setup.py 40.2 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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from typing import Optional, Union
import subprocess
from pathlib import Path

pwd = os.path.dirname(os.path.abspath(__file__))
add_git_version = False
if int(os.environ.get('ADD_GIT_VERSION', '0')) == 1:
    add_git_version = True


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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 os.getenv("VLLM_TARGET_DEVICE") is None:
    if torch.version.hip is not None:
        VLLM_TARGET_DEVICE = "rocm"
        logger.info("Auto-detected ROCm")
    elif torch.version.cuda is not None:
        VLLM_TARGET_DEVICE = "cuda"
        logger.info("Auto-detected CUDA")
    else:
        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 CUDA_HOME is not None:
            try:
                nvcc_version = get_nvcc_cuda_version()
                if nvcc_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.
                    nvcc_threads = envs.NVCC_THREADS
                    if nvcc_threads is not None:
                        nvcc_threads = int(nvcc_threads)
                        logger.info(
                            "Using NVCC_THREADS=%d as the number of nvcc threads.",
                            nvcc_threads,
                        )
                    else:
                        nvcc_threads = 1
                    num_jobs = max(1, num_jobs // nvcc_threads)
            except Exception as e:
                logger.warning("Failed to get NVCC version: %s", e)
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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
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        if _is_cuda() and CUDA_HOME is not None:
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            cmake_args += [f"-DCMAKE_CUDA_COMPILER={CUDA_HOME}/bin/nvcc"]
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        elif _is_hip() and ROCM_HOME is not None:
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            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():
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            # 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."""

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    def run(self) -> None:
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        return
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    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
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    def fetch_metadata_for_variant(
        commit: str, variant: str | None
    ) -> tuple[list[dict], str]:
        """
        Fetches metadata for a specific variant of the precompiled wheel.
        """
        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"
        print(f"Trying to fetch nightly build 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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    @staticmethod
    def is_rocm_system() -> bool:
        """Detect ROCm without relying on torch (for build environment)."""
        if os.getenv("ROCM_PATH"):
            return True
        if os.path.isdir("/opt/rocm"):
            return True
        if which("rocminfo") is not None:
            return True
        try:
            import torch

            return torch.version.hip is not None
        except ImportError:
            return False

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    @staticmethod
    def detect_system_cuda_variant() -> str:
        """Auto-detect CUDA variant from torch, nvidia-smi, or env default."""

        # Map CUDA major version to hosted wheel variants on wheels.vllm.ai
        supported = {12: "cu129", 13: "cu130"}

        # Respect explicitly set VLLM_MAIN_CUDA_VERSION
        if envs.is_set("VLLM_MAIN_CUDA_VERSION"):
            v = envs.VLLM_MAIN_CUDA_VERSION
            print(f"Using VLLM_MAIN_CUDA_VERSION={v}")
            return "cu" + v.replace(".", "")[:3]

        # Try torch.version.cuda
        cuda_version = None
        try:
            import torch

            cuda_version = torch.version.cuda
        except Exception:
            pass

        # Try nvidia-smi
        if not cuda_version:
            try:
                out = subprocess.run(
                    ["nvidia-smi"], capture_output=True, text=True, timeout=10
                )
                if m := re.search(r"CUDA Version:\s*(\d+\.\d+)", out.stdout):
                    cuda_version = m.group(1)
            except Exception:
                pass

        # Fall back to default
        if not cuda_version:
            cuda_version = envs.VLLM_MAIN_CUDA_VERSION

        # Map to supported variant
        major = int(cuda_version.split(".")[0])
        variant = supported.get(major, supported[max(supported)])
        print(f"Detected CUDA {cuda_version}, using variant {variant}")
        return variant

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    @staticmethod
    def find_local_rocm_wheel() -> str | None:
        """Search for a local vllm wheel in common locations."""
        import glob

        for pattern in ["/vllm-workspace/dist/vllm-*.whl", "./dist/vllm-*.whl"]:
            wheels = glob.glob(pattern)
            if wheels:
                return sorted(wheels)[-1]
        return None

    @staticmethod
    def fetch_wheel_from_pypi_index(index_url: str, package: str = "vllm") -> str:
        """Fetch the latest wheel URL from a PyPI-style simple index."""
        import platform
        from html.parser import HTMLParser
        from urllib.parse import urljoin
        from urllib.request import urlopen

        arch = platform.machine()

        class WheelLinkParser(HTMLParser):
            def __init__(self):
                super().__init__()
                self.wheels = []

            def handle_starttag(self, tag, attrs):
                if tag == "a":
                    for name, value in attrs:
                        if name == "href" and value.endswith(".whl"):
                            self.wheels.append(value)

        simple_url = f"{index_url.rstrip('/')}/{package}/"
        print(f"Fetching wheel list from {simple_url}")
        with urlopen(simple_url) as resp:
            html = resp.read().decode("utf-8")

        parser = WheelLinkParser()
        parser.feed(html)

        for wheel in reversed(parser.wheels):
            if arch in wheel:
                if wheel.startswith("http"):
                    return wheel
                return urljoin(simple_url, wheel)

        raise ValueError(f"No compatible wheel found for {arch} at {simple_url}")

    @staticmethod
    def determine_wheel_url_rocm() -> tuple[str, str | None]:
        """Determine the precompiled wheel for ROCm."""
        # Search for local wheel first
        local_wheel = precompiled_wheel_utils.find_local_rocm_wheel()
        if local_wheel is not None:
            print(f"Found local ROCm wheel: {local_wheel}")
            return local_wheel, None

        # Fall back to AMD's PyPI index
        index_url = os.getenv(
            "VLLM_ROCM_WHEEL_INDEX", "https://pypi.amd.com/vllm-rocm/simple"
        )
        print(f"Fetching ROCm precompiled wheel from {index_url}")
        wheel_url = precompiled_wheel_utils.fetch_wheel_from_pypi_index(index_url)
        download_filename = wheel_url.split("/")[-1].split("#")[0]
        print(f"Using ROCm precompiled wheel: {wheel_url}")
        return wheel_url, download_filename

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    @staticmethod
    def determine_wheel_url() -> tuple[str, str | None]:
        """
        Try to determine the precompiled wheel URL or path to use.
        The order of preference is:
        1. user-specified wheel location (can be either local or remote, via
           VLLM_PRECOMPILED_WHEEL_LOCATION)
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        2. user-specified variant (VLLM_PRECOMPILED_WHEEL_VARIANT) from nightly repo
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           or auto-detected CUDA variant based on system (torch, nvidia-smi)
        3. the default variant from nightly repo
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        If downloading from the nightly repo, the commit can be specified via
        VLLM_PRECOMPILED_WHEEL_COMMIT; otherwise, the head commit in the main branch
        is used.
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        """
        wheel_location = os.getenv("VLLM_PRECOMPILED_WHEEL_LOCATION", None)
        if wheel_location is not None:
            print(f"Using user-specified precompiled wheel location: {wheel_location}")
            return wheel_location, None
        else:
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            # ROCm: use local wheel or AMD's PyPI index
            # TODO: When we have ROCm nightly wheels, we can update this logic.
            if precompiled_wheel_utils.is_rocm_system():
                return precompiled_wheel_utils.determine_wheel_url_rocm()

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            import platform

            arch = platform.machine()
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            # try to fetch the wheel metadata from the nightly wheel repo,
            # detecting CUDA variant from system if not specified
            variant = os.getenv("VLLM_PRECOMPILED_WHEEL_VARIANT", None)
            if variant is None:
                variant = precompiled_wheel_utils.detect_system_cuda_variant()
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            commit = os.getenv("VLLM_PRECOMPILED_WHEEL_COMMIT", "").lower()
            if not commit or len(commit) != 40:
                print(
                    f"VLLM_PRECOMPILED_WHEEL_COMMIT not valid: {commit}"
                    ", trying to fetch base commit in main branch"
                )
                commit = precompiled_wheel_utils.get_base_commit_in_main_branch()
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            print(f"Using precompiled wheel commit {commit} with variant {variant}")
            try_default = False
            wheels, repo_url, download_filename = None, None, None
            try:
                wheels, repo_url = precompiled_wheel_utils.fetch_metadata_for_variant(
                    commit, variant
                )
            except Exception as e:
                logger.warning(
                    "Failed to fetch precompiled wheel metadata for variant %s: %s",
                    variant,
                    e,
                )
                try_default = True  # try outside handler to keep the stacktrace simple
            if try_default:
                print("Trying the default variant from remote")
                wheels, repo_url = precompiled_wheel_utils.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%2Bgdbc3d9991-cp38-abi3-manylinux1_x86_64.whl"
    },
    ...]"""
            from urllib.parse import urljoin

            for wheel in wheels:
                # TODO: maybe check more compatibility later? (python_tag, abi_tag, etc)
                if wheel.get("package_name") == "vllm" and arch in wheel.get(
                    "platform_tag", ""
                ):
                    print(f"Found precompiled wheel metadata: {wheel}")
                    if "path" not in wheel:
                        raise ValueError(f"Wheel metadata missing path: {wheel}")
                    wheel_url = urljoin(repo_url, wheel["path"])
                    download_filename = wheel.get("filename")
                    print(f"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}"
                )

        return wheel_url, download_filename

    @staticmethod
    def extract_precompiled_and_patch_package(
        wheel_url_or_path: str, download_filename: str | None
    ) -> dict:
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        import tempfile
        import zipfile

        temp_dir = None
        try:
            if not os.path.isfile(wheel_url_or_path):
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                # use provided filename first, then derive from URL
                wheel_filename = download_filename or wheel_url_or_path.split("/")[-1]
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                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",
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                    # ROCm-specific libraries
                    "vllm/_rocm_C.abi3.so",
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                ]

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                flash_attn_regex = re.compile(
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                    r"vllm/vllm_flash_attn/(?:[^/.][^/]*/)*(?!\.)[^/]*\.py"
                )
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                triton_kernels_regex = re.compile(
                    r"vllm/third_party/triton_kernels/(?:[^/.][^/]*/)*(?!\.)[^/]*\.py"
                )
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                flashmla_regex = re.compile(
                    r"vllm/third_party/flashmla/(?:[^/.][^/]*/)*(?!\.)[^/]*\.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: flash_attn_regex.match(x.filename), wheel.filelist)
                )
                file_members += list(
                    filter(
                        lambda x: triton_kernels_regex.match(x.filename), wheel.filelist
                    )
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                )
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                file_members += list(
                    filter(lambda x: flashmla_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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        try:
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            # Get the latest commit hash of the upstream main branch.
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            curl_cmd = [
                "curl",
                "-s",
                "https://api.github.com/repos/vllm-project/vllm/commits/main",
            ]
            github_token = os.getenv("GH_TOKEN", os.getenv("GITHUB_TOKEN"))
            if github_token:
                curl_cmd += [
                    "-H",
                    f"Authorization: token {github_token}",
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                ]
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            resp_json = subprocess.check_output(curl_cmd).decode("utf-8")
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            upstream_main_commit = json.loads(resp_json)["sha"]
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            print(f"Upstream main branch latest commit: {upstream_main_commit}")
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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:
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    return _is_cuda() or _is_hip()
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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:
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        if ROCM_HOME is None:
            return None
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        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_sha(root: Union[str, Path]) -> str:
    try:
        return subprocess.check_output(['git', 'rev-parse', 'HEAD'], cwd=root).decode('ascii').strip()
    except Exception:
        return 'Unknown'


def get_version_add(sha: Optional[str] = None) -> str:
    command = "git config --global --add safe.directory "+pwd  
    subprocess.run(command, shell=True, capture_output=False, text=True) 
    vllm_root = os.path.dirname(os.path.abspath(__file__))
    add_version_path = os.path.join(os.path.join(vllm_root, "vllm"), "version.py")
    major, minor, _ = torch.__version__.split('.')
    if add_git_version:
        if sha != 'Unknown':
            if sha is None:
                sha = get_sha(vllm_root)
            version = 'das.' + sha[:7]
    else:
        version = 'das'


    # dtk version
    if os.getenv("ROCM_PATH"):
        rocm_path = os.getenv('ROCM_PATH', "")
        rocm_version_path = os.path.join(rocm_path, '.info', "rocm_version")
        with open(rocm_version_path, 'r',encoding='utf-8') as file:
            lines = file.readlines()
        rocm_version=lines[0].replace(".", "")
        version += ".dtk" + rocm_version
    
    new_version_content = f"""
try:
    __version__ = "0.18.1"
    __version_tuple__ = (0, 18, 1)
    __hcu_version__ = f'0.18.1+{version}' 
    
    from vllm.version import __version__, __version_tuple__, __hcu_version__
except Exception as e:
    import warnings

    warnings.warn(f"Failed to read commit hash:\\n + str(e)",
                  RuntimeWarning,
                  stacklevel=2)
    __version__ = "dev"
    __version_tuple__ = (0, 0, __version__)
    
    
def _prev_minor_version_was(version_str):
    '''Check whether a given version matches the previous minor version.

    Return True if version_str matches the previous minor version.

    For example - return True if the current version if 0.7.4 and the
    supplied version_str is '0.6'.

    Used for --show-hidden-metrics-for-version.
    '''
    # Match anything if this is a dev tree
    if __version_tuple__[0:2] == (0, 0):
        return True

    # Note - this won't do the right thing when we release 1.0!
    # assert __version_tuple__[0] == 0
    assert isinstance(__version_tuple__[1], int)
    return version_str == f"{{__version_tuple__[0]}}.{{__version_tuple__[1] - 1}}"


def _prev_minor_version():
    '''For the purpose of testing, return a previous minor version number.'''
    # In dev tree, this will return "0.-1", but that will work fine"
    assert isinstance(__version_tuple__[1], int)
    return f"{{__version_tuple__[0]}}.{{__version_tuple__[1] - 1}}"
"""
    
    with open(add_version_path, encoding="utf-8",mode="w") as file:
        file.write(new_version_content)
    file.close()
    
    
def get_version():
    get_version_add()
    version_file = 'vllm/version.py'
    with open(version_file, encoding='utf-8') as f:
        exec(compile(f.read(), version_file, 'exec'))
    return locals()['__hcu_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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    if not _is_hip():
        version = get_version(write_to="vllm/_version.py")
        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 and not envs.VLLM_SKIP_PRECOMPILED_VERSION_SUFFIX:
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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
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        # rocm_version = get_rocm_version() or torch.version.hip
        # if rocm_version and rocm_version != envs.VLLM_MAIN_CUDA_VERSION:
        #     version += f"{sep}rocm{rocm_version.replace('.', '')[:3]}"
        version = get_version()
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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.
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    # 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 (
        CUDA_HOME and get_nvcc_cuda_version() >= Version("12.3")
    ):
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        # 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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    # FA4 CuteDSL - Python-only component for FA4's cute DSL support
    # Optional since this doesn't produce a .so file, just copies Python files
    ext_modules.append(
        CMakeExtension(name="vllm.vllm_flash_attn._vllm_fa4_cutedsl_C", optional=True)
    )
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    if envs.VLLM_USE_PRECOMPILED or (
        CUDA_HOME and get_nvcc_cuda_version() >= Version("12.9")
    ):
        # FlashMLA requires CUDA 12.9 or later
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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 _is_cpu():
    import platform

    if platform.machine() in ("x86_64", "AMD64"):
        ext_modules.append(CMakeExtension(name="vllm._C"))
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        ext_modules.append(CMakeExtension(name="vllm._C_AVX512"))
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        ext_modules.append(CMakeExtension(name="vllm._C_AVX2"))
    else:
        ext_modules.append(CMakeExtension(name="vllm._C"))

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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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        "entrypoints/serve/instrumentator/static/*.js",
        "entrypoints/serve/instrumentator/static/*.css",
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    ]
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}
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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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    wheel_url, download_filename = precompiled_wheel_utils.determine_wheel_url()
    patch = precompiled_wheel_utils.extract_precompiled_and_patch_package(
        wheel_url, download_filename
    )
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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 = {}
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else:
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    cmdclass = {
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        "build_ext": precompiled_build_ext
        if envs.VLLM_USE_PRECOMPILED
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        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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        # AMD Zen CPU optimizations via zentorch
        "zen": ["zentorch"],
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        "bench": ["pandas", "matplotlib", "seaborn", "datasets", "scipy", "plotly"],
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        "tensorizer": ["tensorizer==2.10.1"],
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        "fastsafetensors": ["fastsafetensors >= 0.2.2"],
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        "instanttensor": ["instanttensor >= 0.1.5"],
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        "runai": ["runai-model-streamer[s3,gcs,azure] >= 0.15.7"],
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        "audio": [
            "librosa",
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            "scipy",
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            "soundfile",
            "mistral_common[audio]",
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            "av",
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        ],  # 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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        # Optional deps for Helion kernel development
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        "helion": ["helion==0.3.2"],
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        # Optional deps for gRPC server (vllm serve --grpc)
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        "grpc": ["smg-grpc-servicer[vllm] >= 0.5.0"],
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        # Optional deps for OpenTelemetry tracing
        "otel": [
            "opentelemetry-sdk>=1.26.0",
            "opentelemetry-api>=1.26.0",
            "opentelemetry-exporter-otlp>=1.26.0",
            "opentelemetry-semantic-conventions-ai>=0.4.1",
        ],
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    },
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    cmdclass=cmdclass,
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    package_data=package_data,
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)