The quickest workaround would be, In your final code just do something like:
my_params_for_hpo = {'key': omegaconf.key} task.connect(my_params_for_hpo, name='hpo_params') call_training_with_value(my_params_for_hpo['key'])This will initialize the my_params_for_hpo with the values from OmegaConf, and allow you to override them in the hyperparameyter section (task.connect is two, in manual it stores the data on the Task, in agent mode, it takes the values from the Task and puts them ba...

store_code_diff_from_remote

 don't seem to change anything in regards of this issue

Correct, it is always from remote

i'll be using the update_task, that worked just fine, thanks 

 (edite

Sure thing.

ShakyJellyfish91 , I took a quick look at the diff between the versions can you hack a non working version (preferably the latest) and verify the issue for me?

Hi FloppyDeer99
Since this thread is a bit old, I might have missed something 🙂
Are we saying the links are not working in the UI ?
(notice the links themselves are generated by the clearml package, so if there was a bug, still not sure here, then old links will remain invalid until manually fixed) Can you verify that the latest clearml generates working links?

Bake to the error:

clearml_agent: ERROR: Failed getting token (error 401 from

): Unauthorized (invalid credentials) (failed to locate provided credentials)

See here:
https://github.com/allegroai/clearml-server/blob/3f2b96266bc51bfce680bd759c7fa9d635ae36d3/docker/docker-compose.yml#L131
You need to provide an access key so it can actually "talk" to the server next to it.

TrickyRaccoon92 I'm not sure I follow, TB do show? and you want to add additional plotly plot ?

pip freezeworks ?

Hi @<1695969549783928832:profile|ObedientTurkey46>

Why do tags only show on a version level, but not on the dataset-level? (see images)

Tags of datasets are tags on "all the dataset versions" i.e. to help someone locate datasets (think locating projects as an analogy). Dataset Version tags are tags on a specific version of the dataset, helping users to locate a specific version of the dataset. Does that make sense ?

well.. having the demo server by default lowers the effort threshold for trying ClearML and getting convinced it can deliver what it promises, and maybe test some simple custom use cases. I

This was exactly what we thought when we set it up in the first place 🙂
(I can't imagine the cost is an issue, probably maintenance/upgrades ...)
There is still support for the demo server, you just need to set the env key:
CLEARML_NO_DEFAULT_SERVER=0 python ...

Yes please 🤩

potential sources of slow down in the training code

Is there one?

You are correct, it is currently not supported in venv mode. We could not find a good use case for it. What is yours?

Would be cool to let it get untracked as well, especially if we want to as an option

How would you decide what should be tracked?

Notice the pipeline step/Task at execution is not aware of the pipeline context

Do we support GPUs in a) docker mode b) k8s glue?

yes on both

Is there a good reference to get started with k8s glue?

A few folks here already set it up, do you have a k8s cluster with GPU support ?

Hmm so I guess the actual code adds it into the reporting itself ...
How about we call:
task.set_initial_iteration(0)

Ok, so it doesn't follow the exact same rules as 

Task.init

?

Correct

I was afraid all the logs and outputs of a hyperparameter optimization task would be deleted just because no artifacts were created. (edited)

Should not happen 🙂

Hi ImpressionableRaven99
In the UI the re is a download button when you hover over the graph.
Are you asking if there is a programmatic interface?
What is the use case for all experiments ?

Is there any contingency plan for an agent to continue running a task without reading the repository on the GitLab server?

Not sure what can be done ... any suggestions ?

At runtime, can I ask the agent to use some cached repository?

sometimes you will have it (as the agent stores a cached copy, but I would hardly count on it (and it might be at different states on different machines...)

... (due to regular maintenance service, something I cannot control).

Maybe let "th...

GiganticTurtle0 is there any git redundancy on your network ? maybe you could configure a fallback server ?

Hi SubstantialElk6
I can't see that is was removed, could you send the full log ?

SubstantialElk6 could you add a github issue to set the direct url for the vscode as a parameter to the cleaml-session?
We already have --vscode-version we could either extend it to include a direct url, or add a new argument.
wdyt ?

JitteryCoyote63 yes this is very odd, seems like a pypi flop ?!
On the website they do say there is 0.5.0 ... I do not get it
https://pypi.org/project/pytorch3d/#history

Could that be the proper way to install ?
https://github.com/facebookresearch/pytorch3d/blob/main/INSTALL.md#3-install-wheels-for-linux

Thanks @<1523702652678967296:profile|DeliciousKoala34> I think I know what the issue is!
The container has 1.3.0a and you need 1.3.0 this is why it is re-downloading (I'll make sure the agent can sort it out, becuase this is Nvidia's version in reality it should be a perfect match)

I prepared my own image and want use this venv

No worries, it creates a "transparent" venv, it uses everything from the docker (the penalty of create a new venv is negligible 🙂 , you end up with the exact same set of packages)

Hello guys, i have 4 workers (2 in default and 2 in service queue on same machine)

Hi @<1526734437587357696:profile|ShaggySquirrel23>
I think what happens is one agent is deleting it's cfg file when it is done, but at least in theory each one should have it's own cfg
One last request can you try with the agent's latest RC version 1.5.3rc2 ?

Sure thing

Thank you!

one thing i noticed is that it's not able to find the branch name on >=1.0.6x , while on 1.0.5 it can

That might be it! let me check the code again...

Are there any services OOB like this?

On the open-source, I can't recall any but will probably be easy to write. Paid tier might have an offering though, not sure 🙂

Hi QuaintJellyfish58
This is odd, this "undefined" project is also marked as "Example" which would explain why you cannot delete it, but not how you ended up with one
Any idea on what changed on your server ?