Thanks @<1523703472304689152:profile|UpsetTurkey67>
I'm pretty sure it has!
Let me check how we can merge it into the cleamrl-agent, sounds good?

Thanks EnviousStarfish54 we are working on moving them there!
BTW, in the mean time, please feel free to open GitHub issue under train, at least until they are moved (hopefully end of Sept).

GiddyPeacock64 and you see the kale (KF) jobs in the kubeflow UI ?

GiddyPeacock64 Are you sending the jobs from JupyterLab Kale extension ?

EDIT:
Is the pipeline step itself calling Task.init?

Hi @<1544853721739956224:profile|QuizzicalFox36>

http:/34.67.35.46:8081/...

notice there is a / missing in the link, how is that possible? it should be http://

Hi FancyWhale93 , in your clear.conf configure default output uri, you can specify the file server as default, or any object storage:
https://github.com/allegroai/clearml-agent/blob/9054ea37c2ef9152f8eca18ee4173893784c5f95/docs/clearml.conf#L409

Hi @<1691258563357315072:profile|ColorfulKitten60>
I think we need some context for this question 🙂

What do you have in the artifacts of this task id: 4a80b274007d4e969b71dd03c69d504c

(you can find it in the pipeline component page)

Yes that's the reason, basically there is a background thread analyzing the code, at the end of the execution if it is till running (hence the question regrading execution time) we give it extra 10seconds to come up with answers, otherwise we terminate, so the code won't get stuck. Makes sense to you?

BTW, VexedKangaroo32 are you using torch launch ?

UnsightlyShark53 See if this one solves the problem :)
BTW: the reasoning for the message is that when running the task with "trains-agent" if the parsing of the argparser happens before the the Task is initialized, the patching code doesn't know if it supposed to override the values. But this scenario was fixed a long time ago, and I think the error was mistakenly left behind...

Perhaps this is something that can be made clearer when updating the docu?

Hmm that is a good point, let's open a git issue and explain there, then update the docs, wdyt?

Alternatively I understand I can also run the agent using...

No you should not if you are running the agent inside a container it cannot work in docker mode and spin its own containers
Bottom line use clearml-agent daemon

I want to store only my raw data in my blob storage, and I want to create a Hyperdataset with all the artificats, metrics, frames,

Yes that's exactly how it works.
None

This line adds a reference to raw file (local/remote)
[https://github.com/allegroai/clearml/blob/1b474dc0b057b69c76bc2daa9eb8be927cb25efa[…]es/hyperdatasets/data-registration/register_dataset_wit...

and this link on it's own works?
if it does, open your browser dev tools (ctrl+shift+I on chrome, I think), I'm assuming you will see a few errors on CORS or the alike, paste them here

I notice that, in my Serving Service situated in the DevOps project, the "endpoints" section doesn't seem to get updated when I tag a new model with "released".

It takes it a few minutes (I think 5 min is the default) to update.
Notice that you need to add the model with

model auto-update --engine triton --endpoint "test_model_pytorch_auto" ...

Not with model add (if for some reason that does not work please let me know)
No need to pass the model version i.e. 1 you can ...

Check the links that are generated in the ui when you upload an artifact or model

odd message though ... it should have said something about boto3

First let's verify the conf:

from clearml.config import config_obj
import json
print(json.dumps(config_obj.get("sdk"), indent=2))

what are you getting

The azure section:
https://github.com/allegroai/trains/blob/master/docs/trains.conf#L117

What's the difference between the example pipeeline and this code ?
Could it be the "parents" argument ? what is it?

Also. finally the columns will be movable and re sizable, I can't wait for the next version ;)

SteadyFox10 could you try replacing the slash in the image name?

👍
Okay But we should definitely output an error on that

 are models technically 

Task

s and can they be treated as such? If not, how to delete a model permanently (both from the server and from AWS storage)?

When you call Task.delete() it actually goes over a;; the models/artifacts and deletes them from the storage

Is "project_name" diff for diff steps ? i.e. PipelineController(..., target_project='my_new_project') is not enough?

Hi MelancholyElk85

However, when I clone the pipeline from web UI and launch it once again, it works. Is there a way to bypass this?

In both cases, are you seeing a different behavior on the same machine running the agent (i.e. clonening from the UI vs code) ?

1633204289496 clearml-services DEBUG docker: invalid reference format.

This is the strange message, like the execution command is not valid...

what's the docker version?