135 lines
4.1 KiB
Python
135 lines
4.1 KiB
Python
# Copyright 2021 AlQuraishi Laboratory
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# Copyright 2021 DeepMind Technologies Limited
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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from setuptools import setup, Extension, find_packages
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import subprocess
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import torch
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from torch.utils.cpp_extension import BuildExtension, CppExtension, CUDAExtension, CUDA_HOME
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from scripts.utils import get_nvidia_cc
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version_dependent_macros = [
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'-DVERSION_GE_1_1',
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'-DVERSION_GE_1_3',
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'-DVERSION_GE_1_5',
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]
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extra_cuda_flags = [
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'-std=c++14',
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'-maxrregcount=50',
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'-U__CUDA_NO_HALF_OPERATORS__',
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'-U__CUDA_NO_HALF_CONVERSIONS__',
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'--expt-relaxed-constexpr',
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'--expt-extended-lambda'
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]
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def get_cuda_bare_metal_version(cuda_dir):
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if cuda_dir==None or torch.version.cuda==None:
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print("CUDA is not found, cpu version is installed")
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return None, -1, 0
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else:
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raw_output = subprocess.check_output([cuda_dir + "/bin/nvcc", "-V"], universal_newlines=True)
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output = raw_output.split()
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release_idx = output.index("release") + 1
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release = output[release_idx].split(".")
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bare_metal_major = release[0]
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bare_metal_minor = release[1][0]
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return raw_output, bare_metal_major, bare_metal_minor
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compute_capabilities = set([
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(3, 7), # K80, e.g.
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(5, 2), # Titan X
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(6, 1), # GeForce 1000-series
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])
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compute_capabilities.add((7, 0))
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_, bare_metal_major, _ = get_cuda_bare_metal_version(CUDA_HOME)
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if int(bare_metal_major) >= 11:
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compute_capabilities.add((8, 0))
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compute_capability, _ = get_nvidia_cc()
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if compute_capability is not None:
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compute_capabilities = set([compute_capability])
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cc_flag = []
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for major, minor in list(compute_capabilities):
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cc_flag.extend([
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'-gencode',
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f'arch=compute_{major}{minor},code=sm_{major}{minor}',
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])
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extra_cuda_flags += cc_flag
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if bare_metal_major != -1:
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modules = [CUDAExtension(
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name="attn_core_inplace_cuda",
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sources=[
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"openfold/utils/kernel/csrc/softmax_cuda.cpp",
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"openfold/utils/kernel/csrc/softmax_cuda_kernel.cu",
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],
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include_dirs=[
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os.path.join(
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os.path.dirname(os.path.abspath(__file__)),
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'openfold/utils/kernel/csrc/'
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)
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],
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extra_compile_args={
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'cxx': ['-O3'] + version_dependent_macros,
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'nvcc': (
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['-O3', '--use_fast_math'] +
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version_dependent_macros +
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extra_cuda_flags
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),
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}
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)]
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else:
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modules = [CppExtension(
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name="attn_core_inplace_cuda",
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sources=[
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"openfold/utils/kernel/csrc/softmax_cuda.cpp",
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"openfold/utils/kernel/csrc/softmax_cuda_stub.cpp",
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],
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extra_compile_args={
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'cxx': ['-O3'],
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}
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)]
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setup(
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name='openfold',
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version='1.0.1',
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description='A PyTorch reimplementation of DeepMind\'s AlphaFold 2',
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author='Gustaf Ahdritz & DeepMind',
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author_email='gahdritz@gmail.com',
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license='Apache License, Version 2.0',
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url='https://github.com/aqlaboratory/openfold',
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packages=find_packages(exclude=["tests", "scripts"]),
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include_package_data=True,
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package_data={
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"openfold": ['utils/kernel/csrc/*'],
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"": ["resources/stereo_chemical_props.txt"]
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},
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ext_modules=modules,
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cmdclass={'build_ext': BuildExtension},
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classifiers=[
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'License :: OSI Approved :: Apache Software License',
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'Operating System :: POSIX :: Linux',
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'Programming Language :: Python :: 3.9,'
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'Topic :: Scientific/Engineering :: Artificial Intelligence',
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],
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)
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