Just created a new deep learning server and am running into an issue running PyTorch code using CUDA. nvidia-smi gives seemingly correct output (below):
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 384.145                Driver Version: 384.145                   |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  TITAN Xp            Off  | 00000000:01:00.0 Off |                  N/A |
|  0%   38C    P0    58W / 250W |      0MiB / 12187MiB |      2%      Default |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID   Type   Process name                             Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+

However, when I run torch.cuda.is_available(), I get the following output:
Python 3.6.6 |Anaconda, Inc.| (default, Jun 28 2018, 17:14:51) 
[GCC 7.2.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> torch.cuda.is_available()
False

Any ideas as to what’s wrong? System information is below.


OS: Ubuntu 16.04


PyTorch Version: 0.4


PyTorch Installation Method: Conda


Python Version: 3.6.6


CUDA/cuDNN Version: 9.2/7.1


GPU Model: 1 NVIDIA Titan XP