10分钟快速上手飞桨 paddle2 cuda10.2 python3.6环境问题

2.1.0
W1116 11:01:32.587469 17644 device_context.cc:404] Please NOTE: device: 0, GPU Compute Capability: 6.1, Driver API Version: 10.2, Runtime API Version: 10.2

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C++ Traceback (most recent call last):
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0   paddle::imperative::Tracer::TraceOp(std::string const&, paddle::imperative::NameVarBaseMap const&, paddle::imperative::NameVarBaseMap const&, paddle::framework::AttributeMap, paddle::platform::Place const&, bool, std::map<std::string, std::string, std::less<std::string >, std::allocator<std::pair<std::string const, std::string > > > const&)
1   paddle::imperative::PreparedOp::Prepare(paddle::imperative::NameVarBaseMap const&, paddle::imperative::NameVarBaseMap const&, paddle::framework::OperatorWithKernel const&, paddle::platform::Place const&, paddle::framework::AttributeMap const&)
2   paddle::imperative::PreparedOp paddle::imperative::PrepareImpl<paddle::imperative::VarBase>(paddle::imperative::details::NameVarMapTrait<paddle::imperative::VarBase>::Type const&, paddle::imperative::details::NameVarMapTrait<paddle::imperative::VarBase>::Type const&, paddle::framework::OperatorWithKernel const&, paddle::platform::Place const&, paddle::framework::AttributeMap const&)
3   paddle::platform::DeviceContextPool::Get(paddle::platform::Place const&)
4   std::__future_base::_Deferred_state<std::thread::_Invoker<std::tuple<paddle::platform::EmplaceDeviceContext<paddle::platform::CUDADeviceContext, paddle::platform::CUDAPlace>(std::map<paddle::platform::Place, std::shared_future<std::unique_ptr<paddle::platform::DeviceContext, std::default_delete<paddle::platform::DeviceContext> > >, std::less<paddle::platform::Place>, std::allocator<std::pair<paddle::platform::Place const, std::shared_future<std::unique_ptr<paddle::platform::DeviceContext, std::default_delete<paddle::platform::DeviceContext> > > > > >*, paddle::platform::Place)::{lambda()#1}> >, std::unique_ptr<paddle::platform::DeviceContext, std::default_delete<paddle::platform::DeviceContext> > >::_M_complete_async()
5   std::__future_base::_State_baseV2::_M_do_set(std::function<std::unique_ptr<std::__future_base::_Result_base, std::__future_base::_Result_base::_Deleter> ()>*, bool*)
6   std::_Function_handler<std::unique_ptr<std::__future_base::_Result_base, std::__future_base::_Result_base::_Deleter> (), std::__future_base::_Task_setter<std::unique_ptr<std::__future_base::_Result<std::unique_ptr<paddle::platform::DeviceContext, std::default_delete<paddle::platform::DeviceContext> > >, std::__future_base::_Result_base::_Deleter>, std::thread::_Invoker<std::tuple<paddle::platform::EmplaceDeviceContext<paddle::platform::CUDADeviceContext, paddle::platform::CUDAPlace>(std::map<paddle::platform::Place, std::shared_future<std::unique_ptr<paddle::platform::DeviceContext, std::default_delete<paddle::platform::DeviceContext> > >, std::less<paddle::platform::Place>, std::allocator<std::pair<paddle::platform::Place const, std::shared_future<std::unique_ptr<paddle::platform::DeviceContext, std::default_delete<paddle::platform::DeviceContext> > > > > >*, paddle::platform::Place)::{lambda()#1}> >, std::unique_ptr<paddle::platform::DeviceContext, std::default_delete<paddle::platform::DeviceContext> > > >::_M_invoke(std::_Any_data const&)
7   paddle::platform::CUDADeviceContext::CUDADeviceContext(paddle::platform::CUDAPlace)
8   std::call_once<paddle::platform::dynload::DynLoad__cudnnGetVersion::operator()<>()::{lambda()#1}>(std::once_flag&, paddle::platform::dynload::DynLoad__cudnnGetVersion::operator()<>()::{lambda()#1}&&)::{lambda()#2}::_FUN()
9   paddle::platform::dynload::GetCUDNNDsoHandle()
10  paddle::framework::SignalHandle(char const*, int)
11  paddle::platform::GetCurrentTraceBackString[abi:cxx11]()

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Error Message Summary:
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FatalError: `Access to an undefined portion of a memory object` is detected by the operating system.
  [TimeInfo: *** Aborted at 1637031692 (unix time) try "date -d @1637031692" if you are using GNU date ***]
  [SignalInfo: *** SIGBUS (@0x7fb8cc0beae0) received by PID 17644 (TID 0x7fb95a4e8700) from PID 18446744072837917408 ***]

Process finished with exit code 255

下载数据集那一步是没有问题的，但是在
mnist = paddle.nn.Sequential(
    paddle.nn.Flatten(),
    paddle.nn.Linear(784, 512),
    paddle.nn.ReLU(),
    paddle.nn.Dropout(0.2),
    paddle.nn.Linear(512, 10)
)
paddle.nn.Linear(784，512)这一步就会终端，报错结果如上所示。请问是什么问题呢？

GVP PaddlePaddle/Paddle

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GVPPaddlePaddle/Paddle

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