Comments (4)
(pid=gcs_server) *** SIGSEGV received at time=1719541509 on cpu 3 ***
*** SIGSEGV received at time=1719541526 on cpu 31 ***
PC: @ 0x7356d8e80806 (unknown) grpc_core::MetadataMap<>::~MetadataMap()
@ 0x735816228420 3376 (unknown)
@ 0x7356d91de24a 48 grpc_core::FilterStackCall::~FilterStackCall()
@ 0x7356d91da4fe 32 grpc_core::Call::DeleteThis()
@ 0x7356d9262374 80 grpc_core::ExecCtx::Flush()
@ 0x7356d8ddf822 32 grpc_core::ExecCtx::~ExecCtx()
@ 0x7356d91d6da7 208 grpc_core::FilterStackCall::ExternalUnref()
@ 0x7356d91d89ab 160 grpc_call_unref
@ 0x7356d8dde010 64 grpc::ClientContext::~ClientContext()
@ 0x7356d88d363a 32 std::_Sp_counted_base<>::_M_release()
@ 0x7356d8b8e147 1376 ray::gcs::PythonGcsSubscriber::DoPoll()
@ 0x7356d8b8eb56 160 ray::gcs::PythonGcsSubscriber::PollLogs()
@ 0x7356d892a0e0 336 __pyx_pw_3ray_7_raylet_16GcsLogSubscriber_3poll()
@ 0x4fdbe2 14269040 method_vectorcall_VARARGS_KEYWORDS
@ 0x740ce0 (unknown) (unknown)
[2024-06-28 02:25:26,286 E 77 2147] logging.cc:343: *** SIGSEGV received at time=1719541526 on cpu 31 ***
[2024-06-28 02:25:26,286 E 77 2147] logging.cc:343: PC: @ 0x7356d8e80806 (unknown) grpc_core::MetadataMap<>::~MetadataMap()
[2024-06-28 02:25:26,287 E 77 2147] logging.cc:343: @ 0x735816228420 3376 (unknown)
[2024-06-28 02:25:26,287 E 77 2147] logging.cc:343: @ 0x7356d91de24a 48 grpc_core::FilterStackCall::~FilterStackCall()
[2024-06-28 02:25:26,287 E 77 2147] logging.cc:343: @ 0x7356d91da4fe 32 grpc_core::Call::DeleteThis()
[2024-06-28 02:25:26,287 E 77 2147] logging.cc:343: @ 0x7356d9262374 80 grpc_core::ExecCtx::Flush()
[2024-06-28 02:25:26,287 E 77 2147] logging.cc:343: @ 0x7356d8ddf822 32 grpc_core::ExecCtx::~ExecCtx()
[2024-06-28 02:25:26,287 E 77 2147] logging.cc:343: @ 0x7356d91d6da7 208 grpc_core::FilterStackCall::ExternalUnref()
[2024-06-28 02:25:26,287 E 77 2147] logging.cc:343: @ 0x7356d91d89ab 160 grpc_call_unref
[2024-06-28 02:25:26,287 E 77 2147] logging.cc:343: @ 0x7356d8dde010 64 grpc::ClientContext::~ClientContext()
[2024-06-28 02:25:26,287 E 77 2147] logging.cc:343: @ 0x7356d88d363a 32 std::_Sp_counted_base<>::_M_release()
[2024-06-28 02:25:26,287 E 77 2147] logging.cc:343: @ 0x7356d8b8e147 1376 ray::gcs::PythonGcsSubscriber::DoPoll()
[2024-06-28 02:25:26,287 E 77 2147] logging.cc:343: @ 0x7356d8b8eb56 160 ray::gcs::PythonGcsSubscriber::PollLogs()
[2024-06-28 02:25:26,287 E 77 2147] logging.cc:343: @ 0x7356d892a0e0 336 __pyx_pw_3ray_7_raylet_16GcsLogSubscriber_3poll()
[2024-06-28 02:25:26,287 E 77 2147] logging.cc:343: @ 0x4fdbe2 14269040 method_vectorcall_VARARGS_KEYWORDS
[2024-06-28 02:25:26,288 E 77 2147] logging.cc:343: @ 0x740ce0 (unknown) (unknown)
Fatal Python error: Segmentation fault
Stack (most recent call first):
File "/opt/conda/lib/python3.10/site-packages/ray/_private/worker.py", line 898 in print_logs
File "/opt/conda/lib/python3.10/threading.py", line 953 in run
File "/opt/conda/lib/python3.10/threading.py", line 1016 in _bootstrap_inner
File "/opt/conda/lib/python3.10/threading.py", line 973 in _bootstrap
Extension modules: xoscar.context, xoscar.core, xoscar._utils, mkl._mklinit, mkl._py_mkl_service, numpy.core._multiarray_umath, numpy.core._multiarray_tests, numpy.linalg._umath_linalg, numpy.fft._pocketfft_internal, numpy.random._common, numpy.random.bit_generator, numpy.random._bounded_integers, numpy.random._mt19937, numpy.random.mtrand, numpy.random._philox, numpy.random._pcg64, numpy.random._sfc64, numpy.random._generator, pyarrow.lib, pandas._libs.tslibs.ccalendar, pandas._libs.tslibs.np_datetime, pandas._libs.tslibs.dtypes, pandas._libs.tslibs.base, pandas._libs.tslibs.nattype, pandas._libs.tslibs.timezones, pandas._libs.tslibs.fields, pandas._libs.tslibs.timedeltas, pandas._libs.tslibs.tzconversion, pandas._libs.tslibs.timestamps, pandas._libs.properties, pandas._libs.tslibs.offsets, pandas._libs.tslibs.strptime, pandas._libs.tslibs.parsing, pandas._libs.tslibs.conversion, pandas._libs.tslibs.period, pandas._libs.tslibs.vectorized, pandas._libs.ops_dispatch, pandas._libs.missing, pandas._libs.hashtable, pandas._libs.algos, pandas._libs.interval, pandas._libs.lib, pyarrow._compute, pandas._libs.ops, pandas._libs.hashing, pandas._libs.arrays, pandas._libs.tslib, pandas._libs.sparse, pandas._libs.internals, pandas._libs.indexing, pandas._libs.index, pandas._libs.writers, pandas._libs.join, pandas._libs.window.aggregations, pandas._libs.window.indexers, pandas._libs.reshape, pandas._libs.groupby, pandas._libs.json, pandas._libs.parsers, pandas._libs.testing, xoscar.serialization.core, scipy._lib._ccallback_c, scipy.sparse._sparsetools, _csparsetools, scipy.sparse._csparsetools, scipy.linalg._fblas, scipy.linalg._flapack, scipy.linalg.cython_lapack, scipy.linalg._cythonized_array_utils, scipy.linalg._solve_toeplitz, scipy.linalg._decomp_lu_cython, scipy.linalg._matfuncs_sqrtm_triu, scipy.linalg.cython_blas, scipy.linalg._matfuncs_expm, scipy.linalg._decomp_update, scipy.sparse.linalg._dsolve._superlu, scipy.sparse.linalg._eigen.arpack._arpack, scipy.sparse.linalg._propack._spropack, scipy.sparse.linalg._propack._dpropack, scipy.sparse.linalg._propack._cpropack, scipy.sparse.linalg._propack._zpropack, scipy.sparse.csgraph._tools, scipy.sparse.csgraph._shortest_path, scipy.sparse.csgraph._traversal, scipy.sparse.csgraph._min_spanning_tree, scipy.sparse.csgraph._flow, scipy.sparse.csgraph._matching, scipy.sparse.csgraph._reordering, xoscar.backends.message, psutil._psutil_linux, psutil._psutil_posix, cython.cimports.libc.math, markupsafe._speedups, _brotli, zstandard.backend_c, torch._C, torch._C._fft, torch._C._linalg, torch._C._nested, torch._C._nn, torch._C._sparse, torch._C._special, simplejson._speedups, yaml._yaml, PIL._imaging, regex._regex, sentencepiece._sentencepiece, msgpack._cmsgpack, google._upb._message, setproctitle, uvloop.loop, ray._raylet, pyarrow._json (total: 113)
from inference.
@jony4 看起来是vllm自己的错误导致了segmentation fault,自己尝试升降级vllm,或者去vllm官方repo寻找解决方案,不属于xinference范畴。
from inference.
使用的 docker 镜像方式部署的。
from inference.
我升级下最新的 docker 镜像看看
from inference.
Related Issues (20)
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- docker启动时报错,详情见具体异常 HOT 2
- Both `max_new_tokens` (=512) and `max_length`(=518) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. HOT 2
- [ maybe a bug ] Occasional exceptions occurred when reasoning with the mlx model yi-1.5-9b-chat HOT 1
- Failed start when base image from pytorch/pytorch:2.1.2-cuda12.1-cudnn8-devel to vllm/vllm-openai:latest HOT 3
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- xinference微调模型的支持
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- v1/completions接口无法使用,返回空字符串 HOT 1
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from inference.