setup.py

import io
import logging
import os
import re
import subprocess
import sys
from shutil import which
from typing import List

import torch
from packaging.version import Version, parse
from setuptools import Extension, find_packages, setup
from setuptools.command.build_ext import build_ext
from torch.utils.cpp_extension import CUDA_HOME

ROOT_DIR = os.path.dirname(__file__)
logger = logging.getLogger(__name__)

# vLLM only supports Linux platform
assert sys.platform.startswith(
    "linux"), "vLLM only supports Linux platform (including WSL)."

MAIN_CUDA_VERSION = "12.1"


def is_sccache_available() -> bool:
    return which("sccache") is not None


def is_ccache_available() -> bool:
    return which("ccache") is not None


def is_ninja_available() -> bool:
    return which("ninja") is not None


def remove_prefix(text, prefix):
    if text.startswith(prefix):
        return text[len(prefix):]
    return text


class CMakeExtension(Extension):

    def __init__(self, name: str, cmake_lists_dir: str = '.', **kwa) -> None:
        super().__init__(name, sources=[], **kwa)
        self.cmake_lists_dir = os.path.abspath(cmake_lists_dir)


class cmake_build_ext(build_ext):
    # A dict of extension directories that have been configured.
    did_config = {}

    #
    # Determine number of compilation jobs and optionally nvcc compile threads.
    #
    def compute_num_jobs(self):
        num_jobs = os.environ.get("MAX_JOBS", None)
        if num_jobs is not None:
            num_jobs = int(num_jobs)
            logger.info(f"Using MAX_JOBS={num_jobs} as the number of jobs.")
        else:
            try:
                # os.sched_getaffinity() isn't universally available, so fall
                #  back to os.cpu_count() if we get an error here.
                num_jobs = len(os.sched_getaffinity(0))
            except AttributeError:
                num_jobs = os.cpu_count()

        nvcc_threads = None
        if _is_cuda():
            nvcc_cuda_version = get_nvcc_cuda_version()
            if nvcc_cuda_version >= Version("11.2"):
                nvcc_threads = int(os.getenv("NVCC_THREADS", 8))
                num_jobs = max(1, round(num_jobs / (nvcc_threads / 4)))

        return num_jobs, nvcc_threads

    #
    # Perform cmake configuration for a single extension.
    #
    def configure(self, ext: CMakeExtension) -> None:
        # If we've already configured using the CMakeLists.txt for
        # this extension, exit early.
        if ext.cmake_lists_dir in cmake_build_ext.did_config:
            return

        cmake_build_ext.did_config[ext.cmake_lists_dir] = True

        # Select the build type.
        # Note: optimization level + debug info are set by the build type
        default_cfg = "Debug" if self.debug else "RelWithDebInfo"
        cfg = os.getenv("CMAKE_BUILD_TYPE", default_cfg)

        # where .so files will be written, should be the same for all extensions
        # that use the same CMakeLists.txt.
        outdir = os.path.abspath(
            os.path.dirname(self.get_ext_fullpath(ext.name)))

        cmake_args = [
            '-DCMAKE_BUILD_TYPE={}'.format(cfg),
            '-DCMAKE_LIBRARY_OUTPUT_DIRECTORY={}'.format(outdir),
            '-DCMAKE_ARCHIVE_OUTPUT_DIRECTORY={}'.format(self.build_temp),
        ]

        verbose = bool(int(os.getenv('VERBOSE', '0')))
        if verbose:
            cmake_args += ['-DCMAKE_VERBOSE_MAKEFILE=ON']

        if is_sccache_available():
            cmake_args += [
                '-DCMAKE_CXX_COMPILER_LAUNCHER=sccache',
                '-DCMAKE_CUDA_COMPILER_LAUNCHER=sccache',
            ]
        elif is_ccache_available():
            cmake_args += [
                '-DCMAKE_CXX_COMPILER_LAUNCHER=ccache',
                '-DCMAKE_CUDA_COMPILER_LAUNCHER=ccache',
            ]

        # Pass the python executable to cmake so it can find an exact
        # match.
        cmake_args += ['-DVLLM_PYTHON_EXECUTABLE={}'.format(sys.executable)]

        if _install_punica():
            cmake_args += ['-DVLLM_INSTALL_PUNICA_KERNELS=ON']

        #
        # Setup parallelism and build tool
        #
        num_jobs, nvcc_threads = self.compute_num_jobs()

        if nvcc_threads:
            cmake_args += ['-DNVCC_THREADS={}'.format(nvcc_threads)]

        if is_ninja_available():
            build_tool = ['-G', 'Ninja']
            cmake_args += [
                '-DCMAKE_JOB_POOL_COMPILE:STRING=compile',
                '-DCMAKE_JOB_POOLS:STRING=compile={}'.format(num_jobs),
            ]
        else:
            # Default build tool to whatever cmake picks.
            build_tool = []

        subprocess.check_call(
            ['cmake', ext.cmake_lists_dir, *build_tool, *cmake_args],
            cwd=self.build_temp)

    def build_extensions(self) -> None:
        # Ensure that CMake is present and working
        try:
            subprocess.check_output(['cmake', '--version'])
        except OSError as e:
            raise RuntimeError('Cannot find CMake executable') from e

        # Create build directory if it does not exist.
        if not os.path.exists(self.build_temp):
            os.makedirs(self.build_temp)

        # Build all the extensions
        for ext in self.extensions:
            self.configure(ext)

            ext_target_name = remove_prefix(ext.name, "vllm.")
            num_jobs, _ = self.compute_num_jobs()

            build_args = [
                '--build', '.', '--target', ext_target_name, '-j',
                str(num_jobs)
            ]

            subprocess.check_call(['cmake', *build_args], cwd=self.build_temp)


def _is_cuda() -> bool:
    return torch.version.cuda is not None and not _is_neuron()


def _is_hip() -> bool:
    return torch.version.hip is not None


def _is_neuron() -> bool:
    torch_neuronx_installed = True
    try:
        subprocess.run(["neuron-ls"], capture_output=True, check=True)
    except (FileNotFoundError, PermissionError, subprocess.CalledProcessError):
        torch_neuronx_installed = False
    return torch_neuronx_installed


def _install_punica() -> bool:
    return bool(int(os.getenv("VLLM_INSTALL_PUNICA_KERNELS", "0")))


def get_hipcc_rocm_version():
    # Run the hipcc --version command
    result = subprocess.run(['hipcc', '--version'],
                            stdout=subprocess.PIPE,
                            stderr=subprocess.STDOUT,
                            text=True)

    # Check if the command was executed successfully
    if result.returncode != 0:
        print("Error running 'hipcc --version'")
        return None

    # Extract the version using a regular expression
    match = re.search(r'HIP version: (\S+)', result.stdout)
    if match:
        # Return the version string
        return match.group(1)
    else:
        print("Could not find HIP version in the output")
        return None


def get_neuronxcc_version():
    import sysconfig
    site_dir = sysconfig.get_paths()["purelib"]
    version_file = os.path.join(site_dir, "neuronxcc", "version",
                                "__init__.py")

    # Check if the command was executed successfully
    with open(version_file, "rt") as fp:
        content = fp.read()

    # Extract the version using a regular expression
    match = re.search(r"__version__ = '(\S+)'", content)
    if match:
        # Return the version string
        return match.group(1)
    else:
        raise RuntimeError("Could not find HIP version in the output")


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

    Adapted from https://github.com/NVIDIA/apex/blob/8b7a1ff183741dd8f9b87e7bafd04cfde99cea28/setup.py
    """
    nvcc_output = subprocess.check_output([CUDA_HOME + "/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_path(*filepath) -> str:
    return os.path.join(ROOT_DIR, *filepath)


def find_version(filepath: str) -> str:
    """Extract version information from the given filepath.

    Adapted from https://github.com/ray-project/ray/blob/0b190ee1160eeca9796bc091e07eaebf4c85b511/python/setup.py
    """
    with open(filepath) as fp:
        version_match = re.search(r"^__version__ = ['\"]([^'\"]*)['\"]",
                                  fp.read(), re.M)
        if version_match:
            return version_match.group(1)
        raise RuntimeError("Unable to find version string.")


def get_vllm_version() -> str:
    version = find_version(get_path("vllm", "__init__.py"))

    if _is_cuda():
        cuda_version = str(get_nvcc_cuda_version())
        if cuda_version != MAIN_CUDA_VERSION:
            cuda_version_str = cuda_version.replace(".", "")[:3]
            version += f"+cu{cuda_version_str}"
    elif _is_hip():
        # Get the HIP version
        hipcc_version = get_hipcc_rocm_version()
        if hipcc_version != MAIN_CUDA_VERSION:
            rocm_version_str = hipcc_version.replace(".", "")[:3]
            version += f"+rocm{rocm_version_str}"
    elif _is_neuron():
        # Get the Neuron version
        neuron_version = str(get_neuronxcc_version())
        if neuron_version != MAIN_CUDA_VERSION:
            neuron_version_str = neuron_version.replace(".", "")[:3]
            version += f"+neuron{neuron_version_str}"
    else:
        raise RuntimeError("Unknown runtime environment")

    return version


def read_readme() -> str:
    """Read the README file if present."""
    p = get_path("README.md")
    if os.path.isfile(p):
        return io.open(get_path("README.md"), "r", encoding="utf-8").read()
    else:
        return ""


def get_requirements() -> List[str]:
    """Get Python package dependencies from requirements.txt."""
    if _is_cuda():
        with open(get_path("requirements.txt")) as f:
            requirements = f.read().strip().split("\n")
    elif _is_hip():
        with open(get_path("requirements-rocm.txt")) as f:
            requirements = f.read().strip().split("\n")
    elif _is_neuron():
        with open(get_path("requirements-neuron.txt")) as f:
            requirements = f.read().strip().split("\n")
    else:
        raise ValueError(
            "Unsupported platform, please use CUDA, ROCM or Neuron.")

    return requirements


ext_modules = []

if _is_cuda():
    ext_modules.append(CMakeExtension(name="vllm._moe_C"))

    if _install_punica():
        ext_modules.append(CMakeExtension(name="vllm._punica_C"))

if not _is_neuron():
    ext_modules.append(CMakeExtension(name="vllm._C"))

package_data = {
    "vllm": ["py.typed", "model_executor/layers/fused_moe/configs/*.json"]
}
if os.environ.get("VLLM_USE_PRECOMPILED"):
    package_data["vllm"].append("*.so")

setup(
    name="vllm",
    version=get_vllm_version(),
    author="vLLM Team",
    license="Apache 2.0",
    description=("A high-throughput and memory-efficient inference and "
                 "serving engine for LLMs"),
    long_description=read_readme(),
    long_description_content_type="text/markdown",
    url="https://github.com/vllm-project/vllm",
    project_urls={
        "Homepage": "https://github.com/vllm-project/vllm",
        "Documentation": "https://vllm.readthedocs.io/en/latest/",
    },
    classifiers=[
        "Programming Language :: Python :: 3.8",
        "Programming Language :: Python :: 3.9",
        "Programming Language :: Python :: 3.10",
        "Programming Language :: Python :: 3.11",
        "License :: OSI Approved :: Apache Software License",
        "Topic :: Scientific/Engineering :: Artificial Intelligence",
    ],
    packages=find_packages(exclude=("benchmarks", "csrc", "docs", "examples",
                                    "tests")),
    python_requires=">=3.8",
    install_requires=get_requirements(),
    ext_modules=ext_modules,
    cmdclass={"build_ext": cmake_build_ext} if not _is_neuron() else {},
    package_data=package_data,
)