Ohh I see, makes total sense. I'm assuming the code base itself can do both 🙂

Sorry that was a reply to:

Otherwise I could simply create these tasks with Task.init,

Hi JitteryCoyote63 , I have to admit, we have not thought of this scenario... what's the exact use case to clone a Task and change the type?

Obviously you can always change the task type, a bit of a hack but should work:
task._edit(type='testing')

I'm assuming the reason it fails is that the docker network is Only available for the specific docker compose. This means when you spin Another docker compose they do not share the same names. Just replace with host name or IP it should work. Notice this has nothing to do with clearml or serving these are docker network configurations

another option is the download fails (i.e. missing credentials on the client side, i.e. clearml.conf)

JitteryCoyote63 you mean? (notice no brackets)
task.update_requirements(".") Either pass a text or a list of lines:
The safest would be '\n'.join(all_req_lines)

Seems like credentials error
Do you have everything setup correctly in your ~/clearml.conf ?

Actually, dumb question: how do I set the setup script for a task?

When you clone/edit the Task in the UI, under Execution / Container you should have it
After you edit it, just push it into the execution with the autoscaler and wait 🙂

Sure, something like : https://github.com/feast-dev/feast

task = Task.get_task('task_id_here') task.mark_started(force=True) task.upload_artifact(..., wait_on_upload=True) task.mark_completed()

What's the error you are getting ?
(open the browser web developer, see if you get something on the console log)

logger.report_scalar("loss", "train", iteration=0, value=100)
logger.report_scalar("loss", "test", iteration=0, value=200)

Yes, or at least credentials and API...
Maybe inside your code you can later copy the model into fixed location ?
This way you have the model in the model repository and a copy in a fixed location (StorageManager can upload to a specific bucket/folder with the same credentials you already have)
Would that work?

should work as well 🙂

Hi CurvedHedgehog15
Yes you are correct, plots are displayed side-by-side in the ui. The reason is that since they are very generic, it is very challenging to actually be able to merge / overlay two arbitrary plots.
I can see two options

1. To allow user to combine two plots in the ui (this way the responsibility is on the user to understand this is possible
2. Maybe add programmatic interface to more easily access the raw data?
   Wdyt?

Also, How do I make the files other than entry script visible to the job?

The assumption for clearml (regradless on how you create a Task) is that you code is either a standlone script (or jupyter notebook) or inside a git repository. In case of a git repository cleamrl-agent will clone the git repository of the code, apply the uncommitted changes and run your code.

agree, but setting the agent’s env variable TMPDIR

I think this needs to be passed to the docker with -e TMPDIR=/new/tmp as additional container args:
see example
None
wdyt?

SmallAnt76
see https://clear.ml/pricing/ , under "What plan should I choose?"
what you are looking for is the first column "open-source". make sense ?

Yes, that sounds like the issue, is the file actually there ?

have a CI/CD (e.g Github Actions) thats update my “production” pipeline on ClearML UI,

I think this is the easiest way, basically the CI/CD launches a pipeline (which under the hood is another type of Task), by querying the latest "Published" pipeline that is also Not archived, then cloning+pushing it to execution queue.
In the UI when you want to "upgrade" the production pipeline you just right click "Publish" on the pipeline you want to launch. Another way is to do the same with Tags...

Is there a way to connect to the task without initiating a new one without overriding the execution?

You can, but not with automagic, you can manually send metrics/logs...
Does that help? or do we need the automagic?

We suddenly have a need to setup our logging after every

task.close()

Hmm that gives me a handle on things, any chance it is easily reproducible ?

Hi TightElk12

would like to understand the limitations of 

Task.current_task()

Basically this will always get you an instance of the current Task. This will work from sub-processes as well as the main process. Is there a specific scenario you have in mind, or a challenge with the use case ?

https://allegro.ai/clearml/docs/docs/faq/faq.html?highlight=clearml_config_file#clearml-configuration

👍

GrievingTurkey78 I have to admit I can't see the difference, can you help me out 🙂

MortifiedDove27
Nice!!!

Hmm SuccessfulKoala55 what do you think?

Is it possible to do something so that the change of the server address is supported and the pictures are pulled up on the new server from the new server?

The link itself (full link) is stored inside the server. Can I assume the access is IP based not host based (i.e. dns) ?

Hi @<1726410010763726848:profile|DistinctToad76>
Why not just report scalars, the x-axis you can use as "iterations" if this is a running in real time to collect the prompts.
If this is a summary then just report a scatter plot (you can also specify the names of the axis and the series)
None