It's seems you are are getting 401 unauthorized , is this the same domain? I'm assuming the issue the logged in cookie is not sent?

LittleShrimp86 what do you have in the Configuration Tab of the Cloned Pipeline?
(I think that it has empty configuration -> which means empty DAG, so it does nothing and leaves)

No worries 🙂

No sure what O'm seeing here

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

Ho @<1739818374189289472:profile|SourSpider22>
What are you trying to install, just the agent? if so pip install clearml-agent is all you need

Hi @<1557899668485050368:profile|FantasticSquid9>
There is some backwards compatibility issue with 1.2 (I think).
Basically what you need it to spin a new one on a new session ID and rergister the endpoints

Hi @<1545216070686609408:profile|EnthusiasticCow4>

is there a way to get the date from the InputModel?

You should be able to with model._get_model_data()
But I think we should have it all exposed, wdyt?

I ended up using 

task_overrides

 for every change, and this way I only need 2 tasks (a base task and a step task, thus I use 

clone_base_task=True

 and it works as expected - yay!)

Very cool!
BTW: you can also provide a function to create the entire Task, see base_task_factory argument in add_step

I think it's still an issue, not critical though, because we have another way to do it and it works

I could not reproduce it, I think the issue w...

Oh no 😞 I wonder if this is connected to:

Any chance the logger is running (or you have) from a subprocess ?

The problem is that even when I mount the SSH key into the root home directory (e.g.,

/root/.ssh/id_rsa

with the correct permissions set to 400) I still encounter the same error.

The agent automatically mount's the .ssh folder from the host into the container, making sure all the permissions are set,

how can I run

pip install -e .

in general the agent will add the "working" dir into the PYTHONPATH so that you should not have to manually do "-e ."
Tha...

Also, how do pipelines compare here?

Pipelines are a type of Task, so like Tasks you can clone and enqueue them, or set them as the target of the trigger.

the most flexible solution would be to have some way of triggering the execution of a script in the parent task environment,

This is the exact idea of the TriggerScheduler None
What am I missing here?

Hmm so yes that is true, if you are changing the bucket values you will have to manually also adjust it in grafana. I wonder if there is a shortcut here, the data is stored in Prometheus, and I would rather try to avoid deleting old data, Wdyt?

In order to facilitate the multiple credentials one must use the Clearml SDK obviously.

Yes 🙂

Hi @<1730033904972206080:profile|FantasticSeaurchin8>
You mean in the UI , or when reporting on the SDK?

It may have been killed or evicted or something after a day or 2.

Actually the ideal setup is to have a "services" pod running all these service on a single pod, with clearml-agent --services-mode. This Pod should always be on and pull jobs from a dedicated queue.
Maybe a nice way to do that is to have the single Task serialize itself, then have the a Pod run the Task every X hours and spin it down

So I would like to to know what it send to the server to create the task/pipeline, ...

MoodyCentipede68 can you post the full docker-compose log (from spinning it until you get the error?)
You can just pipe the output to a file with :
docker-compose ... up > log.txt

NICE! MoodyCentipede68 this is awesome 🙂

Well from the error it seems there is no layer called "dense" , hence triton failing to find the layer returning the reult. Does that make sense?

MoodyCentipede68 could it be that the model is on one account (workspace) and your credentials (the ones provided to the docker compose) are from another workspace?
The error itself point to the triton helper failing to get the model ID from the backend. The models are uploaded to a a specific workspace, and it looks like a mismatch (I.e. the model Id is nowhere to be found) wdyt?

WickedElephant66 this seems like a general network issue, like the docker service is missing your companies firewall certificate.
Can you pull any container from docker hub ?

TrickySheep9 Yes, let's do that!
How do you PR a change ?

I can't see any reason it should not work 😀

hurray 🎊

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)

DistressedGoat23 you are correct, since at the end this become a plotly object the extra_layout is for general purpose layout, but this specific entry is next to the data. Bottom line, can you open a github issue, so we do not forget to fix? In the mean time you can use the general plotly reporting as SweetBadger76 suggested

Hmm let me check, because I think it should have worked

SoggyBeetle95 is this secret a per Task secret, or is it for the agent itself (I.e. for all Tasks the agent will spin)?

Ohh, if this is the case then it kind of makes sense to store on the Task itself. Which means the Task object will have to store it, and then the UI will display it :(
I think the actual solution is a vault , per user, which would allow users to keep their credentials on the sever, the agent to pass those to the Task when it spins it, based on the user. Unfortunately the vault feature is only available on the paid/enterprise version ( with RBAC etc.).
Does that make sense?

SoggyBeetle95 the question is, where does clearml stores these arguments, and the answer is on the Task object (from there the agent will take them and apply to the docker execution). Now since all users see all the tasks, they also see these arguments. Wdyt?