Nick/dynamic shapes experiment #3
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wconstab
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Sep 22, 2021
| self_lazy_tensor.CreateFrom(ir::MakeNode<ir::ops::DynamicSize>( | ||
| self_lazy_tensor.GetIrValue()))); | ||
| }); | ||
| m.def("_add_dim", |
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i didn't anticipate that add_dim was dynamic. the 'dim' constant is the dynamic part, i guess? but how c ome there isn't any special handling of the 'dim' argument in this API?
Krovatkin
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Oct 6, 2021
Summary: Pull Request resolved: pytorch#66009 Fixes ``` test_trace_c10_ops (jit.test_tracer.TestTracer) ... third-party-buck/platform009/build/eigen/include/Eigen/src/Core/Block.h:374:24: runtime error: applying non-zero offset 4 to null pointer #0 0x7f5228f72227 in Eigen::internal::BlockImpl_dense<Eigen::Map<Eigen::Array<float, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, false, true>::BlockImpl_dense(Eigen::Map<Eigen::Array<float, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> >&, long, long, long, long) third-party-buck/platform009/build/eigen/include/Eigen/src/Core/Block.h:374 #1 0x7f5228f7212c in Eigen::BlockImpl<Eigen::Map<Eigen::Array<float, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, false, Eigen::Dense>::BlockImpl(Eigen::Map<Eigen::Array<float, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> >&, long, long, long, long) third-party-buck/platform009/build/eigen/include/Eigen/src/Core/Block.h:166 #2 0x7f5228f720dc in Eigen::Block<Eigen::Map<Eigen::Array<float, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, false>::Block(Eigen::Map<Eigen::Array<float, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> >&, long, long, long, long) third-party-buck/platform009/build/eigen/include/Eigen/src/Core/Block.h:142 #3 0x7f5229b0e059 in Eigen::DenseBase<Eigen::Map<Eigen::Array<float, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::FixedBlockXpr<internal::get_fixed_value<int>::value, internal::get_fixed_value<long>::value>::Type Eigen::DenseBase<Eigen::Map<Eigen::Array<float, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::block<int, long>(long, long, int, long) third-party-buck/platform009/build/eigen/include/Eigen/src/Core/../plugins/BlockMethods.h:98 #4 0x7f5229b0c5ca in caffe2::GenerateProposalsOp<caffe2::CPUContext>::RunOnDevice() caffe2/caffe2/operators/generate_proposals_op.cc:348 ``` Also cleans up some data type and const issues around the area. Test Plan: Sandcastle Reviewed By: xush6528 Differential Revision: D31343046 fbshipit-source-id: fd9096c8e47a0aad529c72fd313f64ca98dcb80b
Krovatkin
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Oct 6, 2021
Summary: Pull Request resolved: pytorch#66060 Fixes ``` testTumHistoryAdditionalLaser (caffe2.caffe2.fb.layers.tests.tum_history_test.TestTumHistory) ... caffe2/caffe2/operators/concat_split_op.h:363:74: runtime error: applying non-zero offset 8 to null pointer #0 0x7f8f39d29795 in caffe2::ConcatOp<caffe2::CPUContext>::RunOnDevice() caffe2/caffe2/operators/concat_split_op.h:363 #1 0x7f8f39c4978d in caffe2::Operator<caffe2::CPUContext>::Run(int) caffe2/caffe2/core/operator.h:987 #2 0x7f8f381fe9c9 in caffe2::SimpleNet::Run() caffe2/caffe2/core/net_simple.cc:67 #3 0x7f8f38ee488e in caffe2::Workspace::RunNet(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) caffe2/caffe2/core/workspace.cc:289 ``` Test Plan: Sandcastle Reviewed By: dzhulgakov, xush6528 Differential Revision: D31366205 fbshipit-source-id: 566aa519677c9d371189e4b1f81d595732861efc
Krovatkin
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Jun 1, 2022
…78136) This prevents `import torch` accidentally crash on machines with no metal devices Should prevent crashes reported in pytorch#77662 (comment) and https://github.com/pytorch/functorch/runs/6560056366?check_suite_focus=true Backtrace to the crash: ``` (lldb) bt * thread #1, stop reason = signal SIGSTOP * frame #0: 0x00007fff7202be57 libobjc.A.dylib`objc_msgSend + 23 frame #1: 0x000000010fd9f524 libtorch_cpu.dylib`at::mps::HeapAllocator::MPSHeapAllocatorImpl::MPSHeapAllocatorImpl() + 436 frame #2: 0x000000010fda011d libtorch_cpu.dylib`_GLOBAL__sub_I_MPSAllocator.mm + 125 frame #3: 0x000000010ada81e3 dyld`ImageLoaderMachO::doModInitFunctions(ImageLoader::LinkContext const&) + 535 frame #4: 0x000000010ada85ee dyld`ImageLoaderMachO::doInitialization(ImageLoader::LinkContext const&) + 40(lldb) up frame #1: 0x000000010fd9f524 libtorch_cpu.dylib`at::mps::HeapAllocator::MPSHeapAllocatorImpl::MPSHeapAllocatorImpl() + 436 libtorch_cpu.dylib`at::mps::HeapAllocator::MPSHeapAllocatorImpl::MPSHeapAllocatorImpl: -> 0x10fd9f524 <+436>: movq %rax, 0x1b0(%rbx) 0x10fd9f52b <+443>: movw $0x0, 0x1b8(%rbx) 0x10fd9f534 <+452>: addq $0x8, %rsp 0x10fd9f538 <+456>: popq %rbx (lldb) disassemble ... 0x10fd9f514 <+420>: movq 0xf19ad15(%rip), %rsi ; "maxBufferLength" 0x10fd9f51b <+427>: movq %r14, %rdi 0x10fd9f51e <+430>: callq *0xeaa326c(%rip) ; (void *)0x00007fff7202be40: objc_msgSend ``` which corresponds to `[m_device maxBufferLength]` call, where `m_device` is not initialized in https://github.com/pytorch/pytorch/blob/2ae3c59e4bcb8e6e75b4a942cacc2d338c88e609/aten/src/ATen/mps/MPSAllocator.h#L171 Pull Request resolved: pytorch#78136 Approved by: https://github.com/seemethere
Krovatkin
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… 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 pytorch#5: <unknown function> + 0x1b5334 (0x5652bdab9334 in ./test_deploy) frame pytorch#6: <unknown function> + 0x1b4f3e (0x5652bdab8f3e in ./test_deploy) frame pytorch#7: <unknown function> + 0x1b519b (0x5652bdab919b in ./test_deploy) frame pytorch#8: loadSearchFile(char const*) + 0x23e (0x7f3ba62f37f8 in /tmp/torch_deploy9ATEFg) frame pytorch#9: deploy_set_self + 0x51 (0x7f3ba62f38f9 in /tmp/torch_deploy9ATEFg) frame pytorch#10: torch::deploy::Interpreter::Interpreter(torch::deploy::InterpreterManager*, std::shared_ptr<torch::deploy::Environment>) + 0x274 (0x5652bdaaa790 in ./test_deploy) frame pytorch#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 pytorch#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 pytorch#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 pytorch#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 pytorch#15: torch::deploy::InterpreterManager::InterpreterManager(unsigned long, std::shared_ptr<torch::deploy::Environment>) + 0x123 (0x5652bdaa83b1 in ./test_deploy) frame pytorch#16: TorchpyTest_InitTwice_Test::TestBody() + 0x65 (0x5652bda075a9 in ./test_deploy) frame pytorch#17: void testing::internal::HandleSehExceptionsInMethodIfSupported<testing::Test, void>(testing::Test*, void (testing::Test::*)(), char const*) + 0x65 (0x5652bda944b7 in ./test_deploy) frame pytorch#18: void testing::internal::HandleExceptionsInMethodIfSupported<testing::Test, void>(testing::Test*, void (testing::Test::*)(), char const*) + 0x5a (0x5652bda8cfe7 in ./test_deploy) frame pytorch#19: testing::Test::Run() + 0x100 (0x5652bda68622 in ./test_deploy) frame pytorch#20: testing::TestInfo::Run() + 0x10f (0x5652bda68fb3 in ./test_deploy) frame pytorch#21: testing::TestSuite::Run() + 0x121 (0x5652bda6980d in ./test_deploy) frame pytorch#22: testing::internal::UnitTestImpl::RunAllTests() + 0x38e (0x5652bda756e6 in ./test_deploy) frame pytorch#23: bool testing::internal::HandleSehExceptionsInMethodIfSupported<testing::internal::UnitTestImpl, bool>(testing::internal::UnitTestImpl*, bool (testing::internal::UnitTestImpl::*)(), char const*) + 0x65 (0x5652bda9586b in ./test_deploy) frame pytorch#24: bool testing::internal::HandleExceptionsInMethodIfSupported<testing::internal::UnitTestImpl, bool>(testing::internal::UnitTestImpl*, bool (testing::internal::UnitTestImpl::*)(), char const*) + 0x5a (0x5652bda8e0f7 in ./test_deploy) frame pytorch#25: testing::UnitTest::Run() + 0xc9 (0x5652bda73fd1 in ./test_deploy) frame pytorch#26: RUN_ALL_TESTS() + 0x11 (0x5652bda169fa in ./test_deploy) frame pytorch#27: main + 0x27 (0x5652bda10ce2 in ./test_deploy) frame pytorch#28: <unknown function> + 0x2d310 (0x7f3bc0431310 in /usr/lib/libc.so.6) frame pytorch#29: __libc_start_main + 0x81 (0x7f3bc04313c1 in /usr/lib/libc.so.6) frame pytorch#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
Krovatkin
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Jun 7, 2022
… to conform with non-quantized countertpart filenames Summary: Names of analogous files in quantized directory (previously snake case) were inconsistent with their non-quantized filename counterparts (pascal case). This is the first of a series of PRs that changes all files in quantized (and sub-directories) dir to have pascal case. `aten/src/ATen/native/quantized/qconv_unpack.cpp` has not been renamed yet because (for reasons currently unknown) after making the name change, `import torch` produces the below error (`qlinear_unpack.cpp` renaming also seems to fail some phabricator CI tests for similar reasons). We suspect that these may be undefined errors and will revisit naming these files in a future PR. ``` terminate called after throwing an instance of 'c10::Error' what(): Type c10::intrusive_ptr<ConvPackedParamsBase<2> > could not be converted to any of the known types. Exception raised from operator() at ../aten/src/ATen/core/jit_type.h:1735 (most recent call first): frame #0: c10::Error::Error(c10::SourceLocation, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >) + 0x55 (0x7f26745c0c65 in /data/users/dzdang/pytorch/torch/lib/libc10.so) frame #1: c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) + 0xb1 (0x7f26745bdcd1 in /data/users/dzdang/pytorch/torch/lib/libc10.so) frame #2: <unknown function> + 0x1494e24 (0x7f2663b14e24 in /data/users/dzdang/pytorch/torch/lib/libtorch_cpu.so) frame #3: <unknown function> + 0xfed0bc (0x7f266366d0bc in /data/users/dzdang/pytorch/torch/lib/libtorch_cpu.so) frame #4: c10::detail::infer_schema::make_function_schema(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >&&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >&&, c10::ArrayRef<c10::detail::infer_schema::ArgumentDef>, c10::ArrayRef<c10::detail::infer_schema::ArgumentDef>) + 0x5a (0x7f266366d71a in /data/users/dzdang/pytorch/torch/lib/libtorch_cpu.so) frame pytorch#5: c10::detail::infer_schema::make_function_schema(c10::ArrayRef<c10::detail::infer_schema::ArgumentDef>, c10::ArrayRef<c10::detail::infer_schema::ArgumentDef>) + 0x7b (0x7f266366e06b in /data/users/dzdang/pytorch/torch/lib/libtorch_cpu.so) frame pytorch#6: <unknown function> + 0x1493f32 (0x7f2663b13f32 in /data/users/dzdang/pytorch/torch/lib/libtorch_cpu.so) frame pytorch#7: <unknown function> + 0xe227dd (0x7f26634a27dd in /data/users/dzdang/pytorch/torch/lib/libtorch_cpu.so) frame pytorch#8: <unknown function> + 0x14e0a (0x7f268c934e0a in /lib64/ld-linux-x86-64.so.2) ..........................truncated............. ``` Test Plan: ``` python test/test_quantization.py ``` Pull Request resolved: pytorch#77037 Approved by: https://github.com/jerryzh168
Krovatkin
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Jul 28, 2022
### Summary: This PR implements PTQ for APoT FakeQuant. It runs models (Resnet-18 pre-trained model, ImageNet dataset) to compare accuracy metrics for different qconfig settings of uniform vs. APoT quantized activation and weight. According to the collected accuracy stats, model #2 (uniform activation and APoT weight) appears to have a slight improvement in accuracy compared to model #1 (uniform activation and uniform weight) for 8-bit and significant improvement for 4-bit (see "Accuracy Stats" section below). ### Test Plan: Run models with: `python test/quantization/core/experimental/fx_graph_mode_apot.py` ### Accuracy Stats: 8-bit (Uniform int8, APoT b = 8 k = 2) **Model #1:** Uniform activation, uniform weight (FX Graph Mode quantized) Evaluation accuracy on test dataset: 64.43% (Top-1), 85.62% (Top-5) **Model #2:** Uniform activation, APoT weight (FX Graph Mode quantized) Evaluation accuracy on test dataset: 64.51% (Top-1), 85.78% (Top-5) **Model #3:** APoT activation, APoT weight (FX Graph Mode quantized) Evaluation accuracy on test dataset: 64.32% (Top-1), 85.78% (Top-5) 4-bit (Uniform int4, APoT b = 4 k = 2) **Model #1:** Uniform activation, uniform weight (FX Graph Mode quantized) Evaluation accuracy on test dataset: 45.63% (Top-1), 71.96% (Top-5) **Model #2:** Uniform activation, APoT weight (FX Graph Mode quantized) Evaluation accuracy on test dataset: 64.24% (Top-1), 85.56% (Top-5) **Model #3:** APoT activation, APoT weight (FX Graph Mode quantized) Evaluation accuracy on test dataset: 45.40% (Top-1), 76.21% (Top-5) **Full Precision model (FX Graph Mode quantized)** Evaluation accuracy on test dataset: 69.76% (Top-1), 89.08% (Top-5) **Eager mode quantized model** Evaluation accuracy on test dataset: 69.49% (Top-1), 88.90% (Top-5) Pull Request resolved: pytorch#81040 Approved by: https://github.com/jerryzh168
Krovatkin
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Aug 11, 2022
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 pytorch#5 0x00007fa6381cd6a9 in __cxa_throw () from /lib/x86_64-linux-gnu/libstdc++.so.6 pytorch#6 0x00007fa6381c42ce in std::__throw_invalid_argument(char const*) () from /lib/x86_64-linux-gnu/libstdc++.so.6 pytorch#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 pytorch#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 pytorch#9 caffe2::serialize::PyTorchStreamReader::init (this=this@entry=0x8c11ce0) at /pytorch_master/caffe2/serialize/inline_container.cc:145 pytorch#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 pytorch#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 pytorch#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 pytorch#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 pytorch#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 pytorch#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 pytorch#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 pytorch#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 pytorch#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 pytorch#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 pytorch#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 pytorch#21 0x00000000035b1d22 in torch::jit::load (filename="", device=device@entry=...) at /pytorch_master/torch/csrc/jit/serialization/import.cpp:424 pytorch#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
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