None
See: Add an experiment hyperparameter:
and add gpu : True

well I do not think you set your pytorch lightining to use cuda:

GPU available: True (cuda), used: False
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
/code/.venv/lib/python3.9/site-packages/lightning/pytorch/trainer/setup.py:176: PossibleUserWarning: GPU available but not used. Set `accelerator` and `devices` using `Trainer(accelerator='gpu', devices=1)`.

@<1523701205467926528:profile|AgitatedDove14> Is there any reason why you mentioned that the "correct" way to work with python and containers is to actually install everything on the system (not venv)?

I've added gpu:True to my hydra config file but the GPU is still not used

Click on the Task it is running and abort it, it seems to be stuck, I guess this is why the others are not pulled

That's the right place but
like you would use hydra --override, which in your case I think it should be "accelerator.gpu" ,

You can also change allow_omegaconf_editin the UI to True, and then you could just edit the OmegaConf in the UI (if you do not changeallow_omegaconf_edit` then the edit in the UI is ignored)

but it still not is able to run any task after I abort and rerun another task

When you "run" a task you are pushing it to a queue, so how come a queue is empty? what happens after you push your newly cloned task to the queue ?

@<1597762318140182528:profile|EnchantingPenguin77> can you provide the full log?