PyTorch Torchvision models give NaN output

Autonomous Machines Jetson & Embedded Systems Jetson Nano
1

Hello,

The models provided in the Torchvision library of PyTorch give NaN output when performing inference with CUDA on the Jetson Nano (Jetpack 4.2). Code below to reproduce:

import torch
import torchvision
from torchvision.models import resnet18

net = resnet18(pretrained=True).eval().cuda()
input = torch.ones([1, 3, 48, 48]).cuda()
with torch.no_grad():
        output = net(input)
        print(output)

I’ve installed PyTorch and Torchvision using instructions found here: https://devtalk.nvidia.com/default/topic/1049071/jetson-nano/pytorch-for-jetson-nano/

Running the same code on the CPU gives a proper output.

Any help would be greatly appreciated!

2

Hi ristoojala, I believe the torchvision models were trained on image size of 224x224, except for Inception-v3 which was trained on 299x299. Does the model work if you use:

input = torch.ones([1, 3, 224, 224]).cuda()

Also the input data has normalization with mean subtraction and standard deviation applied, see here: https://discuss.pytorch.org/t/whats-the-range-of-the-input-value-desired-to-use-pretrained-resnet152-and-vgg19/1683

If you can’t get valid result, you might want to try loading an actual image with this same normalization applied. I’m able to use resnet18 model ok.

3

224x224 input does the trick. Thanks a bunch, I really appreciate your work here on the forums.

Weird that I am able to use a 48x48 input on my desktop.