Can I compile a cuda compatible version of pytorch on a machine with no GPUs available?
I have access to a computer with high CPU count but no GPUs and was wanting to leverage it to compile PyTorch faster. I am compiling within an nvidia docker container which I am then using on my machine that has GPUs. nvidia-smi is returning the gpus properly nvcc seems to be working properly
But when I run torch.cuda.is_available() in python I get:
/opt/conda/envs/computer_vision/lib/python3.8/site-packages/torch/cuda/__init__.py:52: UserWarning: CUDA initialization: CUDA unknown error - this may be due to an incorrectly set up environment, e.g. changing env variable CUDA_VISIBLE_DEVICES after program start. Setting the available devices to be zero. (Triggered internally at  /opt/pytorch/c10/cuda/CUDAFunctions.cpp:100.)
  return torch._C._cuda_getDeviceCount() > 0


Any guidance?