This doesn't seem to be running inside a container...
What's the clearml-agent launch command you are using ? (i.e. do you have --docker flag)

how specifically I map my clearml.conf to the containers?

You add:

    volumes:
      - $HOME/clearml.conf:/root/clearml.conf

to here:
None
and here:
None

EnviousPanda91
in your clearml.conf I think you are missing a section
agent.git_user="" agent.git_pass="" agent.git_host="" agent.force_git_ssh_protocol: true

based on this one:
https://stackoverflow.com/questions/31436407/git-ls-remote-returns-fatal-no-remote-configured-to-list-refs-from
I think this is a specific issue of the local git repo configuration, can you verify
(btw: I tested with git 2.17.1 git ls-remote --get-url will return the remote url, without an error)

I specifically set is as empty with 

export_data['script']['requirements'] = {}

 in order not to reduce overhead during launch. I have everything installed inside the container

Do you have everything inside the container Inside a venv ?

Thanks GreasyPenguin66
How about:
!curlBTW, no need to rebuild the docker, next time you can always do !apt update && apt install -y <package here> 🙂

Hi DrabCockroach54
This seems like a pip issue trying to install from source, try upgrading the pip version and before installing numpy, it should solve it 🤞

pipe.start_locally() will run the DAG compute part on the same machine, where pipe.start() will start it on a remote worker (if it is not already running on a remote worker)
basically "pipe.start()" executed via an agent, will start the compute (no overhead)
does that help?

RobustSnake79 this one seems like scalar type graph + summary table, correct?
BTW: I'm not sure how to include the "Recommendation" part 🙂

yes 🙂

Hi @<1651395720067944448:profile|GiddyHedgehong81>

However I need for a yolov8 (Object detection with arround 20k jpgs and .txt files) the data.yaml file:

Just add the entire folder with your files to a dataset, then get it in your code
Add files (you can do that from CLI for example): None

clearml-data add --files my_folder_with_files

Then from code: [Non...

I guess I got confused since the color choices in

One of the most beloved features we added 🙂

I have a question regarding running the code on the remote machine, each time I run the code I see the console in the ClearML server start downloading all the libraries I used in the code and when I run another code the same thing happens so why it has to download all the libraries again and many times?

I'm assuming you are referring to the installation, the downloaded python packages are cached.
You can turn on full caching by uncommenting the following line:
https://github.com/alleg...

Hi WorriedParrot51
Take a look at the Experiment execution section:
there is script and working directory
working directory is the base of the git repository (which is cloned into the docker file)
So if for some reason trains did not properly detect the current working dir here is what should solve the issue, without changing the PYTHONPATH

script path: ./sub_folder/scripy.py working directory: .
What do you think?

LudicrousParrot69 you mean post execution or while you are executing the hyperparameter optimizer ?

why are there indefinitely growing anonymous tasks, even after i've closed the main schedulers.

The anonymous Tasks are The Dataset you are creating (a Dataset version is also a Task of a certain type with artifacts, the idea is usually Datasets are created from code, hence the need to combine the two).
Make sense ?

Yep, you are right

kubectl get pods -n {namespace} -o=JSONWhat are you getting when running the above on your cluster ?

Hi DisgustedDove53

Now for the clearml-session tasks, a port-forward should be done each time if I need to access the Jupyter notebook UI for example.

So basically this is why the k8s glue has --ports-mode.
Essentially you setup a k8s service (doing the ingest TCP ports) then the template.yaml that is used by the k8s glue should specify said service. Then the clearml-session knows how to access the actual pod, by a the parameters the k8s glue sets on the Task.
Make sense ?

😞 let me verify

. I’m using the default operation mode which uses kubectl run. Should I use templates and specify a service in there to be able to connect to the pods?

Ohh the default "kubectl run" does not support the "ports-mode" 😞

There’s a static number of pod which services are created for…

You got it! 🙂

Any reason not to do so in the conf file ?

Correct (with the port mapping service in it)

Okay yes, that's exactly the reason!! Cross origin blocks the file link

HugeArcticwolf77 actually it is more than that, you can embed the graphs now in the markdown, when you hove over any plot/graph/image you now have a new button that copies the embed test, so that you can directly copy it into your markdown editor (internal or external)
More documentation and screenshots are coming after the holiday, mean time you can check:
https://clear.ml/docs/latest/docs/webapp/webapp_reports
https://clear.ml/docs/latest/assets/images/webapp_report-695dddd2ec8064938bf8...

👍

Okay that kind of makes sense, now my followup question is how are you using the ASG? I mean the clearml autoscaler does not use it, so I just wonder on what the big picture, before we solve this little annoyance 🙂

Let me check if we can reproduce it

Are you suggesting the conf file did not set the default size? It sounds like a bug, can you verify?

well you can always do:
os.system('sed ...')🙂