torch.cuda.is_available() is showing False. as is the tensorflow
Nvidia SMI output:
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 465.19.01 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 | 00000000:01:00.0 On | N/A |
| 0% 43C P8 13W / 260W | 1067MiB / 7979MiB | 26% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 2336 G /usr/lib/xorg/Xorg 102MiB |
| 0 N/A N/A 4822 G /usr/lib/xorg/Xorg 333MiB |
| 0 N/A N/A 5011 G /usr/bin/gnome-shell 56MiB |
| 0 N/A N/A 13415 G ...AAAAAAAAA= --shared-files 558MiB |
Doesn't seem to be any issues with cuda install? any ideas how to get this working within the stack? Pytorch version is 1.8 could this be the reason and how can we upgrade individual packages within the stack?
torch.cuda.is_available() is showing False. as is the tensorflow
Nvidia SMI output:
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 465.19.01 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 | 00000000:01:00.0 On | N/A |
| 0% 43C P8 13W / 260W | 1067MiB / 7979MiB | 26% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 2336 G /usr/lib/xorg/Xorg 102MiB |
| 0 N/A N/A 4822 G /usr/lib/xorg/Xorg 333MiB |
| 0 N/A N/A 5011 G /usr/bin/gnome-shell 56MiB |
| 0 N/A N/A 13415 G ...AAAAAAAAA= --shared-files 558MiB |
Doesn't seem to be any issues with cuda install? any ideas how to get this working within the stack? Pytorch version is 1.8 could this be the reason and how can we upgrade individual packages within the stack?