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setup.py
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setup.py
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# #!python
#cython: language_level=3
#
# https://github.com/rmcgibbo/npcuda-example/blob/master/cython/setup.py
#
# Copyright (c) 2014, Robert T. McGibbon and the Authors
# Copyright (c) 2022 Cameron Fairchild
# Copyright (c) 2022 Opentensor Foundation
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
#
# 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
# THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS
# BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE
# GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
# STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#
import os
from os.path import join as pjoin
from setuptools import find_packages, setup, Extension
from Cython.Distutils import build_ext
from Cython.Build import cythonize
import numpy
def find_in_path(name, path):
"""Find a file in a search path"""
# Adapted fom http://code.activestate.com/recipes/52224
for dir in path.split(os.pathsep):
binpath = pjoin(dir, name)
if os.path.exists(binpath):
return os.path.abspath(binpath)
return None
def locate_cuda():
"""Locate the CUDA environment on the system
Returns a dict with keys 'home', 'nvcc', 'include', and 'lib64'
and values giving the absolute path to each directory.
Starts by looking for the CUDAHOME env variable. If not found,
everything is based on finding 'nvcc' in the PATH.
"""
# First check if the CUDAHOME env variable is in use
if 'CUDA_HOME' in os.environ:
home = os.environ['CUDA_HOME']
nvcc = pjoin(home, 'bin', 'nvcc')
else:
# Otherwise, search the PATH for NVCC
nvcc = find_in_path('nvcc', os.environ['PATH'])
if nvcc is None:
raise EnvironmentError('The nvcc binary could not be '
'located in your $PATH. Either add it to your path, '
'or set $CUDA_HOME')
home = os.path.dirname(os.path.dirname(nvcc))
cudaconfig = {'home': home, 'nvcc': nvcc,
'include': pjoin(home, 'include'),
'lib64': pjoin(home, 'lib64')}
for k, v in iter(cudaconfig.items()):
if not os.path.exists(v):
raise EnvironmentError('The CUDA %s path could not be '
'located in %s' % (k, v))
return cudaconfig
def customize_compiler_for_nvcc(self):
"""Inject deep into distutils to customize how the dispatch
to gcc/nvcc works.
If you subclass UnixCCompiler, it's not trivial to get your subclass
injected in, and still have the right customizations (i.e.
distutils.sysconfig.customize_compiler) run on it. So instead of going
the OO route, I have this. Note, it's kindof like a wierd functional
subclassing going on.
"""
# Tell the compiler it can processes .cu and files
self.src_extensions.append('.cu')
# Save references to the default compiler_so and _comple methods
default_compiler_so = self.compiler_so
super = self._compile
# Now redefine the _compile method. This gets executed for each
# object but distutils doesn't have the ability to change compilers
# based on source extension: we add it.
def _compile(obj, src, ext, cc_args, extra_postargs, pp_opts):
if os.path.splitext(src)[1] == '.cu':
# use the cuda for .cu files
self.set_executable('compiler_so', CUDA['nvcc'])
# use only a subset of the extra_postargs, which are 1-1
# translated from the extra_compile_args in the Extension class
postargs = extra_postargs['nvcc']
else:
postargs = extra_postargs['gcc']
super(obj, src, ext, cc_args, postargs, pp_opts)
# Reset the default compiler_so, which we might have changed for cuda
self.compiler_so = default_compiler_so
# Inject our redefined _compile method into the class
self._compile = _compile
# Run the customize_compiler
class custom_build_ext(build_ext):
def build_extensions(self):
customize_compiler_for_nvcc(self.compiler)
build_ext.build_extensions(self)
CUDA = locate_cuda()
# Obtain the numpy include directory. This logic works across numpy versions.
try:
numpy_include = numpy.get_include()
except AttributeError:
numpy_include = numpy.get_numpy_include()
ext = Extension('cubit',
sources = ['kernels/main.cu', 'cubit.pyx'],
library_dirs=[CUDA['lib64']],
libraries=['cudart'],
language='c++',
runtime_library_dirs=[CUDA['lib64']],
extra_compile_args={
'gcc': [],
'nvcc': ['-Xptxas', '-v', '-O3',
'-gencode', 'arch=compute_86,code=sm_86',
'-gencode', 'arch=compute_80,code=sm_80',
'-gencode', 'arch=compute_75,code=sm_75',
'-gencode', 'arch=compute_70,code=sm_70',
'-gencode', 'arch=compute_61,code=sm_61',
'--ptxas-options=-v', '-c',
'--compiler-options', "'-fPIC'"
]
},
include_dirs = [numpy_include, CUDA['include']])
setup(
name = 'cubit',
# Random metadata. there's more you can supply
author = 'Opentensor Foundation',
author_email = '[email protected]',
url = 'https://github.com/opentensor/cubit',
version = '1.2.1',
ext_modules = cythonize(ext),
# Inject our custom trigger
cmdclass = {'build_ext': custom_build_ext},
# Since the package has c code, the egg cannot be zipped
zip_safe = False,
packages=find_packages(),
)