setup.py 27.9 KB
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# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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import ctypes
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import importlib.util
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import json
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import logging
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import os
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import re
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import shutil
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import subprocess
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import sys
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import sysconfig
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from pathlib import Path
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from shutil import which
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import torch
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from packaging.version import Version, parse
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from setuptools import Extension, setup
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from setuptools.command.build_ext import build_ext
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from setuptools_scm import get_version
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from torch.utils.cpp_extension import CUDA_HOME, ROCM_HOME
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def load_module_from_path(module_name, path):
    spec = importlib.util.spec_from_file_location(module_name, path)
    module = importlib.util.module_from_spec(spec)
    sys.modules[module_name] = module
    spec.loader.exec_module(module)
    return module


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ROOT_DIR = Path(__file__).parent
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logger = logging.getLogger(__name__)
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# cannot import envs directly because it depends on vllm,
#  which is not installed yet
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envs = load_module_from_path("envs", os.path.join(ROOT_DIR, "vllm", "envs.py"))
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VLLM_TARGET_DEVICE = envs.VLLM_TARGET_DEVICE
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if sys.platform.startswith("darwin") and VLLM_TARGET_DEVICE != "cpu":
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    logger.warning("VLLM_TARGET_DEVICE automatically set to `cpu` due to macOS")
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    VLLM_TARGET_DEVICE = "cpu"
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elif not (sys.platform.startswith("linux") or sys.platform.startswith("darwin")):
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    logger.warning(
        "vLLM only supports Linux platform (including WSL) and MacOS."
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        "Building on %s, "
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        "so vLLM may not be able to run correctly",
        sys.platform,
    )
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    VLLM_TARGET_DEVICE = "empty"
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elif (
    sys.platform.startswith("linux")
    and torch.version.cuda is None
    and os.getenv("VLLM_TARGET_DEVICE") is None
    and torch.version.hip is None
):
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    # if cuda or hip is not available and VLLM_TARGET_DEVICE is not set,
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    # fallback to cpu
    VLLM_TARGET_DEVICE = "cpu"
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def is_sccache_available() -> bool:
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    return which("sccache") is not None and not bool(
        int(os.getenv("VLLM_DISABLE_SCCACHE", "0"))
    )
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def is_ccache_available() -> bool:
    return which("ccache") is not None


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


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def is_freethreaded():
    return bool(sysconfig.get_config_var("Py_GIL_DISABLED"))


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class CMakeExtension(Extension):
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    def __init__(self, name: str, cmake_lists_dir: str = ".", **kwa) -> None:
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        super().__init__(name, sources=[], py_limited_api=not is_freethreaded(), **kwa)
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        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.
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    did_config: dict[str, bool] = {}
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    #
    # Determine number of compilation jobs and optionally nvcc compile threads.
    #
    def compute_num_jobs(self):
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        # `num_jobs` is either the value of the MAX_JOBS environment variable
        # (if defined) or the number of CPUs available.
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        num_jobs = envs.MAX_JOBS
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        if num_jobs is not None:
            num_jobs = int(num_jobs)
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            logger.info("Using MAX_JOBS=%d as the number of jobs.", num_jobs)
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        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()
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        nvcc_threads = None
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        if _is_cuda() and get_nvcc_cuda_version() >= Version("11.2"):
            # `nvcc_threads` is either the value of the NVCC_THREADS
            # environment variable (if defined) or 1.
            # when it is set, we reduce `num_jobs` to avoid
            # overloading the system.
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            nvcc_threads = envs.NVCC_THREADS
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            if nvcc_threads is not None:
                nvcc_threads = int(nvcc_threads)
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                logger.info(
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                    "Using NVCC_THREADS=%d as the number of nvcc threads.", nvcc_threads
                )
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            else:
                nvcc_threads = 1
            num_jobs = max(1, num_jobs // nvcc_threads)
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        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"
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        cfg = envs.CMAKE_BUILD_TYPE or default_cfg
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        cmake_args = [
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            "-DCMAKE_BUILD_TYPE={}".format(cfg),
            "-DVLLM_TARGET_DEVICE={}".format(VLLM_TARGET_DEVICE),
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        ]

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        verbose = envs.VERBOSE
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        if verbose:
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            cmake_args += ["-DCMAKE_VERBOSE_MAKEFILE=ON"]
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        if is_sccache_available():
            cmake_args += [
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                "-DCMAKE_C_COMPILER_LAUNCHER=sccache",
                "-DCMAKE_CXX_COMPILER_LAUNCHER=sccache",
                "-DCMAKE_CUDA_COMPILER_LAUNCHER=sccache",
                "-DCMAKE_HIP_COMPILER_LAUNCHER=sccache",
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            ]
        elif is_ccache_available():
            cmake_args += [
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                "-DCMAKE_C_COMPILER_LAUNCHER=ccache",
                "-DCMAKE_CXX_COMPILER_LAUNCHER=ccache",
                "-DCMAKE_CUDA_COMPILER_LAUNCHER=ccache",
                "-DCMAKE_HIP_COMPILER_LAUNCHER=ccache",
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            ]

        # Pass the python executable to cmake so it can find an exact
        # match.
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        cmake_args += ["-DVLLM_PYTHON_EXECUTABLE={}".format(sys.executable)]
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        # Pass the python path to cmake so it can reuse the build dependencies
        # on subsequent calls to python.
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        cmake_args += ["-DVLLM_PYTHON_PATH={}".format(":".join(sys.path))]
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        # Override the base directory for FetchContent downloads to $ROOT/.deps
        # This allows sharing dependencies between profiles,
        # and plays more nicely with sccache.
        # To override this, set the FETCHCONTENT_BASE_DIR environment variable.
        fc_base_dir = os.path.join(ROOT_DIR, ".deps")
        fc_base_dir = os.environ.get("FETCHCONTENT_BASE_DIR", fc_base_dir)
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        cmake_args += ["-DFETCHCONTENT_BASE_DIR={}".format(fc_base_dir)]
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        #
        # Setup parallelism and build tool
        #
        num_jobs, nvcc_threads = self.compute_num_jobs()

        if nvcc_threads:
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            cmake_args += ["-DNVCC_THREADS={}".format(nvcc_threads)]
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        if is_ninja_available():
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            build_tool = ["-G", "Ninja"]
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            cmake_args += [
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                "-DCMAKE_JOB_POOL_COMPILE:STRING=compile",
                "-DCMAKE_JOB_POOLS:STRING=compile={}".format(num_jobs),
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            ]
        else:
            # Default build tool to whatever cmake picks.
            build_tool = []
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        # Make sure we use the nvcc from CUDA_HOME
        if _is_cuda():
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            cmake_args += [f"-DCMAKE_CUDA_COMPILER={CUDA_HOME}/bin/nvcc"]
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        elif _is_hip():
            cmake_args += [f"-DROCM_PATH={ROCM_HOME}"]
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        other_cmake_args = os.environ.get("CMAKE_ARGS")
        if other_cmake_args:
            cmake_args += other_cmake_args.split()

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        subprocess.check_call(
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            ["cmake", ext.cmake_lists_dir, *build_tool, *cmake_args],
            cwd=self.build_temp,
        )
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    def build_extensions(self) -> None:
        # Ensure that CMake is present and working
        try:
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            subprocess.check_output(["cmake", "--version"])
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        except OSError as e:
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            raise RuntimeError("Cannot find CMake executable") from e
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        # Create build directory if it does not exist.
        if not os.path.exists(self.build_temp):
            os.makedirs(self.build_temp)

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        targets = []
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        def target_name(s: str) -> str:
            return s.removeprefix("vllm.").removeprefix("vllm_flash_attn.")

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        # Build all the extensions
        for ext in self.extensions:
            self.configure(ext)
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            targets.append(target_name(ext.name))
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        num_jobs, _ = self.compute_num_jobs()
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        build_args = [
            "--build",
            ".",
            f"-j={num_jobs}",
            *[f"--target={name}" for name in targets],
        ]
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        subprocess.check_call(["cmake", *build_args], cwd=self.build_temp)
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        # Install the libraries
        for ext in self.extensions:
            # Install the extension into the proper location
            outdir = Path(self.get_ext_fullpath(ext.name)).parent.absolute()

            # Skip if the install directory is the same as the build directory
            if outdir == self.build_temp:
                continue

            # CMake appends the extension prefix to the install path,
            # and outdir already contains that prefix, so we need to remove it.
            prefix = outdir
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            for _ in range(ext.name.count(".")):
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                prefix = prefix.parent

            # prefix here should actually be the same for all components
            install_args = [
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                "cmake",
                "--install",
                ".",
                "--prefix",
                prefix,
                "--component",
                target_name(ext.name),
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            ]
            subprocess.check_call(install_args, cwd=self.build_temp)

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    def run(self):
        # First, run the standard build_ext command to compile the extensions
        super().run()

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        # copy vllm/vllm_flash_attn/**/*.py from self.build_lib to current
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        # directory so that they can be included in the editable build
        import glob
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        files = glob.glob(
            os.path.join(self.build_lib, "vllm", "vllm_flash_attn", "**", "*.py"),
            recursive=True,
        )
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        for file in files:
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            dst_file = os.path.join(
                "vllm/vllm_flash_attn", file.split("vllm/vllm_flash_attn/")[-1]
            )
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            print(f"Copying {file} to {dst_file}")
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            os.makedirs(os.path.dirname(dst_file), exist_ok=True)
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            self.copy_file(file, dst_file)

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        if _is_cuda() or _is_hip():
            # copy vllm/third_party/triton_kernels/**/*.py from self.build_lib
            # to current directory so that they can be included in the editable
            # build
            print(
                f"Copying {self.build_lib}/vllm/third_party/triton_kernels "
                "to vllm/third_party/triton_kernels"
            )
            shutil.copytree(
                f"{self.build_lib}/vllm/third_party/triton_kernels",
                "vllm/third_party/triton_kernels",
                dirs_exist_ok=True,
            )

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class precompiled_build_ext(build_ext):
    """Disables extension building when using precompiled binaries."""

    def build_extensions(self) -> None:
        print("Skipping build_ext: using precompiled extensions.")
        return


class precompiled_wheel_utils:
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    """Extracts libraries and other files from an existing wheel."""

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    @staticmethod
    def extract_precompiled_and_patch_package(wheel_url_or_path: str) -> dict:
        import tempfile
        import zipfile

        temp_dir = None
        try:
            if not os.path.isfile(wheel_url_or_path):
                wheel_filename = wheel_url_or_path.split("/")[-1]
                temp_dir = tempfile.mkdtemp(prefix="vllm-wheels")
                wheel_path = os.path.join(temp_dir, wheel_filename)
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                print(f"Downloading wheel from {wheel_url_or_path} to {wheel_path}")
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                from urllib.request import urlretrieve
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                urlretrieve(wheel_url_or_path, filename=wheel_path)
            else:
                wheel_path = wheel_url_or_path
                print(f"Using existing wheel at {wheel_path}")

            package_data_patch = {}

            with zipfile.ZipFile(wheel_path) as wheel:
                files_to_copy = [
                    "vllm/_C.abi3.so",
                    "vllm/_moe_C.abi3.so",
                    "vllm/_flashmla_C.abi3.so",
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                    "vllm/_flashmla_extension_C.abi3.so",
                    "vllm/_sparse_flashmla_C.abi3.so",
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                    "vllm/vllm_flash_attn/_vllm_fa2_C.abi3.so",
                    "vllm/vllm_flash_attn/_vllm_fa3_C.abi3.so",
                    "vllm/cumem_allocator.abi3.so",
                ]

                compiled_regex = re.compile(
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                    r"vllm/vllm_flash_attn/(?:[^/.][^/]*/)*(?!\.)[^/]*\.py"
                )
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                file_members = list(
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                    filter(lambda x: x.filename in files_to_copy, wheel.filelist)
                )
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                file_members += list(
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                    filter(lambda x: compiled_regex.match(x.filename), wheel.filelist)
                )
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                for file in file_members:
                    print(f"[extract] {file.filename}")
                    target_path = os.path.join(".", file.filename)
                    os.makedirs(os.path.dirname(target_path), exist_ok=True)
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                    with (
                        wheel.open(file.filename) as src,
                        open(target_path, "wb") as dst,
                    ):
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                        shutil.copyfileobj(src, dst)

                    pkg = os.path.dirname(file.filename).replace("/", ".")
                    package_data_patch.setdefault(pkg, []).append(
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                        os.path.basename(file.filename)
                    )
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            return package_data_patch
        finally:
            if temp_dir is not None:
                print(f"Removing temporary directory {temp_dir}")
                shutil.rmtree(temp_dir)

    @staticmethod
    def get_base_commit_in_main_branch() -> str:
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        # Force to use the nightly wheel. This is mainly used for CI testing.
        if envs.VLLM_TEST_USE_PRECOMPILED_NIGHTLY_WHEEL:
            return "nightly"
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        try:
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            # Get the latest commit hash of the upstream main branch.
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            resp_json = subprocess.check_output(
                [
                    "curl",
                    "-s",
                    "https://api.github.com/repos/vllm-project/vllm/commits/main",
                ]
            ).decode("utf-8")
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            upstream_main_commit = json.loads(resp_json)["sha"]

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            # In Docker build context, .git may be immutable or missing.
            if envs.VLLM_DOCKER_BUILD_CONTEXT:
                return upstream_main_commit

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            # Check if the upstream_main_commit exists in the local repo
            try:
                subprocess.check_output(
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                    ["git", "cat-file", "-e", f"{upstream_main_commit}"]
                )
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            except subprocess.CalledProcessError:
                # If not present, fetch it from the remote repository.
                # Note that this does not update any local branches,
                # but ensures that this commit ref and its history are
                # available in our local repo.
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                subprocess.check_call(
                    ["git", "fetch", "https://github.com/vllm-project/vllm", "main"]
                )
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            # Then get the commit hash of the current branch that is the same as
            # the upstream main commit.
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            current_branch = (
                subprocess.check_output(["git", "branch", "--show-current"])
                .decode("utf-8")
                .strip()
            )
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            base_commit = (
                subprocess.check_output(
                    ["git", "merge-base", f"{upstream_main_commit}", current_branch]
                )
                .decode("utf-8")
                .strip()
            )
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            return base_commit
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        except ValueError as err:
            raise ValueError(err) from None
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        except Exception as err:
            logger.warning(
                "Failed to get the base commit in the main branch. "
                "Using the nightly wheel. The libraries in this "
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                "wheel may not be compatible with your dev branch: %s",
                err,
            )
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            return "nightly"
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def _no_device() -> bool:
    return VLLM_TARGET_DEVICE == "empty"


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def _is_cuda() -> bool:
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    has_cuda = torch.version.cuda is not None
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    return VLLM_TARGET_DEVICE == "cuda" and has_cuda and not _is_tpu()
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def _is_hip() -> bool:
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    return (
        VLLM_TARGET_DEVICE == "cuda" or VLLM_TARGET_DEVICE == "rocm"
    ) and torch.version.hip is not None
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def _is_tpu() -> bool:
    return VLLM_TARGET_DEVICE == "tpu"


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def _is_cpu() -> bool:
    return VLLM_TARGET_DEVICE == "cpu"


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def _is_xpu() -> bool:
    return VLLM_TARGET_DEVICE == "xpu"


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def _build_custom_ops() -> bool:
    return _is_cuda() or _is_hip() or _is_cpu()


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def get_rocm_version():
    # Get the Rocm version from the ROCM_HOME/bin/librocm-core.so
    # see https://github.com/ROCm/rocm-core/blob/d11f5c20d500f729c393680a01fa902ebf92094b/rocm_version.cpp#L21
    try:
        librocm_core_file = Path(ROCM_HOME) / "lib" / "librocm-core.so"
        if not librocm_core_file.is_file():
            return None
        librocm_core = ctypes.CDLL(librocm_core_file)
        VerErrors = ctypes.c_uint32
        get_rocm_core_version = librocm_core.getROCmVersion
        get_rocm_core_version.restype = VerErrors
        get_rocm_core_version.argtypes = [
            ctypes.POINTER(ctypes.c_uint32),
            ctypes.POINTER(ctypes.c_uint32),
            ctypes.POINTER(ctypes.c_uint32),
        ]
        major = ctypes.c_uint32()
        minor = ctypes.c_uint32()
        patch = ctypes.c_uint32()
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        if (
            get_rocm_core_version(
                ctypes.byref(major), ctypes.byref(minor), ctypes.byref(patch)
            )
            == 0
        ):
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            return f"{major.value}.{minor.value}.{patch.value}"
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        return None
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    except Exception:
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        return None
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def get_nvcc_cuda_version() -> Version:
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    """Get the CUDA version from nvcc.

    Adapted from https://github.com/NVIDIA/apex/blob/8b7a1ff183741dd8f9b87e7bafd04cfde99cea28/setup.py
    """
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    assert CUDA_HOME is not None, "CUDA_HOME is not set"
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    nvcc_output = subprocess.check_output(
        [CUDA_HOME + "/bin/nvcc", "-V"], universal_newlines=True
    )
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    output = nvcc_output.split()
    release_idx = output.index("release") + 1
    nvcc_cuda_version = parse(output[release_idx].split(",")[0])
    return nvcc_cuda_version


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def get_vllm_version() -> str:
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    # Allow overriding the version. This is useful to build platform-specific
    # wheels (e.g. CPU, TPU) without modifying the source.
    if env_version := os.getenv("VLLM_VERSION_OVERRIDE"):
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        print(f"Overriding VLLM version with {env_version} from VLLM_VERSION_OVERRIDE")
        os.environ["SETUPTOOLS_SCM_PRETEND_VERSION"] = env_version
        return get_version(write_to="vllm/_version.py")
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    version = get_version(write_to="vllm/_version.py")
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    sep = "+" if "+" not in version else "."  # dev versions might contain +
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    if _no_device():
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        if envs.VLLM_TARGET_DEVICE == "empty":
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            version += f"{sep}empty"
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    elif _is_cuda():
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        if envs.VLLM_USE_PRECOMPILED:
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            version += f"{sep}precompiled"
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        else:
            cuda_version = str(get_nvcc_cuda_version())
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            if cuda_version != envs.VLLM_MAIN_CUDA_VERSION:
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                cuda_version_str = cuda_version.replace(".", "")[:3]
                # skip this for source tarball, required for pypi
                if "sdist" not in sys.argv:
                    version += f"{sep}cu{cuda_version_str}"
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    elif _is_hip():
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        # Get the Rocm Version
        rocm_version = get_rocm_version() or torch.version.hip
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        if rocm_version and rocm_version != envs.VLLM_MAIN_CUDA_VERSION:
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            version += f"{sep}rocm{rocm_version.replace('.', '')[:3]}"
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    elif _is_tpu():
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        version += f"{sep}tpu"
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    elif _is_cpu():
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        if envs.VLLM_TARGET_DEVICE == "cpu":
            version += f"{sep}cpu"
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    elif _is_xpu():
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        version += f"{sep}xpu"
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    else:
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        raise RuntimeError("Unknown runtime environment")
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    return version


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def get_requirements() -> list[str]:
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    """Get Python package dependencies from requirements.txt."""
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    requirements_dir = ROOT_DIR / "requirements"
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    def _read_requirements(filename: str) -> list[str]:
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        with open(requirements_dir / filename) as f:
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            requirements = f.read().strip().split("\n")
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        resolved_requirements = []
        for line in requirements:
            if line.startswith("-r "):
                resolved_requirements += _read_requirements(line.split()[1])
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            elif (
                not line.startswith("--")
                and not line.startswith("#")
                and line.strip() != ""
            ):
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                resolved_requirements.append(line)
        return resolved_requirements

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    if _no_device():
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        requirements = _read_requirements("common.txt")
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    elif _is_cuda():
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        requirements = _read_requirements("cuda.txt")
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        cuda_major, cuda_minor = torch.version.cuda.split(".")
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        modified_requirements = []
        for req in requirements:
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            if "vllm-flash-attn" in req and cuda_major != "12":
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                # vllm-flash-attn is built only for CUDA 12.x.
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                # Skip for other versions.
                continue
            modified_requirements.append(req)
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        requirements = modified_requirements
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    elif _is_hip():
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        requirements = _read_requirements("rocm.txt")
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    elif _is_tpu():
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        requirements = _read_requirements("tpu.txt")
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    elif _is_cpu():
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        requirements = _read_requirements("cpu.txt")
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    elif _is_xpu():
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        requirements = _read_requirements("xpu.txt")
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    else:
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        raise ValueError("Unsupported platform, please use CUDA, ROCm, or CPU.")
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    return requirements


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ext_modules = []

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if _is_cuda() or _is_hip():
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    ext_modules.append(CMakeExtension(name="vllm._moe_C"))
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    ext_modules.append(CMakeExtension(name="vllm.cumem_allocator"))
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    # Optional since this doesn't get built (produce an .so file). This is just
    # copying the relevant .py files from the source repository.
    ext_modules.append(CMakeExtension(name="vllm.triton_kernels", optional=True))
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if _is_hip():
    ext_modules.append(CMakeExtension(name="vllm._rocm_C"))

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if _is_cuda():
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    ext_modules.append(CMakeExtension(name="vllm.vllm_flash_attn._vllm_fa2_C"))
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    if envs.VLLM_USE_PRECOMPILED or get_nvcc_cuda_version() >= Version("12.3"):
        # FA3 requires CUDA 12.3 or later
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        ext_modules.append(CMakeExtension(name="vllm.vllm_flash_attn._vllm_fa3_C"))
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        # Optional since this doesn't get built (produce an .so file) when
        # not targeting a hopper system
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        ext_modules.append(CMakeExtension(name="vllm._flashmla_C", optional=True))
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        ext_modules.append(
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            CMakeExtension(name="vllm._flashmla_extension_C", optional=True)
        )
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if _build_custom_ops():
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    ext_modules.append(CMakeExtension(name="vllm._C"))

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package_data = {
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    "vllm": [
        "py.typed",
        "model_executor/layers/fused_moe/configs/*.json",
        "model_executor/layers/quantization/utils/configs/*.json",
    ]
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}
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def _fetch_metadata_for_variant(
    commit: str, variant: str | None
) -> tuple[list[dict], str]:
    variant_dir = f"{variant}/" if variant is not None else ""
    repo_url = f"https://wheels.vllm.ai/{commit}/{variant_dir}vllm/"
    meta_url = repo_url + "metadata.json"
    logger.info("Trying to fetch metadata from {}", meta_url)
    from urllib.request import urlopen

    with urlopen(meta_url) as resp:
        # urlopen raises HTTPError on unexpected status code
        wheels = json.loads(resp.read().decode("utf-8"))
    return wheels, repo_url


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# If using precompiled, extract and patch package_data (in advance of setup)
if envs.VLLM_USE_PRECOMPILED:
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    # Attempts:
    # 1. user-specified wheel location (can be either local or remote, via
    #    VLLM_PRECOMPILED_WHEEL_LOCATION)
    # 2. user-specified variant from nightly repo (current main commit via
    #    VLLM_PRECOMPILED_WHEEL_VARIANT)
    # 3. the variant corresponding to VLLM_MAIN_CUDA_VERSION from nightly repo
    # 4. the default variant from nightly repo (current main commit)
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    wheel_location = os.getenv("VLLM_PRECOMPILED_WHEEL_LOCATION", None)
    if wheel_location is not None:
        wheel_url = wheel_location
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        logger.info("Using user-specified precompiled wheel location: {}", wheel_url)
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    else:
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        import platform
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        arch = platform.machine()
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        # try to fetch the wheel metadata from the nightly wheel repo
        main_variant = envs.VLLM_MAIN_CUDA_VERSION.replace(".", "")
        variant = os.getenv("VLLM_PRECOMPILED_WHEEL_VARIANT", main_variant)
        commit = os.getenv(
            "VLLM_PRECOMPILED_WHEEL_COMMIT",
            precompiled_wheel_utils.get_base_commit_in_main_branch(),
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        )
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        logger.info(
            "Using precompiled wheel commit {} with variant {}", commit, variant
        )
        try_default = False
        wheels, repo_url = None, None
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        try:
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            wheels, repo_url = _fetch_metadata_for_variant(commit, variant)
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        except Exception as e:
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            logger.warning(
                "Failed to fetch precompiled wheel metadata for variant {}",
                variant,
                exc_info=e,
            )
            try_default = True  # try outside handler to keep the stacktrace simple
        if try_default:
            logger.info("Trying the default variant")
            wheels, repo_url = _fetch_metadata_for_variant(commit, None)
            # if this also fails, then we have nothing more to try / cache
        assert wheels is not None and repo_url is not None, (
            "Failed to fetch precompiled wheel metadata"
        )
        # The metadata.json has the following format:
        # see .buildkite/scripts/generate-nightly-index.py for details
        """[{
"package_name": "vllm",
"version": "0.11.2.dev278+gdbc3d9991",
"build_tag": null,
"python_tag": "cp38",
"abi_tag": "abi3",
"platform_tag": "manylinux1_x86_64",
"variant": null,
"filename": "vllm-0.11.2.dev278+gdbc3d9991-cp38-abi3-manylinux1_x86_64.whl",
"path": "../vllm-0.11.2.dev278+gdbc3d9991-cp38-abi3-manylinux1_x86_64.whl"
},
...]"""
        for wheel in wheels:
            if wheel.get("package_name") == "vllm" and arch in wheel.get(
                "platform_tag", ""
            ):
                logger.info("Found precompiled wheel metadata: {}", wheel)
                if "path" not in wheel:
                    raise ValueError(f"Wheel metadata missing path: {wheel}")
                # TODO: maybe check more compatibility later? (python_tag, abi_tag, etc)
                wheel_url = repo_url + wheel["path"]
                logger.info("Using precompiled wheel URL: {}", wheel_url)
                break
        else:
            raise ValueError(
                f"No precompiled vllm wheel found for architecture {arch} "
                f"from repo {repo_url}. All available wheels: {wheels}"
            )
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    patch = precompiled_wheel_utils.extract_precompiled_and_patch_package(wheel_url)
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    for pkg, files in patch.items():
        package_data.setdefault(pkg, []).extend(files)

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if _no_device():
    ext_modules = []

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if not ext_modules:
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    cmdclass = {}
else:
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    cmdclass = {
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        "build_ext": precompiled_build_ext
        if envs.VLLM_USE_PRECOMPILED
        else cmake_build_ext
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    }
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setup(
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    # static metadata should rather go in pyproject.toml
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    version=get_vllm_version(),
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    ext_modules=ext_modules,
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    install_requires=get_requirements(),
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    extras_require={
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        "bench": ["pandas", "matplotlib", "seaborn", "datasets"],
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        "tensorizer": ["tensorizer==2.10.1"],
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        "fastsafetensors": ["fastsafetensors >= 0.1.10"],
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        "runai": ["runai-model-streamer[s3,gcs] >= 0.15.0"],
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        "audio": [
            "librosa",
            "soundfile",
            "mistral_common[audio]",
        ],  # Required for audio processing
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        "video": [],  # Kept for backwards compatibility
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        "flashinfer": [],  # Kept for backwards compatibility
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        # Optional deps for AMD FP4 quantization support
        "petit-kernel": ["petit-kernel"],
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    },
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    cmdclass=cmdclass,
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    package_data=package_data,
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)