Torch.cuda.is_available() returns False even CUDA is installed

Any update on this ?

I made a completly fresh install:

conda create -n myenv python=3.8
conda activate myenv
conda install pytorch torchvision torchaudio pytorch-cuda=11.7 -c pytorch -c nvidia

and still have the issue:

>> python3.8 -c 'import torch; print(torch.backends.cudnn.enabled)'
True
>> python3.8 -c 'import torch; print(torch.cuda.is_available())'
/path_to/myenv/lib/python3.8/site-packages/torch/cuda/__init__.py:88: UserWarning: CUDA initialization: CUDA driver initialization failed, you might not have a CUDA gpu. (Triggered internally at /opt/conda/conda-bld/pytorch_1666642975312/work/c10/cuda/CUDAFunctions.cpp:109.)
  return torch._C._cuda_getDeviceCount() > 0

Some useful command outputs:

>> nvidia-smi
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 515.57       Driver Version: 515.57       CUDA Version: 11.7     |
|-------------------------------+----------------------+----------------------+
| 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  NVIDIA A100 80G...  Off  | 00000000:CA:00.0 Off |                   On |
| N/A   38C    P0    65W / 300W |      0MiB / 81920MiB |     N/A      Default |
|                               |                      |              Enabled |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| MIG devices:                                                                |
+------------------+----------------------+-----------+-----------------------+
| GPU  GI  CI  MIG |         Memory-Usage |        Vol|         Shared        |
|      ID  ID  Dev |           BAR1-Usage | SM     Unc| CE  ENC  DEC  OFA  JPG|
|                  |                      |        ECC|                       |
|==================+======================+===========+=======================|
|  No MIG devices found                                                       |
+-----------------------------------------------------------------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+
>> nvcc -V
Copyright (c) 2005-2022 NVIDIA Corporation
Built on Wed_Jun__8_16:49:14_PDT_2022
Cuda compilation tools, release 11.7, V11.7.99
Build cuda_11.7.r11.7/compiler.31442593_0

Finally:

>> python3.8 -m torch.utils.collect_env
Collecting environment information...
/path_to/myenv/lib/python3.8/site-packages/torch/cuda/__init__.py:88: UserWarning: CUDA initialization: CUDA driver initialization failed, you might not have a CUDA gpu. (Triggered internally at /opt/conda/conda-bld/pytorch_1666642975312/work/c10/cuda/CUDAFunctions.cpp:109.)
  return torch._C._cuda_getDeviceCount() > 0
PyTorch version: 1.13.0
Is debug build: False
CUDA used to build PyTorch: 11.7
ROCM used to build PyTorch: N/A

OS: Scientific Linux release 7.9 (Nitrogen) (x86_64)
GCC version: (GCC) 6.3.0
Clang version: Could not collect
CMake version: version 2.8.12.2
Libc version: glibc-2.17

Python version: 3.8.5 | packaged by conda-forge | (default, Sep 24 2020, 16:55:52)  [GCC 7.5.0] (64-bit runtime)
Python platform: Linux-3.10.0-1160.76.1.el7.x86_64-x86_64-with-glibc2.10
Is CUDA available: False
CUDA runtime version: 11.7.99
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: GPU 0: NVIDIA A100 80GB PCIe
Nvidia driver version: 515.57
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] numpy==1.23.4
[pip3] torch==1.13.0
[pip3] torchaudio==0.13.0
[pip3] torchvision==0.14.0
[conda] blas                      1.0                         mkl
[conda] ffmpeg                    4.3                  hf484d3e_0    pytorch
[conda] mkl                       2021.4.0           h06a4308_640
[conda] mkl-service               2.4.0            py38h7f8727e_0
[conda] mkl_fft                   1.3.1            py38hd3c417c_0
[conda] mkl_random                1.2.2            py38h51133e4_0
[conda] numpy                     1.23.4           py38h14f4228_0
[conda] numpy-base                1.23.4           py38h31eccc5_0
[conda] pytorch                   1.13.0          py3.8_cuda11.7_cudnn8.5.0_0    pytorch
[conda] pytorch-cuda              11.7                 h67b0de4_0    pytorch
[conda] pytorch-mutex             1.0                        cuda    pytorch
[conda] torchaudio                0.13.0               py38_cu117    pytorch
[conda] torchvision               0.14.0               py38_cu117    pytorch

Any help would be much appreciated !