I'll reply there 👌

Most of these are configurations (specific for an execution, but one such configuration defines multiple tasks). Some models might be uploaded if the user does not use our built-in link to ClearML model fetching 😄

Thanks for the reply @<1523701827080556544:profile|JuicyFox94> ! I'll debug more and let you know

The last kind when launching the agents.
The former on task execution.

Then perhaps mac treats missing environment variables as empty and linux just crashes? Anyway, the config loading should be deferred, shouldn't it?

I'm saying it's a bug

I don't think there's a PR issue for that yet, at least I haven't created one.

I could have a look at this and maybe make a PR.
Not sure what would the recommended flow be like though 🤔

Also something we are very much interested in (including the logger-based scatter plots etc)

Maybe it's better to approach this the other way, if one uses Task.force_requirements_env_freeze() , then the locally updated packages aren't reflected in poetry 🤔

Nothing I can spot --

ClearML results page: 

ClearML pipeline page: 

Launching the next 2 steps
Launching step [...]
Launching step [...]
Launching step: ...
Parameters:
{...}
Configurations:
{}
Overrides:
{}
Launching step: ...
Parameters:
{...}
Configurations:
{}
Overrides:
{}
ClearML Monitor: GPU monitoring failed getting GPU reading, switching off GPU monitoring
2023-02-21 13:53:48
ClearML Monitor: Could not detect iteration reporting, falling back to itera...

I'll try it out, but I would not like to rewrite that code myself maintain it, that's my point 😅

Or are you suggesting I Task.import_offline_session ?

That's fine as well - the code simply shows the name of the environment variable, not it's value, since that's taken directly from the agent listening to the services queue (and who's then running the scaler)

Hah. Now it worked.

clearml.backend_api.session.defs.ENV_HOST.get() did not work unfortunately 🤔

So some UI that shows the contents of users.get_all ?

FWIW running clearml ==1.9.1 with WebApp: 1.9.2-317 • Server: 1.9.2-317 • API: 2.23

Happens with the latest version indeed.
I can’t share our code, but the gist of it is:

pipe = PipelineController(name=..., project=..., version=...)

pipe.add_function_step(...)  # Many calls

pipe.set_default_execution_queue(...)
pipe.start(queue=..., wait=True)

Or if it wasn't clear, that chunk of code is from clearml's dataset.py

Sorry, not necessarily RBAC (although that is tempting 😉 ), but for now was just wondering if an average joe user has access to see the list of "registered users"?

Don't even need to specify json=... 😉 Thanks!

Local changes are applied before installing requirements, right?

Another example - trying to validate dataset interactions ends with

` else:
self._created_task = True
dataset_project, parent_project = self._build_hidden_project_name(dataset_project, dataset_name)
task = Task.create(
project_name=dataset_project, task_name=dataset_name, task_type=Task.TaskTypes.data_processing)
if bool(Session.check_min_api_server_version(Dataset.__min_api_version)):
get_or_create_proje...

Ah I see, if the pipeline controller begins in a Task it does not add the tags to it…

Or the above;)

Follow up on this btw, from the WebUI/Server POV, I see there's an "Admin" role, etc. Do those have additional views available, such as users etc?

Haha, I've opened so many issues these past few days... Sure, np!

@<1523701070390366208:profile|CostlyOstrich36> I added None btw

Not necessarily on the same branch, no

I'm not sure; the setup is not unique to Mac.
Each user has their own .env file which is given to the code entry point, and at some point will be loaded with dotenv.load_dotenv() .
The environment variables are not set in code anywhere, but the clearml.conf uses them directly.

I've also followed https://clearml.slack.com/archives/CTK20V944/p1628333126247800 but it did not help