add multiprocessing unit tests, working file-descriptor based solution and OSX #11

apaszke · 2016-09-07T17:20:21Z

Don't merge, this PR is only for test purposes

* TH_ALLOCATOR_MAPPED_FROMFD uses an existing file descriptor for mapping (and steals it) * TH_ALLOCATOR_MAPPED_KEEPFD doesn't close the file descriptor until the mapping is freed * TH_ALLOCATOR_MAPPED_UNLINK unlinks the file immediately after mapping it to memory Also, now it's using fstat to check the file size (instead of lseek, which alters the fd state).

Added dynamic dispatch for x86

write returns errno 45 (Operation not supported) when used with a file descriptor obtained via shm_open on OS X.

test/test_multiprocessing.py

+from common import TestCase
+
+
+HAS_SHM = os.path.isdir('/dev/shm')


Summary: This change includes CMake changes to compile the MPI assets when the USE_MPI flag is enabled. If so, the benchmark tool can now be launched through mpirun. Includes the changes done in #11. Closes pytorch/gloo#12 Reviewed By: Yangqing Differential Revision: D4712060 Pulled By: pietern fbshipit-source-id: 0d0e93882f5822583f59304d4256dbdf5dea7483

Fix ATen build for debug python

As [`newFunctionWithName:`](https://developer.apple.com/documentation/metal/mtllibrary/1515524-newfunctionwithname) does not accept error argument, do not attempt to print it as it'll be guaranteed `nil` at that point, that results in a classic null pointer dereference, when `TORCH_CHECK` will attempt to construct `std::string` from it. See below backtrace for example: ``` thread #1, queue = 'metal gpu stream', stop reason = EXC_BAD_ACCESS (code=1, address=0x0) frame #0: 0x000000018a316dc4 libsystem_platform.dylib`_platform_strlen + 4 frame #1: 0x00000001471011bc libtorch_cpu.dylib`std::__1::__constexpr_strlen[abi:v160006](__str=0x0000000000000000) at cstring:114:10 frame #2: 0x0000000147100c24 libtorch_cpu.dylib`std::__1::char_traits<char>::length(__s=0x0000000000000000) at char_traits.h:220:12 * frame #3: 0x0000000147100bf0 libtorch_cpu.dylib`std::__1::basic_ostream<char, std::__1::char_traits<char>>& std::__1::operator<<[abi:v160006]<std::__1::char_traits<char>>(__os=0x000000016fdfb3a0, __str=0x0000000000000000) at ostream:901:57 frame #4: 0x0000000147100bb4 libtorch_cpu.dylib`std::__1::basic_ostream<char, std::__1::char_traits<char>>& c10::detail::_str<char const*>(ss=0x000000016fdfb3a0, t=0x000000016fdfb5d0) at StringUtil.h:55:6 frame #5: 0x00000001471007ac libtorch_cpu.dylib`std::__1::basic_ostream<char, std::__1::char_traits<char>>& c10::detail::_str<char const*, char const*>(ss=0x000000016fdfb3a0, t=0x000000016fdfb4f8, args=0x000000016fdfb5d0) at StringUtil.h:68:10 frame #6: 0x0000000147101444 libtorch_cpu.dylib`std::__1::basic_ostream<char, std::__1::char_traits<char>>& c10::detail::_str<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, char const*, char const*>(ss=0x000000016fdfb3a0, t="index_select_32bit_idx32", args=0x000000016fdfb4f8, args=0x000000016fdfb5d0) at StringUtil.h:68:10 frame #7: 0x0000000147101404 libtorch_cpu.dylib`std::__1::basic_ostream<char, std::__1::char_traits<char>>& c10::detail::_str<char const*, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, char const*, char const*>(ss=0x000000016fdfb3a0, t=0x000000016fdfb500, args="index_select_32bit_idx32", args=0x000000016fdfb4f8, args=0x000000016fdfb5d0) at StringUtil.h:68:10 frame #8: 0x000000014710137c libtorch_cpu.dylib`c10::detail::_str_wrapper<char const*, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&, char const*, char const* const&>::call(args=0x000000016fdfb500, args="index_select_32bit_idx32", args=0x000000016fdfb4f8, args=0x000000016fdfb5d0) at StringUtil.h:75:5 frame #9: 0x0000000147101310 libtorch_cpu.dylib`decltype(auto) c10::str<char [53], std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, char [10], char const*>(args={a\xcb\xa7H\x01\0\0\0}, args="index_select_32bit_idx32", args={\x96\xcb\xa7H\x01\0\0\0}, args=0x000000016fdfb5d0) at StringUtil.h:111:10 frame #10: 0x0000000147100210 libtorch_cpu.dylib`decltype(auto) c10::detail::torchCheckMsgImpl<char [53], std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, char [10], char const*>((null)="Expected indexFunction to be true, but got false. (Could this error message be improved? If so, please report an enhancement request to PyTorch.)", args={a\xcb\xa7H\x01\0\0\0}, args="index_select_32bit_idx32", args={\x96\xcb\xa7H\x01\0\0\0}, args=0x000000016fdfb5d0) at Exception.h:453:10 frame #11: 0x00000001470fffe8 libtorch_cpu.dylib`at::mps::MPSDevice::metalIndexingPSO(this=0x0000600000381670, kernel="index_select_32bit_idx32") at MPSDevice.mm:62:3 ```

As [`newFunctionWithName:`](https://developer.apple.com/documentation/metal/mtllibrary/1515524-newfunctionwithname) does not accept error argument, do not attempt to print it as it'll be guaranteed `nil` at that point, that results in a classic null pointer dereference, when `TORCH_CHECK` will attempt to construct `std::string` from it. See below backtrace for example: ``` thread #1, queue = 'metal gpu stream', stop reason = EXC_BAD_ACCESS (code=1, address=0x0) frame #0: 0x000000018a316dc4 libsystem_platform.dylib`_platform_strlen + 4 frame #1: 0x00000001471011bc libtorch_cpu.dylib`std::__1::__constexpr_strlen[abi:v160006](__str=0x0000000000000000) at cstring:114:10 frame #2: 0x0000000147100c24 libtorch_cpu.dylib`std::__1::char_traits<char>::length(__s=0x0000000000000000) at char_traits.h:220:12 * frame #3: 0x0000000147100bf0 libtorch_cpu.dylib`std::__1::basic_ostream<char, std::__1::char_traits<char>>& std::__1::operator<<[abi:v160006]<std::__1::char_traits<char>>(__os=0x000000016fdfb3a0, __str=0x0000000000000000) at ostream:901:57 frame #4: 0x0000000147100bb4 libtorch_cpu.dylib`std::__1::basic_ostream<char, std::__1::char_traits<char>>& c10::detail::_str<char const*>(ss=0x000000016fdfb3a0, t=0x000000016fdfb5d0) at StringUtil.h:55:6 frame #5: 0x00000001471007ac libtorch_cpu.dylib`std::__1::basic_ostream<char, std::__1::char_traits<char>>& c10::detail::_str<char const*, char const*>(ss=0x000000016fdfb3a0, t=0x000000016fdfb4f8, args=0x000000016fdfb5d0) at StringUtil.h:68:10 frame #6: 0x0000000147101444 libtorch_cpu.dylib`std::__1::basic_ostream<char, std::__1::char_traits<char>>& c10::detail::_str<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, char const*, char const*>(ss=0x000000016fdfb3a0, t="index_select_32bit_idx32", args=0x000000016fdfb4f8, args=0x000000016fdfb5d0) at StringUtil.h:68:10 frame #7: 0x0000000147101404 libtorch_cpu.dylib`std::__1::basic_ostream<char, std::__1::char_traits<char>>& c10::detail::_str<char const*, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, char const*, char const*>(ss=0x000000016fdfb3a0, t=0x000000016fdfb500, args="index_select_32bit_idx32", args=0x000000016fdfb4f8, args=0x000000016fdfb5d0) at StringUtil.h:68:10 frame #8: 0x000000014710137c libtorch_cpu.dylib`c10::detail::_str_wrapper<char const*, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&, char const*, char const* const&>::call(args=0x000000016fdfb500, args="index_select_32bit_idx32", args=0x000000016fdfb4f8, args=0x000000016fdfb5d0) at StringUtil.h:75:5 frame #9: 0x0000000147101310 libtorch_cpu.dylib`decltype(auto) c10::str<char [53], std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, char [10], char const*>(args={a\xcb\xa7H\x01\0\0\0}, args="index_select_32bit_idx32", args={\x96\xcb\xa7H\x01\0\0\0}, args=0x000000016fdfb5d0) at StringUtil.h:111:10 frame #10: 0x0000000147100210 libtorch_cpu.dylib`decltype(auto) c10::detail::torchCheckMsgImpl<char [53], std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, char [10], char const*>((null)="Expected indexFunction to be true, but got false. (Could this error message be improved? If so, please report an enhancement request to PyTorch.)", args={a\xcb\xa7H\x01\0\0\0}, args="index_select_32bit_idx32", args={\x96\xcb\xa7H\x01\0\0\0}, args=0x000000016fdfb5d0) at Exception.h:453:10 frame #11: 0x00000001470fffe8 libtorch_cpu.dylib`at::mps::MPSDevice::metalIndexingPSO(this=0x0000600000381670, kernel="index_select_32bit_idx32") at MPSDevice.mm:62:3 ``` This was introduced by #99855 that replaced `newFunctionWithName:constantValues:error:` with `newFunctionWithName:` Pull Request resolved: #116938 Approved by: https://github.com/Skylion007

[FSDP] grad scaler: finish TODO

user may not know which line of code called collectives in a big code base. When debugging, we can print python-cpp stacktrace in case user call ``ProcessGroup.reduce`` instead of ``torch.distributed.reduce`` ``` LOG(INFO) << "ProcessGroupNCCL::_allgather_base stacktrace: " << get_python_cpp_trace(); ``` output (using _allgather_base as an example): one example python-part trace is ``all_gather_into_tensor from /data/users/weif/pytorch/torch/distributed/distributed_c10d.py:2838`` ``` ProcessGroupNCCL::_allgather_base stacktrace: #0 torch::unwind::unwind() from ??:0 #1 torch::CapturedTraceback::gather(bool, bool, bool) from ??:0 #2 c10d::get_python_cpp_trace[abi:cxx11]() from :0 #3 c10d::ProcessGroupNCCL::_allgather_base(at::Tensor&, at::Tensor&, c10d::AllgatherOptions const&) from ??:0 #4 c10d::ops::(anonymous namespace)::_allgather_base_CUDA(at::Tensor&, at::Tensor&, c10::intrusive_ptr<c10d::ProcessGroup, c10::detail::intrusive_target_default_null_type<c10d::ProcessGroup> > const&, bool, long) from Ops.cpp:0 #5 c10::impl::make_boxed_from_unboxed_functor<c10::impl::detail::WrapFunctionIntoRuntimeFunctor_<std::tuple<at::Tensor, c10::intrusive_ptr<c10d::Work, c10::detail::intrusive_target_default_null_type<c10d::Work> > > (*)(at::Tensor&, at::Tensor&, c10::intrusive_ptr<c10d::ProcessGroup, c10::detail::intrusive_target_default_null_type<c10d::ProcessGroup> > const&, bool, long), std::tuple<at::Tensor, c10::intrusive_ptr<c10d::Work, c10::detail::intrusive_target_default_null_type<c10d::Work> > >, c10::guts::typelist::typelist<at::Tensor&, at::Tensor&, c10::intrusive_ptr<c10d::ProcessGroup, c10::detail::intrusive_target_default_null_type<c10d::ProcessGroup> > const&, bool, long> >, false>::call(c10::OperatorKernel*, c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) from :0 #6 torch::autograd::basicAutogradNotImplementedFallbackImpl(c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) from autograd_not_implemented_fallback.cpp:0 #7 c10d::ProcessGroup::_allgather_base(at::Tensor&, at::Tensor&, c10d::AllgatherOptions const&) from :0 #8 pybind11::cpp_function::initialize<pybind11::cpp_function::initialize<c10::intrusive_ptr<c10d::Work, c10::detail::intrusive_target_default_null_type<c10d::Work> >, c10d::ProcessGroup, at::Tensor&, at::Tensor&, c10d::AllgatherOptions const&, pybind11::name, pybind11::is_method, pybind11::sibling, pybind11::arg, pybind11::arg, pybind11::arg_v, pybind11::call_guard<pybind11::gil_scoped_release> >(c10::intrusive_ptr<c10d::Work, c10::detail::intrusive_target_default_null_type<c10d::Work> > (c10d::ProcessGroup::*)(at::Tensor&, at::Tensor&, c10d::AllgatherOptions const&), pybind11::name const&, pybind11::is_method const&, pybind11::sibling const&, pybind11::arg const&, pybind11::arg const&, pybind11::arg_v const&, pybind11::call_guard<pybind11::gil_scoped_release> const&)::{lambda(c10d::ProcessGroup*, at::Tensor&, at::Tensor&, c10d::AllgatherOptions const&)#1}, c10::intrusive_ptr<c10d::Work, c10::detail::intrusive_target_default_null_type<c10d::Work> >, c10d::ProcessGroup*, at::Tensor&, at::Tensor&, c10d::AllgatherOptions const&, pybind11::name, pybind11::is_method, pybind11::sibling, pybind11::arg, pybind11::arg, pybind11::arg_v, pybind11::call_guard<pybind11::gil_scoped_release> >(pybind11::cpp_function::initialize<c10::intrusive_ptr<c10d::Work, c10::detail::intrusive_target_default_null_type<c10d::Work> >, c10d::ProcessGroup, at::Tensor&, at::Tensor&, c10d::AllgatherOptions const&, pybind11::name, pybind11::is_method, pybind11::sibling, pybind11::arg, pybind11::arg, pybind11::arg_v, pybind11::call_guard<pybind11::gil_scoped_release> >(c10::intrusive_ptr<c10d::Work, c10::detail::intrusive_target_default_null_type<c10d::Work> > (c10d::ProcessGroup::*)(at::Tensor&, at::Tensor&, c10d::AllgatherOptions const&), pybind11::name const&, pybind11::is_method const&, pybind11::sibling const&, pybind11::arg const&, pybind11::arg const&, pybind11::arg_v const&, pybind11::call_guard<pybind11::gil_scoped_release> const&)::{lambda(c10d::ProcessGroup*, at::Tensor&, at::Tensor&, c10d::AllgatherOptions const&)#1}&&, c10::intrusive_ptr<c10d::Work, c10::detail::intrusive_target_default_null_type<c10d::Work> > (*)(c10d::ProcessGroup*, at::Tensor&, at::Tensor&, c10d::AllgatherOptions const&), pybind11::name const&, pybind11::is_method const&, pybind11::sibling const&, pybind11::arg const&, pybind11::arg const&, pybind11::arg_v const&, pybind11::call_guard<pybind11::gil_scoped_release> const&)::{lambda(pybind11::detail::function_call&)#3}::_FUN(pybind11::detail::function_call&) from :0 #9 pybind11::cpp_function::dispatcher(_object*, _object*, _object*) from :0 #10 cfunction_call from /usr/local/src/conda/python-3.10.12/Objects/methodobject.c:543 #11 _PyObject_MakeTpCall from /usr/local/src/conda/python-3.10.12/Objects/call.c:215 #12 _PyObject_VectorcallTstate from /usr/local/src/conda/python-3.10.12/Include/cpython/abstract.h:112 #13 _PyObject_VectorcallTstate from /usr/local/src/conda/python-3.10.12/Include/cpython/abstract.h:114 #14 all_gather_into_tensor from /data/users/weif/pytorch/torch/distributed/distributed_c10d.py:2838 #15 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #16 do_call_core from /usr/local/src/conda/python-3.10.12/Python/ceval.c:5945 #17 wrapper from /data/users/weif/pytorch/torch/distributed/c10d_logger.py:75 #18 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #19 _PyObject_VectorcallTstate from /usr/local/src/conda/python-3.10.12/Include/cpython/abstract.h:114 #20 _all_gather_flat_param from /data/users/weif/pytorch/torch/distributed/fsdp/_flat_param.py:1399 #21 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #22 _PyObject_VectorcallTstate from /usr/local/src/conda/python-3.10.12/Include/cpython/abstract.h:114 #23 unshard from /data/users/weif/pytorch/torch/distributed/fsdp/_flat_param.py:1308 #24 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #25 _PyObject_VectorcallTstate from /usr/local/src/conda/python-3.10.12/Include/cpython/abstract.h:114 #26 _unshard from /data/users/weif/pytorch/torch/distributed/fsdp/_runtime_utils.py:332 #27 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #28 _PyObject_VectorcallTstate from /usr/local/src/conda/python-3.10.12/Include/cpython/abstract.h:114 #29 _pre_forward_unshard from /data/users/weif/pytorch/torch/distributed/fsdp/_runtime_utils.py:448 #30 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #31 _PyObject_VectorcallTstate from /usr/local/src/conda/python-3.10.12/Include/cpython/abstract.h:114 #32 _pre_forward from /data/users/weif/pytorch/torch/distributed/fsdp/_runtime_utils.py:413 #33 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #34 _PyObject_VectorcallTstate from /usr/local/src/conda/python-3.10.12/Include/cpython/abstract.h:114 #35 forward from /data/users/weif/pytorch/torch/distributed/fsdp/fully_sharded_data_parallel.py:839 #36 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #37 do_call_core from /usr/local/src/conda/python-3.10.12/Python/ceval.c:5945 #38 _call_impl from /data/users/weif/pytorch/torch/nn/modules/module.py:1520 #39 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #40 do_call_core from /usr/local/src/conda/python-3.10.12/Python/ceval.c:5945 #41 _wrapped_call_impl from /data/users/weif/pytorch/torch/nn/modules/module.py:1511 #42 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #43 _PyObject_Call_Prepend from /usr/local/src/conda/python-3.10.12/Objects/call.c:431 #44 slot_tp_call from /usr/local/src/conda/python-3.10.12/Objects/typeobject.c:7494 #45 _PyObject_MakeTpCall from /usr/local/src/conda/python-3.10.12/Objects/call.c:215 #46 _PyObject_VectorcallTstate from /usr/local/src/conda/python-3.10.12/Include/cpython/abstract.h:112 #47 inner from /data/users/weif/pytorch/run_fsdp.py:72 #48 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #49 _PyObject_VectorcallTstate from /usr/local/src/conda/python-3.10.12/Include/cpython/abstract.h:114 #50 run from /data/users/weif/pytorch/run_fsdp.py:76 #51 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #52 _PyObject_VectorcallTstate from /usr/local/src/conda/python-3.10.12/Include/cpython/abstract.h:114 #53 main from /data/users/weif/pytorch/run_fsdp.py:133 #54 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #55 _PyObject_VectorcallTstate from /usr/local/src/conda/python-3.10.12/Include/cpython/abstract.h:114 #56 <module> from /data/users/weif/pytorch/run_fsdp.py:137 #57 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #58 PyEval_EvalCode from /usr/local/src/conda/python-3.10.12/Python/ceval.c:1134 #59 run_eval_code_obj from /usr/local/src/conda/python-3.10.12/Python/pythonrun.c:1291 #60 run_mod from /usr/local/src/conda/python-3.10.12/Python/pythonrun.c:1312 #61 pyrun_file from /usr/local/src/conda/python-3.10.12/Python/pythonrun.c:1208 #62 _PyRun_SimpleFileObject from /usr/local/src/conda/python-3.10.12/Python/pythonrun.c:456 #63 _PyRun_AnyFileObject from /usr/local/src/conda/python-3.10.12/Python/pythonrun.c:90 #64 pymain_run_file_obj from /usr/local/src/conda/python-3.10.12/Modules/main.c:357 #65 Py_BytesMain from /usr/local/src/conda/python-3.10.12/Modules/main.c:1090 #66 __libc_start_call_main from ??:0 #67 <unwind unsupported> from ??:0 ``` Pull Request resolved: #118924 Approved by: https://github.com/kwen2501

user may not know which line of code called collectives in a big code base. When debugging, we can print python-cpp stacktrace in case user call ``ProcessGroup.reduce`` instead of ``torch.distributed.reduce`` ``` LOG(INFO) << "ProcessGroupNCCL::_allgather_base stacktrace: " << get_python_cpp_trace(); ``` output (using _allgather_base as an example): one example python-part trace is ``all_gather_into_tensor from /data/users/weif/pytorch/torch/distributed/distributed_c10d.py:2838`` ``` ProcessGroupNCCL::_allgather_base stacktrace: #0 torch::unwind::unwind() from ??:0 #1 torch::CapturedTraceback::gather(bool, bool, bool) from ??:0 #2 c10d::get_python_cpp_trace[abi:cxx11]() from :0 #3 c10d::ProcessGroupNCCL::_allgather_base(at::Tensor&, at::Tensor&, c10d::AllgatherOptions const&) from ??:0 #4 c10d::ops::(anonymous namespace)::_allgather_base_CUDA(at::Tensor&, at::Tensor&, c10::intrusive_ptr<c10d::ProcessGroup, c10::detail::intrusive_target_default_null_type<c10d::ProcessGroup> > const&, bool, long) from Ops.cpp:0 #5 c10::impl::make_boxed_from_unboxed_functor<c10::impl::detail::WrapFunctionIntoRuntimeFunctor_<std::tuple<at::Tensor, c10::intrusive_ptr<c10d::Work, c10::detail::intrusive_target_default_null_type<c10d::Work> > > (*)(at::Tensor&, at::Tensor&, c10::intrusive_ptr<c10d::ProcessGroup, c10::detail::intrusive_target_default_null_type<c10d::ProcessGroup> > const&, bool, long), std::tuple<at::Tensor, c10::intrusive_ptr<c10d::Work, c10::detail::intrusive_target_default_null_type<c10d::Work> > >, c10::guts::typelist::typelist<at::Tensor&, at::Tensor&, c10::intrusive_ptr<c10d::ProcessGroup, c10::detail::intrusive_target_default_null_type<c10d::ProcessGroup> > const&, bool, long> >, false>::call(c10::OperatorKernel*, c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) from :0 #6 torch::autograd::basicAutogradNotImplementedFallbackImpl(c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) from autograd_not_implemented_fallback.cpp:0 #7 c10d::ProcessGroup::_allgather_base(at::Tensor&, at::Tensor&, c10d::AllgatherOptions const&) from :0 #8 pybind11::cpp_function::initialize<pybind11::cpp_function::initialize<c10::intrusive_ptr<c10d::Work, c10::detail::intrusive_target_default_null_type<c10d::Work> >, c10d::ProcessGroup, at::Tensor&, at::Tensor&, c10d::AllgatherOptions const&, pybind11::name, pybind11::is_method, pybind11::sibling, pybind11::arg, pybind11::arg, pybind11::arg_v, pybind11::call_guard<pybind11::gil_scoped_release> >(c10::intrusive_ptr<c10d::Work, c10::detail::intrusive_target_default_null_type<c10d::Work> > (c10d::ProcessGroup::*)(at::Tensor&, at::Tensor&, c10d::AllgatherOptions const&), pybind11::name const&, pybind11::is_method const&, pybind11::sibling const&, pybind11::arg const&, pybind11::arg const&, pybind11::arg_v const&, pybind11::call_guard<pybind11::gil_scoped_release> const&)::{lambda(c10d::ProcessGroup*, at::Tensor&, at::Tensor&, c10d::AllgatherOptions const&)#1}, c10::intrusive_ptr<c10d::Work, c10::detail::intrusive_target_default_null_type<c10d::Work> >, c10d::ProcessGroup*, at::Tensor&, at::Tensor&, c10d::AllgatherOptions const&, pybind11::name, pybind11::is_method, pybind11::sibling, pybind11::arg, pybind11::arg, pybind11::arg_v, pybind11::call_guard<pybind11::gil_scoped_release> >(pybind11::cpp_function::initialize<c10::intrusive_ptr<c10d::Work, c10::detail::intrusive_target_default_null_type<c10d::Work> >, c10d::ProcessGroup, at::Tensor&, at::Tensor&, c10d::AllgatherOptions const&, pybind11::name, pybind11::is_method, pybind11::sibling, pybind11::arg, pybind11::arg, pybind11::arg_v, pybind11::call_guard<pybind11::gil_scoped_release> >(c10::intrusive_ptr<c10d::Work, c10::detail::intrusive_target_default_null_type<c10d::Work> > (c10d::ProcessGroup::*)(at::Tensor&, at::Tensor&, c10d::AllgatherOptions const&), pybind11::name const&, pybind11::is_method const&, pybind11::sibling const&, pybind11::arg const&, pybind11::arg const&, pybind11::arg_v const&, pybind11::call_guard<pybind11::gil_scoped_release> const&)::{lambda(c10d::ProcessGroup*, at::Tensor&, at::Tensor&, c10d::AllgatherOptions const&)#1}&&, c10::intrusive_ptr<c10d::Work, c10::detail::intrusive_target_default_null_type<c10d::Work> > (*)(c10d::ProcessGroup*, at::Tensor&, at::Tensor&, c10d::AllgatherOptions const&), pybind11::name const&, pybind11::is_method const&, pybind11::sibling const&, pybind11::arg const&, pybind11::arg const&, pybind11::arg_v const&, pybind11::call_guard<pybind11::gil_scoped_release> const&)::{lambda(pybind11::detail::function_call&)#3}::_FUN(pybind11::detail::function_call&) from :0 #9 pybind11::cpp_function::dispatcher(_object*, _object*, _object*) from :0 #10 cfunction_call from /usr/local/src/conda/python-3.10.12/Objects/methodobject.c:543 #11 _PyObject_MakeTpCall from /usr/local/src/conda/python-3.10.12/Objects/call.c:215 #12 _PyObject_VectorcallTstate from /usr/local/src/conda/python-3.10.12/Include/cpython/abstract.h:112 #13 _PyObject_VectorcallTstate from /usr/local/src/conda/python-3.10.12/Include/cpython/abstract.h:114 #14 all_gather_into_tensor from /data/users/weif/pytorch/torch/distributed/distributed_c10d.py:2838 #15 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #16 do_call_core from /usr/local/src/conda/python-3.10.12/Python/ceval.c:5945 #17 wrapper from /data/users/weif/pytorch/torch/distributed/c10d_logger.py:75 #18 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #19 _PyObject_VectorcallTstate from /usr/local/src/conda/python-3.10.12/Include/cpython/abstract.h:114 #20 _all_gather_flat_param from /data/users/weif/pytorch/torch/distributed/fsdp/_flat_param.py:1399 #21 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #22 _PyObject_VectorcallTstate from /usr/local/src/conda/python-3.10.12/Include/cpython/abstract.h:114 #23 unshard from /data/users/weif/pytorch/torch/distributed/fsdp/_flat_param.py:1308 #24 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #25 _PyObject_VectorcallTstate from /usr/local/src/conda/python-3.10.12/Include/cpython/abstract.h:114 #26 _unshard from /data/users/weif/pytorch/torch/distributed/fsdp/_runtime_utils.py:332 #27 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #28 _PyObject_VectorcallTstate from /usr/local/src/conda/python-3.10.12/Include/cpython/abstract.h:114 #29 _pre_forward_unshard from /data/users/weif/pytorch/torch/distributed/fsdp/_runtime_utils.py:448 #30 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #31 _PyObject_VectorcallTstate from /usr/local/src/conda/python-3.10.12/Include/cpython/abstract.h:114 #32 _pre_forward from /data/users/weif/pytorch/torch/distributed/fsdp/_runtime_utils.py:413 #33 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #34 _PyObject_VectorcallTstate from /usr/local/src/conda/python-3.10.12/Include/cpython/abstract.h:114 #35 forward from /data/users/weif/pytorch/torch/distributed/fsdp/fully_sharded_data_parallel.py:839 #36 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #37 do_call_core from /usr/local/src/conda/python-3.10.12/Python/ceval.c:5945 #38 _call_impl from /data/users/weif/pytorch/torch/nn/modules/module.py:1520 #39 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #40 do_call_core from /usr/local/src/conda/python-3.10.12/Python/ceval.c:5945 #41 _wrapped_call_impl from /data/users/weif/pytorch/torch/nn/modules/module.py:1511 #42 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #43 _PyObject_Call_Prepend from /usr/local/src/conda/python-3.10.12/Objects/call.c:431 #44 slot_tp_call from /usr/local/src/conda/python-3.10.12/O F438 bjects/typeobject.c:7494 #45 _PyObject_MakeTpCall from /usr/local/src/conda/python-3.10.12/Objects/call.c:215 #46 _PyObject_VectorcallTstate from /usr/local/src/conda/python-3.10.12/Include/cpython/abstract.h:112 #47 inner from /data/users/weif/pytorch/run_fsdp.py:72 #48 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #49 _PyObject_VectorcallTstate from /usr/local/src/conda/python-3.10.12/Include/cpython/abstract.h:114 #50 run from /data/users/weif/pytorch/run_fsdp.py:76 #51 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #52 _PyObject_VectorcallTstate from /usr/local/src/conda/python-3.10.12/Include/cpython/abstract.h:114 #53 main from /data/users/weif/pytorch/run_fsdp.py:133 #54 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #55 _PyObject_VectorcallTstate from /usr/local/src/conda/python-3.10.12/Include/cpython/abstract.h:114 #56 <module> from /data/users/weif/pytorch/run_fsdp.py:137 #57 _PyEval_EvalFrame from /usr/local/src/conda/python-3.10.12/Include/internal/pycore_ceval.h:46 #58 PyEval_EvalCode from /usr/local/src/conda/python-3.10.12/Python/ceval.c:1134 #59 run_eval_code_obj from /usr/local/src/conda/python-3.10.12/Python/pythonrun.c:1291 #60 run_mod from /usr/local/src/conda/python-3.10.12/Python/pythonrun.c:1312 #61 pyrun_file from /usr/local/src/conda/python-3.10.12/Python/pythonrun.c:1208 #62 _PyRun_SimpleFileObject from /usr/local/src/conda/python-3.10.12/Python/pythonrun.c:456 #63 _PyRun_AnyFileObject from /usr/local/src/conda/python-3.10.12/Python/pythonrun.c:90 #64 pymain_run_file_obj from /usr/local/src/conda/python-3.10.12/Modules/main.c:357 #65 Py_BytesMain from /usr/local/src/conda/python-3.10.12/Modules/main.c:1090 #66 __libc_start_call_main from ??:0 #67 <unwind unsupported> from ??:0 ``` Pull Request resolved: #118924 Approved by: https://github.com/kwen2501

#120243) This reverts commit cc7ef43. Manual revert because of the conflict in: test/inductor/test_cpu_repro.py , conflict with this PR: #118365 Pull Request resolved: #120243 Approved by: https://github.com/malfet, https://github.com/huydhn

#126677) …destruction of tensors cached by autocast ## Root Cause For out-of-tree device extension it is loaded after torch (different .so), so the global variable `cached_casts` may be constructed before caching allocator and then destructed in reversed order when exit. ## Fix Lazily initialize `cached_casts` to correct the order. ## How to Reproduce && Test Modify the testcase `TestAutocastGPU.test_cast_cache_is_global` in test/test_autocast.py to run on your out-of-tree device. You will see following failure in the end of test. ```bash ---------------------------------------------------------------------- Ran 1 test in 4.812s OK free: 0x30080ff44000400 terminate called after throwing an instance of 'c10::Error' what(): invalid device pointer: 0x30080ff44000400 Exception raised from free at /projs/framework/betterman/code/pytorch_new/catch/torch_mlu/csrc/framework/core/caching_allocator.cpp:1609 (most recent call first): frame #0: <unknown function> + 0x118fe1 (0x7ffaef4d3fe1 in /projs/framework/betterman/code/pytorch_new/torch/lib/libc10.so) frame #1: <unknown function> + 0x11b1c4 (0x7ffaef4d61c4 in /projs/framework/betterman/code/pytorch_new/torch/lib/libc10.so) frame #2: <unknown function> + 0x117677 (0x7ffaef4d2677 in /projs/framework/betterman/code/pytorch_new/torch/lib/libc10.so) frame #3: <unknown function> + 0x11a2bf (0x7ffaef4d52bf in /projs/framework/betterman/code/pytorch_new/torch/lib/libc10.so) frame #4: <unknown function> + 0x11a186 (0x7ffaef4d5186 in /projs/framework/betterman/code/pytorch_new/torch/lib/libc10.so) frame #5: <unknown function> + 0x119fde (0x7ffaef4d4fde in /projs/framework/betterman/code/pytorch_new/torch/lib/libc10.so) frame #6: <unknown function> + 0x119d2e (0x7ffaef4d4d2e in /projs/framework/betterman/code/pytorch_new/torch/lib/libc10.so) frame #7: <unknown function> + 0x119be0 (0x7ffaef4d4be0 in /projs/framework/betterman/code/pytorch_new/torch/lib/libc10.so) frame #8: <unknown function> + 0x119977 (0x7ffaef4d4977 in /projs/framework/betterman/code/pytorch_new/torch/lib/libc10.so) frame #9: <unknown function> + 0x119313 (0x7ffaef4d4313 in /projs/framework/betterman/code/pytorch_new/torch/lib/libc10.so) frame #10: <unknown function> + 0x118b4c (0x7ffaef4d3b4c in /projs/framework/betterman/code/pytorch_new/torch/lib/libc10.so) frame #11: c10::Error::Error(c10::SourceLocation, std::string) + 0x34 (0x7ffaef4d27c4 in /projs/framework/betterman/code/pytorch_new/torch/lib/libc10.so) frame #12: c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::string const&) + 0x7f (0x7ffaef4d04ed in /projs/framework/betterman/code/pytorch_new/torch/lib/libc10.so) frame #13: torch_mlu::MLUCachingAllocator::Native::NativeCachingAllocator::free(void*) + 0xe6 (0x7ff9a8eeb112 in /projs/framework/betterman/code/pytorch_new/catch/torch_mlu/csrc/lib/libtorch_mlu.so) frame #14: torch_mlu::MLUCachingAllocator::Native::local_raw_delete(void*) + 0x3b (0x7ff9a8ed9480 in /projs/framework/betterman/code/pytorch_new/catch/torch_mlu/csrc/lib/libtorch_mlu.so) frame #15: std::unique_ptr<void, void (*)(void*)>::~unique_ptr() + 0x50 (0x7ffb0a5ea322 in /projs/framework/betterman/code/pytorch_new/torch/lib/libtorch_python.so) frame #16: <unknown function> + 0x1269890 (0x7ffb0a5e4890 in /projs/framework/betterman/code/pytorch_new/torch/lib/libtorch_python.so) frame #17: <unknown function> + 0x1269928 (0x7ffb0a5e4928 in /projs/framework/betterman/code/pytorch_new/torch/lib/libtorch_python.so) frame #18: <unknown function> + 0x127572c (0x7ffb0a5f072c in /projs/framework/betterman/code/pytorch_new/torch/lib/libtorch_python.so) frame #19: <unknown function> + 0x1275758 (0x7ffb0a5f0758 in /projs/framework/betterman/code/pytorch_new/torch/lib/libtorch_python.so) frame #20: <unknown function> + 0xb9bc7 (0x7ffaef474bc7 in /projs/framework/betterman/code/pytorch_new/torch/lib/libc10.so) frame #21: <unknown function> + 0xb97bc (0x7ffaef4747bc in /projs/framework/betterman/code/pytorch_new/torch/lib/libc10.so) frame #22: <unknown function> + 0xdbc50 (0x7ffaef496c50 in /projs/framework/betterman/code/pytorch_new/torch/lib/libc10.so) frame #23: c10::TensorImpl::~TensorImpl() + 0x82 (0x7ffaef49157e in /projs/framework/betterman/code/pytorch_new/torch/lib/libc10.so) frame #24: c10::TensorImpl::~TensorImpl() + 0x1c (0x7ffaef4915aa in /projs/framework/betterman/code/pytorch_new/torch/lib/libc10.so) frame #25: <unknown function> + 0x2f596d9 (0x7ffaf24fc6d9 in /projs/framework/betterman/code/pytorch_new/torch/lib/libtorch_cpu.so) frame #26: <unknown function> + 0x2f589c2 (0x7ffaf24fb9c2 in /projs/framework/betterman/code/pytorch_new/torch/lib/libtorch_cpu.so) frame #27: <unknown function> + 0x2f57b92 (0x7ffaf24fab92 in /projs/framework/betterman/code/pytorch_new/torch/lib/libtorch_cpu.so) frame #28: <unknown function> + 0x2f5c228 (0x7ffaf24ff228 in /projs/framework/betterman/code/pytorch_new/torch/lib/libtorch_cpu.so) frame #29: <unknown function> + 0x30f3f70 (0x7ffaf2696f70 in /projs/framework/betterman/code/pytorch_new/torch/lib/libtorch_cpu.so) frame #30: <unknown function> + 0x30f3f90 (0x7ffaf2696f90 in /projs/framework/betterman/code/pytorch_new/torch/lib/libtorch_cpu.so) frame #31: <unknown function> + 0x30f5004 (0x7ffaf2698004 in /projs/framework/betterman/code/pytorch_new/torch/lib/libtorch_cpu.so) frame #32: <unknown function> + 0x30f5024 (0x7ffaf2698024 in /projs/framework/betterman/code/pytorch_new/torch/lib/libtorch_cpu.so) frame #33: <unknown function> + 0x31207f0 (0x7ffaf26c37f0 in /projs/framework/betterman/code/pytorch_new/torch/lib/libtorch_cpu.so) frame #34: <unknown function> + 0x3120814 (0x7ffaf26c3814 in /projs/framework/betterman/code/pytorch_new/torch/lib/libtorch_cpu.so) frame #35: <unknown function> + 0x30f51e8 (0x7ffaf26981e8 in /projs/framework/betterman/code/pytorch_new/torch/lib/libtorch_cpu.so) frame #36: <unknown function> + 0x30f5148 (0x7ffaf2698148 in /projs/framework/betterman/code/pytorch_new/torch/lib/libtorch_cpu.so) frame #37: <unknown function> + 0x316ecea (0x7ffaf2711cea in /projs/framework/betterman/code/pytorch_new/torch/lib/libtorch_cpu.so) frame #38: <unknown function> + 0x468a7 (0x7ffb0c9ed8a7 in /lib/x86_64-linux-gnu/libc.so.6) frame #39: on_exit + 0 (0x7ffb0c9eda60 in /lib/x86_64-linux-gnu/libc.so.6) <omitting python frames> frame #47: __libc_start_main + 0xf3 (0x7ffb0c9cb083 in /lib/x86_64-linux-gnu/libc.so.6) Aborted (core dumped) ``` Pull Request resolved: #126677 Approved by: https://github.com/ezyang

This does a round trip request on socket connect -- this allows for detecting connection resets etc and retrying before the non-retryable application requests are sent. This adds support for PING to both the libuv and legacy backend. Example error: ``` [trainer85612|12]:W0701 13:41:43.421574 4776 TCPStore.cpp:182] [c10d] recvValue failed on SocketImpl(fd=24, ...): Connection reset by peer [trainer85612|12]:Exception raised from recvBytes at /mnt/code/pytorch/torch/csrc/distributed/c10d/Utils.hpp:669 (most recent call first): ... [trainer85612|12]:#9 c10d::TCPStore::incrementValueBy(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, long) from /packages/.../conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so:84809637 [trainer85612|12]:#10 c10d::TCPStore::waitForWorkers() from /packages/.../conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so:84812868 [trainer85612|12]:#11 c10d::TCPStore::TCPStore(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, c10d::TCPStoreOptions const&) from /packages/.../conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so:84814775 ``` Test plan: ``` python test/distributed/test_store.py -v ``` ``` tristanr@devvm4382 ~/pytorch (d4l3k/tcpstore_ping)> python ~/pt_tests/tcpstore_large_test.py starting pool started 90000 started 30000 started 70000 started 20000 started 80000 started 60000 started 0 [W702 16:16:25.301681870 TCPStore.cpp:343] [c10d] Starting store with 100000 workers but somaxconn is 4096.This might cause instability during bootstrap, consider increasing it. init 20000 set 20000 init 80000 set 80000 init 70000 set 70000 init 60000 set 60000 init 30000 set 30000 init 90000 set 90000 started 40000 init 40000 set 40000 started 50000 init 50000 set 50000 started 10000 init 10000 set 10000 init 0 set 0 run finished 617.2992351055145 ``` Pull Request resolved: #129985 Approved by: https://github.com/rsdcastro, https://github.com/kurman

========= COMPUTE-SANITIZER Test completed successfully! ========= ERROR SUMMARY: 0 errors ## NOTE: HMM very interestingly: If the og_headdim is a odd this works as expected. However when the og_head_dim is a multiple of 2 this segfaults here: ```Shell (lldb) bt * thread #67, name = 'pt_autograd_0', stop reason = signal SIGSEGV: address not mapped to object (fault address: 0x10) * frame #0: 0x00007ffed327fbfe libtriton.so`scheduleRemainingToLastStage(forOp=ForOp @ 0x00007ffcafdfd658, schedule=0x00007ffcafdfd9e0, afterPrologue=<unavailable>, numStages=2) at MatmulLoopPipeline.cpp:893:9 frame #1: 0x00007ffed328d970 libtriton.so`mlir::triton::preProcessLoopAndGetSchedule(forOp=0x00007ffcafdfddc0, numStages=2, options=0x00007ffcafdfde80) at MatmulLoopPipeline.cpp:1230:31 frame #2: 0x00007ffed32a6a43 libtriton.so`mlir::triton::gpu::PipelinePass::runOnOperation() [inlined] pipelineLoop(numStages=2, forOp=ForOp @ 0x00007ffcafdfddc0) at SoftwarePipeliner.cpp:79:47 frame #3: 0x00007ffed32a6998 libtriton.so`mlir::triton::gpu::PipelinePass::runOnOperation(this=0x00007ffc54767f10) at SoftwarePipeliner.cpp:125:36 frame #4: 0x00007ffed385147c libtriton.so`mlir::detail::OpToOpPassAdaptor::run(mlir::Pass*, mlir::Operation*, mlir::AnalysisManager, bool, unsigned int) + 700 frame #5: 0x00007ffed3851df2 libtriton.so`mlir::detail::OpToOpPassAdaptor::runPipeline(mlir::OpPassManager&, mlir::Operation*, mlir::AnalysisManager, bool, unsigned int, mlir::PassInstrumentor*, mlir::PassInstrumentation::PipelineParentInfo const*) + 354 frame #6: 0x00007ffed385481c libtriton.so`mlir::PassManager::run(mlir::Operation*) + 876 frame #7: 0x00007ffed3542bad libtriton.so`<lambda(mlir::PassManager&, mlir::ModuleOp&)>::operator(self=<unavailable>, mod=0x00007ffc54579280, __closure=<unavailable>)(mlir::PassManager &, mlir::ModuleOp &) at ir.cc:1625:19 frame #8: 0x00007ffed3560108 libtriton.so`_FUN [inlined] operator(this=0x0000000000000000, call=0x00007ffcafdfe6e0) at cast.h:1480:37 frame #9: 0x00007ffed35600f0 libtriton.so`_FUN((null)=0x00007ffcafdfe6e0) at pybind11.h:224:21 frame #10: 0x00007ffed9ae5590 libtriton.so`typeinfo for pybind11::handle + 24 frame #11: 0x00007ffed9ae5590 libtriton.so`typeinfo for pybind11::handle + 24 ``` cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv jiayisunx ipiszy yf225 chenyang78 kadeng muchulee8 ColinPeppler amjames desertfire chauhang [ghstack-poisoned]

See #140725 (comment) Running `torch.mps.synchronize()` after metal kernel resulted in infinite wait inside `[_MTLCommandBuffer waitUntilCompleted]` ``` (lldb) bt * thread #1, queue = 'com.apple.main-thread', stop reason = signal SIGSTOP * frame #0: 0x00000001aa919084 Metal`pthread_cond_wait + 12 frame #1: 0x00000001aa78b1b4 Metal`-[_MTLCommandBuffer waitUntilCompleted] + 84 frame #2: 0x00000001032bf358 libtorch_python.dylib`torch::mps::MPSModule_deviceSynchronize(_object*, _object*) + 40 frame #3: 0x0000000100e94c20 Python`cfunction_vectorcall_NOARGS + 100 frame #4: 0x0000000100e389b8 Python`PyObject_Vectorcall + 92 frame #5: 0x0000000100f61e38 Python`_PyEval_EvalFrameDefault + 19040 frame #6: 0x0000000100f5d180 Python`PyEval_EvalCode + 200 frame #7: 0x0000000100fcd1a4 Python`run_eval_code_obj + 104 frame #8: 0x0000000100fccbe4 Python`run_mod + 168 frame #9: 0x0000000100fcb518 Python`pyrun_file + 164 frame #10: 0x0000000100fca854 Python`_PyRun_SimpleFileObject + 256 frame #11: 0x0000000100fca4e8 Python`_PyRun_AnyFileObject + 80 frame #12: 0x0000000100ff2028 Python`pymain_run_file_obj + 164 frame #13: 0x0000000100ff1ce4 Python`pymain_run_file + 72 frame #14: 0x0000000100ff0f74 Python`Py_RunMain + 988 frame #15: 0x0000000100ff1564 Python`pymain_main + 304 frame #16: 0x0000000100ff1604 Python`Py_BytesMain + 40 frame #17: 0x000000019f630274 dyld`start + 2840 ``` Pull Request resolved: #141296 Approved by: https://github.com/huydhn

See pytorch#140725 (comment) Running `torch.mps.synchronize()` after metal kernel resulted in infinite wait inside `[_MTLCommandBuffer waitUntilCompleted]` ``` (lldb) bt * thread pytorch#1, queue = 'com.apple.main-thread', stop reason = signal SIGSTOP * frame #0: 0x00000001aa919084 Metal`pthread_cond_wait + 12 frame pytorch#1: 0x00000001aa78b1b4 Metal`-[_MTLCommandBuffer waitUntilCompleted] + 84 frame pytorch#2: 0x00000001032bf358 libtorch_python.dylib`torch::mps::MPSModule_deviceSynchronize(_object*, _object*) + 40 frame pytorch#3: 0x0000000100e94c20 Python`cfunction_vectorcall_NOARGS + 100 frame pytorch#4: 0x0000000100e389b8 Python`PyObject_Vectorcall + 92 frame pytorch#5: 0x0000000100f61e38 Python`_PyEval_EvalFrameDefault + 19040 frame pytorch#6: 0x0000000100f5d180 Python`PyEval_EvalCode + 200 frame pytorch#7: 0x0000000100fcd1a4 Python`run_eval_code_obj + 104 frame pytorch#8: 0x0000000100fccbe4 Python`run_mod + 168 frame pytorch#9: 0x0000000100fcb518 Python`pyrun_file + 164 frame pytorch#10: 0x0000000100fca854 Python`_PyRun_SimpleFileObject + 256 frame pytorch#11: 0x0000000100fca4e8 Python`_PyRun_AnyFileObject + 80 frame pytorch#12: 0x0000000100ff2028 Python`pymain_run_file_obj + 164 frame pytorch#13: 0x0000000100ff1ce4 Python`pymain_run_file + 72 frame pytorch#14: 0x0000000100ff0f74 Python`Py_RunMain + 988 frame pytorch#15: 0x0000000100ff1564 Python`pymain_main + 304 frame pytorch#16: 0x0000000100ff1604 Python`Py_BytesMain + 40 frame pytorch#17: 0x000000019f630274 dyld`start + 2840 ``` Pull Request resolved: pytorch#141296 Approved by: https://github.com/huydhn

…r_buf_pr Support multiple other buffers for score and mask

See pytorch#140725 (comment) Running `torch.mps.synchronize()` after metal kernel resulted in infinite wait inside `[_MTLCommandBuffer waitUntilCompleted]` ``` (lldb) bt * thread pytorch#1, queue = 'com.apple.main-thread', stop reason = signal SIGSTOP * frame #0: 0x00000001aa919084 Metal`pthread_cond_wait + 12 frame pytorch#1: 0x00000001aa78b1b4 Metal`-[_MTLCommandBuffer waitUntilCompleted] + 84 frame pytorch#2: 0x00000001032bf358 libtorch_python.dylib`torch::mps::MPSModule_deviceSynchronize(_object*, _object*) + 40 frame pytorch#3: 0x0000000100e94c20 Python`cfunction_vectorcall_NOARGS + 100 frame pytorch#4: 0x0000000100e389b8 Python`PyObject_Vectorcall + 92 frame pytorch#5: 0x0000000100f61e38 Python`_PyEval_EvalFrameDefault + 19040 frame pytorch#6: 0x0000000100f5d180 Python`PyEval_EvalCode + 200 frame pytorch#7: 0x0000000100fcd1a4 Python`run_eval_code_obj + 104 frame pytorch#8: 0x0000000100fccbe4 Python`run_mod + 168 frame pytorch#9: 0x0000000100fcb518 Python`pyrun_file + 164 frame pytorch#10: 0x0000000100fca854 Python`_PyRun_SimpleFileObject + 256 frame pytorch#11: 0x0000000100fca4e8 Python`_PyRun_AnyFileObject + 80 frame pytorch#12: 0x0000000100ff2028 Python`pymain_run_file_obj + 164 frame pytorch#13: 0x0000000100ff1ce4 Python`pymain_run_file + 72 frame pytorch#14: 0x0000000100ff0f74 Python`Py_RunMain + 988 frame pytorch#15: 0x0000000100ff1564 Python`pymain_main + 304 frame pytorch#16: 0x0000000100ff1604 Python`Py_BytesMain + 40 frame pytorch#17: 0x000000019f630274 dyld`start + 2840 ``` Pull Request resolved: pytorch#141296 Approved by: https://github.com/huydhn

See pytorch#140725 (comment) Running `torch.mps.synchronize()` after metal kernel resulted in infinite wait inside `[_MTLCommandBuffer waitUntilCompleted]` ``` (lldb) bt * thread #1, queue = 'com.apple.main-thread', stop reason = signal SIGSTOP * frame #0: 0x00000001aa919084 Metal`pthread_cond_wait + 12 frame #1: 0x00000001aa78b1b4 Metal`-[_MTLCommandBuffer waitUntilCompleted] + 84 frame pytorch#2: 0x00000001032bf358 libtorch_python.dylib`torch::mps::MPSModule_deviceSynchronize(_object*, _object*) + 40 frame pytorch#3: 0x0000000100e94c20 Python`cfunction_vectorcall_NOARGS + 100 frame pytorch#4: 0x0000000100e389b8 Python`PyObject_Vectorcall + 92 frame pytorch#5: 0x0000000100f61e38 Python`_PyEval_EvalFrameDefault + 19040 frame pytorch#6: 0x0000000100f5d180 Python`PyEval_EvalCode + 200 frame pytorch#7: 0x0000000100fcd1a4 Python`run_eval_code_obj + 104 frame pytorch#8: 0x0000000100fccbe4 Python`run_mod + 168 frame pytorch#9: 0x0000000100fcb518 Python`pyrun_file + 164 frame pytorch#10: 0x0000000100fca854 Python`_PyRun_SimpleFileObject + 256 frame pytorch#11: 0x0000000100fca4e8 Python`_PyRun_AnyFileObject + 80 frame pytorch#12: 0x0000000100ff2028 Python`pymain_run_file_obj + 164 frame pytorch#13: 0x0000000100ff1ce4 Python`pymain_run_file + 72 frame pytorch#14: 0x0000000100ff0f74 Python`Py_RunMain + 988 frame pytorch#15: 0x0000000100ff1564 Python`pymain_main + 304 frame pytorch#16: 0x0000000100ff1604 Python`Py_BytesMain + 40 frame pytorch#17: 0x000000019f630274 dyld`start + 2840 ``` Pull Request resolved: pytorch#141296 Approved by: https://github.com/huydhn

…ention" Thanks to manman-ren who verified that triton-lang/triton#4247 fixes this issue as well. This is not currently cherry-picked into pytorch-triton. ========= COMPUTE-SANITIZER Test completed successfully! ========= ERROR SUMMARY: 0 errors ## NOTE: HMM very interestingly: If the og_headdim is a odd this works as expected. However when the og_head_dim is a multiple of 2 this segfaults here: ```Shell (lldb) bt * thread #67, name = 'pt_autograd_0', stop reason = signal SIGSEGV: address not mapped to object (fault address: 0x10) * frame #0: 0x00007ffed327fbfe libtriton.so`scheduleRemainingToLastStage(forOp=ForOp @ 0x00007ffcafdfd658, schedule=0x00007ffcafdfd9e0, afterPrologue=<unavailable>, numStages=2) at MatmulLoopPipeline.cpp:893:9 frame #1: 0x00007ffed328d970 libtriton.so`mlir::triton::preProcessLoopAndGetSchedule(forOp=0x00007ffcafdfddc0, numStages=2, options=0x00007ffcafdfde80) at MatmulLoopPipeline.cpp:1230:31 frame #2: 0x00007ffed32a6a43 libtriton.so`mlir::triton::gpu::PipelinePass::runOnOperation() [inlined] pipelineLoop(numStages=2, forOp=ForOp @ 0x00007ffcafdfddc0) at SoftwarePipeliner.cpp:79:47 frame #3: 0x00007ffed32a6998 libtriton.so`mlir::triton::gpu::PipelinePass::runOnOperation(this=0x00007ffc54767f10) at SoftwarePipeliner.cpp:125:36 frame #4: 0x00007ffed385147c libtriton.so`mlir::detail::OpToOpPassAdaptor::run(mlir::Pass*, mlir::Operation*, mlir::AnalysisManager, bool, unsigned int) + 700 frame #5: 0x00007ffed3851df2 libtriton.so`mlir::detail::OpToOpPassAdaptor::runPipeline(mlir::OpPassManager&, mlir::Operation*, mlir::AnalysisManager, bool, unsigned int, mlir::PassInstrumentor*, mlir::PassInstrumentation::PipelineParentInfo const*) + 354 frame #6: 0x00007ffed385481c libtriton.so`mlir::PassManager::run(mlir::Operation*) + 876 frame #7: 0x00007ffed3542bad libtriton.so`<lambda(mlir::PassManager&, mlir::ModuleOp&)>::operator(self=<unavailable>, mod=0x00007ffc54579280, __closure=<unavailable>)(mlir::PassManager &, mlir::ModuleOp &) at ir.cc:1625:19 frame #8: 0x00007ffed3560108 libtriton.so`_FUN [inlined] operator(this=0x0000000000000000, call=0x00007ffcafdfe6e0) at cast.h:1480:37 frame #9: 0x00007ffed35600f0 libtriton.so`_FUN((null)=0x00007ffcafdfe6e0) at pybind11.h:224:21 frame #10: 0x00007ffed9ae5590 libtriton.so`typeinfo for pybind11::handle + 24 frame #11: 0x00007ffed9ae5590 libtriton.so`typeinfo for pybind11::handle + 24 ``` cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv jiayisunx ipiszy yf225 chenyang78 kadeng muchulee8 ColinPeppler amjames desertfire chauhang aakhundov [ghstack-poisoned]

Thanks to manman-ren who verified that triton-lang/triton#4247 fixes this issue as well. T 4D32 his is not currently cherry-picked into pytorch-triton. ========= COMPUTE-SANITIZER Test completed successfully! ========= ERROR SUMMARY: 0 errors ## NOTE: HMM very interestingly: If the og_headdim is a odd this works as expected. However when the og_head_dim is a multiple of 2 this segfaults here: ```Shell (lldb) bt * thread #67, name = 'pt_autograd_0', stop reason = signal SIGSEGV: address not mapped to object (fault address: 0x10) * frame #0: 0x00007ffed327fbfe libtriton.so`scheduleRemainingToLastStage(forOp=ForOp @ 0x00007ffcafdfd658, schedule=0x00007ffcafdfd9e0, afterPrologue=<unavailable>, numStages=2) at MatmulLoopPipeline.cpp:893:9 frame #1: 0x00007ffed328d970 libtriton.so`mlir::triton::preProcessLoopAndGetSchedule(forOp=0x00007ffcafdfddc0, numStages=2, options=0x00007ffcafdfde80) at MatmulLoopPipeline.cpp:1230:31 frame #2: 0x00007ffed32a6a43 libtriton.so`mlir::triton::gpu::PipelinePass::runOnOperation() [inlined] pipelineLoop(numStages=2, forOp=ForOp @ 0x00007ffcafdfddc0) at SoftwarePipeliner.cpp:79:47 frame #3: 0x00007ffed32a6998 libtriton.so`mlir::triton::gpu::PipelinePass::runOnOperation(this=0x00007ffc54767f10) at SoftwarePipeliner.cpp:125:36 frame #4: 0x00007ffed385147c libtriton.so`mlir::detail::OpToOpPassAdaptor::run(mlir::Pass*, mlir::Operation*, mlir::AnalysisManager, bool, unsigned int) + 700 frame #5: 0x00007ffed3851df2 libtriton.so`mlir::detail::OpToOpPassAdaptor::runPipeline(mlir::OpPassManager&, mlir::Operation*, mlir::AnalysisManager, bool, unsigned int, mlir::PassInstrumentor*, mlir::PassInstrumentation::PipelineParentInfo const*) + 354 frame #6: 0x00007ffed385481c libtriton.so`mlir::PassManager::run(mlir::Operation*) + 876 frame #7: 0x00007ffed3542bad libtriton.so`<lambda(mlir::PassManager&, mlir::ModuleOp&)>::operator(self=<unavailable>, mod=0x00007ffc54579280, __closure=<unavailable>)(mlir::PassManager &, mlir::ModuleOp &) at ir.cc:1625:19 frame #8: 0x00007ffed3560108 libtriton.so`_FUN [inlined] operator(this=0x0000000000000000, call=0x00007ffcafdfe6e0) at cast.h:1480:37 frame #9: 0x00007ffed35600f0 libtriton.so`_FUN((null)=0x00007ffcafdfe6e0) at pybind11.h:224:21 frame #10: 0x00007ffed9ae5590 libtriton.so`typeinfo for pybind11::handle + 24 frame #11: 0x00007ffed9ae5590 libtriton.so`typeinfo for pybind11::handle + 24 ``` cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv jiayisunx ipiszy yf225 chenyang78 kadeng muchulee8 ColinPeppler amjames desertfire chauhang aakhundov [ghstack-poisoned]

Summary: Fix memory leak on shutdown when socket is closed. We still need to free the buffer to make valgrind happy. Test Plan: Use `mtiavm`. Repro steps provided by cristianlume. 1. Build ``` buck2 run //mtia/vm:athena-amodel-usd-owl-rank- 2. Run 2 VMs on window 1: ``` mtiavm ssh --vm=0 -- $(buck run @//neteng/ai/rdma_gen/mode/owl //neteng/ai/rdma_gen:rdma_gen --emit-shell) --rdma_mod A95D e=mtiav1 --num_ranks=2 on window 2: ```` mtiavm ssh --vm=1 -- $(buck run @//neteng/ai/rdma_gen/mode/owl //neteng/ai/rdma_gen:rdma_gen --emit-shell) --rdma_mode=mtiav1 --num_ranks=2 --rank=1 --store_host=172.16.1.1 ``` without the fix: ``` ==8766==ERROR: LeakSanitizer: detected memory leaks Direct leak of 8000 byte(s) in 2 object(s) allocated from: #0 0x5696fe in malloc (/data/users/cpio/fbsource/buck-out/v2/gen/fbcode/d4f2c81239ceac96/neteng/ai/rdma_gen/__rdma_gen__/rdma_gen+0x5696fe) pytorch#1 0x7faa8d40c47b in c10d::detail::UvTcpSocket::alloc_buffer(uv_handle_s*, unsigned long, uv_buf_t*) fbcode/caffe2/torch/csrc/distributed/c10d/TCPStoreLibUvBackend.cpp:121 pytorch#2 0x7faa6f62316d in uv__read /home/engshare/third-party2/libuv/1.34.2/src/libuv-v1.34.2/src/unix/stream.c:1143:5 pytorch#3 0x7faa6f6239ef in uv__stream_io /home/engshare/third-party2/libuv/1.34.2/src/libuv-v1.34.2/src/unix/stream.c:1306:5 pytorch#4 0x7faa6f62941f in uv__io_poll /home/engshare/third-party2/libuv/1.34.2/src/libuv-v1.34.2/src/unix/linux-core.c:431:11 pytorch#5 0x7faa6f618629 in uv_run /home/engshare/third-party2/libuv/1.34.2/src/libuv-v1.34.2/src/unix/core.c:375:5 pytorch#6 0x7faa8d3e7320 in c10d::detail::LibUVStoreDaemon::run() fbcode/caffe2/torch/csrc/distributed/c10d/TCPStoreLibUvBackend.cpp:1216 pytorch#7 0x7faa8d3bc933 in void std::__invoke_impl<void, void (c10d::detail::BackgroundThread::*)(), c10d::detail::BackgroundThread*>(std::__invoke_memfun_deref, void (c10d::detail::BackgroundThread::*&&)(), c10d::detail::BackgroundThread*&&) fbcode/third-party-buck/platform010/build/libgcc/include/c++/trunk/bits/invoke.h:74 pytorch#8 0x7faa8d3bc80c in std::__invoke_result<void (c10d::detail::BackgroundThread::*)(), c10d::detail::BackgroundThread*>::type std::__invoke<void (c10d::detail::BackgroundThread::*)(), c10d::detail::BackgroundThread*>(void (c10d::detail::BackgroundThread::*&&)(), c10d::detail::BackgroundThread*&&) fbcode/third-party-buck/platform010/build/libgcc/include/c++/trunk/bits/invoke.h:96 pytorch#9 0x7faa8d3bc7e1 in void std::thread::_Invoker<std::tuple<void (c10d::detail::BackgroundThread::*)(), c10d::detail::BackgroundThread*>>::_M_invoke<0ul, 1ul>(std::_Index_tuple<0ul, 1ul>) fbcode/third-party-buck/platform010/build/libgcc/include/c++/trunk/bits/std_thread.h:253 pytorch#10 0x7faa8d3bc7a4 in std::thread::_Invoker<std::tuple<void (c10d::detail::BackgroundThread::*)(), c10d::detail::BackgroundThread*>>::operator()() fbcode/third-party-buck/platform010/build/libgcc/include/c++/trunk/bits/std_thread.h:260 pytorch#11 0x7faa8d3bc608 in std::thread::_State_impl<std::thread::_Invoker<std::tuple<void (c10d::detail::BackgroundThread::*)(), c10d::detail::BackgroundThread*>>>::_M_run() fbcode/third-party-buck/platform010/build/libgcc/include/c++/trunk/bits/std_thread.h:211 pytorch#12 0x7faa436df5b4 in execute_native_thread_routine (/usr/local/fbcode/platform010/lib/libstdc++.so.6+0xdf5b4) (BuildId: 14a4eafe0cdc86af9a949a6c0c27bf21a033e047) pytorch#13 0x56744a in asan_thread_start(void*) ubsan.c pytorch#14 0x7faa43b2cf5b in __GI___clone3 (/usr/local/fbcode/platform010/lib/libc.so.6+0x12cf5b) (BuildId: 93cdceeb8322234c38e1f2c93ad0ff10c7632fa6) ``` With fix, no leak Differential Revision: D68566104

* update for MIOpen integration

soumith and others added 3 commits August 13, 2016 11:33

fix addmm and addmv documentation when they are methods

68b400f

Add new shared memory allocator to TH

4a1e099

soumith closed this Sep 7, 2016

soumith reopened this Sep 7, 2016

apaszke force-pushed the multiprocessing branch from 7ccc5ea to dbaf05d Compare September 7, 2016 17:35

rguthrie3 and others added 8 commits September 7, 2016 23:31

Added dyanamic dispatch for x86 (#755)

76ac35c

Added dynamic dispatch for x86

adding generic/THVector.h to cmake

dac5a0a

Fix segfault in THMapAllocator

cef9bf7

Fix shm_open and shm_unlink cmake test

043be6f

Add incref/decref for THRefcountedMapAllocator

64938f7

Don't check memory permissions with write on OS X

90a7a79

write returns errno 45 (Operation not supported) when used with a file descriptor obtained via shm_open on OS X.

Update TH

46fa7d9

Initialize THVector dispatch tables

24fe4b8

apaszke force-pushed the multiprocessing branch from dbaf05d to 5b4afd7 Compare September 8, 2016 17:10

soumith reviewed Sep 8, 2016
View reviewed changes

test/test_multiprocessing.py

from common import TestCase

HAS_SHM = os.path.isdir('/dev/shm')

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soumith changed the title ~~Update multiprocessing~~ add multiprocessing unit tests, working file-descriptor based solution and OSX Sep 8, 2016

apaszke added 2 commits September 8, 2016 11:23

Add file descriptor sharing mode to multiprocessing

58f507f

Make travis use run_test.sh

3d6b805

apaszke force-pushed the multiprocessing branch from 5b4afd7 to 3d6b805 Compare September 8, 2016 18:24

apaszke merged commit 3d6b805 into master Sep 8, 2016

soumith deleted the multiprocessing branch September 20, 2016 20:49

rockcat mentioned this pull request Jan 24, 2017

segfault on AMD Athlon CPUs #535

Closed

egborbe mentioned this pull request May 25, 2017

memory leak(cpu, not gpu) in convolution layer #1272

Closed

soumith pushed a commit that referenced this pull request Jul 13, 2017

Merge pull request #11 from soumith/master

b900a49

Fix ATen build for debug python

howard0su mentioned this pull request Jul 16, 2017

Dropout segfaults with -OO #1848

Closed

yogi81 referenced this pull request Aug 16, 2017

libshm needs static libstdc++ on binary build

1d9b10d

jiasenlu mentioned this pull request Sep 6, 2017

segfault in python multithreaded setting #1868

Closed

M-Eng mentioned this pull request Oct 12, 2017

Segfault when using data parallel on PPC64 #3089

Closed

D-jojo mentioned this pull request Jan 5, 2024

libtorch crashing core dump #76229

Closed

pytorch-bot bot pushed a commit that referenced this pull request Jan 9, 2024

Merge pull request #11 from weifengpy/grad_scaler_bug_fix_weif

16e4288

[FSDP] grad scaler: finish TODO

flishwang mentioned this pull request Feb 2, 2024

torch.compile crashes when using DDP and dynamic shapes and torch.utils.checkpoint in 2.2.0 #118984

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heyfavour mentioned this pull request Mar 6, 2024

c++ libtroch Exception when tensor do repeat_interleave then do torch::mm #121293

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ChuBoning mentioned this pull request Jun 24, 2024

A process got stuck in TCPStore::get #129367

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ZenithGenius mentioned this pull request Jul 2, 2024

Got this error when just running my flask script #129992

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baoleai mentioned this pull request Aug 16, 2024

[CUDA12] use MaybeSetDevice in cuda device guard setDevice #132398

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wconstab mentioned this pull request Aug 21, 2024

TORCH_NCCL_NAN_CHECK fails in certain scenarios #134062

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nWEIdia mentioned this pull request Aug 30, 2024

test_parity__foreach_* tests segfault in kineto #134596

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chunyuan-w pushed a commit to chunyuan-w/pytorch that referenced this pull request Nov 28, 2024

Merge pull request pytorch#11 from chunyuan-w/chunyuan/fix_multi_othe…

58b88f6

…r_buf_pr Support multiple other buffers for score and mask

SOCOOL666 mentioned this pull request Dec 20, 2024

LibTorch cannot load PyTorch exported model #47917

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gglin001 added a commit to torch-nupu/pytorch that referenced this pull request Jan 23, 2025

restore changes for torch_nupu (pytorch#11)

3f6049c

YufangMo mentioned this pull request Jan 30, 2025

multi node Error when dist.destroy_process_group #146021

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Dutch-voyage mentioned this pull request Mar 19, 2025

(Will PR) Multiprocessing with CUDA_VISIBLE_DEVICES seems to give the wrong device #149196

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akashveramd pushed a commit to akashveramd/pytorch that referenced this pull request Apr 9, 2025

Update for recent MIOpen integration (pytorch#11)

3406a11

* update for MIOpen integration

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add multiprocessing unit tests, working file-descriptor based solution and OSX #11

add multiprocessing unit tests, working file-descriptor based solution and OSX #11

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		from common import TestCase


		HAS_SHM = os.path.isdir('/dev/shm')

add multiprocessing unit tests, working file-descriptor based solution and OSX #11

add multiprocessing unit tests, working file-descriptor based solution and OSX #11

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