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setup.py
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setup.py
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import io
import logging
import os
import re
import subprocess
import sys
from shutil import which
from typing import List
import torch
from packaging.version import Version, parse
from setuptools import Extension, find_packages, setup
from setuptools.command.build_ext import build_ext
from torch.utils.cpp_extension import CUDA_HOME
ROOT_DIR = os.path.dirname(__file__)
logger = logging.getLogger(__name__)
# Target device of vLLM, supporting [cuda (by default), rocm, neuron, cpu]
VLLM_TARGET_DEVICE = os.getenv("VLLM_TARGET_DEVICE", "cuda")
# vLLM only supports Linux platform
assert sys.platform.startswith(
"linux"), "vLLM only supports Linux platform (including WSL)."
MAIN_CUDA_VERSION = "12.1"
def is_sccache_available() -> bool:
return which("sccache") is not None
def is_ccache_available() -> bool:
return which("ccache") is not None
def is_ninja_available() -> bool:
return which("ninja") is not None
def remove_prefix(text, prefix):
if text.startswith(prefix):
return text[len(prefix):]
return text
class CMakeExtension(Extension):
def __init__(self, name: str, cmake_lists_dir: str = '.', **kwa) -> None:
super().__init__(name, sources=[], **kwa)
self.cmake_lists_dir = os.path.abspath(cmake_lists_dir)
class cmake_build_ext(build_ext):
# A dict of extension directories that have been configured.
did_config = {}
#
# Determine number of compilation jobs and optionally nvcc compile threads.
#
def compute_num_jobs(self):
# `num_jobs` is either the value of the MAX_JOBS environment variable
# (if defined) or the number of CPUs available.
num_jobs = os.environ.get("MAX_JOBS", None)
if num_jobs is not None:
num_jobs = int(num_jobs)
logger.info(f"Using MAX_JOBS={num_jobs} as the number of jobs.")
else:
try:
# os.sched_getaffinity() isn't universally available, so fall
# back to os.cpu_count() if we get an error here.
num_jobs = len(os.sched_getaffinity(0))
except AttributeError:
num_jobs = os.cpu_count()
nvcc_threads = None
if _is_cuda() 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.
nvcc_threads = os.getenv("NVCC_THREADS", None)
if nvcc_threads is not None:
nvcc_threads = int(nvcc_threads)
logger.info(f"Using NVCC_THREADS={nvcc_threads} as the number"
" of nvcc threads.")
else:
nvcc_threads = 1
num_jobs = max(1, num_jobs // nvcc_threads)
return num_jobs, nvcc_threads
#
# Perform cmake configuration for a single extension.
#
def configure(self, ext: CMakeExtension) -> None:
# If we've already configured using the CMakeLists.txt for
# this extension, exit early.
if ext.cmake_lists_dir in cmake_build_ext.did_config:
return
cmake_build_ext.did_config[ext.cmake_lists_dir] = True
# Select the build type.
# Note: optimization level + debug info are set by the build type
default_cfg = "Debug" if self.debug else "RelWithDebInfo"
cfg = os.getenv("CMAKE_BUILD_TYPE", default_cfg)
# where .so files will be written, should be the same for all extensions
# that use the same CMakeLists.txt.
outdir = os.path.abspath(
os.path.dirname(self.get_ext_fullpath(ext.name)))
cmake_args = [
'-DCMAKE_BUILD_TYPE={}'.format(cfg),
'-DCMAKE_LIBRARY_OUTPUT_DIRECTORY={}'.format(outdir),
'-DCMAKE_ARCHIVE_OUTPUT_DIRECTORY={}'.format(self.build_temp),
'-DVLLM_TARGET_DEVICE={}'.format(VLLM_TARGET_DEVICE),
]
verbose = bool(int(os.getenv('VERBOSE', '0')))
if verbose:
cmake_args += ['-DCMAKE_VERBOSE_MAKEFILE=ON']
if is_sccache_available():
cmake_args += [
'-DCMAKE_CXX_COMPILER_LAUNCHER=sccache',
'-DCMAKE_CUDA_COMPILER_LAUNCHER=sccache',
]
elif is_ccache_available():
cmake_args += [
'-DCMAKE_CXX_COMPILER_LAUNCHER=ccache',
'-DCMAKE_CUDA_COMPILER_LAUNCHER=ccache',
]
# Pass the python executable to cmake so it can find an exact
# match.
cmake_args += ['-DVLLM_PYTHON_EXECUTABLE={}'.format(sys.executable)]
if _install_punica():
cmake_args += ['-DVLLM_INSTALL_PUNICA_KERNELS=ON']
#
# Setup parallelism and build tool
#
num_jobs, nvcc_threads = self.compute_num_jobs()
if nvcc_threads:
cmake_args += ['-DNVCC_THREADS={}'.format(nvcc_threads)]
if is_ninja_available():
build_tool = ['-G', 'Ninja']
cmake_args += [
'-DCMAKE_JOB_POOL_COMPILE:STRING=compile',
'-DCMAKE_JOB_POOLS:STRING=compile={}'.format(num_jobs),
]
else:
# Default build tool to whatever cmake picks.
build_tool = []
subprocess.check_call(
['cmake', ext.cmake_lists_dir, *build_tool, *cmake_args],
cwd=self.build_temp)
def build_extensions(self) -> None:
# Ensure that CMake is present and working
try:
subprocess.check_output(['cmake', '--version'])
except OSError as e:
raise RuntimeError('Cannot find CMake executable') from e
# Create build directory if it does not exist.
if not os.path.exists(self.build_temp):
os.makedirs(self.build_temp)
# Build all the extensions
for ext in self.extensions:
self.configure(ext)
ext_target_name = remove_prefix(ext.name, "vllm.")
num_jobs, _ = self.compute_num_jobs()
build_args = [
'--build', '.', '--target', ext_target_name, '-j',
str(num_jobs)
]
subprocess.check_call(['cmake', *build_args], cwd=self.build_temp)
def _is_cuda() -> bool:
return VLLM_TARGET_DEVICE == "cuda" \
and torch.version.cuda is not None \
and not _is_neuron()
def _is_hip() -> bool:
return (VLLM_TARGET_DEVICE == "cuda"
or VLLM_TARGET_DEVICE == "rocm") and torch.version.hip is not None
def _is_neuron() -> bool:
torch_neuronx_installed = True
try:
subprocess.run(["neuron-ls"], capture_output=True, check=True)
except (FileNotFoundError, PermissionError, subprocess.CalledProcessError):
torch_neuronx_installed = False
return torch_neuronx_installed
def _is_cpu() -> bool:
return VLLM_TARGET_DEVICE == "cpu"
def _install_punica() -> bool:
return bool(int(os.getenv("VLLM_INSTALL_PUNICA_KERNELS", "0")))
def get_hipcc_rocm_version():
# Run the hipcc --version command
result = subprocess.run(['hipcc', '--version'],
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
text=True)
# Check if the command was executed successfully
if result.returncode != 0:
print("Error running 'hipcc --version'")
return None
# Extract the version using a regular expression
match = re.search(r'HIP version: (\S+)', result.stdout)
if match:
# Return the version string
return match.group(1)
else:
print("Could not find HIP version in the output")
return None
def get_neuronxcc_version():
import sysconfig
site_dir = sysconfig.get_paths()["purelib"]
version_file = os.path.join(site_dir, "neuronxcc", "version",
"__init__.py")
# Check if the command was executed successfully
with open(version_file, "rt") as fp:
content = fp.read()
# Extract the version using a regular expression
match = re.search(r"__version__ = '(\S+)'", content)
if match:
# Return the version string
return match.group(1)
else:
raise RuntimeError("Could not find HIP version in the output")
def get_nvcc_cuda_version() -> Version:
"""Get the CUDA version from nvcc.
Adapted from https://github.com/NVIDIA/apex/blob/8b7a1ff183741dd8f9b87e7bafd04cfde99cea28/setup.py
"""
nvcc_output = subprocess.check_output([CUDA_HOME + "/bin/nvcc", "-V"],
universal_newlines=True)
output = nvcc_output.split()
release_idx = output.index("release") + 1
nvcc_cuda_version = parse(output[release_idx].split(",")[0])
return nvcc_cuda_version
def get_path(*filepath) -> str:
return os.path.join(ROOT_DIR, *filepath)
def find_version(filepath: str) -> str:
"""Extract version information from the given filepath.
Adapted from https://github.com/ray-project/ray/blob/0b190ee1160eeca9796bc091e07eaebf4c85b511/python/setup.py
"""
with open(filepath) as fp:
version_match = re.search(r"^__version__ = ['\"]([^'\"]*)['\"]",
fp.read(), re.M)
if version_match:
return version_match.group(1)
raise RuntimeError("Unable to find version string.")
def get_vllm_version() -> str:
version = find_version(get_path("vllm", "__init__.py"))
if _is_cuda():
cuda_version = str(get_nvcc_cuda_version())
if cuda_version != MAIN_CUDA_VERSION:
cuda_version_str = cuda_version.replace(".", "")[:3]
version += f"+cu{cuda_version_str}"
elif _is_hip():
# Get the HIP version
hipcc_version = get_hipcc_rocm_version()
if hipcc_version != MAIN_CUDA_VERSION:
rocm_version_str = hipcc_version.replace(".", "")[:3]
version += f"+rocm{rocm_version_str}"
elif _is_neuron():
# Get the Neuron version
neuron_version = str(get_neuronxcc_version())
if neuron_version != MAIN_CUDA_VERSION:
neuron_version_str = neuron_version.replace(".", "")[:3]
version += f"+neuron{neuron_version_str}"
elif _is_cpu():
version += "+cpu"
else:
raise RuntimeError("Unknown runtime environment")
return version
def read_readme() -> str:
"""Read the README file if present."""
p = get_path("README.md")
if os.path.isfile(p):
return io.open(get_path("README.md"), "r", encoding="utf-8").read()
else:
return ""
def get_requirements() -> List[str]:
"""Get Python package dependencies from requirements.txt."""
if _is_cuda():
with open(get_path("requirements.txt")) as f:
requirements = f.read().strip().split("\n")
elif _is_hip():
with open(get_path("requirements-rocm.txt")) as f:
requirements = f.read().strip().split("\n")
elif _is_neuron():
with open(get_path("requirements-neuron.txt")) as f:
requirements = f.read().strip().split("\n")
elif _is_cpu():
with open(get_path("requirements-cpu.txt")) as f:
requirements = f.read().strip().split("\n")
else:
raise ValueError(
"Unsupported platform, please use CUDA, ROCM or Neuron.")
return requirements
ext_modules = []
if _is_cuda():
ext_modules.append(CMakeExtension(name="vllm._moe_C"))
if _install_punica():
ext_modules.append(CMakeExtension(name="vllm._punica_C"))
if not _is_neuron():
ext_modules.append(CMakeExtension(name="vllm._C"))
package_data = {
"vllm": ["py.typed", "model_executor/layers/fused_moe/configs/*.json"]
}
if os.environ.get("VLLM_USE_PRECOMPILED"):
package_data["vllm"].append("*.so")
setup(
name="vllm",
version=get_vllm_version(),
author="vLLM Team",
license="Apache 2.0",
description=("A high-throughput and memory-efficient inference and "
"serving engine for LLMs"),
long_description=read_readme(),
long_description_content_type="text/markdown",
url="https://github.com/vllm-project/vllm",
project_urls={
"Homepage": "https://github.com/vllm-project/vllm",
"Documentation": "https://vllm.readthedocs.io/en/latest/",
},
classifiers=[
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"License :: OSI Approved :: Apache Software License",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
],
packages=find_packages(exclude=("benchmarks", "csrc", "docs", "examples",
"tests")),
python_requires=">=3.8",
install_requires=get_requirements(),
ext_modules=ext_modules,
cmdclass={"build_ext": cmake_build_ext} if not _is_neuron() else {},
package_data=package_data,
)