How to test if installed torch is supported with CUDA

I finally installed CUDA 9.0 and PyTorch 1.0 from *.whl file to make it work on GTX 1070 ( torch.cuda.is_available returns True).

I want to see if the installation itself was with cuda not if cuda is available. How do I check that?

seems conda list works:

pytorch                   1.7.0           py3.8_cuda10.2.89_cudnn7.6.5_0    pytorch

though I wonder why pytorch things there is no gpu… :confused:

(automl-meta-learning) miranda9~/automl-meta-learning $ nvidia-smi
Wed Dec  2 10:25:39 2020       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.36.06    Driver Version: 450.36.06    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  TITAN Xp            Off  | 00000000:02:00.0 Off |                  N/A |
| 53%   83C    P2   256W / 250W |   9121MiB / 12196MiB |     89%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   1  TITAN Xp            Off  | 00000000:03:00.0 Off |                  N/A |
| 45%   70C    P2    70W / 250W |   4041MiB / 12196MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   2  TITAN Xp            Off  | 00000000:82:00.0 Off |                  N/A |
| 31%   45C    P8    12W / 250W |      2MiB / 12196MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   3  TITAN Xp            Off  | 00000000:83:00.0 Off |                  N/A |
| 32%   46C    P8    12W / 250W |      2MiB / 12196MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A     32361      C   python                           9119MiB |
|    1   N/A  N/A     24301      C   python                           4039MiB |
+-----------------------------------------------------------------------------+
(automl-meta-learning) miranda9~/automl-meta-learning $ python
Python 3.8.2 (default, Mar 26 2020, 15:53:00) 
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
torch>>> torch.cuda.is_available()
False

I will try to see if updating pytorch to use cuda 11 works since that seems to be a mistmatch.


update

that didn’t work…

pytorch                   1.7.0           py3.8_cuda11.0.221_cudnn8.0.3_0    pytorch
...
torchvision               0.8.1                py38_cu110    pytorch
...
(automl-meta-learning) miranda9~/automl-meta-learning $ nvidia-smi
Wed Dec  2 10:38:47 2020       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.36.06    Driver Version: 450.36.06    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  TITAN Xp            Off  | 00000000:02:00.0 Off |                  N/A |
| 53%   83C    P2   255W / 250W |   9121MiB / 12196MiB |     97%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   1  TITAN Xp            Off  | 00000000:03:00.0 Off |                  N/A |
| 49%   79C    P2   244W / 250W |   4041MiB / 12196MiB |     69%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   2  TITAN Xp            Off  | 00000000:82:00.0 Off |                  N/A |
| 23%   28C    P8     9W / 250W |      2MiB / 12196MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   3  TITAN Xp            Off  | 00000000:83:00.0 Off |                  N/A |
| 23%   33C    P8     9W / 250W |      2MiB / 12196MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A     32361      C   python                           9119MiB |
|    1   N/A  N/A     24301      C   python                           4039MiB |
+-----------------------------------------------------------------------------+
(automl-meta-learning) miranda9~/automl-meta-learning $ python
Python 3.8.2 (default, Mar 26 2020, 15:53:00) 
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
tor>>> torch.cuda.is_available()
False
>>>
1 Like

duh, need to get a interactive job indicating my interactive script:

condor_submit -i interactive.sub

opps dum mistake.

Request_gpus = 1
Request_cpus = 30
requirements = (CUDADeviceName != "Tesla K40m")
# requirements = (CUDADeviceName == "Quadro RTX 6000")
Queue