setup.py 24.7 KB
Newer Older
1
2
# SPDX-License-Identifier: Apache-2.0

3
import ctypes
4
import importlib.util
5
import json
6
import logging
7
8
import os
import re
9
import subprocess
bnellnm's avatar
bnellnm committed
10
import sys
11
from pathlib import Path
12
from shutil import which
13

Woosuk Kwon's avatar
Woosuk Kwon committed
14
import torch
15
from packaging.version import Version, parse
16
from setuptools import Extension, setup
17
from setuptools.command.build_ext import build_ext
18
from setuptools_scm import get_version
19
from torch.utils.cpp_extension import CUDA_HOME, ROCM_HOME
20

21
22
23
24
25
26
27
28
29

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


30
ROOT_DIR = Path(__file__).parent
31
logger = logging.getLogger(__name__)
32
33
34
35
36
37

# 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
38

39
if sys.platform.startswith("darwin") and VLLM_TARGET_DEVICE != "cpu":
40
    logger.warning(
41
42
43
44
45
46
        "VLLM_TARGET_DEVICE automatically set to `cpu` due to macOS")
    VLLM_TARGET_DEVICE = "cpu"
elif not (sys.platform.startswith("linux")
          or sys.platform.startswith("darwin")):
    logger.warning(
        "vLLM only supports Linux platform (including WSL) and MacOS."
47
48
49
        "Building on %s, "
        "so vLLM may not be able to run correctly", sys.platform)
    VLLM_TARGET_DEVICE = "empty"
50
elif (sys.platform.startswith("linux") and torch.version.cuda is None
51
52
53
      and os.getenv("VLLM_TARGET_DEVICE") is None
      and torch.version.hip is None):
    # if cuda or hip is not available and VLLM_TARGET_DEVICE is not set,
54
55
    # fallback to cpu
    VLLM_TARGET_DEVICE = "cpu"
56

57
MAIN_CUDA_VERSION = "12.4"
58

bnellnm's avatar
bnellnm committed
59
60
61
62
63
64
65
66
67
68
69
70
71

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


72
73
74
75
76
77
78
79
80
81
82
83
def is_url_available(url: str) -> bool:
    from urllib.request import urlopen

    status = None
    try:
        with urlopen(url) as f:
            status = f.status
    except Exception:
        return False
    return status == 200


bnellnm's avatar
bnellnm committed
84
85
86
class CMakeExtension(Extension):

    def __init__(self, name: str, cmake_lists_dir: str = '.', **kwa) -> None:
87
        super().__init__(name, sources=[], py_limited_api=True, **kwa)
bnellnm's avatar
bnellnm committed
88
89
90
91
92
        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.
93
    did_config: dict[str, bool] = {}
bnellnm's avatar
bnellnm committed
94
95
96
97
98

    #
    # Determine number of compilation jobs and optionally nvcc compile threads.
    #
    def compute_num_jobs(self):
99
100
        # `num_jobs` is either the value of the MAX_JOBS environment variable
        # (if defined) or the number of CPUs available.
101
        num_jobs = envs.MAX_JOBS
102
103
        if num_jobs is not None:
            num_jobs = int(num_jobs)
104
            logger.info("Using MAX_JOBS=%d as the number of jobs.", num_jobs)
105
106
107
108
109
110
111
        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
112

113
        nvcc_threads = None
114
115
116
117
118
        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.
119
            nvcc_threads = envs.NVCC_THREADS
120
121
            if nvcc_threads is not None:
                nvcc_threads = int(nvcc_threads)
122
123
124
                logger.info(
                    "Using NVCC_THREADS=%d as the number of nvcc threads.",
                    nvcc_threads)
125
126
127
            else:
                nvcc_threads = 1
            num_jobs = max(1, num_jobs // nvcc_threads)
bnellnm's avatar
bnellnm committed
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144

        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"
145
        cfg = envs.CMAKE_BUILD_TYPE or default_cfg
bnellnm's avatar
bnellnm committed
146
147
148

        cmake_args = [
            '-DCMAKE_BUILD_TYPE={}'.format(cfg),
149
            '-DVLLM_TARGET_DEVICE={}'.format(VLLM_TARGET_DEVICE),
bnellnm's avatar
bnellnm committed
150
151
        ]

152
        verbose = envs.VERBOSE
bnellnm's avatar
bnellnm committed
153
154
155
156
157
        if verbose:
            cmake_args += ['-DCMAKE_VERBOSE_MAKEFILE=ON']

        if is_sccache_available():
            cmake_args += [
158
                '-DCMAKE_C_COMPILER_LAUNCHER=sccache',
bnellnm's avatar
bnellnm committed
159
160
                '-DCMAKE_CXX_COMPILER_LAUNCHER=sccache',
                '-DCMAKE_CUDA_COMPILER_LAUNCHER=sccache',
161
                '-DCMAKE_HIP_COMPILER_LAUNCHER=sccache',
bnellnm's avatar
bnellnm committed
162
163
164
            ]
        elif is_ccache_available():
            cmake_args += [
165
                '-DCMAKE_C_COMPILER_LAUNCHER=ccache',
bnellnm's avatar
bnellnm committed
166
167
                '-DCMAKE_CXX_COMPILER_LAUNCHER=ccache',
                '-DCMAKE_CUDA_COMPILER_LAUNCHER=ccache',
168
                '-DCMAKE_HIP_COMPILER_LAUNCHER=ccache',
bnellnm's avatar
bnellnm committed
169
170
171
172
173
174
            ]

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

175
176
177
178
        # Pass the python path to cmake so it can reuse the build dependencies
        # on subsequent calls to python.
        cmake_args += ['-DVLLM_PYTHON_PATH={}'.format(":".join(sys.path))]

179
180
181
182
183
184
185
186
        # 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)
        cmake_args += ['-DFETCHCONTENT_BASE_DIR={}'.format(fc_base_dir)]

bnellnm's avatar
bnellnm committed
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
        #
        # 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)

219
        targets = []
220
221
222
223

        def target_name(s: str) -> str:
            return s.removeprefix("vllm.").removeprefix("vllm_flash_attn.")

bnellnm's avatar
bnellnm committed
224
225
226
        # Build all the extensions
        for ext in self.extensions:
            self.configure(ext)
227
            targets.append(target_name(ext.name))
bnellnm's avatar
bnellnm committed
228

229
        num_jobs, _ = self.compute_num_jobs()
bnellnm's avatar
bnellnm committed
230

231
232
233
234
235
236
        build_args = [
            "--build",
            ".",
            f"-j={num_jobs}",
            *[f"--target={name}" for name in targets],
        ]
bnellnm's avatar
bnellnm committed
237

238
        subprocess.check_call(["cmake", *build_args], cwd=self.build_temp)
239

240
241
242
243
244
245
246
247
248
249
250
        # 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.
251
252
253
            # We assume only the final component of extension prefix is added by
            # CMake, this is currently true for current extensions but may not
            # always be the case.
254
            prefix = outdir
255
            if '.' in ext.name:
256
257
258
259
260
261
262
263
264
                prefix = prefix.parent

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

265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
    def run(self):
        # First, run the standard build_ext command to compile the extensions
        super().run()

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

280

281
282
283
class repackage_wheel(build_ext):
    """Extracts libraries and other files from an existing wheel."""

284
    def get_base_commit_in_main_branch(self) -> str:
285
286
287
        # Force to use the nightly wheel. This is mainly used for CI testing.
        if envs.VLLM_TEST_USE_PRECOMPILED_NIGHTLY_WHEEL:
            return "nightly"
288
289

        try:
290
291
292
293
294
295
296
            # Get the latest commit hash of the upstream main branch.
            resp_json = subprocess.check_output([
                "curl", "-s",
                "https://api.github.com/repos/vllm-project/vllm/commits/main"
            ]).decode("utf-8")
            upstream_main_commit = json.loads(resp_json)["sha"]

297
298
299
300
301
302
303
304
305
306
307
308
309
            # Check if the upstream_main_commit exists in the local repo
            try:
                subprocess.check_output(
                    ["git", "cat-file", "-e", f"{upstream_main_commit}"])
            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.
                subprocess.check_call([
                    "git", "fetch", "https://github.com/vllm-project/vllm",
                    "main"
                ])
310
311
312

            # Then get the commit hash of the current branch that is the same as
            # the upstream main commit.
313
314
315
            current_branch = subprocess.check_output(
                ["git", "branch", "--show-current"]).decode("utf-8").strip()

316
317
318
            base_commit = subprocess.check_output([
                "git", "merge-base", f"{upstream_main_commit}", current_branch
            ]).decode("utf-8").strip()
319
            return base_commit
320
321
        except ValueError as err:
            raise ValueError(err) from None
322
323
324
325
326
327
        except Exception as err:
            logger.warning(
                "Failed to get the base commit in the main branch. "
                "Using the nightly wheel. The libraries in this "
                "wheel may not be compatible with your dev branch: %s", err)
            return "nightly"
328

329
    def run(self) -> None:
330
331
332
        assert _is_cuda(
        ), "VLLM_USE_PRECOMPILED is only supported for CUDA builds"

333
334
335
336
        wheel_location = os.getenv("VLLM_PRECOMPILED_WHEEL_LOCATION", None)
        if wheel_location is None:
            base_commit = self.get_base_commit_in_main_branch()
            wheel_location = f"https://wheels.vllm.ai/{base_commit}/vllm-1.0.0.dev-cp38-abi3-manylinux1_x86_64.whl"
337
338
339
340
            # Fallback to nightly wheel if latest commit wheel is unavailable,
            # in this rare case, the nightly release CI hasn't finished on main.
            if not is_url_available(wheel_location):
                wheel_location = "https://wheels.vllm.ai/nightly/vllm-1.0.0.dev-cp38-abi3-manylinux1_x86_64.whl"
341

342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
        import zipfile

        if os.path.isfile(wheel_location):
            wheel_path = wheel_location
            print(f"Using existing wheel={wheel_path}")
        else:
            # Download the wheel from a given URL, assume
            # the filename is the last part of the URL
            wheel_filename = wheel_location.split("/")[-1]

            import tempfile

            # create a temporary directory to store the wheel
            temp_dir = tempfile.mkdtemp(prefix="vllm-wheels")
            wheel_path = os.path.join(temp_dir, wheel_filename)

            print(f"Downloading wheel from {wheel_location} to {wheel_path}")

            from urllib.request import urlretrieve

            try:
                urlretrieve(wheel_location, filename=wheel_path)
            except Exception as e:
                from setuptools.errors import SetupError

                raise SetupError(
                    f"Failed to get vLLM wheel from {wheel_location}") from e

        with zipfile.ZipFile(wheel_path) as wheel:
            files_to_copy = [
                "vllm/_C.abi3.so",
                "vllm/_moe_C.abi3.so",
374
                "vllm/_flashmla_C.abi3.so",
375
376
                "vllm/vllm_flash_attn/_vllm_fa2_C.abi3.so",
                "vllm/vllm_flash_attn/_vllm_fa3_C.abi3.so",
377
378
                "vllm/vllm_flash_attn/flash_attn_interface.py",
                "vllm/vllm_flash_attn/__init__.py",
379
                "vllm/cumem_allocator.abi3.so",
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
                # "vllm/_version.py", # not available in nightly wheels yet
            ]
            file_members = filter(lambda x: x.filename in files_to_copy,
                                  wheel.filelist)

            for file in file_members:
                print(f"Extracting and including {file.filename} "
                      "from existing wheel")
                package_name = os.path.dirname(file.filename).replace("/", ".")
                file_name = os.path.basename(file.filename)

                if package_name not in package_data:
                    package_data[package_name] = []

                wheel.extract(file)
                if file_name.endswith(".py"):
                    # python files shouldn't be added to package_data
                    continue

                package_data[package_name].append(file_name)


402
def _is_hpu() -> bool:
403
404
405
406
407
408
409
    # if VLLM_TARGET_DEVICE env var was set explicitly, skip HPU autodetection
    if os.getenv("VLLM_TARGET_DEVICE", None) == VLLM_TARGET_DEVICE:
        return VLLM_TARGET_DEVICE == "hpu"

    # if VLLM_TARGET_DEVICE was not set explicitly, check if hl-smi succeeds,
    # and if it doesn't, check if habanalabs driver is loaded
    is_hpu_available = False
410
    try:
411
412
        out = subprocess.run(["hl-smi"], capture_output=True, check=True)
        is_hpu_available = out.returncode == 0
413
    except (FileNotFoundError, PermissionError, subprocess.CalledProcessError):
414
        if sys.platform.startswith("linux"):
415
416
417
418
419
420
            try:
                output = subprocess.check_output(
                    'lsmod | grep habanalabs | wc -l', shell=True)
                is_hpu_available = int(output) > 0
            except (ValueError, FileNotFoundError, PermissionError,
                    subprocess.CalledProcessError):
421
422
                pass
    return is_hpu_available
423
424


425
426
427
428
def _no_device() -> bool:
    return VLLM_TARGET_DEVICE == "empty"


429
def _is_cuda() -> bool:
430
431
    has_cuda = torch.version.cuda is not None
    return (VLLM_TARGET_DEVICE == "cuda" and has_cuda
432
            and not (_is_neuron() or _is_tpu() or _is_hpu()))
433
434


435
def _is_hip() -> bool:
436
437
    return (VLLM_TARGET_DEVICE == "cuda"
            or VLLM_TARGET_DEVICE == "rocm") and torch.version.hip is not None
438
439


440
def _is_neuron() -> bool:
441
    return VLLM_TARGET_DEVICE == "neuron"
442
443


444
445
446
447
def _is_tpu() -> bool:
    return VLLM_TARGET_DEVICE == "tpu"


448
449
450
451
def _is_cpu() -> bool:
    return VLLM_TARGET_DEVICE == "cpu"


452
453
454
455
def _is_xpu() -> bool:
    return VLLM_TARGET_DEVICE == "xpu"


456
457
458
459
def _build_custom_ops() -> bool:
    return _is_cuda() or _is_hip() or _is_cpu()


460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
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()
479

480
481
        if (get_rocm_core_version(ctypes.byref(major), ctypes.byref(minor),
                                  ctypes.byref(patch)) == 0):
482
            return f"{major.value}.{minor.value}.{patch.value}"
483
        return None
484
    except Exception:
485
        return None
Woosuk Kwon's avatar
Woosuk Kwon committed
486

487

488
489
490
def get_neuronxcc_version():
    import sysconfig
    site_dir = sysconfig.get_paths()["purelib"]
491
492
    version_file = os.path.join(site_dir, "neuronxcc", "version",
                                "__init__.py")
493
494

    # Check if the command was executed successfully
495
    with open(version_file) as fp:
496
497
498
499
500
501
502
503
        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:
504
        raise RuntimeError("Could not find Neuron version in the output")
505
506


bnellnm's avatar
bnellnm committed
507
def get_nvcc_cuda_version() -> Version:
508
509
510
511
    """Get the CUDA version from nvcc.

    Adapted from https://github.com/NVIDIA/apex/blob/8b7a1ff183741dd8f9b87e7bafd04cfde99cea28/setup.py
    """
512
    assert CUDA_HOME is not None, "CUDA_HOME is not set"
bnellnm's avatar
bnellnm committed
513
    nvcc_output = subprocess.check_output([CUDA_HOME + "/bin/nvcc", "-V"],
514
515
516
517
518
519
520
                                          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


521
522
523
524
525
526
527
528
def get_gaudi_sw_version():
    """
    Returns the driver version.
    """
    # Enable console printing for `hl-smi` check
    output = subprocess.run("hl-smi",
                            shell=True,
                            text=True,
529
                            capture_output=True,
530
531
532
533
534
535
536
                            env={"ENABLE_CONSOLE": "true"})
    if output.returncode == 0 and output.stdout:
        return output.stdout.split("\n")[2].replace(
            " ", "").split(":")[1][:-1].split("-")[0]
    return "0.0.0"  # when hl-smi is not available


537
def get_vllm_version() -> str:
538
    version = get_version(write_to="vllm/_version.py")
539
    sep = "+" if "+" not in version else "."  # dev versions might contain +
540

541
    if _no_device():
542
        if envs.VLLM_TARGET_DEVICE == "empty":
543
            version += f"{sep}empty"
544
    elif _is_cuda():
545
        if envs.VLLM_USE_PRECOMPILED:
546
            version += f"{sep}precompiled"
547
548
549
550
551
552
553
        else:
            cuda_version = str(get_nvcc_cuda_version())
            if cuda_version != MAIN_CUDA_VERSION:
                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}"
554
    elif _is_hip():
555
556
557
558
        # Get the Rocm Version
        rocm_version = get_rocm_version() or torch.version.hip
        if rocm_version and rocm_version != MAIN_CUDA_VERSION:
            version += f"{sep}rocm{rocm_version.replace('.', '')[:3]}"
559
560
    elif _is_neuron():
        # Get the Neuron version
bnellnm's avatar
bnellnm committed
561
        neuron_version = str(get_neuronxcc_version())
562
563
        if neuron_version != MAIN_CUDA_VERSION:
            neuron_version_str = neuron_version.replace(".", "")[:3]
564
            version += f"{sep}neuron{neuron_version_str}"
565
566
567
568
569
570
    elif _is_hpu():
        # Get the Intel Gaudi Software Suite version
        gaudi_sw_version = str(get_gaudi_sw_version())
        if gaudi_sw_version != MAIN_CUDA_VERSION:
            gaudi_sw_version = gaudi_sw_version.replace(".", "")[:3]
            version += f"{sep}gaudi{gaudi_sw_version}"
571
    elif _is_tpu():
572
        version += f"{sep}tpu"
573
    elif _is_cpu():
574
575
        if envs.VLLM_TARGET_DEVICE == "cpu":
            version += f"{sep}cpu"
576
    elif _is_xpu():
577
        version += f"{sep}xpu"
578
    else:
579
        raise RuntimeError("Unknown runtime environment")
580

581
582
583
    return version


584
def get_requirements() -> list[str]:
585
    """Get Python package dependencies from requirements.txt."""
586
    requirements_dir = ROOT_DIR / "requirements"
587

588
    def _read_requirements(filename: str) -> list[str]:
589
        with open(requirements_dir / filename) as f:
590
            requirements = f.read().strip().split("\n")
591
592
593
594
        resolved_requirements = []
        for line in requirements:
            if line.startswith("-r "):
                resolved_requirements += _read_requirements(line.split()[1])
595
596
            elif not line.startswith("--") and not line.startswith(
                    "#") and line.strip() != "":
597
598
599
                resolved_requirements.append(line)
        return resolved_requirements

600
    if _no_device():
601
        requirements = _read_requirements("common.txt")
602
    elif _is_cuda():
603
        requirements = _read_requirements("cuda.txt")
604
        cuda_major, cuda_minor = torch.version.cuda.split(".")
605
606
        modified_requirements = []
        for req in requirements:
607
608
            if ("vllm-flash-attn" in req and cuda_major != "12"):
                # vllm-flash-attn is built only for CUDA 12.x.
609
610
611
                # Skip for other versions.
                continue
            modified_requirements.append(req)
612
        requirements = modified_requirements
613
    elif _is_hip():
614
        requirements = _read_requirements("rocm.txt")
615
    elif _is_neuron():
616
        requirements = _read_requirements("neuron.txt")
617
    elif _is_hpu():
618
        requirements = _read_requirements("hpu.txt")
619
    elif _is_tpu():
620
        requirements = _read_requirements("tpu.txt")
621
    elif _is_cpu():
622
        requirements = _read_requirements("cpu.txt")
623
    elif _is_xpu():
624
        requirements = _read_requirements("xpu.txt")
625
626
    else:
        raise ValueError(
627
            "Unsupported platform, please use CUDA, ROCm, Neuron, HPU, "
628
            "or CPU.")
629
630
631
    return requirements


bnellnm's avatar
bnellnm committed
632
633
ext_modules = []

634
if _is_cuda() or _is_hip():
bnellnm's avatar
bnellnm committed
635
636
    ext_modules.append(CMakeExtension(name="vllm._moe_C"))

637
638
639
if _is_hip():
    ext_modules.append(CMakeExtension(name="vllm._rocm_C"))

640
if _is_cuda():
641
    ext_modules.append(CMakeExtension(name="vllm.vllm_flash_attn._vllm_fa2_C"))
642
643
644
645
    if envs.VLLM_USE_PRECOMPILED or get_nvcc_cuda_version() >= Version("12.0"):
        # FA3 requires CUDA 12.0 or later
        ext_modules.append(
            CMakeExtension(name="vllm.vllm_flash_attn._vllm_fa3_C"))
646
647
648
649
650
    if envs.VLLM_USE_PRECOMPILED or get_nvcc_cuda_version() >= Version("12.3"):
        # Optional since this doesn't get built (produce an .so file) when
        # not targeting a hopper system
        ext_modules.append(
            CMakeExtension(name="vllm._flashmla_C", optional=True))
651
    ext_modules.append(CMakeExtension(name="vllm.cumem_allocator"))
652

653
if _build_custom_ops():
bnellnm's avatar
bnellnm committed
654
655
    ext_modules.append(CMakeExtension(name="vllm._C"))

656
package_data = {
657
658
659
660
661
    "vllm": [
        "py.typed",
        "model_executor/layers/fused_moe/configs/*.json",
        "model_executor/layers/quantization/utils/configs/*.json",
    ]
662
}
Simon Mo's avatar
Simon Mo committed
663

664
665
666
if _no_device():
    ext_modules = []

667
668
669
670
671
672
673
674
if not ext_modules:
    cmdclass = {}
else:
    cmdclass = {
        "build_ext":
        repackage_wheel if envs.VLLM_USE_PRECOMPILED else cmake_build_ext
    }

bnellnm's avatar
bnellnm committed
675
setup(
676
    # static metadata should rather go in pyproject.toml
677
    version=get_vllm_version(),
Woosuk Kwon's avatar
Woosuk Kwon committed
678
    ext_modules=ext_modules,
679
    install_requires=get_requirements(),
680
    extras_require={
681
        "tensorizer": ["tensorizer>=2.9.0"],
682
        "fastsafetensors": ["fastsafetensors >= 0.1.10"],
683
        "runai": ["runai-model-streamer", "runai-model-streamer-s3", "boto3"],
684
685
        "audio": ["librosa", "soundfile"],  # Required for audio processing
        "video": ["decord"]  # Required for video processing
686
    },
687
    cmdclass=cmdclass,
Simon Mo's avatar
Simon Mo committed
688
    package_data=package_data,
Woosuk Kwon's avatar
Woosuk Kwon committed
689
)