sync with upstream #156

rohithkrn · 2018-08-28T02:24:21Z

No description provided.

Summary: After this, all combinations of {String frontend, Python AST Frontend}{Python 3-style type annotations, MyPy-style type comments}{Script method, Script function} should properly accept type annotations. Possible TODOs: - Clean up the functions marked HACK - Clean up the Subscript tree-view to better match the Python AST versions - Can we use this for Python functions? That's the only place annotations.get_signature() is still needed Pull Request resolved: pytorch#10279 Differential Revision: D9319726 Pulled By: jamesr66a fbshipit-source-id: b13f7d4f066b0283d4fc1421a1abb9305c3b28fa

…h#10520) Summary: setup.py is the official install script, setup_caffe2.py is not used any more Pull Request resolved: pytorch#10520 Reviewed By: yinghai Differential Revision: D9325548 Pulled By: bddppq fbshipit-source-id: 3dda87f3dff061b574fd1d5c91859044f065ee33

Summary: Pull Request resolved: pytorch#10514 fix the bug which break the windows build in fused_rowwise_random_quantization_ops.h Reviewed By: ezyang, jspark1105 Differential Revision: D9322291 fbshipit-source-id: a6a27e87423b6caa973414ffd7ccb12076f2e1e4

Summary: Previously, it's easy to do `x[0].accessor<float, 2>()`. However, x[0] is a temporary, so the accessor will point to invalid strides/sizes and probably segfault. With this change, such unsafe code is a compile error. Pull Request resolved: pytorch#10518 Reviewed By: goldsborough Differential Revision: D9329288 Pulled By: ebetica fbshipit-source-id: d08763bee9a19a898b9d1ea5ba648f27baa1992f

…ytorch#10227) Summary: Based on: pytorch#10199 Added: (1) send, recv, recvanysource, and barrier for MPI process group. (2) python binding (3) testing Please review: pytorch@2e64f5d Pull Request resolved: pytorch#10227 Reviewed By: ailzhang Differential Revision: D9327138 Pulled By: teng-li fbshipit-source-id: 80496714550a3ca498eb474465ddbd1b8d657d49

Summary: Breaking out of pytorch#8338 This PR is a workaround for a bug with CUDA9.2 + GCC7. Here is the error this PR fixed: .../pytorch/caffe2/operators/elementwise_ops.h: In constructor ‘caffe2::BinaryElementwiseWithArgsOp<InputTypes, Context, Functor, OutputTypeMap>::BinaryElementwiseWithArgsOp(const caffe2::OperatorDef&, caffe2::Workspace*)’: .../pytorch/caffe2/operators/elementwise_ops.h:106:189: error: ‘GetSingleArgument<bool>’ is not a member of ‘caffe2::BinaryElementwiseWithArgsOp<InputTypes, Context, Functor, OutputTypeMap>’ BinaryElementwiseWithArgsOp(const OperatorDef& operator_def, Workspace* ws) Pull Request resolved: pytorch#10510 Reviewed By: orionr Differential Revision: D9319742 Pulled By: mingzhe09088 fbshipit-source-id: ce59e3db14539f071f3c20301e77ca36a6fc3f81

…iants (pytorch#10496) Summary: - fixes pytorch#6219 - removed invariants at pytorch#4707 - assume a sparse tensor with coalesced=true when: 1. its elements are unique and 2. the indices are in sorted order Pull Request resolved: pytorch#10496 Differential Revision: D9311214 Pulled By: weiyangfb fbshipit-source-id: 167fa5a8e9e5f9c800db02f728a1194029f7e4f3

pytorch#10257) Summary: Initial jenkins builds / test scripts for ppc64le. Pull Request resolved: pytorch#10257 Differential Revision: D9331278 Pulled By: ezyang fbshipit-source-id: 6d9a4f300a0233faf3051f8151beb31786dcd838

…orch#10379) Summary: Background: we run pytorch in embedded C++ pipelines, running in C++ GUIs in https://github.com/Kitware/VIAME and without this addition, the call was failing with the below error, but only on certain windows platforms/configurations: OSError: [WinError6] The handle is invalid At: C:\Program Files\VIAME\Python36\site-packages\torch\cuda_init_.py(162):_lazy_init C:\Program Files\VIAME\Python36\site-packages\torch\nn\modules\module.py(249): <lambda> C:\Program Files\VIAME\Python36\site-packages\torch\nn\modules\module.py(182): _apply C:\Program Files\VIAME\Python36\site-packages\torch\nn\modules\module.py(176): _apply C:\Program Files\VIAME\Python36\site-packages\torch\nn\modules\module.py(249): cuda C:\Program Files\VIAME\lib\python3.6None\site-packages\kwiver\arrows\pytorch\pytorch_resnet_f_extractor.py(74):_init_ C:\Program Files\VIAME\lib\python3.6None\site-packages\kwiver\processes\resnet_descriptors.py(132): _configure Pull Request resolved: pytorch#10379 Differential Revision: D9330772 Pulled By: ezyang fbshipit-source-id: 657ae7590879004558158d3c4abef2ec11d9ed57

…boxes than specified. (pytorch#10390) Summary: Pull Request resolved: pytorch#10390 Fixed a bug in box_with_nms_limit where it may produce more bounding boxes than specified. * The original code first finds the threshold for the boxes at the 'detectons_per_im' position, and filters out boxes lower than the threshold. * In some cases that there are multiple boxes have the same threshold, the op will return more boxes than 'detectons_per_im'. Reviewed By: wat3rBro Differential Revision: D9252726 fbshipit-source-id: 63f40829bcd275cb181692bc7547c384cee01499

Summary: We can't rely on the ATen fallback pathway here because we need to parse out the constant attributes explicitly Pull Request resolved: pytorch#10513 Reviewed By: dzhulgakov Differential Revision: D9322133 Pulled By: jamesr66a fbshipit-source-id: 52af947e6c44532ef220cb4b94838ca838b5df06

Summary: Pull Request resolved: pytorch#10395 Order switch ops (NCHW2NHWC and NHWC2NCHW) were only supporting 2D images. This diff generalizes them to 1D and 3D, and also add a unit test we didn't have. Reviewed By: protonu Differential Revision: D9261177 fbshipit-source-id: 56e7ec54c9a8fb71781ac1336f3f28cf024b4bda

Summary: I've implemented affine grid generation for volumetric (5d) inputs. The implementation is based off of the spatial implementation, extended by one dimension. I have a few questions about my implementation vs. the existing one that I will add inline. I have some extensive test cases for the forward pass here: https://gist.github.com/elistevens/6e3bfb20d8d0652b83bd16b3e911285b However, they use `pytest.fixture` extensively, so I'm not sure the best way to incorporate them into the pytorch test suite. Suggestions? I have not tested backwards at all. Diff probably best viewed with whitespace changes ignored. Thanks for considering! Pull Request resolved: pytorch#8322 Differential Revision: D9332335 Pulled By: SsnL fbshipit-source-id: 1b3a91d078ef41a6d0a800514e49298fd817e4df

…torch#10531) Summary: Pull Request resolved: pytorch#10531 fixed a naming issue in pairwise_similarity Reviewed By: huayuli00 Differential Revision: D9331716 fbshipit-source-id: d7de36f20504c08b1c7871ccdffa343221a3da0c

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

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

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: This disables the symbolic override hacks and makes tracing emit the recently added ATen ops for RNNs (`aten::lstm`, `aten::gru`, ...). I managed to reuse pretty much all of the translation code for their symbolics. zdevito Pull Request resolved: pytorch#10638 Differential Revision: D9385830 Pulled By: apaszke fbshipit-source-id: ff06ef7b1ae7c3b7774825e0991bc3887e1ff59b

Summary: Pull Request resolved: pytorch#10239 Make Conv + BN fusion also work for 3D convolutions Reviewed By: duc0 Differential Revision: D9176314 fbshipit-source-id: 6604aa569c5c3afdb4480a5810890bc617e449c4

Summary: Pull Request resolved: pytorch#10827 Reviewed By: boryiingsu Differential Revision: D9484567 fbshipit-source-id: 275eddc9406b5f427d72c0ab9b0da481b5e59ece

Summary: Pull Request resolved: pytorch#10696 Differential Revision: D9437963 Pulled By: cpuhrsch fbshipit-source-id: 7217682f5e4b69c73d943411d738e4892bb465f5

Summary: Update all the caller for the new interface Reviewed By: highker Differential Revision: D9323167 fbshipit-source-id: a39335ceb402db0719f5f2314085ba9a81380308

Summary: Pull Request resolved: pytorch#10854 Reviewed By: ezyang Differential Revision: D9498721 Pulled By: Jorghi12 fbshipit-source-id: 4018383fea5a2a6baff7183b0c0197a4b7a09f20

…ytorch#10844) Summary: Please review the expects carefully to make sure there are no regressions. I tried to go over them one by one when they changed, but it's sometimes easy to miss finer details. Summary of changes: - Renamed `TensorType` to `CompleteTensorType`. Added a new `TensorType` which records only the scalar type, number of dimensions, and device of a value. The argument behind the rename is to encourage people to use `CompleteTensorType` less, as most passes will only have limited information available. To make transition easier `complete_type->cast<TensorType>()` works, and makes our passes work with both kinds of specialization if they don't need extra the extra detail. - Renamed `ArgumentSpec` to `CompleteArgumentSpec`. Added a new `ArgumentSpec`, which matches argument only at the level of the new `TensorType`. - Shape analysis can process graphs with both `CompleteTensorType` and `TensorType`. - Fuser was a part that heavily relied on full shape information being available. Now, we simply try to fuse the largest possible graphs, and have to do run-time checks to make sure they match the code we generate. If they don't, we fall back to regular interpretation. The shape checks are implementing using an optimized method exploiting algebraic properties of shapes with broadcasting, and the relations of broadcasting with pointwise ops. A full written proof of correctness of the shape checking algorithm is included in a comment in `graph_fuser.cpp`. zdevito ezyang mruberry ngimel csarofeen Pull Request resolved: pytorch#10844 Differential Revision: D9498705 Pulled By: apaszke fbshipit-source-id: 0c53c2fcebd871cc2a29c260f8d012276479cc61

Summary: Signed-off-by: Edward Z. Yang <ezyang@fb.com> Pull Request resolved: pytorch#10883 Differential Revision: D9513997 Pulled By: ezyang fbshipit-source-id: 37db956e57d86471323d284869bb844f5a4753ac

Summary: Pull Request resolved: pytorch#10889 Differential Revision: D9512589 Pulled By: gchanan fbshipit-source-id: 8b2b26c9f3a4da31a46f684793ab237e9ef9a323

Summary: PackedSequence is never supposed to be created by user, but unfortunately some community repo is already doing this (e.g., [here](https://github.com/huggingface/torchMoji/blob/7c191048ce906fc0404fe156827d97cb990ebecb/torchmoji/model_def.py#L218-L229)). Some change we made break the calling pattern `PackedSequence(data=x, batch_sizes=y)`. This patch adds back support for that. Pull Request resolved: pytorch#9864 Differential Revision: D9011739 Pulled By: SsnL fbshipit-source-id: 0e2012655d7f4863ec54803550df30874ec35d75

Summary: The scalar situation has gotten a lot better and now we can remove all instances of FIXME_zerol(). cc zdevito Pull Request resolved: pytorch#10900 Differential Revision: D9514206 Pulled By: zou3519 fbshipit-source-id: e4e522f324126c5454cd6de14b832d2d1f6cb0ce

Summary: - Added `__repr__` for Constraints and Transforms. - Arguments passed to the constructor are now rendered with :attr: Closes pytorch#10884 Pull Request resolved: pytorch#10894 Differential Revision: D9514161 Pulled By: apaszke fbshipit-source-id: 4abf60335d876449f2b6477eb9655afed9d5b80b

Summary: I missed these in pytorch#10900 cc apaszke jamesr66a zdevito Pull Request resolved: pytorch#10905 Differential Revision: D9516748 Pulled By: zou3519 fbshipit-source-id: a5c3e3b65a33c339d5c4e9fc160462c3d35705f3

Summary: Pull Request resolved: pytorch#10859 Reviewed By: newstzpz Differential Revision: D9498312 fbshipit-source-id: 08b8a596f774c9102286019f286ca0b74d1f5304

…es. (pytorch#10812) Summary: * Fix the necessary pathways so that tuples and lists can be inputs to the script. * prevent linear algebra functions from being run in shape prop because they frequently will error out for nonsense data. * favor schema-driven python input conversion where possible. remaining cases where we directly create Stacks without schema are only for debugging * Make the error messages when calling script/trace functions more pythonic * Simplify FlattenTuples -- now that tuples are supported we can choose to only flatten tuples when needed. This may have to be revisited pending onnx test results, but is necessary for making tuple io work. Pull Request resolved: pytorch#10812 Differential Revision: D9477982 Pulled By: zdevito fbshipit-source-id: ed06fc426e6ef6deb404602a26c435a7fc40ea0c

Summary: Pull Request resolved: pytorch#10909 Differential Revision: D9516837 Pulled By: gchanan fbshipit-source-id: fad7e3284e74c599b873ebaae2dcdf5013505855

…ytorch#10877) Summary: Pull Request resolved: pytorch#10877 change default value of DeviceOption.numa_node_id to 0 and use has_numa_node_id() to check existence Reviewed By: ilia-cher Differential Revision: D9473891 fbshipit-source-id: 91ac6a152f445644691023110c93d20a3ce80d43

Summary: Previously when tracing slicing & select negative indices would get normalized, fixing the index to the size of the traced tensor. This makes the behavior the same as script so aten::select with negative indices is emitted. Pull Request resolved: pytorch#10560 Differential Revision: D9493614 Pulled By: eellison fbshipit-source-id: ce7a8bae59863723247208d86b9f2948051ccc6c

…ch#10833) Summary: Commits: 1. Make `torch.cuda.*` take device objects 2. Update `torch.distributed` docs to emphasize calling `torch.cuda.set_device` before `init_process_group` Pull Request resolved: pytorch#10833 Differential Revision: D9514241 Pulled By: SsnL fbshipit-source-id: 2497464305fb1e63d6c495291a5744aaa7e2696e

Summary: The goal of this PR is to enable miopen engine(for hip devices) for recurrent operator and also enable corresponding unit test. bddppq petrex Pull Request resolved: pytorch#10840 Differential Revision: D9518980 Pulled By: bddppq fbshipit-source-id: 214661e79a47c5dc6b712ef0fba986bd99db051f

Summary: Moved kl div loss to aten. benchmarks for 5000 iterations on input size (1000,100) New ``` cuda: forward [0.9736350309103727, 0.9922929517924786, 0.9694818360731006] input requires_grad=True: backward [0.5595634011551738, 0.558339926879853, 0.5546616851352155] double backward [1.2445648494176567, 1.2245905152522027, 1.2349751549772918] target requires_grad=True: backward (new C++) [0.9489959231577814, 0.9553070571273565, 0.9556351029314101] double backward (new C++) [1.8184774098917842, 1.8164670099504292, 1.845708406995982] cpu: forward (new C++) [7.892430987209082, 8.3068826389499, 7.985283812973648] input requires_grad=True: backward (new C++) [4.328460982069373, 4.45323242014274, 4.27946363389492] double backward (new C++) [5.153504415880889, 4.629372010007501, 4.712803596165031] target requires_grad=True: backward (new C++) [3.4181493939831853, 3.3771288259886205, 3.7086612950079143] double backward (new C++) [0.21922698011621833, 0.1858532396145165, 0.19477044604718685] ``` Old ``` cuda: forward [3.101281268056482, 3.068499860819429, 3.0527669726870954] input requires_grad=True: backward [0.5650290949270129, 0.5730433077551425, 0.5588279226794839] double backward [1.1287697306834161, 1.13834543293342, 1.1298578432761133] target requires_grad=True: backward [0.9470391101203859, 0.9560198178514838, 0.9750375030562282] double backward [1.85760727385059, 1.7989214668050408, 1.788982989732176] cpu: forward (new C++) [12.474591840058565, 12.511441555805504, 12.666544185951352] input requires_grad=True: backward (new C++) [7.660991386976093, 7.449987292289734, 7.513917901087552] double backward (new C++) [4.073225498665124, 4.264980792999268, 4.429787891916931] target requires_grad=True: backward (new C++) [3.448499082121998, 3.9072313378565013, 3.2433970272541046] double backward (new C++) [2.126378359273076, 1.9045450473204255, 1.7932004742324352] ``` Pull Request resolved: pytorch#10336 Differential Revision: D9213636 Pulled By: li-roy fbshipit-source-id: 27cc530f6276f58d35dc7a1d56dfc758a0fc4a7b

Summary: Pull Request resolved: pytorch#10824 API additions: - Tensor(c10::intrusive_ptr<TensorImpl,UndefinedTensor>&&) - Tensor(const c10::intrusive_ptr<TensorImpl,UndefinedTensor>&) - Tensor::operator=(Tensor&&) && (for completeness sake) - TensorBase::unsafeGetTensorImpl() - TensorBase::unsafeReleaseTensorImpl() - TensorBase::getIntrusivePtr() - TensorImpl::type_id() - Tensor::set_data() - Tensor::is_same(Tensor) - Tensor::use_count() - Tensor::type_id() - Tensor::scalar_type() - WeakTensor::is_same(WeakTensor) - intrusive_ptr::weak_use_count() - weak_intrusive_ptr::weak_use_count() - c10::raw::intrusive_ptr::{incref,decref,make_weak} - c10::raw::weak_intrusive_ptr::{incref,decref,lock} API changes: - Tensor::pImpl is no longer public (and now named tensor_impl_) - Most methods accessed this way are now accessible on Tensor maybe_zero_dim() and set_wrapped_number() being prominent exceptions (they are now accessed through unsafeGetTensorImpl()) - Type is no longer friend of Tensor - TensorBase::reset(TensorImpl*) is deleted - TensorBase::reset(TensorImpl*, bool should_retain) is deleted - TensorBase::swap(TensorBaseImpl&) is deleted; use std::swap instead - TensorBase::get() is deleted; use unsafeGetTensorImpl() instead - TensorBase::detach() is deleted; use unsafeReleaseTensorImpl() instead - TensorBase::retain() is deleted; use _raw_incref() instead - TensorBase::release() is deleted; use _raw_decref() instead - WeakTensor lost most of its methods (it no longer inherits from TensorBase) - TensorImpl::storage() is now a const method - Tensor(TensorBase) constructor removed, instead we go through getIntrusivePtr(). I'm not sure about this change; I happened to have accidentally removed the TensorBase constructor and decided to fix call sites, but I could go the other way. - detail::set_data() is deleted; use Tensor::set_data() instead - c10::raw_intrusive_ptr_target removed; use the functions in c10::raw instead. (The reason for this change, is that it is invalid to cast an intrusive_ptr_target* to a raw_intrusive_ptr_target* to take advantage of the methods. But there is no reason the incref/decref methods shouldn't also work on intrusive_ptr_target; it is primarily an API consideration. We can be more standards compliant by keeping them as functions, which are universally applicable.) - intrusive_ptr::reclaim() and weak_intrusive_ptr::reclaim() now work on pointers of the NullType. (This counts as a bug fix, because the documentation specified that pointers produced by release() are valid to reclaim(), and a release() on a null intrusive_ptr produces the NullType::singleton()) Bug fixes: - Dispatch code for mutable references incorrectly returned a reference to a value argument (which would immediately go out of scope). They now correctly return a tensor by value. - intrusive_ptr copy/move assignment did not work correctly when an object was assigned to itself. We now check for this case and no-op if so. (This bug manifested itself as a Tensor mysteriously becoming an UndefinedTensor after lines of code like 'x = x.mul_(y)') Other changes: - The checked cast functions in Utils.h have now been renamed and detemplatized into checked unwrap functions. - Added type_id() and scalar_type() methods to Tensor - pImpl is no longer public - Documented what the && overloads are doing - All occurrences of 'new TensorImpl' (and similar spellings, like 'new THTensor') have been expunged. This is NO LONGER a valid way to create a new tensor, and if you do this, upon your first incref, you will catch an ASSERT failure saying that only tensors created by intrusive_ptr::release() are valid to reclaim(). Use c10::make_intrusive instead in this situation. - IValue is adjusted to use intrusive_ptr instead of Retainable, and all other sub-classes of Retainable were modified to use intrusive_ptr. When doing this, I had to make the constructors of sub-classes like ConstantList public, so that c10::make_intrusive could invoke them. Fortunately, if you incorrectly stack allocate a ConstantList, and then try to get an intrusive_ptr to it, it will fail, as stack allocated ConstantLists have refcount 0. - IValue very narrowly sidesteps the problem of handling NullType, as it considers intrusive_ptr<TensorImpl> identical to intrusive_ptr<TensorImpl, UndefinedTensor> which is not always true. This was always the case, but there's now a comment explaining what's going on. Some MSVC bugs were uncovered during the preparation of this patch. They are documented as comments in the code. Reviewed By: gchanan Differential Revision: D9481140 fbshipit-source-id: 14a8ea0c231ed88b5715fb86d92730926f9f92fc

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

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

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

James Reed and others added 30 commits August 14, 2018 18:13

remove implicit conversion to cpu (pytorch#10416)

5d27d68

Summary: Fixes pytorch#9934 Pull Request resolved: pytorch#10416 Differential Revision: D9276252 Pulled By: ailzhang fbshipit-source-id: ea7d9d4f9390edefcd0865a98498f6c4307c291d

Propagate NaN through threshold (pytorch#10277)

254dedf

Summary: Fixes pytorch#10238 Pull Request resolved: pytorch#10277 Reviewed By: SsnL Differential Revision: D9199825 Pulled By: soumith fbshipit-source-id: 8ee7f9a72d9546d429f311c3f6028461d3c93fe2

Increase tolerance in ConvBN test

fb09292

Summary: reduce flakiness of test Reviewed By: Maratyszcza Differential Revision: D9344877 fbshipit-source-id: 24d5e1b873f94d816c980f3b7db93248cf10aca5

Revert D9276252: [pytorch][PR] remove implicit conversion to cpu

6f14202

Differential Revision: D9276252 Original commit changeset: ea7d9d4f9390 fbshipit-source-id: 5977bf90d4c84b47e15bc8266cc3ce5602c4e05f

apaszke and others added 24 commits August 24, 2018 20:25

Conv BN fusion for 3D conv (pytorch#10239)

8253cfa

Summary: Pull Request resolved: pytorch#10239 Make Conv + BN fusion also work for 3D convolutions Reviewed By: duc0 Differential Revision: D9176314 fbshipit-source-id: 6604aa569c5c3afdb4480a5810890bc617e449c4

Create class constant for string literal 'blob_names'

17dac3e

Summary: Pull Request resolved: pytorch#10827 Reviewed By: boryiingsu Differential Revision: D9484567 fbshipit-source-id: 275eddc9406b5f427d72c0ab9b0da481b5e59ece

Cache isContiguous and numel

d632ccd

Summary: Pull Request resolved: pytorch#10696 Differential Revision: D9437963 Pulled By: cpuhrsch fbshipit-source-id: 7217682f5e4b69c73d943411d738e4892bb465f5

Update mobile predictor caller's interface

ddc37d7

Summary: Update all the caller for the new interface Reviewed By: highker Differential Revision: D9323167 fbshipit-source-id: a39335ceb402db0719f5f2314085ba9a81380308

Handling failing test on ROCm.

9679fc5

Summary: Pull Request resolved: pytorch#10854 Reviewed By: ezyang Differential Revision: D9498721 Pulled By: Jorghi12 fbshipit-source-id: 4018383fea5a2a6baff7183b0c0197a4b7a09f20

Begin a bestiary of MSVC/NVCC bugs. (pytorch#10883)

3aaad3e

Summary: Signed-off-by: Edward Z. Yang <ezyang@fb.com> Pull Request resolved: pytorch#10883 Differential Revision: D9513997 Pulled By: ezyang fbshipit-source-id: 37db956e57d86471323d284869bb844f5a4753ac

Remove ability of Scalars to hold Tensors.

c3271b5

Summary: Pull Request resolved: pytorch#10889 Differential Revision: D9512589 Pulled By: gchanan fbshipit-source-id: 8b2b26c9f3a4da31a46f684793ab237e9ef9a323

fix xfails involving literals (pytorch#10905)

35beecf

Summary: I missed these in pytorch#10900 cc apaszke jamesr66a zdevito Pull Request resolved: pytorch#10905 Differential Revision: D9516748 Pulled By: zou3519 fbshipit-source-id: a5c3e3b65a33c339d5c4e9fc160462c3d35705f3

move HeatmapMaxKeypointOp unittest to oss

f64f6ee

Summary: Pull Request resolved: pytorch#10859 Reviewed By: newstzpz Differential Revision: D9498312 fbshipit-source-id: 08b8a596f774c9102286019f286ca0b74d1f5304

Fix at::optional compile problems on Windows CUDA.

7842b6d

Summary: Pull Request resolved: pytorch#10909 Differential Revision: D9516837 Pulled By: gchanan fbshipit-source-id: fad7e3284e74c599b873ebaae2dcdf5013505855

sync with upstream

5dd23c9

update docs

0a337b4

rohithkrn requested a review from ezyang as a code owner August 28, 2018 02:24

rohithkrn removed the request for review from ezyang August 28, 2018 02:25

rohithkrn merged commit 3fd5e93 into ROCm:caffe2_specific Aug 29, 2018

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sync with upstream #156

sync with upstream #156

rohithkrn commented Aug 28, 2018

sync with upstream #156

sync with upstream #156

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rohithkrn commented Aug 28, 2018