setup.py

import os
import re
import subprocess
import sys
from datetime import date

import setuptools
import torch
from packaging import version as packaging_version
from torch.utils.cpp_extension import CUDA_HOME, BuildExtension, CUDAExtension


class CustomBuildExtension(BuildExtension):
    def build_extensions(self):
        for ext in self.extensions:
            if not "cxx" in ext.extra_compile_args:
                ext.extra_compile_args["cxx"] = []
            if not "nvcc" in ext.extra_compile_args:
                ext.extra_compile_args["nvcc"] = []
            if self.compiler.compiler_type == "msvc":
                ext.extra_compile_args["cxx"] += ext.extra_compile_args["msvc"]
                ext.extra_compile_args["nvcc"] += ext.extra_compile_args["nvcc_msvc"]
            else:
                ext.extra_compile_args["cxx"] += ext.extra_compile_args["gcc"]
        super().build_extensions()


def get_sm_targets() -> list[str]:
    is_rocm = hasattr(torch.version, 'hip') and torch.version.hip is not None

    if is_rocm:
        # ========== ROCm / AMD 路径 ==========
        # 手动指定或自动检测 AMD gfx 架构
        # 注意：ROCm 不使用 "SM"，而是 "gfxXXXX"
        gfx_arch = os.getenv("AMDGPU_TARGETS", None)
        if gfx_arch is None:
            # 尝试从 PyTorch 获取（部分版本支持）
            try:
                # 示例：'gfx942' for MI300X
                props = torch.cuda.get_device_properties(0)
                # 在 ROCm 中，name 可能包含 gfx 信息，或需查表
                # 这里保守起见，要求用户显式设置
                raise NotImplementedError("Auto-detection of AMD arch not reliable. Set NUNCHAKU_AMD_ARCH=gfx942 etc.")
            except:
                raise RuntimeError(
                    "Running on ROCm, but NUNCHAKU_AMD_ARCH not set. "
                    "Please specify your AMD GPU architecture, e.g.: "
                    "export NUNCHAKU_AMD_ARCH=gfx942  # for MI300X"
                )
        return [gfx_arch]  # 返回如 ["gfx942"]
    else:
        nvcc_path = os.path.join(CUDA_HOME, "bin/nvcc") if CUDA_HOME else "nvcc"
        try:
            nvcc_output = subprocess.check_output([nvcc_path, "--version"]).decode()
            match = re.search(r"release (\d+\.\d+), V(\d+\.\d+\.\d+)", nvcc_output)
            if match:
                nvcc_version = match.group(2)
            else:
                raise Exception("nvcc version not found")
            print(f"Found nvcc version: {nvcc_version}")
        except:
            raise Exception("nvcc not found")

        support_sm120 = packaging_version.parse(nvcc_version) >= packaging_version.parse("12.8")

        install_mode = os.getenv("NUNCHAKU_INSTALL_MODE", "FAST")
        if install_mode == "FAST":
            ret = []
            for i in range(torch.cuda.device_count()):
                capability = torch.cuda.get_device_capability(i)
                sm = f"{capability[0]}{capability[1]}"
                if sm == "120" and support_sm120:
                    sm = "120a"
                assert sm in ["75", "80", "86", "89", "92", "120a"], f"Unsupported SM {sm}"
                if sm not in ret:
                    ret.append(sm)
        else:
            assert install_mode == "ALL"
            ret = ["75", "80", "86", "89", "92"]
            if support_sm120:
                ret.append("120a")
        return ret


if __name__ == "__main__":
    fp = open("nunchaku/__version__.py", "r").read()
    version = eval(fp.strip().split()[-1])

    torch_version = torch.__version__.split("+")[0]
    torch_major_minor_version = ".".join(torch_version.split(".")[:2])
    if "dev" in version:
        version = version + date.today().strftime("%Y%m%d")  # data
    version = version + "+torch" + torch_major_minor_version

    ROOT_DIR = os.path.dirname(__file__)

    ignores = [
        "third_party/cutlass/*",
        "third_party/json/*",
        "third_party/mio/*",
        "third_party/spdlog/*",
    ]

    INCLUDE_DIRS = [
        "src",
        "third_party/cutlass/include",
        "third_party/json/include",
        "third_party/mio/include",
        "third_party/spdlog/include",
        "third_party/Block-Sparse-Attention/csrc/block_sparse_attn",
    ]

    INCLUDE_DIRS = [os.path.join(ROOT_DIR, dir) for dir in INCLUDE_DIRS]

    DEBUG = False

    def ncond(s) -> list:
        if DEBUG:
            return []
        else:
            return [s]

    def cond(s) -> list:
        if DEBUG:
            return [s]
        else:
            return []

    #sm_targets = get_sm_targets()
    #print(f"Detected SM targets: {sm_targets}", file=sys.stderr)

    #assert len(sm_targets) > 0, "No SM targets found"

    GCC_FLAGS = ["-w", "-DENABLE_BF16=1", "-DBUILD_NUNCHAKU=1", "-fvisibility=hidden", "-g", "-std=c++2a", "-UNDEBUG", "-Og"]
    MSVC_FLAGS = ["-w", "/DENABLE_BF16=1", "/DBUILD_NUNCHAKU=1", "/std:c++2a", "/UNDEBUG", "/Zc:__cplusplus", "/FS"]
    NVCC_FLAGS = [
        "-w",
        "-DDCU_ASM",
        "-DENABLE_BF16=1",
        "-DBUILD_NUNCHAKU=1",
        "-g",
        "-std=c++2a",
        "-UNDEBUG",
        "-mllvm",
        "-nv-ptx-asm-transform=true",
        "-finline-asm-ptx",
        #"-Xcudafe",
        #"--diag_suppress=20208",  # spdlog: 'long double' is treated as 'double' in device code
        *cond("-G"),
        "-U__CUDA_NO_HALF_OPERATORS__",
        "-U__CUDA_NO_HALF_CONVERSIONS__",
        "-U__CUDA_NO_HALF2_OPERATORS__",
        "-U__CUDA_NO_HALF2_CONVERSIONS__",
        "-U__CUDA_NO_BFLOAT16_OPERATORS__",
        "-U__CUDA_NO_BFLOAT16_CONVERSIONS__",
        "-U__CUDA_NO_BFLOAT162_OPERATORS__",
        "-U__CUDA_NO_BFLOAT162_CONVERSIONS__",
        #f"--threads={len(sm_targets)}",
        f"--expt-relaxed-constexpr",
        "--expt-extended-lambda",
        #"--ptxas-options=--allow-expensive-optimizations=true",
    ]

    if os.getenv("NUNCHAKU_BUILD_WHEELS", "0") == "0":
        NVCC_FLAGS.append("--generate-line-info")

    #for target in sm_targets:
    #    NVCC_FLAGS += ["-gencode", f"arch=compute_{target},code=sm_{target}"]

    NVCC_MSVC_FLAGS = ["-Xcompiler", "/Zc:__cplusplus", "-Xcompiler", "/FS", "-Xcompiler", "/bigobj"]

    nunchaku_extension = CUDAExtension(
        name="nunchaku._C",
        sources=[
            "nunchaku/csrc/pybind.cpp",
            "src/interop/torch.cpp",
            "src/activation.cpp",
            "src/layernorm.cpp",
            "src/Linear.cpp",
            *ncond("src/FluxModel.cpp"),
            *ncond("src/SanaModel.cpp"),
            "src/Serialization.cpp",
            "src/Module.cpp",
            *ncond("third_party/Block-Sparse-Attention/csrc/block_sparse_attn/src/flash_fwd_hdim64_fp16_sm80.cu"),
            *ncond("third_party/Block-Sparse-Attention/csrc/block_sparse_attn/src/flash_fwd_hdim64_bf16_sm80.cu"),
            *ncond("third_party/Block-Sparse-Attention/csrc/block_sparse_attn/src/flash_fwd_hdim128_fp16_sm80.cu"),
            *ncond("third_party/Block-Sparse-Attention/csrc/block_sparse_attn/src/flash_fwd_hdim128_bf16_sm80.cu"),
            *ncond("third_party/Block-Sparse-Attention/csrc/block_sparse_attn/src/flash_fwd_block_hdim64_fp16_sm80.cu"),
            *ncond("third_party/Block-Sparse-Attention/csrc/block_sparse_attn/src/flash_fwd_block_hdim64_bf16_sm80.cu"),
            *ncond(
                "third_party/Block-Sparse-Attention/csrc/block_sparse_attn/src/flash_fwd_block_hdim128_fp16_sm80.cu"
            ),
            *ncond(
                "third_party/Block-Sparse-Attention/csrc/block_sparse_attn/src/flash_fwd_block_hdim128_bf16_sm80.cu"
            ),
            "src/kernels/activation_kernels.cu",
            "src/kernels/layernorm_kernels.cu",
            "src/kernels/misc_kernels.cu",
            "src/kernels/zgemm/gemm_w4a4.cu",
            "src/kernels/zgemm/gemm_w4a4_test.cu",
            "src/kernels/zgemm/gemm_w4a4_launch_fp16_int4.cu",
            "src/kernels/zgemm/gemm_w4a4_launch_fp16_int4_fasteri2f.cu",
            "src/kernels/zgemm/gemm_w4a4_launch_fp16_fp4.cu",
            "src/kernels/zgemm/gemm_w4a4_launch_bf16_int4.cu",
            "src/kernels/zgemm/gemm_w4a4_launch_bf16_fp4.cu",
            "src/kernels/zgemm/gemm_w8a8.cu",
            "src/kernels/zgemm/attention.cu",
            "src/kernels/dwconv.cu",
            "src/kernels/gemm_batched.cu",
            "src/kernels/gemm_f16.cu",
            "src/kernels/awq/gemm_awq.cu",
            "src/kernels/awq/gemv_awq.cu",
            *ncond("third_party/Block-Sparse-Attention/csrc/block_sparse_attn/flash_api.cpp"),
            *ncond("third_party/Block-Sparse-Attention/csrc/block_sparse_attn/flash_api_adapter.cpp"),
        ],
        extra_compile_args={"gcc": GCC_FLAGS, "msvc": MSVC_FLAGS, "nvcc": NVCC_FLAGS, "nvcc_msvc": NVCC_MSVC_FLAGS},
        include_dirs=INCLUDE_DIRS,
        ignores=ignores,
    )

    setuptools.setup(
        name="nunchaku",
        version=version,
        packages=setuptools.find_packages(),
        ext_modules=[nunchaku_extension],
        cmdclass={"build_ext": CustomBuildExtension},
    )