Hi @<1558986867771183104:profile|ShakyKangaroo32> , it seems that there is no such option to do that via the StorageManager class. Might be useful to have. Maybe open a GitHub feature request for this? Or maybe a pull request? 🙂
Here:
https://clear.ml/docs/latest/docs/configs/clearml_conf#agent-section
What you're looking for is this:sdk.development.default_output_uri
Also configure your api.files_server in ~/clearml.conf to point to your s3 bucket as well 🙂
If you run inside a repository, then yes
Hi AdventurousButterfly15 ,
When running code locally, how are the installed packages detected? Does it detect your entire venv or does it detect only the packages that were used?
What version of the server are you running? What version of the SDK also?
Can you add the full log + a snippet to reproduce this?
Does your image have ssh installed? Can you run ssh from inside the container?
Hi @<1745616566117994496:profile|FantasticGorilla16> , you can always increase disk space on the machine running the server. Another option is to manually delete indices in Elastic, although it would be highly unadvised.
You could also probably clear up space in the file server if it has been heavily used.
What version of ClearML-Serving are you using? Are you running on a self hosted server?
Hi @<1577468638728818688:profile|DelightfulArcticwolf22> , it looks like you're trying to update some parameter of a task after it finished running...
Hi @<1691983266761936896:profile|AstonishingOx62> , I'm not sure I understand what you're trying to do. You have some python code unrelated to ClearML. Does it run without issues? Did you afterwards add Task.init() to that code?
AbruptWorm50 , what optimization method are you using?
How would you use the
user properties
as part of an experiment?
I'm guessing to get the properties. I'm guessing this really depends on your needs / use-case
How are you saving the model?
Hi @<1535069219354316800:profile|PerplexedRaccoon19> , I think you can take the existing example of AWS and modify it to use the relevant API/sdk of another provider
You can disable automatic model logging using auto_connect_frameworks in Task.init()
https://clear.ml/docs/latest/docs/references/sdk/task#taskinit
This however will also disable automatic reporting of scalers. You can also manually force the upload of the final model with
https://clear.ml/docs/latest/docs/references/sdk/model_outputmodel#class-outputmodel
Hi @<1894195589248192512:profile|ClearElephant51> , I suggest sending another email. It might have been missed due to local Holidays
In that case then yes, install the agent on top of the machine with the A100 with 8 GPUs
Because that seems to be connected to data
Hi @<1581454875005292544:profile|SuccessfulOtter28> , you can archive an experiment, go into the archive and then you can delete from there
Hi @<1534706830800850944:profile|ZealousCoyote89> , can you please add the full log?
Hi UnevenDolphin73 , what are you trying to do when you get this? Are you running a self hosted server?
VexedCat68 , it looks like it is being saved locally. Are you running all from the same machine?
ExasperatedCrocodile76 , did you run the original experiment on linux machine with pip and the remote machine is linux with conda package manager?
Hi @<1539417873305309184:profile|DangerousMole43> , I would suggest opening developer tools (F12) and then doing the specific search you're interested in through the UI. Then you can simply send the same via the REST API
I don't think this the intended behavior. Can you please elaborate how it happens exactly?
For example doing a fresh installation of the previous version and using backup data so you have a fresh state. Then try to upgrade again.