setup.py

# Copyright (c) 2023, Albert Gu, Tri Dao.
import warnings
import os
from pathlib import Path

from packaging.version import parse, Version
from setuptools import setup, find_packages
import subprocess


import torch
from torch.utils.cpp_extension import (
    BuildExtension,
    CppExtension,
    CUDAExtension,
    CUDA_HOME,
)

PACKAGE_NAME = "blackmamba"
VERSION = "0.0.1"

with open("README.md", "r", encoding="utf-8") as fh:
    long_description = fh.read()


# ninja build does not work unless include_dirs are abs path
this_dir = os.path.dirname(os.path.abspath(__file__))

# FORCE_BUILD: Force a fresh build locally, instead of attempting to find prebuilt wheels
# SKIP_CUDA_BUILD: Intended to allow CI to use a simple `python setup.py sdist` run to copy over raw files, without any cuda compilation
FORCE_BUILD = os.getenv("MAMBA_FORCE_BUILD", "FALSE") == "TRUE"
SKIP_CUDA_BUILD = os.getenv("MAMBA_SKIP_CUDA_BUILD", "FALSE") == "TRUE"
# For CI, we want the option to build with C++11 ABI since the nvcr images use C++11 ABI
FORCE_CXX11_ABI = os.getenv("MAMBA_FORCE_CXX11_ABI", "FALSE") == "TRUE"


def get_cuda_bare_metal_version(cuda_dir):
    raw_output = subprocess.check_output(
        [cuda_dir + "/bin/nvcc", "-V"], universal_newlines=True
    )
    output = raw_output.split()
    release_idx = output.index("release") + 1
    bare_metal_version = parse(output[release_idx].split(",")[0])

    return raw_output, bare_metal_version


def check_if_cuda_home_none(global_option: str) -> None:
    if CUDA_HOME is not None:
        return
    # warn instead of error because user could be downloading prebuilt wheels, so nvcc won't be necessary
    # in that case.
    warnings.warn(
        f"{global_option} was requested, but nvcc was not found.  Are you sure your environment has nvcc available?  "
        "If you're installing within a container from https://hub.docker.com/r/pytorch/pytorch, "
        "only images whose names contain 'devel' will provide nvcc."
    )


def append_nvcc_threads(nvcc_extra_args):
    return nvcc_extra_args + ["--threads", "4"]


ext_modules = []
if not SKIP_CUDA_BUILD:
    print("\n\ntorch.__version__  = {}\n\n".format(torch.__version__))
    TORCH_MAJOR = int(torch.__version__.split(".")[0])
    TORCH_MINOR = int(torch.__version__.split(".")[1])

    check_if_cuda_home_none(PACKAGE_NAME)
    # Check, if CUDA11 is installed for compute capability 8.0
    cc_flag = []
    if CUDA_HOME is not None:
        _, bare_metal_version = get_cuda_bare_metal_version(CUDA_HOME)
        if bare_metal_version < Version("11.6"):
            raise RuntimeError(
                f"{PACKAGE_NAME} is only supported on CUDA 11.6 and above.  "
                "Note: make sure nvcc has a supported version by running nvcc -V."
            )

    cc_flag.append("-gencode")
    cc_flag.append("arch=compute_70,code=sm_70")
    cc_flag.append("-gencode")
    cc_flag.append("arch=compute_80,code=sm_80")
    if bare_metal_version >= Version("11.8"):
        cc_flag.append("-gencode")
        cc_flag.append("arch=compute_90,code=sm_90")

    # HACK: The compiler flag -D_GLIBCXX_USE_CXX11_ABI is set to be the same as
    # torch._C._GLIBCXX_USE_CXX11_ABI
    # https://github.com/pytorch/pytorch/blob/8472c24e3b5b60150096486616d98b7bea01500b/torch/utils/cpp_extension.py#L920
    if FORCE_CXX11_ABI:
        torch._C._GLIBCXX_USE_CXX11_ABI = True

    ext_modules.append(
        CUDAExtension(
            name="selective_scan_cuda",
            sources=[
                "csrc/selective_scan/selective_scan.cpp",
                "csrc/selective_scan/selective_scan_fwd_fp32.cu",
                "csrc/selective_scan/selective_scan_fwd_fp16.cu",
                "csrc/selective_scan/selective_scan_fwd_bf16.cu",
                "csrc/selective_scan/selective_scan_bwd_fp32_real.cu",
                "csrc/selective_scan/selective_scan_bwd_fp32_complex.cu",
                "csrc/selective_scan/selective_scan_bwd_fp16_real.cu",
                "csrc/selective_scan/selective_scan_bwd_fp16_complex.cu",
                "csrc/selective_scan/selective_scan_bwd_bf16_real.cu",
                "csrc/selective_scan/selective_scan_bwd_bf16_complex.cu",
            ],
            extra_compile_args={
                "cxx": ["-O3", "-std=c++17"],
                "nvcc": append_nvcc_threads(
                    [
                        "-O3",
                        "-std=c++17",
                        "-U__CUDA_NO_HALF_OPERATORS__",
                        "-U__CUDA_NO_HALF_CONVERSIONS__",
                        "-U__CUDA_NO_BFLOAT16_OPERATORS__",
                        "-U__CUDA_NO_BFLOAT16_CONVERSIONS__",
                        "-U__CUDA_NO_BFLOAT162_OPERATORS__",
                        "-U__CUDA_NO_BFLOAT162_CONVERSIONS__",
                        "--expt-relaxed-constexpr",
                        "--expt-extended-lambda",
                        "--use_fast_math",
                        "--ptxas-options=-v",
                        "-lineinfo",
                    ]
                    + cc_flag
                ),
            },
            include_dirs=[Path(this_dir) / "csrc" / "selective_scan"],
        )
    )


setup(
    name=PACKAGE_NAME,
    version=VERSION,
    description="Blackmamba state-space + MoE model",
    long_description=long_description,
    long_description_content_type="text/markdown",
    packages=find_packages(include=['ops'],),
    exclude=(
            "csrc",
            "blackmamba.egg-info",
        ),
    ext_modules=ext_modules,
    cmdclass={"build_ext": BuildExtension},
    python_requires=">=3.7",
    install_requires=[
        "torch",
        "packaging",
        "ninja",
        "einops",
        "triton",
        "transformers",
        "causal_conv1d>=1.1.0",
    ],
)