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Merge build reduction and merge from master #74
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Fix Dynamic Shared Memory.
pytorch#9658) Summary: …unctions. This also unifies the error checkign between scatter/scatterAdd on CUDA. Pull Request resolved: pytorch#9658 Differential Revision: D8941527 Pulled By: gchanan fbshipit-source-id: 750bbac568f607985088211887c4167b67be11ea
Merge from upstream
Summary: This pull request implements low rank multivariate normal distribution where the covariance matrix has the from `W @ W.T + D`. Here D is a diagonal matrix, W has shape n x m where m << n. It used "matrix determinant lemma" and "Woodbury matrix identity" to save computational cost. During the way, I also revise MultivariateNormal distribution a bit. Here are other changes: + `torch.trtrs` works with cuda tensor. So I tried to use it instead of `torch.inverse`. + Use `torch.matmul` instead of `torch.bmm` in `_batch_mv`. The former is faster and simpler. + Use `torch.diagonal` for `_batch_diag` + Reimplement `_batch_mahalanobis` based on `_batch_trtrs_lower`. + Use trtrs to compute term2 of KL. + `variance` relies on `scale_tril` instead of `covariance_matrix` TODO: - [x] Resolve the fail at `_gradcheck_log_prob` - [x] Add test for KL cc fritzo stepelu apaszke Pull Request resolved: pytorch#8635 Differential Revision: D8951893 Pulled By: ezyang fbshipit-source-id: 488ee3db6071150c33a1fb6624f3cfd9b52760c3
Summary: Updated the error message terms _matrices_ and _vectors_ to _2D tensors_ and _1D tensors_ respectively. Pull Request resolved: pytorch#9694 Differential Revision: D8949589 Pulled By: ezyang fbshipit-source-id: 2cdcd72e0e9a4459f3691c133bb16ef218b5cf3f
pytorch#9555) Summary: This is to simplify the data format during benchmarking. After this change, we can use the same benchmarking harness data conversion method to parse data from multiple binaries. This change should be coordinated with the PR: facebook/FAI-PEP#63 Pull Request resolved: pytorch#9555 Reviewed By: pjh5 Differential Revision: D8903024 Pulled By: sf-wind fbshipit-source-id: 61cabcff99f0873729142ec6cb6dc230c685d13a
Summary: Need an overload of `at::from_blob` for Variables. ezyang colesbury ebetica Pull Request resolved: pytorch#9605 Differential Revision: D8926226 Pulled By: goldsborough fbshipit-source-id: e377c0d019d4377f3fc124614c7dcc562aa69990
Summary: Pull Request resolved: pytorch#9717 D8722560 was landed with some build errors, unfortunately the c10 code isn't part of contbuild yet. Fixing them. Differential Revision: D8954141 fbshipit-source-id: 2a082fb8041626e45ccd609f37a8ef807f6dad8a
Summary: Pull Request resolved: pytorch#9550 as titled Differential Revision: D8899226 fbshipit-source-id: 3c7cf026e8cbc0e95770e5a35b213a97bebba385
Summary: This is a modification of the strategy from pytorch#8919 and pytorch#9579. ``` Previously, the CPU architecture-specific kernels self-registered with the DispatchStub. When linking as part of a static library, this requires the flag --whole-archive to be passed to the linker to ensure that the object files for the kernels are included. Caffe2 and TensorFlow use that strategy. We ran into some issues with --whole-archive blowing up the binary size of some downstream projects in Facebook. This PR avoids --whole-archive for CPU kernels. The downside is that the generic code needs to be aware of whether kernels are compiled with AVX and with AVX2 (via HAVE_AVX_CPU_DEFINITION and HAVE_AVX2_CPU_DEFINITION). The CUDA kernels still self-register with DispatchStub because the CPU library is not aware of whether the CUDA library will be available at runtime. There are a few major changes to DispatchStub - The environment variable ATEN_CPU_CAPABILITY overrides the CPU capability detection code (Previous ATEN_DISABLE_AVX/AVX2) - DispatchStub is defined in the generic native code instead of the CPU_CAPABILITY_DEFAULT kernel. ``` Pull Request resolved: pytorch#9664 Differential Revision: D8943350 Pulled By: colesbury fbshipit-source-id: 329229b0ee9ff94fc001b960287814bd734096ef
Summary: Pull Request resolved: pytorch#9622 Implement a ctc_beam_sarch_decoder operator based on ctc_greedy_decoder. Differential Revision: D8903100 fbshipit-source-id: 38973632cb437e5cfcb9ed3a48ed6b901c10efa3
…nsor (pytorch#9667) Summary: Pull Request resolved: pytorch#9667 MKL-DNN doesn't support 64-bit integger (https://github.com/intel/mkl-dnn/blob/cfee61bf81322b1ca315d5ed6cb9a9419618426b/include/mkldnn_types.h#L62-L75). So force converting from `TensorCPU<long>` to `s32` Ideep tensor will cause memory issue. This diff gives an alternative solution, where we just fall through to TensorCPU. The reasoning is that since MKL-DNN doesn't support 64 bit integer tensor, downstream ops have to be in CPUConext. So there is no reason force converting to ideep tensor and back. Reviewed By: pjh5 Differential Revision: D8943544 fbshipit-source-id: f514903cda27e34b8887271c9df56c8220895116
Summary: Pull Request resolved: pytorch#9718 This patch switches the interpreter to use IValue's primitive numbers rather than tensors for computing on integers and floats. In addition to preparing the interpreter for first-class support of other types, this cleans up the handling of primitive numbers, making it possible to just use the normal operator overloading dispatch to find the right implementation for numbers. As a result of this change, a lot of other functionality needed to be updated since it was the first time we use non-tensors in a lot of places in the code base. Notes: * Fixes code_template.py so that multi-line strings are indented correctly when used on a standalone line * Cast operators (`int(x)`) now are functional. Some tests have addition conversions to integers because we no longer allow implicit tensor -> integer conversions following the same convention as in python * prim::ListConstruct/createList has been added to the interpreter for creating lists and this has replaced aten::stack for integers lists * gen_jit_dispatch.py has been refactored so that non-tensor types use operators on IValues to extract the primitives * IValue gains a .to<T> method that is the equivalent of tensor_as but for IValue instead of at::Tensor * `constant_as<T>` is switched over to using IValues's `.to<T>` method, to make conversion from constant->IValue->C++ type more consistent. This functionality combined with `toIValue(Value*)` replaces the `tensor_as` and `as_tensor` family of functions. * conditional expressions (if, loop) and operators related to them are now computed on integers rather than tensors * IValue gains constructors for constructing from at::Scalar and converting to it. However, IValue itself will always store the scalars as a double or int64. * To align with python 3 syntax, TK_INT, TK_FLOAT, and TK_BOOL have been removed from the parser, and int/float/bool are just treated as special identifiers in the compiler, along with print. These are represented as special sugared values with a `call` method implemented. For int/float/bool this implements casting behavior. * Dropped shared_from_this from Type/Module. They were not needed and they making debugging harder because they internally throw/catch exceptions. * Shape propagation has been updated to support running nodes that include floating point primitive types, this required some refactoring of internal functions. * TensorToNum and NumToTensor have actual implementations as operators now * regster_prim_ops now contains implementations of math operators for float/int primitive types, and for mixed (prim <+> tensor) versions. This removes the need for special handling in compiler.cpp * Primitive math is now entirely handled by letting the compiler choose the right overloads. This removes tons of special casing in the compiler. * incorporates eellison's change to allow casting from return values. Due to the addition of primitive support, the code need slight modifications, so I just pre-merged it here. * stack.h gains generic vararg versions of push/pop that know how to convert to/from C++ types: ``` at::Tensor a; at::Scalar b; pop(stack, a, b); at::Tensor c = a + b; push(stack, c); ``` apaszke Pull Request resolved: pytorch#9584 Reviewed By: apaszke Differential Revision: D8910546 Pulled By: zdevito fbshipit-source-id: 0f3e60d4d22217f196a8f606549430e43b7e7e30
…torch#9657) Summary: The underlying reason why this is even an issue is that the conversion into and out of the 'fictional' onnx operators is done in an unhygenic order. This doesn't address that, but it does fix the one observable case where this produces an incorrect result, and unblocks some other work being done. Pull Request resolved: pytorch#9657 Differential Revision: D8940824 Pulled By: anderspapitto fbshipit-source-id: ea827a24c85447fe4ae470336a746329598eee84
Summary: I renamed the variable in the `Embedding` module from `weight` to `table` a few months ago, because it seemed like a more meaningful name. Turns out it's not such a good idea because it deviates from PyTorch, which unnecessarily breaks C++->Python translated code. ebetica ezyang apaszke Pull Request resolved: pytorch#9720 Differential Revision: D8955647 Pulled By: goldsborough fbshipit-source-id: 77228b07d2b733866e8cdecaa6d0686eef4cc3ea
Summary: ebetica made me aware that `nn::Module::clone()` always clones to the current device (usually CPU) instead of preserving the device of each parameter. This PR changes the signature of `clone` from `shared_ptr<Module> clone()` to `shared_ptr<Module> clone(optional<Device> device = nullopt)` with semantics of: 1. If a `device` is given, all parameters/buffers are moved to that device, 2. If no `device` is supplied (default), parameters/buffers retain their device. ezyang apaszke ebetica Pull Request resolved: pytorch#9609 Differential Revision: D8957367 Pulled By: goldsborough fbshipit-source-id: 0d409ae645ed2b8d97d6fc060240de2f3d4bc6c8
Summary: Added `operator<<` overloads for `at::TensorOptions` on request of ebetica Example output: ``` TensorOptions(dtype=Double, device=cpu, layout=Strided, requires_grad=false) ``` ezyang apaszke Pull Request resolved: pytorch#9606 Differential Revision: D8925191 Pulled By: goldsborough fbshipit-source-id: 0503bc2851268276e9561d918290bc723e437c9c
Summary: Basic cleanup, refactoring out some ops to closed source fb Reviewed By: yinghai Differential Revision: D8720722 fbshipit-source-id: 6fdf915c057a5749656d9f34a57fc142de6b076b
Summary: Constituent PRs: - [x] pytorch#9553 Remove unnecessary functions from StorageDerived.h (by cpuhrsch, reviewed by ezyang) - [x] pytorch#9588 Use THTensor/Storage for THVoidTensor/Storage (by cpuhrsch , reviewed by gchanan) - [x] pytorch#9627 Delete context from tensor (by ezyang, reviewed by gchanan) - [x] pytorch#9641 Tensor reorganization (by ezyang, reviewed by gchanan ) - [x] pytorch#9647 Remove dim_ from THTensor (by cpuhrsch, reviewed by ezyang) - [x] pytorch#9650 Remove context (by cpuhrsch, reviewed by gchanan and ezyang) - [x] pytorch#9715 Fix Windows build in tensor merge PR (by ezyang, reviewed by gchanan and SsnL) Upcoming PRs which didn't make this cut: - [x] pytorch#9644 Stride move to TensorImpl, and nits (by ezyang, reviewed by gchanan) - [ ] pytorch#9652 Native localScalar (by ezyang, **UNREVIEWED AND FAILING TESTS**) - [x] pytorch#9710 Devirtualize TensorImpl::toString (by ezyang, reviewed by gchanan) - [ ] pytorch#9654 Use int64_t instead of ptrdiff_t for size / Rename flag to resizable_ (by cpuhrsch, **CHANGES REQUESTED AND FAILING TESTS**) Pull Request resolved: pytorch#9713 Reviewed By: gchanan Differential Revision: D8960882 Pulled By: ezyang fbshipit-source-id: 99747b2c5462c7ff6809b67aacb4197626408204
Summary: Pull Request resolved: pytorch#9700 Differential Revision: D8953615 Pulled By: SsnL fbshipit-source-id: c6aa3c07dd2857dd54889d47e537a6b1e9198c60
Summary: Pull Request resolved: pytorch#9671 Add 1x1 specialization for conv with NCHW order Reviewed By: houseroad Differential Revision: D8944686 fbshipit-source-id: 94bf44f69498b1934b7dfff4c0e989342c7bb61c
Summary: Pull Request resolved: pytorch#9738 Reviewed By: apaszke Differential Revision: D8961728 Pulled By: zdevito fbshipit-source-id: aacba8c03d0d8dfe1e87585d1c2b26703d2ed103
Summary: Approved in pytorch#9644 Pull Request resolved: pytorch#9749 Differential Revision: D8965336 Pulled By: ezyang fbshipit-source-id: d1b0763e592f298395621cfd684715dc0a550cd6
Summary: Not in the same format. Skip at the moment. Pull Request resolved: pytorch#9751 Reviewed By: yinghai Differential Revision: D8965636 Pulled By: houseroad fbshipit-source-id: 81d39c2f5625c14c0e1ee11408b5f7267b53798f
Summary: found by linter, duplication was likely introduced in previous code sync Pull Request resolved: pytorch#9601 Differential Revision: D8922379 Pulled By: bddppq fbshipit-source-id: 1f61bd7f539d823e62920615674a532ec0149623
Summary: Pull Request resolved: pytorch#9766 Differential Revision: D8971173 Pulled By: gchanan fbshipit-source-id: 50bf7778eee7c60f51e1660ad834e161fa40f563
Summary: This can hardly be called an improvement (we now print CPUFloatType instead of CPUFloatTensor) but it was the simplest way I could think of devirtualizing this function in the short term. Probably need some sort of native function that gives string information about a tensor. Signed-off-by: Edward Z. Yang <ezyang@fb.com> Approved in pytorch#9710 Pull Request resolved: pytorch#9758 Differential Revision: D8966935 Pulled By: ezyang fbshipit-source-id: a4641affe0a6153f90cdd9f4f2a1100e46d1a2db
Summary: When building iOS apps with a caffe2 dependency, we were seeing the `caffe2/caffe2/mobile/contrib/ios/mpscnn/mpscnn.mm:33:17: error: method 'copyWithZone:' in protocol 'NSCopying' not implemented [-Werror,-Wprotocol]`. This fixes it by implementing a shallow copy with that method. Pull Request resolved: pytorch#9748 Reviewed By: jerryzh168 Differential Revision: D8954332 Pulled By: williamtwilson fbshipit-source-id: 0cd44408257c0bd3f4ffb80312ea9d13d13e5ff3
Summary: Fixes pytorch#9546 Test cases added Reviewed By: ezyang Differential Revision: D8974842 Pulled By: zou3519 fbshipit-source-id: a7707406c2a21e8e14f9c2a8ad4d64c8b08156df
Summary: Pull Request resolved: pytorch#9793 Enable co-distillation with different archs Reviewed By: pjh5 Differential Revision: D8888479 fbshipit-source-id: eac14d3d9bb6d8e7362bc91e8200bab237d86754
…ch#9655)" (pytorch#9804) Summary: This reverts commit 9ee5133. Pull Request resolved: pytorch#9804 Reviewed By: ezyang Differential Revision: D8987780 Pulled By: SsnL fbshipit-source-id: 75ad70b0b8d672d0b35235fa248b187be64b68e5
pytorch#9775) Summary: …THTensor.hpp. Pull Request resolved: pytorch#9775 Differential Revision: D8977140 Pulled By: gchanan fbshipit-source-id: d6d2461f7cb0511ee1def52ac1032a86349a7105
Summary: Pull Request resolved: pytorch#9788 Differential Revision: D8980951 Pulled By: gchanan fbshipit-source-id: 429b341ac687afe4f1429bb141ef070bf315519c
half the number of jobs for now to make sure we do not run into OOM
pytorch#9731) Summary: …s are the right type Pull Request resolved: pytorch#9731 Reviewed By: soumith Differential Revision: D8958693 Pulled By: jamesr66a fbshipit-source-id: 7db1f86a85188fd2c84d0edaaaac6a096d64ba52
…pytorch#9828) Summary: This was used to build Caffe2 Docker version 170. Signed-off-by: Edward Z. Yang <ezyang@fb.com> Pull Request resolved: pytorch#9828 Differential Revision: D8997808 Pulled By: ezyang fbshipit-source-id: f48938b2b71bc86578c9d9b46c281ed05478724e
Summary: pytorch#9755 broke this, but it was only tested if size zero dims were turned on (it can still happen even if that isn't turned on, because we support size [0] tensors). Pull Request resolved: pytorch#9825 Differential Revision: D8997303 Pulled By: gchanan fbshipit-source-id: 911dce112f73fad0f3980a7f4f9423df0f2d923d
Summary: 1. fixes pytorch#6271 2. implemented torch.rot90() following [numpy.rot90()](https://github.com/numpy/numpy/blob/6a58e25703cbecb6786faa09a04ae2ec8221348b/numpy/lib/function_base.py#L54-L138) Pull Request resolved: pytorch#8628 Reviewed By: ezyang Differential Revision: D8987860 Pulled By: weiyangfb fbshipit-source-id: 8dac3b2a1f6d3288672977aba8b547706ce97fe9
Summary: Pull Request resolved: pytorch#9831 Follow up to D8980903 - replace dataIterator with nodeIterator where the data isn't used. Reviewed By: pjh5 Differential Revision: D8998351 fbshipit-source-id: c333847ecd8b6d8075352322845839b94a63aecc
Summary: Pull Request resolved: pytorch#9792 Update CopyMatrix in math Reviewed By: houseroad Differential Revision: D8982421 fbshipit-source-id: da2056306cde3300124b21eba7a6c2d113111002
Summary: Supersedes pytorch#9405 Pull Request resolved: pytorch#9547 Reviewed By: zdevito Differential Revision: D8900327 Pulled By: jamesr66a fbshipit-source-id: a00a94615af4fbaec98ee3ede0cb54bcfd9108dd
Summary: Pull Request resolved: pytorch#9841 Differential Revision: D9008030 Pulled By: ezyang fbshipit-source-id: 51cac3c75fc52658b22a10a6bf8a479bcf803fb2
Summary: We think this will band-aid some of the new Caffe2 test failures. Signed-off-by: Edward Z. Yang <ezyang@fb.com> Pull Request resolved: pytorch#9830 Differential Revision: D9008052 Pulled By: ezyang fbshipit-source-id: 84f1c0faea429d758d760965d6cbfe9e4c72eb19
Summary: I split it into two parts, _local_scalar and _local_scalar_dense (unchecked) so I could reuse the sparse logic in both paths. _local_scalar became a method on Tensor to work around a circular include problem. This is resurrected copy of pytorch#9652 Pull Request resolved: pytorch#9762 Differential Revision: D8972348 Pulled By: ezyang fbshipit-source-id: 2232dbfc8e1286b8a4a1c67d285c13a7771aad4c
Summary: Signed-off-by: Edward Z. Yang <ezyang@fb.com> Pull Request resolved: pytorch#9856 Differential Revision: D9009100 Pulled By: ezyang fbshipit-source-id: 28f34128fcb7c3d6a115884bf28dc2a6bde5aed6
Summary: Pull Request resolved: pytorch#9844 Reviewed By: yinghai Differential Revision: D9004222 Pulled By: bddppq fbshipit-source-id: 1bdcefc0dfbd5e3422217b5254b2462e5a568d2a
…#9865) Summary: makes the CI flaky Pull Request resolved: pytorch#9865 Differential Revision: D9011882 Pulled By: bddppq fbshipit-source-id: 5124ab97d258eed7585734d64fb01e5df98abd0d
Summary: Pull Request resolved: pytorch#9861 Differential Revision: D9011458 Pulled By: bddppq fbshipit-source-id: 7ab1b1763d56f1290ade7a99682ad461c97f807b
Summary: The PR contains: Fixes for running MIOpen conv operator in a multi worker scenario, along with a performance fix Fixing a typo in MIOpen pool op and adding some extra checks for MIOpen spatial BN op bddppq Pull Request resolved: pytorch#9842 Differential Revision: D9012512 Pulled By: bddppq fbshipit-source-id: 270e1323c20fbfbc4b725f9a4ff34cd073ddaaa8
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When tensor is resized, reference array to it's sizes may become invalid. Make a copy in advance. <details> <summary>ASAN report</summary> ``` ================================================================= ==1115867==ERROR: AddressSanitizer: heap-use-after-free on address 0x61000013d790 at pc 0x03ff8e7da360 bp 0x03fff53c83a0 sp 0x03fff53c8390 READ of size 8 at 0x61000013d790 thread T0 #0 0x3ff8e7da35f in c10::SymInt::is_heap_allocated() const /home/user/pytorch/c10/core/SymInt.h:154 ROCm#1 0x3ff8e7da35f in c10::SymInt::maybe_as_int() const /home/user/pytorch/c10/core/SymInt.h:215 ROCm#2 0x3ff8e7d0a6d in c10::SymInt::sym_eq(c10::SymInt const&) const /home/user/pytorch/c10/core/SymInt.cpp:69 ROCm#3 0x3ff7a9ab0bd in c10::SymInt::operator==(c10::SymInt const&) const /home/user/pytorch/c10/core/SymInt.h:177 ROCm#4 0x3ff7a9aaedd in bool std::__equal<false>::equal<c10::SymInt const*, c10::SymInt const*>(c10::SymInt const*, c10::SymInt const*, c10::SymInt const*) /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++- v11/bits/stl_algobase.h:1162 ROCm#5 0x3ff7a9aae4b in bool std::__equal_aux1<c10::SymInt const*, c10::SymInt const*>(c10::SymInt const*, c10::SymInt const*, c10::SymInt const*) /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/ stl_algobase.h:1211 ROCm#6 0x3ff7a9aae05 in bool std::__equal_aux<c10::SymInt const*, c10::SymInt const*>(c10::SymInt const*, c10::SymInt const*, c10::SymInt const*) /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/s tl_algobase.h:1219 ROCm#7 0x3ff7a9aad97 in bool std::equal<c10::SymInt const*, c10::SymInt const*>(c10::SymInt const*, c10::SymInt const*, c10::SymInt const*) /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/stl_alg obase.h:1556 ROCm#8 0x3ff4b23c771 in c10::ArrayRef<c10::SymInt>::equals(c10::ArrayRef<c10::SymInt>) const /home/user/pytorch/c10/util/ArrayRef.h:188 ROCm#9 0x3ff4cb91bc1 in bool c10::operator!=<c10::SymInt>(c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>) /home/user/pytorch/c10/util/ArrayRef.h:341 ROCm#10 0x3ff6d1b57ff in torch::ADInplaceOrView::resize_(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) /home/user/pytorch/torch/csrc/autograd/Variab leTypeManual.cpp:408 ROCm#11 0x3ff6d1e59c7 in c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c1 0::MemoryFormat>), &torch::ADInplaceOrView::resize_>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> > >::operator()(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) /home/user/pytorch/aten/src/ATen/core/boxing/impl/WrapFunctionIntoFunctor.h:13 ROCm#12 0x3ff6d1e59c7 in c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10: :ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>), &torch::ADInplaceOrView::resize_>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::Sy mInt>, c10::optional<c10::MemoryFormat> > >, at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)>::call(c10::OperatorKernel*, c10::Disp atchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) /home/user/pytorch/aten/src/ATen/core/boxing/impl/make_boxed_from_unboxed_functor.h:480 ROCm#13 0x3ff51ca5129 in at::Tensor const& c10::callUnboxedKernelFunction<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> >(void*, c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>&&, c10::optional<c10::MemoryFormat>&&) /home/user/pytorch/aten/src/ATen/core/boxing/KernelFunction_impl.h:50 ROCm#14 0x3ff51ca6e8f in at::Tensor const& c10::KernelFunction::call<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> >(c10::OperatorHandle const&, c10::D ispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const /home/user/pytorch/aten/src/ATen/core/boxing/KernelFunction_impl.h:90 ROCm#15 0x3ff51ca6e8f in at::Tensor const& c10::Dispatcher::redispatch<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> >(c10::TypedOperatorHandle<at::Ten sor const& (at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)> const&, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:656 ROCm#16 0x3ff5182006b in c10::TypedOperatorHandle<at::Tensor const& (at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)>::redispatch(c10::DispatchKeySet, at::Tensor const&, c 10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:492 ROCm#17 0x3ff5182006b in at::_ops::resize_::redispatch(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) aten/src/ATen/Operators_4.cpp:2144 ROCm#18 0x3ff6d1d5e07 in at::redispatch::resize__symint(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) aten/src/ATen/RedispatchFunctions.h:2847 ROCm#19 0x3ff6d1bbb67 in torch::autograd::VariableType::(anonymous namespace)::resize_(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) /home/user/pyto rch/torch/csrc/autograd/VariableTypeManual.cpp:243 ROCm#20 0x3ff6d1bd197 in c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c1 0::MemoryFormat>), &torch::autograd::VariableType::(anonymous namespace)::resize_>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10 ::optional<c10::MemoryFormat> > >::operator()(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) /home/user/pytorch/aten/src/ATen/core/boxing/impl/WrapFu nctionIntoFunctor.h:13 ROCm#21 0x3ff6d1bd197 in c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10: :ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>), &torch::autograd::VariableType::(anonymous namespace)::resize_>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> > >, at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)>::call(c 10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) /home/user/pytorch/aten/src/ATen/core/boxing/impl/make_boxed_from_unboxed_functor .h:480 ROCm#22 0x3ff51ca5129 in at::Tensor const& c10::callUnboxedKernelFunction<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> >(void*, c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>&&, c10::optional<c10::MemoryFormat>&&) /home/user/pytorch/aten/src/ATen/core/boxing/KernelFunction_impl.h:50 ROCm#23 0x3ff5181ead1 in at::Tensor const& c10::KernelFunction::call<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> >(c10::OperatorHandle const&, c10::D ispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const /home/user/pytorch/aten/src/ATen/core/boxing/KernelFunction_impl.h:90 ROCm#24 0x3ff5181ead1 in at::Tensor const& c10::Dispatcher::call<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> >(c10::TypedOperatorHandle<at::Tensor co nst& (at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)> const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const /home/user/pytorch/at en/src/ATen/core/dispatch/Dispatcher.h:639 ROCm#25 0x3ff5181ead1 in c10::TypedOperatorHandle<at::Tensor const& (at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)>::call(at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:487 ROCm#26 0x3ff5181ead1 in at::_ops::resize_::call(at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) aten/src/ATen/Operators_4.cpp:2137 ROCm#27 0x3ff79b44fcf in at::Tensor::resize__symint(c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const aten/src/ATen/core/TensorBody.h:2452 ROCm#28 0x3ff79a802db in torch::autograd::THPVariable_resize_(_object*, _object*, _object*)::$_0::operator()(at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const /home/us er/pytorch/torch/csrc/autograd/generated/python_variable_methods.cpp:13417 ROCm#29 0x3ff7999f1eb in torch::autograd::THPVariable_resize_(_object*, _object*, _object*) /home/user/pytorch/torch/csrc/autograd/generated/python_variable_methods.cpp:13419 ROCm#30 0x3ffa2c9b009 in method_vectorcall_VARARGS_KEYWORDS Objects/descrobject.c:344 ROCm#31 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#32 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#33 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#34 0x3ffa2dff7d7 in _PyEval_EvalFrameDefault Python/ceval.c:4198 ROCm#35 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#36 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#37 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#38 0x3ffa2c8ab15 in PyVectorcall_Call Objects/call.c:255 ROCm#39 0x3ffa2c8ac65 in _PyObject_Call Objects/call.c:290 ROCm#40 0x3ffa2c8ada9 in PyObject_Call Objects/call.c:317 ROCm#41 0x3ffa2e059c7 in do_call_core Python/ceval.c:5943 ROCm#42 0x3ffa2dffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#43 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#44 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#45 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#46 0x3ffa2c8ab15 in PyVectorcall_Call Objects/call.c:255 ROCm#47 0x3ffa2c8ac65 in _PyObject_Call Objects/call.c:290 ROCm#48 0x3ffa2c8ada9 in PyObject_Call Objects/call.c:317 ROCm#49 0x3ffa2e059c7 in do_call_core Python/ceval.c:5943 ROCm#50 0x3ffa2dffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#51 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#52 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#53 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#54 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#55 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#56 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#57 0x3ffa2dff7d7 in _PyEval_EvalFrameDefault Python/ceval.c:4198 ROCm#58 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#59 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#60 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#61 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#62 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53 ROCm#63 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#64 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#65 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#66 0x3ffa2dff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 ROCm#67 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#68 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#69 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#70 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#71 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#72 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#73 0x3ffa2dff7d7 in _PyEval_EvalFrameDefault Python/ceval.c:4198 ROCm#74 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#75 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#76 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#77 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#78 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53 ROCm#79 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#80 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#81 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#82 0x3ffa2dffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#83 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#84 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#85 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#86 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#87 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53 ROCm#88 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#89 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#90 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#91 0x3ffa2dffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#92 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#93 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#94 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#95 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#96 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53 ROCm#97 0x3ffa2c8ab9b in PyVectorcall_Call Objects/call.c:267 ROCm#98 0x3ffa2c8ac65 in _PyObject_Call Objects/call.c:290 ROCm#99 0x3ffa2c8ada9 in PyObject_Call Objects/call.c:317 ROCm#100 0x3ffa2e059c7 in do_call_core Python/ceval.c:5943 ROCm#101 0x3ffa2dffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#102 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#103 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#104 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#105 0x3ffa2c8a695 in _PyObject_FastCallDictTstate Objects/call.c:153 ROCm#106 0x3ffa2c8b271 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#107 0x3ffa2d3f307 in slot_tp_call Objects/typeobject.c:7494 ROCm#108 0x3ffa2c8a933 in _PyObject_MakeTpCall Objects/call.c:215 ROCm#109 0x3ffa2df0081 in _PyObject_VectorcallTstate Include/cpython/abstract.h:112 ROCm#110 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#111 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#112 0x3ffa2dffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#113 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#114 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#115 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#116 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#117 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#118 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#119 0x3ffa2dff7d7 in _PyEval_EvalFrameDefault Python/ceval.c:4198 ROCm#120 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#121 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#122 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#123 0x3ffa2c8ab15 in PyVectorcall_Call Objects/call.c:255 ROCm#124 0x3ffa2c8ac65 in _PyObject_Call Objects/call.c:290 ROCm#125 0x3ffa2c8ada9 in PyObject_Call Objects/call.c:317 ROCm#126 0x3ffa2e059c7 in do_call_core Python/ceval.c:5943 ROCm#127 0x3ffa2dffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#128 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#129 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#130 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#131 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#132 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#133 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#134 0x3ffa2dff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#135 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#136 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#137 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#138 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#139 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53 ROCm#140 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#141 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#142 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#143 0x3ffa2dff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#144 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#145 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#146 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#147 0x3ffa2c8a695 in _PyObject_FastCallDictTstate Objects/call.c:153 ROCm#148 0x3ffa2c8b271 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#149 0x3ffa2d3f307 in slot_tp_call Objects/typeobject.c:7494 ROCm#150 0x3ffa2c8ad17 in _PyObject_Call Objects/call.c:305 ROCm#151 0x3ffa2c8ada9 in PyObject_Call Objects/call.c:317 ROCm#152 0x3ffa2e059c7 in do_call_core Python/ceval.c:5943 ROCm#153 0x3ffa2dffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#154 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#155 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#156 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#157 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#158 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#159 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#160 0x3ffa2dff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 ROCm#161 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#162 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#163 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#164 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#165 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53 ROCm#166 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#167 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#168 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#169 0x3ffa2dffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#170 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#171 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#172 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#173 0x3ffa2c8ab15 in PyVectorcall_Call Objects/call.c:255 ROCm#174 0x3ffa2c8ac65 in _PyObject_Call Objects/call.c:290 ROCm#175 0x3ffa2c8ada9 in PyObject_Call Objects/call.c:317 ROCm#176 0x3ffa2e059c7 in do_call_core Python/ceval.c:5943 ROCm#177 0x3ffa2dffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#178 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#179 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#180 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#181 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#182 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#183 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#184 0x3ffa2dff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 ROCm#185 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#186 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#187 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#188 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#189 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#190 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#191 0x3ffa2dffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#192 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#193 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#194 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#195 0x3ffa2c8ab15 in PyVectorcall_Call Objects/call.c:255 ROCm#196 0x3ffa2c8ac65 in _PyObject_Call Objects/call.c:290 ROCm#197 0x3ffa2c8ada9 in PyObject_Call Objects/call.c:317 ROCm#198 0x3ffa2e059c7 in do_call_core Python/ceval.c:5943 ROCm#199 0x3ffa2dffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#200 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#201 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#202 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#203 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#204 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#205 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#206 0x3ffa2dff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#207 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#208 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#209 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#210 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#211 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53 ROCm#212 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#213 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#214 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#215 0x3ffa2dff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#216 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#217 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#218 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#219 0x3ffa2c8a695 in _PyObject_FastCallDictTstate Objects/call.c:153 ROCm#220 0x3ffa2c8b271 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#221 0x3ffa2d3f307 in slot_tp_call Objects/typeobject.c:7494 ROCm#222 0x3ffa2c8a933 in _PyObject_MakeTpCall Objects/call.c:215 ROCm#223 0x3ffa2df0081 in _PyObject_VectorcallTstate Include/cpython/abstract.h:112 ROCm#224 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#225 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#226 0x3ffa2dffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#227 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#228 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#229 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#230 0x3ffa2c8ab15 in PyVectorcall_Call Objects/call.c:255 ROCm#231 0x3ffa2c8ac65 in _PyObject_Call Objects/call.c:290 ROCm#232 0x3ffa2c8ada9 in PyObject_Call Objects/call.c:317 ROCm#233 0x3ffa2e059c7 in do_call_core Python/ceval.c:5943 ROCm#234 0x3ffa2dffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#235 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#236 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#237 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#238 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#239 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#240 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#241 0x3ffa2dff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#242 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#243 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#244 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#245 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#246 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53 ROCm#247 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#248 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#249 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#250 0x3ffa2dff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#251 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#252 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#253 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#254 0x3ffa2c8a695 in _PyObject_FastCallDictTstate Objects/call.c:153 ROCm#255 0x3ffa2c8b271 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#256 0x3ffa2d3f307 in slot_tp_call Objects/typeobject.c:7494 ROCm#257 0x3ffa2c8a933 in _PyObject_MakeTpCall Objects/call.c:215 0x61000013d790 is located 80 bytes inside of 192-byte region [0x61000013d740,0x61000013d800) freed by thread T0 here: #0 0x3ffa3237de5 in operator delete(void*) /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_new_delete.cpp:160 ROCm#1 0x3ff8e7e3221 in c10::TensorImpl::~TensorImpl() /home/user/pytorch/c10/core/TensorImpl.cpp:75 previously allocated by thread T0 here: #0 0x3ffa323734f in operator new(unsigned long) /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_new_delete.cpp:99 ROCm#1 0x3ff4aeeb3d1 in c10::intrusive_ptr<c10::TensorImpl, c10::detail::intrusive_target_default_null_type<c10::TensorImpl> > c10::intrusive_ptr<c10::TensorImpl, c10::detail::intrusive_target_default_nul l_type<c10::TensorImpl> >::make<c10::intrusive_ptr<c10::StorageImpl, c10::detail::intrusive_target_default_null_type<c10::StorageImpl> >, c10::DispatchKeySet&, caffe2::TypeMeta&>(c10::intrusive_ptr<c10::S torageImpl, c10::detail::intrusive_target_default_null_type<c10::StorageImpl> >&&, c10::DispatchKeySet&, caffe2::TypeMeta&) /home/user/pytorch/c10/util/intrusive_ptr.h:498 ROCm#2 0x3ff76f79e17 (/home/user/pytorch/build/lib.linux-s390x-cpython-310/torch/lib/libtorch_cpu.so+0x2fb79e17) SUMMARY: AddressSanitizer: heap-use-after-free /home/user/pytorch/c10/core/SymInt.h:154 in c10::SymInt::is_heap_allocated() const Shadow bytes around the buggy address: 0x100c2000027aa0: fa fa fa fa fa fa fa fa fd fd fd fd fd fd fd fd 0x100c2000027ab0: fd fd fd fd fd fd fd fd fd fd fd fd fd fd fd fd 0x100c2000027ac0: fa fa fa fa fa fa fa fa fd fd fd fd fd fd fd fd 0x100c2000027ad0: fd fd fd fd fd fd fd fd fd fd fd fd fd fd fd fd 0x100c2000027ae0: fa fa fa fa fa fa fa fa fd fd fd fd fd fd fd fd =>0x100c2000027af0: fd fd[fd]fd fd fd fd fd fd fd fd fd fd fd fd fd 0x100c2000027b00: fa fa fa fa fa fa fa fa 00 00 00 00 00 00 00 00 0x100c2000027b10: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 0x100c2000027b20: fa fa fa fa fa fa fa fa 00 00 00 00 00 00 00 00 0x100c2000027b30: 00 00 00 00 04 fa fa fa fa fa fa fa fa fa fa fa 0x100c2000027b40: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa Shadow byte legend (one shadow byte represents 8 application bytes): Addressable: 00 Partially addressable: 01 02 03 04 05 06 07 Heap left redzone: fa Freed heap region: fd Stack left redzone: f1 Stack mid redzone: f2 Stack right redzone: f3 Stack after return: f5 Stack use after scope: f8 Global redzone: f9 Global init order: f6 Poisoned by user: f7 Container overflow: fc Array cookie: ac Intra object redzone: bb ASan internal: fe Left alloca redzone: ca Right alloca redzone: cb Shadow gap: cc ==1115867==ABORTING ``` </details> <details> <summary>Additional backtraces (not full)</summary> Memory deallocation: ``` #0 operator delete (ptr=0x61000013d740) at /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_new_delete.cpp:160 ROCm#1 0x000003ffa77e3222 in c10::TensorImpl::~TensorImpl (this=0x61000013d740) at /home/user/pytorch/c10/core/TensorImpl.cpp:75 ROCm#2 0x000003ff63e76e8c in c10::intrusive_ptr<c10::TensorImpl, c10::UndefinedTensorImpl>::reset_ (this=0x3ffd7ec8230) at /home/user/pytorch/c10/util/intrusive_ptr.h:291 ROCm#3 0x000003ff63e76910 in c10::intrusive_ptr<c10::TensorImpl, c10::UndefinedTensorImpl>::~intrusive_ptr (this=0x3ffd7ec8230) at /home/user/pytorch/c10/util/intrusive_ptr.h:370 ROCm#4 0x000003ff63e67240 in at::TensorBase::~TensorBase (this=0x3ffd7ec8230) at /home/user/pytorch/aten/src/ATen/core/TensorBase.h:80 ROCm#5 0x000003ff63e85ee0 in at::Tensor::~Tensor (this=0x3ffd7ec8230) at aten/src/ATen/core/TensorBody.h:90 ROCm#6 0x000003ff63f67304 in resize__functionalization (dispatchKeySet=..., self=..., size=..., memory_format=...) at /home/user/pytorch/aten/src/ATen/FunctionalizeFallbackKernel.cpp:173 ROCm#7 0x000003ff63f89258 in c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>), &(resize__functionalization(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>))>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat> > >::operator()(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>) ( this=0x6030000390a0, args=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/boxing/impl/WrapFunctionIntoFunctor.h:13 ROCm#8 c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>), &(resize__functionalization(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>))>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat> > >, at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>)>::call(c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>) (functor=0x6030000390a0, dispatchKeySet=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/boxing/impl/make_boxed_from_unboxed_functor.h:480 ROCm#9 0x000003ff6aca560a in c10::callUnboxedKernelFunction<at::Tensor const&, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat> > ( unboxed_kernel_func=0x3ff63f88a80 <c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tenso r const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>), &(resize__functionalization(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>))>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat> > >, at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>)>::call(c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>)>, functor=0x6030000390a0, dispatchKeySet=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/boxing/KernelFunction_impl.h:50 ROCm#10 0x000003ff6aca715c in c10::KernelFunction::call<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> > (this=0x6210005e1b28, opHandle=..., dispatchKeySet=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/boxing/KernelFunction_impl.h:96 ROCm#11 c10::Dispatcher::redispatch<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> >(c10::TypedOperatorHandle<at::Tensor const& (at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)> const&, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const ( this=0x3ff919400e0 <c10::Dispatcher::realSingleton()::_singleton>, op=..., currentDispatchKeySet=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:656 ROCm#12 0x000003ff6a82006c in c10::TypedOperatorHandle<at::Tensor const& (at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)>::redispatch(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const ( this=0x3ff919a07e0 <at::_ops::resize_::redispatch(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)::op>, currentDispatchKeySet=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:492 ROCm#13 at::_ops::resize_::redispatch (dispatchKeySet=..., self=..., size=..., memory_format=...) at /home/user/pytorch/build/aten/src/ATen/Operators_4.cpp:2144 ROCm#14 0x000003ff861d5e08 in at::redispatch::resize__symint (dispatchKeySet=..., self=..., size=..., memory_format=...) at aten/src/ATen/RedispatchFunctions.h:2847 ROCm#15 0x000003ff861b579e in torch::ADInplaceOrView::resize_ (ks=..., self=..., size=..., optional_memory_format=...) at /home/user/pytorch/torch/csrc/autograd/VariableTypeManual.cpp:401 ``` Memory access: ``` #0 c10::SymInt::maybe_as_int (this=0x61000013d790) at /home/user/pytorch/c10/core/SymInt.h:215 ROCm#1 0x000003ff734d0a6e in c10::SymInt::sym_eq (this=0x61000013d790, sci=...) at /home/user/pytorch/c10/core/SymInt.cpp:69 ROCm#2 0x000003ff5f6ab0be in c10::SymInt::operator== (this=0x61000013d790, o=...) at /home/user/pytorch/c10/core/SymInt.h:177 ROCm#3 0x000003ff5f6aaede in std::__equal<false>::equal<c10::SymInt const*, c10::SymInt const*> (__first1=0x61000013d790, __last1=0x61000013d7a0, __first2=0x602000015c30) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/stl_algobase.h:1162 ROCm#4 0x000003ff5f6aae4c in std::__equal_aux1<c10::SymInt const*, c10::SymInt const*> (__first1=0x61000013d790, __last1=0x61000013d7a0, __first2=0x602000015c30) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/stl_algobase.h:1211 ROCm#5 0x000003ff5f6aae06 in std::__equal_aux<c10::SymInt const*, c10::SymInt const*> (__first1=0x61000013d790, __last1=0x61000013d7a0, __first2=0x602000015c30) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/stl_algobase.h:1219 ROCm#6 0x000003ff5f6aad98 in std::equal<c10::SymInt const*, c10::SymInt const*> (__first1=0x61000013d790, __last1=0x61000013d7a0, __first2=0x602000015c30) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/stl_algobase.h:1556 ROCm#7 0x000003ff2ff3c772 in c10::ArrayRef<c10::SymInt>::equals (this=0x3ffed7c9900, RHS=...) at /home/user/pytorch/c10/util/ArrayRef.h:188 ROCm#8 0x000003ff31891bc2 in c10::operator!=<c10::SymInt> (a1=..., a2=...) at /home/user/pytorch/c10/util/ArrayRef.h:341 ROCm#9 0x000003ff51eb5800 in torch::ADInplaceOrView::resize_ (ks=..., self=..., size=..., optional_memory_format=...) at /home/user/pytorch/torch/csrc/autograd/VariableTypeManual.cpp:408 ROCm#10 0x000003ff51ee59c8 in c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c 10::MemoryFormat>), &torch::ADInplaceOrView::resize_>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> > >::operator()(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) (this=0x6030007dca40, args=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/boxing/impl/WrapFunctionIntoFunctor.h:13 ROCm#11 c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt >, c10::optional<c10::MemoryFormat>), &torch::ADInplaceOrView::resize_>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional< c10::MemoryFormat> > >, at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)>::call(c10::OperatorKernel*, c10::DispatchKeySet, at::Tenso r const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) (functor=0x6030007dca40, dispatchKeySet=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/boxing/impl/make_boxed_from_unboxed_functor.h:480 ROCm#12 0x000003ff369a512a in c10::callUnboxedKernelFunction<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> > ( unboxed_kernel_func=0x3ff51ee51f0 <c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tenso r const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>), &torch::ADInplaceOrView::resize_>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::Ar rayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> > >, at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)>::call(c10::OperatorKern el*, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)>, functor=0x6030007dca40, dispatchKeySet=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/boxing/KernelFunction_impl.h:50 ROCm#13 0x000003ff369a6e90 in c10::KernelFunction::call<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> > (this=0x6210005e1bc8, opHandle=..., dispatchKeySet=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/boxing/KernelFunction_impl.h:90 ROCm#14 c10::Dispatcher::redispatch<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> >(c10::TypedOperatorHandle<at::Tensor const& (at::Tensor const&, c10::Arr ayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)> const&, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const ( this=0x3ff5d6400e0 <c10::Dispatcher::realSingleton()::_singleton>, op=..., currentDispatchKeySet=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:656 ROCm#15 0x000003ff3652006c in c10::TypedOperatorHandle<at::Tensor const& (at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)>::redispatch(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const ( this=0x3ff5d6a07e0 <at::_ops::resize_::redispatch(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)::op>, currentDispatchKeySet=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:492 ROCm#16 at::_ops::resize_::redispatch (dispatchKeySet=..., self=..., size=..., memory_format=...) at /home/user/pytorch/build/aten/src/ATen/Operators_4.cpp:2144 ROCm#17 0x000003ff51ed5e08 in at::redispatch::resize__symint (dispatchKeySet=..., self=..., size=..., memory_format=...) at aten/src/ATen/RedispatchFunctions.h:2847 ROCm#18 0x000003ff51ebbb68 in torch::autograd::VariableType::(anonymous namespace)::resize_ (ks=..., self=..., size=..., optional_memory_format=...) at /home/user/pytorch/torch/csrc/autograd/VariableTypeManual.cpp:243 ``` </details> Pull Request resolved: pytorch#101064 Approved by: https://github.com/Skylion007, https://github.com/albanD
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this pull request
May 17, 2023
arguments() returns vector member of object returned by schema() call. When object returned by schema() call is destroyed, the vector is deallocated as well, it's lifetime isn't extended. This issue detected while running `pytest -v test/mobile/test_lite_script_type.py -k test_nest_typing_namedtuple_custom_classtype` with ASAN. <details> <summary>ASAN output</summary> ``` ==1134126==ERROR: AddressSanitizer: heap-use-after-free on address 0x60d0005a5790 at pc 0x03ff844488d8 bp 0x03fff584afe8 sp 0x03fff584afd8 READ of size 8 at 0x60d0005a5790 thread T0 #0 0x3ff844488d7 in __gnu_cxx::__normal_iterator<c10::Argument const*, std::vector<c10::Argument, std::allocator<c10::Argument> > >::__normal_iterator(c10::Argument const* const&) /usr/lib/gcc/s390x-i bm-linux-gnu/11/include/g++-v11/bits/stl_iterator.h:1028 ROCm#1 0x3ff8444293f in std::vector<c10::Argument, std::allocator<c10::Argument> >::begin() const /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/stl_vector.h:821 ROCm#2 0x3ff84d807d1 in torch::jit::toPyObject(c10::IValue) /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:617 ROCm#3 0x3ff84d80305 in torch::jit::toPyObject(c10::IValue) /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:604 ROCm#4 0x3ff84856871 in pybind11::detail::type_caster<c10::IValue, void>::cast(c10::IValue, pybind11::return_value_policy, pybind11::handle) /home/user/pytorch/torch/csrc/jit/python/pybind.h:138 ROCm#5 0x3ff85318191 in pybind11::cpp_function::initialize<torch::jit::initJitScriptBindings(_object*)::$_45, c10::IValue, torch::jit::mobile::Module&, pybind11::tuple const&, pybind11::name, pybind11::is _method, pybind11::sibling, pybind11::arg>(torch::jit::initJitScriptBindings(_object*)::$_45&&, c10::IValue (*)(torch::jit::mobile::Module&, pybind11::tuple const&), pybind11::name const&, pybind11::is_me thod const&, pybind11::sibling const&, pybind11::arg const&)::{lambda(pybind11::detail::function_call&)ROCm#1}::operator()(pybind11::detail::function_call&) const /home/user/pytorch/cmake/../third_party/pybin d11/include/pybind11/pybind11.h:249 ROCm#6 0x3ff85317cfd in pybind11::cpp_function::initialize<torch::jit::initJitScriptBindings(_object*)::$_45, c10::IValue, torch::jit::mobile::Module&, pybind11::tuple const&, pybind11::name, pybind11::is _method, pybind11::sibling, pybind11::arg>(torch::jit::initJitScriptBindings(_object*)::$_45&&, c10::IValue (*)(torch::jit::mobile::Module&, pybind11::tuple const&), pybind11::name const&, pybind11::is_me thod const&, pybind11::sibling const&, pybind11::arg const&)::{lambda(pybind11::detail::function_call&)ROCm#1}::__invoke(pybind11::detail::function_call&) /home/user/pytorch/cmake/../third_party/pybind11/incl ude/pybind11/pybind11.h:224 ROCm#7 0x3ff82ee52e9 in pybind11::cpp_function::dispatcher(_object*, _object*, _object*) /home/user/pytorch/cmake/../third_party/pybind11/include/pybind11/pybind11.h:929 ROCm#8 0x3ffab002903 in cfunction_call Objects/methodobject.c:543 ROCm#9 0x3ffaaf8a933 in _PyObject_MakeTpCall Objects/call.c:215 ROCm#10 0x3ffaaf8e919 in _PyObject_VectorcallTstate Include/cpython/abstract.h:112 ROCm#11 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 ROCm#12 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#13 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#14 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#15 0x3ffab0ff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#16 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#17 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#18 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#19 0x3ffaaf8a615 in _PyObject_FastCallDictTstate Objects/call.c:142 ROCm#20 0x3ffaaf8b271 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#21 0x3ffab03f307 in slot_tp_call Objects/typeobject.c:7494 ROCm#22 0x3ffaaf8a933 in _PyObject_MakeTpCall Objects/call.c:215 ROCm#23 0x3ffab0f0081 in _PyObject_VectorcallTstate Include/cpython/abstract.h:112 ROCm#24 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#25 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#26 0x3ffab0ff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 ROCm#27 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#28 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#29 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#30 0x3ffaaf8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#31 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 ROCm#32 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#33 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#34 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#35 0x3ffab0ff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 ROCm#36 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#37 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#38 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#39 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#40 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#41 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#42 0x3ffab0ff7d7 in _PyEval_EvalFrameDefault Python/ceval.c:4198 ROCm#43 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#44 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#45 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#46 0x3ffaaf8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#47 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 ROCm#48 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#49 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#50 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#51 0x3ffab0ffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#52 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#53 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#54 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#55 0x3ffaaf8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#56 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 ROCm#57 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#58 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#59 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#60 0x3ffab0ffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#61 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#62 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#63 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#64 0x3ffaaf8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#65 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 ROCm#66 0x3ffaaf8ab9b in PyVectorcall_Call Objects/call.c:267 ROCm#67 0x3ffaaf8ac65 in _PyObject_Call Objects/call.c:290 ROCm#68 0x3ffaaf8ada9 in PyObject_Call Objects/call.c:317 ROCm#69 0x3ffab1059c7 in do_call_core Python/ceval.c:5943 ROCm#70 0x3ffab0ffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#71 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#72 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#73 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#74 0x3ffaaf8a695 in _PyObject_FastCallDictTstate Objects/call.c:153 ROCm#75 0x3ffaaf8b271 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#76 0x3ffab03f307 in slot_tp_call Objects/typeobject.c:7494 ROCm#77 0x3ffaaf8a933 in _PyObject_MakeTpCall Objects/call.c:215 ROCm#78 0x3ffab0f0081 in _PyObject_VectorcallTstate Include/cpython/abstract.h:112 ROCm#79 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#80 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#81 0x3ffab0ffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#82 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#83 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#84 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#85 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#86 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#87 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#88 0x3ffab0ff7d7 in _PyEval_EvalFrameDefault Python/ceval.c:4198 ROCm#89 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#90 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#91 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#92 0x3ffaaf8ab15 in PyVectorcall_Call Objects/call.c:255 ROCm#93 0x3ffaaf8ac65 in _PyObject_Call Objects/call.c:290 ROCm#94 0x3ffaaf8ada9 in PyObject_Call Objects/call.c:317 ROCm#95 0x3ffab1059c7 in do_call_core Python/ceval.c:5943 ROCm#96 0x3ffab0ffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#97 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#98 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#99 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#100 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#101 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#102 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#103 0x3ffab0ff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#104 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#105 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#106 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#107 0x3ffaaf8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#108 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 ROCm#109 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#110 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#111 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#112 0x3ffab0ff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#113 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#114 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#115 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#116 0x3ffaaf8a695 in _PyObject_FastCallDictTstate Objects/call.c:153 ROCm#117 0x3ffaaf8b271 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#118 0x3ffab03f307 in slot_tp_call Objects/typeobject.c:7494 ROCm#119 0x3ffaaf8ad17 in _PyObject_Call Objects/call.c:305 ROCm#120 0x3ffaaf8ada9 in PyObject_Call Objects/call.c:317 ROCm#121 0x3ffab1059c7 in do_call_core Python/ceval.c:5943 ROCm#122 0x3ffab0ffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#123 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#124 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#125 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#126 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#127 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#128 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#129 0x3ffab0ff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 ROCm#130 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#131 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#132 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#133 0x3ffaaf8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#134 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 ROCm#135 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#136 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#137 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#138 0x3ffab0ffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#139 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#140 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#141 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#142 0x3ffaaf8ab15 in PyVectorcall_Call Objects/call.c:255 ROCm#143 0x3ffaaf8ac65 in _PyObject_Call Objects/call.c:290 ROCm#144 0x3ffaaf8ada9 in PyObject_Call Objects/call.c:317 ROCm#145 0x3ffab1059c7 in do_call_core Python/ceval.c:5943 ROCm#146 0x3ffab0ffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#147 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#148 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#149 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#150 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#151 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#152 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#153 0x3ffab0ff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 ROCm#154 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#155 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#156 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#157 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#158 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#159 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#160 0x3ffab0ffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#161 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#162 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#163 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#164 0x3ffaaf8ab15 in PyVectorcall_Call Objects/call.c:255 ROCm#165 0x3ffaaf8ac65 in _PyObject_Call Objects/call.c:290 ROCm#166 0x3ffaaf8ada9 in PyObject_Call Objects/call.c:317 ROCm#167 0x3ffab1059c7 in do_call_core Python/ceval.c:5943 ROCm#168 0x3ffab0ffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#169 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#170 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#171 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#172 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#173 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#174 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#175 0x3ffab0ff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#176 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#177 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#178 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#179 0x3ffaaf8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#180 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 ROCm#181 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#182 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#183 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#184 0x3ffab0ff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#185 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#186 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#187 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#188 0x3ffaaf8a695 in _PyObject_FastCallDictTstate Objects/call.c:153 ROCm#189 0x3ffaaf8b271 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#190 0x3ffab03f307 in slot_tp_call Objects/typeobject.c:7494 ROCm#191 0x3ffaaf8a933 in _PyObject_MakeTpCall Objects/call.c:215 ROCm#192 0x3ffab0f0081 in _PyObject_VectorcallTstate Include/cpython/abstract.h:112 ROCm#193 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#194 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#195 0x3ffab0ffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#196 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#197 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#198 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#199 0x3ffaaf8ab15 in PyVectorcall_Call Objects/call.c:255 ROCm#200 0x3ffaaf8ac65 in _PyObject_Call Objects/call.c:290 ROCm#201 0x3ffaaf8ada9 in PyObject_Call Objects/call.c:317 ROCm#202 0x3ffab1059c7 in do_call_core Python/ceval.c:5943 ROCm#203 0x3ffab0ffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#204 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#205 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#206 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#207 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#208 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#209 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#210 0x3ffab0ff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#211 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#212 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#213 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#214 0x3ffaaf8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#215 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 ROCm#216 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#216 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#217 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#218 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#219 0x3ffab0ff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#220 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#221 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#222 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#223 0x3ffaaf8a695 in _PyObject_FastCallDictTstate Objects/call.c:153 ROCm#224 0x3ffaaf8b271 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#225 0x3ffab03f307 in slot_tp_call Objects/typeobject.c:7494 ROCm#226 0x3ffaaf8a933 in _PyObject_MakeTpCall Objects/call.c:215 ROCm#227 0x3ffab0f0081 in _PyObject_VectorcallTstate Include/cpython/abstract.h:112 ROCm#228 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#229 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#230 0x3ffab0ffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#231 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#232 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#233 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#234 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#235 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#236 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#237 0x3ffab0ff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 ROCm#238 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#239 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#240 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#241 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#242 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#243 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#244 0x3ffab0ff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 ROCm#245 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#246 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#247 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#248 0x3ffaaf8ab15 in PyVectorcall_Call Objects/call.c:255 ROCm#249 0x3ffaaf8ac65 in _PyObject_Call Objects/call.c:290 0x60d0005a5790 is located 80 bytes inside of 136-byte region [0x60d0005a5740,0x60d0005a57c8) freed by thread T0 here: #0 0x3ffab537de5 in operator delete(void*) /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_new_delete.cpp:160 ROCm#1 0x3ff55984fdb in __gnu_cxx::new_allocator<std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2> >::deallocate(std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2>*, unsigned long) /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/ext/new_allocator.h:145 previously allocated by thread T0 here: #0 0x3ffab53734f in operator new(unsigned long) /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_new_delete.cpp:99 ROCm#1 0x3ff5598443f in __gnu_cxx::new_allocator<std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2> >::allocate(unsigned long, void const*) /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/ext/new_allocator.h:127 ROCm#2 0x3fff5849ecf ([stack]+0xb2ecf) SUMMARY: AddressSanitizer: heap-use-after-free /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/stl_iterator.h:1028 in __gnu_cxx::__normal_iterator<c10::Argument const*, std::vector<c10::Argument, std::allocator<c10::Argument> > >::__normal_iterator(c10::Argument const* const&) Shadow bytes around the buggy address: 0x100c1a000b4aa0: fd fd fd fd fd fd fd fd fd fd fd fa fa fa fa fa 0x100c1a000b4ab0: fa fa fa fa fd fd fd fd fd fd fd fd fd fd fd fd 0x100c1a000b4ac0: fd fd fd fd fd fa fa fa fa fa fa fa fa fa fd fd 0x100c1a000b4ad0: fd fd fd fd fd fd fd fd fd fd fd fd fd fd fd fa 0x100c1a000b4ae0: fa fa fa fa fa fa fa fa fd fd fd fd fd fd fd fd =>0x100c1a000b4af0: fd fd[fd]fd fd fd fd fd fd fa fa fa fa fa fa fa 0x100c1a000b4b00: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa 0x100c1a000b4b10: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa 0x100c1a000b4b20: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa 0x100c1a000b4b30: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa 0x100c1a000b4b40: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa Shadow byte legend (one shadow byte represents 8 application bytes): Addressable: 00 Partially addressable: 01 02 03 04 05 06 07 Heap left redzone: fa Freed heap region: fd Stack left redzone: f1 Stack mid redzone: f2 Stack right redzone: f3 Stack after return: f5 Stack use after scope: f8 Global redzone: f9 Global init order: f6 Poisoned by user: f7 Container overflow: fc Array cookie: ac Intra object redzone: bb ASan internal: fe Left alloca redzone: ca Right alloca redzone: cb Shadow gap: cc ==1134126==ABORTING ``` Additional backtraces (not full): Allocation: ``` #0 __memset_z196 () at ../sysdeps/s390/memset-z900.S:144 ROCm#1 0x000003ff96f3072a in __asan::Allocator::Allocate (this=this@entry=0x3ff97041eb8 <__asan::instance>, size=size@entry=136, alignment=8, alignment@entry=0, stack=<optimized out>, stack@entry=0x3ffdbb45d78, alloc_type=<optimized out>, can_fill=true) at /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_allocator.cpp:599 ROCm#2 0x000003ff96f2c088 in __asan::asan_memalign (alignment=alignment@entry=0, size=size@entry=136, stack=stack@entry=0x3ffdbb45d78, alloc_type=alloc_type@entry=__asan::FROM_NEW) at /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_allocator.cpp:1039 ROCm#3 0x000003ff96fb73b0 in operator new (size=136) at /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_new_delete.cpp:99 ROCm#4 0x000003ff41404440 in __gnu_cxx::new_allocator<std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2> >::allocate (this=0x3ffdbb468c0, __n=1) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/ext/new_allocator.h:127 ROCm#5 0x000003ff414042a0 in std::allocator_traits<std::allocator<std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2> > >::allocate (__a=..., __n=1) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/alloc_traits.h:464 ROCm#6 0x000003ff41403b66 in std::__allocate_guarded<std::allocator<std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2> > > (__a=...) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/allocated_ptr.h:98 ROCm#7 0x000003ff4140372a in std::__shared_count<(__gnu_cxx::_Lock_policy)2>::__shared_count<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::vector<c10::Argument, std::allocator<c10::Argument> >, std::vector<c10::Argument, std::allocator<c10::Argument> > > (this=0x3ffdbb47888, __p=@0x3ffdbb47880: 0x0, __a=..., __args=..., __args=..., __args=..., __args=...) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:648 ROCm#8 0x000003ff41403328 in std::__shared_ptr<c10::FunctionSchema, (__gnu_cxx::_Lock_policy)2>::__shared_ptr<std::allocator<c10::FunctionSchema>, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::vector<c10::Argument, std::allocator<c10::Argument> >, std::vector<c10::Argument, std::allocator<c10::Argument> > > (this=0x3ffdbb47880, __tag=..., __args=..., __args=..., __args=..., __args=...) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:1342 ROCm#9 0x000003ff41402f06 in std::shared_ptr<c10::FunctionSchema>::shared_ptr<std::allocator<c10::FunctionSchema>, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::vector<c10::Argument, std::allocator<c10::Argument> >, std::vector<c10::Argument, std::allocator<c10::Argument> > > ( this=0x3ffdbb47880, __tag=..., __args=..., __args=..., __args=..., __args=...) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr.h:409 ROCm#10 0x000003ff41402b6e in std::allocate_shared<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::vector<c10::Argument, std::allocator<c10::Argument> >, std::vector<c10::Argument, std::allocator<c10::Argument> > > (__a=..., __args=..., __args=..., __args=..., __args=...) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr.h:862 ROCm#11 0x000003ff4140215c in std::make_shared<c10::FunctionSchema, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::vector<c10::Argument, std::allocator<c10::Argument> >, std::vector<c10::Argument, std::allocator<c10::Argument> > > (__args=..., __args=..., __args=..., __args=...) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr.h:878 ROCm#12 0x000003ff413d180c in c10::TupleType::createWithSpec<c10::basic_string_view<char> > (qualName=..., field_names=std::vector of length 1, capacity 1 = {...}, field_types=std::vector of length 1, capacity 1 = {...}, field_defaults=std::vector of length 0, capacity 0) at /home/user/pytorch/aten/src/ATen/core/type.cpp:769 ROCm#13 0x000003ff413b9ca6 in c10::TupleType::createNamed (qualName=..., field_names=std::vector of length 1, capacity 1 = {...}, field_types=std::vector of length 1, capacity 1 = {...}) at /home/user/pytorch/aten/src/ATen/core/type.cpp:725 ROCm#14 0x000003ff4115fbac in c10::ivalue::TupleTypeFactory<c10::TupleType>::fallback (type=...) at /home/user/pytorch/aten/src/ATen/core/dynamic_type.cpp:383 ROCm#15 0x000003ff708217fe in c10::ivalue::Tuple::type<c10::TupleType> (this=0x6080004b8520) at /home/user/pytorch/aten/src/ATen/core/ivalue_inl.h:781 ROCm#16 0x000003ff70800740 in torch::jit::toPyObject (ivalue=...) at /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:613 ROCm#17 0x000003ff70800306 in torch::jit::toPyObject (ivalue=...) at /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:604 ROCm#18 0x000003ff702d6872 in pybind11::detail::type_caster<c10::IValue, void>::cast (src=...) at /home/user/pytorch/torch/csrc/jit/python/pybind.h:138 ROCm#19 0x000003ff70d98192 in pybind11::cpp_function::initialize<torch::jit::initJitScriptBindings(_object*)::$_45, c10::IValue, torch::jit::mobile::Module&, pybind11::tuple const&, pybind11::name, pybind11::is_method, pybind11::sibling, pybind11::arg>(torch::jit::initJitScriptBindings(_object*)::$_45&&, c10::IValue (*)(torch::jit::mobile::Module&, pybind11::tuple const&), pybind11::name const&, pybind11::is_method const&, pybind11::sibling const&, pybind11::arg const&)::{lambda(pybind11::detail::function_call&)ROCm#1}::operator()(pybind11::detail::function_call&) const (this=0x3ffdbb4ca20, call=...) at /home/user/pytorch/cmake/../third_party/pybind11/include/pybind11/pybind11.h:249 ROCm#20 0x000003ff70d97cfe in pybind11::cpp_function::initialize<torch::jit::initJitScriptBindings(_object*)::$_45, c10::IValue, torch::jit::mobile::Module&, pybind11::tuple const&, pybind11::name, pybind11::is_method, pybind11::sibling, pybind11::arg>(torch::jit::initJitScriptBindings(_object*)::$_45&&, c10::IValue (*)(torch::jit::mobile::Module&, pybind11::tuple const&), pybind11::name const&, pybind11::is_method const&, pybind11::sibling const&, pybind11::arg const&)::{lambda(pybind11::detail::function_call&)ROCm#1}::__invoke(pybind11::detail::function_call&) (call=...) at /home/user/pytorch/cmake/../third_party/pybind11/include/pybind11/pybind11.h:224 ROCm#21 0x000003ff6e9652ea in pybind11::cpp_function::dispatcher (self=<PyCapsule at remote 0x3ff83e27720>, args_in=(<torch._C.LiteScriptModule at remote 0x3ff811844b0>, (<Tensor at remote 0x3ff814efb00>,)), kwargs_in=0x0) at /home/user/pytorch/cmake/../third_party/pybind11/include/pybind11/pybind11.h:929 ``` Deallocation: ``` #0 operator delete (ptr=0x60d0005a5740) at /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_new_delete.cpp:160 ROCm#1 0x000003ff44904fdc in __gnu_cxx::new_allocator<std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2> >::deallocate (this=0x3ffc5dc8020, __p=0x60d0005a5740, __t=1) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/ext/new_allocator.h:145 ROCm#2 0x000003ff44904fa8 in std::allocator_traits<std::allocator<std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2> > >::deallocate ( __a=..., __p=0x60d0005a5740, __n=1) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/alloc_traits.h:496 ROCm#3 0x000003ff449041f2 in std::__allocated_ptr<std::allocator<std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2> > >::~__allocated_ptr ( this=0x3ffc5dc8030) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/allocated_ptr.h:74 ROCm#4 0x000003ff44904888 in std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2>::_M_destroy (this=0x60d0005a5740) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:538 ROCm#5 0x000003ff43895a62 in std::_Sp_counted_base<(__gnu_cxx::_Lock_policy)2>::_M_release (this=0x60d0005a5740) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:184 ROCm#6 0x000003ff43895420 in std::__shared_count<(__gnu_cxx::_Lock_policy)2>::~__shared_count (this=0x611000c40648) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:705 ROCm#7 0x000003ff4466e7f4 in std::__shared_ptr<c10::FunctionSchema, (__gnu_cxx::_Lock_policy)2>::~__shared_ptr (this=0x611000c40640) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:1154 ROCm#8 0x000003ff4466d820 in std::shared_ptr<c10::FunctionSchema>::~shared_ptr (this=0x611000c40640) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr.h:122 ROCm#9 0x000003ff448d82f6 in c10::TupleType::~TupleType (this=0x611000c40580) at /home/user/pytorch/aten/src/ATen/core/jit_type.h:1142 ROCm#10 0x000003ff448d8346 in c10::TupleType::~TupleType (this=0x611000c40580) at /home/user/pytorch/aten/src/ATen/core/jit_type.h:1142 ROCm#11 0x000003ff731296a4 in std::_Sp_counted_ptr<c10::TupleType*, (__gnu_cxx::_Lock_policy)2>::_M_dispose (this=0x603000c43ae0) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:348 ROCm#12 0x000003ff71eaf666 in std::_Sp_counted_base<(__gnu_cxx::_Lock_policy)2>::_M_release (this=0x603000c43ae0) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:168 ROCm#13 0x000003ff71eaf330 in std::__shared_count<(__gnu_cxx::_Lock_policy)2>::~__shared_count (this=0x3ffc5dc9368) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:705 ROCm#14 0x000003ff73129ee4 in std::__shared_ptr<c10::TupleType, (__gnu_cxx::_Lock_policy)2>::~__shared_ptr (this=0x3ffc5dc9360) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:1154 ROCm#15 0x000003ff73122390 in std::shared_ptr<c10::TupleType>::~shared_ptr (this=0x3ffc5dc9360) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr.h:122 ROCm#16 0x000003ff73d00788 in torch::jit::toPyObject (ivalue=...) at /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:613 ROCm#17 0x000003ff73d00306 in torch::jit::toPyObject (ivalue=...) at /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:604 ``` </details> Pull Request resolved: pytorch#101400 Approved by: https://github.com/zou3519
lcskrishna
pushed a commit
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May 29, 2023
3 disabled functions are attempting out of bounds reads. Disable them until sleef library is fixed. <details> <summary>ASAN report</summary> ``` ================================================================= ==2030580==ERROR: AddressSanitizer: global-buffer-overflow on address 0x03ff70f54570 at pc 0x03ff6704e960 bp 0x03ffce128940 sp 0x03ffce128930 READ of size 4 at 0x03ff70f54570 thread T0 #0 0x3ff6704e95f in vgather_vf_p_vi2 /home/user/pytorch/third_party/sleef/src/arch/helpers390x_128.h:129 ROCm#1 0x3ff6704e95f in rempif /home/user/pytorch/third_party/sleef/src/libm/sleefsimdsp.c:550 ROCm#2 0x3ff6704e95f in Sleef_cosf4_u10vxe2 /home/user/pytorch/third_party/sleef/src/libm/sleefsimdsp.c:1021 ROCm#3 0x3ff67029cfb in Sleef_cosf4_u10 /home/user/pytorch/build/sleef/src/libm/disps390x_128.c:182 ROCm#4 0x3ff55d21941 in at::vec::ZVECTOR::Vectorized<float, void> at::vec::ZVECTOR::Vectorized<float, void>::mapSleef<float __vector(4) const (*)(float __vector(4)), double __vector(2) const (*)(double __ vector(2)), float, 0>(float __vector(4) const (*)(float __vector(4)), double __vector(2) const (*)(double __vector(2))) const /home/user/pytorch/aten/src/ATen/cpu/vec/vec256/zarch/vec256_zarch.h:991 ROCm#5 0x3ff5689ad01 in at::vec::ZVECTOR::Vectorized<float, void>::cos() const /home/user/pytorch/aten/src/ATen/cpu/vec/vec256/zarch/vec256_zarch.h:1074 ROCm#6 0x3ff5685df97 in at::vml::ZVECTOR::vcos<float>(float*, float const*, long)::{lambda(at::vec::ZVECTOR::Vectorized<float, void>)ROCm#1}::operator()(at::vec::ZVECTOR::Vectorized<float, void>) const /home/ user/pytorch/aten/src/ATen/cpu/vml.h:71 ROCm#7 0x3ff5689b691 in void at::vec::map<float, at::vml::ZVECTOR::vcos<float>(float*, float const*, long)::{lambda(at::vec::ZVECTOR::Vectorized<float, void>)ROCm#1}, 0>(at::vml::ZVECTOR::vcos<float>(float*, float const*, long)::{lambda(at::vec::ZVECTOR::Vectorized<float, void>)ROCm#1} const&, float*, float const*, long) /home/user/pytorch/aten/src/ATen/cpu/vec/functional_base.h:239 ROCm#8 0x3ff5685e0df in void at::vml::ZVECTOR::vcos<float>(float*, float const*, long) /home/user/pytorch/aten/src/ATen/cpu/vml.h:71 ROCm#9 0x3ff563fdde3 in operator() /home/user/pytorch/aten/src/ATen/native/cpu/UnaryOpsKernel.cpp:770 ROCm#10 0x3ff5648e4a3 in operator() /home/user/pytorch/aten/src/ATen/TensorIterator.h:406 ROCm#11 0x3ff5663cae1 in callback_fn<at::TensorIteratorBase::loop_2d_from_1d<at::native::ZVECTOR::cos_kernel(at::TensorIteratorBase&)::<lambda()>::<lambda()>::<lambda(char**, const int64_t*, int64_t)> >(c onst at::native::ZVECTOR::cos_kernel(at::TensorIteratorBase&)::<lambda()>::<lambda()>::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)> > /home/user/pytorch/ c10/util/FunctionRef.h:43 ROCm#12 0x3ff4d45a933 in c10::function_ref<void (char**, long const*, long, long)>::operator()(char**, long const*, long, long) const /home/user/pytorch/c10/util/FunctionRef.h:64 ROCm#13 0x3ff4d455133 in at::internal::serial_for_each(c10::ArrayRef<long>, c10::ArrayRef<long>, char**, unsigned long, c10::function_ref<void (char**, long const*, long, long)>, at::Range) /home/user/pyt orch/aten/src/ATen/TensorIteratorInternal.h:52 ROCm#14 0x3ff4d43b703 in at::TensorIteratorBase::serial_for_each(c10::function_ref<void (char**, long const*, long, long)>, at::Range) const /home/user/pytorch/aten/src/ATen/TensorIterator.cpp:777 ROCm#15 0x3ff4d43ab59 in at::TensorIteratorBase::for_each(c10::function_ref<void (char**, long const*, long, long)>, long) /home/user/pytorch/aten/src/ATen/TensorIterator.cpp:749 ROCm#16 0x3ff5648e851 in for_each<at::native::ZVECTOR::cos_kernel(at::TensorIteratorBase&)::<lambda()>::<lambda()>::<lambda(char**, const int64_t*, int64_t)> > /home/user/pytorch/aten/src/ATen/TensorItera tor.h:421 ROCm#17 0x3ff563fe5f9 in operator() /home/user/pytorch/aten/src/ATen/native/cpu/UnaryOpsKernel.cpp:770 ROCm#18 0x3ff56400915 in operator() /home/user/pytorch/aten/src/ATen/native/cpu/UnaryOpsKernel.cpp:770 ROCm#19 0x3ff56400f1d in at::native::ZVECTOR::cos_kernel(at::TensorIteratorBase&) /home/user/pytorch/aten/src/ATen/native/cpu/UnaryOpsKernel.cpp:770 ROCm#20 0x3ff4f303007 in void at::native::DispatchStub<void (*)(at::TensorIteratorBase&), at::native::cos_stub>::operator()<at::native::structured_cos_out&>(c10::DeviceType, at::native::structured_cos_out &) /home/user/pytorch/aten/src/ATen/native/DispatchStub.h:158 ROCm#21 0x3ff4f2edb3f in at::native::structured_cos_out::impl(at::Tensor const&, at::Tensor const&) /home/user/pytorch/aten/src/ATen/native/UnaryOps.cpp:330 ROCm#22 0x3ff526ef739 in wrapper_CPU_cos /home/user/pytorch/build/aten/src/ATen/RegisterCPU.cpp:4307 ROCm#23 0x3ff52c651d9 in operator() /home/user/pytorch/aten/src/ATen/core/boxing/impl/WrapFunctionIntoFunctor.h:13 ROCm#24 0x3ff52c651d9 in call /home/user/pytorch/aten/src/ATen/core/boxing/impl/make_boxed_from_unboxed_functor.h:463 ROCm#25 0x3ff5076df2f in at::Tensor c10::callUnboxedKernelFunction<at::Tensor, at::Tensor const&>(void*, c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&) /home/user/pytorch/aten/src/ATen/core /boxing/KernelFunction_impl.h:50 ROCm#26 0x3ff5009a93f in at::Tensor c10::KernelFunction::call<at::Tensor, at::Tensor const&>(c10::OperatorHandle const&, c10::DispatchKeySet, at::Tensor const&) const /home/user/pytorch/aten/src/ATen/core /boxing/KernelFunction_impl.h:103 ROCm#27 0x3ff5009a93f in at::Tensor c10::Dispatcher::call<at::Tensor, at::Tensor const&>(c10::TypedOperatorHandle<at::Tensor (at::Tensor const&)> const&, at::Tensor const&) const /home/user/pytorch/aten/s rc/ATen/core/dispatch/Dispatcher.h:639 ROCm#28 0x3ff5009a93f in c10::TypedOperatorHandle<at::Tensor (at::Tensor const&)>::call(at::Tensor const&) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:487 ROCm#29 0x3ff5009a93f in at::_ops::cos::call(at::Tensor const&) /home/user/pytorch/build/aten/src/ATen/Operators_0.cpp:2215 ROCm#30 0x3ff7d813741 in at::Tensor::cos() const /home/user/pytorch/build/aten/src/ATen/core/TensorBody.h:2107 ROCm#31 0x3ff7dc0f2b7 in operator() /home/user/pytorch/torch/csrc/autograd/generated/python_torch_functions_2.cpp:2953 ROCm#32 0x3ff7dc0faf7 in THPVariable_cos /home/user/pytorch/torch/csrc/autograd/generated/python_torch_functions_2.cpp:2955 ROCm#33 0x3ffa5ef5ae1 in cfunction_call Objects/methodobject.c:543 ROCm#34 0x3ffa5e843f3 in _PyObject_Call Objects/call.c:305 ROCm#35 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#36 0x3ffa5feb50d in do_call_core Python/ceval.c:5915 ROCm#37 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#38 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#39 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#40 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#41 0x3ffa5e841fb in PyVectorcall_Call Objects/call.c:255 ROCm#42 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290 ROCm#43 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#44 0x3ff7f87a393 in torch::impl::dispatch::PythonKernelHolder::operator()(c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) /home/user/pytorch/ torch/csrc/utils/python_dispatch.cpp:175 ROCm#45 0x3ff7f8871a7 in c10::BoxedKernel::makeFromFunctor<torch::impl::dispatch::PythonKernelHolder>(std::unique_ptr<torch::impl::dispatch::PythonKernelHolder, std::default_delete<torch::impl::dispatch:: PythonKernelHolder> >)::{lambda(c10::OperatorKernel*, c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*)ROCm#1}::operator()(c10::OperatorKernel*, c10::Op eratorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/core/boxing/BoxedKernel_impl.h:87 ROCm#46 0x3ff7f887261 in c10::BoxedKernel::makeFromFunctor<torch::impl::dispatch::PythonKernelHolder>(std::unique_ptr<torch::impl::dispatch::PythonKernelHolder, std::default_delete<torch::impl::dispatch:: PythonKernelHolder> >)::{lambda(c10::OperatorKernel*, c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*)ROCm#1}::_FUN(c10::OperatorKernel*, c10::Operator Handle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) /home/user/pytorch/aten/src/ATen/core/boxing/BoxedKernel_impl.h:86 ROCm#47 0x3ff7e0d10ab in c10::BoxedKernel::callBoxed(c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/core/b oxing/BoxedKernel_impl.h:41 ROCm#48 0x3ff7e0d1459 in c10::KernelFunction::callBoxed(c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/cor e/boxing/KernelFunction_impl.h:43 ROCm#49 0x3ff7f876421 in c10::Dispatcher::callBoxed(c10::OperatorHandle const&, std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:6 91 ROCm#50 0x3ff4d22bcdd in c10::OperatorHandle::callBoxed(std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:417 ROCm#51 0x3ff65a092d5 in c10::OperatorHandle::callBoxed(std::vector<c10::IValue, std::allocator<c10::IValue> >&) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:421 ROCm#52 0x3ff65a05641 in operator() /home/user/pytorch/torch/csrc/jit/runtime/register_c10_ops.cpp:15 ROCm#53 0x3ff65a08cb5 in __invoke_impl<void, torch::jit::(anonymous namespace)::createOperatorFromC10(const c10::OperatorHandle&)::<lambda(torch::jit::Stack&)>&, std::vector<c10::IValue, std::allocator<c1 0::IValue> >&> /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/invoke.h:61 ROCm#54 0x3ff65a0897b in __invoke_r<void, torch::jit::(anonymous namespace)::createOperatorFromC10(const c10::OperatorHandle&)::<lambda(torch::jit::Stack&)>&, std::vector<c10::IValue, std::allocator<c10:: IValue> >&> /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/invoke.h:111 ROCm#55 0x3ff65a084e1 in _M_invoke /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/std_function.h:290 ROCm#56 0x3ff7eb2cb21 in std::function<void (std::vector<c10::IValue, std::allocator<c10::IValue> >&)>::operator()(std::vector<c10::IValue, std::allocator<c10::IValue> >&) const /usr/lib/gcc/s390x-ibm-lin ux-gnu/11/include/g++-v11/bits/std_function.h:590 ROCm#57 0x3ff7eb1b659 in torch::jit::Operation::operator()(std::vector<c10::IValue, std::allocator<c10::IValue> >&) /home/user/pytorch/aten/src/ATen/core/stack.h:41 ROCm#58 0x3ff7eb08449 in torch::jit::invokeOperatorFromPython(std::vector<std::shared_ptr<torch::jit::Operator>, std::allocator<std::shared_ptr<torch::jit::Operator> > > const&, pybind11::args, pybind11:: kwargs const&, c10::optional<c10::DispatchKey>) /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:764 ROCm#59 0x3ff7eb09d85 in torch::jit::_get_operation_for_overload_or_packet(std::vector<std::shared_ptr<torch::jit::Operator>, std::allocator<std::shared_ptr<torch::jit::Operator> > > const&, c10::Symbol, pybind11::args, pybind11::kwargs const&, bool, c10::optional<c10::DispatchKey>) /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:829 ROCm#60 0x3ff7e573eb9 in operator() /home/user/pytorch/torch/csrc/jit/python/init.cpp:1549 ROCm#61 0x3ff7e6728dd in call_impl<pybind11::object, torch::jit::initJITBindings(PyObject*)::<lambda(const string&, const string&)>::<lambda(pybind11::args, pybind11::kwargs)>&, 0, 1, pybind11::detail::vo id_type> /home/user/pytorch/third_party/pybind11/include/pybind11/cast.h:1439 ROCm#62 0x3ff7e64312f in call<pybind11::object, pybind11::detail::void_type, torch::jit::initJITBindings(PyObject*)::<lambda(const string&, const string&)>::<lambda(pybind11::args, pybind11::kwargs)>&> /h ome/user/pytorch/third_party/pybind11/include/pybind11/cast.h:1408 ROCm#63 0x3ff7e5da259 in operator() /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:249 ROCm#64 0x3ff7e5da441 in _FUN /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:224 ROCm#65 0x3ff7d317a1f in pybind11::cpp_function::dispatcher(_object*, _object*, _object*) /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:929 ROCm#66 0x3ffa5ef5ae1 in cfunction_call Objects/methodobject.c:543 ROCm#67 0x3ffa5e843f3 in _PyObject_Call Objects/call.c:305 ROCm#68 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#69 0x3ffa5feb50d in do_call_core Python/ceval.c:5915 ROCm#70 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#71 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#72 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#73 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#74 0x3ffa5e83d1f in _PyObject_FastCallDictTstate Objects/call.c:142 ROCm#75 0x3ffa5e84937 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#76 0x3ffa5f2f577 in slot_tp_call Objects/typeobject.c:7494 ROCm#77 0x3ffa5e843f3 in _PyObject_Call Objects/call.c:305 ROCm#78 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#79 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943 ROCm#80 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#81 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#82 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#83 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#84 0x3ffa5fd76a3 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#85 0x3ffa5fd772f in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#86 0x3ffa5feb289 in call_function Python/ceval.c:5891 ROCm#87 0x3ffa5fe5c3b in _PyEval_EvalFrameDefault Python/ceval.c:4213 ROCm#88 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#89 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#90 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#91 0x3ffa5e841fb in PyVectorcall_Call Objects/call.c:255 ROCm#92 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290 ROCm#93 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#94 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943 ROCm#95 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#96 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#97 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#98 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#99 0x3ffa5e841fb in PyVectorcall_Call Objects/call.c:255 ROCm#100 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290 ROCm#101 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#102 0x3ff7f87a393 in torch::impl::dispatch::PythonKernelHolder::operator()(c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) /home/user/pytorch /torch/csrc/utils/python_dispatch.cpp:175 ROCm#103 0x3ff7f8871a7 in c10::BoxedKernel::makeFromFunctor<torch::impl::dispatch::PythonKernelHolder>(std::unique_ptr<torch::impl::dispatch::PythonKernelHolder, std::default_delete<torch::impl::dispatch: :PythonKernelHolder> >)::{lambda(c10::OperatorKernel*, c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*)ROCm#1}::operator()(c10::OperatorKernel*, c10::O peratorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/core/boxing/BoxedKernel_impl.h:87 ROCm#104 0x3ff7f887261 in c10::BoxedKernel::makeFromFunctor<torch::impl::dispatch::PythonKernelHolder>(std::unique_ptr<torch::impl::dispatch::PythonKernelHolder, std::default_delete<torch::impl::dispatch: :PythonKernelHolder> >)::{lambda(c10::OperatorKernel*, c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*)ROCm#1}::_FUN(c10::OperatorKernel*, c10::Operato rHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) /home/user/pytorch/aten/src/ATen/core/boxing/BoxedKernel_impl.h:86 ROCm#105 0x3ff7e0d10ab in c10::BoxedKernel::callBoxed(c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/core/ boxing/BoxedKernel_impl.h:41 ROCm#106 0x3ff7e0d1459 in c10::KernelFunction::callBoxed(c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/co re/boxing/KernelFunction_impl.h:43 ROCm#107 0x3ff7f876421 in c10::Dispatcher::callBoxed(c10::OperatorHandle const&, std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h: 691 ROCm#108 0x3ff4d22bcdd in c10::OperatorHandle::callBoxed(std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:417 ROCm#109 0x3ff65a092d5 in c10::OperatorHandle::callBoxed(std::vector<c10::IValue, std::allocator<c10::IValue> >&) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:421 ROCm#110 0x3ff65a05641 in operator() /home/user/pytorch/torch/csrc/jit/runtime/register_c10_ops.cpp:15 ROCm#111 0x3ff65a08cb5 in __invoke_impl<void, torch::jit::(anonymous namespace)::createOperatorFromC10(const c10::OperatorHandle&)::<lambda(torch::jit::Stack&)>&, std::vector<c10::IValue, std::allocator<c 10::IValue> >&> /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/invoke.h:61 ROCm#112 0x3ff65a0897b in __invoke_r<void, torch::jit::(anonymous namespace)::createOperatorFromC10(const c10::OperatorHandle&)::<lambda(torch::jit::Stack&)>&, std::vector<c10::IValue, std::allocator<c10: :IValue> >&> /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/invoke.h:111 ROCm#113 0x3ff65a084e1 in _M_invoke /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/std_function.h:290 ROCm#114 0x3ff7eb2cb21 in std::function<void (std::vector<c10::IValue, std::allocator<c10::IValue> >&)>::operator()(std::vector<c10::IValue, std::allocator<c10::IValue> >&) const /usr/lib/gcc/s390x-ibm-li nux-gnu/11/include/g++-v11/bits/std_function.h:590 ROCm#115 0x3ff7eb1b659 in torch::jit::Operation::operator()(std::vector<c10::IValue, std::allocator<c10::IValue> >&) /home/user/pytorch/aten/src/ATen/core/stack.h:41 ROCm#116 0x3ff7eb08449 in torch::jit::invokeOperatorFromPython(std::vector<std::shared_ptr<torch::jit::Operator>, std::allocator<std::shared_ptr<torch::jit::Operator> > > const&, pybind11::args, pybind11: :kwargs const&, c10::optional<c10::DispatchKey>) /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:764 ROCm#117 0x3ff7eb09d85 in torch::jit::_get_operation_for_overload_or_packet(std::vector<std::shared_ptr<torch::jit::Operator>, std::allocator<std::shared_ptr<torch::jit::Operator> > > const&, c10::Symbol, pybind11::args, pybind11::kwargs const&, bool, c10::optional<c10::DispatchKey>) /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:829 ROCm#118 0x3ff7e573eb9 in operator() /home/user/pytorch/torch/csrc/jit/python/init.cpp:1549 ROCm#119 0x3ff7e6728dd in call_impl<pybind11::object, torch::jit::initJITBindings(PyObject*)::<lambda(const string&, const string&)>::<lambda(pybind11::args, pybind11::kwargs)>&, 0, 1, pybind11::detail::v oid_type> /home/user/pytorch/third_party/pybind11/include/pybind11/cast.h:1439 ROCm#120 0x3ff7e64312f in call<pybind11::object, pybind11::detail::void_type, torch::jit::initJITBindings(PyObject*)::<lambda(const string&, const string&)>::<lambda(pybind11::args, pybind11::kwargs)>&> / home/user/pytorch/third_party/pybind11/include/pybind11/cast.h:1408 ROCm#121 0x3ff7e5da259 in operator() /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:249 ROCm#122 0x3ff7e5da441 in _FUN /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:224 ROCm#123 0x3ff7d317a1f in pybind11::cpp_function::dispatcher(_object*, _object*, _object*) /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:929 ROCm#124 0x3ffa5ef5ae1 in cfunction_call Objects/methodobject.c:543 ROCm#125 0x3ffa5e843f3 in _PyObject_Call Objects/call.c:305 ROCm#126 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#127 0x3ffa5feb50d in do_call_core Python/ceval.c:5915 ROCm#128 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#129 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#130 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#131 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#132 0x3ffa5e83d1f in _PyObject_FastCallDictTstate Objects/call.c:142 ROCm#133 0x3ffa5e84937 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#134 0x3ffa5f2f577 in slot_tp_call Objects/typeobject.c:7494 ROCm#135 0x3ffa5e843f3 in _PyObject_Call Objects/call.c:305 ROCm#136 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#137 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943 ROCm#138 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#139 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#140 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#141 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#142 0x3ffa5e87d2b in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#143 0x3ffa5e882dd in method_vectorcall Objects/classobject.c:83 ROCm#144 0x3ffa5e836d3 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#145 0x3ffa5e84b6f in _PyObject_CallFunctionVa Objects/call.c:485 ROCm#146 0x3ffa5e84f2d in callmethod Objects/call.c:557 ROCm#147 0x3ffa5e85039 in PyObject_CallMethod Objects/call.c:577 ROCm#148 0x3ff7f7efa05 in torch::handle_torch_function_no_python_arg_parser(c10::ArrayRef<pybind11::handle>, _object*, _object*, char const*, _object*, char const*, torch::TorchFunctionName) /home/user/py torch/torch/csrc/utils/python_arg_parser.cpp:338 ROCm#149 0x3ff7eb09b67 in torch::jit::_get_operation_for_overload_or_packet(std::vector<std::shared_ptr<torch::jit::Operator>, std::allocator<std::shared_ptr<torch::jit::Operator> > > const&, c10::Symbol, pybind11::args, pybind11::kwargs const&, bool, c10::optional<c10::DispatchKey>) /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:827 ROCm#150 0x3ff7e573eb9 in operator() /home/user/pytorch/torch/csrc/jit/python/init.cpp:1549 ROCm#151 0x3ff7e6728dd in call_impl<pybind11::object, torch::jit::initJITBindings(PyObject*)::<lambda(const string&, const string&)>::<lambda(pybind11::args, pybind11::kwargs)>&, 0, 1, pybind11::detail::v oid_type> /home/user/pytorch/third_party/pybind11/include/pybind11/cast.h:1439 ROCm#152 0x3ff7e64312f in call<pybind11::object, pybind11::detail::void_type, torch::jit::initJITBindings(PyObject*)::<lambda(const string&, const string&)>::<lambda(pybind11::args, pybind11::kwargs)>&> / home/user/pytorch/third_party/pybind11/include/pybind11/cast.h:1408 ROCm#153 0x3ff7e5da259 in operator() /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:249 ROCm#154 0x3ff7e5da441 in _FUN /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:224 ROCm#155 0x3ff7d317a1f in pybind11::cpp_function::dispatcher(_object*, _object*, _object*) /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:929 ROCm#156 0x3ffa5ef5ae1 in cfunction_call Objects/methodobject.c:543 ROCm#157 0x3ffa5e843f3 in _PyObject_Call Objects/call.c:305 ROCm#158 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#159 0x3ffa5feb50d in do_call_core Python/ceval.c:5915 ROCm#160 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#161 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#162 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#163 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#164 0x3ffa5e83d1f in _PyObject_FastCallDictTstate Objects/call.c:142 ROCm#165 0x3ffa5e84937 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#166 0x3ffa5f2f577 in slot_tp_call Objects/typeobject.c:7494 ROCm#167 0x3ffa5e84027 in _PyObject_MakeTpCall Objects/call.c:215 ROCm#168 0x3ffa5fd767b in _PyObject_VectorcallTstate Include/cpython/abstract.h:112 ROCm#169 0x3ffa5fd772f in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#170 0x3ffa5feb289 in call_function Python/ceval.c:5891 ROCm#171 0x3ffa5fe5ad1 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#172 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#173 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#174 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#175 0x3ffa5fd76a3 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#176 0x3ffa5fd772f in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#177 0x3ffa5feb289 in call_function Python/ceval.c:5891 ROCm#178 0x3ffa5fe5c3b in _PyEval_EvalFrameDefault Python/ceval.c:4213 ROCm#179 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#180 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#181 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#182 0x3ffa5e8427f in PyVectorcall_Call Objects/call.c:267 ROCm#183 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290 ROCm#184 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#185 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943 ROCm#186 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#187 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#188 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#189 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#190 0x3ffa5e841fb in PyVectorcall_Call Objects/call.c:255 ROCm#191 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290 ROCm#192 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#193 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943 ROCm#194 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#195 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#196 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#197 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#198 0x3ffa5e841fb in PyVectorcall_Call Objects/call.c:255 ROCm#199 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290 ROCm#200 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#201 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943 ROCm#202 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#203 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#204 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#205 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#206 0x3ffa5e841fb in PyVectorcall_Call Objects/call.c:255 ROCm#207 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290 ROCm#208 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#209 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943 ROCm#210 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#211 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#212 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#213 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#214 0x3ffa5e83d1f in _PyObject_FastCallDictTstate Objects/call.c:142 ROCm#215 0x3ffa5e84937 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#216 0x3ffa5f2f577 in slot_tp_call Objects/typeobject.c:7494 ROCm#217 0x3ffa5e843f3 in _PyObject_Call Objects/call.c:305 ROCm#218 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#219 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943 ROCm#220 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#221 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#222 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#223 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#224 0x3ffa5fd76a3 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#225 0x3ffa5fd772f in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#226 0x3ffa5feb289 in call_function Python/ceval.c:5891 ROCm#227 0x3ffa5fe5b21 in _PyEval_EvalFrameDefault Python/ceval.c:4198 ROCm#228 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#229 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#230 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#231 0x3ffa5e8427f in PyVectorcall_Call Objects/call.c:267 ROCm#232 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290 ROCm#233 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#234 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943 ROCm#235 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#236 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#237 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#238 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#239 0x3ffa5e8427f in PyVectorcall_Call Objects/call.c:267 ROCm#240 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290 ROCm#241 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#242 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943 ROCm#243 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#244 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#245 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#246 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#247 0x3ffa5e8427f in PyVectorcall_Call Objects/call.c:267 ROCm#248 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290 ROCm#249 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#250 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943 ROCm#251 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#252 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#253 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#254 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#255 0x3ffa5e8427f in PyVectorcall_Call Objects/call.c:267 0x03ff70f54570 is located 0 bytes to the right of global variable 'Sleef_rempitabsp' defined in '/home/user/pytorch/third_party/sleef/src/libm/rempitab.c:986:34' (0x3ff70f53f00) of size 1648 SUMMARY: AddressSanitizer: global-buffer-overflow /home/user/pytorch/third_party/sleef/src/arch/helpers390x_128.h:129 in vgather_vf_p_vi2 Shadow bytes around the buggy address: 0x10007fee1ea850: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 0x10007fee1ea860: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 0x10007fee1ea870: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 0x10007fee1ea880: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 0x10007fee1ea890: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 =>0x10007fee1ea8a0: 00 00 00 00 00 00 00 00 00 00 00 00 00 00[f9]f9 0x10007fee1ea8b0: f9 f9 f9 f9 00 00 00 00 00 00 00 00 00 00 00 00 0x10007fee1ea8c0: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 0x10007fee1ea8d0: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 0x10007fee1ea8e0: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 0x10007fee1ea8f0: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 Shadow byte legend (one shadow byte represents 8 application bytes): Addressable: 00 Partially addressable: 01 02 03 04 05 06 07 Heap left redzone: fa Freed heap region: fd Stack left redzone: f1 Stack mid redzone: f2 Stack right redzone: f3 Stack after return: f5 Stack use after scope: f8 Global redzone: f9 Global init order: f6 Poisoned by user: f7 Container overflow: fc Array cookie: ac Intra object redzone: bb ASan internal: fe Left alloca redzone: ca Right alloca redzone: cb Shadow gap: cc ==2030580==ABORTING ``` </details> It reproduces when running `pytest -v test/test_ops.py -k test_python_ref__refs_cos_cpu_bfloat16` under address sanitizer on s390x. See also: shibatch/sleef#464 Pull Request resolved: pytorch#102266 Approved by: https://github.com/malfet
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