GPU available in Tensorflow but not in Torch
I'm currently working on a server and I would like to be able the GPUs for PyTorch network training. I am not able to detect GPU by using torch but, if I use TensorFlow, I can detect both of the GPUs I am supposed to have. I suppose it's a problem with versions within PyTorch/TensorFlow and the CUDA versions on it.
However, after trying different versions of Pytorch, I am not still able to use them...
I am attaching the specificities of the GPUs and the current version of Tensorflow and Pytorch I am using. Does anyone have any hint on it? Would be very helpful.
| NVIDIA-SMI 4--.--.--    Driver Version: 465.19.01    CUDA Version: 11.3     |
|-------------------------------+----------------------+----------------------|
| 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 GeForce ...  On   | 00000000:02:00.0 Off |                  N/A |
| 27%   39C    P8    17W / 250W |      1MiB / 11176MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   1  NVIDIA GeForce ...  On   | 00000000:81:00.0 Off |                  N/A |
| 28%   45C    P8    11W / 250W |      1MiB / 11178MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+

$ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2020 NVIDIA Corporation
Built on Wed_Jul_22_19:09:09_PDT_2020
Cuda compilation tools, release 11.0, V11.0.221
Build cuda_11.0_bu.TC445_37.28845127_0

Torch version: 1.10.2
Tensorflow Version: 2.6.2
Cuda toolkit: 11.3.1
&gt;&gt;&gt; print('Number of GPUs: %d' % len(tf.config.list_physical_devices('GPU')))
Number of GPUs: 2

&gt;&gt;&gt; torch.cuda.is_available()
False

I am so lost... Thank you in advance!

I finally could resolve this problem by specifying the cuda version of pytorch... The combination of those specific versions was installing the CPU based version.
After installing the correct one, I have been able to use the GPU server without any problem.
