Spaces:
Running
on
T4
Running
on
T4
| # 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](https://docs.nvidia.com/cuda/cuda-compiler-driver-nvcc/index.html#gpu-feature-list)**. To specify the compute capabilities, this **[link](https://developer.nvidia.com/cuda-gpus)** 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](https://pytorch.org/docs/stable/cpp_extension.html)** and **[here](https://github.com/pytorch/extension-cpp/issues/71)** for more details about `TORCH_CUDA_ARCH_LIST` |