Merge from upstream #197

iotamudelta · 2018-09-11T17:57:07Z

No description provided.

Summary: Checking assertExportImport for all of the generated test jit tests. Pull Request resolved: pytorch#10982 Differential Revision: D9636935 Pulled By: eellison fbshipit-source-id: f3f1ce77d454848098f2ac7e0fa18bf8564890be

…rch#11380) Summary: cc SsnL Pull Request resolved: pytorch#11380 Reviewed By: ezyang Differential Revision: D9705877 Pulled By: zou3519 fbshipit-source-id: 02470c25236f57fa02f4ac9d7ed63d38a6355db2

Summary: Pull Request resolved: pytorch#11167 Narrow the Blob API as preparation for merging Blob/IValue - get rid of templated IsType and Operator::InputIsType / OutputIsType - Use 'using' instead of 'typedef' for DestroyCall (just for readability) Reviewed By: ezyang Differential Revision: D9623916 fbshipit-source-id: 952f0b0cf5a525094b02e8d2798dd57a56a9e1d8

Summary: Pull Request resolved: pytorch#11238 - when moving an IValue, free the old value instead of keeping it allocated - making classes final - moving std::string - making ConstantList const Reviewed By: ezyang Differential Revision: D9644700 fbshipit-source-id: ab7228368e4f00f664ba54e1242b0307d91c5e7e

Summary: Pull Request resolved: pytorch#11258 The two intrusive_ptr constructors in Tensor can be combined into one implementation that does both, moving and copying. Reviewed By: ezyang Differential Revision: D9652088 fbshipit-source-id: 5efca02654ba305c99c20bbeb83551469d17a51d

Summary: Pull Request resolved: pytorch#11260 This is needed to make something like this work: intrusive_ptr<TensorImpl, UndefinedTensorImpl> a = make_intrusive<SparseTensorImpl>(...); Reviewed By: ezyang Differential Revision: D9652089 fbshipit-source-id: 19c65e98460ccb27bc69e36d7e558cb9d6e67615

Summary: Pull Request resolved: pytorch#11294 The Tensor(ptr, retain) constructor is error prone and circumvents the intrusive_ptr safety. This diff removes that and pushes the responsibility to callers. Step by step, manual refcounting can be pushed back and possibly eliminated in the end. Reviewed By: ezyang Differential Revision: D9663476 fbshipit-source-id: 7f010e5e47b137a9575960201c5bf5d552c5c2f5

Summary: I'm 80% sure that this fixes the math bug. But I can't repro locally so I don't know. Pull Request resolved: pytorch#11472 Differential Revision: D9755328 Pulled By: SsnL fbshipit-source-id: 130be664d3c6ceee3c0c166c1a86fc9ec3b79d74

…ytorch#11109) Summary: Normalizing by the world size before the reduction is less likely to cause overflow in FP16 training. Pull Request resolved: pytorch#11109 Differential Revision: D9594708 Pulled By: myleott fbshipit-source-id: 93ab53cb782ee1cbe1264e529b333490a0940338

Summary: The controller you requested could not be found. found there are some issues when using comparison operators for half types when certain THC header are included. I was able to reproduce and added a test. I also fix the issue by adding the proper definitions to avoid this issue. Reported in pytorch#10301 (comment) Related: pytorch/tutorials#292 soumith fmassa Pull Request resolved: pytorch#11395 Differential Revision: D9725102 Pulled By: goldsborough fbshipit-source-id: 630425829046bbebea3409bb792a9d62c91f41ad

Summary: NCCL1 uses `int` as its numerical type for fields like `count`, which makes broadcasting tensors larger than `2 << 31 - 1` impossible, and raises opaque error `invalid arguments`. NCCL2 greatly increase the limit on many platforms by using `size_t`. This patch statically detects this type, and raises properly if the broadcast tensor exceeds the limit. No test because I don't think our test suite should broadcast big tensors. Pull Request resolved: pytorch#11466 Differential Revision: D9754753 Pulled By: SsnL fbshipit-source-id: 73506450cae047e06b5b225b39efdb42d5d26685

…11288) Summary: Many constructors like `torch.zeros` or `torch.randn` didn't support size tracing correctly which is fixed by this pass. Same issue has been fixed in legacy tensor constructors. Additionally, new tensor constructors, which do not participate in tracing (most notably `torch.tensor`, `torch.as_tensor` and `torch.from_numpy`) raise a warning when they are used. Finally, entering a traceable operation disables the tracing in its body. This is needed because zdevito Pull Request resolved: pytorch#11288 Reviewed By: ezyang Differential Revision: D9751183 Pulled By: apaszke fbshipit-source-id: 51444a39d76a3e164adc396c432fd5ee3c8d5f7f

Summary: This PR is stacked on pytorch#10610, and only adds changes in one file `.jenkins/pytorch/test.sh`, where we now build the custom op tests and run them. I'd also like to take this PR to discuss whether the [`TorchConfig.cmake`](https://github.com/pytorch/pytorch/blob/master/cmake/TorchConfig.cmake.in) I made is robust enough (we will also see in the CI) orionr Yangqing dzhulgakov what do you think? Also ezyang for CI changes Pull Request resolved: pytorch#10611 Differential Revision: D9597627 Pulled By: goldsborough fbshipit-source-id: f5af8164c076894f448cef7e5b356a6b3159f8b3

…orms we care about. (pytorch#11394) Summary: While the use of memcpy as part of the byte swapping sequence looks funky, all major compilers recognize and optimize this pattern reliably, resulting in essentially optimal code generation. For example, decodeUInt32LE goes from this on iOS arm64: > ldrb w8, [x0, ROCm#3] > ldrb w9, [x0, ROCm#2] > bfi w8, w9, ROCm#8, ROCm#8 > ldrb w9, [x0, #1] > bfi w8, w9, ROCm#16, ROCm#8 > ldrb w9, [x0] > bfi w8, w9, ROCm#24, ROCm#8 > mov x0, x8 > ret To this: > ldr w8, [x0] > rev w0, w8 > ret Pull Request resolved: pytorch#11394 Reviewed By: SsnL Differential Revision: D9728659 Pulled By: resistor fbshipit-source-id: 9afbd4adfad1d1fb7b01f1179e6707ee21fa726f

Summary: Pull Request resolved: pytorch#10974 Pull Request resolved: pytorch#10291 This new operator will do the following: Given a LENGTHS vector and n_splits, output a "split" LENGTHS vector where: 1. Each length in input vector is split into n_splits values (thus output vector should have LENGTHS.size(0) * n_splits elements) 2. The new lengths in output should be evenly split, and if the length is not divisible by n_splits, then order new values in descending order. (e.g. n_splits = 3, length = 5 -> 2 2 1) 3. If n_splits > some element in the array, its split elements will contain 0s. (e.g. n_splits = 3, length = 2 - > 1 1 0) Reviewed By: bddppq, chocjy Differential Revision: D9013119 fbshipit-source-id: 82bf3371ec08c41fc3379177f0007afc142e0d84

Summary: There's a bunch of legacy code where people are explicitly instantiating Variable, and these call-sites have thus far been untraceable (appearing as prim::Constant nodes with the tensor value at the time of tracing). This makes it so that the new variable inherits the traced Value* from the tensor it's being constructed from Pull Request resolved: pytorch#11463 Differential Revision: D9756529 Pulled By: jamesr66a fbshipit-source-id: da99c6a7621957a305f2699ec9cb9def69b1b2d7

…orch#11411) Summary: Pull Request resolved: pytorch#11411 Simple fix Reviewed By: goldsborough Differential Revision: D9730371 fbshipit-source-id: f841327c01faa13cfb6b7fc6e279b8fc50fad1db

Summary: Skip torch tests as well when NO_TEST=1 environment variable is set. Also remove the separate ATen code path for not being built with Caffe2, since it will always be built with Caffe2. cc The controller you requested could not be found. Pull Request resolved: pytorch#11415 Reviewed By: soumith Differential Revision: D9758179 Pulled By: orionr fbshipit-source-id: e3e3327364fccdc57a703aeaad8c4f30452973fb

Summary: Add flags for LMDB and LevelDB, default `OFF`. These can be enabled with ``` USE_LMDB=1 USE_LEVELDB=1 python setup.py build_deps ``` Also add a flag to build Caffe2 ops, which is default `ON`. Disable with ``` NO_CAFFE2_OPS=1 python setup.py build_deps ``` cc Yangqing soumith pjh5 mingzhe09088 Pull Request resolved: pytorch#11462 Reviewed By: soumith Differential Revision: D9758156 Pulled By: orionr fbshipit-source-id: 95fd206d72fdf44df54fc5d0aeab598bff900c63

Summary: ebetica soumith ezyang Pull Request resolved: pytorch#11469 Differential Revision: D9757547 Pulled By: goldsborough fbshipit-source-id: a95673abe949bb81d716dbc03c5c3e2a11cc15d3

Summary: Document the `Functional` module in the C++ API. ebetica ezyang soumith Pull Request resolved: pytorch#11460 Differential Revision: D9757555 Pulled By: goldsborough fbshipit-source-id: 15f8bf6d60bd26f3f4e69fb8e414e186e3c220ee

Summary: Pull Request resolved: pytorch#11497 Differential Revision: D9762014 Pulled By: gchanan fbshipit-source-id: 996419cc5e86d000af953d030ff361adafb921ad

Summary: Pull Request resolved: pytorch#11508 Differential Revision: D9764380 Pulled By: goldsborough fbshipit-source-id: 3abb9c04f46137be833ea26d67734741e14f8010

Summary: The old `torch.distributed` will go to `torch.distributed.deprecated` The old DDP will go to `torch.nn.parallel.deprecated` Now `torch.nn.parallel.DDP` will use c10d DDP Now `torch.distributed` will use C10d frontend API Pull Request resolved: pytorch#11405 Reviewed By: pietern Differential Revision: D9733733 Pulled By: teng-li fbshipit-source-id: d6a3f3e73f8d3a7fcb1f4baef53c78063b8cbb08

…ibuted doc (pytorch#11450) Summary: This is the new documentation for c10d release, and it also deprecates the old torch.distributed document. This PR depends on pytorch#11405 and should only be landed after pytorch#11405 is landed Pull Request resolved: pytorch#11450 Differential Revision: D9765504 Pulled By: teng-li fbshipit-source-id: 48f38b27b8c270baf389f8e478ea226b9ecc63db

Summary: Pull Request resolved: pytorch#11418 Several improvements that aim to make the APIs more straightforward to use - Get rid of helper methods subgraph and nonTerminal . Users now should create a NNMatchGraph directly via graph's createNode and createEdge API - Get rid of operatorSubgraph helper method - invertGraphTraversal flag applies to both the match graph and the scanned graph. This allows user to create match graph in the same direction as the scanned graph, thus reduce confusion. - additional parameters of matchNode (count, includeInSubgraph, nonTerminal) are removed from the constructors and moved into setter methods. (We no longer enforce that MatchNode is immutable but this helps improve code clarity). - Tests are updated to reflect the changes Follow up changes: - Possibly clean up the tests further. This change aims to minimally modify the unit tests. - Help a validity check that enforce the current limitation of the match graph (single source node), and throws if the match graph does not satisfy the criteria. - Have the single source node be detected automatically and callers just need to pass in the matchGraph instead of the source node reference. Differential Revision: D9732565 fbshipit-source-id: ae8320e2bc89b867f6bb4b1c1aad635f4b219fa1

…1358) Summary: [Here's a list](https://gist.github.com/apaszke/f0821840bdcc67a977832dc58acc1b85) of ops that are in `register_aten_ops.cpp`, but aren't supported in shape prop. Everything else should work now. Pull Request resolved: pytorch#11358 Differential Revision: D9753693 Pulled By: apaszke fbshipit-source-id: efeae0126ce16cb56b8797fc5246405588bcae3c

Summary: This enabled `torch.einsum` both in tracing and in script mode. It's used all over Pyro at the moment, and is needed for any use of the JIT in there. Fixes pytorch#11157. zdevito fritzo neerajprad Pull Request resolved: pytorch#11506 Differential Revision: D9764787 Pulled By: apaszke fbshipit-source-id: 9b5251b9e7c5897034602bd07ff67b425d33326c

Summary: This adds a `.expand` method for distributions that is akin to the `torch.Tensor.expand` method for tensors. It returns a new distribution instance with batch dimensions expanded to the desired `batch_shape`. Since this calls `torch.Tensor.expand` on the distribution's parameters, it does not allocate new memory for the expanded distribution instance's parameters. e.g. ```python >>> d = dist.Normal(torch.zeros(100, 1), torch.ones(100, 1)) >>> d.sample().shape torch.Size([100, 1]) >>> d.expand([100, 10]).sample().shape torch.Size([100, 10]) ``` We have already been using the `.expand` method in Pyro in our [patch](https://github.com/uber/pyro/blob/dev/pyro/distributions/torch.py#L10) of `torch.distributions`. We use this in our models to enable dynamic broadcasting. This has also been requested by a few users on the distributions slack, and we believe will be useful to the larger community. Note that currently, there is no convenient and efficient way to expand distribution instances: - Many distributions use `TransformedDistribution` (or wrap over another distribution instance. e.g. `OneHotCategorical` uses a `Categorical` instance) under the hood, or have lazy parameters. This makes it difficult to collect all the relevant parameters, broadcast them and construct new instances. - In the few cases where this is even possible, the resulting implementation would be inefficient since we will go through a lot of broadcasting and args validation logic in `__init__.py` that can be avoided. The `.expand` method allows for a safe and efficient way to expand distribution instances. Additionally, this bypasses `__init__.py` (using `__new__` and populating relevant attributes) since we do not need to do any broadcasting or args validation (which was already done when the instance was first created). This can result in significant savings as compared to constructing new instances via `__init__` (that said, the `sample` and `log_prob` methods will probably be the rate determining steps in many applications). e.g. ```python >>> a = dist.Bernoulli(torch.ones([10000, 1]), validate_args=True) >>> %timeit a.expand([10000, 100]) 15.2 µs ± 224 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each) >>> %timeit dist.Bernoulli(torch.ones([10000, 100]), validate_args=True) 11.8 ms ± 153 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) ``` cc. fritzo, apaszke, vishwakftw, alicanb Pull Request resolved: pytorch#11341 Differential Revision: D9728485 Pulled By: soumith fbshipit-source-id: 3b94c23bc6a43ee704389e6287aa83d1e278d52f

Summary: Moves TensorImpl to core. Renames UndefinedTensor to UndefinedTensorImpl and moves to core. Pull Request resolved: pytorch#11441 Differential Revision: D9736620 Pulled By: gchanan fbshipit-source-id: 0322ae3b903e338de253b35a0d74a9d3e219204b

… test_sparse Differential Revision: D9755189 Original commit changeset: e9d36f437db1 fbshipit-source-id: 8b99edf626418a953a8bd786847a6e0174a3a14d

Summary: More functionality to prep nomnigraph for scheduler implementations Reviewed By: duc0 Differential Revision: D9794686 fbshipit-source-id: b460859d8ff965d0049b2a696bd8d2f5c97f3f86

Summary: Pull Request resolved: pytorch#11805 Some of our headers in Caffe2 pollute the macro namespace with things like MAX, MIN, CHECK, so I renamed these in places where this is a problem. This patch courtesy of gchanan, extracted out of pytorch#11721 Reviewed By: Yangqing Differential Revision: D9917757 fbshipit-source-id: 17fc692ca04b208dcb8ae00731ed60e393284f7c

Summary: For example, outputs of control blocks often have Dynamic type, and when we try to export them to ONNX we get an invalid proto, since `elem_type` is not populated on the TypeInfoProto. This makes it so at least we can get past the checker, since having a dynamic typed output from a control block should still be semantically valid Pull Request resolved: pytorch#11810 Differential Revision: D9922754 Pulled By: jamesr66a fbshipit-source-id: 5c66113cc302a9d9b8b9f5a8605473d3c6ad5af1

Summary: The PR fixes pytorch#10873 The context is aten::add and aten::sub ST overloads don't have alpha, so onnx symbolic does not match. Pull Request resolved: pytorch#10972 Reviewed By: jamesr66a Differential Revision: D9724224 Pulled By: wanchaol fbshipit-source-id: eb5d1b09fa8f1604b288f4a62b8d1f0bc66611af

Summary: cc apaszke Pull Request resolved: pytorch#11799 Differential Revision: D9922745 Pulled By: orionr fbshipit-source-id: b88724b7c2919aabc00d98658e8e563233e01c85

Differential Revision: D9919120 Pulled By: goldsborough fbshipit-source-id: bf14cbe4ab79524495957cb749828046af864aab

Summary: Pull Request resolved: pytorch#11402 - Simplify move constructor/assignment - Make more things noexcept Reviewed By: ezyang Differential Revision: D9728631 fbshipit-source-id: 92562e30ea1e4d05ca857665a02b0ca66b0739e3

iotamudelta · 2018-09-19T00:49:42Z

@pytorchbot retest this please

iotamudelta · 2018-09-19T03:05:33Z

@pytorchbot retest this please

iotamudelta · 2018-09-19T03:57:09Z

@pytorchbot retest this please

iotamudelta · 2018-09-19T04:31:02Z

@pytorchbot retest this please

iotamudelta · 2018-09-19T19:31:01Z

@pytorchbot retest this please

iotamudelta · 2018-09-19T19:50:15Z

@pytorchbot retest this please

iotamudelta · 2018-09-19T20:31:25Z

@pytorchbot retest this please

iotamudelta · 2018-09-19T21:00:29Z

@pytorchbot retest this please

iotamudelta · 2018-09-19T21:26:52Z

@pytorchbot retest this please

iotamudelta · 2018-09-19T23:01:37Z

@pytorchbot retest this please

iotamudelta · 2018-09-20T00:46:27Z

Everything but windows passed this time.

@pytorchbot retest this please

iotamudelta · 2018-09-20T02:25:50Z

Finally!

When tensor is resized, reference array to it's sizes may become invalid. Make a copy in advance. <details> <summary>ASAN report</summary> ``` ================================================================= ==1115867==ERROR: AddressSanitizer: heap-use-after-free on address 0x61000013d790 at pc 0x03ff8e7da360 bp 0x03fff53c83a0 sp 0x03fff53c8390 READ of size 8 at 0x61000013d790 thread T0 #0 0x3ff8e7da35f in c10::SymInt::is_heap_allocated() const /home/user/pytorch/c10/core/SymInt.h:154 ROCm#1 0x3ff8e7da35f in c10::SymInt::maybe_as_int() const /home/user/pytorch/c10/core/SymInt.h:215 ROCm#2 0x3ff8e7d0a6d in c10::SymInt::sym_eq(c10::SymInt const&) const /home/user/pytorch/c10/core/SymInt.cpp:69 ROCm#3 0x3ff7a9ab0bd in c10::SymInt::operator==(c10::SymInt const&) const /home/user/pytorch/c10/core/SymInt.h:177 ROCm#4 0x3ff7a9aaedd in bool std::__equal<false>::equal<c10::SymInt const*, c10::SymInt const*>(c10::SymInt const*, c10::SymInt const*, c10::SymInt const*) /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++- v11/bits/stl_algobase.h:1162 ROCm#5 0x3ff7a9aae4b in bool std::__equal_aux1<c10::SymInt const*, c10::SymInt const*>(c10::SymInt const*, c10::SymInt const*, c10::SymInt const*) /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/ stl_algobase.h:1211 ROCm#6 0x3ff7a9aae05 in bool std::__equal_aux<c10::SymInt const*, c10::SymInt const*>(c10::SymInt const*, c10::SymInt const*, c10::SymInt const*) /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/s tl_algobase.h:1219 ROCm#7 0x3ff7a9aad97 in bool std::equal<c10::SymInt const*, c10::SymInt const*>(c10::SymInt const*, c10::SymInt const*, c10::SymInt const*) /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/stl_alg obase.h:1556 ROCm#8 0x3ff4b23c771 in c10::ArrayRef<c10::SymInt>::equals(c10::ArrayRef<c10::SymInt>) const /home/user/pytorch/c10/util/ArrayRef.h:188 ROCm#9 0x3ff4cb91bc1 in bool c10::operator!=<c10::SymInt>(c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>) /home/user/pytorch/c10/util/ArrayRef.h:341 ROCm#10 0x3ff6d1b57ff in torch::ADInplaceOrView::resize_(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) /home/user/pytorch/torch/csrc/autograd/Variab leTypeManual.cpp:408 ROCm#11 0x3ff6d1e59c7 in c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c1 0::MemoryFormat>), &torch::ADInplaceOrView::resize_>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> > >::operator()(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) /home/user/pytorch/aten/src/ATen/core/boxing/impl/WrapFunctionIntoFunctor.h:13 ROCm#12 0x3ff6d1e59c7 in c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10: :ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>), &torch::ADInplaceOrView::resize_>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::Sy mInt>, c10::optional<c10::MemoryFormat> > >, at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)>::call(c10::OperatorKernel*, c10::Disp atchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) /home/user/pytorch/aten/src/ATen/core/boxing/impl/make_boxed_from_unboxed_functor.h:480 ROCm#13 0x3ff51ca5129 in at::Tensor const& c10::callUnboxedKernelFunction<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> >(void*, c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>&&, c10::optional<c10::MemoryFormat>&&) /home/user/pytorch/aten/src/ATen/core/boxing/KernelFunction_impl.h:50 ROCm#14 0x3ff51ca6e8f in at::Tensor const& c10::KernelFunction::call<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> >(c10::OperatorHandle const&, c10::D ispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const /home/user/pytorch/aten/src/ATen/core/boxing/KernelFunction_impl.h:90 ROCm#15 0x3ff51ca6e8f in at::Tensor const& c10::Dispatcher::redispatch<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> >(c10::TypedOperatorHandle<at::Ten sor const& (at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)> const&, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:656 ROCm#16 0x3ff5182006b in c10::TypedOperatorHandle<at::Tensor const& (at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)>::redispatch(c10::DispatchKeySet, at::Tensor const&, c 10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:492 ROCm#17 0x3ff5182006b in at::_ops::resize_::redispatch(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) aten/src/ATen/Operators_4.cpp:2144 ROCm#18 0x3ff6d1d5e07 in at::redispatch::resize__symint(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) aten/src/ATen/RedispatchFunctions.h:2847 ROCm#19 0x3ff6d1bbb67 in torch::autograd::VariableType::(anonymous namespace)::resize_(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) /home/user/pyto rch/torch/csrc/autograd/VariableTypeManual.cpp:243 ROCm#20 0x3ff6d1bd197 in c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c1 0::MemoryFormat>), &torch::autograd::VariableType::(anonymous namespace)::resize_>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10 ::optional<c10::MemoryFormat> > >::operator()(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) /home/user/pytorch/aten/src/ATen/core/boxing/impl/WrapFu nctionIntoFunctor.h:13 ROCm#21 0x3ff6d1bd197 in c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10: :ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>), &torch::autograd::VariableType::(anonymous namespace)::resize_>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> > >, at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)>::call(c 10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) /home/user/pytorch/aten/src/ATen/core/boxing/impl/make_boxed_from_unboxed_functor .h:480 ROCm#22 0x3ff51ca5129 in at::Tensor const& c10::callUnboxedKernelFunction<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> >(void*, c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>&&, c10::optional<c10::MemoryFormat>&&) /home/user/pytorch/aten/src/ATen/core/boxing/KernelFunction_impl.h:50 ROCm#23 0x3ff5181ead1 in at::Tensor const& c10::KernelFunction::call<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> >(c10::OperatorHandle const&, c10::D ispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const /home/user/pytorch/aten/src/ATen/core/boxing/KernelFunction_impl.h:90 ROCm#24 0x3ff5181ead1 in at::Tensor const& c10::Dispatcher::call<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> >(c10::TypedOperatorHandle<at::Tensor co nst& (at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)> const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const /home/user/pytorch/at en/src/ATen/core/dispatch/Dispatcher.h:639 ROCm#25 0x3ff5181ead1 in c10::TypedOperatorHandle<at::Tensor const& (at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)>::call(at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:487 ROCm#26 0x3ff5181ead1 in at::_ops::resize_::call(at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) aten/src/ATen/Operators_4.cpp:2137 ROCm#27 0x3ff79b44fcf in at::Tensor::resize__symint(c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const aten/src/ATen/core/TensorBody.h:2452 ROCm#28 0x3ff79a802db in torch::autograd::THPVariable_resize_(_object*, _object*, _object*)::$_0::operator()(at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const /home/us er/pytorch/torch/csrc/autograd/generated/python_variable_methods.cpp:13417 ROCm#29 0x3ff7999f1eb in torch::autograd::THPVariable_resize_(_object*, _object*, _object*) /home/user/pytorch/torch/csrc/autograd/generated/python_variable_methods.cpp:13419 ROCm#30 0x3ffa2c9b009 in method_vectorcall_VARARGS_KEYWORDS Objects/descrobject.c:344 ROCm#31 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#32 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#33 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#34 0x3ffa2dff7d7 in _PyEval_EvalFrameDefault Python/ceval.c:4198 ROCm#35 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#36 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#37 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#38 0x3ffa2c8ab15 in PyVectorcall_Call Objects/call.c:255 ROCm#39 0x3ffa2c8ac65 in _PyObject_Call Objects/call.c:290 ROCm#40 0x3ffa2c8ada9 in PyObject_Call Objects/call.c:317 ROCm#41 0x3ffa2e059c7 in do_call_core Python/ceval.c:5943 ROCm#42 0x3ffa2dffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#43 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#44 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#45 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#46 0x3ffa2c8ab15 in PyVectorcall_Call Objects/call.c:255 ROCm#47 0x3ffa2c8ac65 in _PyObject_Call Objects/call.c:290 ROCm#48 0x3ffa2c8ada9 in PyObject_Call Objects/call.c:317 ROCm#49 0x3ffa2e059c7 in do_call_core Python/ceval.c:5943 ROCm#50 0x3ffa2dffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#51 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#52 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#53 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#54 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#55 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#56 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#57 0x3ffa2dff7d7 in _PyEval_EvalFrameDefault Python/ceval.c:4198 ROCm#58 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#59 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#60 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#61 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#62 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53 ROCm#63 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#64 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#65 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#66 0x3ffa2dff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 ROCm#67 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#68 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#69 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#70 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#71 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#72 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#73 0x3ffa2dff7d7 in _PyEval_EvalFrameDefault Python/ceval.c:4198 ROCm#74 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#75 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#76 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#77 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#78 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53 ROCm#79 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#80 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#81 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#82 0x3ffa2dffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#83 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#84 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#85 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#86 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#87 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53 ROCm#88 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#89 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#90 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#91 0x3ffa2dffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#92 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#93 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#94 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#95 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#96 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53 ROCm#97 0x3ffa2c8ab9b in PyVectorcall_Call Objects/call.c:267 ROCm#98 0x3ffa2c8ac65 in _PyObject_Call Objects/call.c:290 ROCm#99 0x3ffa2c8ada9 in PyObject_Call Objects/call.c:317 ROCm#100 0x3ffa2e059c7 in do_call_core Python/ceval.c:5943 ROCm#101 0x3ffa2dffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#102 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#103 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#104 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#105 0x3ffa2c8a695 in _PyObject_FastCallDictTstate Objects/call.c:153 ROCm#106 0x3ffa2c8b271 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#107 0x3ffa2d3f307 in slot_tp_call Objects/typeobject.c:7494 ROCm#108 0x3ffa2c8a933 in _PyObject_MakeTpCall Objects/call.c:215 ROCm#109 0x3ffa2df0081 in _PyObject_VectorcallTstate Include/cpython/abstract.h:112 ROCm#110 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#111 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#112 0x3ffa2dffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#113 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#114 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#115 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#116 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#117 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#118 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#119 0x3ffa2dff7d7 in _PyEval_EvalFrameDefault Python/ceval.c:4198 ROCm#120 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#121 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#122 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#123 0x3ffa2c8ab15 in PyVectorcall_Call Objects/call.c:255 ROCm#124 0x3ffa2c8ac65 in _PyObject_Call Objects/call.c:290 ROCm#125 0x3ffa2c8ada9 in PyObject_Call Objects/call.c:317 ROCm#126 0x3ffa2e059c7 in do_call_core Python/ceval.c:5943 ROCm#127 0x3ffa2dffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#128 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#129 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#130 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#131 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#132 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#133 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#134 0x3ffa2dff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#135 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#136 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#137 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#138 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#139 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53 ROCm#140 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#141 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#142 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#143 0x3ffa2dff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#144 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#145 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#146 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#147 0x3ffa2c8a695 in _PyObject_FastCallDictTstate Objects/call.c:153 ROCm#148 0x3ffa2c8b271 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#149 0x3ffa2d3f307 in slot_tp_call Objects/typeobject.c:7494 ROCm#150 0x3ffa2c8ad17 in _PyObject_Call Objects/call.c:305 ROCm#151 0x3ffa2c8ada9 in PyObject_Call Objects/call.c:317 ROCm#152 0x3ffa2e059c7 in do_call_core Python/ceval.c:5943 ROCm#153 0x3ffa2dffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#154 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#155 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#156 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#157 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#158 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#159 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#160 0x3ffa2dff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 ROCm#161 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#162 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#163 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#164 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#165 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53 ROCm#166 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#167 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#168 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#169 0x3ffa2dffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#170 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#171 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#172 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#173 0x3ffa2c8ab15 in PyVectorcall_Call Objects/call.c:255 ROCm#174 0x3ffa2c8ac65 in _PyObject_Call Objects/call.c:290 ROCm#175 0x3ffa2c8ada9 in PyObject_Call Objects/call.c:317 ROCm#176 0x3ffa2e059c7 in do_call_core Python/ceval.c:5943 ROCm#177 0x3ffa2dffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#178 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#179 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#180 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#181 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#182 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#183 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#184 0x3ffa2dff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 ROCm#185 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#186 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#187 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#188 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#189 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#190 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#191 0x3ffa2dffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#192 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#193 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#194 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#195 0x3ffa2c8ab15 in PyVectorcall_Call Objects/call.c:255 ROCm#196 0x3ffa2c8ac65 in _PyObject_Call Objects/call.c:290 ROCm#197 0x3ffa2c8ada9 in PyObject_Call Objects/call.c:317 ROCm#198 0x3ffa2e059c7 in do_call_core Python/ceval.c:5943 ROCm#199 0x3ffa2dffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#200 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#201 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#202 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#203 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#204 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#205 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#206 0x3ffa2dff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#207 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#208 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#209 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#210 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#211 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53 ROCm#212 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#213 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#214 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#215 0x3ffa2dff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#216 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#217 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#218 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#219 0x3ffa2c8a695 in _PyObject_FastCallDictTstate Objects/call.c:153 ROCm#220 0x3ffa2c8b271 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#221 0x3ffa2d3f307 in slot_tp_call Objects/typeobject.c:7494 ROCm#222 0x3ffa2c8a933 in _PyObject_MakeTpCall Objects/call.c:215 ROCm#223 0x3ffa2df0081 in _PyObject_VectorcallTstate Include/cpython/abstract.h:112 ROCm#224 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#225 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#226 0x3ffa2dffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#227 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#228 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#229 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#230 0x3ffa2c8ab15 in PyVectorcall_Call Objects/call.c:255 ROCm#231 0x3ffa2c8ac65 in _PyObject_Call Objects/call.c:290 ROCm#232 0x3ffa2c8ada9 in PyObject_Call Objects/call.c:317 ROCm#233 0x3ffa2e059c7 in do_call_core Python/ceval.c:5943 ROCm#234 0x3ffa2dffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#235 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#236 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#237 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#238 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#239 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#240 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#241 0x3ffa2dff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#242 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#243 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#244 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#245 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#246 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53 ROCm#247 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#248 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#249 0x3ffa2e05447 in call_function Python/ceval.c:5891 ROCm#250 0x3ffa2dff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#251 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#252 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#253 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#254 0x3ffa2c8a695 in _PyObject_FastCallDictTstate Objects/call.c:153 ROCm#255 0x3ffa2c8b271 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#256 0x3ffa2d3f307 in slot_tp_call Objects/typeobject.c:7494 ROCm#257 0x3ffa2c8a933 in _PyObject_MakeTpCall Objects/call.c:215 0x61000013d790 is located 80 bytes inside of 192-byte region [0x61000013d740,0x61000013d800) freed by thread T0 here: #0 0x3ffa3237de5 in operator delete(void*) /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_new_delete.cpp:160 ROCm#1 0x3ff8e7e3221 in c10::TensorImpl::~TensorImpl() /home/user/pytorch/c10/core/TensorImpl.cpp:75 previously allocated by thread T0 here: #0 0x3ffa323734f in operator new(unsigned long) /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_new_delete.cpp:99 ROCm#1 0x3ff4aeeb3d1 in c10::intrusive_ptr<c10::TensorImpl, c10::detail::intrusive_target_default_null_type<c10::TensorImpl> > c10::intrusive_ptr<c10::TensorImpl, c10::detail::intrusive_target_default_nul l_type<c10::TensorImpl> >::make<c10::intrusive_ptr<c10::StorageImpl, c10::detail::intrusive_target_default_null_type<c10::StorageImpl> >, c10::DispatchKeySet&, caffe2::TypeMeta&>(c10::intrusive_ptr<c10::S torageImpl, c10::detail::intrusive_target_default_null_type<c10::StorageImpl> >&&, c10::DispatchKeySet&, caffe2::TypeMeta&) /home/user/pytorch/c10/util/intrusive_ptr.h:498 ROCm#2 0x3ff76f79e17 (/home/user/pytorch/build/lib.linux-s390x-cpython-310/torch/lib/libtorch_cpu.so+0x2fb79e17) SUMMARY: AddressSanitizer: heap-use-after-free /home/user/pytorch/c10/core/SymInt.h:154 in c10::SymInt::is_heap_allocated() const Shadow bytes around the buggy address: 0x100c2000027aa0: fa fa fa fa fa fa fa fa fd fd fd fd fd fd fd fd 0x100c2000027ab0: fd fd fd fd fd fd fd fd fd fd fd fd fd fd fd fd 0x100c2000027ac0: fa fa fa fa fa fa fa fa fd fd fd fd fd fd fd fd 0x100c2000027ad0: fd fd fd fd fd fd fd fd fd fd fd fd fd fd fd fd 0x100c2000027ae0: fa fa fa fa fa fa fa fa fd fd fd fd fd fd fd fd =>0x100c2000027af0: fd fd[fd]fd fd fd fd fd fd fd fd fd fd fd fd fd 0x100c2000027b00: fa fa fa fa fa fa fa fa 00 00 00 00 00 00 00 00 0x100c2000027b10: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 0x100c2000027b20: fa fa fa fa fa fa fa fa 00 00 00 00 00 00 00 00 0x100c2000027b30: 00 00 00 00 04 fa fa fa fa fa fa fa fa fa fa fa 0x100c2000027b40: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa Shadow byte legend (one shadow byte represents 8 application bytes): Addressable: 00 Partially addressable: 01 02 03 04 05 06 07 Heap left redzone: fa Freed heap region: fd Stack left redzone: f1 Stack mid redzone: f2 Stack right redzone: f3 Stack after return: f5 Stack use after scope: f8 Global redzone: f9 Global init order: f6 Poisoned by user: f7 Container overflow: fc Array cookie: ac Intra object redzone: bb ASan internal: fe Left alloca redzone: ca Right alloca redzone: cb Shadow gap: cc ==1115867==ABORTING ``` </details> <details> <summary>Additional backtraces (not full)</summary> Memory deallocation: ``` #0 operator delete (ptr=0x61000013d740) at /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_new_delete.cpp:160 ROCm#1 0x000003ffa77e3222 in c10::TensorImpl::~TensorImpl (this=0x61000013d740) at /home/user/pytorch/c10/core/TensorImpl.cpp:75 ROCm#2 0x000003ff63e76e8c in c10::intrusive_ptr<c10::TensorImpl, c10::UndefinedTensorImpl>::reset_ (this=0x3ffd7ec8230) at /home/user/pytorch/c10/util/intrusive_ptr.h:291 ROCm#3 0x000003ff63e76910 in c10::intrusive_ptr<c10::TensorImpl, c10::UndefinedTensorImpl>::~intrusive_ptr (this=0x3ffd7ec8230) at /home/user/pytorch/c10/util/intrusive_ptr.h:370 ROCm#4 0x000003ff63e67240 in at::TensorBase::~TensorBase (this=0x3ffd7ec8230) at /home/user/pytorch/aten/src/ATen/core/TensorBase.h:80 ROCm#5 0x000003ff63e85ee0 in at::Tensor::~Tensor (this=0x3ffd7ec8230) at aten/src/ATen/core/TensorBody.h:90 ROCm#6 0x000003ff63f67304 in resize__functionalization (dispatchKeySet=..., self=..., size=..., memory_format=...) at /home/user/pytorch/aten/src/ATen/FunctionalizeFallbackKernel.cpp:173 ROCm#7 0x000003ff63f89258 in c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>), &(resize__functionalization(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>))>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat> > >::operator()(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>) ( this=0x6030000390a0, args=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/boxing/impl/WrapFunctionIntoFunctor.h:13 ROCm#8 c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>), &(resize__functionalization(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>))>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat> > >, at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>)>::call(c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>) (functor=0x6030000390a0, dispatchKeySet=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/boxing/impl/make_boxed_from_unboxed_functor.h:480 ROCm#9 0x000003ff6aca560a in c10::callUnboxedKernelFunction<at::Tensor const&, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat> > ( unboxed_kernel_func=0x3ff63f88a80 <c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tenso r const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>), &(resize__functionalization(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>))>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat> > >, at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>)>::call(c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, c10::optional<c10::MemoryFormat>)>, functor=0x6030000390a0, dispatchKeySet=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/boxing/KernelFunction_impl.h:50 ROCm#10 0x000003ff6aca715c in c10::KernelFunction::call<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> > (this=0x6210005e1b28, opHandle=..., dispatchKeySet=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/boxing/KernelFunction_impl.h:96 ROCm#11 c10::Dispatcher::redispatch<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> >(c10::TypedOperatorHandle<at::Tensor const& (at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)> const&, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const ( this=0x3ff919400e0 <c10::Dispatcher::realSingleton()::_singleton>, op=..., currentDispatchKeySet=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:656 ROCm#12 0x000003ff6a82006c in c10::TypedOperatorHandle<at::Tensor const& (at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)>::redispatch(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const ( this=0x3ff919a07e0 <at::_ops::resize_::redispatch(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)::op>, currentDispatchKeySet=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:492 ROCm#13 at::_ops::resize_::redispatch (dispatchKeySet=..., self=..., size=..., memory_format=...) at /home/user/pytorch/build/aten/src/ATen/Operators_4.cpp:2144 ROCm#14 0x000003ff861d5e08 in at::redispatch::resize__symint (dispatchKeySet=..., self=..., size=..., memory_format=...) at aten/src/ATen/RedispatchFunctions.h:2847 ROCm#15 0x000003ff861b579e in torch::ADInplaceOrView::resize_ (ks=..., self=..., size=..., optional_memory_format=...) at /home/user/pytorch/torch/csrc/autograd/VariableTypeManual.cpp:401 ``` Memory access: ``` #0 c10::SymInt::maybe_as_int (this=0x61000013d790) at /home/user/pytorch/c10/core/SymInt.h:215 ROCm#1 0x000003ff734d0a6e in c10::SymInt::sym_eq (this=0x61000013d790, sci=...) at /home/user/pytorch/c10/core/SymInt.cpp:69 ROCm#2 0x000003ff5f6ab0be in c10::SymInt::operator== (this=0x61000013d790, o=...) at /home/user/pytorch/c10/core/SymInt.h:177 ROCm#3 0x000003ff5f6aaede in std::__equal<false>::equal<c10::SymInt const*, c10::SymInt const*> (__first1=0x61000013d790, __last1=0x61000013d7a0, __first2=0x602000015c30) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/stl_algobase.h:1162 ROCm#4 0x000003ff5f6aae4c in std::__equal_aux1<c10::SymInt const*, c10::SymInt const*> (__first1=0x61000013d790, __last1=0x61000013d7a0, __first2=0x602000015c30) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/stl_algobase.h:1211 ROCm#5 0x000003ff5f6aae06 in std::__equal_aux<c10::SymInt const*, c10::SymInt const*> (__first1=0x61000013d790, __last1=0x61000013d7a0, __first2=0x602000015c30) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/stl_algobase.h:1219 ROCm#6 0x000003ff5f6aad98 in std::equal<c10::SymInt const*, c10::SymInt const*> (__first1=0x61000013d790, __last1=0x61000013d7a0, __first2=0x602000015c30) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/stl_algobase.h:1556 ROCm#7 0x000003ff2ff3c772 in c10::ArrayRef<c10::SymInt>::equals (this=0x3ffed7c9900, RHS=...) at /home/user/pytorch/c10/util/ArrayRef.h:188 ROCm#8 0x000003ff31891bc2 in c10::operator!=<c10::SymInt> (a1=..., a2=...) at /home/user/pytorch/c10/util/ArrayRef.h:341 ROCm#9 0x000003ff51eb5800 in torch::ADInplaceOrView::resize_ (ks=..., self=..., size=..., optional_memory_format=...) at /home/user/pytorch/torch/csrc/autograd/VariableTypeManual.cpp:408 ROCm#10 0x000003ff51ee59c8 in c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c 10::MemoryFormat>), &torch::ADInplaceOrView::resize_>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> > >::operator()(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) (this=0x6030007dca40, args=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/boxing/impl/WrapFunctionIntoFunctor.h:13 ROCm#11 c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt >, c10::optional<c10::MemoryFormat>), &torch::ADInplaceOrView::resize_>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional< c10::MemoryFormat> > >, at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)>::call(c10::OperatorKernel*, c10::DispatchKeySet, at::Tenso r const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) (functor=0x6030007dca40, dispatchKeySet=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/boxing/impl/make_boxed_from_unboxed_functor.h:480 ROCm#12 0x000003ff369a512a in c10::callUnboxedKernelFunction<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> > ( unboxed_kernel_func=0x3ff51ee51f0 <c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor const& (c10::DispatchKeySet, at::Tenso r const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>), &torch::ADInplaceOrView::resize_>, at::Tensor const&, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::Ar rayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> > >, at::Tensor const& (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)>::call(c10::OperatorKern el*, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)>, functor=0x6030007dca40, dispatchKeySet=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/boxing/KernelFunction_impl.h:50 ROCm#13 0x000003ff369a6e90 in c10::KernelFunction::call<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> > (this=0x6210005e1bc8, opHandle=..., dispatchKeySet=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/boxing/KernelFunction_impl.h:90 ROCm#14 c10::Dispatcher::redispatch<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat> >(c10::TypedOperatorHandle<at::Tensor const& (at::Tensor const&, c10::Arr ayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)> const&, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const ( this=0x3ff5d6400e0 <c10::Dispatcher::realSingleton()::_singleton>, op=..., currentDispatchKeySet=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:656 ROCm#15 0x000003ff3652006c in c10::TypedOperatorHandle<at::Tensor const& (at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)>::redispatch(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const ( this=0x3ff5d6a07e0 <at::_ops::resize_::redispatch(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>)::op>, currentDispatchKeySet=..., args=..., args=..., args=...) at /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:492 ROCm#16 at::_ops::resize_::redispatch (dispatchKeySet=..., self=..., size=..., memory_format=...) at /home/user/pytorch/build/aten/src/ATen/Operators_4.cpp:2144 ROCm#17 0x000003ff51ed5e08 in at::redispatch::resize__symint (dispatchKeySet=..., self=..., size=..., memory_format=...) at aten/src/ATen/RedispatchFunctions.h:2847 ROCm#18 0x000003ff51ebbb68 in torch::autograd::VariableType::(anonymous namespace)::resize_ (ks=..., self=..., size=..., optional_memory_format=...) at /home/user/pytorch/torch/csrc/autograd/VariableTypeManual.cpp:243 ``` </details> Pull Request resolved: pytorch#101064 Approved by: https://github.com/Skylion007, https://github.com/albanD

arguments() returns vector member of object returned by schema() call. When object returned by schema() call is destroyed, the vector is deallocated as well, it's lifetime isn't extended. This issue detected while running `pytest -v test/mobile/test_lite_script_type.py -k test_nest_typing_namedtuple_custom_classtype` with ASAN. <details> <summary>ASAN output</summary> ``` ==1134126==ERROR: AddressSanitizer: heap-use-after-free on address 0x60d0005a5790 at pc 0x03ff844488d8 bp 0x03fff584afe8 sp 0x03fff584afd8 READ of size 8 at 0x60d0005a5790 thread T0 #0 0x3ff844488d7 in __gnu_cxx::__normal_iterator<c10::Argument const*, std::vector<c10::Argument, std::allocator<c10::Argument> > >::__normal_iterator(c10::Argument const* const&) /usr/lib/gcc/s390x-i bm-linux-gnu/11/include/g++-v11/bits/stl_iterator.h:1028 #1 0x3ff8444293f in std::vector<c10::Argument, std::allocator<c10::Argument> >::begin() const /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/stl_vector.h:821 #2 0x3ff84d807d1 in torch::jit::toPyObject(c10::IValue) /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:617 ROCm#3 0x3ff84d80305 in torch::jit::toPyObject(c10::IValue) /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:604 ROCm#4 0x3ff84856871 in pybind11::detail::type_caster<c10::IValue, void>::cast(c10::IValue, pybind11::return_value_policy, pybind11::handle) /home/user/pytorch/torch/csrc/jit/python/pybind.h:138 ROCm#5 0x3ff85318191 in pybind11::cpp_function::initialize<torch::jit::initJitScriptBindings(_object*)::$_45, c10::IValue, torch::jit::mobile::Module&, pybind11::tuple const&, pybind11::name, pybind11::is _method, pybind11::sibling, pybind11::arg>(torch::jit::initJitScriptBindings(_object*)::$_45&&, c10::IValue (*)(torch::jit::mobile::Module&, pybind11::tuple const&), pybind11::name const&, pybind11::is_me thod const&, pybind11::sibling const&, pybind11::arg const&)::{lambda(pybind11::detail::function_call&)#1}::operator()(pybind11::detail::function_call&) const /home/user/pytorch/cmake/../third_party/pybin d11/include/pybind11/pybind11.h:249 ROCm#6 0x3ff85317cfd in pybind11::cpp_function::initialize<torch::jit::initJitScriptBindings(_object*)::$_45, c10::IValue, torch::jit::mobile::Module&, pybind11::tuple const&, pybind11::name, pybind11::is _method, pybind11::sibling, pybind11::arg>(torch::jit::initJitScriptBindings(_object*)::$_45&&, c10::IValue (*)(torch::jit::mobile::Module&, pybind11::tuple const&), pybind11::name const&, pybind11::is_me thod const&, pybind11::sibling const&, pybind11::arg const&)::{lambda(pybind11::detail::function_call&)#1}::__invoke(pybind11::detail::function_call&) /home/user/pytorch/cmake/../third_party/pybind11/incl ude/pybind11/pybind11.h:224 ROCm#7 0x3ff82ee52e9 in pybind11::cpp_function::dispatcher(_object*, _object*, _object*) /home/user/pytorch/cmake/../third_party/pybind11/include/pybind11/pybind11.h:929 ROCm#8 0x3ffab002903 in cfunction_call Objects/methodobject.c:543 ROCm#9 0x3ffaaf8a933 in _PyObject_MakeTpCall Objects/call.c:215 ROCm#10 0x3ffaaf8e919 in _PyObject_VectorcallTstate Include/cpython/abstract.h:112 ROCm#11 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 ROCm#12 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#13 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#14 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#15 0x3ffab0ff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#16 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#17 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#18 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#19 0x3ffaaf8a615 in _PyObject_FastCallDictTstate Objects/call.c:142 ROCm#20 0x3ffaaf8b271 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#21 0x3ffab03f307 in slot_tp_call Objects/typeobject.c:7494 ROCm#22 0x3ffaaf8a933 in _PyObject_MakeTpCall Objects/call.c:215 ROCm#23 0x3ffab0f0081 in _PyObject_VectorcallTstate Include/cpython/abstract.h:112 ROCm#24 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#25 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#26 0x3ffab0ff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 ROCm#27 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#28 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#29 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#30 0x3ffaaf8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#31 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 ROCm#32 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#33 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#34 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#35 0x3ffab0ff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 ROCm#36 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#37 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#38 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#39 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#40 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#41 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#42 0x3ffab0ff7d7 in _PyEval_EvalFrameDefault Python/ceval.c:4198 ROCm#43 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#44 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#45 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#46 0x3ffaaf8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#47 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 ROCm#48 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#49 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#50 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#51 0x3ffab0ffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#52 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#53 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#54 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#55 0x3ffaaf8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#56 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 ROCm#57 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#58 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#59 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#60 0x3ffab0ffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#61 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#62 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#63 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#64 0x3ffaaf8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#65 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 ROCm#66 0x3ffaaf8ab9b in PyVectorcall_Call Objects/call.c:267 ROCm#67 0x3ffaaf8ac65 in _PyObject_Call Objects/call.c:290 ROCm#68 0x3ffaaf8ada9 in PyObject_Call Objects/call.c:317 ROCm#69 0x3ffab1059c7 in do_call_core Python/ceval.c:5943 ROCm#70 0x3ffab0ffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#71 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#72 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#73 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#74 0x3ffaaf8a695 in _PyObject_FastCallDictTstate Objects/call.c:153 ROCm#75 0x3ffaaf8b271 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#76 0x3ffab03f307 in slot_tp_call Objects/typeobject.c:7494 ROCm#77 0x3ffaaf8a933 in _PyObject_MakeTpCall Objects/call.c:215 ROCm#78 0x3ffab0f0081 in _PyObject_VectorcallTstate Include/cpython/abstract.h:112 ROCm#79 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#80 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#81 0x3ffab0ffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#82 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#83 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#84 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#85 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#86 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#87 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#88 0x3ffab0ff7d7 in _PyEval_EvalFrameDefault Python/ceval.c:4198 ROCm#89 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#90 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#91 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#92 0x3ffaaf8ab15 in PyVectorcall_Call Objects/call.c:255 ROCm#93 0x3ffaaf8ac65 in _PyObject_Call Objects/call.c:290 ROCm#94 0x3ffaaf8ada9 in PyObject_Call Objects/call.c:317 ROCm#95 0x3ffab1059c7 in do_call_core Python/ceval.c:5943 ROCm#96 0x3ffab0ffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#97 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#98 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#99 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#100 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#101 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#102 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#103 0x3ffab0ff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#104 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#105 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#106 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#107 0x3ffaaf8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#108 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 ROCm#109 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#110 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#111 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#112 0x3ffab0ff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#113 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#114 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#115 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#116 0x3ffaaf8a695 in _PyObject_FastCallDictTstate Objects/call.c:153 ROCm#117 0x3ffaaf8b271 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#118 0x3ffab03f307 in slot_tp_call Objects/typeobject.c:7494 ROCm#119 0x3ffaaf8ad17 in _PyObject_Call Objects/call.c:305 ROCm#120 0x3ffaaf8ada9 in PyObject_Call Objects/call.c:317 ROCm#121 0x3ffab1059c7 in do_call_core Python/ceval.c:5943 ROCm#122 0x3ffab0ffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#123 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#124 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#125 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#126 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#127 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#128 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#129 0x3ffab0ff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 ROCm#130 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#131 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#132 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#133 0x3ffaaf8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#134 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 ROCm#135 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#136 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#137 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#138 0x3ffab0ffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#139 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#140 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#141 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#142 0x3ffaaf8ab15 in PyVectorcall_Call Objects/call.c:255 ROCm#143 0x3ffaaf8ac65 in _PyObject_Call Objects/call.c:290 ROCm#144 0x3ffaaf8ada9 in PyObject_Call Objects/call.c:317 ROCm#145 0x3ffab1059c7 in do_call_core Python/ceval.c:5943 ROCm#146 0x3ffab0ffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#147 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#148 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#149 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#150 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#151 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#152 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#153 0x3ffab0ff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 ROCm#154 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#155 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#156 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#157 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#158 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#159 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#160 0x3ffab0ffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#161 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#162 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#163 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#164 0x3ffaaf8ab15 in PyVectorcall_Call Objects/call.c:255 ROCm#165 0x3ffaaf8ac65 in _PyObject_Call Objects/call.c:290 ROCm#166 0x3ffaaf8ada9 in PyObject_Call Objects/call.c:317 ROCm#167 0x3ffab1059c7 in do_call_core Python/ceval.c:5943 ROCm#168 0x3ffab0ffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#169 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#170 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#171 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#172 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#173 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#174 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#175 0x3ffab0ff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#176 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#177 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#178 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#179 0x3ffaaf8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#180 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 ROCm#181 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#182 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#183 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#184 0x3ffab0ff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#185 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#186 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#187 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#188 0x3ffaaf8a695 in _PyObject_FastCallDictTstate Objects/call.c:153 ROCm#189 0x3ffaaf8b271 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#190 0x3ffab03f307 in slot_tp_call Objects/typeobject.c:7494 ROCm#191 0x3ffaaf8a933 in _PyObject_MakeTpCall Objects/call.c:215 ROCm#192 0x3ffab0f0081 in _PyObject_VectorcallTstate Include/cpython/abstract.h:112 ROCm#193 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#194 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#195 0x3ffab0ffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#196 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#197 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#198 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#199 0x3ffaaf8ab15 in PyVectorcall_Call Objects/call.c:255 ROCm#200 0x3ffaaf8ac65 in _PyObject_Call Objects/call.c:290 ROCm#201 0x3ffaaf8ada9 in PyObject_Call Objects/call.c:317 ROCm#202 0x3ffab1059c7 in do_call_core Python/ceval.c:5943 ROCm#203 0x3ffab0ffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#204 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#205 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#206 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#207 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#208 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#209 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#210 0x3ffab0ff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#211 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#212 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#213 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#214 0x3ffaaf8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#215 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 ROCm#216 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#216 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#217 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#218 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#219 0x3ffab0ff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#220 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#221 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#222 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#223 0x3ffaaf8a695 in _PyObject_FastCallDictTstate Objects/call.c:153 ROCm#224 0x3ffaaf8b271 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#225 0x3ffab03f307 in slot_tp_call Objects/typeobject.c:7494 ROCm#226 0x3ffaaf8a933 in _PyObject_MakeTpCall Objects/call.c:215 ROCm#227 0x3ffab0f0081 in _PyObject_VectorcallTstate Include/cpython/abstract.h:112 ROCm#228 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#229 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#230 0x3ffab0ffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 ROCm#231 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#232 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#233 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#234 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#235 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#236 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#237 0x3ffab0ff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 ROCm#238 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#239 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#240 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#241 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#242 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#243 0x3ffab105447 in call_function Python/ceval.c:5891 ROCm#244 0x3ffab0ff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 ROCm#245 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#246 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 ROCm#247 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 ROCm#248 0x3ffaaf8ab15 in PyVectorcall_Call Objects/call.c:255 ROCm#249 0x3ffaaf8ac65 in _PyObject_Call Objects/call.c:290 0x60d0005a5790 is located 80 bytes inside of 136-byte region [0x60d0005a5740,0x60d0005a57c8) freed by thread T0 here: #0 0x3ffab537de5 in operator delete(void*) /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_new_delete.cpp:160 #1 0x3ff55984fdb in __gnu_cxx::new_allocator<std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2> >::deallocate(std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2>*, unsigned long) /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/ext/new_allocator.h:145 previously allocated by thread T0 here: #0 0x3ffab53734f in operator new(unsigned long) /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_new_delete.cpp:99 #1 0x3ff5598443f in __gnu_cxx::new_allocator<std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2> >::allocate(unsigned long, void const*) /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/ext/new_allocator.h:127 #2 0x3fff5849ecf ([stack]+0xb2ecf) SUMMARY: AddressSanitizer: heap-use-after-free /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/stl_iterator.h:1028 in __gnu_cxx::__normal_iterator<c10::Argument const*, std::vector<c10::Argument, std::allocator<c10::Argument> > >::__normal_iterator(c10::Argument const* const&) Shadow bytes around the buggy address: 0x100c1a000b4aa0: fd fd fd fd fd fd fd fd fd fd fd fa fa fa fa fa 0x100c1a000b4ab0: fa fa fa fa fd fd fd fd fd fd fd fd fd fd fd fd 0x100c1a000b4ac0: fd fd fd fd fd fa fa fa fa fa fa fa fa fa fd fd 0x100c1a000b4ad0: fd fd fd fd fd fd fd fd fd fd fd fd fd fd fd fa 0x100c1a000b4ae0: fa fa fa fa fa fa fa fa fd fd fd fd fd fd fd fd =>0x100c1a000b4af0: fd fd[fd]fd fd fd fd fd fd fa fa fa fa fa fa fa 0x100c1a000b4b00: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa 0x100c1a000b4b10: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa 0x100c1a000b4b20: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa 0x100c1a000b4b30: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa 0x100c1a000b4b40: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa Shadow byte legend (one shadow byte represents 8 application bytes): Addressable: 00 Partially addressable: 01 02 03 04 05 06 07 Heap left redzone: fa Freed heap region: fd Stack left redzone: f1 Stack mid redzone: f2 Stack right redzone: f3 Stack after return: f5 Stack use after scope: f8 Global redzone: f9 Global init order: f6 Poisoned by user: f7 Container overflow: fc Array cookie: ac Intra object redzone: bb ASan internal: fe Left alloca redzone: ca Right alloca redzone: cb Shadow gap: cc ==1134126==ABORTING ``` Additional backtraces (not full): Allocation: ``` #0 __memset_z196 () at ../sysdeps/s390/memset-z900.S:144 #1 0x000003ff96f3072a in __asan::Allocator::Allocate (this=this@entry=0x3ff97041eb8 <__asan::instance>, size=size@entry=136, alignment=8, alignment@entry=0, stack=<optimized out>, stack@entry=0x3ffdbb45d78, alloc_type=<optimized out>, can_fill=true) at /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_allocator.cpp:599 #2 0x000003ff96f2c088 in __asan::asan_memalign (alignment=alignment@entry=0, size=size@entry=136, stack=stack@entry=0x3ffdbb45d78, alloc_type=alloc_type@entry=__asan::FROM_NEW) at /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_allocator.cpp:1039 ROCm#3 0x000003ff96fb73b0 in operator new (size=136) at /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_new_delete.cpp:99 ROCm#4 0x000003ff41404440 in __gnu_cxx::new_allocator<std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2> >::allocate (this=0x3ffdbb468c0, __n=1) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/ext/new_allocator.h:127 ROCm#5 0x000003ff414042a0 in std::allocator_traits<std::allocator<std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2> > >::allocate (__a=..., __n=1) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/alloc_traits.h:464 ROCm#6 0x000003ff41403b66 in std::__allocate_guarded<std::allocator<std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2> > > (__a=...) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/allocated_ptr.h:98 ROCm#7 0x000003ff4140372a in std::__shared_count<(__gnu_cxx::_Lock_policy)2>::__shared_count<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::vector<c10::Argument, std::allocator<c10::Argument> >, std::vector<c10::Argument, std::allocator<c10::Argument> > > (this=0x3ffdbb47888, __p=@0x3ffdbb47880: 0x0, __a=..., __args=..., __args=..., __args=..., __args=...) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:648 ROCm#8 0x000003ff41403328 in std::__shared_ptr<c10::FunctionSchema, (__gnu_cxx::_Lock_policy)2>::__shared_ptr<std::allocator<c10::FunctionSchema>, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::vector<c10::Argument, std::allocator<c10::Argument> >, std::vector<c10::Argument, std::allocator<c10::Argument> > > (this=0x3ffdbb47880, __tag=..., __args=..., __args=..., __args=..., __args=...) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:1342 ROCm#9 0x000003ff41402f06 in std::shared_ptr<c10::FunctionSchema>::shared_ptr<std::allocator<c10::FunctionSchema>, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::vector<c10::Argument, std::allocator<c10::Argument> >, std::vector<c10::Argument, std::allocator<c10::Argument> > > ( this=0x3ffdbb47880, __tag=..., __args=..., __args=..., __args=..., __args=...) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr.h:409 ROCm#10 0x000003ff41402b6e in std::allocate_shared<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::vector<c10::Argument, std::allocator<c10::Argument> >, std::vector<c10::Argument, std::allocator<c10::Argument> > > (__a=..., __args=..., __args=..., __args=..., __args=...) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr.h:862 ROCm#11 0x000003ff4140215c in std::make_shared<c10::FunctionSchema, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::vector<c10::Argument, std::allocator<c10::Argument> >, std::vector<c10::Argument, std::allocator<c10::Argument> > > (__args=..., __args=..., __args=..., __args=...) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr.h:878 ROCm#12 0x000003ff413d180c in c10::TupleType::createWithSpec<c10::basic_string_view<char> > (qualName=..., field_names=std::vector of length 1, capacity 1 = {...}, field_types=std::vector of length 1, capacity 1 = {...}, field_defaults=std::vector of length 0, capacity 0) at /home/user/pytorch/aten/src/ATen/core/type.cpp:769 ROCm#13 0x000003ff413b9ca6 in c10::TupleType::createNamed (qualName=..., field_names=std::vector of length 1, capacity 1 = {...}, field_types=std::vector of length 1, capacity 1 = {...}) at /home/user/pytorch/aten/src/ATen/core/type.cpp:725 ROCm#14 0x000003ff4115fbac in c10::ivalue::TupleTypeFactory<c10::TupleType>::fallback (type=...) at /home/user/pytorch/aten/src/ATen/core/dynamic_type.cpp:383 ROCm#15 0x000003ff708217fe in c10::ivalue::Tuple::type<c10::TupleType> (this=0x6080004b8520) at /home/user/pytorch/aten/src/ATen/core/ivalue_inl.h:781 ROCm#16 0x000003ff70800740 in torch::jit::toPyObject (ivalue=...) at /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:613 ROCm#17 0x000003ff70800306 in torch::jit::toPyObject (ivalue=...) at /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:604 ROCm#18 0x000003ff702d6872 in pybind11::detail::type_caster<c10::IValue, void>::cast (src=...) at /home/user/pytorch/torch/csrc/jit/python/pybind.h:138 ROCm#19 0x000003ff70d98192 in pybind11::cpp_function::initialize<torch::jit::initJitScriptBindings(_object*)::$_45, c10::IValue, torch::jit::mobile::Module&, pybind11::tuple const&, pybind11::name, pybind11::is_method, pybind11::sibling, pybind11::arg>(torch::jit::initJitScriptBindings(_object*)::$_45&&, c10::IValue (*)(torch::jit::mobile::Module&, pybind11::tuple const&), pybind11::name const&, pybind11::is_method const&, pybind11::sibling const&, pybind11::arg const&)::{lambda(pybind11::detail::function_call&)#1}::operator()(pybind11::detail::function_call&) const (this=0x3ffdbb4ca20, call=...) at /home/user/pytorch/cmake/../third_party/pybind11/include/pybind11/pybind11.h:249 ROCm#20 0x000003ff70d97cfe in pybind11::cpp_function::initialize<torch::jit::initJitScriptBindings(_object*)::$_45, c10::IValue, torch::jit::mobile::Module&, pybind11::tuple const&, pybind11::name, pybind11::is_method, pybind11::sibling, pybind11::arg>(torch::jit::initJitScriptBindings(_object*)::$_45&&, c10::IValue (*)(torch::jit::mobile::Module&, pybind11::tuple const&), pybind11::name const&, pybind11::is_method const&, pybind11::sibling const&, pybind11::arg const&)::{lambda(pybind11::detail::function_call&)#1}::__invoke(pybind11::detail::function_call&) (call=...) at /home/user/pytorch/cmake/../third_party/pybind11/include/pybind11/pybind11.h:224 ROCm#21 0x000003ff6e9652ea in pybind11::cpp_function::dispatcher (self=<PyCapsule at remote 0x3ff83e27720>, args_in=(<torch._C.LiteScriptModule at remote 0x3ff811844b0>, (<Tensor at remote 0x3ff814efb00>,)), kwargs_in=0x0) at /home/user/pytorch/cmake/../third_party/pybind11/include/pybind11/pybind11.h:929 ``` Deallocation: ``` #0 operator delete (ptr=0x60d0005a5740) at /var/tmp/portage/sys-devel/gcc-11.3.1_p20230303/work/gcc-11-20230303/libsanitizer/asan/asan_new_delete.cpp:160 #1 0x000003ff44904fdc in __gnu_cxx::new_allocator<std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2> >::deallocate (this=0x3ffc5dc8020, __p=0x60d0005a5740, __t=1) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/ext/new_allocator.h:145 #2 0x000003ff44904fa8 in std::allocator_traits<std::allocator<std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2> > >::deallocate ( __a=..., __p=0x60d0005a5740, __n=1) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/alloc_traits.h:496 ROCm#3 0x000003ff449041f2 in std::__allocated_ptr<std::allocator<std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2> > >::~__allocated_ptr ( this=0x3ffc5dc8030) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/allocated_ptr.h:74 ROCm#4 0x000003ff44904888 in std::_Sp_counted_ptr_inplace<c10::FunctionSchema, std::allocator<c10::FunctionSchema>, (__gnu_cxx::_Lock_policy)2>::_M_destroy (this=0x60d0005a5740) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:538 ROCm#5 0x000003ff43895a62 in std::_Sp_counted_base<(__gnu_cxx::_Lock_policy)2>::_M_release (this=0x60d0005a5740) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:184 ROCm#6 0x000003ff43895420 in std::__shared_count<(__gnu_cxx::_Lock_policy)2>::~__shared_count (this=0x611000c40648) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:705 ROCm#7 0x000003ff4466e7f4 in std::__shared_ptr<c10::FunctionSchema, (__gnu_cxx::_Lock_policy)2>::~__shared_ptr (this=0x611000c40640) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:1154 ROCm#8 0x000003ff4466d820 in std::shared_ptr<c10::FunctionSchema>::~shared_ptr (this=0x611000c40640) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr.h:122 ROCm#9 0x000003ff448d82f6 in c10::TupleType::~TupleType (this=0x611000c40580) at /home/user/pytorch/aten/src/ATen/core/jit_type.h:1142 ROCm#10 0x000003ff448d8346 in c10::TupleType::~TupleType (this=0x611000c40580) at /home/user/pytorch/aten/src/ATen/core/jit_type.h:1142 ROCm#11 0x000003ff731296a4 in std::_Sp_counted_ptr<c10::TupleType*, (__gnu_cxx::_Lock_policy)2>::_M_dispose (this=0x603000c43ae0) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:348 ROCm#12 0x000003ff71eaf666 in std::_Sp_counted_base<(__gnu_cxx::_Lock_policy)2>::_M_release (this=0x603000c43ae0) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:168 ROCm#13 0x000003ff71eaf330 in std::__shared_count<(__gnu_cxx::_Lock_policy)2>::~__shared_count (this=0x3ffc5dc9368) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:705 ROCm#14 0x000003ff73129ee4 in std::__shared_ptr<c10::TupleType, (__gnu_cxx::_Lock_policy)2>::~__shared_ptr (this=0x3ffc5dc9360) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr_base.h:1154 ROCm#15 0x000003ff73122390 in std::shared_ptr<c10::TupleType>::~shared_ptr (this=0x3ffc5dc9360) at /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/shared_ptr.h:122 ROCm#16 0x000003ff73d00788 in torch::jit::toPyObject (ivalue=...) at /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:613 ROCm#17 0x000003ff73d00306 in torch::jit::toPyObject (ivalue=...) at /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:604 ``` </details> Pull Request resolved: pytorch#101400 Approved by: https://github.com/zou3519

3 disabled functions are attempting out of bounds reads. Disable them until sleef library is fixed. <details> <summary>ASAN report</summary> ``` ================================================================= ==2030580==ERROR: AddressSanitizer: global-buffer-overflow on address 0x03ff70f54570 at pc 0x03ff6704e960 bp 0x03ffce128940 sp 0x03ffce128930 READ of size 4 at 0x03ff70f54570 thread T0 #0 0x3ff6704e95f in vgather_vf_p_vi2 /home/user/pytorch/third_party/sleef/src/arch/helpers390x_128.h:129 ROCm#1 0x3ff6704e95f in rempif /home/user/pytorch/third_party/sleef/src/libm/sleefsimdsp.c:550 ROCm#2 0x3ff6704e95f in Sleef_cosf4_u10vxe2 /home/user/pytorch/third_party/sleef/src/libm/sleefsimdsp.c:1021 ROCm#3 0x3ff67029cfb in Sleef_cosf4_u10 /home/user/pytorch/build/sleef/src/libm/disps390x_128.c:182 ROCm#4 0x3ff55d21941 in at::vec::ZVECTOR::Vectorized<float, void> at::vec::ZVECTOR::Vectorized<float, void>::mapSleef<float __vector(4) const (*)(float __vector(4)), double __vector(2) const (*)(double __ vector(2)), float, 0>(float __vector(4) const (*)(float __vector(4)), double __vector(2) const (*)(double __vector(2))) const /home/user/pytorch/aten/src/ATen/cpu/vec/vec256/zarch/vec256_zarch.h:991 ROCm#5 0x3ff5689ad01 in at::vec::ZVECTOR::Vectorized<float, void>::cos() const /home/user/pytorch/aten/src/ATen/cpu/vec/vec256/zarch/vec256_zarch.h:1074 ROCm#6 0x3ff5685df97 in at::vml::ZVECTOR::vcos<float>(float*, float const*, long)::{lambda(at::vec::ZVECTOR::Vectorized<float, void>)ROCm#1}::operator()(at::vec::ZVECTOR::Vectorized<float, void>) const /home/ user/pytorch/aten/src/ATen/cpu/vml.h:71 ROCm#7 0x3ff5689b691 in void at::vec::map<float, at::vml::ZVECTOR::vcos<float>(float*, float const*, long)::{lambda(at::vec::ZVECTOR::Vectorized<float, void>)ROCm#1}, 0>(at::vml::ZVECTOR::vcos<float>(float*, float const*, long)::{lambda(at::vec::ZVECTOR::Vectorized<float, void>)ROCm#1} const&, float*, float const*, long) /home/user/pytorch/aten/src/ATen/cpu/vec/functional_base.h:239 ROCm#8 0x3ff5685e0df in void at::vml::ZVECTOR::vcos<float>(float*, float const*, long) /home/user/pytorch/aten/src/ATen/cpu/vml.h:71 ROCm#9 0x3ff563fdde3 in operator() /home/user/pytorch/aten/src/ATen/native/cpu/UnaryOpsKernel.cpp:770 ROCm#10 0x3ff5648e4a3 in operator() /home/user/pytorch/aten/src/ATen/TensorIterator.h:406 ROCm#11 0x3ff5663cae1 in callback_fn<at::TensorIteratorBase::loop_2d_from_1d<at::native::ZVECTOR::cos_kernel(at::TensorIteratorBase&)::<lambda()>::<lambda()>::<lambda(char**, const int64_t*, int64_t)> >(c onst at::native::ZVECTOR::cos_kernel(at::TensorIteratorBase&)::<lambda()>::<lambda()>::<lambda(char**, const int64_t*, int64_t)>&)::<lambda(char**, const int64_t*, int64_t, int64_t)> > /home/user/pytorch/ c10/util/FunctionRef.h:43 ROCm#12 0x3ff4d45a933 in c10::function_ref<void (char**, long const*, long, long)>::operator()(char**, long const*, long, long) const /home/user/pytorch/c10/util/FunctionRef.h:64 ROCm#13 0x3ff4d455133 in at::internal::serial_for_each(c10::ArrayRef<long>, c10::ArrayRef<long>, char**, unsigned long, c10::function_ref<void (char**, long const*, long, long)>, at::Range) /home/user/pyt orch/aten/src/ATen/TensorIteratorInternal.h:52 ROCm#14 0x3ff4d43b703 in at::TensorIteratorBase::serial_for_each(c10::function_ref<void (char**, long const*, long, long)>, at::Range) const /home/user/pytorch/aten/src/ATen/TensorIterator.cpp:777 ROCm#15 0x3ff4d43ab59 in at::TensorIteratorBase::for_each(c10::function_ref<void (char**, long const*, long, long)>, long) /home/user/pytorch/aten/src/ATen/TensorIterator.cpp:749 ROCm#16 0x3ff5648e851 in for_each<at::native::ZVECTOR::cos_kernel(at::TensorIteratorBase&)::<lambda()>::<lambda()>::<lambda(char**, const int64_t*, int64_t)> > /home/user/pytorch/aten/src/ATen/TensorItera tor.h:421 ROCm#17 0x3ff563fe5f9 in operator() /home/user/pytorch/aten/src/ATen/native/cpu/UnaryOpsKernel.cpp:770 ROCm#18 0x3ff56400915 in operator() /home/user/pytorch/aten/src/ATen/native/cpu/UnaryOpsKernel.cpp:770 ROCm#19 0x3ff56400f1d in at::native::ZVECTOR::cos_kernel(at::TensorIteratorBase&) /home/user/pytorch/aten/src/ATen/native/cpu/UnaryOpsKernel.cpp:770 ROCm#20 0x3ff4f303007 in void at::native::DispatchStub<void (*)(at::TensorIteratorBase&), at::native::cos_stub>::operator()<at::native::structured_cos_out&>(c10::DeviceType, at::native::structured_cos_out &) /home/user/pytorch/aten/src/ATen/native/DispatchStub.h:158 ROCm#21 0x3ff4f2edb3f in at::native::structured_cos_out::impl(at::Tensor const&, at::Tensor const&) /home/user/pytorch/aten/src/ATen/native/UnaryOps.cpp:330 ROCm#22 0x3ff526ef739 in wrapper_CPU_cos /home/user/pytorch/build/aten/src/ATen/RegisterCPU.cpp:4307 ROCm#23 0x3ff52c651d9 in operator() /home/user/pytorch/aten/src/ATen/core/boxing/impl/WrapFunctionIntoFunctor.h:13 ROCm#24 0x3ff52c651d9 in call /home/user/pytorch/aten/src/ATen/core/boxing/impl/make_boxed_from_unboxed_functor.h:463 ROCm#25 0x3ff5076df2f in at::Tensor c10::callUnboxedKernelFunction<at::Tensor, at::Tensor const&>(void*, c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&) /home/user/pytorch/aten/src/ATen/core /boxing/KernelFunction_impl.h:50 ROCm#26 0x3ff5009a93f in at::Tensor c10::KernelFunction::call<at::Tensor, at::Tensor const&>(c10::OperatorHandle const&, c10::DispatchKeySet, at::Tensor const&) const /home/user/pytorch/aten/src/ATen/core /boxing/KernelFunction_impl.h:103 ROCm#27 0x3ff5009a93f in at::Tensor c10::Dispatcher::call<at::Tensor, at::Tensor const&>(c10::TypedOperatorHandle<at::Tensor (at::Tensor const&)> const&, at::Tensor const&) const /home/user/pytorch/aten/s rc/ATen/core/dispatch/Dispatcher.h:639 ROCm#28 0x3ff5009a93f in c10::TypedOperatorHandle<at::Tensor (at::Tensor const&)>::call(at::Tensor const&) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:487 ROCm#29 0x3ff5009a93f in at::_ops::cos::call(at::Tensor const&) /home/user/pytorch/build/aten/src/ATen/Operators_0.cpp:2215 ROCm#30 0x3ff7d813741 in at::Tensor::cos() const /home/user/pytorch/build/aten/src/ATen/core/TensorBody.h:2107 ROCm#31 0x3ff7dc0f2b7 in operator() /home/user/pytorch/torch/csrc/autograd/generated/python_torch_functions_2.cpp:2953 ROCm#32 0x3ff7dc0faf7 in THPVariable_cos /home/user/pytorch/torch/csrc/autograd/generated/python_torch_functions_2.cpp:2955 ROCm#33 0x3ffa5ef5ae1 in cfunction_call Objects/methodobject.c:543 ROCm#34 0x3ffa5e843f3 in _PyObject_Call Objects/call.c:305 ROCm#35 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#36 0x3ffa5feb50d in do_call_core Python/ceval.c:5915 ROCm#37 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#38 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#39 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#40 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#41 0x3ffa5e841fb in PyVectorcall_Call Objects/call.c:255 ROCm#42 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290 ROCm#43 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#44 0x3ff7f87a393 in torch::impl::dispatch::PythonKernelHolder::operator()(c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) /home/user/pytorch/ torch/csrc/utils/python_dispatch.cpp:175 ROCm#45 0x3ff7f8871a7 in c10::BoxedKernel::makeFromFunctor<torch::impl::dispatch::PythonKernelHolder>(std::unique_ptr<torch::impl::dispatch::PythonKernelHolder, std::default_delete<torch::impl::dispatch:: PythonKernelHolder> >)::{lambda(c10::OperatorKernel*, c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*)ROCm#1}::operator()(c10::OperatorKernel*, c10::Op eratorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/core/boxing/BoxedKernel_impl.h:87 ROCm#46 0x3ff7f887261 in c10::BoxedKernel::makeFromFunctor<torch::impl::dispatch::PythonKernelHolder>(std::unique_ptr<torch::impl::dispatch::PythonKernelHolder, std::default_delete<torch::impl::dispatch:: PythonKernelHolder> >)::{lambda(c10::OperatorKernel*, c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*)ROCm#1}::_FUN(c10::OperatorKernel*, c10::Operator Handle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) /home/user/pytorch/aten/src/ATen/core/boxing/BoxedKernel_impl.h:86 ROCm#47 0x3ff7e0d10ab in c10::BoxedKernel::callBoxed(c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/core/b oxing/BoxedKernel_impl.h:41 ROCm#48 0x3ff7e0d1459 in c10::KernelFunction::callBoxed(c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/cor e/boxing/KernelFunction_impl.h:43 ROCm#49 0x3ff7f876421 in c10::Dispatcher::callBoxed(c10::OperatorHandle const&, std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:6 91 ROCm#50 0x3ff4d22bcdd in c10::OperatorHandle::callBoxed(std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:417 ROCm#51 0x3ff65a092d5 in c10::OperatorHandle::callBoxed(std::vector<c10::IValue, std::allocator<c10::IValue> >&) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:421 ROCm#52 0x3ff65a05641 in operator() /home/user/pytorch/torch/csrc/jit/runtime/register_c10_ops.cpp:15 ROCm#53 0x3ff65a08cb5 in __invoke_impl<void, torch::jit::(anonymous namespace)::createOperatorFromC10(const c10::OperatorHandle&)::<lambda(torch::jit::Stack&)>&, std::vector<c10::IValue, std::allocator<c1 0::IValue> >&> /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/invoke.h:61 ROCm#54 0x3ff65a0897b in __invoke_r<void, torch::jit::(anonymous namespace)::createOperatorFromC10(const c10::OperatorHandle&)::<lambda(torch::jit::Stack&)>&, std::vector<c10::IValue, std::allocator<c10:: IValue> >&> /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/invoke.h:111 ROCm#55 0x3ff65a084e1 in _M_invoke /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/std_function.h:290 ROCm#56 0x3ff7eb2cb21 in std::function<void (std::vector<c10::IValue, std::allocator<c10::IValue> >&)>::operator()(std::vector<c10::IValue, std::allocator<c10::IValue> >&) const /usr/lib/gcc/s390x-ibm-lin ux-gnu/11/include/g++-v11/bits/std_function.h:590 ROCm#57 0x3ff7eb1b659 in torch::jit::Operation::operator()(std::vector<c10::IValue, std::allocator<c10::IValue> >&) /home/user/pytorch/aten/src/ATen/core/stack.h:41 ROCm#58 0x3ff7eb08449 in torch::jit::invokeOperatorFromPython(std::vector<std::shared_ptr<torch::jit::Operator>, std::allocator<std::shared_ptr<torch::jit::Operator> > > const&, pybind11::args, pybind11:: kwargs const&, c10::optional<c10::DispatchKey>) /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:764 ROCm#59 0x3ff7eb09d85 in torch::jit::_get_operation_for_overload_or_packet(std::vector<std::shared_ptr<torch::jit::Operator>, std::allocator<std::shared_ptr<torch::jit::Operator> > > const&, c10::Symbol, pybind11::args, pybind11::kwargs const&, bool, c10::optional<c10::DispatchKey>) /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:829 ROCm#60 0x3ff7e573eb9 in operator() /home/user/pytorch/torch/csrc/jit/python/init.cpp:1549 ROCm#61 0x3ff7e6728dd in call_impl<pybind11::object, torch::jit::initJITBindings(PyObject*)::<lambda(const string&, const string&)>::<lambda(pybind11::args, pybind11::kwargs)>&, 0, 1, pybind11::detail::vo id_type> /home/user/pytorch/third_party/pybind11/include/pybind11/cast.h:1439 ROCm#62 0x3ff7e64312f in call<pybind11::object, pybind11::detail::void_type, torch::jit::initJITBindings(PyObject*)::<lambda(const string&, const string&)>::<lambda(pybind11::args, pybind11::kwargs)>&> /h ome/user/pytorch/third_party/pybind11/include/pybind11/cast.h:1408 ROCm#63 0x3ff7e5da259 in operator() /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:249 ROCm#64 0x3ff7e5da441 in _FUN /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:224 ROCm#65 0x3ff7d317a1f in pybind11::cpp_function::dispatcher(_object*, _object*, _object*) /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:929 ROCm#66 0x3ffa5ef5ae1 in cfunction_call Objects/methodobject.c:543 ROCm#67 0x3ffa5e843f3 in _PyObject_Call Objects/call.c:305 ROCm#68 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#69 0x3ffa5feb50d in do_call_core Python/ceval.c:5915 ROCm#70 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#71 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#72 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#73 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#74 0x3ffa5e83d1f in _PyObject_FastCallDictTstate Objects/call.c:142 ROCm#75 0x3ffa5e84937 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#76 0x3ffa5f2f577 in slot_tp_call Objects/typeobject.c:7494 ROCm#77 0x3ffa5e843f3 in _PyObject_Call Objects/call.c:305 ROCm#78 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#79 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943 ROCm#80 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#81 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#82 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#83 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#84 0x3ffa5fd76a3 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#85 0x3ffa5fd772f in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#86 0x3ffa5feb289 in call_function Python/ceval.c:5891 ROCm#87 0x3ffa5fe5c3b in _PyEval_EvalFrameDefault Python/ceval.c:4213 ROCm#88 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#89 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#90 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#91 0x3ffa5e841fb in PyVectorcall_Call Objects/call.c:255 ROCm#92 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290 ROCm#93 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#94 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943 ROCm#95 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#96 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#97 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#98 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#99 0x3ffa5e841fb in PyVectorcall_Call Objects/call.c:255 ROCm#100 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290 ROCm#101 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#102 0x3ff7f87a393 in torch::impl::dispatch::PythonKernelHolder::operator()(c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) /home/user/pytorch /torch/csrc/utils/python_dispatch.cpp:175 ROCm#103 0x3ff7f8871a7 in c10::BoxedKernel::makeFromFunctor<torch::impl::dispatch::PythonKernelHolder>(std::unique_ptr<torch::impl::dispatch::PythonKernelHolder, std::default_delete<torch::impl::dispatch: :PythonKernelHolder> >)::{lambda(c10::OperatorKernel*, c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*)ROCm#1}::operator()(c10::OperatorKernel*, c10::O peratorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/core/boxing/BoxedKernel_impl.h:87 ROCm#104 0x3ff7f887261 in c10::BoxedKernel::makeFromFunctor<torch::impl::dispatch::PythonKernelHolder>(std::unique_ptr<torch::impl::dispatch::PythonKernelHolder, std::default_delete<torch::impl::dispatch: :PythonKernelHolder> >)::{lambda(c10::OperatorKernel*, c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*)ROCm#1}::_FUN(c10::OperatorKernel*, c10::Operato rHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) /home/user/pytorch/aten/src/ATen/core/boxing/BoxedKernel_impl.h:86 ROCm#105 0x3ff7e0d10ab in c10::BoxedKernel::callBoxed(c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/core/ boxing/BoxedKernel_impl.h:41 ROCm#106 0x3ff7e0d1459 in c10::KernelFunction::callBoxed(c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/co re/boxing/KernelFunction_impl.h:43 ROCm#107 0x3ff7f876421 in c10::Dispatcher::callBoxed(c10::OperatorHandle const&, std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h: 691 ROCm#108 0x3ff4d22bcdd in c10::OperatorHandle::callBoxed(std::vector<c10::IValue, std::allocator<c10::IValue> >*) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:417 ROCm#109 0x3ff65a092d5 in c10::OperatorHandle::callBoxed(std::vector<c10::IValue, std::allocator<c10::IValue> >&) const /home/user/pytorch/aten/src/ATen/core/dispatch/Dispatcher.h:421 ROCm#110 0x3ff65a05641 in operator() /home/user/pytorch/torch/csrc/jit/runtime/register_c10_ops.cpp:15 ROCm#111 0x3ff65a08cb5 in __invoke_impl<void, torch::jit::(anonymous namespace)::createOperatorFromC10(const c10::OperatorHandle&)::<lambda(torch::jit::Stack&)>&, std::vector<c10::IValue, std::allocator<c 10::IValue> >&> /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/invoke.h:61 ROCm#112 0x3ff65a0897b in __invoke_r<void, torch::jit::(anonymous namespace)::createOperatorFromC10(const c10::OperatorHandle&)::<lambda(torch::jit::Stack&)>&, std::vector<c10::IValue, std::allocator<c10: :IValue> >&> /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/invoke.h:111 ROCm#113 0x3ff65a084e1 in _M_invoke /usr/lib/gcc/s390x-ibm-linux-gnu/11/include/g++-v11/bits/std_function.h:290 ROCm#114 0x3ff7eb2cb21 in std::function<void (std::vector<c10::IValue, std::allocator<c10::IValue> >&)>::operator()(std::vector<c10::IValue, std::allocator<c10::IValue> >&) const /usr/lib/gcc/s390x-ibm-li nux-gnu/11/include/g++-v11/bits/std_function.h:590 ROCm#115 0x3ff7eb1b659 in torch::jit::Operation::operator()(std::vector<c10::IValue, std::allocator<c10::IValue> >&) /home/user/pytorch/aten/src/ATen/core/stack.h:41 ROCm#116 0x3ff7eb08449 in torch::jit::invokeOperatorFromPython(std::vector<std::shared_ptr<torch::jit::Operator>, std::allocator<std::shared_ptr<torch::jit::Operator> > > const&, pybind11::args, pybind11: :kwargs const&, c10::optional<c10::DispatchKey>) /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:764 ROCm#117 0x3ff7eb09d85 in torch::jit::_get_operation_for_overload_or_packet(std::vector<std::shared_ptr<torch::jit::Operator>, std::allocator<std::shared_ptr<torch::jit::Operator> > > const&, c10::Symbol, pybind11::args, pybind11::kwargs const&, bool, c10::optional<c10::DispatchKey>) /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:829 ROCm#118 0x3ff7e573eb9 in operator() /home/user/pytorch/torch/csrc/jit/python/init.cpp:1549 ROCm#119 0x3ff7e6728dd in call_impl<pybind11::object, torch::jit::initJITBindings(PyObject*)::<lambda(const string&, const string&)>::<lambda(pybind11::args, pybind11::kwargs)>&, 0, 1, pybind11::detail::v oid_type> /home/user/pytorch/third_party/pybind11/include/pybind11/cast.h:1439 ROCm#120 0x3ff7e64312f in call<pybind11::object, pybind11::detail::void_type, torch::jit::initJITBindings(PyObject*)::<lambda(const string&, const string&)>::<lambda(pybind11::args, pybind11::kwargs)>&> / home/user/pytorch/third_party/pybind11/include/pybind11/cast.h:1408 ROCm#121 0x3ff7e5da259 in operator() /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:249 ROCm#122 0x3ff7e5da441 in _FUN /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:224 ROCm#123 0x3ff7d317a1f in pybind11::cpp_function::dispatcher(_object*, _object*, _object*) /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:929 ROCm#124 0x3ffa5ef5ae1 in cfunction_call Objects/methodobject.c:543 ROCm#125 0x3ffa5e843f3 in _PyObject_Call Objects/call.c:305 ROCm#126 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#127 0x3ffa5feb50d in do_call_core Python/ceval.c:5915 ROCm#128 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#129 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#130 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#131 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#132 0x3ffa5e83d1f in _PyObject_FastCallDictTstate Objects/call.c:142 ROCm#133 0x3ffa5e84937 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#134 0x3ffa5f2f577 in slot_tp_call Objects/typeobject.c:7494 ROCm#135 0x3ffa5e843f3 in _PyObject_Call Objects/call.c:305 ROCm#136 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#137 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943 ROCm#138 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#139 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#140 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#141 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#142 0x3ffa5e87d2b in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#143 0x3ffa5e882dd in method_vectorcall Objects/classobject.c:83 ROCm#144 0x3ffa5e836d3 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#145 0x3ffa5e84b6f in _PyObject_CallFunctionVa Objects/call.c:485 ROCm#146 0x3ffa5e84f2d in callmethod Objects/call.c:557 ROCm#147 0x3ffa5e85039 in PyObject_CallMethod Objects/call.c:577 ROCm#148 0x3ff7f7efa05 in torch::handle_torch_function_no_python_arg_parser(c10::ArrayRef<pybind11::handle>, _object*, _object*, char const*, _object*, char const*, torch::TorchFunctionName) /home/user/py torch/torch/csrc/utils/python_arg_parser.cpp:338 ROCm#149 0x3ff7eb09b67 in torch::jit::_get_operation_for_overload_or_packet(std::vector<std::shared_ptr<torch::jit::Operator>, std::allocator<std::shared_ptr<torch::jit::Operator> > > const&, c10::Symbol, pybind11::args, pybind11::kwargs const&, bool, c10::optional<c10::DispatchKey>) /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:827 ROCm#150 0x3ff7e573eb9 in operator() /home/user/pytorch/torch/csrc/jit/python/init.cpp:1549 ROCm#151 0x3ff7e6728dd in call_impl<pybind11::object, torch::jit::initJITBindings(PyObject*)::<lambda(const string&, const string&)>::<lambda(pybind11::args, pybind11::kwargs)>&, 0, 1, pybind11::detail::v oid_type> /home/user/pytorch/third_party/pybind11/include/pybind11/cast.h:1439 ROCm#152 0x3ff7e64312f in call<pybind11::object, pybind11::detail::void_type, torch::jit::initJITBindings(PyObject*)::<lambda(const string&, const string&)>::<lambda(pybind11::args, pybind11::kwargs)>&> / home/user/pytorch/third_party/pybind11/include/pybind11/cast.h:1408 ROCm#153 0x3ff7e5da259 in operator() /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:249 ROCm#154 0x3ff7e5da441 in _FUN /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:224 ROCm#155 0x3ff7d317a1f in pybind11::cpp_function::dispatcher(_object*, _object*, _object*) /home/user/pytorch/third_party/pybind11/include/pybind11/pybind11.h:929 ROCm#156 0x3ffa5ef5ae1 in cfunction_call Objects/methodobject.c:543 ROCm#157 0x3ffa5e843f3 in _PyObject_Call Objects/call.c:305 ROCm#158 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#159 0x3ffa5feb50d in do_call_core Python/ceval.c:5915 ROCm#160 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#161 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#162 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#163 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#164 0x3ffa5e83d1f in _PyObject_FastCallDictTstate Objects/call.c:142 ROCm#165 0x3ffa5e84937 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#166 0x3ffa5f2f577 in slot_tp_call Objects/typeobject.c:7494 ROCm#167 0x3ffa5e84027 in _PyObject_MakeTpCall Objects/call.c:215 ROCm#168 0x3ffa5fd767b in _PyObject_VectorcallTstate Include/cpython/abstract.h:112 ROCm#169 0x3ffa5fd772f in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#170 0x3ffa5feb289 in call_function Python/ceval.c:5891 ROCm#171 0x3ffa5fe5ad1 in _PyEval_EvalFrameDefault Python/ceval.c:4181 ROCm#172 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#173 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#174 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#175 0x3ffa5fd76a3 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#176 0x3ffa5fd772f in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#177 0x3ffa5feb289 in call_function Python/ceval.c:5891 ROCm#178 0x3ffa5fe5c3b in _PyEval_EvalFrameDefault Python/ceval.c:4213 ROCm#179 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#180 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#181 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#182 0x3ffa5e8427f in PyVectorcall_Call Objects/call.c:267 ROCm#183 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290 ROCm#184 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#185 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943 ROCm#186 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#187 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#188 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#189 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#190 0x3ffa5e841fb in PyVectorcall_Call Objects/call.c:255 ROCm#191 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290 ROCm#192 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#193 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943 ROCm#194 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#195 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#196 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#197 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#198 0x3ffa5e841fb in PyVectorcall_Call Objects/call.c:255 ROCm#199 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290 ROCm#200 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#201 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943 ROCm#202 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#203 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#204 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#205 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#206 0x3ffa5e841fb in PyVectorcall_Call Objects/call.c:255 ROCm#207 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290 ROCm#208 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#209 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943 ROCm#210 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#211 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#212 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#213 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#214 0x3ffa5e83d1f in _PyObject_FastCallDictTstate Objects/call.c:142 ROCm#215 0x3ffa5e84937 in _PyObject_Call_Prepend Objects/call.c:431 ROCm#216 0x3ffa5f2f577 in slot_tp_call Objects/typeobject.c:7494 ROCm#217 0x3ffa5e843f3 in _PyObject_Call Objects/call.c:305 ROCm#218 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#219 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943 ROCm#220 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#221 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#222 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#223 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#224 0x3ffa5fd76a3 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 ROCm#225 0x3ffa5fd772f in PyObject_Vectorcall Include/cpython/abstract.h:123 ROCm#226 0x3ffa5feb289 in call_function Python/ceval.c:5891 ROCm#227 0x3ffa5fe5b21 in _PyEval_EvalFrameDefault Python/ceval.c:4198 ROCm#228 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#229 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#230 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#231 0x3ffa5e8427f in PyVectorcall_Call Objects/call.c:267 ROCm#232 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290 ROCm#233 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#234 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943 ROCm#235 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#236 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#237 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#238 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#239 0x3ffa5e8427f in PyVectorcall_Call Objects/call.c:267 ROCm#240 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290 ROCm#241 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#242 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943 ROCm#243 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#244 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#245 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#246 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#247 0x3ffa5e8427f in PyVectorcall_Call Objects/call.c:267 ROCm#248 0x3ffa5e84347 in _PyObject_Call Objects/call.c:290 ROCm#249 0x3ffa5e84483 in PyObject_Call Objects/call.c:317 ROCm#250 0x3ffa5feb7cf in do_call_core Python/ceval.c:5943 ROCm#251 0x3ffa5fe6019 in _PyEval_EvalFrameDefault Python/ceval.c:4277 ROCm#252 0x3ffa5fd7aed in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 ROCm#253 0x3ffa5fe8ba9 in _PyEval_Vector Python/ceval.c:5065 ROCm#254 0x3ffa5e8459b in _PyFunction_Vectorcall Objects/call.c:342 ROCm#255 0x3ffa5e8427f in PyVectorcall_Call Objects/call.c:267 0x03ff70f54570 is located 0 bytes to the right of global variable 'Sleef_rempitabsp' defined in '/home/user/pytorch/third_party/sleef/src/libm/rempitab.c:986:34' (0x3ff70f53f00) of size 1648 SUMMARY: AddressSanitizer: global-buffer-overflow /home/user/pytorch/third_party/sleef/src/arch/helpers390x_128.h:129 in vgather_vf_p_vi2 Shadow bytes around the buggy address: 0x10007fee1ea850: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 0x10007fee1ea860: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 0x10007fee1ea870: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 0x10007fee1ea880: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 0x10007fee1ea890: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 =>0x10007fee1ea8a0: 00 00 00 00 00 00 00 00 00 00 00 00 00 00[f9]f9 0x10007fee1ea8b0: f9 f9 f9 f9 00 00 00 00 00 00 00 00 00 00 00 00 0x10007fee1ea8c0: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 0x10007fee1ea8d0: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 0x10007fee1ea8e0: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 0x10007fee1ea8f0: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 Shadow byte legend (one shadow byte represents 8 application bytes): Addressable: 00 Partially addressable: 01 02 03 04 05 06 07 Heap left redzone: fa Freed heap region: fd Stack left redzone: f1 Stack mid redzone: f2 Stack right redzone: f3 Stack after return: f5 Stack use after scope: f8 Global redzone: f9 Global init order: f6 Poisoned by user: f7 Container overflow: fc Array cookie: ac Intra object redzone: bb ASan internal: fe Left alloca redzone: ca Right alloca redzone: cb Shadow gap: cc ==2030580==ABORTING ``` </details> It reproduces when running `pytest -v test/test_ops.py -k test_python_ref__refs_cos_cpu_bfloat16` under address sanitizer on s390x. See also: shibatch/sleef#464 Pull Request resolved: pytorch#102266 Approved by: https://github.com/malfet

The changes made in github editor didn't go in when doing ghstack land.

Commit Messages: - update the param_id calculation so that it works on both CPX and SPX modes (#271) (#272) - reset parameters for FusedDenseGeluDense similar to FusedDense to make the test_gelu pass (#269) (#270) Co-authored-by: Sriram Kumar <[email protected]> - Fix build error (#263) - Fix warp size (#256) * replace c10_warp_size in fused rope * replace c10_warp_size in fused softmax * replace c10_warp_size in group batch norm * replace c10_warp_size in multiheadattention * replace c10_warp_size in tramsducer * replace c10_warp_size in xentropy * replace c10_warp_size in sync batch normalization * replace c10_warp_size in group batch norm * replace warp_size in multihead attention - Disabling Aiter Installation in default build (#254) * made a flag to switch on/off aiter compile using --aiter when installing apex * Added information on building AITER during installation in readme - Replaced warpsize with C10_WARP_SIZE (#249) - correct the approach to get to the apex folder from the test file (#248) - Apex extensions import test (#245) * add test to extract extensions from setup.py and test if there can be imported * moved test outside tests/L0 - Fixing the C10_warpsize issue. replacing the macros with at::cuda::warp_size() (#237) - Replacing c10_warp_size with platform based warp_size values (#228) fixes :https://ontrack-internal.amd.com/browse/SWDEV-541725 - [master] Added AITER as a submodule and use in fused_rope.py (#222) * Added aiter support in fused_rope.py for all 4 variants. Updated fused rope test, reduced tolerances according to unit test in aiter repo. * Add aiter as a submodule and install it if it is rocm. Switch on aiter backend if it is rocm and aiter is installed * add pandas to the requirements so that aiter can be used without numpy error - ValueError: numpy.dtype size changed, may indicate binary incompatibility. Expected 96 from C header, got 88 from PyObject * Replace ROCM_HOME condition to IS_ROCM_PYTORCH for installing aiter and use pip install -e . instead of python setup.py develop for installing aiter. * Create apex and aiter subclasses for the four variants of FusedRoPEFunc and select apex or aiter subclass based on AITER_ROPE_BACKEND value. The user can specify the environment variable USE_ROCM_AITER_ROPE_BACKEND to select between aiter and apex backends for fused rope. * If the AITER backend is selected, use lowered precision in the unit test otherwise use the original precision 1e-3 * warn user about the lower precision when using aiter backend for fused rope * Update fused_rope.py remove spaces * simplify the switch between aiter and apex subclasses * install aiter without editable mode - Merge pull request #227 from ROCm/amd/dev/iassiour/SWDEV-541770 Do not use warpSize as a constexpr in nhwc_batch_norm_kernel.h - Do not use warpSize as a constexpr in nhwc_batch_norm_kernel.h In ROCm 7.0, the warpSize variable is no longer constexpr. This commit replaces the variable use with the correct values based on the architecture we're running on. - change epilogue parameter for hipblaslt matmul in cuda kernel for fused dense gelu dense (#223) Fixes : https://ontrack-internal.amd.com/browse/SWDEV-534531 - Reset torch default device to cpu after running the amp unit tests. (#220) - Fix unit tests for transformer, fused dense, mlp (#218) * Fix fused_dense_gelu_dense, change the names of the parameters so that they can be accessed by the test appropriately * Update the absolute tolerances in test_mlp from 0 and 1e-7 to 1e-5 * Deactivate the amp state handle for optimization level other than O0. This helps to pass the UT after this. * Update condition for deactivating amp state handle from opt level equal to 1 to opt level not equal to 0 * Update torch set default dtype method to remove warning * Update the method to create overflow buffer for amp optimizer * Update the method to create overflow buffer for amp optimizer * Update the method to create overflow buffer for amp optimizer * reset the default device to cpu so that the generator uses cuda, as run_amp tests set its to cuda - Update fused layer norm code from upstream apex repo. The intra-warp reductions code inside cuWelfordMuSigma2() function in layer norm kernel assumes a warp size of 32, so added a condition for rocm to support gpu warp size (based on earlier apex code). For rocm, adjust the threadsize, based on earlier apex code. (#215) - upgrade matplotlib to resolve setuptools_scm error. (#213) The error: File /tmp/easy_install-_pfhn8pn/matplotlib-3.5.1/.eggs/setuptools_scm-8.3.1-py3.12.egg/setuptools_scm/_integration/pyproject_reading.py, line 36, in read_pyproject section = defn.get(tool, {})[tool_name] ~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^ KeyError: 'setuptools_scm' Solution : https://github.com/matplotlib/matplotlib/blob/v3.8.x/pyproject.toml#L22 matplotlib 3.8 is the first version to have pyproject.toml with this tool.setuptools_scm section. This higher version of setuptools expects this structure in the python packages it installs. Matplotlib 3.5.1 doesn't satisfy this condition. The solution is to change the condition to matplotlib>=3.8. - Update distributed fused adam - integrate Pipeline operations and support different grad (#207) * Fix `DistributedFusedAdam` for grad dtype != param dtype (#1893) * Pipeline `reduce-scatter` and `all-reduce`. (#1895) --------- Co-authored-by: Tailing Yuan <[email protected]> Co-authored-by: Wil Kong <[email protected]> - Update the condition for building the NCCL allocator, PyTorch should be greater than or equal to 2.6 (#204) - Update version.txt (#203) change the version from 1.7.0 to 1.8.0 - [ROCm] Use at::empty to manage workspace memory to avoid hip runtime calls (#197) Optimize the memory for fused_weight_gradient_mlp_cuda module - Update README.md (#198) Add release notes for release/1.5, 1.6 and 1.7 - Update README.md (#196) updated the support versions for apex 1.7.0 PRs: - https://github.com/ROCm/apex/pull/1895 Fixes: - https://example.com/issue-271 - https://example.com/issue-249 - https://example.com/issue-254 - https://example.com/issue-228 - https://example.com/issue-263 - https://example.com/issue-223 - https://example.com/issue-237 - https://example.com/issue-203 - https://example.com/issue-256 - https://example.com/issue-245 - https://example.com/issue-272 - https://example.com/issue-204 - https://ontrack-internal.amd.com/browse/SWDEV-540029 - https://example.com/issue-222 - https://example.com/issue-220 - https://example.com/issue-248 - https://example.com/issue-1893 - https://example.com/issue-198 - https://example.com/issue-215 - https://example.com/issue-213 - https://example.com/issue-1895 - https://example.com/issue-218 - https://example.com/issue-227 - https://example.com/issue-196 - https://example.com/issue-197 - https://example.com/issue-207

Elias Ellison and others added 30 commits September 10, 2018 11:37

add export import test to TestJitGenerated (pytorch#10982)

2158f4a

Summary: Checking assertExportImport for all of the generated test jit tests. Pull Request resolved: pytorch#10982 Differential Revision: D9636935 Pulled By: eellison fbshipit-source-id: f3f1ce77d454848098f2ac7e0fa18bf8564890be

Add option to use CUDA memory leak testing as a context manager (pyto…

040d75d

…rch#11380) Summary: cc SsnL Pull Request resolved: pytorch#11380 Reviewed By: ezyang Differential Revision: D9705877 Pulled By: zou3519 fbshipit-source-id: 02470c25236f57fa02f4ac9d7ed63d38a6355db2

Fix katex math rendering (pytorch#11472)

ea0ee77

Summary: I'm 80% sure that this fixes the math bug. But I can't repro locally so I don't know. Pull Request resolved: pytorch#11472 Differential Revision: D9755328 Pulled By: SsnL fbshipit-source-id: 130be664d3c6ceee3c0c166c1a86fc9ec3b79d74

Resolve ambiguity when including both caffe2 and aten registries (pyt…

3e49a69

…orch#11411) Summary: Pull Request resolved: pytorch#11411 Simple fix Reviewed By: goldsborough Differential Revision: D9730371 fbshipit-source-id: f841327c01faa13cfb6b7fc6e279b8fc50fad1db

Document the Embedding module (pytorch#11469)

9cfdf0d

Summary: ebetica soumith ezyang Pull Request resolved: pytorch#11469 Differential Revision: D9757547 Pulled By: goldsborough fbshipit-source-id: a95673abe949bb81d716dbc03c5c3e2a11cc15d3

Document the Functional module (pytorch#11460)

dd8defe

Summary: Document the `Functional` module in the C++ API. ebetica ezyang soumith Pull Request resolved: pytorch#11460 Differential Revision: D9757555 Pulled By: goldsborough fbshipit-source-id: 15f8bf6d60bd26f3f4e69fb8e414e186e3c220ee

Give copy an optional device argument.

f9d12ee

Summary: Pull Request resolved: pytorch#11497 Differential Revision: D9762014 Pulled By: gchanan fbshipit-source-id: 996419cc5e86d000af953d030ff361adafb921ad

Ignore functional doc error

b14a805

Summary: Pull Request resolved: pytorch#11508 Differential Revision: D9764380 Pulled By: goldsborough fbshipit-source-id: 3abb9c04f46137be833ea26d67734741e14f8010

Will Feng and others added 9 commits September 18, 2018 11:26

Revert D9755189: [pytorch][PR] [API CHANGE] Add empty tensor tests to…

47956dd

… test_sparse Differential Revision: D9755189 Original commit changeset: e9d36f437db1 fbshipit-source-id: 8b99edf626418a953a8bd786847a6e0174a3a14d

Add successor/predecessor functions

9eb7288

Summary: More functionality to prep nomnigraph for scheduler implementations Reviewed By: duc0 Differential Revision: D9794686 fbshipit-source-id: b460859d8ff965d0049b2a696bd8d2f5c97f3f86

Don't build Detectron ops with NO_CAFFE2_OPS=1 (pytorch#11799)

8ad846f

Summary: cc apaszke Pull Request resolved: pytorch#11799 Differential Revision: D9922745 Pulled By: orionr fbshipit-source-id: b88724b7c2919aabc00d98658e8e563233e01c85

Polish CPP docs, Minor Python Docs Fixes (pytorch#11722)

e585f2f

Differential Revision: D9919120 Pulled By: goldsborough fbshipit-source-id: bf14cbe4ab79524495957cb749828046af864aab

Simplify Blob move constructor/assignment (pytorch#11402)

53cf628

Summary: Pull Request resolved: pytorch#11402 - Simplify move constructor/assignment - Make more things noexcept Reviewed By: ezyang Differential Revision: D9728631 fbshipit-source-id: 92562e30ea1e4d05ca857665a02b0ca66b0739e3

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

91c9357

New failure on CI.

846a573

Test fails now.

489f783

Skip for now.

70af48f

iotamudelta merged commit eb85125 into ROCm:master Sep 20, 2018

akashveramd pushed a commit that referenced this pull request Jun 13, 2025

[TorchTrain] Minor fix for #197 (#204)

5d2c148

The changes made in github editor didn't go in when doing ghstack land.

Merge from upstream #197

Merge from upstream #197

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