ReassuredTiger98 , I played with it myself a little bit - It looks like this happens for me when an experiment is running and reporting images and changing metric does the trick - i.e reproduces it. Maybe open a github issue to follow this 🙂 ?

Hi @<1670964701451784192:profile|SteepSquid49> , that sounds like the correct setup 🙂
What were you thinking of improving or do you have some pain points in your current setup?

How would the ec2 instance get the custom package code to it?

From the looks of this example this should be connected automatically actually
https://github.com/allegroai/clearml/blob/master/examples/frameworks/hydra/hydra_example.py

Hi JitteryCoyote63 , I think this is what you're looking for:
https://clear.ml/docs/latest/docs/references/sdk/task#move_to_project

Can you try with Task.connect() ?
https://clear.ml/docs/latest/docs/references/sdk/task#connect

You'll need to assign an agent to run on the queue, something like this: 'clearml-agent daemon -- foreground --queue services'

You ran the same exact command for agent one with --docker and one without --docker and the one without managed to reach the files?

Can you try running it via agent without the docker?

Happy to help 🙂

Hi @<1750327622178443264:profile|CleanOwl48> , you need to set the output_uri in Task.init() for example to True to upload to the files server or to a string if you want to use s3 for example

Hi @<1747428509627715584:profile|CumbersomeDuck6> , are you using a self hosted server?

ReassuredTiger98 , Hi 🙂

Which version of clearml-agent are you using? Do you get the same result if you manually kill the docker container by force?

Hi @<1631102016807768064:profile|ZanySealion18> , I think this is what you're looking for:
None

Hi @<1749965229388730368:profile|UnevenDeer21> , can you add the log of the job that failed?

Also, note that you can set these arguments from the webUI on the task level itself as well, Execution tab and then container section

MelancholyElk85 , fair point 🙂

How do you initialize your tasks?

Hi @<1794901326925139968:profile|SpicyShark55> ,you have it as part of the open source as code - None

Hi @<1643060818490691584:profile|MagnificentHedgehong41> , did you specify a project name? You can go into settings and enable showing hidden projects/experiments and then you will be able to see the pipeline steps in projects as well

Can you hit F12 on the browser and see what happens in the network area when you're trying to delete?

The DataOps feature will abstract your usage of data - None

Hi @<1634001106403069952:profile|DefeatedMole42> , the Pro plan is monthly payment according to usage. You can find more information here - None

It looks as it is running, did the status of the experiment change?

Hi @<1749602873152376832:profile|EncouragingSquid4> , Welcome!
To address your questions:

• I think you can do routing for them but you'd have to set it up.
• I assume the models are being saved to the files server. Can you share a screenshot?

I'm not quite sure I understand. Is this from the clearml-agent?

How are you currently trying to wrap it up in python?

RoughTiger69 , you can also use Task.add_requirements  for a specific package through the script

Example: Task.add_requirements('tensorflow', '2.4.0') Example: Task.add_requirements('tensorflow', '>=2.4') Example: Task.add_requirements('tensorflow') -> use the installed tensorflow version Example: Task.add_requirements('tensorflow', '') -> no version limit

https://clear.ml/docs/latest/docs/references/sdk/model_outputmodel/#update_weights

I think this is what you're looking for then - None
Task.add_requirements

Hi @<1714813627506102272:profile|CheekyDolphin49> , how are you setting the parameter in the HPO?

Pipelines have id's, you can try using a pipeline ID. I think it should work