Hi NastySeahorse61 ,

It looks like deleting smaller tasks didn't make much of a dent. Do you have any tasks that ran for very long or were very intensive on reporting to the server?

Not one known to me, also, it's a good practice to implement (Think of automation) 🙂

Hi @<1523704207914307584:profile|ObedientToad56> , the virtual env is constructed using the detected packages when run locally. You can certainly override that. For example use Task.add_requirements - None

There are also a few additional configurations in the agent section of clearml.conf I would suggest going over

SubstantialElk6 , do you mean compiling them into a language or calling certain functions from the wheel?

@<1544853721739956224:profile|QuizzicalFox36> , yes 🙂

Also how are you uploading? Because if you don't zip the folder and upload with
task.upload_artifact('local folder', artifact_object=os.path('<PATH_TO_FOLDER>'))
This should work

Does it enqueue the task? From what you posted it should simply create a task and then enqueue it without any further action

The "template" task

I suggest reading all of them, starting with pipeline from tasks 🙂

DepressedChimpanzee34 , I think I understand you, however the method eludes me. Can you please provide a snippet of what you're trying to do?

Hi @<1748153283605696512:profile|GreasyPenguin24> , can you add the full log?

The problem was that the plot I created myself

How was the plot created? Can you give me a small snippet to try and play around with?

Sounds like a great feature! Maybe open a github feature request to make it happen 🙂

Hi @<1566596960691949568:profile|UpsetWalrus59> , looks right to me 🙂

Hi @<1523702496097210368:profile|ScantChimpanzee51> , I think you need to be connected to the GS account on the same machine

SubstantialElk6 , I don't think anything like this currently exists in the API. Maybe add a feature request to github?

SubstantialElk6 , I think this is what you're looking for:
https://clear.ml/docs/latest/docs/references/sdk/dataset#get_local_copy
Dataset.get_local_copy(..., part=X)

https://clear.ml/docs/latest/docs/references/sdk/dataset/#get_num_chunks
I think this might also be helpful. Gloss over the functions available in the documentation, I think you might find what you're looking for 🙂

Great, thanks!

Exactly 🙂

Hi TartSeagull57 ,

Which one is fig 1 and which one is fig 2?
How are you logging them?

I don't think you have to, but if your environment is ready you can try 🙂

How did you set it up? Are you sure that's the correct path?

You can run agent as many times as you want on your machine

2 different queues

What do you mean by service?

Just making sure - This path, is it inside the docker or outside the container?

you set up 2 agent runs - one with docker and the other without. Each agent should be listening to a different queue. Makes sense?

Try to set agent.enable_git_ask_pass: true for the agent running inside the container, perhaps that will help

Hi @<1564060263047499776:profile|ThoughtfulCentipede62> , you can specify the Python interpreter in clearml.conf on the remote machine (Search for 'binary' or 'python')
Also, yes ClearML can pull it from an artifactory as long as the machine has access 🙂