Windows MingW64环境下，浮点模型推理报Segmentation Fault

[stephenlyu]

Git version: master head / commit:a9976c93c58afa9abe974d6b0fc9160a7bc7f0c3

系统: Windows 10, MingW64(gcc version 8.1.0 (x86_64-posix-sjlj-rev0, Built by MinGW-W64 project))

CMake命令

cmake -G Ninja -DCMAKE_SYSTEM_PROCESSOR=$PROCESSOR_ARCHITECTURE -DCMAKE_SYSTEM_NAME=Windows -DCMAKE_BUILD_TYPE=Debug ..

编译命令

ninja -j4

Crash Call Stack

Thread 1 received signal SIGSEGV, Segmentation fault.
0x000000006989571b in (anonymous namespace)::mm256_broadcastsi128_si256 (
addr=0x4d48000) at ../source/backend/cpu/x86_x64/avx/GemmFunction.hpp:14
14 return _mm256_broadcastsi128_si256(mm_loadu_si128(addr));
(gdb) bt
#0 0x000000006989571b in (anonymous namespace)::mm256_broadcastsi128_si256 (
addr=0x4d48000) at ../source/backend/cpu/x86_x64/avx/GemmFunction.hpp:14
#1 0x000000006987745d in _AVX_MNNPackedMatMul_2 (C=0x3e978d0, A=0x3f26634,
B=0x4d48000, parameter=0x4455de0)
at ../source/backend/cpu/x86_x64/avx/GemmFunction.hpp:435
#2 0x0000000069889505 in _AVX_MNNPackednMatMulRemainCommon (C=0x3e978d0,
A=0x3f26634, B=0x4d48000, eSize=2, parameter=0x4455de0, cache=0x0,
postParameters=0x0, bias=0x0)
at ../source/backend/cpu/x86_x64/avx/GemmFunction.hpp:636
#3 0x00000000698651ea in _AVX_MNNPackedMatMulRemainFMA (C=0x3e97800,
A=0x3f26600, B=0x4d48000, eSize=15, parameter=0x4455de0, cache=0x0,
postParameters=0x0, bias=0x0)
at ../source/backend/cpu/x86_x64/avx/GemmAVX2FMA.cpp:36
#4 0x000000006984ffa5 in MNNPackedMatMulRemain (C=0x3e97800, A=0x3f26600,
B=0x4d48000, eSize=15, parameter=0x4455de0, cache=0x0,
postParameters=0x0, bias=0x0)
at ../source/backend/cpu/x86_x64/FunctionDispatcher.cpp:191
#5 0x0000000069ae56a1 in MNN::ConvolutionWinograd::<lambda(int)>::operator()(int) const (__closure=0xa0f800, tId=0)
at ../source/backend/cpu/compute/ConvolutionWinograd.cpp:265
#6 0x0000000069ae4861 in MNN::ConvolutionWinograd::<lambda(int)>::operator()(int) const (__closure=0xa0f7d0, tId=0)
at ../source/backend/cpu/compute/ConvolutionWinograd.cpp:336
#7 0x0000000069a5e46a in std::_Function_handler<void(int), MNN::ConvolutionWinograd::onExecute(const std::vectorMNN::Tensor*&, const std::vectorMNN::Tensor*&)::<lambda(int)> >::_M_invoke(const std::_Any_data &, int &&) (
__functor=..., __args#0=@0xa0f768: 0)
at C:/msys64/mingw64/lib/gcc/x86_64-w64-mingw32/8.1.0/include/c++/bits/std_function.h:297
#8 0x0000000069a07f4a in std::function<void (int)>::operator()(int) const (
this=0xa0f7d0, __args#0=0)
at C:/msys64/mingw64/lib/gcc/x86_64-w64-mingw32/8.1.0/include/c++/bits/std_function.h:687
#9 0x000000006989a9fd in MNN::ThreadPool::enqueue(std::pair<std::function<void (int)>, int>&&, int) (task=..., index=-1)
at ../source/backend/cpu/ThreadPool.cpp:253
#10 0x00000000698d8fa3 in MNN::ConvolutionWinograd::onExecute (
this=0x4d47cc0, inputs=std::vector of length 1, capacity 1 = {...},
outputs=std::vector of length 1, capacity 1 = {...})
at ../source/backend/cpu/compute/ConvolutionWinograd.cpp:338
#11 0x0000000069959fcb in MNN::Pipeline::executeCallBack(std::function<bool (std::vector<MNN::Tensor*, std::allocatorMNN::Tensor* > const&, MNN::OperatorInfo const*)> const&, std::function<bool (std::vector<MNN::Tensor*, std::allocatorMNN::Tensor* > const&, MNN::OperatorInfo const*)> const&) (this=0x4474780,
before=..., after=...) at ../source/core/Pipeline.cpp:360
#12 0x00000000699eb5e1 in MNN::Session::runWithCallBack(std::function<bool (std::vector<MNN::Tensor*, std::allocatorMNN::Tensor* > const&, MNN::OperatorInfo const*)> const&, std::function<bool (std::vector<MNN::Tensor*, std::allocatorMNN::Tensor* > const&, MNN::OperatorInfo const*)> const&, bool) const (
this=0x1adbb0, before=..., end=..., sync=false)
at ../source/core/Session.cpp:109
#13 0x00000000699a8219 in MNN::Interpreter::runSessionWithCallBackInfo(MNN::Session const*, std::function<bool (std::vector<MNN::Tensor*, std::allocatorMNN::Tensor* > const&, MNN::OperatorInfo const*)> const&, std::function<bool (std::vector<MNN::Tensor*, std::allocatorMNN::Tensor* > const&, MNN::OperatorInfo const*)> const&, bool) const (this=0x4e8b8f0, session=0x1adbb0, before=...,
callBack=..., sync=false) at ../source/core/Interpreter.cpp:340
#14 0x0000000000463f4d in main (argc=4, argv=0x1a4400)
at ../tools/cpp/timeProfile.cpp:117

[wangzhaode]

请更新到最新版本