[tune](deps): Bump pytorch-lightning from 1.0.3 to 1.2.0 in /python/requirements #5
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
![dependabot[bot]](https://avatars.githubusercontent.com/in/29110?s=60&v=4){kind=small}
Bumps [pytorch-lightning](https://github.com/PyTorchLightning/pytorch-lightning) from 1.0.3 to 1.2.0. - [Release notes](https://github.com/PyTorchLightning/pytorch-lightning/releases) - [Changelog](https://github.com/PyTorchLightning/pytorch-lightning/blob/master/CHANGELOG.md) - [Commits](Lightning-AI/pytorch-lightning@1.0.3...1.2.0) Signed-off-by: dependabot[bot] <[email protected]>
dependabot
bot
added
the
dependencies
|
Superseded by #7. |
dependabot
bot
deleted the
dependabot/pip/python/requirements/pytorch-lightning-1.2.0
branch
krfricke
pushed a commit
that referenced
this pull request
Jul 27, 2022
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.
krfricke
pushed a commit
that referenced
this pull request
Mar 6, 2023
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Bumps pytorch-lightning from 1.0.3 to 1.2.0.
Release notes
Sourced from pytorch-lightning's releases.
... (truncated)
Changelog
Sourced from pytorch-lightning's changelog.
... (truncated)
Commits
3645eb1pypi azure badges - tags (#6068)e12c8a7add Azure tags trigger (#6066)4574023v1.2.0 (#6065)5d6a091default sched (#6062)8f82823Raise AttributeError in lightning_getattr and lightning_setattr when attribut...b0074a4Update auto-opt docs (#6037)c46c23av1.2.0rc2 (#6063)2cf39dcAdd warnings to on_before/after_batch_transfer hooks (#6059)d3a31bcfix docs links (#6057)fc9bb53fix flake8 for new plugins (#5951)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
@dependabot rebase.Dependabot commands and options
You can trigger Dependabot actions by commenting on this PR:
@dependabot rebasewill rebase this PR@dependabot recreatewill recreate this PR, overwriting any edits that have been made to it@dependabot mergewill merge this PR after your CI passes on it@dependabot squash and mergewill squash and merge this PR after your CI passes on it@dependabot cancel mergewill cancel a previously requested merge and block automerging@dependabot reopenwill reopen this PR if it is closed@dependabot closewill close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually@dependabot ignore this major versionwill close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)@dependabot ignore this minor versionwill close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)@dependabot ignore this dependencywill close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)