I saw a strange behaviour on Google Colab. but I do not know why cuda/cudnn only causes Seg Fault. Is there any suggestion
Getting examples and compile and execute mnist.
!git clone http://github.com/pytorch/examples
!cd examples/cpp/mnist;cmake -DCMAKE_PREFIX_PATH=/usr/local/lib/python3.6/dist-packages/torch/lib/ -DTorch_DIR=/usr/local/lib/python3.6/dist-packages/torch/share/cmake/Torch/ ; make
!cd examples/cpp/mnist; ./mnist

Then CUDA cause generates following error.
CUDA available! Training on GPU.

snip

Train Epoch: 10 [59584/60000] Loss: 0.0707
Test set: Average loss: 0.0533 | Accuracy: 0.983
/bin/bash: line 1:  1084 Segmentation fault      (core dumped) ./mnist

For CPU case works fine.
Training on CPU.

snip

Train Epoch: 10 [59584/60000] Loss: 0.0773
Test set: Average loss: 0.0512 | Accuracy: 0.984

Is there any suggestion? (Jupyter notebook problem?)
Command line itself works fine on general terminal.