# Copyright 2021 DeepMind Technologies Limited
#
# 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
from setuptools import setup, Extension, find_packages
import subprocess
import torch
from torch.utils.cpp_extension import BuildExtension, CppExtension, CUDAExtension, CUDA_HOME
from scripts.utils import get_nvidia_cc
version_dependent_macros = [
'-DVERSION_GE_1_1',
'-DVERSION_GE_1_3',
'-DVERSION_GE_1_5',
]
extra_cuda_flags = [
'-std=c++17', # c++14
'-maxrregcount=50',
'-U__CUDA_NO_HALF_OPERATORS__',
'-U__CUDA_NO_HALF_CONVERSIONS__',
'--expt-relaxed-constexpr',
'--expt-extended-lambda'
]
def get_cuda_bare_metal_version(cuda_dir):
if cuda_dir is None or torch.version.cuda is None:
print("CUDA is not found, cpu version is installed")
return None, -1, 0
else:
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
compute_capabilities = set([
(3, 7), # K80, e.g.
(5, 2), # Titan X
(6, 1), # GeForce 1000-series
])
compute_capabilities.add((7, 0))
_, bare_metal_major, _ = get_cuda_bare_metal_version(CUDA_HOME)
if int(bare_metal_major) >= 11:
compute_capabilities.add((8, 0))
compute_capability, _ = get_nvidia_cc()
if compute_capability is not None:
compute_capabilities = set([compute_capability])
cc_flag = []
for major, minor in list(compute_capabilities):
cc_flag.extend([
'-gencode',
f'arch=compute_{major}{minor},code=sm_{major}{minor}',
])
extra_cuda_flags += cc_flag
cc_flag = ['-gencode', 'arch=compute_70,code=sm_70']
if bare_metal_major != -1:
modules = [CUDAExtension(
name="attn_core_inplace_cuda",
sources=[
"src/utils/kernel/csrc/softmax_cuda.cpp",
"src/utils/kernel/csrc/softmax_cuda_kernel.cu",
],
include_dirs=[
os.path.join(
os.path.dirname(os.path.abspath(__file__)),
'src/utils/kernel/csrc/'
)
],
extra_compile_args={
'cxx': ['-O3'] + version_dependent_macros,
'nvcc': (
['-O3', '--use_fast_math'] +
version_dependent_macros +
extra_cuda_flags
),
}
)]
else:
modules = [CppExtension(
name="attn_core_inplace_cuda",
sources=[
"src/utils/kernel/csrc/softmax_cuda.cpp",
"src/utils/kernel/csrc/softmax_cuda_stub.cpp",
],
extra_compile_args={
'cxx': ['-O3'],
}
)]
setup(
name='alphafold3',
version='2.0.0',
description='An open-source implementation of AlphaFold3',
author='Arda Goreci',
author_email='arda@ligo.bio',
license='Apache License, Version 2.0',
url='https://github.com/Ligo-Biosciences/AlphaFold3',
packages=find_packages(include=["flash_attn", "flash_attn.*"], exclude=["tests", "scripts"]),
include_package_data=True,
package_data={
"src": ['utils/kernel/csrc/*'],
"": ["resources/stereo_chemical_props.txt"]
},
ext_modules=modules,
cmdclass={'build_ext': BuildExtension},
classifiers=[
'License :: OSI Approved :: Apache Software License',
'Operating System :: POSIX :: Linux',
'Programming Language :: Python :: 3.9,'
'Topic :: Scientific/Engineering :: Artificial Intelligence',
],
)