[tune](deps): Bump nevergrad from 0.4.2.post5 to 0.4.3.post4 in /python/requirements/tune #1
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Bumps [nevergrad](https://github.com/facebookresearch/nevergrad) from 0.4.2.post5 to 0.4.3.post4. - [Release notes](https://github.com/facebookresearch/nevergrad/releases) - [Changelog](https://github.com/facebookresearch/nevergrad/blob/master/CHANGELOG.md) - [Commits](facebookresearch/nevergrad@0.4.2.post5...0.4.3.post4) --- updated-dependencies: - dependency-name: nevergrad dependency-type: direct:production update-type: version-update:semver-patch ... Signed-off-by: dependabot[bot] <support@github.com>
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Superseded by #20. |
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We encountered SIGSEGV when running Python test `python/ray/tests/test_failure_2.py::test_list_named_actors_timeout`. The stack is: ``` #0 0x00007fffed30f393 in std::basic_string<char, std::char_traits<char>, std::allocator<char> >::basic_string(std::string const&) () from /lib64/libstdc++.so.6 #1 0x00007fffee707649 in ray::RayLog::GetLoggerName() () from /home/admin/dev/Arc/merge/ray/python/ray/_raylet.so #2 0x00007fffee70aa90 in ray::SpdLogMessage::Flush() () from /home/admin/dev/Arc/merge/ray/python/ray/_raylet.so #3 0x00007fffee70af28 in ray::RayLog::~RayLog() () from /home/admin/dev/Arc/merge/ray/python/ray/_raylet.so #4 0x00007fffee2b570d in ray::asio::testing::(anonymous namespace)::DelayManager::Init() [clone .constprop.0] () from /home/admin/dev/Arc/merge/ray/python/ray/_raylet.so #5 0x00007fffedd0d95a in _GLOBAL__sub_I_asio_chaos.cc () from /home/admin/dev/Arc/merge/ray/python/ray/_raylet.so #6 0x00007ffff7fe282a in call_init.part () from /lib64/ld-linux-x86-64.so.2 #7 0x00007ffff7fe2931 in _dl_init () from /lib64/ld-linux-x86-64.so.2 #8 0x00007ffff7fe674c in dl_open_worker () from /lib64/ld-linux-x86-64.so.2 #9 0x00007ffff7b82e79 in _dl_catch_exception () from /lib64/libc.so.6 #10 0x00007ffff7fe5ffe in _dl_open () from /lib64/ld-linux-x86-64.so.2 #11 0x00007ffff7d5f39c in dlopen_doit () from /lib64/libdl.so.2 #12 0x00007ffff7b82e79 in _dl_catch_exception () from /lib64/libc.so.6 #13 0x00007ffff7b82f13 in _dl_catch_error () from /lib64/libc.so.6 #14 0x00007ffff7d5fb09 in _dlerror_run () from /lib64/libdl.so.2 #15 0x00007ffff7d5f42a in dlopen@@GLIBC_2.2.5 () from /lib64/libdl.so.2 #16 0x00007fffef04d330 in py_dl_open (self=<optimized out>, args=<optimized out>) at /tmp/python-build.20220507135524.257789/Python-3.7.11/Modules/_ctypes/callproc.c:1369 ``` The root cause is that when loading `_raylet.so`, `static DelayManager _delay_manager` is initialized and `RAY_LOG(ERROR) << "RAY_testing_asio_delay_us is set to " << delay_env;` is executed. However, the static variables declared in `logging.cc` are not initialized yet (in this case, `std::string RayLog::logger_name_ = "ray_log_sink"`). It's better not to rely on the initialization order of static variables in different compilation units because it's not guaranteed. I propose to change all `RAY_LOG`s to `std::cerr` in `DelayManager::Init()`. The crash happens in Ant's internal codebase. Not sure why this test case passes in the community version though. BTW, I've tried different approaches: 1. Using a static local variable in `get_delay_us` and remove the global variable. This doesn't work because `init()` needs to access the variable as well. 2. Defining the global variable as type `std::unique_ptr<DelayManager>` and initialize it in `get_delay_us`. This works but it requires a lock to be thread-safe.
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… condition (ray-project#55367) ## Why are these changes needed? Workers crash with a fatal `RAY_CHECK` failure when the plasma store connection is broken during shutdown, causing the following error: ``` RAY_CHECK failed: PutInLocalPlasmaStore(object, object_id, true) Status not OK: IOError: Broken pipe ``` Stacktrace: ``` core_worker.cc:720 C Check failed: PutInLocalPlasmaStore(object, object_id, true) Status not OK: IOError: Broken pipe *** StackTrace Information *** /home/ray/anaconda3/lib/python3.11/site-packages/ray/_raylet.so(+0x141789a) [0x7924dd2c689a] ray::operator<<() /home/ray/anaconda3/lib/python3.11/site-packages/ray/_raylet.so(_ZN3ray6RayLogD1Ev+0x479) [0x7924dd2c9319] ray::RayLog::~RayLog() /home/ray/anaconda3/lib/python3.11/site-packages/ray/_raylet.so(+0x95cc8a) [0x7924dc80bc8a] ray::core::CoreWorker::CoreWorker()::{lambda()#13}::operator()() /home/ray/anaconda3/lib/python3.11/site-packages/ray/_raylet.so(_ZN3ray4core11TaskManager27MarkTaskReturnObjectsFailedERKNS_17TaskSpecificationENS_3rpc9ErrorTypeEPKNS5_12RayErrorInfoERKN4absl12lts_2023080213flat_hash_setINS_8ObjectIDENSB_13hash_internal4HashISD_EESt8equal_toISD_ESaISD_EEE+0x679) [0x7924dc868f29] ray::core::TaskManager::MarkTaskReturnObjectsFailed() /home/ray/anaconda3/lib/python3.11/site-packages/ray/_raylet.so(_ZN3ray4core11TaskManager15FailPendingTaskERKNS_6TaskIDENS_3rpc9ErrorTypeEPKNS_6StatusEPKNS5_12RayErrorInfoE+0x416) [0x7924dc86f186] ray::core::TaskManager::FailPendingTask() /home/ray/anaconda3/lib/python3.11/site-packages/ray/_raylet.so(+0x9a90e6) [0x7924dc8580e6] ray::core::NormalTaskSubmitter::RequestNewWorkerIfNeeded()::{lambda()#1}::operator()() /home/ray/anaconda3/lib/python3.11/site-packages/ray/_raylet.so(_ZN3ray3rpc14ClientCallImplINS0_23RequestWorkerLeaseReplyEE15OnReplyReceivedEv+0x68) [0x7924dc94aa48] ray::rpc::ClientCallImpl<>::OnReplyReceived() /home/ray/anaconda3/lib/python3.11/site-packages/ray/_raylet.so(_ZNSt17_Function_handlerIFvvEZN3ray3rpc17ClientCallManager29PollEventsFromCompletionQueueEiEUlvE_E9_M_invokeERKSt9_Any_data+0x15) [0x7924dc79e285] std::_Function_handler<>::_M_invoke() /home/ray/anaconda3/lib/python3.11/site-packages/ray/_raylet.so(+0xd9b4c8) [0x7924dcc4a4c8] EventTracker::RecordExecution() /home/ray/anaconda3/lib/python3.11/site-packages/ray/_raylet.so(+0xd4648e) [0x7924dcbf548e] std::_Function_handler<>::_M_invoke() /home/ray/anaconda3/lib/python3.11/site-packages/ray/_raylet.so(+0xd46906) [0x7924dcbf5906] boost::asio::detail::completion_handler<>::do_complete() /home/ray/anaconda3/lib/python3.11/site-packages/ray/_raylet.so(+0x13f417b) [0x7924dd2a317b] boost::asio::detail::scheduler::do_run_one() /home/ray/anaconda3/lib/python3.11/site-packages/ray/_raylet.so(+0x13f5af9) [0x7924dd2a4af9] boost::asio::detail::scheduler::run() /home/ray/anaconda3/lib/python3.11/site-packages/ray/_raylet.so(+0x13f6202) [0x7924dd2a5202] boost::asio::io_context::run() /home/ray/anaconda3/lib/python3.11/site-packages/ray/_raylet.so(_ZN3ray4core10CoreWorker12RunIOServiceEv+0x91) [0x7924dc793a61] ray::core::CoreWorker::RunIOService() /home/ray/anaconda3/lib/python3.11/site-packages/ray/_raylet.so(+0xcba0b0) [0x7924dcb690b0] thread_proxy /lib/x86_64-linux-gnu/libc.so.6(+0x94ac3) [0x7924dde71ac3] /lib/x86_64-linux-gnu/libc.so.6(+0x126850) [0x7924ddf03850] ``` Stack trace flow: 1. Task lease request fails -> `NormalTaskSubmitter::RequestNewWorkerIfNeeded()` callback. 2. Triggers `TaskManager::FailPendingTask()` -> `MarkTaskReturnObjectsFailed()`. 3. System attempts to store error objects in plasma via `put_in_local_plasma_callback_`. 4. Plasma connection is broken (raylet/plasma store already shut down). 5. `RAY_CHECK_OK()` in the callback causes fatal crash instead of graceful handling. Root Cause: This is a shutdown ordering race condition: 1. Raylet shuts down first: The raylet stops its IO context ([main_service_.stop()](https://github.com/ray-project/ray/blob/77c5475195e56a26891d88460973198391d20edf/src/ray/object_manager/plasma/store_runner.cc#L146)) which closes plasma store connections. 2. Worker still processes callbacks: Core worker continues processing pending callbacks on separate threads. 3. Broken connection: When the callback tries to store error objects in plasma, the connection is already closed. 4. Fatal crash: The `RAY_CHECK_OK()` treats this as an unexpected error and crashes the process. Fix: 1. Shutdown-aware plasma operations - Add `CoreWorker::IsShuttingDown()` method to check shutdown state. - Skip plasma operations entirely when shutdown is in progress. - Prevents attempting operations on already-closed connections. 2. Targeted error handling for connection failures - Replace blanket `RAY_CHECK_OK()` with specific error type checking. - Handle connection errors (Broken pipe, Connection reset, Bad file descriptor) as warnings during shutdown scenarios. - Maintain `RAY_CHECK_OK()` for other error types to catch real issues. --------- Signed-off-by: Sagar Sumit <sagarsumit09@gmail.com>
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Bumps nevergrad from 0.4.2.post5 to 0.4.3.post4.
Release notes
Sourced from nevergrad's releases.
Changelog
Sourced from nevergrad's changelog.
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Commits
0b5a9baAdd sub-optim info for NGOpt and SplitOpt (#1137)3a5a114Use new ConfPortfolio API (#1124)7360f3aSimple new benchs (#1129)308092cMake Portfolio more generic (#1094)bf0a927Adding non-progressive NoisySplit (#1089)97c9e36New NgOpt (#1123)6fd743emax num vars in collaborative coevolution (#1120)ae1b9a3Improving our one-shot optimization methods (#1103)3f21757Ignore mypy for numpy sum axis (#1117)2fb7d17Update mixsimulator experiment (benchmark) (#1107)Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting
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