setup.py

import os
import subprocess
from packaging.version import parse, Version
from typing import List, Set
import warnings

from setuptools import setup, find_packages
import torch
from torch.utils.cpp_extension import BuildExtension, CUDAExtension, CUDA_HOME

# Supported NVIDIA GPU architectures.
SUPPORTED_ARCHS = {"8.0", "8.6", "8.7", "8.9", "9.0"}

# Compiler flags.
CXX_FLAGS = ["-g", "-O3", "-fopenmp", "-lgomp", "-std=c++17", "-DENABLE_BF16"]
NVCC_FLAGS = [
    "-O3",
    "-std=c++17",
    "-U__CUDA_NO_HALF_OPERATORS__",
    "-U__CUDA_NO_HALF_CONVERSIONS__",
    "--use_fast_math",
    "--threads=8",
    "-Xptxas=-v",
    "-diag-suppress=174", # suppress the specific warning
]

ABI = 1 if torch._C._GLIBCXX_USE_CXX11_ABI else 0
CXX_FLAGS += [f"-D_GLIBCXX_USE_CXX11_ABI={ABI}"]
NVCC_FLAGS += [f"-D_GLIBCXX_USE_CXX11_ABI={ABI}"]

if CUDA_HOME is None:
    raise RuntimeError(
        "Cannot find CUDA_HOME. CUDA must be available to build the package.")

def get_nvcc_cuda_version(cuda_dir: str) -> Version:
    """Get the CUDA version from nvcc.

    Adapted from https://github.com/NVIDIA/apex/blob/8b7a1ff183741dd8f9b87e7bafd04cfde99cea28/setup.py
    """
    nvcc_output = subprocess.check_output([cuda_dir + "/bin/nvcc", "-V"],
                                          universal_newlines=True)
    output = nvcc_output.split()
    release_idx = output.index("release") + 1
    nvcc_cuda_version = parse(output[release_idx].split(",")[0])
    return nvcc_cuda_version

def get_torch_arch_list() -> Set[str]:
    # TORCH_CUDA_ARCH_LIST can have one or more architectures,
    # e.g. "8.0" or "7.5,8.0,8.6+PTX". Here, the "8.6+PTX" option asks the
    # compiler to additionally include PTX code that can be runtime-compiled
    # and executed on the 8.6 or newer architectures. While the PTX code will
    # not give the best performance on the newer architectures, it provides
    # forward compatibility.
    env_arch_list = os.environ.get("TORCH_CUDA_ARCH_LIST", None)
    if env_arch_list is None:
        return set()

    # List are separated by ; or space.
    torch_arch_list = set(env_arch_list.replace(" ", ";").split(";"))
    if not torch_arch_list:
        return set()

    # Filter out the invalid architectures and print a warning.
    valid_archs = SUPPORTED_ARCHS.union({s + "+PTX" for s in SUPPORTED_ARCHS})
    arch_list = torch_arch_list.intersection(valid_archs)
    # If none of the specified architectures are valid, raise an error.
    if not arch_list:
        raise RuntimeError(
            "None of the CUDA architectures in `TORCH_CUDA_ARCH_LIST` env "
            f"variable ({env_arch_list}) is supported. "
            f"Supported CUDA architectures are: {valid_archs}.")
    invalid_arch_list = torch_arch_list - valid_archs
    if invalid_arch_list:
        warnings.warn(
            f"Unsupported CUDA architectures ({invalid_arch_list}) are "
            "excluded from the `TORCH_CUDA_ARCH_LIST` env variable "
            f"({env_arch_list}). Supported CUDA architectures are: "
            f"{valid_archs}.")
    return arch_list

# First, check the TORCH_CUDA_ARCH_LIST environment variable.
compute_capabilities = get_torch_arch_list()
if not compute_capabilities:
    # If TORCH_CUDA_ARCH_LIST is not defined or empty, target all available
    # GPUs on the current machine.
    device_count = torch.cuda.device_count()
    for i in range(device_count):
        major, minor = torch.cuda.get_device_capability(i)
        if major < 8:
            raise RuntimeError(
                "GPUs with compute capability below 8.0 are not supported.")
        compute_capabilities.add(f"{major}.{minor}")

nvcc_cuda_version = get_nvcc_cuda_version(CUDA_HOME)
if not compute_capabilities:
    raise RuntimeError("No GPUs found. Please specify the target GPU architectures or build on a machine with GPUs.")

# Validate the NVCC CUDA version.
if nvcc_cuda_version < Version("12.0"):
    raise RuntimeError("CUDA 12.0 or higher is required to build the package.")
if nvcc_cuda_version < Version("12.4"):
    if any(cc.startswith("8.9") for cc in compute_capabilities):
        raise RuntimeError(
            "CUDA 12.4 or higher is required for compute capability 8.9.")
    if any(cc.startswith("9.0") for cc in compute_capabilities):
        raise RuntimeError(
            "CUDA 12.4 or higher is required for compute capability 9.0.")

# Add target compute capabilities to NVCC flags.
for capability in compute_capabilities:
    num = capability[0] + capability[2]
    NVCC_FLAGS += ["-gencode", f"arch=compute_{num},code=sm_{num}"]
    if capability.endswith("+PTX"):
        NVCC_FLAGS += ["-gencode", f"arch=compute_{num},code=compute_{num}"]

ext_modules = []

# Attention kernels.
qattn_extension = CUDAExtension(
    name="spas_sage_attn._qattn",
    sources=[
        "csrc/qattn/pybind.cpp",
        "csrc/qattn/qk_int_sv_f16_cuda.cu",
        "csrc/qattn/qk_int_sv_f8_cuda.cu",
    ],
    extra_compile_args={
        "cxx": CXX_FLAGS,
        "nvcc": NVCC_FLAGS,
    },
)
ext_modules.append(qattn_extension)

fused_extension = CUDAExtension(
    name="spas_sage_attn._fused",
    sources=["csrc/fused/pybind.cpp", "csrc/fused/fused.cu"],
    extra_compile_args={
        "cxx": CXX_FLAGS,
        "nvcc": NVCC_FLAGS,
    },
)
ext_modules.append(fused_extension)

setup(
    name='spas_sage_attn', 
    version='0.1.0',  
    author='Jintao Zhang, Chendong Xiang, Haofeng Huang',  
    author_email='jt-zhang6@gmail.com', 
    packages=find_packages(),  
    description='Accurate and efficient Sparse SageAttention.',  
    long_description=open('README.md').read(),  
    long_description_content_type='text/markdown', 
    url='https://github.com/thu-ml/SpargeAttn', 
    license='BSD 3-Clause License', 
    python_requires='>=3.9', 
    classifiers=[  
        'Development Status :: 3 - Alpha', 
        'Intended Audience :: Developers',  
        'Topic :: Software Development :: Libraries :: Python Modules',
        'License :: OSI Approved :: BSD License',
        'Programming Language :: Python :: 3', 
        'Programming Language :: Python :: 3.9',
        'Programming Language :: Python :: 3.10',
        'Programming Language :: Python :: 3.11',
        'Operating System :: OS Independent',
    ],
    ext_modules=ext_modules,
    cmdclass={"build_ext": BuildExtension},
)