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I am trying to use the deformable convolutions from this repo on a Jetson TX2. Compilation was successful and I can also run them from Python. However, for every call of the DCN I get the following error: error in deformable_im2col: too many resources requested for launch
I was wondering if there are any setting in the .cu files that I can change to fix this error?
Minimal reproducible example
# Execute from parent directory of ops folderimporttorchfromops.dcnimportDeformConvPackdevice=torch.device('cuda')
dcn=DeformConvPack(in_channels=256,
out_channels=256,
kernel_size=(3, 3),
padding=1).to(device)
input=torch.Tensor(16, 256, 26, 20).to(device)
output=dcn(input)
Environment
Jetson TX2 with JetPack 4.3
Python 3.6.9
Pytorch 1.4
Torchvision 0.5
Since I only wanted to install DCNs instead of the whole repo, I used a reduced setup.py (copied from this repo):
Bug fix
After a quick search on Google I found this PyTorch issue which seems related. Unfortunately I have no experience with CUDA at all, so I am not sure if this helps.
The text was updated successfully, but these errors were encountered:
The regular convolutions of PyTorch do not seem to have this problem. Maybe the CUDA_NUM_THREADS constant could be set depending for which architecture the DCNs are built?
Thanks for your reporting! It is a known issue that setting CUDA_NUM_THREADS to 1024 causes the building failure on some old or lightweight devices. We have not found a good way to set it according to the gpu arch. PRs are welcome if you have any ideas.
I don't have any experience with PyTorch CUDA extensions, so I can't help with a PR unfortunately. But maybe just mention it in a README somewhere? That way people could easily fix the issue themselves.
Hi
I am trying to use the deformable convolutions from this repo on a Jetson TX2. Compilation was successful and I can also run them from Python. However, for every call of the DCN I get the following error:
error in deformable_im2col: too many resources requested for launch
I was wondering if there are any setting in the
.cu
files that I can change to fix this error?Minimal reproducible example
Environment
Since I only wanted to install DCNs instead of the whole repo, I used a reduced
setup.py
(copied from this repo):Bug fix
After a quick search on Google I found this PyTorch issue which seems related. Unfortunately I have no experience with CUDA at all, so I am not sure if this helps.
The text was updated successfully, but these errors were encountered: