Segmentation fault (core dumped)

❓ Questions & Help

Hi,

I implemented the program with reference to examples/pointnet2_classification.py and used Google Colablatory’s GPU to learn the model.

I save the model that I learned in Colab and try to call that model in Jetson Xavier NX to make an inference, I get the Segmentation fault (core dumped).

I ran the same code on the Jetson Nano, but in that case Segmentation fault (core dumped) did not occur.

I think I’m getting Segmentation fault (core dumped) when I run test().

How do I solve this problem?

Thanks!

Enviroment

$ uname -a
Linux Jetson Xavier NX 4.9.140-tegra #1 SMP PREEMPT Wed Apr 8 18:15:20 PDT 2020 aarch64 aarch64 aarch64 GNU/Linux

Device	Nano	Xavier NX
OS	Ubuntu 18.04	Ubuntu 18.04
Python	3.6.9	3.6.9
torch	1.4.0	1.4.0a0+7f73f1d
torch.version.cuda	10.0	10.2
nvcc -V	10.0	10.2
torch-scatter	2.0.4	2.0.4
torch-sparse	0.6.1	0.6.1
torch-cluster	1.5.4	1.5.4
torch-spline-conv	1.2.0	1.2.0
torch-geometric	1.4.3	1.4.3

$ pointnet++.py
load model
Test Acc: 0.9238
Segmentation fault (core dumped)

[rusty1s]

Yes, but do you know which operation in model(data) produces this error?

[KCSesh]

@Dave0995 Was any progress ever made on this?

This exact issue is showing for me, still.

self.cfx = cuda.Device(0).make_context() works in a stand alone script.

But it throws a segfault when another process is introduced.