| 1 | # SPDX-License-Identifier: Apache-2.0 |
| 2 | # SPDX-FileCopyrightText: Copyright contributors to the vLLM project |
| 3 | |
| 4 | # ruff: noqa |
| 5 | # code borrowed from https://github.com/pytorch/pytorch/blob/main/torch/utils/collect_env.py |
| 6 | |
| 7 | import datetime |
| 8 | import locale |
| 9 | import os |
| 10 | import subprocess |
| 11 | import sys |
| 12 | |
| 13 | # Unlike the rest of the PyTorch this file must be python2 compliant. |
| 14 | # This script outputs relevant system environment info |
| 15 | # Run it with `python collect_env.py` or `python -m torch.utils.collect_env` |
| 16 | from collections import namedtuple |
| 17 | |
| 18 | import regex as re |
| 19 | |
| 20 | from vllm.envs import environment_variables |
| 21 | |
| 22 | try: |
| 23 | import torch |
| 24 | |
| 25 | TORCH_AVAILABLE = True |
| 26 | except (ImportError, NameError, AttributeError, OSError): |
| 27 | TORCH_AVAILABLE = False |
| 28 | |
| 29 | # System Environment Information |
| 30 | SystemEnv = namedtuple( |
| 31 | "SystemEnv", |
| 32 | [ |
| 33 | "torch_version", |
| 34 | "is_debug_build", |
| 35 | "cuda_compiled_version", |
| 36 | "gcc_version", |
| 37 | "clang_version", |
| 38 | "cmake_version", |
| 39 | "os", |
| 40 | "libc_version", |
| 41 | "python_version", |
| 42 | "python_platform", |
| 43 | "is_cuda_available", |
| 44 | "cuda_runtime_version", |
| 45 | "cuda_module_loading", |
| 46 | "nvidia_driver_version", |
| 47 | "nvidia_gpu_models", |
| 48 | "cudnn_version", |
| 49 | "xpu_available", |
| 50 | "xpu_runtime_version", |
| 51 | "intel_graphics_compiler_version", |
| 52 | "intel_gpu_models", |
| 53 | "oneapi_compiler_version", |
| 54 | "level_zero_loader_version", |
| 55 | "level_zero_driver_version", |
| 56 | "oneccl_version", |
| 57 | "libigdgmm_version", |
| 58 | "vllm_xpu_kernels_version", |
| 59 | "sycl_version", |
| 60 | "pip_version", # 'pip' or 'pip3' |
| 61 | "pip_packages", |
| 62 | "conda_packages", |
| 63 | "hip_compiled_version", |
| 64 | "hip_runtime_version", |
| 65 | "miopen_runtime_version", |
| 66 | "caching_allocator_config", |
| 67 | "is_xnnpack_available", |
| 68 | "cpu_info", |
| 69 | "rocm_version", # vllm specific field |
| 70 | "vllm_version", # vllm specific field |
| 71 | "vllm_build_flags", # vllm specific field |
| 72 | "gpu_topo", # vllm specific field |
| 73 | "env_vars", |
| 74 | ], |
| 75 | ) |
| 76 | |
| 77 | DEFAULT_CONDA_PATTERNS = { |
| 78 | "torch", |
| 79 | "numpy", |
| 80 | "cudatoolkit", |
| 81 | "soumith", |
| 82 | "mkl", |
| 83 | "magma", |
| 84 | "triton", |
| 85 | "optree", |
| 86 | "nccl", |
| 87 | "transformers", |
| 88 | "zmq", |
| 89 | "nvidia", |
| 90 | "pynvml", |
| 91 | "flashinfer-python", |
| 92 | "helion", |
| 93 | } |
| 94 | |
| 95 | DEFAULT_PIP_PATTERNS = { |
| 96 | "torch", |
| 97 | "numpy", |
| 98 | "mypy", |
| 99 | "flake8", |
| 100 | "triton", |
| 101 | "optree", |
| 102 | "onnx", |
| 103 | "nccl", |
| 104 | "transformers", |
| 105 | "zmq", |
| 106 | "nvidia", |
| 107 | "pynvml", |
| 108 | "flashinfer-python", |
| 109 | "helion", |
| 110 | } |
| 111 | |
| 112 | |
| 113 | def run(command): |
| 114 | """Return (return-code, stdout, stderr).""" |
| 115 | shell = True if type(command) is str else False |
| 116 | try: |
| 117 | p = subprocess.Popen( |
| 118 | command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=shell |
| 119 | ) |
| 120 | raw_output, raw_err = p.communicate() |
| 121 | rc = p.returncode |
| 122 | if get_platform() == "win32": |
| 123 | enc = "oem" |
| 124 | else: |
| 125 | enc = locale.getpreferredencoding() |
| 126 | output = raw_output.decode(enc) |
| 127 | if command == "nvidia-smi topo -m": |
| 128 | # don't remove the leading whitespace of `nvidia-smi topo -m` |
| 129 | # because they are meaningful |
| 130 | output = output.rstrip() |
| 131 | else: |
| 132 | output = output.strip() |
| 133 | err = raw_err.decode(enc) |
| 134 | return rc, output, err.strip() |
| 135 | |
| 136 | except FileNotFoundError: |
| 137 | cmd_str = command if isinstance(command, str) else command[0] |
| 138 | return 127, "", f"Command not found: {cmd_str}" |
| 139 | |
| 140 | |
| 141 | def run_and_read_all(run_lambda, command): |
| 142 | """Run command using run_lambda; reads and returns entire output if rc is 0.""" |
| 143 | rc, out, _ = run_lambda(command) |
| 144 | if rc != 0: |
| 145 | return None |
| 146 | return out |
| 147 | |
| 148 | |
| 149 | def run_and_parse_first_match(run_lambda, command, regex): |
| 150 | """Run command using run_lambda, returns the first regex match if it exists.""" |
| 151 | rc, out, _ = run_lambda(command) |
| 152 | if rc != 0: |
| 153 | return None |
| 154 | match = re.search(regex, out) |
| 155 | if match is None: |
| 156 | return None |
| 157 | return match.group(1) |
| 158 | |
| 159 | |
| 160 | def get_conda_packages(run_lambda, patterns=None): |
| 161 | if patterns is None: |
| 162 | patterns = DEFAULT_CONDA_PATTERNS |
| 163 | conda = os.environ.get("CONDA_EXE", "conda") |
| 164 | out = run_and_read_all(run_lambda, [conda, "list"]) |
| 165 | if out is None: |
| 166 | return out |
| 167 | |
| 168 | return "\n".join( |
| 169 | line |
| 170 | for line in out.splitlines() |
| 171 | if not line.startswith("#") and any(name in line for name in patterns) |
| 172 | ) |
| 173 | |
| 174 | |
| 175 | def get_gcc_version(run_lambda): |
| 176 | return run_and_parse_first_match(run_lambda, "gcc --version", r"gcc (.*)") |
| 177 | |
| 178 | |
| 179 | def get_clang_version(run_lambda): |
| 180 | return run_and_parse_first_match( |
| 181 | run_lambda, "clang --version", r"clang version (.*)" |
| 182 | ) |
| 183 | |
| 184 | |
| 185 | def get_cmake_version(run_lambda): |
| 186 | return run_and_parse_first_match(run_lambda, "cmake --version", r"cmake (.*)") |
| 187 | |
| 188 | |
| 189 | def get_nvidia_driver_version(run_lambda): |
| 190 | if get_platform() == "darwin": |
| 191 | cmd = "kextstat | grep -i cuda" |
| 192 | return run_and_parse_first_match( |
| 193 | run_lambda, cmd, r"com[.]nvidia[.]CUDA [(](.*?)[)]" |
| 194 | ) |
| 195 | smi = get_nvidia_smi() |
| 196 | return run_and_parse_first_match(run_lambda, smi, r"Driver Version: (.*?) ") |
| 197 | |
| 198 | |
| 199 | def get_gpu_info(run_lambda): |
| 200 | if get_platform() == "darwin" or ( |
| 201 | TORCH_AVAILABLE |
| 202 | and hasattr(torch.version, "hip") |
| 203 | and torch.version.hip is not None |
| 204 | ): |
| 205 | if TORCH_AVAILABLE and torch.cuda.is_available(): |
| 206 | if torch.version.hip is not None: |
| 207 | prop = torch.cuda.get_device_properties(0) |
| 208 | if hasattr(prop, "gcnArchName"): |
| 209 | gcnArch = " ({})".format(prop.gcnArchName) |
| 210 | else: |
| 211 | gcnArch = "NoGCNArchNameOnOldPyTorch" |
| 212 | else: |
| 213 | gcnArch = "" |
| 214 | return torch.cuda.get_device_name(None) + gcnArch |
| 215 | return None |
| 216 | smi = get_nvidia_smi() |
| 217 | uuid_regex = re.compile(r" \(UUID: .+?\)") |
| 218 | rc, out, _ = run_lambda(smi + " -L") |
| 219 | if rc != 0: |
| 220 | return None |
| 221 | # Anonymize GPUs by removing their UUID |
| 222 | return re.sub(uuid_regex, "", out) |
| 223 | |
| 224 | |
| 225 | def get_running_cuda_version(run_lambda): |
| 226 | return run_and_parse_first_match(run_lambda, "nvcc --version", r"release .+ V(.*)") |
| 227 | |
| 228 | |
| 229 | def get_cudnn_version(run_lambda): |
| 230 | """Return a list of libcudnn.so; it's hard to tell which one is being used.""" |
| 231 | if get_platform() == "win32": |
| 232 | system_root = os.environ.get("SYSTEMROOT", "C:\\Windows") |
| 233 | cuda_path = os.environ.get("CUDA_PATH", "%CUDA_PATH%") |
| 234 | where_cmd = os.path.join(system_root, "System32", "where") |
| 235 | cudnn_cmd = '{} /R "{}\\bin" cudnn*.dll'.format(where_cmd, cuda_path) |
| 236 | elif get_platform() == "darwin": |
| 237 | # CUDA libraries and drivers can be found in /usr/local/cuda/. See |
| 238 | # https://docs.nvidia.com/cuda/cuda-installation-guide-mac-os-x/index.html#install |
| 239 | # https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#installmac |
| 240 | # Use CUDNN_LIBRARY when cudnn library is installed elsewhere. |
| 241 | cudnn_cmd = "ls /usr/local/cuda/lib/libcudnn*" |
| 242 | else: |
| 243 | cudnn_cmd = 'ldconfig -p | grep libcudnn | rev | cut -d" " -f1 | rev' |
| 244 | rc, out, _ = run_lambda(cudnn_cmd) |
| 245 | # find will return 1 if there are permission errors or if not found |
| 246 | if len(out) == 0 or (rc != 1 and rc != 0): |
| 247 | l = os.environ.get("CUDNN_LIBRARY") |
| 248 | if l is not None and os.path.isfile(l): |
| 249 | return os.path.realpath(l) |
| 250 | return None |
| 251 | files_set = set() |
| 252 | for fn in out.split("\n"): |
| 253 | fn = os.path.realpath(fn) # eliminate symbolic links |
| 254 | if os.path.isfile(fn): |
| 255 | files_set.add(fn) |
| 256 | if not files_set: |
| 257 | return None |
| 258 | # Alphabetize the result because the order is non-deterministic otherwise |
| 259 | files = sorted(files_set) |
| 260 | if len(files) == 1: |
| 261 | return files[0] |
| 262 | result = "\n".join(files) |
| 263 | return "Probably one of the following:\n{}".format(result) |
| 264 | |
| 265 | |
| 266 | def get_nvidia_smi(): |
| 267 | # Note: nvidia-smi is currently available only on Windows and Linux |
| 268 | smi = "nvidia-smi" |
| 269 | if get_platform() == "win32": |
| 270 | system_root = os.environ.get("SYSTEMROOT", "C:\\Windows") |
| 271 | program_files_root = os.environ.get("PROGRAMFILES", "C:\\Program Files") |
| 272 | legacy_path = os.path.join( |
| 273 | program_files_root, "NVIDIA Corporation", "NVSMI", smi |
| 274 | ) |
| 275 | new_path = os.path.join(system_root, "System32", smi) |
| 276 | smis = [new_path, legacy_path] |
| 277 | for candidate_smi in smis: |
| 278 | if os.path.exists(candidate_smi): |
| 279 | smi = '"{}"'.format(candidate_smi) |
| 280 | break |
| 281 | return smi |
| 282 | |
| 283 | |
| 284 | def get_rocm_version(run_lambda): |
| 285 | """Returns the ROCm version if available, otherwise 'N/A'.""" |
| 286 | return run_and_parse_first_match( |
| 287 | run_lambda, "hipcc --version", r"HIP version: (\S+)" |
| 288 | ) |
| 289 | |
| 290 | |
| 291 | def get_xpu_available(): |
| 292 | if TORCH_AVAILABLE and hasattr(torch, "xpu") and torch.xpu.is_available(): |
| 293 | return True |
| 294 | return False |
| 295 | |
| 296 | |
| 297 | def get_xpu_runtime_version(): |
| 298 | if TORCH_AVAILABLE and hasattr(torch.version, "xpu"): |
| 299 | return torch.version.xpu |
| 300 | return None |
| 301 | |
| 302 | |
| 303 | def get_pkg_version(run_lambda, pkg): |
| 304 | assert get_platform() == "linux" |
| 305 | |
| 306 | if pkg in ["vllm_xpu_kernels", "oneccl"]: |
| 307 | rc, out, _ = run_lambda(f"pip show {pkg}") |
| 308 | if rc == 0: |
| 309 | match = re.search(r"Version: (.*)", out) |
| 310 | return match.group(1).strip() if match else None |
| 311 | return None |
| 312 | |
| 313 | pkg_map = { |
| 314 | "igc": ["intel-igc-core", "libigc2", "libigc1"], |
| 315 | "level_zero_loader": ["level-zero", "libze1"], |
| 316 | "level_zero_driver": ["libze-intel-gpu1", "intel-level-zero-gpu"], |
| 317 | "libigdgmm": ["libigdgmm12", "libigdgmm"], |
| 318 | } |
| 319 | |
| 320 | pkg_candidates = pkg_map.get(pkg, []) |
| 321 | if not pkg_candidates: |
| 322 | return None |
| 323 | |
| 324 | mgr_name = None |
| 325 | for mgr in ["dpkg", "dnf", "yum", "zypper"]: |
| 326 | rc, _, _ = run_lambda(f"which {mgr}") |
| 327 | if rc == 0: |
| 328 | mgr_name = mgr |
| 329 | break |
| 330 | |
| 331 | if not mgr_name: |
| 332 | return None |
| 333 | |
| 334 | ret = "" |
| 335 | index = -1 |
| 336 | |
| 337 | for pkg_name in pkg_candidates: |
| 338 | if not pkg_name: |
| 339 | continue |
| 340 | |
| 341 | cmd = "" |
| 342 | if mgr_name in ["dnf", "yum"]: |
| 343 | index = 1 |
| 344 | cmd = f"{mgr_name} list | grep -w {pkg_name}" |
| 345 | elif mgr_name == "zypper": |
| 346 | index = 2 |
| 347 | cmd = f"{mgr_name} info {pkg_name} | grep Version" |
| 348 | elif mgr_name == "dpkg": |
| 349 | index = 2 |
| 350 | cmd = f"{mgr_name} -l | grep -w {pkg_name}" |
| 351 | |
| 352 | if cmd: |
| 353 | out = run_and_read_all(run_lambda, cmd) |
| 354 | if out: |
| 355 | ret = out.splitlines()[0] |
| 356 | break |
| 357 | |
| 358 | if not ret or index == -1: |
| 359 | return None |
| 360 | |
| 361 | lst = re.sub(" +", " ", ret).strip().split(" ") |
| 362 | if len(lst) > index: |
| 363 | return lst[index] |
| 364 | |
| 365 | return None |
| 366 | |
| 367 | |
| 368 | def get_intel_graphics_compiler_version(run_lambda): |
| 369 | """Return Intel Graphics Compiler (IGC) version.""" |
| 370 | return get_pkg_version(run_lambda, "igc") |
| 371 | |
| 372 | |
| 373 | def get_level_zero_loader_version(run_lambda): |
| 374 | """Return Level Zero loader runtime version.""" |
| 375 | return get_pkg_version(run_lambda, "level_zero_loader") |
| 376 | |
| 377 | |
| 378 | def get_level_zero_driver_version(run_lambda): |
| 379 | """Return Level Zero driver version.""" |
| 380 | return get_pkg_version(run_lambda, "level_zero_driver") |
| 381 | |
| 382 | |
| 383 | def get_oneapi_ccl_version(run_lambda): |
| 384 | """Return oneAPI Collective Communications Library (oneCCL) version.""" |
| 385 | return get_pkg_version(run_lambda, "oneccl") |
| 386 | |
| 387 | |
| 388 | def get_libigdgmm_version(run_lambda): |
| 389 | return get_pkg_version(run_lambda, "libigdgmm") |
| 390 | |
| 391 | |
| 392 | def get_vllm_xpu_kernels_version(run_lambda): |
| 393 | return get_pkg_version(run_lambda, "vllm_xpu_kernels") |
| 394 | |
| 395 | |
| 396 | def get_intel_gpu_models(): |
| 397 | if TORCH_AVAILABLE and hasattr(torch, "xpu") and torch.xpu.is_available(): |
| 398 | device_count = torch.xpu.device_count() |
| 399 | return "\n".join( |
| 400 | "GPU {}: {}".format(i, torch.xpu.get_device_name(i)) |
| 401 | for i in range(device_count) |
| 402 | ) |
| 403 | return None |
| 404 | |
| 405 | |
| 406 | def get_oneapi_compiler_version(run_lambda): |
| 407 | """Return Intel oneAPI DPC++/C++ Compiler version via icpx.""" |
| 408 | return run_and_parse_first_match( |
| 409 | run_lambda, "icpx --version", r"oneAPI DPC\+\+/C\+\+ Compiler (\S+)" |
| 410 | ) |
| 411 | |
| 412 | |
| 413 | def get_sycl_version(run_lambda): |
| 414 | """Return SYCL/DPC++ compiler build version.""" |
| 415 | return run_and_parse_first_match(run_lambda, "icpx --version", r"\((\d[\d.]+)\)") |
| 416 | |
| 417 | |
| 418 | def get_vllm_version(): |
| 419 | from vllm import __version__, __version_tuple__ |
| 420 | |
| 421 | if __version__ == "dev": |
| 422 | return "N/A (dev)" |
| 423 | version_str = __version_tuple__[-1] |
| 424 | if isinstance(version_str, str) and version_str.startswith("g"): |
| 425 | # it's a dev build |
| 426 | if "." in version_str: |
| 427 | # it's a dev build containing local changes |
| 428 | git_sha = version_str.split(".")[0][1:] |
| 429 | date = version_str.split(".")[-1][1:] |
| 430 | return f"{__version__} (git sha: {git_sha}, date: {date})" |
| 431 | else: |
| 432 | # it's a dev build without local changes |
| 433 | git_sha = version_str[1:] # type: ignore |
| 434 | return f"{__version__} (git sha: {git_sha})" |
| 435 | return __version__ |
| 436 | |
| 437 | |
| 438 | def summarize_vllm_build_flags(): |
| 439 | flags = "CUDA Archs: {}; ROCm: {}; XPU: {}".format( |
| 440 | os.environ.get("TORCH_CUDA_ARCH_LIST", "Not Set"), |
| 441 | "Enabled" if os.environ.get("ROCM_HOME") else "Disabled", |
| 442 | "Enabled" if get_xpu_available() else "Disabled", |
| 443 | ) |
| 444 | return flags |
| 445 | |
| 446 | |
| 447 | def get_gpu_topo(run_lambda): |
| 448 | output = None |
| 449 | |
| 450 | if get_platform() == "linux": |
| 451 | output = run_and_read_all(run_lambda, "nvidia-smi topo -m") |
| 452 | if output is None: |
| 453 | output = run_and_read_all(run_lambda, "rocm-smi --showtopo") |
| 454 | |
| 455 | return output |
| 456 | |
| 457 | |
| 458 | # example outputs of CPU infos |
| 459 | # * linux |
| 460 | # Architecture: x86_64 |
| 461 | # CPU op-mode(s): 32-bit, 64-bit |
| 462 | # Address sizes: 46 bits physical, 48 bits virtual |
| 463 | # Byte Order: Little Endian |
| 464 | # CPU(s): 128 |
| 465 | # On-line CPU(s) list: 0-127 |
| 466 | # Vendor ID: GenuineIntel |
| 467 | # Model name: Intel(R) Xeon(R) Platinum 8375C CPU @ 2.90GHz |
| 468 | # CPU family: 6 |
| 469 | # Model: 106 |
| 470 | # Thread(s) per core: 2 |
| 471 | # Core(s) per socket: 32 |
| 472 | # Socket(s): 2 |
| 473 | # Stepping: 6 |
| 474 | # BogoMIPS: 5799.78 |
| 475 | # Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr |
| 476 | # sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon rep_good nopl |
| 477 | # xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq monitor ssse3 fma cx16 |
| 478 | # pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand |
| 479 | # hypervisor lahf_lm abm 3dnowprefetch invpcid_single ssbd ibrs ibpb stibp ibrs_enhanced |
| 480 | # fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid avx512f avx512dq rdseed adx smap |
| 481 | # avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 |
| 482 | # xsaves wbnoinvd ida arat avx512vbmi pku ospke avx512_vbmi2 gfni vaes vpclmulqdq |
| 483 | # avx512_vnni avx512_bitalg tme avx512_vpopcntdq rdpid md_clear flush_l1d arch_capabilities |
| 484 | # Virtualization features: |
| 485 | # Hypervisor vendor: KVM |
| 486 | # Virtualization type: full |
| 487 | # Caches (sum of all): |
| 488 | # L1d: 3 MiB (64 instances) |
| 489 | # L1i: 2 MiB (64 instances) |
| 490 | # L2: 80 MiB (64 instances) |
| 491 | # L3: 108 MiB (2 instances) |
| 492 | # NUMA: |
| 493 | # NUMA node(s): 2 |
| 494 | # NUMA node0 CPU(s): 0-31,64-95 |
| 495 | # NUMA node1 CPU(s): 32-63,96-127 |
| 496 | # Vulnerabilities: |
| 497 | # Itlb multihit: Not affected |
| 498 | # L1tf: Not affected |
| 499 | # Mds: Not affected |
| 500 | # Meltdown: Not affected |
| 501 | # Mmio stale data: Vulnerable: Clear CPU buffers attempted, no microcode; SMT Host state unknown |
| 502 | # Retbleed: Not affected |
| 503 | # Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp |
| 504 | # Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization |
| 505 | # Spectre v2: Mitigation; Enhanced IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence |
| 506 | # Srbds: Not affected |
| 507 | # Tsx async abort: Not affected |
| 508 | # * win32 |
| 509 | # Architecture=9 |
| 510 | # CurrentClockSpeed=2900 |
| 511 | # DeviceID=CPU0 |
| 512 | # Family=179 |
| 513 | # L2CacheSize=40960 |
| 514 | # L2CacheSpeed= |
| 515 | # Manufacturer=GenuineIntel |
| 516 | # MaxClockSpeed=2900 |
| 517 | # Name=Intel(R) Xeon(R) Platinum 8375C CPU @ 2.90GHz |
| 518 | # ProcessorType=3 |
| 519 | # Revision=27142 |
| 520 | # |
| 521 | # Architecture=9 |
| 522 | # CurrentClockSpeed=2900 |
| 523 | # DeviceID=CPU1 |
| 524 | # Family=179 |
| 525 | # L2CacheSize=40960 |
| 526 | # L2CacheSpeed= |
| 527 | # Manufacturer=GenuineIntel |
| 528 | # MaxClockSpeed=2900 |
| 529 | # Name=Intel(R) Xeon(R) Platinum 8375C CPU @ 2.90GHz |
| 530 | # ProcessorType=3 |
| 531 | # Revision=27142 |
| 532 | |
| 533 | |
| 534 | def get_cpu_info(run_lambda): |
| 535 | rc, out, err = 0, "", "" |
| 536 | if get_platform() == "linux": |
| 537 | rc, out, err = run_lambda("lscpu") |
| 538 | elif get_platform() == "win32": |
| 539 | rc, out, err = run_lambda( |
| 540 | "wmic cpu get Name,Manufacturer,Family,Architecture,ProcessorType,DeviceID, \ |
| 541 | CurrentClockSpeed,MaxClockSpeed,L2CacheSize,L2CacheSpeed,Revision /VALUE" |
| 542 | ) |
| 543 | elif get_platform() == "darwin": |
| 544 | rc, out, err = run_lambda("sysctl -n machdep.cpu.brand_string") |
| 545 | cpu_info = "None" |
| 546 | if rc == 0: |
| 547 | cpu_info = out |
| 548 | else: |
| 549 | cpu_info = err |
| 550 | return cpu_info |
| 551 | |
| 552 | |
| 553 | def get_platform(): |
| 554 | if sys.platform.startswith("linux"): |
| 555 | return "linux" |
| 556 | elif sys.platform.startswith("win32"): |
| 557 | return "win32" |
| 558 | elif sys.platform.startswith("cygwin"): |
| 559 | return "cygwin" |
| 560 | elif sys.platform.startswith("darwin"): |
| 561 | return "darwin" |
| 562 | else: |
| 563 | return sys.platform |
| 564 | |
| 565 | |
| 566 | def get_mac_version(run_lambda): |
| 567 | return run_and_parse_first_match(run_lambda, "sw_vers -productVersion", r"(.*)") |
| 568 | |
| 569 | |
| 570 | def get_windows_version(run_lambda): |
| 571 | system_root = os.environ.get("SYSTEMROOT", "C:\\Windows") |
| 572 | wmic_cmd = os.path.join(system_root, "System32", "Wbem", "wmic") |
| 573 | findstr_cmd = os.path.join(system_root, "System32", "findstr") |
| 574 | return run_and_read_all( |
| 575 | run_lambda, "{} os get Caption | {} /v Caption".format(wmic_cmd, findstr_cmd) |
| 576 | ) |
| 577 | |
| 578 | |
| 579 | def get_lsb_version(run_lambda): |
| 580 | return run_and_parse_first_match( |
| 581 | run_lambda, "lsb_release -a", r"Description:\t(.*)" |
| 582 | ) |
| 583 | |
| 584 | |
| 585 | def check_release_file(run_lambda): |
| 586 | return run_and_parse_first_match( |
| 587 | run_lambda, "cat /etc/*-release", r'PRETTY_NAME="(.*)"' |
| 588 | ) |
| 589 | |
| 590 | |
| 591 | def get_os(run_lambda): |
| 592 | from platform import machine |
| 593 | |
| 594 | platform = get_platform() |
| 595 | |
| 596 | if platform == "win32" or platform == "cygwin": |
| 597 | return get_windows_version(run_lambda) |
| 598 | |
| 599 | if platform == "darwin": |
| 600 | version = get_mac_version(run_lambda) |
| 601 | if version is None: |
| 602 | return None |
| 603 | return "macOS {} ({})".format(version, machine()) |
| 604 | |
| 605 | if platform == "linux": |
| 606 | # Ubuntu/Debian based |
| 607 | desc = get_lsb_version(run_lambda) |
| 608 | if desc is not None: |
| 609 | return "{} ({})".format(desc, machine()) |
| 610 | |
| 611 | # Try reading /etc/*-release |
| 612 | desc = check_release_file(run_lambda) |
| 613 | if desc is not None: |
| 614 | return "{} ({})".format(desc, machine()) |
| 615 | |
| 616 | return "{} ({})".format(platform, machine()) |
| 617 | |
| 618 | # Unknown platform |
| 619 | return platform |
| 620 | |
| 621 | |
| 622 | def get_python_platform(): |
| 623 | import platform |
| 624 | |
| 625 | return platform.platform() |
| 626 | |
| 627 | |
| 628 | def get_libc_version(): |
| 629 | import platform |
| 630 | |
| 631 | if get_platform() != "linux": |
| 632 | return "N/A" |
| 633 | return "-".join(platform.libc_ver()) |
| 634 | |
| 635 | |
| 636 | def is_uv_venv(): |
| 637 | if os.environ.get("UV"): |
| 638 | return True |
| 639 | pyvenv_cfg_path = os.path.join(sys.prefix, "pyvenv.cfg") |
| 640 | if os.path.exists(pyvenv_cfg_path): |
| 641 | with open(pyvenv_cfg_path, "r") as f: |
| 642 | return any(line.startswith("uv = ") for line in f) |
| 643 | return False |
| 644 | |
| 645 | |
| 646 | def get_pip_packages(run_lambda, patterns=None): |
| 647 | """Return `pip list` output. Note: will also find conda-installed pytorch and numpy packages.""" |
| 648 | if patterns is None: |
| 649 | patterns = DEFAULT_PIP_PATTERNS |
| 650 | |
| 651 | def run_with_pip(): |
| 652 | try: |
| 653 | import importlib.util |
| 654 | |
| 655 | pip_spec = importlib.util.find_spec("pip") |
| 656 | pip_available = pip_spec is not None |
| 657 | except ImportError: |
| 658 | pip_available = False |
| 659 | |
| 660 | if pip_available: |
| 661 | cmd = [sys.executable, "-mpip", "list", "--format=freeze"] |
| 662 | elif is_uv_venv(): |
| 663 | print("uv is set") |
| 664 | cmd = ["uv", "pip", "list", "--format=freeze"] |
| 665 | else: |
| 666 | raise RuntimeError( |
| 667 | "Could not collect pip list output (pip or uv module not available)" |
| 668 | ) |
| 669 | |
| 670 | out = run_and_read_all(run_lambda, cmd) |
| 671 | return "\n".join( |
| 672 | line for line in out.splitlines() if any(name in line for name in patterns) |
| 673 | ) |
| 674 | |
| 675 | pip_version = "pip3" if sys.version[0] == "3" else "pip" |
| 676 | out = run_with_pip() |
| 677 | return pip_version, out |
| 678 | |
| 679 | |
| 680 | def get_cachingallocator_config(): |
| 681 | ca_config = os.environ.get("PYTORCH_CUDA_ALLOC_CONF", "") |
| 682 | return ca_config |
| 683 | |
| 684 | |
| 685 | def get_cuda_module_loading_config(): |
| 686 | if TORCH_AVAILABLE and torch.cuda.is_available(): |
| 687 | torch.cuda.init() |
| 688 | config = os.environ.get("CUDA_MODULE_LOADING", "") |
| 689 | return config |
| 690 | else: |
| 691 | return "N/A" |
| 692 | |
| 693 | |
| 694 | def is_xnnpack_available(): |
| 695 | if TORCH_AVAILABLE: |
| 696 | import torch.backends.xnnpack |
| 697 | |
| 698 | return str(torch.backends.xnnpack.enabled) # type: ignore[attr-defined] |
| 699 | else: |
| 700 | return "N/A" |
| 701 | |
| 702 | |
| 703 | def get_env_vars(): |
| 704 | env_vars = "" |
| 705 | secret_terms = ("secret", "token", "api", "access", "password") |
| 706 | report_prefix = ( |
| 707 | "TORCH", |
| 708 | "NCCL", |
| 709 | "PYTORCH", |
| 710 | "CUDA", |
| 711 | "CUBLAS", |
| 712 | "CUDNN", |
| 713 | "OMP_", |
| 714 | "MKL_", |
| 715 | "NVIDIA", |
| 716 | "ZE_", |
| 717 | "ONEAPI_", |
| 718 | "SYCL_", |
| 719 | "NEOReadDebugKeys", |
| 720 | "IGC_", |
| 721 | "CCL_", |
| 722 | "I_MPI_", |
| 723 | ) |
| 724 | for k, v in os.environ.items(): |
| 725 | if any(term in k.lower() for term in secret_terms): |
| 726 | continue |
| 727 | if k in environment_variables: |
| 728 | env_vars = env_vars + "{}={}".format(k, v) + "\n" |
| 729 | if k.startswith(report_prefix): |
| 730 | env_vars = env_vars + "{}={}".format(k, v) + "\n" |
| 731 | |
| 732 | return env_vars |
| 733 | |
| 734 | |
| 735 | def get_env_info(): |
| 736 | run_lambda = run |
| 737 | pip_version, pip_list_output = get_pip_packages(run_lambda) |
| 738 | |
| 739 | if TORCH_AVAILABLE: |
| 740 | version_str = torch.__version__ |
| 741 | debug_mode_str = str(torch.version.debug) |
| 742 | cuda_available_str = str(torch.cuda.is_available()) |
| 743 | cuda_version_str = torch.version.cuda |
| 744 | if ( |
| 745 | not hasattr(torch.version, "hip") or torch.version.hip is None |
| 746 | ): # cuda version |
| 747 | hip_compiled_version = hip_runtime_version = miopen_runtime_version = "N/A" |
| 748 | else: # HIP version |
| 749 | |
| 750 | def get_version_or_na(cfg, prefix): |
| 751 | _lst = [s.rsplit(None, 1)[-1] for s in cfg if prefix in s] |
| 752 | return _lst[0] if _lst else "N/A" |
| 753 | |
| 754 | cfg = torch._C._show_config().split("\n") |
| 755 | hip_runtime_version = get_version_or_na(cfg, "HIP Runtime") |
| 756 | miopen_runtime_version = get_version_or_na(cfg, "MIOpen") |
| 757 | cuda_version_str = "N/A" |
| 758 | hip_compiled_version = torch.version.hip |
| 759 | else: |
| 760 | version_str = debug_mode_str = cuda_available_str = cuda_version_str = "N/A" |
| 761 | hip_compiled_version = hip_runtime_version = miopen_runtime_version = "N/A" |
| 762 | |
| 763 | sys_version = sys.version.replace("\n", " ") |
| 764 | |
| 765 | conda_packages = get_conda_packages(run_lambda) |
| 766 | |
| 767 | rocm_version = get_rocm_version(run_lambda) |
| 768 | vllm_version = get_vllm_version() |
| 769 | vllm_build_flags = summarize_vllm_build_flags() |
| 770 | gpu_topo = get_gpu_topo(run_lambda) |
| 771 | |
| 772 | return SystemEnv( |
| 773 | torch_version=version_str, |
| 774 | is_debug_build=debug_mode_str, |
| 775 | python_version="{} ({}-bit runtime)".format( |
| 776 | sys_version, sys.maxsize.bit_length() + 1 |
| 777 | ), |
| 778 | python_platform=get_python_platform(), |
| 779 | is_cuda_available=cuda_available_str, |
| 780 | cuda_compiled_version=cuda_version_str, |
| 781 | cuda_runtime_version=get_running_cuda_version(run_lambda), |
| 782 | cuda_module_loading=get_cuda_module_loading_config(), |
| 783 | nvidia_gpu_models=get_gpu_info(run_lambda), |
| 784 | nvidia_driver_version=get_nvidia_driver_version(run_lambda), |
| 785 | cudnn_version=get_cudnn_version(run_lambda), |
| 786 | xpu_available=str(get_xpu_available()), |
| 787 | xpu_runtime_version=get_xpu_runtime_version(), |
| 788 | intel_graphics_compiler_version=get_intel_graphics_compiler_version(run_lambda), |
| 789 | intel_gpu_models=get_intel_gpu_models(), |
| 790 | oneapi_compiler_version=get_oneapi_compiler_version(run_lambda), |
| 791 | level_zero_loader_version=get_level_zero_loader_version(run_lambda), |
| 792 | level_zero_driver_version=get_level_zero_driver_version(run_lambda), |
| 793 | oneccl_version=get_oneapi_ccl_version(run_lambda), |
| 794 | libigdgmm_version=get_libigdgmm_version(run_lambda), |
| 795 | vllm_xpu_kernels_version=get_vllm_xpu_kernels_version(run_lambda), |
| 796 | sycl_version=get_sycl_version(run_lambda), |
| 797 | hip_compiled_version=hip_compiled_version, |
| 798 | hip_runtime_version=hip_runtime_version, |
| 799 | miopen_runtime_version=miopen_runtime_version, |
| 800 | pip_version=pip_version, |
| 801 | pip_packages=pip_list_output, |
| 802 | conda_packages=conda_packages, |
| 803 | os=get_os(run_lambda), |
| 804 | libc_version=get_libc_version(), |
| 805 | gcc_version=get_gcc_version(run_lambda), |
| 806 | clang_version=get_clang_version(run_lambda), |
| 807 | cmake_version=get_cmake_version(run_lambda), |
| 808 | caching_allocator_config=get_cachingallocator_config(), |
| 809 | is_xnnpack_available=is_xnnpack_available(), |
| 810 | cpu_info=get_cpu_info(run_lambda), |
| 811 | rocm_version=rocm_version, |
| 812 | vllm_version=vllm_version, |
| 813 | vllm_build_flags=vllm_build_flags, |
| 814 | gpu_topo=gpu_topo, |
| 815 | env_vars=get_env_vars(), |
| 816 | ) |
| 817 | |
| 818 | |
| 819 | env_info_fmt = """ |
| 820 | ============================== |
| 821 | System Info |
| 822 | ============================== |
| 823 | OS : {os} |
| 824 | GCC version : {gcc_version} |
| 825 | Clang version : {clang_version} |
| 826 | CMake version : {cmake_version} |
| 827 | Libc version : {libc_version} |
| 828 | |
| 829 | ============================== |
| 830 | PyTorch Info |
| 831 | ============================== |
| 832 | PyTorch version : {torch_version} |
| 833 | Is debug build : {is_debug_build} |
| 834 | CUDA used to build PyTorch : {cuda_compiled_version} |
| 835 | ROCM used to build PyTorch : {hip_compiled_version} |
| 836 | XPU used to build PyTorch : {xpu_runtime_version} |
| 837 | |
| 838 | ============================== |
| 839 | Python Environment |
| 840 | ============================== |
| 841 | Python version : {python_version} |
| 842 | Python platform : {python_platform} |
| 843 | |
| 844 | {gpu_info} |
| 845 | ============================== |
| 846 | CPU Info |
| 847 | ============================== |
| 848 | {cpu_info} |
| 849 | |
| 850 | ============================== |
| 851 | Versions of relevant libraries |
| 852 | ============================== |
| 853 | {pip_packages} |
| 854 | {conda_packages} |
| 855 | """.strip() |
| 856 | |
| 857 | # both the above code and the following code use `strip()` to |
| 858 | # remove leading/trailing whitespaces, so we need to add a newline |
| 859 | # in between to separate the two sections |
| 860 | env_info_fmt += "\n\n" |
| 861 | |
| 862 | env_info_fmt += """ |
| 863 | ============================== |
| 864 | vLLM Info |
| 865 | ============================== |
| 866 | ROCM Version : {rocm_version} |
| 867 | vLLM Version : {vllm_version} |
| 868 | vLLM Build Flags: |
| 869 | {vllm_build_flags} |
| 870 | GPU Topology: |
| 871 | {gpu_topo} |
| 872 | |
| 873 | ============================== |
| 874 | Environment Variables |
| 875 | ============================== |
| 876 | {env_vars} |
| 877 | """.strip() |
| 878 | |
| 879 | |
| 880 | def pretty_str(envinfo): |
| 881 | def replace_nones(dct, replacement="Could not collect"): |
| 882 | for key in dct.keys(): |
| 883 | if dct[key] is not None: |
| 884 | continue |
| 885 | dct[key] = replacement |
| 886 | return dct |
| 887 | |
| 888 | def replace_bools(dct, true="Yes", false="No"): |
| 889 | for key in dct.keys(): |
| 890 | if dct[key] is True: |
| 891 | dct[key] = true |
| 892 | elif dct[key] is False: |
| 893 | dct[key] = false |
| 894 | return dct |
| 895 | |
| 896 | def prepend(text, tag="[prepend]"): |
| 897 | lines = text.split("\n") |
| 898 | updated_lines = [tag + line for line in lines] |
| 899 | return "\n".join(updated_lines) |
| 900 | |
| 901 | def replace_if_empty(text, replacement="No relevant packages"): |
| 902 | if text is not None and len(text) == 0: |
| 903 | return replacement |
| 904 | return text |
| 905 | |
| 906 | def maybe_start_on_next_line(string): |
| 907 | # If `string` is multiline, prepend a \n to it. |
| 908 | if string is not None and len(string.split("\n")) > 1: |
| 909 | return "\n{}\n".format(string) |
| 910 | return string |
| 911 | |
| 912 | mutable_dict = envinfo._asdict() |
| 913 | |
| 914 | # If nvidia_gpu_models is multiline, start on the next line |
| 915 | mutable_dict["nvidia_gpu_models"] = maybe_start_on_next_line( |
| 916 | envinfo.nvidia_gpu_models |
| 917 | ) |
| 918 | |
| 919 | # If the machine doesn't have CUDA, report some fields as 'No CUDA' |
| 920 | dynamic_cuda_fields = [ |
| 921 | "cuda_runtime_version", |
| 922 | "nvidia_gpu_models", |
| 923 | "nvidia_driver_version", |
| 924 | ] |
| 925 | all_cuda_fields = dynamic_cuda_fields + ["cudnn_version"] |
| 926 | all_dynamic_cuda_fields_missing = all( |
| 927 | mutable_dict[field] is None for field in dynamic_cuda_fields |
| 928 | ) |
| 929 | if ( |
| 930 | TORCH_AVAILABLE |
| 931 | and not torch.cuda.is_available() |
| 932 | and all_dynamic_cuda_fields_missing |
| 933 | ): |
| 934 | for field in all_cuda_fields: |
| 935 | mutable_dict[field] = "No CUDA" |
| 936 | if envinfo.cuda_compiled_version is None: |
| 937 | mutable_dict["cuda_compiled_version"] = "None" |
| 938 | |
| 939 | # If the machine doesn't have XPU, report XPU fields as 'No XPU' |
| 940 | dynamic_xpu_fields = [ |
| 941 | "intel_graphics_compiler_version", |
| 942 | "intel_gpu_models", |
| 943 | "level_zero_loader_version", |
| 944 | "level_zero_driver_version", |
| 945 | "oneccl_version", |
| 946 | "libigdgmm_version", |
| 947 | "vllm_xpu_kernels_version", |
| 948 | ] |
| 949 | all_xpu_fields = dynamic_xpu_fields + [ |
| 950 | "oneapi_compiler_version", |
| 951 | "sycl_version", |
| 952 | ] |
| 953 | all_dynamic_xpu_fields_missing = all( |
| 954 | mutable_dict[field] is None for field in dynamic_xpu_fields |
| 955 | ) |
| 956 | xpu_available = mutable_dict.get("xpu_available") == "True" |
| 957 | if not xpu_available and all_dynamic_xpu_fields_missing: |
| 958 | for field in all_xpu_fields: |
| 959 | mutable_dict[field] = "No XPU" |
| 960 | if envinfo.xpu_runtime_version is None or envinfo.xpu_runtime_version == "N/A": |
| 961 | mutable_dict["xpu_runtime_version"] = "N/A" |
| 962 | |
| 963 | # If intel_gpu_models is multiline, start on the next line |
| 964 | mutable_dict["intel_gpu_models"] = maybe_start_on_next_line( |
| 965 | mutable_dict.get("intel_gpu_models") |
| 966 | ) |
| 967 | |
| 968 | # Replace True with Yes, False with No |
| 969 | mutable_dict = replace_bools(mutable_dict) |
| 970 | |
| 971 | # Replace all None objects with 'Could not collect' |
| 972 | mutable_dict = replace_nones(mutable_dict) |
| 973 | |
| 974 | # If either of these are '', replace with 'No relevant packages' |
| 975 | mutable_dict["pip_packages"] = replace_if_empty(mutable_dict["pip_packages"]) |
| 976 | mutable_dict["conda_packages"] = replace_if_empty(mutable_dict["conda_packages"]) |
| 977 | |
| 978 | # Tag conda and pip packages with a prefix |
| 979 | # If they were previously None, they'll show up as ie '[conda] Could not collect' |
| 980 | if mutable_dict["pip_packages"]: |
| 981 | mutable_dict["pip_packages"] = prepend( |
| 982 | mutable_dict["pip_packages"], "[{}] ".format(envinfo.pip_version) |
| 983 | ) |
| 984 | if mutable_dict["conda_packages"]: |
| 985 | mutable_dict["conda_packages"] = prepend( |
| 986 | mutable_dict["conda_packages"], "[conda] " |
| 987 | ) |
| 988 | mutable_dict["cpu_info"] = envinfo.cpu_info |
| 989 | |
| 990 | CUDA_FMT = """ |
| 991 | ============================== |
| 992 | CUDA / GPU Info |
| 993 | ============================== |
| 994 | Is CUDA available : {is_cuda_available} |
| 995 | CUDA runtime version : {cuda_runtime_version} |
| 996 | CUDA_MODULE_LOADING set to : {cuda_module_loading} |
| 997 | GPU models and configuration : {nvidia_gpu_models} |
| 998 | Nvidia driver version : {nvidia_driver_version} |
| 999 | cuDNN version : {cudnn_version} |
| 1000 | HIP runtime version : {hip_runtime_version} |
| 1001 | MIOpen runtime version : {miopen_runtime_version} |
| 1002 | Is XNNPACK available : {is_xnnpack_available} |
| 1003 | """.strip() |
| 1004 | |
| 1005 | XPU_FMT = """ |
| 1006 | ============================== |
| 1007 | Intel XPU / GPU Info |
| 1008 | ============================== |
| 1009 | Is XPU available : {xpu_available} |
| 1010 | XPU runtime version : {xpu_runtime_version} |
| 1011 | Intel GPU models : {intel_gpu_models} |
| 1012 | |
| 1013 | --Compile time-- |
| 1014 | oneAPI compiler version : {oneapi_compiler_version} |
| 1015 | SYCL compiler build : {sycl_version} |
| 1016 | oneCCL version : {oneccl_version} |
| 1017 | |
| 1018 | --Runtime-- |
| 1019 | Intel Graphics Compiler (IGC): {intel_graphics_compiler_version} |
| 1020 | Intel GMM (libigdgmm) : {libigdgmm_version} |
| 1021 | Level Zero loader version : {level_zero_loader_version} |
| 1022 | Level Zero driver version : {level_zero_driver_version} |
| 1023 | vLLM XPU kernels version : {vllm_xpu_kernels_version} |
| 1024 | """.strip() |
| 1025 | |
| 1026 | invalid_vers = {"N/A", "Could not collect", "None"} |
| 1027 | sections = [] |
| 1028 | |
| 1029 | if ( |
| 1030 | mutable_dict.get("is_cuda_available") in ("True", "Yes") |
| 1031 | or mutable_dict.get("cuda_compiled_version") not in invalid_vers |
| 1032 | ): |
| 1033 | sections.append(CUDA_FMT) |
| 1034 | |
| 1035 | if ( |
| 1036 | mutable_dict.get("xpu_available") in ("True", "Yes") |
| 1037 | or mutable_dict.get("xpu_runtime_version") not in invalid_vers |
| 1038 | ): |
| 1039 | sections.append(XPU_FMT) |
| 1040 | |
| 1041 | mutable_dict["gpu_info"] = ( |
| 1042 | ("\n\n".join(sections) + "\n").format(**mutable_dict) if sections else "" |
| 1043 | ) |
| 1044 | |
| 1045 | return env_info_fmt.format(**mutable_dict) |
| 1046 | |
| 1047 | |
| 1048 | def get_pretty_env_info(): |
| 1049 | return pretty_str(get_env_info()) |
| 1050 | |
| 1051 | |
| 1052 | def main(): |
| 1053 | print("Collecting environment information...") |
| 1054 | output = get_pretty_env_info() |
| 1055 | print(output) |
| 1056 | |
| 1057 | if ( |
| 1058 | TORCH_AVAILABLE |
| 1059 | and hasattr(torch, "utils") |
| 1060 | and hasattr(torch.utils, "_crash_handler") |
| 1061 | ): |
| 1062 | minidump_dir = torch.utils._crash_handler.DEFAULT_MINIDUMP_DIR |
| 1063 | if sys.platform == "linux" and os.path.exists(minidump_dir): |
| 1064 | dumps = [ |
| 1065 | os.path.join(minidump_dir, dump) for dump in os.listdir(minidump_dir) |
| 1066 | ] |
| 1067 | latest = max(dumps, key=os.path.getctime) |
| 1068 | ctime = os.path.getctime(latest) |
| 1069 | creation_time = datetime.datetime.fromtimestamp(ctime).strftime( |
| 1070 | "%Y-%m-%d %H:%M:%S" |
| 1071 | ) |
| 1072 | msg = ( |
| 1073 | "\n*** Detected a minidump at {} created on {}, ".format( |
| 1074 | latest, creation_time |
| 1075 | ) |
| 1076 | + "if this is related to your bug please include it when you file a report ***" |
| 1077 | ) |
| 1078 | print(msg, file=sys.stderr) |
| 1079 | |
| 1080 | |
| 1081 | if __name__ == "__main__": |
| 1082 | main() |