The error message is as follows,
>>> torch.cuda.is_available()
/home/yanjie/anaconda3/envs/sarah/lib/python3.7/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/conda/conda-bld/pytorch_1603729047590/work/c10/cuda/CUDAFunctions.cpp:100.)
  return torch._C._cuda_getDeviceCount() > 0
False

This error is really weird. I was able to use the CUDA in the morning. But somehow after rebooting, the error showed up. I created a new environment with conda but still cannot solve the problem. Based on the error message, I added export CUDA_VISIBLE_DEVICES=1 in the bashrc file but it didn’t help. I’ve also rebooted for infinity times.
############################################################################
The output of nvidia-smi is
±----------------------------------------------------------------------------+
| NVIDIA-SMI 450.119.03   Driver Version: 450.119.03   CUDA Version: 11.0     |
|-------------------------------±---------------------±---------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  GeForce RTX 207…  Off  | 00000000:08:00.0  On |                  N/A |
|  0%   36C    P8    26W / 215W |    276MiB /  7959MiB |      1%      Default |
|                               |                      |                  N/A |
±------------------------------±---------------------±---------------------+
±----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A       986      G   /usr/lib/xorg/Xorg                 53MiB |
|    0   N/A  N/A      1637      G   /usr/lib/xorg/Xorg                 80MiB |
|    0   N/A  N/A      1772      G   /usr/bin/gnome-shell              129MiB |
±----------------------------------------------------------------------------+
############################################################################
The output of nvcc -V is
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2020 NVIDIA Corporation
Built on Thu_Jun_11_22:26:38_PDT_2020
Cuda compilation tools, release 11.0, V11.0.194
Build cuda_11.0_bu.TC445_37.28540450_0
############################################################################
For more other information, I run the collect_env.py and the output is as follows,
Collecting environment information…
/home/yanjie/anaconda3/lib/python3.7/site-packages/torch/cuda/init.py:80: 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/conda/conda-bld/pytorch_1634272126608/work/c10/cuda/CUDAFunctions.cpp:112.)
return torch._C._cuda_getDeviceCount() > 0
PyTorch version: 1.10.0
Is debug build: False
CUDA used to build PyTorch: 10.2
ROCM used to build PyTorch: N/A
OS: Ubuntu 20.04 LTS (x86_64)
GCC version: (Ubuntu 9.3.0-17ubuntu1~20.04) 9.3.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.17
Python version: 3.7.11 (default, Jul 27 2021, 14:32:16)  [GCC 7.5.0] (64-bit runtime)
Python platform: Linux-5.11.0-38-generic-x86_64-with-debian-bullseye-sid
Is CUDA available: False
CUDA runtime version: 11.0.194
GPU models and configuration: GPU 0: GeForce RTX 2070 SUPER
Nvidia driver version: 450.119.03
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Versions of relevant libraries:
[pip3] mypy-extensions==0.4.3
[pip3] numpy==1.20.3
[pip3] numpydoc==1.1.0
[pip3] torch==1.10.0
[pip3] torchaudio==0.10.0
[pip3] torchvision==0.11.1
[conda] blas                      1.0                         mkl
[conda] cudatoolkit               10.2.89              hfd86e86_1
[conda] ffmpeg                    4.3                  hf484d3e_0    pytorch
[conda] mkl                       2021.3.0           h06a4308_520
[conda] mkl-service               2.4.0            py37h7f8727e_0
[conda] mkl_fft                   1.3.1            py37hd3c417c_0
[conda] mkl_random                1.2.2            py37h51133e4_0
[conda] mypy_extensions           0.4.3                    py37_0
[conda] numpy                     1.19.1                   pypi_0    pypi
[conda] numpy-base                1.20.3           py37h74d4b33_0
[conda] numpydoc                  1.1.0              pyhd3eb1b0_1
[conda] pytorch                   1.10.0          py3.7_cuda10.2_cudnn7.6.5_0    pytorch
[conda] pytorch-mutex             1.0                        cuda    pytorch
[conda] torch                     1.5.0                    pypi_0    pypi
[conda] torchaudio                0.10.0               py37_cu102    pytorch
[conda] torchvision               0.11.1               py37_cu102    pytorch
############################################################################
PS: In the morning, when everything is still workable, the runtime CUDA should be 10.1, the cudatoolkit should be 10.2 and the CUDA version shown in the nvidia-smi should be 11.0. I totally have no idea why a simple reboot can be so disastrous.
Thanks