Hi SmallDeer34
Can you see it in TB ? and if so where ?

I think you cannot change it for a running process, do you want me to check for you if this can be done ?

Notice that if you pass string it will split it based on spaces

any idea why i cannot selected text inside the table?

Ichh, seems again like plotly 😞 I have to admit quite annoying to me as well ... I would vote here: None

it fails but with COMPLETED status

Which Task is marked "completed" the pipeline Task or the Step ?

Hmm HandsomeGiraffe70
This seem like a bug, let me see what we can do about that 🙂
could it be the parent version was created with an older version of clearml sdk ?

try: trains-init config

@<1523705099182936064:profile|GrievingDeer61> if you see them in your Tensorboard they will be captured in ClearML as well.
wdyt?

EDIT
examples (tensorboard or tensorboardX):
None
None

Hi @<1545216070686609408:profile|EnthusiasticCow4>
Oh dear, I think this argument is not exposed 😞

• You can open a GH
• If you want to add a PR this is very simple:None

include_archived=False,
):
   if not include_archived:
        system_tags = ["__$all", cls.__tag, "__$not", "archived"]
    else:
        system_tags = [cls.__tag]

...
   system_tag...

It seems the code is trying to access an s3 bucket, could that be the case? PanickyMoth78 any chance you can post the full execution log? (Feel free to DM so it won't end up being public)

task=Task.current_task()
Will get me the task object. (right?)

PanickyMoth78 yes, always, from anywhere, this is a singleton object 🙂

Have to get glue setup, which I couldn’t understand fully, so that’s a different topic

I suggest using the apply template setup (basically you provide a Job/Service template, and it uses that to setup k8s jobs based on the Tasks coming in from the specific queue)

but when I removed output_uri from Task.init, the pickled model has path

file:///Users/luca/path/to/pickle.file

When you run the job on the k8s pod?

Hi UnevenDolphin73 , are those per user/project/system environment variables ?
If these are secrets (that you do not want to expose), maybe it is best just to have them on he agent's machine ?

BTW, I think there is some "vault" support in the paid tiers for these kind of secret, not sure on which level (i.e. user/system/project)

Is it not possible to serve a model with preprocessing pipeline from scikit-learn using clearml-serving?

of course it is, did you first try the example , here: None
If you need to run your own LogisticRegression call you can use this example:
None
Notice this is where the custom endpoint actually calls the prediction: [None](https...

Hi @<1743079861380976640:profile|HighKitten20>

but when I try to use code stored in a GIT (Bitbucket) repo I got a repository cloning error, specifically

did you pass configure the git repo application/pass here: None

Most likely yes, but I don't see how clearml would have an impact here, I am more inclined to think it would be a pytorch dataloader issue, although I don't see why

These are most certainly dataloader process. But clearml-agent when killing the process should also kill all subprocesses, and it might be there is something going on that prenets it from killing the subprocesses ...

Is this easily reproducible ? Can you verify it is still the case with the latest RC of clearml-agent ?

Interesting, do you think you could PR a "fixed" version ?
https://github.com/allegroai/clearml-web/blob/2b6aa6043c3f36e3349c6fe7235b77a3fddd[…]app/webapp-common/shared/single-graph/single-graph.component.ts

Month +- 🙂

FileNotFoundError: [Errno 2] No such file or directory: 'tritonserver': 'tritonserver'

This is oddd.
Can you retry with the latest from the github ?
pip install git+

OutrageousSheep60 before I can answer, maybe you can explain why "zipping" them does not fit your workfow ?

okay that makes sense, if this is the case I would just use clearml-agent execute --id <task_id here> to continue the training Task.
Do notice you have to reload your last chekcpoint from the Task's models/artifacts to continue 🙂
Last question, what is the HPO optimization algorithm, is it just grid/random search or optuna hbop/optuna, if this is the later, how do make it "continue" ?

This is sitting on top of the serving engine itself, acting a s a control plane.
Integration with GKE is being worked on (basically KFServing as the serving engine)

DepressedChimpanzee34 I cannot find cfg.py here
https://github.com/allegroai/clearml/tree/master/examples/frameworks/hydra/config_files
(or anywhere else)

LOL EnormousWorm79 you should have a "do not show again" option, no?

How would one do this? Do I just share a link to the experiment, like

See "Share" in the right click menu on the experiment

I solved the issue by implementing my own ClearML logger

This is awesome! any chance you want to PR it to transformers ?

As long as the ~/.aws is configured, I "think" it should work. (I'm assuming you are referring IAM roles?)
I would also suggest using the latest aws_autoscaler (basically it adds a CLI wizard, I think the functionality is very much the same)

Hi SourOx12
How do you set the iteration when you continue the experiment? is it with Task.init continue_last_task ?

Hi ZippySheep23

Any ideas what might be happening?

I think you passed the upload limit (2.36 GB) 🙂