setup.py 14.9 KB
Newer Older
1
import importlib.util
2
import io
3
import logging
4
5
import os
import re
6
import subprocess
bnellnm's avatar
bnellnm committed
7
import sys
8
from shutil import which
9
from typing import Dict, List
10

Woosuk Kwon's avatar
Woosuk Kwon committed
11
import torch
12
13
14
from packaging.version import Version, parse
from setuptools import Extension, find_packages, setup
from setuptools.command.build_ext import build_ext
bnellnm's avatar
bnellnm committed
15
from torch.utils.cpp_extension import CUDA_HOME
16

17
18
19
20
21
22
23
24
25

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


26
ROOT_DIR = os.path.dirname(__file__)
27
logger = logging.getLogger(__name__)
28
29
30
31
32
33

# cannot import envs directly because it depends on vllm,
#  which is not installed yet
envs = load_module_from_path('envs', os.path.join(ROOT_DIR, 'vllm', 'envs.py'))

VLLM_TARGET_DEVICE = envs.VLLM_TARGET_DEVICE
34

35
36
37
38
# vLLM only supports Linux platform
assert sys.platform.startswith(
    "linux"), "vLLM only supports Linux platform (including WSL)."

39
40
MAIN_CUDA_VERSION = "12.1"

bnellnm's avatar
bnellnm committed
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62

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:
63
        super().__init__(name, sources=[], py_limited_api=True, **kwa)
bnellnm's avatar
bnellnm committed
64
65
66
67
68
        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.
69
    did_config: Dict[str, bool] = {}
bnellnm's avatar
bnellnm committed
70
71
72
73
74

    #
    # Determine number of compilation jobs and optionally nvcc compile threads.
    #
    def compute_num_jobs(self):
75
76
        # `num_jobs` is either the value of the MAX_JOBS environment variable
        # (if defined) or the number of CPUs available.
77
        num_jobs = envs.MAX_JOBS
78
79
        if num_jobs is not None:
            num_jobs = int(num_jobs)
80
            logger.info("Using MAX_JOBS=%d as the number of jobs.", num_jobs)
81
82
83
84
85
86
87
        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()
bnellnm's avatar
bnellnm committed
88

89
        nvcc_threads = None
90
91
92
93
94
        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.
95
            nvcc_threads = envs.NVCC_THREADS
96
97
            if nvcc_threads is not None:
                nvcc_threads = int(nvcc_threads)
98
99
100
                logger.info(
                    "Using NVCC_THREADS=%d as the number of nvcc threads.",
                    nvcc_threads)
101
102
103
            else:
                nvcc_threads = 1
            num_jobs = max(1, num_jobs // nvcc_threads)
bnellnm's avatar
bnellnm committed
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120

        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"
121
        cfg = envs.CMAKE_BUILD_TYPE or default_cfg
bnellnm's avatar
bnellnm committed
122
123
124
125
126
127
128
129
130
131

        # 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),
132
            '-DVLLM_TARGET_DEVICE={}'.format(VLLM_TARGET_DEVICE),
bnellnm's avatar
bnellnm committed
133
134
        ]

135
        verbose = envs.VERBOSE
bnellnm's avatar
bnellnm committed
136
137
138
139
140
141
142
        if verbose:
            cmake_args += ['-DCMAKE_VERBOSE_MAKEFILE=ON']

        if is_sccache_available():
            cmake_args += [
                '-DCMAKE_CXX_COMPILER_LAUNCHER=sccache',
                '-DCMAKE_CUDA_COMPILER_LAUNCHER=sccache',
143
                '-DCMAKE_C_COMPILER_LAUNCHER=sccache',
bnellnm's avatar
bnellnm committed
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
            ]
        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)

190
        targets = []
bnellnm's avatar
bnellnm committed
191
192
193
        # Build all the extensions
        for ext in self.extensions:
            self.configure(ext)
194
            targets.append(remove_prefix(ext.name, "vllm."))
bnellnm's avatar
bnellnm committed
195

196
        num_jobs, _ = self.compute_num_jobs()
bnellnm's avatar
bnellnm committed
197

198
199
200
201
202
203
        build_args = [
            "--build",
            ".",
            f"-j={num_jobs}",
            *[f"--target={name}" for name in targets],
        ]
bnellnm's avatar
bnellnm committed
204

205
        subprocess.check_call(["cmake", *build_args], cwd=self.build_temp)
206
207


208
def _is_cuda() -> bool:
209
210
211
    has_cuda = torch.version.cuda is not None
    return (VLLM_TARGET_DEVICE == "cuda" and has_cuda
            and not (_is_neuron() or _is_tpu()))
212
213


214
def _is_hip() -> bool:
215
216
    return (VLLM_TARGET_DEVICE == "cuda"
            or VLLM_TARGET_DEVICE == "rocm") and torch.version.hip is not None
217
218


219
220
221
222
def _is_neuron() -> bool:
    torch_neuronx_installed = True
    try:
        subprocess.run(["neuron-ls"], capture_output=True, check=True)
223
    except (FileNotFoundError, PermissionError, subprocess.CalledProcessError):
224
        torch_neuronx_installed = False
225
    return torch_neuronx_installed or VLLM_TARGET_DEVICE == "neuron"
226
227


228
229
230
231
def _is_tpu() -> bool:
    return VLLM_TARGET_DEVICE == "tpu"


232
233
234
235
def _is_cpu() -> bool:
    return VLLM_TARGET_DEVICE == "cpu"


236
237
238
239
def _is_openvino() -> bool:
    return VLLM_TARGET_DEVICE == "openvino"


240
241
242
243
def _is_xpu() -> bool:
    return VLLM_TARGET_DEVICE == "xpu"


244
245
246
247
def _build_custom_ops() -> bool:
    return _is_cuda() or _is_hip() or _is_cpu()


bnellnm's avatar
bnellnm committed
248
def _install_punica() -> bool:
249
    return envs.VLLM_INSTALL_PUNICA_KERNELS
250

251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271

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
Woosuk Kwon's avatar
Woosuk Kwon committed
272

273

274
275
276
def get_neuronxcc_version():
    import sysconfig
    site_dir = sysconfig.get_paths()["purelib"]
277
278
    version_file = os.path.join(site_dir, "neuronxcc", "version",
                                "__init__.py")
279
280
281
282
283
284
285
286
287
288
289
290
291
292

    # 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")


bnellnm's avatar
bnellnm committed
293
def get_nvcc_cuda_version() -> Version:
294
295
296
297
    """Get the CUDA version from nvcc.

    Adapted from https://github.com/NVIDIA/apex/blob/8b7a1ff183741dd8f9b87e7bafd04cfde99cea28/setup.py
    """
298
    assert CUDA_HOME is not None, "CUDA_HOME is not set"
bnellnm's avatar
bnellnm committed
299
    nvcc_output = subprocess.check_output([CUDA_HOME + "/bin/nvcc", "-V"],
300
301
302
303
304
305
306
                                          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


307
308
309
310
def get_path(*filepath) -> str:
    return os.path.join(ROOT_DIR, *filepath)


311
def find_version(filepath: str) -> str:
312
313
314
315
316
    """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:
Woosuk Kwon's avatar
Woosuk Kwon committed
317
318
        version_match = re.search(r"^__version__ = ['\"]([^'\"]*)['\"]",
                                  fp.read(), re.M)
319
320
321
322
323
        if version_match:
            return version_match.group(1)
        raise RuntimeError("Unable to find version string.")


324
def get_vllm_version() -> str:
325
    version = find_version(get_path("vllm", "version.py"))
326

327
    if _is_cuda():
bnellnm's avatar
bnellnm committed
328
        cuda_version = str(get_nvcc_cuda_version())
329
330
331
332
        if cuda_version != MAIN_CUDA_VERSION:
            cuda_version_str = cuda_version.replace(".", "")[:3]
            version += f"+cu{cuda_version_str}"
    elif _is_hip():
333
334
335
336
337
        # 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}"
338
339
    elif _is_neuron():
        # Get the Neuron version
bnellnm's avatar
bnellnm committed
340
        neuron_version = str(get_neuronxcc_version())
341
342
343
        if neuron_version != MAIN_CUDA_VERSION:
            neuron_version_str = neuron_version.replace(".", "")[:3]
            version += f"+neuron{neuron_version_str}"
344
345
    elif _is_openvino():
        version += "+openvino"
346
347
    elif _is_tpu():
        version += "+tpu"
348
349
    elif _is_cpu():
        version += "+cpu"
350
351
    elif _is_xpu():
        version += "+xpu"
352
    else:
353
        raise RuntimeError("Unknown runtime environment")
354

355
356
357
    return version


358
def read_readme() -> str:
Stephen Krider's avatar
Stephen Krider committed
359
360
361
362
363
364
    """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 ""
365
366


367
368
def get_requirements() -> List[str]:
    """Get Python package dependencies from requirements.txt."""
369
370
371

    def _read_requirements(filename: str) -> List[str]:
        with open(get_path(filename)) as f:
372
            requirements = f.read().strip().split("\n")
373
374
375
376
377
378
379
380
381
382
        resolved_requirements = []
        for line in requirements:
            if line.startswith("-r "):
                resolved_requirements += _read_requirements(line.split()[1])
            else:
                resolved_requirements.append(line)
        return resolved_requirements

    if _is_cuda():
        requirements = _read_requirements("requirements-cuda.txt")
383
        cuda_major, cuda_minor = torch.version.cuda.split(".")
384
385
        modified_requirements = []
        for req in requirements:
386
387
            if ("vllm-flash-attn" in req
                    and not (cuda_major == "12" and cuda_minor == "1")):
388
389
390
391
                # vllm-flash-attn is built only for CUDA 12.1.
                # Skip for other versions.
                continue
            modified_requirements.append(req)
392
        requirements = modified_requirements
393
    elif _is_hip():
394
        requirements = _read_requirements("requirements-rocm.txt")
395
    elif _is_neuron():
396
        requirements = _read_requirements("requirements-neuron.txt")
397
398
    elif _is_openvino():
        requirements = _read_requirements("requirements-openvino.txt")
399
400
    elif _is_tpu():
        requirements = _read_requirements("requirements-tpu.txt")
401
    elif _is_cpu():
402
        requirements = _read_requirements("requirements-cpu.txt")
403
404
    elif _is_xpu():
        requirements = _read_requirements("requirements-xpu.txt")
405
406
    else:
        raise ValueError(
407
408
            "Unsupported platform, please use CUDA, ROCm, Neuron, "
            "OpenVINO, or CPU.")
409
410
411
    return requirements


bnellnm's avatar
bnellnm committed
412
413
ext_modules = []

414
if _is_cuda() or _is_hip():
bnellnm's avatar
bnellnm committed
415
416
    ext_modules.append(CMakeExtension(name="vllm._moe_C"))

417
if _build_custom_ops():
bnellnm's avatar
bnellnm committed
418
419
    ext_modules.append(CMakeExtension(name="vllm._C"))

420
421
422
    if _install_punica():
        ext_modules.append(CMakeExtension(name="vllm._punica_C"))

423
424
425
package_data = {
    "vllm": ["py.typed", "model_executor/layers/fused_moe/configs/*.json"]
}
426
if envs.VLLM_USE_PRECOMPILED:
427
    ext_modules = []
Simon Mo's avatar
Simon Mo committed
428
429
    package_data["vllm"].append("*.so")

bnellnm's avatar
bnellnm committed
430
setup(
Woosuk Kwon's avatar
Woosuk Kwon committed
431
    name="vllm",
432
    version=get_vllm_version(),
Woosuk Kwon's avatar
Woosuk Kwon committed
433
    author="vLLM Team",
434
    license="Apache 2.0",
Woosuk Kwon's avatar
Woosuk Kwon committed
435
436
    description=("A high-throughput and memory-efficient inference and "
                 "serving engine for LLMs"),
437
438
    long_description=read_readme(),
    long_description_content_type="text/markdown",
439
    url="https://github.com/vllm-project/vllm",
440
    project_urls={
441
442
        "Homepage": "https://github.com/vllm-project/vllm",
        "Documentation": "https://vllm.readthedocs.io/en/latest/",
443
444
445
446
447
    },
    classifiers=[
        "Programming Language :: Python :: 3.8",
        "Programming Language :: Python :: 3.9",
        "Programming Language :: Python :: 3.10",
Woosuk Kwon's avatar
Woosuk Kwon committed
448
        "Programming Language :: Python :: 3.11",
449
450
451
        "License :: OSI Approved :: Apache Software License",
        "Topic :: Scientific/Engineering :: Artificial Intelligence",
    ],
bnellnm's avatar
bnellnm committed
452
    packages=find_packages(exclude=("benchmarks", "csrc", "docs", "examples",
453
                                    "tests*")),
454
455
    python_requires=">=3.8",
    install_requires=get_requirements(),
Woosuk Kwon's avatar
Woosuk Kwon committed
456
    ext_modules=ext_modules,
457
    extras_require={
458
        "tensorizer": ["tensorizer>=2.9.0"],
459
    },
460
    cmdclass={"build_ext": cmake_build_ext} if _build_custom_ops() else {},
Simon Mo's avatar
Simon Mo committed
461
    package_data=package_data,
Woosuk Kwon's avatar
Woosuk Kwon committed
462
)