[tune](deps): Bump torch from 1.7.0 to 1.7.1 in /python/requirements #3
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Bumps [torch](https://github.com/pytorch/pytorch) from 1.7.0 to 1.7.1. - [Release notes](https://github.com/pytorch/pytorch/releases) - [Commits](pytorch/pytorch@v1.7.0...v1.7.1) Signed-off-by: dependabot[bot] <support@github.com>
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Superseded by #6. |
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…ray-project#23821) This PR refactors `LazyBlockList` in service of out-of-band serialization (see [mono-PR](ray-project#22616)) and is a precursor to an execution plan refactor (PR #2) and adding the actual out-of-band serialization APIs (PR #3). The following is included in this refactor: 1. `ReadTask`s are now a first-class concept, replacing calls; 2. read stage progress tracking is consolidated into `LazyBlockList._get_blocks_with_metadta()` and more of the read task complexity, e.g. the read remote function, was pushed into `LazyBlockList` to make `ray.data.read_datasource()` simpler; 3. we are a bit smarter with how we progressively launch tasks and fetch and cache metadata, including fetching the metadata for read tasks in `.iter_blocks_with_metadata()` instead of relying on the pre-read task metadata (which will be less accurate), and we also fix some small bugs in the lazy ramp-up around progressive metadata fetching. (1) is the most important item for supporting out-of-band serialization and fundamentally changes the `LazyBlockList` data model. This is required since we need to be able to reference the underlying read tasks when rewriting read stages during optimization and when serializing the lineage of the Dataset. See the [mono-PR](ray-project#22616) for more context. Other changes: 1. Changed stats actor to a global named actor singleton in order to obviate the need for serializing the actor handle with the Dataset stats; without this, we were encountering serialization failures.
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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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Bumps torch from 1.7.0 to 1.7.1.
Commits
57bffc3Disable autocast cache for tensor views as fix for #48049 (#48696) (#48936)661d1a0[v.1.7.x] Use local env for building CUDA extensions on Windows (#47150) (#48...f65108b[1.7.1] Fix LAPACK functionality detection from static OpenBLAS (#48819)1d9b64d[1.7.1] torch: Stop using _nt_quote_args from distutils (#48618) (#48768)62d6dfc[Release/1.7] Fix index parsing on Python-3.9 (#48744)351b85d[Release/1.7.1] Embedlibiomp5.dylibinto wheel package (#48337)a828009[Release/1.7.1] Fix mul cuda for bool (#48310)76c9339[v1.7.1] third_party: Update pybind to point to fork (#48312)716adbe[Release/1.7.1] Fix torch.version.debug generation (#48319)ea62bc8[Release/1.7.1] Make setup.py Python 2 friendly (#48317)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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