Or maybe there is a log with something more informative which I could check up

This way I would want to keep track of 3 OutputModel s and call update_weights 3 times every update - and probably do 2 redundant uploadings

is there a some sort of OutputModel.remove method? Docs say there isn't

I could insert some updated info to my conference talk if you share the recording by tomorrow morning 😄

Very nice for small pipelines (where every step could be put into a function in a single repository)

No, when I run the pipeline from the console on my local machine, it for some reason launches on clearml-services hostname (despite of the fact I specified the queue with the desired agent with pipe.set_default_execution_queue in my code)

More specifically, there are 2 tasks with almost identical docker commands. The only difference is the image itself. The task with one image works, and with another image it fails. Both images are valid images that lauch nicely on my laptop. Both images exist in the registry. Maybe you have some ideas what could possibly be wrong here?

Yes, it works, thank you! The question remains though: why docker containers won't launch on services

in order to work with ssh cloning, one has to manually install openssh-client to the docker image, looks like that

In short, what helped is
gitlab+deploy-tokenin gitlab url

for https cloning, deploy token is needed

AgitatedDove14 SuccessfulKoala55 maybe you know. How do I add files without uploading them anywhere?

Oh, I need to ask the guy who deployed it

There are some questions in this channel already regarding pipeline V2. Is there any tutorial or changelog or examples I can refer to?

add_files . There is no upload call, because add_files uploads files by itself, if I got it correctly

So now it works smoothly

(this is an answer to the previous message)

I don't think so. it is solved by installing openssh-client to the docker image or by adding deploy token to the cloning url in web ui

where is it in the docs?

ok, thanks

of course, I use custom images all the time, the question was how to do it for a pipeline 😆 setting private attributes directly doesn't look as good practice

I found out this happens with any other image except the default one, regardless of whether I set it with pipe._task.set_base_docker

The image is not needed to run the pipeline logic, I do it just to reduce overhead. Otherwise it would take too long to just build the default image on every launch

PipelineContoller._task.set_base_docker ?? :good-thinking:

I initialize tasks not as functions, but as scripts from different repositories, with different images

but the question was about the pipeline controller, not individual tasks.

After I set base docker for pipeline controller task, I cannot clone the repo...

cloning base tasks and modyfing their parameters

AgitatedDove14 by task you mean the training task or the separate task corresponding to the model itself? The former won't work since I don't want to delete the training task, only the models

AgitatedDove14 thank you. Maybe you know about OutputModel.remove method or something like that?