RuntimeError: a view of a leaf Variable that requires grad is being used in an in-place operation.

[quva-lab]

RuntimeError: a view of a leaf Variable that requires grad is being used in an in-place operation.

[Gabri95]

Hi @SunHaozhe

Unfortunately, I can not test the library with Pytorch 1.8 on CUDA at the moment.

However, looking at your code, I think you can fix the runtime error in the title by using for example
gnn.init.generalized_he_init(conv.weights.data, conv.basisexpansion)
instead of
gnn.init.generalized_he_init(conv.weights, conv.basisexpansion)

The problem is that the weight initialization methods operate in-place (like PyTorch's ones).
I see that PyTorch uses with torch.no_grad() inside the init methods, so maybe I should do the same.

I need to think a bit more about this to make sure it wouldn't cause other problems, but in the meantime you can use the trick above to solve your issue.

Regarding the second issue, I ran the script you mentioned on a machine without GPU (I used my own conda environment with PyTorch 1.8) but I didn't encounter any issue.
However, note that generate_synthetic_data assumes you have a GPU since it explicitly uses .to('cuda').
That means that you need to remove that stametement from your code if you want to run it on CPU.

Let me know if this solves your issues

Best,
Gabriele

[SunHaozhe]

Thanks a lot for your reply! I indeed solved the issue by switching to a machine with CUDA and the correct PyTorch version. This issue can be helpful for everyone who encounter the same problem (if any) :)