Issue about installation of pointnet2_ops_lib

`TORCH_CUDA_ARCH_LIST`

Sometimes you may see an error message like this:

#11 [7/7] RUN pip install ./pointnet2_ops_lib        
#11 16.92   error: subprocess-exited-with-error      
#11 16.92                                            
#11 16.92   × python setup.py bdist_wheel did not run successfully.
#11 16.92   │ exit code: 1
#11 16.92   ╰─> [101 lines of output]
#11 16.92       No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda-12.4'
#11 16.92       running bdist_wheel

...
...
...

#11 16.92       /opt/conda/envs/HoLa-Brep/lib/python3.10/site-packages/torch/utils/cpp_extension.py:1965: UserWarning: TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation.
#11 16.92       If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'].

This error message indicates that the torch library could not find any CUDA hardware (the Docker context cannot locate CUDA hardware), resulting in the absence of any Compute Capabilities. Thus, you need to manually modify setup.py to ensure that the Docker image supports CUDA.

Please check line 19 in setup.py:

os.environ["TORCH_CUDA_ARCH_LIST"] = "3.7+PTX;5.0;6.0;6.1;6.2;7.0;7.5"

Use the command /usr/local/cuda-xx.x/nvcc --list-gpu-arch to check the GPU architecture supported by your GPUs. The output may look like this:

compute_50
compute_52
compute_53
compute_60
compute_61
compute_62
compute_70
compute_72
compute_75
compute_80
compute_86
compute_87
compute_89
compute_90

According to the results of this command, you can check your GPU's architecture name here. To specify the compute capabilities, this link will be helpful.

After specifying everything, you can edit line 19 in setup.py.

For instance, if your GPU is an Nvidia 4090.

os.environ["TORCH_CUDA_ARCH_LIST"] = "5.0;6.0;6.1;6.2;7.0;7.5;8.6;8.9;9.0"

You can check here and here for more details about TORCH_CUDA_ARCH_LIST