Could you please help me with this github issue?
Could you please suggest how I should fix this problem?
(torchenc) mona@goku:~$ python test_torch_encoding.py
/home/mona/venv/torchenc/lib/python3.8/site-packages/torch/cuda/__init__.py:52: UserWarning: CUDA initialization: CUDA unknown error - this may be due to an incorrectly set up environment, e.g. changing env variable CUDA_VISIBLE_DEVICES after program start. Setting the available devices to be zero. (Triggered internally at /pytorch/c10/cuda/CUDAFunctions.cpp:100.)
return torch._C._cuda_getDeviceCount() > 0
Traceback (most recent call last):
File "test_torch_encoding.py", line 5, in <module>
model = encoding.models.get_model('DeepLab_ResNeSt269_PContext', pretrained=True).cuda()
File "/home/mona/venv/torchenc/lib/python3.8/site-packages/torch/nn/modules/module.py", line 463, in cuda
return self._apply(lambda t: t.cuda(device))
File "/home/mona/venv/torchenc/lib/python3.8/site-packages/torch/nn/modules/module.py", line 359, in _apply
module._apply(fn)
File "/home/mona/venv/torchenc/lib/python3.8/site-packages/torch/nn/modules/module.py", line 359, in _apply
module._apply(fn)
File "/home/mona/venv/torchenc/lib/python3.8/site-packages/torch/nn/modules/module.py", line 359, in _apply
module._apply(fn)
File "/home/mona/venv/torchenc/lib/python3.8/site-packages/torch/nn/modules/module.py", line 381, in _apply
param_applied = fn(param)
File "/home/mona/venv/torchenc/lib/python3.8/site-packages/torch/nn/modules/module.py", line 463, in <lambda>
return self._apply(lambda t: t.cuda(device))
File "/home/mona/venv/torchenc/lib/python3.8/site-packages/torch/cuda/__init__.py", line 172, in _lazy_init
torch._C._cuda_init()
RuntimeError: CUDA unknown error - this may be due to an incorrectly set up environment, e.g. changing env variable CUDA_VISIBLE_DEVICES after program start. Setting the available devices to be zero.
(torchenc) mona@goku:~$ echo $CUDA_VISIBLE_DEVICES
(torchenc) mona@goku:~$ nvidia-smi
Sat Jan 30 00:44:47 2021
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 460.32.03 Driver Version: 460.32.03 CUDA Version: 11.2 |
|-------------------------------+----------------------+----------------------+
| 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 GeForce GTX 165... Off | 00000000:01:00.0 Off | N/A |
| N/A 47C P8 3W / N/A | 1695MiB / 3911MiB | 7% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 1155 G /usr/lib/xorg/Xorg 133MiB |
| 0 N/A N/A 1773 G /usr/lib/xorg/Xorg 1124MiB |
| 0 N/A N/A 1952 G /usr/bin/gnome-shell 130MiB |
| 0 N/A N/A 2329 G ...gAAAAAAAAA --shared-files 167MiB |
| 0 N/A N/A 2735 G /usr/lib/firefox/firefox 3MiB |
| 0 N/A N/A 2923 G /usr/lib/firefox/firefox 1MiB |
| 0 N/A N/A 3204 G /usr/lib/firefox/firefox 1MiB |
| 0 N/A N/A 3324 G /usr/lib/firefox/firefox 1MiB |
| 0 N/A N/A 3456 G /usr/lib/firefox/firefox 1MiB |
| 0 N/A N/A 3501 G /usr/lib/firefox/firefox 1MiB |
| 0 N/A N/A 3572 G /usr/lib/firefox/firefox 1MiB |
| 0 N/A N/A 3623 G /usr/lib/firefox/firefox 3MiB |
| 0 N/A N/A 21024 G ...f_3837.log --shared-files 99MiB |
+-----------------------------------------------------------------------------+
(torchenc) mona@goku:~$
The code as in your Website:
import torch
import encoding
# Get the model
model = encoding.models.get_model('DeepLab_ResNeSt269_PContext', pretrained=True).cuda()
model.eval()
# Prepare the image
url = 'https://github.com/zhanghang1989/image-data/blob/master/' + \
'encoding/segmentation/pcontext/2010_001829_org.jpg?raw=true'
filename = 'example.jpg'
img = encoding.utils.load_image(encoding.utils.download(url, filename)).cuda().unsqueeze(0)
# Make prediction
output = model.evaluate(img)
predict = torch.max(output, 1)[1].cpu().numpy() + 1
# Get color pallete for visualization
mask = encoding.utils.get_mask_pallete(predict, 'pascal_voc')
mask.save('output.png')