I tried with the other solutions mentioned in similar posts but torch.cuda.is_available() is still returning false
nvida-smi
Thu Apr 29 22:56:44 2021
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.33.01    Driver Version: 440.33.01    CUDA Version: 10.2     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  GeForce GTX 108...  Off  | 00000000:04:00.0 Off |                  N/A |
| 34%   61C    P2    64W / 250W |   2398MiB / 11176MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   1  GeForce GTX 108...  Off  | 00000000:05:00.0 Off |                  N/A |
| 35%   60C    P2    74W / 250W |   9587MiB / 11178MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   2  GeForce GTX 108...  Off  | 00000000:08:00.0 Off |                  N/A |
| 18%   58C    P2    62W / 250W |   6621MiB / 11178MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   3  GeForce GTX 108...  Off  | 00000000:0A:00.0 Off |                  N/A |
| 47%   80C    P2   239W / 250W |  10687MiB / 11178MiB |     96%      Default |
+-------------------------------+----------------------+----------------------+
|   4  GeForce GTX 108...  Off  | 00000000:85:00.0 Off |                  N/A |
|  0%   91C    P2   156W / 250W |   9647MiB / 11178MiB |     97%      Default |
+-------------------------------+----------------------+----------------------+
|   5  GeForce GTX 108...  Off  | 00000000:86:00.0 Off |                  N/A |
| 37%   63C    P2    63W / 250W |   9087MiB / 11178MiB |     16%      Default |
+-------------------------------+----------------------+----------------------+
|   6  GeForce GTX 108...  Off  | 00000000:89:00.0 Off |                  N/A |
| 28%   50C    P2    64W / 250W |   9747MiB / 11178MiB |     19%      Default |
+-------------------------------+----------------------+----------------------+
|   7  GeForce GTX 108...  Off  | 00000000:8A:00.0 Off |                  N/A |
|  0%   37C    P8    10W / 250W |     10MiB / 11178MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+


python collect_env.py yields the following information:


Collecting environment information...
PyTorch version: 1.8.1
Is debug build: False
CUDA used to build PyTorch: 10.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 16.04.3 LTS (x86_64)
GCC version: (Ubuntu 5.4.0-6ubuntu1~16.04.12) 5.4.0 20160609
Clang version: Could not collect
CMake version: version 3.5.1

Python version: 3.7 (64-bit runtime)
Is CUDA available: False
CUDA runtime version: 10.2.89
GPU models and configuration:
GPU 0: GeForce GTX 1080 Ti
GPU 1: GeForce GTX 1080 Ti
GPU 2: GeForce GTX 1080 Ti
GPU 3: GeForce GTX 1080 Ti
GPU 4: GeForce GTX 1080 Ti
GPU 5: GeForce GTX 1080 Ti
GPU 6: GeForce GTX 1080 Ti
GPU 7: GeForce GTX 1080 Ti

Nvidia driver version: 440.33.01
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A

Versions of relevant libraries:
[pip3] numpy==1.20.1
[pip3] torch==1.8.1
[pip3] torchvision==0.9.1
[conda] blas                      1.0                         mkl
[conda] cudatoolkit               10.1.243             h6bb024c_0
[conda] ffmpeg                    4.3                  hf484d3e_0    pytorch
[conda] mkl                       2021.2.0           h06a4308_296
[conda] mkl-service               2.3.0            py37h27cfd23_1
[conda] mkl_fft                   1.3.0            py37h42c9631_2
[conda] mkl_random                1.2.1            py37ha9443f7_2
[conda] numpy                     1.20.1           py37h93e21f0_0
[conda] numpy-base                1.20.1           py37h7d8b39e_0
[conda] pytorch                   1.8.1           py3.7_cuda10.1_cudnn7.6.3_0    pytorch
[conda] torchvision               0.9.1                py37_cu101    pytorch

```nvcc --version```

Copyright (c) 2005-2019 NVIDIA Corporation
Built on Wed_Oct_23_19:24:38_PDT_2019
Cuda compilation tools, release 10.2, V10.2.89


python -c ‘import torch;print(torch.cuda.is_available())’
False

Tried Conda remove pytorch and reinstalled, but the problem persists. Unable to use ‘Cuda’