Last modified on 25 Sep 2020.
- Verify that your computer has a graphic card (NVIDIA):
lspci -nn | grep '\[03'
- Check the CUDA version on Ubuntu:
nvidia-smi. If have problems, check this note.
- Install the lates version: here.
Problem with CUDA version
For example, need to install corresponding versions:
pip3 install -U torch==1.2.0 pip3 install -U torchvision==0.4.0 pip3 install -U "pillow<7"
NVIDIA too old
The NVIDIA driver on your system is too old (found version 10010).
From this website, problem is solved by
- Switching from
- Restart the computer.
It works on Dell XPS 7950 whose GPU is NVIDIA GTX 1650.
🔅 RuntimeError: cuda runtime error (804) : forward compatibility was attempted on non supported HW at /pytorch/aten/src/THC/THCGeneral.cpp:47 (after update system including nvdia-cli, maybe): check this note.
import torch import torch.nn as nn import torch.nn.functional as F import torch.optim as optim
print('cuda is available? ', torch.cuda.is_available()) print('device_count: ', torch.cuda.device_count()) print('current device: ', torch.cuda.current_device()) print('device name: ', torch.cuda.get_device_name(0))
# Determine supported device def get_device(): if torch.cuda.is_available(): device = torch.device('cuda:0') # or something else else: device = torch.device('cpu') # don't have GPU return device
Convert DataFrame / Series to Tensor
def df_to_tensor(df): device = get_device() # see other section return torch.from_numpy(df.values).float().to(device)
•Notes with this notation aren't good enough. They are being updated. If you can see this, you are so smart. ;)