The solution of problem about: no module named 'enclib_cpu' or no module named 'enclib_gpu'

If you want to solve this problem, you can follow this reference: https://zhuanlan.zhihu.com/p/191314560
To be specific, you can get 'enclib_cpu.so' or 'enclib_gpu.so' by 'build.ninja' in '/site-packages/encoding/lib/cpu' or '/site-packages/encoding/lib/gpu'.
But in this process, I met a new problem: nvcc fatal: Unsupported gpu architecture 'compute_86'
One widely-used solution is to set environment variables to reduce computing power requirements.
e.g. export TORCH_CUDA_ARCH_LIST="7.5"
CUDA 10.1 does not support compute_86, while CUDA 10.1 supports compute_75 at most.
I failed again. This solution was not worked.
My final solution is edit the 'build.ninja': change '-gencode arch=compute_86, code=sm_86' into '-gencode arch=compute_75, code=sm_75'
I got it!
Hope my experience is helpful for ones struggling the same problem.

note:
My environment settings: Ubuntu 20.04 CUDA 10.1 python=3.6 torch=1.4.1
There are many problems for configuring pytorch-encoding in Windows system, in my experience. So the successful configuration may be easier in Linux or mac.

Start by reviewing the build.ninja files under site-packages/encoding/lib/cpu and site-packages/encoding/lib/gpu, then check how the CUDA architecture is selected for the reported Ubuntu, CUDA 10.1, Python 3.6, and PyTorch 1.4.1 environment. Reproduce the nvcc compute_86 failure and determine whether the supported architecture setting or the workaround should be documented.