Merge from upstream #149

iotamudelta · 2018-08-24T01:49:50Z

No description provided.

Summary: This is part of moving the (base) Type to ATen/core; Some Type methods have default argument of type THNN Reduction. Pull Request resolved: pytorch#10703 Differential Revision: D9406060 Pulled By: gchanan fbshipit-source-id: 789bb3387c58bd083cd526a602649105274e1ef6

Summary: Pull Request resolved: pytorch#10721 - Fix compilation warning "declaration of 'i' shadows a previous local [-Werror=shadow-compatible-local]" Reviewed By: newstzpz Differential Revision: D9419688 fbshipit-source-id: 76efc3688782ce4ead3c89e7069211736febfac2

…h#10640) Summary: Set the build environment before installing sccache in order to make sure the docker images have the links set up. Pull Request resolved: pytorch#10640 Reviewed By: yf225 Differential Revision: D9399593 Pulled By: Jorghi12 fbshipit-source-id: a062fed8b7e83460fe9d50a7a27c0f20bcd766c4

Summary: Pull Request resolved: pytorch#10629 Reviewed By: bddppq Differential Revision: D9381106 fbshipit-source-id: 03d42c95d17a70a68fe0f38dad68f1793996dfce

Summary: Pull Request resolved: pytorch#10716 title Reviewed By: idning Differential Revision: D9417357 fbshipit-source-id: 0f71805b1d64a46791d6ee4d8620763f878ffdb6

Summary: Pull Request resolved: pytorch#10373 Differential Revision: D9240316 Pulled By: ezyang fbshipit-source-id: f35c500f61f86e6be405e8bd4040db5146224984

Summary: Let's run CI tests to see what fails given the changes that just landed in pytorch#10624 cc mingzhe09088 ezyang Yangqing Pull Request resolved: pytorch#10692 Reviewed By: mingzhe09088 Differential Revision: D9423617 Pulled By: orionr fbshipit-source-id: 3bda1f118d13f8dd8e823727c93167cae747d8cf

…ytorch#10593) Summary: This should resolves "error C2280: 'std::unique_ptr<caffe2::ObserverBase<caffe2::OperatorBase>,std::default_delete<_Ty>> &std::unique_ptr<_Ty,std::default_delete<_Ty>>::operator =(const std::unique_ptr<_Ty,std::default_delete<_Ty>> &)': attempting to reference a deleted function" from Visual Studio. It should also make error message more human-readable in case if something really messed up. Pull Request resolved: pytorch#10593 Reviewed By: orionr Differential Revision: D9436397 Pulled By: mingzhe09088 fbshipit-source-id: 31711667297b4160196134a34365da734db1c61d

) Summary: This PR adds support for using custom ops in ScriptModules, the last step for our custom op strategy. You can now write ``` import torch torch.ops.load_library('libcustom_ops.so') class Model(torch.jit.ScriptModule): def __init__(self): super(Model, self).__init__() torch.jit.script_method def forward(self, input): return torch.ops.custom.op(input) + 1 model = Model() model.forward(torch.ones(5)) # Works model.save("model.pt") # Works model = torch.jit.load("model.pt") # Works ``` You can then load the `model.pt` in C++ and execute its `forward` method! Missing for this was the fact that the script compiler didn't know to convert `ops.custom.op` into a `BuiltinFunction` which then emits a function call. For this I came up with the following strategy inside `torch/csrc/jit/scrip/init.cpp`: 1. When we access `torch.ops`, we return a `CustomOpValue` (subclass of `PythonValue`), whose purpose is only to return a `CustomOpNamespaceValue` (subclass of `PythonValue`) whenever something under it is accessed. 2. `CustomOpNamespaceValue` will then for each field accessed on it return a `BuiltinFunction`. This doesn't reduce performance for any calls that are not to `torch.ops` (as opposed to inspecting every function call's name the call site, for example). I also had to fix `BuiltinFunction` to not assume the namespace is always `aten::`. A lot of other changes are just tidying up the Python and C++ test harness before I integrate it in CI. zdevito dzhulgakov Pull Request resolved: pytorch#10610 Differential Revision: D9387832 Pulled By: goldsborough fbshipit-source-id: c00f431db56c7502a66fe1f813fe78067f428ecb

Summary: Fixes `__getattr__` to adhere to its Python API contract, and wraps `range()` call in a list since it does not return one anymore in Python 3. Pull Request resolved: pytorch#10525 Reviewed By: ezyang Differential Revision: D9441360 Pulled By: tomdz fbshipit-source-id: d489c0e7cefecc4699ca866fd55ddbfa629688d4

Summary: Pull Request resolved: pytorch#9827 changed unitilized to uninitialized Reviewed By: jerryzh168 Differential Revision: D8995509 fbshipit-source-id: 94518d5542a7bff49fcb9a4505c0c7a959746f78

…ta (pytorch#10718) Summary: zdevito et al came to the conclusion that the ONNX spec does not mandate the widening conversion of integral types when serializing tensor data into raw_data, as opposed to serializing the data into int32_data. PyTorch recently made this change in the export code, which caused import in caffe2 to break because it did not match semantics. This fixes that Pull Request resolved: pytorch#10718 Differential Revision: D9423712 Pulled By: jamesr66a fbshipit-source-id: 479fbae67b028bf4f9c1ca1812c2c7b0c6cccd12

Summary: hotfix for B*8 Differential Revision: D9444060 fbshipit-source-id: 368f8463e684c39ec0ac18bcb11a7b6132d9f874

Summary: The optimized code for `linear()` which uses `addmm` when a bias is given was duplicated three times in the ATen and the C++ API. Let's just have `at::linear` and use that everywhere. apaszke ezyang (who mentioned this in pytorch#10481) Pull Request resolved: pytorch#10755 Differential Revision: D9443881 Pulled By: goldsborough fbshipit-source-id: a64862d1649b5961043d58401625ec267d97d9f3

…rch#10736) Summary: -Fixed C2 core.CreateOperator debug info assignment -Improving core.Net.reroute_tensor Pull Request resolved: pytorch#10736 Differential Revision: D9426659 Pulled By: harouwu fbshipit-source-id: 90caf848c88854e17e568d5f6910dc6c81fd000a

Summary: cc cranmer fixes pytorch#10751 Pull Request resolved: pytorch#10760 Differential Revision: D9444473 Pulled By: SsnL fbshipit-source-id: a4036773a93981801c1283d69f86e30cb0fe3d6d

pytorch#10488) Summary: ``` Use intrusive_ptr in Storage; replace unique_ptr<Storage> with Storage This patch does two major changes: - It replaces the use of Retainable in Storage with a new implementation based on intrusive_ptr. This will be necessary because Caffe2 will be using this class to implement intrusive_ptrs, and we need to line these up for the merge. One good thing about the new implementation is that the default copy/move constructors/assignment operators and destructor work automatically, instead of needing to be hardcoded into Storage/Tensor. - It replaces all places where we returned std::unique_ptr<Storage> with Storage, collapsing an unnecessary double indirection that is no longer necessary now that we have correctly working copy/move constructors. I didn't initially want to do step (2), but it was very important to eliminate all bare uses of new Storage and new StorageImpl, and this making the API change was the most straightforward way to do this. HOW TO FIX YOUR CODE IN THE NEW API - You no longer need to dereference the result of tensor.storage() to pass it to set. So, instead of: x.set_(*y.storage()); just write: x.set_(y.storage()); - If you were accessing methods on StorageImpl via the pImpl() method, you must use the dot operator to run pImpl(). Even better; just drop pImpl, we now have method forwarding. So, instead of: storage->pImpl()->data(); just do: storage->data(); // storage.pImpl()->data() works too but is not as recommended - storage->getDevice() is no more; instead use storage->device().index() MISC CODE UPDATES - retain, release, weak_retain, weak_release and weak_lock are now reimplemented using the "blessed API", and renamed to make it clearer that their use is discouraged. - nvcc OS X and general OS X portability improvements to intrusive_ptr - A new comment in intrusive_ptr describing how stack allocated intrusive_ptr_targets work differently than heap allocated ones from c10::make_intrusive CAVEAT EMPTOR - THStorage_weakRetain used to work on strong pointers, but it NO LONGER works with intrusive_ptr. You must reclaim the strong pointer into a real strong pointer, construct a weak pointer from it, and then release the strong and weak pointers. See StorageSharing.cpp for an example. ``` Pull Request resolved: pytorch#10488 Reviewed By: gchanan Differential Revision: D9306134 Pulled By: ezyang fbshipit-source-id: 02d58ef62dab8e4da6131e1a24834a65c21048e2

Summary: Pull Request resolved: pytorch#10362 This diff implements a manual export from PyText's CRF module to the caffe2 CRF layer. Note that most of the changes in caffe2/python/crf.py are just formatting changes, the only relevant change is the new class CRFUtils. Reviewed By: hikushalhere Differential Revision: D9234126 fbshipit-source-id: 1a67d709034660e8b3d5ac840560b56de63e3f69

…cDevice Summary: The code in Operator::SyncDevice had some duplicate logic and using FinishDeviceComputation sufficed in this case. Reviewed By: yinghai Differential Revision: D9348288 fbshipit-source-id: d8d874bab491e6d448fcd5fa561a8b99d502753b

Summary: Signed-off-by: Edward Z. Yang <[email protected]> Pull Request resolved: pytorch#10731 Differential Revision: D9423675 Pulled By: ezyang fbshipit-source-id: 37221e11d84cc3672b944af598ea229a1d4c38cc

Summary: I've tested locally that this works to build static and non-static binaries with and without CUDA. In terms of ongoing testing, I am working on incorporating this into the release package generation. Pull Request resolved: pytorch#10754 Differential Revision: D9457423 Pulled By: anderspapitto fbshipit-source-id: aa1dcb17c67c0f0c493a9cf93aca4a6e06b21666

Summary: - Similar functionality as NumPy - Added doc string - Added tests Differential Revision: D9240850 Pulled By: SsnL fbshipit-source-id: 1d04cfadb076e99e03bdf699bc41b8fac06831bf

Summary: Pull Request resolved: pytorch#10053 Tensor in Pytorch 1.0 will have Tensor -> TensorImpl -> Storage -> StorageImpl In this diff we split Storage from Tensor in order to align with this design. We'll have Tensor -> Storage -> StorageImpl after this diff Reviewed By: ezyang Differential Revision: D9384781 fbshipit-source-id: 40ded2437715a3a2cc888ef28cbca9a25b1d5350

…pytorch#10702) Summary: Don't regex against strings that may have come from the backtrace. Better to just not regex at all. Pull Request resolved: pytorch#10702 Reviewed By: ezyang Differential Revision: D9406154 Pulled By: jsrmath fbshipit-source-id: 9b17abee2a6e737a32c05f1e3963aef4b6638a47

Summary: Pull Request resolved: pytorch#10758 Differential Revision: D9467554 Pulled By: bddppq fbshipit-source-id: 6853ccd96ac3209e062c110913ea37d6840c8134

…ops (pytorch#10634) Summary: Pull Request resolved: pytorch#10634 ``` Trying example: test_speed_of_rand_quantization(self=<caffe2.caffe2.python.operator_test.rand_quantization_op_speed_test.TestSpeedFloatToFusedRandRowwiseQuantized testMethod=test_speed_of_rand_quantization>, bitwidth_=2, random_=True, data_shape_=array([1024, 1224]), gc=, dc=[, device_type: 1]) Sub+Scale+Sum time: 1.9944190979003908 ms Quantizing time: 2.080512046813965 ms (1.0431669296609765X) De-quantizing time: 0.7375001907348633 ms (0.36978195380863577X) ``` ``` Trying example: test_speed_of_rand_quantization(self=<caffe2.caffe2.python.operator_test.rand_quantization_op_speed_test.TestSpeedFloatToFusedRandRowwiseQuantized testMethod=test_speed_of_rand_quantization>, bitwidth_=1, random_=True, data_shape_=array([1024, 1224]), gc=device_type: 1, dc=[, device_type: 1]) Sub+Scale+Sum time: 1.6691923141479492 ms Quantizing time: 7.500243186950684 ms (4.493336761366071X) De-quantizing time: 1.1209726333618164 ms (0.6715658967876477X) ``` Reviewed By: jspark1105 Differential Revision: D8849770 fbshipit-source-id: 2bb2bac7e633f647f38e419ce980b8958f3bcae2

Summary: Since pytorch#8958 was merged, the BatchSampler samples 0d tensors from WeightedRandomSampler instead of integers. It significantly reduces performance. This PR fix it the same way as pytorch#10361 fix DistributedSampler. Pull Request resolved: pytorch#10636 Differential Revision: D9423869 Pulled By: zou3519 fbshipit-source-id: f94da2d4cccf70e63beea6cfc3d1230b5610ae44

pytorch#10740) Summary: I included "legacy" includes in the old spots for Backend, Generator, Layout; it seemed unlikely that the other ones had direct user includes. This is another step on the path to move Type/Tensor to ATen/core. Pull Request resolved: pytorch#10740 Reviewed By: ezyang Differential Revision: D9435888 Pulled By: gchanan fbshipit-source-id: 89f4f0f445d4498a059d3a79069ba641b22bbcac

Summary: goldsborough Pull Request resolved: pytorch#10627 Reviewed By: ezyang Differential Revision: D9384411 Pulled By: apaszke fbshipit-source-id: ce4f6edb9ffbd0c7e320b9347da10399de472150

Summary: Since ONNX opset version >5, Reshape changed semantics to take a shape tensor as input instead of relying on `shape` attribute to decide what shape to reshape to. ONNXIFI op has been postponing this change as some of the backends such as TensorRT were not ready. Now that the backends have adopted this semantics, we can remove the legacy mode and output opset version 7 ONNX models. This change also flushes out some of the bugs and new requirement. - Converting shape info into int64 tensor - Fix a bug when we output the shape tensor in the mapped workspace instead of the original workspace Pull Request resolved: pytorch#10848 Reviewed By: houseroad Differential Revision: D9495121 Pulled By: yinghai fbshipit-source-id: a6f44a89274c35b33fae9a429813ebf21d9a3d1a

iotamudelta · 2018-08-24T19:28:54Z

@pytorchbot retest this please

…e needed. (pytorch#10180) Summary: When matching schema, first try to match without adding TensorToNum conversions. Then make another pass where TensorToNum conversions are allowed. Pull Request resolved: pytorch#10180 Differential Revision: D9438153 Pulled By: eellison fbshipit-source-id: 80541b5abd06e9d4187e89dda751f44dab6f58c5

Summary: The schema_ field is a private and internal cache for nodes, and no methods meant to manipulate it should be publicly visible. This call wasn't even necessary at its call site, since removeInput will reset the schema by itself. zdevito jamesr66a Pull Request resolved: pytorch#10822 Reviewed By: zdevito Differential Revision: D9498683 Pulled By: apaszke fbshipit-source-id: 42e1743e3737cb7d81f88e556204487d328c0e47

Summary: Fixing the printing of IValue lists, which didn't work previously. Pull Request resolved: pytorch#10777 Differential Revision: D9474264 Pulled By: eellison fbshipit-source-id: 0c7d6e7ecaa3f7908b131ac9f1036f19ac4f8b4f

…ont for kernelPointwiseApply. Differential Revision: D9492561 Original commit changeset: d0f0e2ab7180 fbshipit-source-id: fc822e63b11866195ff7883f360338a41e25d9e2

Summary: This is along the way of removing Tensor as a member of the tagged union in Scalar. This simplifies ordering dependencies, because currently Scalar and Tensor both depend on each other (so we introduce a TensorBase). Also, this API isn't particularly useful publicly: we can't autograd through Scalars, so you still need a Tensor overload basically everywhere anyway. I'm undecided what the final API should be here. We could keep a Tensor constructor on Scalar, but have it generate a local scalar; this is convenient but given this API used to be non-synchronizing, it may not be the best. For now, I'm just using _local_scalar, which is clear, although we should get rid of the prefix _ if that's the API we intend to promote. Pull Request resolved: pytorch#10852 Reviewed By: ezyang Differential Revision: D9496766 Pulled By: gchanan fbshipit-source-id: 16f39b57536b9707132a5a4d915650c381bb57db

…rch#10301) Summary: **Summary**: This PR is a followup of mruberry's pytorch#9318. It tries to achieve the following: - Specializing std common math functions for `at::Half` type. - Create `CUDANumerics.cuh` to contain necessary parts from `THCNumerics.cuh`. - Update `THCNumerics.cuh` with new usage and comments to demonstrate the best practice for developers and hence, making way for its deprecation. - Remove legacy/redundant code path. - Remove unused CUDA HALF macros (see separate PR pytorch#10147) **Comments**: `CUDANumerics.cuh` contains mathematical functions that are either not in the std namespace or are specialized for compilation with CUDA NVCC or CUDA NVRTC. This header is derived from the legacy `THCNumerics.cuh`. Following are some rationale behind why some functions were kept while others were removed: - All arithmetic can now be done in ATen using binary cuda kernel or CUDA tensor pointwise apply (check pytorch#8919 and `CUDAApplyUtils`). `at::Half` comparisons rely on implicit conversion to float. - Functions that are c/c++ standard compliant, have been specialized for user defined types, for instance, the std namespace has been opened up for `at::Half`, that defines math function definitions for `at::Half`. Check `Half-inl.h` - Some standard compliant functions are specialized here for performance reasons. For instance, `powi` is used for `pow` calculation on integral types. Moreover, `abs`, `isinf`, `isnan` are specialized to save one API call vs when used with std. Although this is subject to change, depending on if we really care about saving one API call. - Numeric limits such as `max/min` is removed since they call standard defines. Moreover, numeric limits for `at::Half` is present in `Half-inl.h`. I understood that HIP has some issue with `std::numeric_limits` and this the related github issue I found: ROCm/hip#374. AlexVlx mentions that the issue can be avoided by launching `std::numeric_limits` in `__device__`. Since, we are launching lambdas with device contexts, I don't see an issue why `std::numeric_limits` won't compile on HIP if launched with device context within a kernel, unless I am not aware of the real reason why max/min was there in THCNumerics in the first place. (Haven't ever tried a build with HIP). Here are some reference PRs that was handy in refactoring TH into ATen: - pytorch#6786 - pytorch#5475 - pytorch#9401 - pytorch#8689 - pytorch#8919 Pull Request resolved: pytorch#10301 Differential Revision: D9204758 Pulled By: soumith fbshipit-source-id: 09f489c1656458c02367b6cd31c3eeeca5acdc8a

Summary: Resubmission of pytorch#10755 with fix for ONNX ezyang jamesr66a Pull Request resolved: pytorch#10799 Differential Revision: D9482168 Pulled By: goldsborough fbshipit-source-id: 85d4bdfcf0d451f2e7a1c83c5f5415cdd6caacdc

Summary: After making changes internally, really remove the nanopb submodule. Finalizes pytorch#10772 Reviewed By: yns88 Differential Revision: D9504582 fbshipit-source-id: 4517607e5c8054a255c3984b8265f48fede2935b

Summary: Pull Request resolved: pytorch#10759 Adding a basic registry pattern to pybindstate so that we can have separate 'cc' files register module updates. This is substantially cleaner than using multiple pybind modules (which have been known to cause bugs) Reviewed By: bddppq Differential Revision: D9441878 fbshipit-source-id: af9e9e98385e92b58ca50e935678328c62684d8e

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

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 #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 #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&)#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&)#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 #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 #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 #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 #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 #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&)#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&)#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 #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 #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

Allow a tighter timeout during training than during init. Init includes the first train step, as well as any loading and setup. It can be slower and less predictable due to various factors including lazy initialization or jit compilation. After the first train step, we expect more predictable runtime and benefit from a tighter timeout to give quick feedback on a hang. Tested by pasting this code in 2 places ``` if dp_mesh.get_local_rank() == 0 and train_state.step == 1: import time time.sleep(10) ``` (a) before calling set_pg_timeout, which did not cause a timeout (b) after calling set_pg_timeout, which timed out

gchanan and others added 30 commits August 21, 2018 08:54

Make ONNX_ATEN_FALLBACK as internal default option

b23d59c

Summary: Pull Request resolved: pytorch#10629 Reviewed By: bddppq Differential Revision: D9381106 fbshipit-source-id: 03d42c95d17a70a68fe0f38dad68f1793996dfce

Add util function from core type to dtype (pytorch#10716)

9c321a8

Summary: Pull Request resolved: pytorch#10716 title Reviewed By: idning Differential Revision: D9417357 fbshipit-source-id: 0f71805b1d64a46791d6ee4d8620763f878ffdb6

Add arguments __repr__ in Distribution base class

8a1739b

Summary: Pull Request resolved: pytorch#10373 Differential Revision: D9240316 Pulled By: ezyang fbshipit-source-id: f35c500f61f86e6be405e8bd4040db5146224984

fix typo in error message (pytorch#9827)

6325e5a

Summary: Pull Request resolved: pytorch#9827 changed unitilized to uninitialized Reviewed By: jerryzh168 Differential Revision: D8995509 fbshipit-source-id: 94518d5542a7bff49fcb9a4505c0c7a959746f78

Add enforce back to converter.cc

a2ca634

Summary: hotfix for B*8 Differential Revision: D9444060 fbshipit-source-id: 368f8463e684c39ec0ac18bcb11a7b6132d9f874

Fixes *fft docs (pytorch#10760)

abb209e

Summary: cc cranmer fixes pytorch#10751 Pull Request resolved: pytorch#10760 Differential Revision: D9444473 Pulled By: SsnL fbshipit-source-id: a4036773a93981801c1283d69f86e30cb0fe3d6d

Delete THD master_worker (pytorch#10731)

2276351

Summary: Signed-off-by: Edward Z. Yang <[email protected]> Pull Request resolved: pytorch#10731 Differential Revision: D9423675 Pulled By: ezyang fbshipit-source-id: 37221e11d84cc3672b944af598ea229a1d4c38cc

Add matrix_rank (pytorch#10338)

5fb9b31

Summary: - Similar functionality as NumPy - Added doc string - Added tests Differential Revision: D9240850 Pulled By: SsnL fbshipit-source-id: 1d04cfadb076e99e03bdf699bc41b8fac06831bf

Reduce rocm link time with ThinLTO

754ec9e

Summary: Pull Request resolved: pytorch#10758 Differential Revision: D9467554 Pulled By: bddppq fbshipit-source-id: 6853ccd96ac3209e062c110913ea37d6840c8134

Merge remote-tracking branch 'upstream/master' into ifu

ce957ac

apaszke and others added 2 commits August 24, 2018 11:26

Ignore stack frames coming from python3 object file (pytorch#10627)

8130b1a

Summary: goldsborough Pull Request resolved: pytorch#10627 Reviewed By: ezyang Differential Revision: D9384411 Pulled By: apaszke fbshipit-source-id: ce4f6edb9ffbd0c7e320b9347da10399de472150

iotamudelta and others added 22 commits August 24, 2018 15:01

Skip failing test.

104646e

Merge remote-tracking branch 'upstream/master' into ifu

5834fd9

Re-sync with internal repository (pytorch#10868)

474684c

Merge remote-tracking branch 'upstream/master' into ifu

f88ee77

fix ivalue printing for lists (pytorch#10777)

0ef5cfd

Summary: Fixing the printing of IValue lists, which didn't work previously. Pull Request resolved: pytorch#10777 Differential Revision: D9474264 Pulled By: eellison fbshipit-source-id: 0c7d6e7ecaa3f7908b131ac9f1036f19ac4f8b4f

Revert D9492561: [pytorch][PR] Moving the operator argument to the fr…

0d5584d

…ont for kernelPointwiseApply. Differential Revision: D9492561 Original commit changeset: d0f0e2ab7180 fbshipit-source-id: fc822e63b11866195ff7883f360338a41e25d9e2

Create at::linear (pytorch#10799)

148ea2a

Summary: Resubmission of pytorch#10755 with fix for ONNX ezyang jamesr66a Pull Request resolved: pytorch#10799 Differential Revision: D9482168 Pulled By: goldsborough fbshipit-source-id: 85d4bdfcf0d451f2e7a1c83c5f5415cdd6caacdc

Remove the nanopb submodule

c172ffb

Summary: After making changes internally, really remove the nanopb submodule. Finalizes pytorch#10772 Reviewed By: yns88 Differential Revision: D9504582 fbshipit-source-id: 4517607e5c8054a255c3984b8265f48fede2935b

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

Merge remote-tracking branch 'upstream/master' into ifu

5a43ef6

Skip: new failure.

231f80a

iotamudelta merged commit 1e8e84b into ROCm:master Aug 27, 2018

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Merge from upstream #149

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iotamudelta commented Aug 24, 2018

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Merge from upstream #149

Merge from upstream #149

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iotamudelta commented Aug 24, 2018

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iotamudelta commented Aug 24, 2018

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