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setup.py
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setup.py
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from setuptools import setup, find_packages
import os
from glob import glob
import torch
from torch.utils.cpp_extension import CUDA_HOME, CUDAExtension, CppExtension
extra_compile_args = {"cxx": ["-std=c++14"]}
define_macros = []
sources = glob(os.path.join('DSS', 'csrc', '*.cpp'))
source_cuda = glob(os.path.join('DSS', 'csrc', '*.cu'))
force_cuda = os.getenv("FORCE_CUDA", "0") == "1"
if (torch.cuda.is_available() and CUDA_HOME is not None) or force_cuda:
extension = CUDAExtension
sources += source_cuda
define_macros += [("WITH_CUDA", None)]
nvcc_args = [
"-DCUDA_HAS_FP16=1",
"-D__CUDA_NO_HALF_OPERATORS__",
"-D__CUDA_NO_HALF_CONVERSIONS__",
"-D__CUDA_NO_HALF2_OPERATORS__",
]
nvcc_flags_env = os.getenv("NVCC_FLAGS", "")
if nvcc_flags_env != "":
nvcc_args.extend(nvcc_flags_env.split(" "))
# It's better if pytorch can do this by default ..
CC = os.environ.get("CC", None)
if CC is not None:
CC_arg = "-ccbin={}".format(CC)
if CC_arg not in nvcc_args:
if any(arg.startswith("-ccbin") for arg in nvcc_args):
raise ValueError("Inconsistent ccbins")
nvcc_args.append(CC_arg)
extra_compile_args["nvcc"] = nvcc_args
else:
print('Cuda is not available!')
include_dirs = torch.utils.cpp_extension.include_paths()
ext_modules = [
CUDAExtension('DSS._C', sources,
include_dirs=['DSS/csrc']+include_dirs,
define_macros=define_macros,
extra_compile_args=extra_compile_args
)
]
INSTALL_REQUIREMENTS = ['numpy', 'torch', 'plyfile',]
class BuildExtension(torch.utils.cpp_extension.BuildExtension):
def __init__(self, *args, **kwargs):
super().__init__(use_ninja=False, *args, **kwargs)
setup(
name='DSS',
description='Differentiable Surface Splatter',
author='Yifan Wang, Lixin Xue and Felice Serena',
packages=find_packages(exclude=('tests')),
license='MIT License',
version='1.0',
install_requires=INSTALL_REQUIREMENTS,
ext_modules=ext_modules,
cmdclass={'build_ext': BuildExtension}
)