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Merge upstream into master #232

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Merge upstream into master #232

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apaszke and others added 30 commits September 26, 2018 11:45
Summary: Pull Request resolved: pytorch#12052

Differential Revision: D10044910

Pulled By: apaszke

fbshipit-source-id: 015ef372966d7594e1b450e348d457429f6ef20d
Summary:
Couple questions:

1) I used the log1p implementation in pytorch#8969 as a guide especially for testing.  I'm not sure what the ```skipIfROCM``` annotation is for, so unsure if i need it for my test.

2) I implemented the branching logic in the narrow function itself; is this the right place to do so?  I noticed that there a number of places where sparse-specific logic is handled with just an if statement in this file.  Or should I implement a separate dispatch in native_functions.yml as in the log1p?

And of course, happy to make any any other updates/changes that I may have missed as well.  This is my first PR to the project.
Pull Request resolved: pytorch#11342

Differential Revision: D9978430

Pulled By: weiyangfb

fbshipit-source-id: e73dc20302ab58925afb19e609e31f4a38c634ad
Summary:
Pull Request resolved: pytorch#12057

Add simple put operators for various types of stats

Reviewed By: mlappelbaum

Differential Revision: D9925268

fbshipit-source-id: cec02b0027d2d0ef3d35741be4b02c429d492810
Summary:
Pull Request resolved: pytorch#12065

Had compilation issues using CAFFE_DURATION in some contexts, specifically due to namespace resolution. Since this is a macro, it should fully qualify.

Reviewed By: heslami

Differential Revision: D10036132

fbshipit-source-id: b8d55dfe5e991ca702ce5b7483f0ffc699882c85
…ch#12108)

Summary:
An efficient atomicAdd for halfs has been added in `cuda_fp16.h` in CUDA 10:
```__CUDA_FP16_DECL__ __half atomicAdd(__half *address, __half val);```

Through this change, PyTorch will be able to utilize efficient atomicAdd when building with CUDA 10.
Pull Request resolved: pytorch#12108

Differential Revision: D10053385

Pulled By: soumith

fbshipit-source-id: 946c90691a8f6bdcf6d6e367a507ac3c9970b750
Summary: Pull Request resolved: pytorch#12114

Reviewed By: soumith

Differential Revision: D10060349

Pulled By: JoelMarcey

fbshipit-source-id: ed88bf95f78742b089adb043e88613a5db006a10
…#12040)

Summary:
We generate specialized list operations for int, float, and Tensor lists so that small lists of integers like the arguments to conv do not involve tons of boxing code.

This PR adds a fallback GenericList for List types that contain any other type. It does so by adding type variables to `jit::Type`, and machinery for matching/replacing the type variables during `tryMatchSchema` and operator lookup.

It also modifies the builtin list ops to include a fallback that works on a GenericList object that simply holds IValues. This is distinguished from IValue's tuple type so that conversion to/from Python still happens losslessly.
Pull Request resolved: pytorch#12040

Differential Revision: D10037098

Pulled By: zdevito

fbshipit-source-id: 0c5f2864d12e7d33554bf34cc29e5fb700dde150
Summary:
Pull Request resolved: pytorch#12032

See title

Reviewed By: dinhviethoa

Differential Revision: D10023757

fbshipit-source-id: dbf0a043b2afab767f052bd4c5e8de13e0f57dcc
Summary:
I wrote some high level docs for the larger PyTorch C++ universe and the C++ frontend specifically. Happy for reviews, but let's please also land this ASAP so I can point users at something that looks more ready baked than the C++ docs landing page (https://pytorch.org/cppdocs) does right now.

ezyang soumith

CC ebetica
Pull Request resolved: pytorch#12079

Differential Revision: D10080785

Pulled By: goldsborough

fbshipit-source-id: 3028de41373f307468eb1e3802aa27871c93b2e3
Summary:
migrant all tests in aten to use gtest except of basic.cpp
Sinc features of gtest are different from catch test, some of the tests has been re-writted with similar meaning.

Basic test has some version conflict with valgrind according to CI, therefore this testcase is still implementing catch.
It will be resolved by a different pr.

Pull Request resolved: pytorch#11846

Differential Revision: D10080860

Pulled By: zrphercule

fbshipit-source-id: 439d4cf33fb6ccbe79b797860342853c63e59081
Summary:
You can't GetDeviceType an undefined tensor, so test for this case
first.  This allows you to safely move tensors out of blobs.

Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Pull Request resolved: pytorch#12125

Reviewed By: smessmer

Differential Revision: D10080075

Pulled By: ezyang

fbshipit-source-id: bb99b089b6daa9d4db99015208f939d7ce4d4a79
Summary:
Apply weight decay for Adam in-place instead of via copy.

Synced offline with soumith , who mentioned that it should be OK. This is also consistent with other optimizers, e.g. https://github.com/pytorch/pytorch/blob/eee01731a5d33d5be58d875711bd2577e38dbddf/torch/optim/sgd.py#L93
Pull Request resolved: pytorch#12107

Reviewed By: soumith

Differential Revision: D10071787

Pulled By: jma127

fbshipit-source-id: 5fd7939c79039693b225c44c4c80450923b8d673
Summary:
This does 6 things:

- add c10/util/Registry.h as the unified registry util
  - cleaned up some APIs such as export condition
- fully remove aten/core/registry.h
- fully remove caffe2/core/registry.h
- remove a bogus aten/registry.h
- unifying all macros
- set up registry testing in c10

Also, an important note that we used to mark the templated Registry class as EXPORT - this should not happen, because one should almost never export a template class. This PR fixes that.
Pull Request resolved: pytorch#12077

Reviewed By: ezyang

Differential Revision: D10050771

Pulled By: Yangqing

fbshipit-source-id: 417b249b49fed6a67956e7c6b6d22374bcee24cf
…#10726 (pytorch#11579)

Summary:
As reported in Issue pytorch#10726, the jit compiler, when running on ppc64le,  may produce an isomorphic output but fail a diff test against the expected output file.  The expected output file is created from a test that was ran on x86_64.  This ensures that if ppc64le test output is different, the output is instead compared to an expected output file created when the test is run on a ppc64le system.
Pull Request resolved: pytorch#11579

Differential Revision: D10080890

Pulled By: soumith

fbshipit-source-id: 7249bf6b5dfa7c853368a3688a982bc9ed642bc9
Summary:
Pull Request resolved: pytorch#12132

TSIA. No code change involved.

Reviewed By: bwasti

Differential Revision: D10083237

fbshipit-source-id: bdab029015b9d0f1fa1f866c68aa5945cc68db9d
…ytorch#11686)

Summary:
the speed-up of a single operation is up to 6X on BDW.
Pull Request resolved: pytorch#11686

Reviewed By: yinghai

Differential Revision: D9828129

Pulled By: wesolwsk

fbshipit-source-id: 7dbacea90609e18438f6fe1229c641937d0696c8
Summary:
Add observers for ideep operators.
Pull Request resolved: pytorch#9093

Reviewed By: salexspb

Differential Revision: D9952949

Pulled By: yinghai

fbshipit-source-id: 1678d1a738f8781dc75eb3cb9dfb309f7b7934fb
…#11975)

Summary:
Export symbols for pybind and other libs after caffe2 rebase
Pull Request resolved: pytorch#11975

Differential Revision: D10042615

Pulled By: yinghai

fbshipit-source-id: 6de562d99403099113093716834abc51bf726e94
…() (pytorch#11970)

Summary:
Pull Request resolved: pytorch#11970

Adds an ATen-core-headers target, which caffe2_cpu_internal depends
on, and makes ATen-core depend on caffe2_headers.  If you link against
ATen-core, you must ALSO link against caffe2_cpu_internal; if you
link against caffe2_cpu_internal, you must ALSO link against ATen-core,
otherwise you'll have undefined symbols.

Then, we merge template data<T>() method with Caffe2 implementation,
demonstrating that includes to Caffe2 (core) from ATen/core are working

Reviewed By: jerryzh168

Differential Revision: D9967509

fbshipit-source-id: 3d220c38b2c3c646f8ff2884fdcc889fa9276c7a
Summary:
Pull Request resolved: pytorch#11971

- Switched TensorImpl::data<T>() to use Storage::unsafe_data<T>() to work
  around an outstanding bug in the Storage::data<T>() implementation
  where it only works on Ts which are valid ScalarType
- Qualify a bunch of identifiers which still live in caffe2:: namespace
- strides returns an IntList now
- s/update_strides/update_to_contiguous_strides/
- Correctly compute type_id_ for the Storage only constructor from Caffe2.
  This is special cased to only work for CPU and CUDA dense tensors.
- Fix some signed-unsigned comparisons in Caffe2 code (OSS build for
  ATen/core has more restrictive warning tests.)

Reviewed By: jerryzh168

Differential Revision: D9995559

fbshipit-source-id: 9c74032e011189e1c7e9a98d20f2bd1e25ad2e5c
Summary:
reduce sum negative indices turn to positive as caffe2 not supporting it. GE/LE symbolic operand order is wrong..
Pull Request resolved: pytorch#12123

Reviewed By: houseroad

Differential Revision: D10095467

Pulled By: wanchaol

fbshipit-source-id: eb20248de5531c25040ee68b89bd18743498138d
Summary: Pull Request resolved: pytorch#11972

Reviewed By: gchanan, Yangqing, jerryzh168

Differential Revision: D9995633

fbshipit-source-id: 6b4645c9d4bb0bc4301cd4bcfa76cf85331b8379
… is_variable

Summary: Pull Request resolved: pytorch#12087

Reviewed By: jerryzh168

Differential Revision: D10050781

fbshipit-source-id: 0b6c9d7caf3b1000691f86fcc7f2ef203936a29f
Summary: Pull Request resolved: pytorch#12089

Reviewed By: jerryzh168

Differential Revision: D10050859

fbshipit-source-id: 843067aacfa2a519657220bc39a0f499582a48a4
Summary:
Pull Request resolved: pytorch#12090

This is a slight pessimization because we need to do a
full recompute of is_contiguous(), even though a modification
of dim-0 is guaranteed to preserve contiguity.

Reviewed By: jerryzh168

Differential Revision: D10050905

fbshipit-source-id: b99233e21c9f4275b0db6e76740462e5430ce152
Summary: Pull Request resolved: pytorch#12091

Reviewed By: jerryzh168

Differential Revision: D10051012

fbshipit-source-id: 772ecd2e377f7d4e1ae510c1f647f6c8b71e5a57
Summary: Pull Request resolved: pytorch#12092

Reviewed By: jerryzh168

Differential Revision: D10051005

fbshipit-source-id: c36d1c8d12fb41baf8d1a1a9f38776deeff242de
Summary: Pull Request resolved: pytorch#12094

Reviewed By: jerryzh168

Differential Revision: D10051079

fbshipit-source-id: 87fb91f31c33ce9b64c4654e79e0131ae391cd78
Summary: Pull Request resolved: pytorch#12095

Reviewed By: jerryzh168

Differential Revision: D10051078

fbshipit-source-id: f56b6fc5d1cb8ae4b636e88efe607fe65cc1d7a0
Summary: Pull Request resolved: pytorch#12096

Reviewed By: jerryzh168

Differential Revision: D10051126

fbshipit-source-id: a9b95d00512a0b4e6339d4f3f0bb180dd0c79247
weiyangfb and others added 24 commits September 30, 2018 11:55
Summary:
- fix pytorch#8330
- add `torch.copy_(Sparse, Sparse)` with autograd support
Pull Request resolved: pytorch#9005

Differential Revision: D8987885

Pulled By: weiyangfb

fbshipit-source-id: b317a41da22ee1eae2835622a0ed28a6771a3a06
Summary:
We're waiting for the libtorch links to show up on the website. I had a fake link in the docs so far which is misleading. This PR changes it to a temporary markdown file until the web people fix the site tomorrow.
Pull Request resolved: pytorch#12212

Differential Revision: D10121872

Pulled By: goldsborough

fbshipit-source-id: f1bd1315f7333b9168e99983f3f6b679c9b0c52a
…ainInputGradient (pytorch#12186)

Summary:
Pull Request resolved: pytorch#12186

specialized implementation, preconvert embeddings to float and do everything on fp32

Reviewed By: jspark1105

Differential Revision: D10100603

fbshipit-source-id: 3255b4addb6fda24722bd519163099f5d354d084
Summary:
Pull Request resolved: pytorch#12205

We're more interested in testing the performance of DNNLOWP_ACC16 engine.

Reviewed By: llyfacebook

Differential Revision: D10121080

fbshipit-source-id: 7def38be838feb7636f7dd0c8ed352c2df398ec1
Summary:
Allow trailing commas in assign statements or tuples, which also allows single element tuples.
Pull Request resolved: pytorch#11723

Differential Revision: D10052162

Pulled By: eellison

fbshipit-source-id: 344d908a3ad942a23ebd9f341794bc9734226aa8
…pytorch#11688)"" (pytorch#12121)

Summary:
Pull Request resolved: pytorch#12121

Pull Request resolved: pytorch#12055

Original commit changeset: 6ca9de65b707

Reviewed By: ezyang

Differential Revision: D10033396

fbshipit-source-id: ca9f4b2f7ef0561f619b833415d394a8b9972bf4
…ch#12101)

Summary:
Pull Request resolved: pytorch#12101

clean up some duplicate test code

Reviewed By: ZolotukhinM

Differential Revision: D10051914

fbshipit-source-id: 698ff144a85e8c70572116c5ddb415cd2396b4e3
Summary:
Original commit changeset: f5614a5d2607

D9986213 is causing Multifeed Aggregator a [huge performance different](https://our.intern.facebook.com/intern/ads/analyze_canary/412951953278781781/) and is blocking aggregator push since last Friday night: https://fburl.com/feedtools/b6izvwjz
We need to land this revert ASAP to unblock aggregator push.

Reviewed By: orionr

Differential Revision: D10123245

fbshipit-source-id: d83da8e00a1250f5d09811a0a587c127e377aab2
Summary:
- revert `\gamma` changes at landed PR: pytorch#12126
- minor fix for docs of `torch.norm()`

SsnL
Pull Request resolved: pytorch#12214

Differential Revision: D10127337

Pulled By: weiyangfb

fbshipit-source-id: 15eb8abda39ec9e8b2e815e2a22096cae786995a
Differential Revision:
D10123245

Original commit changeset: d83da8e00a12

fbshipit-source-id: fca91fea58b7df208edc2e218a1d514f9821ec7b
Summary:
Pull Request resolved: pytorch#11949

Unify naming style

Reviewed By: yinghai

Differential Revision: D9931227

fbshipit-source-id: b6956bd98ed8625623e4747d616989f9f3a2ed46
Summary:
Pull Request resolved: pytorch#12183

Adding more debug info printed from plan executor

Reviewed By: manojkris

Differential Revision: D10113104

fbshipit-source-id: dddc9aec8012c8575ab305033388412fdaaac537
Summary: Pull Request resolved: pytorch#12182

Differential Revision: D10129630

Pulled By: bddppq

fbshipit-source-id: f0217336474b807f03f84a4b8052ce92a6e3564b
Summary:
Pull Request resolved: pytorch#12122

We are deprecating support for c extensions. Please use cpp extension in the future.

Reviewed By: Yangqing

Differential Revision: D10060541

fbshipit-source-id: 4f7149e06a254bd7af463fd7aa9740f65369963a
Summary: Pull Request resolved: pytorch#12223

Differential Revision: D10133697

Pulled By: bddppq

fbshipit-source-id: c1de99afccdad415ac1beb85d3b8ab44f9b58738
Summary:
Considered four different existing formats: 1) static graph, 2) torch script, 3) pickle files, 4) PyTorch C++ serialize APIs
Pull Request resolved: pytorch#12149

Reviewed By: BIT-silence

Differential Revision: D10098106

Pulled By: houseroad

fbshipit-source-id: 94ec7fc57c842e50fae5286ddeda657a4967a07a
Summary: Original commit changeset: 0cea9469cea0

Differential Revision: D10135814

fbshipit-source-id: 9563361cc00f4ce5dc2e903c0fcb10643ee9af26
Summary: Pull Request resolved: pytorch#12240

Reviewed By: jerryzh168

Differential Revision: D10133933

fbshipit-source-id: 05935bd527177f936c1d08626888d43dedbf5ce4
Summary:
Pull Request resolved: pytorch#12200

moved crf_viterbi_op, copied crf_predict and crf_viterbi_test to oss

Reviewed By: Yangqing

Differential Revision: D10118341

fbshipit-source-id: 51e30e57d280d6ca75fc0b488f743794f23b589f
Summary:
Pull Request resolved: pytorch#11848

Avoid crossing the boundary between devices when using DFS scheduling

Reviewed By: romain-intel

Differential Revision: D9931091

fbshipit-source-id: 1f3cf52127830048ed1db50b01677b66eeed8b32
Summary:
Skip the recently introduced tests that fail on ROCm
Pull Request resolved: pytorch#12229

Differential Revision: D10138146

Pulled By: bddppq

fbshipit-source-id: a0f1ff97fabb71f635a468e8030dbe32d388de49
…his case. (pytorch#12236)

Summary:
Strides appear to cause a huge memory regression in some of our internal
training workflows. This diff stems the bleeding, while we figure out exactly
what happened.

Pull Request resolved: pytorch#12236

Reviewed By: dzhulgakov

Differential Revision: D10134319

fbshipit-source-id: 1547c89a65c05473c409c0977c19c99dcaefb89c
…d"" (pytorch#12232)

Summary:
Pull Request resolved: pytorch#12232

Original commit changeset: fca91fea58b7

This adds proper modifications to the DeviceType <->DeviceOption conversion code added in D10033396

Reviewed By: jerryzh168

Differential Revision: D10132473

fbshipit-source-id: 801ef777e2950982cb47b48051b1471a0a91e64b
Differential Revision:
D10098106

Original commit changeset: 94ec7fc57c84

fbshipit-source-id: 38f729b0970618f38359797b806cbbcd865f4715
@rohithkrn rohithkrn requested a review from ezyang as a code owner October 2, 2018 17:14
@rohithkrn rohithkrn removed the request for review from ezyang October 2, 2018 17:15
@rohithkrn rohithkrn closed this Oct 2, 2018
lcskrishna pushed a commit to lcskrishna/pytorch that referenced this pull request May 15, 2023
When tensor is resized, reference array to it's sizes may become invalid. Make a copy in advance.

<details>
<summary>ASAN report</summary>

```
=================================================================
==1115867==ERROR: AddressSanitizer: heap-use-after-free on address 0x61000013d790 at pc 0x03ff8e7da360 bp 0x03fff53c83a0 sp 0x03fff53c8390
READ of size 8 at 0x61000013d790 thread T0
    #0 0x3ff8e7da35f in c10::SymInt::is_heap_allocated() const /home/user/pytorch/c10/core/SymInt.h:154
    ROCm#1 0x3ff8e7da35f in c10::SymInt::maybe_as_int() const /home/user/pytorch/c10/core/SymInt.h:215
    ROCm#2 0x3ff8e7d0a6d in c10::SymInt::sym_eq(c10::SymInt const&) const /home/user/pytorch/c10/core/SymInt.cpp:69
    ROCm#3 0x3ff7a9ab0bd in c10::SymInt::operator==(c10::SymInt const&) const /home/user/pytorch/c10/core/SymInt.h:177
    ROCm#4 0x3ff7a9aaedd in bool std::__equal<false>::equal<c10::SymInt const*, c10::SymInt const*>(c10::SymInt const*, c10::SymInt const*, c10::SymInt const*) /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-
v11/bits/stl_algobase.h:1162
    ROCm#5 0x3ff7a9aae4b in bool std::__equal_aux1<c10::SymInt const*, c10::SymInt const*>(c10::SymInt const*, c10::SymInt const*, c10::SymInt const*) /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/
stl_algobase.h:1211
    ROCm#6 0x3ff7a9aae05 in bool std::__equal_aux<c10::SymInt const*, c10::SymInt const*>(c10::SymInt const*, c10::SymInt const*, c10::SymInt const*) /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/s
tl_algobase.h:1219
    ROCm#7 0x3ff7a9aad97 in bool std::equal<c10::SymInt const*, c10::SymInt const*>(c10::SymInt const*, c10::SymInt const*, c10::SymInt const*) /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/stl_alg
obase.h:1556
    ROCm#8 0x3ff4b23c771 in c10::ArrayRef<c10::SymInt>::equals(c10::ArrayRef<c10::SymInt>) const /home/user/pytorch/c10/util/ArrayRef.h:188
    ROCm#9 0x3ff4cb91bc1 in bool c10::operator!=<c10::SymInt>(c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>) /home/user/pytorch/c10/util/ArrayRef.h:341
    ROCm#10 0x3ff6d1b57ff in torch::ADInplaceOrView::resize_(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) /home/user/pytorch/torch/csrc/autograd/Variab
leTypeManual.cpp:408
    ROCm#11 0x3ff6d1e59c7 in c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c1
0::MemoryFormat>), &torch::ADInplaceOrView::resize_>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>
> >::operator()(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) /home/user/pytorch/aten/src/ATen/core/boxing/impl/WrapFunctionIntoFunctor.h:13
    ROCm#12 0x3ff6d1e59c7 in c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10:
:ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>), &torch::ADInplaceOrView::resize_>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::Sy
mInt>, c10::optional<c10::MemoryFormat> > >, at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)>::call(c10::OperatorKernel*, c10::Disp
atchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) /home/user/pytorch/aten/src/ATen/core/boxing/impl/make_boxed_from_unboxed_functor.h:480
    ROCm#13 0x3ff51ca5129 in at::Tensor const& c10::callUnboxedKernelFunction<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> >(void*, c10::OperatorKernel*,
c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>&&, c10::optional<c10::MemoryFormat>&&) /home/user/pytorch/aten/src/ATen/core/boxing/KernelFunction_impl.h:50
    ROCm#14 0x3ff51ca6e8f in at::Tensor const& c10::KernelFunction::call<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> >(c10::OperatorHandle const&, c10::D
ispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const /home/user/pytorch/aten/src/ATen/core/boxing/KernelFunction_impl.h:90
    ROCm#15 0x3ff51ca6e8f in at::Tensor const& c10::Dispatcher::redispatch<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> >(c10::TypedOperatorHandle<at::Ten
sor const& (at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)> const&, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)
const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:656
    ROCm#16 0x3ff5182006b in c10::TypedOperatorHandle<at::Tensor const& (at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)>::redispatch(c10::DispatchKeySet, at::Tensor const&, c
10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:492
    ROCm#17 0x3ff5182006b in at::_ops::resize_::redispatch(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) aten/src/ATen/Operators_4.cpp:2144
    ROCm#18 0x3ff6d1d5e07 in at::redispatch::resize__symint(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) aten/src/ATen/RedispatchFunctions.h:2847
    ROCm#19 0x3ff6d1bbb67 in torch::autograd::VariableType::(anonymous namespace)::resize_(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) /home/user/pyto
rch/torch/csrc/autograd/VariableTypeManual.cpp:243
    ROCm#20 0x3ff6d1bd197 in c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c1
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::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:
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.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*,
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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
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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
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er/pytorch/torch/csrc/autograd/generated/python_variable_methods.cpp:13417
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    ROCm#208 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065
    ROCm#209 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#210 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114
    ROCm#211 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53
    ROCm#212 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114
    ROCm#213 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123
    ROCm#214 0x3ffa2e05447 in call_function Python/ceval.c:5891
    ROCm#215 0x3ffa2dff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181
    ROCm#216 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46
    ROCm#217 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065
    ROCm#218 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#219 0x3ffa2c8a695 in _PyObject_FastCallDictTstate Objects/call.c:153
    ROCm#220 0x3ffa2c8b271 in _PyObject_Call_Prepend Objects/call.c:431
    ROCm#221 0x3ffa2d3f307 in slot_tp_call Objects/typeobject.c:7494
    ROCm#222 0x3ffa2c8a933 in _PyObject_MakeTpCall Objects/call.c:215
    ROCm#223 0x3ffa2df0081 in _PyObject_VectorcallTstate Include/cpython/abstract.h:112
    ROCm#224 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123
    ROCm#225 0x3ffa2e05447 in call_function Python/ceval.c:5891
    ROCm#226 0x3ffa2dffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231
    ROCm#227 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46
    ROCm#228 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065
    ROCm#229 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#230 0x3ffa2c8ab15 in PyVectorcall_Call Objects/call.c:255
    ROCm#231 0x3ffa2c8ac65 in _PyObject_Call Objects/call.c:290
    ROCm#232 0x3ffa2c8ada9 in PyObject_Call Objects/call.c:317
    ROCm#233 0x3ffa2e059c7 in do_call_core Python/ceval.c:5943
    ROCm#234 0x3ffa2dffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277
    ROCm#235 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46
    ROCm#236 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065
    ROCm#237 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#238 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114
    ROCm#239 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123
    ROCm#240 0x3ffa2e05447 in call_function Python/ceval.c:5891
    ROCm#241 0x3ffa2dff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181
    ROCm#242 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46
    ROCm#243 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065
    ROCm#244 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#245 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114
    ROCm#246 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53
    ROCm#247 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114
    ROCm#248 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123
    ROCm#249 0x3ffa2e05447 in call_function Python/ceval.c:5891
    ROCm#250 0x3ffa2dff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181
    ROCm#251 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46
    ROCm#252 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065
    ROCm#253 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#254 0x3ffa2c8a695 in _PyObject_FastCallDictTstate Objects/call.c:153
    ROCm#255 0x3ffa2c8b271 in _PyObject_Call_Prepend Objects/call.c:431
    ROCm#256 0x3ffa2d3f307 in slot_tp_call Objects/typeobject.c:7494
    ROCm#257 0x3ffa2c8a933 in _PyObject_MakeTpCall Objects/call.c:215

0x61000013d790 is located 80 bytes inside of 192-byte region [0x61000013d740,0x61000013d800)
freed by thread T0 here:
    #0 0x3ffa3237de5 in operator delete(void*) /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_new_delete.cpp:160
    ROCm#1 0x3ff8e7e3221 in c10::TensorImpl::~TensorImpl() /home/user/pytorch/c10/core/TensorImpl.cpp:75

previously allocated by thread T0 here:
    #0 0x3ffa323734f in operator new(unsigned long) /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_new_delete.cpp:99
    ROCm#1 0x3ff4aeeb3d1 in c10::intrusive_ptr<c10::TensorImpl, c10::detail::intrusive_target_default_null_type<c10::TensorImpl> > c10::intrusive_ptr<c10::TensorImpl, c10::detail::intrusive_target_default_nul
l_type<c10::TensorImpl> >::make<c10::intrusive_ptr<c10::StorageImpl, c10::detail::intrusive_target_default_null_type<c10::StorageImpl> >, c10::DispatchKeySet&, caffe2::TypeMeta&>(c10::intrusive_ptr<c10::S
torageImpl, c10::detail::intrusive_target_default_null_type<c10::StorageImpl> >&&, c10::DispatchKeySet&, caffe2::TypeMeta&) /home/user/pytorch/c10/util/intrusive_ptr.h:498
    ROCm#2 0x3ff76f79e17  (/home/user/pytorch/build/lib.linux-s390x-cpython-310/torch/lib/libtorch_cpu.so+0x2fb79e17)

SUMMARY: AddressSanitizer: heap-use-after-free /home/user/pytorch/c10/core/SymInt.h:154 in c10::SymInt::is_heap_allocated() const
Shadow bytes around the buggy address:
  0x100c2000027aa0: fa fa fa fa fa fa fa fa fd fd fd fd fd fd fd fd
  0x100c2000027ab0: fd fd fd fd fd fd fd fd fd fd fd fd fd fd fd fd
  0x100c2000027ac0: fa fa fa fa fa fa fa fa fd fd fd fd fd fd fd fd
  0x100c2000027ad0: fd fd fd fd fd fd fd fd fd fd fd fd fd fd fd fd
  0x100c2000027ae0: fa fa fa fa fa fa fa fa fd fd fd fd fd fd fd fd
=>0x100c2000027af0: fd fd[fd]fd fd fd fd fd fd fd fd fd fd fd fd fd
  0x100c2000027b00: fa fa fa fa fa fa fa fa 00 00 00 00 00 00 00 00
  0x100c2000027b10: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00
  0x100c2000027b20: fa fa fa fa fa fa fa fa 00 00 00 00 00 00 00 00
  0x100c2000027b30: 00 00 00 00 04 fa fa fa fa fa fa fa fa fa fa fa
  0x100c2000027b40: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa
Shadow byte legend (one shadow byte represents 8 application bytes):
  Addressable:           00
  Partially addressable: 01 02 03 04 05 06 07
  Heap left redzone:       fa
  Freed heap region:       fd
  Stack left redzone:      f1
  Stack mid redzone:       f2
  Stack right redzone:     f3
  Stack after return:      f5
  Stack use after scope:   f8
  Global redzone:          f9
  Global init order:       f6
  Poisoned by user:        f7
  Container overflow:      fc
  Array cookie:            ac
  Intra object redzone:    bb
  ASan internal:           fe
  Left alloca redzone:     ca
  Right alloca redzone:    cb
  Shadow gap:              cc
==1115867==ABORTING
```
</details>

<details>
<summary>Additional backtraces (not full)</summary>

Memory deallocation:
```
#0  operator delete (ptr=0x61000013d740) at /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_new_delete.cpp:160
ROCm#1  0x000003ffa77e3222 in c10::TensorImpl::~TensorImpl (this=0x61000013d740) at /home/user/pytorch/c10/core/TensorImpl.cpp:75
ROCm#2  0x000003ff63e76e8c in c10::intrusive_ptr<c10::TensorImpl, c10::UndefinedTensorImpl>::reset_ (this=0x3ffd7ec8230) at /home/user/pytorch/c10/util/intrusive_ptr.h:291
ROCm#3  0x000003ff63e76910 in c10::intrusive_ptr<c10::TensorImpl, c10::UndefinedTensorImpl>::~intrusive_ptr (this=0x3ffd7ec8230) at /home/user/pytorch/c10/util/intrusive_ptr.h:370
ROCm#4  0x000003ff63e67240 in at::TensorBase::~TensorBase (this=0x3ffd7ec8230) at /home/user/pytorch/aten/src/ATen/core/TensorBase.h:80
ROCm#5  0x000003ff63e85ee0 in at::Tensor::~Tensor (this=0x3ffd7ec8230) at aten/src/ATen/core/TensorBody.h:90
ROCm#6  0x000003ff63f67304 in resize__functionalization (dispatchKeySet=..., self=..., size=..., memory_format=...) at /home/user/pytorch/aten/src/ATen/FunctionalizeFallbackKernel.cpp:173
ROCm#7  0x000003ff63f89258 in c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>), &(resize__functionalization(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>))>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat> > >::operator()(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>) (
    this=0x6030000390a0, args=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/boxing/impl/WrapFunctionIntoFunctor.h:13
ROCm#8  c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>), &(resize__functionalization(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>))>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat> > >, at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>)>::call(c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>) (functor=0x6030000390a0, dispatchKeySet=..., args=..., args=...,
    args=...) at /home/user/pytorch/aten/src/ATen/core/boxing/impl/make_boxed_from_unboxed_functor.h:480
ROCm#9  0x000003ff6aca560a in c10::callUnboxedKernelFunction<at::Tensor const&, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat> > (
    unboxed_kernel_func=0x3ff63f88a80 <c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tenso
r const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>), &(resize__functionalization(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>))>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat> > >, at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>)>::call(c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>)>, functor=0x6030000390a0,
    dispatchKeySet=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/boxing/KernelFunction_impl.h:50
ROCm#10 0x000003ff6aca715c in c10::KernelFunction::call<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> > (this=0x6210005e1b28, opHandle=...,
    dispatchKeySet=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/boxing/KernelFunction_impl.h:96
ROCm#11 c10::Dispatcher::redispatch<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> >(c10::TypedOperatorHandle<at::Tensor const& (at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)> const&, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const (
    this=0x3ff919400e0 <c10::Dispatcher::realSingleton()::_singleton>, op=..., currentDispatchKeySet=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:656
ROCm#12 0x000003ff6a82006c in c10::TypedOperatorHandle<at::Tensor const& (at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)>::redispatch(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const (
    this=0x3ff919a07e0 <at::_ops::resize_::redispatch(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)::op>, currentDispatchKeySet=..., args=...,
    args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:492
ROCm#13 at::_ops::resize_::redispatch (dispatchKeySet=..., self=..., size=..., memory_format=...) at /home/user/pytorch/build/aten/src/ATen/Operators_4.cpp:2144
ROCm#14 0x000003ff861d5e08 in at::redispatch::resize__symint (dispatchKeySet=..., self=..., size=..., memory_format=...) at aten/src/ATen/RedispatchFunctions.h:2847
ROCm#15 0x000003ff861b579e in torch::ADInplaceOrView::resize_ (ks=..., self=..., size=..., optional_memory_format=...) at /home/user/pytorch/torch/csrc/autograd/VariableTypeManual.cpp:401
```

Memory access:
```
#0  c10::SymInt::maybe_as_int (this=0x61000013d790) at /home/user/pytorch/c10/core/SymInt.h:215
ROCm#1  0x000003ff734d0a6e in c10::SymInt::sym_eq (this=0x61000013d790, sci=...) at /home/user/pytorch/c10/core/SymInt.cpp:69
ROCm#2  0x000003ff5f6ab0be in c10::SymInt::operator== (this=0x61000013d790, o=...) at /home/user/pytorch/c10/core/SymInt.h:177
ROCm#3  0x000003ff5f6aaede in std::__equal<false>::equal<c10::SymInt const*, c10::SymInt const*> (__first1=0x61000013d790, __last1=0x61000013d7a0, __first2=0x602000015c30)
    at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/stl_algobase.h:1162
ROCm#4  0x000003ff5f6aae4c in std::__equal_aux1<c10::SymInt const*, c10::SymInt const*> (__first1=0x61000013d790, __last1=0x61000013d7a0, __first2=0x602000015c30)
    at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/stl_algobase.h:1211
ROCm#5  0x000003ff5f6aae06 in std::__equal_aux<c10::SymInt const*, c10::SymInt const*> (__first1=0x61000013d790, __last1=0x61000013d7a0, __first2=0x602000015c30)
    at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/stl_algobase.h:1219
ROCm#6  0x000003ff5f6aad98 in std::equal<c10::SymInt const*, c10::SymInt const*> (__first1=0x61000013d790, __last1=0x61000013d7a0, __first2=0x602000015c30)
    at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/stl_algobase.h:1556
ROCm#7  0x000003ff2ff3c772 in c10::ArrayRef<c10::SymInt>::equals (this=0x3ffed7c9900, RHS=...) at /home/user/pytorch/c10/util/ArrayRef.h:188
ROCm#8  0x000003ff31891bc2 in c10::operator!=<c10::SymInt> (a1=..., a2=...) at /home/user/pytorch/c10/util/ArrayRef.h:341
ROCm#9  0x000003ff51eb5800 in torch::ADInplaceOrView::resize_ (ks=..., self=..., size=..., optional_memory_format=...) at /home/user/pytorch/torch/csrc/autograd/VariableTypeManual.cpp:408
ROCm#10 0x000003ff51ee59c8 in c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c
10::MemoryFormat>), &torch::ADInplaceOrView::resize_>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>
 > >::operator()(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) (this=0x6030007dca40, args=..., args=..., args=..., args=...)
    at /home/user/pytorch/aten/src/ATen/core/boxing/impl/WrapFunctionIntoFunctor.h:13
ROCm#11 c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt
>, c10::optional<c10::MemoryFormat>), &torch::ADInplaceOrView::resize_>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<
c10::MemoryFormat> > >, at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)>::call(c10::OperatorKernel*, c10::DispatchKeySet, at::Tenso
r const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) (functor=0x6030007dca40, dispatchKeySet=..., args=..., args=..., args=...)
    at /home/user/pytorch/aten/src/ATen/core/boxing/impl/make_boxed_from_unboxed_functor.h:480
ROCm#12 0x000003ff369a512a in c10::callUnboxedKernelFunction<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> > (
    unboxed_kernel_func=0x3ff51ee51f0 <c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tenso
r const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>), &torch::ADInplaceOrView::resize_>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::Ar
rayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> > >, at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)>::call(c10::OperatorKern
el*, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)>, functor=0x6030007dca40, dispatchKeySet=..., args=..., args=..., args=...)
    at /home/user/pytorch/aten/src/ATen/core/boxing/KernelFunction_impl.h:50
ROCm#13 0x000003ff369a6e90 in c10::KernelFunction::call<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> > (this=0x6210005e1bc8, opHandle=...,
    dispatchKeySet=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/boxing/KernelFunction_impl.h:90
ROCm#14 c10::Dispatcher::redispatch<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> >(c10::TypedOperatorHandle<at::Tensor const& (at::Tensor const&, c10::Arr
ayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)> const&, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const (
    this=0x3ff5d6400e0 <c10::Dispatcher::realSingleton()::_singleton>, op=..., currentDispatchKeySet=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:656
ROCm#15 0x000003ff3652006c in c10::TypedOperatorHandle<at::Tensor const& (at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)>::redispatch(c10::DispatchKeySet, at::Tensor const&,
c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const (
    this=0x3ff5d6a07e0 <at::_ops::resize_::redispatch(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)::op>, currentDispatchKeySet=..., args=...,
    args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:492
ROCm#16 at::_ops::resize_::redispatch (dispatchKeySet=..., self=..., size=..., memory_format=...) at /home/user/pytorch/build/aten/src/ATen/Operators_4.cpp:2144
ROCm#17 0x000003ff51ed5e08 in at::redispatch::resize__symint (dispatchKeySet=..., self=..., size=..., memory_format=...) at aten/src/ATen/RedispatchFunctions.h:2847
ROCm#18 0x000003ff51ebbb68 in torch::autograd::VariableType::(anonymous namespace)::resize_ (ks=..., self=..., size=..., optional_memory_format=...)
    at /home/user/pytorch/torch/csrc/autograd/VariableTypeManual.cpp:243
```
</details>
Pull Request resolved: pytorch#101064
Approved by: https://github.com/Skylion007, https://github.com/albanD
alugorey pushed a commit to alugorey/pytorch that referenced this pull request May 17, 2023
arguments() returns vector member of object returned by schema() call.
When object returned by schema() call is destroyed, the vector is deallocated as well,
it's lifetime isn't extended.

This issue detected while running `pytest -v test/mobile/test_lite_script_type.py -k test_nest_typing_namedtuple_custom_classtype` with ASAN.

<details>
<summary>ASAN output</summary>

```
==1134126==ERROR: AddressSanitizer: heap-use-after-free on address 0x60d0005a5790 at pc 0x03ff844488d8 bp 0x03fff584afe8 sp 0x03fff584afd8
READ of size 8 at 0x60d0005a5790 thread T0
    #0 0x3ff844488d7 in __gnu_cxx::__normal_iterator<c10::Argument const*, std::vector<c10::Argument, std::allocator<c10::Argument> > >::__normal_iterator(c10::Argument const* const&) /usr/lib/gcc/s390x-i
bm-linux-gnu/11/include/g++-v11/bits/stl_iterator.h:1028
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    ROCm#224 0x3ffaaf8b271 in _PyObject_Call_Prepend Objects/call.c:431
    ROCm#225 0x3ffab03f307 in slot_tp_call Objects/typeobject.c:7494
    ROCm#226 0x3ffaaf8a933 in _PyObject_MakeTpCall Objects/call.c:215
    ROCm#227 0x3ffab0f0081 in _PyObject_VectorcallTstate Include/cpython/abstract.h:112
    ROCm#228 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123
    ROCm#229 0x3ffab105447 in call_function Python/ceval.c:5891
    ROCm#230 0x3ffab0ffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231
    ROCm#231 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46
    ROCm#232 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065
    ROCm#233 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#234 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114
    ROCm#235 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123
    ROCm#236 0x3ffab105447 in call_function Python/ceval.c:5891
    ROCm#237 0x3ffab0ff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213
    ROCm#238 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46
    ROCm#239 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065
    ROCm#240 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#241 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114
    ROCm#242 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123
    ROCm#243 0x3ffab105447 in call_function Python/ceval.c:5891
    ROCm#244 0x3ffab0ff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213
    ROCm#245 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46
    ROCm#246 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065
    ROCm#247 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#248 0x3ffaaf8ab15 in PyVectorcall_Call Objects/call.c:255
    ROCm#249 0x3ffaaf8ac65 in _PyObject_Call Objects/call.c:290

0x60d0005a5790 is located 80 bytes inside of 136-byte region [0x60d0005a5740,0x60d0005a57c8)
freed by thread T0 here:
    #0 0x3ffab537de5 in operator delete(void*) /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_new_delete.cpp:160
    ROCm#1 0x3ff55984fdb in __gnu_cxx::new_allocator<std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2> >::deallocate(std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2>*, unsigned long) /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/ext/new_allocator.h:145

previously allocated by thread T0 here:
    #0 0x3ffab53734f in operator new(unsigned long) /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_new_delete.cpp:99
    ROCm#1 0x3ff5598443f in __gnu_cxx::new_allocator<std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2> >::allocate(unsigned long, void const*) /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/ext/new_allocator.h:127
    ROCm#2 0x3fff5849ecf  ([stack]+0xb2ecf)

SUMMARY: AddressSanitizer: heap-use-after-free /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/stl_iterator.h:1028 in __gnu_cxx::__normal_iterator<c10::Argument const*, std::vector<c10::Argument, std::allocator<c10::Argument> > >::__normal_iterator(c10::Argument const* const&)
Shadow bytes around the buggy address:
  0x100c1a000b4aa0: fd fd fd fd fd fd fd fd fd fd fd fa fa fa fa fa
  0x100c1a000b4ab0: fa fa fa fa fd fd fd fd fd fd fd fd fd fd fd fd
  0x100c1a000b4ac0: fd fd fd fd fd fa fa fa fa fa fa fa fa fa fd fd
  0x100c1a000b4ad0: fd fd fd fd fd fd fd fd fd fd fd fd fd fd fd fa
  0x100c1a000b4ae0: fa fa fa fa fa fa fa fa fd fd fd fd fd fd fd fd
=>0x100c1a000b4af0: fd fd[fd]fd fd fd fd fd fd fa fa fa fa fa fa fa
  0x100c1a000b4b00: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa
  0x100c1a000b4b10: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa
  0x100c1a000b4b20: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa
  0x100c1a000b4b30: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa
  0x100c1a000b4b40: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa
Shadow byte legend (one shadow byte represents 8 application bytes):
  Addressable:           00
  Partially addressable: 01 02 03 04 05 06 07
  Heap left redzone:       fa
  Freed heap region:       fd
  Stack left redzone:      f1
  Stack mid redzone:       f2
  Stack right redzone:     f3
  Stack after return:      f5
  Stack use after scope:   f8
  Global redzone:          f9
  Global init order:       f6
  Poisoned by user:        f7
  Container overflow:      fc
  Array cookie:            ac
  Intra object redzone:    bb
  ASan internal:           fe
  Left alloca redzone:     ca
  Right alloca redzone:    cb
  Shadow gap:              cc
==1134126==ABORTING
```

Additional backtraces (not full):
Allocation:
```
#0  __memset_z196 () at ../sysdeps/s390/memset-z900.S:144
ROCm#1  0x000003ff96f3072a in __asan::Allocator::Allocate (this=this@entry=0x3ff97041eb8 <__asan::instance>, size=size@entry=136, alignment=8, alignment@entry=0, stack=<optimized out>,
    stack@entry=0x3ffdbb45d78, alloc_type=<optimized out>, can_fill=true) at /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_allocator.cpp:599
ROCm#2  0x000003ff96f2c088 in __asan::asan_memalign (alignment=alignment@entry=0, size=size@entry=136, stack=stack@entry=0x3ffdbb45d78, alloc_type=alloc_type@entry=__asan::FROM_NEW)
    at /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_allocator.cpp:1039
ROCm#3  0x000003ff96fb73b0 in operator new (size=136) at /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_new_delete.cpp:99
ROCm#4  0x000003ff41404440 in __gnu_cxx::new_allocator<std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2> >::allocate (this=0x3ffdbb468c0,
    __n=1) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/ext/new_allocator.h:127
ROCm#5  0x000003ff414042a0 in std::allocator_traits<std::allocator<std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2> > >::allocate (__a=...,
    __n=1) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/alloc_traits.h:464
ROCm#6  0x000003ff41403b66 in std::__allocate_guarded<std::allocator<std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2> > > (__a=...)
    at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/allocated_ptr.h:98
ROCm#7  0x000003ff4140372a in std::__shared_count<(__gnu_cxx::_Lock_policy)2>::__shared_count<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::vector<c10::Argument, std::allocator<c10::Argument> >, std::vector<c10::Argument, std::allocator<c10::Argument> > > (this=0x3ffdbb47888, __p=@0x3ffdbb47880: 0x0, __a=..., __args=..., __args=..., __args=..., __args=...)
    at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:648
ROCm#8  0x000003ff41403328 in std::__shared_ptr<c10::FunctionSchema, (__gnu_cxx::_Lock_policy)2>::__shared_ptr<std::allocator<c10::FunctionSchema>, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::vector<c10::Argument, std::allocator<c10::Argument> >, std::vector<c10::Argument, std::allocator<c10::Argument> > > (this=0x3ffdbb47880, __tag=..., __args=..., __args=..., __args=..., __args=...) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:1342
ROCm#9  0x000003ff41402f06 in std::shared_ptr<c10::FunctionSchema>::shared_ptr<std::allocator<c10::FunctionSchema>, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::vector<c10::Argument, std::allocator<c10::Argument> >, std::vector<c10::Argument, std::allocator<c10::Argument> > > (
    this=0x3ffdbb47880, __tag=..., __args=..., __args=..., __args=..., __args=...) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr.h:409
ROCm#10 0x000003ff41402b6e in std::allocate_shared<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::vector<c10::Argument, std::allocator<c10::Argument> >, std::vector<c10::Argument, std::allocator<c10::Argument> > > (__a=...,
    __args=..., __args=..., __args=..., __args=...) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr.h:862
ROCm#11 0x000003ff4140215c in std::make_shared<c10::FunctionSchema, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::vector<c10::Argument, std::allocator<c10::Argument> >, std::vector<c10::Argument, std::allocator<c10::Argument> > > (__args=..., __args=..., __args=..., __args=...)
    at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr.h:878
ROCm#12 0x000003ff413d180c in c10::TupleType::createWithSpec<c10::basic_string_view<char> > (qualName=..., field_names=std::vector of length 1, capacity 1 = {...},
    field_types=std::vector of length 1, capacity 1 = {...}, field_defaults=std::vector of length 0, capacity 0) at /home/user/pytorch/aten/src/ATen/core/type.cpp:769
ROCm#13 0x000003ff413b9ca6 in c10::TupleType::createNamed (qualName=..., field_names=std::vector of length 1, capacity 1 = {...}, field_types=std::vector of length 1, capacity 1 = {...})
    at /home/user/pytorch/aten/src/ATen/core/type.cpp:725
ROCm#14 0x000003ff4115fbac in c10::ivalue::TupleTypeFactory<c10::TupleType>::fallback (type=...) at /home/user/pytorch/aten/src/ATen/core/dynamic_type.cpp:383
ROCm#15 0x000003ff708217fe in c10::ivalue::Tuple::type<c10::TupleType> (this=0x6080004b8520) at /home/user/pytorch/aten/src/ATen/core/ivalue_inl.h:781
ROCm#16 0x000003ff70800740 in torch::jit::toPyObject (ivalue=...) at /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:613
ROCm#17 0x000003ff70800306 in torch::jit::toPyObject (ivalue=...) at /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:604
ROCm#18 0x000003ff702d6872 in pybind11::detail::type_caster<c10::IValue, void>::cast (src=...) at /home/user/pytorch/torch/csrc/jit/python/pybind.h:138
ROCm#19 0x000003ff70d98192 in pybind11::cpp_function::initialize<torch::jit::initJitScriptBindings(_object*)::$_45, c10::IValue, torch::jit::mobile::Module&, pybind11::tuple const&, pybind11::name, pybind11::is_method, pybind11::sibling, pybind11::arg>(torch::jit::initJitScriptBindings(_object*)::$_45&&, c10::IValue (*)(torch::jit::mobile::Module&, pybind11::tuple const&), pybind11::name const&, pybind11::is_method const&, pybind11::sibling const&, pybind11::arg const&)::{lambda(pybind11::detail::function_call&)ROCm#1}::operator()(pybind11::detail::function_call&) const (this=0x3ffdbb4ca20, call=...)
    at /home/user/pytorch/cmake/../third_party/pybind11/include/pybind11/pybind11.h:249
ROCm#20 0x000003ff70d97cfe in pybind11::cpp_function::initialize<torch::jit::initJitScriptBindings(_object*)::$_45, c10::IValue, torch::jit::mobile::Module&, pybind11::tuple const&, pybind11::name, pybind11::is_method, pybind11::sibling, pybind11::arg>(torch::jit::initJitScriptBindings(_object*)::$_45&&, c10::IValue (*)(torch::jit::mobile::Module&, pybind11::tuple const&), pybind11::name const&, pybind11::is_method const&, pybind11::sibling const&, pybind11::arg const&)::{lambda(pybind11::detail::function_call&)ROCm#1}::__invoke(pybind11::detail::function_call&) (call=...)
    at /home/user/pytorch/cmake/../third_party/pybind11/include/pybind11/pybind11.h:224
ROCm#21 0x000003ff6e9652ea in pybind11::cpp_function::dispatcher (self=<PyCapsule at remote 0x3ff83e27720>,
    args_in=(<torch._C.LiteScriptModule at remote 0x3ff811844b0>, (<Tensor at remote 0x3ff814efb00>,)), kwargs_in=0x0) at /home/user/pytorch/cmake/../third_party/pybind11/include/pybind11/pybind11.h:929
```

Deallocation:
```
#0  operator delete (ptr=0x60d0005a5740) at /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_new_delete.cpp:160
ROCm#1  0x000003ff44904fdc in __gnu_cxx::new_allocator<std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2> >::deallocate (this=0x3ffc5dc8020,
    __p=0x60d0005a5740, __t=1) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/ext/new_allocator.h:145
ROCm#2  0x000003ff44904fa8 in std::allocator_traits<std::allocator<std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2> > >::deallocate (
    __a=..., __p=0x60d0005a5740, __n=1) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/alloc_traits.h:496
ROCm#3  0x000003ff449041f2 in std::__allocated_ptr<std::allocator<std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2> > >::~__allocated_ptr (
    this=0x3ffc5dc8030) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/allocated_ptr.h:74
ROCm#4  0x000003ff44904888 in std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2>::_M_destroy (this=0x60d0005a5740)
    at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:538
ROCm#5  0x000003ff43895a62 in std::_Sp_counted_base<(__gnu_cxx::_Lock_policy)2>::_M_release (this=0x60d0005a5740) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:184
ROCm#6  0x000003ff43895420 in std::__shared_count<(__gnu_cxx::_Lock_policy)2>::~__shared_count (this=0x611000c40648) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:705
ROCm#7  0x000003ff4466e7f4 in std::__shared_ptr<c10::FunctionSchema, (__gnu_cxx::_Lock_policy)2>::~__shared_ptr (this=0x611000c40640)
    at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:1154
ROCm#8  0x000003ff4466d820 in std::shared_ptr<c10::FunctionSchema>::~shared_ptr (this=0x611000c40640) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr.h:122
ROCm#9  0x000003ff448d82f6 in c10::TupleType::~TupleType (this=0x611000c40580) at /home/user/pytorch/aten/src/ATen/core/jit_type.h:1142
ROCm#10 0x000003ff448d8346 in c10::TupleType::~TupleType (this=0x611000c40580) at /home/user/pytorch/aten/src/ATen/core/jit_type.h:1142
ROCm#11 0x000003ff731296a4 in std::_Sp_counted_ptr<c10::TupleType*, (__gnu_cxx::_Lock_policy)2>::_M_dispose (this=0x603000c43ae0)
    at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:348
ROCm#12 0x000003ff71eaf666 in std::_Sp_counted_base<(__gnu_cxx::_Lock_policy)2>::_M_release (this=0x603000c43ae0) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:168
ROCm#13 0x000003ff71eaf330 in std::__shared_count<(__gnu_cxx::_Lock_policy)2>::~__shared_count (this=0x3ffc5dc9368) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:705
ROCm#14 0x000003ff73129ee4 in std::__shared_ptr<c10::TupleType, (__gnu_cxx::_Lock_policy)2>::~__shared_ptr (this=0x3ffc5dc9360)
    at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:1154
ROCm#15 0x000003ff73122390 in std::shared_ptr<c10::TupleType>::~shared_ptr (this=0x3ffc5dc9360) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr.h:122
ROCm#16 0x000003ff73d00788 in torch::jit::toPyObject (ivalue=...) at /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:613
ROCm#17 0x000003ff73d00306 in torch::jit::toPyObject (ivalue=...) at /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:604
```
</details>
Pull Request resolved: pytorch#101400
Approved by: https://github.com/zou3519
lcskrishna pushed a commit to lcskrishna/pytorch that referenced this pull request May 29, 2023
3 disabled functions are attempting out of bounds reads. Disable them until sleef library is fixed.

<details>
<summary>ASAN report</summary>

```
=================================================================
==2030580==ERROR: AddressSanitizer: global-buffer-overflow on address 0x03ff70f54570 at pc 0x03ff6704e960 bp 0x03ffce128940 sp 0x03ffce128930
READ of size 4 at 0x03ff70f54570 thread T0
    #0 0x3ff6704e95f in vgather_vf_p_vi2 /home/user/pytorch/third_party/sleef/src/arch/helpers390x_128.h:129
    ROCm#1 0x3ff6704e95f in rempif /home/user/pytorch/third_party/sleef/src/libm/sleefsimdsp.c:550
    ROCm#2 0x3ff6704e95f in Sleef_cosf4_u10vxe2 /home/user/pytorch/third_party/sleef/src/libm/sleefsimdsp.c:1021
    ROCm#3 0x3ff67029cfb in Sleef_cosf4_u10 /home/user/pytorch/build/sleef/src/libm/disps390x_128.c:182
    ROCm#4 0x3ff55d21941 in at::vec::ZVECTOR::Vectorized<float, void> at::vec::ZVECTOR::Vectorized<float, void>::mapSleef<float __vector(4) const (*)(float __vector(4)), double __vector(2) const (*)(double __
vector(2)), float, 0>(float __vector(4) const (*)(float __vector(4)), double __vector(2) const (*)(double __vector(2))) const /home/user/pytorch/aten/src/ATen/cpu/vec/vec256/zarch/vec256_zarch.h:991
    ROCm#5 0x3ff5689ad01 in at::vec::ZVECTOR::Vectorized<float, void>::cos() const /home/user/pytorch/aten/src/ATen/cpu/vec/vec256/zarch/vec256_zarch.h:1074
    ROCm#6 0x3ff5685df97 in at::vml::ZVECTOR::vcos<float>(float*, float const*, long)::{lambda(at::vec::ZVECTOR::Vectorized<float, void>)ROCm#1}::operator()(at::vec::ZVECTOR::Vectorized<float, void>) const /home/
user/pytorch/aten/src/ATen/cpu/vml.h:71
    ROCm#7 0x3ff5689b691 in void at::vec::map<float, at::vml::ZVECTOR::vcos<float>(float*, float const*, long)::{lambda(at::vec::ZVECTOR::Vectorized<float, void>)ROCm#1}, 0>(at::vml::ZVECTOR::vcos<float>(float*,
float const*, long)::{lambda(at::vec::ZVECTOR::Vectorized<float, void>)ROCm#1} const&, float*, float const*, long) /home/user/pytorch/aten/src/ATen/cpu/vec/functional_base.h:239
    ROCm#8 0x3ff5685e0df in void at::vml::ZVECTOR::vcos<float>(float*, float const*, long) /home/user/pytorch/aten/src/ATen/cpu/vml.h:71
    ROCm#9 0x3ff563fdde3 in operator() /home/user/pytorch/aten/src/ATen/native/cpu/UnaryOpsKernel.cpp:770
    ROCm#10 0x3ff5648e4a3 in operator() /home/user/pytorch/aten/src/ATen/TensorIterator.h:406
    ROCm#11 0x3ff5663cae1 in callback_fn<at::TensorIteratorBase::loop_2d_from_1d<at::native::ZVECTOR::cos_kernel(at::TensorIteratorBase&)::<lambda()>::<lambda()>::<lambda(char**, const int64_t*, int64_t)> >(c
onst at::native::ZVECTOR::cos_kernel(at::TensorIteratorBase&)::<lambda()>::<lambda()>::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)> > /home/user/pytorch/
c10/util/FunctionRef.h:43
    ROCm#12 0x3ff4d45a933 in c10::function_ref<void (char**, long const*, long, long)>::operator()(char**, long const*, long, long) const /home/user/pytorch/c10/util/FunctionRef.h:64
    ROCm#13 0x3ff4d455133 in at::internal::serial_for_each(c10::ArrayRef<long>, c10::ArrayRef<long>, char**, unsigned long, c10::function_ref<void (char**, long const*, long, long)>, at::Range) /home/user/pyt
orch/aten/src/ATen/TensorIteratorInternal.h:52
    ROCm#14 0x3ff4d43b703 in at::TensorIteratorBase::serial_for_each(c10::function_ref<void (char**, long const*, long, long)>, at::Range) const /home/user/pytorch/aten/src/ATen/TensorIterator.cpp:777
    ROCm#15 0x3ff4d43ab59 in at::TensorIteratorBase::for_each(c10::function_ref<void (char**, long const*, long, long)>, long) /home/user/pytorch/aten/src/ATen/TensorIterator.cpp:749
    ROCm#16 0x3ff5648e851 in for_each<at::native::ZVECTOR::cos_kernel(at::TensorIteratorBase&)::<lambda()>::<lambda()>::<lambda(char**, const int64_t*, int64_t)> > /home/user/pytorch/aten/src/ATen/TensorItera
tor.h:421
    ROCm#17 0x3ff563fe5f9 in operator() /home/user/pytorch/aten/src/ATen/native/cpu/UnaryOpsKernel.cpp:770
    ROCm#18 0x3ff56400915 in operator() /home/user/pytorch/aten/src/ATen/native/cpu/UnaryOpsKernel.cpp:770
    ROCm#19 0x3ff56400f1d in at::native::ZVECTOR::cos_kernel(at::TensorIteratorBase&) /home/user/pytorch/aten/src/ATen/native/cpu/UnaryOpsKernel.cpp:770
    ROCm#20 0x3ff4f303007 in void at::native::DispatchStub<void (*)(at::TensorIteratorBase&), at::native::cos_stub>::operator()<at::native::structured_cos_out&>(c10::DeviceType, at::native::structured_cos_out
&) /home/user/pytorch/aten/src/ATen/native/DispatchStub.h:158
    ROCm#21 0x3ff4f2edb3f in at::native::structured_cos_out::impl(at::Tensor const&, at::Tensor const&) /home/user/pytorch/aten/src/ATen/native/UnaryOps.cpp:330
    ROCm#22 0x3ff526ef739 in wrapper_CPU_cos /home/user/pytorch/build/aten/src/ATen/RegisterCPU.cpp:4307
    ROCm#23 0x3ff52c651d9 in operator() /home/user/pytorch/aten/src/ATen/core/boxing/impl/WrapFunctionIntoFunctor.h:13
    ROCm#24 0x3ff52c651d9 in call /home/user/pytorch/aten/src/ATen/core/boxing/impl/make_boxed_from_unboxed_functor.h:463
    ROCm#25 0x3ff5076df2f in at::Tensor c10::callUnboxedKernelFunction<at::Tensor, at::Tensor const&>(void*, c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&) /home/user/pytorch/aten/src/ATen/core
/boxing/KernelFunction_impl.h:50
    ROCm#26 0x3ff5009a93f in at::Tensor c10::KernelFunction::call<at::Tensor, at::Tensor const&>(c10::OperatorHandle const&, c10::DispatchKeySet, at::Tensor const&) const /home/user/pytorch/aten/src/ATen/core
/boxing/KernelFunction_impl.h:103
    ROCm#27 0x3ff5009a93f in at::Tensor c10::Dispatcher::call<at::Tensor, at::Tensor const&>(c10::TypedOperatorHandle<at::Tensor (at::Tensor const&)> const&, at::Tensor const&) const /home/user/pytorch/aten/s
rc/ATen/core/dispatch/Dispatcher.h:639
    ROCm#28 0x3ff5009a93f in c10::TypedOperatorHandle<at::Tensor (at::Tensor const&)>::call(at::Tensor const&) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:487
    ROCm#29 0x3ff5009a93f in at::_ops::cos::call(at::Tensor const&) /home/user/pytorch/build/aten/src/ATen/Operators_0.cpp:2215
    ROCm#30 0x3ff7d813741 in at::Tensor::cos() const /home/user/pytorch/build/aten/src/ATen/core/TensorBody.h:2107
    ROCm#31 0x3ff7dc0f2b7 in operator() /home/user/pytorch/torch/csrc/autograd/generated/python_torch_functions_2.cpp:2953
    ROCm#32 0x3ff7dc0faf7 in THPVariable_cos /home/user/pytorch/torch/csrc/autograd/generated/python_torch_functions_2.cpp:2955
    ROCm#33 0x3ffa5ef5ae1 in cfunction_call Objects/methodobject.c:543
    ROCm#34 0x3ffa5e843f3 in _PyObject_Call Objects/call.c:305
    ROCm#35 0x3ffa5e84483 in PyObject_Call Objects/call.c:317
    ROCm#36 0x3ffa5feb50d in do_call_core Python/ceval.c:5915
    ROCm#37 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277
    ROCm#38 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46
    ROCm#39 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065
    ROCm#40 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#41 0x3ffa5e841fb in PyVectorcall_Call Objects/call.c:255
    ROCm#42 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290
    ROCm#43 0x3ffa5e84483 in PyObject_Call Objects/call.c:317
    ROCm#44 0x3ff7f87a393 in torch::impl::dispatch::PythonKernelHolder::operator()(c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) /home/user/pytorch/
torch/csrc/utils/python_dispatch.cpp:175
    ROCm#45 0x3ff7f8871a7 in c10::BoxedKernel::makeFromFunctor<torch::impl::dispatch::PythonKernelHolder>(std::unique_ptr<torch::impl::dispatch::PythonKernelHolder, std::default_delete<torch::impl::dispatch::
PythonKernelHolder> >)::{lambda(c10::OperatorKernel*, c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*)ROCm#1}::operator()(c10::OperatorKernel*, c10::Op
eratorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/core/boxing/BoxedKernel_impl.h:87
    ROCm#46 0x3ff7f887261 in c10::BoxedKernel::makeFromFunctor<torch::impl::dispatch::PythonKernelHolder>(std::unique_ptr<torch::impl::dispatch::PythonKernelHolder, std::default_delete<torch::impl::dispatch::
PythonKernelHolder> >)::{lambda(c10::OperatorKernel*, c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*)ROCm#1}::_FUN(c10::OperatorKernel*, c10::Operator
Handle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) /home/user/pytorch/aten/src/ATen/core/boxing/BoxedKernel_impl.h:86
    ROCm#47 0x3ff7e0d10ab in c10::BoxedKernel::callBoxed(c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/core/b
oxing/BoxedKernel_impl.h:41
    ROCm#48 0x3ff7e0d1459 in c10::KernelFunction::callBoxed(c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/cor
e/boxing/KernelFunction_impl.h:43
    ROCm#49 0x3ff7f876421 in c10::Dispatcher::callBoxed(c10::OperatorHandle const&, std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:6
91
    ROCm#50 0x3ff4d22bcdd in c10::OperatorHandle::callBoxed(std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:417
    ROCm#51 0x3ff65a092d5 in c10::OperatorHandle::callBoxed(std::vector<c10::IValue, std::allocator<c10::IValue> >&) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:421
    ROCm#52 0x3ff65a05641 in operator() /home/user/pytorch/torch/csrc/jit/runtime/register_c10_ops.cpp:15
    ROCm#53 0x3ff65a08cb5 in __invoke_impl<void, torch::jit::(anonymous namespace)::createOperatorFromC10(const c10::OperatorHandle&)::<lambda(torch::jit::Stack&)>&, std::vector<c10::IValue, std::allocator<c1
0::IValue> >&> /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/invoke.h:61
    ROCm#54 0x3ff65a0897b in __invoke_r<void, torch::jit::(anonymous namespace)::createOperatorFromC10(const c10::OperatorHandle&)::<lambda(torch::jit::Stack&)>&, std::vector<c10::IValue, std::allocator<c10::
IValue> >&> /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/invoke.h:111
    ROCm#55 0x3ff65a084e1 in _M_invoke /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/std_function.h:290
    ROCm#56 0x3ff7eb2cb21 in std::function<void (std::vector<c10::IValue, std::allocator<c10::IValue> >&)>::operator()(std::vector<c10::IValue, std::allocator<c10::IValue> >&) const /usr/lib/gcc/s390x-ibm-lin
ux-gnu/11/include/g++-v11/bits/std_function.h:590
    ROCm#57 0x3ff7eb1b659 in torch::jit::Operation::operator()(std::vector<c10::IValue, std::allocator<c10::IValue> >&) /home/user/pytorch/aten/src/ATen/core/stack.h:41
    ROCm#58 0x3ff7eb08449 in torch::jit::invokeOperatorFromPython(std::vector<std::shared_ptr<torch::jit::Operator>, std::allocator<std::shared_ptr<torch::jit::Operator> > > const&, pybind11::args, pybind11::
kwargs const&, c10::optional<c10::DispatchKey>) /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:764
    ROCm#59 0x3ff7eb09d85 in torch::jit::_get_operation_for_overload_or_packet(std::vector<std::shared_ptr<torch::jit::Operator>, std::allocator<std::shared_ptr<torch::jit::Operator> > > const&, c10::Symbol,
pybind11::args, pybind11::kwargs const&, bool, c10::optional<c10::DispatchKey>) /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:829
    ROCm#60 0x3ff7e573eb9 in operator() /home/user/pytorch/torch/csrc/jit/python/init.cpp:1549
    ROCm#61 0x3ff7e6728dd in call_impl<pybind11::object, torch::jit::initJITBindings(PyObject*)::<lambda(const string&, const string&)>::<lambda(pybind11::args, pybind11::kwargs)>&, 0, 1, pybind11::detail::vo
id_type> /home/user/pytorch/third_party/pybind11/include/pybind11/cast.h:1439
    ROCm#62 0x3ff7e64312f in call<pybind11::object, pybind11::detail::void_type, torch::jit::initJITBindings(PyObject*)::<lambda(const string&, const string&)>::<lambda(pybind11::args, pybind11::kwargs)>&> /h
ome/user/pytorch/third_party/pybind11/include/pybind11/cast.h:1408
    ROCm#63 0x3ff7e5da259 in operator() /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:249
    ROCm#64 0x3ff7e5da441 in _FUN /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:224
    ROCm#65 0x3ff7d317a1f in pybind11::cpp_function::dispatcher(_object*, _object*, _object*) /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:929
    ROCm#66 0x3ffa5ef5ae1 in cfunction_call Objects/methodobject.c:543
    ROCm#67 0x3ffa5e843f3 in _PyObject_Call Objects/call.c:305
    ROCm#68 0x3ffa5e84483 in PyObject_Call Objects/call.c:317
    ROCm#69 0x3ffa5feb50d in do_call_core Python/ceval.c:5915
    ROCm#70 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277
    ROCm#71 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46
    ROCm#72 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065
    ROCm#73 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#74 0x3ffa5e83d1f in _PyObject_FastCallDictTstate Objects/call.c:142
    ROCm#75 0x3ffa5e84937 in _PyObject_Call_Prepend Objects/call.c:431
    ROCm#76 0x3ffa5f2f577 in slot_tp_call Objects/typeobject.c:7494
    ROCm#77 0x3ffa5e843f3 in _PyObject_Call Objects/call.c:305
    ROCm#78 0x3ffa5e84483 in PyObject_Call Objects/call.c:317
    ROCm#79 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943
    ROCm#80 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277
    ROCm#81 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46
    ROCm#82 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065
    ROCm#83 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#84 0x3ffa5fd76a3 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114
    ROCm#85 0x3ffa5fd772f in PyObject_Vectorcall Include/cpython/abstract.h:123
    ROCm#86 0x3ffa5feb289 in call_function Python/ceval.c:5891
    ROCm#87 0x3ffa5fe5c3b in _PyEval_EvalFrameDefault Python/ceval.c:4213
    ROCm#88 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46
    ROCm#89 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065
    ROCm#90 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#91 0x3ffa5e841fb in PyVectorcall_Call Objects/call.c:255
    ROCm#92 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290
    ROCm#93 0x3ffa5e84483 in PyObject_Call Objects/call.c:317
    ROCm#94 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943
    ROCm#95 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277
    ROCm#96 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46
    ROCm#97 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065
    ROCm#98 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#99 0x3ffa5e841fb in PyVectorcall_Call Objects/call.c:255
    ROCm#100 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290
    ROCm#101 0x3ffa5e84483 in PyObject_Call Objects/call.c:317
    ROCm#102 0x3ff7f87a393 in torch::impl::dispatch::PythonKernelHolder::operator()(c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) /home/user/pytorch
/torch/csrc/utils/python_dispatch.cpp:175
    ROCm#103 0x3ff7f8871a7 in c10::BoxedKernel::makeFromFunctor<torch::impl::dispatch::PythonKernelHolder>(std::unique_ptr<torch::impl::dispatch::PythonKernelHolder, std::default_delete<torch::impl::dispatch:
:PythonKernelHolder> >)::{lambda(c10::OperatorKernel*, c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*)ROCm#1}::operator()(c10::OperatorKernel*, c10::O
peratorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/core/boxing/BoxedKernel_impl.h:87
    ROCm#104 0x3ff7f887261 in c10::BoxedKernel::makeFromFunctor<torch::impl::dispatch::PythonKernelHolder>(std::unique_ptr<torch::impl::dispatch::PythonKernelHolder, std::default_delete<torch::impl::dispatch:
:PythonKernelHolder> >)::{lambda(c10::OperatorKernel*, c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*)ROCm#1}::_FUN(c10::OperatorKernel*, c10::Operato
rHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) /home/user/pytorch/aten/src/ATen/core/boxing/BoxedKernel_impl.h:86
    ROCm#105 0x3ff7e0d10ab in c10::BoxedKernel::callBoxed(c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/core/
boxing/BoxedKernel_impl.h:41
    ROCm#106 0x3ff7e0d1459 in c10::KernelFunction::callBoxed(c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/co
re/boxing/KernelFunction_impl.h:43
    ROCm#107 0x3ff7f876421 in c10::Dispatcher::callBoxed(c10::OperatorHandle const&, std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:
691
    ROCm#108 0x3ff4d22bcdd in c10::OperatorHandle::callBoxed(std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:417
    ROCm#109 0x3ff65a092d5 in c10::OperatorHandle::callBoxed(std::vector<c10::IValue, std::allocator<c10::IValue> >&) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:421
    ROCm#110 0x3ff65a05641 in operator() /home/user/pytorch/torch/csrc/jit/runtime/register_c10_ops.cpp:15
    ROCm#111 0x3ff65a08cb5 in __invoke_impl<void, torch::jit::(anonymous namespace)::createOperatorFromC10(const c10::OperatorHandle&)::<lambda(torch::jit::Stack&)>&, std::vector<c10::IValue, std::allocator<c
10::IValue> >&> /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/invoke.h:61
    ROCm#112 0x3ff65a0897b in __invoke_r<void, torch::jit::(anonymous namespace)::createOperatorFromC10(const c10::OperatorHandle&)::<lambda(torch::jit::Stack&)>&, std::vector<c10::IValue, std::allocator<c10:
:IValue> >&> /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/invoke.h:111
    ROCm#113 0x3ff65a084e1 in _M_invoke /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/std_function.h:290
    ROCm#114 0x3ff7eb2cb21 in std::function<void (std::vector<c10::IValue, std::allocator<c10::IValue> >&)>::operator()(std::vector<c10::IValue, std::allocator<c10::IValue> >&) const /usr/lib/gcc/s390x-ibm-li
nux-gnu/11/include/g++-v11/bits/std_function.h:590
    ROCm#115 0x3ff7eb1b659 in torch::jit::Operation::operator()(std::vector<c10::IValue, std::allocator<c10::IValue> >&) /home/user/pytorch/aten/src/ATen/core/stack.h:41
    ROCm#116 0x3ff7eb08449 in torch::jit::invokeOperatorFromPython(std::vector<std::shared_ptr<torch::jit::Operator>, std::allocator<std::shared_ptr<torch::jit::Operator> > > const&, pybind11::args, pybind11:
:kwargs const&, c10::optional<c10::DispatchKey>) /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:764
    ROCm#117 0x3ff7eb09d85 in torch::jit::_get_operation_for_overload_or_packet(std::vector<std::shared_ptr<torch::jit::Operator>, std::allocator<std::shared_ptr<torch::jit::Operator> > > const&, c10::Symbol,
 pybind11::args, pybind11::kwargs const&, bool, c10::optional<c10::DispatchKey>) /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:829
    ROCm#118 0x3ff7e573eb9 in operator() /home/user/pytorch/torch/csrc/jit/python/init.cpp:1549
    ROCm#119 0x3ff7e6728dd in call_impl<pybind11::object, torch::jit::initJITBindings(PyObject*)::<lambda(const string&, const string&)>::<lambda(pybind11::args, pybind11::kwargs)>&, 0, 1, pybind11::detail::v
oid_type> /home/user/pytorch/third_party/pybind11/include/pybind11/cast.h:1439
    ROCm#120 0x3ff7e64312f in call<pybind11::object, pybind11::detail::void_type, torch::jit::initJITBindings(PyObject*)::<lambda(const string&, const string&)>::<lambda(pybind11::args, pybind11::kwargs)>&> /
home/user/pytorch/third_party/pybind11/include/pybind11/cast.h:1408
    ROCm#121 0x3ff7e5da259 in operator() /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:249
    ROCm#122 0x3ff7e5da441 in _FUN /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:224
    ROCm#123 0x3ff7d317a1f in pybind11::cpp_function::dispatcher(_object*, _object*, _object*) /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:929
    ROCm#124 0x3ffa5ef5ae1 in cfunction_call Objects/methodobject.c:543
    ROCm#125 0x3ffa5e843f3 in _PyObject_Call Objects/call.c:305
    ROCm#126 0x3ffa5e84483 in PyObject_Call Objects/call.c:317
    ROCm#127 0x3ffa5feb50d in do_call_core Python/ceval.c:5915
    ROCm#128 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277
    ROCm#129 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46
    ROCm#130 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065
    ROCm#131 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#132 0x3ffa5e83d1f in _PyObject_FastCallDictTstate Objects/call.c:142
    ROCm#133 0x3ffa5e84937 in _PyObject_Call_Prepend Objects/call.c:431
    ROCm#134 0x3ffa5f2f577 in slot_tp_call Objects/typeobject.c:7494
    ROCm#135 0x3ffa5e843f3 in _PyObject_Call Objects/call.c:305
    ROCm#136 0x3ffa5e84483 in PyObject_Call Objects/call.c:317
    ROCm#137 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943
    ROCm#138 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277
    ROCm#139 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46
    ROCm#140 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065
    ROCm#141 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#142 0x3ffa5e87d2b in _PyObject_VectorcallTstate Include/cpython/abstract.h:114
    ROCm#143 0x3ffa5e882dd in method_vectorcall Objects/classobject.c:83
    ROCm#144 0x3ffa5e836d3 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114
    ROCm#145 0x3ffa5e84b6f in _PyObject_CallFunctionVa Objects/call.c:485
    ROCm#146 0x3ffa5e84f2d in callmethod Objects/call.c:557
    ROCm#147 0x3ffa5e85039 in PyObject_CallMethod Objects/call.c:577
    ROCm#148 0x3ff7f7efa05 in torch::handle_torch_function_no_python_arg_parser(c10::ArrayRef<pybind11::handle>, _object*, _object*, char const*, _object*, char const*, torch::TorchFunctionName) /home/user/py
torch/torch/csrc/utils/python_arg_parser.cpp:338
    ROCm#149 0x3ff7eb09b67 in torch::jit::_get_operation_for_overload_or_packet(std::vector<std::shared_ptr<torch::jit::Operator>, std::allocator<std::shared_ptr<torch::jit::Operator> > > const&, c10::Symbol,
 pybind11::args, pybind11::kwargs const&, bool, c10::optional<c10::DispatchKey>) /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:827
    ROCm#150 0x3ff7e573eb9 in operator() /home/user/pytorch/torch/csrc/jit/python/init.cpp:1549
    ROCm#151 0x3ff7e6728dd in call_impl<pybind11::object, torch::jit::initJITBindings(PyObject*)::<lambda(const string&, const string&)>::<lambda(pybind11::args, pybind11::kwargs)>&, 0, 1, pybind11::detail::v
oid_type> /home/user/pytorch/third_party/pybind11/include/pybind11/cast.h:1439
    ROCm#152 0x3ff7e64312f in call<pybind11::object, pybind11::detail::void_type, torch::jit::initJITBindings(PyObject*)::<lambda(const string&, const string&)>::<lambda(pybind11::args, pybind11::kwargs)>&> /
home/user/pytorch/third_party/pybind11/include/pybind11/cast.h:1408
    ROCm#153 0x3ff7e5da259 in operator() /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:249
    ROCm#154 0x3ff7e5da441 in _FUN /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:224
    ROCm#155 0x3ff7d317a1f in pybind11::cpp_function::dispatcher(_object*, _object*, _object*) /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:929
    ROCm#156 0x3ffa5ef5ae1 in cfunction_call Objects/methodobject.c:543
    ROCm#157 0x3ffa5e843f3 in _PyObject_Call Objects/call.c:305
    ROCm#158 0x3ffa5e84483 in PyObject_Call Objects/call.c:317
    ROCm#159 0x3ffa5feb50d in do_call_core Python/ceval.c:5915
    ROCm#160 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277
    ROCm#161 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46
    ROCm#162 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065
    ROCm#163 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#164 0x3ffa5e83d1f in _PyObject_FastCallDictTstate Objects/call.c:142
    ROCm#165 0x3ffa5e84937 in _PyObject_Call_Prepend Objects/call.c:431
    ROCm#166 0x3ffa5f2f577 in slot_tp_call Objects/typeobject.c:7494
    ROCm#167 0x3ffa5e84027 in _PyObject_MakeTpCall Objects/call.c:215
    ROCm#168 0x3ffa5fd767b in _PyObject_VectorcallTstate Include/cpython/abstract.h:112
    ROCm#169 0x3ffa5fd772f in PyObject_Vectorcall Include/cpython/abstract.h:123
    ROCm#170 0x3ffa5feb289 in call_function Python/ceval.c:5891
    ROCm#171 0x3ffa5fe5ad1 in _PyEval_EvalFrameDefault Python/ceval.c:4181
    ROCm#172 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46
    ROCm#173 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065
    ROCm#174 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#175 0x3ffa5fd76a3 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114
    ROCm#176 0x3ffa5fd772f in PyObject_Vectorcall Include/cpython/abstract.h:123
    ROCm#177 0x3ffa5feb289 in call_function Python/ceval.c:5891
    ROCm#178 0x3ffa5fe5c3b in _PyEval_EvalFrameDefault Python/ceval.c:4213
    ROCm#179 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46
    ROCm#180 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065
    ROCm#181 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#182 0x3ffa5e8427f in PyVectorcall_Call Objects/call.c:267
    ROCm#183 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290
    ROCm#184 0x3ffa5e84483 in PyObject_Call Objects/call.c:317
    ROCm#185 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943
    ROCm#186 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277
    ROCm#187 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46
    ROCm#188 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065
    ROCm#189 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#190 0x3ffa5e841fb in PyVectorcall_Call Objects/call.c:255
    ROCm#191 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290
    ROCm#192 0x3ffa5e84483 in PyObject_Call Objects/call.c:317
    ROCm#193 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943
    ROCm#194 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277
    ROCm#195 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46
    ROCm#196 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065
    ROCm#197 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#198 0x3ffa5e841fb in PyVectorcall_Call Objects/call.c:255
    ROCm#199 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290
    ROCm#200 0x3ffa5e84483 in PyObject_Call Objects/call.c:317
    ROCm#201 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943
    ROCm#202 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277
    ROCm#203 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46
    ROCm#204 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065
    ROCm#205 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#206 0x3ffa5e841fb in PyVectorcall_Call Objects/call.c:255
    ROCm#207 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290
    ROCm#208 0x3ffa5e84483 in PyObject_Call Objects/call.c:317
    ROCm#209 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943
    ROCm#210 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277
    ROCm#211 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46
    ROCm#212 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065
    ROCm#213 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#214 0x3ffa5e83d1f in _PyObject_FastCallDictTstate Objects/call.c:142
    ROCm#215 0x3ffa5e84937 in _PyObject_Call_Prepend Objects/call.c:431
    ROCm#216 0x3ffa5f2f577 in slot_tp_call Objects/typeobject.c:7494
    ROCm#217 0x3ffa5e843f3 in _PyObject_Call Objects/call.c:305
    ROCm#218 0x3ffa5e84483 in PyObject_Call Objects/call.c:317
    ROCm#219 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943
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    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
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    ROCm#229 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065
    ROCm#230 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#231 0x3ffa5e8427f in PyVectorcall_Call Objects/call.c:267
    ROCm#232 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290
    ROCm#233 0x3ffa5e84483 in PyObject_Call Objects/call.c:317
    ROCm#234 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943
    ROCm#235 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277
    ROCm#236 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46
    ROCm#237 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065
    ROCm#238 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#239 0x3ffa5e8427f in PyVectorcall_Call Objects/call.c:267
    ROCm#240 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290
    ROCm#241 0x3ffa5e84483 in PyObject_Call Objects/call.c:317
    ROCm#242 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943
    ROCm#243 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277
    ROCm#244 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46
    ROCm#245 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065
    ROCm#246 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#247 0x3ffa5e8427f in PyVectorcall_Call Objects/call.c:267
    ROCm#248 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290
    ROCm#249 0x3ffa5e84483 in PyObject_Call Objects/call.c:317
    ROCm#250 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943
    ROCm#251 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277
    ROCm#252 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46
    ROCm#253 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065
    ROCm#254 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342
    ROCm#255 0x3ffa5e8427f in PyVectorcall_Call Objects/call.c:267

0x03ff70f54570 is located 0 bytes to the right of global variable 'Sleef_rempitabsp' defined in '/home/user/pytorch/third_party/sleef/src/libm/rempitab.c:986:34' (0x3ff70f53f00) of size 1648
SUMMARY: AddressSanitizer: global-buffer-overflow /home/user/pytorch/third_party/sleef/src/arch/helpers390x_128.h:129 in vgather_vf_p_vi2
Shadow bytes around the buggy address:
  0x10007fee1ea850: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00
  0x10007fee1ea860: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00
  0x10007fee1ea870: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00
  0x10007fee1ea880: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00
  0x10007fee1ea890: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00
=>0x10007fee1ea8a0: 00 00 00 00 00 00 00 00 00 00 00 00 00 00[f9]f9
  0x10007fee1ea8b0: f9 f9 f9 f9 00 00 00 00 00 00 00 00 00 00 00 00
  0x10007fee1ea8c0: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00
  0x10007fee1ea8d0: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00
  0x10007fee1ea8e0: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00
  0x10007fee1ea8f0: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00
Shadow byte legend (one shadow byte represents 8 application bytes):
  Addressable:           00
  Partially addressable: 01 02 03 04 05 06 07
  Heap left redzone:       fa
  Freed heap region:       fd
  Stack left redzone:      f1
  Stack mid redzone:       f2
  Stack right redzone:     f3
  Stack after return:      f5
  Stack use after scope:   f8
  Global redzone:          f9
  Global init order:       f6
  Poisoned by user:        f7
  Container overflow:      fc
  Array cookie:            ac
  Intra object redzone:    bb
  ASan internal:           fe
  Left alloca redzone:     ca
  Right alloca redzone:    cb
  Shadow gap:              cc
==2030580==ABORTING
```
</details>

It reproduces when running `pytest -v test/test_ops.py -k test_python_ref__refs_cos_cpu_bfloat16` under address sanitizer on s390x.

See also: shibatch/sleef#464

Pull Request resolved: pytorch#102266
Approved by: https://github.com/malfet
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