detail::getCUDAHooks().initCUDA() triggers SEGV

Hi All,

I have C++ module subclass torch::nn::Module. I built the module into

MNISTImpl::MNISTImpl() {
conv1_ = register_module(“conv1_”,
torch::nn::Conv2d(torch::nn::Conv2dOptions(1, 6, 5).stride(1)));
pool1_ = register_module(“pool1_”, torch::nn::AvgPool2d(torch::nn::AvgPool2dOptions(2).stride(2)));
conv2_ = register_module(“conv2_”, torch::nn::Conv2d(torch::nn::Conv2dOptions(6, 16, 5).stride(1)));
pool2_ = register_module(“pool2_”, torch::nn::AvgPool2d(torch::nn::AvgPool2dOptions(2).stride(2)));
fc1_ = register_module(“fc1_”, torch::nn::Linear(400, 120));
fc2_ = register_module(“fc2_”, torch::nn::Linear(120, 84));
fc3_ = register_module(“fc3_”, torch::nn::Linear(84, 10));

Then from another project’s build script, I link,

// Grab GPU if available
torch::Device device(torch::kCPU);
if (torch::cuda::is_available()) {
device = torch::Device(torch::kCUDA, 0);


myMNIST->to(device) triggers SEGV exception. The stacktrace is

#1 0x00007fc8029ca181 in std::unique_ptr<THCState, void ()(THCState)>::reset (
this=0x7fc7fef36c58 at::globalContext()::globalContext_+24,
__p=0x7fc7f8ce40f0 at::Context::Context():{lambda(THHState*)#2}::_FUN(THHState*))
at …/gcc-7.4.0/bin/…/include/c++/7.4.0/bits/unique_ptr.h:376
#2 0x00007fc8029c9e82 in std::unique_ptr<THCState, void ()(THCState)>::operator= (
this=0x7fc7fef36c58 at::globalContext()::globalContext_+24, __u=…)
at …/gcc-7.4.0/bin/…/include/c++/7.4.0/bits/unique_ptr.h:283
#3 0x00007fc8029c4064 in at::Context::lazyInitCUDA()::{lambda()#1}::operator()() const (this=0x7fc8091bd150)
** at …/pytorch/torch/include/ATen/Context.h:74**
#4 0x00007fc8029d7def in std::__invoke_impl<void, at::Context::lazyInitCUDA()::{lambda()#1}>(std::__invoke_other, at::Context::lazyInitCUDA()::{lambda()#1}&&) (__f=…)
at …/gcc-7.4.0/bin/…/include/c++/7.4.0/bits/invoke.h:60

Frame 3 shows

(gdb) f 3
#3 0x00007fc8029c4064 in at::Context::lazyInitCUDA()::{lambda()#1}::operator()() const (this=0x7fc8091bd150)
at …/pytorch/torch/include/ATen/Context.h:74
74 thc_state = detail::getCUDAHooks().initCUDA();

It seems that torch::Device(torch::kCUDA, 0) tries to initiate CUDA again and fails.

My questions are:

  1. Why does the second CUDA initialization, myMNIST->to(device), inside a .so fail why the caller of such .so has initialized CUDA already device = torch::Device(torch::kCUDA, 0);?
  2. How can I pass a flag to torch so that myMNIST->to(device) would not call call initCUDA() again?

Thank you very much.

Which libtorch version are you using?
Also, could you share an executable project so that we could reproduce this issue?

Hello @ptrblck,
I built libtorch from source with tag v1.6.0.
If the caller program does not trigger CUDA, i.e. device = torch::Device(torch::kCPU);, then myMNIST->to(device) is a no-op.
And the caller program finishes without an issue.

Let me call the caller program main and the MNIST library I have google tests built along side of and all the tests including ones engaging CUDA pass.

main build script links with -lmodule. I wonder whether main is built with different libstdc++ (and/or other runtime libraries) from what is built upon. So far, I can’t verify such theory yet.

Would you please suggest anything else?

A minimal project to reproduce this issue would be very welcome, as I don’t know what can cause this issue.