AlphaPose/detector/nms/src/nms_kernel.cu:5:10: fatal error: THC/THC.h: No such file or directory 5 | #include <THC/THC.h>

[lucasjinreal]

For decent pytorch version 1.11 (maybe 1.10), this file removed:

AlphaPose/detector/nms/src/nms_kernel.cu:5:10: fatal error: THC/THC.h: No such file or directory
    5 | #include <THC/THC.h>

[Fang-Haoshu]

Oh... Did you manage to fix it?

[lucasjinreal]

No, I suggest using torchvision.ops.boxes.nms to do nms operation, however, which needs modification on detector. But since Alphapose already included that source code, it also worthy to modificate to standard way

[lucasjinreal]

Please using my fork version: it works on torch 1.11

https://github.com/jinfagang/AlphaPose

[peteruhrig]

I cloned your repo:

git clone https://github.com/jinfagang/AlphaPose.git

And then ran:

python3 setup.py build develop --user

And I get the same error message:

detector/nms/src/nms_kernel.cu:5:10: fatal error: THC/THC.h: No such file or directory
    5 | #include <THC/THC.h>
      |          ^~~~~~~~~~~
compilation terminated.
error: command '/usr/local/cuda/bin/nvcc' failed with exit status 1

Do I need to use a certain branch?

[peteruhrig]

And it turns out that this is a real show-stopper for A40 and A100 cards. They require CUDA 11.1 or higher, thus PyTorch 1.11 or higher, which does not contain the THC component any more. Thus, as of now, I don't see how to run AlphaPose on recent cards.

[yc-cui]

@jinfagang Still the same error. You didn't modify the code in detector/nms/src/nms_kernel.cu at branch master.

[yc-cui]

And it turns out that this is a real show-stopper for A40 and A100 cards. They require CUDA 11.1 or higher, thus PyTorch 1.11 or higher, which does not contain the THC component any more. Thus, as of now, I don't see how to run AlphaPose on recent cards.

@peteruhrig Any good suggestions?

[peteruhrig]

I don't speak C/C++ well enough, but my understanding is that it is possible to replace the functions used with ones that are still supported, as discussed here: https://www.exxactcorp.com/blog/Deep-Learning/pytorch-1-11-0-now-available (scroll down to the CUDA section) My guess is that this is not very difficult for someone who knows what they are doing, and maybe that is what @jinfagang did but forgot to push back to his repo, but I don't understand it enough to be able to do this myself.