forked from pytorch/pytorch
-
Notifications
You must be signed in to change notification settings - Fork 51
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Merge from upstream #121
Merged
Merged
Merge from upstream #121
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Summary: Pull Request resolved: pytorch#10369 Differential Revision: D9300187 Pulled By: ezyang fbshipit-source-id: bf29966ad6aa221332b7232a965fb85e652f866d
Summary: Pull Request resolved: pytorch#10415 Reviewed By: ezyang Differential Revision: D9274954 Pulled By: gchanan fbshipit-source-id: 353a52d91556d5b81c3510eb2bf399d102c9a0a4
Summary: Pull Request resolved: pytorch#10405 Differential Revision: D9302794 Pulled By: soumith fbshipit-source-id: e4a7db8d33400a5a050d05fd1679de8bc3cbcf30
…in CPU are implemented. GPU mode is pending) Summary: This operator implements b (1/2/4/8) bit stochastic quantization of a floating matrix in a row-wise fashion. 8/b floating values are concatenated to a byte and returned in uint8 tensor. PR: pytorch#8629 Reviewed By: harouwu Differential Revision: D8493264 fbshipit-source-id: 01f64066568a1e5a2b87c6d2134bd31cdf119c02
Summary: Pull Request resolved: pytorch#10426 We were seeing linker errors for TanhGradientOperator in multifeed. Since we only use the float specialization, we might as well define it that way. Reviewed By: yinghai Differential Revision: D9280622 fbshipit-source-id: d2ffb698c73a84bb062de5e1f3bda741330e4228
Summary: A bootcamper was confused by the word "locally" and thought it meant on his macbook as opposed to his FB dev machine. Besides the confusion for the FB context, the word "locally" isn't really necessary at all soumith ezyang Pull Request resolved: pytorch#10495 Reviewed By: soumith Differential Revision: D9311480 Pulled By: goldsborough fbshipit-source-id: 2779c7c60f903a1822a50d140ed32a346feec39e
Summary: petrex Pull Request resolved: pytorch#10468 Reviewed By: yinghai Differential Revision: D9301178 Pulled By: bddppq fbshipit-source-id: 5da88aa4d79a5142f8e744cdcd8ae85951bc387c
Summary: Fixes pytorch#10456 The graph fuser was fusing together groups with prim::FusedConcat (the producer) with other ops (the consumer) if the consumer is fusable. For example, ``` import torch torch.jit.script def fn(x, y, z): x1 = x + y y1 = x - y w = torch.cat([x1, y1]) return w + z x = torch.randn(2, 2, dtype=torch.float, device='cpu') y = torch.randn(2, 2, dtype=torch.float, device='cpu') z = torch.randn(4, 2, dtype=torch.float, device='cpu') fn(x, y, z) fn.graph_for(x, y, z) ``` produced the following graph: ``` graph(%x : Float(2, 2) %y : Float(2, 2) %z : Float(4, 2)) { %3 : int = prim::Constant[value=1]() %y1 : Float(2, 2) = aten::sub(%x, %y, %3) %8 : int = prim::Constant[value=0]() %14 : Float(4, 2) = prim::FusionGroup_0[device=-1](%z, %y1, %x, %y) return (%14); } with prim::FusionGroup_0 = graph(%1 : Float(4, 2) %5 : Float(2, 2) %7 : Float(2, 2) %8 : Float(2, 2)) { %11 : int = prim::Constant[value=1]() %9 : int = prim::Constant[value=1]() %x1 : Float(2, 2) = aten::add(%7, %8, %9) %w : Float(4, 2) = prim::FusedConcat[dim=0](%x1, %5) %2 : int = prim::Constant[value=1]() %3 : Float(4, 2) = aten::add(%w, %1, %2) return (%3); } ``` this is a problem because it violates two invariants: 1) all inputs to the FusionGroup must have the same size 2) prim::FusedConcat's output must not be used inside the FusionGroup This PR fixes this problem by checking if the output to a FusionGroup came from a prim::FusedConcat node when deciding whether to fuse the consumer and producer. If the producer is a value that came from a prim::FusedConcat node in a FusionGroup, then consumer & producer do not get fused. cc apaszke zdevito Pull Request resolved: pytorch#10466 Differential Revision: D9296686 Pulled By: zou3519 fbshipit-source-id: ed826fa9c436b42c04ca7d4d790cece804c162bd
Summary: Targets the issue discussed at pytorch#7399 (comment). Pull Request resolved: pytorch#10453 Differential Revision: D9311591 Pulled By: soumith fbshipit-source-id: ac0712e10bdac4ea3f76d6fbad2178ec958b3a31
Summary: Fixes pytorch#3671 . Pull Request resolved: pytorch#9508 Differential Revision: D9307186 Pulled By: soumith fbshipit-source-id: 39dcaa6fd2d330d7085802acd6f63c19270164fa
…h#10100) Summary: Pull Request resolved: pytorch#10100 nomnigraph has until this point tried to ignore external input and output, as they aren't very well defined (does order matter?). but for DCE and some of Keren's work they are becoming necessary. I went ahead and added this to the core nomnigraph converter Reviewed By: yinghai Differential Revision: D9105487 fbshipit-source-id: a2e10e3cc84515611d6ab7d4bc54cf99b77729c0
…pytorch#10293) Summary: AffineChannel is being used by public Detectron models, e.g. Mask-RCNN and Faster-RCNN. This PR folds this op into convolution the same way as BN to speed up inference. Pull Request resolved: pytorch#10293 Differential Revision: D9276789 Pulled By: yinghai fbshipit-source-id: fbf6dd2c1be05f5713f760752e7245b1320a122b
@pytorchbot retest this please |
1 similar comment
@pytorchbot retest this please |
… method type (pytorch#8740) Summary: This is related to pytorch#5255 When adding cuda support for the model, this error comes: `` AttributeError: 'SpatialFullConvolution' object has no attribute 'finput' `` here is my short code for test. https://gist.github.com/kaleaht/26518c3deea5d1d3dda722fbf1f3ecdc I converted torch7's model also from here. https://github.com/art-programmer/FloorplanTransformation Pull Request resolved: pytorch#8740 Differential Revision: D8872735 Pulled By: SsnL fbshipit-source-id: 8d97f8b59cdf4049e87be14b78c4608fd973d149
Summary: "accelerate compute" a verb shouldn't go with another verb. Pull Request resolved: pytorch#10204 Differential Revision: D9316699 Pulled By: fmassa fbshipit-source-id: f1126c594905c3236ffd6b7e57a92552d3d4c1f1
@pytorchbot retest this please |
Summary: This commit adds the ability to insert a node with inputs, using the schema to check the inputs are valid types, fill in any default values, and perform standard implicit conversions. Since it is schema based, it will discover and use the right overload. Constructors to `NamedValue` enable it to be constructed using `IValue` constants so it is possible to use constant values in the input list as well: ``` g.insert(aten::add, {v, 3}); ``` Keyword arguments are also supported: ``` g.insert(aten::add, {v}, {{"other", t}, {"scalar", 1}}); ``` Pull Request resolved: pytorch#10198 Differential Revision: D9307252 Pulled By: zdevito fbshipit-source-id: 644620aa85047d1eae1288383a619d50fec44d9b
Summary: Fixing some compiler warnings while looking at symbol visibility. cc smessmer ezyang Pull Request resolved: pytorch#10297 Reviewed By: soumith Differential Revision: D9195336 Pulled By: orionr fbshipit-source-id: 04cbfd3549984caec7bdd1a5b39a6d25e80348e9
Summary: We missed 2 places to add tags when we create tensor descriptors. Pull Request resolved: pytorch#10502 Reviewed By: Maratyszcza Differential Revision: D9312075 Pulled By: yinghai fbshipit-source-id: 329e83ec5470b0a778d2eda525dd6f2143facbdf
Summary: - Exposed get_debug_graph for ScriptModule (gets the debug graph for its forward Method) - Added forward/backward expect tests for lstm and milstm cells. These are intended to prevent regressions cc apaszke zdevito Pull Request resolved: pytorch#10506 Differential Revision: D9316590 Pulled By: zou3519 fbshipit-source-id: 3c2510d8363e9733ccbc5c7cc015cd1d028efecf
Summary: Test only for existence for now. I had to skip a lot of them so there a FIXME in the test. Also I'm not testing torch.* because of namespace issue. Pull Request resolved: pytorch#10311 Differential Revision: D9196341 Pulled By: SsnL fbshipit-source-id: 9c2ca1ffe660bc1cc664474993f8a21198525ccc
Summary: Pull Request resolved: pytorch#10389 Added some unit test for box_with_nms_limit_op. Reviewed By: wat3rBro Differential Revision: D9237860 fbshipit-source-id: 2d65744bd387314071b68d2a0c934289fc64a731
Summary: It just calls into `ninja install`. For iterative work on libtorch.so/_C.so, `python setup.py rebuild_libtorch develop` should provide quick iteration Pull Request resolved: pytorch#10036 Differential Revision: D9317869 Pulled By: anderspapitto fbshipit-source-id: 45ea45a1b445821add2fb9d823a724fc319ebdd2
Summary: Pull Request resolved: pytorch#10486 Reviewed By: ml7 Differential Revision: D9305283 fbshipit-source-id: 0d1316f9a72670ddbe8d95ead93603d00ad0f63b
…torch#10244) Summary: Pull Request resolved: pytorch#10244 Use CAFFE_ENFORCE_EQ(x, y) instead of CAFFE_ENFORCE(x == y) in conv_op_impl.h for error messages with more information. Reviewed By: viswanathgs Differential Revision: D9177091 fbshipit-source-id: cf8d10afec1ce6793d3ae0b62f05648722a4130b
Summary: There are three classes `RNNCell`, `LSTMCell`, `GRUCell` inherited from `RNNCellBase`, all defining the identical initialization function `reset_parameters`. Lets move it to the common base. Another option is to have different initialization for RNN, LSTM and GRU. Maybe those weights whose output is processed with sigmoid (i.e. gain=1) should be initialized differently from those going to tanh (gain=5/3)? Pull Request resolved: pytorch#10399 Differential Revision: D9316978 Pulled By: SsnL fbshipit-source-id: a2d9408f0b5c971a3e6c3d42e4673725cf03ecc1
Do not use it for the offsets.
Summary: optimize max and min reduction for ATen CPU path, current code path from TH module runs in sequential on CPU. Pull Request resolved: pytorch#10343 Differential Revision: D9330799 Pulled By: ezyang fbshipit-source-id: 5b8271e0ca3e3e73f88a9075aa541c8756001b7c
…Node (pytorch#10512) Summary: Pull Request resolved: pytorch#10512 SubtreeMatchCriteria now becomes a graph of MatchNode MatchNode consists of NodeMatchCriteria, nonTerminal and count. This is a cleaner internal representation of the data structure and will bring us much closer to DAG matching. Note that I still keep the debugString method because convertToDotGraph doesn't currently work with Subgraph. Reviewed By: bwasti Differential Revision: D9321695 fbshipit-source-id: 58a76f007a9a95d18cf807d419c2b595e9bc847f
Summary: Two tests in the 'nn' test bucket may fail when the torch.half (float16) data type is used. The assertions used in the tests intend to allow slight floating point imprecision in the results, but the tolerances used for the comparisons are too strict for the half type. Relax the tolerances so that slight float16 imprecision won't cause test failures. The affected tests are: - test_variable_sequence_cuda - test_Conv2d_groups_nobias For more information, see issue: pytorch#7420 Pull Request resolved: pytorch#10519 Differential Revision: D9343751 Pulled By: soumith fbshipit-source-id: 90aedf48f6e22dd4fed9c7bde7cd7c7b6885845a
@pytorchbot retest this please |
Summary: Fixes pytorch#9934 Pull Request resolved: pytorch#10416 Differential Revision: D9276252 Pulled By: ailzhang fbshipit-source-id: ea7d9d4f9390edefcd0865a98498f6c4307c291d
Summary: Needed by the Gloo development team. Verifying nothing breaks in CI. Pull Request resolved: pytorch#10545 Reviewed By: Maratyszcza Differential Revision: D9344413 Pulled By: orionr fbshipit-source-id: 207edb71170870bacec47a635a12d7f55b6c1275
Summary: Support broadcasting in _kl_categorical_categorical this makes it possible to do: ``` import torch.distributions as dist import torch p_dist = dist.Categorical(torch.ones(1,10)) q_dist = dist.Categorical(torch.ones(100,10)) dist.kl_divergence(p_dist, q_dist) ``` Pull Request resolved: pytorch#10533 Differential Revision: D9341252 Pulled By: soumith fbshipit-source-id: 34575b30160b43b6c9e4c3070dd7ef07c00ff5d7
Summary: Pull Request resolved: pytorch#10522 Move filler interface to operator schema to avoid extra code for caffe2 mobile. Reviewed By: dzhulgakov Differential Revision: D9312940 fbshipit-source-id: 77fb2406f0c6b171a1912a207e05e36da50c6966
win keeps failing b/c of the integration from master. |
Summary: Since we can't specify version number to `choco install curl`, we should not assume that `7.57.0` is the curl version that's in the Windows AMI. Pull Request resolved: pytorch#10476 Differential Revision: D9303129 Pulled By: yf225 fbshipit-source-id: 198544be68330860fbcf93c99bc995f4e280bda7
Summary: Fixes pytorch#10238 Pull Request resolved: pytorch#10277 Reviewed By: SsnL Differential Revision: D9199825 Pulled By: soumith fbshipit-source-id: 8ee7f9a72d9546d429f311c3f6028461d3c93fe2
Summary: reduce flakiness of test Reviewed By: Maratyszcza Differential Revision: D9344877 fbshipit-source-id: 24d5e1b873f94d816c980f3b7db93248cf10aca5
Summary: In the shortcut for n_sample=1, when category 0 has 0 weight, we should not map the (uniform) sample 0 to category 0. The conversion uniform->multinomial was apparently written to work on a (0,1] range (like curand uses), but PyTorch uses a [0,1) range. Fixes: pytorch#4858. Thank you, Roy Fejgin for reporting. Pull Request resolved: pytorch#9960 Reviewed By: soumith Differential Revision: D9341793 Pulled By: ailzhang fbshipit-source-id: 6b1a96419a7bc58cc594f761f34c6408ff6354cf
Summary: This is the first of two changes that are supposed to improve how we handle RNNs in the JIT. They still get traced as `PythonOp`s, but now it will be much easier to actually expose them to the JIT as e.g. `aten::lstm`, and ignore the Python interpreter entirely. This needs some symbolic adjustments that will be part of a second PR. Even when we fix symbolics, there will still be a bit of a problem with statefulness of the cuDNN API (we need a mutable cache for the dropout state, but our IR has no way of representing that). zdevito ezyang Pull Request resolved: pytorch#10481 Reviewed By: ezyang Differential Revision: D9341113 Pulled By: apaszke fbshipit-source-id: 0ae30ead72a1b12044b7c12369d11e5ca8ec30b5
Summary: This PR removes couple of macros throughout TH* as part of the re-factoring effort for ATen. Removing these macros should avoid confusion among developers who are trying to move things from TH* to ATen. This PR is part of the THCNumerics deprecation that I have been working on following up on mruberry's pytorch#9318. I am separating these two commits to see if removal of these macros doesn't upset the pytorch public CI, as well as internal builds. - Commit pytorch@1248de7 removes the code paths guarded by `CUDA_HALF_INSTRUCTIONS` macro. Since the macro was removed in commit pytorch@2f186df, `ifdef CUDA_HALF_INSTRUCTIONS` would return false and hence the code path that is kept after this change is for the false case of `ifdef CUDA_HALF_INSTRUCTIONS` - Commit pytorch@520c99b removes the code paths guarded by `CUDA_HALF_TENSOR` macro. Since Pytorch now provides support for only CUDA 8.0 and above, `CUDA_HALF_TENSOR` is always true since CUDA 8.0 satisfies `CUDA_HAS_FP16` and hence, the code path that is kept after this change is for the true case of `ifdef CUDA_HALF_TENSOR`. Pull Request resolved: pytorch#10147 Differential Revision: D9345940 Pulled By: soumith fbshipit-source-id: c9392261dd432d304f1cdaf961760cbd164a59d0
Differential Revision: D9276252 Original commit changeset: ea7d9d4f9390 fbshipit-source-id: 5977bf90d4c84b47e15bc8266cc3ce5602c4e05f
…ensorByteStringToUInt8FillOp (pytorch#10385) Summary: Pull Request resolved: pytorch#10385 Pull Request resolved: pytorch#10354 Pull Request resolved: pytorch#10316 Because Protobuf encodes uint8_t tensors using a less space efficient varint uin32_t encoding, we are adding a new operator that reads back a byte string into a uint8_t tensor. Reviewed By: harouwu Differential Revision: D9004839 fbshipit-source-id: dfd27085c813fdeff13fee15eef4a2e7fef72845
…pytorch#10530) Summary: In my environment, it looks like setup.py hangs when running ``` FULL_CAFFE2=1 python setup.py build_deps ``` Removing this fixes things, but we might also want to look at `tests_require`, which came over from `setup_caffe2.py`. cc pjh5 Pull Request resolved: pytorch#10530 Differential Revision: D9349597 Pulled By: orionr fbshipit-source-id: 589145eca507dfaf16386884ee2fbe60299660b4
Summary: Pull a fix in FP16 for compilation bug when using Intel Compiler Pull Request resolved: pytorch#10548 Differential Revision: D9349469 Pulled By: Maratyszcza fbshipit-source-id: 43e6dc5c3c18319d31eca23426770c73795feec5
Summary: This should make ASAN tests run faster. Pull Request resolved: pytorch#9902 Differential Revision: D9032986 Pulled By: yf225 fbshipit-source-id: 3d2edec2d7ce78bc995d25865aa82ba6d3f971d0
@pytorchbot retest this please |
Note: this PR also contains the fix (well, technically speaking various versions of it) for the elementwise_kernel hang on ROCm. |
lcskrishna
pushed a commit
to lcskrishna/pytorch
that referenced
this pull request
May 15, 2023
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
alugorey
pushed a commit
to alugorey/pytorch
that referenced
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
to lcskrishna/pytorch
that referenced
this pull request
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
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
No description provided.