bump up master by jjsjann123 · Pull Request #19 · csarofeen/pytorch

jjsjann123 · 2020-04-17T17:32:37Z

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…pytorch#36222) Summary: Pull Request resolved: pytorch#36222 Reland of pytorch#35706, with fixes to code analyzer. It is extremely common to define implementations of operators at a specific dispatch key, so we add an overload to impl specifically for this case. I then delete most uses of torch::dispatch dispatch_autograd call sites can't make use of this overload. So instead the new preferred way to specify something as autograd is to pass kAutograd as the dispatch key (short form, analogous to kCPU/kCUDA which we support today). I flip flopped about whether or not kAutograd should have the type DispatchKey or some other type (to help better encapsulate the DispatchKey enum); this is more direct and I can't think of any BC problems from this usage. Some other reorganization I did: - I renamed all of the worker functions in op_registration to have a leading underscore and made them private, just to make it more clear what the public versus private API were (the private API shouldn't be used by users because it doesn't come with && overloads) Note that this means I needed to adjust the regex in the code analyzer, because - In a few places where I was touching lines already, I replaced full DispatchKey typed out enums with shorter kFoo names, similar to kAutograd but I didn't publish these globally. - Code analyzer now prints a unified diff, and in the other order (because I tend to think of the diff as reporting how the /new/ result is different) Signed-off-by: Edward Z. Yang <ezyang@fb.com> Test Plan: Imported from OSS Differential Revision: D20929256 Pulled By: ezyang fbshipit-source-id: c69b803d2b3a1a8aff70e14da33d3adec5239f13

…s. (pytorch#36223) Summary: Pull Request resolved: pytorch#36223 Previously pytorch#35714 There are a lot of unboxed only defs. We're committed to removing them at the end of the half but as I am about to do a lot of porting to the new API, let's get them into a form where they're easy to remove. This is a new overload impl_UNBOXED that will pass the function pointer straight to CppFunction::makeUnboxedOnly I don't attempt to make the _UNBOXED API complete; in particular, catchall declarations don't get this sugar (as there are very few of them). To get some coverage of _UNBOXED API for code analysis, I switched one of our unboxed tests to be an impl rather than a def. This shouldn't materially affect coverage. Signed-off-by: Edward Z. Yang <ezyang@fb.com> Test Plan: Imported from OSS Differential Revision: D20929259 Pulled By: ezyang fbshipit-source-id: 72d2061b6c8a6afbcd392b47f53ade18de2f9184

Summary: GitHub commits: facebook/fb303@fe67bb7 facebook/fbthrift@027c164 facebook/folly@8045a2a facebook/litho@0595318 facebook/proxygen@faeba96 facebook/rocksdb@e860f88 facebookincubator/fizz@a8a1113 pytorch/FBGEMM@959cdee Test Plan: n/a Reviewed By: zpao fbshipit-source-id: 652dbf7024ea374506fa5c46440a1ab9d630e28b

Summary: Pull Request resolved: pytorch#36319 On the way to resolving pytorch#35216. This is a fix for just the master branch but once this goes in, I'll send a cherry-pick to release/1.5 The problem is that we were not calling `format` on a string that had templates (e.g., '{input}', '{dim}'). This change makes it so that we call format on the entire docstring for `torch.min`. Test Plan: - The `torch.max` docs are OK: https://pytorch.org/docs/master/torch.html#torch.max and don't need changing. - `torch.min` docs, before this change: see second screenshot in pytorch#35216. - after this change: <Insert link here on github> ![image](https://user-images.githubusercontent.com/5652049/78921702-4e2acc00-7a63-11ea-9ea0-89636ff6fb0a.png) Differential Revision: D20946702 Pulled By: zou3519 fbshipit-source-id: a1a28707e41136a9bb170c8a4191786cf037a0c2

Summary: Pull Request resolved: pytorch#36019 Once the autograd engine is finished with a GraphTask it would call `markCompleted` on the Future. This could trigger callbacks on the Future that could throw exceptions. If one of the callbacks did throw an exception, we would call setErrorIfNeeded, which would be no-op since the Future is already marked as completed. This would effectively mean we would be swallowing exceptions. To avoid this, we do the following: 1) Rethrow the exception in `mark_graph_task_completed`. 2) In `setErrorIfNeeded`, log the error if we are ignoring it. ghstack-source-id: 101607329 Test Plan: Verified appropriate logging. Differential Revision: D20854806 fbshipit-source-id: 76bdf403cfd6d92f730ca1483ad5dba355f83e58

…pytorch#36324) Summary: Pull Request resolved: pytorch#36324 Test Plan: . Imported from OSS Differential Revision: D20948046 fbshipit-source-id: 2dd8f0c6fbe8fd84293420b97592dc586d25def9

Summary: GitHub commits: facebook/fb303@12efe7c facebook/fbthrift@af95859 facebookarchive/fbzmq@07c56b2 facebook/folly@4a29e9c facebook/proxygen@1aaa4f7 facebook/wangle@8326713 facebookincubator/fizz@26862c2 facebookincubator/katran@819d357 facebook/mvfst@9f18c23 pytorch/FBGEMM@81b956b Test Plan: n/a Reviewed By: zpao fbshipit-source-id: 643525fbe02fc99e1258047ae13f0fe3704e3709

…rch#36280) Summary: Pull Request resolved: pytorch#36280 Test Plan: . Imported from OSS Differential Revision: D20948352 fbshipit-source-id: 92188806b9c129458ebb2cdc47599427e3b6e216

…h#35279) Summary: Pull Request resolved: pytorch#35279 Supported benchmarking pytorch jit self-contained models. * By specifying flag `--no_inputs=True`, the binary supports benchmarking self-contained torchscript model (model runs without inputs, `model.forward()`) * This allows moving data preparation part outside of this binary. Reviewed By: kimishpatel Differential Revision: D20585639 fbshipit-source-id: c28e50503534c90023c1430479d26f1c1ce740b1

Summary: Pull Request resolved: pytorch#35370 Test Plan: Imported from OSS Differential Revision: D20641812 Pulled By: z-a-f fbshipit-source-id: 42bb1ed96d6b6e0a5da6e693d02ff616c33d9ef6

Summary: Reviving this PR pytorch#35401 eellison. I believe after the profiled graph executor fix the test failures are handled. Pull Request resolved: pytorch#36243 Differential Revision: D20950623 Pulled By: eellison fbshipit-source-id: 5fbee426d1a098d84d5938540d45ce00828299be

Summary: AnyType wasn't listed as a mutable type, so the assertion triggered (yay!). Also update the `isMutableTypeInternal(from) != isMutableTypeInternal` logic to be more encompassing. Pull Request resolved: pytorch#36178 Differential Revision: D20922356 Pulled By: eellison fbshipit-source-id: 7060a62b18e98dc24b6004a66225c196aadb566e

Summary: Pull Request resolved: pytorch#36354 TestQuantizeScript is splitted to - TestQuantizeScriptJitPasses - TestQuantizeScriptPTSQOps (post training static quantization ops) Test Plan: . Imported from OSS Differential Revision: D20956731 fbshipit-source-id: 860cd24ea3f49450126ce2d872894492bdc822d8

Summary: This PR addresses Issue pytorch#36279. Previously, printing of complex tensors would sometimes yield extra spaces before the elements as shown below: ``` print(torch.tensor([[1 + 1.340j, 3 + 4j], [1.2 + 1.340j, 6.5 + 7j]], dtype=torch.complex64)) ``` would yield ``` tensor([[(1.0000 + 1.3400j), (3.0000 + 4.0000j)], [(1.2000 + 1.3400j), (6.5000 + 7.0000j)]], dtype=torch.complex64) ``` This occurs primarily because when the max width for the element is being assigned, the formatter's max_width is calculated prior to truncating the float values. As a result, ```self.max_width``` would end up being much longer than the final length of the element string to be printed. I address this by adding a boolean variable that checks if a complex tensor contains only ints and change the control flow for calculating ```self.max_width``` accordingly. Here are some sample outputs of both float and complex tensors: ``` tensor([[0., 0.], [0., 0.]], dtype=torch.float64) tensor([[(0.+0.j), (0.+0.j)], [(0.+0.j), (0.+0.j)]], dtype=torch.complex64) tensor([1.2000, 1.3400], dtype=torch.float64) tensor([(1.2000+1.3400j)], dtype=torch.complex64) tensor([[(1.0000+1.3400j), (3.0000+4.0000j)], [(1.2000+1.3400j), (6.5000+7.0000j)]], dtype=torch.complex64) tensor([1.0000, 2.0000, 3.0000, 4.5000]) tensor([(1.+2.j)], dtype=torch.complex64) ``` cc ezyang anjali411 dylanbespalko Pull Request resolved: pytorch#36331 Differential Revision: D20955663 Pulled By: anjali411 fbshipit-source-id: c26a651eb5c9db6fcc315ad8d5c1bd9f4b4708f7

…pytorch#35997) Summary: Pull Request resolved: pytorch#35997 When the number of blocks is large enough, we are already achieving blalanced SM allocation. But we still should keep the number of inputs per thread large, because thread reduce is cheap. Benchmark for Half on V100: https://github.com/zasdfgbnm/things/blob/master/2020Q2/reduction-benchmark.ipynb On large tensor, it is: 1.37ms vs 1.25ms Test Plan: Imported from OSS Differential Revision: D20927533 Pulled By: ngimel fbshipit-source-id: 40df52e439cc1c01cda66c6195b600f301c5e984

…future (pytorch#36014) Summary: Pull Request resolved: pytorch#36014 Benchmark on RTX2080Ti: 2.13ms vs 1.88ms https://github.com/zasdfgbnm/things/blob/master/2020Q2/reduction-benchmark-refactor.ipynb Test Plan: Imported from OSS Differential Revision: D20927535 Pulled By: ngimel fbshipit-source-id: b65b749b58cebe0751e4ec7e1cf359543c401580

Summary: Pull Request resolved: pytorch#36352 Test Plan: Imported from OSS Differential Revision: D20955781 Pulled By: z-a-f fbshipit-source-id: 37fbcf329a6abcd9a367a73ad65ce543ed9ffe47

Summary: GitHub commits: facebook/fbthrift@54dc44b facebook/litho@726a62c facebook/proxygen@9557561 facebook/rocksdb@66a95f0 pytorch/FBGEMM@f1d3330 Test Plan: n/a Reviewed By: zpao fbshipit-source-id: 3585db200a5d84ba01b8cf90a3bd7bf003314345

Summary: Pull Request resolved: pytorch#36093 Unwrap any tuples (including NamedTuples) in the module forward function input list to be arglist. 1. Supports multiple tuple inputs, and traces their use through CallMethods and TupleIndex 2. Does not unwrap inner use of other tuples that did not show up in the original toplevel graph inputs We work from the ScriptModule level instead of the Graph level because: 1. If the ScriptModule was previously called with the original set of inputs, the GraphExecutor caches the ExecutionPlan (specifically, ArgumentSpecCreator is derived from the Graph and type check the inputs passed in) 2. Since we are changing this graph's inputs, we clone the module and clear the GraphExecutor. Since we work from ScriptModule level, we cannot take advantage of jit level syntactic sugar like run_pass(), so I jit exposed this as a cpp extension. Let me know if there are other ideas about this. Test Plan: buck test caffe2/torch/fb/model_transform:signature_translation_test Todo: Verify use in bento Untranslated graph: ``` > graph(%self : __torch__.test_jit.SparseNNWrapper, > %inputs.1 : NamedTuple(dense : Tensor, sparse : Dict(int, Tensor))): > %2 : __torch__.test_jit.SparseNN = prim::GetAttr[name="main_module"](%self) > %4 : Tensor = prim::CallMethod[name="forward"](%2, %inputs.1) # /data/users/ansha/fbsource/fbcode/buck-out/dev/gen/caffe2/test/jit#binary,link-tree/test_jit.py:12141:23 > return (%4) ``` Translated graph: ``` > graph(%self : __torch__.test_jit.___torch_mangle_1.SparseNNWrapper, > %inputs.1_0 : Tensor, > %inputs.1_1 : Dict(int, Tensor)): > %2 : __torch__.test_jit.___torch_mangle_2.SparseNN = prim::GetAttr[name="main_module"](%self) > %3 : Tensor = prim::CallMethod[name="forward"](%2, %inputs.1_0, %inputs.1_1) # /data/users/ansha/fbsource/fbcode/buck-out/dev/gen/caffe2/test/jit#binary,link-tree/test_jit.py:12141:23 > return (%3) ``` Reviewed By: houseroad Differential Revision: D20313673 fbshipit-source-id: fddd07c9537dc8b6f480a14d697bea10ecc74470

Summary: This was left off of pytorch#35741, but the max supported file format change has been landed for several weeks, so this should be fine to land. ](https://our.intern.facebook.com/intern/diff/20875051/) Pull Request resolved: pytorch#36085 Pulled By: driazati Reviewed By: eellison Differential Revision: D20875051 fbshipit-source-id: c3b84c85d791cb6f286a2ed38ca5cd1219b332b2

…6297) Summary: Pull Request resolved: pytorch#36297 Pull Request resolved: pytorch/FBGEMM#343 We moved FakeFP16 back to close source and kept `RoundToFloat16` function in "fbgemm/FbgemmConvert.h". This is because FakeFP16 introduced dependency on MKL in the FBGEMM core. Also it doesn't seem to be needed for open source, as it is not used anywhere. Test Plan: CI Reviewed By: jspark1105 Differential Revision: D20937962 fbshipit-source-id: 9487a9fd2282b6df2f754c22bea36f2255a5c791

Summary: GitHub commits: pytorch/FBGEMM@20b6cf1 Test Plan: n/a Reviewed By: zpao fbshipit-source-id: f5a64d847512d25a138f666d25e03c58277327f0

…36366) Summary: Pull Request resolved: pytorch#36366 fix issues introduced in D20528758 Reviewed By: linbinyu Differential Revision: D20959367 fbshipit-source-id: 920055a6782b9c6729177f7101f2f9eb3e40ebf8

…tive build (pytorch#35426) Summary: Pull Request resolved: pytorch#35426 Use selective build with the full set of operators (vs. manually register each used op with "_" prefix). Lite interpreter relies on JIT operator dispatch. In future we still need JIT operator dispatch dispatch ops that are not registered in c10. Currently the selective build is for c10/aten dispatch in BUCK. There is JIT selective code-gen in OSS but not ported to BUCK yet. This diff is also porting the selective code-gen in BUCK. * The selected op list is passed to gen_jit_dispatch.py. * The list passed to gen_jit_dispatch is the top-level ops (USED_PT_OPS) only, because the selective c10/aten dispatch already registered other ops that are called from the top-level ops. ghstack-source-id: 101885215 (Note: this ignores all push blocking failures!) Test Plan: 1. In Python, run torch.jit.export_opnames(scripted_M_mod) 2. Append the operator names into fbcode/caffe2/pt_ops.bzl and the BUCK target. 3. Run ``` buck run xplat/caffe2/fb/lite_predictor:lite_predictor_bi -- --model=/home/myuan/temp/bi_pytext_0315.bc --input_dims "1,4" --input_type int64 --pytext_len=4 ``` Should provide expected results. In addition, the size of the generated code for JIT registration, for example, ```register_aten_ops_0.cpp```, should be significantly reduced (from ~250 KB to ~80KB). The non-selected op registration schema are still kept, but the registration functor is replaced by ```DUMMY_OPERATION``` Reviewed By: ljk53 Differential Revision: D20408831 fbshipit-source-id: ec75dd762c4613aeda3b2094f5dad11804dc9492

Summary: Benchmark: (Debian 10, Release build, gcc 8.3, no turbo, Intel(R) Xeon(R) E-2136 CPU @ 3.30GHz) ```python import timeit for op in ('gt', 'lt', 'ge', 'le', 'eq', 'ne'): for dtype in ('torch.float', 'torch.double', 'torch.int16', 'torch.int32', 'torch.int64'): for n, t in [(10_000, 100000), (100_000, 10000)]: print(f'a.{op}_(b), numel() == {n} for {t} times, dtype={dtype}') print(timeit.timeit(f'a.{op}_(b)', setup=f'import torch; a = torch.arange(1, {n}, dtype={dtype}); b = torch.arange({n}, 1, -1, dtype={dtype})', number=t)) ``` Before: ``` a.gt_(b), numel() == 10000 for 100000 times, dtype=torch.float 0.778998922000028 a.gt_(b), numel() == 100000 for 10000 times, dtype=torch.float 0.6359690249992127 a.gt_(b), numel() == 10000 for 100000 times, dtype=torch.double 1.0801493119997758 a.gt_(b), numel() == 100000 for 10000 times, dtype=torch.double 0.9360321379990637 a.gt_(b), numel() == 10000 for 100000 times, dtype=torch.int16 0.7341018620008981 a.gt_(b), numel() == 100000 for 10000 times, dtype=torch.int16 0.6345281440007966 a.gt_(b), numel() == 10000 for 100000 times, dtype=torch.int32 0.7396387640001194 a.gt_(b), numel() == 100000 for 10000 times, dtype=torch.int32 0.6429641230006382 a.gt_(b), numel() == 10000 for 100000 times, dtype=torch.int64 0.7759611700003006 a.gt_(b), numel() == 100000 for 10000 times, dtype=torch.int64 0.6672059659995284 a.lt_(b), numel() == 10000 for 100000 times, dtype=torch.float 0.7724312530008319 a.lt_(b), numel() == 100000 for 10000 times, dtype=torch.float 0.6392585769990546 a.lt_(b), numel() == 10000 for 100000 times, dtype=torch.double 0.7917451840003196 a.lt_(b), numel() == 100000 for 10000 times, dtype=torch.double 0.6455550159989798 a.lt_(b), numel() == 10000 for 100000 times, dtype=torch.int16 0.739991647998977 a.lt_(b), numel() == 100000 for 10000 times, dtype=torch.int16 0.6572993859990675 a.lt_(b), numel() == 10000 for 100000 times, dtype=torch.int32 0.7627949479992822 a.lt_(b), numel() == 100000 for 10000 times, dtype=torch.int32 0.6476544910001394 a.lt_(b), numel() == 10000 for 100000 times, dtype=torch.int64 0.7965036850000615 a.lt_(b), numel() == 100000 for 10000 times, dtype=torch.int64 0.6780715599998075 a.ge_(b), numel() == 10000 for 100000 times, dtype=torch.float 0.7653547080008138 a.ge_(b), numel() == 100000 for 10000 times, dtype=torch.float 0.6383065829995758 a.ge_(b), numel() == 10000 for 100000 times, dtype=torch.double 0.7895260240002244 a.ge_(b), numel() == 100000 for 10000 times, dtype=torch.double 0.6508346030004759 a.ge_(b), numel() == 10000 for 100000 times, dtype=torch.int16 0.7409299750015634 a.ge_(b), numel() == 100000 for 10000 times, dtype=torch.int16 0.6383492870008922 a.ge_(b), numel() == 10000 for 100000 times, dtype=torch.int32 0.7620547579990671 a.ge_(b), numel() == 100000 for 10000 times, dtype=torch.int32 0.6474270239996258 a.ge_(b), numel() == 10000 for 100000 times, dtype=torch.int64 0.8070051169997896 a.ge_(b), numel() == 100000 for 10000 times, dtype=torch.int64 0.6712598600006459 a.le_(b), numel() == 10000 for 100000 times, dtype=torch.float 0.7627660060006747 a.le_(b), numel() == 100000 for 10000 times, dtype=torch.float 0.6406353189995571 a.le_(b), numel() == 10000 for 100000 times, dtype=torch.double 1.0826010620003217 a.le_(b), numel() == 100000 for 10000 times, dtype=torch.double 0.9391552950000914 a.le_(b), numel() == 10000 for 100000 times, dtype=torch.int16 0.7427801039993938 a.le_(b), numel() == 100000 for 10000 times, dtype=torch.int16 0.6365172640016681 a.le_(b), numel() == 10000 for 100000 times, dtype=torch.int32 0.7679271510005492 a.le_(b), numel() == 100000 for 10000 times, dtype=torch.int32 0.6453389289999905 a.le_(b), numel() == 10000 for 100000 times, dtype=torch.int64 0.788032889000533 a.le_(b), numel() == 100000 for 10000 times, dtype=torch.int64 0.6708840760002204 a.eq_(b), numel() == 10000 for 100000 times, dtype=torch.float 1.078837263999958 a.eq_(b), numel() == 100000 for 10000 times, dtype=torch.float 0.9397531720005645 a.eq_(b), numel() == 10000 for 100000 times, dtype=torch.double 1.1031508050000411 a.eq_(b), numel() == 100000 for 10000 times, dtype=torch.double 0.9412319389994082 a.eq_(b), numel() == 10000 for 100000 times, dtype=torch.int16 0.7509566959997755 a.eq_(b), numel() == 100000 for 10000 times, dtype=torch.int16 0.638570957000411 a.eq_(b), numel() == 10000 for 100000 times, dtype=torch.int32 0.7592877549996047 a.eq_(b), numel() == 100000 for 10000 times, dtype=torch.int32 0.6458840529994632 a.eq_(b), numel() == 10000 for 100000 times, dtype=torch.int64 0.7984061539991671 a.eq_(b), numel() == 100000 for 10000 times, dtype=torch.int64 0.6776346309998189 a.ne_(b), numel() == 10000 for 100000 times, dtype=torch.float 0.7724407899986545 a.ne_(b), numel() == 100000 for 10000 times, dtype=torch.float 0.6581534130000364 a.ne_(b), numel() == 10000 for 100000 times, dtype=torch.double 0.8303323249983805 a.ne_(b), numel() == 100000 for 10000 times, dtype=torch.double 0.6954390920000151 a.ne_(b), numel() == 10000 for 100000 times, dtype=torch.int16 0.745512373998281 a.ne_(b), numel() == 100000 for 10000 times, dtype=torch.int16 0.6360954970004968 a.ne_(b), numel() == 10000 for 100000 times, dtype=torch.int32 0.7569978400006221 a.ne_(b), numel() == 100000 for 10000 times, dtype=torch.int32 0.6450422030011396 a.ne_(b), numel() == 10000 for 100000 times, dtype=torch.int64 0.7889118379989668 a.ne_(b), numel() == 100000 for 10000 times, dtype=torch.int64 0.6693385389989999 ``` After: ``` a.gt_(b), numel() == 10000 for 100000 times, dtype=torch.float 0.2444220920006046 a.gt_(b), numel() == 100000 for 10000 times, dtype=torch.float 0.2031730359994981 a.gt_(b), numel() == 10000 for 100000 times, dtype=torch.double 0.35491806199934217 a.gt_(b), numel() == 100000 for 10000 times, dtype=torch.double 0.3905606850003096 a.gt_(b), numel() == 10000 for 100000 times, dtype=torch.int16 0.16665379499863775 a.gt_(b), numel() == 100000 for 10000 times, dtype=torch.int16 0.10095906300011848 a.gt_(b), numel() == 10000 for 100000 times, dtype=torch.int32 0.21650469999985944 a.gt_(b), numel() == 100000 for 10000 times, dtype=torch.int32 0.18737469400002738 a.gt_(b), numel() == 10000 for 100000 times, dtype=torch.int64 0.35481256200000644 a.gt_(b), numel() == 100000 for 10000 times, dtype=torch.int64 0.36696120199849247 a.lt_(b), numel() == 10000 for 100000 times, dtype=torch.float 0.21976138800164335 a.lt_(b), numel() == 100000 for 10000 times, dtype=torch.float 0.20275393200063263 a.lt_(b), numel() == 10000 for 100000 times, dtype=torch.double 0.3695997209997586 a.lt_(b), numel() == 100000 for 10000 times, dtype=torch.double 0.39441510399956314 a.lt_(b), numel() == 10000 for 100000 times, dtype=torch.int16 0.15657078300137073 a.lt_(b), numel() == 100000 for 10000 times, dtype=torch.int16 0.0992998069996247 a.lt_(b), numel() == 10000 for 100000 times, dtype=torch.int32 0.20425128799979575 a.lt_(b), numel() == 100000 for 10000 times, dtype=torch.int32 0.20352934599941364 a.lt_(b), numel() == 10000 for 100000 times, dtype=torch.int64 0.35883567900054913 a.lt_(b), numel() == 100000 for 10000 times, dtype=torch.int64 0.39059587599876977 a.ge_(b), numel() == 10000 for 100000 times, dtype=torch.float 0.21457727400047588 a.ge_(b), numel() == 100000 for 10000 times, dtype=torch.float 0.18836135499986995 a.ge_(b), numel() == 10000 for 100000 times, dtype=torch.double 0.35971907199927955 a.ge_(b), numel() == 100000 for 10000 times, dtype=torch.double 0.3688875009993353 a.ge_(b), numel() == 10000 for 100000 times, dtype=torch.int16 0.1576009280015569 a.ge_(b), numel() == 100000 for 10000 times, dtype=torch.int16 0.09524034199966991 a.ge_(b), numel() == 10000 for 100000 times, dtype=torch.int32 0.2064543649994448 a.ge_(b), numel() == 100000 for 10000 times, dtype=torch.int32 0.18726435600001423 a.ge_(b), numel() == 10000 for 100000 times, dtype=torch.int64 0.35351785300008487 a.ge_(b), numel() == 100000 for 10000 times, dtype=torch.int64 0.3680737989998306 a.le_(b), numel() == 10000 for 100000 times, dtype=torch.float 0.2132134399998904 a.le_(b), numel() == 100000 for 10000 times, dtype=torch.float 0.2140274829998816 a.le_(b), numel() == 10000 for 100000 times, dtype=torch.double 0.36539215199991304 a.le_(b), numel() == 100000 for 10000 times, dtype=torch.double 0.39128020300086064 a.le_(b), numel() == 10000 for 100000 times, dtype=torch.int16 0.15712150600120367 a.le_(b), numel() == 100000 for 10000 times, dtype=torch.int16 0.10149904400168452 a.le_(b), numel() == 10000 for 100000 times, dtype=torch.int32 0.2103407699996751 a.le_(b), numel() == 100000 for 10000 times, dtype=torch.int32 0.2134442910009966 a.le_(b), numel() == 10000 for 100000 times, dtype=torch.int64 0.35387034300038067 a.le_(b), numel() == 100000 for 10000 times, dtype=torch.int64 0.38917528399906587 a.eq_(b), numel() == 10000 for 100000 times, dtype=torch.float 0.2190484450002259 a.eq_(b), numel() == 100000 for 10000 times, dtype=torch.float 0.2030815980015177 a.eq_(b), numel() == 10000 for 100000 times, dtype=torch.double 0.3710030169986567 a.eq_(b), numel() == 100000 for 10000 times, dtype=torch.double 0.36419657899932645 a.eq_(b), numel() == 10000 for 100000 times, dtype=torch.int16 0.15986497499943653 a.eq_(b), numel() == 100000 for 10000 times, dtype=torch.int16 0.10145393699895067 a.eq_(b), numel() == 10000 for 100000 times, dtype=torch.int32 0.21011781599918322 a.eq_(b), numel() == 100000 for 10000 times, dtype=torch.int32 0.20121852699958254 a.eq_(b), numel() == 10000 for 100000 times, dtype=torch.int64 0.36681504499938455 a.eq_(b), numel() == 100000 for 10000 times, dtype=torch.int64 0.364472848999867 a.ne_(b), numel() == 10000 for 100000 times, dtype=torch.float 0.2290963309988001 a.ne_(b), numel() == 100000 for 10000 times, dtype=torch.float 0.21674784300012107 a.ne_(b), numel() == 10000 for 100000 times, dtype=torch.double 0.3829616689999966 a.ne_(b), numel() == 100000 for 10000 times, dtype=torch.double 0.39437660300063726 a.ne_(b), numel() == 10000 for 100000 times, dtype=torch.int16 0.1661020749997988 a.ne_(b), numel() == 100000 for 10000 times, dtype=torch.int16 0.10052955100036343 a.ne_(b), numel() == 10000 for 100000 times, dtype=torch.int32 0.21827425599985872 a.ne_(b), numel() == 100000 for 10000 times, dtype=torch.int32 0.21522501399886096 a.ne_(b), numel() == 10000 for 100000 times, dtype=torch.int64 0.37058242300008715 a.ne_(b), numel() == 100000 for 10000 times, dtype=torch.int64 0.39304063900090114 ``` Pull Request resolved: pytorch#35117 Differential Revision: D20721181 Pulled By: pbelevich fbshipit-source-id: 4e38cc0f42393483db91b2dc53ffc507f91ed904

…om manual to selective build Test Plan: revert-hammer Differential Revision: D20408831 Original commit changeset: ec75dd762c46 fbshipit-source-id: f1874088a5970dd220cc027d0020ab6223b9bd93

…tration migrate from manual to selective build Test Plan: revert-hammer Differential Revision: D20964368 Original commit changeset: f1874088a597 fbshipit-source-id: d9317ed97a98e2b04c190785b5564536b1096282

Summary: Pull Request resolved: pytorch#36244 Differential Revision: D20963949 Pulled By: ezyang fbshipit-source-id: 8c6aa4831021788052269e7aa8282d11eba4e085

Summary: Per title. A test is added to test_type_promotion for the behavior. This behavior is consistent with NumPy's. For complex inputs to `abs` the result is cast to float after the computation since the computation of abs must be performed on the original complex tensor. While `std::abs` returns a float value when called on complex inputs, returning a FloatTensor directly would require additional loop instantiations in TensorIterator. This may be worthwhile to pursue in the future. Pull Request resolved: pytorch#35871 Differential Revision: D20961711 Pulled By: mruberry fbshipit-source-id: 232f62cf64caa4154eb2194969efa51d2082d842

Summary: Re-land of pytorch#35530 and pytorch#34645 Pull Request resolved: pytorch#36138 Differential Revision: D20893770 Pulled By: ezyang fbshipit-source-id: 75ab688a086f5fb87412a853df5246c0c39704ca

Summary: Pull Request resolved: pytorch#36690 Adds the static quantization hook for LayerNorm Test Plan: ``` python test/quantization/test_quantized_nn_mods.py ModuleAPITest.test_layer_norm python test/quantization/test_quantization.py EagerModePostTrainingQuantTest.test_normalization ``` Imported from OSS Differential Revision: D21055401 fbshipit-source-id: 188329f35359576d50ed0db5fb675ce68c28bf7d

Summary: re-created the same PR: pytorch#36639 because ghimport does not support importing binary files right now Pull Request resolved: pytorch#36771 Test Plan: python test/quantization/test_backward_compatibility.py Differential Revision: D21080503 Pulled By: jerryzh168 fbshipit-source-id: 1dca08208bccead60bba03e5fb5d39e1a1d7c20d

Summary: Pull Request resolved: pytorch#36740 Issue pytorch#23986 Test Plan: python test/quantization/test_quantized_nn_mods.py Imported from OSS Differential Revision: D21077551 fbshipit-source-id: fdd15db3284975c99b3e250a568fa94c617d21eb

Summary: Mimic `.bzl` parsing logic from pytorch/FBGEMM#344 Generate `libtorch_cmake_sources` by running following script: ``` def read_file(path): with open(path) as f: return f.read() def get_cmake_torch_srcs(): caffe2_cmake = read_file("caffe2/CMakeLists.txt") start = caffe2_cmake.find("set(TORCH_SRCS") end = caffe2_cmake.find(")", start) return caffe2_cmake[start:end+1] def get_cmake_torch_srcs_list(): caffe2_torch_srcs = get_cmake_torch_srcs() unfiltered_list = [x.strip() for x in get_cmake_torch_srcs().split("\n") if len(x.strip())>0] return [x.replace("${TORCH_SRC_DIR}/","torch/") for x in unfiltered_list if 'TORCH_SRC_DIR' in x] import imp build_variables = imp.load_source('build_variables', 'tools/build_variables.bzl') libtorch_core_sources = set(build_variables.libtorch_core_sources) caffe2_torch_srcs = set(get_cmake_torch_srcs_list()) if not libtorch_core_sources.issubset(caffe2_torch_srcs): print("libtorch_core_sources must be a subset of caffe2_torch_srcs") print(sorted(caffe2_torch_srcs.difference(libtorch_core_sources))) ``` Move common files between `libtorch_cmake_sources` and `libtorch_extra_sources` to `libtorch_jit_core_sources` Pull Request resolved: pytorch#36737 Test Plan: CI Differential Revision: D21078753 Pulled By: malfet fbshipit-source-id: f46ca48d48aa122188f028136c14687ff52629ed

Summary: Pull Request resolved: pytorch#36745 As we hold a mutex for our custom C++ Node, when calling reentrant backward from custom C++ function, we will cocurrently holding many mutexes up to MAX_DEPTH. TSAN only allow 65 mutexes at once, otherwise it will complain. This PR lower the limit according to TSAN. TSAN Reference: google/sanitizers#950 Test Plan: Imported from OSS Differential Revision: D21072604 Pulled By: wanchaol fbshipit-source-id: 99cd1acab41a203d834fa4947f4e6f0ffd2e70f2

Summary: This should fix pytorch#36434 We create new nodes to insert explicit uses of loop counters while doing liveness analysis. This was totally fine when we had a two-pass liveness (since we don't really care about liveness sets for those nodes), but with the fixed-point algorithm we can *never* achieve the fixed point because the initial liveness sets for these new nodes start empty and we always add some live values to those sets thus `changed_` is always set `true`. Now it's amazing that this didn't get exposed and worked for such a long time! Apparently, when we destroyed and recreated those new nodes they were allocated at the exact same addresses in the memory!!!!!! And we use those addresses as keys to get liveness sets, so these new nodes **inherited** the liveness sets � I was still a bit sceptical of this explanation, so I added more tracing to liveness analysis and AFAICT this is exactly how we were able to get away with this bug for such a long time!!! Here's a few excerpts from the trace. Before we enter a loop we create a node to use loop's upper bound. ``` [DEBUG liveness.cpp:121] @#$Creating a store for mtc : 0x555777c19eb0 ``` When processing the loop, we also process this node. Its liveness sets are empty! ``` [DEBUG liveness.cpp:099] Processing node = prim::Store(%3) addr = 0x555777c19eb0 [DEBUG liveness.cpp:148] @#$liveness_sets_[it] : {} ``` We are done with this loop. We remove the node we added ``` [DEBUG liveness.cpp:127] @#$Destroying a store for ctc : 0x555777c19eb0 ``` We are about to process the loop for the second time, so we create the use node again. Note, it's allocated at the exact same address!!! ``` [DEBUG liveness.cpp:118] @#$Creating a store for ctc : 0x555777c19eb0 ``` Now we process it again. But now it has non-empty sets even though it's a brand new node!!!! ``` [DEBUG liveness.cpp:099] Processing node = prim::Store(%i) addr = 0x555777c19eb0 [DEBUG liveness.cpp:148] @#$liveness_sets_[it] : {2, 3, 10} ``` Pull Request resolved: pytorch#36697 Differential Revision: D21059313 Pulled By: Krovatkin fbshipit-source-id: b0fdeb4418e0e73f34187826877179260f21cf7b

…tion (pytorch#36621) Summary: Pull Request resolved: pytorch#36621 Instead of doing in-place transformation inside optimizeForMobile method, we would like to maintain the original structure for passed scriptedModule, so before optmization starts, we use the cloned module to do subsequent optimization process and return the optimized cloned module. Test Plan: unit test python test/test_mobile_optimizer.py Imported from OSS Differential Revision: D21028406 fbshipit-source-id: 756172ef99b1c1df6bb7d00e5deca85a4c239a87

…ytorch#36705) Summary: Pull Request resolved: pytorch#36705 ghstack-source-id: 102257937 Test Plan: waitforbuildbot Differential Revision: D21058176 fbshipit-source-id: 1d32730d61420324856cc641f888751418c1dd26

Test Plan: revert-hammer Differential Revision: D21080503 Original commit changeset: 1dca08208bcc fbshipit-source-id: 5cd8c22130ff28b9231f657f80961e94b65b5792

Summary: Pull Request resolved: pytorch#36763 Differential Revision: D21083309 Pulled By: Krovatkin fbshipit-source-id: 4fb5b95bd3e01bd83a406d4394f266d7fd168f21

Summary: Pull Request resolved: pytorch#36564 - ghstack-source-id: 102292162 Test Plan: waitforsandcastle Differential Revision: D21014324 fbshipit-source-id: 5b95eafbb668bed174cd2c826e308e74e329f552

Summary: Fixes clang format. Pull Request resolved: pytorch#36787 Differential Revision: D21084603 Pulled By: mruberry fbshipit-source-id: 7e29da135f9a2aa126cb68640e33c1914fd570e3

Summary: Pull Request resolved: pytorch#36750 - It seems the JIT schema for aten::backward and the schema in native_functions.yaml diverged on whether the retain_graph/keep_graph parameter takes a `bool` or a `bool?`. Make them identical again. - Also remove the mutability annotation for the self parameter. This does not make sense together with AliasAnalysisKind::CONSERVATIVE and it triggered an assertion - After fixing the mutability annotation, we can fix that assertion so that it doesn't exclude aten::backward from its check anymore - Last but not least, remove the unboxed_only marker from aten::backward. This requires us to add a special case in register_c10_ops.cpp for it, because JIT still has its own implementation. ghstack-source-id: 102351871 Test Plan: waitforsandcastle Differential Revision: D21004102 fbshipit-source-id: 19bd1adbd8103c214d32e5126671a809adec581e

…pytorch#36480) Summary: Pull Request resolved: pytorch#36480 Test Plan: Imported from OSS Differential Revision: D20992505 Pulled By: zheng-xq fbshipit-source-id: 3d4e5401b59b9507b5f2db659e511bd1af53f5ab

Summary: Pull Request resolved: pytorch#36760 If you look at pytorch#34136, you will notice a commit (pytorch@80c15c0) that didn't get merged. This is to address that, to avoid crashing on remainder when the rhs is 0. Test Plan: Imported from OSS Differential Revision: D21078776 Pulled By: gchanan fbshipit-source-id: 0ac138cbafac28cf8d696a2a413d3c542138cff9

…torch#36780) Summary: Pull Request resolved: pytorch#36780 Fixes: pytorch#36773 Test Plan: Imported from OSS Differential Revision: D21081993 Pulled By: gchanan fbshipit-source-id: 624b0077f88208aafa131ab7b3e5f1fe9dd70987

Summary: Pull Request resolved: pytorch#36736 Fixes: pytorch#36499 Changes: 1) Moves some bindings from LegacyNNDefinitions to Activation so all of log_sigmoid lives together 2) Properly handle non-contiguous / incorrectly sized out parameters to log_sigmoid. This is done by copying from a buffer if necessary. 3) Require that the internal buffer (different from 2)) is contiguous. This should always be the case because it's always created internally. 4) Adds a test Test Plan: Imported from OSS Differential Revision: D21070934 Pulled By: gchanan fbshipit-source-id: 94577313c32d1ef04d65c1d6657598304a39fe6e

Summary: This pull request changes the datatype for `test_RNN_cpu_vs_cudnn_no_dropout` on ROCm testing to float. Currently MIOpen RNN does not support double datatype, so using only double would not run this test using MIOpen. To correctly test PyTorch RNN operator using MIOpen, we would need to test it using float tensors and module. The changes in this PR addresses the comments in pytorch#34615 ezyang iotamudelta Pull Request resolved: pytorch#36772 Differential Revision: D21089533 Pulled By: ezyang fbshipit-source-id: b5781e4ca270d64c6b949b3f0436e7b4eb870e27

Summary: pytorch#36351 make `hardsigmoid_backward` use tensoriterator but that can be done only after proper device dispatch. Pull Request resolved: pytorch#36704 Differential Revision: D21068126 Pulled By: ailzhang fbshipit-source-id: 6a6a74216f2b50fa7d15f692cd1583d3d233580a

Summary: Several people have asked me about proper Amp usage with gradient accumulation. In particular, it's [unclear to people](NVIDIA/apex#439 (comment)) that you should only call `scaler.unscale_()` (if desired) and `scaler.update()` in iterations where you actually plan to step. This PR adds a minimal accumulation example. I built the docs locally and it looks free from sphinx errors, at least. Pull Request resolved: pytorch#36601 Differential Revision: D21082295 Pulled By: ngimel fbshipit-source-id: b2faa6c02b9f7e1972618a0f1d5360a03f0450ac

…rch#36709) Summary: Pull Request resolved: pytorch#36709 Test Plan: Imported from OSS Differential Revision: D21083393 Pulled By: ngimel fbshipit-source-id: ea3f7f29709c9a6e5b3ec45ba809cb2cf6c5e0c8

Summary: Pull Request resolved: pytorch#60987 We were seeing deadlocks as follows during shutdown: ``` Thread 1 (LWP 2432101): #0 0x00007efca470190b in __pause_nocancel () from /lib64/libc.so.6 #1 0x00007efca49de485 in __pthread_mutex_lock_full () from /lib64/libpthread.so.0 #2 0x00007ef91d4c42c6 in __cuda_CallJitEntryPoint () from /lib64/libnvidia-ptxjitcompiler.so.1 #3 0x00007efc651ac8f1 in ?? () from /lib64/libcuda.so #4 0x00007efc651aee03 in ?? () from /lib64/libcuda.so csarofeen#5 0x00007efc64f76b84 in ?? () from /lib64/libcuda.so csarofeen#6 0x00007efc64f77f5d in ?? () from /lib64/libcuda.so csarofeen#7 0x00007efc64eac858 in ?? () from /lib64/libcuda.so csarofeen#8 0x00007efc64eacfbc in ?? () from /lib64/libcuda.so csarofeen#9 0x00007efc7810a924 in ?? () from /usr/local/cuda/lib64/libcublas.so.11 csarofeen#10 0x00007efc780fa2be in ?? () from /usr/local/cuda/lib64/libcublas.so.11 csarofeen#11 0x00007efc78111044 in ?? () from /usr/local/cuda/lib64/libcublas.so.11 csarofeen#12 0x00007efc7811580a in ?? () from /usr/local/cuda/lib64/libcublas.so.11 csarofeen#13 0x00007efc78115aa4 in ?? () from /usr/local/cuda/lib64/libcublas.so.11 csarofeen#14 0x00007efc781079ec in ?? () from /usr/local/cuda/lib64/libcublas.so.11 csarofeen#15 0x00007efc780e6a7a in ?? () from /usr/local/cuda/lib64/libcublas.so.11 csarofeen#16 0x00007efc7811cfa5 in ?? () from /usr/local/cuda/lib64/libcublas.so.11 csarofeen#17 0x00007efc777ea98c in ?? () from /usr/local/cuda/lib64/libcublas.so.11 csarofeen#18 0x00007efc777ebd80 in ?? () from /usr/local/cuda/lib64/libcublas.so.11 csarofeen#19 0x00007efc777ea2c9 in ?? () from /usr/local/cuda/lib64/libcublas.so.11 csarofeen#20 0x00007efc778c2e2d in cublasDestroy_v2 () from /usr/local/cuda/lib64/libcublas.so.11 csarofeen#21 0x00007efc51a3fb56 in std::_Sp_counted_ptr_inplace<at::cuda::(anonymous namespace)::DeviceThreadHandlePool<cublasContext*, &at::cuda::(anonymous namespace)::createCublasHandle, &at::cuda::(anonymous namespace)::destroyCublasHandle>, std::allocator<at::cuda::(anonymous namespace)::DeviceThreadHandlePool<cublasContext*, &at::cuda::(anonymous namespace)::createCublasHandle, &at::cuda::(anonymous namespace)::destroyCublasHandle> >, (__gnu_cxx::_Lock_policy)2>::_M_dispose() () from /data/users/pritam/pytorch/torch/lib/libtorch_cuda.so csarofeen#22 0x00007efc51a3fc5f in std::shared_ptr<at::cuda::(anonymous namespace)::DeviceThreadHandlePool<cublasContext*, &at::cuda::(anonymous namespace)::createCublasHandle, &at::cuda::(anonymous namespace)::destroyCublasHandle> >::~shared_ptr() () from /data/users/pritam/pytorch/torch/lib/libtorch_cuda.so csarofeen#23 0x00007efca4648b0c in __run_exit_handlers () from /lib64/libc.so.6 csarofeen#24 0x00007efca4648c40 in exit () from /lib64/libc.so.6 csarofeen#25 0x0000558c8852e5f9 in Py_Exit (sts=0) at /tmp/build/80754af9/python_1614362349910/work/Python/pylifecycle.c:2292 csarofeen#26 0x0000558c8852e6a7 in handle_system_exit () at /tmp/build/80754af9/python_1614362349910/work/Python/pythonrun.c:636 csarofeen#27 0x0000558c8852e742 in PyErr_PrintEx (set_sys_last_vars=<optimized out>, set_sys_last_vars=<optimized out>) at /tmp/build/80754af9/python_1614362349910/work/Python/pythonrun.c:646 csarofeen#28 0x0000558c88540dd6 in PyRun_SimpleStringFlags (command=0x7efca4dc9050 "from multiprocessing.spawn import spawn_main; spawn_main(tracker_fd=9, pipe_handle=13)\n", flags=0x7ffe3a986110) at /tmp/build/80754af9/python_1614362349910/work/Python/pythonrun.c:457 csarofeen#29 0x0000558c88540ead in pymain_run_command (cf=0x7ffe3a986110, command=<optimized out>) at /tmp/build/80754af9/python_1614362349910/work/Modules/main.c:420 csarofeen#30 pymain_run_python (pymain=0x7ffe3a986220) at /tmp/build/80754af9/python_1614362349910/work/Modules/main.c:2907 csarofeen#31 pymain_main (pymain=0x7ffe3a986220) at /tmp/build/80754af9/python_1614362349910/work/Modules/main.c:3460 csarofeen#32 0x0000558c8854122c in _Py_UnixMain (argc=<optimized out>, argv=<optimized out>) at /tmp/build/80754af9/python_1614362349910/work/Modules/main.c:3495 csarofeen#33 0x00007efca4632493 in __libc_start_main () from /lib64/libc.so.6 csarofeen#34 0x0000558c884e5e90 in _start () at ../sysdeps/x86_64/elf/start.S:103 ``` This was likely caused due to a static singleton that wasn't leaky. Following the guidance in https://isocpp.org/wiki/faq/ctors#construct-on-first-use-v2 to use a leaky singleton instead. ghstack-source-id: 132847448 Test Plan: Verified locally. Reviewed By: malfet Differential Revision: D29468866 fbshipit-source-id: 89250594c5cd2643417b1da584c658b742dc5a5c

… of libtorch_python (pytorch#78028) Summary: This moves torch::class_<WorkerInfo> into `rpc_agent.cpp` so it gets registered in libtorch instead of libtorch_python. This is intermediate work to getting torch::deploy to load an unmodified copy of libtorch. Current RPC is incompatible due to duplicate registrations. ``` unknown file: Failure C++ exception with description "Exception Caught inside torch::deploy embedded library: Custom class with name __torch__.torch.classes.dist_rpc.WorkerInfo is already registered. Ensure that registration with torch::class_ is only called once. Exception raised from registerCustomClass at ../aten/src/ATen/core/custom_class.cpp:61 (most recent call first): frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x3e (0x7f3bd9adb92e in /home/tristanr/venvs/multipy/lib/python3.8/site-packages/torch/lib/libc10.so) frame #1: c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::string const&) + 0x5c (0x7f3bd9ab7068 in /home/tristanr/venvs/multipy/lib/python3.8/site-packages/torch/lib/libc10.so) frame #2: torch::registerCustomClass(std::shared_ptr<c10::ClassType>) + 0x110 (0x7f3bc2258980 in /home/tristanr/venvs/multipy/lib/python3.8/site-packages/torch/lib/libtorch_cpu.so) frame #3: torch::detail::class_base::class_base(std::string const&, std::string const&, std::string, std::type_info const&, std::type_info const&) + 0x3b9 (0x7f3bc225a419 in /home/tristanr/venvs/multipy/lib/python3.8/site-packages/torch/lib/libtorch_cpu.so) frame #4: [0x7f3ba45cfea1] frame #5: <unknown function> + 0x1b5334 (0x5652bdab9334 in ./test_deploy) frame #6: <unknown function> + 0x1b4f3e (0x5652bdab8f3e in ./test_deploy) frame #7: <unknown function> + 0x1b519b (0x5652bdab919b in ./test_deploy) frame #8: loadSearchFile(char const*) + 0x23e (0x7f3ba62f37f8 in /tmp/torch_deploy9ATEFg) frame #9: deploy_set_self + 0x51 (0x7f3ba62f38f9 in /tmp/torch_deploy9ATEFg) frame #10: torch::deploy::Interpreter::Interpreter(torch::deploy::InterpreterManager*, std::shared_ptr<torch::deploy::Environment>) + 0x274 (0x5652bdaaa790 in ./test_deploy) frame #11: void __gnu_cxx::new_allocator<torch::deploy::Interpreter>::construct<torch::deploy::Interpreter, torch::deploy::InterpreterManager*, std::shared_ptr<torch::deploy::Environment>&>(torch::deploy::Interpreter*, torch::deploy::InterpreterManager*&&, std::shared_ptr<torch::deploy::Environment>&) + 0x81 (0x5652bdaaf58b in ./test_deploy) frame #12: void std::allocator_traits<std::allocator<torch::deploy::Interpreter> >::construct<torch::deploy::Interpreter, torch::deploy::InterpreterManager*, std::shared_ptr<torch::deploy::Environment>&>(std::allocator<torch::deploy::Interpreter>&, torch::deploy::Interpreter*, torch::deploy::InterpreterManager*&&, std::shared_ptr<torch::deploy::Environment>&) + 0x4a (0x5652bdaae320 in ./test_deploy) frame #13: void std::vector<torch::deploy::Interpreter, std::allocator<torch::deploy::Interpreter> >::_M_realloc_insert<torch::deploy::InterpreterManager*, std::shared_ptr<torch::deploy::Environment>&>(__gnu_cxx::__normal_iterator<torch::deploy::Interpreter*, std::vector<torch::deploy::Interpreter, std::allocator<torch::deploy::Interpreter> > >, torch::deploy::InterpreterManager*&&, std::shared_ptr<torch::deploy::Environment>&) + 0xee (0x5652bdaae4a0 in ./test_deploy) frame #14: void std::vector<torch::deploy::Interpreter, std::allocator<torch::deploy::Interpreter> >::emplace_back<torch::deploy::InterpreterManager*, std::shared_ptr<torch::deploy::Environment>&>(torch::deploy::InterpreterManager*&&, std::shared_ptr<torch::deploy::Environment>&) + 0xb6 (0x5652bdaad258 in ./test_deploy) frame #15: torch::deploy::InterpreterManager::InterpreterManager(unsigned long, std::shared_ptr<torch::deploy::Environment>) + 0x123 (0x5652bdaa83b1 in ./test_deploy) frame #16: TorchpyTest_InitTwice_Test::TestBody() + 0x65 (0x5652bda075a9 in ./test_deploy) frame #17: void testing::internal::HandleSehExceptionsInMethodIfSupported<testing::Test, void>(testing::Test*, void (testing::Test::*)(), char const*) + 0x65 (0x5652bda944b7 in ./test_deploy) frame #18: void testing::internal::HandleExceptionsInMethodIfSupported<testing::Test, void>(testing::Test*, void (testing::Test::*)(), char const*) + 0x5a (0x5652bda8cfe7 in ./test_deploy) frame #19: testing::Test::Run() + 0x100 (0x5652bda68622 in ./test_deploy) frame #20: testing::TestInfo::Run() + 0x10f (0x5652bda68fb3 in ./test_deploy) frame #21: testing::TestSuite::Run() + 0x121 (0x5652bda6980d in ./test_deploy) frame #22: testing::internal::UnitTestImpl::RunAllTests() + 0x38e (0x5652bda756e6 in ./test_deploy) frame #23: bool testing::internal::HandleSehExceptionsInMethodIfSupported<testing::internal::UnitTestImpl, bool>(testing::internal::UnitTestImpl*, bool (testing::internal::UnitTestImpl::*)(), char const*) + 0x65 (0x5652bda9586b in ./test_deploy) frame #24: bool testing::internal::HandleExceptionsInMethodIfSupported<testing::internal::UnitTestImpl, bool>(testing::internal::UnitTestImpl*, bool (testing::internal::UnitTestImpl::*)(), char const*) + 0x5a (0x5652bda8e0f7 in ./test_deploy) frame #25: testing::UnitTest::Run() + 0xc9 (0x5652bda73fd1 in ./test_deploy) frame #26: RUN_ALL_TESTS() + 0x11 (0x5652bda169fa in ./test_deploy) frame #27: main + 0x27 (0x5652bda10ce2 in ./test_deploy) frame #28: <unknown function> + 0x2d310 (0x7f3bc0431310 in /usr/lib/libc.so.6) frame #29: __libc_start_main + 0x81 (0x7f3bc04313c1 in /usr/lib/libc.so.6) frame #30: _start + 0x25 (0x5652bda063b5 in ./test_deploy) ``` Test Plan: CI Differential Revision: D36564258 Pull Request resolved: pytorch#78028 Approved by: https://github.com/rohan-varma

Hi! I was playing with libfuzzer and found bug when loading a model from file via `torch::jit::load` function. There is an unhandled exception in caffe2/serialize when calling a `stoull` function on unsanitized version string. The bug can be reproduced with `aot_model_compiler` binary: ``` aot_model_compiler --model=crash-stoull --model_name=name --model_version=1 --input_dims='1,3,224,224;2,2' --input_types='float;float' ``` Crash file is provided in [crash.zip](https://github.com/pytorch/pytorch/files/8701504/crash.zip). gdb output: ``` Temporary breakpoint 1, main (argc=6, argv=0x7ffcd160f9f8) at /pytorch_master/binaries/aot_model_compiler.cc:87 87 "Run NNC AOT compiler for pytorch model. Example usage:\n" (gdb) c Continuing. terminate called after throwing an instance of 'std::invalid_argument' what(): stoull Program received signal SIGABRT, Aborted. __GI_raise (sig=sig@entry=6) at ../sysdeps/unix/sysv/linux/raise.c:50 50 ../sysdeps/unix/sysv/linux/raise.c: No such file or directory. (gdb) bt #0 __GI_raise (sig=sig@entry=6) at ../sysdeps/unix/sysv/linux/raise.c:50 #1 0x00007fa637f16859 in __GI_abort () at abort.c:79 #2 0x00007fa6381c1911 in ?? () from /lib/x86_64-linux-gnu/libstdc++.so.6 #3 0x00007fa6381cd38c in ?? () from /lib/x86_64-linux-gnu/libstdc++.so.6 #4 0x00007fa6381cd3f7 in std::terminate() () from /lib/x86_64-linux-gnu/libstdc++.so.6 #5 0x00007fa6381cd6a9 in __cxa_throw () from /lib/x86_64-linux-gnu/libstdc++.so.6 #6 0x00007fa6381c42ce in std::__throw_invalid_argument(char const*) () from /lib/x86_64-linux-gnu/libstdc++.so.6 #7 0x000000000247d567 in __gnu_cxx::__stoa<unsigned long long, unsigned long long, char, int> (__str=0x7ffcd160f228 "ZZ", __idx=0x0, __base=10, __convf=<optimized out>, __name=<optimized out>) at /usr/bin/../lib/gcc/x86_64-linux-gnu/10/../../../../include/c++/10/ext/string_conversions.h:83 #8 std::__cxx11::stoull (__str="ZZ", __idx=0x0, __base=10) at /usr/bin/../lib/gcc/x86_64-linux-gnu/10/../../../../include/c++/10/bits/basic_string.h:6577 #9 caffe2::serialize::PyTorchStreamReader::init (this=this@entry=0x8c11ce0) at /pytorch_master/caffe2/serialize/inline_container.cc:145 #10 0x000000000247d9c7 in caffe2::serialize::PyTorchStreamReader::PyTorchStreamReader (this=0x8c11ce0, in=std::shared_ptr<class caffe2::serialize::ReadAdapterInterface> (empty) = {...}) at /pytorch_master/caffe2/serialize/inline_container.cc:88 #11 0x00000000035b7ba4 in __gnu_cxx::new_allocator<caffe2::serialize::PyTorchStreamReader>::construct<caffe2::serialize::PyTorchStreamReader, std::shared_ptr<caffe2::serialize::ReadAdapterInterface> > ( __p=0x2, __args=..., this=<optimized out>) at /usr/bin/../lib/gcc/x86_64-linux-gnu/10/../../../../include/c++/10/ext/new_allocator.h:150 #12 std::allocator_traits<std::allocator<caffe2::serialize::PyTorchStreamReader> >::construct<caffe2::serialize::PyTorchStreamReader, std::shared_ptr<caffe2::serialize::ReadAdapterInterface> > (__a=..., __p=0x2, __p@entry=0x8c11ce0, __args=...) at /usr/bin/../lib/gcc/x86_64-linux-gnu/10/../../../../include/c++/10/bits/alloc_traits.h:512 #13 0x00000000035b1988 in std::_Sp_counted_ptr_inplace<caffe2::serialize::PyTorchStreamReader, std::allocator<caffe2::serialize::PyTorchStreamReader>, (__gnu_cxx::_Lock_policy)2>::_Sp_counted_ptr_inplace<std::shared_ptr<caffe2::serialize::ReadAdapterInterface> > (this=0x8c11cd0, __a=..., __args=...) at /usr/bin/../lib/gcc/x86_64-linux-gnu/10/../../../../include/c++/10/bits/shared_ptr_base.h:551 #14 std::__shared_count<(__gnu_cxx::_Lock_policy)2>::__shared_count<caffe2::serialize::PyTorchStreamReader, std::allocator<caffe2::serialize::PyTorchStreamReader>, std::shared_ptr<caffe2::serialize::ReadAdapterInterface> > (this=0x7ffcd160f3a8, __p=@0x7ffcd160f3a0: 0x10, __args=..., __a=...) at /usr/bin/../lib/gcc/x86_64-linux-gnu/10/../../../../include/c++/10/bits/shared_ptr_base.h:683 #15 std::__shared_ptr<caffe2::serialize::PyTorchStreamReader, (__gnu_cxx::_Lock_policy)2>::__shared_ptr<std::allocator<caffe2::serialize::PyTorchStreamReader>, std::shared_ptr<caffe2::serialize::ReadAdapterInterface> > (this=0x7ffcd160f3a0, __args=..., __tag=...) at /usr/bin/../lib/gcc/x86_64-linux-gnu/10/../../../../include/c++/10/bits/shared_ptr_base.h:1371 #16 std::shared_ptr<caffe2::serialize::PyTorchStreamReader>::shared_ptr<std::allocator<caffe2::serialize::PyTorchStreamReader>, std::shared_ptr<caffe2::serialize::ReadAdapterInterface> > (this=0x7ffcd160f3a0, __args=..., __tag=...) at /usr/bin/../lib/gcc/x86_64-linux-gnu/10/../../../../include/c++/10/bits/shared_ptr.h:408 #17 std::allocate_shared<caffe2::serialize::PyTorchStreamReader, std::allocator<caffe2::serialize::PyTorchStreamReader>, std::shared_ptr<caffe2::serialize::ReadAdapterInterface> > (__args=..., __a=...) at /usr/bin/../lib/gcc/x86_64-linux-gnu/10/../../../../include/c++/10/bits/shared_ptr.h:859 #18 std::make_shared<caffe2::serialize::PyTorchStreamReader, std::shared_ptr<caffe2::serialize::ReadAdapterInterface> > (__args=...) at /usr/bin/../lib/gcc/x86_64-linux-gnu/10/../../../../include/c++/10/bits/shared_ptr.h:875 #19 torch::jit::load (rai=std::shared_ptr<class caffe2::serialize::ReadAdapterInterface> (empty) = {...}, device=device@entry=..., Python Exception <class 'gdb.error'> No type named std::__detail::_Hash_node<struct std::pair<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> > >, true>.: extra_files=std::unordered_map with 0 elements) at /pytorch_master/torch/csrc/jit/serialization/import.cpp:474 #20 0x00000000035b1ef6 in torch::jit::load (filename="crash-stoull", device=device@entry=..., Python Exception <class 'gdb.error'> No type named std::__detail::_Hash_node<struct std::pair<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> > >, true>.: extra_files=std::unordered_map with 0 elements) at /pytorch_master/torch/csrc/jit/serialization/import.cpp:444 #21 0x00000000035b1d22 in torch::jit::load (filename="", device=device@entry=...) at /pytorch_master/torch/csrc/jit/serialization/import.cpp:424 #22 0x00000000008f9be3 in main (argc=1, argv=0x7ffcd160f9f8) at /pytorch_master/binaries/aot_model_compiler.cc:128 ``` Pull Request resolved: pytorch#77557 Approved by: https://github.com/Gamrix

…ytorch#94300) Hi! I've been fuzzing different pytorch modules, and found a crash inside one of them. Specifically, I'm talking about a module for unpickling and a function called `Unpickler::readInstruction()`. Running this function with provided crash file results in a crash, which occurs while calling `auto dict = stack_.at(dict_pos).toGenericDict();` [unpickler.cpp:561](https://github.com/pytorch/pytorch/blob/0e94fbc0c8ab1572c88159c1a4c397b6eb824c01/torch/csrc/jit/serialization/unpickler.cpp#L561). The crash occurs, because the index `dict_pos` is out of bounds (which itself happens because the stack size is 0). Besides this pull-request, there is another one related to unpickler hardening: pytorch#84343 All tests were performed on this pytorch version: [abc54f9](https://github.com/pytorch/pytorch/tree/abc54f93145830b502400faa92bec86e05422fbd) ### How to reproduce 1. To reproduce the crash, use provided docker: [Dockerfile](https://github.com/ispras/oss-sydr-fuzz/tree/master/projects/pytorch) 2. Build the container: `docker build -t oss-sydr-fuzz-pytorch-reproduce .` 3. Copy crash file to the current directory: - [crash-042dff5e121580425d9d34d0f293918f3c9fbf1e.zip](https://github.com/pytorch/pytorch/files/10674361/crash-042dff5e121580425d9d34d0f293918f3c9fbf1e.zip) 4. Run the container: ``docker run --privileged --network host -v `pwd`:/homedir --rm -it oss-sydr-fuzz-pytorch-reproduce /bin/bash`` 5. And execute the binary: `/message_deserialize_sydr /homedir/crash-042dff5e121580425d9d34d0f293918f3c9fbf1e` After execution completes you will see this error message: ```txt terminate called after throwing an instance of 'std::out_of_range' what(): vector::_M_range_check: __n (which is 18446744073709551613) >= this->size() (which is 0) ``` And this stacktrace: ```asan erminate called after throwing an instance of 'std::out_of_range' what(): vector::_M_range_check: __n (which is 18446744073709551613) >= this->size() (which is 0) ==39== ERROR: libFuzzer: deadly signal #0 0x5d0df1 in __sanitizer_print_stack_trace /llvm-project/compiler-rt/lib/asan/asan_stack.cpp:87:3 #1 0x545727 in fuzzer::PrintStackTrace() /llvm-project/compiler-rt/lib/fuzzer/FuzzerUtil.cpp:210:5 csarofeen#2 0x52b933 in fuzzer::Fuzzer::CrashCallback() /llvm-project/compiler-rt/lib/fuzzer/FuzzerLoop.cpp:233:3 csarofeen#3 0x7f9118e0341f (/lib/x86_64-linux-gnu/libpthread.so.0+0x1441f) csarofeen#4 0x7f9118c2300a in raise (/lib/x86_64-linux-gnu/libc.so.6+0x4300a) csarofeen#5 0x7f9118c02858 in abort (/lib/x86_64-linux-gnu/libc.so.6+0x22858) csarofeen#6 0x7f9119040910 (/lib/x86_64-linux-gnu/libstdc++.so.6+0x9e910) csarofeen#7 0x7f911904c38b (/lib/x86_64-linux-gnu/libstdc++.so.6+0xaa38b) csarofeen#8 0x7f911904c3f6 in std::terminate() (/lib/x86_64-linux-gnu/libstdc++.so.6+0xaa3f6) csarofeen#9 0x7f911904c6a8 in __cxa_throw (/lib/x86_64-linux-gnu/libstdc++.so.6+0xaa6a8) csarofeen#10 0x7f91190433aa (/lib/x86_64-linux-gnu/libstdc++.so.6+0xa13aa) csarofeen#11 0x63acdf in std::vector<c10::IValue, std::allocator<c10::IValue> >::_M_range_check(unsigned long) const /usr/bin/../lib/gcc/x86_64-linux-gnu/10/../../../../include/c++/10/bits/stl_vector.h:1073:4 csarofeen#12 0xce8f93e in std::vector<c10::IValue, std::allocator<c10::IValue> >::at(unsigned long) /usr/bin/../lib/gcc/x86_64-linux-gnu/10/../../../../include/c++/10/bits/stl_vector.h:1094:2 csarofeen#13 0xce8f93e in torch::jit::Unpickler::readInstruction() /pytorch_fuzz/torch/csrc/jit/serialization/unpickler.cpp:546:26 csarofeen#14 0xce8d527 in torch::jit::Unpickler::run() /pytorch_fuzz/torch/csrc/jit/serialization/unpickler.cpp:235:27 csarofeen#15 0xce8d1c2 in torch::jit::Unpickler::parse_ivalue() /pytorch_fuzz/torch/csrc/jit/serialization/unpickler.cpp:192:3 csarofeen#16 0xcdf0792 in torch::jit::unpickle(std::function<unsigned long (char*, unsigned long)>, std::function<c10::StrongTypePtr (c10::QualifiedName const&)>, c10::ArrayRef<at::Tensor>, c10::Type::SingletonOrSharedTypePtr<c10::Type> (*)(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&)) /pytorch_fuzz/torch/csrc/jit/serialization/pickle.cpp:127:20 csarofeen#17 0xcdf104d in torch::jit::unpickle(char const*, unsigned long, std::function<c10::StrongTypePtr (c10::QualifiedName const&)>, c10::ArrayRef<at::Tensor>, c10::Type::SingletonOrSharedTypePtr<c10::Type> (*)(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&)) /pytorch_fuzz/torch/csrc/jit/serialization/pickle.cpp:137:10 csarofeen#18 0xe0532db in torch::distributed::rpc::ScriptRemoteCall::fromMessage(torch::distributed::rpc::Message const&) /pytorch_fuzz/torch/csrc/distributed/rpc/script_remote_call.cpp:74:16 csarofeen#19 0xe0ffa10 in torch::distributed::rpc::deserializeRequest(torch::distributed::rpc::Message const&) /pytorch_fuzz/torch/csrc/distributed/rpc/utils.cpp:108:14 csarofeen#20 0x602a41 in LLVMFuzzerTestOneInput /message_deserialize_fuzz.cc:192:27 csarofeen#21 0x52ce61 in fuzzer::Fuzzer::ExecuteCallback(unsigned char const*, unsigned long) /llvm-project/compiler-rt/lib/fuzzer/FuzzerLoop.cpp:611:15 csarofeen#22 0x516d7c in fuzzer::RunOneTest(fuzzer::Fuzzer*, char const*, unsigned long) /llvm-project/compiler-rt/lib/fuzzer/FuzzerDriver.cpp:324:6 csarofeen#23 0x51cacb in fuzzer::FuzzerDriver(int*, char***, int (*)(unsigned char const*, unsigned long)) /llvm-project/compiler-rt/lib/fuzzer/FuzzerDriver.cpp:860:9 csarofeen#24 0x546062 in main /llvm-project/compiler-rt/lib/fuzzer/FuzzerMain.cpp:20:10 csarofeen#25 0x7f9118c04082 in __libc_start_main (/lib/x86_64-linux-gnu/libc.so.6+0x24082) csarofeen#26 0x51169d in _start (/message_deserialize_fuzz+0x51169d) NOTE: libFuzzer has rudimentary signal handlers. Combine libFuzzer with AddressSanitizer or similar for better crash reports. SUMMARY: libFuzzer: deadly signal ``` Pull Request resolved: pytorch#94300 Approved by: https://github.com/malfet, https://github.com/apach301

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 #1 0x3ff8e7da35f in c10::SymInt::maybe_as_int() const /home/user/pytorch/c10/core/SymInt.h:215 csarofeen#2 0x3ff8e7d0a6d in c10::SymInt::sym_eq(c10::SymInt const&) const /home/user/pytorch/c10/core/SymInt.cpp:69 csarofeen#3 0x3ff7a9ab0bd in c10::SymInt::operator==(c10::SymInt const&) const /home/user/pytorch/c10/core/SymInt.h:177 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#8 0x3ff4b23c771 in c10::ArrayRef<c10::SymInt>::equals(c10::ArrayRef<c10::SymInt>) const /home/user/pytorch/c10/util/ArrayRef.h:188 csarofeen#9 0x3ff4cb91bc1 in bool c10::operator!=<c10::SymInt>(c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>) /home/user/pytorch/c10/util/ArrayRef.h:341 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#27 0x3ff79b44fcf in at::Tensor::resize__symint(c10::ArrayRef<c10::SymInt>, c10::optional<c10::MemoryFormat>) const aten/src/ATen/core/TensorBody.h:2452 csarofeen#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 csarofeen#29 0x3ff7999f1eb in torch::autograd::THPVariable_resize_(_object*, _object*, _object*) /home/user/pytorch/torch/csrc/autograd/generated/python_variable_methods.cpp:13419 csarofeen#30 0x3ffa2c9b009 in method_vectorcall_VARARGS_KEYWORDS Objects/descrobject.c:344 csarofeen#31 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#32 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#33 0x3ffa2e05447 in call_function Python/ceval.c:5891 csarofeen#34 0x3ffa2dff7d7 in _PyEval_EvalFrameDefault Python/ceval.c:4198 csarofeen#35 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#36 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#37 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#38 0x3ffa2c8ab15 in PyVectorcall_Call Objects/call.c:255 csarofeen#39 0x3ffa2c8ac65 in _PyObject_Call Objects/call.c:290 csarofeen#40 0x3ffa2c8ada9 in PyObject_Call Objects/call.c:317 csarofeen#41 0x3ffa2e059c7 in do_call_core Python/ceval.c:5943 csarofeen#42 0x3ffa2dffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 csarofeen#43 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#44 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#45 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#46 0x3ffa2c8ab15 in PyVectorcall_Call Objects/call.c:255 csarofeen#47 0x3ffa2c8ac65 in _PyObject_Call Objects/call.c:290 csarofeen#48 0x3ffa2c8ada9 in PyObject_Call Objects/call.c:317 csarofeen#49 0x3ffa2e059c7 in do_call_core Python/ceval.c:5943 csarofeen#50 0x3ffa2dffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 csarofeen#51 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#52 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#53 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#54 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#55 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#56 0x3ffa2e05447 in call_function Python/ceval.c:5891 csarofeen#57 0x3ffa2dff7d7 in _PyEval_EvalFrameDefault Python/ceval.c:4198 csarofeen#58 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#59 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#60 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#61 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#62 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53 csarofeen#63 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#64 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#65 0x3ffa2e05447 in call_function Python/ceval.c:5891 csarofeen#66 0x3ffa2dff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 csarofeen#67 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#68 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#69 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#70 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#71 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#72 0x3ffa2e05447 in call_function Python/ceval.c:5891 csarofeen#73 0x3ffa2dff7d7 in _PyEval_EvalFrameDefault Python/ceval.c:4198 csarofeen#74 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#75 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#76 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#77 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#78 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53 csarofeen#79 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#80 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#81 0x3ffa2e05447 in call_function Python/ceval.c:5891 csarofeen#82 0x3ffa2dffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 csarofeen#83 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#84 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#85 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#86 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#87 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53 csarofeen#88 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#89 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#90 0x3ffa2e05447 in call_function Python/ceval.c:5891 csarofeen#91 0x3ffa2dffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 csarofeen#92 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#93 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#94 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#95 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#96 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53 csarofeen#97 0x3ffa2c8ab9b in PyVectorcall_Call Objects/call.c:267 csarofeen#98 0x3ffa2c8ac65 in _PyObject_Call Objects/call.c:290 csarofeen#99 0x3ffa2c8ada9 in PyObject_Call Objects/call.c:317 csarofeen#100 0x3ffa2e059c7 in do_call_core Python/ceval.c:5943 csarofeen#101 0x3ffa2dffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 csarofeen#102 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#103 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#104 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#105 0x3ffa2c8a695 in _PyObject_FastCallDictTstate Objects/call.c:153 csarofeen#106 0x3ffa2c8b271 in _PyObject_Call_Prepend Objects/call.c:431 csarofeen#107 0x3ffa2d3f307 in slot_tp_call Objects/typeobject.c:7494 csarofeen#108 0x3ffa2c8a933 in _PyObject_MakeTpCall Objects/call.c:215 csarofeen#109 0x3ffa2df0081 in _PyObject_VectorcallTstate Include/cpython/abstract.h:112 csarofeen#110 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#111 0x3ffa2e05447 in call_function Python/ceval.c:5891 csarofeen#112 0x3ffa2dffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 csarofeen#113 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#114 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#115 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#116 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#117 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#118 0x3ffa2e05447 in call_function Python/ceval.c:5891 csarofeen#119 0x3ffa2dff7d7 in _PyEval_EvalFrameDefault Python/ceval.c:4198 csarofeen#120 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#121 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#122 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#123 0x3ffa2c8ab15 in PyVectorcall_Call Objects/call.c:255 csarofeen#124 0x3ffa2c8ac65 in _PyObject_Call Objects/call.c:290 csarofeen#125 0x3ffa2c8ada9 in PyObject_Call Objects/call.c:317 csarofeen#126 0x3ffa2e059c7 in do_call_core Python/ceval.c:5943 csarofeen#127 0x3ffa2dffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 csarofeen#128 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#129 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#130 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#131 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#132 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#133 0x3ffa2e05447 in call_function Python/ceval.c:5891 csarofeen#134 0x3ffa2dff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 csarofeen#135 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#136 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#137 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#138 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#139 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53 csarofeen#140 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#141 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#142 0x3ffa2e05447 in call_function Python/ceval.c:5891 csarofeen#143 0x3ffa2dff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 csarofeen#144 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#145 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#146 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#147 0x3ffa2c8a695 in _PyObject_FastCallDictTstate Objects/call.c:153 csarofeen#148 0x3ffa2c8b271 in _PyObject_Call_Prepend Objects/call.c:431 csarofeen#149 0x3ffa2d3f307 in slot_tp_call Objects/typeobject.c:7494 csarofeen#150 0x3ffa2c8ad17 in _PyObject_Call Objects/call.c:305 csarofeen#151 0x3ffa2c8ada9 in PyObject_Call Objects/call.c:317 csarofeen#152 0x3ffa2e059c7 in do_call_core Python/ceval.c:5943 csarofeen#153 0x3ffa2dffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 csarofeen#154 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#155 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#156 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#157 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#158 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#159 0x3ffa2e05447 in call_function Python/ceval.c:5891 csarofeen#160 0x3ffa2dff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 csarofeen#161 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#162 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#163 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#164 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#165 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53 csarofeen#166 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#167 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#168 0x3ffa2e05447 in call_function Python/ceval.c:5891 csarofeen#169 0x3ffa2dffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 csarofeen#170 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#171 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#172 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#173 0x3ffa2c8ab15 in PyVectorcall_Call Objects/call.c:255 csarofeen#174 0x3ffa2c8ac65 in _PyObject_Call Objects/call.c:290 csarofeen#175 0x3ffa2c8ada9 in PyObject_Call Objects/call.c:317 csarofeen#176 0x3ffa2e059c7 in do_call_core Python/ceval.c:5943 csarofeen#177 0x3ffa2dffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 csarofeen#178 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#179 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#180 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#181 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#182 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#183 0x3ffa2e05447 in call_function Python/ceval.c:5891 csarofeen#184 0x3ffa2dff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 csarofeen#185 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#186 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#187 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#188 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#189 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#190 0x3ffa2e05447 in call_function Python/ceval.c:5891 csarofeen#191 0x3ffa2dffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 csarofeen#192 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#193 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#194 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#195 0x3ffa2c8ab15 in PyVectorcall_Call Objects/call.c:255 csarofeen#196 0x3ffa2c8ac65 in _PyObject_Call Objects/call.c:290 csarofeen#197 0x3ffa2c8ada9 in PyObject_Call Objects/call.c:317 csarofeen#198 0x3ffa2e059c7 in do_call_core Python/ceval.c:5943 csarofeen#199 0x3ffa2dffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 csarofeen#200 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#201 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#202 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#203 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#204 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#205 0x3ffa2e05447 in call_function Python/ceval.c:5891 csarofeen#206 0x3ffa2dff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 csarofeen#207 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#208 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#209 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#210 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#211 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53 csarofeen#212 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#213 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#214 0x3ffa2e05447 in call_function Python/ceval.c:5891 csarofeen#215 0x3ffa2dff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 csarofeen#216 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#217 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#218 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#219 0x3ffa2c8a695 in _PyObject_FastCallDictTstate Objects/call.c:153 csarofeen#220 0x3ffa2c8b271 in _PyObject_Call_Prepend Objects/call.c:431 csarofeen#221 0x3ffa2d3f307 in slot_tp_call Objects/typeobject.c:7494 csarofeen#222 0x3ffa2c8a933 in _PyObject_MakeTpCall Objects/call.c:215 csarofeen#223 0x3ffa2df0081 in _PyObject_VectorcallTstate Include/cpython/abstract.h:112 csarofeen#224 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#225 0x3ffa2e05447 in call_function Python/ceval.c:5891 csarofeen#226 0x3ffa2dffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 csarofeen#227 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#228 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#229 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#230 0x3ffa2c8ab15 in PyVectorcall_Call Objects/call.c:255 csarofeen#231 0x3ffa2c8ac65 in _PyObject_Call Objects/call.c:290 csarofeen#232 0x3ffa2c8ada9 in PyObject_Call Objects/call.c:317 csarofeen#233 0x3ffa2e059c7 in do_call_core Python/ceval.c:5943 csarofeen#234 0x3ffa2dffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 csarofeen#235 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#236 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#237 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#238 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#239 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#240 0x3ffa2e05447 in call_function Python/ceval.c:5891 csarofeen#241 0x3ffa2dff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 csarofeen#242 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#243 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#244 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#245 0x3ffa2c8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#246 0x3ffa2c8eddd in method_vectorcall Objects/classobject.c:53 csarofeen#247 0x3ffa2df00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#248 0x3ffa2df013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#249 0x3ffa2e05447 in call_function Python/ceval.c:5891 csarofeen#250 0x3ffa2dff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 csarofeen#251 0x3ffa2df052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#252 0x3ffa2e02b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#253 0x3ffa2c8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#254 0x3ffa2c8a695 in _PyObject_FastCallDictTstate Objects/call.c:153 csarofeen#255 0x3ffa2c8b271 in _PyObject_Call_Prepend Objects/call.c:431 csarofeen#256 0x3ffa2d3f307 in slot_tp_call Objects/typeobject.c:7494 csarofeen#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 #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 #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 csarofeen#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 #1 0x000003ffa77e3222 in c10::TensorImpl::~TensorImpl (this=0x61000013d740) at /home/user/pytorch/c10/core/TensorImpl.cpp:75 csarofeen#2 0x000003ff63e76e8c in c10::intrusive_ptr<c10::TensorImpl, c10::UndefinedTensorImpl>::reset_ (this=0x3ffd7ec8230) at /home/user/pytorch/c10/util/intrusive_ptr.h:291 csarofeen#3 0x000003ff63e76910 in c10::intrusive_ptr<c10::TensorImpl, c10::UndefinedTensorImpl>::~intrusive_ptr (this=0x3ffd7ec8230) at /home/user/pytorch/c10/util/intrusive_ptr.h:370 csarofeen#4 0x000003ff63e67240 in at::TensorBase::~TensorBase (this=0x3ffd7ec8230) at /home/user/pytorch/aten/src/ATen/core/TensorBase.h:80 csarofeen#5 0x000003ff63e85ee0 in at::Tensor::~Tensor (this=0x3ffd7ec8230) at aten/src/ATen/core/TensorBody.h:90 csarofeen#6 0x000003ff63f67304 in resize__functionalization (dispatchKeySet=..., self=..., size=..., memory_format=...) at /home/user/pytorch/aten/src/ATen/FunctionalizeFallbackKernel.cpp:173 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#13 at::_ops::resize_::redispatch (dispatchKeySet=..., self=..., size=..., memory_format=...) at /home/user/pytorch/build/aten/src/ATen/Operators_4.cpp:2144 csarofeen#14 0x000003ff861d5e08 in at::redispatch::resize__symint (dispatchKeySet=..., self=..., size=..., memory_format=...) at aten/src/ATen/RedispatchFunctions.h:2847 csarofeen#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 #1 0x000003ff734d0a6e in c10::SymInt::sym_eq (this=0x61000013d790, sci=...) at /home/user/pytorch/c10/core/SymInt.cpp:69 csarofeen#2 0x000003ff5f6ab0be in c10::SymInt::operator== (this=0x61000013d790, o=...) at /home/user/pytorch/c10/core/SymInt.h:177 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#7 0x000003ff2ff3c772 in c10::ArrayRef<c10::SymInt>::equals (this=0x3ffed7c9900, RHS=...) at /home/user/pytorch/c10/util/ArrayRef.h:188 csarofeen#8 0x000003ff31891bc2 in c10::operator!=<c10::SymInt> (a1=..., a2=...) at /home/user/pytorch/c10/util/ArrayRef.h:341 csarofeen#9 0x000003ff51eb5800 in torch::ADInplaceOrView::resize_ (ks=..., self=..., size=..., optional_memory_format=...) at /home/user/pytorch/torch/csrc/autograd/VariableTypeManual.cpp:408 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#16 at::_ops::resize_::redispatch (dispatchKeySet=..., self=..., size=..., memory_format=...) at /home/user/pytorch/build/aten/src/ATen/Operators_4.cpp:2144 csarofeen#17 0x000003ff51ed5e08 in at::redispatch::resize__symint (dispatchKeySet=..., self=..., size=..., memory_format=...) at aten/src/ATen/RedispatchFunctions.h:2847 csarofeen#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 csarofeen#2 0x3ff84d807d1 in torch::jit::toPyObject(c10::IValue) /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:617 csarofeen#3 0x3ff84d80305 in torch::jit::toPyObject(c10::IValue) /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:604 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#7 0x3ff82ee52e9 in pybind11::cpp_function::dispatcher(_object*, _object*, _object*) /home/user/pytorch/cmake/../third_party/pybind11/include/pybind11/pybind11.h:929 csarofeen#8 0x3ffab002903 in cfunction_call Objects/methodobject.c:543 csarofeen#9 0x3ffaaf8a933 in _PyObject_MakeTpCall Objects/call.c:215 csarofeen#10 0x3ffaaf8e919 in _PyObject_VectorcallTstate Include/cpython/abstract.h:112 csarofeen#11 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 csarofeen#12 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#13 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#14 0x3ffab105447 in call_function Python/ceval.c:5891 csarofeen#15 0x3ffab0ff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 csarofeen#16 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#17 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#18 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#19 0x3ffaaf8a615 in _PyObject_FastCallDictTstate Objects/call.c:142 csarofeen#20 0x3ffaaf8b271 in _PyObject_Call_Prepend Objects/call.c:431 csarofeen#21 0x3ffab03f307 in slot_tp_call Objects/typeobject.c:7494 csarofeen#22 0x3ffaaf8a933 in _PyObject_MakeTpCall Objects/call.c:215 csarofeen#23 0x3ffab0f0081 in _PyObject_VectorcallTstate Include/cpython/abstract.h:112 csarofeen#24 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#25 0x3ffab105447 in call_function Python/ceval.c:5891 csarofeen#26 0x3ffab0ff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 csarofeen#27 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#28 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#29 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#30 0x3ffaaf8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#31 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 csarofeen#32 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#33 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#34 0x3ffab105447 in call_function Python/ceval.c:5891 csarofeen#35 0x3ffab0ff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 csarofeen#36 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#37 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#38 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#39 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#40 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#41 0x3ffab105447 in call_function Python/ceval.c:5891 csarofeen#42 0x3ffab0ff7d7 in _PyEval_EvalFrameDefault Python/ceval.c:4198 csarofeen#43 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#44 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#45 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#46 0x3ffaaf8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#47 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 csarofeen#48 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#49 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#50 0x3ffab105447 in call_function Python/ceval.c:5891 csarofeen#51 0x3ffab0ffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 csarofeen#52 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#53 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#54 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#55 0x3ffaaf8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#56 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 csarofeen#57 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#58 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#59 0x3ffab105447 in call_function Python/ceval.c:5891 csarofeen#60 0x3ffab0ffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 csarofeen#61 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#62 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#63 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#64 0x3ffaaf8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#65 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 csarofeen#66 0x3ffaaf8ab9b in PyVectorcall_Call Objects/call.c:267 csarofeen#67 0x3ffaaf8ac65 in _PyObject_Call Objects/call.c:290 csarofeen#68 0x3ffaaf8ada9 in PyObject_Call Objects/call.c:317 csarofeen#69 0x3ffab1059c7 in do_call_core Python/ceval.c:5943 csarofeen#70 0x3ffab0ffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 csarofeen#71 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#72 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#73 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#74 0x3ffaaf8a695 in _PyObject_FastCallDictTstate Objects/call.c:153 csarofeen#75 0x3ffaaf8b271 in _PyObject_Call_Prepend Objects/call.c:431 csarofeen#76 0x3ffab03f307 in slot_tp_call Objects/typeobject.c:7494 csarofeen#77 0x3ffaaf8a933 in _PyObject_MakeTpCall Objects/call.c:215 csarofeen#78 0x3ffab0f0081 in _PyObject_VectorcallTstate Include/cpython/abstract.h:112 csarofeen#79 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#80 0x3ffab105447 in call_function Python/ceval.c:5891 csarofeen#81 0x3ffab0ffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 csarofeen#82 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#83 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#84 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#85 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#86 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#87 0x3ffab105447 in call_function Python/ceval.c:5891 csarofeen#88 0x3ffab0ff7d7 in _PyEval_EvalFrameDefault Python/ceval.c:4198 csarofeen#89 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#90 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#91 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#92 0x3ffaaf8ab15 in PyVectorcall_Call Objects/call.c:255 csarofeen#93 0x3ffaaf8ac65 in _PyObject_Call Objects/call.c:290 csarofeen#94 0x3ffaaf8ada9 in PyObject_Call Objects/call.c:317 csarofeen#95 0x3ffab1059c7 in do_call_core Python/ceval.c:5943 csarofeen#96 0x3ffab0ffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 csarofeen#97 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#98 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#99 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#100 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#101 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#102 0x3ffab105447 in call_function Python/ceval.c:5891 csarofeen#103 0x3ffab0ff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 csarofeen#104 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#105 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#106 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#107 0x3ffaaf8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#108 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 csarofeen#109 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#110 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#111 0x3ffab105447 in call_function Python/ceval.c:5891 csarofeen#112 0x3ffab0ff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 csarofeen#113 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#114 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#115 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#116 0x3ffaaf8a695 in _PyObject_FastCallDictTstate Objects/call.c:153 csarofeen#117 0x3ffaaf8b271 in _PyObject_Call_Prepend Objects/call.c:431 csarofeen#118 0x3ffab03f307 in slot_tp_call Objects/typeobject.c:7494 csarofeen#119 0x3ffaaf8ad17 in _PyObject_Call Objects/call.c:305 csarofeen#120 0x3ffaaf8ada9 in PyObject_Call Objects/call.c:317 csarofeen#121 0x3ffab1059c7 in do_call_core Python/ceval.c:5943 csarofeen#122 0x3ffab0ffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 csarofeen#123 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#124 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#125 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#126 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#127 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#128 0x3ffab105447 in call_function Python/ceval.c:5891 csarofeen#129 0x3ffab0ff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 csarofeen#130 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#131 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#132 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#133 0x3ffaaf8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#134 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 csarofeen#135 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#136 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#137 0x3ffab105447 in call_function Python/ceval.c:5891 csarofeen#138 0x3ffab0ffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 csarofeen#139 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#140 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#141 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#142 0x3ffaaf8ab15 in PyVectorcall_Call Objects/call.c:255 csarofeen#143 0x3ffaaf8ac65 in _PyObject_Call Objects/call.c:290 csarofeen#144 0x3ffaaf8ada9 in PyObject_Call Objects/call.c:317 csarofeen#145 0x3ffab1059c7 in do_call_core Python/ceval.c:5943 csarofeen#146 0x3ffab0ffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 csarofeen#147 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#148 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#149 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#150 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#151 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#152 0x3ffab105447 in call_function Python/ceval.c:5891 csarofeen#153 0x3ffab0ff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 csarofeen#154 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#155 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#156 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#157 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#158 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#159 0x3ffab105447 in call_function Python/ceval.c:5891 csarofeen#160 0x3ffab0ffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 csarofeen#161 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#162 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#163 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#164 0x3ffaaf8ab15 in PyVectorcall_Call Objects/call.c:255 csarofeen#165 0x3ffaaf8ac65 in _PyObject_Call Objects/call.c:290 csarofeen#166 0x3ffaaf8ada9 in PyObject_Call Objects/call.c:317 csarofeen#167 0x3ffab1059c7 in do_call_core Python/ceval.c:5943 csarofeen#168 0x3ffab0ffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 csarofeen#169 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#170 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#171 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#172 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#173 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#174 0x3ffab105447 in call_function Python/ceval.c:5891 csarofeen#175 0x3ffab0ff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 csarofeen#176 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#177 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#178 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#179 0x3ffaaf8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#180 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 csarofeen#181 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#182 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#183 0x3ffab105447 in call_function Python/ceval.c:5891 csarofeen#184 0x3ffab0ff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 csarofeen#185 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#186 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#187 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#188 0x3ffaaf8a695 in _PyObject_FastCallDictTstate Objects/call.c:153 csarofeen#189 0x3ffaaf8b271 in _PyObject_Call_Prepend Objects/call.c:431 csarofeen#190 0x3ffab03f307 in slot_tp_call Objects/typeobject.c:7494 csarofeen#191 0x3ffaaf8a933 in _PyObject_MakeTpCall Objects/call.c:215 csarofeen#192 0x3ffab0f0081 in _PyObject_VectorcallTstate Include/cpython/abstract.h:112 csarofeen#193 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#194 0x3ffab105447 in call_function Python/ceval.c:5891 csarofeen#195 0x3ffab0ffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 csarofeen#196 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#197 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#198 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#199 0x3ffaaf8ab15 in PyVectorcall_Call Objects/call.c:255 csarofeen#200 0x3ffaaf8ac65 in _PyObject_Call Objects/call.c:290 csarofeen#201 0x3ffaaf8ada9 in PyObject_Call Objects/call.c:317 csarofeen#202 0x3ffab1059c7 in do_call_core Python/ceval.c:5943 csarofeen#203 0x3ffab0ffd39 in _PyEval_EvalFrameDefault Python/ceval.c:4277 csarofeen#204 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#205 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#206 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#207 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#208 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#209 0x3ffab105447 in call_function Python/ceval.c:5891 csarofeen#210 0x3ffab0ff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 csarofeen#211 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#212 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#213 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#214 0x3ffaaf8e941 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#215 0x3ffaaf8eddd in method_vectorcall Objects/classobject.c:53 csarofeen#216 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#216 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#217 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#218 0x3ffab105447 in call_function Python/ceval.c:5891 csarofeen#219 0x3ffab0ff779 in _PyEval_EvalFrameDefault Python/ceval.c:4181 csarofeen#220 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#221 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#222 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#223 0x3ffaaf8a695 in _PyObject_FastCallDictTstate Objects/call.c:153 csarofeen#224 0x3ffaaf8b271 in _PyObject_Call_Prepend Objects/call.c:431 csarofeen#225 0x3ffab03f307 in slot_tp_call Objects/typeobject.c:7494 csarofeen#226 0x3ffaaf8a933 in _PyObject_MakeTpCall Objects/call.c:215 csarofeen#227 0x3ffab0f0081 in _PyObject_VectorcallTstate Include/cpython/abstract.h:112 csarofeen#228 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#229 0x3ffab105447 in call_function Python/ceval.c:5891 csarofeen#230 0x3ffab0ffa57 in _PyEval_EvalFrameDefault Python/ceval.c:4231 csarofeen#231 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#232 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#233 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#234 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#235 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#236 0x3ffab105447 in call_function Python/ceval.c:5891 csarofeen#237 0x3ffab0ff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 csarofeen#238 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#239 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#240 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#241 0x3ffab0f00a9 in _PyObject_VectorcallTstate Include/cpython/abstract.h:114 csarofeen#242 0x3ffab0f013d in PyObject_Vectorcall Include/cpython/abstract.h:123 csarofeen#243 0x3ffab105447 in call_function Python/ceval.c:5891 csarofeen#244 0x3ffab0ff905 in _PyEval_EvalFrameDefault Python/ceval.c:4213 csarofeen#245 0x3ffab0f052b in _PyEval_EvalFrame Include/internal/pycore_ceval.h:46 csarofeen#246 0x3ffab102b67 in _PyEval_Vector Python/ceval.c:5065 csarofeen#247 0x3ffaaf8aec1 in _PyFunction_Vectorcall Objects/call.c:342 csarofeen#248 0x3ffaaf8ab15 in PyVectorcall_Call Objects/call.c:255 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#14 0x000003ff4115fbac in c10::ivalue::TupleTypeFactory<c10::TupleType>::fallback (type=...) at /home/user/pytorch/aten/src/ATen/core/dynamic_type.cpp:383 csarofeen#15 0x000003ff708217fe in c10::ivalue::Tuple::type<c10::TupleType> (this=0x6080004b8520) at /home/user/pytorch/aten/src/ATen/core/ivalue_inl.h:781 csarofeen#16 0x000003ff70800740 in torch::jit::toPyObject (ivalue=...) at /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:613 csarofeen#17 0x000003ff70800306 in torch::jit::toPyObject (ivalue=...) at /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:604 csarofeen#18 0x000003ff702d6872 in pybind11::detail::type_caster<c10::IValue, void>::cast (src=...) at /home/user/pytorch/torch/csrc/jit/python/pybind.h:138 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#9 0x000003ff448d82f6 in c10::TupleType::~TupleType (this=0x611000c40580) at /home/user/pytorch/aten/src/ATen/core/jit_type.h:1142 csarofeen#10 0x000003ff448d8346 in c10::TupleType::~TupleType (this=0x611000c40580) at /home/user/pytorch/aten/src/ATen/core/jit_type.h:1142 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#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 csarofeen#16 0x000003ff73d00788 in torch::jit::toPyObject (ivalue=...) at /home/user/pytorch/torch/csrc/jit/python/pybind_utils.cpp:613 csarofeen#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

ezyang and others added 30 commits April 9, 2020 14:56

[quant] Move graph mode quantization tests to test_quantize_script.py (…

358466f

…pytorch#36324) Summary: Pull Request resolved: pytorch#36324 Test Plan: . Imported from OSS Differential Revision: D20948046 fbshipit-source-id: 2dd8f0c6fbe8fd84293420b97592dc586d25def9

[quant][fix] at::print for per channel affine quantized tensors (pyto…

f2bae8e

…rch#36280) Summary: Pull Request resolved: pytorch#36280 Test Plan: . Imported from OSS Differential Revision: D20948352 fbshipit-source-id: 92188806b9c129458ebb2cdc47599427e3b6e216

Base class for the quantized ConvTranspose (pytorch#35370)

c5662dd

Summary: Pull Request resolved: pytorch#35370 Test Plan: Imported from OSS Differential Revision: D20641812 Pulled By: z-a-f fbshipit-source-id: 42bb1ed96d6b6e0a5da6e693d02ff616c33d9ef6

Adding Conv1d to quantization default_mappings (pytorch#36352)

891a533

Summary: Pull Request resolved: pytorch#36352 Test Plan: Imported from OSS Differential Revision: D20955781 Pulled By: z-a-f fbshipit-source-id: 37fbcf329a6abcd9a367a73ad65ce543ed9ffe47

Updating submodules

391a36a

Summary: GitHub commits: facebook/fbthrift@54dc44b facebook/litho@726a62c facebook/proxygen@9557561 facebook/rocksdb@66a95f0 pytorch/FBGEMM@f1d3330 Test Plan: n/a Reviewed By: zpao fbshipit-source-id: 3585db200a5d84ba01b8cf90a3bd7bf003314345

Updating submodules

31dca07

Summary: GitHub commits: pytorch/FBGEMM@20b6cf1 Test Plan: n/a Reviewed By: zpao fbshipit-source-id: f5a64d847512d25a138f666d25e03c58277327f0

[caffe2/detectron2] fix Mask R-CNN caffe2 conversion on GPU (pytorch#…

9a4bc67

…36366) Summary: Pull Request resolved: pytorch#36366 fix issues introduced in D20528758 Reviewed By: linbinyu Differential Revision: D20959367 fbshipit-source-id: 920055a6782b9c6729177f7101f2f9eb3e40ebf8

Revert D20408831: [Lite Interpreter] Operator registration migrate fr…

586481a

…om manual to selective build Test Plan: revert-hammer Differential Revision: D20408831 Original commit changeset: ec75dd762c46 fbshipit-source-id: f1874088a5970dd220cc027d0020ab6223b9bd93

Revert D20964368: Revert D20408831: [Lite Interpreter] Operator regis…

a91097b

…tration migrate from manual to selective build Test Plan: revert-hammer Differential Revision: D20964368 Original commit changeset: f1874088a597 fbshipit-source-id: d9317ed97a98e2b04c190785b5564536b1096282

Correct a ValueError in dataloader to TypeError (pytorch#36244)

817e4f9

Summary: Pull Request resolved: pytorch#36244 Differential Revision: D20963949 Pulled By: ezyang fbshipit-source-id: 8c6aa4831021788052269e7aa8282d11eba4e085

[RELAND] Add __torch_function__ benchmarks (pytorch#36138)

7c825ba

Summary: Re-land of pytorch#35530 and pytorch#34645 Pull Request resolved: pytorch#36138 Differential Revision: D20893770 Pulled By: ezyang fbshipit-source-id: 75ab688a086f5fb87412a853df5246c0c39704ca

vkuzo and others added 21 commits April 16, 2020 18:18

Revert D21080503: [pytorch][PR] [quant] Add backward compatiblity test

f00014b

Test Plan: revert-hammer Differential Revision: D21080503 Original commit changeset: 1dca08208bcc fbshipit-source-id: 5cd8c22130ff28b9231f657f80961e94b65b5792

[pytorch][PR] Re-enable a failing test (pytorch#36763)

b5483b8

Summary: Pull Request resolved: pytorch#36763 Differential Revision: D21083309 Pulled By: Krovatkin fbshipit-source-id: 4fb5b95bd3e01bd83a406d4394f266d7fd168f21

Move unboxing for factory ops to after dispatch (pytorch#36564)

a89d1ed

Summary: Pull Request resolved: pytorch#36564 - ghstack-source-id: 102292162 Test Plan: waitforsandcastle Differential Revision: D21014324 fbshipit-source-id: 5b95eafbb668bed174cd2c826e308e74e329f552

Fixes clang format (pytorch#36787)

b45b967

Summary: Fixes clang format. Pull Request resolved: pytorch#36787 Differential Revision: D21084603 Pulled By: mruberry fbshipit-source-id: 7e29da135f9a2aa126cb68640e33c1914fd570e3

Make trivial thread-idx for degenerate statements without thread-idx. (…

32bbf12

…pytorch#36480) Summary: Pull Request resolved: pytorch#36480 Test Plan: Imported from OSS Differential Revision: D20992505 Pulled By: zheng-xq fbshipit-source-id: 3d4e5401b59b9507b5f2db659e511bd1af53f5ab

Vectorize reduction when reducing on fastest striding dimension (pyto…

d92005f

…rch#36709) Summary: Pull Request resolved: pytorch#36709 Test Plan: Imported from OSS Differential Revision: D21083393 Pulled By: ngimel fbshipit-source-id: ea3f7f29709c9a6e5b3ec45ba809cb2cf6c5e0c8

zasdfgbnm approved these changes Apr 17, 2020

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jjsjann123 merged commit d92005f into master Apr 17, 2020

csarofeen deleted the cs_master branch May 17, 2020 14:10

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