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setup.py
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setup.py
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from setuptools import setup
import torch.utils.cpp_extension as torch_cpp_ext
from torch.utils.cpp_extension import BuildExtension, CUDAExtension
import os
import pathlib
setup_dir = os.path.dirname(os.path.realpath(__file__))
HERE = pathlib.Path(__file__).absolute().parent
def remove_unwanted_pytorch_nvcc_flags():
REMOVE_NVCC_FLAGS = [
'-D__CUDA_NO_HALF_OPERATORS__',
'-D__CUDA_NO_HALF_CONVERSIONS__',
'-D__CUDA_NO_BFLOAT16_CONVERSIONS__',
'-D__CUDA_NO_HALF2_OPERATORS__',
]
for flag in REMOVE_NVCC_FLAGS:
try:
torch_cpp_ext.COMMON_NVCC_FLAGS.remove(flag)
except ValueError:
pass
def get_cuda_arch_flags():
return [
'-gencode', 'arch=compute_75,code=sm_75', # Turing
'-gencode', 'arch=compute_80,code=sm_80', # Ampere
'-gencode', 'arch=compute_86,code=sm_86', # Ampere
]
def third_party_cmake():
import subprocess, sys, shutil
cmake = shutil.which('cmake')
if cmake is None:
raise RuntimeError('Cannot find CMake executable.')
retcode = subprocess.call([cmake, HERE])
if retcode != 0:
sys.stderr.write("Error: CMake configuration failed.\n")
sys.exit(1)
# install fast hadamard transform
hadamard_dir = os.path.join(HERE, 'third-party/fast-hadamard-transform')
pip = shutil.which('pip')
retcode = subprocess.call([pip, 'install', '-e', hadamard_dir])
if __name__ == '__main__':
third_party_cmake()
remove_unwanted_pytorch_nvcc_flags()
setup(
name='quarot',
ext_modules=[
CUDAExtension(
name='quarot._CUDA',
sources=[
'quarot/kernels/bindings.cpp',
'quarot/kernels/gemm.cu',
'quarot/kernels/quant.cu',
'quarot/kernels/flashinfer.cu',
],
include_dirs=[
os.path.join(setup_dir, 'quarot/kernels/include'),
os.path.join(setup_dir, 'third-party/cutlass/include'),
os.path.join(setup_dir, 'third-party/cutlass/tools/util/include')
],
extra_compile_args={
'cxx': [],
'nvcc': get_cuda_arch_flags(),
}
)
],
cmdclass={
'build_ext': BuildExtension
}
)