GPU Error with PyTorch in Virtual Machine

I am trying to use GPU in a virtual machine with PyTorch.

Running following PyTorch functions to check the availability of the GPU:


results in the following output:
GRID V100S-16C
<torch.cuda.device object at 0x7f7e596bdb80>
GRID V100S-16C

Furthermore, Nvidia-smi prints the following:

Sun Sep  3 17:00:29 2023       
| NVIDIA-SMI 450.142.00   Driver Version: 450.142.00   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  GRID V100S-16C      On   | 00000000:02:02.0 Off |                  N/A |
| N/A   N/A    P0    N/A /  N/A |   1104MiB / 16384MiB |      0%      Default |
|                               |                      |                  N/A |
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|  No running processes found                                                 |

Running the following code:

import torch

torch.ones((1, 1)).to('cuda')

results in the following error message:

RuntimeError Traceback (most recent call last)
Cell In[3], line 3
1 import torch
----> 3 torch.ones((1, 1)).to(‘cuda’)

RuntimeError: CUDA error: CUDA-capable device(s) is/are busy or unavailable
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
Compile with TORCH_USE_CUDA_DSA to enable device-side assertions.

I tried to set CUDA_LAUNCH_BLOCKING=1 but the error still occurs and the error message remains the same.

Do you have any idea what the problem might be and how I can fix it? Please let me know if further information is required to be able to understand my problem. Thanks in advance, Daniel.