Can we do training using CPU?

[Md Naimul Hasan]

Hi, thanks for the training code.
Can we train the code using cpu only?
What changes we need to make in that case?

[Md Naimul Hasan]

I get the error when run the following command: I'm using the repo in VMware which is why unable to use GPU
@mpc001 , looking forward to hearing from you.

CUDA_VISIBLE_DEVICES='' python3 main.py --config-path /home/ubuntu/TCN_LIPREADING_ROOT/Lipreading_using_Temporal_Convolutional_Networks/configs/lrw_resnet18_mstcn.json --annonation-direc /home/ubuntu/TCN_LIPREADING_ROOT/Lipreading_using_Temporal_Convolutional_Networks/LRW_data --data-dir /home/ubuntu/TCN_LIPREADING_ROOT/Lipreading_using_Temporal_Convolutional_Networks/datasets/visual_data
Model and log being saved in: ./train_logs/tcn/2022-04-14T18:30:41
Traceback (most recent call last):
File "main.py", line 261, in
main()
File "main.py", line 201, in main
model = get_model_from_json()
File "main.py", line 181, in get_model_from_json
model = Lipreading( modality=args.modality,
File "/home/ubuntu/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 688, in cuda
return self._apply(lambda t: t.cuda(device))
File "/home/ubuntu/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 578, in _apply
module._apply(fn)
File "/home/ubuntu/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 578, in _apply
module._apply(fn)
File "/home/ubuntu/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 578, in _apply
module._apply(fn)
[Previous line repeated 1 more time]
File "/home/ubuntu/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 601, in _apply
param_applied = fn(param)
File "/home/ubuntu/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 688, in
return self._apply(lambda t: t.cuda(device))
File "/home/ubuntu/.local/lib/python3.8/site-packages/torch/cuda/init.py", line 216, in _lazy_init
torch._C._cuda_init()
RuntimeError: The NVIDIA driver on your system is too old (found version 10010). Please update your GPU driver by downloading and installing a new version from the URL: http://www.nvidia.com/Download/index.aspx Alternatively, go to: https://pytorch.org to install a PyTorch version that has been compiled with your version of the CUDA driver.

[jingtian feng]

i use cpu to test just through delete all the ".cuda()" function in the main , but i can not bear the very very slow speed
hope to help you