Segmentation fault

[LeonardoLed]

Hi there:
I also tried install from another computer and I managed to install the gcn. With python 3.6, but at the moment when I want to run demo :

python main.py --model gcn --gpu 0

My terminal shows this problem:

# python main.py --model gcn --gpu 0
GCN(
(model): Sequential(
(0): GConv(1, 10, kernel_size=(4, 5, 5), stride=(1, 1), padding=(2, 2), bias=False)
(1): BatchNorm2d(40, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(2): ReLU(inplace)
(3): GConv(10, 20, kernel_size=(4, 5, 5), stride=(1, 1), padding=(2, 2), bias=False)
(4): BatchNorm2d(80, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(5): ReLU(inplace)
(6): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
(7): GConv(20, 40, kernel_size=(4, 5, 5), stride=(1, 1), bias=False)
(8): BatchNorm2d(160, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(9): ReLU(inplace)
(10): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
(11): GConv(40, 80, kernel_size=(4, 5, 5), stride=(1, 1), bias=False)
(12): BatchNorm2d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(13): ReLU(inplace)
)
(fc1): Linear(in_features=80, out_features=1024, bias=True)
(relu): ReLU(inplace)
(dropout): Dropout(p=0.5)
(fc2): Linear(in_features=1024, out_features=10, bias=True)
)
/home/deeplearninglapi/Gabor_CNN_PyTorch/gcn/layers/GConv.py:67: TracerWarning: Converting a tensor to a Python index might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
for i in range(x.size(1)):
Segmentation fault (core dumped)

I searched out what is the meaning of "Segmentation fault" but I didn't find the real problem. Do you know what the problem is about?

Thanks a lot